Articles | Volume 8, issue 4
https://doi.org/10.5194/esd-8-1191-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/esd-8-1191-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
19 Dec 2017
Research article |
| 19 Dec 2017
Future supply and demand of net primary production in the Sahel
Florian Sallaba
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
Stefan Olin
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
Kerstin Engström
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
Abdulhakim M. Abdi
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
Niklas Boke-Olén
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
Veiko Lehsten
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
Jonas Ardö
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
Jonathan W. Seaquist
CORRESPONDING AUTHOR
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
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Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billdesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Gharun Mana, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2024-165, https://doi.org/10.5194/egusphere-2024-165, 2024
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The movement of water, carbon, and energy from the earth surface to the atmosphere, or flux, is an important process to understand that impacts all of our lives. Here we outline a method to estimate global water and CO2 fluxes based on direct measurements from site around the world called FLUXCOM-X. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
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Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
David Martín Belda, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth
Geosci. Model Dev., 15, 6709–6745, https://doi.org/10.5194/gmd-15-6709-2022, https://doi.org/10.5194/gmd-15-6709-2022, 2022
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We present a number of augmentations to the ecosystem model LPJ-GUESS, which will allow us to use it in studies of the interactions between the land biosphere and the climate. The new module enables calculation of fluxes of energy and water into the atmosphere that are consistent with the modelled vegetation processes. The modelled fluxes are in fair agreement with observations across 21 sites from the FLUXNET network.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
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Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Deborah Zani, Veiko Lehsten, and Heike Lischke
Geosci. Model Dev., 15, 4913–4940, https://doi.org/10.5194/gmd-15-4913-2022, https://doi.org/10.5194/gmd-15-4913-2022, 2022
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The prediction of species migration under rapid climate change remains uncertain. In this paper, we evaluate the importance of the mechanisms underlying plant migration and increase the performance in the dynamic global vegetation model LPJ-GM 1.0. The improved model will allow us to understand past vegetation dynamics and predict the future redistribution of species in a context of global change.
Jianyong Ma, Sam S. Rabin, Peter Anthoni, Anita D. Bayer, Sylvia S. Nyawira, Stefan Olin, Longlong Xia, and Almut Arneth
Biogeosciences, 19, 2145–2169, https://doi.org/10.5194/bg-19-2145-2022, https://doi.org/10.5194/bg-19-2145-2022, 2022
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Improved agricultural management plays a vital role in protecting soils from degradation in eastern Africa. We simulated the impacts of seven management practices on soil carbon pools, nitrogen loss, and crop yield under different climate scenarios in this region. This study highlights the possibilities of conservation agriculture when targeting long-term environmental sustainability and food security in crop ecosystems, particularly for those with poor soil conditions in tropical climates.
Jianyong Ma, Stefan Olin, Peter Anthoni, Sam S. Rabin, Anita D. Bayer, Sylvia S. Nyawira, and Almut Arneth
Geosci. Model Dev., 15, 815–839, https://doi.org/10.5194/gmd-15-815-2022, https://doi.org/10.5194/gmd-15-815-2022, 2022
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The implementation of the biological N fixation process in LPJ-GUESS in this study provides an opportunity to quantify N fixation rates between legumes and to better estimate grain legume production on a global scale. It also helps to predict and detect the potential contribution of N-fixing plants as
green manureto reducing or removing the use of N fertilizer in global agricultural systems, considering different climate conditions, management practices, and land-use change scenarios.
Joel Dawson White, Lena Ström, Veiko Lehsten, Janne Rinne, and Dag Ahrén
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-353, https://doi.org/10.5194/bg-2021-353, 2022
Revised manuscript not accepted
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Microbes that produce CH4 play an important role to climate. Microbes which emit CH4 from wetlands is poorly understood. We observed that microbial community was of importance in explaining CH4 emission. We found, that microbes that produce CH4 hold the ability to produce and consume CH4 in multiple ways. This is important in terms of future climate scenarios, where wetlands are expected to shift. Therefore, we expect the community to be highly adaptive to future climate scenarios.
Adrian Gustafson, Paul A. Miller, Robert G. Björk, Stefan Olin, and Benjamin Smith
Biogeosciences, 18, 6329–6347, https://doi.org/10.5194/bg-18-6329-2021, https://doi.org/10.5194/bg-18-6329-2021, 2021
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We performed model simulations of vegetation change for a historic period and a range of climate change scenarios at a high spatial resolution. Projected treeline advance continued at the same or increased rates compared to our historic simulation. Temperature isotherms advanced faster than treelines, revealing a lag in potential vegetation shifts that was modulated by nitrogen availability. At the year 2100 projected treelines had advanced by 45–195 elevational metres depending on the scenario.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
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The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Anteneh Getachew Mengistu, Gizaw Mengistu Tsidu, Gerbrand Koren, Maurits L. Kooreman, K. Folkert Boersma, Torbern Tagesson, Jonas Ardö, Yann Nouvellon, and Wouter Peters
Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, https://doi.org/10.5194/bg-18-2843-2021, 2021
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In this study, we assess the usefulness of Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval (SIFTER) data from the GOME-2A instrument and near-infrared reflectance of vegetation (NIRv) from MODIS to capture the seasonality and magnitudes of gross primary production (GPP) derived from six eddy-covariance flux towers in Africa in the overlap years between 2007–2014. We also test the robustness of sun-induced fluoresence and NIRv to compare the seasonality of GPP for the major biomes.
