Articles | Volume 21, issue 2
https://doi.org/10.5194/bg-21-381-2024
© Author(s) 2024. 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-21-381-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jan 2024
Research article |
| 22 Jan 2024
| 22 Jan 2024
Connecting competitor, stress-tolerator and ruderal (CSR) theory and Lund Potsdam Jena managed Land 5 (LPJmL 5) to assess the role of environmental conditions, management and functional diversity for grassland ecosystem functions
Stephen Björn Wirth
CORRESPONDING AUTHOR
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
Institute of Crop Science and Plant Breeding, Grass and Forage Science/Organic Agriculture, Kiel University, Hermann-Rodewald-Str. 9, 24118, Kiel, Germany
Arne Poyda
Institute of Crop Science and Plant Breeding, Grass and Forage Science/Organic Agriculture, Kiel University, Hermann-Rodewald-Str. 9, 24118, Kiel, Germany
Friedhelm Taube
Institute of Crop Science and Plant Breeding, Grass and Forage Science/Organic Agriculture, Kiel University, Hermann-Rodewald-Str. 9, 24118, Kiel, Germany
Britta Tietjen
Freie Universität Berlin, Institute of Biology, Theoretical Ecology, Königin-Luise-Str. 2/4, Gartenhaus, 14195 Berlin, Germany
Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), 14195 Berlin, Germany
Christoph Müller
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
Kirsten Thonicke
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
Anja Linstädter
University of Potsdam, Institute of Biochemistry and Biology, Potsdam, Germany
Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany
Kai Behn
University of Potsdam, Institute of Biochemistry and Biology, Potsdam, Germany
Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany
Sibyll Schaphoff
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
Werner von Bloh
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
Susanne Rolinski
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
Related authors
No articles found.
Edna Johanna Molina Bacca, Miodrag Stevanović, Benjamin Leon Bodirsky, Jonathan C. Doelman, Louise Parsons Chini, Jan Volkholz, Katja Frieler, Christopher Reyer, George Hurtt, Florian Humpenöder, Kristine Karstens, Jens Heinke, Christoph Müller, Jan Philipp Dietrich, Hermann Lotze-Campen, Elke Stehfest, and Alexander Popp
EGUsphere, https://doi.org/10.5194/egusphere-2024-2441, https://doi.org/10.5194/egusphere-2024-2441, 2024
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
EGUsphere, https://doi.org/10.5194/egusphere-2024-1914, https://doi.org/10.5194/egusphere-2024-1914, 2024
Short summary
Short summary
Under climate change, the conditions for wildfires to form are becoming more frequent in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a crucial platform for future developments.
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1973, https://doi.org/10.5194/egusphere-2024-1973, 2024
Short summary
Short summary
Climate change is causing an increase in extreme wildfires in Europe but drivers of fire are not well understood, especially across different land cover types. We used statistical models with satellite data, climate data and socioeconomic data to determine what affects burning in cropland and non-cropland area Europe. We found different drivers of burning in cropland burning vs non-cropland, to the point that some variable, e.g. population density, had completely the opposite effects.
Markus Drüke, Wolfgang Lucht, Werner von Bloh, Stefan Petri, Boris Sakschewski, Arne Tobian, Sina Loriani, Sibyll Schaphoff, Georg Feulner, and Kirsten Thonicke
Earth Syst. Dynam., 15, 467–483, https://doi.org/10.5194/esd-15-467-2024, https://doi.org/10.5194/esd-15-467-2024, 2024
Short summary
Short summary
The planetary boundary framework characterizes major risks of destabilization of the Earth system. We use the comprehensive Earth system model POEM to study the impact of the interacting boundaries for climate change and land system change. Our study shows the importance of long-term effects on carbon dynamics and climate, as well as the need to investigate both boundaries simultaneously and to generally keep both boundaries within acceptable ranges to avoid a catastrophic scenario for humanity.
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
Short summary
Short summary
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, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, and Christoph Müller
EGUsphere, https://doi.org/10.5194/egusphere-2023-2946, https://doi.org/10.5194/egusphere-2023-2946, 2024
Short summary
Short summary
We present a new approach to model 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, the nitrogen (N) deficit and carbon (C) costs. The new approach improved global sums and spatial patterns of BNF compared to the scientific literature and the models’ ability to project future C and N cycle dynamics.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim 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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1460, https://doi.org/10.5194/egusphere-2023-1460, 2023
Short summary
Short summary
Europe is regularly affected by compound events and natural hazards that occur simultaneously or with a temporal lag and are connected with disproportional impacts. Within the interdisciplinary project climXtreme (https://climxtreme.net/) we investigate the interplay of these events, their characteristics and changes, intensity, frequency and uncertainties in the past, present and future, as well as the associated impacts on different socio-economic sectors in Germany and Central Europe.
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
Short summary
Short summary
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.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
Short summary
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.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
Short summary
Short summary
The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
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
Short summary
Short summary
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.
Phillip Papastefanou, Christian S. Zang, Zlatan Angelov, Aline Anderson de Castro, Juan Carlos Jimenez, Luiz Felipe Campos De Rezende, Romina C. Ruscica, Boris Sakschewski, Anna A. Sörensson, Kirsten Thonicke, Carolina Vera, Nicolas Viovy, Celso Von Randow, and Anja Rammig
Biogeosciences, 19, 3843–3861, https://doi.org/10.5194/bg-19-3843-2022, https://doi.org/10.5194/bg-19-3843-2022, 2022
Short summary
Short summary
The Amazon rainforest has been hit by multiple severe drought events. In this study, we assess the severity and spatial extent of the extreme drought years 2005, 2010 and 2015/16 in the Amazon. Using nine different precipitation datasets and three drought indicators we find large differences in drought stress across the Amazon region. We conclude that future studies should use multiple rainfall datasets and drought indicators when estimating the impact of drought stress in the Amazon region.
Tobias K. D. Weber, Joachim Ingwersen, Petra Högy, Arne Poyda, Hans-Dieter Wizemann, Michael Scott Demyan, Kristina Bohm, Ravshan Eshonkulov, Sebastian Gayler, Pascal Kremer, Moritz Laub, Yvonne Funkiun Nkwain, Christian Troost, Irene Witte, Tim Reichenau, Thomas Berger, Georg Cadisch, Torsten Müller, Andreas Fangmeier, Volker Wulfmeyer, and Thilo Streck
Earth Syst. Sci. Data, 14, 1153–1181, https://doi.org/10.5194/essd-14-1153-2022, https://doi.org/10.5194/essd-14-1153-2022, 2022
Short summary
Short summary
Presented are measurement results from six agricultural fields operated by local farmers in southwestern Germany over 9 years. Six eddy-covariance stations measuring water, energy, and carbon fluxes between the vegetated soil surface and the atmosphere provided the backbone of the measurement sites and were supplemented by extensive soil and vegetation state monitoring. The dataset is ideal for testing process models characterizing fluxes at the vegetated soil surface and in the atmosphere.
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
Short summary
Short summary
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.
Josue De Los Rios, Arne Poyda, Thorsten Reinsch, Christof Kluß, Ralf Loges, and Friedhelm Taube
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-6, https://doi.org/10.5194/bg-2022-6, 2022
Manuscript not accepted for further review
Short summary
Short summary
Land use change (LUC) and conventional tillage (CT) are resulting in the reduction of the high soil organic carbon (SOC) stocks stored in grassland ecosystems during their conversion and renovation, contributing thus to global warming. Using no-tillage (NT) is seen as an avenue to minimize or even conserve SOC stocks during these events. Our results show that SOC losses are greatly reduced after grassland conversion to arable land, whereas during renovation it contributes to conserve them.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Markus Drüke, Werner von Bloh, Stefan Petri, Boris Sakschewski, Sibyll Schaphoff, Matthias Forkel, Willem Huiskamp, Georg Feulner, and Kirsten Thonicke
Geosci. Model Dev., 14, 4117–4141, https://doi.org/10.5194/gmd-14-4117-2021, https://doi.org/10.5194/gmd-14-4117-2021, 2021
Short summary
Short summary
In this study, we couple the well-established and comprehensively validated state-of-the-art dynamic LPJmL5 global vegetation model to the CM2Mc coupled climate model (CM2Mc-LPJmL v.1.0). Several improvements to LPJmL5 were implemented to allow a fully functional biophysical coupling. The new climate model is able to capture important biospheric processes, including fire, mortality, permafrost, hydrological cycling and the the impacts of managed land (crop growth and irrigation).
Yvonne Jans, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Hydrol. Earth Syst. Sci., 25, 2027–2044, https://doi.org/10.5194/hess-25-2027-2021, https://doi.org/10.5194/hess-25-2027-2021, 2021
Short summary
Short summary
Growth of and irrigation water demand on cotton may be challenged by future climate change. To analyze the global cotton production and irrigation water consumption under spatially varying present and future climatic conditions, we use the global terrestrial biosphere model LPJmL. Our simulation results suggest that the beneficial effects of elevated [CO2] on cotton yields overcompensate yield losses from direct climate change impacts, i.e., without the beneficial effect of [CO2] fertilization.
Bruno Ringeval, Christoph Müller, Thomas A. M. Pugh, Nathaniel D. Mueller, Philippe Ciais, Christian Folberth, Wenfeng Liu, Philippe Debaeke, and Sylvain Pellerin
Geosci. Model Dev., 14, 1639–1656, https://doi.org/10.5194/gmd-14-1639-2021, https://doi.org/10.5194/gmd-14-1639-2021, 2021
Short summary
Short summary
We assess how and why global gridded crop models (GGCMs) differ in their simulation of potential yield. We build a GCCM emulator based on generic formalism and fit its parameters against aboveground biomass and yield at harvest simulated by eight GGCMs. Despite huge differences between GGCMs, we show that the calibration of a few key parameters allows the emulator to reproduce the GGCM simulations. Our simple but mechanistic model could help to improve the global simulation of potential yield.
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Abigail Snyder, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Karina Williams, Ziwei Wang, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 3995–4018, https://doi.org/10.5194/gmd-13-3995-2020, https://doi.org/10.5194/gmd-13-3995-2020, 2020
Short summary
Short summary
Improving our understanding of the impacts of climate change on crop yields will be critical for global food security in the next century. The models often used to study the how climate change may impact agriculture are complex and costly to run. In this work, we describe a set of global crop model emulators (simplified models) developed under the Agricultural Model Intercomparison Project. Crop model emulators make agricultural simulations more accessible to policy or decision makers.
Femke Lutz, Stephen Del Grosso, Stephen Ogle, Stephen Williams, Sara Minoli, Susanne Rolinski, Jens Heinke, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 13, 3905–3923, https://doi.org/10.5194/gmd-13-3905-2020, https://doi.org/10.5194/gmd-13-3905-2020, 2020
Short summary
Short summary
Previous findings have shown deviations between the LPJmL5.0-tillage model and results from meta-analyses on global estimates of tillage effects on N2O emissions. By comparing model results with observational data of four experimental sites and outputs from field-scale DayCent model simulations, we show that advancing information on agricultural management, as well as the representation of soil moisture dynamics, improves LPJmL5.0-tillage and the estimates of tillage effects on N2O emissions.
Thomas A. M. Pugh, Tim Rademacher, Sarah L. Shafer, Jörg Steinkamp, Jonathan Barichivich, Brian Beckage, Vanessa Haverd, Anna Harper, Jens Heinke, Kazuya Nishina, Anja Rammig, Hisashi Sato, Almut Arneth, Stijn Hantson, Thomas Hickler, Markus Kautz, Benjamin Quesada, Benjamin Smith, and Kirsten Thonicke
Biogeosciences, 17, 3961–3989, https://doi.org/10.5194/bg-17-3961-2020, https://doi.org/10.5194/bg-17-3961-2020, 2020
Short summary
Short summary
The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle. Estimates from six contemporary models found this time to range from 12.2 to 23.5 years for the global mean for 1985–2014. Future projections do not give consistent results, but 13 model-based hypotheses are identified, along with recommendations for pragmatic steps to test them using existing and novel observations, which would help to reduce large current uncertainty.
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Juraj Balkovic, Philippe Ciais, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, Munir Hoffmann, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Nikolay Khabarov, Marian Koch, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Xuhui Wang, Karina Williams, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 2315–2336, https://doi.org/10.5194/gmd-13-2315-2020, https://doi.org/10.5194/gmd-13-2315-2020, 2020
Short summary
Short summary
Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Crop models, which represent plant biology, are necessary tools for this purpose since they allow representing future climate, farmer choices, and new agricultural geographies. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, under the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to evaluate and improve crop models.
