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Humpenöder, F.; Popp, A.; Stevanovic, M.; Müller, C.; Bodirsky, B.L.; Bonsch, M.; Dietrich, J.P.; Lotze-Campen, H.; Weindl, I.; Biewald, A.; Rolinski, S. |
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Land-use and carbon cycle responses to moderate climate change: implications for land-based mitigation |
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2015 |
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Environmental Science and Technology |
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Environ Sci Technol |
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49 |
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11 |
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6731-6739 |
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Climate change has impacts on agricultural yields, which could alter cropland requirements and hence deforestation rates. Thus, land-use responses to climate change might influence terrestrial carbon stocks. Moreover, climate change could alter the carbon storage capacity of the terrestrial biosphere and hence the land-based mitigation potential. We use a global spatially explicit economic land-use optimization model to (a) estimate the mitigation potential of a climate policy that provides economic incentives for carbon stock conservation and enhancement, (b) simulate land-use and carbon cycle responses to moderate climate change (RCP2.6), and (c) investigate the combined effects throughout the 21st century. The climate policy immediately stops deforestation and strongly increases afforestation, resulting in a global mitigation potential of 191 GtC in 2100. Climate change increases terrestrial carbon stocks not only directly through enhanced carbon sequestration (62 GtC by 2100) but also indirectly through less deforestation due to higher crop yields (16 GtC by 2100). However, such beneficial climate impacts increase the potential of the climate policy only marginally, as the potential is already large under static climatic conditions. In the broader picture, this study highlights the importance of land-use dynamics for modeling carbon cycle responses to climate change in integrated assessment modeling. |
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0013-936x |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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4998 |
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Hoveid, Ø. |
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A prototype dynamic stochastic equilibrium model of the global food system |
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2015 |
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FACCE MACSUR Reports |
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4 |
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SP4-6 |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, 25–27 November 2014, Hurdalsjø, Norway |
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MA @ admin @ |
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2196 |
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Hoveid, Ø. |
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An economist’s wish list for soil and crop modelling |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-25 |
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A requirement for successful integration of soil, crop and economic models is a relevant interface of the three. Economic farming models deal with choice of crops, crop management during growing season and stock management after harvest. With detailed daily weather information the state of the soil might be simulated so that a suitable sowing date can be estimated. Moreover with rational beliefs with respect to future crop prices, and with a crop model which responds to management, the management during the growing season might be optimized with respect to choice of cultivar, fertilization and irrigation. So far, as reflected by Müller and Robertson (2014), predictions of future crop yields according to crop models take only to small extent such farmer responses into account, and might therefore overestimate the responses of crop harvests to climate.Comparison of soil, crop and economic simulations with observed weather and crop outcomes might lead to estimation/calibration of unobserved parameters in all models. Such exercises need generic soil, crop and economic models which do not leave modelling outcomes to the crop modeller’s or economist’s discretion. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2140 |
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Hoveid, Ø. |
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A prototype stochastic dynamic equilibrium model of the global food system |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-24 |
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The risks of food consumption are primarily linked to those of food production due to stochastic weather. Other sources of risk are associated with break-down of food trade or transport for weather or political reasons. Hopefully, future cures against increased risk due to climate change may be found with new agricultural technologies, systems of storage from favorable to unfavorable periods, more flexible trade-arrangements between favorable and unfavorable places. However, in the short run one has to rely on the available technology, storage facilities and trade agreements. With a realistic model of the stochastic global food system, it should be possible to measure risks of certain extreme unfavorable events.A realistic case will have countries with different climate in different growing seasons. Markets will be open for trade at a number of points per year, in which decisions of production, storage, trade and consumption can be coordinated as a static equilibrium. Determinants of this equilibrium are the weather up to this date reflected in the state of crops, the available harvested stocks and the decision-maker’s preferences. With a global stochastic process of weather, a stochastic sequence of equilibria follows. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2139 |
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Author |
Hoveid, Ø. |
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Title |
Prototype of stochastic equilibrium model of the food system |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-T2.5 |
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Food security is an issue of risk. If climate change is not responded to with diet, technology and/or policy changes, it may lead to reduced food security for the world population, in particular the poorer part which in longer periods may not afford to purchase food in sufficient quantity and quality. In order to improve the situation, certain policy changes may be required. In some cases are policy recommendations relatively obvious, while in other cases a deeper insight in the stochastic dynamics of food supply and storage is required to assess the consequences of policy proposals. The relatively obvious part is that farmers need be responsive in periods of low total production, so that sufficient supply restores quickly. Moreover, trade should allow local shortages to be covered. Many national policies with the goal of self-sufficiency aim in the opposite direction with stable prices and production and relatively less flexibility in production. The stochastic dynamics of food supply can be analysed in more detail with a dynamic stochastic general equilibrium model (DSGE). Although agriculture by nature is about taking decisions under uncertainty, quantitative stochastic dynamic models for policy analysis in agriculture have not yet emerged. The contribution in MACSUR is a formalization of a class of DSGE-s based on representation of biological processes managed with regard to outcomes due to uncertain nature. No Label |
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MA @ admin @ |
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2115 |
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