Articles | Volume 4, issue 2
https://doi.org/10.5194/esd-4-385-2013
© 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/esd-4-385-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Nov 2013
Research article |
| 01 Nov 2013
Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa
M. Lindeskog
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 22362 Lund, Sweden
A. Arneth
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstr. 19, 82467 Garmisch-Partenkirchen, Germany
A. Bondeau
Climate Impacts and Vulnerabilities, Potsdam Institute for Climate Impact Research (PIK), P.O. Box 60 1203, 14412 Potsdam, Germany
Mediterranean Institute of Biodiversity and Ecology (IMBE), CNRS/Aix-Marseille University/IRD/UAPV, Bâtiment Villemin, Europole de l'Arbois, BP 80, 13545 Aix-en-Provence cedex 04, France
K. Waha
Earth System Analysis, Potsdam Institute for Climate Impact Research (PIK), P.O. Box 60 1203, 14412 Potsdam, Germany
J. Seaquist
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 22362 Lund, Sweden
S. Olin
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 22362 Lund, Sweden
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 22362 Lund, Sweden
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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
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Manuscript not accepted for further review
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Kerstin Engström, Stefan Olin, Mark D. A. Rounsevell, Sara Brogaard, Detlef P. van Vuuren, Peter Alexander, Dave Murray-Rust, and Almut Arneth
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Wenli Wang, Annette Rinke, John C. Moore, Duoying Ji, Xuefeng Cui, Shushi Peng, David M. Lawrence, A. David McGuire, Eleanor J. Burke, Xiaodong Chen, Bertrand Decharme, Charles Koven, Andrew MacDougall, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Christine Delire, Isabelle Gouttevin, Tomohiro Hajima, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, Benjamin Smith, Tetsuo Sueyoshi, and Artem B. Sherstiukov
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On Earth, vegetation does not merely adapt to climate but also imposes significant influences on climate with both local and remote effects. In this study we evaluated the role of vegetation in African climate with a regional Earth system model. By the comparison between the experiments with and without dynamic vegetation changes, we found that vegetation can influence climate remotely, resulting in modulating rainfall patterns over Africa.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
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In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
Wolfgang Knorr, Frank Dentener, Stijn Hantson, Leiwen Jiang, Zbigniew Klimont, and Almut Arneth
Atmos. Chem. Phys., 16, 5685–5703, https://doi.org/10.5194/acp-16-5685-2016, https://doi.org/10.5194/acp-16-5685-2016, 2016
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Wildfires are generally expected to increase in frequency and severity due to climate change. For Europe this could mean increased air pollution levels during the summer. Until 2050, predicted changes are moderate, but under a scenario of strong climate change, these may increase considerably during the later part of the current century. In Portugal and several parts of the Mediterranean, emissions may become relevant for meeting WHO concentration targets.
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.
V. Haverd, B. Smith, M. Raupach, P. Briggs, L. Nieradzik, J. Beringer, L. Hutley, C. M. Trudinger, and J. Cleverly
Biogeosciences, 13, 761–779, https://doi.org/10.5194/bg-13-761-2016, https://doi.org/10.5194/bg-13-761-2016, 2016
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We present a new approach for modelling coupled phenology and carbon allocation in savannas, and test it using data from the OzFlux network. Model behaviour emerges from complex feedbacks between the plant physiology and vegetation dynamics, in response to resource availability, and not from imposed hypotheses about the controls on tree-grass co-existence. Results indicate that resource limitation is a stronger determinant of tree cover than disturbance in Australian savannas.
S. Peng, P. Ciais, G. Krinner, T. Wang, I. Gouttevin, A. D. McGuire, D. Lawrence, E. Burke, X. Chen, B. Decharme, C. Koven, A. MacDougall, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, C. Delire, T. Hajima, D. Ji, D. P. Lettenmaier, P. A. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
The Cryosphere, 10, 179–192, https://doi.org/10.5194/tc-10-179-2016, https://doi.org/10.5194/tc-10-179-2016, 2016
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Soil temperature change is a key indicator of the dynamics of permafrost. Using nine process-based ecosystem models with permafrost processes, a large spread of soil temperature trends across the models. Air temperature and longwave downward radiation are the main drivers of soil temperature trends. Based on an emerging observation constraint method, the total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000.
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.
M. A. Rawlins, A. D. McGuire, J. S. Kimball, P. Dass, D. Lawrence, E. Burke, X. Chen, C. Delire, C. Koven, A. MacDougall, S. Peng, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, P. Ciais, B. Decharme, I. Gouttevin, T. Hajima, D. Ji, G. Krinner, D. P. Lettenmaier, P. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
Biogeosciences, 12, 4385–4405, https://doi.org/10.5194/bg-12-4385-2015, https://doi.org/10.5194/bg-12-4385-2015, 2015
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We used outputs from nine models to better understand land-atmosphere CO2 exchanges across Northern Eurasia over the period 1960-1990. Model estimates were assessed against independent ground and satellite measurements. We find that the models show a weakening of the CO2 sink over time; the models tend to overestimate respiration, causing an underestimate in NEP; the model range in regional NEP is twice the multimodel mean. Residence time for soil carbon decreased, amid a gain in carbon storage.
J. Tang, P. A. Miller, A. Persson, D. Olefeldt, P. Pilesjö, M. Heliasz, M. Jackowicz-Korczynski, Z. Yang, B. Smith, T. V. Callaghan, and T. R. Christensen
Biogeosciences, 12, 2791–2808, https://doi.org/10.5194/bg-12-2791-2015, https://doi.org/10.5194/bg-12-2791-2015, 2015
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
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
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 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.
