Humidtropics presentation describing how the Program organizes its regional research, and which principles and procedures it applies for site selection - Meeting of CGIAR’s Independent Science and Partnership Council (ISPC), September 2014.
2. Outline
1. Systems Research - Humidtropics
2. Action Areas and Flagship Projects
3. Regions & Site Selection Process
4. Extrapolation and scaling
5. Concluding Comments
4. Systems Research
• Involves whole-system analysis and interactions
– multi cropping systems,
– integrated crop – livestock,
– NRM – productivity-markets/institutions interactions
– gender and generational issues, etc.
• The blending of local and technical knowledge
• Matching of technological options to the biophysical
and socio-economic contexts
• Participatory multi-stakeholder engagement and
partnerships.
Livelihood enhancement, Sustainable Intensification
and NR integrity
5. Systems-CRPs
• Core business: Integrated systems
approaches
• The “melting pot” dimension: integration
across CRPs operating within AEZ
• Strategic partnership with selected CRPs
• Elements exist within other CRPs
6. 10 Elements of “Systemness”
1. Systems mindset
– Boundaries
– Components
2. Inter-”disciplinary” Teams
– Partnerships
– New competencies
3. Stakeholder engagement
– R4D, Innovation Platforms
4. Integrated systems:
interactions and trade-offs
5. Innovation: hardware,
software and ‘orgware’
6. Scale dimension:
-scaling up/out
7. Gender research:
-women and youth
8. Capacity building
-across “actors”
9. Development orientation
- IDOs
10. Learning
- mechanisms and
strategies
7. 100%
0%
Transitioning Towards Increased ‘Systemness’
Systems Research
- Situation analysis
- R4D Platforms
- Partnerships
- ETC.
Ongoing Research of Centres
• Various domains
• Progressive alignment towards
systems and IDOs
2012 2020
8. Theory of Change
B)
C)
Systems
Innovations
Poverty Destitute Status (SLO 2) Wealthy
Humidtropics
Strategic Objectives
All Four SLOs
High NR integrity
High productivity
Effective Institutions
High NR Integrity
High Productivity
A)
A2
Ineffective Institutions
Low NR Integrity
Low Productivity
A1
Degraded Ecosystem Integrity (SLO 4) Healthy
9. Program Framework
Better livelihood opportunities in a sustainable environment
West Africa
humid
lowlands
East and
Central
Africa humid
highlands
Central
Mekong
Central
America and
Caribbean
Cross-cutting
Themes
Tier 1
Sustainable
Intensification
Systems
Innovation
Women & Youth
Empowerment
Livelihoods
Improvement
Productivity + Environment Gender Income + Nutrition + Youth Innovation
Flagship Projects IDOs SOs
Tier 2
West Africa
Moist Savanna
Southern
Africa Moist
Savanna
Northern
Andes
Transect
Indonesian
Humid
Lowlands
SRTs
Systems Analysis and
Global Synthesis
Integrated Systems Improvement
Productivity x NRM x Institutions
Scaling and Institutional
Innovation
12. Flagship Projects
Instruments for research structuring, organization
and implementation.
Two types:
1. Crosscutting Flagship
2. Area-Based Flagships
• East and Central Africa
• West Africa
• Central America and the Caribbean
• Central Mekong
13. Flagship Projects Portfolio -
…The Hamburger Model
Crosscutting
Flagship
Area-based
Flagships
E
C
A
H
W
A
H
L
C
A
C
C
M
e
k
o
n
g
Crosscutting
Crosscutting Gender
Capacity Development
Monitoring and Evaltn.
Global Synthesis
Situation Analysis
Tools and Methods
Int. Systems Res.
• Nutrition
Innovation
14. Crosscutting Flagship
- Emerging Research Areas
Strengthening scientific coherence - in relation to our
Theory of Change and Program Hypotheses
1. Foresight (in partnership with others, CRPs)
2. Integrated soil fertility mgt. X Productivity X Markets
3. Social science and policy dimensions ???
How do these areas interact with the regional
Flagships? ……
… and with other CRPs???
