PIM Webinar, January 29, 2020. Climate change poses a threat to food security and nutrition, largely through its impacts on agricultural production. To help developing countries identify where adaptation measures are most needed, IFPRI, with support from the CGIAR Research Programs on Policy, Institutions, and Markets (PIM) and Climate Change, Agriculture, and Food Security (CCAFS), conducted a multiyear study to assess the potential impact of climate change on the agriculture sector through 2050, taking into account the likely landscape of political and economic challenges that policy makers will face. The study integrated results from climate and economic models, and included detailed biophysical and bioeconomic analyses of Guatemala, Honduras, El Salvador, Nicaragua, and Costa Rica in Central America and Colombia and Peru in the Andean region of South America. Presenters and panelists: Timothy Thomas, Research Fellow, International Food Policy Research Institute (IFPRI) Deissy Martínez Barón, Regional Program Coordinator for Latin America, CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS) Ana R. Rios, Natural Resources and Climate Change Senior Specialist, Inter-American Development Bank More at http://bit.ly/ClimateChangeAgWebinar

2. Authors and acknowledgments
Research team:
Timothy S. Thomas (IFPRI)
Deissy Martínez Barón (CCAFS)
Ana R. Rios (IDB)
This work was undertaken as part of and jointly funded by the CGIAR Research Programs on Policies,
Institutions, and Markets (PIM) and on Climate Change, Agriculture and Food Security (CCAFS).
Support from The Bill & Melinda Gates Foundation (BMGF), The Inter-American Development Bank
(IDB), and the International Center for Tropical Agriculture (CIAT) is gratefully acknowledged.
The opinions and views expressed here belong to the authors and may not be attributed to nor be taken to
reflect the official opinions of BMGF, CCAFS, CGIAR, CIAT, IDB, IFPRI, PIM, or any of their respective donors or
affiliates.
Ana María Loboguerrero Rodriguez (CCAFS)
Graciella Magrin (Instituto Nacional de Tecnología Agropecuaria)
Vicente Barros (Universidad de Buenos Aires)

3. Overview
Multi-year study using biophysical and bioeconomic models to examine the effect
of climate change on agriculture at both the national and pixel levels
Study area:
• Five countries in Central America: Costa Rica, Guatemala, Honduras, Nicaragua, El
Salvador
• Two Andean countries: Colombia and Peru

4. Characteristics of the region
• Diverse ecosystems spanning mountainous areas, plains, and coastal zones
• High and persistent levels of poverty that reach 45% in Central America and 30%
in South America
• Countries can be divided into 2 categories based on the levels of GDP per capita,
rurality, and share of agriculture in GDP:
• Guatemala, Honduras, El Salvador and Nicaragua with lower per capita GDPs
($1,963-$4,129), higher rural population (34%-49%), and the agricultural
sector provides 10.8%-20.5% of GDP
• Costa Rica, Colombia and Peru where GDP per capita is considerably higher
($6,551-$10,415), the rural population is lower (22%-24% of the total
population) and the contribution of the agricultural sector to the national
economy is smaller (5.6%-7.4%)

5. Climate models: temperature change, climate of 1960–
1990 to 2050
Change in mean daily maximum temperature for the warmest month, in 0C
GFDL-ESM2M MIROC-ESM-CHEM
Source: Data from
Müller and Robertson
(2014), which used
downscaled versions of
four CMIP5 GCMs
(Taylor, Stouffer, and
Meehl 2012), under
RCP8.5, and re-based to
WorldClim 1.4 (Hijmans
et al. 2005).

6. Climate Models: Precipitation Change, climate of 1960–
1990 to 2050
Annual precipitation change in millimeters
GFDL-ESM2M IPSL-CM5A-LR
Source: Data from
Müller and Robertson
(2014), which used
downscaled versions of
four CMIP5 GCMs
(Taylor, Stouffer, and
Meehl 2012), under
RCP8.5, and re-based to
WorldClim 1.4 (Hijmans
et al. 2005).

7. Crop model usage
• Use four of seven biophysical models from the Agricultural Model
Intercomparison and Improvement Project (AgMIP) Gridded Global Crop Model
Intercomparison (GGCMI)
• Analysis done using climate model data for 2050
• Done for each half degree pixel (approximately 50 kilometers per side)
• Assumes CO2 fertilization

8. Leading crops by area for Central America
Hectares cultivated
Crops Guatemala Honduras El Salvador Nicaragua Costa Rica Total Total (%)
Maize 835,825 440,941 268,821 347,398 1,892,985 36.3
Coffee 249,574 267,064 144,085 240,099 97,045 997,867 19.1
Beans 237,819 130,808 105,612 119,396 21,317 614,952 11.8
Sugar cane 241,304 76,516 67,327 64,767 59,07 508,984 9.8
Sorghum 27,133 50,705 99,217 92,105 269,160 5.2
Oil palm 58,667 110,667 60,167 229,501 4.4
Bananas 64,605 25,525 42,158 132,288 2.5
Source: FAOSTAT.
Notes: Mean of 2010-2012.