Matias Heino, Joseph H. A. Guillaume, Christoph Müller, Toshichika Iizumi, and Matti Kummu
Earth Syst. Dynam., 11, 113–128, https://doi.org/10.5194/esd-11-113-2020, https://doi.org/10.5194/esd-11-113-2020, 2020
Short summary
Short summary
In this study, we analyse the impacts of three major climate oscillations on global crop production. Our results show that maize, rice, soybean, and wheat yields are influenced by climate oscillations to a wide extent and in several important crop-producing regions. We observe larger impacts if crops are rainfed or fully fertilized, while irrigation tends to mitigate the impacts. These results can potentially help to increase the resilience of the global food system to climate-related shocks.
Markus Drüke, Matthias Forkel, Werner von Bloh, Boris Sakschewski, Manoel Cardoso, Mercedes Bustamante, Jürgen Kurths, and Kirsten Thonicke
Geosci. Model Dev., 12, 5029–5054, https://doi.org/10.5194/gmd-12-5029-2019, https://doi.org/10.5194/gmd-12-5029-2019, 2019
Short summary
Short summary
This work shows the successful application of a systematic model–data integration setup, as well as the implementation of a new fire danger formulation, in order to optimize a process-based fire-enabled dynamic global vegetation model. We have demonstrated a major improvement in the fire representation within LPJmL4-SPITFIRE in terms of the spatial pattern and the interannual variability of burned area in South America as well as in the modelling of biomass and the distribution of plant types.
Maarten C. Braakhekke, Jonathan C. Doelman, Peter Baas, Christoph Müller, Sibyll Schaphoff, Elke Stehfest, and Detlef P. van Vuuren
Earth Syst. Dynam., 10, 617–630, https://doi.org/10.5194/esd-10-617-2019, https://doi.org/10.5194/esd-10-617-2019, 2019
Short summary
Short summary
We developed a computer model that simulates forests plantations at global scale and how fast such forests can take up CO2 from the atmosphere. Using this new model, we performed simulations for a scenario in which a large fraction (14 %) of global croplands and pastures are either converted to planted forests or natural forests. We find that planted forests take up CO2 substantially faster than natural forests and are therefore a viable strategy for reducing climate change.
Bruno Ringeval, Marko Kvakić, Laurent Augusto, Philippe Ciais, Daniel Goll, Nathaniel D. Mueller, Christoph Müller, Thomas Nesme, Nicolas Vuichard, Xuhui Wang, and Sylvain Pellerin
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-298, https://doi.org/10.5194/bg-2019-298, 2019
Preprint withdrawn
Short summary
Short summary
Crossed fertilization additions lead to the definition of nutrient interaction categories. However, the implications of such categories in terms of nutrient interaction modeling are not clear. We developed a theoretical analysis of nitrogen and phosphorus fertilization experiments, then applied it to current estimates of nutrient limitation in cropland. We found that a true co-limitation could affect up to 42 % of the global maize area when using a given formalism of nutrient interaction.
Kirsten Thonicke, Fanny Langerwisch, Matthias Baumann, Pedro J. Leitão, Tomáš Václavík, Ane Alencar, Margareth Simões, Simon Scheiter, Liam Langan, Mercedes Bustamante, Ignacio Gasparri, Marina Hirota, Jan Börner, Raoni Rajao, Britaldo Soares-Filho, Alberto Yanosky, José-Manuel Ochoa-Quinteiro, Lucas Seghezzo, Georgina Conti, and Anne Cristina de la Vega-Leinert
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-221, https://doi.org/10.5194/bg-2019-221, 2019
Publication in BG not foreseen
Short summary
Short summary
Tropical dry forests and savannas harbor unique biodiversity and provide critical ecosystem services (ES), yet they are under severe pressure globally. We need to improve our understanding of how and when this pressure provokes tipping points in biodiversity and the associated social-ecological systems. We propose an approach to investigate how drivers leading to natural vegetation decline trigger biodiversity tipping and illustrate it using the example of the Dry Diagonal in South America.
Femke Lutz, Tobias Herzfeld, Jens Heinke, Susanne Rolinski, Sibyll Schaphoff, Werner von Bloh, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 12, 2419–2440, https://doi.org/10.5194/gmd-12-2419-2019, https://doi.org/10.5194/gmd-12-2419-2019, 2019
Short summary
Short summary
Tillage practices are under-represented in global biogeochemical models so that assessments of agricultural greenhouse gas emissions and climate mitigation options are hampered. We describe the implementation of tillage modules into the model LPJmL5.0, including multiple feedbacks between soil water, nitrogen, and productivity. By comparing simulation results with observational data, we show that the model can reproduce reported tillage effects on carbon and water dynamics and crop yields.
Vera Porwollik, Susanne Rolinski, Jens Heinke, and Christoph Müller
Earth Syst. Sci. Data, 11, 823–843, https://doi.org/10.5194/essd-11-823-2019, https://doi.org/10.5194/essd-11-823-2019, 2019
Short summary
Short summary
This study describes the generation of a classification and the global spatially explicit mapping of six crop-specific tillage systems for around the year 2005. Tillage practices differ by the kind of equipment used, soil surface and depth affected, timing, and their purpose within the cropping systems. The identified tillage systems including a downscale algorithm of national Conservation Agriculture area values were allocated to crop-specific cropland areas with a resolution of 5 arcmin.
Jens Heinke, Christoph Müller, Mats Lannerstad, Dieter Gerten, and Wolfgang Lucht
Earth Syst. Dynam., 10, 205–217, https://doi.org/10.5194/esd-10-205-2019, https://doi.org/10.5194/esd-10-205-2019, 2019
Ravshan Eshonkulov, Arne Poyda, Joachim Ingwersen, Hans-Dieter Wizemann, Tobias K. D. Weber, Pascal Kremer, Petra Högy, Alim Pulatov, and Thilo Streck
Biogeosciences, 16, 521–540, https://doi.org/10.5194/bg-16-521-2019, https://doi.org/10.5194/bg-16-521-2019, 2019
Short summary
Short summary
We compared the energy balance closure (EBC) under varying environmental conditions and investigated a wide range of possible reasons for the energy imbalance. As measures for the imbalance, we used ordinary linear regression, the energy balance ratio (EBR), and the energy residual. The EBR was also investigated as a function of buoyancy, friction velocity, and atmospheric stability. Moreover, the relationship between the EBC and flux source area or footprint was also investigated.
Anja Rammig, Jens Heinke, Florian Hofhansl, Hans Verbeeck, Timothy R. Baker, Bradley Christoffersen, Philippe Ciais, Hannes De Deurwaerder, Katrin Fleischer, David Galbraith, Matthieu Guimberteau, Andreas Huth, Michelle Johnson, Bart Krujit, Fanny Langerwisch, Patrick Meir, Phillip Papastefanou, Gilvan Sampaio, Kirsten Thonicke, Celso von Randow, Christian Zang, and Edna Rödig
Geosci. Model Dev., 11, 5203–5215, https://doi.org/10.5194/gmd-11-5203-2018, https://doi.org/10.5194/gmd-11-5203-2018, 2018
Short summary
Short summary
We propose a generic approach for a pixel-to-point comparison applicable for evaluation of models and remote-sensing products. We provide statistical measures accounting for the uncertainty in ecosystem variables. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest.
Werner von Bloh, Sibyll Schaphoff, Christoph Müller, Susanne Rolinski, Katharina Waha, and Sönke Zaehle
Geosci. Model Dev., 11, 2789–2812, https://doi.org/10.5194/gmd-11-2789-2018, https://doi.org/10.5194/gmd-11-2789-2018, 2018
Short summary
Short summary
The dynamics of the terrestrial carbon cycle are of central importance for Earth system science. Nutrient limitations, especially from nitrogen, are important constraints on vegetation growth and the terrestrial carbon cycle. We extended the well-established global vegetation, hydrology, and crop model LPJmL with a nitrogen cycle. We find significant improvement in global patterns of crop productivity. Regional differences in crop productivity can now be largely reproduced by the model.
Sibyll Schaphoff, Werner von Bloh, Anja Rammig, Kirsten Thonicke, Hester Biemans, Matthias Forkel, Dieter Gerten, Jens Heinke, Jonas Jägermeyr, Jürgen Knauer, Fanny Langerwisch, Wolfgang Lucht, Christoph Müller, Susanne Rolinski, and Katharina Waha
Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018, https://doi.org/10.5194/gmd-11-1343-2018, 2018
Short summary
Short summary
Here we provide a comprehensive model description of a global terrestrial biosphere model, named LPJmL4, incorporating the carbon and water cycle and the quantification of agricultural production. The model allows for the consistent and joint quantification of climate and land use change impacts on the biosphere. The model represents the key ecosystem functions, but also the influence of humans on the biosphere. It comes with an evaluation paper to demonstrate the credibility of LPJmL4.
Sibyll Schaphoff, Matthias Forkel, Christoph Müller, Jürgen Knauer, Werner von Bloh, Dieter Gerten, Jonas Jägermeyr, Wolfgang Lucht, Anja Rammig, Kirsten Thonicke, and Katharina Waha
Geosci. Model Dev., 11, 1377–1403, https://doi.org/10.5194/gmd-11-1377-2018, https://doi.org/10.5194/gmd-11-1377-2018, 2018
Short summary
Short summary
Here we provide a comprehensive evaluation of the now launched version 4.0 of the LPJmL biosphere, water, and agricultural model. The article is the second part to a comprehensive description of the LPJmL4 model. We have evaluated the model against various datasets of satellite observations, agricultural statistics, and in situ measurements by applying a range of metrics. We are able to show that the LPJmL4 model simulates many parameters and relations reasonably.
Susanne Rolinski, Christoph Müller, Jens Heinke, Isabelle Weindl, Anne Biewald, Benjamin Leon Bodirsky, Alberte Bondeau, Eltje R. Boons-Prins, Alexander F. Bouwman, Peter A. Leffelaar, Johnny A. te Roller, Sibyll Schaphoff, and Kirsten Thonicke
Geosci. Model Dev., 11, 429–451, https://doi.org/10.5194/gmd-11-429-2018, https://doi.org/10.5194/gmd-11-429-2018, 2018
Short summary
Short summary
One-third of the global land area is covered with grasslands which are grazed by or mowed for livestock feed. These areas contribute significantly to the carbon capture from the atmosphere when managed sensibly. To assess the effect of this management, we included different options of grazing and mowing into the global model LPJmL 3.6. We found in polar regions even low grazing pressure leads to soil carbon loss whereas in temperate regions up to 1.4 livestock units per hectare can be sustained.
Matthias Forkel, Wouter Dorigo, Gitta Lasslop, Irene Teubner, Emilio Chuvieco, and Kirsten Thonicke
Geosci. Model Dev., 10, 4443–4476, https://doi.org/10.5194/gmd-10-4443-2017, https://doi.org/10.5194/gmd-10-4443-2017, 2017
Short summary
Short summary
Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
Short summary
Short summary
This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Finn Müller-Hansen, Maja Schlüter, Michael Mäs, Jonathan F. Donges, Jakob J. Kolb, Kirsten Thonicke, and Jobst Heitzig
Earth Syst. Dynam., 8, 977–1007, https://doi.org/10.5194/esd-8-977-2017, https://doi.org/10.5194/esd-8-977-2017, 2017
Short summary
Short summary
Today, human interactions with the Earth system lead to complex feedbacks between social and ecological dynamics. Modeling such feedbacks explicitly in Earth system models (ESMs) requires making assumptions about individual decision making and behavior, social interaction, and their aggregation. In this overview paper, we compare different modeling approaches and techniques and highlight important consequences of modeling assumptions. We illustrate them with examples from land-use modeling.
Istem Fer, Britta Tietjen, Florian Jeltsch, and Christian Wolff
Biogeosciences, 14, 4355–4374, https://doi.org/10.5194/bg-14-4355-2017, https://doi.org/10.5194/bg-14-4355-2017, 2017
Short summary
Short summary
El Niño–Southern Oscillation (ENSO) has been identified as one of the main drivers for the interannual variability in eastern African rainfall. But we know little about its direct impact on vegetation and how it might change in the future. In this study, we quantified this relationship and predict its future under certain climate change scenarios. Results suggest that we need to consider an increase in future ENSO intensity to cover the full range of potential changes in vegetation responses.
Matthieu Guimberteau, Philippe Ciais, Agnès Ducharne, Juan Pablo Boisier, Ana Paula Dutra Aguiar, Hester Biemans, Hannes De Deurwaerder, David Galbraith, Bart Kruijt, Fanny Langerwisch, German Poveda, Anja Rammig, Daniel Andres Rodriguez, Graciela Tejada, Kirsten Thonicke, Celso Von Randow, Rita C. S. Von Randow, Ke Zhang, and Hans Verbeeck
Hydrol. Earth Syst. Sci., 21, 1455–1475, https://doi.org/10.5194/hess-21-1455-2017, https://doi.org/10.5194/hess-21-1455-2017, 2017
Finn Müller-Hansen, Manoel F. Cardoso, Eloi L. Dalla-Nora, Jonathan F. Donges, Jobst Heitzig, Jürgen Kurths, and Kirsten Thonicke
Nonlin. Processes Geophys., 24, 113–123, https://doi.org/10.5194/npg-24-113-2017, https://doi.org/10.5194/npg-24-113-2017, 2017
Short summary
Short summary
Deforestation and subsequent land uses in the Brazilian Amazon have huge impacts on greenhouse gas emissions, local climate and biodiversity. To better understand these land-cover changes, we apply complex systems methods uncovering spatial patterns in regional transition probabilities between land-cover types, which we estimate using maps derived from satellite imagery. The results show clusters of similar land-cover dynamics and thus complement studies at the local scale.
