Articles | Volume 13, issue 12
https://doi.org/10.5194/bg-13-3735-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-13-3735-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Reviews and syntheses
| 
28 Jun 2016
Reviews and syntheses |
| 28 Jun 2016
Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems
Biology Department, San Diego State University, San Diego, CA, USA
Northeast Institute of Geography and Agro-ecology, Chinese Academy of
Sciences, Changchun, Jilin, China
Department of Biological Sciences, University of Texas at El Paso, El
Paso, TX, USA
Fengming Yuan
Climate Change Science Institute and Environmental Sciences Division, Oak
Ridge National Laboratory, Oak Ridge, TN, USA
Paul J. Hanson
Climate Change Science Institute and Environmental Sciences Division, Oak
Ridge National Laboratory, Oak Ridge, TN, USA
Stan D. Wullschleger
Climate Change Science Institute and Environmental Sciences Division, Oak
Ridge National Laboratory, Oak Ridge, TN, USA
Peter E. Thornton
Climate Change Science Institute and Environmental Sciences Division, Oak
Ridge National Laboratory, Oak Ridge, TN, USA
William J. Riley
Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley,
CA, USA
Xia Song
Biology Department, San Diego State University, San Diego, CA, USA
Department of Biological Sciences, University of Texas at El Paso, El
Paso, TX, USA
David E. Graham
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Changchun Song
Northeast Institute of Geography and Agro-ecology, Chinese Academy of
Sciences, Changchun, Jilin, China
Hanqin Tian
International Center for Climate and Global Change Research, School of
Forestry and Wildlife Sciences, Auburn University, Auburn, AL, USA
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This article is included in the Encyclopedia of Geosciences
Binyuan Xu, Hanqin Tian, Shufen Pan, Xiaoyong Li, Ran Meng, Óscar Melo, Anne McDonald, María de los Ángeles Picone, Xiao-Peng Song, Edson Severnini, Katharine G. Young, and Feng Zhao
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Revised manuscript under review for ESSD
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This article is included in the Encyclopedia of Geosciences
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
This article is included in the Encyclopedia of Geosciences
Rui Su, Kexin Li, Nannan Wang, Fenghui Yuan, Ying Zhao, Yunjiang Zuo, Ying Sun, Liyuan He, Xiaofeng Xu, and Lihua Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3347, https://doi.org/10.5194/egusphere-2024-3347, 2024
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This research examines the effect of sulfate on methane oxidation in soil, finding that sulfate may facilitate methane oxidation. Considering methane's role as a greenhouse gas and rising sulfate deposition, the study aims to predict changes in methane oxidation due to acid deposition. Future experiments will explore microbial mechanisms, as sulfate reduces methane emissions while enhancing its consumption, providing insights for mitigation strategies.
This article is included in the Encyclopedia of Geosciences
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024, https://doi.org/10.5194/bg-21-5173-2024, 2024
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Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Using machine learning, we develop and compare predictive relationships in observations (Obs) and ESMs. We find different relationships between environmental factors and SOC stocks in Obs and ESMs. SOC prediction in ESMs may be improved by representing the functional relationships of environmental controllers in a way consistent with observations.
This article is included in the Encyclopedia of Geosciences
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
This article is included in the Encyclopedia of Geosciences
Charles E. Miller, Peter C. Griffith, Elizabeth Hoy, Naiara S. Pinto, Yunling Lou, Scott Hensley, Bruce D. Chapman, Jennifer Baltzer, Kazem Bakian-Dogaheh, W. Robert Bolton, Laura Bourgeau-Chavez, Richard H. Chen, Byung-Hun Choe, Leah K. Clayton, Thomas A. Douglas, Nancy French, Jean E. Holloway, Gang Hong, Lingcao Huang, Go Iwahana, Liza Jenkins, John S. Kimball, Tatiana Loboda, Michelle Mack, Philip Marsh, Roger J. Michaelides, Mahta Moghaddam, Andrew Parsekian, Kevin Schaefer, Paul R. Siqueira, Debjani Singh, Alireza Tabatabaeenejad, Merritt Turetsky, Ridha Touzi, Elizabeth Wig, Cathy J. Wilson, Paul Wilson, Stan D. Wullschleger, Yonghong Yi, Howard A. Zebker, Yu Zhang, Yuhuan Zhao, and Scott J. Goetz
Earth Syst. Sci. Data, 16, 2605–2624, https://doi.org/10.5194/essd-16-2605-2024, https://doi.org/10.5194/essd-16-2605-2024, 2024
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NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) conducted airborne synthetic aperture radar (SAR) surveys of over 120 000 km2 in Alaska and northwestern Canada during 2017, 2018, 2019, and 2022. This paper summarizes those results and provides links to details on ~ 80 individual flight lines. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band SAR data.
This article is included in the Encyclopedia of Geosciences
Liyuan He, Jorge L. Mazza Rodrigues, Melanie A. Mayes, Chun-Ta Lai, David A. Lipson, and Xiaofeng Xu
Biogeosciences, 21, 2313–2333, https://doi.org/10.5194/bg-21-2313-2024, https://doi.org/10.5194/bg-21-2313-2024, 2024
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Soil microbes are the driving engine for biogeochemical cycles of carbon and nutrients. This study applies a microbial-explicit model to quantify bacteria and fungal biomass carbon in soils from 1901 to 2016. Results showed substantial increases in bacterial and fungal biomass carbon over the past century, jointly influenced by vegetation growth and soil temperature and moisture. This pioneering century-long estimation offers crucial insights into soil microbial roles in global carbon cycling.
This article is included in the Encyclopedia of Geosciences
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
This article is included in the Encyclopedia of Geosciences
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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Nathan Alec Conroy, Jeffrey M. Heikoop, Emma Lathrop, Dea Musa, Brent D. Newman, Chonggang Xu, Rachael E. McCaully, Carli A. Arendt, Verity G. Salmon, Amy Breen, Vladimir Romanovsky, Katrina E. Bennett, Cathy J. Wilson, and Stan D. Wullschleger
The Cryosphere, 17, 3987–4006, https://doi.org/10.5194/tc-17-3987-2023, https://doi.org/10.5194/tc-17-3987-2023, 2023
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This study combines field observations, non-parametric statistical analyses, and thermodynamic modeling to characterize the environmental causes of the spatial variability in soil pore water solute concentrations across two Arctic catchments with varying extents of permafrost. Vegetation type, soil moisture and redox conditions, weathering and hydrologic transport, and mineral solubility were all found to be the primary drivers of the existing spatial variability of some soil pore water solutes.
This article is included in the Encyclopedia of Geosciences
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
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Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
This article is included in the Encyclopedia of Geosciences
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
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Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
This article is included in the Encyclopedia of Geosciences
Xiaoyong Li, Hanqin Tian, Chaoqun Lu, and Shufen Pan
Earth Syst. Sci. Data, 15, 1005–1035, https://doi.org/10.5194/essd-15-1005-2023, https://doi.org/10.5194/essd-15-1005-2023, 2023
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We reconstructed land use and land cover (LULC) history for the conterminous United States during 1630–2020 by integrating multi-source data. The results show the widespread expansion of cropland and urban land and the shrinking of natural vegetation in the past four centuries. Forest planting and regeneration accelerated forest recovery since the 1920s. The datasets can be used to assess the LULC impacts on the ecosystem's carbon, nitrogen, and water cycles.
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Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
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We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
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Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
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Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
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Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
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To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
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Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo
Biogeosciences, 19, 2245–2262, https://doi.org/10.5194/bg-19-2245-2022, https://doi.org/10.5194/bg-19-2245-2022, 2022
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The relative ratio of wetland methane (CH4) emission pathways determines how much CH4 is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH4 concentration. We suggest using this approach in land surface models to accurately represent CH4 emission dynamics and response to climate change. Our results also highlight that both CH4 flux and belowground concentration data are important to constrain model parameters.
This article is included in the Encyclopedia of Geosciences
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
This article is included in the Encyclopedia of Geosciences
Ruqi Yang, Jun Wang, Ning Zeng, Stephen Sitch, Wenhan Tang, Matthew Joseph McGrath, Qixiang Cai, Di Liu, Danica Lombardozzi, Hanqin Tian, Atul K. Jain, and Pengfei Han
Earth Syst. Dynam., 13, 833–849, https://doi.org/10.5194/esd-13-833-2022, https://doi.org/10.5194/esd-13-833-2022, 2022
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We comprehensively investigate historical GPP trends based on five kinds of GPP datasets and analyze the causes for any discrepancies among them. Results show contrasting behaviors between modeled and satellite-based GPP trends, and their inconsistencies are likely caused by the contrasting performance between satellite-derived and modeled leaf area index (LAI). Thus, the uncertainty in satellite-based GPP induced by LAI undermines its role in assessing the performance of DGVM simulations.
