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1. 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, and Jackson, Robert B

Subjects
Earth Sciences, Agricultural, Veterinary and Food Sciences, Biological Sciences, Machine Learning and Artificial Intelligence, Bioengineering, Networking and Information Technology R&D (NITRD), Machine learning, time series, imputation, gap-filling, methane, flux, wetlands, Agricultural and Veterinary Sciences, Meteorology & Atmospheric Sciences, Agricultural, veterinary and food sciences, Biological sciences, Earth sciences
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 improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

Published
2021

2. Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

Author

Knox, Sara H, Bansal, Sheel, McNicol, Gavin, Schafer, Karina, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Baldocchi, Dennis, Delwiche, Kyle, Desai, Ankur R, Euskirchen, Eugenie, Liu, Jinxun, Lohila, Annalea, Malhotra, Avni, Melling, Lulie, Riley, William, Runkle, Benjamin RK, Turner, Jessica, Vargas, Rodrigo, Zhu, Qing, Alto, Tuula, Fluet‐Chouinard, Etienne, Goeckede, Mathias, Melton, Joe R, Sonnentag, Oliver, Vesala, Timo, Ward, Eric, Zhang, Zhen, Feron, Sarah, Ouyang, Zutao, Alekseychik, Pavel, Aurela, Mika, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Goodrich, Jordan P, Gottschalk, Pia, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kang, Minseok, Koebsch, Franziska, Mammarella, Ivan, Nilsson, Mats B, Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sparks, Jed P, Tuittila, Eeva‐Stiina, Vourlitis, George L, Wong, Guan X, Windham‐Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B

Subjects
Earth Sciences, Climate Change Impacts and Adaptation, Environmental Sciences, Carbon Dioxide, Ecosystem, Fresh Water, Methane, Seasons, Wetlands, eddy covariance, generalized additive modeling, lags, methane, mutual information, predictors, random forest, synthesis, time scales, wetlands, Biological Sciences, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract

While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

Published
2021

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

Author

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

Subjects
Earth Sciences, Atmospheric Sciences, Climate Action, Geochemistry, Physical Geography and Environmental Geoscience, Atmospheric sciences, Geoinformatics, Physical geography and environmental geoscience
Abstract

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20g g€¯S to 20g g€¯N) the spring onset of elevated CH4 emissions starts 3g€¯d earlier, and the CH4 emission season lasts 4g€¯d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at 10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Published
2021

6. Modellgestützte Wirkungsanalysen ausgewählter Maßnahmen und Strategien

Author

Baum, Sarah, Conradt, Tobias, Dechow, René, Elsasser, Peter, Englert, Hermann, Ermisch, Nils, Gömann, Horst, Goetzke, Roland, Gottschalk, Pia, Gutsch, Martin, Henseler, Martin, Hoymann, Jana, Köthke, Margret, Kreins, Peter, Lasch-Born, Petra, Suckow, Felicitas, Wechsung, Frank, Gömann, Horst, editor, and Fick, Johanna, editor

Published
2021
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7. Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Author

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

Published
2020

13. Monitoring cropland daily carbon dioxide exchange at field scales with Sentinel-2 satellite imagery.

Author

Gottschalk, Pia, Kalhori, Aram, Li, Zhan, Wille, Christian, and Sachs, Torsten

Subjects
REMOTE-sensing images, CARBON dioxide, FARMS, AGRICULTURE, LEAF area, ESTIMATES
Abstract

Improving the accuracy of monitoring cropland CO2 exchange at heterogeneous spatial scales is of high importance to limit spatial and temporal uncertainty of terrestrial carbon (C) dynamic estimates. A combination of field scale eddy covariance (EC) CO2 flux data and spatially matched Sentinel-2 derived vegetation indices (VIs) was tested as an approach to upscale agricultural C flux. The ability of different VIs to estimate daily net ecosystem exchange (NEE) and gross primary productivity (GPP) based on linear regression models was assessed. Most VIs showed high (>0.9) and statistically significant (p<0.001) correlations with GPP and NEE although some VIs deviated from the seasonal pattern of CO2 exchange. In contrast, correlations between ecosystem respiration (Reco) and VIs were weak and statistically not significant, and no attempt was made to estimate Reco from VIs. Linear regression models explained generally more than 80 % and 70 % of the variability of NEE and GPP, respectively, with high variability amongst the individual VIs. The performance in estimating daily C fluxes varied amongst VIs depending on C flux component (NEE or GPP) and observation period. RMSE values ranged from 1.35 g C m-2 d-1 using the Green Normilized Difference Vegetation Index (GNDVI) for NEE to 5 g C m-2 d-1 using the Simple Ratio (SR) for GPP. This equated to an underestimated net C uptake of only 41 g C m-2 (18 %) and an overestimation of gross C uptake of 854 g C m-2 (73 %). Differences between measured and estimated C fluxes were mainly explained by the diversion of the C flux and VI signal during winter, when C uptake stayed low while VI values indicated an increased C uptake due to relatively high crop leaf area. Overall, results exhibited similar error margins as mechanistic crop models. Thus, they indicated suitability and developability of the proposed approach to monitor cropland C exchange with satellite derived VIs. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Modelling soil organic carbon dynamics under land use and climate change

