Norman E. Breuer

Forecast Skill and Farmers' Skills: Seasonal Climate Forecasts and Agricultural Risk Management in the Southeastern United States

During the last 10 yr, research on seasonal climate forecasts as an agricultural risk management tool has pursued three directions: modeling potential impacts and responses, identifying opportunities and constraints, and analyzing risk communication aspects. Most of these approaches tend to frame seasonal climate forecasts as a discrete product with direct and linear effects. In contrast, the authors propose that agricultural management is a performative process, constituted by a combination of planning, experimentation, and improvisation and drawing on a mix of technical expertise, situated knowledge, cumulative experience, and intuitive skill as farmers navigate a myriad of risks in the pursuit of livelihood goals and economic opportunities. This study draws on ethnographic interviews conducted with 38 family farmers in southern Georgia, examining their livelihood goals and social values, strategies for managing risk, and interactions with weather and climate information, specifically their responses to seasonal climate forecasts. Findings highlight the social nature of information processing and risk management, indicating that both material conditions and valuebased attitudes bear upon the ways farmers may integrate climate predictions into their agricultural management practices. These insights translate into specific recommendations that will enhance the salience, credibility, and legitimacy of seasonal climate forecasts among farmers and will promote the incorporation of such information into a skillful performance in the face of climate uncertainty.

The art of the science: Climate forecasts for wildfire management in the southeastern United States

This article illustrates how a wildfire risk forecast evolved iteratively based on stakeholder consultations. An assessment based on phone interviews indicates that such forecasts can assist fire management decisions, such as deployment of human, financial, and material resources and management of forest, timber, and habitats, and public safety. But careful attention to communication, collaboration, and capacity building is key to realizing this potential.

AgClimate: Information and Tools for Decision Making in Agriculture

AgClimate is a response to the need for information and tools on proactive adaptations to seasonal climate variability forecasts in the Southeastern US. Extension agents, agricultural producers, forest managers, crop consultants, and policy makers may use this decision support system to aid in decision making concerning management adjustments in light of climate forecasts. Adaptations include those that maximize yields as well as others that might mitigate potential losses. AgClimate is a web-based DSS that was designed and implemented in partnership with state Extension Services. It has two main components: the front end interface and a set of dynamic tools. The website was deployed in a Linux environment with specific applications and Perl modules installed. The dynamic tools were developed using the PHP web programming language interacting with FLASH movies and MySQL databases. The main navigation menu includes the AgClimate tools, forecasts, crops, forestry, pasture, livestock, and a climate and El Nino section with background information. The AgClimate tools section contains two applications or tools that allow a user to exam the climate forecast for his/her county based on the ENSO phase and to evaluate yield potentials for peanut, tomato and potato in a limited number of counties.

Farmer Interest in and Uses of Climate Forecasts for Florida and the Carolinas: Conditional Perspectives of Extension Personnel

AbstractIn baseline surveys that were conducted in Florida, North Carolina, and South Carolina, extension personnel were asked whether, how, and which farmers would use climate forecasts to manage production and other aspects of their agribusinesses. In making such assessments extensionists use their expertise to account for, the authors assume, net benefits to farmers of the forecasts, given any help that they also expect to provide their clients. Models of conditional probabilities are estimated to show how the assessments depend on the expertise and other characteristics of the extensionist and her clientele. For example, if a person has worked at least 7 years in extension, she is more likely to agree or strongly agree that farmers are interested in using climate forecasts. An extensionist who works with field crop producers is more likely than one who does not to think that a farmer can use climate forecasts to improve planting schedules, harvest planning, crop selection, nutrient management, and lan...