Approaches to Analysis of Climate Change Impacts Impacts

2.1. Conceptual Approach

　Climate refers to an average meteorological phenomenon that has occurred repeatedly in a specific region or regions over a prolonged period of time. Agricultural production is carried out through selection of crops suitable for the climate of a specific region and the application of proper farming methods. Therefore, agriculture is a climate-dependent bio-industry with notable regional characteristics. Regional characteristics refer to the ecosystem characteristics determined by the climate of the region, and the climate is one of the representative physical characteristics of the region. Climate change disturbs the agricultural ecosystem that previously existed in a state of relative stability which by bringing about changes in agricultural climatic elements such as temperature, precipitation, and sunlight which in turn influences the arable, livestock, and hydrology sectors.

The flow of climate change impacts on the agricultural sector can be illustrated as shown in <Figure 3-2>. The climate change impact first manifested in the arable and the livestock sector are biological changes including the change of the flowering and earing seasons, quality change, and a shift in the areas suitable for cultivation.⁸ Climate

8 The impacts of climate change in the agricultural production are divided into the primary impacts and the secondary impacts. The primary impacts refer to the changes in the composition of atmosphere due to the increased greenhouse gases, which include the change in crop growth response and the change in energy and moisture balance in the farmland colony. The secondary impact caused by the change in agricultural climate resources affected by the primary impacts include the shift in suitable places of cultivation and the physical and chemical changes in the farmland soil (Y. E. Na. et al., 2007, p.94).

Figure 3-2. Flow of the climate change impact on the agricultural sector

Climate Change

Changes in the agricultural climate resources

change affects the agricultural ecosystem, leading to an increase in blights and pests and causing population movement and changes to biodiversity. In the livestock sector, climate change brings about biological changes including fertilization and breeding and also affects the production of pasture.

　Climate change also affects hydrology, including the underground water level, water temperature, river flow, and the water quality of lakes and marshes, by impacting precipitation, evaporation, and soil moisture content. In particular, the increase of precipitation by climate change leads to the increase of outflow while the temperature rise increases evapotranspiration, resulting in the reduction of outflow. In order to understand the quantitative impacts of climate change on water resources, a deterministic hydrology model, based on a general circulation model, is used.　

As illustrated above, climate change has wide ranging impacts on the rural economy including agricultural productivity, farm households’

revenue and asset values, and also affects the agricultural infrastructure

through changes in the water sources available for agriculture.

　So far, the quantitative analyses of the impacts of climate change on the agricultural sector have been experimental, centering on the cross-sectional analysis. The experimental analyses are carried out on the basis of agro- economic simulation models. They are similar to the controlled experiments in which related variables are regulated, in that variables related to greenhouse gases such as temperature level and carbon dioxide emission level are regulated. In these experiments, the impact of climate change on agricultural production can also be estimated.

Agro-ecological zone analysis is carried out by using the crop simulation model (called the crop model for short) that tracks the changes in agricultural production and agro-ecological zones which result from climate change. Crop growth is determined by the interaction of three elements; the genetic characteristics of crop, the cultivation technology, and the environment (climate, soil, etc.). The crop model refers to a computer program that can estimate the crop growth and its quantity when these three elements are entered. Using the crop model, it is possible to estimate and analyze the agricultural production under climate change. The Crop Estimation through Resource and Environment Synthesis (CERES) model developed in the USA by integrating the crop model and the resource environment can assume a certain situation that is likely to happen and forecast possible results.

To analyze how, and to what extent, the change in temperature and precipitation following global warming affects the agricultural sector, various experiments, simulations and other research are carried out, both in laboratories and in the fields. As the impacts of climate change on the agricultural sector vary greatly with the related variables, it is difficult to stereotype certain analysis results. Therefore, what is attempted here is a simple classification of the impacts of climate change into positive and negative effects based on the results of the research done so far in the related fields <Figure 3-3>.

