urn '2'}; (Ir kpllvrr) (.1 '45.. I o) .P .111. .r 5!! u It!!! 592?:13.) I. . (.1... l. :1 II. if. E». $3.331}. SITY LIBRARI TITITTITTITTTTHTTITTTTTT| l 3 1293 0089 HTTHI This is to certify that the thesis entitled USING PHEROMONE TRAPS TO STUDY THE FLIGHT ACTIVITY OF EUROPEAN CORN BORER (LEPIDOPTERAzPYRALIDAE) AS IT RELATES T0 OVIPOSITION AND DAMAGE IN VEGETABLE CROPS presented by JAMES ROBERT JASINSKI has been accepted towards fulfillment of the requirements for M .8. degree in ENTUMOLOGY WJM, Major pKfessorV Date March 194 1993 0-7539 MS U is an Affirmative Action/Equal Opportunity Institution l LIBRARY Michigan State University PLACE IN RETURN BOX to rem TO AVOID FINE S return on or befo a this checkout from your record. DATE DUE DATE DUE DATE DUE 03 i CLETKFUU/ NOV 0 6 200.9 102009 MSU Is An Affirmative Action/Equal Opportunity institution c:\circ\datedm pm3-p.1 USING PI-IEROMONE TRAPS TO STUDY THE FLIGHT ACTIVITY OF EUROPEAN CORN BORER (LEPIDOPTERAzPYRALIDAETAS IT RELATES TO OVIPOSITION AND DAMAGE IN VEGETABLE CROPS By James Robert J asinski A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Entomology 1993 ABSTRACT USING PHEROMONE TRAPS TO STUDY THE FLIGHT ACTIVITY OF EUROPEAN CORN BORER (LEPIDOPTERAzPYRALIDAE) As IT RELATES TO OVIPOSITION AND DAMAGE IN VEGETABLE CROPS James Robert J asinski The European corn borer is a pest of vegetable and field crops throughout the mid-central and eastern states. My goal was to establish a relationship between flight activity and oviposition. Pheromone traps monitored male flight activity at numerous field corn, sweet corn, and pepper sites during 1990-92. Egg mass sampling was also performed at several of the monitored fields in 1991-92. In 1991, second and third flight peaks were large, with egg mass densities and larval infestation moderate to high. In 1992, second flight peaks were much lower, with low egg mass densities and nearly undetectable larval infestation. I found no consistent correlation between flight activity and oviposition. Seasonal temperature accumulation, geographical, and environmental variation may influence flight activity, egg mass density, and damage. At this time, trap catch thresholds have not been established to advise growers when to initiate spray programs. Shred it or Dread it (Ode to the European corn borer) (slightly edited) Across the Midwest, there is a pest, and corn is the crop that it likes to infest. Its eggs and young larvae occur in the whorl, but later, worms migrate to the stalk near the soil. Then before harvest, to prepare for the Fall, they girdle the stems and cause plants to fall. The worms rest snugly intact in the stubble, now safely protected from weather and trouble. If ignored through the Winter and allowed to survive, they emerge in the Spring in numbers that thrive. But all is not lost, for the farmers who act, for there's a method at hand to combat this attack. After the harvest, when most tractors sit idle, remount your John Deere and enter the battle. By plowing your field and shredding the stalks, you'll expose those poor worms to a cruel winter shock. No longer protected in their cozy nest, Mother Nature comes along, and takes care of the rest. So remember this phrase (it's the name of the game), shred it or dread it, and this pest you can tame. -James Wangberg iii ACKNOWLEDGMENTS First and foremost, I would like to thank Ed Grafius for accepting me into his program when my original plans went adrift. He has provided me with a sensible approach to pest management, and inspired me to meet new challenges in the future. I also want to acknowledge Stu Gage; despite our initial disagreements, he is still the person responsible for directing me into the entomology graduate program. I would also like to thank my graduate guidance committee, Drs. Dick Chase, Doug Landis, and Dave Smitley, for providing me with constructive suggestions on my research project, data collection and analysis, and thesis writing. The Chairman of the Department, Mark Scriber, has also been very enthusiastic with his support of me through the summers, equipment for my program, and monies for travel to entomology meetings to broaden my personal and professional horizons. I would also like to give a special mention to Fred Stehr, who always had a moment to chat and a handful of tasty forage to snack upon. Up on the fourth floor, fellow Hagiie members Z man and John (Crimson Head) provided hours Of comic and mostly insane relief. Tony D., Amy, Corey, Jen, the spiders, the snake, and the Madagascar hissing roaches have certainly made memorable and lively the whole grad experience. Special thanks to the Smitley lab Ogre for his numerous lab equipment loans and Mac advice. For friends now involved in Other graduate endeavors, Matt, iv Darcy, and Cathy, the most fun you will ever have awaits in writing your thesis. The entomology bowling team was also a lot Of fun, even though we never won the championship! I wouldn't be able to live with myself if I didn't mention my sports connection, Fred 'who needs the R' Wanna, who just possibly might be the only man more injury prone than I am. Without All Sports Lettering, the Dinosores, and nO corn borers to trap in '92, how else was I going to spend my summer? I would also like to thank Heinz U.S.A., Green Bay Food Company, and the Michigan Cooperative Extension Service for providing my research funding. In addition, I need to individually recognize and personally thank Tom Dudek, Hannah Stevens, Randy Cooper, Paul Marks, Norm Myers, Pete Vergot III, Ted Thar, Jim Lincoln, Jim Neibauer, and Mike Staton; all of whom are agents with the Extension service. Without their enthusiasm and help in collecting information or recruiting growers into the corn borer network, my research could not have been possible. Lastly, I need to let my family know that they gave and listened and understood perhaps just the right amount to help me pick my way through this experience. To my mom, who eternally asks the question, "How did you decide to study bugs?" my only reply is a lifelong fondness for our mutual and numerically superior arthropod friends. To my dad, who's major wish is to have me graduate and move somewhere warm so he can come visit me during the winter, I'm working on it! To my sister Sue, who now thinks I am a bug doctor, I have to say not yet, that would take another five years of study sis! And to my brother Joe, who still thinks I should have gone into engineering for the big bucks, I think its too late to change my major now! TABLE OF CONTENTS LIST OF TABLES ...................................................................................... vii LIST OF FIGURES .................................................................................................. xi INTRODUCTION ....................................................................................................... 1 CHAPTER 1 Flight activity of the European corn borer, Ostrinia nubulalis (Hiibner) in 1990, 1991, 1992 .......................................... 13 Materials and Methods ..................................................................................................... 17 Results and Discussion ..................................................................................................... 24 Conclusions ...................................................................................................................... 46 CHAPTER 2 Relating flight activity of the European corn borer,03m'nia nubilalis (Hiibner), to egg mass density at several sites in 1991 and 1992 ............................................................................................ 48 Materials and Methods ..................................................................................................... 51 Results and Discussion ..................................................................................................... 56 Conclusions ...................................................................................................................... 65 CONCLUSIONS ........................................................................................................ 67 APPENDIX .................................................................................................................. 72 Seasonal flight activity curves LITERATURE CITED ........................................................................................... 94 Vi CHAPTER 1 ' TABLE 1A TABLE 13 TABLE 1C TABLE 2A TABLE 2B TABLE 2C LIST OF TABLES Counties, weather stations, sites, and crops monitored during the European corn borer flight activity network in 1990 ........................... 20 Counties, weather stations, sites, and crops monitored during the European corn borer flight activity network in 1991 ........................... 21 Counties, weather stations, sites, and crops monitored during the European corn borer flight activity network in 1992 ........................... 