Articles | Volume 20, issue 14
https://doi.org/10.5194/bg-20-2813-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-2813-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Jul 2023
Research article |
| 17 Jul 2023
| 17 Jul 2023
Global evaluation of terrestrial biogeochemistry in the Energy Exascale Earth System Model (E3SM) and the role of the phosphorus cycle in the historical terrestrial carbon balance
Xiaojuan Yang
CORRESPONDING AUTHOR
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Lab, Oak Ridge, TN
37831, USA
Peter Thornton
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Lab, Oak Ridge, TN
37831, USA
Daniel Ricciuto
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Lab, Oak Ridge, TN
37831, USA
Yilong Wang
Key Laboratory of Land Surface Pattern and Simulation, Institute of
Geographic Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing, China
Laboratoire des Sciences du Climat et de l'Environnement,
CEA-CNRS-UVSQ-Université Paris Saclay, 91191, Gif-sur-Yvette CEDEX,
France
Forrest Hoffman
Climate Change Science Institute and Computational Sciences and Engineering Division, Oak Ridge National
Lab, Oak Ridge, TN 37831, USA
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Bin Wang, M. Luke McCormack, Daniel M. Ricciuto, Xiaojuan Yang, Min Xu, and Forrest M. Hoffman
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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Plants send about a third of their captured carbon below ground, to roots and soil fungi that take up water and nutrients. Most climate models still treat the entire root system as one uniform mass. We built a new land-model version that separates roots into three types: transport roots, absorptive roots, and fungal partners. Tested at twenty sites worldwide, it cut errors in simulated ecosystem carbon exchange by more than half, sharpening projections of how land will respond to climate change.
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Boreal peatlands store much of the global soil carbon and the service is closely related to nutrient cycling. This study improved a major land surface model to better represent how plants gain nitrogen and phosphorus through fine roots and mycorrhizal association. The new model more accurately captured observed carbon fluxes than the default model at an experimental site in Minnesota, and suggests shifts in nutrient uptake strategy mitigates transition from carbon sink to source under warming.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Kjetil Aas, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Nicolas Bellouin, Alice Benoit-Cattin, Carla F. Berghoff, Raffaele Bernardello, Laurent Bopp, Ida Bagus Mandhara Brasika, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Nathan O. Collier, Thomas H. Colligan, Margot Cronin, Laique M. Djeutchouang, Xinyu Dou, Matt P. Enright, Kazutaka Enyo, Michael Erb, Wiley Evans, Richard A. Feely, Liang Feng, Daniel J. Ford, Adrianna Foster, Filippa Fransner, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Jefferson Goncalves De Souza, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Bertrand Guenet, Özgür Gürses, Kirsty Harrington, Ian Harris, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Akihiko Ito, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Steve D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Yawen Kong, Jan Ivar Korsbakken, Charles Koven, Taro Kunimitsu, Xin Lan, Junjie Liu, Zhiqiang Liu, Zhu Liu, Claire Lo Monaco, Lei Ma, Gregg Marland, Patrick C. McGuire, Galen A. McKinley, Joe R. Melton, Natalie Monacci, Erwan Monier, Eric J. Morgan, David R. Munro, Jens D. Müller, Shin-Ichiro Nakaoka, Lorna R. Nayagam, Yosuke Niwa, Tobias Nutzel, Are Olsen, Abdirahman M. Omar, Naiqing Pan, Sudhanshu Pandey, Denis Pierrot, Zhangcai Qin, Pierre Regnier, Gregor Rehder, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, Ingunn Skjelvan, T. Luke Smallman, Victoria Spada, Mohanan G. Sreeush, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Didier Swingedouw, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Xiangjun Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Erik van Ooijen, Guido R. van der Werf, Sebastiaan J. van de Velde, Anthony P. Walker, Rik Wanninkhof, Xiaojuan Yang, Wenping Yuan, Xu Yue, and Jiye Zeng
Earth Syst. Sci. Data, 18, 3211–3288, https://doi.org/10.5194/essd-18-3211-2026, https://doi.org/10.5194/essd-18-3211-2026, 2026
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Short summary
The Global Carbon Budget 2025 describes the methodology, main results, and datasets 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 (1750–2025). 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.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data, 17, 2713–2733, https://doi.org/10.5194/essd-17-2713-2025, https://doi.org/10.5194/essd-17-2713-2025, 2025
Short summary
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We have developed new maps that reveal how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2500 gauges and a wealth of climate and environmental information. The maps are a critical step in understanding and predicting how carbon moves through our environment, hence making them a useful tool for tackling climate challenges.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets 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 (1750–2024). 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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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
Short summary
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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.
Forrest M. Hoffman, Birgit Hassler, Ranjini Swaminathan, Jared Lewis, Bouwe Andela, Nathan Collier, Dóra Hegedűs, Jiwoo Lee, Charlotte Pascoe, Mika Pflüger, Martina Stockhause, Paul Ullrich, Min Xu, Lisa Bock, Felicity Chun, Bettina K. Gier, Douglas I. Kelley, Axel Lauer, Julien Lenhardt, Manuel Schlund, Mohanan G. Sreeush, Katja Weigel, Ed Blockley, Rebecca Beadling, Romain Beucher, Demiso D. Dugassa, Valerio Lembo, Jianhua Lu, Swen Brands, Jerry Tjiputra, Elizaveta Malinina, Brian Medeiros, Enrico Scoccimarro, Jeremy Walton, Phil Kershaw, André Lanfer Marquez, Malcolm J. Roberts, Eleanor O'Rourke, Beth Dingley, Briony Turner, Helene Hewitt, and John P. Dunne
Geosci. Model Dev., 19, 7415–7455, https://doi.org/10.5194/gmd-19-7415-2026, https://doi.org/10.5194/gmd-19-7415-2026, 2026
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The Rapid Evaluation Framework (REF) is a community-driven platform for benchmarking and performance assessment of Earth system models. Built upon four disparate community evaluation tools, the REF is designed to provide model-data comparisons for the Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project. The REF will be run at the Earth System Grid Federation to enable model devleopers and scientists to quickly identify model biases and performance issues.
Bin Wang, M. Luke McCormack, Daniel M. Ricciuto, Xiaojuan Yang, Min Xu, and Forrest M. Hoffman
EGUsphere, https://doi.org/10.5194/egusphere-2026-2759, https://doi.org/10.5194/egusphere-2026-2759, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Plants send about a third of their captured carbon below ground, to roots and soil fungi that take up water and nutrients. Most climate models still treat the entire root system as one uniform mass. We built a new land-model version that separates roots into three types: transport roots, absorptive roots, and fungal partners. Tested at twenty sites worldwide, it cut errors in simulated ecosystem carbon exchange by more than half, sharpening projections of how land will respond to climate change.
