Articles | Volume 11, issue 7
Geosci. Model Dev., 11, 2789–2812, 2018
https://doi.org/10.5194/gmd-11-2789-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: The Lund–Potsdam–Jena managed Land (LPJmL) dynamic...
Geosci. Model Dev., 11, 2789–2812, 2018
https://doi.org/10.5194/gmd-11-2789-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper 12 Jul 2018
Model description paper | 12 Jul 2018
Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0)
Werner von Bloh et al.
Related authors
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.
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.
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.
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.
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.
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
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
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi T. T. Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul K. Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-386, https://doi.org/10.5194/essd-2021-386, 2021
Preprint under review for ESSD
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Taraka Davies-Barnard, Sönke Zaehle, and Pierre Friedlingstein
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-290, https://doi.org/10.5194/bg-2021-290, 2021
Preprint under review for BG
Short summary
Short summary
Biological nitrogen fixation is the largest natural input of new nitrogen onto land. Earth System Models mainly represent global total terrestrial biological nitrogen fixation within observational uncertainties, but overestimate tropical fixation. The model range of increase in biological nitrogen fixation increase in the SSP3-7.0 scenario is 3 to 87 %. While biological nitrogen fixation is an key source of new nitrogen, its predictive power for net primary productivity in models is limited.
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.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
Short summary
Short summary
The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
Short summary
Short summary
Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
Short summary
Short summary
Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters have been emerging, especially in the last 2 decades. A collection of model simulations in conjunction with causal theory points at climatic changes as a key driver of vegetation changes in natural ecosystems. Most models underestimate the observed vegetation browning, especially in tropical rainforests, which could be due to an excessive CO2 fertilization effect in models.
Vera Porwollik, Susanne Rolinski, Jens Heinke, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-215, https://doi.org/10.5194/bg-2021-215, 2021
Revised manuscript accepted for BG
Short summary
Short summary
The study assesses the impacts of cover crop practices on soil carbon, nitrogen leaching, and crop yields in comparison to a control management scenario with bare soil fallowing by applying the global vegetation model LPJml (V.5.0-tillage-cc). The potential and determinants of environmental and agronomic benefits of the practice vary with respect to management duration, type of tillage, mineral fertilizer application rate, and environmental conditions of the cropland.
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).
Martina Franz and Sönke Zaehle
Biogeosciences, 18, 3219–3241, https://doi.org/10.5194/bg-18-3219-2021, https://doi.org/10.5194/bg-18-3219-2021, 2021
Short summary
Short summary
The combined effects of ozone and nitrogen deposition on the terrestrial carbon uptake and storage has been unclear. Our simulations, from 1850 to 2099, show that ozone-related damage considerably reduced gross primary production and carbon storage in the past. The growth-stimulating effect induced by nitrogen deposition is offset until the 2050s. Accounting for nitrogen deposition without considering ozone effects might lead to an overestimation of terrestrial carbon uptake and storage.
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
Short summary
Short summary
We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, https://doi.org/10.5194/gmd-14-2161-2021, 2021
Short summary
Short summary
Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
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.
Daniele Peano, Deborah Hemming, Stefano Materia, Christine Delire, Yuanchao Fan, Emilie Joetzjer, Hanna Lee, Julia E. M. S. Nabel, Taejin Park, Philippe Peylin, David Wårlind, Andy Wiltshire, and Sönke Zaehle
Biogeosciences, 18, 2405–2428, https://doi.org/10.5194/bg-18-2405-2021, https://doi.org/10.5194/bg-18-2405-2021, 2021
Short summary
Short summary
Global climate models are the scientist’s tools used for studying past, present, and future climate conditions. This work examines the ability of a group of our tools in reproducing and capturing the right timing and length of the season when plants show their green leaves. This season, indeed, is fundamental for CO2 exchanges between land, atmosphere, and climate. This work shows that discrepancies compared to observations remain, demanding further polishing of these tools.
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.
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 Discuss., https://doi.org/10.5194/bg-2020-468, https://doi.org/10.5194/bg-2020-468, 2020
Preprint under review for BG
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.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Tea Thum, Julia E. M. S. Nabel, Aki Tsuruta, Tuula Aalto, Edward J. Dlugokencky, Jari Liski, Ingrid T. Luijkx, Tiina Markkanen, Julia Pongratz, Yukio Yoshida, and Sönke Zaehle
Biogeosciences, 17, 5721–5743, https://doi.org/10.5194/bg-17-5721-2020, https://doi.org/10.5194/bg-17-5721-2020, 2020
Short summary
Short summary
Global vegetation models are important tools in estimating the impacts of global climate change. The fate of soil carbon is of the upmost importance as its emissions will enhance the atmospheric carbon dioxide concentration. To evaluate the skill of global vegetation models to model the soil carbon and its responses to environmental factors, it is important to use different data sources. We evaluated two different soil carbon models by using atmospheric carbon dioxide concentrations.
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
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.
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.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, https://doi.org/10.5194/hess-24-1485-2020, 2020
Short summary
Short summary
Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Lin Yu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 13, 783–803, https://doi.org/10.5194/gmd-13-783-2020, https://doi.org/10.5194/gmd-13-783-2020, 2020
Short summary
Short summary
In this paper, we have developed a new soil organic carbon model that describes the formation and turnover of soil organic matter in a more mechanistic manner. With this model, we are able to better represent how microorganisms and nutrient processes influence the below-ground carbon storage and better explain some observed features of soil organic matter. We hope this model can increase our confidence in predictions of future climate change, particularly on how soil can mitigate the process.
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.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
Short summary
Short summary
The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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.
Nicolas Vuichard, Palmira Messina, Sebastiaan Luyssaert, Bertrand Guenet, Sönke Zaehle, Josefine Ghattas, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 12, 4751–4779, https://doi.org/10.5194/gmd-12-4751-2019, https://doi.org/10.5194/gmd-12-4751-2019, 2019
Short summary
Short summary
In this research, we present a new version of the global terrestrial ecosystem model ORCHIDEE in which carbon and nitrogen cycles are coupled. We evaluate its skills at simulating primary production at 78 sites and at a global scale. Based on a set of additional simulations in which carbon and nitrogen cycles are coupled and uncoupled, we show that the functional responses of the model with carbon–nitrogen interactions better agree with our current understanding of photosynthesis.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
Short summary
Short summary
To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
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.
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019, https://doi.org/10.5194/gmd-12-4075-2019, 2019
Short summary
Short summary
We assess the differences of six stomatal conductance formulations, embedded into a land–vegetation model JSBACH, on 10 boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event at one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation-dependent model behaviour that we are able to partially amend.
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.
Karel Castro-Morales, Gregor Schürmann, Christoph Köstler, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Biogeosciences, 16, 3009–3032, https://doi.org/10.5194/bg-16-3009-2019, https://doi.org/10.5194/bg-16-3009-2019, 2019
Short summary
Short summary
To obtain nearly 30 years of global terrestrial carbon fluxes, we simultaneously incorporated in a land surface model three different time periods of two observational data sets: absorbed photosynthetic active radiation and atmospheric CO2 concentrations. One decade of data is enough to improve the modeled long-term trends and seasonal amplitudes of the assimilated variables, particularly in boreal regions. This model has the potential to provide short-term predictions of land carbon fluxes.
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.
Mingkai Jiang, Sönke Zaehle, Martin G. De Kauwe, Anthony P. Walker, Silvia Caldararu, David S. Ellsworth, and Belinda E. Medlyn
Geosci. Model Dev., 12, 2069–2089, https://doi.org/10.5194/gmd-12-2069-2019, https://doi.org/10.5194/gmd-12-2069-2019, 2019
Short summary
Short summary
Here we used a simple analytical framework developed by Comins and McMurtrie (1993) to investigate how different model assumptions affected plant responses to elevated CO2. This framework is useful in revealing both the consequences and the mechanisms through which different assumptions affect predictions. We therefore recommend the use of this framework to analyze the likely outcomes of new assumptions before introducing them to complex model structures.
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
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
Short summary
Short summary
The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Martina Franz, Rocio Alonso, Almut Arneth, Patrick Büker, Susana Elvira, Giacomo Gerosa, Lisa Emberson, Zhaozhong Feng, Didier Le Thiec, Riccardo Marzuoli, Elina Oksanen, Johan Uddling, Matthew Wilkinson, and Sönke Zaehle
Biogeosciences, 15, 6941–6957, https://doi.org/10.5194/bg-15-6941-2018, https://doi.org/10.5194/bg-15-6941-2018, 2018
Short summary
Short summary
Four published ozone damage functions previously used in terrestrial biosphere models were evaluated regarding their ability to simulate observed biomass dose–response relationships using the O-CN model. Neither damage function was able to reproduce the observed ozone-induced biomass reductions. Calibrating a plant-functional-type-specific relationship between accumulated ozone uptake and leaf-level photosynthesis did lead to a good agreement between observed and modelled ozone damage.
Yilong Wang, Philippe Ciais, Daniel Goll, Yuanyuan Huang, Yiqi Luo, Ying-Ping Wang, A. Anthony Bloom, Grégoire Broquet, Jens Hartmann, Shushi Peng, Josep Penuelas, Shilong Piao, Jordi Sardans, Benjamin D. Stocker, Rong Wang, Sönke Zaehle, and Sophie Zechmeister-Boltenstern
Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, https://doi.org/10.5194/gmd-11-3903-2018, 2018
Short summary
Short summary
We present a new modeling framework called Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines a data-constrained C-cycle analysis with data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. GOLUM-CNP provides a traceable tool, where a consistency between different datasets of global C, N, and P cycles has been achieved.
Johannes Meyerholt and Sönke Zaehle
Biogeosciences, 15, 5677–5698, https://doi.org/10.5194/bg-15-5677-2018, https://doi.org/10.5194/bg-15-5677-2018, 2018
Short summary
Short summary
Terrestrial biosphere models employ various representations of ecosystem nitrogen loss, some based on soil N availability, some based on net N mineralization. We show in local and global simulations that this variety leads to pronounced uncertainty in the predicted magnitude and sign of ecosystem N loss change under elevated CO2. Suprisingly, this uncertainty barely affects predicted carbon storage responses to elevated CO2, illustrating the need for new benchmarks especially in the boreal zone.
Karel Castro-Morales, Thomas Kleinen, Sonja Kaiser, Sönke Zaehle, Fanny Kittler, Min Jung Kwon, Christian Beer, and Mathias Göckede
Biogeosciences, 15, 2691–2722, https://doi.org/10.5194/bg-15-2691-2018, https://doi.org/10.5194/bg-15-2691-2018, 2018
Short summary
Short summary
We present year-round methane emissions from wetlands in Northeast Siberia that were simulated with a land surface model. Ground-based flux measurements from the same area were used for evaluation of the model results, finding a best agreement with the observations in the summertime emissions that take place in this region predominantly through plants. During winter, methane emissions through the snow contribute 4 % of the total annual methane budget, but these are still underestimated.
Christian Rödenbeck, Sönke Zaehle, Ralph Keeling, and Martin Heimann
Biogeosciences, 15, 2481–2498, https://doi.org/10.5194/bg-15-2481-2018, https://doi.org/10.5194/bg-15-2481-2018, 2018
Short summary
Short summary
In this paper we investigate how the CO2 exchange between the land vegetation and the atmosphere varies from year to year. We quantify the relation between variations in the CO2 exchange and variations in air temperature. For this quantification, we use long-term measurements of CO2 in the air at many locations, a simulation code for the transport of carbon dioxide through the atmosphere, and a data set of air temperature. The results help us to understand the mechanisms of CO2 exchange.
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.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
Short summary
Short summary
The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
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.