Author

Gottschalk, Pia

Subjects
631.417, Soil management, Soil fertility, Soils
Abstract

Soil organic matter (SOM) models simplify the complex turnover dynamics of organic matter in soils. Stabilization mechanisms are currently thought to play a dominant role in SOM turnover but they are not explicitly accounted for in most SOM models. One study addresses the implementation of an approach to account for the stabilization mechanism of physical protection in the SOC model RothC using 13C abundance measurements in conjunction with soil size fractionation data. SOM models are increasingly used to support policy decisions on carbon (C) mitigation and credibility of model predictions move into the focus of research. A site scale, Monte Carlo based model uncertainty analysis of a SOM model was carried out. One of the major results was that uncertainty and factor importance depend on the combination of external drivers. A different approach was used with the SOM ECOSSE model to estimate uncertainties in soil organic carbon (SOC) stock changes of mineral and organic soils in Scotland. The average statistical model error from site scale evaluation was transferred to regional scale uncertainty to give an indication of the uncertainty in national scale predictions. National scale simulations were carried out subsequently to quantify SOC stock changes differentiating between organic and mineral soils and land use change types. Organic soils turned out to be most vulnerable to SOC losses in the last decades. The final study of this thesis emplyed the RothC model to simulate possible futures of global SOC stock changes under land use change and ten different climate scenarios. Land use change turned out to be of minor importance. The regionally balance between soil C inputs and decomposition leads to a diverse map of regional C gains and losses with different degrees of certainty.

Published
2012

19. Estimating changes in Scottish soil carbon stocks using ECOSSE. II. Application

Author

Smith, Jo, Gottschalk, Pia, Bellarby, Jessica, Chapman, Stephen, Lilly, Allan, Towers, Willie, Bell, John, Coleman, Kevin, Nayak, Dali, Richards, Mark, Hillier, Jon, Flynn, Helen, Wattenbach, Martin, Aitkenhead, Matt, Yeluripati, Jagadeesh, Farmer, Jenny, Milne, Ronnie, Thomson, Amanda, Evans, Chris, Whitmore, Andy, Falloon, Pete, and Smith, Pete