D. Wårlind, B. Smith, T. Hickler, and A. Arneth
Biogeosciences, 11, 6131–6146, https://doi.org/10.5194/bg-11-6131-2014, https://doi.org/10.5194/bg-11-6131-2014, 2014
W. Zhang, C. Jansson, P. A. Miller, B. Smith, and P. Samuelsson
Biogeosciences, 11, 5503–5519, https://doi.org/10.5194/bg-11-5503-2014, https://doi.org/10.5194/bg-11-5503-2014, 2014
V. Haverd, B. Smith, L. P. Nieradzik, and P. R. Briggs
Biogeosciences, 11, 4039–4055, https://doi.org/10.5194/bg-11-4039-2014, https://doi.org/10.5194/bg-11-4039-2014, 2014
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
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
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
G. Strandberg, E. Kjellström, A. Poska, S. Wagner, M.-J. Gaillard, A.-K. Trondman, A. Mauri, B. A. S. Davis, J. O. Kaplan, H. J. B. Birks, A. E. Bjune, R. Fyfe, T. Giesecke, L. Kalnina, M. Kangur, W. O. van der Knaap, U. Kokfelt, P. Kuneš, M. Lata\l owa, L. Marquer, F. Mazier, A. B. Nielsen, B. Smith, H. Seppä, and S. Sugita
Clim. Past, 10, 661–680, https://doi.org/10.5194/cp-10-661-2014, https://doi.org/10.5194/cp-10-661-2014, 2014
M. D. A. Rounsevell, A. Arneth, P. Alexander, D. G. Brown, N. de Noblet-Ducoudré, E. Ellis, J. Finnigan, K. Galvin, N. Grigg, I. Harman, J. Lennox, N. Magliocca, D. Parker, B. C. O'Neill, P. H. Verburg, and O. Young
Earth Syst. Dynam., 5, 117–137, https://doi.org/10.5194/esd-5-117-2014, https://doi.org/10.5194/esd-5-117-2014, 2014
R. Valentini, A. Arneth, A. Bombelli, S. Castaldi, R. Cazzolla Gatti, F. Chevallier, P. Ciais, E. Grieco, J. Hartmann, M. Henry, R. A. Houghton, M. Jung, W. L. Kutsch, Y. Malhi, E. Mayorga, L. Merbold, G. Murray-Tortarolo, D. Papale, P. Peylin, B. Poulter, P. A. Raymond, M. Santini, S. Sitch, G. Vaglio Laurin, G. R. van der Werf, C. A. Williams, and R. J. Scholes
Biogeosciences, 11, 381–407, https://doi.org/10.5194/bg-11-381-2014, https://doi.org/10.5194/bg-11-381-2014, 2014
Related subject area
Earth system interactions with the biosphere: landuse
The biogeophysical effects of idealized land cover and land management changes in Earth system models
The response of the regional longwave radiation balance and climate system in Europe to an idealized afforestation experiment
Comparison of uncertainties in land-use change fluxes from bookkeeping model parameterisation
Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches
Biases in the albedo sensitivity to deforestation in CMIP5 models and their impacts on the associated historical radiative forcing
Impact of environmental changes and land management practices on wheat production in India
Impacts of future agricultural change on ecosystem service indicators
Biogeophysical impacts of forestation in Europe: first results from the LUCAS (Land Use and Climate Across Scales) regional climate model intercomparison
A multi-model analysis of teleconnected crop yield variability in a range of cropping systems
Different response of surface temperature and air temperature to deforestation in climate models
Changes in crop yields and their variability at different levels of global warming
A global assessment of gross and net land change dynamics for current conditions and future scenarios
Quantification of the impacts of climate change and human agricultural activities on oasis water requirements in an arid region: a case study of the Heihe River basin, China
Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era
Managing fire risk during drought: the influence of certification and El Niño on fire-driven forest conversion for oil palm in Southeast Asia
Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments
Uncertainties in the land-use flux resulting from land-use change reconstructions and gross land transitions
Continuous and consistent land use/cover change estimates using socio-ecological data
Vulnerability to climate change and adaptation strategies of local communities in Malawi: experiences of women fish-processing groups in the Lake Chilwa Basin
Deforestation in Amazonia impacts riverine carbon dynamics
Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework
Ocean–atmosphere interactions modulate irrigation's climate impacts
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Local sources of global climate forcing from different categories of land use activities
Effects of climate variability on savannah fire regimes in West Africa
Sustainable management of river oases along the Tarim River (SuMaRiO) in Northwest China under conditions of climate change
Terminology as a key uncertainty in net land use and land cover change carbon flux estimates
Towards decision-based global land use models for improved understanding of the Earth system
The impact of nitrogen and phosphorous limitation on the estimated terrestrial carbon balance and warming of land use change over the last 156 yr
A theoretical framework for the net land-to-atmosphere CO2 flux and its implications in the definition of "emissions from land-use change"
Spatio-temporal analysis of the urban–rural gradient structure: an application in a Mediterranean mountainous landscape (Serra San Bruno, Italy)
Effects of land cover change on temperature and rainfall extremes in multi-model ensemble simulations
Urbanization suitability maps: a dynamic spatial decision support system for sustainable land use
The influence of vegetation on the ITCZ and South Asian monsoon in HadCM3
Steven J. De Hertog, Felix Havermann, Inne Vanderkelen, Suqi Guo, Fei Luo, Iris Manola, Dim Coumou, Edouard L. Davin, Gregory Duveiller, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 14, 629–667, https://doi.org/10.5194/esd-14-629-2023, https://doi.org/10.5194/esd-14-629-2023, 2023
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Land cover and land management changes are important strategies for future land-based mitigation. We investigate the climate effects of cropland expansion, afforestation, irrigation and wood harvesting using three Earth system models. Results show that these have important implications for surface temperature where the land cover and/or management change occur and in remote areas. Idealized afforestation causes global warming, which might offset the cooling effect from enhanced carbon uptake.
Marcus Breil, Felix Krawczyk, and Joaquim G. Pinto
Earth Syst. Dynam., 14, 243–253, https://doi.org/10.5194/esd-14-243-2023, https://doi.org/10.5194/esd-14-243-2023, 2023
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We provide evidence that biogeophysical effects of afforestation can counteract the favorable biogeochemical climate effect of reduced CO2 concentrations. By changing the land surface characteristics, afforestation reduces vegetation surface temperatures, resulting in a reduced outgoing longwave radiation in summer, although CO2 concentrations are reduced. Since forests additionally absorb a lot of solar radiation due to their dark surfaces, afforestation has a total warming effect.
Ana Bastos, Kerstin Hartung, Tobias B. Nützel, Julia E. M. S. Nabel, Richard A. Houghton, and Julia Pongratz
Earth Syst. Dynam., 12, 745–762, https://doi.org/10.5194/esd-12-745-2021, https://doi.org/10.5194/esd-12-745-2021, 2021
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Fluxes from land-use change and management (FLUC) are a large source of uncertainty in global and regional carbon budgets. Here, we evaluate the impact of different model parameterisations on FLUC. We show that carbon stock densities and allocation of carbon following transitions contribute more to uncertainty in FLUC than response-curve time constants. Uncertainty in FLUC could thus, in principle, be reduced by available Earth-observation data on carbon densities at a global scale.
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
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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.
Quentin Lejeune, Edouard L. Davin, Grégory Duveiller, Bas Crezee, Ronny Meier, Alessandro Cescatti, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 1209–1232, https://doi.org/10.5194/esd-11-1209-2020, https://doi.org/10.5194/esd-11-1209-2020, 2020
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Trees are darker than crops or grasses; hence, they absorb more solar radiation. Therefore, land cover changes modify the fraction of solar radiation reflected by the land surface (its albedo), with consequences for the climate. We apply a new statistical method to simulations conducted with 15 recent climate models and find that albedo variations due to land cover changes since 1860 have led to a decrease in the net amount of energy entering the atmosphere by −0.09 W m2 on average.
