A framework for exploring rural futures through collective learning. M Wedderburn
Download as PPTX, PDF0 likes327 views
This document presents a framework for exploring rural futures through collective learning. It identifies key drivers of change for rural systems, including production efficiency, product quality, natural resource management, biosecurity, markets, climate change, and urban influence. The objectives are to build capacity for exploring strategies and policies, facilitate stakeholder interaction, and use participatory modeling to stimulate collective learning about future scenarios. A case study applying this framework with a study group in Manawatu, New Zealand is also discussed.
![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
industry
ANIMAL HEALTH BIOSECURITY
•Biosecurity issues
WELFARE •Biosecurity incursions such as current clover SKILLS &
•Changing animal welfare expectations from root weevil
community or market
•Animal health
•Disease outbreak (issues) animal EDUCATION
•Education x 2
•Animal welfare •Skills & education
•Education system
REGULATION 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 iconic
areas
COST OF CAPITAL
•N-loss •Availability of finance
•Limits on physical production due to emissions to •Lack of capital
•Interest charges
water & 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 conditions
production
•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?](https://image.slidesharecdn.com/1030mwedderburn-111027221504-phpapp02/85/A-framework-for-exploring-rural-futures-through-collective-learning-M-Wedderburn-11-320.jpg)
A framework for exploring rural futures through collective learning. M Wedderburn
- 1. A FRAMEWORK FOR EXPLORING RURAL FUTURES THROUGH COLLECTIVE LEARNING M.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-Blake AgResearch University of Otago University of Queensland Lincoln University NZER
- 2. COUPLING OF HUMAN CAPABILITY AND NATURAL CAPITAL (SOCIAL-ECOLOGICAL SYSTEM) IS NEW ZEALAND’S COMPETITIVE ADVANTAGE
- 3. GLOBAL INTERCONNECTION World Production NZ% of World Production World Trade NZ% of World Trade Million tonne Million tonne Beef 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. LAND USE CHANGE AND FLEXIBILITY A KEY CHARACTERISTIC FOR SUCCESS Dairy Number Milking Effective Cows/ Total Area of of Farms Cows/Farm Area (ha) Ha Pasture in Dairying 1990 13,357 160 67 2.4 894,919 2007 11,630 337 121 2.81 1,407,230 Sheep & Number Total Stock Effective Stock Total Area of Beef of Farms Units per Area (ha) Units/ Pasture in Sheep and Farm Ha Beef farming 1990 21,300 3,155 516 6.5 10,990,800 2007 13,600 4,268 645 6.2 8,772,000 Source: Meat and Wool NZ, Livestock Improvement
- 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. Framework for exploring Futures Drivers obj 2 Stakeholder workshops 4 Agent Based model 3 System 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. Testing the Framework Manawatu Study Group
- 8. Framework for exploring Futures Drivers obj 2 Stakeholder workshops 4 Issues 1 Identification Collective learning
- 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. DRIVERS External Mega Themes •Biosecurity •Market Access Others •Farmer capacity development •Industry development and evolution – power and relationships: farmers/processors/retailers/consumer
- 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 industry ANIMAL HEALTH BIOSECURITY •Biosecurity issues WELFARE •Biosecurity incursions such as current clover SKILLS & •Changing animal welfare expectations from root weevil community or market •Animal health •Disease outbreak (issues) animal EDUCATION •Education x 2 •Animal welfare •Skills & education •Education system REGULATION 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 iconic areas COST OF CAPITAL •N-loss •Availability of finance •Limits on physical production due to emissions to •Lack of capital •Interest charges water & 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 conditions production •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. 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 succession Capital cost of S land Land Use Input costs Economic Farm structure outcomes 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. INSIGHTS •Stimulated discussion about the interconnectedness of the system •Revealed the different world views of stakeholders •Not all stakeholders found the building of a conceptual map intuitive •Guided the prioritisation of drivers to form scenarios
- 14. Framework for exploring Futures Drivers obj 2 Stakeholder workshops 4 Issues 1 Identification Collective SH workshops 4 learning Future Scenarios 2
- 15. DRIVERS THAT GUIDED DEVELOPMENT OF 2020 FARM SYSTEMS •productivity and profitability, •labour and staff skills, •regulation, environmental constraints/limits and continued well being (survivability).
- 16. Current and future 2020 () attributes of dairy and sheep and beef base 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. 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. Micro Macro Farmers Rural community Supply chain Society - Farmax and Farm Catchment- Region National International Overseer Weekly Season Multi-year intergenerational
- 19. OUTCOMES •Many of the farm parameters, e.g., stocking rate, MS per cow and per hectare, were not significantly pushed beyond the current top performing farms in the region. •Agreement that in 10 years’ time the “average” farmer would continue down a business-as usual- pathway, shifting to a position that reflected the current top 10% of the industry.
- 20. OK AS FAR AS IT GOES BUT ......... The next generation of tools will require the linking of human behaviour with economic and environmental objectives and the building of stakeholder understanding of the emergent properties, behaviours and unintended consequences of farm systems experiencing multiple drivers required in Steps 4 and 5 of the framework
- 21. Variables influencing farmer ability to make changes 1 1 100% = 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. Transit/ Birth and F/Time Busin/s T/over of Gen C n of socialis/n on farm expans farm respons Transit/n Transit/ Birth and F/Time Busin/s T/over of Busin/s Gen B of Consol/n n of Retire/t socialis/n on farm expans farm expans respons respons Transit/n T/over of Busin/s Gen A Consol/n of Retire/t farm expans respons MODERATE LIMITED HIGH LIMITED MODERATE LIMITED HIGH LIMITED MODERATE Change CHANGE CHANGE CHANGE CHANGE CHANGE CHANGE CHANGE CHANGE CHANGE Farmer life cycle: traditional succession and impacts on change
- 23. AGENT BASED MODEL FARM DESCRIPTIONS
- 24. AGENT BASED MODEL FARMER TYPES
- 25. INSIGHTS ON FRAMEWORK •Need a diversity of world views •Participants expanding their perceptions and the knowledge they will need to take into consideration when strategic planning. •Allows the exploration of multiple pressures simultaneously • It is generic but is anchored in context and place.
- 26. REFLECTIONS BY THE RESEARCH TEAM •Ability to apply models to systems •Building interdisciplinarity •Developing the ability to have conversations across social and biophysical •Joined up view •Tackling complexity and uncertainty
- 27. CHARACTERISTICS OF THE TEAM MEMBERS •Abundance mentality (no hoarding) •Connectors •Good discipline science •Confident enough to simplify and bring into a context •Translator •Leadership •Shared goal
- 28. Thanks to the funder FRST