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Diversification in Australian broadacre farming:  can simulation models handle the manager’s objectives and constraints? A...
Australian broadacre farming: the broad brush <ul><li>Farms are large, and getting larger </li></ul><ul><ul><li>Trend towa...
Biophysical simulation models of mixed farms <ul><li>APSIM soil and crop models </li></ul><ul><li>GRAZPLAN pasture model  ...
Key drivers and constraints on diversification <ul><li>Risk mitigation </li></ul><ul><ul><li>portfolio diversification red...
1. Risk mitigation <ul><ul><li>Portfolio diversification reduces economic risk </li></ul></ul><ul><li>Magnitude of this ef...
2. Exploiting spatial variability <ul><ul><li>Different land uses are optimal on different land classes </li></ul></ul><ul...
3. Production complementarities <ul><li>Simulation modelling the only way to extrapolate from experimentation </li></ul><u...
4. Management flexibility <ul><li>Divert resources between enterprises tactically </li></ul>Coolamon, New South Wales: Fut...
<ul><li>Soil C levels, salinity management, herbicide resistance … </li></ul><ul><li>The simulation models can do: </li></...
5. Resource maintenance <ul><li>Soil C levels, salinity management, herbicide resistance … </li></ul><ul><li>The simulatio...
6. Resource allocation <ul><li>Limited supplies of water, cash, machinery & labour </li></ul><ul><li>Typically done with l...
6. Resource allocation <ul><li>Limited supplies of water, cash, machinery & labour </li></ul><ul><li>Labour & machinery ca...
7. Management focus <ul><ul><li>“ Enterprises doubled, management squared” </li></ul></ul><ul><li>Simulation analyses tend...
A final observation <ul><li>These modelling analyses have treated mixed farming systems as  stochastic but stationary proc...
Thank you Lindsay Bell CSIRO Ecosystem Sciences Toowoomba Phone:  +61 7 4688 1221 Email:  Lindsay.Bell@csiro.au Andrew Moo...
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Diversification in Australian broadacre farming: can simulation models handle the manager's objectives and constraints? Andrew Moore

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

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Diversification in Australian broadacre farming: can simulation models handle the manager's objectives and constraints? Andrew Moore

