AusAID Food Security through Rural Development Initiative,Farming systems research and modelling,Agricultural Production Systems Simulator

1. Systems modeling is as essential component of systems
research - past and planned cases in Africa
Peter Carberry
CSIRO Sustainable Agriculture Flagship

2. Outline
• AusAID Food Security through Rural Development
Initiative
• Farming systems research
• Farming systems modelling
• Current status

3. Food Security through Rural Development
Initiative
• Australian Government commitment
• $464 million to encourage greater food security globally
• $100 million for Africa
• 4 years (but re-occurring)
• African Food Security Initiative
1. Increasing agricultural productivity through increased
investments in agricultural research and development;
2. Improving rural livelihoods by helping to address market
failures that hinder economic development in rural areas;
and
3. Building community resilience by supporting social protection
mechanisms that enable vulnerable people to withstand
shocks.
• Administered through AusAID

4. Agricultural research and development in
Africa
1. Sustainable Intensification of Maize-Legume Farming
Systems for Food Security in Eastern and Southern
Africa (SIMLESA) ($20M)
• Funding via ACIAR’s project development process
• CIMMYT led
• Australian partners
2. AusAID/CSIRO African Food Security Initiative ($30M)
• AusAID support for CAADP Pillar 4
• CSIRO led
• African partners
• CORAF in West Africa
• BecA in East Africa

5. SIMLESA collaboration
SIMLESA, 2010
4 PhD scholarships
granted
University of Sydney (Risk management)
African Universities University of Western Sydney (Socio economics)
IRI AusAid Charles Sturt University (Policy & innovation)
TIAR CSIRO University of Southern Queensland (Climate change)

6. SIMLESA aims
Aims at increasing farm-household food security and productivity, in the context of
climate risk and change, through the development of more resilient, profitable and
sustainable maize-legume farming systems
Socio-economic More productive, Improved range
characterization resilient and of maize and
sustainable legume varieties
Input and output smallholder available for
value chain maize-legume smallholders
practices, tactics
Whole farm and strategies
resource
allocations
Scaling out and capacity building
30% increase in maize yields and 30% reduction in risk
500,000 households over the next 10 years

7. AusAID/CSIRO African Food Security Initiative
• CORAF/WECARD
• Dakar, Senegal
• 22 member States
• Mandated to coordinate the implementation of
CAADP Pillar IV in West and Central Africa
• BecA
• Nairobi, Kenya
• Managed by ILRI (International Livestock Research
Institute)
• Shared agricultural research and biosciences
development platform

8. Pillar I - Land Management
NEPAD CAADP Pillar II - Rural Infrastructure
Pillar III - Food Supply
Agricultural Research CAADP Pillar IV
and Dissemination
WCA RECs FARA FAAP
NASRO CORAF/WECARD ASARECA CARDESA
Strategic • Empowerment
National Plans • Pluralism in delivery
Plans of • Subsidiarity
Operational • Evidence-based approaches
ARI • Sustainability
Univ. Plans
• Integration of
Ministries Research/extension
Programmes • MIS
NGO
CSO • Cost sharing
Projects • Integration of gender

9. Research agenda and current/future
projects
• BecA:
• Food and Nutrition Science (FANS) scoping study
• Analyse food systems (farm to consumption)
• Identify opportunities within value-chains
• Animal health
• Pest des Petits Ruminants (PPR) disease control
• African swine fever
• Capacity building/Challenge Fund
• CORAF/WECARD:
• 5 projects being developed
• 3 farming systems focus in the sub-humid to semi-arid zone
• Seeds systems project – based in Mali
• Animal Health Project – Ticks and tick-borne diseases

10. Australian RDE expertise highly relevant to
dryland agriculture in Africa
• Similarity in environments
• Shared constraints to biological productivity
• Agricultural research and extension
• Systems science and modelling
• Conservation agriculture
• Livestock/crop integration
• Water management (droughts and flooding)
• Eucalypt and Acacia based forestry
• Participatory extension models including private sector and NGOs
• Natural resource management
• Community based approaches to NRM
• Rangelands and biodiversity science
• Climate science
• Seasonal climate forecasting
• Economic and policy research
• Analysis of market and trade liberalisation
• Research infrastructure and institutional arrangements
• Collaborative research centres
• Australian scientists with overseas research experience