22 Mean trap catch and its associated standard error to mean ratio for all eligible trapping sites in 1990 .............................................................. 25 Mean trap catch and its associated standard error to mean ratio for all eligible trapping sites in 1991 .............................................................. 26 Mean trap catch and its associated standard error to mean ratio for all eligible trapping sites in 1992 .............................................................. 27 Vii TABLE 3A TABLE 3B TABLE 3C TABLE 3D TABLE 4 TABLE 5 TABLE 6 TABLE 7 Second flight initiation and peak activity of European corn borers caught at each site in 1990 ................................................................... 33 Second flight initiation and peak activity Of European corn borers caught at each site in 1991 ................................................................... 34 Third flight initiation and peak activity Of European corn borers caught at each site in 1991 ............................................................................... 35 Second flight initiation and peak activity of European corn borers caught at each site in 1992 ................................................................... 36 Mean i standard error of second flight initiation and peak activity for 1990 ...................................................................................................... 38 Mean 1: standard error Of second flight initiation and peak activity for 1991 OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO 38 Mean -_i-_ standard error of third flight initiation and peak activity for 1991 ...................................................................................................... 38 Mean i standard error Of second flight initiation and peak activity for 1992 ...................................................................................................... 39 viii TABLE 8 TABLE 9 TABLE 10 Mean 1: S. E. of second and third flight initiation and peak activity at the statewide level for 1990, 1991, and 1992. Temperature for flight initiation was accumulated from March 1 and May 14 to account for photoperiod differences. A mean for all sites involved during 1990-92 is also shown ........................................................................................ 39 Mean 3; standard error Of second flight initiation and peak activity at multi-year sites from 1990-92 .............................................................. 39 Mean i S. E. of second flight initiation and peak activity by climatological division from 1990-92. Temperature for flight initiation accumulated from March 1 and May 14 to account for phOtOperiod differences ............................................................................................ 4O ix CHAPTER 2 TABLE 11 TABLE 12 TABLE 13 A TABLE 13 B TABLE 14 A TABLE 14 B 1991 European corn borer egg mass sampling sites ............................ 52 1992 European corn borer egg mass sampling sites ............................ 55 Weekly European corn borer egg mass per plant sampling results froom August 5 to September 2, 1991 ................................................ 59 P and F values Of weekly egg mass means at all sites from August 5 to September 4, 1991. Only Morrison and SWMREC are significant (One way ANOVA, p<0.05) ................................................................ 59 Correlation of flight activity against egg mass laying at all sites in 1991. None were significant (p<0.05) ................................................ 63 Correlation of flight activity lagged one week against egg mass density at all sites in 1991 ................................................................................. 63 LIST OF FIGURES CHAPTER 1 FIGURE 1 Weekly mean trap catch frequency distribution Of European corn borer moths at all sites in 1990 and 1991 ...................................................... 28 FIGURE 2 Weekly mean trap catch frequency distribution of European corn borer moths at all sites in 1992. Total mean trap catch frequency distribution for 1990-92 is also shown .................................................................... 29 FIGURE 3 Linear regression of total number of European corn borer trapped during the season against the total number of field corn acres in 1990, 1991, and 1992. None are significant (p<0.05) ................................... 44 FIGURE 4 Linear regression of second and third peak flights Of European corn borer moths caught at each site in 1990, 1991, and 1992, against total number of field corn acres. Only the third flight Of 1991 is significant (p=0.05) ................................................................................................ 45 CHAPTER 2 FIGURE 5 FIGURE 6 1991 Seasonal flight activity curves for European corn borer in Gratiot (A), Berrien (B), and Van Buren (C) counties ........................ 57 1992 Seasonal flight activity curves for European corn borer in Gratiot (A), Newaygo (B), and Kent (C) counties ............................... 61 xii APPENDIX FIGURES 7 A & B FIGURES 7 C & D FIGURES 8 A & B FIGURES 8 C & D FIGURES 8 E & F 1990 Seasonal flight activity curves for European corn borer in Berrien (A) and Kent (B) counties. Degree day accum- ulation (base 50' F) shown beside second flight peaks .......... 72 1990 Seasonal flight activity curves for European corn borer in Macomb (C) and Monroe (D) counties. Degree day accum- ulation (base 50° F) shown beside second flight peaks .......... 73 1991 Seasonal flight activity curves for European corn borer in Allegan (A) and Berrien (B) counties. Degree day accum- ulation (base 50° F) shown beside second and third flight peaks ....................................................................................... 74 1991 Seasonal flight activity curves for European corn borer in Gratiot (C) and Kent (D) counties. Degree day accum- ulation (base 50' F) shown beside second and third flight peaks ....................................................................................... 75 1991 Seasonal flight activity curves for European corn borer in Macomb (E) and Manistee (F) counties. Degree day accum- ulation (base 50° F) shown beside third flight peak ................. 76 xiii FIGURE88G&H FIGURES 8 I& J FIGURES 8 K & L FIGURES9A&B FIGURE 9 C FIGURES 9 D & E 1991 Seasonal flight activity curves for European corn borer in Monroe (G) and Muskegon (I-I) counties. Degree day accumulation (base 50' F) shown beside second and third flight peaks ............................................................................. 77 1991 Seasonal flight activity curves for European corn borer in Newaygo (I) and Oceana (J) counties. Degree day accumulation (base 50' F) shown beside second and third flight peaks ............................................................................. 78 1991 Seasonal flight activity curves for European corn borer in Oceana (K) and Saginaw (L) counties. Degree day accumulation (base 50’ F) shown beside third flight peaks...79 1992 Seasonal flight activity curves for European corn borer in Allegan (A) and Berrien (B) counties. Degree day accumulation (base 50’ F) shown beside second flight peak.80 1992 Seasonal flight activity curves for European corn borer in Gratiot (C) county. Degree day accumulation (base 50" F) shown beside second flight peak ............................................ 81 1992 Seasonal flight activity curves for European corn borer in Ingham (D) and Kent (E) counties. Degree day accu- mulation (base 50’ F) shown beside second flight peak ........ 82 xiv FIGURES 9 F & G FIGURES9H&I FIGURE 10 A FIGURE 10 B FIGURE 10 C FIGURE 10 D 1992 Seasonal flight activity curves for European corn borer in Macomb (F) and Midland (G) counties. Degree day accum- ulation (base 50' F) shown beside second flight peak ............. 83 1992 Seasonal flight activity curves for European corn borer in Monroe (H) and Newaygo (1) counties. Degree day accum- ulation (base 50‘ F) shown beside second flight peak ............. 84 1990, 1991, and 1992 multi-year seasonal flight activity curves for European corn borer in Bay county. Degree day accumulation (base 50' F) shown beside second flight peak.85 1990, 1991, and 1992 multi-year seasonal flight activity curves for European corn borer in Ingham county. Degree day accumulation (base 50° F) shown beside second and third flight peaks ............................................................................. 86 , 1990, 1991, and 1992 multi-year seasonal flight activity curves for European corn borer in Oceana county. Degree day accumulation (base 50' F) shown beside second and third flight peaks ............................................................................. 87 1990, 1991, and 1992 multi-year seasonal flight activity curves for European corn borer in Oceana county. Degree day accumulation (base 50" F) shown beside second and third flight peaks ............................................................................. 