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Revisiting N fertilization rates in low-rainfall

grain cropping regions of Australia

A risk analysis

M. Monjardino, T. McBeath, L. Brennan, R. Llewellyn

56 th AARES Conference, 8-10 February 2012, Fremantle


Research problem

Grain production is increasingly risky as

wheat revenue variance has more than

doubled in Australia over the past 15 years

(Kingwell, 2011).

Consequently, decisions surrounding the

most profitable fertiliser rates pose a major

risk management dilemma to farmers.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Context

• Agriculture the most volatile sector of the Australian economy,

and more volatile than agriculture elsewhere;

• In particular, low-rainfall farmers operate in increasingly

challenging conditions, including:

• High climate and seasonal risk and uncertainty;

• High spatial variability;

• Low nutrient use efficiency (low uptake, losses);

• Intense market volatility;

• Tighter budgets

• 2.2%/yr decline in terms of trade

• fertilizers now 60% of total var. costs of growing a crop

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Index

Context

• Agriculture the most volatile sector of the Australian economy,

and more volatile than agriculture elsewhere;

• In particular, low-rainfall farmers operate in increasingly

challenging conditions, including:

• High climate and seasonal risk and uncertainty;

• High spatial variability;

• Low nutrient use efficiency (low uptake, losses);

• Intense market volatility;

• Tighter budgets

• 2.2%/yr decline in terms of trade

• fertilizers now 60% of total var. costs of growing a crop

250

200

150

100

50

Terms of trade

Prices received

Prices paid

ABARE

Prices paid for fert.

0

1969 1979 1989 1999 2009

Years

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Context – N management

• History of fixed low rates of N in low-rainfall regions as to

minimize downside risk in anticipation of poor seasons;

• N considered risk-increasing input (literature);

• Recommendations based on average season/rules of thumb;

• N fertilizer applications often up front at sowing, but ‘playing the

season’ on the rise with intensification of cropping;

• Slow increase in uptake of precision technologies for fertilization

(e.g. VRT).

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Research question

Since consistently low N inputs lead to N deficiency, which is likely

to be one of the main causes of a gap between actual and

potential yield, especially in the wetter seasons…

Could those farmers in the low-rainfall Australian wheatbelt who

adopt a low-input strategy in the attempt to minimize economic

risk in fact be missing out on greater returns from more intense

cropping in the more favourable seasons

In a nutshell:

Are dryland farmers under-fertilizing with N

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Methodology

We analyse the problem by using a combination of different

tools:

• Case-study climatic and agronomic data

• Crop simulation modelling

• Profit function

• Monte Carlo simulation

• Probability theory

• Finance theory techniques

• Stochastic efficiency analysis

… to evaluate the combined impact of yield and price risk on

long-term performance of N fertiliser strategies on different soil

types.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Study area – the Mallee

. Karoonda

Map of the SA/Vic Mallee region

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Study area – the Mallee

• Mallee region located across SA, Vic and bit of NSW;

• Approximately 4million ha of cropping land;

• Highly variable soils in dune-swale land system;

• Typical Mediterranean-type climate;

• Mean annual rainfall 250-350 mm;

• Mean annual evaporation around 2000 mm;

• Poor soils with low water-holding capacity;

• Cereals exposed to moisture stress and drought:

• Total crop failure in 10% of seasons;

• High water stress in 30-50% of seasons;

• Crop damage due to unpredictable factors (e.g. locusts last year).

• District average N rate: 15 kg N/ha.

. Karoonda

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Yield simulation response curves

APSIM-simulated wheat crops grown for a range of scenarios

assuming the following conditions:

• Data for 3 representative land management zones in Karoonda;

• Starting mineral soil N of 18, 36, 52 kg N/ha for each zone (0-

110 cm);

• Soil water reset each year on Jan 1 to harvest lower limit

determined by prior simulation;

• Surface residue reset to 1.5 t/ha at the same time;

• Soil N and OM reset on April 1 each year;

• Crops sown soon after break, based on rainfall and timing.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Land management zones

Zone Location Av. % of

typical

farm

Main soil

type

Level of

subsoil

constr.

