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Comparison of Trap Designs for Detection of Euwallacea nr. fornicatus and Other Scolytinae (Coleoptera: Curculionidae) That Vector Fungal Pathogens of Avocado Trees in Florida.

Authors :
Kendra, Paul E
Montgomery, Wayne S
Narvaez, Teresa I
Carrillo, Daniel
Source :
Journal of Economic Entomology; Jun2020, Vol. 113 Issue 3, p980-987, 8p
Publication Year :
2020

Abstract

Laurel wilt and Fusarium dieback are vascular diseases caused by fungal symbionts of invasive ambrosia beetles (Coleoptera: Curculionidae: Scolytinae). Both diseases threaten avocado trees in Florida. Redbay ambrosia beetle, Xyleborus glabratus , is the primary vector of the laurel wilt pathogen, Raffaelea lauricola , but in recent years this symbiont has been transferred laterally to at least nine other species of ambrosia beetle, which now comprise a community of secondary vectors. Dieback disease, caused by Fusarium spp. fungi, is spread by shot hole borers in the Euwallacea fornicatus species complex. In this study, we conducted field tests in Florida avocado groves to compare efficacy of four trap designs for detection of Scolytinae. Treatments included an 8-funnel Lindgren trap, black 3-vane flight interception trap, green 3-vane interception trap, white sticky panel trap, and an unbaited sticky panel (control). In two tests targeting E. nr. fornicatus and X. glabratus , traps were baited with a two-component lure (α-copaene and quercivorol). In a test targeting other species, traps were baited with a low-release ethanol lure. For E. nr. fornicatus, sticky panels and black interception traps captured significantly more beetles than Lindgren traps; captures with green traps were intermediate. With ethanol-baited traps, 20 species of bark/ambrosia beetle were detected. Trap efficacy varied by species, but in general, sticky traps captured the highest number of beetles. Results indicate that sticky panel traps are more effective for monitoring ambrosia beetles than Lindgren funnel traps, the current standard, and may provide an economical alternative for pest detection in avocado groves. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00220493
Volume :
113
Issue :
3
Database :
Complementary Index
Journal :
Journal of Economic Entomology
Publication Type :
Academic Journal
Accession number :
143765128
Full Text :
https://doi.org/10.1093/jee/toz311