Articles | Volume 10, issue 1
https://doi.org/10.5194/bg-10-339-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-10-339-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A model-based constraint on CO2 fertilisation
P. B. Holden
Environment, Earth and Ecosystems, Open University, Milton Keynes, UK
N. R. Edwards
Environment, Earth and Ecosystems, Open University, Milton Keynes, UK
D. Gerten
Potsdam Institute for Climate Impact Research, Potsdam, Germany
S. Schaphoff
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Related authors
Peng Sun, Philip B. Holden, and H. John B. Birks
Clim. Past, 20, 2373–2398, https://doi.org/10.5194/cp-20-2373-2024, https://doi.org/10.5194/cp-20-2373-2024, 2024
Short summary
Short summary
We develop the Multi Ensemble Machine Learning Model (MEMLM) for reconstructing palaeoenvironments from microfossil assemblages. The machine-learning approaches, which include random tree and natural language processing techniques, substantially outperform classical approaches under cross-validation, but they can fail when applied to reconstruct past environments. Statistical significance testing is found sufficient to identify these unreliable reconstructions.
Rémy Asselot, Philip B. Holden, Frank Lunkeit, and Inga Hense
Earth Syst. Dynam., 15, 875–891, https://doi.org/10.5194/esd-15-875-2024, https://doi.org/10.5194/esd-15-875-2024, 2024
Short summary
Short summary
Phytoplankton are tiny oceanic algae able to absorb the light penetrating the ocean. The light absorbed by these organisms is re-emitted as heat in the surrounding environment, a process commonly called phytoplankton light absorption (PLA). As a consequence, PLA increases the oceanic temperature. We studied this mechanism with a climate model under different climate scenarios. We show that phytoplankton light absorption is reduced under strong warming scenarios, limiting oceanic warming.
Negar Vakilifard, Richard G. Williams, Philip B. Holden, Katherine Turner, Neil R. Edwards, and David J. Beerling
Biogeosciences, 19, 4249–4265, https://doi.org/10.5194/bg-19-4249-2022, https://doi.org/10.5194/bg-19-4249-2022, 2022
Short summary
Short summary
To remain within the Paris climate agreement, there is an increasing need to develop and implement carbon capture and sequestration techniques. The global climate benefits of implementing negative emission technologies over the next century are assessed using an Earth system model covering a wide range of plausible climate states. In some model realisations, there is continued warming after emissions cease. This continued warming is avoided if negative emissions are incorporated.
Rémy Asselot, Frank Lunkeit, Philip B. Holden, and Inga Hense
Biogeosciences, 19, 223–239, https://doi.org/10.5194/bg-19-223-2022, https://doi.org/10.5194/bg-19-223-2022, 2022
Short summary
Short summary
Previous studies show that phytoplankton light absorption can warm the atmosphere, but how this warming occurs is still unknown. We compare the importance of air–sea heat versus CO2 flux in the phytoplankton-induced atmospheric warming and determine the main driver. To shed light on this research question, we conduct simulations with a climate model of intermediate complexity. We show that phytoplankton mainly warms the atmosphere by increasing the air–sea CO2 flux.
Rémy Asselot, Frank Lunkeit, Philip Holden, and Inga Hense
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-91, https://doi.org/10.5194/esd-2021-91, 2021
Revised manuscript not accepted
Short summary
Short summary
Phytoplankton absorbing light can influence the climate system but its future effect on the climate is still unclear. We use a climate model to investigate the role of phytoplankton light absorption under global warming. We find out that the effect of phytoplankton light absorption is smaller under a high greenhouse gas emissions compared to reduced and intermediate greenhouse gas emissions. Additionally, we show that phytoplankton light absorption is an important mechanism for the carbon cycle.
Sibyll Schaphoff, David Hötten, Christoph Müller, Dieter Gerten, Sebastian Ostberg, and Werner von Bloh
Geosci. Model Dev., 19, 7615–7651, https://doi.org/10.5194/gmd-19-7615-2026, https://doi.org/10.5194/gmd-19-7615-2026, 2026
Short summary
Short summary
Methane is a powerful driver of climate change, yet emissions from wetlands and farming remain uncertain. We improved a global vegetation model that links water, plants and soils to methane production and release. The model now captures waterlogged areas, methane creation and escape, and flood-tolerant plants. It reproduces global wetland patterns and emissions more realistically, helping assess how climate and land-use change may affect future methane release and improve climate projections.
