Articles | Volume 16, issue 9
https://doi.org/10.5194/gmd-16-2455-2023
© 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/gmd-16-2455-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
09 May 2023
Model description paper |
| 09 May 2023
| 09 May 2023
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Potsdam Institute for Climate Impact Research (PIK), Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Susanne Rolinski
Potsdam Institute for Climate Impact Research (PIK), Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Christoph Müller
Potsdam Institute for Climate Impact Research (PIK), Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
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Livestock rearing in semi-arid steppe regions is traditionally extensive but under pressure both from increasing demand and by climate change. We demonstrate by applying a vegetation model that increasing management intensity by increasing fertilization and animal densities result in increasing livestock productivity but also environmental impacts in a nonlinear way. That allows to find management combinations with low environmental impacts without jeopardizing livestock productivity.
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We present a new modelling framework that links global vegetation and agricultural modelling with human decision-making processes in an integrated simulation approach. This makes it possible to explore how farming practices and environmental changes influence each other over time. By combining climate, land use, and social dynamics in one system, the framework opens new ways to study food security, climate adaptation strategies, and long-term impacts.
Luana Schwarz, Jannes Breier, Hannah Prawitz, Max Bechthold, Werner von Bloh, Sara M. Constantino, Dieter Gerten, Jobst Heitzig, Ronja Hotz, Leander John, Christoph Müller, Johan Rockström, and Jonathan F. Donges
EGUsphere, https://doi.org/10.5194/egusphere-2025-4079, https://doi.org/10.5194/egusphere-2025-4079, 2025
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We present a novel global model that links farmer decisions with ecological processes to explore how agricultural systems co-evolve. Unlike previous tools, it captures feedbacks between society and nature at up-to planetary scale. We find that conservation practices can restore soil health and support stable harvests. Adoption spreads through learning and norms, showing how regeneration at the farm scale can ripple outward, contributing to global sustainability and Earth system resilience.
Lily-belle Sweet, Christoph Müller, Jonas Jägermeyr, and Jakob Zscheischler
EGUsphere, https://doi.org/10.5194/egusphere-2025-3006, https://doi.org/10.5194/egusphere-2025-3006, 2025
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This study presents a method to identify climate drivers of an impact, such as agricultural yield failure, from high-resolution weather data. The approach systematically generates, selects and combines predictors that generalise across different environments. Tested on crop model simulations, the identified drivers are used to create parsimonious models that achieve high predictive performance over long time horizons, offering a more interpretable alternative to black-box models.
Edna Johanna Molina Bacca, Miodrag Stevanović, Benjamin Leon Bodirsky, Jonathan Cornelis Doelman, Louise Parsons Chini, Jan Volkholz, Katja Frieler, Christopher Paul Oliver Reyer, George Hurtt, Florian Humpenöder, Kristine Karstens, Jens Heinke, Christoph Müller, Jan Philipp Dietrich, Hermann Lotze-Campen, Elke Stehfest, and Alexander Popp
Earth Syst. Dynam., 16, 753–801, https://doi.org/10.5194/esd-16-753-2025, https://doi.org/10.5194/esd-16-753-2025, 2025
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Land-use change projections are vital for impact studies. This study compares updated land-use model projections, including CO2 fertilization among other upgrades, from the MAgPIE and IMAGE models under three scenarios, highlighting differences, uncertainty hotspots, and harmonization effects. Key findings include reduced bioenergy crop demand projections and differences in grassland area allocation and sizes, with socioeconomic–climate scenarios' largest effect on variance starting in 2030.