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Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
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Dóra Hidy, Zoltán Barcza, Roland Hollós, Laura Dobor, Tamás Ács, Dóra Zacháry, Tibor Filep, László Pásztor, Dóra Incze, Márton Dencső, Eszter Tóth, Katarína Merganičová, Peter Thornton, Steven Running, and Nándor Fodor
Geosci. Model Dev., 15, 2157–2181, https://doi.org/10.5194/gmd-15-2157-2022, https://doi.org/10.5194/gmd-15-2157-2022, 2022
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Biogeochemical models used by the scientific community can support society in the quantification of the expected environmental impacts caused by global climate change. The Biome-BGCMuSo v6.2 biogeochemical model has been created by implementing a lot of developments related to soil hydrology as well as the soil carbon and nitrogen cycle and by integrating crop model components. Detailed descriptions of developments with case studies are presented in this paper.
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Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
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Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
This article is included in the Encyclopedia of Geosciences
Jinyun Tang, William J. Riley, and Qing Zhu
Geosci. Model Dev., 15, 1619–1632, https://doi.org/10.5194/gmd-15-1619-2022, https://doi.org/10.5194/gmd-15-1619-2022, 2022
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We here describe version 2 of BeTR, a reactive transport model created to help ease the development of biogeochemical capability in Earth system models that are used for quantifying ecosystem–climate feedbacks. We then coupled BeTR-v2 to the Energy Exascale Earth System Model to quantify how different numerical couplings of plants and soils affect simulated ecosystem biogeochemistry. We found that different couplings lead to significant uncertainty that is not correctable by tuning parameters.
This article is included in the Encyclopedia of Geosciences
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
This article is included in the Encyclopedia of Geosciences
Hui Tao, Kaishan Song, Ge Liu, Qiang Wang, Zhidan Wen, Pierre-Andre Jacinthe, Xiaofeng Xu, Jia Du, Yingxin Shang, Sijia Li, Zongming Wang, Lili Lyu, Junbin Hou, Xiang Wang, Dong Liu, Kun Shi, Baohua Zhang, and Hongtao Duan
Earth Syst. Sci. Data, 14, 79–94, https://doi.org/10.5194/essd-14-79-2022, https://doi.org/10.5194/essd-14-79-2022, 2022
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During 1984–2018, lakes in the Tibetan-Qinghai Plateau had the clearest water (mean 3.32 ± 0.38 m), while those in the northeastern region had the lowest Secchi disk depth (SDD) (mean 0.60 ± 0.09 m). Among the 10 814 lakes with > 10 years of SDD results, 55.4 % and 3.5 % experienced significantly increasing and decreasing trends of SDD, respectively. With the exception of Inner Mongolia–Xinjiang, more than half of lakes in all the other regions exhibited a significant trend of increasing SDD.
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Jing Tao, Qing Zhu, William J. Riley, and Rebecca B. Neumann
The Cryosphere, 15, 5281–5307, https://doi.org/10.5194/tc-15-5281-2021, https://doi.org/10.5194/tc-15-5281-2021, 2021
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We improved the DOE's E3SM land model (ELMv1-ECA) simulations of soil temperature, zero-curtain period durations, cold-season CH4, and CO2 emissions at several Alaskan Arctic tundra sites. We demonstrated that simulated CH4 emissions during zero-curtain periods accounted for more than 50 % of total emissions throughout the entire cold season (Sep to May). We also found that cold-season CO2 emissions largely offset warm-season net uptake currently and showed increasing trends from 1950 to 2017.
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Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
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We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
This article is included in the Encyclopedia of Geosciences
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
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Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters have been emerging, especially in the last 2 decades. A collection of model simulations in conjunction with causal theory points at climatic changes as a key driver of vegetation changes in natural ecosystems. Most models underestimate the observed vegetation browning, especially in tropical rainforests, which could be due to an excessive CO2 fertilization effect in models.
This article is included in the Encyclopedia of Geosciences
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
This article is included in the Encyclopedia of Geosciences
Daniel M. Ricciuto, Xiaojuan Yang, Dali Wang, and Peter E. Thornton
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-163, https://doi.org/10.5194/bg-2021-163, 2021
Publication in BG not foreseen
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This paper uses a novel approach to quantify the impacts of the choice of decomposition model on carbon and nitrogen cycling. We compare the models to experimental data that examined litter decomposition over five different biomes. Despite widely differing assumptions, the models produce similar patterns of decomposition when nutrients are limiting. This differs from past analyses that did not consider the impacts of changing environmental conditions or nutrients.
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Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
This article is included in the Encyclopedia of Geosciences
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
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We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
This article is included in the Encyclopedia of Geosciences
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
This article is included in the Encyclopedia of Geosciences
Debjani Sihi, Xiaofeng Xu, Mónica Salazar Ortiz, Christine S. O'Connell, Whendee L. Silver, Carla López-Lloreda, Julia M. Brenner, Ryan K. Quinn, Jana R. Phillips, Brent D. Newman, and Melanie A. Mayes
Biogeosciences, 18, 1769–1786, https://doi.org/10.5194/bg-18-1769-2021, https://doi.org/10.5194/bg-18-1769-2021, 2021
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Humid tropical soils are important sources and sinks of methane. We used model simulation to understand how different kinds of microbes and observed soil moisture and oxygen dynamics contribute to production and consumption of methane along a wet tropical hillslope during normal and drought conditions. Drought alters the diffusion of oxygen and microbial substrates into and out of soil microsites, resulting in enhanced methane release from the entire hillslope during drought recovery.
This article is included in the Encyclopedia of Geosciences
Zihao Bian, Hanqin Tian, Qichun Yang, Rongting Xu, Shufen Pan, and Bowen Zhang
Earth Syst. Sci. Data, 13, 515–527, https://doi.org/10.5194/essd-13-515-2021, https://doi.org/10.5194/essd-13-515-2021, 2021
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The estimation of manure nutrient production and application is critical for the efficient use of manure nutrients. This study developed four manure nitrogen and phosphorus datasets with high spatial resolution and a long time period (1860–2017) in the US. The datasets can provide useful information for stakeholders and scientists who focus on agriculture, nutrient budget, and biogeochemical cycle.
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Xiaoying Shi, Daniel M. Ricciuto, Peter E. Thornton, Xiaofeng Xu, Fengming Yuan, Richard J. Norby, Anthony P. Walker, Jeffrey M. Warren, Jiafu Mao, Paul J. Hanson, Lin Meng, David Weston, and Natalie A. Griffiths
Biogeosciences, 18, 467–486, https://doi.org/10.5194/bg-18-467-2021, https://doi.org/10.5194/bg-18-467-2021, 2021
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The Sphagnum mosses are the important species of a wetland ecosystem. To better represent the peatland ecosystem, we introduced the moss species to the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. We tested the model against field observations and used the model to make projections of the site's carbon cycle under warming and atmospheric CO2 concentration scenarios.
This article is included in the Encyclopedia of Geosciences
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
This article is included in the Encyclopedia of Geosciences
Robinson I. Negrón-Juárez, Jennifer A. Holm, Boris Faybishenko, Daniel Magnabosco-Marra, Rosie A. Fisher, Jacquelyn K. Shuman, Alessandro C. de Araujo, William J. Riley, and Jeffrey Q. Chambers
Biogeosciences, 17, 6185–6205, https://doi.org/10.5194/bg-17-6185-2020, https://doi.org/10.5194/bg-17-6185-2020, 2020
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The temporal variability in the Landsat satellite near-infrared (NIR) band captured the dynamics of forest regrowth after disturbances in Central Amazon. This variability was represented by the dynamics of forest regrowth after disturbances were properly represented by the ELM-FATES model (Functionally Assembled Terrestrial Ecosystem Simulator (FATES) in the Energy Exascale Earth System Model (E3SM) Land Model (ELM)).
This article is included in the Encyclopedia of Geosciences
Kuang-Yu Chang, William J. Riley, Patrick M. Crill, Robert F. Grant, and Scott R. Saleska
Biogeosciences, 17, 5849–5860, https://doi.org/10.5194/bg-17-5849-2020, https://doi.org/10.5194/bg-17-5849-2020, 2020
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Methane (CH4) is a strong greenhouse gas that can accelerate climate change and offset mitigation efforts. A key assumption embedded in many large-scale climate models is that ecosystem CH4 emissions can be estimated by fixed temperature relations. Here, we demonstrate that CH4 emissions cannot be parameterized by emergent temperature response alone due to variability driven by microbial and abiotic interactions. We also provide mechanistic understanding for observed CH4 emission hysteresis.
