1. An historical analysis of the changes in pasture
production and growing season in three dairy
regions of South East Australia
Richard Rawnsley1, Brendan Cullen2, Karen Christie1 and Richard Eckard2
1Tasmanian Institute of Agricultural Research, University of Tasmania, Burnie, Tasmania 7320, Australia
2Melbourne School of Land and Environment, University of Melbourne, Victoria 3010, Australia

2. Biophysical Modelling approach
• SE Vic, SW Vic and Tas dairy regions are predominantly pasture based.
• Changes in the “wetness”, “dryness” and “length of growing season” will be
key drivers for adaptation.
• Why ?
– Strong influence on key management decision such as:
• Stocking rate and calving date
• Wintering off and implementation of infrastructure such as feedpads, herd homes etc.
• Nitrogen usage and conservation practices
• Drying off times and herd culling
• Planting of forage crops, irrigation start up, scheduling and requirements

3. Biophysical Modelling approach
• What have we done?
– Defined growing season
• 14 day average growth rate > “break even” point.
– Eg. At 2.0 cows/ha and 15 kg DMI/day = 30 kg DM/ha.day.
– Defined wetness
• Soil moisture > field capacity
– Defined dryness
• Readily Available Water (0.5PAW) removed
– Modelled with biophysical pasture simulation model DairyMod
(Johnson et al. 2008).
Johnson IR, Chapman DF, Snow VO, Eckard RJ, Parsons AJ, Lambert MG, Cullen BR (2008)
DairyMod and EcoMod: Biophysical pastoral simulation models for Australia and New Zealand.
Australian Journal of Experimental Agriculture 48, 621–631.

5. Are the models accurate ?
Figure 1. Measured and modelled monthly mean daily net herbage accumulation rates (kg
DM/ha.day), including measured variability (grey shaded). Adapted from Cullen et al. 2008.
Cullen BR, Eckard RJ, Callow MN, Johnson IR, Chapman DF, Rawnsley RP, Garcia SC, White T, Snow VO (2008)
Simulating pasture growth rates in Australian and New Zealand grazing systems. Australian Journal of Agricultural
Research 59, 761-768.

6. Historical Analysis of SE Aus
2008 a 2008 b 2008 c
2004 2004 2004
2000 2000 2000
1996 1996 1996
1992 1992 1992
1988 1988 1988
1984 1984 1984
1980 1980 1980
1976 1976 1976
1972 1972 1972
1968 1968 1968
1964 1964 1964
1960 1960 1960
05-Nov
26-Nov
05-Nov
26-Nov
05-Nov
26-Nov
18-Feb
11-Mar
01-Apr
22-Apr
18-Feb
11-Mar
01-Apr
22-Apr
18-Feb
11-Mar
01-Apr
22-Apr
02-Jul
23-Jul
13-Aug
03-Sep
24-Sep
07-Jan
28-Jan
02-Jul
23-Jul
13-Aug
03-Sep
24-Sep
07-Jan
28-Jan
02-Jul
23-Jul
13-Aug
03-Sep
24-Sep
07-Jan
28-Jan
15-Oct
15-Oct
15-Oct
17-Dec
17-Dec
17-Dec
Figure 2 The simulated commencement date and duration of the growing period, for
years 1960/61 to 2008/09 at Elliott (a), Ellinbank (b) and Terang (c).

7. Historical Analysis of SE Aus
a b c
100 100 100
80 80 80
Percentile
Percentile
Percentile
60 60 60
40 40 40
20 20 20
0 0 0
1960
1964
1968
1972
1976
1980
1984
1988
1992
1996
2000
2004
2008
1960
1964
1968
1972
1976
1980
1984
1988
1992
1996
2000
2004
2008
1960
1964
1968
1972
1976
1980
1984
1988
1992
1996
2000
2004
2008
Figure 3 The simulated number of days in years, expressed as yearly percentiles that the
14 day mean pasture growth rate > 30 kg DM/ha , for years 1960/61 to 2008/09 at Elliott
(a), Ellinbank (b) and Terang (c)

8. Historical Analysis of SE Aus
4
3
2
1
Z value
0
-1
-2
-3
-4
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Figure 4 The Standardised Precipitation Index (SPI) for cumulative 12
month precipitation (1900-2010) for Ellinbank

9. Historical Analysis of SE Aus Z value rain
Z value production
4
Precipitation
3 Pasture production
2
4
1
Z value
3 0
2 -1
-2
1
Z value
-3
0
-4
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
-1
-2 Figure 5 The Standardised Precipitation Index (SPI) for cumulative 12 month
precipitation (1900-2010) and the corresponding Z value for simulated
-3 annual pasture production for Ellinbank
-4
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

10. Historical Analysis of SE Aus
3
April to September
2
1
Z value
0
-1
-2
-3
1900 1920 1940 1960 1980 2000
3
October to March
2
1
Z value
0
-1
-2
-3
1900 1920 1940 1960 1980 2000
Figure 6 The 6 month Standardised Precipitation Index (SPI) for April to September
(RED) and October to March (BLUE) for Ellinbank

11. Historical Analysis of SE Aus
24000 24000
R2 = 0.00 R2 = 0.49
22000 22000
Annual Pasture Yield (kg DM/ha)
Annual Pasture Yield (kg DM/ha)
20000 20000
18000 18000
16000 16000
14000 14000
12000 12000
10000 10000
8000 8000
6000 6000
-3 -2 -1 0 1 2 3 -3 -2 -1 0 1 2 3
6 month SPI (September to April) 6 month SPI (October to March)
Figure 7 The regression between simulated annual pasture yield (kg
DM/ha.year) against the 6 month Standardised Precipitation Index (SPI) for
April to September (RED) and October to March (BLUE) for Ellinbank

12. Summary
• In recent years the number of days that feed supply > feed demand has declined
at all three sites
• There is sufficient variation in historical records to examine adaptation options
• There is an urgent need for whole of farm system analysis to accurately simulate
production, profitability and risk
• There are potentially three levels of adaptation that need be explored
– Adapting within the current feed base
– Modifying the feed base by adopting different forage options
– Adapting to a new farming system

13. Acknowledgments
This project is supported by funding from Dairy Australia, Meat
and Livestock Australia and the Australian Government
Department of Agriculture, Fisheries and Forestry under its
Australia’s Farming Future Climate Change Research Program