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: Lindsay.Bell@csiro.au

Andrew MooreCSIRO Plant IndustryCanberra

Phone: +61 2 6246 5298Email: Andrew.Moore@csiro.au