A FRAMEWORK FOR EXPLORING RURAL  FUTURES THROUGH COLLECTIVE LEARNINGM.E. Wedderburn, T.T. Kingi, A.D. Mackay, M.Brown, O. ...
COUPLING OF HUMAN CAPABILITY AND NATURAL CAPITAL(SOCIAL-ECOLOGICAL SYSTEM) IS NEW ZEALAND’S COMPETITIVE                   ...
GLOBAL INTERCONNECTION               World Production         NZ% of World Production            World Trade        NZ% of...
LAND USE CHANGE AND FLEXIBILITY    A KEY CHARACTERISTIC FOR            SUCCESSDairy     Number     Milking            Effe...
RURAL FUTURES OBJECTIVES• Build capacity to explore, test and develop strategies, policies and  decisions to address futur...
Framework for exploring Futures                    Drivers obj 2                                                   Stakeho...
Testing the FrameworkManawatu Study Group
Framework for exploring Futures     Drivers obj 2                                    Stakeholder workshops 4              ...
DRIVERS:INTERNAL MEGA THEMES•Production efficiency, optimising productivity  • Efficiency - energy use, inputs e.g. fertil...
DRIVERSExternal Mega Themes•Biosecurity•Market AccessOthers•Farmer capacity development•Industry development and evolution...
OWNERSHIP SCALE                                           SUCCESSION                                           LABOUR SUPP...
R&D funding                                      S                                       Resulting causal loop diagram    ...
INSIGHTS•Stimulated discussion about the interconnectednessof the system•Revealed the different world views of stakeholder...
Framework for exploring Futures     Drivers obj 2                                    Stakeholder workshops 4              ...
DRIVERS THAT GUIDED DEVELOPMENT      OF 2020 FARM SYSTEMS•productivity and profitability,•labour and staff skills,•regulat...
Current and future 2020 () attributes of dairy and sheep and beefbase model farms in the Horizons region Attribute        ...
Framework for exploring Futures                 Drivers obj 2                                                Stakeholder w...
Micro                                        Macro               Farmers   Rural community     Supply chain   Society- Far...
OUTCOMES•Many of the farm parameters, e.g., stocking rate,MS per cow and per hectare, were not significantlypushed beyond ...
OK AS FAR AS IT GOES BUT .........The next generation of tools will require the linking ofhuman behaviour with economic an...
Variables influencing farmer ability to make changes                                        1                             ...
Transit/                                                       Birth and    F/Time     Busin/s              T/over ofGen C...
AGENT BASED MODEL FARM DESCRIPTIONS
AGENT BASED MODEL FARMER TYPES
INSIGHTS ON FRAMEWORK•Need a diversity of world views•Participants expanding their perceptions and theknowledge they will ...
REFLECTIONS BY THE RESEARCH TEAM•Ability to apply models to systems•Building interdisciplinarity•Developing the ability to...
CHARACTERISTICS OF THE TEAM            MEMBERS•Abundance mentality (no hoarding)•Connectors•Good discipline science•Confid...
Thanks to the funderFRST
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A framework for exploring rural futures through collective learning. M Wedderburn

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A presentation made at the WCCA 2011 event in Brisbane, Australia.

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A framework for exploring rural futures through collective learning. M Wedderburn

  1. 1. A FRAMEWORK FOR EXPLORING RURAL FUTURES THROUGH COLLECTIVE LEARNINGM.E. Wedderburn, T.T. Kingi, A.D. Mackay, M.Brown, O. Montes de Oca, K. Maani,R. Burton, H. Campbell, S. Peoples, J Manhire, R.Dynes, B. Kaye-BlakeAgResearchUniversity of OtagoUniversity of QueenslandLincoln UniversityNZER
  2. 2. COUPLING OF HUMAN CAPABILITY AND NATURAL CAPITAL(SOCIAL-ECOLOGICAL SYSTEM) IS NEW ZEALAND’S COMPETITIVE ADVANTAGE
  3. 3. GLOBAL INTERCONNECTION World Production NZ% of World Production World Trade NZ% of World Trade Million tonne Million tonneBeef 61 1% 6 7%Game Meat 2 3% 6 42%Sheep Meat 9 6% 1 38%Wool 2 10% 0.9 17%Whole Milk 550 3% 7 1%Casein 0.2 21%Butter 7 6% 0.8 48%Cheese 14 3% 1.2 22%Milk Powder 7 5% 2.5 35% Source: FAOSTAT & USDA Production figures at http://faostat.fao.org/site/569/DesktopDefault.aspx?PageID=569 Export figures are at http://faostat.fao.org/site/535/DesktopDefault.aspx?PageID=535
