Reflections on a “systems approach” for Drylands CRP-Brian Keating

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Reflections on a “systems approach” for Drylands CRP-Brian Keating

Reflections on a “systems approach” for Drylands CRP-Brian Keating

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  • 1. Reflections on a “systems approach” for Drylands CRP Brian Keating and ISAC colleagues
  • 2. “…in spite of fashionable lip-service to systems ideas, and in spite of frequent exhortations to use a systems approach, we are rarely told what it consists of, or exactly how we might use it. There has been a notable lack of determined persistent efforts, first to define what ‘a systems approach’ means and then to go out and use it in tackling problems, in order to experience that interaction between theory and practice which is the best recipe for intellectual progress.” Peter Checkland (1981) Systems Thinking, Systems Practice. This topic has a long and deep literature .... (often outside of agriculture)
  • 3. Models and on-farm participative research • Agriculture is part of a “human activity system” with production and management elements • Agriculture is only part of a systems approach to food and nutritional security ad poverty reduction • Our systems approach should be focused on “problem solving” at the science-practice interface • Innovation in agri-food systems needs more than research. Four observations Self-evident
  • 4. Systems focus Farm System O U T P U T S CropsSoil Animals I N P U T S CLIMATE PRODUCTION SYSTEM MARKETS MANAGEMENT SYSTEM Monitoring Deliberative planning & control Action Internal Environment Needs, values, goals, etc Knowledge, cognitive limits, etc. Resources SURFACE AND GROUND WATER Adapted from Sorensen & Kristensen, 1992 Policy environment
  • 5. Hierarchy of scales and multiple drivers of change Herrero et al, Science (2010)
  • 6. Models and on-farm participative research • Agriculture is part of a “human activity system” with production and management elements • Agriculture is only part of a systems approach to food and nutritional security and poverty reduction • Our systems approach should be focused on “problem solving” at the science-practice interface • Innovation in agri-food systems needs more than research. Four observations
  • 7. AGRICULTURE - Sustainable Productivity Improvement Innovation research & extension Infrastructure Finance & Responsible Investment Human Resources Markets & Trade Resource Tenure Enabling Policies, Regulations & Institutions Supporting Private Sector and Civil Society Engagement and Investment International Leadership & Coordination Global Public GoodsDomestic Policy Reform Understanding Risks and Opportunities – Foresight and Scenario Analysis Transforming Small Scale Agriculture / Agribusiness Food & Nutrition Security (availability, access, utilization, stability) Inclusive Growth & Jobs for rural women, men and youth Growth, Jobs and Resilience Agriculture and Food Sector Growth and Efficiency Food Availability & Utilisation Food Affordability Food Availability Nutrition Interventions Food Utilisation Human Productivity Security and stability Food Affordability Social Protection Food Affordability
  • 8. Models and on-farm participative research • Agriculture is part of a “human activity system” with production and management elements and a wider context • Agriculture is only part of a systems approach to food and nutritional security and poverty reduction • Our systems approach should be focused on “problem solving” at the science-practice interface (Impact focused) • Innovation in agri-food systems needs more than research. Four opening observations
  • 9. Systems thinking - systems practice – Creation of knowledge relevant to system design and management • --- but there has always been the problem of “adoption”. – Use of scientific knowledge in intervention in system owners’ design and management • This is the essence of “systems PRACTICE”. • Embedded in a strong “problem solving” paradigm Peter Checkland (1981) .
  • 10. increasing ‘integration’ Jackson (2000) Systems Approaches to Management The Systems Movement Systems thinking in the disciplines Study of systems in their own right Systems thinking for “problem solving” (Multidisciplinary) (in practice) organisational integration interactive science - practice integration Systems thinking is integrative (cf. analytical thinking)
  • 11. Models and on-farm participative research • Agriculture is part of a “human activity system” with production and management elements • Agriculture is only part of a systems approach to food and nutritional security and poverty reduction • Our systems approach should be focused on “problem solving” at the science-practice interface • Innovation in agri-food systems needs more than just research. Four opening observations
  • 12. What is an Innovation System? = The conditions that are needed to enable innovation. Definition: A network of organizations, enterprises, and individuals focused on bringing new products, new processes, and new forms of organization into economic and social use, together with the practices or institutions and policies that affect their behavior and performance.
