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Document Type

Peer-Review Article

Abstract

Detection of emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), an invasive forest pest, is difficult in low density populations war- ranting continual development of various trapping techniques and protocols. Understanding and predicting landing behavior of A. planipennis may assist in the further development of trapping techniques and improvement of trapping protocols for widespread survey programs in North America. Three multiple regression models were developed using ash tree vigor and crown light exposure to predict the landing behavior of A. planipennis. These models were then used to predict the landing density of A. planipennis at separate sites and in separate years. Successful prediction of A. planipennis capture density at the test sites was limited. Even though the multiple regression models were not effective at predicting landing behavior of A. planipennis, tree characteristics were used to predict the likelihood of A. planipennis landing. Trees predicted as having high likelihood of landing had 3.5 times as many A. planipennis adults/m2 on stem traps than trees predicted as having low likelihood of landing. While the landing density of A. planipennis may not be efficiently predicted, the utility of these predictions may be in the form of identifying trees with a high likelihood of A. planipennis landing. Those high likelihood trees may assist in improving existing detection programs and techniques in North American forests.

Included in

Entomology Commons

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