This article is included in the Encyclopedia of Geosciences
George C. Hurtt, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, Justin Fisk, Shinichiro Fujimori, Kees Klein Goldewijk, Tomoko Hasegawa, Peter Havlik, Andreas Heinimann, Florian Humpenöder, Johan Jungclaus, Jed O. Kaplan, Jennifer Kennedy, Tamás Krisztin, David Lawrence, Peter Lawrence, Lei Ma, Ole Mertz, Julia Pongratz, Alexander Popp, Benjamin Poulter, Keywan Riahi, Elena Shevliakova, Elke Stehfest, Peter Thornton, Francesco N. Tubiello, Detlef P. van Vuuren, and Xin Zhang
Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, https://doi.org/10.5194/gmd-13-5425-2020, 2020
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To estimate the effects of human land use activities on the carbon–climate system, a new set of global gridded land use forcing datasets was developed to link historical land use data to eight future scenarios in a standard format required by climate models. This new generation of land use harmonization (LUH2) includes updated inputs, higher spatial resolution, more detailed land use transitions, and the addition of important agricultural management layers; it will be used for CMIP6 simulations.
This article is included in the Encyclopedia of Geosciences
Haifan Liu, Heng Dai, Jie Niu, Bill X. Hu, Dongwei Gui, Han Qiu, Ming Ye, Xingyuan Chen, Chuanhao Wu, Jin Zhang, and William Riley
Hydrol. Earth Syst. Sci., 24, 4971–4996, https://doi.org/10.5194/hess-24-4971-2020, https://doi.org/10.5194/hess-24-4971-2020, 2020
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It is still challenging to apply the quantitative and comprehensive global sensitivity analysis method to complex large-scale process-based hydrological models because of variant uncertainty sources and high computational cost. This work developed a new tool and demonstrate its implementation to a pilot example for comprehensive global sensitivity analysis of large-scale hydrological modelling. This method is mathematically rigorous and can be applied to other large-scale hydrological models.
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Cited articles
Anisimov, O. A.: Potential feedback of thawing permafrost to the global climate system through methane emission, Environ. Res. Lett., 2, 045016, https://doi.org/10.1088/1748-9326/2/4/045016, 2007.
Arah, J. R. M. and Kirk, G. J. D.: Modeling rice plant-mediated methane emission, Nutr. Cycl. Agroecosys., 58, 221–230, 2000.
Arah, J. R. M. and Stephen, K. D.: A model of the processes leading to methane emission from peatland, Atmos. Environ., 32, 3257–3264, 1998.
Aronson, E. and Helliker, B.: Methane flux in non-wetland soils in response to nitrogen addition: a meta-analysis, Ecology, 91, 3242–3251, 2010.
Askaer, L., Elberling, B., Friborg, T., Jørgensen, C. J., and Hansen, B. U.: Plant-mediated CH4 transport and C gas dynamics quantified in-situ in a Phalaris arundinacea-dominant wetland, Plant Soil, 343, 287–301, 2011.
Aulakh, M. S., Wassmann, R., Rennenberg, H., and Fink, S.: Pattern and amount of aerenchyma relate to variable methane transport capacity of different rice cultivars, Plant Biol., 2, 182–194, 2000.
Banger, K., Tian, H., and Lu, C.: Do nitrogen fertilizers stimulate or inhibit methane emissions from rice fields?, Glob. Change Biol., 18, 3259–3267, 2012.
Barber, T. R., Burke, R. A., and Sackett, W. M.: Diffusive flux of methane from warm wetlands, Global Biogeochem. Cy., 2, 411–425, 1988.
Barlett, K. B. and Harriss, R. C.: Review and assessment of methane emissions from wetlands, Chemosphere, 26, 261–320, 1993.
Becker, T., Kutzbach, L., Forbrich, I., Schneider, J., Jager, D., Thees, B., and Wilmking, M.: Do we miss the hot spots? – The use of very high resolution aerial photographs to quantify carbon fluxes in peatlands, Biogeosciences, 5, 1387–1393, https://doi.org/10.5194/bg-5-1387-2008, 2008.
Beckett, P. M., Armstrong, W., and Armstrong, J.: Mathematical modelling of methane transport by Phragmites: the potential for diffusion within the roots and rhizosphere, Aquat. Bot., 69, 293–312, 2001.
Beerling, D. J., Gardiner, T., Leggett, G., Mcleod, A., and Quick, W. P.: Missing methane emissions from leaves of terrestrial plants, Glob. Change Biol., 14, 1821–1826, 2008.
Bellisario, L., Bubier, J., Moore, T., and Chanton, J.: Controls on CH4 emissions from a northern peatland, Global Biogeochem. Cy., 13, 81–91, 1999.
Bhadra, A., Mukhopadhyay, S. N., and Ghose, T. K.: A kinetic model for methanogenesis of acetic acid in a multireactor system, Biotechnol. Bioeng., 26, 257–264, 1984.
Blazewicz, S. J., Petersen, D. G., Waldrop, M. P., and Firestone, M. K.: Anaerobic oxidation of methane in tropical and boreal soils: Ecological significance in terrestrial methane cycling, J. Geophys. Res.-Biogeo., 117, G02033, https://doi.org/10.1029/2011JG001864, 2012.
Blodau, C.: Carbon cycling in peatlands-A review of processes and controls, Environ. Rev., 10, 111–134, 2002.
Bohn, T. J. and Lettenmaier, D. P.: Systematic biases in large-scale estimates of wetland methane emissions arising from water table formulations, Geophys. Res. Lett., 37, L22401, https://doi.org/10.1029/2010GL045450, 2010.
Bohn, T. J., Lettenmaier, D. P., Sathulur, K., Bowling, L. C., Podest, E., McDonald, K. C., and Friborg, T.: Methane emissions from western Siberian wetlands: heterogeneity and sensitivity to climate change, Environ. Res. Lett., 2, 045015, https://doi.org/10.1088/1748-9326/2/4/045015, 2007.
Bohn, T. J., Melton, J. R., Ito, A., Kleinen, T., Spahni, R., Stocker, B. D., Zhang, B., Zhu, X., Schroeder, R., Glagolev, M. V., Maksyutov, S., Brovkin, V., Chen, G., Denisov, S. N., Eliseev, A. V., Gallego-Sala, A., McDonald, K. C., Rawlins, M. A., Riley, W. J., Subin, Z. M., Tian, H., Zhuang, Q., and Kaplan, J. O.: WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia, Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, 2015.
Bridgham, S. D., Cadillo-Quiroz, H., Keller, J. K., and Zhuang, Q.: Methane emissions from wetlands: biogeochemical, microbial, and modeling perspective from local to global scales, Glob. Change Biol., 19, 1325–1346, 2013.
Butterbach-Bahl, K., Papen, H., and Rennenberg, H.: Impact of gas transport through rice cultivars on methane emission from rice paddy fields, Plant Cell Environ., 20, 1175–1183, 1997.
Cai, Z.: Greenhouse gas budget for terrestrial ecosystems in China, Science China – Earth Sciences, 55, 173–182, 2012.
Caldwell, S. L., Laidler, J. R., Brewer, E. A., Eberly, J. O., Sandborgh, S. C., and Colwell, F. S.: Anaerobic oxidation of methane: mechanisms, bioenergetics, and ecology of associated microorganisms, Environ. Sci. Technol., 42, 6791–6799, 2008.
Cao, M. K., Dent, J. B., and Heal, O. W.: Modeling methane emissions from rice paddies, Global Biogeochem. Cy., 9, 183–195, 1995.
Cao, M. K., Gregson, K., and Marshall, S.: Global methane emission from wetlands and its sensitivity to climate change, Atmos. Environ., 32, 3293–3299, 1998.
Casella, G. and Robert, C. (Eds.): Monte Carlo statistical methods, Springer, New York, 2005.
Chanton, J. P.: The effect of gas transport on the isotope signature of methane in wetlands, Org. Geochem., 36, 753–768, 2005.
Chanton, J. P., Martens, C. S., and Kelley, C. A.: Gas transport from methane-saturated, tidal freshwater and wetland sediments, Limnol. Oceanogr, 34, 807–819, 1989.
Chen, H., Zhu, Q., Peng, C., Wu, N., Wang, Y., Fang, X., Jiang, H., Xiang, W., Chang, J., Deng, X., and Yu, G.: Methane emissions from rice paddies natural wetlands, and lakes in China: synthesis and new estimate, Glob. Change Biol., 19, 19–32, 2012.