Published
2010

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

Author

Irvin, Jeremy, primary, Zhou, Sharon, additional, McNicol, Gavin, additional, Lu, Fred, additional, Liu, Vincent, additional, Fluet-Chouinard, Etienne, additional, Ouyang, Zutao, additional, Knox, Sara Helen, additional, Lucas-Moffat, Antje, additional, Trotta, Carlo, additional, Papale, Dario, additional, Vitale, Domenico, additional, Mammarella, Ivan, additional, Alekseychik, Pavel, additional, Aurela, Mika, additional, Avati, Anand, additional, Baldocchi, Dennis, additional, Bansal, Sheel, additional, Bohrer, Gil, additional, Campbell, David I, additional, Chen, Jiquan, additional, Chu, Housen, additional, Dalmagro, Higo J, additional, Delwiche, Kyle B, additional, Desai, Ankur R, additional, Euskirchen, Eugenie, additional, Feron, Sarah, additional, Goeckede, Mathias, additional, Heimann, Martin, additional, Helbig, Manuel, additional, Helfter, Carole, additional, Hemes, Kyle S, additional, Hirano, Takashi, additional, Iwata, Hiroki, additional, Jurasinski, Gerald, additional, Kalhori, Aram, additional, Kondrich, Andrew, additional, Lai, Derrick YF, additional, Lohila, Annalea, additional, Malhotra, Avni, additional, Merbold, Lutz, additional, Mitra, Bhaskar, additional, Ng, Andrew, additional, Nilsson, Mats B, additional, Noormets, Asko, additional, Peichl, Matthias, additional, Rey-Sanchez, A. Camilo, additional, Richardson, Andrew D, additional, Runkle, Benjamin RK, additional, Schäfer, Karina VR, additional, Sonnentag, Oliver, additional, Stuart-Haëntjens, Ellen, additional, Sturtevant, Cove, additional, Ueyama, Masahito, additional, Valach, Alex C, additional, Vargas, Rodrigo, additional, Vourlitis, George L, additional, Ward, Eric J, additional, Wong, Guan Xhuan, additional, Zona, Donatella, additional, Alberto, Ma. Carmelita R, additional, Billesbach, David P, additional, Celis, Gerardo, additional, Dolman, Han, additional, Friborg, Thomas, additional, Fuchs, Kathrin, additional, Gogo, Sébastien, additional, Gondwe, Mangaliso J, additional, Goodrich, Jordan P, additional, Gottschalk, Pia, additional, Hörtnagl, Lukas, additional, Jacotot, Adrien, additional, Koebsch, Franziska, additional, Kasak, Kuno, additional, Maier, Regine, additional, Morin, Timothy H, additional, Nemitz, Eiko, additional, Oechel, Walter C, additional, Oikawa, Patricia Y, additional, Ono, Keisuke, additional, Sachs, Torsten, additional, Sakabe, Ayaka, additional, Schuur, Edward A, additional, Shortt, Robert, additional, Sullivan, Ryan C, additional, Szutu, Daphne J, additional, Tuittila, Eeva-Stiina, additional, Varlagin, Andrej, additional, Verfaillie, Joeseph G, additional, Wille, Christian, additional, Windham-Myers, Lisamarie, additional, Poulter, Benjamin, additional, and Jackson, Robert B, additional

Published
2021
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21. Congruent changes in microbial community dynamics and ecosystem methane fluxes following natural drought in two restored fens

Author

Unger, Viktoria, primary, Liebner, Susanne, additional, Koebsch, Franziska, additional, Yang, Sizhong, additional, Horn, Fabian, additional, Sachs, Torsten, additional, Kallmeyer, Jens, additional, Knorr, Klaus-Holger, additional, Rehder, Gregor, additional, Gottschalk, Pia, additional, and Jurasinski, Gerald, additional

Published
2021
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22. 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., Institute for Atmospheric and Earth System Research (INAR), Micrometeorology and biogeochemical cycles, Viikki Plant Science Centre (ViPS), Ecosystem processes (INAR Forest Sciences), Earth Sciences, and Earth and Climate

Subjects
1171 Geosciences, Earth sciences, SDG 17 - Partnerships for the Goals, Physical Geography, ddc:550, 114 Physical sciences, 1172 Environmental sciences, Atmospheric Sciences
Abstract

Methane (CH$_{4}$) emissions from natural landscapes constitute roughly half of global CH$_{4}$ contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH$_{4}$ flux are ideal for constraining ecosystem-scale CH$_{4}$ emissions due to quasi-continuous and high-temporal-resolution CH$_{4}$ flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH$_{4}$ Version 1.0, the first open-source global dataset of CH$_{4}$ EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH$_{4}$ fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH$_{4}$ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH$_{4}$ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH$_{4}$ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH$_{4}$ fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH$_{4}$ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20° S to 20° N) the spring onset of elevated CH$_{4}$ emissions starts 3 d earlier, and the CH$_{4}$ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH$_{4}$ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH$_{4}$ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH$_{4}$ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH$_{4}$ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH$_{4}$ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH$_{4}$ peak). FLUXNET-CH$_{4}$ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH$_{4}$ cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH$_{4}$ data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Published
2021

23. The carbon balance of European croplands: A cross-site comparison of simulation models

Author

Wattenbach, Martin, Sus, Oliver, Vuichard, Nicolas, Lehuger, Simon, Gottschalk, Pia, Li, Longhui, Leip, Adrian, Williams, Mathew, Tomelleri, Enrico, Kutsch, Werner Leo, Buchmann, Nina, Eugster, Werner, Dietiker, Dominique, Aubinet, Marc, Ceschia, Eric, Béziat, Pierre, Grünwald, Thomas, Hastings, Astley, Osborne, Bruce, Ciais, Philippe, Cellier, Pierre, and Smith, Pete

