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Integrated systems research
for farms and livelihoods
Jeroen Groot
Wageningen University and Research
Africa RISING Phase II planning meeting
5 - 8 October, 2016
Lilongwe, Malawi
Systems approach
 Larger-whole implications
 Interactions among components
 Multifunctionality of components and system
 Portfolio of methods
 Multidisciplinary
 Boundary objects
 Experiments, models
 Research products
 Design tools: SI framework, impact pathways, influence diagrams
Influence diagram (example boundary object)
BiomassBiomass Ground
cover
Ground
cover
ErosionErosion TopographyTopographySoil
properties
Soil
properties
Water
supply
Water
supply
Herd mgtHerd mgt
Land
allocation
Land
allocation
AdoptionAdoption
Labor
availability
Labor
availability
Fodder
species
Fodder
species
Inputs
(e.g. fertilizer)
Inputs
(e.g. fertilizer)
Herd sizeHerd size
Portfolio of methods(examples)
 On-station and on-farm experiments
 Participatory
 Focus Group Discussions; interviews; livelihood analysis
 Participatory mapping; resource flow maps; transect walks
 Problem trees; Appreciative Inquiry; Most significant change
 Co-innovation, project management
 Farm analysis and redesign
 Farm surveys, typologies
 Crop, animal and environmental simulation
 Farm and landscape modeling
 Scaling approaches
Systems and integration
 System:
 Limited part of reality
 Interacting components
 Delineation
 Integration:
 What does the research result mean at the target system level?
 What is the pertinent management unit?  farm / household
Boundary
Components
(or sub-systems)
Output(s)Input(s)
Interrelationships
Fields, animals
Farms
Landscape
Household
Farmer(s)
Institutions
Markets
Businesses
Platforms
Community
Groups
Research
emphasis
Phase I Phase II
AGRO-ECOLOGICAL LANDSCAPE
SOCIO-INSTITUTIONAL LANDSCAPE
Analysis DesignStructure
Function
Purpose
Purpose
Function
Structure
New facts, new
realities
Conclusions Decisions
Knowledge
Questions
Problems
Reality
(agroecosystems)
After Goewie (1993) and
Tittonell et al (2015)
Specifications
Means- vs. goal-oriented
 Means-oriented:
 Evaluation of quality of measures and techniques at field and farm level
 Often labeled “sustainable” a-priori
 Goal-oriented:
 Comparison of the productive, environmental and social performance
 Using a set of explicit goals, made operational through indicators (MF)
 Different spatial and temporal scales and organization levels
 Focus on the outcomes (goals), that can be reached by different
system configurations and implemented measures and techniques
Trade-offs at system level
 When improving the system for one goal, an other goal can be
compromised (ex. F1 = profit, F2 = soil quality – i.r.t. livestock)
 Evaluate trade-offs in terms of goals at the target system level
 Often there are multiple ways to reconfigure to reach goals
Best guess scenarios
F1
F2 a.
Single objective optimization Pareto-based optimization
F1 F1
F2 F2b. c.
Ex. Trade-offs between multiple goals
original farm
configuration
Ex. Goals for HHs (1): Labor/leisure
time
 Farm labor balance
 Gendered labor distribution
 Household labor allocation
Ex. Goals for HHs (2): Budget
 On and off-farm income
 Expenditures, food and other
 Available free HH budget
Beyond trade-offs: integrative
solutions Try to identify solutions to problems that overcome trade-offs and
avoid compromise
 Integrative solutions require insight into whole-system responses to
different forms of use and an overview of services provided
 Example crop residue use:
 Allocations: as mulch, feed, firewood, building material
 Goals: improve soil fertility, feed animals, cooking, heating, building
 Solutions…
Dealing with diversity
 Farms and households differ in:
 Size and structure (farm, HH)
 Development stage (HH)
 Goals and constraints (HH)
 Distributions: overview of the ranges and variation
 Typologies: grouping of diverse population into similar types
 Farms/HHs with different characteristics need different solutions
System X
System Y
Trajectories of change
 How to attain goals in a
sequence of changes?
 Different pathways
(sequences of solutions)
for different farm/HH
types
Conclusions
 Evaluate research outcomes in the context of the target system
 Focus on the goals of farms and households, how to attain these
 Explore the system-level trade-offs, look for integrative solutions
 Identify the trajectory (-ies) to follow to reach the ultimate goals
 Accommodate diversity in farm and household structure and goals
 Embrace a portfolio-approach combining multiple methods
Africa Research in Sustainable Intensification for the Next Generation
africa-rising.net
This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
Thank You
Ex. Farm configuration
Ex. Goals for farms (1): Nutrient yield
Yield is expressed as the number
of people (consumer units) that
can be sufficiently nourished for a
given nutrient
Ex. Goals for farms (2): Operating
profit
Sustainable by design (example boundary object)
Is it good for the environment?
Is it profitable?
Is the farm productive without
causing degradation?
Are farmers safe in making
and using their products?
Do farm operations contribute to
environmental quality?
Do all HH members have
access to resources?
Are people treated the same?
Do farmers and workers
get a living wage?
Do men and women paid
the same for the same job?
Integrated systems research for farms and livelihoods in Africa RISING phase II

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Integrated systems research for farms and livelihoods in Africa RISING phase II