88 FIGURE 10 E FIGURE 10 F FIGURE 10 G FIGURE 10 H FIGURE 11 1990, 1991, and 1992 multi-year seasonal flight activity curves for European corn borer in Ottawa County. Degree day accumulation (base 50' F) shown beside second flight peak.89 1990, 1991, and 1992 multi-year seasonal flight activity curves for European corn borer in Saginaw county. Degree day accumulation (base 50' F) shown beside second and third flight peaks ............................................................................. 90 1990, 1991, and 1992 multi-year seasonal flight activity curves for European corn borer in Van Buren county. Degree day accumulation (base 50' F) shown beside second and third flight peaks ............................................................................. 91 1990, 1991, and 1992 multi-year seasonal flight activity curves for European corn borer in Van Buren county. Degree day accumulation (base 50‘ F) shown beside second and third flight peaks ............................................................................. 92 Site distribution of the European corn borer monitoring network in Michigan's lower peninsula, 1990-92. The region each site belongs to is also shown on the distribution map....93 INTRODUCTION History The European corn borer, Ostrim'a nubilalis (Hiibner), has been a pest on various field _ and vegetable crops in the United States and Canada for nearly eighty years; This insect was first reported in Michigan around 1921 (Caffrey and Worthley 1922). The corn borer has traditionally been a concern for field and sweet corn growers, although it has managed to expand its host range to vegetable and fruit crops. The European corn borer was known as Pyrausta nubilalis (Hiibner) in the literature prior to the 1950's. A revision of this genus by Marion (1957) provided several arguments for a shift away from Pyrausta to the more recent Ostrinia. These arguments were accepted, and henceforth has been referred to as Ostrinia nubilalis (Hiibner) in communication and the literature. There are several reported time tables for the importation of this insect into North America. The confusion lies mostly in the lag time between first Observance to the outbreak of the insect, to its recognition as a pest. Vinal (1917) appears to have provided the first Official report of this novel pest in North America, near Boston, Massachusetts. This insect was known however, to Canadian farmers as far back as 1910 near Port Stanley, Ontario, but never officially reported until 1920 (McLaine 1922). Most researchers agree it arrived on the East coast through shipments of broom corn from Hungary and Italy. Felt (1922) believes there is evidence for multiple importation's because it was initially reported along the western edge of New York bordering Lake Erie, and in Boston, Massachusetts. The concept that different strains were also brought to the North America equates very well with facts such as variable voltinism and host plant ranges for different populations of moths. Beck and Apple (1961) showed that there are two geographical races between Canada and the US. based on larval diapause characteristics. The original populations of corn borers in New York were univoltine and those in Massachusetts bivoltine. Barber (1925) noticed a small percentage of the first generation New York corn borer pupating in the summer, producing a second generation, while Caffrey and Worthley (1927) also noted some tendency for diapause in the normally bivoltine Massachusetts population. These observations illustrate that each population can exhibit voltine plasticity based on climatic conditions (Beck and Apple 1961). Development As with most insects, the European corn borer life cycle is linked to abiotic factors which determine its rate of development. Temperature, humidity, and photoperiod all affect survival and development of eggs, larvae, and pupae. Gravid females begin the cycle by laying egg masses, each composed of 15-30 eggs, mostly on the underside of host plant leaves (Showers et al. 1989). Eclosion rates can be drastically affected by two factors, low humidity and cool temperatures. At 65% relative humidity, egg hatch under optimal temperatures reaches only 25 i 16%, while 85% relative humidity results in 78 i 3% egg hatch (Godfrey and Holtzer 1991). Increasing temperatures at constant humidity corresponds to higher percentages of egg hatch, but above 33° C a steep reduction in eclosion is observed (Godfrey and Holtzer 1991). Showers et a1. (1989) has found that under field conditions (varying temperatures and humidities) egg hatch can occur in only 3-7 days. The economically destructive phase of the life cycle is the larval stage; adults are not believed to require food, just water. Under optimal conditions, larvae reared in the lab can mature through five instars in as little as 17 days (Calvin et al. 1991). Depending upon environmental factors, the final instar either pupates or enters diapause. If it is going to pupate, the pupae can spend between 4 to 33 days in that stage under lab conditions before emerging, due to geographic variation in populations (Calvin et al. 1991). If conditions trigger the diapause response, then it will overwinter as a fifth instar, eventually pupating and emerging in the spring. Dispersal The dispersal of the European corn borer after introduction into the United States is quite remarkable. Both initial populations (western New York and Boston, Massachusetts) expanded slowly and met near the border between the two states in the I mid 1930's (Palmer et al. 1985). From here it is thought that both populations underwent potentially extensive gene pool exchanges, resulting in strains capable Of modifying their voltinism as the environmental conditions changed during their range expansion to the west, north and south (Palmer et al. 1985, Kelsheimer and Neiswander 1931, Neiswander 1947, Bottger and Kent 1931, Ficht and Hienton 1939, Vance 1939). Spread Of the now mixed population was very rapid westward, owing its success to preferred habitat in the corn belt and slight variation of photoperiod and temperature. The spread southward was slowed due to extended photoperiods and increased temperatures which were different from what it had adapted to in the northern latitudes (Palmer et al. 1985). Voltinism There are three main ecotypes of corn borers: Northern, Central, and Southern, based on voltinism capability (Showers et al. 1975). The Northern type produces 1 complete generation per growing season, and is commonly found in Quebec, Minnesota, and Wisconsin. The Central type can produce 2 complete generations per growing season and is found mostly in Iowa, Ohio, Ontario, and Nebraska. The Southern ecotype can produce 3+ complete generations per growing season and is found in Alabama, Georgia, and Missouri (Showers 1975b). Interestingly enough, very little direct research has been reported on corn borer voltinism in Michigan, which contains a mixture of the Central and Northern types. TO avoid ambiguity in this manuscript, the following definitions of generation will be adopted from Jackson and Peters (1963). A complete generation assumes all individuals complete all stages of development; an incomplete generation assumes no individuals complete all levels of development; and a partial generation refers tO a population where a certain proportion of individuals complete all stages Of development. In Michigan, a voltine transition zone passes through the heart of the lower peninsula, with Northern ecotype corn borers above it and Central ecotype corn borers below it. According to Palmer et al. (1985) and Showers et al. (1989) there is a univoltine race in the upper peninsula and northern half of the lower peninsula, a bivoltine race in the southern-most two tiers Of counties in the lower peninsula, and a band of 1-2 complete generation corn borer sandwiched between them. Our research has shown that at least 2/3 Of the lower peninsula is capable of producing 2 adult flights (2 complete generations) leaving final instars in field refuse and stubble at the end of the season. In years with elevated temperatures such as 1991, 3 adult flights (3 complete generations) were observed at most locations in the lower peninsula, again leaving final instars in field refuse at the end of the season. Our pheromone trapping research in conjunction with the Michigan State University field crop research project has provided mounting evidence that a univoltine population exists in the thumb region of east central Michigan (Doug Landis, pers. com.). This allopatric distribution throughout Michigan Of various strains of corn .