Publication Date

Spring 2017

Advisor(s) - Committee Chair

Stephen King (Director), Dominique Gumirakiza, and Linda Brown

Degree Program

Department of Agriculture

Degree Type

Master of Science in Agriculture

Abstract

Currently three systems are used to categorize honey production regions in the United States, one from the United States Department of Agriculture, one from the American Bee Journal used for its monthly U.S. Honey Crop and Markets report, and one from Bee Culture’s monthly regional honey price report. These systems follow political state boundaries and are based upon climate, bee forage, and regional beekeeping practices. While these systems are popular with the general beekeeping community, to our knowledge, their accuracy has not been studied.

Although differing geographic regions can vary in bee forage species availability, states with similar geography and flora should have similar honey production. This is not the case because states within the same honey production region vary in honey production, possibly due to smaller ecotype divisions within the larger honey production regions. Due to this ecotype gradient, some models divide the United States into far more regions based upon ecotypes and disregard political boundaries. While a model based on ecotypes that disregard state political boundaries may be more accurate, it is not currently possible to statistically evaluate them due to how honey production data are collected.

This study developed nine novel regional honey production models that regard political boundaries while attempting to satisfy ecotype similarity. The first four alternative models are based solely on Level II ecoregions and were developed by a best fit manual approach that minimized the number of ecoregions per honey production region. The five remaining models were created using statistical k-means partitioning cluster analysis and are purely data based. Also discussed is a linear regression model produced by Page et al. Differences within and between the models were analyzed using descriptive statistics and ANOVA in order to determine an improved model that describes regional honey production in the United States.

Many of the models, both preexisting and those developed for this study, had insignificant means and are not viable. Of those that had significant means, a k-means cluster based model was determined to be the statistically superior model and can be considered an improved regional honey production model for the United States.

Disciplines

Ecology and Evolutionary Biology | Entomology

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