May 16 in Parallel Session 3B "Erratic Weather Patterns: Dealing with Climate Change". Presented by Alex De Pinto, IFPRI.

1. Does Climate Smart Agriculture
Contribute to Resilience?
Alex De Pinto
Senior Research Fellow
Environment and Production Technology Division
International Food Policy Research Institute
Addis Ababa, MAY 2014

2. A few definitions
 From one of the last documents circulated by the CSA
Alliance:
Climate Smart Agriculture, three pillars
• Sustainably increasing agricultural productivity;
• Adapting and building resilience to climate change;
• Mitigating greenhouse gas emissions.
 Distinction between Adaptation and Resilience:
• Adaptation capacity: the ability of humans to deal with
change in their environment (Folke et al., 2004).
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3. An empirical example from India
 ACIAR project on: Capturing the potential for
greenhouse gas offsets in Indian agriculture
 Period under consideration 2010-2050
 Essential components are:
• IMPACT model: a global partial equilibrium model of
agricultural commodities
• A spatially-explicit model of land use choices which
captures the main determinants of land use choices
• Crop model (DNDC) to simulate yield, GHG emissions,
and changes in soil organic carbon
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4. Data and Simulations
 Basic data on output prices (country-wide) and production
costs (state-wide) taken from the Agricultural Statistics,
2013.
 Extensive (but not exhaustive yet) search of published,
and not yet published, data on changes in production
costs related to adoption of alternative agricultural
practices.
 From DNDC we derive:
• Yields changes
• Carbon dioxide (CO2, from mineralization of organic matter)
• Nitrous oxide (N2O)
• Methane (CH4)
• Soil organic carbon (SOC) accumulation/depletion
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5. Simulated Cropping Systems
Cropping system Karif Rabi
Groundnut-wheat Groundnut Wheat
Maize-wheat Maize Wheat
Pearl millet-wheat Pearl Wheat
Rice-fallow Rice fallow
Rice-pulses Rice pulses
Rice-rice Rice Rice
Rice-wheat Rice Wheat
Sorghum-wheat Sorghum Wheat
Soybean-wheat Soybean Wheat
Source: Efficient alternative cropping systems. Gangwar and
Singh, 2012
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6. Simulated Practices
Management
technique Description
Conventional
Prior to first crop in rotation tillage to 30cm depth; subsequent tillages
(following each crop in rotation) to 10cm depth. fertilizer N applied as
urea on plant date; manure applied on plant date
No-till Tillage only mulches residue
AWD
Rice paddy is initially flooded to 10 cm – water level is reduced at rate
of -0.5 cm/day to -5cm and then re-flooded at rate of 0.5 cm/day till to
10 cm
No-till + organic
fertilizer (manure)
Tillage only mulches residue
50% of chemical fertilizer N replaced with organic fertilizer N (manure)
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7. Technical Mitigation Potential
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8. Relevant Information: CSA
(calculated from a selection of states)
 Effects of Adoption of Select Mitigation Practices on
Yields
 Effects of Adoption of Select Mitigation Practices on
GWP
 Effects of Adoption of Select Mitigation Practices on
SOC
 Effects of Adoption of Select Mitigation Practices on
Net Revenues
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9. Climate Smart Agriculture
Sustainably Increase
Productivity Adaptation Mitigation
Best
CSA
Output SOC SOC
Net
Revenue
GWP
No Till + + ++ + +
Org. Fert. +
No Till -- -- +++ -- ++
AWD - + + 0 +++
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10. Sustainably Increase
Productivity Adaptation Mitigation
Best
CSA
Output SOC SOC
Net
Revenue
GWP
No Till + + ++ + +
Org. Fert. +
No Till -- -- +++ -- ++
AWD - + + 0 +++
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11. Sustainably Increase
Productivity Adaptation Mitigation
Best
CSA
Output SOC SOC
Net
Revenue
GWP
No Till + + ++ + +
Org. Fert. +
No Till -- -- +++ -- ++
AWD - + + 0 +++
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12. Sustainably Increase
Productivity Adaptation Mitigation
Best
CSA
Output SOC SOC
Net
Revenue
GWP
No Till + + ++ + +
Org. Fert. +
No Till -- -- +++ -- ++
AWD - + + 0 +++
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13. Relevant Information: Resilience
(resilience refers to the production system)
 Effects of Adoption of Select Mitigation Practices on
Yields under extreme events
 Effects of Adoption of Select Mitigation Practices on
Yield variability
 Climate extremes were calculated by considering 97.5
and 0.25 percentiles based on annual precipitation
records for the period of 2004 to 2050 at each pixel.
Then assumed that climate extremes would
be. upper 2.5% and lower 2.5% events at each pixel
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14. CSA vs. Resilience
Sustainably Increase
Productivity Adaptation Mitigation Resilience
Output SOC SOC
Net
Revenue
GWP
Better
Output in
Weather
Extreme
years
Reduced
yield
variability
Net
Revenue
No Till
+ ++ ++ + + + - +
Org.
Fert. +
No Till
- - +++ +++ - - ++ - - - - - -
AWD
- + + 0 +++ - + 0
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15. Conclusions
 There seems to be compatibility between CSA
and increased resilience of the productive system,
but….
 We first need to fully explore and agree on the
definition of CSA, i.e. boundaries and trade-offs,
 The analysis results indicate a large spatial
variability: difficult to make blanket statements of
best practices,
 This type of multi-objective analysis becomes
complicated very quickly and it complicates the
formulation of policy recommendations.
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