Page 101 - Climate Change and Food Systems

crops in the IMPACT model based on similarities in their photosynthetic metabolic pathways. Crop area also adjusts in response to climate change, due to changes in water availability for irrigated area and changes in the suitability of cropping areas.
To quantify uncertainty on the demand side, Nelson et al. (2010) develop three projections
of optimistic, pessimistic, and middle-of-the-
road (baseline) scenarios for future income and population growth. With five climate scenarios and three demand scenarios, they thus carry out 15 simulations, reporting both mean and standard deviations for key results.
Nelson et al. (2010) find that climate change
will slightly reduce average annual yield growth over 2010-2050 from rates that are projected to be otherwise positive for all countries/commodities. Global food prices are expected to rise in the future as demand, driven by population growth and rising incomes, increases relative to supply; climate change will add to those upward price pressures. By 2050, mean projected price increases are
87 percent for maize, 31 percent for rice, and
44 percent for wheat in the most optimistic scenario, compared to 2010. The mean price increases in 2050 with climate change, relative
to the 2050 price with perfect mitigation, are
33 percent , 18 percent and 23 percent for maize, rice and wheat. These results are driven by climate change-induced yield reductions countered by yield-boosting technology change, and demand- raising population and gross domestic product (GDP) growth.
In the IMPACT model, food security is proxied by two measures: average daily per capita calorie availability and the number of malnourished children under 5. Without climate change, productivity gains and income growth will reduce the number of malnourished children by up to
46 percent in 2050 relative to 2010 in the most optimistic scenario. Some of this achievement will be lost due to climate change.
Using this model, the authors run a scenario of protracted drought in South Asia and assume that adaptation takes place and translates into higher
agricultural productivity growth rates (between
2 to 2.5 percent annually for many crops) and improved irrigation efficiency. Under this scenario, the number of malnourished children declines and world agricultural price increases are substantially lowered, in some cases more than offsetting
the price increases caused by climate change. These results are driven more by assumed higher productivity rates than by increased irrigation water efficiency since most crop production in Asia is currently rainfed. The authors also conclude that global trade plays a dampening effect, absorbing some of the impacts of climate shocks to individual regions.
Felkner et al.’s (2009) partial equilibrium
analysis of rice production in Thailand is of substantial interest because it describes the importance of economic adaptations in reducing the negative yield effects of climate change described in crop yield simulation models. Their study integrates GCM and DSSAT crop simulation models with an estimated three-stage production function to describe rice yield and output in a northeastern province of Thailand. Crop simulation models, calibrated to household rice plots, describe the effects of changes in climate and the use of intermediate inputs, such as seeds and fertilizers, on output at the end of stages one and two of the growing season. The economic model describes farmers’ input demand in response to realized output at intermediate stages in the growth process, their adaptive expectations about rainfall, and the prices of inputs and outputs.
Projected climate change is described by ensemble mean monthly projections from multiple climate models processed by a weather simulator to generate 100 realizations each of future climate in 2040-2069 relative to 1960-90. They choose output for the highest (A1F) and lowest (B1) emission scenarios from GCMs used in the Third Assessment.
At the plot level, the predictions of the DSSAT models and the economic models are starkly different. DSSAT models, which assume no adaptive changes in inputs, predict severe declines in yields for about one third of the plots,
chapter 3: economic modelling of climate impacts and adaptation in agriculture: a survey of methods, results and gaps
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