  1. 1. Diversification in Australian broadacre farming: can simulation models handle the manager’s objectives and constraints? Andrew Moore & Lindsay Bell
  2. 2. Australian broadacre farming: the broad brush <ul><li>Farms are large, and getting larger </li></ul><ul><ul><li>Trend toward more cropping </li></ul></ul><ul><li>Largely deregulated markets </li></ul><ul><ul><li>Little direct government support </li></ul></ul><ul><ul><li>Exposed to price volatility </li></ul></ul><ul><li>Multiple pressures on inputs </li></ul><ul><ul><li>Long term cost-price squeeze </li></ul></ul><ul><ul><li>Labour shortages </li></ul></ul><ul><li>Major “Millenium Drought” </li></ul>ABARES survey data
  3. 3. Biophysical simulation models of mixed farms <ul><li>APSIM soil and crop models </li></ul><ul><li>GRAZPLAN pasture model </li></ul><ul><ul><li>Common water uptake logic </li></ul></ul><ul><li>GRAZPLAN ruminant model </li></ul><ul><ul><li>Crop models extended for defoliation </li></ul></ul><ul><li>Event-based management </li></ul><ul><ul><li>Full-featured management scripting language </li></ul></ul><ul><li>First applications in 2006 </li></ul>Barley Canola Grass Phalaris Clover Lucerne Water Soil C+N Wheat Paddock Barley Canola Grass Phalaris Clover Lucerne Water Soil C+N Wheat Paddock Barley Canola Grass Phalaris Clover Lucerne Livestock Cashbook Water Soil C+N Wheat Paddock Barley Canola Grass Phalaris Clover Lucerne Simulation Manager Weather Water Soil C+N Wheat Paddock
  4. 4. Key drivers and constraints on diversification <ul><li>Risk mitigation </li></ul><ul><ul><li>portfolio diversification reduces economic risk </li></ul></ul><ul><li>Exploiting spatial variability </li></ul><ul><ul><li>different land uses are optimal on different land classes </li></ul></ul><ul><li>Production complementarities </li></ul><ul><ul><li>legume N, crop disease breaks, forage supply </li></ul></ul><ul><li>Management flexibility </li></ul><ul><ul><li>divert resources between enterprises tactically </li></ul></ul><ul><li>Maintenance of land & genetic resources </li></ul><ul><ul><li>soil C levels, salinity management, herbicide resistance … </li></ul></ul><ul><li>Resource allocation </li></ul><ul><ul><li>Limited supplies of water, cash, machinery & labour </li></ul></ul><ul><li>Management focus </li></ul><ul><ul><li>“ enterprises doubled, management squared” </li></ul></ul>
  5. 5. 1. Risk mitigation <ul><ul><li>Portfolio diversification reduces economic risk </li></ul></ul><ul><li>Magnitude of this effect has not previously been quantified </li></ul><ul><li>Simulation models are ideally suited to explore this question </li></ul>Temora, New South Wales: Bell & Moore, this conference
  6. 6. 2. Exploiting spatial variability <ul><ul><li>Different land uses are optimal on different land classes </li></ul></ul><ul><li>Simulation models can capture key differences between soils </li></ul><ul><li>Difficult to assess typical levels of soil variability across a region </li></ul><ul><ul><li>New mapping initiatives (e.g. GlobalSoilMap.net) may help </li></ul></ul>Australian Soil Resource Information System
  7. 7. 3. Production complementarities <ul><li>Simulation modelling the only way to extrapolate from experimentation </li></ul><ul><li>N supply through fixation by legumes </li></ul><ul><ul><li>Captured by the models </li></ul></ul><ul><li>Disease & weed management </li></ul><ul><ul><li>Modelling crop & pasture diseases is the next scientific challenge </li></ul></ul><ul><ul><li>Lawes’ talk at this conference </li></ul></ul><ul><li>More diverse feed bases </li></ul><ul><ul><li>Dual-purpose cereals </li></ul></ul><ul><ul><li>Stubbles: to graze or not to graze? </li></ul></ul>Waikerie, South Australia: Descheemaeker & Moore, this conference
  8. 8. 4. Management flexibility <ul><li>Divert resources between enterprises tactically </li></ul>Coolamon, New South Wales: Future Farming Industries CRC (unpublished)
  9. 9. <ul><li>Soil C levels, salinity management, herbicide resistance … </li></ul><ul><li>The simulation models can do: </li></ul><ul><ul><li>Water losses – deep drainage, runoff </li></ul></ul><ul><ul><li>Soil carbon changes (required precision is increasing) </li></ul></ul><ul><ul><li>Bare ground/erosion risk </li></ul></ul>5. Resource maintenance Coolamon, New South Wales: Robertson et al. (2009)
  10. 10. 5. Resource maintenance <ul><li>Soil C levels, salinity management, herbicide resistance … </li></ul><ul><li>The simulation models can do: </li></ul><ul><ul><li>Water losses – deep drainage, runoff </li></ul></ul><ul><ul><li>Soil carbon changes (required precision is increasing) </li></ul></ul><ul><ul><li>Bare ground/erosion risk </li></ul></ul><ul><li>Soil acidity is a gap </li></ul><ul><li>Herbicide resistance management has generally been modelled using simpler approaches </li></ul><ul><ul><li>Thornby et al . (2009) have linked weed population-genetic models to APSIM using Vensim </li></ul></ul><ul><ul><li>Larger set of scientific questions around modelling population genetics in agricultural systems </li></ul></ul>
  11. 11. 6. Resource allocation <ul><li>Limited supplies of water, cash, machinery & labour </li></ul><ul><li>Typically done with linear programming “bio-economic” models </li></ul><ul><ul><li>Use of simulation models to estimate (or constrain) technical coefficients </li></ul></ul>
  12. 12. 6. Resource allocation <ul><li>Limited supplies of water, cash, machinery & labour </li></ul><ul><li>Labour & machinery can be accounted for in the same way as cash flows </li></ul>GRDC Water Use Efficiency Program <ul><li>Allocation of resources between years and paddocks rather than enterprises: </li></ul><ul><ul><li>Soil water, via control of weeds in summer fallows </li></ul></ul><ul><ul><li>Labour & machinery (e.g. sowing time allocation) </li></ul></ul><ul><li>Hybrid modelling analyses needed </li></ul><ul><ul><li>Use of simulation models to estimate (or constrain) technical coefficients </li></ul></ul>
  13. 13. 7. Management focus <ul><ul><li>“ Enterprises doubled, management squared” </li></ul></ul><ul><li>Simulation analyses tend to assume a “perfect” manager </li></ul><ul><li>Area for future research (interface between “hard” & “soft” systems) </li></ul>
  14. 14. A final observation <ul><li>These modelling analyses have treated mixed farming systems as stochastic but stationary processes </li></ul><ul><ul><li>“ Slow” variables held (or forced) constant </li></ul></ul><ul><li>This assumption isn’t valid for some of the problems requiring analysis </li></ul><ul><ul><li>Climate adaptation pathways </li></ul></ul><ul><ul><li>Carbon sequestration as a source of cash flow </li></ul></ul><ul><li>How do we interpret modelling outputs in non-stationary contexts? </li></ul>
  15. 15. Thank you Lindsay Bell CSIRO Ecosystem Sciences Toowoomba Phone: +61 7 4688 1221 Email: Lindsay.Bell@csiro.au Andrew Moore CSIRO Plant Industry Canberra Phone: +61 2 6246 5298 Email: Andrew.Moore@csiro.au

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