Shilpa Gahlot, Tzu-Shun Lin, Atul K. Jain, Somnath Baidya Roy, Vinay K. Sehgal, and Rajkumar Dhakar
Earth Syst. Dynam., 11, 641–652, https://doi.org/10.5194/esd-11-641-2020, https://doi.org/10.5194/esd-11-641-2020, 2020
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Spring wheat, a staple for millions of people in India and the world, is vulnerable to changing environmental and management factors. Using a new spring wheat model, we find that over the 1980–2016 period elevated CO2 levels, irrigation, and nitrogen fertilizers led to an increase of 30 %, 12 %, and 15 % in countrywide production, respectively. In contrast, rising temperatures have reduced production by 18 %. These effects vary across the country, thereby affecting production at regional scales.
Sam S. Rabin, Peter Alexander, Roslyn Henry, Peter Anthoni, Thomas A. M. Pugh, Mark Rounsevell, and Almut Arneth
Earth Syst. Dynam., 11, 357–376, https://doi.org/10.5194/esd-11-357-2020, https://doi.org/10.5194/esd-11-357-2020, 2020
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We modeled how agricultural performance and demand will shift as a result of climate change and population growth, and how the resulting adaptations will affect aspects of the Earth system upon which humanity depends. We found that the impacts of land use and management can have stronger impacts than climate change on some such
ecosystem services. The overall impacts are strongest in future scenarios with more severe climate change, high population growth, and/or resource-intensive lifestyles.
Edouard L. Davin, Diana Rechid, Marcus Breil, Rita M. Cardoso, Erika Coppola, Peter Hoffmann, Lisa L. Jach, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Kai Radtke, Mario Raffa, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Tölle, Kirsten Warrach-Sagi, and Volker Wulfmeyer
Earth Syst. Dynam., 11, 183–200, https://doi.org/10.5194/esd-11-183-2020, https://doi.org/10.5194/esd-11-183-2020, 2020
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
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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.
Johannes Winckler, Christian H. Reick, Sebastiaan Luyssaert, Alessandro Cescatti, Paul C. Stoy, Quentin Lejeune, Thomas Raddatz, Andreas Chlond, Marvin Heidkamp, and Julia Pongratz
Earth Syst. Dynam., 10, 473–484, https://doi.org/10.5194/esd-10-473-2019, https://doi.org/10.5194/esd-10-473-2019, 2019
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For local living conditions, it matters whether deforestation influences the surface temperature, temperature at 2 m, or the temperature higher up in the atmosphere. Here, simulations with a climate model show that at a location of deforestation, surface temperature generally changes more strongly than atmospheric temperature. Comparison across climate models shows that both for summer and winter the surface temperature response exceeds the air temperature response locally by a factor of 2.
Sebastian Ostberg, Jacob Schewe, Katelin Childers, and Katja Frieler
Earth Syst. Dynam., 9, 479–496, https://doi.org/10.5194/esd-9-479-2018, https://doi.org/10.5194/esd-9-479-2018, 2018
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It has been shown that regional temperature and precipitation changes in future climate change scenarios often scale quasi-linearly with global mean temperature change (∆GMT). We show that an important consequence of these physical climate changes, namely changes in agricultural crop yields, can also be described in terms of ∆GMT to a large extent. This makes it possible to efficiently estimate future crop yield changes for different climate change scenarios without need for complex models.
Richard Fuchs, Reinhard Prestele, and Peter H. Verburg
Earth Syst. Dynam., 9, 441–458, https://doi.org/10.5194/esd-9-441-2018, https://doi.org/10.5194/esd-9-441-2018, 2018
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We analysed current global land change dynamics based on high-resolution (30–100 m) remote sensing products. We integrated these empirical data into a future simulation model to assess global land change dynamics in the future (2000 to 2040). The consideration of empirically derived land change dynamics in future models led globally to ca. 50 % more land changes than currently assumed in state-of-the-art models. This impacts the results of other global change studies (e.g. climate change).
Xingran Liu and Yanjun Shen
Earth Syst. Dynam., 9, 211–225, https://doi.org/10.5194/esd-9-211-2018, https://doi.org/10.5194/esd-9-211-2018, 2018
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The impacts of climate change and human activities on oasis water requirements in Heihe River basin were quantified with the methods of partial derivative and slope in this study. The results showed that the oasis water requirement increased sharply from 10.8 × 108 to 19.0 × 108 m3 during 1986–2013. Human activities were the dominant driving forces. Changes in climate, land scale and structure contributed to the increase in water requirement at rates of 6.9, 58.1, and 25.3 %, respectively.
Ben Parkes, Dimitri Defrance, Benjamin Sultan, Philippe Ciais, and Xuhui Wang
Earth Syst. Dynam., 9, 119–134, https://doi.org/10.5194/esd-9-119-2018, https://doi.org/10.5194/esd-9-119-2018, 2018
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We present an analysis of three crops in West Africa and their response to short-term climate change in a world where temperatures are 1.5 °C above the preindustrial levels. We show that the number of crop failures for all crops is due to increase in the future climate. We further show the difference in yield change across several West African countries and show that the yields are not expected to increase fast enough to prevent food shortages.
Praveen Noojipady, Douglas C. Morton, Wilfrid Schroeder, Kimberly M. Carlson, Chengquan Huang, Holly K. Gibbs, David Burns, Nathalie F. Walker, and Stephen D. Prince
Earth Syst. Dynam., 8, 749–771, https://doi.org/10.5194/esd-8-749-2017, https://doi.org/10.5194/esd-8-749-2017, 2017
Reinhard Prestele, Almut Arneth, Alberte Bondeau, Nathalie de Noblet-Ducoudré, Thomas A. M. Pugh, Stephen Sitch, Elke Stehfest, and Peter H. Verburg
Earth Syst. Dynam., 8, 369–386, https://doi.org/10.5194/esd-8-369-2017, https://doi.org/10.5194/esd-8-369-2017, 2017
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Land-use change is still overly simplistically implemented in global ecosystem and climate models. We identify and discuss three major challenges at the interface of land-use and climate modeling and propose ways for how to improve land-use representation in climate models. We conclude that land-use data-provider and user communities need to engage in the joint development and evaluation of enhanced land-use datasets to improve the quantification of land use–climate interactions and feedback.
Anita D. Bayer, Mats Lindeskog, Thomas A. M. Pugh, Peter M. Anthoni, Richard Fuchs, and Almut Arneth
Earth Syst. Dynam., 8, 91–111, https://doi.org/10.5194/esd-8-91-2017, https://doi.org/10.5194/esd-8-91-2017, 2017
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We evaluate the effects of land-use and land-cover changes on carbon pools and fluxes using a dynamic global vegetation model. Different historical reconstructions yielded an uncertainty of ca. ±30 % in the mean annual land use emission over the last decades. Accounting for the parallel expansion and abandonment of croplands on a sub-grid level (tropical shifting cultivation) substantially increased the effect of land use on carbon stocks and fluxes compared to only accounting for net effects.