Initial

fert.

status

Resp. to

fertiliser

Average

wheat

yld (t/ha)

Dune Hill-top 30 Sand Low Low Good 2.1

Slope

Mid-

slope

50 Sandy

to clay

loam

Med Med Average 1.7

Flat

Plain or

swale

20 Medheavy

clay

High High Poor 1.1

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Dune

Slope

Flat

Wheat yield map reflecting the typical paddock elevation of the Mallee

(Source: Davoren, CSIRO 2010) (0-0.5 t/ha; 0.5-0.8 t/ha; 0.8-1.5t/ha)

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


N fertilization scenarios

• Eight N fertilizer application rates:

• 0, 7.5, 15, 30, 60, 90, 120, 150 kg N/ha

• applied up front at sowing (rate X + 0) and in combination with an inseason

application at GS 31-40 (tactical or split) in each zone.

• Tactical N application triggered in APSIM by the simultaneous

occurrence of threshold values of:

• soil water (> crop lower limit);

• soil N (< 100 kg N ha -1 );

• rainfall (≥ 10 mm over 3 days) within GS31-40.

(Tactical application of N was not triggered in 21 seasons (35%)).

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Wheat yield (t/ha)

Wheat yield (t/ha)

N fertilization scenarios

• Eight N fertilizer application rates:

• 0, 7.5, 15, 30, 60, 90, 120, 150 kg N/ha

• applied up front at sowing (rate X + 0) and in combination with an inseason

application at GS 31-40 (tactical or split) in each zone.

• Tactical N application triggered in APSIM by the simultaneous

occurrence of threshold values of:

• soil water (> crop lower limit);

• soil N (< 100 kg N ha -1 );

• rainfall (≥ 10 mm over 3 days) within GS31-40.

(Tactical application of N was not triggered in 21 seasons (35%)).

0.5

0.4

0.3

0.2

0.1

0

2002

0 20 40 60 80 100 120 140 160

N rate (kg/ha)

5

4

3

2

1

0

1958

0 20 40 60 80 100120140160

N rate (kg/ha)

Dune

Slope

Flat

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Data sets

• APSIM-generated wheat yields based on 60-year rainfall timeseries

(1950-2010);

• Historical prices (1970-2010) for wheat grain and urea fertiliser

(46% N) (adjusted to 1998 consumer price index);

• Wheat x N price correlation coefficient of 0.12.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Yield variability

• Frequency distributions of wheat yields generated for each of

the N treatments;

• PDF with the best fit (as measured by the AD stats test) selected

for use in Monte Carlo simulation of economic net returns.

• Mean yields, SD, CV, as well as Deciles, used for comparison of

yield production and variance.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Profit function

NR nz = (Y nz x P w ) – ((R n1z +(R n2z x f))*P n ) – C o – (C t * f)

NR nz

Y nz

P w

R n1z

R n2z

P n

C o

C t

f

net returns by total N rate n on management zone z ($/ha)

crop yield by total N rate n on management zone z (kg/ha)

price of ASW wheat grain ($/kg)

rate of N applied at sowing on management zone z (kg N/ha)

rate of N applied in-season on management zone z (kg N/ha)

price of N (i.e. price of urea/0.46) ($ kg/N)

other costs ($/ha)

operational cost of applying extra fertilizer in-season ($/ha)

frequency of seasons with tactical N application in-season

C o = C v + C f + I v + D m

C v variable costs of growing wheat, incl seed purchase and treatment, herbicides, fuel and oil,

and fertilizers other than N

C f

fixed costs of production apportioned on a $/ha basis such as repairs and maintenance,

labour, insurance and levies

I v interest on variable costs (half at 8%)

depreciation of machinery investment (10% of $200/ha in machinery investment)

D m

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Variability of net returns

• @RISK used to generate 1000 Monte Carlo simulations of

the profit function with random samples for yield and prices

drawn from their PDFs;

• PDF of economic net returns developed for all scenarios;

• Quantification of NR for alternative scenarios using a

combination of 8 measures of risk around the mean...

