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Stevanović, M.; Popp, A.; Lotze-Campen, H.; Dietrich, J.P.; Müller, C.; Bonsch, M.; Schmitz, C.; Bodirsky, B.L.; Humpenöder, F.; Weindl, I. |
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Title |
The impact of high-end climate change on agricultural welfare |
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Journal Article |
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2016 |
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Science Advances |
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Sci. Adv. |
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2 |
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8 |
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e1501452 |
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Climate change threatens agricultural productivity worldwide, resulting in higher food prices. Associated economic gains and losses differ not only by region but also between producers and consumers and are affected by market dynamics. On the basis of an impact modeling chain, starting with 19 different climate projections that drive plant biophysical process simulations and ending with agro-economic decisions, this analysis focuses on distributional effects of high-end climate change impacts across geographic regions and across economic agents. By estimating the changes in surpluses of consumers and producers, we find that climate change can have detrimental impacts on global agricultural welfare, especially after 2050, because losses in consumer surplus generally outweigh gains in producer surplus. Damage in agriculture may reach the annual loss of 0.3% of future total gross domestic product at the end of the century globally, assuming further opening of trade in agricultural products, which typically leads to interregional production shifts to higher latitudes. Those estimated global losses could increase substantially if international trade is more restricted. If beneficial effects of atmospheric carbon dioxide fertilization can be realized in agricultural production, much of the damage could be avoided. Although trade policy reforms toward further liberalization help alleviate climate change impacts, additional compensation mechanisms for associated environmental and development concerns have to be considered. |
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MA @ admin @ |
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5003 |
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Kriegler, E.; Bauer, N.; Popp, A.; Humpenöder, F.; Leimbach, M.; Strefler, J.; Baumstark, L.; Bodirsky, B.L.; Hilaire, J.; Klein, D.; Mouratiadou, I.; Weindl, I.; Bertram, C.; Dietrich, J.-P.; Luderer, G.; Pehl, M.; Pietzcker, R.; Piontek, F.; Lotze-Campen, H.; Biewald, A.; Bonsch, M.; Giannousakis, A.; Kreidenweis, U.; Müller, C.; Rolinski, S.; Schultes, A.; Schwanitz, J.; Stevanovic, M.; Calvin, K.; Emmerling, J.; Fujimori, S.; Edenhofer, O. |
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Title |
Fossil-fueled development (SSP5): An energy and resource intensive scenario for the 21st century |
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Journal Article |
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2017 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
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42 |
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297-315 |
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Shared Socio-economic Pathway; SSP5; Emission scenario; Energy transformation; Land-use change; Integrated assessment modeling |
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Highlights • The SSP5 scenarios mark the upper end of the scenario literature in fossil fuel use, food demand, energy use and greenhouse gas emissions. • The SSP5 marker scenario results in a radiative forcing pathway close to the highest Representative Concentration Pathway (RCP8.5). • An investigation of mitigation policies in SSP5 confirms high socio-economic challenges to mitigation in SSP5. • In SSP5, ambitious climate targets require land based carbon management options such as avoided deforestation and bioenergy production with CCS. • The SSP5 scenarios provide useful reference points for future climate change, impact, adaption, mitigation and sustainable development analysis. Abstract This paper presents a set of energy and resource intensive scenarios based on the concept of Shared Socio-Economic Pathways (SSPs). The scenario family is characterized by rapid and fossil-fueled development with high socio-economic challenges to mitigation and low socio-economic challenges to adaptation (SSP5). A special focus is placed on the SSP5 marker scenario developed by the REMIND-MAgPIE integrated assessment modeling framework. The SSP5 baseline scenarios exhibit very high levels of fossil fuel use, up to a doubling of global food demand, and up to a tripling of energy demand and greenhouse gas emissions over the course of the century, marking the upper end of the scenario literature in several dimensions. These scenarios are currently the only SSP scenarios that result in a radiative forcing pathway as high as the highest Representative Concentration Pathway (RCP8.5). This paper further investigates the direct impact of mitigation policies on the SSP5 energy, land and emissions dynamics confirming high socio-economic challenges to mitigation in SSP5. Nonetheless, mitigation policies reaching climate forcing levels as low as in the lowest Representative Concentration Pathway (RCP2.6) are accessible in SSP5. The SSP5 scenarios presented in this paper aim to provide useful reference points for future climate change, climate impact, adaption and mitigation analysis, and broader questions of sustainable development. |
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0959-3780 |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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5005 |
