|Allen, Margaret - Meg|
|WALLET, BRADLEY - Automated Decisions, Llc|
|Boykin, Deborah - Debbie|
|SMITH, WAYNE - Oklahoma Cooperative Extension System|
Submitted to: Environmental Entomology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/16/2009
Publication Date: 6/1/2009
Citation: Vogt, J.T., Allen, M.L., Wallet, B., Boykin, D.L., Smith, W.A. 2009. Distribution patterns of imported fire ants (Hymenoptera: Formicidae) on a sheep and goat farm in Oklahoma. Environmental Entomology. 38(3):551-560
Interpretive Summary: Density of fire ant colonies can change abruptly and dramatically within fields and between larger areas, but little is known about environmental factors that favor high fire ant populations. ARS researchers discovered relationships between fire ant density and several environmental factors using freely-available U. S. Geological Survey data as well as aerial imagery. The ability to predict areas with highest fire ant abundance will allow regulatory personnel to target their limited resources toward areas where fire ants are likely to occur, saving time and money.
Technical Abstract: Imported fire ant colonies were quantified in 1000 m2 circular subplots spaced about 125 m apart on a sheep and goat farm in Oklahoma. Mound counts and cumulative above-ground mound volume were used as measures of fire ant population density, and were subjected to regression analyses to determine effects of selected landscape metrics and habitat characteristics. The most important predictive variables correlated with fire ant population density were canopy cover (negative association) and incoming solar radiation (insolation, w*h/m2) at various times of year (positive association). Several predictive variables had small but significant effects on fire ant density, including distance from water, median silt content of soil, elevation, and distance from trees. A model predicting cumulative mound volume/plot with summer solstice insolation, elevation, distance from a cistern, distance from water, canopy cover, and distance from trees was the best and explained about 42% of the variation in population density. Results indicate that remotely sensed data in combination with publicly-available U. S. Geological Survey data may be useful in predicting areas of high fire ant abundance across areas at a field scale.