Jannes Breier, Luana Schwarz, Hannah Prawitz, Werner von Bloh, Christoph Müller, Stephen Björn Wirth, Max Bechthold, Dieter Gerten, and Jonathan F. Donges
Geosci. Model Dev., 19, 6829–6855, https://doi.org/10.5194/gmd-19-6829-2026, https://doi.org/10.5194/gmd-19-6829-2026, 2026
Short summary
Short summary
We present a new modelling framework that combines simulations of environmental change and human decision-making in an integrated approach. It allows researchers to explore how farming decisions affect land, water, and climate, and how these environmental changes influence future decisions. By connecting people and nature, it helps investigate food security, climate adaptation, and sustainability challenges, and supports the development of more realistic scenarios of future environmental change.
Heindriken Dahlmann, Lauren S. Andersen, Sibyll Schaphoff, Fabian Stenzel, Johanna Braun, Christoph Müller, and Dieter Gerten
Hydrol. Earth Syst. Sci., 30, 3185–3201, https://doi.org/10.5194/hess-30-3185-2026, https://doi.org/10.5194/hess-30-3185-2026, 2026
Short summary
Short summary
Green water stress can negatively affect agricultural production and is often mitigated through irrigation. In this global modelling study, we investigate where and to what extent the implementation of irrigation helps to compensate for green water stress but at the same time leads to an increase in blue water scarcity. Our findings highlight the need to consider both water stresses together, along with their dynamic interactions, for sustainable water management.
Dieter Gerten, Bruna Almeida, Steven J. Lade, and Anna Norberg
EGUsphere, https://doi.org/10.5194/egusphere-2025-4761, https://doi.org/10.5194/egusphere-2025-4761, 2025
Short summary
Short summary
Transgression of planetary boundaries increases the risk of Earth system destabilization, in particular as the impacts may compound each other. This Perspective unravels processes underlying interactions between the planetary boundaries for freshwater change, climate change and land-system change. It proposes a systematic model-based assessment of drivers and impacts of their interactions, emphasising the need to maintain multiple boundaries collectively so as to avoid uncontrolled feedbacks.
Luana Schwarz, Jannes Breier, Hannah Prawitz, Max Bechthold, Werner von Bloh, Sara M. Constantino, Dieter Gerten, Jobst Heitzig, Ronja Hotz, Leander John, Christoph Müller, Johan Rockström, and Jonathan F. Donges
EGUsphere, https://doi.org/10.5194/egusphere-2025-4079, https://doi.org/10.5194/egusphere-2025-4079, 2025
Short summary
Short summary
We present a novel global model that links farmer decisions with ecological processes to explore how agricultural systems co-evolve. Unlike previous tools, it captures feedbacks between society and nature at up-to planetary scale. We find that conservation practices can restore soil health and support stable harvests. Adoption spreads through learning and norms, showing how regeneration at the farm scale can ripple outward, contributing to global sustainability and Earth system resilience.
Arne Tobian, Sarah Cornell, Ingo Fetzer, Dieter Gerten, and Johan Rockström
EGUsphere, https://doi.org/10.5194/egusphere-2025-2202, https://doi.org/10.5194/egusphere-2025-2202, 2025
Short summary
Short summary
The land use change reallocation tool LUCATOO enables the creation of future land use change scenario datasets tailored to specific requirements in model study applications. Its usability is demonstrated in the planetary boundaries interaction context. Being written in the programming language R and made openly accessible, LUCATOO can be easily adapted to be employed in contexts other than the planetary boundaries framework.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
Short summary
Short summary
We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Peng Sun, Philip B. Holden, and H. John B. Birks
Clim. Past, 20, 2373–2398, https://doi.org/10.5194/cp-20-2373-2024, https://doi.org/10.5194/cp-20-2373-2024, 2024
Short summary
Short summary
We develop the Multi Ensemble Machine Learning Model (MEMLM) for reconstructing palaeoenvironments from microfossil assemblages. The machine-learning approaches, which include random tree and natural language processing techniques, substantially outperform classical approaches under cross-validation, but they can fail when applied to reconstruct past environments. Statistical significance testing is found sufficient to identify these unreliable reconstructions.
