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Author Weindl, I.; Lotze-Campen, H.; Popp, A.; Müller, C.; Havlík, P.; Herrero, M.; Schmitz, C.; Rolinski, S. url  doi
openurl 
  Title Livestock in a changing climate: production system transitions as an adaptation strategy for agriculture Type Journal Article
  Year 2015 Publication Environmental Research Letters Abbreviated Journal Environ. Res. Lett.  
  Volume 10 Issue (up) 9 Pages 094021  
  Keywords livestock; climate impacts; land use modeling; adaptation costs; production systems; greenhouse-gas emissions; global change; management implications; developing-countries; crop productivity; change mitigation; food security; model; impacts; carbon  
  Abstract Livestock farming is the world’s largest land use sector and utilizes around 60% of the global biomass harvest. Over the coming decades, climate change will affect the natural resource base of livestock production, especially the productivity of rangeland and feed crops. Based on a comprehensive impact modeling chain, we assess implications of different climate projections for agricultural production costs and land use change and explore the effectiveness of livestock system transitions as an adaptation strategy. Simulated climate impacts on crop yields and rangeland productivity generate adaptation costs amounting to 3% of total agricultural production costs in 2045 (i.e. 145 billion US$). Shifts in livestock production towards mixed crop-livestock systems represent a resource-and cost-efficient adaptation option, reducing agricultural adaptation costs to 0.3% of total production costs and simultaneously abating deforestation by about 76 million ha globally. The relatively positive climate impacts on grass yields compared with crop yields favor grazing systems inter alia in South Asia and North America. Incomplete transitions in production systems already have a strong adaptive and cost reducing effect: a 50% shift to mixed systems lowers agricultural adaptation costs to 0.8%. General responses of production costs to system transitions are robust across different global climate and crop models as well as regarding assumptions on CO2 fertilization, but simulated values show a large variation. In the face of these uncertainties, public policy support for transforming livestock production systems provides an important lever to improve agricultural resource management and lower adaptation costs, possibly even contributing to emission reduction.  
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  Language English Summary Language Original Title  
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  ISSN 1748-9326 ISBN Medium Article  
  Area Expedition Conference  
  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4718  
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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. url  doi
openurl 
  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 (up) 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  
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  Series Volume Series Issue Edition  
  ISSN 1758-678x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur, IPCC-AR5 Approved no  
  Call Number MA @ admin @ Serial 4599  
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Author Nelson, G.C.; Valin, H.; Sands, R.D.; Havlík, P.; Ahammad, H.; Deryng, D.; Elliott, J.; Fujimori, S.; Hasegawa, T.; Heyhoe, E.; Kyle, P.; Von Lampe, M.; Lotze-Campen, H.; Mason d’Croz, D.; van Meijl, H.; van der Mensbrugghe, D.; Müller, C.; Popp, A.; Robertson, R.; Robinson, S.; Schmid, E.; Schmitz, C.; Tabeau, A.; Willenbockel, D. doi  openurl
  Title Climate change effects on agriculture: economic responses to biophysical shocks Type Journal Article
  Year 2014 Publication Proceedings of the National Academy of Sciences of the United States of America Abbreviated Journal Proc. Natl. Acad. Sci. U. S. A.  
  Volume 111 Issue (up) 9 Pages 3274-3279  
  Keywords Agriculture/*economics; Carbon Dioxide/analysis; *Climate Change; Commerce/statistics & numerical data; Computer Simulation; Crops, Agricultural/*growth & development; Forecasting; Humans; *Models, Economic; agricultural productivity; climate change adaptation; integrated assessment; model intercomparison  
  Abstract Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.  
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  Language English Summary Language Original Title  
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  ISSN 0027-8424 1091-6490 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4535  
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Author Trnka, M.; Feng, S.; Semenov, M.A.; Olesen, J.E.; Kersebaum, K.C.; Roetter, R.P.; Semeradova, D.; Klem, K.; Huang, W.; Ruiz-Ramos, M.; Hlavinka, P.; Meitner, J.; Balek, J.; Havlik, P.; Buntgen, U. doi  openurl
  Title Mitigation efforts will not fully alleviate the increase in water scarcity occurrence probability in wheat-producing areas Type Journal Article
  Year 2019 Publication Science Advances Abbreviated Journal Sci. Adv.  
  Volume 5 Issue (up) 9 Pages eaau2406  
  Keywords climate-change impacts; sub-saharan africa; atmospheric co2; crop; yields; drought; agriculture; variability; irrigation; adaptation; carbon  
  Abstract Global warming is expected to increase the frequency and intensity of severe water scarcity (SWS) events, which negatively affect rain-fed crops such as wheat, a key source of calories and protein for humans. Here, we develop a method to simultaneously quantify SWS over the world’s entire wheat-growing area and calculate the probabilities of multiple/sequential SWS events for baseline and future climates. Our projections show that, without climate change mitigation (representative concentration pathway 8.5), up to 60% of the current wheat-growing area will face simultaneous SWS events by the end of this century, compared to 15% today. Climate change stabilization in line with the Paris Agreement would substantially reduce the negative effects, but they would still double between 2041 and 2070 compared to current conditions. Future assessments of production shocks in food security should explicitly include the risk of severe, prolonged, and near- simultaneous droughts across key world wheat-producing areas.  
  Address 2020-02-14  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2375-2548 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5227  
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