Christensen, T. and Cox, P.: Response of methane emission from Arctic tundra to climatic change: results from a model simulation, Tellus B, 47, 301–309, 1995.
Christensen, T. R., Prentice, I. C., Kaplan, J. O., Haxeltine, A., and Sitch, S.: Methane flux from northern wetlands and tundra an ecosystem source modeling approach, Tellus, 48B, 652–661, 1996.
Colmer, T.: Long distance transport of gases in plants: a perspective on internal aeration and radial oxygen loss from roots, Plant Cell Environ., 26, 17–36, 2003.
Conrad, R.: Contribution of hydrogen to methane production and control of hydrogen concentration in methanogenic soils and sediments, FEMS Microbiol. Ecol., 28, 193–202, 1999.
Conrad, R.: Control of methane production in terrestrial ecosystems, in: Exchange of trace gases between terrestrial ecosystems and the atmosphere, edited by: Andrease, M. O. and Schimel, D. S., Springer, New York, 39–58, 1989.
Conrad, R.: Soil microbial processes involved in production and consumption of atmospheric trace gases, in: Advances in microbial ecology, Springer, 207–250, 1995.
Conrad, R.: Soil microorganisms as controllers of atmospheric trace gases (H2, CO, CH4, OCS, N2O, and NO), Microbiol. Rev., 60, 609–640, 1996.
Conrad, R.: Quantification of methanogenic pathways using stable carbon isotopic signatures: a review and a proposal, Org. Geochem., 36, 739–752, 2005.
Conrad, R.: The global methane cycle: recent advances in understanding the microbial processes involved, Environ. Microbiol. Reports, 1, 285–292, 2009.
Conrad, R. and Claus, P.: Contribution of methanol to the production of methane and its 13C-isotopic signature in anoxic rice field soil, Biogeochemistry, 73, 381–393, 2005.
Conrad, R. and Klose, M.: How specific is the inhibition by methyl fluoride of acetoclastic methanogenesis in anoxic rice field soil?, FEMS Microbiol. Ecol., 30, 47-56, 1999.
Cresto Aleina, F., Runkle, B. R. K., Kleinen, T., Kutzbach, L., Schneider, J., and Brovkin, V.: Modeling micro-topographic controls on boreal peatland hydrology and methane fluxes, Biogeosciences, 12, 5689–5704, https://doi.org/10.5194/bg-12-5689-2015, 2015.
Curry, C. L.: Modeling the soil consumption of atmospheric methane at the global scale, Global Biogeochem. Cy., 21, GB4012, https://doi.org/10.1029/2006GB002818, 2007.
Curry, C. L.: The consumption of atmospheric methane by soil in a simulated future climate, Biogeosciences, 6, 2355–2367, https://doi.org/10.5194/bg-6-2355-2009, 2009.
De Haas, Y., Windig, J., Calus, M., Dijkstra, J., De Haan, M., Bannink, A., and Veerkamp, R.: Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection, J. Dairy Sci., 94, 6122–6134, 2011.
De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Walker, A. P., Dietze, M. C., Wang, Y. P., Luo, Y., Jain, A. K., El Masri, B., and Hickler, T.: Where does the carbon go? A model–data intercomparison of vegetation carbon allocation and turnover processes at two temeperate forest free air CO2, enrichment sites, New Phytol., 203, 883–899, 2014.
Del Grosso, S. J., Ojima, D., Parton, W. J., Mosier, A., Peterson, G., and Schimel, D.: Simulated effects of dryland cropping intensification on soil organic matter and greenhouse gas exchanges using the DAYCENT ecosystem model, Environ. Pollut., 116, S75–S83, 2002.
Del Grosso, S. J., Ojima, D. S., Parton, W. J., Stehfest, E., Heistemann, M., DeAngelo, B. J., and Rose, S.: Global scale DAYCENT model analysis of greenhouse gas emissions and mitigation strategies for cropped soils, Global Planet. Change, 67, 44–50, 2009.
Del Grosso, S. J., Parton, W. J., Mosier, A. R., Ojima, D. S., Potter, C. S., Borken, W., Brumme, R., Butterbach-Bahl, K., Crill, P. M., Dobbie, K. E., and Smith, K. A.: General CH4 oxidation model and comparisons of CH4 oxidation in natural and managed systems, Global Biogeochem. Cy., 14, 999–1019, 2000.
DeLong, E. F., Harwood, C. S., Chisholm, P. W., Karl, D. M., Moran, M. A., Schmidt, T. M., Tiedje, J. M., Treseder, K. K., and Worden, A. Z.: Incorporating microbial processes into climate models, The American Academy of Microbiology, Washington DC, 2011.
De Visscher, A. and Van Cleemput, O.: Simulation model for gas diffusion and methane oxidation in landfill cover soils, Waste Manage., 23, 581–591, 2003.
Ding, A. and Wang, M.: Model for methane emission from rice paddies and its application in southern China, Adv. Atmos. Sci., 13, 159–168, 1996.
Dueck, T. A., De Visser, R., Poorter, H., Persijn, S., Gorissen, A., De Visser, W., Schapendonk, A., Verhagen, J., Snel, J., and Harren, F. J.: No evidence for substantial aerobic methane emission by terrestrial plants: a 13C labelling approach, New Phytol., 175, 29–35, 2007.
Eliseev, A. V., Mokhov, I. I., Arzhanov, M. M., Demchenko, P. F., and Denisov, S. N.: Interaction of the methane cycle and processes in wetland ecosystems in a climate model of intermediate complexity, Atmos. Ocean. Phys., 44, 139–152, 2008.
Elliott, S., Maltrud, M., Reagan, M., Moridis, G., and Cameron Smith, P.: Marine methane cycle simulations for the period of early global warming, J. Geophys. Res.-Biogeo., 116, G01010, https://doi.org/10.1029/2010JG001300, 2011.
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., and Johnson, J.: The soil moisture active passive (SMAP) mission, Proceedings of the IEEE, 98, 704–716, 2010.
Evans, M. R., Grimm, V., Johst, K., Knuuttila, T., de Langhe, R., Lessells, C. M., Merz, M., O'Malley, M. A., Orzack, S. H., and Weisberg, M.: Do simple models lead to generality in ecology?, Trends Ecol. Evol., 28, 578–583, 2013.
Falz, K. Z., Holliger, C., Grosskopf, R., Liesack, W., Nozhevnikova, A., Müller, B., Wehrli, B., and Hahn, D.: Vertical distribution of methanogens in the anoxic sediment of Rotsee (Switzerland), Appl. Environ. Microb., 65, 2402–2408, 1999.
Fan, Z., David McGuire, A., Turetsky, M. R., Harden, J. W., Michael Waddington, J., and Kane, E. S.: The response of soil organic carbon of a rich fen peatland in interior Alaska to projected climate change, Glob. Change Biol., 19, 604–620, 2013.
Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T., Betts, R., Fahey, D. W., Haywood, J., Lean, J., Lowe, D. C., Myhre, G., Nganga, J., Prinn, N. R., Raga, G., Schulz, M., and Dorland, R. V.: Changes in atmospheric constituents and in radiative forcing, in: Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change, edited by: Solomon, S., Qin, D., Manning, M., and Chen, Z., Cambridge University Press, Cambridge, United Kingdom and New York, USA, 133–216, 2007.
Frankenberg, C., Meirink, J. F., Van Weele, M., Platt, U., and Wagner, T.: Assessing methane emissions from global space-borne observations, Science, 308, 1010–1014, 2005.
Frenzel, P. and Karofeld, E.: CH4 emission from a hollow-ridge complex in a raised bog: the role of CH4 production and oxidation, Biogeochemistry, 51, 91–112, 2000.
Frenzel, P. and Rudolph, J.: Methane emission from a wetland plant: the role of CH4 oxidation in Eriophorum, Plant Soil, 202, 27–32, 1998.
Gao, C., Wang, H., Weng, E., Lakshmivarahan, S., Zhang, Y., and Luo, Y.: Assimilation of multiple data sets with the ensemble Kalman filter to improve forecasts of forest carbon dynamics, Ecol. Appl., 21, 1461–1473, 2011.
Gao, X., Schlosser, C. A., Sokolov, A., Anthony, K. W., Zhuang, Q., and Kicklighter, D.: Permafrost degradation and methane: low risk of biogeochemical climate-warming feedback, Environ. Res. Lett., 8, 035014, https://doi.org/10.1088/1748-9326/8/3/035014, 2013.
