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Models of farms and their application. Daniel Rodriguez
 

Models of farms and their application. Daniel Rodriguez

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A presentation from the WCCA 2011 event held in Brisbane, Australia.

A presentation from the WCCA 2011 event held in Brisbane, Australia.

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  • Increase our (both researchers and the farming community) understanding (...we are all learning...) on what is changing and what are the likely consequences if those changes would persistWork with our farmers and agronomists towards reducing their exposure to change (now and the next 5-10 years), by increasing our understanding on what farming systems are more profitable and less riskySmall number of representative future climates
  • The past 10 years brought a flurry of farm scale models to understand resource management at this level, which is seen as relevant compared to a sole focus on the field scale, certainly in mixed or specialized animal production systems. Different types of models have been developed: static versus dynamic, summary versus detailed (mechanistic?), goal-oriented versus process-based, geared to evaluation of a single system versus assessment of multiple alternative systems to assess trade-offs among goals. Questions would include: relation between choice of modelling method and specific setting (data availability, goals of study), types of results generated (scenarios, trade-offs, blueprints), which kinds of system delimitations and interrelations among components, how much detail is required, etc.

Models of farms and their application. Daniel Rodriguez Models of farms and their application. Daniel Rodriguez Presentation Transcript

  • Models of farms and their application Daniel Rodriguez
  • A complex system Rodriguez and Sadras, 2011
  • Household ModellingFor the sustainable intensification of agricultureHuman dimensions Household surveys and typologies, Understanding vulnerabilities: interviews, and discussion groups identifying priorities and optionsUncertainties (unknowns)Strategic: Sensitivity and scenario Increased preparedness,analyses, use of downscaled GCMs increased resilience and profitabilityRisks (known unknowns)Tactical: What if? Improved risk management through the relevant use of forecasting tools
  • Participatory whole farmmodelling Diagnosis and evaluation Describe, current Explain, current farmer’sSupporting implementation production systems and decision on resource their problems allocation and their consequences Social desirability Design, new Explore, options for management systems agro-technological that contribute to improvement in face of increasing resilience and possible future scenarios profitability in agriculture Ex-ante understanding, impacts, performances & trade offs
  • Representing complex systems Acceptance State contingent Functional Dynamic Scenario and Linear sensitivity programing analyses Deterministic Stochastic Variable environmentEvolutionaryapproaches What if? Empirical questions StaticData availability / level of ignorance
  • How optimum is optimum enough? “…In my judgment, farmers decisions made in this ad hoc way are usually very good. They are not perfect (farmers are human!) but they are usually near enough…” David Pannell So, what is the fuss about optimization?
  • Trade-offs Alternative farming systems • Practices • Tillage & ground cover • Moisture seekingObjective 1 • Tactics More of 1 More of • Planting rules both • Soil water thresholds • Crop sequences & intensity • Long fallowing Less of 2 • Forage conservation • Strategies • Crop selection (winter / summer) • Water allocations • Land allocations • Cropping / grazing mix Objective 2 • Farmers’ preference • Risk preference & its trade offs • Plastic vs rigid
  • Thanks