  4. 4. LAND USE CHANGE AND FLEXIBILITY A KEY CHARACTERISTIC FOR SUCCESSDairy Number Milking Effective Cows/ Total Area of of Farms Cows/Farm Area (ha) Ha Pasture in Dairying1990 13,357 160 67 2.4 894,9192007 11,630 337 121 2.81 1,407,230Sheep & Number Total Stock Effective Stock Total Area ofBeef of Farms Units per Area (ha) Units/ Pasture in Sheep and Farm Ha Beef farming1990 21,300 3,155 516 6.5 10,990,8002007 13,600 4,268 645 6.2 8,772,000 Source: Meat and Wool NZ, Livestock Improvement
  5. 5. RURAL FUTURES OBJECTIVES• Build capacity to explore, test and develop strategies, policies and decisions to address future issues• The future of systems dynamics research in agriculture lies in the integration of biophysical and social elements• To facilitate the use of quantitative and qualitative information produced in the programme in the processes involving stakeholder interaction• To explore participatory modelling and processes during this interaction (i.e. systems dynamics, bayesian networks, influence diagrams) to stimulate collective learning
  6. 6. Framework for exploring Futures Drivers obj 2 Stakeholder workshops 4Agent Based model 3System dynamics 4 Reflect 6 Issues 1 Identification Test Strategies 5 Collective SH workshops 4 Policies learning Future Scenarios 2 Decisions 4 3 Evaluation of system Farm system Farmer behaviour 1 performance representation Biological Libraries 2 and behaviour System workshops 4 Models Agent Based model 3 Stakeholder experience 4
  7. 7. Testing the FrameworkManawatu Study Group
  8. 8. Framework for exploring Futures Drivers obj 2 Stakeholder workshops 4 Issues 1 Identification Collective learning
  9. 9. DRIVERS:INTERNAL MEGA THEMES•Production efficiency, optimising productivity • Efficiency - energy use, inputs e.g. fertiliser, chemicals, precision agriculture, organic agriculture • New technologies impact – infomatics, nanotechnologies, genetic engineering•Product quality, market signals • Production to specification, new markets/products • Product – quality, attributes, safety, health • From Quality assurance to Environmental Management Systems•Natural resources quality, availability, production impact • Decrease negative impacts, enhance resource use efficiency, climate change risks • Reporting production impacts – traceability
  10. 10. DRIVERSExternal Mega Themes•Biosecurity•Market AccessOthers•Farmer capacity development•Industry development and evolution – power andrelationships: farmers/processors/retailers/consumer
  11. 11. OWNERSHIP SCALE SUCCESSION LABOUR SUPPLY•Farm amalgamation •Aging farmers •Skilled labour/expertise•Offshore investment •Farm succession planning •Skilled labour & management•Maori ownership •[ wish to treat children equally either imposing •Staff•Ownership high debt on those farming or fragmenting •Labour•Form of ownership of farming business family farms] •Lack of incentive for people to get into the industryANIMAL HEALTH BIOSECURITY •Biosecurity issuesWELFARE •Biosecurity incursions such as current clover SKILLS &•Changing animal welfare expectations from root weevilcommunity or market•Animal health •Disease outbreak (issues) animal EDUCATION •Education x 2•Animal welfare •Skills & education •Education systemREGULATION URBAN INFLUENCE •People skills – relevance, availability•Farm regulatory intervention •Urban influence •Increasing difficulty of suitable training for „farm•“One Plan” •Urban housing cadets‟ and their ilk•Regulatory hindrances •“reverse sensitivity” i.e. lifestyle blocks with•Understanding of decision makers different expectations of rural environment•Resource consents, consented activities•Landscape protection, expectations esp in iconicareas COST OF CAPITAL•N-loss •Availability of finance•Limits on physical production due to emissions to •Lack of capital •Interest chargeswater & air• Lack of certainty around private property rights CLIMATE CHANGE •Interest rates x 2•Environmental constraints eg nitrogen loss •Climate change & international rules •Do gooders (environmentalists)•Statute •Climate changes (weather)•Govt legislation •Climate change•Reduced or restricted fertiliser usage and fall off in •Climatic conditionsproduction •Weather•RMA•Stable planning environment - political •Changing climate LAND USE BASE •Land soil type •Land location •Soils – sustainability •Geography •Hill country erosion What are the drivers that influence future farm systems?