Michael Marshall, Michael Norton-Griffiths, Harvey Herr, Richard Lamprey, Justin Sheffield, Tor Vagen, and Joseph Okotto-Okotto
Earth Syst. Dynam., 8, 55–73, https://doi.org/10.5194/esd-8-55-2017, https://doi.org/10.5194/esd-8-55-2017, 2017
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The transition of land from one cover type to another can adversely affect the Earth system. A growing body of research aims to map these transitions in space and time to better understand the impacts. Here we develop a statistical model that is parameterized by socio-ecological geospatial data and extensive aerial/ground surveys to visualize and interpret these transitions on an annual basis for 30 years in Kenya. Future work will use this method to project land suitability across Africa.
Hanne Jørstad and Christian Webersik
Earth Syst. Dynam., 7, 977–989, https://doi.org/10.5194/esd-7-977-2016, https://doi.org/10.5194/esd-7-977-2016, 2016
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This research is about climate change adaptation. It demonstrates how adaptation to climate change can avoid social tensions if done in a sustainable way. Evidence is drawn from Malawi in southern Africa.
Fanny Langerwisch, Ariane Walz, Anja Rammig, Britta Tietjen, Kirsten Thonicke, and Wolfgang Cramer
Earth Syst. Dynam., 7, 953–968, https://doi.org/10.5194/esd-7-953-2016, https://doi.org/10.5194/esd-7-953-2016, 2016
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Amazonia is heavily impacted by climate change and deforestation. During annual flooding terrigenous material is imported to the river, converted and finally exported to the ocean or the atmosphere. Changes in the vegetation alter therefore riverine carbon dynamics. Our results show that due to deforestation organic carbon amount will strongly decrease both in the river and exported to the ocean, while inorganic carbon amounts will increase, in the river as well as exported to the atmosphere.
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.
Nir Y. Krakauer, Michael J. Puma, Benjamin I. Cook, Pierre Gentine, and Larissa Nazarenko
Earth Syst. Dynam., 7, 863–876, https://doi.org/10.5194/esd-7-863-2016, https://doi.org/10.5194/esd-7-863-2016, 2016
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We simulated effects of irrigation on climate with the NASA GISS global climate model. Present-day irrigation levels affected air pressures and temperatures even in non-irrigated land and ocean areas. The simulated effect was bigger and more widespread when ocean temperatures in the climate model could change, rather than being fixed. We suggest that expanding irrigation may affect global climate more than previously believed.
Andreas Krause, Thomas A. M. Pugh, Anita D. Bayer, Mats Lindeskog, and Almut Arneth
Earth Syst. Dynam., 7, 745–766, https://doi.org/10.5194/esd-7-745-2016, https://doi.org/10.5194/esd-7-745-2016, 2016
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We used a vegetation model to study the legacy effects of different land-use histories on ecosystem recovery in a range of environmental conditions. We found that recovery trajectories are crucially influenced by type and duration of former agricultural land use, especially for soil carbon. Spatially, we found the greatest sensitivity to land-use history in boreal forests and subtropical grasslands. These results are relevant for measurements, climate modeling and afforestation projects.
Grace W. Ngaruiya and Jürgen Scheffran
Earth Syst. Dynam., 7, 441–452, https://doi.org/10.5194/esd-7-441-2016, https://doi.org/10.5194/esd-7-441-2016, 2016
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Climate change complicates rural conflict resolution dynamics and institutions. There is urgent need for conflict-sensitive adaptation in Africa. The study of social network data reveals three forms of fused conflict resolution arrangements in Loitoktok, Kenya. Where, extension officers, council of elders, local chiefs and private investors are potential conduits of knowledge. Efficiency of rural conflict resolution can be enhanced by diversification in conflict resolution actors and networks.
Daniel Paradis, Harold Vigneault, René Lefebvre, Martine M. Savard, Jean-Marc Ballard, and Budong Qian
Earth Syst. Dynam., 7, 183–202, https://doi.org/10.5194/esd-7-183-2016, https://doi.org/10.5194/esd-7-183-2016, 2016
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According to groundwater flow and mass transport simulations, nitrate concentration for year 2050 would increase mainly due to the attainment of equilibrium conditions of the aquifer system related to actual nitrogen loadings, and to the increase in nitrogen loadings due to changes in agricultural practices. Impact of climate change on the groundwater recharge would contribute only slightly to that increase.
Yan Li, Nathalie De Noblet-Ducoudré, Edouard L. Davin, Safa Motesharrei, Ning Zeng, Shuangcheng Li, and Eugenia Kalnay
Earth Syst. Dynam., 7, 167–181, https://doi.org/10.5194/esd-7-167-2016, https://doi.org/10.5194/esd-7-167-2016, 2016
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The impact of deforestation is to warm the tropics and cool the extratropics, and the magnitude of the impact depends on the spatial extent and the degree of forest loss. That also means location matters for the impact of deforestation on temperature because such an impact is largely determined by the climate condition of that region. For example, under dry and wet conditions, deforestation can have quite different climate impacts.
Kazi Farzan Ahmed, Guiling Wang, Liangzhi You, and Miao Yu
Earth Syst. Dynam., 7, 151–165, https://doi.org/10.5194/esd-7-151-2016, https://doi.org/10.5194/esd-7-151-2016, 2016
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A prototype model LandPro was developed to study climate change impact on land use in West Africa. LandPro considers climate and socioeconomic factors in projecting anthropogenic future land use change (LULCC). The model projections reflect that relative impact of climate change on LULCC in West Africa is region dependent. Results from scenario analysis suggest that science-informed decision-making by the farmers in agricultural land use can potentially reduce crop area expansion in the region.
T. Brücher, M. Claussen, and T. Raddatz
Earth Syst. Dynam., 6, 769–780, https://doi.org/10.5194/esd-6-769-2015, https://doi.org/10.5194/esd-6-769-2015, 2015
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A major link between climate and humans in northern Africa, and the Sahel in particular, is land use. We assess possible feedbacks between the type of land use and harvest intensity and climate by analysing a series of idealized GCM experiments using the MPI-ESM. Our study suggests marginal feedback between land use changes and climate changes triggered by strong greenhouse gas emissions.
B. D. Stocker and F. Joos
Earth Syst. Dynam., 6, 731–744, https://doi.org/10.5194/esd-6-731-2015, https://doi.org/10.5194/esd-6-731-2015, 2015
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Estimates for land use change CO2 emissions (eLUC) rely on different approaches, implying conceptual differences of what eLUC represents. We use an Earth System Model and quantify differences between two commonly applied methods to be ~20% for historical eLUC but increasing under a future scenario. We decompose eLUC into component fluxes, quantify them, and discuss best practices for global carbon budget accountings and model-data intercomparisons relying on different methods to estimate eLUC.
E. Teferi, S. Uhlenbrook, and W. Bewket
Earth Syst. Dynam., 6, 617–636, https://doi.org/10.5194/esd-6-617-2015, https://doi.org/10.5194/esd-6-617-2015, 2015
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This study concludes that integrated analysis of course and fine-scale, inter-annual and intra-annual trends enables a more robust identification of changes in vegetation condition. Seasonal trend analysis was found to be very useful in identifying changes in vegetation condition that could be masked if only inter-annual vegetation trend analysis were performed. The finer-scale intra-annual trend analysis revealed trends that were more linked to human activities.