Gauthier, M., Bradley, R. L., and Šimek, M.: More evidence that anaerobic oxidation of methane is prevalent in soils: Is it time to upgrade our biogeochemical models?, Soil Biol. Biochem., 80, 167–174, 2015.
Gedney, N., Cox, P., and Huntingford, C.: Climate feedback from wetland methane emissions, Geophys. Res. Lett., 31, L20503, https://doi.org/10.1029/2004GL020919, 2004.
Gerard, G. and Chanton, J.: Quantification of methane oxidation in the rhizosphere of emergent aquatic macrophytes: defining upper limits, Biogeochemistry, 23, 79–97, 1993.
Gong, J., Kellomaki, S., Wang, K., Zhang, C., Shurpali, N., and Martikainen, P. J.: Modeling CO2 and CH4 flux changes in pristine peatlands of Finland under changing climate conditions, Ecol. Model., 263, 64–80, 2013.
Grant, R. and Roulet, N.: Methane efflux from boreal wetlands: Theory and testing of the ecosystem model Ecosys with chamber and tower flux measurements, Global Biogeochem. Cy., 16, 2-1–2-16, 2002.
Grant, R., Juma, N., and McGill, W.: Simulation of carbon and nitrogen transformations in soil: mineralization, Soil Biol. Biochem., 25, 1317–1329, 1993.
Grant, R. F.: Simulation of methanogenesis in the mathematical model Ecosys, Soil Biol. Biochem., 30, 883–896, 1998.
Grant, R. F.: A review of the Canadian ecosystem model ecosys, in: Modeling Carbon and Nitrogen Dynamics for Soil Management, edited by: Shaffer, M. J., Ma, L., and Hansen, S., CRC Press, New York,173–264, 2001.
Gulledge, J. and Schimel, J. P.: Low-concentration kinetics of atmospheric CH4 oxidation in soil and mechanism of NH4+ inhibition, Appl. Environ. Microb., 64, 4291–4298, 1998a.
Gulledge, J. and Schimel, J. P.: Moisture control over atmospheric CH4 consumption and CO2 production in diverse Alaskan soils, Soil Biol. Biochem., 30, 1127–1132, 1998b.
Hakemian, A. S. and Rosenzweig, A. C.: The biochemistry of methane oxidation, Annu. Rev. Biochem., 76, 223–241, 2007.
Hanson, R. S. and Hanson, T. E.: Methanotrophic bacteria, Microbiol. Mol. Biol. R., 60, 60, 439–471, 1996.
Heilman, M. A. and Carlton, R. G.: Methane oxidation associated with submersed vascular macrophytes and its impact on plant diffusive methane flux, Biogeochemistry, 52, 207–224, 2001.
Higgins, I. J., Best, D. J., Hammond, R. C., and Scott, D.: Methane-oxidizing microorganisms, Microbiol. Rev., 45, 556–590, 1981.
Hodson, E. L., Poulter, B., Zimmermann, N. E., Prigent, C., and Kaplan, J. O.: The El Nino-Southern Oscillation and wetland methane interannual variability, Geophys. Res. Lett., 38, L08810, https://doi.org/10.1029/2011GL046861, 2011.
Holgerson, M. A. and Raymond, P. A.: Large contribution to inland water CO2 and CH4 emissions from very small ponds, Nat. Geosci., 9, 222-226, 2016.
Hopcroft, P. O., Valdes, P. J., and Beerling, D. J.: Simulating idealized Dansgaard-Oeschger events and their potential impacts on the global methane cycle, Quarternary Sci. Rev., 30, 3258–3268, 2011.
Hosono, T. and Nouchi, I.: The dependence of methane transport in rice plants on the root zone temperature, Plant Soil, 191, 233–240, 1997.
Huang, Y., Sass, R. L., and Fisher, F. M.: Model estimates of methane emission from irrigated rice cultivation of China, Glob. Change Biol., 4, 809–821, https://doi.org/10.1046/j.1365-2486.1998.00175.x, 1998a.
Huang, Y., Sass, R. L., and Fisher, F. M.: A semi-empirical model of methane emission from flooded rice paddy soils, Glob. Change Biol., 4, 247–268, 1998b.
Huang, Y., Zhang, W., Zheng, X., Li, J., and Yu, Y.: Modeling methane emission from rice paddies with various agricultural practices, J. Geophys. Res., 109, D08113, https://doi.org/10.1029/2003JD004401, 2004.
Inatomi, M., Ito, A., Ishijima, K., and Murayama, S.: Greenhouse gas budget of a cool-temperate deciduous broad-leaved forest in Japan estimated using a process-based model, Ecosystems, 13, 472–483, 2010.
IPCC: Summary for policymakers, Cambridge, United Kingdom and New York, NY, USA, 2013.
Ito, A. and Inatomi, M.: Use of a process-based model for assessing the methane budgets of global terrestrial ecosystems and evaluation of uncertainty, Biogeosciences, 9, 759–773, https://doi.org/10.5194/bg-9-759-2012, 2012.
Karl, D. M., Beversdorf, L., Björkman, K. M., Church, M. J., Martinez, A., and Delong, E. F.: Aerobic production of methane in the sea, Nat. Geosci., 1, 473–478, 2008.
Keppler, F., Hamilton, J. T. G., Brass, M., and Rockmann, T.: Methane emissions from terrestrial plants under aerobic conditions, Nature, 439, 187–191, 2006.
Kettunen, A.: Connecting methane fluxes to vegetation cover and water table fluctuations at microsite level: a modeling study, Global Biogeochem. Cy., 17, 1051, https://doi.org/10.1029/2002GB001958, 2003.
King, G. M.: In Situ Analyses of Methane Oxidation Associated with the Roots and Rhizomes of a Bur Reed, Sparganium eurycarpum, in a Maine Wetland, Appl. Environ. Microb., 62, 4548–4555, 1996.
Kotsyurbenko, O. R., Chin, K. J., Glagolev, M. V., Stubner, S., Simankova, M. V., Nozhevnikova, A. N., and Conrad, R.: Acetoclastic and hydrogenotrophic methane production and methanogenic populations in an acidic West Siberian peat bog, Environ. Microbiol., 6, 1159–1173, 2004.
Koven, C. D., Ringeval, B., Friedlingstein, P., Ciais, P., Cadule, P., Khvorostyanov, D., Krinner, G., and Tarnocai, C.: Permafrost carbon-climate feedbacks accelerate global warming, P. Natl. Acad. Sci. USA, 108, 14769–14774, 2011.
Koven, C. D., Riley, W. J., Subin, Z. M., Tang, J. Y., Torn, M. S., Collins, W. D., Bonan, G. B., Lawrence, D. M., and Swenson, S. C.: The effect of vertically resolved soil biogeochemistry and alternate soil C and N models on C dynamics of CLM4, Biogeosciences, 10, 7109–7131, https://doi.org/10.5194/bg-10-7109-2013, 2013.
Krüger, M., Frenzel, P., and Conrad, R.: Microbial processes influencing methane emission from rice fields, Glob. Change Biol., 7, 49–63, 2001.
Krumholz, L. R., Hollenback, J. L., Roskes, S. J., and Ringelberg, D. B.: Methanogenesis and methanotrophy within a Sphagnum peatland, FEMS Microbiol. Ecol., 18, 215–224, 1995.
Lai, D. Y. F.: Methane dynamics in Northern Peatlands: A Review, Pedosphere, 19, 409–421, 2009.
Larsen, P. E., Gibbons, S. M., and Gilbert, J. A.: Modeling microbial community structure and functional diversity across time and space, FEMS Microbiol. Lett., 332, 91–98, 2012.
Lenhart, K., Bunge, M., Ratering, S., New, T. R., Schuttmann, I., Greule, M., Kammann, C., Schnell, S., Muller, C., Zorn, H., and Keppler, F.: Evidence for methane production by saprotrophic fungi, Nat. Commun., 3, 1046, https://doi.org/10.1038/ncomms2049, 2012.
Li, C.: Modeling trace gas emissions from agricultural ecosystems, Nutr. Cycl. Agroecosys., 58, 259–276, 2000.
Li, C., Frolking, S., Xiao, X., Moore III, B., Boles, S., Qiu, J., Huang, Y., Salas, W., and Sass, R.: Modeling impacts of farming management alternatives on CO2, CH4, and N2O emissions: a case study for water management of rice agriculture of China, Global Biogeochem. Cy., 19, GB3010, https://doi.org/10.1029/2004GB002341, 2005.
Li, T., Huang, Y., Zhang, W., and Yu, Y.-Q.: Methane emissions associated with the conversion of marshland to cropland and climate change on the Sanjiang Plain of northeast China from 1950 to 2100, Biogeosciences, 9, 5199–5215, https://doi.org/10.5194/bg-9-5199-2012, 2012.