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Economic-risk measures

1. Mean of expected NR (magnitude);

2. Mode of expected NR (frequency);

3. Standard deviation of NR, SD (dispersion);

4. Coefficient of variation, CV (variance);

5. Probability of break-even, P(NR ≥ 0) (positive NR);

6. Conditional value at risk of the lowest 10% of possible

outcomes, CVaR0.1, (risk of extreme financial loss associated

with unfavourable events);

7. Return on total fertilizer investment at risk (R N );

8. Return on tactical fertilizer investment at risk (R NT ).

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


CVaR0.1

Prob. of break even

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Farmers’ preferences

• Fertilization preferences under risk revealed through a

Stochastic Efficiency with Respect to a Function (SERF)

analysis (Hardaker et al., 2004);

• SERF ranks a set of alternative (N) strategies in terms of

Certainty Equivalence (CE) for a specified range of risk

attitudes, which is measured by a Constant Absolute Risk

Aversion coefficient (0.0 < CARA < 1.0);

• Constant aversion to risk implies a utility function, e.g. the

negative exponential utility function:

U(W) = 1- Є -cW

W

wealth or income expressed as a wealth equivalent

c constant absolute risk aversion (CARA) coefficient (c > 0)

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Results

1. Yield variance analysis

2. Economic-risk performance

3. Impact of risk aversion

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Yield variance (Slope, 0 – 30 kg N/ha up front )

Mean

SD

CV

% years

Kg N/ha

(kg/ha)

(kg/ha)

< 0.25 t/ha < 0.5 t/ha < 1.0 t/ha < 2.0 t/ha > 5.0 t/ha

0

15

30

+ 0 343 143 0.42 20 90 100 100 0

+ 15 779 462 0.59 20 47 63 100 0

+ 30 735 569 0.77 20 47 63 100 0

+ 60 741 578 0.78 20 47 63 100 0

+ 90 744 584 0.78 20 47 63 100 0

+ 150 746 584 0.78 20 47 63 100 0

+ 0 579 250 0.43 18 27 100 100 0

+ 15 1153 1087 0.94 18 27 57 78 0

+ 30 1261 1378 1.08 18 27 57 75 0

+ 60 1322 1647 1.24 18 27 57 70 0

+ 90 1322 1603 1.20 18 27 58 70 0

+ 150 1339 1780 1.32 18 27 58 70 0

+ 0 883 414 0.47 15 23 45 100 0

+ 15 1319 1028 0.78 17 23 43 75 0

+ 30 1389 1218 0.88 17 23 43 70 0

+ 60 1465 1367 0.93 17 23 43 70 0

+ 90 1477 1411 0.95 17 23 43 70 0

+ 150 1485 1467 0.99 17 23 43 70 0

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Yield variance (Slope, 0 – 30 kg N/ha up front )

Mean

SD

CV

% years

Kg N/ha

(kg/ha)

(kg/ha)

< 0.25 t/ha < 0.5 t/ha < 1.0 t/ha < 2.0 t/ha > 5.0 t/ha

0

15

30

+ 0 343 143 0.42 20 90 100 100 0

+ 15 779 462 0.59 20 47 63 100 0

+ 30 735 569 0.77 20 47 63 100 0

+ 60 741 578 0.78 20 47 63 100 0

+ 90 744 584 0.78 20 47 63 100 0

+ 150 746 584 0.78 20 47 63 100 0

+ 0 579 250 0.43 18 27 100 100 0

+ 15 1153 1087 0.94 18 27 57 78 0

+ 30 1261 1378 1.08 18 27 57 75 0

+ 60 1322 1647 1.24 18 27 57 70 0

+ 90 1322 1603 1.20 18 27 58 70 0

+ 150 1339 1780 1.32 18 27 58 70 0

+ 0 883 414 0.47 15 23 45 100 0

+ 15 1319 1028 0.78 17 23 43 75 0

+ 30 1389 1218 0.88 17 23 43 70 0

+ 60 1465 1367 0.93 17 23 43 70 0

+ 90 1477 1411 0.95 17 23 43 70 0

+ 150 1485 1467 0.99 17 23 43 70 0

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Yield variance (Slope, 0 – 30 kg N/ha up front )

Mean

SD

CV

% years

Kg N/ha

(kg/ha)

(kg/ha)