D. S. Ward and N. M. Mahowald
Earth Syst. Dynam., 6, 175–194, https://doi.org/10.5194/esd-6-175-2015, https://doi.org/10.5194/esd-6-175-2015, 2015
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The radiative forcing of land use and land cover change activities has recently been computed for a set of forcing agents including long-lived greenhouse gases, short-lived agents (ozone and aerosols), and land surface albedo change. Here we address where the global forcing comes from and what land use activities, such as deforestation or agriculture, contribute the most forcing. We find that changes in forest and crop area can be used to predict the land use radiative forcing in some regions.
E. T. N'Datchoh, A. Konaré, A. Diedhiou, A. Diawara, E. Quansah, and P. Assamoi
Earth Syst. Dynam., 6, 161–174, https://doi.org/10.5194/esd-6-161-2015, https://doi.org/10.5194/esd-6-161-2015, 2015
C. Rumbaur, N. Thevs, M. Disse, M. Ahlheim, A. Brieden, B. Cyffka, D. Duethmann, T. Feike, O. Frör, P. Gärtner, Ü. Halik, J. Hill, M. Hinnenthal, P. Keilholz, B. Kleinschmit, V. Krysanova, M. Kuba, S. Mader, C. Menz, H. Othmanli, S. Pelz, M. Schroeder, T. F. Siew, V. Stender, K. Stahr, F. M. Thomas, M. Welp, M. Wortmann, X. Zhao, X. Chen, T. Jiang, J. Luo, H. Yimit, R. Yu, X. Zhang, and C. Zhao
Earth Syst. Dynam., 6, 83–107, https://doi.org/10.5194/esd-6-83-2015, https://doi.org/10.5194/esd-6-83-2015, 2015
J. Pongratz, C. H. Reick, R. A. Houghton, and J. I. House
Earth Syst. Dynam., 5, 177–195, https://doi.org/10.5194/esd-5-177-2014, https://doi.org/10.5194/esd-5-177-2014, 2014
M. D. A. Rounsevell, A. Arneth, P. Alexander, D. G. Brown, N. de Noblet-Ducoudré, E. Ellis, J. Finnigan, K. Galvin, N. Grigg, I. Harman, J. Lennox, N. Magliocca, D. Parker, B. C. O'Neill, P. H. Verburg, and O. Young
Earth Syst. Dynam., 5, 117–137, https://doi.org/10.5194/esd-5-117-2014, https://doi.org/10.5194/esd-5-117-2014, 2014
Q. Zhang, A. J. Pitman, Y. P. Wang, Y. J. Dai, and P. J. Lawrence
Earth Syst. Dynam., 4, 333–345, https://doi.org/10.5194/esd-4-333-2013, https://doi.org/10.5194/esd-4-333-2013, 2013
T. Gasser and P. Ciais
Earth Syst. Dynam., 4, 171–186, https://doi.org/10.5194/esd-4-171-2013, https://doi.org/10.5194/esd-4-171-2013, 2013
G. Modica, M. Vizzari, M. Pollino, C. R. Fichera, P. Zoccali, and S. Di Fazio
Earth Syst. Dynam., 3, 263–279, https://doi.org/10.5194/esd-3-263-2012, https://doi.org/10.5194/esd-3-263-2012, 2012
A. J. Pitman, N. de Noblet-Ducoudré, F. B. Avila, L. V. Alexander, J.-P. Boisier, V. Brovkin, C. Delire, F. Cruz, M. G. Donat, V. Gayler, B. van den Hurk, C. Reick, and A. Voldoire
Earth Syst. Dynam., 3, 213–231, https://doi.org/10.5194/esd-3-213-2012, https://doi.org/10.5194/esd-3-213-2012, 2012
M. Cerreta and P. De Toro
Earth Syst. Dynam., 3, 157–171, https://doi.org/10.5194/esd-3-157-2012, https://doi.org/10.5194/esd-3-157-2012, 2012
M. P. McCarthy, J. Sanjay, B. B. B. Booth, K. Krishna Kumar, and R. A. Betts
Earth Syst. Dynam., 3, 87–96, https://doi.org/10.5194/esd-3-87-2012, https://doi.org/10.5194/esd-3-87-2012, 2012
Cited articles
Ahlström, A., Miller, P. A., and Smith, B.: Too early to infer a global NPP decline since 2000, Geophys. Res. Lett., 39, L15403, https://doi.org/10.1029/2012GL052336, 2012a.
Ahlström, A., Schurgers, G., Arneth, A., and Smith, B.: Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections, Environ. Res. Lett., 7, 0440082012b, https://doi.org/10.1088/1748-9326/7/4/044008, 2012b.
Ainsworth, E. A. and Long, S. P.: What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2, New Phytol., 165, 351–371, 2005.
Arneth, A., Sitch, S., Bondeau, A., Butterbach-Bahl, K., Foster, P., Gedney, N., de Noblet-Ducoudré, N., Prentice, I. C., Sanderson, M., Thonicke, K., Wania, R., and Zaehle, S.: From biota to chemistry and climate: towards a comprehensive description of trace gas exchange between the biosphere and atmosphere, Biogeosciences, 7, 121–149, https://doi.org/10.5194/bg-7-121-2010, 2010a.
Arneth, A., Harrison, S. P., Zaehle, S., Tsigaridis, K., Menon, S., Bartlein, P. J., Feichter, J., Korhola, A., Kulmala, M., O'Donnell, D., Schurgers, G., Sorvari, S., and Vesala, T.: Terrestrial biogeochemical feedbacks in the climate system, Nat. Geosci., 3, 525–532, https://doi.org/10.1038/ngeo905, 2010b.
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.
Berg, A., Sultan, B., and de Noblet-Ducoudré, N.: Including tropical croplands in a terrestrial biosphere model: application to West Africa, Climatic Change, 104, 755–782, https://doi.org/10.1007/s10584-010-9874-x, 2011.
Bombelli, A., Henry, M., Castaldi, S., Adu-Bredu, S., Arneth, A., de Grandcourt, A., Grieco, E., Kutsch, W. L., Lehsten, V., Rasile, A., Reichstein, M., Tansey, K., Weber, U., and Valentini, R.: An outlook on the Sub-Saharan Africa carbon balance, Biogeosciences, 6, 2193-2205, https://doi.org/10.5194/bg-6-2193-2009, 2009.
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, Global Change Biol., 13, 679-706, https://doi.org/10.1111/j.1365-2486.2006.01305.x, 2007.
Brovkin, V., Sitch, S., von Bloh, W., Claussen, M., Bauer, E., and Cramer, W.: Role of land cover changes for atmospheric CO2 increase and climate change during the last 150 years, Global Change Biol. 10, 1253–1266, https://doi.org/10.1111/j.1365-2486.2004.00812.x, 2004.