11. Farming Systems Research – Collinson 1982
On-farm
research
Operations
research
On-station
research

12. Rigour v’s relevance?
High
Control
Envir. expts.
On-station expts.
Data Simulations
integrity On-farm
/ Rigour trials
On-farm
demonstrations
Surveys Case studies SCIENCE
Archives Stories NONSCIENCE
Myths
Low Personal opinion Legends
Low High
Currency / Relevance
Bonoma 1985, Crookston 1994

13. A shifting emphasis in research?
High
Control
Envir. expts.
On-station expts.
Data Simulations
integrity On-farm
/ Rigour trials
On-farm
demonstrations
Surveys Case studies SCIENCE
Archives Stories NONSCIENCE
Myths
Low Personal opinion Legends
Low High
Currency / Relevance
Bonoma 1985, Crookston 1994

14. Participatory research (1994)
• Honest in admitting to being long on
rhetoric and short on achievements
• High time costs of participation
• Dependence on qualitative data
• Difficulties in data & analysis
• Poor evaluation
• Difficulties in publication
Rhetoric and reality • Lack of recognition & rewards
• 11 case studies … on-ground impacts
mostly promises
Okali, Sumberg and
Farrington, 1994

15. Participatory research (2003)
• Now lots of participatory methodologies
promoted (>30)
• The promise of bringing “practical reality
to bear on generalised concepts”
• Problems of evaluation, data analysis &
publication persist
• A call for organisational learning &
change
Uniting science &
• 23 case studies … the rhetoric
participation
continues?
Pound, Snapp, McDougall
and Braun (eds) 2003

17. A preferred shift in emphasis?
High
Control
Envir. expts.
On-station expts.
Data Simulations
integrity On-farm
/ Rigour trials
On-farm
demonstrations
Surveys Case studies SCIENCE
Archives Stories NONSCIENCE
Myths
Low Personal opinion Legends
Low High
Currency / Relevance

18. A proposed methodology
High
Participatory Action
Research & systems
Control
Envir. expts. modelling
On-station expts.
Data Simulations
integrity On-farm
/ Rigour trials
On-farm
demonstrations
Surveys Case studies SCIENCE
Archives Stories NONSCIENCE
Myths
Low Personal opinion Legends
Low High
Currency / Relevance
Carberry, P.S., 2001. Are science rigour and industry relevance both achievable in
participatory action research? Agricultural Science, 14:22-28

19. APSRU’s systems approach
Farming Systems Research – Collinson 1982 APSRU Strategic Plan 1991 -1995

20. Agricultural Production Systems
Simulator (APSIM) www.apsim.info
The soil provides a central focus, crops, seasons and
managers come and go, finding the soil in one
state and leaving it in another
Simulates:
 mechanistic growth of crops, pastures, trees,
weeds ...
 dynamics of populations (eg. weed seedbank)
 key soil processes (water, solutes, N, P, carbon,
pH)
 surface residue dynamics & erosion
 dryland or irrigated systems
 range of management options
 crop rotations + fallowing + mixtures
 short or long term effects
 one or two (multi-point) dimensions
 high software engineering standards
 language independent (VENSIM™ module maker)
 now includes pests nor diseases
 links to livestock modules

21. Example APSIM applications
• cereal-legume rotations (Probert et • climate change impacts (Howden et al.,
1999)
al.1995)
• ley farming systems (Carberry et al. • agribusiness value chain (Brennan et al.,
2000)
1996)
• intercropping systems (Carberry et al.
• tree windbreak systems (Meinke et al. 2001)
1996) • deep drainage assessment (Keating et al.,
2001)
• alley farming systems (Nelson et al.
1998) • soil acidification (Verburg et al., 2001)
• drought policy formation (Keating & • risk assessment of GMO (Smith et al. 2001)
Meinke 1998) • effluent irrigation (Brennan et al., 2002)
• erosion impacts (Connolly et al. 1998)
• agroforestry systems (Huth et al., 2002)
• genetic trait identification (Robertson et
• crop-weed competition (Keating et al. 1999)
al. 1999)
• seasonal climate forecasting (Hammer • smallholder farming systems (Carberry,
2004)
et al. 1999)
• on-farm trial analyses (Robertson et al. • biodiversity assessment (Huth et al., 2008)
1999)