Rémy Asselot, Philip B. Holden, Frank Lunkeit, and Inga Hense
Earth Syst. Dynam., 15, 875–891, https://doi.org/10.5194/esd-15-875-2024, https://doi.org/10.5194/esd-15-875-2024, 2024
Short summary
Short summary
Phytoplankton are tiny oceanic algae able to absorb the light penetrating the ocean. The light absorbed by these organisms is re-emitted as heat in the surrounding environment, a process commonly called phytoplankton light absorption (PLA). As a consequence, PLA increases the oceanic temperature. We studied this mechanism with a climate model under different climate scenarios. We show that phytoplankton light absorption is reduced under strong warming scenarios, limiting oceanic warming.
Markus Drüke, Wolfgang Lucht, Werner von Bloh, Stefan Petri, Boris Sakschewski, Arne Tobian, Sina Loriani, Sibyll Schaphoff, Georg Feulner, and Kirsten Thonicke
Earth Syst. Dynam., 15, 467–483, https://doi.org/10.5194/esd-15-467-2024, https://doi.org/10.5194/esd-15-467-2024, 2024
Short summary
Short summary
The planetary boundary framework characterizes major risks of destabilization of the Earth system. We use the comprehensive Earth system model POEM to study the impact of the interacting boundaries for climate change and land system change. Our study shows the importance of long-term effects on carbon dynamics and climate, as well as the need to investigate both boundaries simultaneously and to generally keep both boundaries within acceptable ranges to avoid a catastrophic scenario for humanity.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
Short summary
Short summary
In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Sebastian Ostberg, Christoph Müller, Jens Heinke, and Sibyll Schaphoff
Geosci. Model Dev., 16, 3375–3406, https://doi.org/10.5194/gmd-16-3375-2023, https://doi.org/10.5194/gmd-16-3375-2023, 2023
Short summary
Short summary
We present a new toolbox for generating input datasets for terrestrial ecosystem models from diverse and partially conflicting data sources. The toolbox documents the sources and processing of data and is designed to make inconsistencies between source datasets transparent so that users can make their own decisions on how to resolve these should they not be content with our default assumptions. As an example, we use the toolbox to create input datasets at two different spatial resolutions.
Chinchu Mohan, Tom Gleeson, James S. Famiglietti, Vili Virkki, Matti Kummu, Miina Porkka, Lan Wang-Erlandsson, Xander Huggins, Dieter Gerten, and Sonja C. Jähnig
Hydrol. Earth Syst. Sci., 26, 6247–6262, https://doi.org/10.5194/hess-26-6247-2022, https://doi.org/10.5194/hess-26-6247-2022, 2022
Short summary
Short summary
The relationship between environmental flow violations and freshwater biodiversity at a large scale is not well explored. This study intended to carry out an exploratory evaluation of this relationship at a large scale. While our results suggest that streamflow and EF may not be the only determinants of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods or with other biodiversity data or metrics.
Negar Vakilifard, Richard G. Williams, Philip B. Holden, Katherine Turner, Neil R. Edwards, and David J. Beerling
Biogeosciences, 19, 4249–4265, https://doi.org/10.5194/bg-19-4249-2022, https://doi.org/10.5194/bg-19-4249-2022, 2022
Short summary
Short summary
To remain within the Paris climate agreement, there is an increasing need to develop and implement carbon capture and sequestration techniques. The global climate benefits of implementing negative emission technologies over the next century are assessed using an Earth system model covering a wide range of plausible climate states. In some model realisations, there is continued warming after emissions cease. This continued warming is avoided if negative emissions are incorporated.
Vili Virkki, Elina Alanärä, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu
Hydrol. Earth Syst. Sci., 26, 3315–3336, https://doi.org/10.5194/hess-26-3315-2022, https://doi.org/10.5194/hess-26-3315-2022, 2022
Short summary
Short summary
Direct and indirect human actions have altered streamflow across the world since pre-industrial times. Here, we apply a method of environmental flow envelopes (EFEs) that develops the existing global environmental flow assessments by methodological advances and better consideration of uncertainty. By assessing the violations of the EFE, we comprehensively quantify the frequency, severity, and trends of flow alteration during the past decades, illustrating anthropogenic effects on streamflow.