— borer may be the result Of invasion from Canada of the Northern ecotype and invasion from southern states of the Central ecotype. Diapause is directly linked to voltinism, and is induced by two factors, increasing scotophase (dark photoperiod) and decreasing temperature. Arbuthnot (1949) was among the first to realize the importance of temperature in estimating the number Of corn borer generations. Later Mutchmor and Beckel (1959) elucidated the effecr Of photoperiod on diapause. Beck (1962) showed that it was actually increasing scotoperiod which triggered diapause. The ability of the corn borer to increase the number of generations it undergoes as it enters its southern range is a function of avoiding obligatory diapause. In lower latitudes, the Southern strain is prevented from becoming a year round pest due to diapause restrainsts resulting from abundant light and temperature, which theoretically could allOw for continuous generations (Showers 1979). Pheromone Races Within the three major corn borer ecotypes, Northern, Central and Southern, there are also pheromonal distinctions that further divide their populations based on the production and response Of moths to various isomeric blends Of ll-tetradecenyl acetate, first identified by Klun and Brindley (1970). Female moths emit this 6 chemical, which is a mating (sex) pheromone to attract con-strain specific males. The strain designations are based upon the ratio of transzcis isomers; moths responding to 97:3 mixture are referred to as "Z" or "Iowa" strain, while those responding to a 3:97 isomer mixture are designated as "E" or "New York" strain. Of the two, the Iowa strain is the most commonly found strain in both North America and Europe, with the New York strain predominantly confined to Italy and North eastern United States (Klun 1975). One hypothesis Offered by Klun and Huettel (1988) for the limited distribution of the New York strain states that there is an unidentified disadvantage inherent to individuals who possess E strain alleles. There appears to be very little cross attractiveness between the two strains, i.e., New York females attract predominantly New York males, with the converse being true Of the Iowa strain. In areas of sympatry however, hybridization between the two strains is capable of producing limited yet novel ratios of transzcis isomers (Roelofs et a1. 1985). There is no strict association between voltine strains and pheromone races. It was soon discovered that the two strains Of corn borers had different host plant ranges. Originally, the Iowa strain corn borer had a fairly restricted plant host range, being found predominantly in field and sweet corn. Currently it is also considered a pest in popcorn, peppers, snap beans, and potatoes, while being more of a nuisance insect in apples, cotton, lima bean, soybean, sorghum, tomato and onion in the North central region from time to time (Showers et al. 1989). Felt (1922) reported the strain of corn borer in Massachusetts was found to feed on over 170 different plant species, including a range of fruits and vegetables, an early indication of the polyphagy of this insect. We have now come to identify this as the New York strain. The extensive host range of both strains may cause concern for vegetable and fruit growers in the midwest who have yet to deal with the corn borer in their overall insect management strategy. In Michigan, corn borer is recognized as an economically important pest in field corn, sweet corn, peppers, and snap beans. In 1990 and 1992, we monitored for New York strain moths in addition to the Iowa strain corn borers (a concern to growers due to expanded host range) at several locations and have yet to detect a significant New York strain population in Michigan. It appears the Iowa strain is dominant in Michigan. ' The basic habits for both male and female adult corn borers include resting during the day on vegetation in crop fields, weedy field edges, or adjacent grassy areas. These grassy areas are referred to as action sites; places where mating is known to occur. Foxtail grasses, Setaria sp., typically dominate these areas along with other weeds and vegetation (Showers et al. 1976, Sappington & Showers 1983, DeRozari et a1. 1977). At dusk, the females become active and fly from neighboring refugia to action sites nearby the crop field. Females that have been previously mated move to adjacent crop fields to begin ovipositing egg masses. Upon finishing for the night, they either fly back to the action site or to another field, perhaps searching for the proper microclimate or refugia (Sappington and Showers 1983). Meanwhile, virgin females continue to collect in grassy areas where dew formation occurs early (DeRozari et al. 1977). The virgin female moths appear to be seeking free water (dew) in these areas in order to become sexually active (DeRozari et al. 1977) while at the same time increasing their fecundity (Kira et al. 1969). The females then begin to release the pheromone, which allows males to track the pheromone plume upwind to the action sites where the receptive mates are waiting (Lingren 1979, Showers et a1. 1980). 8 Showers et al. (1974) examined the abdomens of mated females and determined almost all only mated once, and that egg deposition could begin within 48 hours after copulation. After mating, the female usually remains in the action site close to the crop field until she is ready to oviposit. Males continue to compete in the action sites during the night for the remaining calling virgin female moths, and may rest there in the grassy shelters during the day. Monitoring European corn borer populations have been monitored in various ways. Initially, scouting fields for eggs and larvae infested plants was the most common way to estimate insect pressure, but later, monitoring using black light traps was investigated for their potential utility. Black light trapping was used because it could attract both male and female adult moths of many economically important insects. Developing rules and thresholds based on black light trap counts also helped growers manage their fields or alerted them when to begin field scouting. But black light trapping attracted a wide array of insects, which meant it took additional time and experience to sort through and properly identify the collected insects. Regular trap maintenance and the need for an electrical power supply made it cumbersome set up and to operate. Clearly a better way was needed. It soon became apparent that the system of tracking moth populations for management purposes was more complicated than merely setting up a black light and noting the initial and peak flight activity. When Klun and Brindley (1970) discovered synthetic pheromone blends which could attract corn borers, pheromone trapping was explored as a corn borer monitoring technique. Water pan, sticky, and mesh traps with synthetic lures were designed to mimic a calling female, thereby attracting and capturing males who were sexually active. Pheromone trapping does have several 9 advantages over black light trapping. It eliminates sorting through large, mixed insect samples by attracting only the species of interest, it does not require a power source and requires very little maintenance during the season. The major drawback of pheromone trapping is its inability to directly characterize the female moth population around the field. The number of males caught per time interval is a relative measure of activity at that site, which can be used for pest management decisions. It is currently thought the greater the activity, the higher the potential for oviposition and damage; the lower the activity, the lower the suspected oviposition and damage. There are a few uncertainties associated with pheromone trapping. Oloumi-Sadeghi et al. (1975) believes the traps are poor competitors for males as compared to virgin females until the abundance of calling females is lessened. At this point however, oviposition has already occurred to a significant extent before peak activity is detected in the pheromone traps. Subsequent work by Fletcher-Howell et al. (1983) states that pheromone traps offer a reliable technique for monitoring ECB. It appears as though no definite agreement about the usefulness of these traps as a management tool is yet established. Seasonal meteorological events coupled with heterogeneous insect populations undoubtedly plays a critical role in producing a reliable pheromone trapping system. When pheromone trap results are compared to results of black light traps, a few interesting differences are apparent. Oloumi-Sadeghi et al. (1975), Durant et al. (1986), and Legg and Chiang (1984b) all found that peak black light trap catches preceded peak pheromone sticky trap catches by up to seven days. Another possible explanation for pheromone traps detecting moth activity after the black light traps is that males are not sexually active immediately after emerging. In most cases, the black light trap caught greater numbers of moths compared to pheromone trapped 10 moths, as well. Kennedy and Anderson (1980) found black light trapping more reliable than pheromone trapping because it can detect fluctuations in seasonal moth activity much more readily. Legg and Chiang (1984b) realized the inability to measure female moth activity was the weak link in the system of using pheromone traps to determine or predict oviposition in corn fields. They attacked the problem by trying to establish two predictive models. The first model was based on pheromone trapped males correlated with oviposition and the second correlated pheromone trapped males, black light trapped females, and oviposition. No relationship was found to exist between pheromone trapped males and oviposition (eliminating the first model), but a correlation between pheromone trapped males and black light trapped females was significant if the male flight was lagged one week. Legg and Chiang (unpublished) suggested that the positive relationship between black light trapped females and egg mass density did exist. This' allowed for a two step predictive model to be constructed whereby pheromone trapped males can be correlated to black light trapped females which in turn can be related to egg mass density. The loss of synchronicity between the two trap systems suggests corn borer mating behavior, weather, and individual field characteristics can all be confounding factors (Legg and Chiang 1984b). Monitoring crop fields is a major component to any insect management program. Sampling methodology exists for corn borer egg masses on corn (Calvin et a1. 