  • 13. A dynamic view of “Innovation systems” Adapted from A. Hall (2012) Partnerships in agricultural innovation - Who puts them together and are they enough? In OECD Conference on Improving Agricultural Knowledge and Innovation systems Technology triggers Market triggers Social triggers Environmental triggers Research Organisations Enterprises Support Organisations Markets and Consumers “Go-between” Organisations Protocols Enabling Policy Environment Innovations of economic, environmen tal or social significance New capacity to innovate
  • 14. Long history of systems research methods
  • 15. A Research Typology (Oquist, 1978) Acta Sociologica l21, 143-163. • Descriptive research – e.g. broaden the knowledge of the production and management system, characterise system resources • Predictive (nomothetic) research – e.g., Test understanding by developing predictive and generalisable models of a system • Prescriptive (policy / operations) research – e.g., Use data or models to identify optimal strategies for desired outcome • Participatory action research – e.g., learn via inquiry within the life experience of participants Each type assumes and builds on the prior type How the world works! How to change the world ! In Drylands we are going to need all four types of research – in the journey from Discovery through Diagnosis to Pilot and Scale Out. This journey will not necessarily be linear
  • 16. Methodological innovation – FSR foundation From Dillon and Anderson (1984), after Collinson (1982)
  • 17. Linking Operations Research to FSR In the late 80’s and early 90’s, McCown and colleagues combined the “simulation modelling of agricultural systems with the client- orientation of FSR”
  • 18. Action Learning IntentLearning Action Knowledge When the main intent is deliberative “changing of a reality” (action), the learning is action learning. Plan ActReflect Observe Action Learning Cycle
  • 19. An elaborated view of Farming Systems Research (FSR) A Framework for intervention that substitutes a production systems model for the actual system in facilitated action learning (after McCown, 2008)
  • 20. Models and on-farm participative research • On-farm ==> Relevance • Participative ==> Ownership and relevance • Systems Analysis (incl. Models) ==> Explanation and generality • Generality – Extrapolation in time (over variable seasons) – Extrapolation in space (other soils, climates, livelihood circumstances) Models and on-farm participative research
  • 21. A crowded history of research for development approaches 1980’s 1990’s 2000’s 1960’s 1970’s On Station Research Extension based technology transfer NIE FSR OFR RRA PRA PAR PTD FTR FFS PPB AKIS PI&D IRD BB’s MBTs SRLsFARMSCAPE INRM IGNRM IAR4D IS IP ERI CASE PLAR RDs CCNR AR ARD FS
  • 22. What trends can we observe ? • Moving from descriptive to predictive/diagnostic approaches including the use of systems analysis and modelling tools • Increasing participation from a broader range of actors • Emergence of a value chain focus to complement an on-farm focus • Increasing recognition of the significance of enabling institutions and governance • Contested paradigms; hard systems vs soft systems; positivism vs constructivism; researcher knowledge / farmer knowledge • Greater recognition of social equity and gender issues
  • 23. Some propositions for Drylands to consider in shaping a “systems approach”
  • 24. 1. A systems approach shaped by problem solving “in practice” • A “systems approach” that is best defined in terms of the outcomes we seek. • That is, it is a “whatever it takes” approach to improving food security, reducing poverty and enhancing resilience in the world’s drylands. • Our approach does not prejudge the need for a particular technology, a particular commodity-related intervention or a particularly disciplinary consideration. • Approach draws upon diverse sources of scientific and local knowledge to improve the food security and livelihoods of the dryland peoples. Systems research at the scale of impact
  • 25. 2. Agricultural Livelihood System • The primary focus for our systems approach (level n) will be the “agricultural livelihood system”. • That is the set of farm, farming and human activity systems that determine the livelihood opportunities for agricultural households, enterprises or communities. • Implicit in this focus is consideration of the food and nutritional security, health and well being, employment and income generation of dryland peoples.
  • 26. 3. Systems Context • Our systems context (n+1) is the wider environmental and institutional setting • Including government policy, business activity, input and output markets, value chains, knowledge systems, social and cultural norms, gender bias etc. • We consider this wider context to be the “innovation system” and we recognise scientific research is only one part of the innovation process, albeit a potentially catalytic or transformational part
  • 27. 4. Science based diagnosis and intervention design • Our explanatory insight (n-1) comes from our descriptive and predictive capacity around the key components and the many interactions that shape agricultural livelihoods. • Components include but are not limited to crop, livestock and tree options and technologies within farming systems, agricultural inputs and output availability and prices, natural resources used in farming in particular soil fertility and water management, tillage systems, energy systems, labour and capital, nutrition and health consequences of diets, education systems and off-farm income generation ….. • We can’t discard our scientific method/value-add in our efforts to get more participative and relevant
  • 28. 5. An evolving research methodology • Diagnosis of constraints and opportunities at the agricultural livelihood level will be our primary entry point for “discovery” science in dryland systems. • These will be holistically analysed for development constraints in order to identify the system bottlenecks and effective remedies. • For the latter we will draw upon indigenous knowledge as well as technological discoveries and developments from other CRPs and the wider agricultural R&D system.