Wei Li, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi, Almut Arneth, Valerio Avitabile, Nuno Carvalhais, Anna B. Harper, Etsushi Kato, Charles Koven, Yi Y. Liu, Julia E.M.S. Nabel, Yude Pan, Julia Pongratz, Benjamin Poulter, Thomas A. M. Pugh, Maurizio Santoro, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Andy Wiltshire, Rasoul Yousefpour, and Sönke Zaehle
Biogeosciences, 14, 5053–5067, https://doi.org/10.5194/bg-14-5053-2017, https://doi.org/10.5194/bg-14-5053-2017, 2017
Short summary
Short summary
We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
Daniel S. Goll, Nicolas Vuichard, Fabienne Maignan, Albert Jornet-Puig, Jordi Sardans, Aurelie Violette, Shushi Peng, Yan Sun, Marko Kvakic, Matthieu Guimberteau, Bertrand Guenet, Soenke Zaehle, Josep Penuelas, Ivan Janssens, and Philippe Ciais
Geosci. Model Dev., 10, 3745–3770, https://doi.org/10.5194/gmd-10-3745-2017, https://doi.org/10.5194/gmd-10-3745-2017, 2017
Short summary
Short summary
We describe a representation of the terrestrial phosphorus cycle for the ORCHIDEE land surface model. The model is able to reproduce the observed shift from nitrogen to phosphorus limited net primary productivity along a soil formation chronosequence in Hawaii, as well as the contrasting responses of net primary productivity to nutrient addition. However, the simulated nutrient use efficiencies are lower, as observed primarily due to biases in the nutrient content and turnover of woody biomass.
Tea Thum, Sönke Zaehle, Philipp Köhler, Tuula Aalto, Mika Aurela, Luis Guanter, Pasi Kolari, Tuomas Laurila, Annalea Lohila, Federico Magnani, Christiaan Van Der Tol, and Tiina Markkanen
Biogeosciences, 14, 1969–1987, https://doi.org/10.5194/bg-14-1969-2017, https://doi.org/10.5194/bg-14-1969-2017, 2017
Short summary
Short summary
Modelling seasonal cycle at the coniferous forests poses a challenge. We implemented a model for sun-induced chlorophyll fluorescence (SIF) to a land surface model JSBACH. It was used to study the seasonality of the carbon cycle in the Fenno-Scandinavian region. Comparison was made to direct CO2 flux measurements and satellite observations of SIF. SIF proved to be a better proxy for photosynthesis than the fraction of absorbed photosynthetically active radiation.
Martina Franz, David Simpson, Almut Arneth, and Sönke Zaehle
Biogeosciences, 14, 45–71, https://doi.org/10.5194/bg-14-45-2017, https://doi.org/10.5194/bg-14-45-2017, 2017
Short summary
Short summary
Ozone is a toxic air pollutant that can damage plant leaves and impact their carbon uptake from the atmosphere. We extend a terrestrial biosphere model to account for ozone damage of plants and investigate the impact on the terrestrial carbon cycle. Our approach accounts for ozone transport from the free troposphere to leaf level. We find that this substantially affects simulated ozone uptake into the plants. Simulations indicate that ozone damages plants less than expected from previous studies
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.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
Short summary
Short summary
The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Fang Zhao, Ning Zeng, Ghassem Asrar, Pierre Friedlingstein, Akihiko Ito, Atul Jain, Eugenia Kalnay, Etsushi Kato, Charles D. Koven, Ben Poulter, Rashid Rafique, Stephen Sitch, Shijie Shu, Beni Stocker, Nicolas Viovy, Andy Wiltshire, and Sonke Zaehle
Biogeosciences, 13, 5121–5137, https://doi.org/10.5194/bg-13-5121-2016, https://doi.org/10.5194/bg-13-5121-2016, 2016
Short summary
Short summary
The increasing seasonality of atmospheric CO2 is strongly linked with enhanced land vegetation activities in the last 5 decades, for which the importance of increasing CO2, climate and land use/cover change was evaluated in single model studies (Zeng et al., 2014; Forkel et al., 2016). Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.
Gregor J. Schürmann, Thomas Kaminski, Christoph Köstler, Nuno Carvalhais, Michael Voßbeck, Jens Kattge, Ralf Giering, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, https://doi.org/10.5194/gmd-9-2999-2016, 2016
Short summary
Short summary
We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
Short summary
Short summary
How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
Johannes Meyerholt, Sönke Zaehle, and Matthew J. Smith
Biogeosciences, 13, 1491–1518, https://doi.org/10.5194/bg-13-1491-2016, https://doi.org/10.5194/bg-13-1491-2016, 2016
Short summary
Short summary
We investigated how today's state-of-the-art terrestrial biosphere models represent biological nitrogen fixation and what the consequences of varying representation are for model predictions under ambient conditions and under scenarios of elevated atmospheric carbon dioxide concentrations. We found that varying global nitrogen fixation rates are simulated under ambient conditions and that the responses of the simulated carbon and nitrogen cycles are significantly affected under perturbation.
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.
G. Murray-Tortarolo, P. Friedlingstein, S. Sitch, V. J. Jaramillo, F. Murguía-Flores, A. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. D. Stocker, A. Wiltshire, S. Zaehle, and N. Zeng
Biogeosciences, 13, 223–238, https://doi.org/10.5194/bg-13-223-2016, https://doi.org/10.5194/bg-13-223-2016, 2016
Short summary
Short summary
We modelled the carbon (C) cycle in Mexico for three different time periods: past (20th century), present (2000-2005) and future (2006-2100). We used different available products to estimate C stocks and fluxes in the country. Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century (unless the most extreme climate-change scenarios are reached).
D. Fowler, C. E. Steadman, D. Stevenson, M. Coyle, R. M. Rees, U. M. Skiba, M. A. Sutton, J. N. Cape, A. J. Dore, M. Vieno, D. Simpson, S. Zaehle, B. D. Stocker, M. Rinaldi, M. C. Facchini, C. R. Flechard, E. Nemitz, M. Twigg, J. W. Erisman, K. Butterbach-Bahl, and J. N. Galloway
Atmos. Chem. Phys., 15, 13849–13893, https://doi.org/10.5194/acp-15-13849-2015, https://doi.org/10.5194/acp-15-13849-2015, 2015
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
Short summary
Short summary
Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
S. Olin, M. Lindeskog, T. A. M. Pugh, G. Schurgers, D. Wårlind, M. Mishurov, S. Zaehle, B. D. Stocker, B. Smith, and A. Arneth
Earth Syst. Dynam., 6, 745–768, https://doi.org/10.5194/esd-6-745-2015, https://doi.org/10.5194/esd-6-745-2015, 2015
Short summary
Short summary
Croplands are vital ecosystems for human well-being. Properly managed they can supply food, store carbon and even sequester carbon from the atmosphere. Conversely, if poorly managed, croplands can be a source of nitrogen to inland and coastal waters, causing algal blooms, and a source of carbon dioxide to the atmosphere, accentuating climate change. Here we studied cropland management types for their potential to store carbon and minimize nitrogen losses while maintaining crop yields.
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
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. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
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
B. Smith, D. Wårlind, A. Arneth, T. Hickler, P. Leadley, J. Siltberg, and S. Zaehle
Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, https://doi.org/10.5194/bg-11-2027-2014, 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
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 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
Related subject area
Biogeosciences
BioRT-Flux-PIHM v1.0: a biogeochemical reactive transport model at the watershed scale
Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model
Explicit silicate cycling in the Kiel Marine Biogeochemistry Model version 3 (KMBM3) embedded in the UVic ESCM version 2.9
Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations
OMEN-SED(-RCM) (v1.1): a pseudo-reactive continuum representation of organic matter degradation dynamics for OMEN-SED
Testing stomatal models at the stand level in deciduous angiosperm and evergreen gymnosperm forests using CliMA Land (v0.1)
Comparing an exponential respiration model to alternative models for soil respiration components in a Canadian wildfire chronosequence (FireResp v1.0)
Accounting for forest management in the estimation of forest carbon balance using the dynamic vegetation model LPJ-GUESS (v4.0, r9710): implementation and evaluation of simulations for Europe
FABM-NflexPD 1.0: assessing an instantaneous acclimation approach for modeling phytoplankton growth
A model for marine sedimentary carbonate diagenesis and paleoclimate proxy signal tracking: IMP v1.0
Using the International Tree-Ring Data Bank (ITRDB) records as century-long benchmarks for global land-surface models
Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS
A model-independent data assimilation (MIDA) module and its applications in ecology
Optical model for the Baltic Sea with an explicit CDOM state variable: a case study with Model ERGOM (version 1.2)
WAP-1D-VAR v1.0: development and evaluation of a one-dimensional variational data assimilation model for the marine ecosystem along the West Antarctic Peninsula
SCOPE 2.0: a model to simulate vegetated land surface fluxes and satellite signals
A dynamic local scale vegetation model for lycophytes (LYCOm)
SolveSAPHE-r2 (v2.0.1): revisiting and extending the Solver Suite for Alkalinity-PH Equations for usage with CO2, HCO3− or CO32− input data
Modeling gas exchange and biomass production in West African Sahelian and Sudanian ecological zones
Partitioning soil organic carbon into its centennially stable and active fractions with machine-learning models based on Rock-Eval® thermal analysis (PARTYSOCv2.0 and PARTYSOCv2.0EU)
Addressing biases in Arctic–boreal carbon cycling in the Community Land Model Version 5
Locating trees to mitigate outdoor radiant load of humans in urban areas using a metaheuristic hill climbing algorithm – Introducing TreePlanter v1.0
Afforestation impact on soil temperature in regional climate model simulations over Europe
Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance
Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model
CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 2: Global benchmarking
The importance of turbulent ocean-sea ice nutrient exchanges for simulation of ice algal biomass and production with CICE6.1 and Icepack 1.2
How to reconstruct aerosol-induced diffuse radiation scenario for simulating GPP in land surface models? An evaluation of reconstruction methods with ORCHIDEE_DFv1.0_DFforc
SPEAD 1.0 – Simulating Plankton Evolution with Adaptive Dynamics in a two-trait continuous fitness landscape applied to the Sargasso Sea
Rapid development of fast and flexible environmental models: the Mobius framework v1.0
Potential yield simulated by global gridded crop models: using a process-based emulator to explain their differences
Integrated modeling of canopy photosynthesis, fluorescence, and the transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum (STEMMUS–SCOPE v1.0.0)
Sensitivity of asymmetric Oxygen Minimum Zones to remineralization rate and mixing intensity in the tropical Pacific using a basin-scale model (OGCM-DMEC V1.2)
CoupModel (v6.0): an ecosystem model for coupled phosphorus, nitrogen, and carbon dynamics – evaluated against empirical data from a climatic and fertility gradient in Sweden
Improving the representation of cropland sites in the Community Land Model (CLM) version 5.0
Numerical model to simulate long-term soil organic carbon and ground ice budget with permafrost and ice sheets (SOC-ICE-v1.0)
Calibrating soybean parameters in JULES 5.0 from the US-Ne2/3 FLUXNET sites and the SoyFACE-O3 experiment
Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation–fire model SSiB4/TRIFFID-Fire v1.0
Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0
Improving Yasso15 soil carbon model estimates with ensemble adjustment Kalman filter state data assimilation
Oceanic and atmospheric methane cycling in the cGENIE Earth system model – release v0.9.14
Modeling the impacts of diffuse light fraction on photosynthesis in ORCHIDEE (v5453) land surface model
Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites
A multi-isotope model for simulating soil organic carbon cycling in eroding landscapes (WATEM_C v1.0)
One-dimensional models of radiation transfer in heterogeneous canopies: a review, re-evaluation, and improved model
Definitions and methods to estimate regional land carbon fluxes for the second phase of the REgional Carbon Cycle Assessment and Processes Project (RECCAP-2)
An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen version 2 (FANv2)
Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)
Short-term forecasting of regional biospheric CO2 fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)
FLiES-SIF version 1.0: three-dimensional radiative transfer model for estimating solar induced fluorescence
Wei Zhi, Yuning Shi, Hang Wen, Leila Saberi, Gene-Hua Crystal Ng, Kayalvizhi Sadayappan, Devon Kerins, Bryn Stewart, and Li Li
Geosci. Model Dev., 15, 315–333, https://doi.org/10.5194/gmd-15-315-2022, https://doi.org/10.5194/gmd-15-315-2022, 2022
Short summary
Short summary
Watersheds are the fundamental Earth surface functioning unit that connects the land to aquatic systems. Here we present the recently developed BioRT-Flux-PIHM v1.0, a watershed-scale biogeochemical reactive transport model, to improve our ability to understand and predict solute export and water quality. The model has been verified against the benchmark code CrunchTope and has recently been applied to understand reactive transport processes in multiple watersheds of different conditions.
