Based on the interpretation of the storylines for the SRES scenarios, specific assumptions have been made for:
Two kinds of assumptions are made regarding the caloric intake of animal products: scenario specific assumptions, and product- or region-specific assumptions.
1. Scenario specific assumptions
The regional preference levels for the consumption of meat (beef, pork, goat meat and mutton) and eggs for the B1 and B2 scenarios are assumed to be 10% lower in 2050 and 20% lower in 2100 when compared to the A1 and A2 scenarios. This assumption is based on the environmental and health aspects associated with the production and consumption of meat and (to a lesser extent) eggs. These environmental and health aspects are assumed to be important in the B1 and B2 scenarios and less so in the A1 and A2 scenarios on the basis of the scenario narratives.
2. Product and region-specific assumptions
Specific assumptions are made for all scenarios for milk (in general) and pork (North Africa and Middle East) and beef (South Asia):
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Assumptions are made for oilcrops to prevent unrealistic future levels of intake: for less industrialized regions the fraction oilcrops of total intake of affluent products is assumed to approach the 1995 values for OECD Europe when incomes approach the 1995 GDP of OECD Europe.
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Food trade in IMAGE 2.2 is determined by so-called Desired Self Sufficiency Ratios (DSSRs), which are defined as the ratio of the regional production and the regional consumption. Exporting regions have DSSRs greater than 1. For each region there exists 13 DSSRs; one for each food product. The addition 'Desired' refers to the fact that exporting regions determine the amount of food that can be traded and therefore, determine the maximum amount that can be imported by regions with DSSRs less than one (see model context, agricultural economy model).
DSSRs have been assigned values such that food trade is maximal in the open and rich world of the A1 scenario. It is assumed food trade is slightly less in the B1 scenario, followed by the A2 scenario and finally the B2 scenario.
In general, DSSR-values after 1995 are computed as follows:
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Multiplication factors for export fractions in the SRES scenarios. Higher values result in more food trade. |
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Obviously, these rules are too general, and therefore it is necessary to define exceptions to these rules, based on (scenario-related) common sense and insights on future trade patterns as reported by FAO and other well-accepted authorities. Without going into too much detail, the following exceptions have been made in the implementation of the SRES scenarios:
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Livestock production characteristics include carcass weight at slaughtering, extraction rate (i.e., off-take rate, which is the fraction of the animal population slaughtered each year), feed efficiency, the fraction of pasture and fodder species, and residues in the diet.
These characteristics are assumed to advance towards target values, specific for each animal category (see tables below). The target can be reached in a scenario-specific target year.
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For less industrialized regions the production characteristics of goats, sheep, pigs and poultry are moving, along with economic development, towards targets according to a logarithmic function of GDP. The target value is realized when income reaches the 1995 GDP for OECD Europe.
If a industrialized region has a higher feed efficiency, carcass weight and off-take rate than indicated in the target values, or a lower fraction of grass and residues in the diet, the livestock production characteristics will remain stable in the future.
If an industrialized region has a lower feed efficiency, carcass weight and off-take rate than the target values, or a higher fraction of grass and residues in the diet than the target value, the livestock production characteristics will move in a linear fashion towards the target values. This target is reached in a scenario-specific target year.
Current trends toward a lower degree of dependency on grazing systems (Alexandratos, 1995; de Haan et al., 1999; FAO, 1996) are assumed to continue, leading to an increasing use of food crops.
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Maximum values are assumed for management factors (for explanation on management factor: see indicators). The maximum achievable yields under practical conditions, which are assumed to be independent of economic growth, are the same for all scenarios (see table below). However, the rate at which regions advance towards these maximum values depends on the scenario.
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Maximum values for the management factor for pasture and fodder species and the food and biofuel crops. |
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| Pasture and fodder species | Regions I 1 |
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| Regions II 2 |
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| Regions III 3 |
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| Regions IV 3 |
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| Temperate cereals |
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| Rice |
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| Maize |
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| Tropical cereals |
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| Pulses |
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| Root and tuber crops |
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| Oilcrops |
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| Maize as biofuel |
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| Sugar cane as biofuel |
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| Woody biofuels |
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| Nonwoody biofuels |
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| 1 Canada, USA, East Asia, Oceania 2 Central America, South America, Northern Africa, Western Africa, Eastern Africa, Southern Africa, former USSR, Japan 3 Middle East, Southeast Asia 4 OECD Europe, Eastern Europe, South Asia |
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Growth paths are specified in the table below on the basis of relative differences in economic growth between regions.
