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Ruiz-Ramos, M.; Ferrise, R.; Rötter, R. |
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Concepts and methods developed for probabilistic evaluation of a number of alternative adaptation options |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C4.5.1 |
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The purpose of this document is to define the protocol for a second study (IRS2) based on impact response surfaces (IRSs) in the frame of CropM/WP4. General considerations of IRS construction are described in the protocol developed for Phase I of the IRS analysis (IRS1)Access to the full document is restricted to MACSUR members until 2015-11-01. No Label |
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MA @ admin @ |
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2105 |
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Savary, S.; Nelson, A.D.; Djurle, A.; Esker, P.; Sparks, A.; Amorim, L.; Bergamin Filho, A.; Caffi, T.; Castilla, N.; Garrett, K.; McRoberts, N.; Rossi, V.; Yuen, J.; Willocquet, L. |
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Concepts, approaches, and avenues for modelling crop health and crop losses |
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2017 |
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FACCE MACSUR Reports |
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10 |
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C1.5-D |
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Main text in preparation for publication in a peer-reviewed journal) |
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CropM |
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MA @ admin @ |
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4952 |
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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.; Wisser, D. |
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Title |
Constraints and potentials of future irrigation water availability on agricultural production under climate change |
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Journal Article |
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2013 |
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Proceedings of the National Academy of Sciences of the United States of America |
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Proc. Natl. Acad. Sci. U. S. A. |
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111 |
Issue |
9 |
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3239-3244 |
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Agricultural Irrigation/economics/*methods; Agriculture/economics/*methods; Carbon Dioxide/analysis; *Climate Change; Computer Simulation; Forecasting; *Models, Theoretical; Water Supply/*statistics & numerical data; adaptation; agriculture; hydrology; uncertainty |
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We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400-1,400 Pcal (8-24% of present-day total) when CO2 fertilization effects are accounted for or 1,400-2,600 Pcal (24-43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20-60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600-2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required. |
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2016-10-31 |
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0027-8424 1091-6490 |
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CropM |
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MA @ admin @ |
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4790 |
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Tao, F.; Roetter, R.P.; Palosuo, T.; Hernandez Diaz-Ambrona, C.G.; Ines Minguez, M.; Semenov, M.A.; Kersebaum, K.C.; Nendel, C.; Specka, X.; Hoffmann, H.; Ewert, F.; Dambreville, A.; Martre, P.; Rodriguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Hohn, J.G.; Salo, T.; Ferrise, R.; Bindi, M.; Cammarano, D.; Schulman, A.H. |
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Title |
Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments |
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Journal Article |
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2018 |
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Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
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24 |
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3 |
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1291-1307 |
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barley; climate change; Europe; impact; super-ensemble; uncertainty; Nitrogen Dynamics; Multimodel Ensembles; Simulation-Models; Change; Scenarios; Yield; Rice; Weather; Growth; Wheat; Maize |
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Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources. |
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2018-03-08 |
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1354-1013 |
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CropM, ft_macsur |
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MA @ admin @ |
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5194 |
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Dirnböck, T.; Bezák, P.; Dullinger, S.; Haberl, H.; Lotze-Campen, H.; Mirtl, M.; Peterseil, J.; Redpath, S.; Singh, S.J.; Travis, J.; Wijdeven, S.M.J. |
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Title |
Critical Scales for Long-Term Socio-ecological Biodiversity Research |
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Book Chapter |
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2013 |
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Abbreviated Journal |
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123-138 |
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TradeM |
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Springer |
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Dordrecht |
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Singh, S.J.; Haberl, H.; Chertow, M.; Mirtl, M.; Schmid, M. |
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Long Term Socio-Ecological Research |
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Human-environment interactions (2) |
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MA @ admin @ |
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2390 |
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