Ciais, P., Piao, S.-L., Cadule, P., Friedlingstein, P., and Chédin, A.: Variability and recent trends in the African terrestrial carbon balance, Biogeosciences, 6, 1935–1948, https://doi.org/10.5194/bg-6-1935-2009, 2009.
Ciais, P., Bombelli, A., Williams, M., Piao, S. L., Chave, J., Ryan, C. M., Henry, M., Brender, P., and Valentini, R.: The carbon balance of Africa: synthesis of recent research studies, Philos. T. Roy. Soc. A, 369, 2038–2057, https://doi.org/10.1098/rsta.2010.0328, 2011.
DeFries, R. S., Houghton, R. A., Hansen, M. C., Field, C. B., Skole, D., and Townshend, J.: Carbon emissions from tropical deforestation and regrowth based on satellite observations for the 1980s and 1990s, P. Natl. Acad. Sci., 99, 14256–14261, https://doi.org/10.1073/pnas.182560099, 2002.
de Noblet-Ducoudré, N., Gervois, S., Ciais, P., Viovy, N., Brisson, N., Seguin, B., and Perrier, A.: Coupling the Soil-Vegetation-Atmosphere-Transfer Scheme ORCHIDEE to the agronomy model STICS to study the influence of croplands on the European carbon and water budgets, Agronomie, 24, 397–407, https://doi.org/10.1051/agro:2004038, 2004.
Doherty, R. M., Sitch, S., Smith, B., Lewis, S. L., and Thornton, P. K.: Implications of future climate and atmospheric CO2 content for regional biogeochemistry, biogeography and ecosystem across East Africa, Global Change Biol., 16, 617–640, https://doi.org/10.1111/j.1365-2486.2009.01997.x, 2010.
Döll, P. and Siebert, S.: A digital global map of irrigated areas-documentation, University of Kassel, Kassel, 1999.
Easterling, W. E., Aggarwal, P. K., Batima, P., Brander, K. M., Erda, L., Howden, S. M., Kirilenko, A., Morton, J., Soussana, J.-F., Schmidhuber, J., and Tubiello, F. N.: Food, fibre and forest products, in: Climate Change 2007: Impacts, Adaptation and Vulnerability, Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J., and Hanson, C. E., Cambridge University Press, Cambridge, UK, 273–313, 2007.
Evans, L. T.: Adapting and improving crops: the endless task, Philos. T. Roy. Soc. B, 352, 901–906, https://doi.org/10.1098/rstb.1997.0069, 1997.
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, https://doi.org/10.1126/science.1111772, 2005.
Friend, A. D., Arneth, A., Kiang, N. Y., Lomass, M., Ogée, J., Rödenbeck, C., Running, S. W., Santaren, J.-D., Sitch, S., Viovy, N., Woodward, F. I., and Zaehle, S.: FLUXNET and modelling the global carbon cycle, Global Change Biol., 13, 610–633, https://doi.org/10.1111/j.1365-2486.2006.01223.x, 2007.
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, https://doi.org/10.1016/j.jhydrol.2003.09.029, 2004.
Gervois, S., de Noblet-Ducoudré, N., Viovy, N., and Ciais, P.: Including croplands in a global biosphere model: methodology and evaluation at specific sites, Earth Interact., 8, 1–25, 2004.
Hall, P.: The poor quality of official socio-economic statistics relating to the rural tropical world: with special reference to south India, Mod. Asian Stud., 18, 491–514, 1984.
Hansen, M. C., Defries, R. S., Townshend, J. R. G., and Sohlberg, R.: Global land cover classification at 1 km spatial resolution using a classification tree approach, Int. J. Remote Sens., 21, 1331–1364, 2000.
Hély, C., Bremond, L., Alleaume, S., Smith, B., Sykes, M. T., and Guiot, J.: Sensitivity of African biomes to changes in the precipitation regime, Global Ecol. Biogeogr., 15, 258–270, https://doi.org/10.1111/j.1466-822x.2006.00235.x, 2006.
Heywood, V. H. (Ed.): Global biodiversity assessment, United nations environment programme, Cambridge University Press, Cambridge, 1995.
Hickler, T., Smith, B., Sykes, M. T., Davis, M. B., Sugita, S., and Walker, K.: Using a generalized vegetation model to simulate vegetation dynamics in the western Great Lakes region, USA, under alternative disturbance regimes, Ecology, 85, 519–530, 2004.
Hickler, T., Eklundh, L., Seaquist, J. W., Smith, B., Ardö, J., Olsson, L., Sykes, M. T., and Sjöström, M.: Precipitation controls Sahel greening trend, Geophys. Res. Lett., 32, L21415, https://doi.org/10.1029/2005GL024370, 2005.
Hickler, T., Prentice, I. C., Smith, B., Sykes, M. T., and Zaehle, S.: Implementing plant hydraulic architecture within the LPJ Dynamic Global Vegetation Model, Global Ecol. Biogeogr., 15, 567–577, https://doi.org/10.1111/j.1466-8238.2006.00254.x, 2006.
Hickler, T., Vohland, K., Feehan, J., Miller, P. A., Smith, B., Costa, L., Giesecke, T., Fronzek, S., Carter, T. R., Cramer, W., Kühn, I., and Sykes, M. T.: Projecting the future distribution of European potential natural vegetation zones with a generalized, tree species-based dynamic vegetation model, Global Ecol. Biogeogr., 21, 50–63, https://doi.org/10.1111/j.1466-8238.2010.00613.x, 2012.
Hidy, D., Barcza, Z., Haszpra, L., Churkina, G., Pinter, K., and Nagy, Z.: Development of the Biome-BGC model for simulation of managed herbaceous ecosystems, Ecol. Model., 226, 99–119, https://doi.org/10.1016/j.ecolmodel.2011.11.008, 2012.
Holben, B. N.: Characteristics of maximum-value composite images from temporal AVHRR data, Int. J. Remote Sens., 7, 1417–1437, https://doi.org/10.1080/01431168608948945, 1986.
Houghton, R. A.: Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000, Tellus B, 55, 378–390, https://doi.org/10.1034/j.1600-0889.2003.01450.x, 2003.
Houghton, R. A., Hobbie, J. E., Melillo, J. M., Moore, B., Peterson, B. J., Shaver, G. R., and Woodwell, G. M.: Changes in the carbon content of terrestrial biota and soils between 1860 and 1980: a net release of CO2 to the atmosphere, Ecol. Monogr., 53, 235–262, 1983.
IMAGE team: Implementation of the SRES scenarios: a comprehensive analysis of emissions, climate change and impacts in the 21st century, National institute for public health and the environment, CD-ROM publication 481508018, RIVM, Bilthoven, the Netherlands, 2001.