Vera Porwollik, Susanne Rolinski, Jens Heinke, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Biogeosciences, 19, 957–977, https://doi.org/10.5194/bg-19-957-2022, https://doi.org/10.5194/bg-19-957-2022, 2022
Short summary
Short summary
The study assesses impacts of grass cover crop cultivation on cropland during main-crop off-season periods applying the global vegetation model LPJmL (V.5.0-tillage-cc). Compared to simulated bare-soil fallowing practices, cover crops led to increased soil carbon content and reduced nitrogen leaching rates on the majority of global cropland. Yield responses of main crops following cover crops vary with location, duration of altered management, crop type, water regime, and tillage practice.
Rémy Asselot, Frank Lunkeit, Philip B. Holden, and Inga Hense
Biogeosciences, 19, 223–239, https://doi.org/10.5194/bg-19-223-2022, https://doi.org/10.5194/bg-19-223-2022, 2022
Short summary
Short summary
Previous studies show that phytoplankton light absorption can warm the atmosphere, but how this warming occurs is still unknown. We compare the importance of air–sea heat versus CO2 flux in the phytoplankton-induced atmospheric warming and determine the main driver. To shed light on this research question, we conduct simulations with a climate model of intermediate complexity. We show that phytoplankton mainly warms the atmosphere by increasing the air–sea CO2 flux.
Rémy Asselot, Frank Lunkeit, Philip Holden, and Inga Hense
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-91, https://doi.org/10.5194/esd-2021-91, 2021
Revised manuscript not accepted
Short summary
Short summary
Phytoplankton absorbing light can influence the climate system but its future effect on the climate is still unclear. We use a climate model to investigate the role of phytoplankton light absorption under global warming. We find out that the effect of phytoplankton light absorption is smaller under a high greenhouse gas emissions compared to reduced and intermediate greenhouse gas emissions. Additionally, we show that phytoplankton light absorption is an important mechanism for the carbon cycle.
Cited articles
Arora, V. K. and Montenegro, A.: Small temperature benefits provided by realistic afforestation efforts, Nat. Geosci., 4, 514–518, https://doi.org/10.1038/NGEO1182, 2011.
Beer, C., Reichstein, M., Tomelieri, E., Ciais, P., Jung, M., Carvalhais, N., Rödenbeck, C., Altaf Arain, M., Baldocchi, D., Bonan, G. B., Bondeau, A., Cescatti, A., Lasslop, G., Lindroth, A., Lomas, M., Luyssaert, S., Margolis, H., Oleson, K. W., Roupsard, O., Veenendaal, E., Viovy, N., Williams, C., Woodward, F. I., and Papale, D.: Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate, Science, 329, 834–838, https://doi.org/10.1126/science.1184984, 2010.
Betts, R. A.: Offset of the potential carbon sink from boreal reforestation by decreases in surface albedo, Nature, 408, 187–190, 2000.
Betts, R. A., Boucher, O., Collins, M., Cox, P. M., Falloon, P. D., Gedney, N., Hemming, D. L., Huntingford, C., Jones, C. D., Sexton, D. M. H., and Webb, M. J: Projected increase in continental runoff due to plant responses to increasing carbon dioxide, Nature, 448, 1037–1042, https://doi.org/10.1038/nature06045, 2007.
Bonan, G. B. and Levis, S.: Quantifying carbon-nitrogen feedbacks in the Community Land Model (CLM4), Geophys. Res. Lett., 37, L07401, https://doi.org/10.1029/2010GL042430, 2010.
Bond, W. J., Midgely, G. F., and Woodward, F. I.: The importance of low atmospheric CO2 and fire in promoting the spread of grasslands and savannas, Glob. Change Biol., 9, 973–982, https://doi.org/10.1046/j.1365-2486.2003.00577.x, 2003.
Bondeau, A., Smith, P. C., Zaehle, S., Schaphoff, S., Lucht, W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679–706, https://doi.org/10.1111/j.1365-2486.2006.01305.x, 2007.
Broecker, W. S., Takahashi, T., Simpson, H. J., and Peng, T.-H.: Fate of fossil fuel carbon dioxide and the global carbon budget, Science, 206, 4417, 409–418, http://www.jstor.org.libezproxy.open.ac.uk/stable/1749304, 1979.
