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Mason d'croz (dec 2015) inai - impact3, a selection of projections from ipcc scenario

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Mason d'croz (dec 2015) inai - impact3, a selection of projections from ipcc scenario

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Presentation for the second annual International Conference on Agro-Industrial Projections hosted by INAI (www.inai.org.ar, www.inai.org.ar/notas.asp?id=193) in Buenos Aires, Argentina.

https://globalfutures.cgiar.org/2015/12/20/to-latin-america-for-global-connections

Presentation for the second annual International Conference on Agro-Industrial Projections hosted by INAI (www.inai.org.ar, www.inai.org.ar/notas.asp?id=193) in Buenos Aires, Argentina.

https://globalfutures.cgiar.org/2015/12/20/to-latin-america-for-global-connections

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Mason d'croz (dec 2015) inai - impact3, a selection of projections from ipcc scenario

  1. 1. IMPACT v3.2 Projections A selection of scenario results based on the IPCC’s 5th Assessment report Daniel Mason-D’Croz IFPRI
  2. 2. The IMPACT system of models • Complete recoding of IMPACT • Disaggregation geographically and by commodity • Improved water & crop models • New data management system • Modular framework
  3. 3. Source: Nelson et al., PNAS (2014) Modeling climate impacts on agriculture: biophysical and economic effects General circulation models (GCMs) Global gridded crop models (GGCMs) Global economic modelsΔ Temp Δ Precip … Δ Yield (biophys) Δ Area Δ Yield Δ Cons. Δ Trade Climate Biophysical Economic Source: HadGem RCP 8.5 Source: IFPRI DSSAT Maize simulation
  4. 4. Socioeconomic and climate drivers Shared Socioeconomic Pathways (SSPs) Representative Concentration Pathways (RCPs) Source: Downloaded from the RCP Database version 2.0.5 (2015). RCP 2.6: van Vuuren et al. 2006; van Vuuren et al. 2007. RCP 4.5: Clark et al. 2007; Smith and Wigley 2006; Wise et al 2009. RCP 6.0: Fujino et al 2006; Hijioka et al 2008. RCP 8.5: Riahi and Nakicenovic, 2007. CO2 eq. (ppm)Radiative forcing (W/m2) Population (billion) GDP (trillion USD, 2005 ppp)
  5. 5. IMPACT model results • Yields – sources of growth, climate effects by commodity and region • Prices – comparing socioeconomic and climate effects • Total demand – comparing commodities • Per-capita food demand – by commodity and region • Composition of demand – by commodity and region • Net trade – by commodity and region • Food security – by region
  6. 6. Changing diets, by region (SSP2, kcal/person/day) 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 2010 2030 2050 2010 2030 2050 2010 2030 2050 2010 2030 2050 2010 2030 2050 2010 2030 2050 2010 2030 2050 2010 2030 2050 2010 2030 2050 WLD EAP EUR FSU LAC MEN NAM SAS SSA Total Animal Products Cereals Fruits & Vegetables Oils & Sugar
  7. 7. Decomposition of global supply growth of animal products (SSP2, NoCC) Source: IFPRI, IMPACT version 3.2, November 2015
  8. 8. Decomposition of changing demand for cereals and oilmeals (SSP2, NoCC) Cereals Oilmeals Source: IFPRI, IMPACT version 3.2, November 2015
  9. 9. Decomposition of global supply growth in cereal and oilseeds (SSP2, NoCC) Source: IFPRI, IMPACT version 3.2, November 2015
  10. 10. Climate impacts on yield effect, by region (SSP2) Source: IFPRI, IMPACT version 3.2, November 2015 Roots & tubers WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean; MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa; Cereals Fruits & Vegetables Oilseeds Pulses Sugar
  11. 11. Comparing maize and wheat climate yield impacts, by region (SSP2) Source: IFPRI, IMPACT version 3.2, November 2015 WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean; MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa; Cereals Maize Wheat
  12. 12. Price effects of socioeconomic and climate drivers Cereals Fruits & vegetables Meat RCPsSSPs Source: IFPRI, IMPACT version 3.2, November 2015
  13. 13. Net trade in Cereals (mmt, SSP2) EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa Source: IFPRI, IMPACT version 3.2, November 2015
  14. 14. Net trade in select cereals(mmt, SSP2) EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa Source: IFPRI, IMPACT version 3.2, November 2015 Rice Wheat Maize
  15. 15. Comparing trade in vegetable oils and oil meals (mmt, NoCC) EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa Source: IFPRI, IMPACT version 3.2, November 2015
  16. 16. Prevalence of hunger in 2050, by region Source: IFPRI, IMPACT version 3.2, November 2015 EAP = East Asia and Pacific; SAS = South Asia; FSU = Former Soviet Union; MEN = Middle East and North Africa; SSA = Sub-Saharan Africa; LAC = Latin America and Caribbean
  17. 17. Total number of climate-related deaths in 2050 by risk factor and region (SSP2 RCP 8.5) Source: Springmann et al (2015) HIC = High Income Country; AFR = Africa; AMR = Americas; EMR = Eastern Mediterranean; EUR = Europe; SEA = South-East Asia; WPR = Western Pacific
  18. 18. Thank you d.mason-dcroz@cigar.org For more information: http://www.ifpri.org/program/impact-model http://globalfutures.cigar.org http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/129825