Yaoping Wang, Daniel M. Ricciuto, Jiafu Mao, Sören E. Weber, Verity G. Salmon, Xiaoying Shi, Xiaojuan Yang, Natalie A. Griffiths, Paul J. Hanson, Anthony P. Walker, Jonathan Stelling, Katherine Duchesneau, Camille E. Defrenne, Jeffrey M. Warren, Stephen D. Sebestyen, Kyle J. Pearson, Keith Oleheiser, Joshua M. Birkebak, Mark Guilliams, Misha B. Krassovski, Melanie A. Mayes, and Peter E. Thornton
Geosci. Model Dev., 19, 5827–5855, https://doi.org/10.5194/gmd-19-5827-2026, https://doi.org/10.5194/gmd-19-5827-2026, 2026
Short summary
Short summary
Boreal peatlands store much of the global soil carbon and the service is closely related to nutrient cycling. This study improved a major land surface model to better represent how plants gain nitrogen and phosphorus through fine roots and mycorrhizal association. The new model more accurately captured observed carbon fluxes than the default model at an experimental site in Minnesota, and suggests shifts in nutrient uptake strategy mitigates transition from carbon sink to source under warming.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Kjetil Aas, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Nicolas Bellouin, Alice Benoit-Cattin, Carla F. Berghoff, Raffaele Bernardello, Laurent Bopp, Ida Bagus Mandhara Brasika, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Nathan O. Collier, Thomas H. Colligan, Margot Cronin, Laique M. Djeutchouang, Xinyu Dou, Matt P. Enright, Kazutaka Enyo, Michael Erb, Wiley Evans, Richard A. Feely, Liang Feng, Daniel J. Ford, Adrianna Foster, Filippa Fransner, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Jefferson Goncalves De Souza, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Bertrand Guenet, Özgür Gürses, Kirsty Harrington, Ian Harris, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Akihiko Ito, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Steve D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Yawen Kong, Jan Ivar Korsbakken, Charles Koven, Taro Kunimitsu, Xin Lan, Junjie Liu, Zhiqiang Liu, Zhu Liu, Claire Lo Monaco, Lei Ma, Gregg Marland, Patrick C. McGuire, Galen A. McKinley, Joe R. Melton, Natalie Monacci, Erwan Monier, Eric J. Morgan, David R. Munro, Jens D. Müller, Shin-Ichiro Nakaoka, Lorna R. Nayagam, Yosuke Niwa, Tobias Nutzel, Are Olsen, Abdirahman M. Omar, Naiqing Pan, Sudhanshu Pandey, Denis Pierrot, Zhangcai Qin, Pierre Regnier, Gregor Rehder, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, Ingunn Skjelvan, T. Luke Smallman, Victoria Spada, Mohanan G. Sreeush, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Didier Swingedouw, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Xiangjun Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Erik van Ooijen, Guido R. van der Werf, Sebastiaan J. van de Velde, Anthony P. Walker, Rik Wanninkhof, Xiaojuan Yang, Wenping Yuan, Xu Yue, and Jiye Zeng
Earth Syst. Sci. Data, 18, 3211–3288, https://doi.org/10.5194/essd-18-3211-2026, https://doi.org/10.5194/essd-18-3211-2026, 2026
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Short summary
The Global Carbon Budget 2025 describes the methodology, main results, and datasets 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 (1750–2025). 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.
Elias C. Massoud, Nathan Collier, Yaoping Wang, Jiafu Mao, Adrian Harpold, Steven A. Kannenberg, Gerbrand Koren, Mukesh Kumar, Pushpendra Raghav, Pallav Ray, Mingjie Shi, Jing Tao, Sreedevi P. Vasu, Huiqi Wang, Qing Zhu, and Forrest M. Hoffman
Geosci. Model Dev., 19, 3427–3453, https://doi.org/10.5194/gmd-19-3427-2026, https://doi.org/10.5194/gmd-19-3427-2026, 2026
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Soil moisture helps control how plants grow and how land exchanges water and energy with the atmosphere. We evaluated how well 16 Earth System Models represent soil moisture and its links to plant activity using a benchmarking system and observational data. Many models simulate surface soil moisture well but show larger errors deeper in the soil and in colder regions. Models that represent plant–soil water interactions more directly better capture how ecosystems respond to water availability.
Konstantin Gregor, Benjamin F. Meyer, Tillmann Gaida, Victor Justo Vasquez, Karina Bett-Williams, Matthew Forrest, João P. Darela-Filho, Sam Rabin, Marcos Longo, Joe R. Melton, Johan Nord, Peter Anthoni, Vladislav Bastrikov, Thomas Colligan, Christine Delire, Michael C. Dietze, George Hurtt, Akihiko Ito, Lasse T. Keetz, Jürgen Knauer, Johannes Köster, Tzu-Shun Lin, Lei Ma, Marie Minvielle, Stefan Olin, Sebastian Ostberg, Hao Shi, Reiner Schnur, Qing Sun, Peter E. Thornton, and Anja Rammig
Geosci. Model Dev., 19, 2407–2436, https://doi.org/10.5194/gmd-19-2407-2026, https://doi.org/10.5194/gmd-19-2407-2026, 2026
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Geoscientific models are crucial for understanding Earth’s processes. However, they sometimes do not adhere to highest software quality standards, and scientific results are often hard to reproduce due to the complexity of the workflows. Here we gather the expertise of 20 modeling groups and software engineers to define best practices for making geoscientific models maintainable, usable, and reproducible. We conclude with an open-source example serving as a reference for modeling communities.
Junyan Ding, Nate McDowell, Vanessa Bailey, Nate Conroy, Donnie J. Day, Yilin Fang, Kenneth M. Kemner, Matthew L. Kirwan, Charlie D. Koven, Matthew Kovach, Patrick Megonigal, Kendalynn A. Morris, Teri O'Meara, Stephanie C. Pennington, Roberta B. Peixoto, Peter Thornton, Mike Weintraub, Peter Regier, Leticia Sandoval, Fausto Machado-Silva, Alice Stearns, Nick Ward, and Stephanie J. Wilson
Biogeosciences, 22, 6963–6978, https://doi.org/10.5194/bg-22-6963-2025, https://doi.org/10.5194/bg-22-6963-2025, 2025
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We used a vegetation model to study why coastal forests are dying due to rising water levels and what happens to the ecosystem when marshes take over. We found that tree death is mainly caused by water-damaged roots, leading to major changes in the environment, such as reduced water use and carbon storage. Our study helps explain how coastal ecosystems are shifting and offers new ideas to explore in future field research.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data, 17, 2713–2733, https://doi.org/10.5194/essd-17-2713-2025, https://doi.org/10.5194/essd-17-2713-2025, 2025
Short summary
Short summary
We have developed new maps that reveal how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2500 gauges and a wealth of climate and environmental information. The maps are a critical step in understanding and predicting how carbon moves through our environment, hence making them a useful tool for tackling climate challenges.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets 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 (1750–2024). 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.
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.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
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.