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.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim G. Pinto, Markus Augenstein, Ting-Chen Chen, Hendrik Feldmann, Petra Friederichs, Daniel Gliksman, Laura Goulier, Karsten Haustein, Jens Heinke, Lisa Jach, Florian Knutzen, Stefan Kollet, Jürg Luterbacher, Niklas Luther, Susanna Mohr, Christoph Mudersbach, Christoph Müller, Efi Rousi, Felix Simon, Laura Suarez-Gutierrez, Svenja Szemkus, Sara M. Vallejo-Bernal, Odysseas Vlachopoulos, and Frederik Wolf
Nat. Hazards Earth Syst. Sci., 25, 541–564, https://doi.org/10.5194/nhess-25-541-2025, https://doi.org/10.5194/nhess-25-541-2025, 2025
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Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
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We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Felix Jäger, Jonas Schwaab, Yann Quilcaille, Michael Windisch, Jonathan Doelman, Stefan Frank, Mykola Gusti, Petr Havlik, Florian Humpenöder, Andrey Lessa Derci Augustynczik, Christoph Müller, Kanishka Balu Narayan, Ryan Sebastian Padrón, Alexander Popp, Detlef van Vuuren, Michael Wögerer, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 15, 1055–1071, https://doi.org/10.5194/esd-15-1055-2024, https://doi.org/10.5194/esd-15-1055-2024, 2024
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Climate change mitigation strategies developed with socioeconomic models rely on the widespread (re)planting of trees to limit global warming below 2°. However, most of these models neglect climate-driven shifts in forest damage like fires. By assessing existing mitigation scenarios, we show the exposure of projected forestation areas to fire-promoting weather conditions. Our study highlights the problem of ignoring climate-driven shifts in forest damage and ways to address it.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
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In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
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We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
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.
Sebastian Ostberg, Christoph Müller, Jens Heinke, and Sibyll Schaphoff
Geosci. Model Dev., 16, 3375–3406, https://doi.org/10.5194/gmd-16-3375-2023, https://doi.org/10.5194/gmd-16-3375-2023, 2023
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We present a new toolbox for generating input datasets for terrestrial ecosystem models from diverse and partially conflicting data sources. The toolbox documents the sources and processing of data and is designed to make inconsistencies between source datasets transparent so that users can make their own decisions on how to resolve these should they not be content with our default assumptions. As an example, we use the toolbox to create input datasets at two different spatial resolutions.
Efi Rousi, Andreas H. Fink, Lauren S. Andersen, Florian N. Becker, Goratz Beobide-Arsuaga, Marcus Breil, Giacomo Cozzi, Jens Heinke, Lisa Jach, Deborah Niermann, Dragan Petrovic, Andy Richling, Johannes Riebold, Stella Steidl, Laura Suarez-Gutierrez, Jordis S. Tradowsky, Dim Coumou, André Düsterhus, Florian Ellsäßer, Georgios Fragkoulidis, Daniel Gliksman, Dörthe Handorf, Karsten Haustein, Kai Kornhuber, Harald Kunstmann, Joaquim G. Pinto, Kirsten Warrach-Sagi, and Elena Xoplaki
Nat. Hazards Earth Syst. Sci., 23, 1699–1718, https://doi.org/10.5194/nhess-23-1699-2023, https://doi.org/10.5194/nhess-23-1699-2023, 2023
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The objective of this study was to perform a comprehensive, multi-faceted analysis of the 2018 extreme summer in terms of heat and drought in central and northern Europe, with a particular focus on Germany. A combination of favorable large-scale conditions and locally dry soils were related with the intensity and persistence of the events. We also showed that such extremes have become more likely due to anthropogenic climate change and might occur almost every year under +2 °C of global warming.
Kristine Karstens, Benjamin Leon Bodirsky, Jan Philipp Dietrich, Marta Dondini, Jens Heinke, Matthias Kuhnert, Christoph Müller, Susanne Rolinski, Pete Smith, Isabelle Weindl, Hermann Lotze-Campen, and Alexander Popp
Biogeosciences, 19, 5125–5149, https://doi.org/10.5194/bg-19-5125-2022, https://doi.org/10.5194/bg-19-5125-2022, 2022
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Soil organic carbon (SOC) has been depleted by anthropogenic land cover change and agricultural management. While SOC models often simulate detailed biochemical processes, the management decisions are still little investigated at the global scale. We estimate that soils have lost around 26 GtC relative to a counterfactual natural state in 1975. Yet, since 1975, SOC has been increasing again by 4 GtC due to a higher productivity, recycling of crop residues and manure, and no-tillage practices.
