2.3. Model of International Relations in Agriculture (MOIRA)
2.3.3. Data sources 1. Soils:
FAO/UNESCO (1974) Soil Map of the World, 1 :5,000,000.
Stace, H. (1968). A Handbook of Australian Soil. Glenside.
Dudal, R., R. Tavernier and D. Osmond (1966). Soil Map of Europe. FA0:Rome.
2. Irrigation:
Moen, H.J. and K.J. Beek, (1974), Literature study on the potential irrigated acreage in the world. I.L.R.I., Wageningen.
3. Photosynthesis:
Wit, C.T. de, (1965), Photosynthesis of leaf canopies.
Agr. Res. Rep. 663, Wageningen.
4. Population:
Projections are from K.C. Zachariah and R. Cica, Population Projections
for Bank Member Countries 197@2000 (World Bank, Development Economic Department, Population and Human Resources Division).
The fast fertility decline variant was used in the standard run of MOIRA.
5. Economic Growth Rates:
Assumed economic growth rates are based on projections of total GDP derived from UN and World Bank reports. (W.Leontief, "Impact of Prospective Environmental h u e s and Policies in the International Development Strategy" and IBRD, "Additional External Capital Requirements for Developing Countries").
These provide l@yearly overall GDP growth rates for 15 regions of the world with 3 variants based on different assumptions with respect to capacity and speed of adjustment of developing countries to new relations. assess the current analytic capability of the U.S. government.
Global 2000 projects trends to A. D. 2000 for population, GNP, climate, technology, food and agriculture, fisheries, forestry, water, energy, fuel minerals, and non-fuel minerals. Experts then assess the impacts on the environment of these projections. The environmental impacts of each of the above projections is considered in turn, forming a significant part of the study (Vol. 2, Chapter 13). Finally, the results are compared with those of other global models.
For the purposes of the Agriculture group of the Biosphere project, we have concen- trated on examining the food and agriculture projections (Vol. 2, Chapter 6) and the asso- ciated environmental implications (Vol. 2, pp. 272-297). The basis of the food and agri- culture results is the USDA's Grain-Oil-Livestock (GOL) model, which is discussed in depth in Vol. 2, pp. 545-561. GOL is a static equilibrium model. Results generated by the GOL model use projections from other models for conditions in non-agricultural sectors.
2.4.1.1. Scale and resolution
The Technical Report (Vol. 2: 4556) discusses the scope of the research. The study considers the time period between 1975 and 2000. Food and agriculture projections are made for two points in time, 1985 and 2000. No estimations are available for intervening years. The study is global in scope, with a strong U. S. bias. This bias arises because the submodels used are agency models that were designed to assess impacts on the U. S.
GOL uses region-specific models to estimate arable area, fertilizer use, and total food production and consumption. Output is reported for the regions and for assorted group ings (e.g. exporters, industrialized, centrally-planned, LDC's).
2.4.1.2. Approach
Global 2000 relied on various models that are used by different U. S. government agencies for their long-range forecasting. First, population and economic growth were forecast. These projections were used to determine demands for natural resources. These demands plus the direct effects of population and economic development were then used to calculate environmental effects. The process was not iterative, so the environmental effects did not influence population, the economy, nor the use of natural resources.
The goal of the study is to determine the outcomes of present policies if these poli- cies were to continue unchanged for twenty years (except population growth, which is assumed t o slow due to of increased population control). Global 2000 assumes no innova- tive strategies for meeting the problems that it projects nor is there feedback from the problems t o policy mechanisms.
The GOL model and methodology are discussed in Vol. 2 of the report (pp. 73-74).
It is a conglomeration of 28 regional agricultural sector models. The 930 econometric equations describe grain, oilseed, and livestock demand, supply, and trade. The GOL model does not explicitly consider environmental issues, although they are discussed in the report. assumptions that were used in each of the submodels and cross-references them.
Many overriding assumptions were imposed upon the agency models to give them consistency. Among them: (1) There will be no change in public policy, except for increased population control. (2) The rate of technological growth will be linear, with no major breakthroughs and no serious setbacks. (3) There will not be any social opposition t o new technologies. (4) Trade will continue under present arrangements, with no d i s r u p rich and poor nations will increase.
Global 2000 projects a 90% increase in food production occurring between 1970 and 2000. This will mean a per capita increase of 15%. Intensification of agriculture (i.e.
higher inputs of fertilizer, pesticides, irrigation, and mechanization) will account for most of the growth in production, although in the developing world, much of the increase will come from cultivating more land. For example arable land will expand only 4% globally but will increase by 21% in Latin America.
Table 2.4 lists the population and per capita income growth rates that were used t o drive the GOL model, along with rates of fertilizer use, amount of arable land and yield variations. These are given for Western industrialized nations and centrally planned coun- tries, LDC's, and for the world. For the same four groups Figures 2.10 through 2.13 show the projected growth in food production.
Table 2.4 Input and projections of the GOL model. Regions Industrialized Centrally LDC's World planned Year 1975 2000 1975 2000 1975 2000 1975 2000 Population growth (Z/yr) (V.2:78) Alt. I 0.57 0.52 1.25 1.21 2.50 2.37 1.79 1.77 I1 0.48 0.34 0.99 0.94 2.36 2.04 1.63 1.48 111 0.67 0.71 1.45 1.43 2.66 2.71 1.95 2.05 Per oap inaome growth (5/yr) (V.278) Alt. I 3.41. 2.571 2.35 2.20 2.54 2.01 2.26 1.53 I1 4.40 3.35 3.22 3.15 3.52 3.00 3.23 2.42 111 2.41 1.77 1.50 1.25 1.55 1.03 1.29 0.66 Fertllizer (thousand rnetrio tons N, P205,KZO as 2:l:l) (V.2:lOO) 39900 84000 28125 77500 11925 58750 79950 220250 Fertilizer kg / arable ha (V.2:101) Arable area (million ha) (V.297) Yield variations due to olirnate G) (V.2:79) Aggregate of regional variatlons weighted by produotion Calaulated using world yield series - - - - - - - - - *,# Per oapita lnaome growth rates are given for the periods 1975- 1985 (*) and 1985-2000 (#).