Doaa Aboelyazeed, Chonggang Xu, Forrest M. Hoffman, Jiangtao Liu, Alex W. Jones, Chris Rackauckas, Kathryn Lawson, and Chaopeng Shen
Biogeosciences, 20, 2671–2692, https://doi.org/10.5194/bg-20-2671-2023, https://doi.org/10.5194/bg-20-2671-2023, 2023
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Photosynthesis is critical for life and has been affected by the changing climate. Many parameters come into play while modeling, but traditional calibration approaches face many issues. Our framework trains coupled neural networks to provide parameters to a photosynthesis model. Using big data, we independently found parameter values that were correlated with those in the literature while giving higher correlation and reduced biases in photosynthesis rates.
Bharat Sharma, Jitendra Kumar, Auroop R. Ganguly, and Forrest M. Hoffman
Biogeosciences, 20, 1829–1841, https://doi.org/10.5194/bg-20-1829-2023, https://doi.org/10.5194/bg-20-1829-2023, 2023
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Rising atmospheric carbon dioxide increases vegetation growth and causes more heatwaves and droughts. The impact of such climate extremes is detrimental to terrestrial carbon uptake capacity. We found that due to overall climate warming, about 88 % of the world's regions towards the end of 2100 will show anomalous losses in net biospheric productivity (NBP) rather than gains. More than 50 % of all negative NBP extremes were driven by the compound effect of dry, hot, and fire conditions.
Elise Potier, Grégoire Broquet, Yilong Wang, Diego Santaren, Antoine Berchet, Isabelle Pison, Julia Marshall, Philippe Ciais, François-Marie Bréon, and Frédéric Chevallier
Atmos. Meas. Tech., 15, 5261–5288, https://doi.org/10.5194/amt-15-5261-2022, https://doi.org/10.5194/amt-15-5261-2022, 2022
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Atmospheric inversion at local–regional scales over Europe and pseudo-data assimilation are used to evaluate how CO2 and 14CO2 ground-based measurement networks could complement satellite CO2 imagers to monitor fossil fuel (FF) CO2 emissions. This combination significantly improves precision in the FF emission estimates in areas with a dense network but does not strongly support the separation of the FF from the biogenic signals or the spatio-temporal extrapolation of the satellite information.
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.
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.
Martijn M. T. A. Pallandt, Jitendra Kumar, Marguerite Mauritz, Edward A. G. Schuur, Anna-Maria Virkkala, Gerardo Celis, Forrest M. Hoffman, and Mathias Göckede
Biogeosciences, 19, 559–583, https://doi.org/10.5194/bg-19-559-2022, https://doi.org/10.5194/bg-19-559-2022, 2022
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Thawing of Arctic permafrost soils could trigger the release of vast amounts of carbon to the atmosphere, thus enhancing climate change. Our study investigated how well the current network of eddy covariance sites to monitor greenhouse gas exchange at local scales captures pan-Arctic flux patterns. We identified large coverage gaps, e.g., in Siberia, but also demonstrated that a targeted addition of relatively few sites can significantly improve network performance.
Yaoping Wang, Jiafu Mao, Mingzhou Jin, Forrest M. Hoffman, Xiaoying Shi, Stan D. Wullschleger, and Yongjiu Dai
Earth Syst. Sci. Data, 13, 4385–4405, https://doi.org/10.5194/essd-13-4385-2021, https://doi.org/10.5194/essd-13-4385-2021, 2021
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We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and multilayer) by merging a wide range of data sources, including in situ and satellite observations, reanalysis, offline land surface model simulations, and Earth system model simulations. Given the great value of long-term, multilayer, gap-free soil moisture products to climate research and applications, we believe this paper and the presented datasets would be of interest to many different communities.
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021, https://doi.org/10.5194/gmd-14-5217-2021, 2021
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In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
Cited articles
Ainsworth, E. A. and Long, S. P.: What have we learned from 15 years of
free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of
photosynthesis, canopy properties and plant production to rising CO2, New
Phytol., 165, 351–372, https://doi.org/10.1111/j.1469-8137.2004.01224.x, 2005.
Aragão, L. E. O. C., Malhi, Y., Metcalfe, D. B., Silva-Espejo, J. E., Jiménez, E., Navarrete, D., Almeida, S., Costa, A. C. L., Salinas, N., Phillips, O. L., Anderson, L. O., Alvarez, E., Baker, T. R., Goncalvez, P. H., Huamán-Ovalle, J., Mamani-Solórzano, M., Meir, P., Monteagudo, A., Patiño, S., Peñuela, M. C., Prieto, A., Quesada, C. A., Rozas-Dávila, A., Rudas, A., Silva Jr., J. A., and Vásquez, R.: Above- and below-ground net primary productivity across ten Amazonian forests on contrasting soils, Biogeosciences, 6, 2759–2778, https://doi.org/10.5194/bg-6-2759-2009, 2009.
Arora, V. K., Boer, G. J., Friedlingstein, P., Eby, M., Jones, C. D.,
Christian, J. R., Bonan, G., Bopp, L., Brovkin, V., and Cadule, P.:
Carbon–concentration and carbon–climate feedbacks in CMIP5 Earth system
models, J. Clim., 26, 5289–5314, 2013.
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020.
Avitabile, V., Herold, M., Heuvelink, G. B., Lewis, S. L., Phillips, O. L.,
Asner, G. P., Armston, J., Ashton, P. S., Banin, L., and Bayol, N.: An
integrated pan-tropical biomass map using multiple reference datasets,
Glob. Change Biol., 22, 1406–1420, 2016.
Baig, S., Medlyn, B. E., Mercado, L. M., and Zaehle, S.: Does the growth
response of woody plants to elevated CO2 increase with temperature? A
model-oriented meta-analysis, Glob. Change Biol., 21, 4303–4319, 2015.
Barron, A. R., Wurzburger, N., Bellenger, J. P., Wright, S. J., Kraepiel, A.
M., and Hedin, L. O.: Molybdenum limitation of asymbiotic nitrogen fixation
in tropical forest soils, Nat. Geosci., 2, 42–45, 2008.
Batjes, N. H.: Total carbon and nitrogen in the soils of the world, Eur.
J. Soil Sci., 65, 10–21, 2014.
Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais,
N., Rödenbeck, C., Arain, M. A., Baldocchi, D., and Bonan, G. B.:
Terrestrial gross carbon dioxide uptake: global distribution and covariation
with climate, Science, 329, 834–838, 2010.
Bonan, G. B., Lawrence, P. J., Oleson, K. W., Levis, S., Jung, M.,
Reichstein, M., Lawrence, D. M., and Swenson, S. C.: Improving canopy
processes in the Community Land Model version 4 (CLM4) using global flux
fields empirically inferred from FLUXNET data, J. Geophys.
Res.-Biogeo., 116, https://doi.org/10.1029/2010JG001593, 2011.
Bonan, G. B., Lombardozzi, D. L., Wieder, W. R., Oleson, K. W., Lawrence, D.