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Annual growth percentages for the management factor for groups of world regions in the four SRES scenarios |
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* I: Canada, USA, OECD Europe, Oceania, Japan
II:Central America, South America, North Africa , Middle East, East Asia, Southeast Asia III:Western Africa, Eastern Africa IV:Western Africa V:Southern Africa, South Asia VI:Eastern Europe, former USSR |
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The increase of agricultural productivity reduces the need for expansion of the agricultural area used. B1 is a scenario in which environmental values (such as forests) are important. To account for this aspect, the growth rates for the management factor for A1 and B1 are identical, although the A1 scenario has a faster economic growth. Similarly, the growth rates for the A2 scenario (with the lowest economic growth) equal those of the B2 scenario (with intermediate econimc growth rates).
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Regional cropping intensities (for more details: see indicators) move towards region-specific scenario-independent maximum values (see table below). Increasing cropping intensities reduces the need for expansion of the agricultural area used.
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Maximum values of cropping intensity and the growth path towards this maximum value for different regions and scenarios |
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Region
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| Canada, USA, OECD Europe, Eastern Europe, former USSR, Oceania, Japan |
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| Central America |
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| South America |
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| Northern Africa |
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| Western Africa |
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| Eastern Africa |
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| Southern Africa |
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| Middle East |
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| South Asia |
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| East Asia |
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| Southeast Asia |
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Each scenario has a specific target year in which the maximum value is reached: B1 is a scenario in which environmental values are important. To account for this aspect, the B1 scenario has the same target year of 2025 for Annex I countries and 2050 for non-Annex I countries as the A1 scenario, although the latter shows a more rapid economic growth than B1. Similarly, the target year of 2050 for Annex I countries and 2100 for non-Annex I countries for the A2 scenario (with the lowest economic growth) is the same as that for B2 (with intermediate economic growth).
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Target year for maximum cropping intensity |
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| Scenario |
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| Annex I 1 | Non-Annex I 2 | |
| A1, B1 | 99% of the max. reached in 2025 | 99% of max. reached in 2050 |
| A2, B2 | 99% of the max. reached in 2050 | 99% of max. reached in 2100 |
| 1 Annex I: Canada, USA, OECD Europe, Eastern Europe, former USSR, Oceania, Japan 2 Non-Annex I: Central America, South America, Northern Africa, Western Africa, Eastern Africa, Southern Africa, Middle East, South Asia, East Asia, Southeast Asia |
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The maximum nutrient input for crops is 300 kg Nitrogen, Phosphorus, Potassium (NPK) per hectare per year for the A1 and A2 scenarios, and 250 kg NPK per hectare per year for B1 and B2. These maximum values represent the 1995 OECD Europe NPK rate minus 10% and 20%, respectively.
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Assumptions on fertilizer use |
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| Scenario |
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| Industrialized regions are assumed to move in a linear fashion towards the input levels specified below. The growth in less industrialized regions is according to a logarithmic function based on GDP. | |
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300 kg NPK from synthetic fertilizers + animal manure per hectare of harvested land in 2025. N in synthetic fertilizer is a fixed fraction of NPK |
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300 kg NPK from synthetic fertilizers + animal manure per hectare of harvested land in 2050. N in synthetic fertilizer is a fixed fraction of NPK |
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250 kg NPK from synthetic fertilizers + animal manure per hectare of harvested land in 2050. N in synthetic fertilizer is a fixed fraction of NPK |
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The fraction synthetic fertilizers applied to grass and fodder species of total fertilizer use is assumed to move towards the fraction of OECD Europe in 1995. |
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The fraction of animal manure that is available for application to crops and grasslands (i.e., stored manure, which is all animal manure excluding excretion during grazing and burning of animal manure) is assumed to approach the level of OECD Europe when regions approach the 1995 OECD Europe 1995 GDP per capita. This is to simulate intensification of livestock production whereby more animal manure becomes available. |
Assumptions for reduction in wood production are made for the B1 and B2 scenarios only. In the A1 and A2 scenarios, forest destruction due to wood extraction is considered less important. Regional reduction of wood production in the B1 scenario comes to 40% for 2050 and 60% for 2100, and is linear in between. In the B2 scenario it is 0 for 2025, 40% for 2100 and linear in between.
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