Vera Porwollik, Susanne Rolinski, Jens Heinke, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Biogeosciences, 19, 957–977, https://doi.org/10.5194/bg-19-957-2022, https://doi.org/10.5194/bg-19-957-2022, 2022
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The study assesses impacts of grass cover crop cultivation on cropland during main-crop off-season periods applying the global vegetation model LPJmL (V.5.0-tillage-cc). Compared to simulated bare-soil fallowing practices, cover crops led to increased soil carbon content and reduced nitrogen leaching rates on the majority of global cropland. Yield responses of main crops following cover crops vary with location, duration of altered management, crop type, water regime, and tillage practice.
Tobias Herzfeld, Jens Heinke, Susanne Rolinski, and Christoph Müller
Earth Syst. Dynam., 12, 1037–1055, https://doi.org/10.5194/esd-12-1037-2021, https://doi.org/10.5194/esd-12-1037-2021, 2021
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Soil organic carbon sequestration on cropland has been proposed as a climate change mitigation strategy. We simulate different agricultural management practices under climate change scenarios using a global biophysical model. We find that at the global aggregated level, agricultural management practices are not capable of enhancing total carbon storage in the soil, yet for some climate regions, we find that there is potential to enhance the carbon content in cropland soils.
Boris Sakschewski, Werner von Bloh, Markus Drüke, Anna Amelia Sörensson, Romina Ruscica, Fanny Langerwisch, Maik Billing, Sarah Bereswill, Marina Hirota, Rafael Silva Oliveira, Jens Heinke, and Kirsten Thonicke
Biogeosciences, 18, 4091–4116, https://doi.org/10.5194/bg-18-4091-2021, https://doi.org/10.5194/bg-18-4091-2021, 2021
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This study shows how local adaptations of tree roots across tropical and sub-tropical South America explain patterns of biome distribution, productivity and evapotranspiration on this continent. By allowing for high diversity of tree rooting strategies in a dynamic global vegetation model (DGVM), we are able to mechanistically explain patterns of mean rooting depth and the effects on ecosystem functions. The approach can advance DGVMs and Earth system models.
Cited articles
Abu Ghalia, M. and Dahman, Y.: Synthesis and utilization of natural
fiber-reinforced poly (lactic acid) bionanocomposites, in: Lignocellulosic
Fibre and Biomass-Based Composite Materials, Elsevier, 313–345,
https://doi.org/10.1016/B978-0-08-100959-8.00015-9, 2017. a
Amthor, J. S.: Efficiency of Lignin Biosynthesis: a Quantitative Analysis,
Ann. Botany, 91, 673–695, https://doi.org/10.1093/aob/mcg073, 2003. a, b
Baucher, M., Monties, B., Montagu, M. V., and Boerjan, W.: Biosynthesis and
Genetic Engineering of Lignin, Crit. Rev. Plant Sci., 17,
125–197, https://doi.org/10.1080/07352689891304203, 1998. a
Büchner, M. and Reyer, C.: ISIMIP3a atmospheric composition input data
(v1.2), ISIMIP Repository [data set], https://doi.org/10.48364/ISIMIP.664235.2, 2022. a, b
Chang, J., Ciais, P., Gasser, T., Smith, P., Herrero, M., Havlík, P.,
Obersteiner, M., Guenet, B., Goll, D. S., Li, W., Naipal, V., Peng, S., Qiu,
C., Tian, H., Viovy, N., Yue, C., and Zhu, D.: Climate warming from managed
grasslands cancels the cooling effect of carbon sinks in sparsely grazed and
natural grasslands, Nat. Commun., 12, 118,
https://doi.org/10.1038/s41467-020-20406-7, 2021. a
Chang, J. F., Viovy, N., Vuichard, N., Ciais, P., Wang, T., Cozic, A., Lardy, R., Graux, A.-I., Klumpp, K., Martin, R., and Soussana, J.-F.: Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe, Geosci. Model Dev., 6, 2165–2181, https://doi.org/10.5194/gmd-6-2165-2013, 2013. a
Clipes, R., Detmann, E., Silva, J., Vieira, R., Nunes, L., Lista, F., and
Ponciano, N.: Evaluation of acid detergent insoluble protein as an estimator
of rumen non-degradable protein in tropical grass forages, Arquivo
Brasileiro de Medicina Veterinária e Zootecnia, 58, 694–697,
https://doi.org/10.1590/S0102-09352006000400041, 2006. a
Coleman, S. W.: Predicting Forage Intake by Grazing Ruminants, Proceedings of
2005 Florida Ruminant Nutrition Symposium, 1–2 February 2005, Gainesville, Florida, 72–90, 2005. a
Coleman, S. W., Gunter, S. A., Sprinkle, J. E., and Neel, J. P.: Difficulties
associated with predicting forage intake by grazing beef cows, J.