Liu, L. and Greaver, T.: A review of nitrogen enrichment effects on three biogenic GHGs: the CO2 sink may be largely offset by stimulated N2O and CH4 emission, Ecol. Lett., 12, 1103–1117, 2009.
Lovley, D. P. and Klug, M. J.: Model for distribution of sulfate reduction and methanogenesis in freshwater sediments, Geochim. Cosmochim. Ac., 50, 11–18, 1986.
Luo, Y. Q., Randerson, J. T., Abramowitz, G., Bacour, C., Blyth, E., Carvalhais, N., Ciais, P., Dalmonech, D., Fisher, J. B., Fisher, R., Friedlingstein, P., Hibbard, K., Hoffman, F., Huntzinger, D., Jones, C. D., Koven, C., Lawrence, D., Li, D. J., Mahecha, M., Niu, S. L., Norby, R., Piao, S. L., Qi, X., Peylin, P., Prentice, I. C., Riley, W., Reichstein, M., Schwalm, C., Wang, Y. P., Xia, J. Y., Zaehle, S., and Zhou, X. H.: A framework for benchmarking land models, Biogeosciences, 9, 3857–3874, https://doi.org/10.5194/bg-9-3857-2012, 2012.
Martens, C. S., Albert, D. B., and Alperin, M. J.: Biogeochemical processes controlling methane in gassy coastal sediments – Part 1, A model coupling organic matter flux to gas production, oxidation and transport, Cont. Shelf Res., 18, 1741–1770, 1998.
Martinson, G. O., Werner, F. A., Scherber, C., Conrad, R., Corre, M. D., Flessa, H., Wolf, K., Klose, M., Gradstein, S. R., and Veldkamp, E.: Methane emissions from tank bromeliads in neotropical forests, Nat. Geosci., 3, 766–769, 2010.
Massman, W., Sommerfeld, R., Mosier, A., Zeller, K., Hehn, T., and Rochelle, S.: A model investigation of turbulence driven pressure pumping effects on the rate of diffusion of CO2, N2O, and CH4 through layered snowpacks, J. Geophys. Res.-Atmos., 102, 18851–18863, 1997.
Mastepanov, M., Sigsgaard, C., Dlugokencky, E. J., Houweling, S., Strom, L., Tamstorf, M. P., and Christensen, T. R.: Large tundra methane burst during onset of freezing, Nature, 456, 628–630, 2008.
Matthews, E. and Fung, I.: Methane emissions from natural wetlands: global distribution, area and environmental characteristics of sources, Global Biogeochem. Cy., 1, 61–86, 1987.
Matthews, R. B., Wassmann, R., and Arah, J. R. M.: Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in Asia, I. model development, Nutr. Cycl. Agroecosys., 58, 141–159, 2000.
Mau, S., Blees, J., Helmke, E., Niemann, H., and Damm, E.: Vertical distribution of methane oxidation and methanotrophic response to elevated methane concentrations in stratified waters of the Arctic fjord Storfjorden (Svalbard, Norway), Biogeosciences, 10, 6267–6278, https://doi.org/10.5194/bg-10-6267-2013, 2013.
McCalley, C. K., Woodcroft, B. J., Hodgkins, S. B., Wehr, R. A., Kim, E.-H., Mondav, R., Crill, P. M., Chanton, J. P., Rich, V. I., Tyson, G. W., and Saleska, S. R.: Methane dynamics regulated by microbial community response to permafrost thaw, Nature, 514, 478–481, 2014.
Melloh, R. A. and Crill, P. M.: Winter methane dynamics in a temperate peatland, Global Biogeochem. Cy., 10, 247–254, 1996.
Melton, J. R., Wania, R., Hodson, E. L., Poulter, B., Ringeval, B., Spahni, R., Bohn, T., Avis, C. A., Beerling, D. J., Chen, G., Eliseev, A. V., Denisov, S. N., Hopcroft, P. O., Lettenmaier, D. P., Riley, W. J., Singarayer, J. S., Subin, Z. M., Tian, H., Zürcher, S., Brovkin, V., van Bodegom, P. M., Kleinen, T., Yu, Z. C., and Kaplan, J. O.: Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP), Biogeosciences, 10, 753–788, https://doi.org/10.5194/bg-10-753-2013, 2013.
Meng, L., Hess, P. G. M., Mahowald, N. M., Yavitt, J. B., Riley, W. J., Subin, Z. M., Lawrence, D. M., Swenson, S. C., Jauhiainen, J., and Fuka, D. R.: Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations, Biogeosciences, 9, 2793–2819, https://doi.org/10.5194/bg-9-2793-2012, 2012.
Mer, J. L. and Roger, P.: Production, oxidation, emission and consumption of methane by soils: a review, Eur. J. Soil Biol., 37, 25–50, 2001.
Miller, K. E., Lai, C.-T., Friedman, E. S., Angenent, L. T., and Lipson, D. A.: Methane suppression by iron and humic acids in soils of the Arctic Coastal Plain, Soil Biol. Biochem., 83, 176–183, 2015.
Mokhov, I. I., Eliseev, A. V., and Denisov, S. N.: Model diagnostics of variations in methane emissions by wetlands in the second half of the 20th century based on reanalysis data, Dokl. Earth Sci., 417, 1293–1297, 2007.
Monechi, S., Coccioni, R., and Rampino, M. R.: Large ecosystem perturbations: causes and consequences, Geological Society of America, Boulder, Colo., 2007.
Morrissey, L. and Livingston, G.: Methane emissions from Alaska arctic tundra: An assessment of local spatial variability, J. Geophys. Res.-Atmos., 97, 16661–16670, 1992.
Mosier, A., Delgado, J., Cochran, V., Valentine, D., and Parton, W.: Impact of agriculture on soil consumption of atmospheric CH4 and a comparison of CH4
Murase, J. and Kimura, M.: Methane production and its fate in paddy fields: IX. Methane flux distribution and decomposition of methane in the subsoil during the growth period of rice plants, Soil Sci. Plant Nutr., 42, 187–190, 1996.
Nauta, A. L., Heijmans, M. M., Blok, D., Limpens, J., Elberling, B., Gallagher, A., Li, B., Petrov, R. E., Maximov, T. C., and van Huissteden, J.: Permafrost collapse after shrub removal shifts tundra ecosystem to a methane source, Nature Climate Change, 5, 67–70, 2015.
Nazaries, L., Murrell, J. C., Millard, P., Baggs, L., and Singh, B. K.: Methane, microbes and models: fundamental understanding of the soil methane cycle for future predictions, Environ. Microbiol., 15, 2395–417, https://doi.org/10.1111/1462-2920.12149, 2013.
Nouchi, I., Mariko, S., and Aoki, K.: Mechanism of methane transport from the rhizosphere to the atmosphere through rice plants, Plant Physiol. 94, 59–66, 1990.
Nouchi, I., Hosono, T., Aoki, K., and Minami, K.: Seasonal variation in methane flux from rice paddies associated with methane concentration in soil water, rice biomass and temperature, and its modelling, Plant Soil, 161, 195–208, 1994.
Ogle, K. and Barber, J. J.: Bayesian data–model integration in plant physiological and ecosystem ecology, in: Progress in botany, Springer Verlag, Berlin, Heidelberg, 281–311, 2008.
Pareek, S., Matsui, S., Kim, S. K., and Shimizu, Y.: Mathematical modeling and simulation of methane gas production in simulated landfill column reactors under sulfidogenic and methanogenic environments, Water Sci. Technol., 39, 235–242, 1999.
Peng, C., Guiot, J., Wu, H., Jiang, H., and Luo, Y.: Integrating models with data in ecology and palaeoecology: advances towards a model–data fusion approach, Ecol. Lett., 14, 522–536, 2011.
Philippot, L., Andersson, S. G., Battin, T. J., Prosser, J. I., Schimel, J. P., Whitman, W. B., and Hallin, S.: The ecological coherence of high bacterial taxonomic ranks, Nat. Rev. Microbiol., 8, 523–529, 2010.
Potter, C. S.: An ecosystem simulation model for methane production and emission from wetlands, Global Biogeochem. Cy., 11, 495–506, 1997.
Potter, C. S., Davidson, E. A., and Verchot, L. V.: Estimation of global biogeochemical controls and seasonality in soil methane consumption, Chemosphere, 32, 2219–2246, 1996.
Ren, W., Tian, H., Xu, X., Liu, M., Lu, C., Chen, G., Melillo, J., Reilly, J., and Liu, J.: Spatial and temporal patterns of CO2 and CH4 fluxes in China's croplands in response to multifactor environmental changes, Tellus B, 63, 222–240, 2011.