Christian Folberth, Joshua Elliott, Christoph Müller, Juraj Balkovic, James Chryssanthacopoulos, Roberto C. Izaurralde, Curtis D. Jones, Nikolay Khabarov, Wenfeng Liu, Ashwan Reddy, Erwin Schmid, Rastislav Skalský, Hong Yang, Almut Arneth, Philippe Ciais, Delphine Deryng, Peter J. Lawrence, Stefan Olin, Thomas A. M. Pugh, Alex C. Ruane, and Xuhui Wang
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-527, https://doi.org/10.5194/bg-2016-527, 2016
Manuscript not accepted for further review
Short summary
Short summary
Global crop models differ in numerous aspects such as algorithms, parameterization, input data, and management assumptions. This study compares five global crop model frameworks, all based on the same field-scale model, to identify differences induced by the latter three. Results indicate that foremost nutrient supply, soil handling, and crop management induce substantial differences in crop yield estimates whereas crop cultivars primarily result in scaling of yield levels.
Fanny Langerwisch, Ariane Walz, Anja Rammig, Britta Tietjen, Kirsten Thonicke, and Wolfgang Cramer
Earth Syst. Dynam., 7, 953–968, https://doi.org/10.5194/esd-7-953-2016, https://doi.org/10.5194/esd-7-953-2016, 2016
Short summary
Short summary
Amazonia is heavily impacted by climate change and deforestation. During annual flooding terrigenous material is imported to the river, converted and finally exported to the ocean or the atmosphere. Changes in the vegetation alter therefore riverine carbon dynamics. Our results show that due to deforestation organic carbon amount will strongly decrease both in the river and exported to the ocean, while inorganic carbon amounts will increase, in the river as well as exported to the atmosphere.
Arne Poyda, Thorsten Reinsch, Christof Kluß, Ralf Loges, and Friedhelm Taube
Biogeosciences, 13, 5221–5244, https://doi.org/10.5194/bg-13-5221-2016, https://doi.org/10.5194/bg-13-5221-2016, 2016
Short summary
Short summary
Fen soils in northwest Germany are mainly intensively utilized for dairy farming. To estimate their climatic impact, the greenhouse gas exchange of four sites with different management intensity was measured using closed manual chambers. Results showed that long-term drainage intensity is more important for the global warming potential of fen soils than the type of management. Lowest yield-related emissions were achieved on a three-cut grassland with a high mean groundwater level.
F. Langerwisch, A. Walz, A. Rammig, B. Tietjen, K. Thonicke, and W. Cramer
Earth Syst. Dynam., 7, 559–582, https://doi.org/10.5194/esd-7-559-2016, https://doi.org/10.5194/esd-7-559-2016, 2016
Short summary
Short summary
In Amazonia, carbon fluxes are considerably influenced by annual flooding. We applied the newly developed model RivCM to several climate change scenarios to estimate potential changes in riverine carbon. We find that climate change causes substantial changes in riverine organic and inorganic carbon, as well as changes in carbon exported to the atmosphere and ocean. Such changes could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean.
Gregor Ratzmann, Ute Gangkofner, Britta Tietjen, and Rasmus Fensholt
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-48, https://doi.org/10.5194/bg-2016-48, 2016
Revised manuscript not accepted
Short summary
Short summary
Anticipating impacts of changes in rainfall regimes on dryland ecosystems requires the understanding of the functional response to rainfall of those water limited environments. Here we show for two arid/semi-arid African regions based on satellite data that higher rainfall variability leads to a more dynamic vegetation response to rainfall. This applies irrespective of vegetation type. It moreover indicates that regions experiencing a higher rainfall variability may be more resilient to drought.
M. Fader, S. Shi, W. von Bloh, A. Bondeau, and W. Cramer
Hydrol. Earth Syst. Sci., 20, 953–973, https://doi.org/10.5194/hess-20-953-2016, https://doi.org/10.5194/hess-20-953-2016, 2016
Short summary
Short summary
At present, the Mediterranean region could save 35 % of water by implementing more efficient irrigation and conveyance systems (EICS). By 2080–2090 the region may face an increase in gross irrigation requirements (IRs) of up to 74 % due to climate change and population growth. EICS may be able to compensate to some degree these increases. Most countries in the northern and eastern Mediterranean have a high risk of not being able to meet future IRs due to water scarcity.
S. Sippel, F. E. L. Otto, M. Forkel, M. R. Allen, B. P. Guillod, M. Heimann, M. Reichstein, S. I. Seneviratne, K. Thonicke, and M. D. Mahecha
Earth Syst. Dynam., 7, 71–88, https://doi.org/10.5194/esd-7-71-2016, https://doi.org/10.5194/esd-7-71-2016, 2016
Short summary
Short summary
We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
M. Fader, W. von Bloh, S. Shi, A. Bondeau, and W. Cramer
Geosci. Model Dev., 8, 3545–3561, https://doi.org/10.5194/gmd-8-3545-2015, https://doi.org/10.5194/gmd-8-3545-2015, 2015
Short summary
Short summary
This study presents the inclusion of 10 Mediterranean agricultural plants in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses.
The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With this development presented, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture.
W. Greuell, J. C. M. Andersson, C. Donnelly, L. Feyen, D. Gerten, F. Ludwig, G. Pisacane, P. Roudier, and S. Schaphoff
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-10289-2015, https://doi.org/10.5194/hessd-12-10289-2015, 2015
Revised manuscript has not been submitted
Short summary
Short summary
The main aims of this paper are the evaluation of five large-scale hydrological models across Europe and the assessment of the suitability of the models for making projections under climate change. While we found large inter-model differences in biases, the skill to simulate interannual variability in discharge did not differ much between the models. Assuming that the skill of a model to simulate interannual variability provides a measure for the model’s ability to make projections under climate
K. Nishina, A. Ito, P. Falloon, A. D. Friend, D. J. Beerling, P. Ciais, D. B. Clark, R. Kahana, E. Kato, W. Lucht, M. Lomas, R. Pavlick, S. Schaphoff, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 6, 435–445, https://doi.org/10.5194/esd-6-435-2015, https://doi.org/10.5194/esd-6-435-2015, 2015
Short summary
Short summary
Our study focused on uncertainties in terrestrial C cycling under newly developed scenarios with CMIP5. This study presents first results for examining relative uncertainties of projected terrestrial C cycling in multiple projection components. Only using our new model inter-comparison project data sets enables us to evaluate various uncertainty sources in projection periods. The information on relative uncertainties is useful for climate science and climate change impact evaluation.
T. Schneider von Deimling, G. Grosse, J. Strauss, L. Schirrmeister, A. Morgenstern, S. Schaphoff, M. Meinshausen, and J. Boike
Biogeosciences, 12, 3469–3488, https://doi.org/10.5194/bg-12-3469-2015, https://doi.org/10.5194/bg-12-3469-2015, 2015
Short summary
Short summary
We have modelled the carbon release from thawing permafrost soils under various scenarios of future warming. Our results suggests that up to about 140Pg of carbon could be released under strong warming by end of the century. We have shown that abrupt thaw processes under thermokarst lakes can unlock large amounts of perennially frozen carbon stored in deep deposits (which extend many metres into the soil).
C. Yue, P. Ciais, P. Cadule, K. Thonicke, and T. T. van Leeuwen
Geosci. Model Dev., 8, 1321–1338, https://doi.org/10.5194/gmd-8-1321-2015, https://doi.org/10.5194/gmd-8-1321-2015, 2015
Short summary
Short summary
We conducted parallel simulations using a global land surface model, with and without fires being included, respectively. When the anthropogenic land cover change fire is excluded, we find that natural wildfires have reduced the global land carbon uptake by 0.3Pg C per year over 1901-2012. This is equivalent to 20% of the land carbon uptake in a world without fire. This fire-induced reduction in carbon uptake could be partly explained by climate variability, in particular the ENSO events.
S. Rolinski, A. Rammig, A. Walz, W. von Bloh, M. van Oijen, and K. Thonicke
Biogeosciences, 12, 1813–1831, https://doi.org/10.5194/bg-12-1813-2015, https://doi.org/10.5194/bg-12-1813-2015, 2015
Short summary
Short summary
Extreme weather events can but do not have to cause extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions.
We use a simple probabilistic risk assessment and apply it to terrestrial ecosystems, defining a hazard as negative net biome productivity. In Europe, ecosystems are vulnerable to drought in the Mediterranean and temperate region, whereas vulnerability in Scandinavia is not caused by water shortages.
J. Elliott, C. Müller, D. Deryng, J. Chryssanthacopoulos, K. J. Boote, M. Büchner, I. Foster, M. Glotter, J. Heinke, T. Iizumi, R. C. Izaurralde, N. D. Mueller, D. K. Ray, C. Rosenzweig, A. C. Ruane, and J. Sheffield
Geosci. Model Dev., 8, 261–277, https://doi.org/10.5194/gmd-8-261-2015, https://doi.org/10.5194/gmd-8-261-2015, 2015
Short summary
Short summary
We present and describe the Global Gridded Crop Model Intercomparison (GGCMI) project, an ongoing international effort to 1) validate global models of crop productivity, 2) improve models through detailed analysis of processes, and 3) assess the impacts of climate change on agriculture and food security. We present analysis of data inputs for the project, detailed protocols for conducting and evaluating simulation outputs, and example results.
A. Rammig, M. Wiedermann, J. F. Donges, F. Babst, W. von Bloh, D. Frank, K. Thonicke, and M. D. Mahecha
Biogeosciences, 12, 373–385, https://doi.org/10.5194/bg-12-373-2015, https://doi.org/10.5194/bg-12-373-2015, 2015
M. Forkel, N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner, and K. Thonicke
Biogeosciences, 11, 7025–7050, https://doi.org/10.5194/bg-11-7025-2014, https://doi.org/10.5194/bg-11-7025-2014, 2014
M. Van Oijen, J. Balkovi, C. Beer, D. R. Cameron, P. Ciais, W. Cramer, T. Kato, M. Kuhnert, R. Martin, R. Myneni, A. Rammig, S. Rolinski, J.-F. Soussana, K. Thonicke, M. Van der Velde, and L. Xu
Biogeosciences, 11, 6357–6375, https://doi.org/10.5194/bg-11-6357-2014, https://doi.org/10.5194/bg-11-6357-2014, 2014
Short summary
Short summary
We use a new risk analysis method, and six vegetation models, to analyse how climate change may alter drought risks in European ecosystems. The conclusions are (1) drought will pose increasing risks to productivity in the Mediterranean area; (2) this is because severe droughts will become more frequent, not because ecosystems will become more vulnerable; (3) future C sequestration will be at risk because carbon gain in primary productivity will be more affected than carbon loss in respiration.
C. Yue, P. Ciais, P. Cadule, K. Thonicke, S. Archibald, B. Poulter, W. M. Hao, S. Hantson, F. Mouillot, P. Friedlingstein, F. Maignan, and N. Viovy
Geosci. Model Dev., 7, 2747–2767, https://doi.org/10.5194/gmd-7-2747-2014, https://doi.org/10.5194/gmd-7-2747-2014, 2014
Short summary
Short summary
ORCHIDEE-SPITFIRE model could moderately capture the decadal trend and variation of burned area during the 20th century, and the spatial and temporal patterns of contemporary vegetation fires. The model has a better performance in simulating fires for regions dominated by climate-driven fires, such as boreal forests. However, it has limited capability to reproduce the infrequent but important large fires in different ecosystems, where urgent model improvement is needed in the future.
