This document discusses adapting agriculture to climate variability and extreme events. It covers adapting at local, regional, and global scales through forecasting, using crop models and historical data to identify optimal planting dates, developing genetically adapted crop varieties, and enhancing systemic resilience through strategies like strategic storage, import diversification and flexible biofuel policies. The importance of understanding changes in extreme events for agricultural production is also emphasized.

1. Adaptating agriculture to climate
variability and extreme events
Julian Ramirez-Villegas
School of Earth and Environment, University of Leeds
CGIAR Research Program on Climate Change, Agriculture and Food
Security (CCAFS)

2. The importance of local climate
variability
Ray et al. (2015) Nat. Comms.

3. … of major modes of variability
Iizumi et al. (2014) Nat. Comms.

4. …And of extremes
Porter et al. (2014)

5. Types of changes climate and
implications for extremes
IPCC (2012) SREX

6. Sillmann et al. (2013) JGR

7. Porter et al. (2014)

8. Extremes across temporal scales
Sub-daily, daily, sub-seasonal, seasonal and yearly
Asseng et al. (2015) NCC
Trnka et al. (2014) NCC
GFS Resilience Taskforce (2015)

9. Extremes across spatial scales
• Global production shocks mediated by markets, with
impacts on prices
• Local weather-driven productivity and planted / harvested
area reductions
GFS Resilience Taskforce (2015)
Challinor et al. (2010)

10. Adaptation across timescales
Ramirez-Villegas and Khoury (2013) Clim. Chang.

11. Adaptating to changes in variability
and extremes
• At the local and regional scale --forecasting
Identify the most appropriate planting
date (with best environmental supply)
for rice crop in the period May - Dec
2014.
Farmers want to: Where
2
4
6
8
-76 -75 -74 -73 -72
Cluster_Multianual Cluster_Nina
-76
Agro-climatic rice
productive regions
Implement seasonal weather
forecasts + historical events of "El
Niño“+ mechanistic crop models
How?

12. Seasonal precipitation forecast
Crop yield simulation
F733
F2000
F60
<--- Sowing window --->
Validating recommendations
in the field (2014)
F733: 6860 kg/ha
F60: 4600 kg/ha
Barrios et al. (in prep)

13. Adapting to changes in variability and
extremes
• The role of genotypic adaptation
MeanyieldYieldvariability
Ramirez-Villegas and Challinor (under review)

14. Adapting to global shocks and
amplifications
• Less clear, but foremost, develop understanding of
changes in extremes in production (both area and
yield). Both global and regional-scale models have
roles to play
• Agricultural adaptation. Again both models have
roles to play (e.g. Land use vs. Agronomy).
• Enhance systemic resilience in global market system
(control export controls, flexibilise biofuel mandates,
market monitoring)
• National resilience: strategic storage, advance
contracts, dietary or import diversification