Figure 3-3. Potential impacts of global warming on the agricultural

Change in areas suitable for cultivation disasters such as moisture stress and drought

Increase of soil erosion Increase in productivity

due to the increased CO₂concentration

Reduction of heating cost for protected cultivation

<Negative Impacts>

<Positive Impacts>

The positive impacts of global warming include an increase in crop productivity due to the fertilization effect brought about by the increase in carbon dioxide concentration in the atmosphere, the expansion of the areas available for the production of tropical and/or subtropical crops (mango, avocado, atemoya, etc.), the expansion of two-crop farming due to the lengthened cultivation period, a reduction of damage to wintering crops by low temperatures, and a reduction in the of heating cost for agricultural crops grown in the protected cultivation facilities.

The negative impacts of global warming include reduced crop quantity and quality due to the reduced growth period following extreme temperature rise; reduced sugar content, crop discoloration, and reduced storage stability of fruit; increasing damage from weeds, blights, and harmful insects in agricultural crops; reduced land fertility due to the accelerated decomposition of organic substances; and the increased soil erosion due to increased rainfall.

In addition, each crop has different climate and environmental conditions requirements. So, if climate change induced temperature rise occurs, the boundary and suitable areas for cultivation move north and thus main areas of production also change. This change in the main

areas of production would represent a crisis for certain areas but an opportunity for other areas, thus it cannot be classified explicitly as either a positive or negative impact.

As examined thus far, the impacts of climate change on the agricultural sector have ambivalent characteristics of positive impacts creating opportunities and of negative impacts causing crises. Therefore, it is very important to formulate adaptation strategies that can maximize the opportunities and minimize the crises, for the sound development of future agriculture.

2.2. Theories for Analyzing the Impacts of Climate Change

2.2.1. Analysis of the impacts of climate change on the agricultural production

　For the quantitative assessment of the impacts of climate change, including temperature and precipitation, on agricultural production, the Integrated Assessment Model (IAM) is used. The IAM integrates scientific data and is applied mostly as a dynamic model that takes a long period of time into consideration. Typical climate-crop integration models include the CERES model and the climate change optimization model. The CERES-Rice model, for example, estimates rice growth and yield, using weather conditions, soil, cultivar parameters, and the cultivation-related information. As a model for making mid/long-term estimations of agricultural production under climate change, the CERES- Rice model is widely used for estimating rice production in the period from 2030~2100 (K. M. Shim et al., 2008).

　ORYZA2000, a model for estimating agricultural production under climate change, was developed jointly by Wageningen University of Netherlands and International Rice Research Institute in order to perform

a simulated analysis of rice growth in 2000. With the parameters set for crop and climate, this model can estimate the rice yield and the fertilization effect of carbon dioxide in each area under the impacts of climate change.

　In addition to these models, there are other agricultural production estimation models that take climate change into consideration such as Agricultural Production System Simulator (APSIM), the dynamic crop model, the Erosion Productivity Impact Calculator (EPIC), and the CENTURY model, which estimates soil organism change, crop growth and carbon storage over a long period of time.

2.2.2. Analysis of the economic impacts of climate change on the agricultural sector

Economic analysis of the impacts of climate change is based on scientific facts, as scientific uncertainty is directly related to economic uncertainty. Economic impact analysis models separate the cultivation areas into two boundaries in consideration of the combined uncertainty and the spatial heterogeneity of variables (Zilberman, et al., 2004).

For example, taking temperate crops and arctic crops as the vegetation and the Northern hemisphere as the cultivation area, the profit and loss of each of the two crops per unit area, both before and after climate change, can be illustrated as shown in <Figure 3-4>. As shown in the following figure, assuming that α is the distance from the North Pole, the temperate crops before climate change could be cultivated in b1~a1*, while the arctic crops in a1*~a1. After climate change, the temperate crops could be cultivated in b2~a2*, whereas the arctic crops in a2*~a2. According to this assumption, the soil in b1~b2 will most likely undergo desertification while the soil in a1~a2 will become arable. In other words, indicates the areas where economic losses occur due to desertification brought on by the impacts of global warming whereas indicates the areas where profits are made as more

Figure 3-4. Economic analysis model for the climate change impact

Boundary Boundary

π

a2 a1 a2* a1* b2 b1 α

North South

Profit Loss

land becomes arable.