  • 29. 6. “Fit for purpose” participative approaches • Efforts to simulate desired change supported by appropriate engagement/innovation brokering at appropriate scales with appropriate actors (eg. farmers, community groups, value chain and market participants, private sector investors, government policy etc.) - Not a one size fits all … • Research contribution will be always informed by a solid scientific base, including efforts to interpret system functionality and generalize interventions to other times and places • National and regional institutions and development partners will be drawn in at the outset and the “scale out” objective adaptively planned as a “research in development” activity
  • 30. 7. Cross-cutting research methods and capabilities are needed • Spatial information systems • Data acquisition and management (includes household survey methods and human research ethics) • Farming systems modelling (development, validation, deployment in diagnosis and participative design ) • Bio-economic modeling / agent based socio-ecological modeling (Households/communities) • Value chain and business systems analysis • Building gender considerations into research for/in development • Global and regional change scenarios (links to CCAFS ?) • Capacity building in participative process/ knowledge brokering – Innovation Platforms, Hubs, Facilities, PPPs etc Get serious with SRT 1 and 4
  • 31. Thankyou
  • 32. Modelling and systems analysis tools
  • 33. Integrated Modelling Methodology Systems characterisation soil ANIMAL crops TPS herd livestock Biological simulation system Databases limits constraints resources mgmt practices Multiple criteria LP models DYNAFEED Sustainable resource management strategies Socio-economic I/O Herrero et al. 1996, 1997
  • 34. NUANCES-FARMSIM Van Wijk et al., 2009, Ag. Systems
  • 35. Integrated analysis tool (IAT) Crop, forage yield Feasible/most profitable strategy Livestock Model Economic Model Inputs Climate Soil Management Prices Costs Labour Machinery Outputs Crops Forage Cattle Labour Income APSIM Crop-Forage Model Herd structure & Management Livestock yield Forage yield Household Modelling Workshop Dockside 19th-20th November 2013 Slide 13
  • 36. Modelling alternative household resource allocations Baseline household survey N>500 APSFarm-LivSimRelevant interventions Better informed discussions, investments & decisions Profits Risks SustainabilityFood security SIMLESA program •Stubble management •N fertilisation Courtesy of D. Rodriguez
  • 37. • Longitudinal data • Participatory methods • Key informants • Systems’ classification • Selection of farms • Household modeling • Sensitivity analyses • Participatory appraisals • Recommendation domains • Toolboxes of interventions • Farmers / NARS • Stakeholder workshops • Participatory appraisals Participatory modelling Ecoregion Farms CBA Case studies Range of interventions to test for each system (filtering) Scenario formulation (Farm and policy level) Selection of a fewer range of options Site targeting Dissemination & implementation Policy-making Testing options in the field (Herrero, 1999)
  • 38. Baseline data Data collection protocol : – Climate – Family structure – Land management – Livestock management – Labour allocation – Family’s dietary pattern – Farm’s sales and expenses
  • 39. Systems modelling approaches Class of model An example of model application Model Examples Gene to Phenotype - more efficient crop improvement programs QTL based models (e.g.Yin et al., 2004) Crop-Soil - identification of optimal agronomic practices and/or varietal adaptation Simulation Models (CERES, GRO models) Farming System - farming systems design within soil, climate and management constraints Systems Simulation models (e.g., APSIM, DSSAT, CROPSYS) Farm Household / Enterprise - optimal resource allocation (inputs, labour, enterprise mix) to raise farm productivity Bio-economic optimisation models (e.g. MIDAS, MUDAS); NUANCES Regional Dynamics - cross-sectoral responses to change drivers and intervention strategies CGE Models, Regional Stocks and Flows, Agent- based models National Economy - impacts of interventions in the agricultural sector on economic growth, employment, balance of trade etc National CGE models (e.g. MONASH) or stocks and flows models (e.g. ASFF) Earth Systems/ Global Economy and Trade - climate change impacts on global food supply and agricultural trade Global Trade models (e.g. GTAP, IMPACT, IFPRI models)
  • 40. Global Scenarios Regional Scenarios Farmer/village perspectives Action research Participatory scenario building Global visioning activities Global impacts modelling Regional impacts modelling Household & community impacts modelling Linking research at different levels Thornton et al 2012
  • 41. A more integrative approach in the CGIAR ? From Stripe Review – NRM Research in CGIAR Natural Resource Management (incl. agronomy) Genetic and other technologies Enabling Institutions Development Impact