  12. 12. R&D funding S Resulting causal loop diagram S Rural/Urban Climate Change Efficiency and O community awareness Production S S Environment water quality and quantity S Environmental S policy Regulation Management Labour S On farm S S response Attitude Farmer Profitability Values successionCapital cost of S landLand Use Input costs Economic Farm structureoutcomes Off farm income signals S S S X rate S Alternative Industry O industry organisation Trade Family and S S S community Consumer trends Local community cultural obligations
  13. 13. INSIGHTS•Stimulated discussion about the interconnectednessof the system•Revealed the different world views of stakeholders•Not all stakeholders found the building of aconceptual map intuitive•Guided the prioritisation of drivers to formscenarios
  14. 14. Framework for exploring Futures Drivers obj 2 Stakeholder workshops 4 Issues 1 Identification Collective SH workshops 4 learning Future Scenarios 2
  15. 15. DRIVERS THAT GUIDED DEVELOPMENT OF 2020 FARM SYSTEMS•productivity and profitability,•labour and staff skills,•regulation, environmental constraints/limits andcontinued well being (survivability).
  16. 16. Current and future 2020 () attributes of dairy and sheep and beefbase model farms in the Horizons region Attribute Dairy Sheep and Beef Ownership Owner operated Owner operated Effective area 250ha 800ha Fertiliser N kg/ha 150 (200) 25 (75) Imported feed KgDM/cow 450 (2000) Stocking Rate 2.8 cows/ha (3.16) 10.3 (11.4) SU/ha Productivity KgMS/cow 950 (1230) Lambing 125% (138%) Beef yearling 320kg (350) Lacked Stretch
  17. 17. Framework for exploring Futures Drivers obj 2 Stakeholder workshops 4 Issues 1 Identification Collective SH workshops 4 learning Future Scenarios 2 4 3 Evaluation of system Farm system Farmer behaviour 1 performance representation Biological Libraries 2 and behaviour System workshops 4 Models Agent Based model 3 Stakeholder experience 4
  18. 18. Micro Macro Farmers Rural community Supply chain Society- Farmax and Farm Catchment- Region National International Overseer Weekly Season Multi-year intergenerational
  19. 19. OUTCOMES•Many of the farm parameters, e.g., stocking rate,MS per cow and per hectare, were not significantlypushed beyond the current top performing farms inthe region.•Agreement that in 10 years’ time the “average”farmer would continue down a business-as usual-pathway, shifting to a position that reflected thecurrent top 10% of the industry.
  20. 20. OK AS FAR AS IT GOES BUT .........The next generation of tools will require the linking ofhuman behaviour with economic and environmentalobjectivesand the building of stakeholder understanding of theemergent properties, behaviours and unintendedconsequences of farm systems experiencing multipledrivers required in Steps 4 and 5 of the framework
  21. 21. Variables influencing farmer ability to make changes 1 1100% = Maximum influence 13 100 2 1=farm size 90 80 2=land class 70 3=debt levels 60 12 3 4=labour avail 50 40 5=gender 30 6=knowledge/exp 20 11 4 7=farm goals 10 0 8=sense of place 9=networks 10=biophysical/cli 10 5 mate 11=local economy 12=international 9 6 Series1 13=lifestage Farmer 1 Series2 Farmer 2 Series3 8 7 Farmer 3
  22. 22. Transit/ Birth and F/Time Busin/s T/over ofGen C n of socialis/n on farm expans farm respons Transit/n Transit/ Birth and F/Time Busin/s T/over of Busin/sGen B of Consol/n n of Retire/t socialis/n on farm expans farm expans respons respons Transit/n T/over of Busin/sGen A Consol/n of Retire/t farm expans respons MODERATE LIMITED HIGH LIMITED MODERATE LIMITED HIGH LIMITED MODERATEChange CHANGE CHANGE CHANGE CHANGE CHANGE CHANGE CHANGE CHANGE CHANGE Farmer life cycle: traditional succession and impacts on change
  23. 23. AGENT BASED MODEL FARM DESCRIPTIONS
  24. 24. AGENT BASED MODEL FARMER TYPES
  25. 25. INSIGHTS ON FRAMEWORK•Need a diversity of world views•Participants expanding their perceptions and theknowledge they will need to take into considerationwhen strategic planning.•Allows the exploration of multiple pressuressimultaneously• It is generic but is anchored in context and place.
  26. 26. REFLECTIONS BY THE RESEARCH TEAM•Ability to apply models to systems•Building interdisciplinarity•Developing the ability to have conversations acrosssocial and biophysical•Joined up view•Tackling complexity and uncertainty
  27. 27. CHARACTERISTICS OF THE TEAM MEMBERS•Abundance mentality (no hoarding)•Connectors•Good discipline science•Confident enough to simplify and bring into acontext•Translator•Leadership•Shared goal
  28. 28. Thanks to the funderFRST
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