Published
2010
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24. FLUXNET-CH4: a global, multi-ecosystem datasetand analysis of methane seasonalityfrom freshwater wetlands

Author

Knox, Sara, Alberto, Ma, Matthes, Jaclyn, Sanchez, Camilo, Wong, Guan, Delwiche, Kyle, Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma. Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David, Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David, Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo, Dengel, Sigrid, Desai, Ankur, Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso, Goodrich, Jordan, Gottschalk, Pia, Graham, Scott, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle, Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken, Lai, Derrick, Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy, Nemitz, Eiko, Nilsson, Mats, Niu, Shuli, Oechel, Walter, Oikawa, Patricia, Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele, Richardson, Andrew, Riley, William, Runkle, Benjamin, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward, Schäfer, Karina, Sonnentag, Oliver, Sparks, Jed, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan, Szutu, Daphne, Thom, Jonathan, Torn, Margaret, Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex, Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph, Vesala, Timo, Vourlitis, George, Ward, Eric, Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert, Institut des Sciences de la Terre d'Orléans - UMR7327 (ISTO), Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Biogéosystèmes Continentaux - UMR7327, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC)

Subjects
[SDU]Sciences of the Universe [physics], [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Abstract

International audience; Abstract. Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Published
2021

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

Author

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

Published
2021
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28. Methane uptake by various forest soils with and without litter

Author

Walkiewicz, Anna, primary, Bulak, Piotr, additional, Osborne, Bruce, additional, Khalil, Mohammad Ibrahim, additional, Islam, Syed Faiz-ul, additional, Kruijt, Bart, additional, Hutjes, Ronald, additional, Spengler, Daniel, additional, Gottschalk, Pia, additional, Sachs, Torsten, additional, Klumpp, Katja, additional, Vigan, Aurore, additional, Hassouna, Mélynda, additional, Henessy, Donagh, additional, and Shalloo, Laurence, additional

Published
2020
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29. Regionale Auswirkungen des Globalen Wandels: Der Extremsommer 2018 in Nordostdeutschland

Author

Heinrich, Ingo, Balanzategui, Daniel, Bens, Oliver, Blume, Theresa, Brauer, Achim, Dietze, Elisabeth, Gottschalk, Pia, Güntner, Andreas, Harfenmeister, Katharina, Helle, Gerhard, Hohmann, Christian, Itzerott, Sibylle, Kaiser, Knut, Liebner, Susanne, Merz, Bruno, Pinkerneil, Sylvia, Plessen, Birgit, Sachs, Torsten, Schwab, Markus J., Spengler, Daniel, Vallentin, Claudia, and Wille, Christian

Subjects
Mathematics::Combinatorics, Computer Science::Discrete Mathematics, Computer Science::Social and Information Networks
Abstract

System Erde; 9, The main focus of the TERENO Northeastern German Lowland Observatory (TERENO-Northeast) is the regional impact of Global Change. Since 2011, the observatory has recorded changes in the geo-, hydro-, bio- and atmosphere at six main study sites. The year 2018, particularly in northeast Germany, was record-breaking in regard to dryness and heat. The mean temperature in Mecklenburg-Vorpommern was 2 °C above the long-term average and precipitation was very low at 440 mm (normally around 600 mm). The extreme summer of 2018 was a special opportunity for TERENO-Northeast to measure the regional effects of climate change. One of the consequences was the large number of forest fires, with one major fire destroying around 400 hectares. Other extreme reactions of the ecosystems were shown in TERENO-Northeast. For example, for the first time since its rewetting, Polder Zarnekov fell dry, with unpredictable consequences for the greenhouse gas exchanges. The forest ecosystems of Müritz National Park, on the other hand, survived the extreme summer surprisingly well, partly because the months before the drought were relatively damp. The research activities of TERENO-Northeast form an important basis to develop realistic options for improved adaptation strategies to the ongoing global change with its particular region-specific effects and challenges.

