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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
  6. 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
  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
  18. Ex. Farm configuration
  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.
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