1986 and Linker et al. 1990) and for larval infestation (Ferro and Weber 1988, Showers et al. 1989). Dively (unpublished) and Ferro and Weber (1988) have also established flight thresholds for pheromone trapped insects in order to guide spray schedules, particularly with the corn earworm, Helicoverpa zea (Boddie), and the EurOpean corn borer, Ostrinia nubilalis (Hiibner). These management decision "keys" are constructed 11 upon trap catch per time interval above or below a temperature threshold. These threshold guidelines are currently set so low that essentially they function as an insect presence or absence indicator, with management action taken immediately upon detection. This research project is broadly aimed at developing a management system using pheromone traps in Michigan for field corn, sweet corn, and peppers. The extent to which pheromone trapping is currently utilized by growers involves only establishing initial flight and peak flight activity; as no guidelines are currently available in Michigan to dictate spray intervals based on trap catches. Objectives The aim of this research is to establish baseline information about European corn borer flight activity and give direction to future research efforts. This insect poses a problem to both food processing companies and vegetable growers, producing a negative company image if found as a contaminant or causing economic loss for the grower who's shipment is rejected due to larval infestation. The eventual goal is to better manage and understand corn borer biology as it exists in Michigan, and to reduce chemical input onto a commodity if it is not warranted. Specifically the objectives are: mm: 1. To note the weekly inter-trap catch variation at the same site. 2. To determine if moth catch bias exists between outer and middle traps placed in a linear arrangement. 3. To compare flight activity between monitoring sites during the same season. 4. To compare flight activity at the eight multi-year sites sampled over a three year period. 5. To associate flight activity events such as flight initiation and peak flight with accumulated degree days. 12 6. To correlate the seasonal total of moths trapped and the peak flight activity with acreage of field corn produced in the same county. Charm 1. To determine the relationship between flight activity and egg mass sampling at selected sites. 2. To determine if female corn borers prefer to oviposit near the edge or interior of a field. CHAPTER 1 Flight activity of the European corn borer Ostrinia nubilalis (Hiibner) in 1990, 1991, and 1992 Introduction The European corn borer (ECB) is a widely distributed and polyphagous insect across the country. It has been known to feed on over 170 plants, such as field corn, sweet corn, peppers, snap beans, cotton, and apples, to name a few (Felt 1922). Control of this insect is challenging due to various combinations of voltine and pheromone strains. In order to assess the presence of egg masses, larvae, or adults, various sampling protocols have been developed ranging from inspecting individual plants to black light trapping (Legg and Chiang 1984, Showers et al. 1989, Ferro and Fletcher-Howell 1985, Elliot et a1. 1978). One of the most recent methods employed for detecting corn borer moths is pheromone trapping (Kennedy and Anderson 1980, Boivin et al. 1986, Fletcher-Howell et al. 1983). By placing a synthetic lure in a cone shaped mesh trap, male moths are attracted to and eventually captured in the trap. The number of male moths caught per time period (such as one week) gives a relative measure of corn borer moth activity at that site. In Michigan, the overwintering population of corn borer larvae in corn stubble and other plant stems complete their development in the spring and reach peak flight activity at the end of May to mid June. The second flight peak usually occurs in mid August. Both flights produce larvae which can infest and damage field corn, sweet corn and other vegetables such as peppers and snap beans. Most larvae produced by the second adult flight will enter diapause and complete their development in the following spring. Under 13 14 unseasonably warm conditions, corn borer flight can peak three times; late May to early June, late July to early August, and again in early September. Larvae produced by the third flight form an incomplete third generation and will not mature into adults until next season. The potential for damage to occur in sweet corn and other vegetables is much greater under these conditions, through earlier exposure to injury and an additional generation of corn borers. Adequate crop protection may require a more intense or extended insecticide program. The ability to reliably measure flight activity and predict egg and larval development is important for crop protection and insect management strategies. There are "rules of thumb" for estimating initial egg mass deposition, length of various instars, and timing of peak flights. Apple (1952) and Jarvis and Brindley (1964) found that overwintering population of com borers emerge between 397 and 526 (average ca. 450) accumulated degree days base 50' F (DD50) and within days begin laying egg masses. Each subsequent generation requires approximately 1000 DD50 to complete its development with'the first complete generation beginning to emerge around 1450 DD50, and the second complete generation around 2450 DD50. Showers et al. (1989) agrees that about 1000 DD50 are required to complete one generation of corn borer development. However, they suggest waiting 100 DD50 after the first moth is detected via pheromone or light trap in the spring to predict peak egg eclosion. To determine which system works best in Michigan would require an intensive field scouting project to estimate population density, i.e., searching plants for corn borer egg masses and larvae, and tracking adult populations very early in the season. Since the introduction of synthetic pheromones to trap and detect agricultural pests, it has become much easier to collect information about population activity and adult emergence throughout the season. Over the past several years we have used pheromone trapping to 15 develop an empirical relationship between flight activity and temperature accumulation to validate or modify our current understanding of when and to what scale do flight events occur. The main limitation to this type of trapping system is its inability to capture female moths, which has implications when trying to predict ovipositional trends directly from male moth flight. These traps attract only mate seeking males, but competition from sexually receptive calling females may interfere with or delay trap catch. As a result, Oloumi-Sadeghi et al. (1975) believes pheromone trap catch is a response dependent upon the number of calling females. In the past, black light traps have been used to determine male and female activity within emerging populations near crop fields. Black lighting operates for the most part independent of direct sexual behavior, relying instead on the dazzle effect (Robinson 1952). According to this theory, each insect species has its own "zone of attraction", a radius around the light trap that if it strays into will be drawn into the trap. Usually this distance is 10 m, but no specific zone has been determined for the European corn borer. Attraction to black light traps may also be affected by temperature, wind, moonlight, and objects which may pose as obstructions. Trapping by either method tries to reach the same goal of identifying a point or threshold where some sort of action decision, such as spraying, should be