Economic and Social Development Department Food and Agriculture
Organization of the
United Nations
How climate change may affect global food demand and supply in the long-term?
Aikaterini Kavallari
Global Perspective Studies Team
Economic and Social Development Department
Challenges to ensure sustainable food security in the future
Economic and Social Development Department
131
48
15
68
30
6
0
20
40
60
80
100
120
140
0
200
400
600
800
1,000
1,200
1,400
sub-Saharan Africa South Asia East Asia Near East & N.Africa
Latin America Developedcountries
Incremental population growth 2005/07-2050, millions (left-axis)
Percent population growth 2005/07-2050 (right-axis)
Source: United Nations Population Division (2009).
An additional 2.5 billion persons—to 9.1 billion in 2050
Economic and Social Development Department
0
5
10
15
20
25
30
35
40
45
Developingcountries
sub-Saharan Africa South Asia East Asia Near East & N.Africa
Latin America
Average per capita incomes relative to developed countries 2006, percent
Average per capita incomes relative to developed countries 2050, percent
GDP per capita gaps converge only modestly
Source: Development Prospects Group, The World Bank.
Economic and Social Development Department
Agricultural production growth slows down
Source: FAO.
24
77
60
57
317
170
0 50 100 150 200 250 300 350
Developedcountries
Developingcountries
World
Percent change over period
1961/63-2005/07 2005/07-2050
Economic and Social Development Department
Potential impacts of climate change on global food demand and supply
- empirical results based on Agricultural Model Intercomparison and Improvement Project (AgMIP) Phase 1-
Economic and Social Development Department
The climate modeling chain in AgMIP: from biophysical to socioeconomic
General circulation
models (GCMS)
Global gridded
crop models
(GGCMs)
Global economic
models
DTemp DPrec
Dyield (Biophysical)
DArea DYield DCons DTrade
Climate Biophysical Economic
RCP’s Farm
practices CO2
Pop. GDP
Source: Nelson et al., PNAS (2013).
Reference scenario: SSP2 (no climate change) Climate scenario: RCP 8.5
Economic and Social Development Department
-25
-20
-15
-10
-5
0
5
Wheat Rice Coarse grains Oil seeds Sugar CR5
IPSL/LPJ HADGEM2/LPJ IPSL/DSSAT HADGEM2/DSSAT
Source: Nelson et al. (2014).
Note: CR5: average of the five crops
Climate change impacts, percent change in exogenous yields relative to reference in 2050
Economic and Social Development Department
Perc
en
t ch
an
ge
-60
-40
-20
0
20
40
60
n
Mean
SD
2891
-0.17
(0.131)
2891
-0.11
(0.166)
2891
0.11
(0.249)
2891
-0.02
(0.25)
2891
-0.01
(0.264)
2891
-0.03
(0.063)
2891
0.2
(0.242)
YEXO YTOT AREA PROD TRSH CONS PRICE
Climate induced changes to global yields, land use, production, trade, consumption and prices relative to reference for CR5 in 2050
Source: Nelson et al. (2014). Notes: YEXO: exogenous yields,; YTOT: final yields; AREA: crop area; PROD: domestic production; TRSH: net imports relative to production; CONS: consumption; PRICE: average producer prices
Economic and Social Development Department
Conclusions
Economic and Social Development Department
Take away messages
• Climate impacts will negatively affect commodity prices, with many of the increases ranging from 5-25%
• Food consumption is expected to drop implying that climate change may well exacerbate food security concerns
• Globally consumption responds less than supply because food demand is not so sensitive to price changes
• Still effects will be felt more in specific regions with already stressed natural resources
• Variability in trade and crop area responses is due to the varying assumptions about trade flexibility and ease of land conversion in the models -> both of which imply different degrees of adaptation to changes in agricultural markets
Economic and Social Development Department
Further reading
Special issue of Agricultural Economics (2014): http://onlinelibrary.wiley.com/doi/10.1111/agec.2014.45.issue-1/issuetoc • von Lampe, Willenbockel et al., “Why do global long-term scenarios for agriculture
differ? An overview of the AgMIP Global Economic Model Intercomparison”
• Robinson, van Meijl, Willenbockel et al., “Comparing supply-side specifications in models of global agriculture and the food system”
• Valin, Sands, van der Mensbrugghe et al., “The future of food demand: understanding differences in global economic models”
• Schmitz, van Meijl et al., “Land-use change trajectories up to 2050: insights from a global agro-economic model comparison”
• Müller and Robertson, “Projecting future crop productivity for global economic modeling”
• Nelson, van der Mensbrugghe et al., “Agriculture and climate change in global scenarios: why don’t the models agree”
• Lotze-Campen, von Lampe, Kyle et al., “Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison”
Special issue
Proceedings of the National Academy of Sciences (PNAS) (2014): http://www.pnas.org/content/111/9/3274.abstract
• Nelson, Valin et al., “Climate change effects on agriculture: Economic responses to biophysical shocks”
Economic and Social Development Department
Annex
Economic and Social Development Department
Terminology
• SSPs: Shared Socioeconomic Pathways • RCPs: Representative Concentration Pathways • IPR: Intrinsic Productivity Rate • AgMIP: Agricultural Model Intercomparison Project
(http://www.agmip.org/) • LPJml: Lund-Potsdam-Jena managed Land Dynamic Global
Vegetation and Water Balance Model • DSSAT: Decision Support System for Agricultural Technology • HadGEM2: Hadley Centre Global Environment Model version 2 • IPSL: climate model of the Institute Pierre Simon Laplace
Economic and Social Development Department
Reference scenario details
• Based on the SSP2 narrative • Assumes a middle of the road growth of the economy with
intermediate socioeconomic challenges to climate change adaptation and mitigation
• Population and GDP growth path taken over from the SSP database, based in IIASA and OECD projections respectively https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=about
Economic and Social Development Department
Climate scenario details
• Radiative forcing of over 8.5 watts per square meter by the end of the century
• Excludes potentially positive effects of increasing CO2 concentration
• Crop models assume constant management practices (e.g. sowing dates)
• Crop models did not include effects of increased ozone concentration, increased weather variability and greater biotic stress