Entomology, Department of


First Advisor

Gary L. Hein

Date of this Version



Overmyer, L. M. 2020. Factors Influencing Wheat Curl Mite Aceria tosichella Keifer Dispersal. Thesis. University of Nebraska-Lincoln. 1-110.


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska in Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Entomology, Under the Supervision of Professor Gary L. Hein. Lincoln, Nebraska: May 2020

Copyright 2020 Lindsay M. Overmyer


The wheat curl mite (Aceria tosichella Keifer) (WCM) is a vector of three plant viruses to wheat (Triticum aestivum L.) including: Wheat streak mosaic virus (WSMV), Triticum mosaic virus (TriMV), and High Plains wheat mosaic virus. This wheat-mite-virus complex causes significant yield loss in winter wheat across the Great Plains. Management of WCM host plants during the time between wheat harvest and planting of the new wheat crop (the green bridge) is critical in reducing potential risk and loss from this complex. The primary green bridge host, in the central Great Plains, is volunteer wheat. If volunteer wheat is not managed, it can serve as a host in which mite populations can build up and later be dispersed by the wind into neighboring wheat fields, causing virus spread.

Because population dynamics in vegetative volunteer wheat is not well understood, two studies were designed to focus on WCM population buildup and dispersal. Differential mite populations were established in both studies. In a greenhouse study, mite-infested wheat was placed in wind tunnels to evaluate mite dispersal from virus-infected wheat. A field study was also conducted in which mite dispersal (i.e. virus spread) was monitored around a single infested plant in a plot. Results indicated that mite density was the primary factor determining the extent of mite dispersal and virus spread. In addition, temperature impacted the extent of mite population build up and virus spread. Both studies will aid in the development of more accurate predictive risk models of virus risk.

Advisor: Gary L. Hein

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