15. Site Selection
Spatial analysis – ‘Hard’ criteria
• Use the 3 key variable site selection process, based
on:
• Poverty
• Market access
• Risk of degradation
• Combinations of High and Low for each of these leads
to 8 categories (HHH, HLH, HLL, etc.)
• Those categories which are the dominant features of
the Action Site should be included to some degree in
the Field Sites
16. Site Selection
‘Soft’ criteria - Dialogue with partners and local
experts
• Local knowledge
• Local partnerships and views of local experts
with better grounded knowledge and experience
may bring in other ground considerations
influencing choice of Field Sites
• Institutional, political, security considerations, etc.
• Developmental opportunities
18. Site Selection
Development Domains in
the ECA Flagship
• Site selection guidelines produced
• Three key variables are used (scaled as hi or lo)
• All combinations are mapped to encompass the range
of social, political, and environmental heterogeneity
• Spatial analysis is subjected to stakeholder
consultation for final selection
Poverty Level
Risk of Degradation
(HANNP)
Market Access
20. West Africa Flagship
• Southern part of four selected countries: Nigeria,
Cameroun, Ghana, Cote d’Ivoire
• About 28% of population live with less than US$1.25/day
• Average market access is about 3 hours
• 58% of land area is estimated to be degraded
22. West Africa Flagship
• West Africa Flagship: 4 Action Sites
• Two operational: Nigeria and Cameroon
23. Cameroon Sites Selection Criteria
i) population density
ii) potential for poverty reduction
iii) potential to reduce land degradation and social
conflicts
iv) action to protect agro-biodiversity hotspots
v) enhanced social learning for multi-cultural
communities
vi) potential for cross-border trade and market chains
vii) national interests in collaboration
Combination of hard and soft criteria
24. Data Sources for Site Selection
• Population: Global Rural-Urban Mapping Project*,
Version 1 data:
• Poverty Reduction: HarvestChoice Poverty maps,
commissioned by the CGIAR SRF Team
• Land degradation: Human Appropriation of Net
Primary Productivity (HANPP)*
• Trade and market chains: Market Access and
Influence data*
• ETC., ETC.
31. Similarity Mapping
• Map variables of relevance to a
given issue
• Environmental suitability for particular
farming systems
• Access to specialised markets
• Chose area of interest
• Source area (AA, AS, FS)
• Target area
• Run similarity model
• Chose variables
• Chose statistical method
• Evaluate outputs
• Select similarity threshold
• Quantify relevant variables in target
area – rural population, poor farmers,
land degradation
32. Collaboration with CRPs
Systems CRPs
• Regular consultations among Directors
• Joint events: Enhancing coherence in systems research
– S-CRPs workshop on “Capacity to Innovate” as an IDO, Amsterdam,
March, 2014
– IFSA/CGIAR Symposium on Global Partnerships in systems research and
innovation, Berlin, April, 2014.
– Integrated Systems Conference for Sustainable Intensification: 3-6 March,
2015, IITA, Ibadan, Nigeria
Other CRPs
Co-location, Coordination, Collaboration
– I. RTB, A4NH, L&F
– II Maize, FTA, PIM, CCAFS
– Humidtropics Focal Point for Cross-CRP interaction
33. Humidtropics: Diverse agricultural systems
Food security and cash crops
RTB
Banana Beans Cassava Maize Coffee
Natural resource status
Rwanda East-DR Congo
Livestock
Potato
34. Humidtropics and RTB team up
- Co-Location
- Potato lines (RTB-CIP) that produce tubers at
warmer temperatures are being tested in
Western Kenya action area as part of the
systems intensification research of Humidtropics
Humidtropics
integration of varieties
into system: best fit,
trade-offs and
interactions
RTB-CIP
screening potato
varieties, for
possible fit into the
humid tropics.
Zone of
convergence Humidtropics R4D
Platform
35. Conclusion
Humidtropics is making progress ….
…. within reasonable limits!!
• Increased coherence and trust building:
• Combining crosscutting with regional Flagships
• Site selection links to extrapolation domains
• Make partnerships count for good
– Regional organizations
– R4D Platforms
• More efforts in CRPs collaboration
– Co-location, Coordination, Collaboration
• Overall, positive feel! Great Expectations!!
