Page 91 - Climate Change and Food Systems

chapter 3: economic modelling of climate impacts and adaptation in agriculture: a survey of methods, results and gaps
targeting methane and black carbon reduction that could, in combination, reduce projected mean global warming by about 0.5C by 2050.
4. Pathway models
Climate change operates indirectly, through multiple pathways, to affect economic activity and human well-being. These pathways include the biophysical effects of changes in temperature, precipitation
and CO2 on crop yields, human health, and plant pests and diseases. Sea level rise reduces the
land available for cultivation and other economic activities. Storms and flooding can destroy infrastructure, raising the costs of transportation
and communication in all sectors of an economy. Climate change also affects hydrological processes and alters surface and groundwater dynamics, with significant impacts on agriculture and non-agriculture water supply. Pathway models quantify such impacts of climate change and generate data used as inputs (or shocks) into economic models. The economic impact assessment models surveyed here focus largely on the economic effects of crop yield shocks, as well as the effects of water supply and demand dynamics. Only briefly do we touch on other pathways, such as rising sea levels, that have direct implications for agriculture. Most include only crop yield shocks, but an increasing number of economic models now account for multiple pathways.
4.1 Crop yield models
Dynamic crop growth simulation models
Crop yield models describe the effects of changes in temperature, precipitation and, in some cases, CO2 on crop yields. There are two different types of crop yield models: dynamic crop growth simulation models and statistical yield models.
(and the extent of its deviation from an initial
state, typically chosen as the pre-industrial CO2 concentration level of 280 part per million value or ppmv) and the corresponding increase in radiative energy on the earth surface (measured in watts/ m2). Increased radiative energy in turn translates into higher average temperature (IPCC, 2007).
Dynamic crop growth simulation models simulate plant growth processes and yields.
They are called “process” models because they explicitly describe the effects of location-specific environmental conditions (such as temperature and precipitation), plant genetics and farm management practices (such as fertilizer use or planting times) on the biological plant growth process. The models are dynamic in the sense that they simulate incremental, usually daily, changes in plant growth in response to changes in environmental conditions and management practices over the duration of the growing season. The models exclude the role of labour and most exclude plant pests and disease, albeit a new generation of models used for the IPPC Fifth Assessment does attempt to include some of these additional effects.
A crop growth simulation model is calibrated
to local growing conditions, often at the field level, using site data on weather for the duration of the growing season, site soils and farm management practices. Selected model parameters are then adjusted, or calibrated, until the crop model
can replicate the historic, daily plant growth process over the growing season. To simulate climate change impacts, projected changes in temperatures and rainfall replace the historic observations, and plant growth responses are observed. A growing number of models also simulate the effects of higher atmospheric concentrations of CO2. While higher CO2 levels can stimulate plant vegetative growth, the magnitude of this effect is highly debated (Ainsworth et al., 2008; Tubiello et al., 2007).
A large number of crop growth simulation models have been used to support the analysis of climate change, agriculture and food security. A meta-analysis by Rivington and Koo (2010) finds that the most widely used is the Decision Support System for Agrotechnology (DSSAT) (Jones, et al. 2003). DSSAT contains sub-process models, or modules, for land, management practices, soil and weather, and provides 17 crop models, including the CERES, CROPGRO, InfoCrop and Simulate Underground Bulking STorage Organs (SUBSTOR)
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