M., Hoffman, F. M., and Collier, N.: Model structure and climate data
uncertainty in historical simulations of the terrestrial carbon cycle
(1850–2014), Global Biogeochem. Cy., 33, 1310–1326, 2019.
Braakhekke, M. C., Rebel, K. T., Dekker, S. C., Smith, B., Beusen, A. H. W., and Wassen, M. J.: Nitrogen leaching from natural ecosystems under global change: a modelling study, Earth Syst. Dynam., 8, 1121–1139, https://doi.org/10.5194/esd-8-1121-2017, 2017.
Brenner, J., Porter, W., Phillips, J. R., Childs, J., Yang, X., and Mayes,
M. A.: Phosphorus sorption on tropical soils with relevance to Earth system
model needs, Soil Res., 57, 17–27, 2019.
Burrows, S., Maltrud, M., Yang, X., Zhu, Q., Jeffery, N., Shi, X., Ricciuto,
D., Wang, S., Bisht, G., and Tang, J.: The DOE E3SM v1. 1 Biogeochemistry
Configuration: Description and Simulated Ecosystem-Climate Responses to
Historical Changes in Forcing, J. Adv. Model. Earth
Syst., 12, e2019MS001766, https://doi.org/10.1029/2019MS001766, 2020.
Butler, O. M., Elser, J. J., Lewis, T., Mackey, B., and Chen, C.: The
phosphorus-rich signature of fire in the soil–plant system: a global
meta-analysis, Ecol. Lett., 21, 335–344, 2018.
Cabugao, K. G., Timm, C. M., Carrell, A. A., Childs, J., Lu, T.-Y. S.,
Pelletier, D. A., Weston, D. J., and Norby, R. J.: Root and rhizosphere
bacterial phosphatase activity varies with tree species and soil phosphorus
availability in Puerto Rico tropical forest, Front. Plant Sci., 8,
1834, https://doi.org/10.3389/fpls.2017.01834, 2017.
Campbell, J., Berry, J., Seibt, U., Smith, S. J., Montzka, S., Launois, T.,
Belviso, S., Bopp, L., and Laine, M.: Large historical growth in global
terrestrial gross primary production, Nature, 544, 84–87, 2017.
Cleveland, C., Townsend, A., Schimel, D., Fisher, H., Howarth, R., Hedin,
L., Perakis, S., Latty, E., Von Fischer, J., and Elseroad, A.: Global
patterns of terrestrial biological nitrogen (N2) fixation in natural
ecosystems, Global Biogeochem. Cy., 13, 623–645, 1999.
Collier, N., Hoffman, F. M., Lawrence, D. M., Keppel-Aleks, G., Koven, C.
D., Riley, W. J., Mu, M., and Randerson, J. T.: The International Land Model
Benchmarking (ILAMB) system: design, theory, and implementation, J.
Adv. Model. Earth Syst., 10, 2731–2754, 2018.
Crews, T. E., Farrington, H., and Vitousek, P. M.: Changes in asymbiotic,
heterotrophic nitrogen fixation on leaf litter of Metrosideros polymorpha
with long-term ecosystem development in Hawaii, Ecosystems, 3, 386–395,
2000.
Crous, K. Y., Osvaldsson, A., and Ellsworth, D. S.: Is phosphorus limiting
in a mature Eucalyptus woodland? Phosphorus fertilisation stimulates stem
growth, Plant Soil, 391, 293–305, 2015.
Davies-Barnard, T. and Friedlingstein, P.: The Global Distribution of
Biological Nitrogen Fixation in Terrestrial Natural Ecosystems, Global
Biogeochem. Cy., 34, e2019GB006387, https://doi.org/10.1029/2019gb006387, 2020.
Davies-Barnard, T., Meyerholt, J., Zaehle, S., Friedlingstein, P., Brovkin, V., Fan, Y., Fisher, R. A., Jones, C. D., Lee, H., Peano, D., Smith, B., Wårlind, D., and Wiltshire, A. J.: Nitrogen cycling in CMIP6 land surface models: progress and limitations, Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, 2020.
DeFries, R., Field, C., Fung, I., Collatz, G., and Bounoua, L.: Combining
satellite data and biogeochemical models to estimate global effects of
human-induced land cover change on carbon emissions and primary
productivity, Global Biogeochem. Cy., 13, 803–815, 1999.
Du, E., Terrer, C., Pellegrini, A. F., Ahlström, A., van Lissa, C. J.,
Zhao, X., Xia, N., Wu, X., and Jackson, R. B.: Global patterns of
terrestrial nitrogen and phosphorus limitation, Nat. Geosci., 13,
221–226, 2020.
Duarte, H. F., Raczka, B. M., Ricciuto, D. M., Lin, J. C., Koven, C. D., Thornton, P. E., Bowling, D. R., Lai, C.-T., Bible, K. J., and Ehleringer, J. R.: Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements, Biogeosciences, 14, 4315–4340, https://doi.org/10.5194/bg-14-4315-2017, 2017.
E3SM Project (DOE): Energy Exascale Earth System Model v1.0, Computer software [code], https://doi.org/10.11578/E3SM/dc.20180418.36, 2018.
Edwards, E., McCaffery, S., and Evans, J.: Phosphorus availability and
elevated CO2 affect biological nitrogen fixation and nutrient fluxes in a
clover dominated sward, New Phytol., 169, 157–167, 2006.
Ehlers, I., Augusti, A., Betson, T. R., Nilsson, M. B., Marshall, J. D., and
Schleucher, J.: Detecting long-term metabolic shifts using isotopomers:
CO2-driven suppression of photorespiration in C3 plants over the 20th
century, P. Natl. Acad. Sci. USA, 112, 15585–15590,
2015.
Ellsworth, D. S., Anderson, I. C., Crous, K. Y., Cooke, J., Drake, J. E.,
Gherlenda, A. N., Gimeno, T. E., Macdonald, C. A., Medlyn, B. E., and
Powell, J. R.: Elevated CO2 does not increase eucalypt forest productivity
on a low-phosphorus soil, Nat. Clim. Change, 7, 279–282, 2017.
Elser, J. J., Bracken, M. E. S., Cleland, E. E., Gruner, D. S., Harpole, W.
S., Hillebrand, H., Ngai, J. T., Seabloom, E. W., Shurin, J. B., and Smith,
J. E.: Global analysis of nitrogen and phosphorus limitation of primary
producers in freshwater, marine and terrestrial ecosystems, Ecol. Lett.,
10, 1135–1142, https://doi.org/10.1111/j.1461-0248.2007.01113.x, 2007.
Erb, K.-H., Kastner, T., Plutzar, C., Bais, A. L. S., Carvalhais, N.,
Fetzel, T., Gingrich, S., Haberl, H., Lauk, C., and Niedertscheider, M.:
Unexpectedly large impact of forest management and grazing on global
vegetation biomass, Nature, 553, 73–76, 2018.
