James W. Mjelde

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential

Sectoral Implications of Farm Program Modifications

The overall and distributional effects of farm programs and selected revisions are examined using a mathematical programming sector model. The model incorporates market distortions caused by price supports, target prices, program participation, deficiency payments and marketing loans. Current farm programs are found to increase producer prices, depress consumer prices, and in turn result in excess production and higher consumption and exports. Domestic and foreign consumers as well as domestic producers are subsidized by farm programs. Social deadweight loss occurs as government payments exceed welfare benefits received by consumers and producers. Society as a whole benefits from reductions in program provisions.

Valuing Water Supply Reliability

Instead of creating water supply systems that fully insulate mankind from climate-imposed water deficiencies, it is possible that for municipal water systems a nonzero probability of water supply shortfall is efficient. Perfect water supply reliability, meaning no chance of future shortfall, is not optimal when water development costs are high. Designing an efficient strategy requires an assessment of consumer preferences pertaining to the reliability of water supply. Contingent valuations of both current and future shortfalls are reported. The consistency of these measures is gauged using an expected utility model. Copyright 2000, Oxford University Press.

Valuing Forecast Characteristics in a Dynamic Agricultural Production System

A dynamic programming model of east-central Illinois corn production is utilized to determine the value of seasonal climate forecasts. Results indicate that the value of climate forecasts is sensitive to economic conditions as well as forecast characteristics. A trade-off between forecast accuracy and lead time exists. A less accurate forecast received earlier in the production process may be more valuable than a more accurate forecast received later. Additional characteristics evaluated include forecast periods of greatest importance, prior knowledge assumptions, and interactions between forecasting adjacent periods.

The forecasting of International Expo tourism using quantitative and qualitative techniques.

Abstract This study predicts the number of visitors to an international tourism Expo to be held in Korea in 2012, an unprecedented event for the host city. Forecasting demand for such a mega-event has received only limited attention in the literature. Unlike most studies forecasting international tourism demand, forecasting Expo demand involves using both quantitative forecasting models and qualitative technique because of data limitations. Combining quantitative techniques with willingness-to-visit (WTV) surveys predicts the Expo demand at 8.9 million visitors. In comparison using the Delphi method, experts predict Expo demand at 6.8 million visitors. For this study, the Delphi method provides more conservative estimates than estimates from combining quantitative techniques with WTV. Policy implications presented are directed toward Expo planners and practitioners in terms of demand and supply side, application of these results in the decision-making process, and future challenges surrounding demand forecasting.

Valuing climate forecast information

Abstract The article describes research opportunities associated with evaluating the characteristics of climate forecasts in settings where sequential decisions are made. Illustrative results are provided for corn production in east central Illinois. These results indicate that the production process examined has sufficient flexibility to utilize climate forecasts for specific production seasons but the value of those forecasts is sensitive to economic parameters as well as forecasts characteristics. Forecasts periods of greatest importance, as well as the relationships between forecast value, accuracy, and lead time, are evaluated.

Use of Seasonal Climate Forecasts in Rangeland-Based Livestock Operations in West Texas

Abstract The potential for west Texas ranchers to increase the profitability of their enterprises by becoming more proactive in their management practices by using seasonal climate forecasts is investigated using a focus group and ecological–economic modeling. The focus group felt forecasts could potentially be used in making decisions concerning stocking rates, brush control, and deer herd management. Further, the focus group raised concerns about the potential misuse of “value-added” forage forecasts. These concerns necessitate a revisiting of the value-added concept by the climate-forecasting community. Using only stocking-rate decisions, the potential value of seasonal forage forecasts is estimated. As expected, the economic results suggest the value of the forecasts depends on the restocking and destocking price along with other economic factors. More important, the economic results and focus-group reactions to these results suggest the need for multiyear modeling when examining the potential impact ...

Using the Southern Oscillation to Forecast Texas Winter Wheat and Sorghum Crop Yields

Abstract Time series models are used to examine the impact of Southern Oscillation (SO) extreme events in estimating and forecasting Texas sorghum and winter wheat yields. It is shown that a significant correlation between the SO events and yield does not necessarily translate into better forecasts. Including SO events in forecasting yields decreases the forecasts mean squared error for winter wheat, but has no significant impact on sorghum forecasts. The most important factor impacting yields over the dataset length (1876–1993 for wheat and 1924–92 for sorghum) is technological change. This change is more important for the period after World War II. Examining the dataset by periods, before rapid technology change and after, indicates the SO impacts crop yields differently between periods.

Biophysical Simulation in Support of Crop Production Decisions: A Case Study in the Black-lands Region of Texas

Economic feasibility of Texas Blacklands corn production in relation to sorghum, wheat, and cotton is studied. Biophysical simulation generated yield data are integrated with an economic decision model using quadratic programming. Given the various scenarios analyzed, corn is economically feasible for the Blacklands. A crop mix of half corn and half cotton production is selected under risk neutrality with wheat entering if risk aversion is present. Corn and grain sorghum production are highly substitutable. Profit effects attributed to changing corn planting dates are more pronounced than profit changes resulting from altering corn population or maturity class.

Preferences and willingness to pay for bird-watching tour and interpretive services using a choice experiment.

This study identifies the activity and experience preferences of bird-watchers and estimates their willingness to pay (WTP) for bird-watching-related ecotourism tour and interpretive services using choice experiment methods. An on site survey was conducted of tourists attending the Cheonsuman International Birdwatching Fair, South Koreas most popular bird-watching festival. Results indicate that respondents are more likely to prefer intermediate length bird-watching courses, interpretive opportunities and services, seeing special birds, and lower admission fees. WTP for bird-watching interpretive services is approximately