By Patricia Masikati

1. Assisting smallholder farmers in mixed
crop-livestock systems to understand
the potential effects of management
options and climate change through
participatory modeling
Patricia Masikati
Beating Famine Conference 14- 17 April 2015
Lilongwe, Malawi

2. Outline
• Participatory approaches in mixed farming
systems
• Frame work
• Participatory modeling
• Use of approach in Agroforestry systems
• Key messages

3. • Complex systems with various interacting subsystems
• Productive resources are limited and used inefficiently as evidenced by
continued low production
• Low technology adoption
• Limited integration of diverse viewpoints from experts and specialized
stakeholders during technology development
• Viewed as an important route to increase productvity and sustainability
of small-holder farmers
Integrated crop-livestock systems

4. • Inclusion of stakeholders in technology
development, implementation and marketing
of the products
• Participatory modeling: combines
participatory research approach and
computer based modeling that engages
stakeholders
• Iterative processes to bring about widely
accepted solutions
• Facilitates cooperative learning and
developments of solutions
Participatory methods

5. • Iterative process-more widely
accepted solution
• Cooperative learning and
development of solutions
• Improvements as new situations
arise
Framework

6. Participatory modeling approach
Day 1
Day 1Day 2Day 3

7. On-farm testing

8. Water efficient farming systems
0
2000
4000
6000
8000
10000
12000
System2 system1
Total available biomass kg
Insiza
mazhayimbe
0
1
2
3
4
System2 WP System1 WP
System WP kg/m3
Insiza
mazhayimbe
-6000
-4000
-2000
0
2000
4000
System2 system1
Feed deficits kg/year
Insiza
mazhayimbe
Result presentation and discussion
Effect of inclusion of forage crops in current farming systems on total biomass, feed
deficits and total biomass water productivity. System 1 = Maize, Mucuna and Bana
grass, system 2 = Maize and groundnuts.

9. 0
10
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80
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100
0 50 100 150 200 250 300 350 400 450
Probabilityofexceedence(%)
% grain requirement met
Control
Micro-dose
Mz_muc
100%
0
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50
60
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80
90
100
0 25 50 75 100 125 150 175 200 225 250
Probabilityofexceedence(%)
% DM requirement met
Control
Micro-dose
Mz_muc
100%
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200 250 300 350 400 450
Probabilityofexceedence(%)
% grain requirement met
Control
Micro-dose
Mz_muc
100%
0
10
20
30
40
50
60
70
80
90
100
0 25 50 75 100 125 150 175 200
Probabilityofexceedence(%)
% DM requirement met
Control
Micro-dose
Mz_muc
100%
Current climate
Future climate
Longterm Impacts of food and feed requirements

10. Potential Use of Approach in Agroforestry Systems
• Tradeoffs and synergies occurring both on-
and off-site and varying over time
• Involves a number of stakeholder,
• Benefits achieved in the longterm, CSA
Lloyd S et al., 1993
• Agroforestry systems are complex
with various interrelating factors
• Involves multiple products or
benefits (non and intended),

11. Possible Agroforestry arrangements with 25% tree cover
Lloyd S et al., 1993

12. • Potential to achieve many of the environmental, economic
and social objectives which field experiments and other
participatory approaches might not be able fathom.
• Targeting of relevant and significant interventions in farming
systems
• Facilitates analysis of individual components to understand
simplistic relationships, evaluation of more complex
interactions and determine overall systems efficiency.
• Ex-ante impact assessments and interactions from increased
management input and increased diversity, along with
determining efficient risk reduction strategies in the context of
climate change
Modeling Agroforestry Systems

13. • Systems modeling has been used to achieve relevant and
significant interventions in commercial farm management
systems e.g. Australia
• Modeling has not yet received much significant attention in
complex farming systems and decision-making processes in
SSA.
• Constraints to application of this methodology are mainly lack
of data (biophysical, socio-economic), expertise and validated
modeling tools or models.
Constraints

14. • Use of these tools
• Would significantly contribute to sharpen our understanding
on impacts of different interventions
• Targeting of relevent interventions to improve, systems
efficiency with much less resources as compared to field
experiments.
• Assist in determining profitable and feasible intervention
before implementation.
• As said by Dosskey and Wells, 2000 “Few things disappoint a
landowner such as spending money, time, and effort on a project that
fails…. Especially one like agroforestry, where it can be years before
problems become apparent”.
Avenue worth pursuing

15. • The complex nature of smallholder farming systems means that
there are many entry points and a wide range of technologies
and strategies on offer
• Computer-based participatory modeling offers scientists,
farmers and specialized stakeholders a tool to develop and
evaluate the impact of interventions at varying scales in time
and space
• The process allows farmers, scientist and other stakeholders
to understand the impact of their decisions, evaluate new
options and define possible production and management
options tailored to their particular circumstances
• However technology adoption is not mainly based on its
agronomic performance but by other factors/uses that would be
important to the overall farm production and household needs
Key messages

16. THANK YOU