Adapting agriculture to progressive climate changeJulian Ramirez

& Theme 1 team

(c) Neil Palmer (CIAT)

Contents

• Background– The problem: Climate, climate change and

agriculture– The framework: CCAFS

• Theme 1 workplan• Modelling impacts of climate change• An example with beans

(c) Neil Palmer (CIAT)

Background: climate, climate change and agriculture

• Agriculture is a niche-dependent activity– Located in suitable AND subjectively selected

areas– Affected by variations in climatic and social drivers

• Yet there are shared strengths and weaknesses, each system is an specific case

• Climate is the least predictabl driver of agriculture

• Climate will change

(c) Neil Palmer (CIAT)

• Population growth• Non-environmentally

friendly technologies/practices

LEAD TO GREENHOUSE GASES EMISSIONS OUTBREAKS

Background: CCAFS

• Stands for Challenge Program on Climate Change, Agriculture and Food Security

• Created by the Consultative Group on International Agricultural Research (CGIAR)

“Assessing impacts of climate change, facilitate adaptation and alleviate poverty under changing

conditions”

Background: CCAFS

• Who does the research?15 centres + ~70 regional offices

Background: CCAFS

• Where is it commited to work? Why?

Prone to drought & flooding, but with

strong regional climate institutions

for adapting

Prone to drought & flooding (cyclones), and risk from sea level rise

Background: CCAFS

• How does it act?

(2030s)

Theme 1: Adaptation pathways under progressive climate change

• What does a 2C degree warmer world mean for agriculture?

• What precipitation trend is expected for the different regions

• What practices and technologies do exist?• Which of these can be transferred to facilitate

adaption? How?• What new need to be developed/adjusted for

adaption• How to communicate all this?

Assessing impacts of future climate

Climate model projections by 2030s

Research areas: Available and usable climate data

BCCR-BCM2.0 CCCMA-CGCM3.1-T47 CNRM-CM3

CSIRO-MK3.0 CSIRO-MK3.5 GFDL-CM2.0

GFDL-CM2.1 INGV-ECHAM4 INM-CM3.0

IPSL-CM4 MIROC3.2-MEDRES MIUB-ECHO-G

MPI-ECHAM5 MRI-CGCM2.3.2A NCAR-CCSM3.0

NCAR-PCM1 UKMO-HADCM3 UKMO-HADGEM1

Temperature trend 21st century

Modelling approaches

• Selection of crops to assess• Selection of crop models to use• Collating input climate and agricultural

data• Design of experiments• Calibration, validation and crop model

runs

(c) Neil Palmer (CIAT)

Developing adaptation strategies

• Explore adaptation options– Genetic improvement– On-farm management practices

• Test them via modelling• Build “adaptation packages”• Assess technology transfer options

(c) Neil Palmer (CIAT)

Examples: Modelling bean production

Growing season (days) 90

13.6

17.5

23.1

25.6

Minimum absolute rainfall (mm)

200

Minimum optimum rainfall (mm)

363

Maximum optimum rainfall (mm)

450

Maximum absolute rainfall (mm)

710

Killing temperature (°C) 0

Minimum absolute temperature (°C)

13.6

Minimum optimum temperature (°C)

17.5

Maximum optimum temperature (°C)

23.1

Maximum absolute temperature (°C)

25.6

What will likely happen?

2020 – A2

2020 – A2 - changes

Developing adaption strategies

Most effective genetic improvement strategy for areas that are likely to be vulnerable to the 2050s climate.