enacted to prevent crop loss. There is a corn borer flight threshold published for pheromone trapping of ECB in Massachusetts (Ferro and Weber 1988), based on the first male trapped in the season. Given this level of flight activity (initial detection) there is a predetermined spray guideline which the grower can elect to follow in an effort to safeguard the crop from corn borer infestation. In reality, with such an extremely sensitive and low threshold, 3 minimal spray schedule would always need to be maintained, even during periods of the lowest levels of activity. While this might be appropriate for sweet corn because all stages of the plant are susceptible to infestation, it may not be a suitable method for peppers or other vegetables if only the fruit is attacked. The maintenance of a spray 16 program throughout the entire season after initial moth detection is undoubtedly and perhaps unnecessarily expensive to the grower. By establishing and fine tuning pheromone trap thresholds, perhaps a more discriminating use of pesticides will result, providing an added level of safety to the grower, environment, and consumer. The extension of ECB trap thresholds beyond their use as indicators of presence or absence of moths (current monitoring system in Massachusetts) with subsequent spray recommendation is a goal we are striving to meet. Our long term goal is to implement the use of pheromone traps as pest management tools to allow growers to respond appropriately to varying levels of corn borer activity. The objectives of this study are: 1. To note the weekly inter-trap catch variation at the same site 2. To determine if moth catch bias exists between outer and middle traps placed in a linear arrangement 3. To compare flight activity between monitoring sites during the same season 4. To compare flight activity at the eight multi-year sites sampled over a three year period 5. To associate flight activity events such as flight initiation and peak flight with accumulated degree days 6. To correlate the seasonal total of moths trapped and the peak flight activity with acreage of field corn produced in the same county 17 Materials and Methods Trap Placement and Location At most monitoring sites, three traps (Heliothis mesh traps, Scentry Incorporated, Buckeye, AZ) baited with an Iowa strain Pherocon ‘9 pheromone lure (T récé Incorporated, Salinas, CA) were placed within '10 m of the crop being monitOred. The remaining monitoring sites had 1, 2, or 4 traps per field. Traps were located in weedy areas (potential mating areas) adjacent to the crop field, about 30 m apart. The plant composition in the weedy border areas ranged from predominantly grasses to mixtures of grasses and broadleaf plants. The density of grasses and broad leaf plants in these areas varied according to site. The preferred trap placement habitats were the fairly dense and grassy areas, especially foxtail grasses, Setaria spp., aid corn borer mating (DeRozari et al. 1977 and Schurr 1970). Where possible, the traps were placed so the predominant wind direction (westerly) would blow the pheromone trail out across the potential mating area. Each trap was secured to a 2.1 or metal fence post that had been driven into the ground. The bottom of the trap was approximately 30 cm above the vegetation canopy. As the season progressed it was necessary at some sites to either trim vegetation at the base of the trap or move the trap higher on the post. In all three years of the study, the importance of proper trap placement in relation to the field and vegetation composition beneath the trap was stressed to the participators of the network (growers and Extension Agents ). In 1990, Ed Grafius inspected Bay, Oceana, Ottawa, Saginaw, and Van Buren counties to insure consistency of trap placement in the field. In 1991, I inspected sites in Berrien, Gratiot, Ingham, Oceana, Saginaw, and Van Buren counties to assure traps were placed in suitable habitat and in the proper position. In 1992, I visited sites in all but six counties to insure proper trap placement in the suspected action site area. The remainder of sites in 1990, 1991, and 1992 not seen by Ed or myself were inspected by the 18 respective county Extension agent to conform to the set standards. Brief notes concerning crop fields and vegetation composing the action site were taken in 1992. To quantify trap to trap catch variation possibly due to placement and location, standard error to mean ratios were calculated using weekly trap catch means for all eligible sites throughout the study. To demonstrate the range of seasonal trap catch, frequency distributions have been generated based on weekly trap catch means. Trap to Trap Variation By standardizing trap placement, we sought to reduce variability between the traps caused by factors such as different grasses and broadleaf plants, proximity to the monitored crop, and trap height above grassy areas. Wind direction was an important factor that had to be accounted for using this design. Using a paired comparisons t-test, it was hypothesized that there would be no difference between outer trap catches and middle trap catch at all eligible sites for 1990, 1991, and 1992 (Sokal and Rohlf 1981). Site to Site Variation (Within Year) In 1990, a European corn borer monitoring network was established across the southern 2/3 of the lower peninsula of Michigan, which was expanded in 1991 and 1992. The network consisted of numerous field sites where pheromone traps were used to survey corn borer flight activity from spring through fall. Field sites were selected based on grower cooperation in all years of the study, and their spatial distribution across Michigan can be seen in Figure 11 of the Appendix. In 1990, 13 sites were monitored for corn borer from June 20 to September 26. In 1991, 24 sites were monitored from June 5 to September 25. In the final year, 1992, 23 sites were monitored from June 1 to September 30. The monitoring sites (Tables lA-C) were adjacent to fields of sweet corn, field corn, or peppers, located on private farms (except 19 for two Michigan State University Research Stations) where the grower was contacted by a Michigan State University Extension agent and agreed to participate in the study. A few sites were added and dropped sporadically over the three year period due to varying levels of grower cooperation. During 1990-92, the pheromone traps at every site were checked weekly on Wednesday by network participators. The only exception being two sites in Van Buren county in 1992 which reported on Monday. The number of male moths caught in the traps were sent to Michigan State University for central compiling of corn borer activity across the state. Results were reported weekly in the Michigan State University Vegetable Crop Advisory Team newsletter. If a cooperator collected the trap catch information but did not report it for the week, it was entered the following week. If a cooperator did not collect the trap catch information for a week, then an average flight activity was calculated based on the number of weeks skipped. For example, suppose 6O moths total were trapped over two weeks, each week would be assigned 30 moths, which would be further divided by the number of traps at the site to arrive at the average flight activity. The latter occurred infrequently throughout all years of the study. Flight variation between sites was investigated by comparing specific events of a flight activity curve, such as flight initiation and peak flight activity. The role temperature might play in governing the two was deemed important so the Michigan Department of Agriculture (MDA) weather station or Federal Aviation Administration (FAA) weather station nearest to each monitored site was selected to record maximum and minimum daily temperatures for correlating these events. The weather station used for each specific site can be found in Tables 1 A-C. These temperatures were converted to degree day units base 50“ F by Dr. Jeff Andresen of the MDA Climatology Division according to the methods described in Baskerville and Emins (1969). The degree day data serves only Table 1A. Counties, weather stations, sites, and crops monitored during the European 20 corn borer flight activity network in 1990. 1990 Counties Weather Station Site Crop Bay Saginaw *Yagalia Field Corn Berrien SWMI Hort SWMRECI Sweet Corn Ingham MSU Hort *Collins Field Corn Kent Kent City Thome N .A. Macomb Almont Klutchey N .A Macomb Almont Oliver N.A. Monroe Toledo Mathis N .A. Oceana Mears *Evans Bell Peppers. Oceana Mears *Ramey Bell Peppers Ottawa Allendale *Dykstra Sweet Corn Saginaw Saginaw Valley *Hemmeter Sweet Corn Van Buren Paw Paw *Morrison Sweet Corn Van Buren Paw Paw *Razjer Sweet Corn N.A. - Not Available * Denotes site was used all for 3 years of the study. 1 Southwest Michigan Research and Extension Center 21 Table 13. Counties, weather stations, sites, and crops monitored during the European corn borer flight activity network in 1991. 