Published
2019

30. Energy partitioning and water use efficiency anomalies 2018 at Eddy-Covariance sites across ecosystems

Author

Graf, Alexander, Klosterhalfen, Anne, Konopka, Jan, De Ligne, Anne, Longdoz, Bernard, Mauder, Matthias, Ney, Patrizia, Rabbel, Inken, Rebmann, Corinna, Sachs, Torsten, Schmidt, Marius, Schrader, Frederik, Bernhofer, Christian, Vincke, Caroline, Völksch, Ingo, Weber, Stephan, Wille, Christian, Vereecken, Harry, Brümmer, Christian, Drüe, Clemens, Gottschalk, Pia, Grünwald, Thomas, Heinemann, Günther, Heinesch, Bernard, and Klatt, Janina

Subjects
ddc:550
Abstract

Droughts and heat waves deeply interact with the exchange of energy and matter between land surface and atmosphere. The conditions associated with a combined heat wave and drought can have positive or negative effects on the sensible heat flux (H), latent heat flux (LE), and net flux of CO2 (NEE). In return, while each of these fluxes can exert different local feedbacks on temperature, atmospheric humidity and soil moisture, all of them result in bulk heating of the troposphere (H and LE through direct local and indirect non-local heat transfer, and NEE through radiative forcing). H is positively affected by increased solar irradiation, but can be supressed by advection of warm air diminishing the gradient between surface and air temperature. Potential LE is positively affected by irradiation, temperature and water vapour pressure deficit, but actual LE can be suppressed by stomatal closure of plants and by reduced soil moisture from low rainfall and high past LE. NEE is the result of plant photosynthesis (GPP) and plant and soil respiration (R), both of which can be enhanced by high temperatures or irradiation, and suppressed by drought. Focusing on direct measurements mostly by a network of Eddy-Covariance (EC) stations of the ICOS (www.icosri.eu), TERENO (www.tereno.net) and other networks, we hypothesize that the net effect of the 2018 event at a site, and thus its feedback on global warming, depends on the balance between co-existing positive and negative effects of the combined heat wave and drought on the respective fluxes. Variables such as albedo, growing degreedays (GDD), soil moisture and ecosystem-level water use efficiency help to separate these co-existing positive and negative effects from each other. Preliminary results indicate different degrees of heterogeneity between sites fordifferent variables. As expected, reduced precipitation and soil moisture, as well as increased GDD, could be found at almost all sites in the affected region. NEE was mostly less negative, indicating a weaker sink or even a source forCO2, as expected from past studies on earlier events. The network density and number of site-years available now confirms that this was true for all major ecosystem types - forest, grassland and (rainfed) cropland, and resultedin increased atmospheric CO2 concentrations. However, notable exceptions occurred at elevated low mountain range sites and during early stages of the event, supporting the hypothesis of a balance between positive andnegative effects, where the former may prevail at strongly energy-limited sites with a usually large water surplus. H was mostly above-average, indicating that local heat production contributed to the event and was typically notsuppressed by warm air advection. LE as well as inferred GPP and R reacted most heterogeneously across sites, demonstrating the large discrepancy between potentially high fluxes due to high irradiation and temperature on theone hand, and suppression by water shortage on the other hand. Despite the variability in LE, its relation to NEE was such that ecosystem-level water use was less efficient than usual at the majority of sites through reduced CO2uptake.

Published
2019

35. Soil carbon, multiple benefits

Author

Milne, Eleanor, primary, Banwart, Steven A., additional, Noellemeyer, Elke, additional, Abson, David J., additional, Ballabio, Cristiano, additional, Bampa, Francesca, additional, Bationo, Andre, additional, Batjes, Niels H., additional, Bernoux, Martial, additional, Bhattacharyya, Tapas, additional, Black, Helaina, additional, Buschiazzo, Daniel E., additional, Cai, Zucong, additional, Cerri, Carlos Eduardo, additional, Cheng, Kun, additional, Compagnone, Claude, additional, Conant, Rich, additional, Coutinho, Heitor L.C., additional, de Brogniez, Delphine, additional, Balieiro, Fabiano de Carvalho, additional, Duffy, Christopher, additional, Feller, Christian, additional, Fidalgo, Elaine C.C., additional, da Silva, Cristiane Figueira, additional, Funk, Roger, additional, Gaudig, Greta, additional, Gicheru, Patrick T., additional, Goldhaber, Marty, additional, Gottschalk, Pia, additional, Goulet, Frederic, additional, Goverse, Tessa, additional, Grathwohl, Peter, additional, Joosten, Hans, additional, Kamoni, Peter T., additional, Kihara, Job, additional, Krawczynski, Rene, additional, La Scala, Newton, additional, Lemanceau, Philippe, additional, Li, Lianqing, additional, Li, Zichuan, additional, Lugato, Emanuele, additional, Maron, Pierre-Alain, additional, Martius, Christopher, additional, Melillo, Jerry, additional, Montanarella, Luca, additional, Nikolaidis, Nikolaos, additional, Nziguheba, Generose, additional, Pan, Genxing, additional, Pascual, Unai, additional, Paustian, Keith, additional, Piñeiro, Gervasio, additional, Powlson, David, additional, Quiroga, Alberto, additional, Richter, Dan, additional, Sigwalt, Annie, additional, Six, Johan, additional, Smith, Jo, additional, Smith, Pete, additional, Stocking, Michael, additional, Tanneberger, Franziska, additional, Termansen, Mette, additional, van Noordwijk, Meine, additional, van Wesemael, Bas, additional, Vargas, Rodrigo, additional, Victoria, Reynaldo Luiz, additional, Waswa, Boaz, additional, Werner, David, additional, Wichmann, Sabine, additional, Wichtmann, Wendelin, additional, Zhang, Xuhui, additional, Zhao, Yongcun, additional, Zheng, Jinwei, additional, and Zheng, Jufeng, additional