Wim Verbruggen, Guy Schurgers, Stéphanie Horion, Jonas Ardö, Paulo N. Bernardino, Bernard Cappelaere, Jérôme Demarty, Rasmus Fensholt, Laurent Kergoat, Thomas Sibret, Torbern Tagesson, and Hans Verbeeck
Biogeosciences, 18, 77–93, https://doi.org/10.5194/bg-18-77-2021, https://doi.org/10.5194/bg-18-77-2021, 2021
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A large part of Earth's land surface is covered by dryland ecosystems, which are subject to climate extremes that are projected to increase under future climate scenarios. By using a mathematical vegetation model, we studied the impact of single years of extreme rainfall on the vegetation in the Sahel. We found a contrasting response of grasses and trees to these extremes, strongly dependent on the way precipitation is spread over the rainy season, as well as a long-term impact on CO2 uptake.
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
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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.
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
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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.
Veiko Lehsten, Michael Mischurow, Erik Lindström, Dörte Lehsten, and Heike Lischke
Geosci. Model Dev., 12, 893–908, https://doi.org/10.5194/gmd-12-893-2019, https://doi.org/10.5194/gmd-12-893-2019, 2019
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To assess the effect of climate on vegetation, dynamic vegetation models simulate their response e.g. to climate change. Most currently used dynamic vegetation models ignore the fact that for colonization of a new area not only do the climatic conditions have to be suitable, but seeds also need to arrive at the site to allow the species to migrate there. In this paper we are developing a novel method which allows us to simulate migration within dynamic vegetation models even at large scale.
Kerstin Engström, Mats Lindeskog, Stefan Olin, John Hassler, and Benjamin Smith
Earth Syst. Dynam., 8, 773–799, https://doi.org/10.5194/esd-8-773-2017, https://doi.org/10.5194/esd-8-773-2017, 2017
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Applying a global carbon tax on fossil was shown to lead to increased bioenergy production in four out of five scenarios. Increased bioenergy production led to global cropland changes that were up to 50 % larger by 2100 compared to the reference case (without global carbon tax). For scenarios with strong cropland expansion due to high population growth coupled with low technological change or bioenergy production, the biosphere was simulated to switch from a carbon sink into a carbon source.
Christoph Müller, Joshua Elliott, James Chryssanthacopoulos, Almut Arneth, Juraj Balkovic, Philippe Ciais, Delphine Deryng, Christian Folberth, Michael Glotter, Steven Hoek, Toshichika Iizumi, Roberto C. Izaurralde, Curtis Jones, Nikolay Khabarov, Peter Lawrence, Wenfeng Liu, Stefan Olin, Thomas A. M. Pugh, Deepak K. Ray, Ashwan Reddy, Cynthia Rosenzweig, Alex C. Ruane, Gen Sakurai, Erwin Schmid, Rastislav Skalsky, Carol X. Song, Xuhui Wang, Allard de Wit, and Hong Yang
Geosci. Model Dev., 10, 1403–1422, https://doi.org/10.5194/gmd-10-1403-2017, https://doi.org/10.5194/gmd-10-1403-2017, 2017
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Crop models are increasingly used in climate change impact research and integrated assessments. For the Agricultural Model Intercomparison and Improvement Project (AgMIP), 14 global gridded crop models (GGCMs) have supplied crop yield simulations (1980–2010) for maize, wheat, rice and soybean. We evaluate the performance of these models against observational data at global, national and grid cell level. We propose an open-access benchmark system against which future model versions can be tested.
Torbern Tagesson, Jonas Ardö, Bernard Cappelaere, Laurent Kergoat, Abdulhakim Abdi, Stéphanie Horion, and Rasmus Fensholt
Biogeosciences, 14, 1333–1348, https://doi.org/10.5194/bg-14-1333-2017, https://doi.org/10.5194/bg-14-1333-2017, 2017
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Vegetation growth in semi-arid regions is an important sink for human-induced fossil fuel emissions of CO2 and this study addresses the strong need for improved understanding and spatially explicit estimates of CO2 uptake by semi-arid ecosystems. We show that a model incorporating photosynthetic parameters upscaled using satellite-based earth observation simulates CO2 uptake well for the Sahel, one of the largest semi-arid regions in the world.
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
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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.
Kerstin Engström, Stefan Olin, Mark D. A. Rounsevell, Sara Brogaard, Detlef P. van Vuuren, Peter Alexander, Dave Murray-Rust, and Almut Arneth
Earth Syst. Dynam., 7, 893–915, https://doi.org/10.5194/esd-7-893-2016, https://doi.org/10.5194/esd-7-893-2016, 2016
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The development of global cropland in the future depends on how many people there will be, how much meat and milk we will eat, how much food we will waste and how well farms will be managed. Uncertainties in these factors mean that global cropland could decrease from today's 1500 Mha to only 893 Mha in 2100, which would free land for biofuel production. However, if population rises towards 12 billion and global yields remain low, global cropland could also increase up to 2380 Mha in 2100.
Almut Arneth, Risto Makkonen, Stefan Olin, Pauli Paasonen, Thomas Holst, Maija K. Kajos, Markku Kulmala, Trofim Maximov, Paul A. Miller, and Guy Schurgers
Atmos. Chem. Phys., 16, 5243–5262, https://doi.org/10.5194/acp-16-5243-2016, https://doi.org/10.5194/acp-16-5243-2016, 2016
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We study the potentially contrasting effects of enhanced ecosystem CO2 release in response to warmer temperatures vs. emissions of biogenic volatile organic compounds and their formation of secondary organic aerosol through a combination of measurements and modelling at a remote location in Eastern Siberia. The study aims to highlight the number of potentially opposing processes and complex interactions between vegetation physiology, soil processes and trace-gas exchanges in the climate system.
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
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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.
