|Armstrong, John - Scott|
Submitted to: Journal of Economic Entomology
Publication Type: Peer reviewed journal
Publication Acceptance Date: 11/10/2009
Publication Date: 3/7/2010
Citation: Merrill, S., Gebre-Anlak, A., Armstrong, J.S., Peairs, F.B. 2010. Non-linear degree day models for post-diapause development of the sunflower stem weevil (Curculionidae: Coleoptera). Journal of Economic Entomology. 103(2):302-307. Interpretive Summary: One of the most destructive and economically challenging pests of cultivated sunflower grown for seed or oil production on the central Great Plains is the sunflower stem weevil. After emerging from the base of last years sunflower stalk, the female mates and lays her eggs in the current years planted sunflower stalk, where the larvae migrate down to the base to spend the winter. The following late spring, adults emerge and the life-cycle starts over. The structural damage, disease transmission, and economic loss caused by the larvae living within the stalk are devastating to sunflower yields because the plant will lodge before harvest, making it impossible to harvest the sunflower heads on the soil surface. Our degree day based prediction model, developed over several years, predicts that 5% of adults will emergence from stalks at 262 accumulated degree days (ADD), 50% at 540 ADD, 75% at 657 ADD, and 90% at 777 ADD. Knowing when to expect an emerging population of sunflower stem weevils can greatly improve knowing when to look for them, as well as when to make management decisions like applying insecticides.
Technical Abstract: The sunflower stem weevil, Cylindrocopturus adspersus (LeConte) (Coloptera: Curculionidae), has caused yield losses across much of the western Great Plains. Little is known about the field biology of this pest. Simple prediction models, such as degree day models, are an integral tool for development of C. adspersus management strategies. Using data collected in Colorado, Kansas and Nebraska, we sought for predictable variation between the C. adspersus developmental stages of pupation, adult eclosion, and emergence and accumulated degree days (ADD). Accurate phenological models can time scouting efforts and pesticide applications. The distributions of the relationship between phenological data and ADD fit non-linear, Gaussian distributions better than uniform distributions. Phenological models were developed to describe these distributions for pupation, adult presence within the stalk and adult emergence. The pupation model predicts 50% pupation at 197 ADD and 90% at 307 ADD. The adult eclosion model predicts 50% adult presence in the stalks at 396 ADD and 90% at 529 ADD. A model averaged result from two emergence models predicts that 5% adult emergence from stalks will occur at 262 ADD, 50% emergence at 540 ADD, 75% emergence at 657 ADD, and 90% at 777 ADD. Scouting for adults thus can be initiated at 262 ADD or more. Current chemical controls target adults to percent egg-laying, and applications, therefore, should not be made before this point.