L. Batlle-Bayer, B. J. J. M. van den Hurk, C. Müller, and J. van Minnen
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-5-585-2014, https://doi.org/10.5194/esdd-5-585-2014, 2014
Revised manuscript has not been submitted
K. Nishina, A. Ito, D. J. Beerling, P. Cadule, P. Ciais, D. B. Clark, P. Falloon, A. D. Friend, R. Kahana, E. Kato, R. Keribin, W. Lucht, M. Lomas, T. T. Rademacher, R. Pavlick, S. Schaphoff, N. Vuichard, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 5, 197–209, https://doi.org/10.5194/esd-5-197-2014, https://doi.org/10.5194/esd-5-197-2014, 2014
P. Dass, C. Müller, V. Brovkin, and W. Cramer
Earth Syst. Dynam., 4, 409–424, https://doi.org/10.5194/esd-4-409-2013, https://doi.org/10.5194/esd-4-409-2013, 2013
J. Heinke, S. Ostberg, S. Schaphoff, K. Frieler, C. Müller, D. Gerten, M. Meinshausen, and W. Lucht
Geosci. Model Dev., 6, 1689–1703, https://doi.org/10.5194/gmd-6-1689-2013, https://doi.org/10.5194/gmd-6-1689-2013, 2013
S. Ostberg, W. Lucht, S. Schaphoff, and D. Gerten
Earth Syst. Dynam., 4, 347–357, https://doi.org/10.5194/esd-4-347-2013, https://doi.org/10.5194/esd-4-347-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
P. B. Holden, N. R. Edwards, D. Gerten, and S. Schaphoff
Biogeosciences, 10, 339–355, https://doi.org/10.5194/bg-10-339-2013, https://doi.org/10.5194/bg-10-339-2013, 2013
Related subject area
Biogeochemistry: Modelling, Terrestrial
Optimizing the terrestrial ecosystem gross primary productivity using carbonyl sulfide (COS) within a two-leaf modeling framework
Modeling integrated soil fertility management for maize production in Kenya using a Bayesian calibration of the DayCent model
When and why microbial-explicit soil organic carbon models can be unstable
The impacts of modelling prescribed vs. dynamic land cover in a high-CO2 future scenario – greening of the Arctic and Amazonian dieback
Climate-based prediction of carbon fluxes from deadwood in Australia
Integration of tree hydraulic processes and functional impairment to capture the drought resilience of a semiarid pine forest
The effect of temperature on photosystem II efficiency across plant functional types and climate
Modeling microbial carbon fluxes and stocks in global soils from 1901 to 2016
Elevated atmospheric CO2 concentration and vegetation structural changes contributed to gross primary productivity increase more than climate and forest cover changes in subtropical forests of China
Mechanisms of soil organic carbon and nitrogen stabilization in mineral associated organic matter – Insights from modelling in phase space
Non-steady-state stomatal conductance modeling and its implications: from leaf to ecosystem
Modelled forest ecosystem carbon–nitrogen dynamics with integrated mycorrhizal processes under elevated CO2
A chemical kinetics theory for interpreting the non-monotonic temperature dependence of enzymatic reactions
Using Free Air CO2 Enrichment data to constrain land surface model projections of the terrestrial carbon cycle
Multiscale assessment of North American terrestrial carbon balance
Simulating net ecosystem exchange under seasonal snow cover at an Arctic tundra site
2001–2022 global gross primary productivity dataset using an ensemble model based on random forest
X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X
Spatial biases reduce the ability of Earth system models to simulate soil heterotrophic respiration fluxes
Tropical dry forest response to nutrient fertilization: a model validation and sensitivity analysis
A global fuel characteristic model and dataset for wildfire prediction
Future prediction of Siberian wildfire and aerosol emissions via the improved fire module of the spatially explicit individual-based dynamic global vegetation model
Can models adequately reflect how long-term nitrogen enrichment alters the forest soil carbon cycle?
Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers
Empirical upscaling of OzFlux eddy covariance for high-resolution monitoring of terrestrial carbon uptake in Australia
A modeling approach to investigate drivers, variability and uncertainties in O2 fluxes and O2 : CO2 exchange ratios in a temperate forest
Modeling coupled nitrification–denitrification in soil with an organic hotspot
A new method for estimating carbon dioxide emissions from drained peatland forest soils for the greenhouse gas inventory of Finland
Enabling a process-oriented hydro-biogeochemical model to simulate soil erosion and nutrient losses
Potassium limitation of forest productivity – Part 1: A mechanistic model simulating the effects of potassium availability on canopy carbon and water fluxes in tropical eucalypt stands
Potassium limitation of forest productivity – Part 2: CASTANEA-MAESPA-K shows a reduction in photosynthesis rather than a stoichiometric limitation of tissue formation
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
Assessing carbon storage capacity and saturation across six central US grasslands using data–model integration
Optimizing the carbonic anhydrase temperature response and stomatal conductance of carbonyl sulfide leaf uptake in the Simple Biosphere model (SiB4)
Exploring environmental and physiological drivers of the annual carbon budget of biocrusts from various climatic zones with a mechanistic data-driven model
Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance
Mapping of ESA's Climate Change Initiative land cover data to plant functional types for use in the CLASSIC land model
Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies
Effect of droughts and climate change on future soil weathering rates in Sweden
Information content in time series of litter decomposition studies and the transit time of litter in arid lands
Long-term changes of nitrogen leaching and the contributions of terrestrial nutrient sources to lake eutrophication dynamics on the Yangtze Plain of China
Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations
Effect of land-use legacy on the future carbon sink for the conterminous US
Peatlands and their carbon dynamics in northern high latitudes from 1990 to 2300: a process-based biogeochemistry model analysis
Improved representation of phosphorus exchange on soil mineral surfaces reduces estimates of phosphorus limitation in temperate forest ecosystems
A coupled ground heat flux–surface energy balance model of evaporation using thermal remote sensing observations
Modeling nitrous oxide emissions from agricultural soil incubation experiments using CoupModel
Local-scale evaluation of the simulated interactions between energy, water and vegetation in ISBA, ORCHIDEE and a diagnostic model
Implementation and initial calibration of carbon-13 soil organic matter decomposition in the Yasso model
The carbon budget of the managed grasslands of Great Britain – informed by earth observations
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
Short summary
Short summary
Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
Biogeosciences, 21, 3691–3716, https://doi.org/10.5194/bg-21-3691-2024, https://doi.org/10.5194/bg-21-3691-2024, 2024
Short summary
Short summary
We used the DayCent model to assess the potential impact of integrated soil fertility management (ISFM) on maize production, soil fertility, and greenhouse gas emission in Kenya. After adjustments, DayCent represented measured mean yields and soil carbon stock changes well and N2O emissions acceptably. Our results showed that soil fertility losses could be reduced but not completely eliminated with ISFM and that, while N2O emissions increased with ISFM, emissions per kilogram yield decreased.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
Biogeosciences, 21, 3441–3461, https://doi.org/10.5194/bg-21-3441-2024, https://doi.org/10.5194/bg-21-3441-2024, 2024
Short summary
Short summary
The occurrence of unstable equilibrium points (EPs) could impede the applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identify when instability can occur and describe mathematical conditions to avoid such unstable EPs. We discuss implications for further model development, highlighting the important role of considering basic ecological principles to ensure biologically meaningful models.
Sian Kou-Giesbrecht, Vivek K. Arora, Christian Seiler, and Libo Wang
Biogeosciences, 21, 3339–3371, https://doi.org/10.5194/bg-21-3339-2024, https://doi.org/10.5194/bg-21-3339-2024, 2024
Short summary
Short summary
Terrestrial biosphere models can either prescribe the geographical distribution of biomes or simulate them dynamically, capturing climate-change-driven biome shifts. We isolate and examine the differences between these different land cover implementations. We find that the simulated terrestrial carbon sink at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover due to important range shifts in the Arctic and Amazon.
Elizabeth S. Duan, Luciana Chavez Rodriguez, Nicole Hemming-Schroeder, Baptiste Wijas, Habacuc Flores-Moreno, Alexander W. Cheesman, Lucas A. Cernusak, Michael J. Liddell, Paul Eggleton, Amy E. Zanne, and Steven D. Allison
Biogeosciences, 21, 3321–3338, https://doi.org/10.5194/bg-21-3321-2024, https://doi.org/10.5194/bg-21-3321-2024, 2024
Short summary
Short summary
Understanding the link between climate and carbon fluxes is crucial for predicting how climate change will impact carbon sinks. We estimated carbon dioxide (CO2) fluxes from deadwood in tropical Australia using wood moisture content and temperature. Our model predicted that the majority of deadwood carbon is released as CO2, except when termite activity is detected. Future models should also incorporate wood traits, like species and chemical composition, to better predict fluxes.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine K. Ruehr
Biogeosciences, 21, 2973–2994, https://doi.org/10.5194/bg-21-2973-2024, https://doi.org/10.5194/bg-21-2973-2024, 2024
Short summary
Short summary
A hydraulic model approach is presented that can be added to any physiologically based ecosystem model. Simulated plant water potential triggers stomatal closure, photosynthesis decline, root–soil resistance increases, and sapwood and foliage senescence. The model has been evaluated at an extremely dry site stocked with Aleppo pine and was able to represent gas exchange, soil water content, and plant water potential. The model also responded realistically regarding leaf senescence.
Patrick Neri, Lianhong Gu, and Yang Song
Biogeosciences, 21, 2731–2758, https://doi.org/10.5194/bg-21-2731-2024, https://doi.org/10.5194/bg-21-2731-2024, 2024
Short summary
Short summary
A first-of-its-kind global-scale model of temperature resilience and tolerance of photosystem II maximum quantum yield informs how plants maintain their efficiency of converting light energy to chemical energy for photosynthesis under temperature changes. Our finding explores this variation across plant functional types and habitat climatology, highlighting diverse temperature response strategies and a method to improve global-scale photosynthesis modeling under climate change.
Liyuan He, Jorge L. Mazza Rodrigues, Melanie A. Mayes, Chun-Ta Lai, David A. Lipson, and Xiaofeng Xu
Biogeosciences, 21, 2313–2333, https://doi.org/10.5194/bg-21-2313-2024, https://doi.org/10.5194/bg-21-2313-2024, 2024
Short summary
Short summary
Soil microbes are the driving engine for biogeochemical cycles of carbon and nutrients. This study applies a microbial-explicit model to quantify bacteria and fungal biomass carbon in soils from 1901 to 2016. Results showed substantial increases in bacterial and fungal biomass carbon over the past century, jointly influenced by vegetation growth and soil temperature and moisture. This pioneering century-long estimation offers crucial insights into soil microbial roles in global carbon cycling.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
Short summary
Short summary
Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Stefano Manzoni and Francesca Cotrufo
EGUsphere, https://doi.org/10.5194/egusphere-2024-1092, https://doi.org/10.5194/egusphere-2024-1092, 2024
Short summary
Short summary
Organic carbon and nitrogen are stabilized in soils via microbial assimilation and stabilization of necromass (in vivo pathway) or via adsorption of the products of extra-cellular decomposition (ex vivo pathway). Here we use a diagnostic model to quantify which stabilization pathway is prevalent, using data on residue-derived carbon and nitrogen incorporation in mineral associated organic matter. We find that the in vivo pathway is dominant in fine-textured soils with low organic matter content.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
Short summary
Short summary
Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
Short summary
Short summary
Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
Short summary
Short summary
A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024, https://doi.org/10.5194/bg-21-1017-2024, 2024
Short summary
Short summary
Observations are used to reduce uncertainty in land surface models (LSMs) by optimising poorly constraining parameters. However, optimising against current conditions does not necessarily ensure that the parameters treated as invariant will be robust in a changing climate. Manipulation experiments offer us a unique chance to optimise our models under different (here atmospheric CO2) conditions. By using these data in optimisations, we gain confidence in the future projections of LSMs.
Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024, https://doi.org/10.5194/bg-21-869-2024, 2024
Short summary
Short summary
Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
Short summary
Short summary
We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Xin Chen, Tiexi Chen, Xiaodong Li, Yuanfang Chai, Shengjie Zhou, Renjie Guo, and Jie Dai
EGUsphere, https://doi.org/10.5194/egusphere-2024-114, https://doi.org/10.5194/egusphere-2024-114, 2024
Short summary
Short summary
We provides an ensemble model-based GPP dataset (ERF_GPP) that explains 83.7 % of the monthly variation in GPP across 171 sites, higher than other single remote sensing model. In addition, ERF_GPP improves the phenomenon of “high value underestimation and low value overestimation” in GPP estimation to some extent. Overall, ERF_GPP provides a more reliable estimate of global GPP and will facilitate further development of carbon cycle research.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billdesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Gharun Mana, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2024-165, https://doi.org/10.5194/egusphere-2024-165, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the earth surface to the atmosphere, or flux, is an important process to understand that impacts all of our lives. Here we outline a method to estimate global water and CO2 fluxes based on direct measurements from site around the world called FLUXCOM-X. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
Short summary
Short summary
Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Shuyue Li, Bonnie Waring, Jennifer Powers, and David Medvigy
Biogeosciences, 21, 455–471, https://doi.org/10.5194/bg-21-455-2024, https://doi.org/10.5194/bg-21-455-2024, 2024
Short summary
Short summary
We used an ecosystem model to simulate primary production of a tropical forest subjected to 3 years of nutrient fertilization. Simulations parameterized such that relative allocation to fine roots increased with increasing soil phosphorus had leaf, wood, and fine root production consistent with observations. However, these simulations seemed to over-allocate to fine roots on multidecadal timescales, affecting aboveground biomass. Additional observations across timescales would benefit models.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
Short summary
Short summary
Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
EGUsphere, https://doi.org/10.5194/egusphere-2024-105, https://doi.org/10.5194/egusphere-2024-105, 2024
Short summary
Short summary
SPITFIRE fire module was integrated into SEIB Dynamic Global Vegetation Model to improve the model's accuracy in depicting forest fire frequency, intensity, and extent in Siberia. Projected fires showed a continuous increase in higher emissions of greenhouse gases and aerosols from 2023 to 2100 under all RCP scenarios. This study contributes to a better understanding of fire dynamics, land ecosystem-climate interactions, and global material cycles under the threat of escalating fires in Siberia.