T. Tagesson, R. Fensholt, S. Huber, S. Horion, I. Guiro, A. Ehammer, and J. Ardö
Biogeosciences, 12, 4621–4635, https://doi.org/10.5194/bg-12-4621-2015, https://doi.org/10.5194/bg-12-4621-2015, 2015
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Relationships between ecosystem properties of semi-arid savanna and reflected solar radiance between 35 and 1800nm were investigated. Normalised combinations of reflectance for the near infrared, shortwave infrared, and 600 to 700nm were strongly affected by solar and viewing angle effects. Ecosystem properties of savannas were strongly correlated with reflectance at 350-1800nm, and normalised combinations of reflectance were strong predictors of the savanna ecosystem properties.
S. Olin, G. Schurgers, M. Lindeskog, D. Wårlind, B. Smith, P. Bodin, J. Holmér, and A. Arneth
Biogeosciences, 12, 2489–2515, https://doi.org/10.5194/bg-12-2489-2015, https://doi.org/10.5194/bg-12-2489-2015, 2015
M. Baudena, S. C. Dekker, P. M. van Bodegom, B. Cuesta, S. I. Higgins, V. Lehsten, C. H. Reick, M. Rietkerk, S. Scheiter, Z. Yin, M. A. Zavala, and V. Brovkin
Biogeosciences, 12, 1833–1848, https://doi.org/10.5194/bg-12-1833-2015, https://doi.org/10.5194/bg-12-1833-2015, 2015
P. Bodin, S. Olin, T. A. M. Pugh, and A. Arneth
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-5-1571-2014, https://doi.org/10.5194/esdd-5-1571-2014, 2014
Revised manuscript has not been submitted
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Food security is defined as stable access to food of good nutritional quality. In regions where food security is highly dependent on local production it is thus of importance to produce not only enough calories but also to minimize variation in yield. This trade-off is investigated here using simulated crop yield and by selecting relative distributions of crops. The results show a large potential to either increase food production or to decrease its variance by applying optimized crop selection.
A. Arneth, S. Olin, R. Makkonen, P. Paasonen, T. Holst, M. Kajos, M. Kulmala, T. Maximov, P. A. Miller, and G. Schurgers
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-19149-2014, https://doi.org/10.5194/acpd-14-19149-2014, 2014
Revised manuscript not accepted
M. Lindeskog, A. Arneth, A. Bondeau, K. Waha, J. Seaquist, S. Olin, and B. Smith
Earth Syst. Dynam., 4, 385–407, https://doi.org/10.5194/esd-4-385-2013, https://doi.org/10.5194/esd-4-385-2013, 2013
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Earth Syst. Dynam., 12, 1529–1542, https://doi.org/10.5194/esd-12-1529-2021, https://doi.org/10.5194/esd-12-1529-2021, 2021
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Mohammad M. Khabbazan and Hermann Held
Earth Syst. Dynam., 10, 135–155, https://doi.org/10.5194/esd-10-135-2019, https://doi.org/10.5194/esd-10-135-2019, 2019
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We find that for mitigation scenarios, prescribing atmosphere–ocean general circulation models' (AOGCMs') respective equilibrium climate sensitivities (ECSs) and transient climate responses (TCRs) to the one-box model results in too high global mean temperature projections due to the information loss resulting from the reduction of complexity. The one-box model offers a good emulator of these AOGCMs, provided the AOGCM's ECS and TCR values are mapped onto effective one-box counterparts.
Marcus C. Sarofim and Michael R. Giordano
Earth Syst. Dynam., 9, 1013–1024, https://doi.org/10.5194/esd-9-1013-2018, https://doi.org/10.5194/esd-9-1013-2018, 2018
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The 100-year GWP is the most widely used metric for comparing the climate impact of different gases such as methane and carbon dioxide. However, there have been recent arguments for the use of different timescales. This paper uses straightforward estimates of future damages to quantitatively determine the appropriate timescale as a function of how society discounts the future and finds that the 100-year timescale is consistent with commonly used discount rates.
Nicola Botta, Patrik Jansson, and Cezar Ionescu
Earth Syst. Dynam., 9, 525–542, https://doi.org/10.5194/esd-9-525-2018, https://doi.org/10.5194/esd-9-525-2018, 2018
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We study the impact of uncertainty on optimal greenhouse gas (GHG) emission policies for a stylized emission problem. The results suggest that uncertainties about the implementability of decisions on emission reductions (or increases) call for more precautionary policies. In contrast, uncertainties about the implications of exceeding critical cumulated emission thresholds tend to make early emission reductions less rewarding.
Kerstin Engström, Mats Lindeskog, Stefan Olin, John Hassler, and Benjamin Smith
Earth Syst. Dynam., 8, 773–799, https://doi.org/10.5194/esd-8-773-2017, https://doi.org/10.5194/esd-8-773-2017, 2017
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Applying a global carbon tax on fossil was shown to lead to increased bioenergy production in four out of five scenarios. Increased bioenergy production led to global cropland changes that were up to 50 % larger by 2100 compared to the reference case (without global carbon tax). For scenarios with strong cropland expansion due to high population growth coupled with low technological change or bioenergy production, the biosphere was simulated to switch from a carbon sink into a carbon source.
Joel C. Gill and Bruce D. Malamud
Earth Syst. Dynam., 7, 659–679, https://doi.org/10.5194/esd-7-659-2016, https://doi.org/10.5194/esd-7-659-2016, 2016
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Understanding interactions between hazards and other processes can help us to better understand the complex environment in which disasters occur. This enhanced understanding may help us to better manage hazards and reduce the risk of disasters occurring. Interactions (e.g. one hazard triggering another hazard) are noted between (i) natural hazards, such as earthquakes; (ii) human activity, such as groundwater abstraction; and (iii) technological hazards/disasters, such as building collapse.