Huilin Huang, Yongkang Xue, Ye Liu, Fang Li, and Gregory S. Okin
Geosci. Model Dev., 14, 7639–7657, https://doi.org/10.5194/gmd-14-7639-2021, https://doi.org/10.5194/gmd-14-7639-2021, 2021
Short summary
Short summary
This study applies a fire-coupled dynamic vegetation model to quantify fire impact at monthly to annual scales. We find fire reduces grass cover by 4–8 % annually for widespread areas in south African savanna and reduces tree cover by 1 % at the periphery of tropical Congolese rainforest. The grass cover reduction peaks at the beginning of the rainy season, which quickly diminishes before the next fire season. In contrast, the reduction of tree cover is irreversible within one growing season.
Karin Kvale, David P. Keller, Wolfgang Koeve, Katrin J. Meissner, Christopher J. Somes, Wanxuan Yao, and Andreas Oschlies
Geosci. Model Dev., 14, 7255–7285, https://doi.org/10.5194/gmd-14-7255-2021, https://doi.org/10.5194/gmd-14-7255-2021, 2021
Short summary
Short summary
We present a new model of biological marine silicate cycling for the University of Victoria Earth System Climate Model (UVic ESCM). This new model adds diatoms, which are a key aspect of the biological carbon pump, to an existing ecosystem model. Our modifications change how the model responds to warming, with net primary production declining more strongly than in previous versions. Diatoms in particular are simulated to decline with climate warming due to their high nutrient requirements.
Shannon de Roos, Gabriëlle J. M. De Lannoy, and Dirk Raes
Geosci. Model Dev., 14, 7309–7328, https://doi.org/10.5194/gmd-14-7309-2021, https://doi.org/10.5194/gmd-14-7309-2021, 2021
Short summary
Short summary
A spatially distributed version of the field-scale crop model AquaCrop v6.1 was developed for applications at various spatial scales. Multi-year 1 km simulations over central Europe were evaluated against biomass and surface soil moisture products derived from optical and microwave satellite missions, as well as in situ observations of soil moisture. The regional version of the AquaCrop model provides a suitable setup for subsequent satellite-based data assimilation.
Philip Pika, Dominik Hülse, and Sandra Arndt
Geosci. Model Dev., 14, 7155–7174, https://doi.org/10.5194/gmd-14-7155-2021, https://doi.org/10.5194/gmd-14-7155-2021, 2021
Short summary
Short summary
OMEN-SED is a model for early diagenesis in marine sediments simulating organic matter (OM) degradation and nutrient dynamics. We replaced the original description with a more realistic one accounting for the widely observed decrease in OM reactivity. The new model reproduces pore water profiles and sediment–water interface fluxes across different environments. This functionality extends the model’s applicability to a broad range of environments and timescales while requiring fewer parameters.
Yujie Wang, Philipp Köhler, Liyin He, Russell Doughty, Renato K. Braghiere, Jeffrey D. Wood, and Christian Frankenberg
Geosci. Model Dev., 14, 6741–6763, https://doi.org/10.5194/gmd-14-6741-2021, https://doi.org/10.5194/gmd-14-6741-2021, 2021
Short summary
Short summary
We present the first step in testing a new land model as part of a new Earth system model. Our model links plant hydraulics, stomatal optimization theory, and a comprehensive canopy radiation scheme. We compared model-predicted carbon and water fluxes to flux tower observations and model-predicted sun-induced chlorophyll fluorescence to satellite retrievals. Our model quantitatively predicted the carbon and water fluxes as well as the canopy fluorescence yield.
John Zobitz, Heidi Aaltonen, Xuan Zhou, Frank Berninger, Jukka Pumpanen, and Kajar Köster
Geosci. Model Dev., 14, 6605–6622, https://doi.org/10.5194/gmd-14-6605-2021, https://doi.org/10.5194/gmd-14-6605-2021, 2021
Short summary
Short summary
Forest fires heavily affect carbon stocks and fluxes of carbon in high-latitude forests. Long-term trends in soil respiration following forest fires are associated with recovery of aboveground biomass. We evaluated models for soil autotrophic and heterotrophic respiration with data from a chronosequence of stand-replacing forest fires in northern Canada. The best model that reproduced expected patterns in soil respiration components takes into account soil microbe carbon as a model variable.
Mats Lindeskog, Benjamin Smith, Fredrik Lagergren, Ekaterina Sycheva, Andrej Ficko, Hans Pretzsch, and Anja Rammig
Geosci. Model Dev., 14, 6071–6112, https://doi.org/10.5194/gmd-14-6071-2021, https://doi.org/10.5194/gmd-14-6071-2021, 2021
Short summary
Short summary
Forests play an important role in the global carbon cycle and for carbon storage. In Europe, forests are intensively managed. To understand how management influences carbon storage in European forests, we implement detailed forest management into the dynamic vegetation model LPJ-GUESS. We test the model by comparing model output to typical forestry measures, such as growing stock and harvest data, for different countries in Europe.
Onur Kerimoglu, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 14, 6025–6047, https://doi.org/10.5194/gmd-14-6025-2021, https://doi.org/10.5194/gmd-14-6025-2021, 2021
Short summary
Short summary
In large-scale models, variations in cellular composition of phytoplankton are often insufficiently represented. Detailed modeling approaches exist, but they require additional state variables that increase the computational costs. In this study, we test an instantaneous acclimation model in a spatially explicit setup and show that its behavior is mostly similar to that of a variant with an additional state variable but different from that of a fixed composition variant.
Yoshiki Kanzaki, Dominik Hülse, Sandra Kirtland Turner, and Andy Ridgwell
Geosci. Model Dev., 14, 5999–6023, https://doi.org/10.5194/gmd-14-5999-2021, https://doi.org/10.5194/gmd-14-5999-2021, 2021
Short summary
Short summary
Sedimentary carbonate plays a central role in regulating Earth’s carbon cycle and climate, and also serves as an archive of paleoenvironments, hosting various trace elements/isotopes. To help obtain
trueenvironmental changes from carbonate records over diagenetic distortion, IMP has been newly developed and has the capability to simulate the diagenesis of multiple carbonate particles and implement different styles of particle mixing by benthos using an adapted transition matrix method.
Jina Jeong, Jonathan Barichivich, Philippe Peylin, Vanessa Haverd, Matthew Joseph McGrath, Nicolas Vuichard, Michael Neil Evans, Flurin Babst, and Sebastiaan Luyssaert
Geosci. Model Dev., 14, 5891–5913, https://doi.org/10.5194/gmd-14-5891-2021, https://doi.org/10.5194/gmd-14-5891-2021, 2021
Short summary
Short summary
We have proposed and evaluated the use of four benchmarks that leverage tree-ring width observations to provide more nuanced verification targets for land-surface models (LSMs), which currently lack a long-term benchmark for forest ecosystem functioning. Using relatively unbiased European biomass network datasets, we identify the extent to which presumed biases in the much larger International Tree-Ring Data Bank might degrade the validation of LSMs.
Jianyong Ma, Stefan Olin, Peter Anthoni, Sam S. Rabin, Anita D. Bayer, Sylvia S. Nyawira, and Almut Arneth
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-260, https://doi.org/10.5194/gmd-2021-260, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
The implementation of biological N fixation process to LPJ-GUESS in this study provides an opportunity to quantify N fixation rates between legumes, as well as to better estimate grain legumes' production on global scale. It also helps to predict and detect the potential contribution of N-fixing plants as 'green manure' to reducing or removing the use of N fertilizer in global agricultural systems, considering different climate conditions, management practices, and land-use change scenarios.
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021, https://doi.org/10.5194/gmd-14-5217-2021, 2021
Short summary
Short summary
In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
Thomas Neumann, Sampsa Koponen, Jenni Attila, Carsten Brockmann, Kari Kallio, Mikko Kervinen, Constant Mazeran, Dagmar Müller, Petra Philipson, Susanne Thulin, Sakari Väkevä, and Pasi Ylöstalo
Geosci. Model Dev., 14, 5049–5062, https://doi.org/10.5194/gmd-14-5049-2021, https://doi.org/10.5194/gmd-14-5049-2021, 2021
Short summary
Short summary
The Baltic Sea is heavily impacted by surrounding land. Therefore, the concentration of colored dissolved organic matter (CDOM) of terrestrial origin is relatively high and impacts the light penetration depth. Estimating a correct light climate is essential for ecosystem models. In this study, a method is developed to derive riverine CDOM from Earth observation methods. The data are used as boundary conditions for an ecosystem model, and the advantage over former approaches is shown.
Hyewon Heather Kim, Ya-Wei Luo, Hugh W. Ducklow, Oscar M. Schofield, Deborah K. Steinberg, and Scott C. Doney
Geosci. Model Dev., 14, 4939–4975, https://doi.org/10.5194/gmd-14-4939-2021, https://doi.org/10.5194/gmd-14-4939-2021, 2021
Short summary
Short summary
The West Antarctic Peninsula (WAP) is a rapidly warming region, revealed by multi-decadal observations. Despite the region being data rich, there is a lack of focus on ecosystem model development. Here, we introduce a data assimilation ecosystem model for the WAP region. Experiments by assimilating data from an example growth season capture key WAP features. This study enables us to glue the snapshots from available data sets together to explain the observations in the WAP.
Peiqi Yang, Egor Prikaziuk, Wout Verhoef, and Christiaan van der Tol
Geosci. Model Dev., 14, 4697–4712, https://doi.org/10.5194/gmd-14-4697-2021, https://doi.org/10.5194/gmd-14-4697-2021, 2021
Short summary
Short summary
Since the first publication 12 years ago, the SCOPE model has been applied in remote sensing studies of solar-induced chlorophyll fluorescence (SIF), energy balance fluxes, gross primary productivity (GPP), and directional thermal signals. Here, we present a thoroughly revised version, SCOPE 2.0, which features a number of new elements.
Suman Halder, Susanne K. M. Arens, Kai Jensen, Tais Wittchen Dahl, and Philipp Porada
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-202, https://doi.org/10.5194/gmd-2021-202, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
A dynamic vegetation model, designed to estimate potential impacts of early vascular vegetation namely, lycophytes, on global biogeochemical cycles. Lycophyte Model estimates the productivity and physiological properties of lycophytes under a broad climatic range which is then utilized to adjudge their weathering potential. LYCOm lays the foundation for global estimation of the variability of atmospheric carbon dioxide levels and climate on geological time scales due to the advent of lycophytes.
Guy Munhoven
Geosci. Model Dev., 14, 4225–4240, https://doi.org/10.5194/gmd-14-4225-2021, https://doi.org/10.5194/gmd-14-4225-2021, 2021
Short summary
Short summary
SolveSAPHE (Munhoven, 2013) was the first package to calculate pH reliably from any physically sensible pair of total alkalinity (AlkT) and dissolved inorganic carbon (CT) data and to do so in an autonomous and efficient way. Here, we extend it to use CO2, HCO3 or CO3 instead of CT. For each one of these pairs, the new SolveSAPHE calculates all of the possible pH values (0, 1, or 2), again without any prior knowledge of the solutions.
Jaber Rahimi, Expedit Evariste Ago, Augustine Ayantunde, Sina Berger, Jan Bogaert, Klaus Butterbach-Bahl, Bernard Cappelaere, Jean-Martial Cohard, Jérôme Demarty, Abdoul Aziz Diouf, Ulrike Falk, Edwin Haas, Pierre Hiernaux, David Kraus, Olivier Roupsard, Clemens Scheer, Amit Kumar Srivastava, Torbern Tagesson, and Rüdiger Grote
Geosci. Model Dev., 14, 3789–3812, https://doi.org/10.5194/gmd-14-3789-2021, https://doi.org/10.5194/gmd-14-3789-2021, 2021
Short summary
Short summary
West African Sahelian and Sudanian ecosystems are important regions for global carbon exchange, and they provide valuable food and fodder resources. Therefore, we simulated net ecosystem exchange and aboveground biomass of typical ecosystems in this region with an improved process-based biogeochemical model, LandscapeDNDC. Carbon stocks and exchange rates were particularly correlated with the abundance of trees. Grass and crop yields increased under humid climatic conditions.
