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Deryng, D., J. Elliot, C. Folberth, C. Müller, T.A.M. Pugh, K.J. Boote, D. Conway, A.C. Ruane, D. Gerten, J.W. Jones, N. Khabarov, S. Olin, S. Schaphoff, E. Schmid, H. Yang, and C. Rosenzweig. (2016). Regional disparities in the beneficial effects of rising CO2 concentrations on crop water productivity. Naturere Climate Change, 6(8), 786–790.
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Ginaldi, F., M. Bindi, A.D. Marta, R. Ferrise, S. Orlandini, and F. Danuso. (2016). Interoperability of agronomic long term experiment databases and crop model intercomparison: the Italian experience. EJA, 77, 209–222.
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Müller, C., and J. Elliott. (2015). The Global Gridded Crop Model Intercomparison: Approaches, insights and caveats for modelling climate change impacts on agriculture at the global scale. In Aziz Elbehri (Ed.), Climate Change and food systems: global assessments and implications for food security and trade (pp. 28–59). Rome: Food and Agriculture Organization of the United Nations (FAO).
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Shikuku, K. M., R.O. Valdivia, B.K. Paul, C. Mwongera, L. Winowiecki, P. Läderach, M. Herrero, and S. Silvestri. (2016). Prioritizing climate-smart livestock technologies in rural Tanzania: A minimum data approach. Agricultural Systems, In Press.
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Bennetzen, E. H., P. Smith, J.F. Soussana, and J. R. Porter. (2012). Identity-Based Estimation of Greenhouse Gas Emissions from Crop Production: Case Study from Denmark. European Journal of Agronomy, 41, 66–72.
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  This literature database is maintained by the The Agricultural Model Intercomparison and Improvement Project (AgMIP). You're welcome to send any questions or suggestions to our feedback address. The database is powered by refbase, an open source database front-end for managing scientific literature & citations. powered by refbase