Published
2015
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36. Library of model components for process simulation relevant to production activities, Prototype 1 versions

Author

Donatelli, Marcello, Rizzoli, Andrea E., Van Evert, Frits K., Rutgers, Ben, Trevisan, Marco, Sorce, Andrea, Balderacchi, Matteo, Di Guardo, Andrea, Ewert, Frank, Leffelaar, Peter, Meuter, Eelco, Adam, Myriam, Smith, Jo, Gottschalk, Pia, Acutis, Marco, Trevisiol, Patrizia, Gentile, Antonella, Bellocchi, Gianni, Carlini, Laura, Duru, Michel, Cruz, Pablo, Gary, Christian, Kansou, Kamal, Wery, Jacques, Dupraz, Christian, Braudeau, Erik, and Martin, Pierre

Subjects
Production Economics
Published
2007
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37. Agricultural production and externalities simulator (APES) prototype to be used in prototype 1 of SEAMLESS-IF

Author

Donatelli, Marcello, Evert, Frits, Rutgers, Ben, Trevisan, Marco, Sorce, Andrea, Balderacchi, Matteo, Di Guardo, Andrea, Ewert, Franck, Leffelaar, Peter A., Meuter, Eelco, Myriam ADAM, Smith, Jo, Gottschalk, Pia, Acutis, Marco, Trevisiol, Patricia, Gentile, Antonella, Bellocchi, Gianni, Carlini, Laura, Duru, Michel, Cruz, Pablo, Gary, Christian, Kansou, Kamal, Wery, Jacques, Dupraz, Christian, Braudeau, Eric, and Pierre Martin

Subjects
E16 - Economie de la production, U10 - Méthodes mathématiques et statistiques, Agriculture, Modèle de simulation
Published
2007

38. Benefits of soil carbon: report on the outcomes of an international scientific committee on problems of the environment rapid assessment workshop

Author

Banwart, Steve, primary, Black, Helaina, additional, Cai, Zucong, additional, Gicheru, Patrick, additional, Joosten, Hans, additional, Victoria, Reynaldo, additional, Milne, Eleanor, additional, Noellemeyer, Elke, additional, Pascual, Unai, additional, Nziguheba, Generose, additional, Vargas, Rodrigo, additional, Bationo, Andre, additional, Buschiazzo, Daniel, additional, de-Brogniez, Delphine, additional, Melillo, Jerry, additional, Richter, Dan, additional, Termansen, Mette, additional, van Noordwijk, Meine, additional, Goverse, Tessa, additional, Ballabio, Cristiano, additional, Bhattacharyya, Tapas, additional, Goldhaber, Marty, additional, Nikolaidis, Nikolaos, additional, Zhao, Yongcun, additional, Funk, Roger, additional, Duffy, Chris, additional, Pan, Genxing, additional, la Scala, Newton, additional, Gottschalk, Pia, additional, Batjes, Niels, additional, Six, Johan, additional, van Wesemael, Bas, additional, Stocking, Michael, additional, Bampa, Francesca, additional, Bernoux, Martial, additional, Feller, Christian, additional, Lemanceau, Philippe, additional, and Montanarella, Luca, additional