Finzi, A. C., Norby, R. J., Calfapietra, C., Gallet-Budynek, A., Gielen, B.,
Holmes, W. E., Hoosbeek, M. R., Iversen, C. M., Jackson, R. B., and Kubiske,
M. E.: Increases in nitrogen uptake rather than nitrogen-use efficiency
support higher rates of temperate forest productivity under elevated CO2,
P. Natl. Acad. Sci. USA, 104, 14014–14019, 2007.
Fleischer, K., Rammig, A., De Kauwe, M. G., Walker, A. P., Domingues, T. F.,
Fuchslueger, L., Garcia, S., Goll, D. S., Grandis, A., and Jiang, M.: Amazon
forest response to CO2 fertilization dependent on plant phosphorus
acquisition, Nat. Geosci., 12, 736–741, 2019.
Gerber, S., Hedin, L. O., Oppenheimer, M., Pacala, S. W., and Shevliakova,
E.: Nitrogen cycling and feedbacks in a global dynamic land model, Global
Biogeochem. Cy., 24, GB1001, https://doi.org/10.1029/2008gb003336, 2010.
Ghimire, B., Riley, W. J., Koven, C. D., Mu, M., and Randerson, J. T.:
Representing leaf and root physiological traits in CLM improves global
carbon and nitrogen cycling predictions, J. Adv. Model.
Earth Syst., 8, 598–613, 2016.
Goll, D. S., Brovkin, V., Parida, B. R., Reick, C. H., Kattge, J., Reich, P. B., van Bodegom, P. M., and Niinemets, Ü.: Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling, Biogeosciences, 9, 3547–3569, https://doi.org/10.5194/bg-9-3547-2012, 2012.
Goll, D. S., Winkler, A. J., Raddatz, T., Dong, N., Prentice, I. C., Ciais, P., and Brovkin, V.: Carbon–nitrogen interactions in idealized simulations with JSBACH (version 3.10), Geosci. Model Dev., 10, 2009–2030, https://doi.org/10.5194/gmd-10-2009-2017, 2017a.
Goll, D. S., Vuichard, N., Maignan, F., Jornet-Puig, A., Sardans, J., Violette, A., Peng, S., Sun, Y., Kvakic, M., Guimberteau, M., Guenet, B., Zaehle, S., Penuelas, J., Janssens, I., and Ciais, P.: A representation of the phosphorus cycle for ORCHIDEE (revision 4520), Geosci. Model Dev., 10, 3745–3770, https://doi.org/10.5194/gmd-10-3745-2017, 2017b.
Haverd, V., Smith, B., Canadell, J. G., Cuntz, M., Mikaloff-Fletcher, S.,
Farquhar, G., Woodgate, W., Briggs, P. R., and Trudinger, C. M.: Higher than
expected CO2 fertilization inferred from leaf to global observations, Glob.
Change Biol., 26, 2390–2402, 2020.
Herbert, D. A. and Fownes, J. H.: Phosphorus limitation of forest leaf area
and net primary production on a highly weathered soil, Biogeochemistry, 29,
223–235, 1995.
Herbert, D. A., Williams, M., and Rastetter, E. B.: A model analysis of N
and P limitation on carbon accumulation in Amazonian secondary forest after
alternate land-use abandonment, Biogeochemistry, 65, 121–150, 2003.
Hoffman, F., Koven, C., Keppel-Aleks, G., Lawrence, D., Riley, W.,
Randerson, J., Ahlström, A., Abramowitz, G., Baldocchi, D., and Best,
M.: International land model benchmarking (ILAMB) 2016 Workshop Report, US
Department of Energy, Office of Science, 10, 1330803, https://doi.org/10.2172/1330803, 2017.
Hoffman, F. M., Randerson, J. T., Arora, V. K., Bao, Q., Cadule, P., Ji, D.,
Jones, C. D., Kawamiya, M., Khatiwala, S., and Lindsay, K.: Causes and
implications of persistent atmospheric carbon dioxide biases in Earth System
Models, J. Geophys. Res.-Biogeo., 119, 141–162, 2014.
Hou, E., Tan, X., Heenan, M., and Wen, D.: A global dataset of plant
available and unavailable phosphorus in natural soils derived by Hedley
method, Sci. Data, 5, 180166, https://doi.org/10.1038/sdata.2018.166, 2018.
Hou, E., Luo, Y., Kuang, Y., Chen, C., Lu, X., Jiang, L., Luo, X., and Wen,
D.: Global meta-analysis shows pervasive phosphorus limitation of
aboveground plant production in natural terrestrial ecosystems, Nat.
Commun., 11, 1–9, 2020.
Houghton, R. A.: The contemporary carbon cycle, Treat. Geochem., 8,
473–513, 2003.
Houlton, B. Z., Wang, Y.-P., Vitousek, P. M., and Field, C. B.: A unifying
framework for dinitrogen fixation in the terrestrial biosphere, Nature, 454,
327–330, https://doi.org/10.1038/nature07028, 2008.
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., and Ferreira, L.
G.: Overview of the radiometric and biophysical performance of the MODIS
vegetation indices, Remote Sens. Environ., 83, 195–213, 2002.
Hungate, B. A., Dukes, J. S., Shaw, M. R., Luo, Y., and Field, C. B.:
Nitrogen and climate change, Science, 302, 1512–1513, 2003.
Hungate, B. A., Stiling, P. D., Dijkstra, P., Johnson, D. W., Ketterer, M.
E., Hymus, G. J., Hinkle, C. R., and Drake, B. G.: CO2 elicits long-term
decline in nitrogen fixation, Science, 304, 1291, https://doi.org/10.1126/science.1095549, 2004.
Jahnke, R. A.: The phosphorus cycle, in: Global Biogeochemical Cycles, edited by: Butcher, S. S., Charlson, R. J., Orians, G. H., and Wolfe, G. V., Academic Press, London, 301–315, 1992.
Jiang, M., Caldararu, S., Zaehle, S., Ellsworth, D. S., and Medlyn, B. E.:
Towards a more physiological representation of vegetation phosphorus
processes in land surface models, New Phytol., 222, 1223–1229, 2019.
Jobbágy, E. G. and Jackson, R. B.: The vertical distribution of soil
organic carbon and its relation to climate and vegetation, Ecol.
Appl., 10, 423–436, 2000.
Joiner, J., Yoshida, Y., Zhang, Y., Duveiller, G., Jung, M., Lyapustin, A.,
Wang, Y., and Tucker, C. J.: Estimation of terrestrial global gross primary
production (GPP) with satellite data-driven models and eddy covariance flux
data, Remote Sens., 10, 1346, https://doi.org/10.3390/rs10091346, 2018.
Jones, C. D., Arora, V., Friedlingstein, P., Bopp, L., Brovkin, V., Dunne, J., Graven, H., Hoffman, F., Ilyina, T., John, J. G., Jung, M., Kawamiya, M., Koven, C., Pongratz, J., Raddatz, T., Randerson, J. T., and Zaehle, S.: C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6, Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, 2016.