Lauric Cécillon, François Baudin, Claire Chenu, Bent T. Christensen, Uwe Franko, Sabine Houot, Eva Kanari, Thomas Kätterer, Ines Merbach, Folkert van Oort, Christopher Poeplau, Juan Carlos Quezada, Florence Savignac, Laure N. Soucémarianadin, and Pierre Barré
Geosci. Model Dev., 14, 3879–3898, https://doi.org/10.5194/gmd-14-3879-2021, https://doi.org/10.5194/gmd-14-3879-2021, 2021
Short summary
Short summary
Partitioning soil organic carbon (SOC) into fractions that are stable or active on a century scale is key for more accurate models of the carbon cycle. Here, we describe the second version of a machine-learning model, named PARTYsoc, which reliably predicts the proportion of the centennially stable SOC fraction at its northwestern European validation sites with Cambisols and Luvisols, the two dominant soil groups in this region, fostering modelling works of SOC dynamics.
Leah Birch, Christopher R. Schwalm, Sue Natali, Danica Lombardozzi, Gretchen Keppel-Aleks, Jennifer Watts, Xin Lin, Donatella Zona, Walter Oechel, Torsten Sachs, Thomas Andrew Black, and Brendan M. Rogers
Geosci. Model Dev., 14, 3361–3382, https://doi.org/10.5194/gmd-14-3361-2021, https://doi.org/10.5194/gmd-14-3361-2021, 2021
Short summary
Short summary
The high-latitude landscape or Arctic–boreal zone has been warming rapidly, impacting the carbon balance both regionally and globally. Given the possible global effects of climate change, it is important to have accurate climate model simulations. We assess the simulation of the Arctic–boreal carbon cycle in the Community Land Model (CLM 5.0). We find biases in both the timing and magnitude photosynthesis. We then use observational data to improve the simulation of the carbon cycle.
Nils Wallenberg, Fredrik Lindberg, and David Rayner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-81, https://doi.org/10.5194/gmd-2021-81, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
Exposure to solar radiation on clear and warm days can lead to heat stress and thermal discomfort. This can be alleviated by planting trees providing shade in particularly warm areas. Here, we use a model to locate trees and optimize their blocking of solar radiation. Our results show that locations can differ depending e.g. tree size (juvenile or mature) and number of trees that are positioned simultaneously. The model is available as a tool, for accessibility by researchers and others.
Giannis Sofiadis, Eleni Katragkou, Edouard L. Davin, Diana Rechid, Nathalie de Noblet-Ducoudre, Marcus Breil, Rita M. Cardoso, Peter Hoffmann, Lisa Jach, Ronny Meier, Priscilla Mooney, Pedro M. M. Soares, Susanna Strada, Merja H. Tolle, and Kirsten Warrach Sagi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-69, https://doi.org/10.5194/gmd-2021-69, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
Afforestation is currently promoted as a greenhouse gases mitigation strategy. In our study, we examine the differences in soil temperature and moisture between grounds covered either by forests or grass. The main conclusion emerged is that forest-covered grounds are cooler but drier than open lands in summer. Therefore, afforestation disrupts the seasonal cycle of soil temperature, which in turn could trigger changes in crucial chemical processes such as soil carbon sequestration.
Alexey N. Shiklomanov, Michael C. Dietze, Istem Fer, Toni Viskari, and Shawn P. Serbin
Geosci. Model Dev., 14, 2603–2633, https://doi.org/10.5194/gmd-14-2603-2021, https://doi.org/10.5194/gmd-14-2603-2021, 2021
Short summary
Short summary
Airborne and satellite images are a great resource for calibrating and evaluating computer models of ecosystems. Typically, researchers derive ecosystem properties from these images and then compare models against these derived properties. Here, we present an alternative approach where we modify a model to predict what the satellite would see more directly. We then show how this approach can be used to calibrate model parameters using airborne data from forest sites in the northeastern US.
Leonardo Calle and Benjamin Poulter
Geosci. Model Dev., 14, 2575–2601, https://doi.org/10.5194/gmd-14-2575-2021, https://doi.org/10.5194/gmd-14-2575-2021, 2021
Short summary
Short summary
We developed a model to simulate and track the age of ecosystems on Earth. We found that the effect of ecosystem age on net primary production and ecosystem respiration is as important as climate in large areas of every vegetated continent. The LPJ-wsl v2.0 age-class model simulates dynamic age-class distributions on Earth and represents another step forward towards understanding the role of demography in global ecosystems.
Christian Seiler, Joe R. Melton, Vivek K. Arora, and Libo Wang
Geosci. Model Dev., 14, 2371–2417, https://doi.org/10.5194/gmd-14-2371-2021, https://doi.org/10.5194/gmd-14-2371-2021, 2021
Short summary
Short summary
This study evaluates how well the CLASSIC land surface model reproduces the energy, water, and carbon cycle when compared against a wide range of global observations. Special attention is paid to how uncertainties in the data used to drive and evaluate the model affect model skill. Our results show the importance of incorporating uncertainties when evaluating land surface models and that failing to do so may potentially misguide future model development.
Pedro Duarte, Philipp Assmy, Karley Campbell, and Arild Sundfjord
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-58, https://doi.org/10.5194/gmd-2021-58, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
Sea ice modelling is an important part of Earth System Models (ESMs). The results of ESMs are used by the Intergovernmental Panel on Climate Change in their reports. In this study we present an improvement to calculate the exchange of nutrients between the ocean and the sea ice. This nutrient exchange is an essential process to keep the ice associated ecosystem functioning. We found out that previous calculation methods may underestimate the primary production of the ice-associated ecosystem.
Yuan Zhang, Olivier Boucher, Philippe Ciais, Laurent Li, and Nicolas Bellouin
Geosci. Model Dev., 14, 2029–2039, https://doi.org/10.5194/gmd-14-2029-2021, https://doi.org/10.5194/gmd-14-2029-2021, 2021
Short summary
Short summary
We investigated different methods to reconstruct spatiotemporal distribution of the fraction of diffuse radiation (Fdf) to qualify the aerosol impacts on GPP using the ORCHIDEE_DF land surface model. We find that climatological-averaging methods which dampen the variability of Fdf can cause significant bias in the modeled diffuse radiation impacts on GPP. Better methods to reconstruct Fdf are recommended.
Guillaume Le Gland, Sergio M. Vallina, S. Lan Smith, and Pedro Cermeño
Geosci. Model Dev., 14, 1949–1985, https://doi.org/10.5194/gmd-14-1949-2021, https://doi.org/10.5194/gmd-14-1949-2021, 2021
Short summary
Short summary
We present an ecological model called SPEAD wherein various phytoplankton compete for nutrients. Phytoplankton in SPEAD are characterized by two continuously distributed traits: optimal temperature and nutrient half-saturation. Trait diversity is sustained by allowing the traits to mutate at each generation. We show that SPEAD agrees well with a more classical discrete model for only a fraction of the cost. We also identify realistic values for the mutation rates to be used in future models.
Magnus Dahler Norling, Leah Amber Jackson-Blake, José-Luis Guerrero Calidonio, and James Edward Sample
Geosci. Model Dev., 14, 1885–1897, https://doi.org/10.5194/gmd-14-1885-2021, https://doi.org/10.5194/gmd-14-1885-2021, 2021
Short summary
Short summary
In order to allow researchers to quickly prototype and build models of natural systems, we have created the Mobius framework. Such models can, for instance, be used to ask questions about what the impacts of land-use changes are to water quality in a river or lake, or the response of biogeochemical systems to climate change. The Mobius framework makes it quick to build models that run fast, which enables the user to explore many different scenarios and model formulations.
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.
Yunfei Wang, Yijian Zeng, Lianyu Yu, Peiqi Yang, Christiaan Van der Tol, Qiang Yu, Xiaoliang Lü, Huanjie Cai, and Zhongbo Su
Geosci. Model Dev., 14, 1379–1407, https://doi.org/10.5194/gmd-14-1379-2021, https://doi.org/10.5194/gmd-14-1379-2021, 2021
Short summary
Short summary
This study integrates photosynthesis and transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum system, via a simplified 1D root growth model. The results indicated that the simulation of land surface fluxes was significantly improved by considering the root water uptake, especially when vegetation was experiencing severe water stress. This finding highlights the importance of enhanced soil heat and moisture transfer in simulating ecosystem functioning.
Kai Wang, Xiujun Wang, Raghu Murtugudde, Dongxiao Zhang, and Rong-Hua Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-431, https://doi.org/10.5194/gmd-2020-431, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
We use observational data of dissolved oxygen (DO) and organic nitrogen to calibrate a basin-scale model (OGCM-DEMC V1.2), and then evaluate model capacity for simulating mid-depth DO in the tropical Pacific. Sensitivity studies show that enhanced vertical mixing combined with reduced biological consumption performs well in reproducing the asymmetric OMZs. We find that DO is more sensitive to biological processes in the upper OMZs but to physical processes in the lower OMZs.
Hongxing He, Per-Erik Jansson, and Annemieke I. Gärdenäs
Geosci. Model Dev., 14, 735–761, https://doi.org/10.5194/gmd-14-735-2021, https://doi.org/10.5194/gmd-14-735-2021, 2021
Short summary
Short summary
This study presents the integration of the phosphorus (P) cycle into CoupModel (v6.0, Coup-CNP). The extended Coup-CNP, which explicitly considers the symbiosis between soil microbes and plant roots, enables simulations of coupled C, N, and P dynamics for terrestrial ecosystems. Simulations from the new Coup-CNP model provide strong evidence that P fluxes need to be further considered in studies of how ecosystems and C turnover react to climate change.
Theresa Boas, Heye Bogena, Thomas Grünwald, Bernard Heinesch, Dongryeol Ryu, Marius Schmidt, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, https://doi.org/10.5194/gmd-14-573-2021, 2021
Short summary
Short summary
In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
Kazuyuki Saito, Hirokazu Machiya, Go Iwahana, Tokuta Yokohata, and Hiroshi Ohno
Geosci. Model Dev., 14, 521–542, https://doi.org/10.5194/gmd-14-521-2021, https://doi.org/10.5194/gmd-14-521-2021, 2021
Short summary
Short summary
Soil organic carbon (SOC) and ground ice (ICE) are essential but under-documented information to assess the circum-Arctic permafrost degradation impacts. A simple numerical model of essential SOC and ICE dynamics, developed and integrated north of 50° N for 125,000 years since the last interglacial, reconstructed the history and 1° distribution of SOC and ICE consistent with current knowledge, together with successful demonstration of climatic and topographical controls on SOC evolution.
Felix Leung, Karina Williams, Stephen Sitch, Amos P. K. Tai, Andy Wiltshire, Jemma Gornall, Elizabeth A. Ainsworth, Timothy Arkebauer, and David Scoby
Geosci. Model Dev., 13, 6201–6213, https://doi.org/10.5194/gmd-13-6201-2020, https://doi.org/10.5194/gmd-13-6201-2020, 2020
Short summary
Short summary
Ground-level ozone (O3) is detrimental to plant productivity and crop yield. Currently, the Joint UK Land Environment Simulator (JULES) includes a representation of crops (JULES-crop). The parameters for O3 damage in soybean in JULES-crop were calibrated against photosynthesis measurements from the Soybean Free Air Concentration Enrichment (SoyFACE). The result shows good performance for yield, and it helps contribute to understanding of the impacts of climate and air pollution on food security.
Huilin Huang, Yongkang Xue, Fang Li, and Ye Liu
Geosci. Model Dev., 13, 6029–6050, https://doi.org/10.5194/gmd-13-6029-2020, https://doi.org/10.5194/gmd-13-6029-2020, 2020
Short summary
Short summary
We developed a fire-coupled dynamic vegetation model that captures the spatial distribution, temporal variability, and especially the seasonal variability of fire regimes. The fire model is applied to assess the long-term fire impact on ecosystems and surface energy. We find that fire is an important determinant of the structure and function of the tropical savanna. By changing the vegetation composition and ecosystem characteristics, fire significantly alters surface energy balance.