Jain, A. K. and Yang, X.: Modeling the effects of two different land cover change data sets on the carbon stocks of plants and soils in concert with CO2 and climate change, Global Biogeochem. Cy., 19, GB2015, https://doi.org/10.1029/2004GB002349, 2005.
Kaspersen, P. S., Fensholt, R., and Huber, S.: A spatiotemporal analysis of climatic drivers for observed changes in Sahelian vegetation productivity (1982–2007), Int. J. Geophys., 2011, 715321, https://doi.org/10.1155/2011/715321, 2011.
Klein Goldewijk, K. and Battjes, J. J.: A hundred year (1890–1990) database for integrated environmental assessments (HYDE, version 1.1), National institute of public health and the environment (RIVM), Bilthoven, the Netherlands, 1997.
Klein Goldewijk, L., Beusen, A., van Drecht, G., and de Vos, M.: The HYDE 3.1 spatially explicit database of human-induced global land use change over the past 12,000 years, Global Ecol. Biogeogr., 20, 73–86, https://doi.org/10.1111/j.1466-8238.2010.00587.x, 2011.
Kucharik, C. J. and Brye, K. R.: Integrated biosphere simulator (IBIS) yield and nitrate loss predictions for Wisconsin maize receiving varied amounts of nitrogen fertilizer, J. Environ. Qual., 32, 247–268, 2003.
Kucharik, C. J. and Twine, T. E.: Residue, respiration, and residuals: Evaluation of a dynamic agroecosystem model using eddy flux measurements and biometric data, Agr. Forest Meteorol., 146, 134–158, https://doi.org/10.1016/j.agrformet.2007.05.011, 2007.
Lal, R.: Carbon sequestration in dryland ecosystems of West Asia and North Africa, Land Degrad. Dev., 13, 45–59, https://doi.org/10.1002/ldr.477, 2002.
Leff, B., Ramankutty, N., and Foley, J. A.: Geographic distribution of major crops across the world, Global Biogeochem. Cy., 18, GB1009, https://doi.org/10.1029/2003GB002108, 2004.
Lehsten, V., Tansey, K., Balzter, H., Thonicke, K., Spessa, A., Weber, U., Smith, B., and Arneth, A.: Estimating carbon emissions from African wildfires, Biogeosciences, 6, 349–360, https://doi.org/10.5194/bg-6-349-2009, 2009.
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.
Lewis, S. L., Lopez-Gonzalez, G., Sonke, B., Affum-Baffoe, K., Baker, T. R., Ojo, L. O., Phillips, O. L., Reitsma, J. M., White, L., Comiskey, J. A., Djuikouo, K. M.-N., Ewango, C. E. N., Feldpausch, T. R., Hamilton, A. L., Gloor, M., Hart, T., Hladik, A., Lloyd, J., Lovett, J. C., Makana, J. R., Malhi, Y., Mbago, F. M., Ndangalasi, H. J., Peacock, J., Peh, K. S. H., Sheil, D., Sunderland, T. C. H., Swaine, M. D., Taplin, J., Taylor, D., Thomas, S. C., Votere, R., and Woll, H.: Increasing carbon storage in intact African tropical forests, Nature, 457, 1003–1006, https://doi.org/10.1038/nature07771, 2009.
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, https://doi.org/10.1111/j.1466-8238.2010.00563.x, 2010.
Liu, J., Fritz, S., van Wesenbeeck, C. F. A., Fuchs, M., You, L., Obersteiner, M., and Yang, H.: A spatially explicit assessment of current and future hotspots of hunger in Sub-Saharan Africa in the context of global change, Global Planet. Change, 64, 222–235, https://doi.org/10.1016/j.gloplacha.2008.09.007, 2008.
Lobell, D. B., Cassman, K. G., and Field, C. B.: Crop yield gaps: their importance, magnitudes and causes, Annu. Rev. Environ. Res., 34, 179–204, https://doi.org/10.1146/annurev.environ.041008.093740, 2009.
Long, S. P., Ainsworth, E. A., Leakey, A. D. B., Nösberger, J., and Ort, D. R.: Food for thought: lower-than-expected crop yield stimulation with rising CO2 concentrations, Science, 312, 1918–1921, https://doi.org/10.1126/science.1114722, 2006.
McGuire, A. D., Sitch, S., Clein, J. S., Dargaville, R., Esser, G., Foley, J., Heimann, M., Joos, F., Kaplan, J., Kicklighter, D. W., Meier, R. A., Melillo, J. M., Moore III, B., Prentice, I. C., Ramankutty, N., Reichenau, T., Schloss, A., Tian, H., Williams, L. J., and Wittenberg, U.: Carbon balance of the terrestrial biosphere in the twentieth century: Analyses of CO2, climate and land use effects with four process-based ecosystem models, Global Biogechem. Cy., 15, 183–206, https://doi.org/10.1029/2000GB001298, 2001.
Millennium Ecosystem Assessment: Ecosystems and Human Well-being: Synthesis, World Resources Institute, Island Press, Washington, D.C., 2005.
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.
Morales, P., Sykes, M. T., Prentice, I. C., Smith, P., Smith, B., Bugmann, H., Zierl, B., Friedlingstein, P., Viovy, N., Sabaté, S., Sanchez, A., Pla, E., Gracia, C. A., Sitch, S., Arneth, A., and Ogee, J.: Comparing and evaluating process-based ecosystem model predictions of carbon and water fluxes in major European forest biomes, Global Change Biol., 11, 2211–2233, https://doi.org/10.1111/j.1365-2486.2005.01036.x, 2005.
Müller, C., Eickhout, B., Zaehle, S., Bondeau, A., Cramer, W., and Lucht, W.: Effects of changes in CO2, climate, and land use on the carbon balance of the land biosphere during the 21st century, J. Geophys. Res.-Biogeo., 112, G02032, https://doi.org/10.1029/2006JG000388, 2007.
Müller, C., Bondeau, A., Popp, A., Waha, K., and Fader, M.: Climate change impacts on agricultural yields, Potsdam Institute for Climate Impact Research (PIK), Background note for the World Development Report 2010, Contribution to the World Development Report 2010: Development and Climate Change, The World Bank, Washington, D.C., 2009.
Müller, C., Cramer, W., Hare, W. L., and Lotze-Campen, H.: Climate change risks for African agriculture, P. Natl. Acad. Sci., 108, 4313–4315, https://doi.org/10.1073/pnas.1015078108, 2011.
Piao, S., Sitch, S., Ciais, P., Friedlingstein, P., Peylin, P., Wang, X., Ahlström, A., Anav, A., Canadell, J. G., Cong, N., Huntingford, C., Jung, M., Levis, S., Levy, P. E., Li, J., Lin, X., Lomas, M. R., Lu, M., Luo, Y., Ma, Y., Myneni, R. B., Poulter, B., Sun, Z., Wang, T., Viovy, N., Zaehle, S., and Zeng, N.: Evaluation of terrestrial carbon cycle models for their response to climate variabiity and and to CO2 trends, Global Change Biol., 19, 2117–2132, https://doi.org/10.1111/gcb.12187, 2013.