Brooke A. Eastman, William R. Wieder, Melannie D. Hartman, Edward R. Brzostek, and William T. Peterjohn
Biogeosciences, 21, 201–221, https://doi.org/10.5194/bg-21-201-2024, https://doi.org/10.5194/bg-21-201-2024, 2024
Short summary
Short summary
We compared soil model performance to data from a long-term nitrogen addition experiment in a forested ecosystem. We found that in order for soil carbon models to accurately predict future forest carbon sequestration, two key processes must respond dynamically to nitrogen availability: (1) plant allocation of carbon to wood versus roots and (2) rates of soil organic matter decomposition. Long-term experiments can help improve our predictions of the land carbon sink and its climate impact.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
Short summary
Short summary
The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
Short summary
Short summary
Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
Short summary
Short summary
A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023, https://doi.org/10.5194/bg-20-3895-2023, 2023
Short summary
Short summary
Manure application to agricultural land often results in large and variable N2O emissions. We propose a model with a parsimonious structure to investigate N transformations around such N2O hotspots. The model allows for new detailed insights into the interactions between transport and microbial activities regarding N2O emissions in heterogeneous soil environments. It highlights the importance of solute diffusion to N2O emissions from such hotspots which are often ignored by process-based models.
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023, https://doi.org/10.5194/bg-20-3827-2023, 2023
Short summary
Short summary
In Finland peatlands cover one-third of land area. For half of those, with 4.3 Mha being drained for forestry, Finland reports sinks and sources of greenhouse gases in forest lands on organic soils following its UNFCCC commitment. We describe a new method for compiling soil CO2 balance that follows changes in tree volume, tree harvests and temperature. An increasing trend of emissions from 1.4 to 7.9 Mt CO2 was calculated for drained peatland forest soils in Finland for 1990–2021.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
Short summary
Short summary
Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Biogeosciences, 20, 3093–3117, https://doi.org/10.5194/bg-20-3093-2023, https://doi.org/10.5194/bg-20-3093-2023, 2023
Short summary
Short summary
Potassium is an essential element for living organisms. Trees are dependent upon this element for certain functions that allow them to build their trunks using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations, we were able to investigate the effect that a lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
Biogeosciences, 20, 3119–3135, https://doi.org/10.5194/bg-20-3119-2023, https://doi.org/10.5194/bg-20-3119-2023, 2023
Short summary
Short summary
After simulating the effects of low levels of potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in Part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees in acquiring carbon is enough to explain why they produce less wood when they are in soils with low levels of potassium.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
Short summary
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.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda D. Smith, and Yiqi Luo
Biogeosciences, 20, 2707–2725, https://doi.org/10.5194/bg-20-2707-2023, https://doi.org/10.5194/bg-20-2707-2023, 2023
Short summary
Short summary
The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
Short summary
Short summary
Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
Short summary
Short summary
We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
Short summary
Short summary
This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Biogeosciences, 20, 2265–2282, https://doi.org/10.5194/bg-20-2265-2023, https://doi.org/10.5194/bg-20-2265-2023, 2023
Short summary
Short summary
Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
Short summary
Short summary
Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899, https://doi.org/10.5194/bg-20-1879-2023, https://doi.org/10.5194/bg-20-1879-2023, 2023
Short summary
Short summary
In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health.
In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
Short summary
Short summary
Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
Short summary
Short summary
Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, https://doi.org/10.5194/bg-20-1313-2023, 2023
Short summary
Short summary
The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
Benjamin S. Felzer
Biogeosciences, 20, 573–587, https://doi.org/10.5194/bg-20-573-2023, https://doi.org/10.5194/bg-20-573-2023, 2023
Short summary
Short summary
The future of the terrestrial carbon sink depends upon the legacy of past land use, which determines the stand age of the forest and nutrient levels in the soil, both of which affect vegetation growth. This study uses a modeling approach to determine the effects of land-use legacy in the conterminous US from 1750 to 2099. Not accounting for land legacy results in a low carbon sink and high biomass, while water variables are not as highly affected.
Bailu Zhao and Qianlai Zhuang
Biogeosciences, 20, 251–270, https://doi.org/10.5194/bg-20-251-2023, https://doi.org/10.5194/bg-20-251-2023, 2023
Short summary
Short summary
In this study, we use a process-based model to simulate the northern peatland's C dynamics in response to future climate change during 1990–2300. Northern peatlands are projected to be a C source under all climate scenarios except for the mildest one before 2100 and C sources under all scenarios afterwards.
We find northern peatlands are a C sink until pan-Arctic annual temperature reaches −2.09 to −2.89 °C. This study emphasizes the vulnerability of northern peatlands to climate change.
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
Short summary
Short summary
In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Bimal K. Bhattacharya, Kaniska Mallick, Devansh Desai, Ganapati S. Bhat, Ross Morrison, Jamie R. Clevery, William Woodgate, Jason Beringer, Kerry Cawse-Nicholson, Siyan Ma, Joseph Verfaillie, and Dennis Baldocchi
Biogeosciences, 19, 5521–5551, https://doi.org/10.5194/bg-19-5521-2022, https://doi.org/10.5194/bg-19-5521-2022, 2022
Short summary
Short summary
Evaporation retrieval in heterogeneous ecosystems is challenging due to empirical estimation of ground heat flux and complex parameterizations of conductances. We developed a parameter-sparse coupled ground heat flux-evaporation model and tested it across different limits of water stress and vegetation fraction in the Northern/Southern Hemisphere. The model performed particularly well in the savannas and showed good potential for evaporative stress monitoring from thermal infrared satellites.
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832, https://doi.org/10.5194/bg-19-4811-2022, https://doi.org/10.5194/bg-19-4811-2022, 2022
Short summary
Short summary
In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
Jan De Pue, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs
Biogeosciences, 19, 4361–4386, https://doi.org/10.5194/bg-19-4361-2022, https://doi.org/10.5194/bg-19-4361-2022, 2022
Short summary
Short summary
The functioning of ecosystems involves numerous biophysical processes which interact with each other. Land surface models (LSMs) are used to describe these processes and form an essential component of climate models. In this paper, we evaluate the performance of three LSMs and their interactions with soil moisture and vegetation. Though we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
Jarmo Mäkelä, Laura Arppe, Hannu Fritze, Jussi Heinonsalo, Kristiina Karhu, Jari Liski, Markku Oinonen, Petra Straková, and Toni Viskari
Biogeosciences, 19, 4305–4313, https://doi.org/10.5194/bg-19-4305-2022, https://doi.org/10.5194/bg-19-4305-2022, 2022
Short summary
Short summary
Soils account for the largest share of carbon found in terrestrial ecosystems, and accurate depiction of soil carbon decomposition is essential in understanding how permanent these carbon storages are. We present a straightforward way to include carbon isotope concentrations into soil decomposition and carbon storages for the Yasso model, which enables the model to use 13C as a natural tracer to track changes in the underlying soil organic matter decomposition.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170, https://doi.org/10.5194/bg-19-4147-2022, https://doi.org/10.5194/bg-19-4147-2022, 2022
Short summary
Short summary
This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
Cited articles
Degree of Herbage Selection by Grazing Cattle, J. Dairy Sci., 37, 89–102, https://doi.org/10.3168/jds.S0022-0302(54)91236-9, 1954. a
Acocks, J. P. H.: Veld Types of South Africa, 3rd ed, Memoirs of the Botanical Survey of South Africa. Botanical Research Institute, Cape Town, South Africa, 1988. a
Bai, Y. and Cotrufo, M. F.: Grassland Soil Carbon Sequestration: Current Understanding, Challenges, and Solutions, Science, 377, 603–608, https://doi.org/10.1126/science.abo2380, 2022. a
Bai, Y., Han, X., Wu, J., Chen, Z., and Li, L.: Ecosystem Stability and Compensatory Effects in the Inner Mongolia Grassland, Nature, 431, 181–184, https://doi.org/10.1038/nature02850, 2004. a
Bazzaz, F. A.: Habitat Selection in Plants, Am. Nat., 137, 116–130, 1991. a
Bergmann, J., Weigelt, A., van der Plas, F., Laughlin, D. C., Kuyper, T. W., Guerrero-Ramirez, N., Valverde-Barrantes, O. J., Bruelheide, H., Freschet, G. T., Iversen, C. M., Kattge, J., McCormack, M. L., Meier, I. C., Rillig, M. C., Roumet, C., Semchenko, M., Sweeney, C. J., van Ruijven, J., York, L. M., and Mommer, L.: The Fungal Collaboration Gradient Dominates the Root Economics Space in Plants, Sci. Adv., 6, eaba3756, https://doi.org/10.1126/sciadv.aba3756, 2020. a, b
Boote, K. J., Hoogenboom, G., Jones, J. W., and Ingram, K. T.: Modeling Nitrogen Fixation and Its Relationship to Nitrogen Uptake in the CROPGRO Model, in: Quantifying and Understanding Plant Nitrogen Uptake for Systems Modeling, CRC Press, ISBN 978-0-429-14053-2, 2009. a
Branson, F. A.: Two New Factors Affecting Resistance of Grasses to Grazing, J. Range Manage., 6, 165, https://doi.org/10.2307/3893839, 1953. a
Brovkin, V., van Bodegom, P. M., Kleinen, T., Wirth, C., Cornwell, W. K., Cornelissen, J. H. C., and Kattge, J.: Plant-driven variation in decomposition rates improves projections of global litter stock distribution, Biogeosciences, 9, 565–576, https://doi.org/10.5194/bg-9-565-2012, 2012. a