Virginie Moreaux, Simon Martel, Alexandre Bosc, Delphine Picart, David Achat, Christophe Moisy, Raphael Aussenac, Christophe Chipeaux, Jean-Marc Bonnefond, Soisick Figuères, Pierre Trichet, Rémi Vezy, Vincent Badeau, Bernard Longdoz, André Granier, Olivier Roupsard, Manuel Nicolas, Kim Pilegaard, Giorgio Matteucci, Claudy Jolivet, Andrew T. Black, Olivier Picard, and Denis Loustau
Geosci. Model Dev., 13, 5973–6009, https://doi.org/10.5194/gmd-13-5973-2020, https://doi.org/10.5194/gmd-13-5973-2020, 2020
Short summary
Short summary
The model GO+ describes the functioning of managed forests based upon biophysical and biogeochemical processes. It accounts for the impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes versatile descriptions of management operations. Its sensitivity and uncertainty are detailed and predictions are compared with observations about mass and energy exchanges, hydrological data, and tree growth variables from different sites.
Toni Viskari, Maisa Laine, Liisa Kulmala, Jarmo Mäkelä, Istem Fer, and Jari Liski
Geosci. Model Dev., 13, 5959–5971, https://doi.org/10.5194/gmd-13-5959-2020, https://doi.org/10.5194/gmd-13-5959-2020, 2020
Short summary
Short summary
The research here established whether a Bayesian statistical method called state data assimilation could be used to improve soil organic carbon (SOC) forecasts. Our test case was a fallow experiment where SOC content was measured over several decades from a plot where all vegetation was removed. Our results showed that state data assimilation improved projections and allowed for the detailed model state be updated with coarse total carbon measurements.
Christopher T. Reinhard, Stephanie L. Olson, Sandra Kirtland Turner, Cecily Pälike, Yoshiki Kanzaki, and Andy Ridgwell
Geosci. Model Dev., 13, 5687–5706, https://doi.org/10.5194/gmd-13-5687-2020, https://doi.org/10.5194/gmd-13-5687-2020, 2020
Short summary
Short summary
We provide documentation and testing of new developments for the oceanic and atmospheric methane cycles in the cGENIE Earth system model. The model is designed to explore Earth's methane cycle across a wide range of timescales and scenarios, in particular assessing the mean climate state and climate perturbations in Earth's deep past. We further document the impact of atmospheric oxygen levels and ocean chemistry on fluxes of methane to the atmosphere from the ocean biosphere.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
Short summary
Short summary
We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Petra Lasch-Born, Felicitas Suckow, Christopher P. O. Reyer, Martin Gutsch, Chris Kollas, Franz-Werner Badeck, Harald K. M. Bugmann, Rüdiger Grote, Cornelia Fürstenau, Marcus Lindner, and Jörg Schaber
Geosci. Model Dev., 13, 5311–5343, https://doi.org/10.5194/gmd-13-5311-2020, https://doi.org/10.5194/gmd-13-5311-2020, 2020
Short summary
Short summary
The process-based model 4C has been developed to study climate impacts on forests and is now freely available as an open-source tool. This paper provides a comprehensive description of the 4C version (v2.2) for scientific users of the model and presents an evaluation of 4C. The evaluation focused on forest growth, carbon water, and heat fluxes. We conclude that 4C is widely applicable, reliable, and ready to be released to the scientific community to use and further develop the model.
Zhengang Wang, Jianxiu Qiu, and Kristof Van Oost
Geosci. Model Dev., 13, 4977–4992, https://doi.org/10.5194/gmd-13-4977-2020, https://doi.org/10.5194/gmd-13-4977-2020, 2020
Short summary
Short summary
This study developed a spatially distributed carbon cycling model applicable in an eroding landscape. It includes all three carbon isotopes so that it is able to represent the carbon isotopic compositions. The model is able to represent the observations that eroding area is enriched in 13C and depleted of 14C compared to depositional area. Our simulations show that the spatial variability of carbon isotopic properties in an eroding landscape is mainly caused by the soil redistribution.
Brian N. Bailey, María A. Ponce de León, and E. Scott Krayenhoff
Geosci. Model Dev., 13, 4789–4808, https://doi.org/10.5194/gmd-13-4789-2020, https://doi.org/10.5194/gmd-13-4789-2020, 2020
Short summary
Short summary
Numerous models of plant radiation interception based on a range of assumptions are available in the literature, but the importance of each assumption is not well understood. In this work, we evaluate several assumptions common in simple models of radiation interception in canopies with widely spaced plants by comparing against a detailed 3-D model. This yielded a simple model based on readily measurable parameters that could accurately predict interception for a wide range of architectures.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Pep Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, A. M. Roxanna Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoli Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-259, https://doi.org/10.5194/gmd-2020-259, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
The phase-2 of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4 and N2O emissions and sinks for ten regions of the globe. In this manuscript, we provide definitions, review different methods and make recommendations to the RECCAP community for estimating different components of the total land-atmosphere carbon exchange for each region in a consistent and complete approach.
Julius Vira, Peter Hess, Jeff Melkonian, and William R. Wieder
Geosci. Model Dev., 13, 4459–4490, https://doi.org/10.5194/gmd-13-4459-2020, https://doi.org/10.5194/gmd-13-4459-2020, 2020
Short summary
Short summary
Mostly emitted by the agricultural sector, ammonia has an important role in atmospheric chemistry. We developed a model to simulate how ammonia emissions respond to changes in temperature and soil moisture, and we evaluated agricultural ammonia emissions globally. The simulated emissions agree with earlier estimates over many regions, but the results highlight the variability of ammonia emissions and suggest that emissions in warm climates may be higher than previously thought.
Emily Kyker-Snowman, William R. Wieder, Serita D. Frey, and A. Stuart Grandy
Geosci. Model Dev., 13, 4413–4434, https://doi.org/10.5194/gmd-13-4413-2020, https://doi.org/10.5194/gmd-13-4413-2020, 2020
Short summary
Short summary
Microbes drive carbon (C) and nitrogen (N) transformations in soil, and soil models have started to include explicit microbial physiology and functioning to try to reduce uncertainty in soil–climate feedbacks. Here, we add N cycling to a microbially explicit soil C model and reproduce C and N dynamics in soil during litter decomposition across a range of sites. We discuss model-generated hypotheses about soil C and N cycling and highlight the need for landscape-scale model evaluation data.
Jinxuan Chen, Christoph Gerbig, Julia Marshall, and Kai Uwe Totsche
Geosci. Model Dev., 13, 4091–4106, https://doi.org/10.5194/gmd-13-4091-2020, https://doi.org/10.5194/gmd-13-4091-2020, 2020
Short summary
Short summary
One of the essential challenge for atmospheric CO2 forecasting is predicting CO2 flux variation on synoptic timescale. For CAMS CO2 forecast, a process-based vegetation model is used.
In this research we evaluate another type of model (i.e., the light-use-efficiency model VPRM), which is a data-driven approach and thus ideal for realistic estimation, on its ability of flux prediction. Errors from different sources are assessed, and overall the model is capable of CO2 flux prediction.
Yuma Sakai, Hideki Kobayashi, and Tomomichi Kato
Geosci. Model Dev., 13, 4041–4066, https://doi.org/10.5194/gmd-13-4041-2020, https://doi.org/10.5194/gmd-13-4041-2020, 2020
Short summary
Short summary
Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. The canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. We develop the three-dimensional Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind SIF emission from complex forest canopies.
Cited articles
Arneth, A., Sitch, S., Pongratz, J., Stocker, B. D., Ciais, P., Poulter, B.,
Bayer, A. D., Bondeau, A., Calle, L., Chini, L. P., Gasser, T., Fader, M.,
Friedlingstein, P., Kato, E., Li, W., Lindeskog, M., Nabel, J. E. M. S.,
Pugh, T. A. M., Robertson, E., Viovy, N., Yue, C., and Zaehle, S.: Historical
carbon dioxide emissions caused by land-use changes are possibly larger than
assumed, Nat. Geosci., 10, 79–84, https://doi.org/10.1038/ngeo2882, 2017. a
Arnold, J. G., Kiniry, J. R., Williams, J. R., Haney, E. B., and Neitsch,
S. L.: Soil and water assessment tool input/output documentation version
2012, Texas Water Resources Institute, College Station, Texas, 2012. a
Ascott, M. J., Gooddy, D. C., Wang, L., Stuart, M. E., Lewis, M. A., Ward,
R. S., and Binley, A. M.: Global patterns of nitrate storage in the vadose
zone, Nat. Comm., 8, 1416, https://doi.org/10.1038/s41467-017-01321-w, 2017. a
Atkin, O., Schortemeyer, M., McFarlane, N., and Evans, J.: The response of
fast- and slow-growing Acacia species to elevated atmospheric CO2: an
analysis of the underlying components of relative growth rate, Oecologica,
120, 544–554, https://doi.org/10.1007/s004420050889, 1999. a
Baker, T. R., Phillips, O. L., Laurance, W. F., Pitman, N. C. A., Almeida,
S., Arroyo, L., DiFiore, A., Erwin, T., Higuchi, N., Killeen, T. J.,
Laurance, S. G., Nascimento, H., Monteagudo, A., Neill, D. A., Silva, J. N.
M., Malhi, Y., López Gonzalez, G., Peacock, J., Quesada, C. A., Lewis, S.
L., and Lloyd, J.: Do species traits determine patterns of wood production in
Amazonian forests?, Biogeosciences, 6, 297–307,
https://doi.org/10.5194/bg-6-297-2009, 2009. a
Barnard, D. M. and Bauerle, W. L.: The implications of minimum stomatal
conductance on modeling water flux in forest canopies, J. Geophys.
Res.-Biogeo., 118, 1322–1333, https://doi.org/10.1002/jgrg.20112, 2013. a
Batjes, N. H. (Ed.): Global Data Set of Derived Soil Properties, 0.5-Degree
Grid (ISRIC-WISE), Oak Ridge National Laboratory Distributed Active Archive
Center, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/546., 2000. a, b
Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., Schamm, K.,
Schneider, U., and Ziese, M.: A description of the global land-surface
precipitation data products of the Global Precipitation Climatology Centre
with sample applications including centennial (trend) analysis from
1901–present, Earth Syst. Sci. Data, 5, 71–99,
https://doi.org/10.5194/essd-5-71-2013, 2013. a
Bessou, C., Mary, B., Léonard, J., Roussel, M., Gréhan, E., and
Gabrielle, B.: Modelling soil compaction impacts on nitrous oxide emissions
in arable fields, Eur. J. Soil Sci., 61, 348–363,
https://doi.org/10.1111/j.1365-2389.2010.01243.x, 2010. a
Bodirsky, B. L., Popp, A., Weindl, I., Dietrich, J. P., Rolinski, S.,
Scheiffele, L., Schmitz, C., and Lotze-Campen, H.: N2O emissions from the
global agricultural nitrogen cycle – current state and future scenarios,
Biogeosciences, 9, 4169–4197, https://doi.org/10.5194/bg-9-4169-2012, 2012. a, b
Bouwman, A. F., Beusen, A. H. W., Griffioen, J., Van Groenigen, J. W.,
Hefting, M. M., Oenema, O., Van Puijenbroek, P. J. T. M., Seitzinger, S.,
Slomp, C. P., and Stehfest, E.: Global trends and uncertainties in
terrestrial denitrification and N2O emissions, Philos. T. Roy. Soc.
B, 368, 20130112, https://doi.org/10.1098/rstb.2013.0112, 2013. a
Chang, J., Ciais, P., Wang, X., Piao, S., Asrar, G., Betts, R., Chevallier,
F., Dury, M., François, L., Frieler, K., Ros, A. G. C., Henrot, A.-J.,
Hickler, T., Ito, A., Morfopoulos, C., Munhoven, G., Nishina, K., Ostberg,
S., Pan, S., Peng, S., Rafique, R., Reyer, C., Rödenbeck, C., Schaphoff,
S., Steinkamp, J., Tian, H., Viovy, N., Yang, J., Zeng, N., and Zhao, F.:
Benchmarking carbon fluxes of the ISIMIP2a biome models, Environ. Res. Lett.
