ccafs science meeting item 07 mario herrero - household modeling
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CCAFS Science Meeting presentation by Mario Herrero - "Household modeling for ex-ante evaluation and targeting of climate smart agriculture"TRANSCRIPT
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Household modeling for ex-ante
evaluation and targeting of climate
smart agriculture
Mario Herrero
CCAFS Science Meeting, Copenhagen, May 2012
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At ILRI: Mariana Rufino, Mark van Wijk, Carlos Quiros
CCAFS theme leaders: Philip Thornton (funding/strategy),
Jim Hansen, Lini Wollenberg, Andy Jarvis
CCAFS Regional Coordinators (funding): James Kinyangi
(EA), Robert Zougmore (WA), Pramod Aggarwal (SA)
CG centres: IWMI, ICRISAT, CIMMYT, ICRAF (for now)
Universities and Research Centres: Wageningen,
Hohenheim, Tasmania, Oregon, Washington State (for now)
This work involves many others
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CCAFS engaged heavily in analysing regional and global
impacts on agriculture and exploring future pathways of
agricultural development through scenario analysis
Considerable work on adaptation and mitigation practices at a
local level
Ex-ante assessment and targeting: what might work where
and how this might change depending on the notions of the
future
Household modelling: offers the possibility of helping with
these issues.
A well established area, large community of scientists
Not widely used in climate change activities yet.
Background
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W. Africa 1966 – pastoral system 2004 – crop-livestock system
Systems and livelihoods in transition: the target is moving! Can we ensure that the next transition is sustainable, equitable and helps
feed the world?
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National
Production
Mixed
rainfed
temperate
Mixed
rainfed
humid
Mixed
rainfed
arid
2030 2050 2030 2050 2030 2050 2030 2050
Burundi 9.1 9.1 14.4 18.1 -1.8 -8.8 - -
Kenya 15.0 17.8 33.3 46.5 -4.6 -9.8 -1.1 -8.4
Rwanda 10.8 14.9 13.4 18.8 5.4 3.6 1.1 2.7
Tanzania -3.1 -8.1 7.5 8.7 -1.6 -6.4 -5.1 -11.1
Uganda -2.2 -8.6 4.9 3.1 -4.6 -12.9 -1.1 -6.3
A game of winners and losers…at all scales Simulated percentage maize production changes to 2030 and 2050, by
country and system
Mean of 4 combinations of GCM and emissions scenario
Thornton et al. (2010)
Winners
Losers
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Understanding complex systems
Herrero et al, Science (2010)
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J F M A M J J A S O N D
Rainy Dry Dry
Groundnuts
Yams
Sorghum
Grazing Critical Crop
residue
Cut &
Carry
Prot. & Ene.
deficit Food security
Energy
deficit Family’s
nutrition
Feeding calendar
Cropping calendar
Weather calendar
Monthly calendar of different activities of the system
Cash demands Very
high Low High High Low Lo
w
High High
Wa, Upper West, Ghana
Gonzalez-Estrada et al. 2006
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0
0.5
1income
food security
GHGwater use
external inputs
mixed
pastoral
There are always trade-offs Different practices…
Different farming systems….
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Plot Crop
Homestead Enset, coffee, kale, sweet potato, maize
Plot1 Maize
Plot 2 Sweet potato, wheat
Plot 3 Maize
Plot 4 Sweet potato
Plot 5 Barley
Plot 6 Maize
Plot 7 Unimproved pasture
What’s the likely impact of alternative
interventions?
Site: Sodo, Ethiopia
Profit: Birr 2,381/yr Livestock: 1 cow, 1 ox
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Site: Sodo, Ethiopia
Critical Adequate
Current
management
Food security
Cow feeding
Labour/capital
Cash
Soil fertility
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Food security
Cow feeding
Labour/capital
Cash
Soil fertility
Site: Sodo, Ethiopia
Critical Adequate
Intervention 1
Food crop Application of fertilizer to
maize plots.
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Food security
Cow feeding
Labour/capital
Cash
Soil fertility
Site: Sodo, Ethiopia
Critical Adequate
Intervention 2
Feed crop Replace native grassland
with improved pasture.
