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

Farmer Interest in and Uses of Climate Forecasts for Florida and the Carolinas: Conditional... 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 land allocation. An extensionist is more likely to assess that farmers who produce particular crops can use climate forecasts to be more successful if she works with them. An extensionist whose clientele’s average farm size exceeds 200 acres is more likely to indicate that a farmer can use climate forecasts to improve irrigation management, harvest planning, and crop selection. In addition to serving as references for future work, these conditional assessments almost always provide more nuanced and useful information than unconditional ones about potential farmer interest in and uses of climate forecasts for the three-state region. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Weather, Climate, and Society American Meteorological Society

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

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1948-8335
D.O.I.
10.1175/WCAS-D-16-0057.1
Publisher site
See Article on Publisher Site

Abstract

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 land allocation. An extensionist is more likely to assess that farmers who produce particular crops can use climate forecasts to be more successful if she works with them. An extensionist whose clientele’s average farm size exceeds 200 acres is more likely to indicate that a farmer can use climate forecasts to improve irrigation management, harvest planning, and crop selection. In addition to serving as references for future work, these conditional assessments almost always provide more nuanced and useful information than unconditional ones about potential farmer interest in and uses of climate forecasts for the three-state region.

Journal

Weather, Climate, and SocietyAmerican Meteorological Society

Published: Jan 25, 2018

References

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