South Australian Research and Development Institute
Trial location(s)
Eyre Peninsula, SA
Aims
To report on the combined use of sophisticated biophysical models such as Grass Gro with localised rainfall, temperature and carbon dioxide levels predicted from various climate models out to 2030.
Key messages
The main impacts of climate change by 2030 on grazing livestock enterprises is likely to be shorter growing seasons, greater variability in pasture growth, reduced pasture quality, less available pasture, reduced wool quality and increased variability in farm gross margins. Possible adaptations to alleviate
some of these impacts are;
Minimising the need for supplementary feed by reviewing lambing and calving times, age at first joining, stocking rates and sale times,
Increase flexibility in systems by varying sale times/rules, confinement feeding, movement, more animal trading (core breeding), agistment, matching feed demand to pasture production, and
Improved pasture utilisation by grazing management.
Lead research organisation
South Australian Research and Development Institute
Host research organisation
N/A
Trial funding source
MLA
Related program
Eyre Peninsula Farming Systems
Acknowledgments
Tim Prance, T Prance Rural Consulting for setting up case study scenarios on Eyre Peninsula and all over SA and for reviewing this article.
Mary Crawford and Daniel Schuppan from Rural Solutions, SA for checking simulations and to Mary for setting up Pillaworta workshop. Russell Pattinson the project coordinator for reviewing this article.
Trial source data and summary not available Check the trial
report PDF for trial results.
Climate
Derived climate information
No observed climate data available for this trial. Derived climate data is
determined from trial site location and national weather sources.
Eyre Peninsula SA
SILO weather estimates sourced from https://www.longpaddock.qld.gov.au/silo/
Jeffrey, S.J., Carter, J.O., Moodie, K.B. and Beswick, A.R. (2001). Using spatial interpolation to
construct a comprehensive archive of Australian climate data , Environmental Modelling and Software, Vol
16/4, pp 309-330. DOI: 10.1016/S1364-8152(01)00008-1.