22. Need examples of successful PAR
achieving science innovation & impact
… 17 years of action research

23. ACIAR Kenyan Project (1985-1992)

24. Modelling was a “new frontier” in 1985

25. Observed grain yields – average 1990-1999
3.00 3 -
Average grain yirld (t/ha)
2.50 2.5
2.00 2
1.50 1.5
1.00 1
0.50 0.5
0.00 0
lo w al Stepc1 p
ro ulc
h utStep 2 ge Step 3nputStep 4
fal itio
n
er m inp ti lla i
e d Int m d gh
a r
Tra C 50
% diu ce Hi
AB B D Me ed
u G
E F R
Predicted averages : 1957 – 1988
Keating, Wafula & Watiki 1990, Climatic Risk Symposium

26. Example - Linking Logics workshop
• Initiative of ICRISAT /
CIMMYT
• October 2001, Zimbabwe
• Hosted at Jusanani
carpentry workshop owned
by farmer Richard
Ndimande
• Mkubazi School, PO Box
44, Tsholotsho.
• Between 30-40 farmers
attended each day

27. Peter Carberry, Christy Gladwin and Steve Twomlow, 2004. Linking
Simulation Modelling to Participatory Research in Smallholder Farming
Systems. ACIAR Proceedings No. 114. pp32-46
What worked?
Why did farmers give the simulations
credibility?
What indicators of impact?
How to scale up?
Follow-on project with ICRISAT -
Using systems simulation to
enhance the effectiveness of
agricultural change agents in the
southern African semi-arid tropics
(SAT)

28. Forward projections – with APSIM

29. New initiatives informed by past efforts

30. Systems simulation across different scales
gene crop farm catchment region
QTL map for Sorghum
Broadened spatial scale

31. … genes in environments
Farming system
Crop
Plant Traits Traits
Cell
Traits
Nucleus enzymes
Genes YIELD
substrate products
• Interaction across scales:
– Environment signals Profitability
– Gene responses = trait expression
Hammer, G., Sinclair, T., Chapman, S. and van Oosterom, E. (2004). On systems thinking, systems
biology and the in silico plant. Plant Physiology 134: 909-911.

32. … analysing decisions at the whole farm
level
APSFARM
APSFARM Farm Manager
APSIM Paddock Manager
Report Climate
Forecast
Livestock E Economics
N
Pastures Soilwat
G
Crops I
N SoilN
Surface Residue E
Irrigation Erosion
Rodriguez et al., 2009

33. Systems simulation of the normal, novel &
natural
The normal, the novel & the natural
Growth, water use and life form analysis of cropping,
novel agroforestry systems and native woodland
Increased boundaries to the biophysical system

34. … below ground dynamics in multi-point
agroforestry systems
Soil Water
Extraction
50 m
1.5 m
Neil Huth 2007

35. Combining bio-physical & ecological models
Habitat complexity
9
score
Habitat Complexity Score
6
Ecologic
al model
3
Trees Only
Trees + Grass
Trees + Grass + Shrubs
Edge Trees Only
0
0 10 20 30 40
Woodlot Age (years) Species richness
50
0 to 5
5 to 10
APSIM 40 10 to 15
15
30
Species
Tradeoffs in
20
economic &
ecological 10
performance 0
1 10 100 1000
Neil Huth 2009 Area (ha)

36. In summary
• AusAID Food Security through Rural Development
Initiative represents a significant re-entry of Australia
in supporting African RDE
• Significant that agriculture RDE is a key delivery
platform
• Systems modelling will be a key contribution from
Australia