Brown, J. S. and Venable, D. L.: Evolutionary Ecology of Seed-Bank Annuals in Temporally Varying Environments, Am. Nat., 127, 31–47, https://doi.org/10.1086/284465, 1986. a, b
Buzhdygan, O. Y., Meyer, S. T., Weisser, W. W., Eisenhauer, N., Ebeling, A., Borrett, S. R., Buchmann, N., Cortois, R., De Deyn, G. B., de Kroon, H., Gleixner, G., Hertzog, L. R., Hines, J., Lange, M., Mommer, L., Ravenek, J., Scherber, C., Scherer-Lorenzen, M., Scheu, S., Schmid, B., Steinauer, K., Strecker, T., Tietjen, B., Vogel, A., Weigelt, A., and Petermann, J. S.: Biodiversity Increases Multitrophic Energy Use Efficiency, Flow and Storage in Grasslands, Nat. Ecol. Evol., 4, 393–405, https://doi.org/10.1038/s41559-020-1123-8, 2020. a
Caccianiga, M., Luzzaro, A., Pierce, S., Ceriani, R. M., and Cerabolini, B.: The Functional Basis of a Primary Succession Resolved by CSR Classification, Oikos, 112, 10–20, https://doi.org/10.1111/j.0030-1299.2006.14107.x, 2006. a, b
Campbell, B. D. and Grime, J. P.: An Experimental Test of Plant Strategy Theory, Ecology, 73, 15–29, https://doi.org/10.2307/1938717, 1992. a
Cerabolini, B. E. L., Pierce, S., Verginella, A., Brusa, G., Ceriani, R. M., and Armiraglio, S.: Why Are Many Anthropogenic Agroecosystems Particularly Species-Rich?, Plant Biosyst. Int. J. Deal. Asp. Plant Biol., 150, 550–557, https://doi.org/10.1080/11263504.2014.987848, 2016. a
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
Chaplot, V., Bouahom, B., and Valentin, C.: Soil Organic Carbon Stocks in Laos: Spatial Variations and Controlling Factors, Glob. Change Biol., 16, 1380–1393, https://doi.org/10.1111/j.1365-2486.2009.02013.x, 2010. a
Chen, S., Wang, W., Xu, W., Wang, Y., Wan, H., Chen, D., Tang, Z., Tang, X., Zhou, G., Xie, Z., Zhou, D., Shangguan, Z., Huang, J., He, J.-S., Wang, Y., Sheng, J., Tang, L., Li, X., Dong, M., Wu, Y., Wang, Q., Wang, Z., Wu, J., Chapin, F. S., and Bai, Y.: Plant Diversity Enhances Productivity and Soil Carbon Storage, P. Natl. Acad. Sci. USA, 115, 4027–4032, https://doi.org/10.1073/pnas.1700298114, 2018. a
Chuan, X., Carlyle, C. N., Bork, E. W., Chang, S. X., and Hewins, D. B.: Long-Term Grazing Accelerated Litter Decomposition in Northern Temperate Grasslands, Ecosystems, 21, 1321–1334, https://doi.org/10.1007/s10021-018-0221-9, 2018. a
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
Cordova, F. J., Wallace, J. D., and Pieper, R. D.: Forage Intake by Grazing Livestock: A Review, J. Range Manag., 31, 430–438, https://doi.org/10.2307/3897201, 1978. a, b
Díaz, S., Kattge, J., Cornelissen, J. H. C., Wright, I. J., Lavorel, S., Dray, S., Reu, B., Kleyer, M., Wirth, C., Prentice, I. C., Garnier, E., Bönisch, G., Westoby, M., Poorter, H., Reich, P. B., Moles, A. T., Dickie, J., Gillison, A. N., Zanne, A. E., Chave, J., Wright, S. J., Sheremet'ev, S. N., Jactel, H., Baraloto, C., Cerabolini, B., Pierce, S., Shipley, B., Kirkup, D., Casanoves, F., Joswig, J. S., Günther, A., Falczuk, V., Rüger, N., Mahecha, M. D., and Gorné, L. D.: The Global Spectrum of Plant Form and Function, Nature, 529, 167–171, https://doi.org/10.1038/nature16489, 2016. a, b, c, d, e, f, g
Doetterl, S., Berhe, A. A., Nadeu, E., Wang, Z., Sommer, M., and Fiener, P.: Erosion, Deposition and Soil Carbon: A Review of Process-Level Controls, Experimental Tools and Models to Address C Cycling in Dynamic Landscapes, Earth-Sci. Rev., 154, 102–122, https://doi.org/10.1016/j.earscirev.2015.12.005, 2016. a
DWD: Wetter Und Klima – Deutscher Wetterdienst – Leistungen – Klimadaten Deutschland – Monats- Und Tageswerte (Archiv), https://www.dwd.de/DE/leistungen/klimadatendeutschland/klarchivtagmonat.html;jsessionid=A3AB03AA43161688F8D557F88FBF0BF8.live11053?nn=16102 (16 June 2022), 2021. a
Fei, S., Jo, I., Guo, Q., Wardle, D. A., Fang, J., Chen, A., Oswalt, C. M., and Brockerhoff, E. G.: Impacts of Climate on the Biodiversity-Productivity Relationship in Natural Forests, Nat. Commun., 9, 5436, https://doi.org/10.1038/s41467-018-07880-w, 2018. a
Forkel, M., Carvalhais, N., Schaphoff, S., v. Bloh, W., Migliavacca, M., Thurner, M., and Thonicke, K.: Identifying environmental controls on vegetation greenness phenology through model–data integration, Biogeosciences, 11, 7025–7050, https://doi.org/10.5194/bg-11-7025-2014, 2014. a
Forkel, M., Drüke, M., Thurner, M., Dorigo, W., Schaphoff, S., Thonicke, K., von Bloh, W., and Carvalhais, N.: Constraining Modelled Global Vegetation Dynamics and Carbon Turnover Using Multiple Satellite Observations, Sci. Rep., 9, 18757, https://doi.org/10.1038/s41598-019-55187-7, 2019. a, b
Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, 2022. a
Godde, C. M., de Boer, I. J. M., zu Ermgassen, E., Herrero, M., van Middelaar, C. E., Muller, A., Röös, E., Schader, C., Smith, P., van Zanten, H. H. E., and Garnett, T.: Soil Carbon Sequestration in Grazing Systems: Managing Expectations, Clim. Change, 161, 385–391, https://doi.org/10.1007/s10584-020-02673-x, 2020. a
Grime, J. P.: Vegetation Classification by Reference to Strategies, Nature, 250, 26–31, https://doi.org/10.1038/250026a0, 1974. a, b, c
Grime, J. P., Hodgson, J. G., and Hunt, R.: Comparative Plant Ecology: A Functional Approach to Common British Species, Springer Dordrecht, ISBN 978-94-017-1094-7, 1988. a
Guo, Q.: The Diversity–Biomass–Productivity Relationships in Grassland Management and Restoration, Bas. Appl. Ecol., 8, 199–208, https://doi.org/10.1016/j.baae.2006.02.005, 2007. a
Guuroh, R. T., Ruppert, J. C., Ferner, J., Čanak, K., Schmidtlein, S., and Linstädter, A.: Drivers of Forage Provision and Erosion Control in West African Savannas–A Macroecological Perspective, Agr. Ecosyst. Environ., 251, 257–267, https://doi.org/10.1016/j.agee.2017.09.017, 2018. a
Hardin, G.: The Competitive Exclusion Principle, Science, 131, 1292–1297, https://doi.org/10.1126/science.131.3409.1292, 1960. a
Herzfeld, T., Heinke, J., Rolinski, S., and Müller, C.: Soil organic carbon dynamics from agricultural management practices under climate change, Earth Syst. Dynam., 12, 1037–1055, https://doi.org/10.5194/esd-12-1037-2021, 2021. a
Hodgson, J. G., Wilson, P. J., Hunt, R., Grime, J. P., and Thompson, K.: Allocating C-S-R Plant Functional Types: A Soft Approach to a Hard Problem, Oikos, 85, 282–294, https://doi.org/10.2307/3546494, 1999. a
Hoffmann, C., Giese, M., Dickhoefer, U., Wan, H., Bai, Y., Steffens, M., Liu, C., Butterbach-Bahl, K., and Han, X.: Effects of Grazing and Climate Variability on Grassland Ecosystem Functions in Inner Mongolia: Synthesis of a 6-Year Grazing Experiment, J. Arid Environ., 135, 50–63, https://doi.org/10.1016/j.jaridenv.2016.08.003, 2016. a, b, c
Huhtanen, P., Nousiainen, J. I., Rinne, M., Kytölä, K., and Khalili, H.: Utilization and Partition of Dietary Nitrogen in Dairy Cows Fed Grass Silage-Based Diets, J. Dairy Sci., 91, 3589–3599, https://doi.org/10.3168/jds.2008-1181, 2008. a
Hunt, R., Hodgson, J., Thompson, K., Bungener, P., Dunnett, N., and Askew, A.: A New Practical Tool for Deriving a Functional Signature for Herbaceous Vegetation, Appl. Veg. Sci., 7, 163–170, https://doi.org/10.1111/j.1654-109X.2004.tb00607.x, 2004. a
Hyder, D. N.: Defoliation in Relation to Vegetative Growth, in: The Biology and Utilization of Grasses, edited by: Youngner V. B. and McKell, C. M., Academic Press, New York, 302–317, 1972. a
Isbell, F., Craven, D., Connolly, J., Loreau, M., Schmid, B., Beierkuhnlein, C., Bezemer, T. M., Bonin, C., Bruelheide, H., de Luca, E., Ebeling, A., Griffin, J. N., Guo, Q., Hautier, Y., Hector, A., Jentsch, A., Kreyling, J., Lanta, V., Manning, P., Meyer, S. T., Mori, A. S., Naeem, S., Niklaus, P. A., Polley, H. W., Reich, P. B., Roscher, C., Seabloom, E. W., Smith, M. D., Thakur, M. P., Tilman, D., Tracy, B. F., van der Putten, W. H., van Ruijven, J., Weigelt, A., Weisser, W. W., Wilsey, B., and Eisenhauer, N.: Biodiversity Increases the Resistance of Ecosystem Productivity to Climate Extremes, Nature, 526, 574–577, https://doi.org/10.1038/nature15374, 2015. a
Jacobsen, A. L., Pratt, R. B., Venturas, M. D., and Hacke, U. G.: Large Volume Vessels Are Vulnerable to Water-Stress-Induced Embolism in Stems of Poplar, IAWA J., 40, 4-S4, https://doi.org/10.1163/22941932-40190233, 2019. a
Jägermeyr, J., Gerten, D., Heinke, J., Schaphoff, S., Kummu, M., and Lucht, W.: Water savings potentials of irrigation systems: global simulation of processes and linkages, Hydrol. Earth Syst. Sci., 19, 3073–3091, https://doi.org/10.5194/hess-19-3073-2015, 2015. a
Jebari, A., Álvaro-Fuentes, J., Pardo, G., Batalla, I., Martín, J. A. R., and Del Prado, A.: Effect of Dairy Cattle Production Systems on Sustaining Soil Organic Carbon Storage in Grasslands of Northern Spain, Reg. Environ Change, 22, 67, https://doi.org/10.1007/s10113-022-01927-x, 2022. a
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, https://doi.org/10.1890/1051-0761(2000)010[0423:TVDOSO]2.0.CO;2, 2000. a
Johnson, H. A. and Biondini, M. E.: Root Morphological Plasticity and Nitrogen Uptake of 59 Plant Species from the Great Plains Grasslands, U.S.A., Basic and Applied Ecology, 2, 127–143, https://doi.org/10.1078/1439-1791-00044, 2001. a
Kaschuk, G., Kuyper, T. W., Leffelaar, P. A., Hungria, M., and Giller, K. E.: Are the Rates of Photosynthesis Stimulated by the Carbon Sink Strength of Rhizobial and Arbuscular Mycorrhizal Symbioses?, Soil Biol. Biochem., 41, 1233–1244, https://doi.org/10.1016/j.soilbio.2009.03.005, 2009. a
Kattge, J., Díaz, S., Lavorel, S., Prentice, I. C., Leadley, P., Bönisch, G., Garnier, E., Westoby, M., Reich, P. B., Wright, I. J., Cornelissen, J. H. C., Violle, C., Harrison, S. P., Van Bodegom, P. M., Reichstein, M., Enquist, B. J., Soudzilovskaia, N. A., Ackerly, D. D., Anand, M., Atkin, O., Bahn, M., Baker, T. R., Baldocchi, D., Bekker, R., Blanco, C. C., Blonder, B., Bond, W. J., Bradstock, R., Bunker, D. E., Casanoves, F., Cavender-Bares, J., Chambers, J. Q., Chapin Iii, F. S., Chave, J., Coomes, D., Cornwell, W. K., Craine, J. M., Dobrin, B. H., Duarte, L., Durka, W., Elser, J., Esser, G., Estiarte, M., Fagan, W. F., Fang, J., Fernández-Méndez, F., Fidelis, A., Finegan, B., Flores, O., Ford, H., Frank, D., Freschet, G. T., Fyllas, N. M., Gallagher, R. V., Green, W. A., Gutierrez, A. G., Hickler, T., Higgins, S. I., Hodgson, J. G., Jalili, A., Jansen, S., Joly, C. A., Kerkhoff, A. J., Kirkup, D., Kitajima, K., Kleyer, M., Klotz, S., Knops, J. M. H., Kramer, K., Kühn, I., Kurokawa, H., Laughlin, D., Lee, T. D., Leishman, M., Lens, F., Lenz, T., Lewis, S. L., Lloyd, J., Llusià, J., Louault, F., Ma, S., Mahecha, M. D., Manning, P., Massad, T., Medlyn, B. E., Messier, J., Moles, A. T., Müller, S. C., Nadrowski, K., Naeem, S., Niinemets, Ü., Nöllert, S., Nüske, A., Ogaya, R., Oleksyn, J., Onipchenko, V. G., Onoda, Y., Ordoñez, J., Overbeck, G., Ozinga, W. A., Patiño, S., Paula, S., Pausas, J. G., Peñuelas, J., Phillips, O. L., Pillar, V., Poorter, H., Poorter, L., Poschlod, P., Prinzing, A., Proulx, R., Rammig, A., Reinsch, S., Reu, B., Sack, L., Salgado-Negret, B., Sardans, J., Shiodera, S., Shipley, B., Siefert, A., Sosinski, E., Soussana, J.-F., Swaine, E., Swenson, N., Thompson, K., Thornton, P., Waldram, M., Weiher, E., White, M., White, S., Wright, S. J., Yguel, B., Zaehle, S., Zanne, A. E., and Wirth, C.: TRY – a Global Database of Plant Traits, Glob. Change Biol., 17, 2905–2935, https://doi.org/10.1111/j.1365-2486.2011.02451.x, 2011. a