12, 045002, https://doi.org/10.1088/1748-9326/aa63fa, 2017. a
Cleveland, C. C., Townsend, A. R., Schimel, D. S., Fisher, H., Howarth,
R. W., Hedin, L. O., Perakis, S. S., Latty, E. F., Von Fischer, J. C.,
Elseroad, A., and Wasson, M. F.: Global patterns of terrestrial biological
nitrogen (N2) fixation in natural ecosystems, Global Biogeochem. Cy.,
13, 623–645, https://doi.org/10.1029/1999GB900014, 1999. a, b
Collatz, G. J., Berry, J. A., Farquhar, G. D., and Pierce, J.: The
relationship between the Rubisco reaction mechanism and models of
photosynthesis, Plant Cell Environ., 13, 219–225, 1990. a
Comins, H. N. and McMurtrie, R. E.: Long-Term Response of Nutrient-Limited
Forests to CO2 Enrichment; Equilibrium Behavior of Plant-Soil Models,
Ecol. Appl., 3, 666–681, https://doi.org/10.2307/1942099, 1993. a
Cornelissen, J., Diez, P., and Hunt, R.: Seedling growth, allocation and
leaf attributes in a wide range of woody plant species and types, J.
Ecol., 84, 755–765, https://doi.org/10.2307/2261337, 1996. a
Cornelissen, J., Werger, M., CastroDiez, P., vanRheenen, J., and Rowland, A.:
Foliar nutrients in relation to growth, allocation and leaf traits in
seedlings of a wide range of woody plant species and types, Oecologia,
111, 460–469, https://doi.org/10.1007/s004420050259, 1997. a
Cornelissen, J., Quested, H., Gwynn-Jones, D., Van Logtestijn, R., De Beus,
M., Kondratchuk, A., Callaghan, T., and Aerts, R.: Leaf digestibility and
litter decomposability are related in a wide range of subarctic plant species
and types, Funct. Ecol., 18, 779–786,
https://doi.org/10.1111/j.0269-8463.2004.00900.x, 2004. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, I., Biblot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Greer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M.,
Matricardi, M., McNally, A. P., Mong-Sanz, B. M., Morcette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart,
F.: The ERA-Interim reanalysis: Configuration and performance of the data
assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011. a
Doran, J. W., Mielke, L. N., and Stamatiadis, S.: Microbial activity and N
cycling as regulated by soil water-filled pore space, in: 11th International
Conference, Int. Soil Tillage Res. Orgo (ISTRO), Edinburgh, Scotland, 1988. a
Elliott, J., Müller, C., Deryng, D., Chryssanthacopoulos, J., Boote, K.
J., Büchner, M., Foster, I., Glotter, M., Heinke, J., Iizumi, T.,
Izaurralde, R. C., Mueller, N. D., Ray, D. K., Rosenzweig, C., Ruane, A. C.,
and Sheffield, J.: The Global Gridded Crop Model Intercomparison: data and
modeling protocols for Phase 1 (v1.0), Geosci. Model Dev., 8, 261–277,
https://doi.org/10.5194/gmd-8-261-2015, 2015. a, b, c, d
FAOSTAT: FAOSTAT, Food and Agriculture Organization of the United
Nations, available at: http://www.fao.org/faostat/en/#data/QC, last
access: 3 June 2017. a
Fisher, J. B., Sitch, S., Malhi, Y., Fisher, R. A., Huntingford, C., and Tan,
S.-Y.: Carbon cost of plant nitrogen acquisition: A mechanistic, globally
applicable model of plant nitrogen uptake, retranslocation, and fixation,
Global Biogeochem. Cy., 24, GB1014, https://doi.org/10.1029/2009GB003621, 2010. 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, b
Fortunel, C., Garnier, E., Joffre, R., Kazakou, E., Quested, H., Grigulis,
K., Lavorel, S., Ansquer, P., Castro, H., Cruz, P., Dolezal, J., Eriksson,
O., Freitas, H., Golodets, C., Jouany, C., Kigel, J., Kleyer, M., Lehsten,
V., Leps, J., Meier, T., Pakeman, R., Papadimitriou, M., Papanastasis, V. P.,
Quetier, F., Robson, M., Sternberg, M., Theau, J.-P., Thebault, A., and
Zarovali, M.: Leaf traits capture the effects of land use changes and
climate on litter decomposability of grasslands across Europe, Ecology,
90, 598–611, https://doi.org/10.1890/08-0418.1, 2009. a
Freschet, G. T., Cornelissen, J. H. C., van Logtestijn, R. S. P., and Aerts,
R.: Evidence of the “plant economics spectrum” in a subarctic flora, J.
Ecol., 98, 362–373, https://doi.org/10.1111/j.1365-2745.2009.01615.x, 2010a. a
Freschet, G. T., Cornelissen, J. H. C., van Logtestijn, R. S. P., and Aerts,
R.: Substantial nutrient resorption from leaves, stems and roots in a
subarctic flora: what is the link with other resource economics traits?,
New Phytol., 186, 879–889, https://doi.org/10.1111/j.1469-8137.2010.03228.x,
2010b. a
Friend, A. D., Stevens, A. K., Knox, R. G., and Cannell, M. G. R.: A
process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid
v3.0), Ecol. Model., 95, 249–287, https://doi.org/10.1016/S0304-3800(96)00034-8, 1997. a
Friend, A. D., Lucht, W., Rademacher, T. T., Keribin, R., Betts, R., Cadule,
P., Ciais, P., Clark, D. B., Dankers, R., Falloon, P. D., Ito, A., Kahana,
R., Kleidon, A., Lomas, M. R., Nishina, K., Ostberg, S., Pavlick, R., Peylin,
P., Schaphoff, S., Vuichard, N., Warszawski, L., Wiltshire, A., and Woodward,
F. I.: Carbon residence time dominates uncertainty in terrestrial vegetation
responses to future climate and atmospheric CO2, P. Natl. Acad. Sci.
USA, 111, 3280–3285, https://doi.org/10.1073/pnas.1222477110, 2014. a
Fyllas, N. M., Patiño, S., Baker, T. R., Bielefeld Nardoto, G.,
Martinelli, L. A., Quesada, C. A., Paiva, R., Schwarz, M., Horna, V.,
Mercado, L. M., Santos, A., Arroyo, L., Jiménez, E. M., Luizão, F.
J., Neill, D. A., Silva, N., Prieto, A., Rudas, A., Silviera, M., Vieira, I.
C. G., Lopez-Gonzalez, G., Malhi, Y., Phillips, O. L., and Lloyd, J.:
Basin-wide variations in foliar properties of Amazonian forest: phylogeny,
soils and climate, Biogeosciences, 6, 2677–2708,
https://doi.org/10.5194/bg-6-2677-2009, 2009. a
Galloway, J. N., Dentener, F. J., Capone, D. G., Boyer, E. W., Howarth,
R. W., Seitzinger, S. P., Asner, G. P., Cleveland, C. C., Green, P. A.,
Holland, E. A., Karl, D. M., Michaels, A. F., Porter, J. H., Townsend, A. R.,
and Vöosmarty, C. J.: Nitrogen Cycles: Past, Present, and Future,
Biogeochemistry, 70, 153–226, https://doi.org/10.1007/s10533-004-0370-0, 2004. a
Galloway, J. N., Leach, A. M., Bleeker, A., and Erisman, J. W.: A chronology
of human understanding of the nitrogen cycle, Philos. T. Roy. Soc. B, 368,
https://doi.org/10.1098/rstb.2013.0120, 2013. a
Garnier, E., Lavorel, S., Ansquer, P., Castro, H., Cruz, P., Dolezal, J.,
Eriksson, O., Fortunel, C., Freitas, H., Golodets, C., Grigulis, K., Jouany,
C., Kazakou, E., Kigel, J., Kleyer, M., Lehsten, V., Leps, J., Meier, T.,
Pakeman, R., Papadimitriou, M., Papanastasis, V. P., Quested, H., Quetier,
F., Robson, M., Roumet, C., Rusch, G., Skarpe, C., Sternberg, M., Theau,
J.-P., Thebault, A., Vile, D., and Zarovali, M. P.: Assessing the effects of
land-use change on plant traits, communities and ecosystem functioning in
grasslands: A standardized methodology and lessons from an application to 11
European sites, Ann. Bot., 99, 967–985, https://doi.org/10.1093/aob/mcm215,
2007. a
Han, W., Fang, J., Guo, D., and Zhang, Y.: Leaf nitrogen and phosphorus
stoichiometry across 753 terrestrial plant species in China, New Phytol.,
168, 377–385, https://doi.org/10.1111/j.1469-8137.2005.01530.x, 2005. a
Harris, I., Jones, P., Osborn, T., and Lister, D.: Updated high-resolution
grids of monthly climatic observations – the CRU TS3.10 Dataset, Int.
J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014. a
Haxeltine, A. and Prentice, I. C.: A General Model for the Light-Use
Efficiency of Primary Production, Funct. Ecol., 10, 551–561,
https://doi.org/10.2307/2390165, 1996. a
Hutchings, N. J., Reinds, G. J., Leip, A., Wattenbach, M., Bienkowski, J. F.,
Dalgaard, T., Dragosits, U., Drouet, J. L., Durand, P., Maury, O., and de
Vries, W.: A model for simulating the timelines of field operations at a
European scale for use in complex dynamic models, Biogeosciences, 9,
4487–4496, https://doi.org/10.5194/bg-9-4487-2012, 2012. a
Jackson, R. B., Canadell, J., Ehleringer, J. R., Mooney, H. A.,
Sala, O.E., and Schulze, E. D.: A global analysis of root distributions
for terrestrial biomes, Oecologia, 108, 389–411, https://doi.org/10.1007/BF00333714,
1996. a
Kabala, C., Karczewska, A., Gałka, B., Cuske, M., and Sowiński, J.:
Seasonal dynamics of nitrate and ammonium ion concentrations in soil
solutions collected using MacroRhizon suction cups, Environ. Monit. Assess.,
189, 304, https://doi.org/10.1007/s10661-017-6022-3, 2017. 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, b, c
Kelley, D. I., Prentice, I. C., Harrison, S. P., Wang, H., Simard, M.,
Fisher, J. B., and Willis, K. O.: A comprehensive benchmarking system for
evaluating global vegetation models, Biogeosciences, 10, 3313–3340,
https://doi.org/10.5194/bg-10-3313-2013, 2013. a
Klein Goldewijk, K. and van Drecht, G. (Eds.): HYDE 3: Current and historical
population and land cover, in: Integrated modelling of global environmental
change, An overview of IMAGE 2.4., Netherlands Environmental Assessment
Agency (MNP), Bilthoven, the Netherlands, 93–111, 2006. a
Kollas, C., Kersebaum, K. C., Nendel, C., Manevski, K., Müller, C.,
Palosuo, T., Armas-Herrera, C. M., Beaudoin, N., Bindi, M., Charfeddine, M.,
Conradt, T., Constantin, J., Eitzinger, J., Ewert, F., Ferrise, R., Gaiser,
T., Cortazar-Atauri, I. G. d., Giglio, L., Hlavinka, P., Hoffmann, H.,
Hoffmann, M. P., Launay, M., Manderscheid, R., Mary, B., Mirschel, W.,
Moriondo, M., Olesen, J. E., Öztürk, I., Pacholski, A.,
Ripoche-Wachter, D., Roggero, P. P., Roncossek, S., Rötter, R. P., Ruget,
F., Sharif, B., Trnka, M., Ventrella, D., Waha, K., Wegehenkel, M., Weigel,
H.-J., and Wu, L.: Crop rotation modelling – A European model
intercomparison, Eur. J. Agron., 70, 98–111,
https://doi.org/10.1016/j.eja.2015.06.007, 2015. a
Krysanova, V. and Wechsung, F.: SWIM (Soil and Water Integrated Model) User
Manual, available at: https://www.pik-potsdam.de/members/valen/swim
(last access: 31 July 2014), 2000. a
Kurokawa, H. and Nakashizuka, T.: Leaf herbivory and decomposability in a
Malaysian tropical rain forest, Ecology, 89, 2645–2656,
https://doi.org/10.1890/07-1352.1, 2008. a
Lamarque, J.-F., Dentener, F., McConnell, J., Ro, C.-U., Shaw, M., Vet, R.,
Bergmann, D., Cameron-Smith, P., Dalsoren, S., Doherty, R., Faluvegi, G.,
Ghan, S. J., Josse, B., Lee, Y. H., MacKenzie, I. A., Plummer, D., Shindell,
D. T., Skeie, R. B., Stevenson, D. S., Strode, S., Zeng, G., Curran, M.,
Dahl-Jensen, D., Das, S., Fritzsche, D., and Nolan, M.: Multi-model mean
nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate
Model Intercomparison Project (ACCMIP): evaluation of historical and
projected future changes, Atmos. Chem. Phys., 13, 7997–8018,
https://doi.org/10.5194/acp-13-7997-2013, 2013. a
Laughlin, D. C., Leppert, J. J., Moore, M. M., and Sieg, C. H.: A
multi-trait test of the leaf-height-seed plant strategy scheme with 133
species from a pine forest flora, Funct. Ecol., 24, 493–501,
https://doi.org/10.1111/j.1365-2435.2009.01672.x, 2010. a
Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken,
J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R.