Published
2014
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42. Projected changes in the organic carbon stocks of cropland mineral soils of European Russia and the Ukraine, 1990?2070

Author

SMITH, JO, primary, SMITH, PETE, additional, WATTENBACH, MARTIN, additional, GOTTSCHALK, PIA, additional, ROMANENKOV, VLADIMIR A., additional, SHEVTSOVA, LUDMILA K., additional, SIROTENKO, OLEG D., additional, RUKHOVICH, DMITRY I., additional, KOROLEVA, POLINA V., additional, ROMANENKO, IRINA A., additional, and LISOVOI, NICOLAI V., additional

Published
2007
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43. Simulation of soil organic carbon response at forest cultivation sequences using 13C measurements

Author

Gottschalk, Pia, Bellarby, Jessica, Chenu, Claire, Foereid, Bente, Smith, Pete, Wattenbach, Martin, Zingore, Shamie, and Smith, Jo

Subjects
*SIMULATION methods & models, *ORGANIC compounds, *TILLAGE, *CARBON isotopes, *DEFORESTATION, *CARBON in soils, *SOIL conservation, *CHEMICAL weathering
Abstract

Abstract: When deforestation is followed by continuous arable cropping, a permanent decline of between 22% and 42% in the soil organic carbon (SOC) has been reported. This systematic loss of soil carbon (C) is mainly attributed to the loss of physically protected SOC. The Rothamsted Carbon model (RothC) does not include a description of the processes of physical protection of SOC and so losses of C during continuous cultivation of previously uncultivated land are not likely to be accurately simulated. Our results show that in the first years following deforestation, RothC does not capture the fast drop in forest derived soil C. However, the model does satisfactorily simulate the changes in SOC derived from the following crops. Uncertainty in input data and accounting for erosion, does not explain the underestimation of decomposition after deforestation by RothC. A simple approach to increase decomposition by multiplying rate constants is evaluated. This approach needs high multiplication rates and leads to an overestimation of plant input values to sustain SOC equilibrium levels. However, the ability of RothC to simulate changes in the forest derived SOC can be greatly improved with an implementation of a simple approach to account for SOC dynamics due to the loss of physically protected C. This approach implements a new soil carbon pool into RothC which represents the labile but protected carbon fraction which builds up under minimally disturbed land uses, and which loses its protection once the soil is disturbed. The new pool is calibrated using 13C natural abundance analysis in conjunction with soil fractionation. [Copyright &y& Elsevier]

Published
2010
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44. Atmospheric carbon fluxes of a formerly drained fen up to 14 years after rewetting.

Author

Gottschalk, Pia, Wille, Christian, Koebsch, Franziska, and Sachs, Torsten

Subjects
*VALLEYS, *WATER table, *LONG-Term Evolution (Telecommunications), *EDDY flux, *CARBON cycle, *TSUNAMI hazard zones, *POTAMOGETON, *LAKE sediments
Abstract

Drained and degraded peatlands constitute significant and long-term carbon dioxide sources and thus contribute to climate warming. In the northeast German state of Mecklenburg-Western Pomerania, an estimated 20-30 % of the statewide carbon dioxide emissions are attributed to drained peatlands and one strategy to reduce national greenhouse gas emissions is therefore the re-wetting of peatlands to restore their natural carbon sink capacity. However, the long-term evolution of carbon fluxes of rewetted fens are highly site specific and uncertainty remains with regard to if and when such sites turn into carbon sinks.Surface-atmosphere fluxes of CO2 and CH4 were measured at "Polder Zarnekow" (Fluxnet ID: DE-Zrk), a formerly drained and rewetted rich fen located in the Peene River valley. Draining of the fen began in the 18th century and was intensified between 1960 and 1990, when the water table was lowered to > 1 m below the surface. Mineralization of the peat caused the surface to subside to levels below the adjoining Peene River. The site was rewetted by inundation during the winter of 2004/2005 and a shallow lake with a fluctuating water table of up to 1.2 m depth and an area of about 7 ha developed. A layer of organic sediment formed at the bottom of the lake, which originated from the fen's former vegetation and has since been annually replenished by dying aquatic plants and helophytes. A first observation period predating the establishment of the current infrastructure covers the years 2007–2009 and continuous monitoring has been ongoing since 2013. Preliminary results suggest that methane emissions are remaining high (28-39 g m-2 y-2) while CO2 effluxes show a declining trend eventually turning the site from a CO2 source to a CO2 sink in 2018.We present a time series of surface-atmosphere carbon fluxes and annual carbon balances (excluding lateral transport) from 2014 to 2018. Drivers of the turbulent fluxes are analysed on various time scales and the role of observed temporary summertime drying of the lake in the net carbon balance is analyzed. [ABSTRACT FROM AUTHOR]