Jung, C.-G., Shin, H.-J., Park, M.-J., Joh, H.-K., and Kim, S.-J.:
Evaluation of MODIS Gross Primary Production (GPP) by Comparing with GPP
from CO2 Flux Data Measured in a Mixed Forest Area, J. Korean
Soc. Agr. Eng., 53, 1–8, 2011.
Kobayashi, H. and Dye, D. G.: Atmospheric conditions for monitoring the
long-term vegetation dynamics in the Amazon using normalized difference
vegetation index, Remote Sens. Environ., 97, 519–525, 2005.
Köchy, M., Hiederer, R., and Freibauer, A.: Global distribution of soil organic carbon – Part 1: Masses and frequency distributions of SOC stocks for the tropics, permafrost regions, wetlands, and the world, SOIL, 1, 351–365, https://doi.org/10.5194/soil-1-351-2015, 2015.
Körner, C., Asshoff, R., Bignucolo, O., Hättenschwiler, S., Keel, S. G., Peláez-Riedl, S., Pepin, S., Siegwolf, R. T., and Zotz, G.: Carbon flux and growth in mature deciduous forest trees exposed to elevated CO2, Science, 309, 1360–1362, 2005.
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.
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C.,
Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., and Kennedy, D.:
The Community Land Model version 5: Description of new features,
benchmarking, and impact of forcing uncertainty, J. Adv.
Model. Earth Syst., https://doi.org/10.1029/2018MS001583, 2019.
Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S., O'Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., and Zaehle, S.: Global Carbon Budget 2016, Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, 2016.
LeBauer, D. S. and Treseder, K. K.: Nitrogen limitation of net primary
productivity in terrestrial ecosystems is globally distributed, Ecology, 89,
371–379, 2008.
Lin, B.-L., Sakoda, A., Shibasaki, R., Goto, N., and Suzuki, M.: Modelling a
global biogeochemical nitrogen cycle in terrestrial ecosystems, Ecol.
Model., 135, 89–110, 2000.
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.
Mao, J., Ricciuto, D. M., Thornton, P. E., Warren, J. M., King, A. W., Shi, X., Iversen, C. M., and Norby, R. J.: Evaluating the Community Land Model in a pine stand with shading manipulations and 13CO2 labeling, Biogeosciences, 13, 641–657, https://doi.org/10.5194/bg-13-641-2016, 2016.
Marklein, A. R. and Houlton, B. Z.: Nitrogen inputs accelerate phosphorus
cycling rates across a wide variety of terrestrial ecosystems, New
Phytol., 193, 696–704, 2012.
Matthews, E.: Global litter production, pools, and turnover times: Estimates
from measurement data and regression models, J. Geophys.
Res.-Atmos., 102, 18771–18800, 1997.
McGill, W. and Cole, C.: Comparative aspects of cycling of organic C, N, S
and P through soil organic matter, Geoderma, 26, 267–286, 1981.
Melillo, J., Steudler, P., Aber, J., Newkirk, K., Lux, H., Bowles, F.,
Catricala, C., Magill, A., Ahrens, T., and Morrisseau, S.: Soil warming and
carbon-cycle feedbacks to the climate system, Science, 298, 2173–2176, 2002.
Metcalfe, D. B., Ricciuto, D., Palmroth, S., Campbell, C., Hurry, V., Mao,
J., Keel, S. G., Linder, S., Shi, X., and Näsholm, T.: Informing climate
models with rapid chamber measurements of forest carbon uptake, Glob.
Change Biol., 23, 2130–2139, 2017.
Mitchard, E. T., Feldpausch, T. R., Brienen, R. J., Lopez-Gonzalez, G.,
Monteagudo, A., Baker, T. R., Lewis, S. L., Lloyd, J., Quesada, C. A., and
Gloor, M.: Markedly divergent estimates of A mazon forest carbon density
from ground plots and satellites, Global Ecol. Biogeogr., 23,
935–946, 2014.
Nakhavali, M. A., Mercado, L. M., Hartley, I. P., Sitch, S., Cunha, F. V., di Ponzio, R., Lugli, L. F., Quesada, C. A., Andersen, K. M., Chadburn, S. E., Wiltshire, A. J., Clark, D. B., Ribeiro, G., Siebert, L., Moraes, A. C. M., Schmeisk Rosa, J., Assis, R., and Camargo, J. L.: Representation of the phosphorus cycle in the Joint UK Land Environment Simulator (vn5.5_JULES-CNP), Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, 2022.
Nasto, M. K., Alvarez-Clare, S., Lekberg, Y., Sullivan, B. W., Townsend, A.
R., and Cleveland, C. C.: Interactions among nitrogen fixation and soil
phosphorus acquisition strategies in lowland tropical rain forests, Ecol.
Lett., 17, 1282–1289, 2014.
Norby, R. J., Gu, L., Haworth, I. C., Jensen, A. M., Turner, B. L., Walker,
A. P., Warren, J. M., Weston, D. J., Xu, C., and Winter, K.: Informing
models through empirical relationships between foliar phosphorus, nitrogen
and photosynthesis across diverse woody species in tropical forests of
Panama, New Phytol., 215, 1425–1437, 2017.
Olander, L. P. and Vitousek, P. M.: Regulation of soil phosphatase and
chitinase activityby N and P availability, Biogeochemistry, 49, 175–191,
2000.
Oleson, K., Lawrence, D., Bonan, G., Drewniak, B., Huang, M., Koven, C.,
Levis, S., Li, F., Riley, W., and Subin, Z.: Technical Description of
version 4.5 of the Community Land Model (CLM)(NCAR Technical Note No.
NCAR/TN-503+ STR). Citeseer, National Center for Atmospheric Research, P.O.
Box, 3000, https://doi.org/10.5065/D6RR1W7M, 2013.
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A.,
Phillips, O. L., Shvidenko, A., Lewis, S. L., and Canadell, J. G.: A large
and persistent carbon sink in the world's forests,
Science, 333, 988–993, 2011.
Post, W. M., Pastor, J., Zinke, P. J., and Stangenberger, A. G.: Global
patterns of soil nitrogen storage, Nature, 317, 613–616, 1985.
Quesada, C. A., Phillips, O. L., Schwarz, M., Czimczik, C. I., Baker, T. R., Patiño, S., Fyllas, N. M., Hodnett, M. G., Herrera, R., Almeida, S., Alvarez Dávila, E., Arneth, A., Arroyo, L., Chao, K. J., Dezzeo, N., Erwin, T., di Fiore, A., Higuchi, N., Honorio Coronado, E., Jimenez, E. M., Killeen, T., Lezama, A. T., Lloyd, G., López-González, G., Luizão, F. J., Malhi, Y., Monteagudo, A., Neill, D. A., Núñez Vargas, P., Paiva, R., Peacock, J., Peñuela, M. C., Peña Cruz, A., Pitman, N., Priante Filho, N., Prieto, A., Ramírez, H., Rudas, A., Salomão, R., Santos, A. J. B., Schmerler, J., Silva, N., Silveira, M., Vásquez, R., Vieira, I., Terborgh, J., and Lloyd, J.: Basin-wide variations in Amazon forest structure and function are mediated by both soils and climate, Biogeosciences, 9, 2203–2246, https://doi.org/10.5194/bg-9-2203-2012, 2012.