　As climate change results in both profits and losses due to both increases and decreases of arable land, availability, it is not clear whether the overall impact of climate change is negative or positive.

Therefore, other effects should be considered. Another effect is the

“fertilization effect”, which refers to the impact of increasing carbon dioxide on agricultural production, whereas the daylight effect refers to the phenomenon where agricultural yield decreases due to reduced daylight hours which accompany the shift north of cultivation regions.

The pest effect implies that as weather becomes warmer, pests moves north and yields becomes smaller; the water effect refers to early snow melting and flooding due to global warming; and the protein effect refers to an effect where the increase in carbon concentration brings about an increase in agricultural production but also a reduction in protein production. Lastly, the settlement cost effect refers to the phenomenon where climate change requires additional costs for redistribution and settlement (a1~a2 → a1*~a2*).

2.2.3. Types of economic analysis models

　In order to analyze the economic effects of climate change on agriculture, scientific in-depth analyses of the relationship between climate variables and crop variables and the relationship between climate and economic variables are needed. Most of the economic analyses concerning climate change impacts depend on the past data about climate variables and crop variables. However, it remains very difficult to carry out reliable economic analyses given that the phenomena that are likely to happen under the new conditions caused by temperature rise and precipitation change are significantly affected by many other variables.

In reality, as climate change is analyzed assuming hypothetical changes several decades into the future, there are difficulties in setting future variables of price and profit and therefore several hypothetical conditions are set for analysis. Like this, there are considerable restrictions in analyzing the economic impacts of climate change. But, in general, the models used for economic impact analysis can be classified into four types:⁹

　The first category is the agro-economic model, based on the crop response function and the production function, which is used for estimating the impacts of climate change on the agricultural yield and production cost. This model is subdivided into parametric method that sets specific functions and nonparametric or semi-parametric methods that do not use functions (Solomou and Wu, 1999). The agro-economic model is useful for analyzing the change in agricultural productivity and changes in farm revenue in various environmental conditions and areas under conditions of climate change.

9 Methodologies and models concerning the analysis of economic impacts of cli-mate change on the agricultural sector are presented in detail in the articles by Chang (2002), Kurukulasuriya and Rosenthal (2003), Zilberman (2004), and Adger (2006).

　The second category is the hedonic price model that reflects the impacts of climate change on asset values. This model uses the current asset values for estimating the price sensitivity of land value to climate parameters. Typical example of the hedonic price model that analyzes the economic impacts of climate change by relating the land value to the climate change is the Ricardian Model developed by Mendelsohn, Nordhaus, and Shaw (1994).¹⁰

　 The third category is the programming simulation model that estimates the optimum product supply and the demand for investment using information about climate and land utilization under hypothetical conditions. Using the agricultural sector model, it is possible to draw the balanced price, production level and profits of conservation tillage in various areas after greenhouse gas reduction (Adams, 1989; Chang, 2002). In particular, the stochastic simulation is applied for measuring the extent of changes in production and profitability in various areas by taking the concerned uncertainty and risk into consideration (van Asseldonk and Langeveld, 2007). In order to apply the mathematical programming model to the analysis of climate change impacts, various technical parameters about climate elements and environmental elements are needed. Therefore, it is used in connection with the climate-crop integration model.

10 Regarding approaches to the analysis of economic impacts of climate change, Mendelsohn, Nordhaus, and Shaw (1994) present the Ricardian model, pointing out that the crop response function and the production function approach are un-realistic given that they do not take adjustment and adaptation related to climate change into consideration. The Ricardian model approach is to measure the eco-nomic, climatic, and environmental factors from the land value, which is preferred to the traditional estimation methods as it automatically takes farmers’ efficient adaptation to climate change into consideration. However, it has been argued that the Ricardian model has a shortcoming, which is that the adjustment cost is not considered in the relationship between climate change and profit from land.

　The last category includes the Computable General Equilibrium (CGE) model and the Dynamic Integrated model of Climate and the Economy (DICE) that relate climate change to the agricultural production and the economic system (Lewandrowski and Schimmelpfennig, 1999;

Cline, 2007). These models are utilized for estimating the macroscopic impacts of climate change on the growth of the agricultural sector and gross domestic product.