Published
2019

46. Supplementary material from Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Author

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

Subjects
13. Climate action, 15. Life on land
Abstract

Data processing methods; Energy balance closure; Intra-annual temporal dynamics of ET; Tables S1-S2; Figures S1-S2

47. Flux processing and auxiliary data from The impact of occasional drought periods on vegetation spread and greenhouse gas exchange in rewetted fens

Author

Koebsch, Franziska, Gottschalk, Pia, Beyer, Florian, Wille, Christian, Jurasinski, Gerald, and Sachs, Torsten

Subjects
2. Zero hunger, 13. Climate action, 15. Life on land, 6. Clean water
Abstract

Peatland rewetting aims at stopping the emissions of carbon dioxide (CO2) and establishing net carbon sinks. However, in times of global warming, restoration projects must increasingly deal with extreme events such as drought periods. Here, we evaluate the effect of the European summer drought 2018 on vegetation development and the exchange of methane (CH4) and CO2 in two rewetted minerotrophic fens (Hütelmoor - Hte and Zarnekow - Zrk) including potential carry-over effects in the post-drought year. Drought was a major stress factor for the established vegetation but also promoted the rapid spread of new vegetation, which will likely gain a lasting foothold in Zrk. Accordingly, drought increased not only respiratory CO2 losses but also photosynthetic CO2 uptake. Altogether, the drought reduced the net CO2 sink in Hte, while it stopped the persistent net CO2 emissions of Zrk. In addition, the drought reduced CH4 emissions in both fens, though this became most apparent in the post-drought year and suggests a lasting shift towards non-methanogenic organic matter decomposition. Occasional droughts can be beneficial for the restoration of the peatland carbon sink function if the newly grown vegetation increases CO2 sequestration in the long term. Nonetheless, care must be taken to prevent extensive peat decay.This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

48. Flux processing and auxiliary data from The impact of occasional drought periods on vegetation spread and greenhouse gas exchange in rewetted fens

Author

Koebsch, Franziska, Gottschalk, Pia, Beyer, Florian, Wille, Christian, Jurasinski, Gerald, and Sachs, Torsten

Subjects
2. Zero hunger, 13. Climate action, 15. Life on land, 6. Clean water
Abstract

Peatland rewetting aims at stopping the emissions of carbon dioxide (CO2) and establishing net carbon sinks. However, in times of global warming, restoration projects must increasingly deal with extreme events such as drought periods. Here, we evaluate the effect of the European summer drought 2018 on vegetation development and the exchange of methane (CH4) and CO2 in two rewetted minerotrophic fens (Hütelmoor - Hte and Zarnekow - Zrk) including potential carry-over effects in the post-drought year. Drought was a major stress factor for the established vegetation but also promoted the rapid spread of new vegetation, which will likely gain a lasting foothold in Zrk. Accordingly, drought increased not only respiratory CO2 losses but also photosynthetic CO2 uptake. Altogether, the drought reduced the net CO2 sink in Hte, while it stopped the persistent net CO2 emissions of Zrk. In addition, the drought reduced CH4 emissions in both fens, though this became most apparent in the post-drought year and suggests a lasting shift towards non-methanogenic organic matter decomposition. Occasional droughts can be beneficial for the restoration of the peatland carbon sink function if the newly grown vegetation increases CO2 sequestration in the long term. Nonetheless, care must be taken to prevent extensive peat decay.This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

49. Supplementary material from Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Author

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

Subjects
13. Climate action, 15. Life on land
Abstract

Data processing methods; Energy balance closure; Intra-annual temporal dynamics of ET; Tables S1-S2; Figures S1-S2

50. Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Author

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

Subjects
net carbon uptake, 13. Climate action, eddy covariance, evapotranspiration, heat flux, water-use efficiency, 15. Life on land, energy balance
Abstract

Philosophical Transactions of the Royal Society B: Biological Sciences, 375 (1810), ISSN:0962-8436, ISSN:1471-2970, ISSN:0080-4622

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