Anim. Sci., 92, 2775–2784, https://doi.org/10.2527/jas.2013-7090, 2014. a, b
Conant, R. T., Cerri, C. E. P., Osborne, B. B., and Paustian, K.: Grassland
management impacts on soil carbon stocks: a new synthesis, Ecol.
Appl., 27, 662–668, https://doi.org/10.1002/eap.1473, 2017. a, b
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Müller Schmied, H., Hersbach, H., and Buontempo, C.: WFDE5: bias-adjusted ERA5 reanalysis data for impact studies, Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, 2020. a
Dijkstra, J., Oenema, O., van Groenigen, J., Spek, J., van Vuuren, A., and
Bannink, A.: Diet effects on urine composition of cattle and N2O emissions,
Animal, 7, 292–302, https://doi.org/10.1017/S1751731113000578, 2013. a, b
Faverdin, P., Baratte, C., Delagarde, R., and Peyraud, J. L.: GrazeIn: a model
of herbage intake and milk production for grazing dairy cows. 1. Prediction
of intake capacity, voluntary intake and milk production during lactation,
Grass Forage Sci., 66, 29–44, https://doi.org/10.1111/j.1365-2494.2010.00776.x,
2011. a
Fernández-Martínez, M., Sardans, J., Chevallier, F., Ciais, P.,
Obersteiner, M., Vicca, S., Canadell, J. G., Bastos, A., Friedlingstein, P.,
Sitch, S., Piao, S. L., Janssens, I. A., and Peñuelas, J.: Global
trends in carbon sinks and their relationships with CO2 and temperature,
Nat. Clim. Change, 9, 73–79, https://doi.org/10.1038/s41558-018-0367-7, 2019. a
Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Bakker, D. C. E., Hauck, J., Le Quéré, C., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Bates, N. R., Becker, M., Bellouin, N., Bopp, L., Chau, T. T. T., Chevallier, F., Chini, L. P., Cronin, M., Currie, K. I., Decharme, B., Djeutchouang, L. M., Dou, X., Evans, W., Feely, R. A., Feng, L., Gasser, T., Gilfillan, D., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Luijkx, I. T., Jain, A., Jones, S. D., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lienert, S., Liu, J., Marland, G., McGuire, P. C., Melton, J. R., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Niwa, Y., Ono, T., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Schwingshackl, C., Séférian, R., Sutton, A. J., Sweeney, C., Tanhua, T., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F., van der Werf, G. R., Vuichard, N., Wada, C., Wanninkhof, R., Watson, A. J., Willis, D., Wiltshire, A. J., Yuan, W., Yue, C., Yue, X., Zaehle, S., and Zeng, J.: Global Carbon Budget 2021, Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, 2022. a
Glasser, F., Doreau, M., Maxin, G., and Baumont, R.: Fat and fatty acid
content and composition of forages: A meta-analysis, Animal Feed Sci.