Denman, K. L., Brasseur, G., Chidthaisong, A., Ciais, P., Cox, P. M., Dickinson, R. E., Hauglustaine, D., Heinze, C., Holland, E., Jacob, D., Lohmann, U., Ramachandran, S., da Silva Dias, P. L., Wofsy, S. C., and Zhang, X.: Couplings between changes in the climate system and biogeochemistry, in: Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, UK and New York, USA, 2007.
Eby, M., Weaver, A. J., Alexander, K., Zickfeld, K., Abe-Ouchi, A., Cimatoribus, A. A., Crespin, E., Drijfhout, S. S., Edwards, N. R., Eliseev, A. V., Feulner, G., Fichefet, T., Forest, C. E., Goosse, H., Holden, P. B., Joos, F., Kawamiya, M., Kicklighter, D., Kienert, H., Matsumoto, K., Mokhov, I. I., Monier, E., Olsen, S. M., Pedersen, J. O. P., Perrette, M., Philippon-Berthier, G., Ridgwell, A., Schlosser, A., Schneider von Deimling, T., Shaffer, G., Smith, R. S., Spahni, R., Sokolov, A. P., Steinacher, M., Tachiiri, K., Tokos, K., Yoshimori, M., Zeng, N., and Zhao, F.: Historical and idealized climate model experiments: an EMIC intercomparison, Clim. Past Discuss., 8, 4121–4181, https://doi.org/10.5194/cpd-8-4121-2012, 2012.
Edwards, N. R., Cameron, D., and Rougier, J.: Precalibrating an intermediate complexity climate model, Clim. Dynam., 37, 1469–1482, https://doi.org/10.1007/s00382-010-0921-0, 2011.
Fader, M., Rost, S., Müller, C., Bondeau, A., and Gerten, A.: Virtual water content of temperate cereals and maize: Present and potential future patterns, J. Hydrol., 384, 218–231, https://doi.org/10.1016/j.jhydrol.2009.12.011, 2010.
Field, C. B., Jackson, R. B., and Mooney, H. A.: Stomatal responses to increased CO2: implications from the plant to the global scale, Plant Cell Environ., 18, 1214–1225, 1995.
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V., Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C., Joos, F., Kato, F., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D., Raddatz, T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K.-G., Schnur, R., Strassman, K., Weaver, A. J., Yoshikawa, C., and Zeng, N.: Climate-carbon cycle feedback analysis: results from the C4MIP model intercomparison, J. Climate, 19, 3337–3353, https://doi.org/http://dx.doi.org/10.1175/JCLI3800.1, 2006.
Girardin, M. P., Bernier, P. Y., Raulier, F., Tardif, J. C., Conciatori, F., and Guo, X. J.: Testing for a CO2 fertilisation effect on growth of Canadian boreal forests, J. Geophys. Res., 116, G01012, https://doi.org/10.1029/2010JG001287, 2011.
Hansen, F. V.: Albedos, U.S Army Research Laboratory Report number ARL-TR-57, 1993.
Hickler, T., Smith, B., Prentice, I. C., Mjöfors, K., Miller, P., Arneth, A., and Sykes, M. Y.: CO2 fertilisation in temperate FACE experiments not representative of boreal and tropical forests, Glob. Change Biol., 14, 1531–1542, https://doi.org//j.1365-2486.2008.01598.x, 2008.
Holden, P. B., Edwards, N. R., Oliver, K. I. C., Lenton, T. M., and Wilkinson, R. D.: A probabilistic calibration of climate sensitivity and terrestrial carbon change in GENIE-1, Clim. Dynam., 35, 785–806, https://doi.org/10.1007/s00382-009-0630-8, 2010.
Holden, P. B., Edwards, N. R., Müller, S. A., Oliver, K. I. C., Death, R. M., and Ridgwell, A.: Controls on the spatial distribution of oceanic δ13C$_\text{DIC}$, Biogeosciences Discuss., 9, 11843–11883, https://doi.org/10.5194/bgd-9-11843-2012, 2012.
Houghton, R. A.: Carbon flux to the atmosphere from land-use changes: 1850–2005, in: TRENDS: A Compendium of Data on Global Change, Carbon Dioxide Information Analysis Centre, Oak Ridge National Laboratory, Tennessee, 2008.
