Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government system s are diverse and varied. They range from farms, to input supply businesses , to marketing and government policy systems, among others. These systems a re dynamic and responsive to fluctuations in climate. Skill in climate pred iction offers considerable opportunities to managers via its potential to r ealise system improvements (i.e. increased food production and profit and/o r reduced risks). Realising these opportunities, however, is not straightfo rward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested exte nsively. While there has been much written about impacts of climate variabi lity, there has been relatively little done in relation to applying knowled ge of climate predictions to modify actions ahead of likely impacts. Howeve r, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultu ral systems. In this paper, we outline the basis for climate prediction, with emphasis o n the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agric ulture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case s tudies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of som e of the key research and development groups in this field around the world . The case studies include applications at field/farm scale to dryland crop ping systems in Australia, Zimbabwe, and Argentina. This spectrum covers re source-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applica tions of climate prediction in commodity forecasting (wheat in Australia) a nd examine implications on global wheat trade and price associated with glo bal consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplina ry Knowledge in a manner most suited to decision-makers. This approach ofte n includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analyst s and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between informati on demand and supply as well as appreciation of awareness limitations of de cision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to succes sful applications of climate prediction. We consider that advances of the future will be made by better connecting a gricultural scientists and practitioners with the science of climate predic tion. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate pred ictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. A ll rights reserved.