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RESEARCH ARTICLE
Contents Vol 58(10)

How do probabilistic seasonal climate forecasts compare with other innovations that Australian farmers are encouraged to adopt?

Peter Hayman A D , Jason Crean B , John Mullen C and Kevin Parton B
+ Author Affiliations
- Author Affiliations

A SARDI Waite Research Precinct, Adelaide, SA 5000, Australia.

B School of Rural Management, Charles Sturt University, Orange, NSW 2800, Australia.

C NSW Department of Primary Industries, Locked Bag 21, Orange, NSW 2800, Australia.

D Corresponding author. Email: hayman.peter@saugov.sa.gov.au

Australian Journal of Agricultural Research 58(10) 975-984 https://doi.org/10.1071/AR06200
Submitted: 15 June 2006  Accepted: 17 August 2007   Published: 30 October 2007

Abstract

Seasonal climate forecasts (SCFs) from public institutions have been issued to Australian farmers since the late 1980s. Surveys suggest that 30–50% of farmers take seasonal climate forecasts into account when making farm management decisions. Even for the farmers who have adopted SCFs, integrating them into decisions on the farm seems to be a greater challenge than first thought.

We use adoption theory to consider SCFs as an innovation presented to farmers. We consider the problem that SCFs is seeking to solve, the nature of the innovation, and how SCFs compare with other innovations that Australian farmers are encouraged to adopt. We conclude that there are unique challenges presented by the problem of managing climate uncertainty. Demonstrating the relative advantage of a probabilistic SCF is difficult because it is an information-based public good, relatively complex, difficult to trial, and only partially compatible with existing practices. In their favour, SCFs are free or relatively low cost and the information can be applied across different paddocks and different enterprises. We compare and contrast SCFs with other innovations that Australian farmers have been encouraged to adopt over their working life time, such as grain-price forecasts, new wheat varieties, the increased use of nitrogen fertiliser, no-tillage, and precision agriculture.


Acknowledgments

This work was partially funded by the Australian Centre for International Agricultural Research through the project ‘Bridging the Gap between SCF and Agricultural Decision Makers in Australia and the Philippines’ and the Grains Research Development Corporation and Land and Water Australia through the project ‘Communication and Evaluation of MCVP Grains Projects’. Victor Sadras, Melissa Rebbeck, and Bronya Alexander provided useful comments, as did two anonymous referees. We are grateful to Neil Plummer, Bureau of Meteorology, and Barry White, Land and Water Australia, for access to survey data.


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1www.daff.gov.au/content/publications.cfm?ObjectID=C6CB6741-1D69-4F3E-B1DEECBD0653A17E

2Rogers defines innovation as an idea, practice, or object that is perceived to be new by potential adopters. Communication is a process in which participants create and share information with one another in order to reach mutual understanding. It is a two-way process of convergence (or divergence) rather than a one-way, linear act involving the transfer of information from one person to another. Time is an element of the innovation-diffusion process, innovativeness, and the innovation’s rate of adoption. A social system is a set of interrelated units that are engaged in joint problem solving to accomplish a common goal.

3We have not yet explored the implications of this characteristic for the willingness to pay by users for this service and hence for its demand.

4Whopper Cropper is a database of pre-run output files from the daily time-step cropping simulation model, APSIM that can be queried.