< 0.25 t/ha < 0.5 t/ha < 1.0 t/ha < 2.0 t/ha > 5.0 t/ha

0

15

30

+ 0 343 143 0.42 20 90 100 100 0

+ 15 779 462 0.59 20 47 63 100 0

+ 30 735 569 0.77 20 47 63 100 0

+ 60 741 578 0.78 20 47 63 100 0

+ 90 744 584 0.78 20 47 63 100 0

+ 150 746 584 0.78 20 47 63 100 0

+ 0 579 250 0.43 18 27 100 100 0

+ 15 1153 1087 0.94 18 27 57 78 0

+ 30 1261 1378 1.08 18 27 57 75 0

+ 60 1322 1647 1.24 18 27 57 70 0

+ 90 1322 1603 1.20 18 27 58 70 0

+ 150 1339 1780 1.32 18 27 58 70 0

+ 0 883 414 0.47 15 23 45 100 0

+ 15 1319 1028 0.78 17 23 43 75 0

+ 30 1389 1218 0.88 17 23 43 70 0

+ 60 1465 1367 0.93 17 23 43 70 0

+ 90 1477 1411 0.95 17 23 43 70 0

+ 150 1485 1467 0.99 17 23 43 70 0

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Yield variance - summary

• Lowest CV of the mean yield around 15 kg N/ha at sowing , i.e.

farmers currently target lower yield variance;

• However, up front N rates up to 90 kg N/ha in the dune, 60 kg

N/ha in the slope and 30 kg N/ha in the flat, could be beneficial

in terms of increasing yields significantly, while still managing

yield variance.

• 60 kg N/ha in-season the point at which the highest yield

variance occurred in most cases.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Economic-risk performance (Dune)

Kg N/ha

Mean

Mode

SD

CV P (NR ≥ 0)

CVaR 0.1

R N

R NT

($/ha)

($/ha)

($/ha)

(%)

($/ha)

($NR/$N)

($NR/N T )

+ 0 -30 -41 24 0.81 11 -68 1.9

15

30

60

90

+ 7.5 27 -42 79 2.92 57 -78 3.7 5.1

+ 15 27 -61 87 3.21 54 -84 2.8 2.6

+ 30 24 -91 93 3.84 53 -96 1.8 1.2

+ 60 10 -96 98 9.92 47 -117 0.9 0.4

+ 0 22 31 49 2.22 69 -67 2.6

+ 7.5 103 25 123 1.19 79 -78 4.2 7.2

+ 15 117 40 146 1.24 77 -84 3.8 4.2

+ 30 118 123 157 1.33 76 -96 2.9 2.1

+ 60 102 -33 159 1.57 70 -114 1.7 0.9

+ 0 106 -2 109 1.02 82 -84 2.7

+ 7.5 185 182 203 1.10 82 -149 3.5 6.8

+ 15 200 162 222 1.11 82 -128 3.4 4.3

+ 30 206 42 236 1.14 81 -139 2.9 2.3

+ 60 198 78 260 1.31 77 -150 2.1 1.0

+ 0 183 273 171 0.93 83 -125 2.6

+ 7.5 208 186 243 1.17 81 -195 2.7 2.2

+ 15 225 187 274 1.22 80 -167 2.6 1.8

+ 30 228 57 290 1.27 79 -147 2.3 1.0

+ 60 215 376 310 1.44 75 -199 1.8 0.3

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Economic-risk performance (Slope)

Kg N/ha

Mean

Mode

SD

CV P (NR ≥ 0)

CVaR 0.1

R N

R NT

($/ha)

($/ha)

($/ha)

(%)

($/ha)

($NR/$N)

($NR/N T )