A. M. Foley, P. B. Holden, N. R. Edwards, J.-F. Mercure, P. Salas, H. Pollitt, and U. Chewpreecha
Earth Syst. Dynam., 7, 119–132, https://doi.org/10.5194/esd-7-119-2016, https://doi.org/10.5194/esd-7-119-2016, 2016
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We introduce GENIEem-PLASIM-ENTSem (GPem), a climate-carbon cycle emulator, showing how model emulation can be used in integrated assessment modelling to resolve regional climate impacts and systematically capture uncertainty. In a case study, we couple GPem to FTT:Power-E3MG, a non-equilibrium economic model with technology diffusion. We find that when the electricity sector is decarbonised by 90 %, further emissions reductions must be achieved in other sectors to avoid dangerous climate change.
J. Karstensen, G. P. Peters, and R. M. Andrew
Earth Syst. Dynam., 6, 287–309, https://doi.org/10.5194/esd-6-287-2015, https://doi.org/10.5194/esd-6-287-2015, 2015
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We quantify uncertainties in estimates of global temperature change from regional and sectoral territorial- and consumption-based emissions. We find that the uncertainties are sensitive to the emission allocations, mix of pollutants, the metric used and its time horizon, and the level of aggregation of the results. Uncertainties in the final results are dominated by metric parameters and emission uncertainties, while the economic data appear to have small uncertainties at the national level.
D. J. L. Olivié and G. P. Peters
Earth Syst. Dynam., 4, 267–286, https://doi.org/10.5194/esd-4-267-2013, https://doi.org/10.5194/esd-4-267-2013, 2013
B. Aamaas, G. P. Peters, and J. S. Fuglestvedt
Earth Syst. Dynam., 4, 145–170, https://doi.org/10.5194/esd-4-145-2013, https://doi.org/10.5194/esd-4-145-2013, 2013
S. Hagemann, C. Chen, D. B. Clark, S. Folwell, S. N. Gosling, I. Haddeland, N. Hanasaki, J. Heinke, F. Ludwig, F. Voss, and A. J. Wiltshire
Earth Syst. Dynam., 4, 129–144, https://doi.org/10.5194/esd-4-129-2013, https://doi.org/10.5194/esd-4-129-2013, 2013
C. M. Torre and M. Selicato
Earth Syst. Dynam., 4, 51–61, https://doi.org/10.5194/esd-4-51-2013, https://doi.org/10.5194/esd-4-51-2013, 2013
C. Azar and D. J. A. Johansson
Earth Syst. Dynam., 3, 139–147, https://doi.org/10.5194/esd-3-139-2012, https://doi.org/10.5194/esd-3-139-2012, 2012
O. Boucher
Earth Syst. Dynam., 3, 49–61, https://doi.org/10.5194/esd-3-49-2012, https://doi.org/10.5194/esd-3-49-2012, 2012
Cited articles
Abdi, A. M., Seaquist, J., Tenenbaum, D. E., Eklundh, L., and Ardo, J.: The supply and demand of net primary production in the Sahel, Environ. Res. Lett., 9, 094003, https://doi.org/10.1088/1748-9326/9/9/094003, 2014.
Ahlström, A., Xia, J. Y., Arneth, A., Luo, Y., and Smith, B.: Importance of vegetation dynamics for future terrestrial carbon cycling, Environmental Research Letters, 10, 054019, https://doi.org/10.1088/1748-9326/10/8/089501, 2015.
Ahmed, S. A., Diffenbaugh, N. S., Hertel, T. W., and Martin, W. J.: Agriculture and Trade Opportunities for Tanzania: Past Volatility and Future Climate Change, Rev. Dev. Econ., 16, 429–447, 2012.
Alexander, P., Prestele, R., Verburg, P. H., Arneth, A., Baranzelli, C., Batista, E. S. F., Brown, C., Butler, A., Calvin, K., Dendoncker, N., Doelman, J. C., Dunford, R., Engstrom, K., Eitelberg, D., Fujimori, S., Harrison, P. A., Hasegawa, T., Havlik, P., Holzhauer, S., Humpenoder, F., Jacobs-Crisioni, C., Jain, A. K., Krisztin, T., Kyle, P., Lavalle, C., Lenton, T., Liu, J., Meiyappan, P., Popp, A., Powell, T., Sands, R. D., Schaldach, R., Stehfest, E., Steinbuks, J., Tabeau, A., van Meijl, H., Wise, M. A., and Rounsevell, M. D.: Assessing uncertainties in land cover projections, Glob. Change Biol., 3, 767–781, https://doi.org/10.1111/gcb.13447, 2016.
Ardö, J.: Comparison between remote sensing and a dynamic vegetation model for estimating terrestrial primary production of Africa, Carbon Balance and Management, 10, 8, https://doi.org/10.1186/s13021-015-0018-5, 2015.
Balogun, O., Yusuf, S., and Ayantoye, K.: The threats of climate change: implication for food crisis in sub-sahara Africa, in: Sustainable Food Security in the Era of Local and Global Environmental Change, edited by: Behnassi, M., Pollmann, O., and Kissinger, G., Springer, Dordrecht, 2013.
Barbier, B., Yacouba, H., Karambiri, H., Zoromé, M., and Somé, B.: Human Vulnerability to Climate Variability in the Sahel: Farmers' Adaptation Strategies in Northern Burkina Faso, Environ. Manage., 43, 790–803, 2009.