Kölbl, A., Steffens, M., Wiesmeier, M., Hoffmann, C., Funk, R., Krümmelbein, J., Reszkowska, A., Zhao, Y., Peth, S., Horn, R., Giese, M., and Kögel-Knabner, I.: Grazing Changes Topography-Controlled Topsoil Properties and Their Interaction on Different Spatial Scales in a Semi-Arid Grassland of Inner Mongolia, P.R. China, Plant Soil, 340, 35–58, https://doi.org/10.1007/s11104-010-0473-4, 2011. a
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World Map of the Köppen-Geiger Climate Classification Updated, Metz, 15, 259–263, https://doi.org/10.1127/0941-2948/2006/0130, 2006. a, b
Koven, C. D., Hugelius, G., Lawrence, D. M., and Wieder, W. R.: Higher Climatological Temperature Sensitivity of Soil Carbon in Cold than Warm Climates, Nat. Clim. Change, 7, 817–822, https://doi.org/10.1038/nclimate3421, 2017. a
Kull, O.: Acclimation of Photosynthesis in Canopies: Models and Limitations, Oecologia, 133, 267–279, https://doi.org/10.1007/s00442-002-1042-1, 2002. a
Lange, S. and Büchner, M.: Secondary ISIMIP3b Bias-Adjusted Atmospheric Climate Input Data, https://doi.org/10.48364/ISIMIP.581124.1, 2022. a
Lee, M. A.: A Global Comparison of the Nutritive Values of Forage Plants Grown in Contrasting Environments, J. Plant Res., 131, 641–654, https://doi.org/10.1007/s10265-018-1024-y, 2018. a
Lepš, J., Osbornová-Kosinová, J., and Rejmánek, M.: Community Stability, Complexity and Species Life History Strategies, Vegetatio, 50, 53–63, https://doi.org/10.1007/BF00120678, 1982. a
Li, J., Lin, S., Taube, F., Pan, Q., and Dittert, K.: Above and Belowground Net Primary Productivity of Grassland Influenced by Supplemental Water and Nitrogen in Inner Mongolia, Plant Soil, 340, 253–264, https://doi.org/10.1007/s11104-010-0612-y, 2011. a, b, c
Liu, J., Li, L., Ji, L., Li, Y., Liu, J., and Li, F. Y.: Divergent Effects of Grazing versus Mowing on Plant Nutrients in Typical Steppe Grasslands of Inner Mongolia, J. Plant Ecol., 16, rtac032, https://doi.org/10.1093/jpe/rtac032, 2023. a
Liu, Y., Wu, L., Baddeley, J. A., and Watson, C. A.: Models of Biological Nitrogen Fixation of Legumes. A Review, Agronomy Sust. Developm., 31, 155–172, https://doi.org/10.1051/agro/2010008, 2011. a
Liu, Y. Y., Evans, J. P., McCabe, M. F., de Jeu, R. A. M., van Dijk, A. I. J. M., Dolman, A. J., and Saizen, I.: Changing Climate and Overgrazing Are Decimating Mongolian Steppes, PLOS ONE, 8, e57599, https://doi.org/10.1371/journal.pone.0057599, 2013. a
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
Ma, J., Olin, S., Anthoni, P., Rabin, S. S., Bayer, A. D., Nyawira, S. S., and Arneth, A.: Modeling symbiotic biological nitrogen fixation in grain legumes globally with LPJ-GUESS (v4.0, r10285), Geosci. Model Dev., 15, 815–839, https://doi.org/10.5194/gmd-15-815-2022, 2022. a, b
May, F., Grimm, V., and Jeltsch, F.: Reversed Effects of Grazing on Plant Diversity: The Role of below-Ground Competition and Size Symmetry, Oikos, 118, 1830–1843, https://doi.org/10.1111/j.1600-0706.2009.17724.x, 2009. a, b
McSherry, M. E. and Ritchie, M. E.: Effects of Grazing on Grassland Soil Carbon: A Global Review, Glob. Change Biol., 19, 1347–1357, https://doi.org/10.1111/gcb.12144, 2013. a, b
Meier, I. C. and Leuschner, C.: Variation of Soil and Biomass Carbon Pools in Beech Forests across a Precipitation Gradient, Glob. Change Biol., 16, 1035–1045, https://doi.org/10.1111/j.1365-2486.2009.02074.x, 2010. a
Munjonji, L., Ayisi, K. K., Mudongo, E. I., Mafeo, T. P., Behn, K., Mokoka, M. V., and Linstädter, A.: Disentangling Drought and Grazing Effects on Soil Carbon Stocks and CO2 Fluxes in a Semi-Arid African Savanna, Front. Environ. Sci., 8, https://doi.org/10.3389/fenvs.2020.590665, 2020. a, b, c, d, e
Newman, J. A., Parsons, A. J., Thornley, J. H. M., Penning, P. D., and Krebs, J. R.: Optimal Diet Selection by a Generalist Grazing Herbivore, Funct. Ecol., 9, 255–268, https://doi.org/10.2307/2390572, 1995. a
Noy-Meir, I.: Responses of Two Semiarid Rangeland Communities to Protection from Grazing, Isr. J. Plant Sci., 39, 431–442, https://doi.org/10.1080/0021213X.1990.10677166, 1990. a
Onoda, Y., Wright, I. J., Evans, J. R., Hikosaka, K., Kitajima, K., Niinemets, Ü., Poorter, H., Tosens, T., and Westoby, M.: Physiological and Structural Tradeoffs Underlying the Leaf Economics Spectrum, New Phytol., 214, 1447–1463, https://doi.org/10.1111/nph.14496, 2017. a
Parsons, A., Newman, J., Penning, P., Harvey, A., and Orr, R.: Diet Preference of Sheep: Effects of Recent Diet, Physiological State and Species Abundance, J. Anim. Ecol., 63, 465–478, https://doi.org/10.2307/5563, 1994. a
Patterson, T. G. and Larue, T. A.: Root Respiration Associated with Nitrogenase Activity (C2H2) of Soybean, and a Comparison of Estimates 1, Plant Physiol., 72, 701–705, https://doi.org/10.1104/pp.72.3.701, 1983. a
Pfeiffer, M., Langan, L., Linstädter, A., Martens, C., Gaillard, C., Ruppert, J. C., Higgins, S. I., Mudongo, E. I., and Scheiter, S.: Grazing and Aridity Reduce Perennial Grass Abundance in Semi-Arid Rangelands – Insights from a Trait-Based Dynamic Vegetation Model, Ecol. Model., 395, 11–22, https://doi.org/10.1016/j.ecolmodel.2018.12.013, 2019. a, b
Pierce, S., Brusa, G., Vagge, I., and Cerabolini, B. E. L.: Allocating CSR Plant Functional Types: The Use of Leaf Economics and Size Traits to Classify Woody and Herbaceous Vascular Plants, Funct. Ecol., 27, 1002–1010, https://doi.org/10.1111/1365-2435.12095, 2013. a, b
Pierce, S., Negreiros, D., Cerabolini, B. E. L., Kattge, J., Díaz, S., Kleyer, M., Shipley, B., Wright, S. J., Soudzilovskaia, N. A., Onipchenko, V. G., van Bodegom, P. M., Frenette-Dussault, C., Weiher, E., Pinho, B. X., Cornelissen, J. H. C., Grime, J. P., Thompson, K., Hunt, R., Wilson, P. J., Buffa, G., Nyakunga, O. C., Reich, P. B., Caccianiga, M., Mangili, F., Ceriani, R. M., Luzzaro, A., Brusa, G., Siefert, A., Barbosa, N. P. U., Chapin, F. S., Cornwell, W. K., Fang, J., Fernandes, G. W., Garnier, E., Stradic, S. L., Peñuelas, J., Melo, F. P. L., Slaviero, A., Tabarelli, M., and Tampucci, D.: A Global Method for Calculating Plant CSR Ecological Strategies Applied across Biomes World-Wide, Funct. Ecol., 31, 444–457, https://doi.org/10.1111/1365-2435.12722, 2017. a, b, c
Piñeiro, G., Paruelo, J. M., Oesterheld, M., and Jobbágy, E. G.: Pathways of Grazing Effects on Soil Organic Carbon and Nitrogen, Rangel. Ecol. Manage., 63, 109–119, https://doi.org/10.2111/08-255.1, 2010. a
Quillet, A., Peng, C., and Garneau, M.: Toward Dynamic Global Vegetation Models for Simulating Vegetation–Climate Interactions and Feedbacks: Recent Developments, Limitations, and Future Challenges, Environ. Rev., 18, 333–353, https://doi.org/10.1139/A10-016, 2010. a
R Core Team: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, https://www.R-project.org/ (last access: 8 April 2020), 2019. a
Rechenthin, C. A.: Elementary Morphology of Grass Growth and How It Affects Utilization, Range Manage., 9, 167–170, 1956. a
Reinsch, T., Loges, R., Kluß, C., and Taube, F.: Effect of Grassland Ploughing and Reseeding on CO2 Emissions and Soil Carbon Stocks, Agriculture, Ecosyst. Environ., 265, 374–383, https://doi.org/10.1016/j.agee.2018.06.020, 2018a. a, b
Reinsch, T., Loges, R., Kluß, C., and Taube, F.: Renovation and Conversion of Permanent Grass-Clover Swards to Pasture or Crops: Effects on Annual N2O Emissions in the Year after Ploughing, Soil Till. Res., 175, 119–129, https://doi.org/10.1016/j.still.2017.08.009, 2018b. a, b, c, d
Reinsch, T., Malisch, C., Loges, R., and Taube, F.: Nitrous Oxide Emissions from Grass–Clover Swards as Influenced by Sward Age and Biological Nitrogen Fixation, Grass Forage Sci., 75, 372–384, https://doi.org/10.1111/gfs.12496, 2020. a, b
Ren, H., Taube, F., Stein, C., Zhang, Y., Bai, Y., and Hu, S.: Grazing Weakens Temporal Stabilizing Effects of Diversity in the Eurasian Steppe, Ecol. Evol., 8, 231–241, https://doi.org/10.1002/ece3.3669, 2017. 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, c, d, e, f, g, h, i
Rolinski, S., Wirth, S. B., Müller, C., and Tietjen, B.: Strategies for Assessing Grassland Degradation, in: Jt. XXIV Int, Grassl, XI Int, Rangel, Kenya 2021 Virtual Congr, Oral Pap, Proc., vol. 1, Kenya Agricultural and Livestock Research Organisation, Nairobi, Kenia, 383–387, ISBN 978-996-30-093-5, 2021. a
Ruppert, J. C., Harmoney, K., Henkin, Z., Snyman, H. A., Sternberg, M., Willms, W., and Linstädter, A.: Quantifying Drylands' Drought Resistance and Recovery: The Importance of Drought Intensity, Dominant Life History and Grazing Regime, Glob. Change Biol., 21, 1258–1270, https://doi.org/10.1111/gcb.12777, 2015. a
Ryle, G. J. A., Powell, C. E., and Gordon, A. J.: The Respiratory Costs of Nitrogen Fixation in Soyabean, Cowpea, and White Clover: I. Nitrogen Fixation and the Respiration of the Nodulated Root, J. Exp. Bot., 30, 135–144, https://doi.org/10.1093/jxb/30.1.135, 1979. a
Sakschewski, B., von Bloh, W., Boit, A., Rammig, A., Kattge, J., Poorter, L., Peñuelas, J., and Thonicke, K.: Leaf and Stem Economics Spectra Drive Diversity of Functional Plant Traits in a Dynamic Global Vegetation Model, Glob. Change Biol., 21, 2711–2725, https://doi.org/10.1111/gcb.12870, 2015. a, b, c, d, e
Salisbury, E. J.: The Reproductive Capacity of Plants, Nature, 151, 319–320, https://doi.org/10.1038/151319a0, 1943. a
Schaphoff, S., von Bloh, W., Rammig, A., Thonicke, K., Biemans, H., Forkel, M., Gerten, D., Heinke, J., Jägermeyr, J., Knauer, J., Langerwisch, F., Lucht, W., Müller, C., Rolinski, S., and Waha, K.: LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description, Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018, 2018. a, b, c, d, e, f, g, h, i
Scheiter, S., Langan, L., and Higgins, S. I.: Next-Generation Dynamic Global Vegetation Models: Learning from Community Ecology, New Phytol., 198, 957–969, https://doi.org/10.1111/nph.12210, 2013. a
Scheiter, S., Pfeiffer, M., Behn, K., Ayisi, K. K., Siebert, F., and Linstädter, A.: Managing Southern African Rangeland Systems in the Face of Drought – a Synthesis of Observation, Experimentation, and Modelling for Policy and Decision Support, in: Sustainability of Southern African Ecosystems under Global Change, edited by: von Maltitz, G. P., Midgley, G. F., Veitch, J., Brümmer, C., Rötter, R. P., Viehberg, F. A., and Veste, M., vol. 248 of Ecological Studies, Springer, ISBN 978-3-031-10948-5, https://doi.org/10.1007/978-3-031-10948-5, 2023. a, b, c
