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Distribution of Zelus Longipes (Hemiptera: Reduviidae) in South

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Distribution of Zelus Longipes (Hemiptera: Reduviidae) in South Distribution of Zelus longipes (Hemiptera: Reduviidae) in South Florida Corn Fields and Its Functional Response to Corn-Infesting Picture-Winged Flies (Diptera: Ulidiidae) Author(s): M. Kalsi, D. R. Seal, G. S. Nuessly, J. L. Capinera, and C. G. Martin Source: Environmental Entomology, 43(5):1223-1234. 2014. Published By: Entomological Society of America URL: http://www.bioone.org/doi/full/10.1603/EN13271 BioOne (www.bioone.org) is a nonprofit, online aggregation of core research in the biological, ecological, and environmental sciences. BioOne provides a sustainable online platform for over 170 journals and books published by nonprofit societies, associations, museums, institutions, and presses. Your use of this PDF, the BioOne Web site, and all posted and associated content indicates your acceptance of BioOne’s Terms of Use, available at www.bioone.org/page/terms_of_use. Usage of BioOne content is strictly limited to personal, educational, and non-commercial use. Commercial inquiries or rights and permissions requests should be directed to the individual publisher as copyright holder. BioOne sees sustainable scholarly publishing as an inherently collaborative enterprise connecting authors, nonprofit publishers, academic institutions, research libraries, and research funders in the common goal of maximizing access to critical research. BIOLOGICAL CONTROLÐPARASITOIDS AND PREDATORS Distribution of Zelus longipes (Hemiptera: Reduviidae) in South Florida Corn Fields and Its Functional Response to Corn-Infesting Picture-Winged Flies (Diptera: Ulidiidae) 1 1,2 3 4 1 M. KALSI, D. R. SEAL, G. S. NUESSLY, J. L. CAPINERA, AND C. G. MARTIN Environ. Entomol. 43(5): 1223Ð1234 (2014); DOI: http://dx.doi.org/10.1603/EN13271 ABSTRACT The milkweed assassin bug, Zelus longipes (L.) (Hemiptera: Reduviidae), is a generalist predator and a potential biological control agent of picture-winged ßies (Diptera: Ulidiidae), which cause considerable economic damage to sweet corn yields in Florida. We studied the potential of Z. longipes as a biocontrol agent of four ulidiid pests in corn Þelds: Euxesta stigmatias Loew, Euxesta eluta Loew, Euxesta annonae F., and Chaetopsis massyla Walker. Within-plant and within-Þeld distributions of Z. longipes and ulidiids and functional responses of Z. longipes to ulidiid prey were determined. Highest numbers of Z. longipes and ulidiids in the R1, R2, and R3 corn stages were generally in the basal or middle leaves at 09:00 h EST, ears at 13:00 h EST, and top and tassel at 17:00 h EST. Hence, there seemed to be a coordinated migration of Z. longipes and ulidiids from the lowest to the highest parts of the corn plant during the day. Within the corn Þeld, aggregated (clumped) distributions were most common for Z. longipes and ulidiids especially in the later R2 and R3 stages based on TaylorÕs power law, IwaoÕs patchiness regression, index of dispersion, and LloydÕs patchiness indices of dispersion. However, predator and prey populations were lower in the R1 stage, and there were inconsistent results for dispersion indices among times of day and between predators and prey. Ulidiid distributions in R1 were mostly regular (uniform) at 13:00 h EST, but aggregated at 09:00 h and 17:00 h. However, Z. longipes R1 distributions were mostly aggregated at 13:00 h, but random or regular at 09:00 h and 17:00 h EST. Handling times for male and female Z. longipes were 1.0Ð1.39 h and 0.67Ð0.97 h, respectively, and each had a type II functional response to E. stigmatias, E. eluta, and E. annonae and consumed about Þve ßies per day. Although the population abundance of Z. longipes can vary between seasons, it appears to be a promising biocontrol agent of ulidiid ßies in corn. KEY WORDS within-Þeld distribution, functional response, milkweed assassin bug, Euxesta, Chae- topsis Since the 1960s, the United States has been the worldÕs oviposit in corn silk, and the larvae have three instars largest producer of sweet corn (Zea mays L.) in metric that feed on corn silk, kernels, and the remainder of tons (Hansen and Brester 2012). The two sweet corn the cob (Seal et al. 1996, Nuessly and Capinera 2010). market production types, fresh-market and processed, Only one maggot and its resulting damage can render were valued at US$836 million and US$336 million, a corn cob (and sometimes a truckload of them) un- respectively, in 2009 (ERS 2010). From 2004Ð2009, marketable (D.R.S., personal communication). Florida led the nation in production of fresh-market Chemical insecticides have been widely used to sweet corn, with 19Ð27% of the annual crop value control adult ulidiid ßies, but the other life stages (Mossler 2008, ERS 2010). Since the early 1900s, in- remain protected inside corn ears. The surviving adult festation by picture-winged ßies (Diptera: Ulidiidae) ßies from adjacent Þelds can reenter treated corn has plagued sweet corn production in the United Þelds after insecticide application (Goyal 2010); States (Barber 