Boke-Olén, N., Abdi, A. M., Hall, O., and Lehsten, V.: High resolution population projections from radiative forcing and socio-economic models, 2000–2100, Scientific Data, 4, 160130, https://doi.org/10.1038/sdata.2016.130, 2017.
Brandt, M., Mbow, C., Diouf, A. A., Verger, A., Samimi, C., and Fensholt, R.: Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel, Glob. Change Biol., 21, 1610–1620, 2015.
Brown, M. E.: Remote sensing technology and land use analysis in food security assessment, Journal of Land Use Science, 11, 623–641, 2016.
Burnham, K. P. and Anderson, D. R.: Model Selection and Multimodal Inference. A Practical Information-Theoretic Approach, Springer, New York, 2002.
Campbell, M. M., Casterline, J., Castillo, F., Graves, A., Hall, T. L., May, J. F., Perlman, D., Potts, M., Speidel, J. J., Walsh, J., Wehner, M. F., and Zulu, E. M.: Population and climate change: who will the grand convergence leave behind?, The Lancet Global Health, 2, e253–e254, 2014.
Canadell, J. G. and Schulze, E. D.: Global potential of biospheric carbon management for climate mitigation, Nature Communications, 5, 5282, https://doi.org/10.1038/ncomms6282, 2014.
Ceccato, P., Cressman, K., Giannini, A., and Trzaska, S.: The desert locust upsurge in West Africa (2003–2005): Information on the desert locust early warning system and the prospects for seasonal climate forecasting, Int. J. Pest Manage., 53, 7–13, 2007.
Chidumayo, E. N. and Gumbo, D. J.: The dry forests and woodlands of Africa: managing for products and services, Routledge, London, 2010.
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A. J., and Wehner, M.: Long-term Climate Change: Projections, Commitments and Irreversibility, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
D'Odorico, P., Carr, J. A., Laio, F., Ridolfi, L., and Vandoni, S.: Feeding humanity through global food trade, Earths Future, 2, 458–469, 2014.
Del Grosso, S., Parton, W., Stohlgren, T., Zheng, D., Bachelet, D., Prince, S., Hibbard, K., and Olson, R.: Global potential net primary production predicted from vegetation class, precipitation, and temperature, Ecology, 89, 2117–2126, 2008.
Dile, Y. T., Karlberg, L., Temesgen, M., and Rockstrom, J.: The role of water harvesting to achieve sustainable agricultural intensification and resilience against water related shocks in sub-Saharan Africa, Agr. Ecosyst. Environ., 181, 69–79, 2013.
Dufresne, J. L., Foujols, M. A., Denvil, S., Caubel, A., Marti, O., Aumont, O., Balkanski, Y., Bekki, S., Bellenger, H., Benshila, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., de Noblet, N., Duvel, J. P., Ethe, C., Fairhead, L., Fichefet, T., Flavoni, S., Friedlingstein, P., Grandpeix, J. Y., Guez, L., Guilyardi, E., Hauglustaine, D., Hourdin, F., Idelkadi, A., Ghattas, J., Joussaume, S., Kageyama, M., Krinner, G., Labetoulle, S., Lahellec, A., Lefebvre, M. P., Lefevre, F., Levy, C., Li, Z. X., Lloyd, J., Lott, F., Madec, G., Mancip, M., Marchand, M., Masson, S., Meurdesoif, Y., Mignot, J., Musat, I., Parouty, S., Polcher, J., Rio, C., Schulz, M., Swingedouw, D., Szopa, S., Talandier, C., Terray, P., Viovy, N., and Vuichard, N.: Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5, Clim. Dynam., 40, 2123–2165, 2013.
Dunne, J. P., John, J. G., Shevliakova, E., Stouffer, R. J., Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Sentman, L. T., Adcroft, A. J., Cooke, W., Dunne, K. A., Griffies, S. M., Hallberg, R. W., Harrison, M. J., Levy, H., Wittenberg, A. T., Phillips, P. J., and Zadeh, N.: GFDL's ESM2 Global Coupled Climate-Carbon Earth System Models. Part II: Carbon System Formulation and Baseline Simulation Characteristics, J. Climate, 26, 2247–2267, 2013.
Eklundh, L. and Olsson, L.: Vegetation index trends for the African Sahel 1982–1999, Geophys. Res. Lett., 30, 1430, https://doi.org/10.1029/2002GL016772, 2003.
Elliott, J., Deryng, D., Müller, C., Frieler, K., Konzmann, M., Gerten, D., Glotter, M., Flörke, M., Wada, Y., Best, N., Eisner, S., Fekete, B.M., Folberth, C., Foster, I., Gosling, S.N., Haddeland, I., Khabarov, N., Ludwig, F., Masaki, Y., Olin, S., Rosenzweig, C., Ruane, A.C., Satoh, Y., Schmid, E., Stacke, T., Tang, Q., and Wisser, D.: Constraints and potentials of future irrigation water availability on agricultural production under climate change, P. Natl. Acad. Sci. USA, 111, 3239–3244, https://doi.org/10.1073/pnas.1222474110, 2014
Engström, K., Olin, S., Rounsevell, M. D. A., Brogaard, S., van Vuuren, D. P., Alexander, P., Murray-Rust, D., and Arneth, A.: Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework, Earth Syst. Dynam., 7, 893–915, https://doi.org/10.5194/esd-7-893-2016, 2016a.
Engström, K., Rounsevell, M. D. A., Murray-Rust, D., Hardacre, C., Alexander, P., Cui, X. F., Palmer, P. I., and Arneth, A.: Applying Occam's razor to global agricultural land use change, Environ. Modell. Softw., 75, 212–229, 2016b.
