Mixed crop-livestock businesses reduce price and climate - induced variability in farm returns: a...
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Mixed crop-livestock businesses reduce price- and climate-induced variability in farm returns: a model-derived case study
Lindsay Bell & Andrew Moore
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Rationale
Mixed crop-livestock systems have dominated Australian agriculture historically
• Their ‘decline’ a concern
What do mixed farming systems have to offer?• Risk mitigation • Production synergies• Management flexibility
• Difficult to disentangle various attributes• Farm-level data confounded by multiple elements
Modelling a useful mechanism• Examine various elements in isolation • Quantify the nature & scale of benefits/costs
• Manage spatial variability• Resource maintenance• Optimise resource allocation
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Examining ‘risk mitigation’
The question
How does a mixture of enterprises (crop & livestock) help mitigate annual fluctuations in farm returns?
Modelling approach• 30 years (1980-2010) returns estimated• Cropping enterprise production – APSIM• Livestock enterprise production – GRAZPLAN• Prices/costs from ABARE index of prices received and paid • Completely separated enterprises
• no interactions between crop or livestock operations• Common soil (no spatial variability)
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System attributes
Temora
Climate-soil
Mean annual rainfall = 521 mm
Soil – Brown chromosol, 125 mm PAWC to 1.2 m depth
Livestock enterprise
Self-replacing Merino ewe/cross-bred lamb enterprise
Annual grass-subterranean clover pasture
Cropping enterprise
Wheat – canola – wheat – barley – wheat rotation
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Calculating annual enterprise Gross Margin
Annual Cropping enterprise GM per ha
Grain yielda × Price year aΣCosts included - based on NSW 2010 GM estimates (NSW Government)
• Seed• Fertiliser• Harvesting
• Herbicide• Fuel
- Cost 2010 × PI year a × 0.2Σ5 crops
CPI year a
CPI 2010
Deflated price index year a = × ABARE price indices
Deflated price index (PI) year a
Deflated price index (PI) 2010
Price year a = × Price 2010
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Calculating annual enterprise Gross Margin
Annual Livestock enterprise GM per ha
class # sheep year a × shorn fleece hd-1
year a × Price year aΣWool Income =
lambs
ewes # sold year a × liveweight × Price year aΣLivestock sales =
Costs included - based on NSW 2010 GM estimates (NSW Government)
• Shearing, marking, health treatments (per hd)• Supplement fed (whole flock)• Commissions (per kg wool, % livestock sales)
GM ha-1 = (Wool income + livestock sales – Σ costs)
1000 ha
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Isolating sources of variability
Sources of variability
Price fluctuations (from price indices)
Production levels(simulated)
Production only Period average Annually variable
Price only Annually variable Period average
Combined Annually variable Annually variable
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Correlation of annual gross margin returns
Production only1:1
r2 = 0.12
0
100
200
300
400
500
600
0 200 400 600
Cropping GM
Live
stoc
k G
M
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Price only1:1
r2 =0.02
0
100
200
300
400
500
600
0 200 400 600
Cropping GM
Live
stoc
k G
MCorrelation of annual gross margin returns
Production only1:1
r2 = 0.12
0
100
200
300
400
500
600
0 200 400 600
Cropping GM
Live
stoc
k G
M
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Correlation of annual gross margin returns
Production only1:1
r2 = 0.12
0
100
200
300
400
500
600
0 200 400 600
Cropping GM
Live
stoc
k G
M
Price only1:1
r2 =0.02
0
100
200
300
400
500
600
0 200 400 600
Cropping GM
Live
stoc
k G
M
Combined1:1
r2 = 0.003
0
100
200
300
400
500
600
0 100 200 300 400 500 600
Cropping GM
Live
stoc
k G
M
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Farm allocation effect on GM variability
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.00 0.20 0.40 0.60 0.80 1.00
Proportion of Area in Cropping
CV o
f Gro
ss M
argi
nCombinedProduction variabil ity onlyPrice variabil ity only
0.3 0.55
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Risk-return trade-off in mixed farms
0% Crop
100% Crop
140
160
180
200
220
240
260
280
40 60 80 100 120
Standard Deviation of Gross Margin
Ave
rage
Gro
ss M
argi
nCombinedProduction variabil ity onlyPrice variabil ity only
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Key points
1. Little correlation between annual cropping and livestock returns
2. Specialisation comes at a cost • More exposed to climate-induced production variability• Crop-only farms more exposed to price variability than livestock-
only farms
3. 30-50% crop area had less variable returns• Even when totally separated in space and time• Additional benefits not considered
Thank you
Lindsay BellCSIRO Ecosystems SciencesToowoomba
Phone: +61 7 4688 1221Email: [email protected]
Andrew MooreCSIRO Plant IndustryCanberra
Phone: +61 2 6246 5298Email: [email protected]