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J., Fischer, G., Fisk, J. P., Hibbard, K., Houghton, R. A., Janetos, A., Jones, C. D., Kindermann, G., Kinoshita, T., Klein Goldewijk, K., Riahi, K., Shevliakova, E., Smith, S., Stehfest, E., Thomson, A., Thornton, P., van Vuuren, D. P., and Wang, Y. P.: Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands, Climatic Change, 109, 117–161, https://doi.org/10.1007/s10584-011-0153-2, 2011.
Janssens, I. A., Freibauer, A., Schlamadinger, B., Ceulemans, R., Ciais, P., Dolman, A. J., Heimann, M., Nabuurs, G.-J., Smith, P., Valentini, R., and Schulze, E.-D.: The carbon budget of terrestrial ecosystems at country-scale – a European case study, Biogeosciences, 2, 15–26, https://doi.org/10.5194/bg-2-15-2005, 2005.
Joos, F., Meyer, R., Bruno, M., and Leuenberger, M.: The variability in the carbon sinks as reconstructed for the last 1000 years, Geophys. Res. Lett., 26, 1437–1440, https://doi.org/10.1029/1999GL900250, 1999.
Joos, F., Roth, R., Fuglestvedt, J. S., Peters, G. P., Enting, I. G., von Bloh, W., Brovkin, V., Burke, E. J., Eby, M., Edwards, N. R., Friedrich, T., Frölicher, T. L., Halloran, P. R., Holden, P. B., Jones, C., Kleinen, T., Mackenzie, F., Matsumoto, K., Meinshausen, M., Plattner, G.-K., Reisinger, A., Segschneider, J., Shaffer, G., Steinacher, M., Strassmann, K., Tanaka, K., Timmermann, A., and Weaver, A. J.: Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis, Atmos. Chem. Phys. Discuss., 12, 19799–19869, https://doi.org/10.5194/acpd-12-19799-2012, 2012.
Koerner, C.: Plant CO2 responses: an issue of definition, time and resource supply, New Phytologist, 172, 393–411, https://doi.org/10.1111/j.1469-8137.2006.01886.x, 2006.
Le Quéré, C., Raupach, M. R., Canadell, J. G., Marland, G., Bopp, L., Ciais, P., Conway, T. J., Doney, S. C., Feely, R. A., Foster, P., Friedlingstein, P., Gurney, K., Houghton, R. A., House, J. I., Huntingford, C., Levy, P. E. Lomas, M. R., Majkut, J., Metzl, N., Ometto, J. P., Peters, G. P., Prentice, I. C., Randerson, J. T., Running, S. W., Sarmiento, J. L., Schuster, U., Sitch, S., Takahashi, T., Viovy, N., van der Werf, G. R., and Woodward, F. I.: Trends in the sources and sinks of carbon dioxide, Nat. Geosci., 2, 831–836, https://doi.org/10.1038/ngeo689, 2009.
Leipprand, A. and Gerten, D.: Global effects of doubled atmospheric CO2 content on evapotranspiration, soil moisture and runoff under potential vegetation, Hydrol. Sci., 51, 171–185, https://doi.org/10.1623/hysj.51.1.171, 2006.
Lenton, T. M., Williamson, M. S., Edwards, N. R., Marsh, R., Price, A. R., Ridgwell, A. J., Shepherd, J. G., Cox, S. J., and The GENIE team: Millennial timescale carbon cycle and climate change in an efficient Earth system model, Clim. Dynam., 26, 687–711, https://doi.org/10.1007/s00382-006-0109-9, 2006.
Marsh, R., Müller, S. A., Yool, A., and Edwards, N. R.: Incorporation of the C-GOLDSTEIN efficient climate model into the GENIE framework: "eb_go_gs" configurations of GENIE, Geosci. Model Dev., 4, 957–992, https://doi.org/10.5194/gmd-4-957-2011, 2011.
Mitchell, T. D. and Jones, P. D.: An improved method of constructing a database of monthly climate observations and associated high-resolution grids, Int. J. Climatol., 25, 693–712, https://doi.org/10.1002/joc.1181, 2005.