Ricciuto, D. M., Davis, K. J., and Keller, K.: A bayesian calibration of a simple carbon cycle model: the role of observations in estimating and reducing uncertainty, Global Biogeochem. Cy., 22, GB2030, https://doi.org/2010.1029/2006GB002908, 2008.
Ridgwell, A. J., Marshall, S. J., and Gregson, K.: Consumption of atmospheric methane by soils: a process-based model, Global Biogeochem. Cy., 13, 59–70, 1999.
Riley, W. J., Subin, Z. M., Lawrence, D. M., Swenson, S. C., Torn, M. S., Meng, L., Mahowald, N. M., and Hess, P.: Barriers to predicting changes in global terrestrial methane fluxes: analyses using CLM4Me, a methane biogeochemistry model integrated in CESM, Biogeosciences, 8, 1925–1953, https://doi.org/10.5194/bg-8-1925-2011, 2011.
Ringeval, B., de Noblet-Ducoudre, N., Ciais, P., Bousquet, P., Prigent, C., Para, F., and Rossow, W. B.: An attempt to quantify the impact of changes in wetland extent on methane emissions on the seasonal and interannual time scales, Global Biogeochem. Cy., 24, GB2003, https://doi.org/10.1029/2008GB003354, 2010.
Ringeval, B., Friedlingstein, P., Koven, C., Ciais, P., de Noblet-Ducoudré, N., Decharme, B., and Cadule, P.: Climate-CH4 feedback from wetlands and its interaction with the climate-CO2 feedback, Biogeosciences, 8, 2137–2157, https://doi.org/10.5194/bg-8-2137-2011, 2011.
Rodhe, H.: A comparison of the contribution of various gases to the greenhouse effect, Science, 248, 1217–1219, 1990.
Schimel, J.: Ecosystem consequences of microbial diversity and community structure, in: Arctic and alpine biodiversity: patterns, causes and ecosystem consequences, Springer, Springer-Verlag, Berlin, Heidelberg, 239–254, 1995.
Schimel, J. P. and Gulledge, J.: Microbial community structure and global trace gases, Glob. Change Biol., 4, 745–758, 1998.
Schleip, C., Rais, A., and Menzel, A.: Bayesian analysis of temperature sensitivity of plant phenology in Germany, Agr. Forest Meteorol., 149, 1699–1708, 2009.
Schütz, H., Seiler, W., and Conrad, R.: Processes involved in formation and emission of methane in rice paddies, Biogeochemistry, 7, 33–53, 1989.
Segers, R.: Methane production and methane consumption: a review of processes underlying wetland methane fluxes, Biogeochemistry, 41, 23–51, 1998.
Segers, R. and Kengen, S. W. M.: Methane production as a function of anaerobic carbon mineralization: a process model, Soil Biol. Biochem., 30, 1107–1117, 1998.
Segers, R. and Leffelaar, P. A.: Modeling methane fluxes in wetlands with gas-transporting plants 1, single-root scale, J. Geophys. Res., 106, 3511–3528, 2001a.
Segers, R. and Leffelaar, P. A.: Modeling methane fluxes in wetlands with gas-transporting plants 3, plot scale, J. Geophys. Res., 106, 3541–3558, 2001b.
Segers, R., Rappoldt, C., and Leffelaar, P. A.: Modeling methane fluxes in wetlands with gas-transporting plants 2, soil layer scale, J. Geophys. Res., 106, 3529–3540, 2001.
Shoemaker, J. K., Keenan, T. F., Hollinger, D. Y., and Richardson, A. D.: Forest ecosystem changes from annual methane source to sink depending on late summer water balance, Geophys. Res. Lett., 41, 673–679, 2014.
Smemo, K. A. and Yavitt, J. B.: Anaerobic oxidation of methane: an underappreciated aspect of methane cycling in peatland ecosystems?, Biogeosciences, 8, 779–793, https://doi.org/10.5194/bg-8-779-2011, 2011.
Söhngen, N.: Über Bakterien, welche Methan als Kohlenstoffnahrung und Energiequelle gebrauchen, Zentrabl Bakteriol Parasitenk Infektionskr, 15, 513–517, 1906.
Song, C., Xu, X., Sun, X., Tian, H., Sun, L., Miao, Y., Wang, X., and Guo, Y.: Large methane emission upon spring thaw from natural wetlands in the northern permafrost region, Environ. Res. Lett., 7, 034009, https://doi.org/10.1088/1748-9326/7/3/034009, 2012.
Spahni, R., Wania, R., Neef, L., van Weele, M., Pison, I., Bousquet, P., Frankenberg, C., Foster, P. N., Joos, F., Prentice, I. C., and van Velthoven, P.: Constraining global methane emissions and uptake by ecosystems, Biogeosciences, 8, 1643–1665, https://doi.org/10.5194/bg-8-1643-2011, 2011.
Ström, L., Mastepanov, M., and Christensen, T. R.: Species-specific effects of vascular plants on carbon turnover and methane emissions from wetlands, Biogeochemistry, 75, 65–82, 2005.
Summons, R. E., Franzmann, P. D., and Nichols, P. D.: Carbon isotopic fractionation associated with methylotrophic methanogenesis, Org. Geochem., 28, 465–475, 1998.
Tagesson, T., Mastepanov, M., Mölder, M., Tamstorf, M. P., Eklundh, L., Smith, B., Sigsgaard, C., Lund, M., Ekberg, A., and Falk, J. M.: Modelling of growing season methane fluxes in a high-Arctic wet tundra ecosystem 1997–2010 using in situ and high-resolution satellite data, Tellus B, 65, 19722, https://doi.org/10.3402/tellusb.v65i0.19722, 2013.
Tang, J. and Zhuang, Q.: Equifinality in parameterization of process based biogeochemistry models: A significant uncertainty source to the estimation of regional carbon dynamics, J. Geophys. Res.-Biogeo., 113, G04010, https://doi.org/10.1029/2008JG000757, 2008.
Tang, J., Zhuang, Q., Shannon, R. D., and White, J. R.: Quantifying wetland methane emissions with process-based models of different complexities, Biogeosciences, 7, 3817–3837, https://doi.org/10.5194/bg-7-3817-2010, 2010.
Tang, J. Y. and Riley, W. J.: A total quasi-steady-state formulation of substrate uptake kinetics in complex networks and an example application to microbial litter decomposition, Biogeosciences, 10, 8329–8351, https://doi.org/10.5194/bg-10-8329-2013, 2013.
Tang, J. Y. and Riley, W. J.: Technical Note: Simple formulations and solutions of the dual-phase diffusive transport for biogeochemical modeling, Biogeosciences, 11, 3721–3728, https://doi.org/10.5194/bg-11-3721-2014, 2014.
Tian, H., Xu, X., Liu, M., Ren, W., Zhang, C., Chen, G., and Lu, C.: Spatial and temporal patterns of CH4 and N2O fluxes in terrestrial ecosystems of North America during 1979–2008: application of a global biogeochemistry model, Biogeosciences, 7, 2673–2694, https://doi.org/10.5194/bg-7-2673-2010, 2010.
Tokida, T., Mizoguchi, M., Miyazaki, T., Kagemoto, A., Nagata, O., and Hatano, R.: Episodic release of methane bubbles from peatland during spring thaw, Chemosphere, 70, 165–171, 2007.
Topp, E. and Pattey, E.: Soils as sources and sinks for atmospheric methane, Can. J. Soil Sci., 77, 167–177, 1997.
Tveit, A. T., Urich, T., Frenzel, P., and Svenning, M. M.: Metabolic and trophic interactions modulate methane production by Arctic peat microbiota in response to warming, P. Natl. Acad. Sci. USA, 112, E2507–E2516, 2015.
Valentine, D. L. and Reeburgh, W. S.: New perspectives on anaerobic methane oxidation, Environ. Microbiol., 2, 477–484, 2000.
van Bodegom, P. M., Leffelaar, P. A., Stams, A. J. M., and Wassmann, R.: Modeling methane emissions from rice fields: variability, uncertainty, and sensitivity analysis of processes involved, Nutr. Cycl. Agroecosys., 58, 231–248, 2000.
van Bodegom, P. M., Wassmann, R., and Metra-Corton, T. M.: A process-based model for methane emission predictions from flooded rice paddies, Global Biogeochem. Cy., 15, 247–263, 2001.
Van Oijen, M., Rougier, J., and Smith, R.: Bayesian calibration of process-based forest models: bridging the gap between models and data, Tree Physiol., 25, 915–927, 2005.