15

30

60

90

+ 0 7 55 57 8.46 57 -94 2.2

+ 7.5 84 23 153 1.83 69 -121 4.8 6.9

+ 15 113 -38 242 2.14 67 -126 4.6 4.8

+ 30 131 29 400 3.06 64 -131 3.3 2.7

+ 60 117 -52 342 2.92 59 -151 1.9 1.3

+ 0 55 133 92 1.69 72 -111 2.7

+ 7.5 114 166 188 1.64 71 -144 3.7 5.4

+ 15 134 88 234 1.75 69 -149 3.4 3.4

+ 30 137 -23 263 1.93 65 -146 2.7 1.8

+ 60 133 -45 300 2.25 60 -168 1.7 0.9

+ 0 105 144 165 1.58 68 -143 2.1

+ 7.5 142 9 250 1.76 69 -188 2.4 3.2

+ 15 161 -43 306 1.91 67 -178 2.5 2.6

+ 30 158 -181 363 2.30 56 -180 2.0 1.1

+ 60 143 -102 367 2.63 55 -201 1.4 0.4

+ 0 128 63 253 1.98 65 -198 1.7

+ 7.5 149 16 330 2.21 63 -205 1.8 2.1

+ 15 142 -159 358 2.52 55 -199 1.6 0.8

+ 30 142 -187 371 2.61 53 -210 1.4 0.3

+ 60 123 -142 376 3.05 51 -234 1.0 0.0

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Economic-risk performance (Flat)

Kg N/ha

Mean

($/ha)

Mode

($/ha)

SD

($/ha)

CV P (NR ≥ 0)

(%)

CVaR 0.1

($/ha)

R N

($NR/$N)

R NT

($NR/N T )

+ 0 55 86 133 2.39 67 -175 2.1

+ 7.5 79 38 193 2.45 67 -261 2.6 2.1

7.5

+ 15 95 -7 198 2.09 64 -163 2.4 1.8

+ 30 134 -76 487 3.63 54 -140 2.4 1.7

+ 60 122 -143 483 3.96 48 -160 1.2 0.8

+ 0 66 23 154 2.34 68 -200 1.7

+ 7.5 95 -4 197 2.07 64 -165 2.4 2.7

15

+ 15 135 -83 437 3.24 56 -138 3.0 3.0

+ 30 145 -128 498 3.44 53 -148 2.4 1.9

+ 60 154 -82 845 5.50 50 -167 1.4 0.9

+ 0 74 26 188 2.55 66 -260 1.2

+ 7.5 129 -95 387 2.99 54 -149 2.4 4.9

30

+ 15 177 -88 1018 5.74 52 -151 2.7 3.9

+ 30 173 -92 738 4.26 50 -164 2.3 2.3

+ 60 168 -139 808 4.79 45 -182 1.5 1.1

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Economic-risk performance

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Economic-risk performance

• Highest mean NR with mid to high N rates (> 30 kg N/ha)

applied up front and/or tactically on all three zones, especially

the dune;

• The standout strategies include 30 - 90 kg N/ha in the dune, 15-

60 kg N/ha in the slope, but only two scenarios (15 + 7.5 and

7.5 + 15 kg N/ha) offer a benefit relative to the standard rate in

the flat.

• The least attractive economic-risk scenarios result both from

under-fertilizing with zero/low N inputs and from over-fertilizing

with excessively high inputs (especially in-season).

• The results indicate that there is much scope to use more N

within a paddock, especially in the dune and the slope zones,

as well as potential for a small practice change in the flat zone.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Best economic-risk scenarios

• In summary, the best scenarios overall in terms of economics

and risk performance are assumed to meet all of the following

conditions:

• Mean NR ≥ Mean NR 15 kgN/ha in that zone

• CV≤ 3.0

• P(NR≥0) > 50% and P(NR≥0) > P(NR≥0) 15 kgN/ha in that zone

• CVaR 0.1 ≤ -$150/ha

• R N ≥ R N 15 kgN/ha and R N >0

• R NT ≥ $1.0 per dollar of N tactical

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Dune

Slope

Flat

Best economic-risk scenarios

Kg N ha -1

Mean

CV P (NR ≥ 0)

CVaR 0.1

R N

R NT

($/ ha)

(%)

($/ha)

($NR/$N)

($NR/$N T )