Murphy, J. M., Booth, B. B. B., Collins, M., Harris, G. R., Sexton, D. M. H., and Webb, M. J.: A methodology for probabilistic predictions of regional climate change from perturbed physics ensembles, Phil. Trans. R. Soc. A, 365, 1993–2028, https://doi.org/10.1098/rsta.2007.2077, 2007.
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., Pregizter, 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, Proc. Natl. Aca. Sci. USA, 102, 18052–18056, https://doi.org/10.1073/pnas.0509478102, 2005.
Norby, R. J., Warren, J. M., Iversen, C. M., Garten, C. T., Medlyn, B. E., and McMurtrie, R. E.: CO2 enhancement of forest productivity constrained by limited nitrogen availability, Proc. Natl. Acad. Sci. USA, 107, 19368–19373, https://doi.org/10.1073/pnas.1006463107, 2010.
Olofsson, J. and Hickler, T.: Effects of human land-use on the global carbon cycle during the last 6,000 years, Veget. Hist. Archaeobot., 17, 605–615, https://doi.org/10.1007/s00334-007-0126-6, 2008.
Pongratz, J., Reick, C., Raddatz, T., and Claussen, M.: A reconstruction of global agricultural areas and land cover for the last millennium, Global Biogeochem. Cy., 22, GB3018, https://doi.org/10.1029/2007GB003153, 2008.
Raddatz, T.: Historical landcover change and wood harvest CO2 emissions, MPI for Meteorology, Hamburg, Germany, available at: www.mpimet.mpg.de/en/science/the-land-in-the-earth-system/climate-biogeosphere-interaction/landuse-change-emission-data.html (last access: 23 January 2013)), 2010.
Ridgwell, A. and Hargreaves, J.: Regulation of atmospheric CO2 by deep-sea sediments in an Earth system model, Global Biogeochem. Cy., 21, GB2008, https://doi.org/10.1029/2006GB002764, 2007.
Ridgwell, A., Hargreaves, J. C., Edwards, N. R., Annan, J. D., Lenton, T. M., Marsh, R., Yool, A., and Watson, A.: Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling, Biogeosciences, 4, 87–104, https://doi.org/10.5194/bg-4-87-2007, 2007.
Rougier, J.: Probabilistic inference for future climate using an ensemble of climate model evaluations, Climate Change, 82, 247–264, https://doi.org/10.1007/s10584-006-9156-9, 2007.
Sabine, C., Feely, R. A., Gruber, N., Key, R. M., Lee, K., Bullister, J. L., Wanninkhof, R., Wong, C. S., Wallace, D. W. R., Tilbrook, B., Millero, F. J., Peng, T.-H., Kozyr, A., Ono, T., and Rios, A. F.: The oceanic sink for anthropogenic CO2, Science, 305, 367–371, https://doi.org/10.1126/science.1097403, 2004.
Siegenthaler, U. and Oeschger, H.: Biospheric CO2 emissions during the past 200 years reconstructed by deconvolution of ice core data, Tellus, 39B, 140–154, https://doi.org/10.1111/j.1600-0889.1987.tb00278.x, 1987.
Sitch, S., Smith, B., Prentice, C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonike, 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.
Smith, B., Prentice, I. C., and Sykes, M. T.: Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space, Glob. Ecol. Biogeogr., 10, 621–637, https://doi.org/10.1046/j.1466-822X.2001.t01-1-00256.x, 2001.
Stocker, B. D., Strassmann, K., and Joos, F.: Sensitivity of Holocene atmospheric CO2 and the modern carbon budget to early human land use: analyses with a process-based model, Biogeosciences, 8, 69–88, https://doi.org/10.5194/bg-8-69-2011, 2011.
Waha, K., van Bussel, L. G. J., Müller, C., and Bondeau, A.: Climate-driven simulation of global crop sowing dates, Glob. Ecol. Biogeogr., 21, 247–259, https://doi.org/ 10.1111/j.1466-8238.2011.00678.x, 2012.
Williamson, M. S., Lenton, T. M., Shepherd, J. G., and Edwards, N. R.: An efficient numerical terrestrial scheme (ENTS) for Earth system modelling, Ecol. Model., 198, 362–374, https://doi.org/10.1016/j.ecolmodel.2006.05.027, 2006.
Altmetrics
Final-revised paper
Preprint