1991 Counties Weather StatTon Site Crop Allegan Fennville VanderBand Field Corn Bay Saginaw *Yagalia Sweet Corn Berrien SWMI Hort SWMRECI Sweet Corn Gratiot Vestaburg Strouse Cherry Peppers Gratiot Vestaburg "Strouse Banana Peppers Gratiot Vestaburg MStrouse Bell Peppers Ingham MSU Hort *Collins Field Corn Kent Kent City Miedema Sweet Corn Kent Kent City Morse Banana Peppers Macomb Almont DeCock Sweet Corn Macomb Almont Krause Field Corn Manistee Bear Lake Cooper Sweet Corn Monroe Toledo Heck Sweet Corn Muskegon Muskegon Farr Sweet Corn Newaygo Fremont Vogel Sweet Corn Oceana Mears Cooper Sweet Corn Oceana Mears Cooper Field Corn Oceana Mears Vlasic Peppers Oceana Mears *Evans Bell Peppers Oceana Mears *Ramey Bell Peppers Ottawa Allendale *Dykstra Bell Peppers Saginaw Saginaw Valley Vlasic Peppers Saginaw Saginaw Valley *Hemmeter Sweet Corn Van Buren Paw Paw *Morrison Sweet Corn Van Buren Paw Paw *Razjer Sweet Corn * Denotes site was used for all 3 years oftFe study. ** Denotes sites were monitored using same traps. 1 Southwest Michigan Research and Extension Center 22 Table 1C. Counties, weather stations, sites, and crops monitored during the EurOpean corn borer flight activity network in 1992. 1992 Counties Weather Station Site Crop Allegan Fennville Vander Band Field Corn Bay Saginaw *Yagalia Field Corn Berrien SWMI Hort SWMRBC1 Sweet Corn Gratiot Vestaburg Graham Sweet Corn Gratiot Vestaburg Roberts Bell Peppers Gratiot Vestaburg Schaub Bell Peppers Gratiot Vestaburg Strouse Cherry Peppers Gratiot Vestaburg Strouse Bell Peppers Ingham MSU Hort *Collins Field Corn Ingham MSU Hort MSU Hort Ban/Bell Peppers Kent Kent City Miedema Sweet Corn Kent Kent City Morse Banana Peppers Macomb Almont DeCock Sweet Corn . Midland NA Fleming NA 2 Midland NA Vermeesch NA Monroe Toledo Charter Sweet Corn Newaygo Fremont Karnematt Bell Peppers Oceana Mears *Evans Bell Peppers Oceana Mears *Ramey Bell Peppers Ottawa Allendale *Dykstra Sweet Corn Saginaw Saginaw Valley *Hemmeter Sweet Corn Van Buren Paw Paw *Morrison Sweet Corn Van Buren Paw Paw *Raijer Sweet Corn N .A. - Not Available * Denotes site was used for all 3 years of the study 1 Southwest Michigan Research and Extension Center 23 as an estimate of flight activity occurrence, since temperature accumulation can vary significantly as the distance from the reporting station to the actual field monitored increases. The FAA stations are primarily based at airports, which can also affect temperature readings due to differing heat retention capacities of concrete versus soil. This information was used specifically to identify flight activity events such as initiation and peaks at the local level, but can be partitioned to regional and state levels. Means and standard error of flight events at each site from 1990-1992 were calculated. Multi-Year Sites (Variation Between Years) Eight corn borer monitoring sites remained constant over the span of this project, referred to as multi-year sites, allowing investigation of how flight activity changes from year to year. In most cases, the crop remained the same, and the actual trap placement may have been altered by at most a few hundred meters. It was our intent to determine if certain sites are prone to perennially high or low levels of corn borer infestation. If this is the case, then it would appear that temperature has no direct effect on the magnitude of corn borers trapped at a particular site. Temporally, flight initiation and peaks within a season are dependent upon temperature; cool seasons delaying events while warm seasons accelerate them. Since this study spans three years with fairly dissimilar temperature accumulations, overlap of peaks on a Julian scale is not expected. However, using degree day accumulations, there should be general agreement between years on the initial and peak flight emergence at each site. Standard error and mean calculations were performed on initiation and peak flight on each site. Spearrnans rank correlation test were used to test peak consistency at the multi-year sites. County Level Field Corn Effects In 1990 and 1991, field corn acreage for counties involved in the corn borer monitoring network were obtained from Michigan Agricultural Statistics (1992). Actual data were 24 not available for 1992 so corn acreage's from 1990 and 1991 were averaged and used for the field corn acreage's in 1992. Field corn acreage was compared to both the peak flight and the total number of corn borer moths trapped at each site in 1990, 1991, and 1992 to determine what role the total corn production per county has on local corn borer populations. Vegetable fields located in counties with large acreage's of field corn may be prone to larger corn borer infestations. The total number of corn borers caught in traps at each site during 1990-92 were regressed against total acres of field corn in those counties. The second flight peak trap catch for each site during 1990-92 was also regressed against total acres of field corn in those counties, as was the third flight peak of 1991. Results and Discussion Trap Placement and Location Inter-trap catch variability was measured at all eligible sites using standard error to mean ratios (Table 2A-C). Sites had to have more than two traps to be included in the analysis. In general, as that ratio becomes larger, it reflects greater differences between individual trap catches. The smallest measure of standard error to mean in 1990 was found to be 0.04, with the largest ballooning to 0.82. In 1991 and 1992 , the lows and highs were 0.05, 0.87 and 0.01, 0.87 respectively. The largest standard error to mean ratios actually occurred with lower trap catches, due to one trap catching moths and the others registering zero. Because such high variability does exist between weekly trap catches, it is difficult to endorse the concept of using only one trap to monitor a field. A more balanced strategy might include the use of several traps at one site and relying upon the average trap count. Frequency distributions of weekly trap catch means (including counts from single trap sites) for all sites in 1990, 1991, and 1992 (Figures 1 and 2). There is a steep decline in 25 Table 2A. Mean trap catch and its associated standard error to mean ratio for all eligible trapping sites in 1990. Site Mean Low Mean High MothS/ttaD/week S.E. / Mean Moths/trap/week S .E. / Mean CollTns 7.6 0.04 0.3 0.82 Dykstra 3.0 0.31 0.3 0.82 Evans 6.6 0.1 1 0.6 0.82 Hemmeter 6.0 0.36 3.6 0.71 Klutchey 3.0 0.42 0.6 0.82 Mathis 2.3 0.31 0.3 0.82 Morrison 4.6 0.15 1.0 0.82 Oliver 0.3 0.82 0.6 0.82 Razjer 15.0 0.33 0.3 0.82 Ramey 1.3 0.20 0.3 0.82 Thome 0.6 0.41 0.6 0.82 Yagalia 4.3 0.53 1.0 0.82 26 Table 2B. Mean trap catch and its associated standard error to mean ratio for all eligible trapping sites in 1991. Site Mean Low Mean High Moths/trap/week S.E./Mean Moths/trap/week S.E./Mean Collins 1.3 0.25 1.6 0.82 DeCock 4.0 0.14 1.0 0.82 Dykstra 1 19.3 0.06 0.3 0.82 Evans 230.0 0.23 1.3 0.66 Farr 6.5 0.05 0.5 0.71 Heck 10.0 0.10 3.6 0.87 Hemmeter 26.6 0.13 0.6 0.82 Krause 20.9 0.06 2.6 0.82 - Miedema 1.3 0.25 0.6 0.82 Morris 47.6 0.28 0.3 0.82 Morse 3.6 0.09 4.3 0.77 Razjer 2.3 0.14 0.3 0.82 Ramey 373.3 0.17 15.0 0.54 Strouse bells 98.0 0.04 129.5 0.47 Strouse cherry 29.3 0.13 2.3 0.62 Vanderband 3.5 0.10 48.5 0.63 Vogel 4.5 0.07 74.0 0.44 Yagalia 4.6 0.20 0.3 0.82 27 Table 2C. Mean trap catch and its associated standard error to mean ratio for all eligible trapping sites in 1992. Site Mean Low Mean High MothSIUap/week S.E.lMean Moms/trap/week S .E./Mean Charter 73 0.10 0.3 0.82 Collins 18.3 0.13 0.6 0.82 DeCock 47.6 0.20 0.3 0.82 Dykstra l 1.3 0.05 0.3 0.82 Evans 3.0 0.42 0.6 0.82 Graham 4.3 0.17 0.3 0.82 Hemmeter 4.0 0.14 1.3 0.54 Hort Fanrr 17.3 0.10 1.0 0.82 Karnematt 30.5 0.01 0.5 0.71 Miedema 1.3 0.54 0.3 0.82 Morrison 16.0 0.08 0.3 0.82 Razjer 4.0 0.31 0.3 0.82 Ramey 2.5 0.22 0.8 0.87 Roberts 1 l 0.08 0.3 0.82 Schaub 3.3 0.22 0.6 0.82 Strouse bells 2.5 0.14 5.5 0.71 Strouse cherry 8.3 0.16 1.6 0.82 SWMRECI 1.5 0.24 1.0 0.71 Vanderband 214.5 0.10 0.5 0.71 Yagalia 2.6 0.10 0.3 0.82 1 Southwest Michigan Research and Extension Center 28 p I ”J . w 9 me- E M... .._ "mm-—m L _ “om.m¢ 1 _ "me-.¢ L moe.om A _” m u . E . J nu .o«.o. n) . w .m_.PF .o..o 1m I O / m .m m . .w .. o w 8 6 4 xocoscobm n=261 1991 Mean trap catch ranges (ECB / Trap / Week) 200' xocosvobm Weekly mean trap catch frequency distribution of European corn borer moths at all sites in 1990 and 1991. Figure l. 29 oom-_ou . . _ . r n can. 2:. mm 3-5 m ”3.1:; m onuom “u.“ 11°95..ch In 89:: 3-3 u 2...: u 3. 2... omée H mm. —m u 3.. 2. me 2. I, 2.8 3.3 u 3. E M oeém mm..n ,Imm..m . 1m 3.3 on on 1. me. I. 2 4,. 3.3 .3. Z 0., a . 0 I,“ mm. 3 me, -31.: W Am 3:3 .01, 1m P l 4,... mu. 5 1. F — .1.“ 3.3 to Ft 0 , t,” m P0 F F I m I o lfivxot1.”..xtvxmtrth...”