Engström, K., Lindeskog, M., Olin, S., Hassler, J., and Smith, B.: Impacts of climate mitigation strategies in the energy sector on global land use and carbon balance, Earth Syst. Dynam., 8, 773–799, https://doi.org/10.5194/esd-8-773-2017, 2017.
FAO: The Digitized Soil Map of the World (Release 1.0), World Soil Resources Report 67/1, Food and Agriculture Organization of the United Nations, Rome, 1991.
FAOSTAT: FAO Statistical Databases, Food and Agriculture Organization of the United Nations, Rome, Italy, 2015.
FAOSTAT: Food Aid Shipments (WFP), http://faostat3.fao.org/download/X/FA/E, last access: 16 August 2016.
Foley, J. A.: Net Primary Productivity in the Terrestrial Biosphere – the Application of a Global-Model, J. Geophys. Res., 99, 20773–20783, 1994.
Foley, J. A., Defries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., Chapin, F. S., Coe, M. T., Daily, G. C., Gibbs, H. K., Helkowski, J. H., Holloway, T., Howard, E. A., Kucharik, C. J., Monfreda, C., Patz, J. A., Prentice, I. C., Ramankutty, N., and Snyder, P. K.: Global consequences of land use, Science, 309, 570–574, 2005.
Foley, J. A., Ramankutty, N., Brauman, K. A., Cassidy, E. S., Gerber, J. S., Johnston, M., Mueller, N. D., O'Connell, C., Ray, D. K., West, P. C., Balzer, C., Bennett, E. M., Carpenter, S. R., Hill, J., Monfreda, C., Polasky, S., Rockstrom, J., Sheehan, J., Siebert, S., Tilman, D., and Zaks, D. P.: Solutions for a cultivated planet, Nature, 478, 337–342, 2011.
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.
Gerten, D., Schaphoff, S., Haberlandt, U., Lucht, W., and Sitch, S.: Terrestrial vegetation and water balance – hydrological evaluation of a dynamic global vegetation model, J. Hydrol., 286, 249–270, 2004.
Godfray, H. C., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., Pretty, J., Robinson, S., Thomas, S. M., and Toulmin, C.: Food security: the challenge of feeding 9 billion people, Science, 327, 812–818, 2010.
Gonzalez, P., Neilson, R. P., Lenihan, J. M., and Drapek, R. J.: Global patterns in the vulnerability of ecosystems to vegetation shifts due to climate change, Global Ecol. Biogeogr., 19, 755–768, 2010.
Haberl, H., Erb, K. H., Krausmann, F., Gaube, V., Bondeau, A., Plutzar, C., Gingrich, S., Lucht, W., and Fischer-Kowalski, M.: Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems, P. Natl. Acad. Sci. USA, 104, 12942–12947, 2007.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset, Int. J. Climatol., 34, 623–642, 2014.
Harrison, P. A., Dunford, R. W., Holman, I. P., and Rounsevell, M. D. A.: Climate change impact modelling needs to include cross-sectoral interactions, Nature Climate Change, 6, 885–890, https://doi.org/10.1038/nclimate3039, 2016.
Hempel, S., Frieler, K., Warszawski, L., Schewe, J., and Piontek, F.: A trend-preserving bias correction – the ISI-MIP approach, Earth Syst. Dynam., 4, 219–236, https://doi.org/10.5194/esd-4-219-2013, 2013.
Herrmann, S. M., Sall, I., and Sy, O.: People and pixels in the Sahel: a study linking coarse-resolution remote sensing observations to land users' perceptions of their changing environment in Senegal, Ecol. Soc., 19, 2014.
Hertel, T. W.: The challenges of sustainably feeding a growing planet, Food Security, 7, 185–198, 2015.
Hickler, T., Smith, B., Prentice, I. C., Mjöfors, K., Miller, P., Arneth, A., and Sykes, M. T.: CO2fertilization in temperate FACE experiments not representative of boreal and tropical forests, Glob. Change Biol., 14, 1531–1542, 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., Goldewijk, K. 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, 2011.
Ibrahim, F. N.: Causes of the Famine among the Rural Population of the Sahelian Zone of the Sudan, GeoJournal, 17, 133–141, 1988.
IPCC: 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4: Agriculture, Forestry, and Other Land Use, edited by: Eggleston, H. S., Buendia, L., Miwa, K., Ngara, T., and Tanabe, K., IGES, Japan, 2006.
Iversen, T., Bentsen, M., Bethke, I., Debernard, J. B., Kirkevåg, A., Seland, Ø., Drange, H., Kristjansson, J. E., Medhaug, I., Sand, M., and Seierstad, I. A.: The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections, Geosci. Model Dev., 6, 389–415, https://doi.org/10.5194/gmd-6-389-2013, 2013.
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, 1996.
Kastner, T., Rivas, M. J., Koch, W., and Nonhebel, S.: Global changes in diets and the consequences for land requirements for food, P. Natl. Acad. Sci. USA, 109, 6868–6872, 2012.
Kearney, J.: Food consumption trends and drivers, Philos. T. Roy. Soc. B, 365, 2793–2807, 2010.
Kebede, A. S., Dunford, R., Mokrech, M., Audsley, E., Harrison, P. A., Holman, I. P., Nicholls, R. J., Rickebusch, S., Rounsevell, M. D. A., Sabaté, S., Sallaba, F., Sanchez, A., Savin, C., Trnka, M., and Wimmer, F.: Direct and indirect impacts of climate and socio-economic change in Europe: a sensitivity analysis for key land- and water-based sectors, Climatic Change, 128, 261–277, 2015.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World map of the Koppen-Geiger climate classification updated, Meteorol. Z., 15, 259–263, 2006.