TbOr
- u tutol + per capita
Figure 2.10 World food production (Source: Tables 6 7 , 6 8 , CEQ, Vo1.2:91-94)
. . Tear
t6tai + per capita
Figure 2.11 Food production in LDCs (Source: Tables 6 7 , 6 8 , CEQ, Vo1.2:91-94)
Year
total + per capita
Figure 2.12 Food production in western industrialized countries (Source: Tables 67,68,
CEQ,
Vo1.2:91-94)Yea r
+ per capita
Figure 2.13 Food production in centrally planned economies (Source: Tables 67, 68,
CEQ,
Vo1.2:91-94)Population growth alone will double water demand. Expanded agricultural and non-agricultural consumption will lead to regional water shortages.
Forests, mostly tropical, will be lost at the rate of 18-20 million hectares per year.
This means that the LDC's will lose 40% of their present forests. Needs for fuelwood will exceed supplies by 25%, and stocks of commercial timber will decline 50% per capita.
With forest clearing we will lose up to 20% of extant species.
Table 2.5 Key assumptions of the three alternative scenarios in Global 2000.
(Source: CEQ, 1980:Vo1.2:77)
Scenarios
Parameters I:A I:B I1 111
Population growth
(%/year) 1.8 1.8
Per capita income
growth (%/year) 1.5 1.5
Petroleum prices Constant Double Constant Double
(197476 by 2000 level)
Weather Variation in yields Good weather Bad
comparable to last raises yield weather
25 years. 1 S.E. above minus 1
1950-75 S.E.
yield series Growth in yields For all scenarios, the trend of the last 20 years is
projected to continue, but yields are raised or lowered by weather and by the producer prices that are generated under each scenario.
2.4.2. Evaluation
2.4.2.1. Classical sensitivity analysis
The GOL model considers four scenarios. Key assumptions of the scenarios are sum- marized in Table 2.5. Alternative I uses median projections for population and per capita income growth rates. Yields increase a t rates consistent with the technological advances of the previous 20 years. Climate is comparable to the previous 25 years. Trade arrange- ments do not change. There are two versions of Alternative I. First, constant energy prices are assumed (197476 levels). In the second version these prices double by year 2000.
Alternative 11, the optimistic run, uses lower population and higher income growth rates, favorable climatic conditions and constant energy prices. Alternative 111 is the pes- simistic forecast. The direction of the variables is the reverse of Alternative 11.
The differences between the results of the alternative scenarios are not large, that is, the model is not very sensitive t o the relatively small changes in parameters of the four scenarios.
Results of the four runs are presented in tables (Tables 6 7 t o 6 1 1 , pp. 91-96 of Vol.
2). Figures 2.10 t o 2.13 show the increase in food production over time for the world, LDC's, centrally-planned and western industrialized countries.
It is useful t o examine the sensitivity of the model t o the complete set of variables t o establish upper and lower boundaries of estimates. However it is impossible t o discern the sensitivity of the GOL model t o variables individually.
2.4.2.2. Structural analysis
The key assumption of the study, that is no change in public policy, although useful for the study's purposes, is not realistic. In view of the large number of undesirable conse- quences t h a t are forecast, policies will change. However, it is beyond the scope of the study t o assess the effects of potential policy shifts.
The main structural problem is that the agency models are only weakly connected and all links are unidirectional. Projections from population and income models drive demand, which causes environmental impacts. This structural weakness causes several major problems. There is no feedback, for example, between environmental components and income growth. Also, there is no way t o deal with competing demands on the same natural and economic resources. Agriculture and energy production for example are assumed to use the same fixed stock of water.
Despite attempts t o achieve consistency between models, there are many discrepan- cies. Submodels use different patterns of regionalization with between 5 and 28 regions in the world. There are also inconsistencies in the values assigned t o the same variables (OTA, 1982).
2.4.2.3. Sources of surprise
There are many ways of introducing surprises into the study. The researchers were aware of this and discuss it in a separate section along with reviewers' comments. A list of surprises is presented in Vo1.2, p.715. Some surprises could be incorporated in Global 2000 by adding feedback effects on natural resources. For instance, available arable land could be assumed t o decrease due t o land depletion and pollution of aquifers in irrigated areas (water withdrawals for energy development would have the same effect). Another approach would be t o violate the assumptions of the study where they are untenable.
Given the rising disparity between rich and poor countries, crowding, scarcity of resources, and increases in the real price of food, the assumption t h a t there would not be any major wars could easily be violated.
2.4.2.4. Relevance to long-term, large-scale environmental studies
T h e greatest contribution t h a t Global 2000 can make to studies of development- environment interactions is its detailed projections of environmental impacts. More than 200 pages of the report were devoted t o these issues. Limiting the study's usefulness t o long-term studies are the short time horizon and the structural problems.
2.4.2.5. Ease of use
Results of the study are presented in a very useful format. The Summary volume presents a concise overview of all aspects of the study. In Volume 2, the data, both input parameters and results, are presented in tables and graphs. These are straightforward and clear.
On the negative side, the sheer bulk makes working through the study difficult; i t takes time t o "get t o know one's way around." Compounding the problem, the index is mediocre.
Finally there is no model for a person to use. That is, there is no software. All the various agency models were used and coordinated by a large research team which has dis- banded.