Pingali, P. L. and Pandey, S.: Meeting world maize needs: technological opportunities and priorities for the public sector, in: CIMMYT 1999/2000 World maize facts and trends, Meeting world maize needs: technological opportunities and priorities for the public sector, edited by: Pingali, P. L., CIMMYT, Mexico, 1–24, 2001.
Pitman, A. J., de Noblet-Ducoudré, N., Cruz, F. T., Davin, E. L., Bonan, G. B., Brovkin, V., Claussen, M., Delire, C., Ganzeveld, L., Gayler, V., van den Hurk, B. J. J. M., Lawrence, P. J., van der Molen, M. K., Müller, C., Reick, C. H., Seneviratne, S. I., Strengers, B. J., and Voldoire, A.: Uncertainties in climate responses to past land cover change: First results from the LUCID intercomparison study, Geophys. Res. Lett., 36, L14814, https://doi.org/10.1029/2009GL039076, 2009.
Ramankutty, N. and Foley, J. A.: Estimating historical changes in global land cover: croplands from 1700 to 1992, Global Biogechem. Cy., 13, 997–1028, https://doi.org/10.1029/1999GB900046, 1999.
Roudier, P., Sultan, B., Quirion, P., and Berg, A.: The impact of future climate change on West African crop yields: what does the recent literature say?, Global Environ. Change, 21, 1073–1083, https://doi.org/10.1016/j.gloenvcha.2011.04.007, 2011.
Rowhani, P., Lobell, D. B., Linderman, M., and Ramankutty, N.: Climate variability and crop production in Tanzania, Agr. Forest Metereol., 151, 449–460, https://doi.org/10.1016/j.agrformet.2010.12.002, 2011.
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.
Sellers, P. J.: Vegetation-canopy spectral reflectance and biophysical processes, in: Theory and applications of optical remote sensing, edited by: Asrar, G., Wiley, New York, 297–335, 1989.
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 vegetaion model, Global Change Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003.
Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M., Piao, S. L., Betts, R., Ciais, P., Cox, P., Friedlingstein, P., Jones, C. D., Prentice, I. C., and Woodward, F. I.: Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs), Global Change Biol., 14, 1–25, https://doi.org/10.1111/j.1365-2486.2008.01626.x, 2008.
Smith, B., Prentice, 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, https://doi.org/10.1046/j.1466-822X.2001.t01-1-00256.x, 2001.
Smith, B., Knorr, W., Widlowski, J.-L., Pinty, B., and Gobron, N.: Combining remote sensing data with process modelling to monitor boreal conifer forest carbon balances, Forest Ecol. Manage., 255, 3985–3994, https://doi.org/10.1016/j.foreco.2008.03.056, 2008.
Thonicke, K., Venevsky, S., Sitch, S., and Cramer, W. : The role of fire disturbance for global vegetation dynamics: coupling fire into a Dynamic Global Vegetation Model, Global Ecol. Biogeogr., 10, 661–678, https://doi.org/10.1046/j.1466-822X.2001.00175.x, 2001.
Tittonell, P., Vanlauwe, B., Corbeels, M., and Giller, K. E.: Yield gaps, nutient use efficiency and response to fertilizers by maize across heterogeneous smallholder farms of western Kenya, Plant Soil, 313, 19–37, https://doi.org/10.1007/s11104-008-9676-3, 2008.
Tubiello, F. N., Amthor, J. S., Boote, K. J., Donatelli, M., Easterling, W., Fischer, G., Gifford, R. M., Howden, M., Reilly, J., and Rosenzweig, C.: Crop response to elevated CO2 and world food supply: A comment on "Food for Thought\ldots" by Long et al., Science, 312, 1918–1921, 2006, Eur. J. Agron., 26, 215–223, https://doi.org/10.1016/j.eja.2006.10.002, 2007.
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D., Pak, E. W., Mahoney, R., Vermote, E., and Saleous, N. E.: An Extended AVHRR 8-km NDVI data set compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote Sens., 26, 4485–4498, https://doi.org/10.1080/01431160500168686, 2005.
Van den Hoof, C., Hanert, E., and Vidale, P. L.: Simulating dynamic crop growth with an adapted land surface model – JULES-SUCROS: Model development and validation, Agr. Forest Meteorol., 151, 137–153, https://doi.org/10.1016/j.agrformet.2010.09.011, 2011.
Van der Werf, G. R., Randerson, J. T., Giglio, L., Gobron, N., and Dolman, A. J.: Climate controls on the variability of fires in the tropics and subtropics, Global Biogeochem. Cy., 22, GB3028, https://doi.org/10.1029/2007GB003122, 2008.
Waha, K., van Bussel, L. G. J., Müller, C., and Bondeau, A.: Climate-driven simulation of global crop sowing dates, Global Ecol. Biogeogr., 21, 247–259, https://doi.org/10.1111/j.1466-8238.2011.00678.x, 2012.
Waha, K., Müller, C., Bondeau, A., Dietrich, J. P., Kurukulasuriya, P., Heinke, J., and Lotze-Campen, H.: Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa, Global Environ. Change, 23, 130–143, https://doi.org/10.1016/j.gloenvcha.2012.11.001, 2013.
Weber, U., Jung, M., Reichstein, M., Beer, C., Braakhekke, M. C., Lehsten, V., Ghent, D., Kaduk, J., Viovy, N., Ciais, P., Gobron, N., and Rödenbeck, C.: The interannual variability of Africa's ecosystem productivity: a multi-model analysis, Biogeosciences, 6, 285–295, https://doi.org/10.5194/bg-6-285-2009, 2009.
Williams, C. A., Hanan, N. P., Neff, J. C., Scholes, R. J., Berry, J. A., Denning, A. S., and Baker, D. F.: Africa and the global carbon cycle, Carbon Balance Manage., 2, 3, https://doi.org/10.1186/1750-0680-2-3, 2007.
Wramneby, A., Smith, B., and Samuelsson, P.: Hotspots of vegetation-climate feedbacks under future greenhouse forcing in Europe, J. Geophys. Res., 115, D21119, https://doi.org/10.1029/2010JD014307, 2010.
You, L., Wood, S., and Wood-Sichra, U.: Generating plausible crop distribution maps for Sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach, Agr. Syst., 99, 126–140, 2009.
Zaehle, S., Ciais, P., Friend, A. D., and Prieur, V.: Carbon benefits of anthropogenic reactive nitrogen offset by nitrous oxide emissions, Nat. Geosci., 4, 601–605, https://doi.org/10.1038/NGEO1207, 2011.
Ziervogel, G., Cartwright, A., Tas, A., Adejuwon, J., Zermoglio, F., Shale, M., and Smith, B.: Climate change and adaptation in African agriculture, Rep., Stockholm Environment Institute, Stockholm, 2008.
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