Raczka, B., Duarte, H. F., Koven, C. D., Ricciuto, D., Thornton, P. E., Lin, J. C., and Bowling, D. R.: An observational constraint on stomatal function in forests: evaluating coupled carbon and water vapor exchange with carbon isotopes in the Community Land Model (CLM4.5), Biogeosciences, 13, 5183–5204, https://doi.org/10.5194/bg-13-5183-2016, 2016.
Reed, S. C., Cleveland, C. C., and Townsend, A. R.: Relationships among
phosphorus, molybdenum and free-living nitrogen fixation in tropical rain
forests: results from observational and experimental analyses,
Biogeochemistry, 1–13, https://doi.org/10.1007/s10533-013-9835-3, 2013.
Reed, S. C., Yang, X., and Thornton, P. E.: Incorporating phosphorus cycling
into global modeling efforts: a worthwhile, tractable endeavor, New
Phytol., 208, 324–329, 2015.
Santoro, M., Beaudoin, A., Beer, C., Cartus, O., Fransson, J. E., Hall, R.
J., Pathe, C., Schmullius, C., Schepaschenko, D., and Shvidenko, A.: Forest
growing stock volume of the northern hemisphere: Spatially explicit
estimates for 2010 derived from Envisat ASAR, Remote Sens. Environ.,
168, 316–334, 2015.
Sellar, A. A., Jones, C. G., Mulcahy, J., Tang, Y., Yool, A., Wiltshire, A.,
O'connor, F. M., Stringer, M., Hill, R., and Palmieri, J.: UKESM1:
Description and evaluation of the UK Earth System Model, J. Adv.
Model. Earth Syst., https://doi.org/10.1029/2019MS001739, 2019.
Shabanov, N. V., Huang, D., Yang, W., Tan, B., Knyazikhin, Y., Myneni, R.
B., Ahl, D. E., Gower, S. T., Huete, A. R., and Aragão, L. E. O.:
Analysis and optimization of the MODIS leaf area index algorithm retrievals
over broadleaf forests, IEEE T. Geosci. Remote Sens.,
43, 1855–1865, 2005.
Smil, V.: P Phosphorus in the Environment: Natural Flows and Human
Interferences, Ann. Rev. Energ. Environ., 25, 53–88, 2000.
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S.: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model, Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, 2014.
Sun, Y., Peng, S., Goll, D. S., Ciais, P., Guenet, B., Guimberteau, M.,
Hinsinger, P., Janssens, I. A., Peñuelas, J., and Piao, S.: Diagnosing
phosphorus limitations in natural terrestrial ecosystems in carbon cycle
models, Earth's Future, 5, 730–749, 2017.
Sun, Y., Goll, D. S., Ciais, P., Peng, S., Margalef, O., Asensio, D.,
Sardans, J., and Peñuelas, J.: Spatial pattern and environmental drivers
of acid phosphatase activity in Europe, Front. Big Data, 2, 2019, https://doi.org/10.3389/fdata.2019.00051, 2020.
Sun, Y., Goll, D. S., Chang, J., Ciais, P., Guenet, B., Helfenstein, J., Huang, Y., Lauerwald, R., Maignan, F., Naipal, V., Wang, Y., Yang, H., and Zhang, H.: Global evaluation of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 (r5986), Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021, 2021.
Terrer, C., Jackson, R. B., Prentice, I. C., Keenan, T. F., Kaiser, C.,
Vicca, S., Fisher, J. B., Reich, P. B., Stocker, B. D., and Hungate, B. A.:
Nitrogen and phosphorus constrain the CO2 fertilization of global plant
biomass, Nat. Clim. Change, 9, 684–689, 2019.
Thornton, P. E., Doney, S. C., Lindsay, K., Moore, J. K., Mahowald, N., Randerson, J. T., Fung, I., Lamarque, J.-F., Feddema, J. J., and Lee, Y.-H.: Carbon-nitrogen interactions regulate climate-carbon cycle feedbacks: results from an atmosphere-ocean general circulation model, Biogeosciences, 6, 2099–2120, https://doi.org/10.5194/bg-6-2099-2009, 2009.
Thornton, P. E., Lamarque, J.-F., Rosenbloom, N. A., and Mahowald, N. M.:
Influence of carbon-nitrogen cycle coupling on land model response to CO2
fertilization and climate variability, Global Biogeochem. Cy., 21,
GB4018, https://doi.org/10.1029/2006gb002868, 2007.
Thum, T., Caldararu, S., Engel, J., Kern, M., Pallandt, M., Schnur, R., Yu, L., and Zaehle, S.: A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996), Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, 2019.
Todd-Brown, K. E. O., Randerson, J. T., Post, W. M., Hoffman, F. M., Tarnocai, C., Schuur, E. A. G., and Allison, S. D.: Causes of variation in soil carbon simulations from CMIP5 Earth system models and comparison with observations, Biogeosciences, 10, 1717–1736, https://doi.org/10.5194/bg-10-1717-2013, 2013.
Treseder, K. K. and Vitousek, P. M.: Effects of soil nutrient availability
on investment in acquisition of N and P in Hawaiian rain forests, Ecology,
82, 946–954, 2001.
van den Hurk, B., Kim, H., Krinner, G., Seneviratne, S. I., Derksen, C., Oki, T., Douville, H., Colin, J., Ducharne, A., Cheruy, F., Viovy, N., Puma, M. J., Wada, Y., Li, W., Jia, B., Alessandri, A., Lawrence, D. M., Weedon, G. P., Ellis, R., Hagemann, S., Mao, J., Flanner, M. G., Zampieri, M., Materia, S., Law, R. M., and Sheffield, J.: LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project – aims, setup and expected outcome, Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, 2016.
Vicca, S., Luyssaert, S., Penuelas, J., Campioli, M., Chapin III, F., Ciais,
P., Heinemeyer, A., Högberg, P., Kutsch, W., and Law, B. E.: Fertile
forests produce biomass more efficiently, Ecol. Lett., 15, 520–526,
2012.
Vitousek, P. M., Porder, S., Houlton, B. Z., and Chadwick, O. A.:
Terrestrial phosphorus limitation: mechanisms, implications, and
nitrogen-phosphorus interactions, Ecol. Appl., 20, 5–15, 2010.