Tech., 185, 19–34, https://doi.org/10.1016/j.anifeedsci.2013.06.010, 2013. a
He, M., Zhou, G., Yuan, T., Groenigen, K. J., Shao, J., and Zhou, X.: Grazing
intensity significantly changes the C : N : P stoichiometry in grassland
ecosystems, Global Ecol. Biogeogr., 29, 355–369,
https://doi.org/10.1111/geb.13028, 2020. a
Heinke, J., Lannerstad, M., Gerten, D., Havlík, P., Herrero, M.,
Notenbaert, A. M. O., Hoff, H., and Müller, C.: Water Use in Global
Livestock Production – Opportunities and Constraints for Increasing Water
Productivity, Water Resour. Res., 56, e2019WR026995, https://doi.org/10.1029/2019WR026995,
2020. a
Heinke, J., Rolinski, S., and Müller, C.: LPJmL5.0-grazing Model Code, Zenodo [code],
https://doi.org/10.5281/zenodo.6806652, 2022. a
Herrero, M., Fawcett, R., Silveira, V., Busqué, J., Bernués, A.,
and Dent, J.: Modelling the growth and utilisation of kikuyu grass
(Pennisetum clandestinum) under grazing. 1. Model definition and
parameterisation, Agr. Syst., 65, 73–97,
https://doi.org/10.1016/S0308-521X(00)00028-7, 2000. a, b
Herrero, M., Havlik, P., Valin, H., Notenbaert, A., Rufino, M. C., Thornton,
P. K., Blummel, M., Weiss, F., Grace, D., and Obersteiner, M.: Biomass use,
production, feed efficiencies, and greenhouse gas emissions from global
livestock systems, P. Natl. Acad. Sci. USA, 110,
20888–20893, https://doi.org/10.1073/pnas.1308149110, 2013. a, b
Hodgson, J.: The control of herbage intake in the grazing ruminant,
P. Nutr. Soc., 44, 339–346,
https://doi.org/10.1079/PNS19850054, 1985. a
IPCC: Emissions from livestock and manure management, in: 2006 IPCC Guidelines
for National Greenhouse Gas inventories, pp. 10.1–10.87, Prepared by the
National Greenhouse Gas Inventories Programme, Hayama, Japan,
https://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_10_Ch10_Livestock.pdf (last access: 16 September 2021),
2006. a, b
Johnson, I. and Parsons, A.: A theoretical analysis of grass growth under
grazing, J. Theor. Biol., 112, 345–367,
https://doi.org/10.1016/S0022-5193(85)80292-7, 1985. a, b
Kim, H.: Global Soil Wetness Project Phase 3 Atmospheric Boundary Conditions
(Experiment 1), Data Integration and Analysis System (DIAS) [data set], https://doi.org/10.20783/DIAS.501, 2017. a
Klein Goldewijk, K., Beusen, A., Doelman, J., and Stehfest, E.: Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953, https://doi.org/10.5194/essd-9-927-2017, 2017. a, b
Kondo, M., Patra, P. K., Sitch, S., Friedlingstein, P., Poulter, B.,
Chevallier, F., Ciais, P., Canadell, J. G., Bastos, A., Lauerwald, R., Calle,
L., Ichii, K., Anthoni, P., Arneth, A., Haverd, V., Jain, A. K., Kato, E.,
Kautz, M., Law, R. M., Lienert, S., Lombardozzi, D., Maki, T., Nakamura, T.,
Peylin, P., Rödenbeck, C., Zhuravlev, R., Saeki, T., Tian, H., Zhu, D.,
and Ziehn, T.: State of the science in reconciling top‐down and
bottom‐up approaches for terrestrial CO2 budget, Global Change Biol.,
26, 1068–1084, https://doi.org/10.1111/gcb.14917, 2020. a
Kozlowski, L. P.: Proteome-pI: Proteome isoelectric point database, Nucleic
Acids Res., 45, D1112–D1116, https://doi.org/10.1093/nar/gkw978, 2017. a
Lange, S., Mengel, M., Treu, S., and Büchner, M.: ISIMIP3a atmospheric
climate input data (v1.0), ISIMIP Repository [data set], https://doi.org/10.48364/ISIMIP.982724, 2022. a, b
Lutz, F., Herzfeld, T., Heinke, J., Rolinski, S., Schaphoff, S., von Bloh, W., Stoorvogel, J. J., and Müller, C.: Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage), Geosci. Model Dev., 12, 2419–2440, https://doi.org/10.5194/gmd-12-2419-2019, 2019. a, b