Körner, C.: Plant CO2 responses: an issue of definition, time and resource supply, New Phytol., 172, 393–411, 2006.
Kwakkel, J. H. and Pruyt, E.: Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty, Technol. Forecast. Soc., 80, 419–431, 2013.
Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M. G., Shindell, D., Smith, S. J., Stehfest, E., Van Aardenne, J., Cooper, O. R., Kainuma, M., Mahowald, N., McConnell, J. R., Naik, V., Riahi, K., and van Vuuren, D. P.: Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application, Atmos. Chem. Phys., 10, 7017–7039, https://doi.org/10.5194/acp-10-7017-2010, 2010.
Licker, R., Johnston, M., Foley, J. A., Barford, C., Kucharik, C. J., Monfreda, C., and Ramankutty, N.: Mind the gap: how do climate and agricultural management explain the "yield gap" of croplands around the world?, Global Ecol. Biogeogr., 19, 769–782, 2010.
Lindeskog, M., Arneth, A., Bondeau, A., Waha, K., Seaquist, J., Olin, S., and Smith, B.: Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa, Earth Syst. Dynam., 4, 385–407, https://doi.org/10.5194/esd-4-385-2013, 2013.
Luyssaert, S., Inglima, I., and Jung, M.: Global Forest Ecosystem Structure and Function Data for Carbon Balance Research, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/949, 2009.
Lynch, K., Binns, T., and Olofin, E.: Urban agriculture under threat – The land security question in Kano, Nigeria, Cities, 18, 159–171, 2001.
Metzger, M. J., Bunce, R. G. H., Jongman, R. H. G., Sayre, R., Trabucco, A., and Zomer, R.: A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring, Global Ecol. Biogeogr., 22, 630–638, 2013.
Michaletz, S. T., Cheng, D., Kerkhoff, A. J., and Enquist, B. J.: Convergence of terrestrial plant production across global climate gradients, Nature, 512, 39–43, 2014.
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. Climat., 25, 693–712, 2005.
Mokany, K., Raison, R. J., and Prokushkin, A. S.: Critical analysis of root : shoot ratios in terrestrial biomes, Glob. Change Biol., 12, 84–96, 2006.
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, 2012.
Olin, S., Lindeskog, M., Pugh, T. A. M., Schurgers, G., Wårlind, D., Mishurov, M., Zaehle, S., Stocker, B. D., Smith, B., and Arneth, A.: Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching, Earth Syst. Dynam., 6, 745–768, https://doi.org/10.5194/esd-6-745-2015, 2015.
O'Neill, B. C., Kriegler, E., Riahi, K., Ebi, K. L., Hallegatte, S., Carter, T. R., Mathur, R., and van Vuuren, D. P.: A new scenario framework for climate change research: the concept of shared socioeconomic pathways, Climatic Change, 122, 387–400, 2014.
O'Neill, B. C., Kriegler, E., Ebi, K. L., Kemp-Benedict, E., Riahi, K., Rothman, D. S., van Ruijven, B. J., van Vuuren, D. P., Birkmann, J., Kok, K., Levy, M., and Solecki, W.: The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century, Global Environ. Chang., 42, 169–180, 2017.
Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., and Kassem, K. R.: Terrestrial Ecoregions of the World: A New Map of Life on Earth: A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity, BioScience, 51, 933–938, 2001.
Olsson, L.: On the Causes of Famine Drought, Desertification and Market Failure in the Sudan, Ambio, 22, 395–403, 1993.
Owuor, S.: Migrants, urban poverty and the changing nature of urban-rural linkages in Kenya, Dev. South. Afr., 24, 109–122, 2007.
Pinstrup-Andersen, P.: Food security: definition and measurement, Food Security, 1, 5–7, 2009.
Pretty, J.: Agricultural sustainability: concepts, principles and evidence, Philos. T. Roy. Soc. B, 363, 447–465, 2008.
Pretty, J.: Sustainable intensification in Africa, Int. J. Agric. Sustain., 9, 3–4, 2011.
Pugh, T. A. M., Arneth, A., Olin, S., Ahlström, A., Bayer, A. D., Goldewijk, K. K., Lindeskog, M., and Schurgers, G.: Simulated carbon emissions from land-use change are substantially enhanced by accounting for agricultural management, Environ. Res. Lett., 10, 124008, https://doi.org/10.1088/1748-9326/10/12/124008, 2015.
Pugh, T. A. M., Müller, C., Arneth, A., Haverd, V., and Smith, B.: Key knowledge and data gaps in modelling the influence of CO2 concentration on the terrestrial carbon sink, J. Plant Physiol., 203, 3–15, https://doi.org/10.1016/j.jplph.2016.05.001, 2016.
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, https://doi.org/10.1029/2007GB002952, 2008.
Ray, D. K., Mueller, N. D., West, P. C., and Foley, J. A.: Yield Trends Are Insufficient to Double Global Crop Production by 2050, PLoS ONE, 8, e66428, https://doi.org/10.1371/journal.pone.0066428, 2013.
Reich, P. F. and Eswaran, H.: Global resources, in: Encyclopedia of Soil Science, edited by: Lal, R., Marcel Dekker, New York, 607–611, 2002.
Rosenzweig, C., Elliott, J., Deryng, D., Ruane, A. C., Müller, C., Arneth, A., Boote, K. J., Folberth, C., Glotter, M., Khabarov, N., Neumann, K., Piontek, F., Pugh, T. A. M., Schmid, E., Stehfest, E., Yang, H., and Jones, J. W.: Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison, P. Natl. Acad. Sci. USA, 111, 3268–3273, https://doi.org/10.1073/pnas.1222463110, 2014.