Volta, A.: Lettere dell'lllustrissimo Signor Volta Alessandro sull'aria inflammabile native dele paludi, in: Giuseppe Marelli, Milano, 1777.
Wagner, D., Lipski, A., Embacher, A., and Gattinger, A.: Methane fluxes in permafrost habitats of the Lena Delta: effects of microbial community structure and organic matter quality, Environ. Microbiol., 7, 1582–1592, 2005.
Wahlen, M.: The global methane cycle, Annu. Rev. Earth Pl. Sc., 21, 407–426, 1993.
Walter, B. P. and Heimann, M.: A process-based, climate-sensitive model to derive methane emissions from natural wetlands: Application to five wetland sites, sensitivity to model parameters, and climate, Global Biogeochem. Cy., 14, 745–765, 2000.
Walter, B. P., Heimann, M., Shannon, R. D., and White, J. R.: A process-based model to derive methane emissions from natural wetlands, Geophys. Res. Lett., 23, 3731–3734, 1996.
Wang, Z., Han, X., Wang, G. G., Song, Y., and Gulledge, J.: Aerobic methane emission from plants in the Inner Mongolia Steppe, Environ. Sci. Technol., 42, 62–68, 2007.
Wania, R.: Modelling northern peatland land surface processes, vegetation dynamics and methane emissions, Doktorarbeit, University of Bristol, Bristol, 1–140, 2007.
Wania, R., Ross, I., and Prentice, I. C.: Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes, Global Biogeochem. Cy., 23, GB3014, https://doi.org/10.1029/2008GB003412, 2009.
Wania, R., Ross, I., and Prentice, I. C.: Implementation and evaluation of a new methane model within a dynamic global vegetation model: LPJ-WHyMe v1.3.1, Geosci. Model Dev., 3, 565–584, https://doi.org/10.5194/gmd-3-565-2010, 2010.
Wania, R., Melton, J. R., Hodson, E. L., Poulter, B., Ringeval, B., Spahni, R., Bohn, T., Avis, C. A., Chen, G., Eliseev, A. V., Hopcroft, P. O., Riley, W. J., Subin, Z. M., Tian, H., van Bodegom, P. M., Kleinen, T., Yu, Z. C., Singarayer, J. S., Zürcher, S., Lettenmaier, D. P., Beerling, D. J., Denisov, S. N., Prigent, C., Papa, F., and Kaplan, J. O.: Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP), Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, 2013.
Wassmann, R., Neue, H., Lantin, R., Makarim, K., Chareonsilp, N., Buendia, L., and Rennenberg, H.: Characterization of methane emissions from rice fields in Asia. II. Differences among irrigated, rainfed, and deepwater rice, Nutr. Cycl. Agroecosys., 58, 13–22, 2000.
Watanabe, K. and Ito, M.: In situ observation of the distribution and activity of microorganisms in frozen soil, Cold Reg. Sci. Technol., 54, 1–6, 2008.
Watts, J. D., Kimball, J. S., Parmentier, F. J. W., Sachs, T., Rinne, J., Zona, D., Oechel, W., Tagesson, T., Jackowicz-Korczynski, M., and Aurela, M.: A satellite data driven biophysical modeling approach for estimating northern peatland and tundra CO2 and CH4 fluxes, Biogeosciences, 11, 1961–1980, https://doi.org/10.5194/bg-11-1961-2014, 2014.
Weller, G., Chapin, F. S., Everett, K. R., Hobbie, J. E., Kane, D., Oechel, W. C., Ping, C. L., Reeburgh, W. S., Walker, D., and Walsh, J.: The arctic flux study: A regional view of trace gas release, J. Biogeogr., 22, 365–374, 1995.
Whiting, G. J. and Chanton, J. P.: Control of the diurnal pattern of methane emission from emergent aquatic macrophytes by gas transport mechanisms, Aquat. Bot., 54, 237–253, 1996.
Xu, S., Jaffe, P. R., and Mauzerall, D. L.: A process-based model for methane emission from flooded rice paddy systems, Ecol. Model., 205, 475–491, 2007.
Xu, X.: Modeling methane and nitrous oxide exchanges between the atmosphere and terrestrial ecosystems over North America in the context of multifactor global change, PhD Dissertation, School of Forestry and Wildlife Sciences, Auburn University, Auburn, 199 pp., 2010.
Xu, X., Schimel, J. P., Thornton, P. E., Song, X., Yuan, F., and Goswami, S.: Substrate and environmental controls on microbial assimilation of soil organic carbon: a framework for Earth system models, Ecol. Lett., 17, 547–555, 2014.
Xu, X., Elias, D. A., Graham, D. E., Phelps, T. J., Carrol, S. L., Wullschleger, S. D., and Thornton, P. E.: A microbial functional group based module for simulating methane production and consumption: application to an incubation permafrost soil, J. Geophys. Res.-Biogeo., 120, 1315–1333, 2015.
Xu, X. and Tian, H.: Methane exchange between marshland and the atmosphere over China during 1949–2008, Global Biogeochem. Cy., 26, GB2006, https://doi.org/10.1029/2010GB003946, 2012.
Xu, X. F., Tian, H. Q., Zhang, C., Liu, M. L., Ren, W., Chen, G. S., Lu, C. Q., and Bruhwiler, L.: Attribution of spatial and temporal variations in terrestrial methane flux over North America, Biogeosciences, 7, 3637–3655, https://doi.org/10.5194/bg-7-3637-2010, 2010.
Xu, X. F., Hahn, M., Kumar, J., Yuan, F. M., Tang, G. P., Thornton, P., Torn, M., and Wullschleger, S.: Upscaling plot-scale methane flux to an eddy covariance tower domain in Barrow, AK: integrating in-situ data with a microbial functional group-based model, AGU Annual Fall meeting, San Francisco, 2014.
Yokota, T., Yoshida, Y., Eguchi, N., Ota, Y., Tanaka, T., Watanabe, H., and Maksyutov, S.: Global concentrations of CO2 and CH4 retrieved from GOSAT: First preliminary results, Sola, 5, 160–163, 2009.
Yvon-Durocher, G., Allen, A. P., Bastviken, D., Conrad, R., Gudasz, C., St-Pierre, A., Thanh-Duc, N., and Del Giorgio, P. A.: Methane fluxes show consistent temperature dependence across microbial to ecosystem scales, Nature, 507, 488–491, 2014.
Zhang, Y., Sachs, T., Li, C., and Boike, J.: Upscaling methane fluxes from closed chambers to eddy covariance based on a permafrost biogeochemistry integrated model, Glob. Change Biol., 18, 1428–1440, 2012.
Zhu, X., Zhuang, Q., Chen, M., Sirin, A., Melillo, J., Kicklighter, D., Sokolov, A., and Song, L.: Rising methane emissions in response to climate change in Northern Eurasia during the 21st century, Environ. Res. Lett., 6, 045211, https://doi.org/10.1088/1748-9326/6/4/045211, 2011.
Zhu, Q., Riley, W. J., Tang, J., and Koven, C. D.: Multiple soil nutrient competition between plants, microbes, and mineral surfaces: model development, parameterization, and example applications in several tropical forests, Biogeosciences, 13, 341–363, https://doi.org/10.5194/bg-13-341-2016, 2016.
Zhuang, Q., Melillo, J. M., Kicklighter, D. W., Prinn, R. G., McGuire, A. D., Steudler, P. A., Felzer, B. S., and Hu, S.: Methane fluxes between terrestrial ecosystems and the atmosphere at northern high latitudes during the past century: A retrospective analysis with a process-based biogeochemistry model, Global Biogeochem. Cy., 18, GB3010, https://doi.org/10.1029/2004GB002239, 2004.
Zona, D., Gioli, B., Commane, R., Lindaas, J., Wofsy, S. C., Miller, C. E., Dinardo, S. J., Dengei, S., Sweeney, C., Karion, A., Chang, R. Y.-W., Henderson, J. M., Murphy, P. C., Goodrich, J. P., Moreaux, V., Liljedahi, A., Watts, J. D., Kimball, J. S., Lipson, D. A., and Oechel, W. C.: Cold season emissions dominate the Arctic tundra methane budget, P. Natl. Acad. Sci. USA, 113, 40–45, 2016.
Short summary
Accurately projecting future climate change requires a good methane modeling. However, how good the current models are and what are the key improvements needed remain unclear. This paper reviews the 40 published methane models to characterize the strengths and weakness of current methane models and further lay out the roadmap for future model improvements.
Accurately projecting future climate change requires a good methane modeling. However, how good...
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