McSherry, M. E. and Ritchie, M. E.: Effects of grazing on grassland soil
carbon: a global review, Global Change Biol., 19, 1347–1357,
https://doi.org/10.1111/gcb.12144, 2013. a
Moore, J. E., Brant, M. H., Kunkle, W. E., and Hopkins, D. I.: Effects of
supplementation on voluntary forage intake, diet digestibility, and animal
performance, J. Animal Sci., 77, 122,
https://doi.org/10.2527/1999.77suppl_2122x, 1999. a
Riedo, M., Grub, A., Rosset, M., and Fuhrer, J.: A pasture simulation model
for dry matter production, and fluxes of carbon, nitrogen, water and energy,
Ecol. Model., 105, 141–183, https://doi.org/10.1016/S0304-3800(97)00110-5,
1998. a
Rolinski, S., Müller, C., Heinke, J., Weindl, I., Biewald, A., Bodirsky, B. L., Bondeau, A., Boons-Prins, E. R., Bouwman, A. F., Leffelaar, P. A., te Roller, J. A., Schaphoff, S., and Thonicke, K.: Modeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6, Geosci. Model Dev., 11, 429–451, https://doi.org/10.5194/gmd-11-429-2018, 2018. a, b
Santos, J. and Huber, J.: Feeds, Prediction of Energy and Proteins | Feed
Proteins, in: Encyclopedia of Dairy Sciences, 2nd edn., edited by:
Fuquay, J. W., Academic Press, San Diego, 409–417,
https://doi.org/10.1016/B978-0-12-374407-4.00174-6, 2002. a
Tedeschi, L. O., Molle, G., Menendez, H. M., Cannas, A., and Fonseca, M. A.:
The assessment of supplementation requirements of grazing ruminants using
nutrition models, Translational Animal Science, 3, 811–828,
https://doi.org/10.1093/tas/txy140, 2019.
a
Tomé, D., Cordella, C., Dib, O., and Péron, C.: Nitrogen and
protein content measurement and nitrogen to protein conversion factors for
dairy and soy protein-based foods: a systematic review and modelling
analysis, World Health Organization and Food and Agriculture Organization of
the United Nations, Geneva,
https://apps.who.int/iris/handle/10665/331206 (last access: 25 November 2021), 2019. a
Tulloh, N. M.: Physical studies of the alimentary tract of grazing cattle,
New Zeal. J. Agr. Res., 9, 999–1008,
https://doi.org/10.1080/00288233.1966.10429360, 1966. a
von Bloh, W., Schaphoff, S., Müller, C., Rolinski, S., Waha, K., and Zaehle, S.: Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0), Geosci. Model Dev., 11, 2789–2812, https://doi.org/10.5194/gmd-11-2789-2018, 2018. a
Vuichard, N., Soussana, J.-F., Ciais, P., Viovy, N., Ammann, C., Calanca, P.,
Clifton-Brown, J., Fuhrer, J., Jones, M., and Martin, C.: Estimating the
greenhouse gas fluxes of European grasslands with a process-based model: 1.
Model evaluation from in situ measurements, Global Biogeochem. Cycles,
21, 1–14, https://doi.org/10.1029/2005GB002611, 2007. a
Weiss, W.: Feeds, Prediction of Energy and Proteins | Feed Energy, in:
Encyclopedia of Dairy Sciences, 2nd edn., edited by: Fuquay, J. W., Academic Press, San Diego, 403–408,
https://doi.org/10.1016/B978-0-12-374407-4.00173-4, 2011. a
Weiss, W., Conrad, H., and St. Pierre, N.: A theoretically-based model for
predicting total digestible nutrient values of forages and concentrates,
Animal Feed Sci. Tech., 39, 95–110,
https://doi.org/10.1016/0377-8401(92)90034-4, 1992. a, b
Yang, J. and Tian, H.: ISIMIP3b N-deposition input data (v1.0), ISIMIP Repository [data set],
https://doi.org/10.48364/ISIMIP.600567, 2020. a, b
Zhou, G., Zhou, X., He, Y., Shao, J., Hu, Z., Liu, R., Zhou, H., and
Hosseinibai, S.: Grazing intensity significantly affects belowground carbon
and nitrogen cycling in grassland ecosystems: a meta-analysis, Global Change
Biol., 23, 1167–1179, https://doi.org/10.1111/gcb.13431, 2017. a
Short summary
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of...