1939). Goyal et al. (2010) reported that hence, serious injury to corn ears may occur following Euxesta stigmatias Loew, Euxesta eluta Loew, Euxesta this reinfestation (Seal 2001). Because of the lack of annonae F., and Chaetopsis massyla Walker (Diptera: knowledge on economic thresholds and the failure of Ulidiidae) all attack sweet corn in Florida. The ßies insecticides to provide sufÞcient control of these pests, growers may apply insecticides daily to keep the 1 University of Florida, Tropical Research and Education Center corn marketable (Goyal 2010). However, awareness (TREC), 18905 SW 280th St., Homestead, FL 33031. about detrimental effects of chemical insecticides is 2 Corresponding author, e-mail: dseal3@uß.edu. leading to a more widespread use of nonchemical 3 University of Florida, Everglades Research and Education Center, integrated pest management (IPM) options such as 3200 E Palm Beach Rd., Belle Glade, FL 33430. 4 Department of Entomology and Nematology, University of Flor- biocontrol. Pupal parasitoids of E. stigmatias and pos- ida, Bldg., 970 Natural Area Dr., Gainesville, FL 32611. sibly other corn-infesting ulidiids include Splangia 0046-225X/14/1223Ð1234$04.00/0 ᭧ 2014 Entomological Society of America 1224 ENVIRONMENTAL ENTOMOLOGY Vol. 43, no. 5 spp. (Hymenoptera: Pteromalidae) and an unidenti- responses. A functional response per unit time is the Þed Eurytomid wasp (Hymenoptera: Eurytomidae) change in prey consumption in relation to the change (Ba´ez et al. 2010). Kalsi et al. (2014) surveyed corn in prey density (Hassell 1978, Cogni et al. 2000), and Þelds concurrent with the current study and found is a behavioral response because it involves searching that nonpredatory arthropods other than ulidiids (Coll and Ridgway 1995). A functional response is the found in corn ears included Lobiopa insularis Castel- increase in prey consumed as a function of prey of- nau and Carpophilus lugubris Murray (Coleoptera: Ni- fered, and there are three types of responses: types I, tudilidae), an unidentiÞed Thrips sp. (Thysanoptera: II, and III (Holling 1959a). In type I, the rate of prey Thripidae), mites (Acari), muscoid ßies (Diptera: Mus- consumption linearly increases with increasing prey cidae), roaches (Blattaria), an ant (Hymenoptera: For- availability at all food densities or at food densities up micidae), an earwig (Dermaptera: ForÞculidae), and a to a maximum, beyond which the intake rate is con- booklouse (Psocoptera). Predators of ulidiids in- stant (Holling 1959a,b). Type II is characterized by a cluded Orius insidiosus Say (Hemiptera: Anthocori- decreased rate of intake with increasing number of dae), Anotylus insignitus (Gravenhorst) (Coleoptera: prey offered, and it assumes that the consumer (pred- Staphylinidae), Chrysoperla carnea Smith (Neurop- ator) is limited by its ability to process food (Holling tera: Chrysopidae), Zelus longipes (L.) (Hemiptera: 1959a,b). A type III response is similar to a type II Reduviidae), and potentially other arthropod species because saturation occurs at high prey densities (Hol- (Kalsi et al. 2014). Thus, at least nine nonpredatory ling 1959a,b). However, at low prey densities, the and four predatory species other than the ulidiids relationship of prey consumed to prey available is were found in corn ears concurrent with the current accelerating (more than linearly increasing). The ac- study (Kalsi et al. 2014). O. insidiosus is generally the celerating function results from learning time, prey most common of these predators (Kalsi 2011). It feeds switching, or a combination of both (Holling 1959a,b). on the eggs and larvae and less frequently on the adults The functional response of a predator is important in of corn-infesting ulidiids, and there are few other determining its effectiveness as a biological control known predators of adult ßies (Ba´ez et al. 2010, agent. Feeding by a predator and possibly prey selec- Nuessly and Capinera 2010, Kalsi 2011). tion each depend on the investment of energy ex- Developing a biocontrol program in an agricultural pressed as two key parameters related to functional system requires ecological information on the pest and response: handling time and attack rate (Krebs and its natural enemies (Pearce and Zalucki 2006). Mon- Davies 1993, Juliano 2001). The handling time of a itoring the abundance of predators and prey is often predator for a prey involves the time required to at- a key option in IPM. To effectively determine densi- tack, capture, consume, and digest before the preda- ties, it requires choosing the ideal sample size for torÕs hunger motivates another attack (Holling 1963, minimizing costs yet maximizing effectiveness. An ef- Thompson 1975). The attack rate of a predator is fective sample size can also help to determine if eco- determined by the probability of occurrence of the nomic thresholds have been reached calling for eco- predatorÐprey encounter, the predator attacking on nomic investment in pest control. Knowledge of the this encounter, and the attack resulting in a successful ecology or physiology of a predator helps when eval- prey capture (Holling 1963, Thompson 1975).
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