9. Leading crops by area for Andean Region
Hectares cultivated
Crops Colombia Peru Total Total (%)
Coffee 765,183 342,993 1,108,176 20.5
Maize 510,419 492,930 1,003,349 18.6
Rice 487,621 379,730 867,351 16.1
Plantains 368,506 151,551 520,057 9.6
Sugar cane 356,177 79,393 435,570 8.1
Potatoes 102,869 299,513 402,382 7.4
Cassava 204,060 97,371 301,431 5.6
Beans 116,060 80,752 196,812 3.6
Oil palm 165,500 0 165,500 3.1
Source: FAOSTAT.
Notes: Mean of 2010-2012

10. Median projections for
rainfed maize, percent
change 2000-2050
Source: Authors’ calculations based on data from the
Agricultural Model Intercomparison and Improvement
Project (AgMIP) Global Gridded Crop Model
Intercomparison (GGCMI; see Rosenzweig et al. 2014).
Notes: The median at each pixel was computed from
all possible combinations of four crop models and four
climate models. All are from AGMIP GGCMI for
Representative Concentration Pathway 8.5 (RCP8.5).

11. Rainfed maize yield changes due to climate
change, 2000-2050, percent change
Country GFDL HadGEM IPSL MIROC Median of 4
Colombia -8.3 -8.5 -23.1 -8.0 -8.4
Costa Rica -7.1 -8.4 -14.5 -5.0 -7.8
Guatemala -11.1 -13.7 -20.8 -18.2 -16.0
Honduras -6.2 -10.7 -24.8 -12.8 -11.7
Nicaragua -2.5 -9.8 -23.5 -5.4 -7.6
Peru -1.6 -5.0 -10.3 -10.0 -7.5
El Salvador -5.9 -18.0 -27.3 -13.5 -15.8
Source: Authors using composite of AgMIP GGCMI (Rosenzweig et al. 2014).

12. IMPACT Bioeconomic Model
159 countries, 154 water
basins, 320 total units
39 crops, 6 livestock
types, 17 processed foods
Post-solution models:
nutrition and health, CGE
model, land use
Source: Taken
from Robinson
et al. (2015).

13. Changes in maize yields, 2010-2050
Yield change, 2010
to 2050, ignoring
climate change
Effect of climate change on yield, relative to no climate
change, in 2050
Country
Median of 4
climate models
Minimum of 4
climate models
Maximum of 4
climate models
Costa Rica 55.8 -6.2 -13.3 -2.2
Guatemala 72.2 -13.5 -18.5 -10.8
Honduras 67.1 -9.4 -21.7 -6.3
Nicaragua 84.1 -7.1 -18.7 -4.1
El Salvador 50.3 -13.1 -26.2 -5.8
Colombia 32.2 -8.0 -11.2 -5.1
Peru 49.6 5.8 5.0 6.0
Source: Authors using IMPACT model (Robinson et al. 2015).

14. Production changes for 7 crops for the region
(all 7 countries), 2010-2050
Yield (tons per hectare)
Area harvested (thousands of
hectares) Production (thousands of tons)
Crop 2010
% chg,
2010-
2050,
NoCC
% Diff, NoCC
to Median,
2050 2010
% chg,
2010-
2050,
NoCC
% Diff,
NoCC to
Median,
2050 2010
% chg,
2010-
2050,
NoCC
% Diff,
NoCC to
Median,
2050
Maize 2.13 53.9 -5.1 2,806 32.1 -1.3 5,990 103.4 -6.3
Sugar cane 97.27 27.4 -27.6 1,008 54.1 14.5 98,046 96.2 -17.2
Rice 4.07 12.6 2.8 930 -8.1 0.5 3,782 3.5 3.3
Beans 0.89 50.9 -11.8 825 43.2 -3.4 737 116 -14.8
Sorghum 2.19 51.4 -11.3 302 62.6 7.9 661 146.1 -4.2
Oil palm 18.38 24.2 -1.1 365 45.8 0.0 6,709 81.1 -1.1
Cassava 11.32 57 -3.7 299 18.7 1.6 3,383 86.3 -2.2
Source: Authors using IMPACT model (Robinson et al. 2015).

15. How might modeling help policy makers?
Quantitative data for prioritization
Range of uncertainty → planning flexibility
Prioritization at sub-national scales
Modelling itself is not enough, feedback is
key

16. Recommendations from the study
Agricultural research and extension systems are critical.
Take a deeper look to expansion of irrigation.
Consider spillover effects on food security and poverty reduction when
aiming for yields improvement.
There is a knowledge gap in coffee yield effect of climate change in some
locations.
Allowing cultivation in higher elevations needs to be supported by robust
land use and conservation laws.
Development of sugar more suitable to hotter environments should be
considered a priority in agricultural research.
Differences in types of farmers are key to consider when developing
adaptation strategies.

17. Publications
All documents can be found at
▪ https://www.ifpri.org/project/agricultural-adaptation-climate-
change-latin-america-and-caribbean
▪ https://www.ifpri.org/collections/related/publications/20919
Most documents are in Spanish and English (Spanish discussion papers
to be loaded by the end of this week). Documents include:
▪ Country reports (60-100 pages per report) for each of the 7 countries
▪ Technical report on the methodologies used in the study
▪ Project paper and blog summarizing regional findings
▪ Links to the presentation at COP24

18. If you want to learn more, get in touch:
Timothy Thomas, Research Fellow, International Food Policy Research Institute (IFPRI)
(tim.thomas@cgiar.org)
Ana R. Rios, Natural Resources and Climate Change Senior Specialist, Inter-American Development Bank
(ARIOS@iadb.org)
Deissy Martínez Barón, Regional Program Coordinator for Latin America, CGIAR Research Program on
Climate Change, Agriculture, and Food Security (CCAFS) (d.m.baron@cgiar.org)
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