Running, S. W.: A regional look at HANPP: human consumption is increasing, NPP is not, Environ. Res. Lett., 9, 111003, https://doi.org/10.1088/1748-9326/9/11/111003, 2014.
Running, S. W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., and Hashimoto, H.: A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production, BioScience, 54, 547–560, 2004.
Sallaba, F., Lehsten, D., Seaquist, J., and Sykes, M. T.: A rapid NPP meta-model for current and future climate and CO2 scenarios in Europe, Ecol. Model., 302, 29–41, 2015.
Sallaba, F., Olin, S., Engström, K., Abdi, A. M., Boke-Olen, N., Lehsten, V., Ardö, J., and Seaquist, J. W.: NPP Supply and demand projections for the Sahel, DataGURU, https://doi.org/10.18161/sahel_npp.201712, 2017.
Schwarz, G.: Estimating the Dimension of a Model, Ann. Stat., 6, 461–464, https://doi.org/10.1214/aos/1176344136, 1978.
Seaquist, J. W., Hickler, T., Eklundh, L., Ardö, J., and Heumann, B. W.: Disentangling the effects of climate and people on Sahel vegetation dynamics, Biogeosciences, 6, 469–477, https://doi.org/10.5194/bg-6-469-2009, 2009.
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, 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, Global Ecol. Biogeogr., 10, 621–637, 2001.
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.
Smith, J. U. and Smith, P.: Introduction to environmental modelling, Oxford University Press, Oxford, New York, 2007.
Smith, P.: Delivering food security without increasing pressure on land, Global Food Security, 2, 18–23, 2013.
Smith, P., Smith, J. U., Powlson, D. S., McGill, W. B., Arah, J. R. M., Chertov, O. G., Coleman, K., Franko, U., Frolking, S., Jenkinson, D. S., Jensen, L. S., Kelly, R. H., Klein-Gunnewiek, H., Komarov, A. S., Li, C., Molina, J. A. E., Mueller, T., Parton, W. J., Thornley, J. H. M., and Whitmore, A. P.: A comparison of the performance of nine soil organic matter models using datasets from seven long-term experiments, Geoderma, 81, 153–225, 1997.
Smith, W., Cleveland, C. C., Reed, S. C., and Running, S. W.: Agricultural conversion without external water and nutrient inputs reduces terrestrial vegetation productivity, Geophys. Res. Lett., 41, 449-455, 2014.
Smith, W. K., Reed, S. C., Cleveland, C. C., Ballantyne, A. P., Anderegg, W. R. L., Wieder, W. R., Liu, Y. Y., and Running, S. W.: Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization, Nature Climate Change, 6, 306–310, 2016.
Tang, G. P., Beckage, B., Smith, B., and Miller, P. A.: Estimating potential forest NPP, biomass and their climatic sensitivity in New England using a dynamic ecosystem model, Ecosphere, 1, art18, https://doi.org/10.1890/ES10-00087.1, 2010.
Tilman, D., Balzer, C., Hill, J., and Befort, B. L.: Global food demand and the sustainable intensification of agriculture, P. Natl. Acad. Sci USA, 108, 20260–20264, 2011.
Trenberth, K. E., Dai, A., van der Schrier, G., Jones, P. D., Barichivich, J., Briffa, K. R., and Sheffield, J.: Global warming and changes in drought, Nature Climate Change, 4, 17–22, 2014.
Tschirley, D., Reardon, T., Dolislager, M., and Snyder, J.: The Rise of a Middle Class in East and Southern Africa: Implications for Food System Transformation, Journal of International Development, 27, 628–646, 2015.
UN (United Nations): Sahel Regional Strategy Mid-Year Review 2013, United Nations Office for the Coordination of Humanitarian Affairs, 2013.
UN (United Nations): Transforming our world: The 2030 Agenda for sustainable development, UN-DESA, 2016.
van Vuuren, D. P., de Vries, B., Beusen, A., and Heuberger, P. S. C.: Conditional probabilistic estimates of 21st century greenhouse gas emissions based on the storylines of the IPCC-SRES scenarios, Global Environ. Chang., 18, 635–654, 2008.
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The representative concentration pathways: an overview, Climatic Change, 109, 5–31, 2011.
van Vuuren, D. P., Kriegler, E., O'Neill, B. C., Ebi, K. L., Riahi, K., Carter, T. R., Edmonds, J., Hallegatte, S., Kram, T., Mathur, R., and Winkler, H.: A new scenario framework for Climate Change Research: scenario matrix architecture, Climatic Change, 122, 373–386, 2013.
Watanabe, M., Chikira, M., Imada, Y., and Kimoto, M.: Convective Control of ENSO Simulated in MIROC, Journal of Climate, 24, 543-562, 2011.
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.
Willmott, C. J., Robeson, S. M., and Matsuura, K.: A refined index of model performance, Int. J. Climatol., 32, 2088–2094, 2012.
Wirsenius, S.: Human use of land and organic materials: modeling the turnover of biomass in the global food system, PhD thesis, Department of Physical Resource Theory, Chalmers University of Technology, Göteborg, Sweden, 2000.
Yengoh, G. T. and Ardö, J.: Crop yield gaps in Cameroon, Ambio, 43, 175–190, 2014.
Short summary
The UN sustainable development goals for eradicating hunger are at high risk for failure in the Sahel. We show that the demand for food and feed biomass will begin to outstrip its supply in the 2040s if current trends continue. Though supply continues to increase it is outpaced by a greater increase in demand due to a combination of population growth and a shift to diets rich in animal proteins. This underscores the importance of policy interventions that would act to mitigate such developments.
The UN sustainable development goals for eradicating hunger are at high risk for failure in the...
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