Schimel, D., Stephens, B. B., and Fisher, J. B.: Effect of Increasing CO2 on the Terrestrial Carbon Cycle, P. Natl. Acad. Sci. USA, 112, 436–441, https://doi.org/10.1073/pnas.1407302112, 2015. a
Schmid, J. S., Huth, A., and Taubert, F.: Influences of Traits and Processes on Productivity and Functional Composition in Grasslands: A Modeling Study, Ecol. Model., 440, 109395, https://doi.org/10.1016/j.ecolmodel.2020.109395, 2021. a
Schmidtlein, S., Feilhauer, H., and Bruelheide, H.: Mapping Plant Strategy Types Using Remote Sensing, J. Veg. Sci., 23, 395–405, https://doi.org/10.1111/j.1654-1103.2011.01370.x, 2012. a
Schönbach, P., Wan, H., Gierus, M., Loges, R., Müller, K., Lin, L., Susenbeth, A., and Taube, F.: Effects of Grazing and Precipitation on Herbage Production, Herbage Nutritive Value and Performance of Sheep in Continental Steppe, Grass Forage Sci., 67, 535–545, https://doi.org/10.1111/j.1365-2494.2012.00874.x, 2012. a, b, c
Shi, Y., Ao, Y., Sun, B., Knops, J. M. H., Zhang, J., Guo, Z., De, X., Han, J., Yang, Y., Jiang, X., Mu, C., and Wang, J.: Productivity of Leymus Chinensis Grassland Is Co-Limited by Water and Nitrogen and Resilient to Climate Change, Plant Soil, 474, 411–422, https://doi.org/10.1007/s11104-022-05344-1, 2022. a
Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M., Piao, S. L., Betts, R., Ciais, P., Cox, P., Friedlingstein, P., Jones, C. D., Prentice, I. C., and Woodward, F. I.: Evaluation of the Terrestrial Carbon Cycle, Future Plant Geography and Climate-Carbon Cycle Feedbacks Using Five Dynamic Global Vegetation Models (DGVMs), Glob. Change Biol., 14, 2015–2039, https://doi.org/10.1111/j.1365-2486.2008.01626.x, 2008. a
Sleutel, S., De Neve, S., and Hofman, G.: Assessing Causes of Recent Organic Carbon Losses from Cropland Soils by Means of Regional-Scaled Input Balances for the Case of Flanders (Belgium), Nutr. Cycl. Agroecosyst., 78, 265–278, https://doi.org/10.1007/s10705-007-9090-x, 2007. a
Stuart-Hill, G. and Mentis, M.: Coevolution of African Grasses and Large Herbivores, Proc. Annu. Congr. Grassl. Soc. South. Afr., 17, 122–128, https://doi.org/10.1080/00725560.1982.9648969, 1982. a, b
Taubert, F., Frank, K., and Huth, A.: A Review of Grassland Models in the Biofuel Context, Ecol. Model., 245, 84–93, https://doi.org/10.1016/j.ecolmodel.2012.04.007, 2012. a
Taubert, F., Hetzer, J., Schmid, J. S., and Huth, A.: Confronting an Individual-Based Simulation Model with Empirical Community Patterns of Grasslands, PLOS ONE, 15, e0236546, https://doi.org/10.1371/journal.pone.0236546, 2020a. a
Taubert, F., Hetzer, J., Schmid, J. S., and Huth, A.: The Role of Species Traits for Grassland Productivity, Ecosphere, 11, e03205, https://doi.org/10.1002/ecs2.3205, 2020b. a
Teng, Y., Zhan, J., Agyemang, F. B., and Sun, Y.: The Effects of Degradation on Alpine Grassland Resilience: A Study Based on Meta-Analysis Data, Glob. Ecol. Conserv., 24, e01336, https://doi.org/10.1016/j.gecco.2020.e01336, 2020. a
Thompson, K.: Seeds and Seed Banks, New Phytol., 106, 23–34, https://doi.org/10.1111/j.1469-8137.1987.tb04680.x, 1987. a, b
Thonicke, K., Billing, M., von Bloh, W., Sakschewski, B., Niinemets, Ü., Peñuelas, J., Cornelissen, J. H. C., Onoda, Y., van Bodegom, P., Schaepman, M. E., Schneider, F. D., and Walz, A.: Simulating Functional Diversity of European Natural Forests along Climatic Gradients, J. Biogeogr., 47, 1069–1085, https://doi.org/10.1111/jbi.13809, 2020. a, b
Tilman, D. and El Haddi, A.: Drought and Biodiversity in Grasslands, Oecologia, 89, 257–264, https://doi.org/10.1007/BF00317226, 1992. a
Tribe, D. E. and Gordon, J. G.: An experimental study of palatability, Agric. Progr., 25, 94–101, 1950. a
Tron, S., Bodner, G., Laio, F., Ridolfi, L., and Leitner, D.: Can Diversity in Root Architecture Explain Plant Water Use Efficiency? A Modeling Study, Ecol. Model., 312, 200–210, https://doi.org/10.1016/j.ecolmodel.2015.05.028, 2015. a
Van Oijen, M., Rougier, J., and Smith, R.: Bayesian Calibration of Process-Based Forest Models: Bridging the Gap between Models and Data, Tree Physiol., 25, 915–927, https://doi.org/10.1093/treephys/25.7.915, 2005. 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, b, c
Wan, H., Bai, Y., Hooper, D. U., Schönbach, P., Gierus, M., Schiborra, A., and Taube, F.: Selective Grazing and Seasonal Precipitation Play Key Roles in Shaping Plant Community Structure of Semi-Arid Grasslands, Landscape Ecol., 30, 1767–1782, https://doi.org/10.1007/s10980-015-0252-y, 2015. a, b
Waring, R. H.: Estimating Forest Growth and Efficiency in Relation to Canopy Leaf Area, in: Advances in Ecological Research, edited by: MacFadyen, A. and Ford, E. D., vol. 13, Academic Press, 327–354, https://doi.org/10.1016/S0065-2504(08)60111-7, 1983. a
Waring, R. H. and Schlesinger, W. H.: Forest Ecosystems: Concepts and Management, Academic Press, Orlando, Florida, ISBN 978-0127354415, 1985. a
Weigelt, A., Mommer, L., Andraczek, K., Iversen, C. M., Bergmann, J., Bruelheide, H., Fan, Y., Freschet, G. T., Guerrero-Ramírez, N. R., Kattge, J., Kuyper, T. W., Laughlin, D. C., Meier, I. C., van der Plas, F., Poorter, H., Roumet, C., van Ruijven, J., Sabatini, F. M., Semchenko, M., Sweeney, C. J., Valverde-Barrantes, O. J., York, L. M., and McCormack, M. L.: An Integrated Framework of Plant Form and Function: The Belowground Perspective, New Phytol., 232, 42–59, https://doi.org/10.1111/nph.17590, 2021. a, b
Weisser, W. W., Roscher, C., Meyer, S. T., Ebeling, A., Luo, G., Allan, E., Beßler, H., Barnard, R. L., Buchmann, N., Buscot, F., Engels, C., Fischer, C., Fischer, M., Gessler, A., Gleixner, G., Halle, S., Hildebrandt, A., Hillebrand, H., de Kroon, H., Lange, M., Leimer, S., Le Roux, X., Milcu, A., Mommer, L., Niklaus, P. A., Oelmann, Y., Proulx, R., Roy, J., Scherber, C., Scherer-Lorenzen, M., Scheu, S., Tscharntke, T., Wachendorf, M., Wagg, C., Weigelt, A., Wilcke, W., Wirth, C., Schulze, E.-D., Schmid, B., and Eisenhauer, N.: Biodiversity Effects on Ecosystem Functioning in a 15-Year Grassland Experiment: Patterns, Mechanisms, and Open Questions, Basic Appl. Ecol., 23, 1–73, https://doi.org/10.1016/j.baae.2017.06.002, 2017. a
Westoby, M., Leishman, M., and Lord, J.: Comparative Ecology of Seed Size and Dispersal, Philos. T. Roy. Soc. B, 351, 1309–1318, https://doi.org/10.1098/rstb.1996.0114, 1996. a
White, R. P., Murray, S., and Rohweder, M.: Pilot Analysis of Global Ecosystems: Grassland Ecosystems, Pilot Anal. Glob. Ecosyst. Grassl. Ecosyst., ISBN 1-56973-461-5, 2000. a
Wiesmeier, M., Barthold, F., Blank, B., and Kögel-Knabner, I.: Digital Mapping of Soil Organic Matter Stocks Using Random Forest Modeling in a Semi-Arid Steppe Ecosystem, Plant Soil, 340, 7–24, https://doi.org/10.1007/s11104-010-0425-z, 2011. a, b, c
Wiesmeier, M., Kreyling, O., Steffens, M., Schoenbach, P., Wan, H., Gierus, M., Taube, F., Kölbl, A., and Kögel-Knabner, I.: Short-Term Degradation of Semiarid Grasslands–Results from a Controlled-Grazing Experiment in Northern China, J. Plant Nutr. Soil Sci., 175, 434–442, https://doi.org/10.1002/jpln.201100327, 2012. a, b
Wiesmeier, M., Urbanski, L., Hobley, E., Lang, B., von Lützow, M., Marin-Spiotta, E., van Wesemael, B., Rabot, E., Ließ, M., Garcia-Franco, N., Wollschläger, U., Vogel, H.-J., and Kögel-Knabner, I.: Soil Organic Carbon Storage as a Key Function of Soils – A Review of Drivers and Indicators at Various Scales, Geoderma, 333, 149–162, https://doi.org/10.1016/j.geoderma.2018.07.026, 2019. a
Wirth, S. B., Taubert, F., Tietjen, B., Müller, C., and Rolinski, S.: Do Details Matter?, Disentangling the Processes Related to Plant Species Interactions in Two Grassland Models of Different Complexity, Ecol. Model., 460, 109737, https://doi.org/10.1016/j.ecolmodel.2021.109737, 2021. a, b, c
Wirth, S. B., Müller, C., and Rolinski, S.: Code and Data Connecting competitor, stress-tolerator and ruderal (CSR) theory and Lund Potsdam Jena managed Land 5 (LPJmL 5) to assess the role of environmental conditions, management and functional diversity for grassland ecosystem functions, Zenodo, https://doi.org/10.5281/zenodo.10217244, 2023. a
Woodward, F. I. and Diament, A. D.: Functional Approaches to Predicting the Ecological Effects of Global Change, Funct. Ecol., 5, 202–212. https://doi.org/10.2307/2389258, 1991. a
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z., Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., Diemer, M., Flexas, J., Garnier, E., Groom, P. K., Gulias, J., Hikosaka, K., Lamont, B. B., Lee, T., Lee, W., Lusk, C., Midgley, J. J., Navas, M.-L., Niinemets, U., Oleksyn, J., Osada, N., Poorter, H., Poot, P., Prior, L., Pyankov, V. I., Roumet, C., Thomas, S. C., Tjoelker, M. G., Veneklaas, E. J., and Villar, R.: The Worldwide Leaf Economics Spectrum, Nature, 428, 821–827, https://doi.org/10.1038/nature02403, 2004. a, b, c
Xie, Q., Huete, A., Hall, C. C., Medlyn, B. E., Power, S. A., Davies, J. M., Medek, D. E., and Beggs, P. J.: Satellite-Observed Shifts in C3/C4 Abundance in Australian Grasslands Are Associated with Rainfall Patterns, Remote Sens. Environ., 273, 112983, https://doi.org/10.1016/j.rse.2022.112983, 2022.
Yang, Y., Zhu, Q., Peng, C., Wang, H., and Chen, H.: From Plant Functional Types to Plant Functional Traits: A New Paradigm in Modelling Global Vegetation Dynamics, Prog. Phys. Geogr., 39, 514–535, https://doi.org/10.1177/0309133315582018, 2015. a
Yang, Y., Tilman, D., Furey, G., and Lehman, C.: Soil Carbon Sequestration Accelerated by Restoration of Grassland Biodiversity, Nat. Commun., 10, 718, https://doi.org/10.1038/s41467-019-08636-w, 2019. a, b
Yu, Q., Wu, H., Wang, Z., Flynn, D. F. B., Yang, H., Lü, F., Smith, M., and Han, X.: Long Term Prevention of Disturbance Induces the Collapse of a Dominant Species without Altering Ecosystem Function, Sci. Rep., 5, 14320, https://doi.org/10.1038/srep14320, 2015. a
Yu, T. and Zhuang, Q.: Modeling biological nitrogen fixation in global natural terrestrial ecosystems, Biogeosciences, 17, 3643–3657, https://doi.org/10.5194/bg-17-3643-2020, 2020. a, b, c
Zaehle, S., Sitch, S., Smith, B., and Hatterman, F.: Effects of Parameter Uncertainties on the Modeling of Terrestrial Biosphere Dynamics, Glob. Biogeochem. Cycles, 19, GB3020, https://doi.org/10.1029/2004GB002395, 2005. a
Zimmermann, J., Higgins, S. I., Grimm, V., Hoffmann, J., and Linstädter, A.: Grass Mortality in Semi-Arid Savanna: The Role of Fire, Competition and Self-Shading, Perspectives in Plant Ecology, Evol. Syst., 12, 1–8, https://doi.org/10.1016/j.ppees.2009.09.003, 2010. a, b, c
Short summary
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.
In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply...
Altmetrics
Final-revised paper
Preprint