  • 1. Integrated systems research for farms and livelihoods Jeroen Groot Wageningen University and Research Africa RISING Phase II planning meeting 5 - 8 October, 2016 Lilongwe, Malawi
  • 2. Systems approach  Larger-whole implications  Interactions among components  Multifunctionality of components and system  Portfolio of methods  Multidisciplinary  Boundary objects  Experiments, models  Research products  Design tools: SI framework, impact pathways, influence diagrams
  • 3. Influence diagram (example boundary object) BiomassBiomass Ground cover Ground cover ErosionErosion TopographyTopographySoil properties Soil properties Water supply Water supply Herd mgtHerd mgt Land allocation Land allocation AdoptionAdoption Labor availability Labor availability Fodder species Fodder species Inputs (e.g. fertilizer) Inputs (e.g. fertilizer) Herd sizeHerd size
  • 4. Portfolio of methods(examples)  On-station and on-farm experiments  Participatory  Focus Group Discussions; interviews; livelihood analysis  Participatory mapping; resource flow maps; transect walks  Problem trees; Appreciative Inquiry; Most significant change  Co-innovation, project management  Farm analysis and redesign  Farm surveys, typologies  Crop, animal and environmental simulation  Farm and landscape modeling  Scaling approaches
  • 5. Systems and integration  System:  Limited part of reality  Interacting components  Delineation  Integration:  What does the research result mean at the target system level?  What is the pertinent management unit?  farm / household Boundary Components (or sub-systems) Output(s)Input(s) Interrelationships
  • 7. Analysis DesignStructure Function Purpose Purpose Function Structure New facts, new realities Conclusions Decisions Knowledge Questions Problems Reality (agroecosystems) After Goewie (1993) and Tittonell et al (2015) Specifications
  • 8. Means- vs. goal-oriented  Means-oriented:  Evaluation of quality of measures and techniques at field and farm level  Often labeled “sustainable” a-priori  Goal-oriented:  Comparison of the productive, environmental and social performance  Using a set of explicit goals, made operational through indicators (MF)  Different spatial and temporal scales and organization levels  Focus on the outcomes (goals), that can be reached by different system configurations and implemented measures and techniques
  • 9. Trade-offs at system level  When improving the system for one goal, an other goal can be compromised (ex. F1 = profit, F2 = soil quality – i.r.t. livestock)  Evaluate trade-offs in terms of goals at the target system level  Often there are multiple ways to reconfigure to reach goals Best guess scenarios F1 F2 a. Single objective optimization Pareto-based optimization F1 F1 F2 F2b. c.
  • 10. Ex. Trade-offs between multiple goals original farm configuration
  • 11. Ex. Goals for HHs (1): Labor/leisure time  Farm labor balance  Gendered labor distribution  Household labor allocation
  • 12. Ex. Goals for HHs (2): Budget  On and off-farm income  Expenditures, food and other  Available free HH budget
  • 13. Beyond trade-offs: integrative solutions Try to identify solutions to problems that overcome trade-offs and avoid compromise  Integrative solutions require insight into whole-system responses to different forms of use and an overview of services provided  Example crop residue use:  Allocations: as mulch, feed, firewood, building material  Goals: improve soil fertility, feed animals, cooking, heating, building  Solutions…
  • 14. Dealing with diversity  Farms and households differ in:  Size and structure (farm, HH)  Development stage (HH)  Goals and constraints (HH)  Distributions: overview of the ranges and variation  Typologies: grouping of diverse population into similar types  Farms/HHs with different characteristics need different solutions System X System Y
  • 15. Trajectories of change  How to attain goals in a sequence of changes?  Different pathways (sequences of solutions) for different farm/HH types
  • 16. Conclusions  Evaluate research outcomes in the context of the target system  Focus on the goals of farms and households, how to attain these  Explore the system-level trade-offs, look for integrative solutions  Identify the trajectory (-ies) to follow to reach the ultimate goals  Accommodate diversity in farm and household structure and goals  Embrace a portfolio-approach combining multiple methods
  • 17. Africa Research in Sustainable Intensification for the Next Generation africa-rising.net This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence. Thank You
  • 19. Ex. Goals for farms (1): Nutrient yield Yield is expressed as the number of people (consumer units) that can be sufficiently nourished for a given nutrient
  • 20. Ex. Goals for farms (2): Operating profit
  • 21. Sustainable by design (example boundary object) Is it good for the environment? Is it profitable? Is the farm productive without causing degradation? Are farmers safe in making and using their products? Do farm operations contribute to environmental quality? Do all HH members have access to resources? Are people treated the same? Do farmers and workers get a living wage? Do men and women paid the same for the same job?

Editor's Notes

  1. Analysis-oriented research starts from a question arising from curiosity and not necessarily linked to any application. In analysis-oriented research the aim of obtaining knowledge about the functioning of biological systems is supported by methods that study existing structures in (eco-)systems to reveal their functions and hence their purpose. This leads to increased understanding of system functioning and is translated into research outputs such as journal articles, conference presentations and other knowledge products that are valued as scientific performance. Because the research process is basically curiosity driven, initial goals may be adjusted along the way when intermediate results suggest more interesting avenues of research. Design-oriented research on the other hand, starts from a particular problem that it aims to resolve. The research process proceeds by synthesizing existing knowledge on functions that should be mobilized to achieve the purpose, and to elaborate one or more structures that will support these functions. The result is integrated knowledge and takes the form of inventions or decisions. Implementing these may trigger new questions that feed into the analysis-oriented research cycle. As in design-oriented research problem definition concerns problem-‘owners’ outside the research domain, the relevance of the research outcome depends on negotiation about the topics of research, and the research process adjusts itself to these emergent problem adjustments (e.g. Tittonell, 2013; Rossing et al., 1997). Later in this Chapter we will distinguish design-oriented research that supports decision making and design-oriented research that supports implementation.