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Food security
Cow feeding
Labour/capital
Cash
Soil fertility
Site: Sodo, Ethiopia
Critical Adequate
Intervention 3
Food/feed crop Introduction of cowpea in
the system.
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Food security
Cow feeding
Labour/capital
Cash
Soil fertility
Site: Sodo, Ethiopia
Critical Adequate
Intervention 4
Food crop Subsidy for barley
production
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Adaptation, risk management and
mitigation options will depend largely
on how we shape the world
• Several options exist though largely dependent on our vision of world development and how it plays out in different regions
• essential to link household modelling to scenarios of change
• Different paradigms of agricultural development (industrial vs pro-poor smallholders, large vs family farms)
• Globalisation and trade patterns
• Consumption patterns
• Carbon constraints
• Roles and incentives for technology adoption
• Growth in other sectors
• Power relationships
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Global Scenarios
Regional Scenarios
Farmer/village
perspectives Action research
Participatory
scenario building
Global visioning
activities
Global impacts
modelling
Regional impacts
modelling
Household &
community
impacts modelling
Linking research at different levels
Thornton et al 2012
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Ex-ante analysis and targeting of
options
• Studying livelihoods transitions
• Targeting the vulnerable (winners and losers)
• Which options could fit in which systems under which conditions?
• How upscalable to broader recommendation domains/regions?
• How robust are options across scenarios and farming systems
• Priority setting for investments (how many farmers, what areas, how much?)
• Mitigation / adaptation synergies
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CCAFS activities in relation to
household modelling
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Household data collection in the CCAFS sites
• Development of simplified, but robust and standard data collection protocols
• Collecting detailed information from representative farming systems from the CCAFS sites
• 150-200 households per site: approx 3000 surveys
• Data collection during 2012
• Statistical analysis and modelling of adaptation, risk management and mitigation options from 2012 (with input from centres and themes)
• Funded by Theme 4 and the regions
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All survey materials and data at ccafs.cgiar.org/resources/baseline-surveys Dataverse at dvn.iq.harvard.edu Adaptation and Mitigation Knowledge Network at amkn.org
CCAFS sites in West Africa, East Africa and South Asia
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Data collection + household modeling protocol :
Climate
Family structure/gender
Land management
Livestock management
Labour allocation
Family’s dietary pattern
Farm’s sales and expenses, income
Herrero et al 2007
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A review of farm household modelling with a focus on climate change
• A systematic review of 16000 thousand references
• Covered long term adaptation, risk mangement and mitigation
• Covered diverse modelling techniques (LP, agent based models, simulation, others)
• Identification of useful tools for CCAFS work
• Integrated models using more than one modelling technique more suitable for CC questions
• Engagement with other modellers
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Workshop: Farm-household Modeling with a focus on Food security, Climate change adaptation, Risk management and Mitigation: a way forward
• Goal: to identify current potential of and weaknesses in farm- and household-level models, and laying out practical pathways to improve these models to address CCFAS systems questions
Amsterdam, The Netherlands 23 to 25 April 2012
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Conclusions from the workshop • Modelling approaches are available to address household-level
questions. This needs to include higher levels of integration to capture key drivers.
• It is possible to analyze household-level questions related to climate change in a reasonable short time (6 months to 1 year) span with the existing tools.
• Activities to develop repositories for models and data are urgently needed to increase further development of models and make better use of existing knowledge.
• A team of modellers with different expertise is needed to address questions related to climate change agriculture and food security.
• The research questions must lead to the suite of models and expertise needed. Not much model development is needed.
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Next steps
• Continue the data collection in the regions
• Develop suitable databases and repositories for the information for open access by CCAFS and partners
• Data analyses
• Linking with the international household modelling teams to prepare potential tools for analysis
• Extensions to community-level modelling
• Maybe fund some additional development as needed
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Conclusions
• Household modelling can play a key role in the ex-ante evaluation and targeting of adaptation and mitigation work of CCAFS
• It can help link work at multiple-scales: for example the scenarios work in the regions to impacts and options in different types of farming systems
• It can lead to robust multi-centre and multi-theme work by exploiting complementary skills to solve complex problems
• ….and provide realistic, sometimes simplified, answers
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Thank you