A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp,
L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney,
S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V.,
Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A.,
Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi,
D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R.,
Nabel, J. E. M. S., Nakaoka, S.-I., O'Brien, K., Olsen, A., Omar, A. M., Ono,
T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U.,
Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A.
J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van
der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., and Zaehle, S.:
Global Carbon Budget 2016, Earth Syst. Sci. Data, 8, 605–649,
https://doi.org/10.5194/essd-8-605-2016, 2016. a, b
Lehner, B. and Döll, P.: Development and validation of a global database
of lakes, reservoirs and wetlands, J. Hydrol., 296, 1–22,
https://doi.org/10.1016/j.jhydrol.2004.03.028, 2004. a
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B.,
Crouzet, P., Döll, P., Endejan, M., Frenken, K., and Magome, J.:
High-resolution mapping of the world's reservoirs and dams for sustainable
river-flow management, Front. Ecol. Environ., 9, 494–502,
https://doi.org/10.1890/100125, 2011. a
Lin, B.-L., Sakoda, A., Shibasaki, R., Goto, N., and Suzuki, M.: Modelling a
global biogeochemical nitrogen cycle in terrestrial ecosystems, Ecol. Model.,
135, 89–110, https://doi.org/10.1016/S0304-3800(00)00372-0, 2000. a
Loveys, B., Atkinson, L., Sherlock, D., Roberts, R., Fitter, A., and Atkin,
O.: Thermal acclimation of leaf and root respiration: an investigation
comparing inherently fast- and slow-growing plant species, Glob. Change
Biol., 9, 895–910, https://doi.org/10.1046/j.1365-2486.2003.00611.x, 2003. a
Luyssaert, S., Inglima, I., Jung, M., Richardson, A. D., Reichstein, M.,
Papale, D., Piao, S. L., Schulze, E. D., Wingate, L., Matteucci, G., Aragao,
L., Aubinet, M., Beer, C., Bernhofer, C., Black, K. G., Bonal, D., Bonnefond,
J. M., Chambers, J., Ciais, P., Cook, B., Davis, K. J., Dolman, A. J.,
Gielen, B., Goulden, M., Grace, J., Granier, A., Grelle, A., Griffis, T.,
Grünwald, T., Guidolotti, G., Hanson, P. J., Harding, R., Hollinger,
D. Y., Hutyra, L. R., Kolari, P., Kruijt, B., Kutsch, W., Lagergren, F.,
Laurila, T., Law, B. E., Le Maire, G., Lindroth, A., Loustau, D., Malhi, Y.,
Mateus, J., Migliavacca, M., Misson, L., Montagnani, L., Moncrieff, J.,
Moors, E., Munger, J. W., Nikinmaa, E., Ollinger, S. V., Pita, G., Rebmann,
C., Roupsard, O., Saigusa, N., Sanz, M. J., Seufert, G., Sierra, C., Smith,
M. L., Tang, J., Valentini, R., Vesala, T., and Janssens, I. A.: CO2
balance of boreal, temperate, and tropical forests derived from a global
database, Glob. Change Biol., 13, 2509–2537,
https://doi.org/10.1111/j.1365-2486.2007.01439.x, 2007. a, b
Malhi, S. S. and McGill, W. B.: Nitrification in three Alberta soils:
Effect of temperature, moisture and substrate concentration, Soil Biol.
Biochem., 14, 393–399, https://doi.org/10.1016/0038-0717(82)90011-6, 1982. a
Montes, F., Rotz, C. A., and Chaoui, H.: Process Modeling of Ammonia
Volatilization from Ammonium Solution and Manure Surfaces: A Review with
Recommended Models, T. ASABE, 52, 1707–1720, https://doi.org/10.13031/2013.29133,
2009. a
Mueller, N. D., Gerber, J. S., Johnston, M., Ray, D. K., Ramankutty, N., and
Foley, J. A.: Closing yield gaps through nutrient and water management,
Nature, 490, 254–257, https://doi.org/10.1038/nature11420, 2012. a
Müller, C., Bondeau, A., Lotze-Campen, H., Cramer, W., and Lucht, W.:
Comparative impact of climatic and nonclimatic factors on global terrestrial
carbon and water cycles, Global Biogeochem. Cy., 20, GB4015,
https://doi.org/10.1029/2006GB002742, 2006. a
Müller, C., Stehfest, E., van Minnen, J. G., Strengers, B., von Bloh, W.,
Beusen, A. H., Schaphoff, S., Kram, T., and Lucht, W.: Drivers and patterns
of land biosphere carbon balance reversal, Environ. Res. Lett., 11, 044002,
https://doi.org/10.1088/1748-9326/11/4/044002, 2016. a, b
Müller, C., Elliott, J., Chryssanthacopoulos, J., Arneth, A., Balkovic,
J., Ciais, P., Deryng, D., Folberth, C., Glotter, M., Hoek, S., Iizumi, T.,
Izaurralde, R. C., Jones, C., Khabarov, N., Lawrence, P., Liu, W., Olin, S.,
Pugh, T. A. M., Ray, D. K., Reddy, A., Rosenzweig, C., Ruane, A. C., Sakurai,
G., Schmid, E., Skalsky, R., Song, C. X., Wang, X., de Wit, A., and Yang, H.:
Global gridded crop model evaluation: benchmarking, skills, deficiencies and
implications, Geosci. Model Dev., 10, 1403–1422,
https://doi.org/10.5194/gmd-10-1403-2017, 2017. a, b, c
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., and Williams, J. R.: Soil and
water assessment tool theoretical documentation, Texas Water Resources
Institute, College Station, Texas, 2005. a
New, M., Hulme, M., and Jones, P.: Representing Twentieth-Century
Space–Time Climate Variability. Part II: Development of
1901–96 Monthly Grids of Terrestrial Surface Climate, J. Climate,
13, 2217–2238, https://doi.org/10.1175/1520-0442(2000)013<2217:RTCSTC>2.0.CO;2, 2000. a
Niinemets, U.: Components of leaf dry mass per area – thickness and density
– alter leaf photosynthetic capacity in reverse directions in woody plants,
New Phytol., 144, 35–47, https://doi.org/10.1046/j.1469-8137.1999.00466.x,
1999. a
Niinemets, U.: Global-scale climatic controls of leaf dry mass per area,
density, and thickness in trees and shrubs, Ecology, 82, 453–469,
https://doi.org/10.1890/0012-9658(2001)082<0453:GSCCOL>2.0.CO;2, 2001. a
Norby, R. J., DeLucia, E. H., Gielen, B., Calfapietra, C., Giardina, C. P.,
King, J. S., Ledford, J., McCarthy, H. R., Moore, D. J. P., Ceulemans, R.,
De Angelis, P., Finzi, A. C., Karnosky, D. F., Kubiske, M. E., Lukac, M.,
Pregitzer, K. S., Scarascia-Mugnozza, G. E., Schlesinger, W. H., and Oren,
R.: Forest response to elevated CO2 is conserved across a broad range of
productivity, P. Natl. Acad. Sci. USA, 102, 18052–18056,
https://doi.org/10.1073/pnas.0509478102, 2005. a
Ogaya, R. and Penuelas, J.: Comparative field study of Quercus ilex and
Phillyrea latifolia: photosynthetic response to experimental drought
conditions, Environ. Exp. Bot., 50, 137–148,
https://doi.org/10.1016/S0098-8472(03)00019-4, 2003. a
Ogaya, R. and Penuelas, J.: Contrasting foliar responses to drought in
Quercus ilex and Phillyrea latifolia, Biol. Plantarum, 50, 373–382,
https://doi.org/10.1007/s10535-006-0052-y, 2006. a
Ogaya, R. and Penuelas, J.: Tree growth, mortality, and above-ground biomass
accumulation in a holm oak forest under a five-year experimental field
drought, Plant Ecol., 189, 291–299, https://doi.org/10.1007/s11258-006-9184-6,
2007. a
Ogaya, R. and Penuelas, J.: Changes in leaf δ13C and
δ15N for three Mediterranean tree species in relation to soil water
availability, Acta Oecol., 34, 331–338,
https://doi.org/10.1016/j.actao.2008.06.005, 2008. a
Ordonez, J. C., van Bodegom, P. M., Witte, J.-P. M., Bartholomeus, R. P., van
Hal, J. R., and Aerts, R.: Plant Strategies in Relation to Resource Supply
in Mesic to Wet Environments: Does Theory Mirror Nature?, Am. Nat., 175,
225–239, https://doi.org/10.1086/649582, 2010. a
ORNL DAAC: Oak Ridge National Laboratory Distributed Active Archive Center
(ORNL DAAC), available at: http://fluxnet.ornl.gov/ (last access:
19 October 2015), 2011. a
Pakeman, R. J., Garnier, E., Lavorel, S., Ansquer, P., Castro, H., Cruz, P.,
Dolezal, J., Eriksson, O., Freitas, H., Golodets, C., Kigel, J., Kleyer, M.,
Leps, J., Meier, T., Papadimitriou, M., Papanastasis, V. P., Quested, H.,
Quetier, F., Rusch, G., Sternberg, M., Theau, J.-P., Thebault, A., and Vile,
D.: Impact of abundance weighting on the response of seed traits to climate
and land use, J. Ecol., 96, 355–366,
https://doi.org/10.1111/j.1365-2745.2007.01336.x, 2008. a
Pakeman, R. J., Leps, J., Kleyer, M., Lavorel, S., Garnier, E., and the VISTA
consortium: Relative climatic, edaphic and management controls of plant
functional trait signatures, J. Veg. Sci., 20, 148–159,
https://doi.org/10.1111/j.1654-1103.2009.05548.x, 2009. a
Parton, W. J., Mosier, A. R., Ojima, D. S., Valentine, D. W., Schimel, D. S.,
Weier, K., and Kulmala, A. E.: Generalized model for N2 and N2O
production from nitrification and denitrification, Global Biogeochem. Cy.,
10, 401–412, https://doi.org/10.1029/96GB01455, 1996. a, b
Patiño, S., Lloyd, J., Paiva, R., Baker, T. R., Quesada, C. A., Mercado,
L. M., Schmerler, J., Schwarz, M., Santos, A. J. B., Aguilar, A., Czimczik,
C. I., Gallo, J., Horna, V., Hoyos, E. J., Jimenez, E. M., Palomino, W.,
Peacock, J., Peña-Cruz, A., Sarmiento, C., Sota, A., Turriago, J. D.,
Villanueva, B., Vitzthum, P., Alvarez, E., Arroyo, L., Baraloto, C., Bonal,
D., Chave, J., Costa, A. C. L., Herrera, R., Higuchi, N., Killeen, T., Leal,
E., Luizão, F., Meir, P., Monteagudo, A., Neil, D., Núñez-Vargas,
P., Peñuela, M. C., Pitman, N., Priante Filho, N., Prieto, A., Panfil, S.