+ 7.5 103 1.19 79 -78 4.2 7.2

30 + 15 117 1.24 77 -84 3.8 4.2

+ 30 118 1.33 76 -96 2.9 2.1

+ 0 106 1.02 82 -84 2.7

+ 7.5 185 1.10 82 -149 3.5 6.8

60 + 15 200 1.11 82 -128 3.4 4.3

+ 30 206 1.14 81 -139 2.9 2.3

+ 60 198 1.31 77 -150 2.1 1.0

90

+ 0 183 0.93 83 -125 2.6

+ 30 228 1.27 79 -147 2.3 1.0

+ 7.5 58 2.22 64 -110 5.5 6.2

7.5 + 15 84 1.56 68 -108 4.8 4.2

+ 30 87 2.80 59 -124 3.0 2.2

15

+ 7.5 84 1.83 69 -121 4.8 6.9

+ 15 113 2.14 67 -126 4.6 4.8

+ 0 55 1.69 72 -111 2.7

30

+ 7.5 114 1.64 71 -144 3.7 5.4

+ 15 134 1.75 69 -149 3.4 3.4

+ 30 137 1.93 65 -146 2.7 1.8

60 + 0 105 1.58 68 -143 2.1

7.5 +15 95 2.09 64 -163 2.4 1.8

15 +7.5 95 2.07 64 -165 2.4 2.7

CSIRO. Insert presentation title, do not remove CSIRO from start of footer


Selection of top economic-risk scenarios

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Selection of top economic-risk scenarios

80%

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Selection of top economic-risk scenarios

80%

20%

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Selection of top economic-risk scenarios

60%

15%

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Selection of top economic-risk scenarios

40%

10%

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Impact of risk aversion

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Impact of risk aversion

Upfront overtake tactical

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Impact of risk aversion

Upfront overtake tactical

Typical rate overtakes top scenarios

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Impact of risk aversion

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Impact of risk aversion

Upfront overtakes tactical

Typical rate overtakes top scenarios

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Impact of risk aversion

Mallee farmers

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Conclusions

• Mallee dryland farmers relatively risk-averse and potentially

missing out on the returns available from more intense

cropping in the good years on most of their farm (80%);

• In other words, when long-term yield and price risks are

factored in, it is evident that farmers are better off if they

reduce the probability of under-fertilizing in the dry seasons

(i.e. making a loss), while increasing the probability of

sufficiently fertilizing when the season develops well (by

providing enough N up front or ‘playing the season’);

• Some tactical fertilization can increase farmers’ mean NR

while in some cases reducing income variance, although full

potential of tactical fert is likely to be realised when factors like

grain protein, crop rotation and whole-farm farm budget are

factored in the analysis;

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Conclusions

• Use of variable fertiliser rates based on soil-specific

management zones has the potential to not only increase profit

but reduce risk, based on a number of risk metrics;

• High riskiness and complexity of dryland cropping presents

opportunity to manage nutrients more efficiently and explore

sustainable intensification;

• If Mallee farmers are able to establish the relevance of this

analysis to their own farm and soil conditions by e.g. defining

the % of a certain soil type on their farm, and relating the

analysis to the initial N fertility on their given management unit,

then these results could usefully inform individual farmers’

decisions.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Study limitations

• Variance of yield potentials in APSIM lower than actual crops

since the model cannot accurately capture all phenomena,

including unpredictable damage by weather, pests, diseases

and weeds, or occasional crop failures caused by ‘haying off’ in

extremely dry seasons;

• The model has been fixed to have the same starting N

conditions for every season in a given soil type, which may in

fact vary considerably with prior management.

• Need to place study in whole-farm context as mixed-enterprise

farms likely to cope better with risk.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


Future directions

• Validate Mallee case study against data attained from growers;

• Follow-up analysis to test the effect of higher intensity of

cropping on increasing initial soil test N values;

• Conduct similar analysis for P to test value of replacement

strategies;

• Apply risk framework to other regionally relevant nutrient

management case studies across Australia to compare risk

profiles and management options.

CSIRO. Revisiting N fertilisation rates in low-rainfall grain cropping regions. A risk analysis


CSIRO Ecosystem Sciences

Marta Monjardino

Social and Economic Sciences

Phone: 61 (0)8 8303 8413

Email: marta.monjardino@csiro.au

Web: www.csiro.au/ces

Acknowledgements

A. Whitbread

M. Robertson

J. Kandulu

E. Qureshi

J. Ouzman

D. Gobbett

I. Fillery

(all from CSIRO)

Thank you

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