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Stevanović, M.; Popp, A.; Bodirsky, B.L.; Humpenöder, F.; Müller, C.; Weindl, I.; Dietrich, J.P.; Lotze-Campen, H.; Kreidenweis, U.; Rolinski, S.; Biewald, A.; Wang, X. |
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Mitigation Strategies for Greenhouse Gas Emissions from Agriculture and Land-Use Change: Consequences for Food Prices |
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Journal Article |
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2017 |
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Environmental Science and Technology |
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Environmental Science and Technology |
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51 |
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1 |
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365-374 |
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The land use sector of agriculture, forestry, and other land use (AFOLU) plays a central role in ambitious climate change mitigation efforts. Yet, mitigation policies in agriculture may be in conflict with food security related targets. Using a global agro-economic model, we analyze the impacts on food prices under mitigation policies targeting either incentives for producers (e.g., through taxes) or consumer preferences (e.g., through education programs). Despite having a similar reduction potential of 43-44% in 2100, the two types of policy instruments result in opposite outcomes for food prices. Incentive-based mitigation, such as protecting carbon-rich forests or adopting low-emission production techniques, increase land scarcity and production costs and thereby food prices. Preference-based mitigation, such as reduced household waste or lower consumption of animal-based products, decreases land scarcity, prevents emissions leakage, and concentrates production on the most productive sites and consequently lowers food prices. Whereas agricultural emissions are further abated in the combination of these mitigation measures, the synergy of strategies fails to substantially lower food prices. Additionally, we demonstrate that the efficiency of agricultural emission abatement is stable across a range of greenhouse-gas (GHG) tax levels, while resulting food prices exhibit a disproportionally larger spread. |
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0013-936x |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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5007 |
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Wang, E.; Martre, P.; Zhao, Z.; Ewert, F.; Maiorano, A.; Rötter, R.P.; Kimball, B.A.; Ottman, M.J.; Wall, G.W.; White, J.W.; Reynolds, M.P.; Alderman, P.D.; Aggarwal, P.K.; Anothai, J.; Basso, B.; Biernath, C.; Cammarano, D.; Challinor, A.J.; De Sanctis, G.; Doltra, J.; Fereres, E.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L.A.; Izaurralde, R.C.; Jabloun, M.; Jones, C.D.; Kersebaum, K.C.; Koehler, A.-K.; Liu, L.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Palosuo, T.; Priesack, E.; Eyshi Rezaei, E.; Ripoche, D.; Ruane, A.C.; Semenov, M.A.; Shcherbak, I.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P.; Waha, K.; Wallach, D.; Wang, Z.; Wolf, J.; Zhu, Y.; Asseng, S. |
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The uncertainty of crop yield projections is reduced by improved temperature response functions |
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Journal Article |
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2017 |
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Nature Plants |
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Nature Plants |
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3 |
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17102 |
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Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections. Erratum: doi: 10.1038/nplants.2017.125 |
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2017-08-28 |
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CropM, ft_macsur |
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MA @ admin @ |
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5173 |
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Challinor, A.J.; Müller, C.; Asseng, S.; Deva, C.; Nicklin, K.J.; Wallach, D.; Vanuytrecht, E.; Whitfield, S.; Ramirez-Villegas, J.; Koehler, A.-K. |
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Improving the use of crop models for risk assessment and climate change adaptation |
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2017 |
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Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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159 |
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296-306 |
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Crop model; Risk assessment; Climate change impacts; Adaptation; Climate models; Uncertainty |
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Highlights
• 14 criteria for use of crop models in assessments of impacts, adaptation and risk • Working with stakeholders to identify timing of risks is key to risk assessments. • Multiple methods needed to critically assess the use of climate model output • Increasing transparency and inter-comparability needed in risk assessments
Abstract
Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper. |
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phase 2+ |
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0308521x |
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CropM, ft_macsur |
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MA @ admin @ |
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5175 |
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