N., Rudas, A., Salomão, R., Silva, N., Silveira, M., Soares de Almeida,
S., Torres-Lezama, A., Vásquez-Martínez, R., Vieira, I., Malhi, Y.,
and Phillips, O. L.: Branch xylem density variations across the Amazon Basin,
Biogeosciences, 6, 545–568, https://doi.org/10.5194/bg-6-545-2009, 2009. a
Penuelas, J., Sardans, J., Llusia, J., Owen, S. M., Carnicer, J.,
Giambelluca, T. W., Rezende, E. L., Waite, M., and Niinemets, U.: Faster
returns on “leaf economics” and different biogeochemical niche in invasive
compared with native plant species, Glob. Change Biol., 16,
2171–2185, https://doi.org/10.1111/j.1365-2486.2009.02054.x, 2010a. a
Penuelas, J., Sardans, J., Llusia, J., Owen, S. M., Silva, J., and Niinemets,
U.: Higher Allocation to Low Cost Chemical Defenses in Invasive Species of
Hawaii, J. Chem. Ecol., 36, 1255–1270,
https://doi.org/10.1007/s10886-010-9862-7, 2010b. a
Portmann, F. T., Siebert, S., and Döll, P.: MIRCA2000 – Global
monthly irrigated and rainfed crop areas around the year 2000: A new
high-resolution data set for agricultural and hydrological modeling, Global
Biogeochem. Cy., 24, 1–24, https://doi.org/10.1029/2008GB003435, 2010. a
Post, W. M., Pastor, J., Zinke, P. J., and Stangenberger, A. G.: Global
patterns of soil nitrogen storage, Nature, 317, 613–616,
https://doi.org/10.1038/317613a0, 1985. a
Potter, P., Ramankutty, N., Bennett, E. M., and Donner, S. D.: Characterizing
the Spatial Patterns of Global Fertilizer Application and Manure Production,
Earth Interact., 14, 1–22, https://doi.org/10.1175/2009EI288.1, 2010. a
Quested, H., Cornelissen, J., Press, M., Callaghan, T., Aerts, R., Trosien,
F., Riemann, P., Gwynn-Jones, D., Kondratchuk, A., and Jonasson, S.:
Decomposition of sub-arctic plants with differing nitrogen economies: A
functional role for hemiparasites, Ecology, 84, 3209–3221,
https://doi.org/10.1890/02-0426, 2003. 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
Sardans, J., Penuelas, J., and Ogaya, R.: Drought-induced changes in C and N
stoichiometry in a Quercus ilex Mediterranean forest, Forest Sci., 54,
513–522, 2008a. a
Sardans, J., Penuelas, J., Prieto, P., and Estiarte, M.: Changes in Ca, Fe,
Mg, Mo, Na, and S content in a Mediterranean shrubland under warming and
drought, J. Geophys. Res.-Biogeo., 113, G03039,
https://doi.org/10.1029/2008JG000795, 2008b. a
Schaphoff, S., Forkel, M., Müller, C., Knauer, J., von Bloh, W., Gerten,
D., Jägermeyr, J., Lucht, W., Rammig, A., Thonicke, K., and Waha, K.:
LPJmL4 – a dynamic global vegetation model with managed land – Part 2:
Model evaluation, Geosci. Model Dev., 11, 1377–1403,
https://doi.org/10.5194/gmd-11-1377-2018, 2018a. a, b, c, d, e, f
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,
2018b. a, b, c, d, e, f, g
Schewe, J., Heinke, J., Gerten, D., Haddeland, I., Arnell, N. W., Clark,
D. B., Dankers, R., Eisner, S., Fekete, B. M., Colón-González, F. J.,
Gosling, S. N., Kim, H., Liu, X., Masaki, Y., Portmann, F. T., Satoh, Y.,
Stacke, T., Tang, Q., Wada, Y., Wisser, D., Albrecht, T., Frieler, K.,
Piontek, F., Warszawski, L., and Kabat, P.: Multimodel assessment of water
scarcity under climate change, P. Natl. Acad. Sci. USA, 111, 3245–3250,
https://doi.org/10.1073/pnas.1222460110, 2014. a
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
Schimel, J. P. and Bennett, J.: Nitrogen mineralization: Challenges of a
changing paradigm, Ecology, 85, 591–602, https://doi.org/10.1890/03-8002, 2004. a
Schlesinger, W. H. and Jasechko, S.: Transpiration in the global water cycle,
Agr. Forest Meteorol., 189–190, 115–117,
https://doi.org/10.1016/j.agrformet.2014.01.011, 2014. a
Siebert, S., Kummu, M., Porkka, M., Döll, P., Ramankutty, N., and
Scanlon, B. R.: A global data set of the extent of irrigated land from 1900
to 2005, Hydrol. Earth Syst. Sci., 19, 1521–1545,
https://doi.org/10.5194/hess-19-1521-2015, 2015. a
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W.,
Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and
Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and
terrestrial carbon cycling in the LPJ dynamic global vegetation model,
Glob. Change Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x,
2003. a, b, c, d, e, f, g
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg,
J., and Zaehle, S.: Implications of incorporating N cycling and N limitations
on primary production in an individual-based dynamic vegetation model,
Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014,
2014. a, b, c, d, e, f, g, h, i, j, k, l
Smith, W., Reed, S., Cleveland, C., Ballantyne, A., Anderegg, W., Wieder, W.,
Liu, Y., and Running, S.: Large divergence of satellite and Earth system
model estimates of global terrestrial CO2 fertilization, Nat. Clim.
Change, 6, 306–310, https://doi.org/10.1038/nclimate2879, 2016. a
Sutton, M., Bleeker, A., Howard, C., Bekunda, M., Grizzetti, B., de Vries,
W., van Grinsven, H., Abrol, Y., Adhya, T., Billen, G., Davidson, E., Datta,
A., Diaz, R., Erisman, J., Liu, X., Oenema, O., Palm, C., Raghuram, N., Reis,
S., Scholz, R., Sims, T., Westhoek, H., and Zhang, F.: Our nutrient world:
the challenge to produce more food and energy with less pollution,
NERC/Centre for Ecology & Hydrology, Edinburgh, available at:
http://nora.nerc.ac.uk/500700/, 2013. a
Thornley, J. H. M.: A Transport-resistance Model of Forest Growth and
Partitioning, Ann. Bot., 68, 211–216, 1991. a
Thornton, P. E., Lamarque, J.-F., Rosenbloom, N. A., and Mahowald, N. M.:
Influence of carbon-nitrogen cycle coupling on land model response to CO2
fertilization and climate variability, Global Biogeochem. Cy., 21, GB4018,
https://doi.org/10.1029/2006GB002868, 2007. a
University of East Anglia
Climatic Research Unit and Harris, I. C.: CRU TS3.23: Climatic Research Unit
(CRU) Time-Series (TS) Version 3.23 of High Resolution Gridded Data of
Month-by-month Variation in Climate (Jan. 1901–Dec. 2014), Centre for
Environmental Data Analysis,
https://doi.org/10.5285/4c7fdfa6-f176-4c58-acee-683d5e9d2ed5, 2015. a
Vitousek, P. M., Menge, D. N. L., Reed, S. C., and Cleveland, C. C.:
Biological nitrogen fixation: rates, patterns and ecological controls in
terrestrial ecosystems, Philos. T. Roy. Soc. B, 368, 20130119,
https://doi.org/10.1098/rstb.2013.0119, 2013. a
von Bloh, W., Schaphoff, S., Müller, C., Rolinski, S., Waha, K., and
Zaehle, S.: LPJmL5 Model Code. V 5.0.001, GFZ Data sevices,
https://doi.org/10.5880/pik.2018.011, 2018. a
Vorosmarty, C. and Fekete, B.: ISLSCP II River Routing Data (STN-30p), ISLSCP
Initiative II Collection, data set, edited by: Hall, F. G., Collatz, G.,
Meeson, B., Los, S., Brown de Colstoun, E., and Landis, D., ORNL Distributed
Active Archive Center, https://doi.org/10.3334/ORNLDAAC/1005, 2011. a
Walvoord, M. A., Phillips, F. M., Stonestrom, D. A., Evans, R. D., Hartsough,
P. C., Newman, B. D., and Striegl, R. G.: A Reservoir of Nitrate Beneath
Desert Soils, Science, 302, 1021–1024, https://doi.org/10.1126/science.1086435, 003. a
Warszawski, L., Friend, A., Ostberg, S., Frieler, K., Lucht, W., Schaphoff,
S., Beerling, D., Cadule, P., Ciais, P., Clark, D. B., Kahana, R., Ito, A.,
Keribin, R., Kleidon, A., Lomas, M., Nishina, K., Pavlick, R., Rademacher,
T. T., Buechner, M., Piontek, F., Schewe, J., Serdeczny, O., and
Schellnhuber, H. J.: A multi-model analysis of risk of ecosystem shifts under
climate change, Environ. Res. Lett., 8, 044018,
https://doi.org/10.1088/1748-9326/8/4/044018, 2013.
a
White, M. A., Thornton, P. E., Running, S. W., and Nemani, R. R.:
Parameterization and Sensitivity Analysis of the BIOME–BGC Terrestrial
Ecosystem Model: Net Primary Production Controls, Earth Interact., 4, 1–85,
https://doi.org/10.1175/1087-3562(2000)004<0003:PASAOT>2.0.CO;2, 2000. a, b
Wieder, W. R., Cleveland, C. C., Smith, W. K., and Todd-Brown, K.: Future
productivity and carbon storage limited by terrestrial nutrient availability,
Nat. Geosci., 8, 441–444, https://doi.org/10.1038/ngeo2413, 2015. a
Willis, C. G., Halina, M., Lehman, C., Reich, P. B., Keen, A., McCarthy, S.,
and Cavender-Bares, J.: Phylogenetic community structure in Minnesota oak
savanna is influenced by spatial extent and environmental variation,
Ecography, 33, 565–577, https://doi.org/10.1111/j.1600-0587.2009.05975.x,
2010. a
Willmott, C. J.: Some comments on the evaluation of model performance, B. Am.
Meteorol. Soc., 63, 1309–1313,
https://doi.org/10.1175/1520-0477(1982)063<1309:SCOTEO>2.0.CO;2, 1982. a
Xu, L. and Baldocchi, D.: Seasonal trends in photosynthetic parameters and
stomatal conductance of blue oak (Quercus douglasii) under prolonged summer
drought and high temperature, Tree Physiol., 23, 865–877, 2003. a
Xu-Ri and Prentice, I. C.: Terrestrial nitrogen cycle simulation with a
dynamic global vegetation model, Glob. Change Biol., 14, 1745–1764,
https://doi.org/10.1111/j.1365-2486.2008.01625.x, 2008. a, b, c
Zaehle, S. Jones, C. D., Houlton, B., Lamarque, J.-F., and Robertson, E.:
Nitrogen availability reduces CMIP5 projections of twenty-first-century land
carbon uptake, J. Climate, 28, 2494–2511, https://doi.org/10.1175/JCLI-D-13-00776.1,
2015. a
Zaehle, S., Friend, A. D., Friedlingstein, P., Dentener, F., Peylin, P., and
Schulz, M.: Carbon and nitrogen cycle dynamics in the O-CN land surface
model: 2. Role of the nitrogen cycle in the historical terrestrial carbon
balance, Global Biogeochem. Cy., 24, GB1006, https://doi.org/10.1029/2009GB003522,
2010a. a, b
Zaehle, S., Sitch, S., Prentice, I. C., Liski, J., Cramer, W., Erhard, M.,
Hickler, T., and Smith, B.: The importance of age-related decline in forest
NPP for modeling regional carbon balances, Ecol. Appl., 16, 1555–1574,
https://doi.org/10.1890/1051-0761(2006)016<1555:TIOADI>2.0.CO;2, 2010b. a, b
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.
The dynamics of the terrestrial carbon cycle are of central importance for Earth system science....
Special issue