The Intergovernmental Panel on Climatic Change (IPCC) reports that the average air
temperature at the end of 21st century will rise 4.0 degrees Celsius from current levels in the
case of the fossil energy intensive scenario, i.e., A1FI (IPCC (2007)). Agricultural production
will be affected by global warming through changes in yields and market prices.
The relationship between yield or productivity and climate changes has been investigated
since the late 1950’s. These studies are based on crop models and expand the relationship
between biomass and environment to a regional or global scale. The global model focusing on
productivity in dry matter production by Lieth (1975) is a forerunner of these studies. Recent
models are more sophisticated; for example, Jones and Thornton (2003) evaluated the impacts
of climate changes on maize production by using a rainfall model, a crop model, and outputs of
the Global Circulation Model (GCM).
Development of these biological or ecosystem studies has led to more accurate projection of
changes in global vegetation patterns. However, environmental changes in a region will affect
agricultural productions in other regions through trade in agricultural products. Considering
relationships between food producers and consumers through trade, it is likely that climate
change, such as global warming, may cause drastic changes in agricultural markets even in the
mid-term.
Will producers and consumers of farm products be negatively affected by global warming?
To provide an answer to the question, some synthesized models are developed. Parry et al.
(1999, 2004, 2005) combined a supply and demand model of agricultural products, i.e., Basic
Linked System, and crop models such as CERES-Wheat. On the other hand, Wu et al. (2007)
combined a crop choice model, a crop yield model, i.e., EPIC, and a world food model, i.e.,
IFPSIM (1996). The former model is based on the supply and demand model of agricultural
products and it is extended to a model which can evaluate climate changes. The latter model is
based on the GIS based crop yield model and it is extended to the global scale model.
The yield functions of these models are based on crop process models and the maps of
outputs of these models are based on GIS technologies. Evaluating the economic impacts of
climate changes on the food security, supply and demand models are necessary. These models
are suitable for the “platform” of synthesized models which will be consisted of models of the
crop, the soil, the water, and the market, because the supply and demand models treat consumers
such as rural poor.This research examines possible effects of climatic change focusing on global warming and
its impacts on world agricultural product markets, by using a world food model (IFPSIM)
developed by the Japan International Research Center for Agricultural Sciences (JIRCAS).
The basic world food model was developed by Oga and Yanagishima (1996) and is extended to
consider changes in temperature and rainfall and their impact on crop yields (Furuya & Koyama
(2005)). Furthermore, the model is extended to a stochastic world food model (Furuya &
Kobayashi (2009)). The term of the outlook is 25 years, which is considered a mid-term
projection in this context.
IPCC constructed several socio-economic based scenarios i.e., A1B, B1, A2, and B2, which
are called SRES (Special Reports on Emission Scenarios) (IPCC (2000)). GDP and population
measures for these scenarios are localized for each country by the Data Distribution Center
(DDC) of IPCC and climate data such as temperature and rainfall for each scenario are reported
by the Hadley Center. These data are combined for the scenarios used in this research.
The A1B scenario assumes that trade liberalization progresses and the economic growth rate
is high. Furthermore, technological progress for the energy industry is well balanced between
fossil and clean energies. The annual per capita income is $21,000 in 2050, while population
reaches 8.7 billion people. The A2 scenario assumes that each country holds its own culture
and trade, labor movement, and that technology transfer is restricted. Given these constraints,
per capita GDP grows slowly and the annual average per capita income is $7,200 in 2050, while
the world population reaches 11 billion people.
The B1 scenario assumes that consumption of natural resource is at a low level and low
CO2 emission energy technology is developed, while the low population growth rate and high
economic growth rate are same as those in the A1 scenarios. The B2 scenario assumes that
trade is restricted and the cultural practices of each country are maintained such as those in the
A2 scenario; however, low CO2 emission energy technology is developed. The per capita
income is $12,000 in 2050 while the world population reaches 9.4 billion people in this
scenario.
Impacts of global warming on the food consumption of the two large population countries
are investigated. Table 1 shows the increasing rate of per capita consumption of several
primary agricultural commodities in China. The rate of growth shown is the difference in
consumption between 2010 and 2030 divided by consumption in 2010. The growth rate of the
A1B scenario is higher than other three. Particularly, consumption of coarse grains and
soybeans increase steadily under the A1B scenario, because higher income leads to greater
consumption of livestock products and feed input demand will increase. The consumption of
rice decreases for all scenarios due to the negative income elasticity of demand.
Table 2 shows the growth rate of per capita consumption in India. The growth rate of
consumption of rice is quite high, while that of maize is almost zero. The growth rate for
soybeans is high for A1B, B1, and B2 scenarios; however, in scenario A2 it is quite a bit lower.
This distinction comes from the restricted trade under the A2 scenario. Changes in the consumption of food in developing countries depends on the growth of
income and the eating habits. Not only researches of food production but analyses of
consumer behavior in developing countries will be important for researches related to climate
changes.