Focus on DELIVERY!
Notas del editor
These ‘Hard’ i.e. data-driven selection criteria were as described in the site selection guidelines
In addition to the ‘hard’ spatial criteria described on the previous slide there are ‘soft’ criteria to be accounted for in site selection – the spatial analysis should inform this discussion.
Maps of the four Flagship project Areas showing the different Action Sites in each. These are overlain on the global Ruminant production systems maps (Robinson et al 2011) which show livestock only areas (LG*), mixed rainfed areas (MR*), and mixed irrigated areas (MI*) …. For each of which is distinguished hyper-arid (**Y), arid and semi-arid (**A), humid and sub-humid (**H;) and temperate and tropical highlands (**T). (other is largely forested areas). The Humidtropics should fall within **H and **T.
This is based on the descriptions provided in the site selection paper (Duncan et al .. ) LLL means low poverty; low market access and low risk of degradation, for example. The idea proposed is that different combinations of these define ‘development domains’ and that the selected field sites should embrace the diversity of the development domains in a given Action Site (and ultimately, Action Area).
This is an example for W. Kenya where there were two dominant development domains identified so two (initial) field sites were selected from each (though Kisumu is more variable, apparently).
An important part of the Global synthesis work (FP cluster 1.1) is to quantify the Humidtropics areas and to that end we are geo-referencing all of our Action Areas and Action Sites. This is essential if we are to know who and how many are the direct beneficiaries of the research in the Action Sites and, as research outputs are scaled through various platforms and partnerships, who are the potential beneficiaries in the broader Humidtropics agro-ecological zone.
Important layers for quantification include rural population, arable land, forest resources, livestock numbers, and such-like
(Field Sites will also be included in the future but we don[t have very detailed and complete descriptions of these at the moment)
In order to estimate the number of poor farmers and farming families that the Humidtropics programme can impact directly (in Action Sites) and indirectly, through scaling out, we start from the human population – for which very detailed maps now exist (AfriPop, for example, in this example for Western Kenya.
Work is on-going under Global Synthesis (FP Cluster 1.1) to move from estimates of total population, to rural population (masking out urban areas); to Agricultural population (by estimating the % of the rural population engaged in Agriculture); and thence to poor farmers of various types (e.g. poor mixed, crop-livestock farmers) based on combinations of farming systems estimates and of poverty.
This is how we estimate the potential reach of the Humidtropics programme.
Linked to the above we are developing a ‘Similarity Mapping’ tool to estimate the extent of areas similar to those within our Action Areas, Action Sites and field sites.
This slide shows the delineation of an area of interest (the red hashed area) and a ‘training site’ the W. Kenya Action Site in this example. It also shows three examples of the type of data layer that can be used to define similarity – in this case demography (human population density), infrastructure (market access), and agro-ecology (length of growing period).
The next slide goes through the process.
The process for similarity mapping is outlined on the right hand side and the map shows a similarity map for Eastern Africa – based on the W. Kenya Action Site as the ‘training site’ and the data layers shown in the previous slide: (1) demography (human population density), (2) infrastructure (market access), and (3) agro-ecology (length of growing period).
Four different statistical methods are available in the programme - this example uses Euclidean similarity, which transforms the covariates prior to analysis using a Principal Components Analysis (PCA).
Models can be run globally (taking account of all Humidtropics Action Sites) or regionally (AS) or for smaller areas (FS) – for which more specific data layers may be available.
It would be appropriate to produce different models for different types of intervention – e.g. one could include variables that determine suitability for a particular crop.
The idea is that this will show the extent of areas that are ‘similar’ to our area of research (AA, AS, FS) - by setting a threshold we can then quantify that area (how many poor farmers are there, for example) and that is the potential reach of the research in question. The actual reach then depends on scaling, which is determined by partnerships, platforms and uptake rates.
This tool is a nice example of something that can promote cross-SRT action: this SRT1 (targetting) output feeds directly into SRT3 (scaling) – via the technical proposal emerging from SRT2 (intervention).