Vitousek, P. M., Menge, D. N., Reed, S. C., and Cleveland, C. C.: Biological
nitrogen fixation: rates, patterns and ecological controls in terrestrial
ecosystems, Philos. T. R. Soc. B, 368, 20130119, https://doi.org/10.1098/rstb.2013.0119, 2013.
Walker, A. P., Beckerman, A. P., Gu, L., Kattge, J., Cernusak, L. A.,
Domingues, T. F., Scales, J. C., Wohlfahrt, G., Wullschleger, S. D., and
Woodward, F. I.: The relationship of leaf photosynthetic traits–Vcmax and
Jmax–to leaf nitrogen, leaf phosphorus, and specific leaf area: a
meta-analysis and modeling study, Ecol. Evol., 4, 3218–3235, 2014.
Walker, T. and Syers, J.: The fate of phosphorus during pedogenesis,
Geoderma, 15, 1–19, 1976.
Wang, Y., Ciais, P., Goll, D., Huang, Y., Luo, Y., Wang, Y.-P., Bloom, A. A., Broquet, G., Hartmann, J., Peng, S., Penuelas, J., Piao, S., Sardans, J., Stocker, B. D., Wang, R., Zaehle, S., and Zechmeister-Boltenstern, S.: GOLUM-CNP v1.0: a data-driven modeling of carbon, nitrogen and phosphorus cycles in major terrestrial biomes, Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, 2018.
Wang, Y. P., Houlton, B. Z., and Field, C. B.: A model of biogeochemical
cycles of carbon, nitrogen, and phosphorus including symbiotic nitrogen
fixation and phosphatase production, Global Biogeochem. Cy., 21,
GB1018, https://doi.org/10.1029/2006gb002797, 2007.
Wang, Y.-P., Law, R. M., and Pak, B.: A global model of carbon, nitrogen and
phosphorus cycles for the terrestrial biosphere, Biogeosciences, 7,
2261–2282, https://doi.org/10.5194/bg-7-2261-2010, 2010.
Welp, L. R., Keeling, R. F., Meijer, H. A., Bollenbacher, A. F., Piper, S.
C., Yoshimura, K., Francey, R. J., Allison, C. E., and Wahlen, M.:
Interannual variability in the oxygen isotopes of atmospheric CO2 driven by
El Niño, Nature, 477, 579–582, 2011.
Wieder, W. R., Cleveland, C. C., Lawrence, D. M., and Bonan, G. B.: Effects
of model structural uncertainty on carbon cycle projections: biological
nitrogen fixation as a case study, Environ. Res. Lett., 10,
044016, https://doi.org/10.1088/1748-9326/10/4/044016, 2015a.
Wieder, W. R., Cleveland, C. C., Smith, W. K., and Todd-Brown, K.: Future
productivity and carbon storage limited by terrestrial nutrient
availability, Nat. Geosci., 8, 441, https://doi.org/10.1038/ngeo2413, 2015b.
Wieder, W. R., Lawrence, D. M., Fisher, R. A., Bonan, G. B., Cheng, S. J.,
Goodale, C. L., Grandy, A. S., Koven, C. D., Lombardozzi, D. L., and Oleson,
K. W.: Beyond static benchmarking: Using experimental manipulations to
evaluate land model assumptions, Global Biogeochem. Cy., 33,
1289–1309, 2019.
Wong, S.-C.: Elevated atmospheric partial pressure of CO2 and plant growth: II. Non-structural carbohydrate content in cotton plants and its effect on growth parameters, Photosyn. Res., 23, 171–180, 1990.
Wright, S. J., Turner, B. L., Yavitt, J. B., Harms, K. E., Kaspari, M.,
Tanner, E. V., Bujan, J., Griffin, E. A., Mayor, J. R., and Pasquini, S. C.:
Plant responses to fertilization experiments in lowland, species-rich,
tropical forests, Ecology, 99, 1129–1138, 2018.
Xu, R. I. and Prentice, I. C.: Terrestrial nitrogen cycle simulation with a
dynamic global vegetation model, Glob. Change Biol., 14, 1745–1764,
https://doi.org/10.1111/j.1365-2486.2008.01625.x, 2008.
Yang, X.: ELMv1 outputs for global scale evaluation, figshare [data set], https://doi.org/10.6084/m9.figshare.12021348.v1, 2020.
Yang, X. and Post, W. M.: Phosphorus transformations as a function of pedogenesis: A synthesis of soil phosphorus data using Hedley fractionation method, Biogeosciences, 8, 2907–2916, https://doi.org/10.5194/bg-8-2907-2011, 2011.
Yang, X., Wittig, V., Jain, A., and Post, W.: Integration of nitrogen cycle
dynamics into the Integrated Science Assessment Model for the study of
terrestrial ecosystem responses to global change, Global Biogeochem.
Cy., 23, https://doi.org/10.1029/2009GB003474, 2009.
Yang, X., Post, W. M., Thornton, P. E., and Jain, A.: The distribution of soil phosphorus for global biogeochemical modeling, Biogeosciences, 10, 2525–2537, https://doi.org/10.5194/bg-10-2525-2013, 2013.
Yang, X., Thornton, P. E., Ricciuto, D. M., and Post, W. M.: The role of phosphorus dynamics in tropical forests – a modeling study using CLM-CNP, Biogeosciences, 11, 1667–1681, https://doi.org/10.5194/bg-11-1667-2014, 2014.
Yang, X., Thornton, P. E., Ricciuto, D. M., and Hoffman, F. M.: Phosphorus
feedbacks constraining tropical ecosystem responses to changes in
atmospheric CO2 and climate, Geophys. Res. Lett., 43, 7205–7214,
https://doi.org/10.1002/2016GL069241, 2016.
Yang, X., Ricciuto, D. M., Thornton, P. E., Shi, X., Xu, M., Hoffman, F.,
and Norby, R. J.: The effects of phosphorus cycle dynamics on carbon sources
and sinks in the Amazon region: a modeling study using ELM v1, J.
Geophys. Res.-Biogeo., 124, https://doi.org/10.1029/2019JG005082, 2019.
Zaehle, S., Friend, A., Friedlingstein, P., Dentener, F., Peylin, P., and
Schulz, M.: Carbon and nitrogen cycle dynamics in the O-CN land surface
model: 2. Role of the nitrogen cycle in the historical terrestrial carbon
balance, Global Biogeochem. Cy., 24, https://doi.org/10.1029/2009GB003522, 2010.
Zhang, Q., Wang, Y.-P., Matear, R., Pitman, A., and Dai, Y.: Nitrogen and
phosphorous limitations significantly reduce future allowable CO2 emissions,
Geophys. Res. Lett., 41, 632–637, 2014.
Zhu, Q., Riley, W. J., Tang, J., Collier, N., Hoffman, F. M., Yang, X., and
Bisht, G.: Representing nitrogen, phosphorus, and carbon interactions in the
E3SM land model: Development and global benchmarking, J. Adv.
Model. Earth Syst., 11, 2238–2258, 2019.
Short summary
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.
We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N)...
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