Editor's Notes

  • The complexities involved in projecting food supply and demand over the longer term have raised interest in closer comparison of different projection exercises; thus AgMIP (acknowledge USDA support).
  • More people means there will be increased aggregate demand. But the story is complicated by changing consumption patterns. Economic development leads to increasing demand for animal products, fruits and vegetables, and oils and sugars, while per capita demand for cereals levels off globally.
    Increasing calorie consumption across the board. Good for decreasing hunger and food insecurity. Large increases in vegetable oils and sugar will make the prevalence of obesity higher.
  • Large increase in demand for poultry, and milk
    Pork demand doesn’t increase as much, as large population increases are in more Muslim regions (MENA, SSA, SAS)
    Pig Numbers decline by 375 million while productivity increases significantly
    Chicken Numbers (broilers and layers) increase 8.8 billion
    Cow Numbers (meat and milk) increase around 260 million
    Sheep-lamb-goats increase by 360 million
  • Increasing population will lead to increased aggregate demand for cereals in all regions. However, food demand in most regions is not increase, and much of the increase globally is driven by growing demand from the livestock sector.
    The large increase in feed demand for cereals is matched by increasing feed demand for oilmeals, particularly soybean meal
  • Total agriculture sees an increase in total land increases by 16% in 2050 compared to 2010, or about 200 million addition ha of harvested area
    Total agricultural productivity increases by 50%
    Cereal supply is dominated by increasing productivity, whereas oilseeds see a larger role for extension, particularly palm fruit in Southeast Asia and LAC, threatening increasing deforestation.
  • Agriculture and LUC contributed about 8000 mt CO2 equivalent emissions in 2010
    Changing diets for Animals can decrease carbon intensity of livestock production
    New technologies and management practices like wet and dry for rice can decrease methane emissions from crop cultivation
    Increased demand in perishables (F&V and animal products) may increase carbon intensity in value chains in the global food system
  • Climate change will offer asymmetric shocks across the different commodities and regions. Some regions may benefit from longer growing seasons, or increased precipitation while others will suffer from heat stress and declining precipitation. In general northern latitudes are projected to benefit from gradual climate change through 2050, whereas the tropics are projected to suffer. South Asia in particular may suffer from climate change.
  • Aggregations mask regional and commodity variation. For example, for cereals maize suffers from climate change globally with few exceptions, whereas what may benefit from climate change, particularly in northern latitudes such as in Europe and the Former Soviet Union.
  • Prices will adjust according to shifting production and consumption patterns. Climate change has the potential to significantly increase crop prices. For cereals it could more than double the increase in in prices observed from 2010 to 2050 caused by increasing population and economic development. This is particularly true for maize, where prices increase may be as much as 55 percent higher than without climate change.
    Livestock is less effected by climate change. Livestock diets are flexible with significant opportunities for substitution allow the livestock to adapt to changing cereal and oilmeal supplies. Livestock and Fruits and vegetables are more sensitive to changes in income. Higher income growth spurs rapid increase in demand. Cereal demand is more stable, and is driven by indirect demand through increased demand for animal products
  • Asymmetric climate shocks will require increased movement of goods from areas that might benefit from climate change to areas that will likely suffer from climate change. Developed countries will continue to be cereal exporters, but climate change will diminish the productive capacity of several key cereal exporters like the US, and Australia. The decline in exports will need to be mitigated by increased exports in the Former Soviet Union and increasing self-sufficiency in East Asia.
  • Rice is traded at much smaller rates than other cereals. Most rice is consumed in the country where it is produced.
    South Asia rice imports projected to increase significantly, with East Asia increasing exports to meet this demand
    Climate change threatens to push several southern wheat producing regions into larger importers. Increased exports from Europe and FSU will be needed to meet this demand
    Climate change projected to hit maize production in NAM heavily. EAP and LAC will need to pick up the slack, but they will be hard pressed to do so, which explains in part the higher maize price increases compared to other cereals
  • Similar to the asymmetric nature of climate change, different regions will be growing at different rates, which will also require goods to be moved around to reach demanding markets.
    Vegetable oil and oil meal trade is not greatly effected by climate change, but will respond more to changing consumption patterns caused by different assumptions on economic development.
    EAP is a major exporter of vegetable oils, but at the same time a major importer of oil meals. This is due to palm being the dominant vegetable oil in EAP, which leaves little oil meal by-product. The region exports palm oil and imports soybean meal from NAM and LAC
  • According to FAO there are 838 million people at risk of hunger in 2010. General economic development under SSP2 will increase purchasing power globally, with most regions projected to decrease the number of hungry. The only exception is MEN, where the share of the total population at risk is declining, but at a slower rate than the increase of the total population.
    Climate change threatens to slow down progress towards achieving the SDG of 0 hunger.
    Different economic development pathways have even larger effects on the prevalence of hunger, with SSP3 and SSP4 leading to major issues of food insecurity throughout the developing world with LAC, MEN, and SSA projected to see increasing hunger in SSP3. Slower economic growth like that projected in SSP3 or SSP4 combined with climate change could lead to a future where little progress on decreasing hunger is achieved.
  • Increasing consumption up to a point has many benefits, as undernutrition increases the likelihood of dying of disease. However, over-consumption increases the likelihood of many non-communicable diseases (i.e. diabetes, heart disease, stroke etc.). Increasing food prices therefore has positive and negative effects with respect to climate-related deaths. In developed countries it will potentially decrease over-consumption and lead to fewer deaths. However, for developing countries it will lead to a higher prevalence of under-consumption increasing the number of deaths.
    Increasing consumption of fruits and vegetables is critical to decreasing the risk of many diseases. High F&V prices, decreases the consumption of F&V compared to SSP2 NoCC, which increases deaths.

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