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Author Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Ruane, A.C.; Boote, K.J.; Thorburn, P.J.; Rötter, R.P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J.
Title Uncertainty in simulating wheat yields under climate change Type Journal Article
Year 2013 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change
Volume 3 Issue 9 Pages 827-832
Keywords crop production; models; food; co2; temperature; projections; adaptation; scenarios; ensemble; impacts
Abstract Projections of climate change impacts on crop yields are inherently uncertain(1). Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate(2). However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models(1,3) are difficult(4). Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1758-678x ISBN (down) Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur, IPCC-AR5 Approved no
Call Number MA @ admin @ Serial 4599
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Author Montesino-San Martín, M.; Olesen, J.E.; Porter, J.R.
Title Can crop-climate models be accurate and precise? A case study for wheat production in Denmark Type Journal Article
Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 202 Issue Pages 51-60
Keywords Uncertainty; Model intercomparison; Bayesian approach; Climate change; Wheat; Denmark; uncertainty analysis; simulation-models; bayesian-approach; change; impact; yields; variability; projections; scale; calibration; framework
Abstract Crop models, used to make projections of climate change impacts, differ greatly in structural detail. Complexity of model structure has generic effects on uncertainty and error propagation in climate change impact assessments. We applied Bayesian calibration to three distinctly different empirical and mechanistic wheat models to assess how differences in the extent of process understanding in models affects uncertainties in projected impact. Predictive power of the models was tested via both accuracy (bias) and precision (or tightness of grouping) of yield projections for extrapolated weather conditions. Yields predicted by the mechanistic model were generally more accurate than the empirical models for extrapolated conditions. This trend does not hold for all extrapolations; mechanistic and empirical models responded differently due to their sensitivities to distinct weather features. However, higher accuracy comes at the cost of precision of the mechanistic model to embrace all observations within given boundaries. The approaches showed complementarity in sensitivity to weather variables and in accuracy for different extrapolation domains. Their differences in model precision and accuracy make them suitable for generic model ensembles for near-term agricultural impact assessments of climate change.
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1923 ISBN (down) Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4572
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Author Galán, E.; Sanchis, E.; Estellés, F.; Calvet, S.; del Prado, A.
Title Heat stress effects in milk yield and milk traits at farm scale Type Journal Article
Year 2016 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences
Volume 7 Issue 03 Pages 238-239
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2040-4700 ISBN (down) Medium
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4871
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Author Schönhart, M.
Title Heat stress impacts on cows in a case study landscape measured by an integrated modelling framework Type Journal Article
Year 2016 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences
Volume 7 Issue 03 Pages 235-237
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN 2040-4700 ISBN (down) Medium
Area Expedition Conference
Notes LiveM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4872
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Author Mendes, L.B.; Herrero, M.; Havlík, P.; Mosnier, A.; Balieiro, S.F.; Moreira, R.E.M.; Obersteiner, M.
Title Simulation of enteric methane emissions from individual beef cattle in tropical pastures of improving quality: a case study with the model RUMINANT Type Journal Article
Year 2016 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences
Volume 7 Issue 03 Pages 233-234
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2040-4700 ISBN (down) Medium
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4873
Permanent link to this record