«N.A{wawxxxixkGKKRGKSURKQPESRfixtunxmfivfiwmet Um I o - q 1 no 4 u .0 a .0 o m m o m m m m. 5553.5 5532”“ Total mean trap Mean trap catch ranges (ECB / Trap / Week) Weekly mean trap catch frequency distribution of European corn borer moths at all sites in 1992. catch frequency distribution for 1990-1992 is also shown. Figure 2. 30 the frequency of trap catch means above 5 moths per trap per week. Using 15 moths per trap per week as an arbitrary action threshold, the proportion of times that trap means are equal to or below this level provides a good argument for the importance of understanding flight and oviposition interactions at these low levels. For example, in 1990, approximately 87% of all trap means were under this level, in 1991, approximately 57%, and in 1992, approximately 88%. If trap catch means are combined for all years, approximately 78% of all means in the past three years have been under 15 moths per traps per week. The point is if the majority of flight activity is relatively low, by understanding how flight behavior and oviposition impact crop protection under these conditions, gains can be made in pest management by establishing action thresholds above 1 moth per trap per week using this monitoring system. At levels exceeding 15 moths per trap per week (arbitrary arrived at), growers are apt to be spraying for protective measures if nothing else, even though theoretically, a trap threshold may not have been exceeded. It needs to be realized however, that various crops can be managed under different trap catch thresholds depending on the level of damage tolerable before economic viability is lost. Trap to Trap Variation In 1990, of a possible 12 sites, the outer traps caught significantly more moths than the middle trap at the Hemmeter, Razjer, and Yagalia sites (P<0.05). In 1991, of a possible 14 sites, the outer traps caught significantly more moths than the middle trap at Hemmeter, Razjer, Heck and Krause sites (P<0.05). In 1992, of a possible 16 sites, the outer traps caught significantly more moths than the middle trap at Ramey, Graham, and Horticulture Farm sites (P<0.05). The fact that only a handful of individual sites each year showed significant differences for trap preference compared with the total number of sites, indicates this arrangement 31 of traps at the monitoring site is fairly appropriate and non-biased. There may be factors such as the wind which can bias trap catch under the right set of circumstances, but this is not often the case. With the pheromone traps being arranged in a row, and the wind blowing in the right direction, male moths following a pheromone trail must bypass either outer trap first to be caught in the middle trap. This could explain the occasional tendency for the outer trap catches to outnumber the middle ones. Showers et al. (1974b) also noted the downwind pheromone trap usually contained more moths. To further reduce this additive effect from neighboring traps in the future, it may be prudent to . arrange the traps in a non-linear configuration in the grassy areas or increase the distance between traps. This way the pheromone plumes will either dissipate before reaching neighboring traps or it will be less likely for the plumes to lie directly in each others path. Site to Site Variation (Within Year) By graphing corn borer flight activity weekly, seasonal flight activity curves have been generated for all sites and all years of the study and are located in the Appendix. Figures 7-9 contain seasonal flight activity curves for 1990-1992 and are arranged alphabetically by county within each year. Figures 10A-H in the Appendix contain the seasonal flight activity curves of the multi-year sites. The variation in magnitude and occurrence of flight initiation and peak activity between sites and between years is of particular note. The main basis for distinguishing trends on the county, regional, or state level involves interpretation of the flight activity curves from sites within those borders. Each curve provides at least two major pieces of information, initiation of flight and peak flight activity. Initiation of a flight is subjectively determined when a low level of flight activity (a few moths per trap per week) begins to increase weekly toward a maximum value, the peak. In reference to a flight activity curve, peak flight activity has a 32 mathematical component based on degree day accumulation which allows it to be vaguely predictable, but in this context it is used more subjectively to define a weekly increase in moth trap catch to a maximum, and then a decline in weekly trap catch. In theory, these peak events should occur within windows at approximately 450, 1450, and 2450 DD50. The highest trap catch equals the peak flight activity, and based on its magnitude, may be related to the level of egg mass laying and eventual damage to a crop. It is sometimes difficult to distinguish exactly when peak flight activity is occurring, due to the naturally erratic flight behavior of the corn borer, and its dependence on proper environmental factors for flight. Tables 3A-D contain flight initiation dates for all eligible sites. In 1990, the second flight initiation occurred between August 1 to August 8. In 1991, with the number of sites nearly doubling, the second flight initiation spanned from July 110 to July 24. There was a third generation in most sites in 1991, leading to a third initiation between August 7 and September 4. The last year, 1992, the second flight initiation ranged from August 6 to September 3. The peak activity of the second flight (and third flight in 1991) for each site and year is also shown in Tables 3A-D. In 1990 there was a spread of peak flight between a low of 2.6 and high of 64 moths per trap per week at different sites. Many sites in 1991 experienced both a second and a third peak flight, attributed to the unusually high accumulation of degree days. The second» adult flight peaks ranged from 9 to 152.5 moths per trap per week, while the third adult flight peaks ranged from 31.3 to 539 moths per trap per week. Comparing the second and third flight activity peaks at each individual site showed that the latter was always larger than the former, with the exception of two sites, Strouse's bell and cherry pepper fields. The large third flight was probably due to low biotic and abiotic larval mortality during the second generation. At a few sites in 1991, there appeared to be no distinguishable second flight peaks. However, later in the season flight peaks were noted, and due to the corresponding 33 Table 3A. Second flight initiation and peak activity of European corn borers caught at each site in 1990. Site 2nd Flight Accumulated 2nd Flight Peak AccumuTated Initiation DD 50 Moths/trap/week DD50 Collins - - NTIiP. - Dykstra - - N .D.P. - Evans August 8 1491 7.3 1730 Hemmeter August 1 1508 62.3 2008 Klutchey August 8 1691 3.0 2101 Mathis August 8 1933 2.6 2101 Morrison August 8 1673 54.3 1933 Oliver - - N.D.P. - Razjer August 8 1673 32.3 1933 Ramey - - N.D.P. - . SWMRECI - - l 1.0 2460 Thome August 8 1534 3.0 1916 Ya alia August 1 1574 64.0 1938 . .P. - No Distingurshable Peak 1 Southwest Michigan Research and Extension Center 34 Table 3B. Second flight initiation and peak activity of European corn borers caught at each site in 1991. Site 2nd Flight AccumuTated 2nd Flight Peak Accumulated Initiation DD50 Moths/trap/week DD50 Collins July 17 1688 9.0 2000 Cooper 1 - - N .D.P. - Cooper 1 July 17 1471 81.0 1746 Cooper 2 - - NHDP. - Decock - - N .D.P. - Dykstra - - N.D.P. - Evans July 24 1654 9.0 1746 Farr July 17 1592 11.0 1891 Heck July 17 1939 15.0 2296 Hemmeter July 17 1511 16.6 1803 Krause ' - - N.D.P. - Miedema - - N.D.P. - Morrison July 17 1724 47.6 2028 Morse - _ - N.D.P. - Razjer July 24 1917 3.0 2028 Ramey July 10 1345 16.6 1654 Strouse cherry July 17 1533 122.3 1897 Strouse bells July 17 1533 152.5 1807 SWMREC 4 July 17 1746 71.0 2050 Vanderband - - N .D.P. - Vlasic 1 - - N.D.P. " Vlasic 3 ' - N.D.P. - Vogel July 17 1504 15.5 1679 Yagalia - - N .D.P. - 1 Oceana County 2 Manistee County 3 Saginaw County 4SWMREC- Southwest Michigan Research and Extension Center N .D.P. - No Distinguishable Peak 35 Table 3C. Third flight initiation and peak activity of European corn borers caught at each site in 1991. Site 3rd Flight Accumulated 3rd Flight Peak Accumulated Initiation DD 50_ Moths/tra a/week DD 50 Collins Augusfil 2375 62.0 2916 Cooper 1 August 21 2121 425.0 2289 Cooper 1 August 21 2121 332.0 2419 Cooper 2 September 4 2188 539.0 231 1 Decock August 14 2321 135.0 2767 Dykstra August 7 2036 278.0 2569 Evans August 14 1986 230.0 2289 Farr ' September 4 2615 179.5 2887 Heck August 14 2608 46.6 2937 Hemmeter August 28 2338 31.3 2708 Krause August 14 ' 2321 51.3 2767 Miedema August 28 2272 68.0 2623 Morrison August 21 2431 94.6 2741 Morse - - N.D.P. - Razjer August 21 2431 35.3 2880 Ramey August 14 1986 373.3 2289 Strouse cherry August 28 2291 103.0 2629 Strouse bells August 28 2291 130.0 2409 SWMREC4 August 21 2439 187.0 2744 Vanderband August 28 2308 48.5 2693 Vlasic 1 August 21 2121 265.0 2548 Vogel August 7 1880 204.0 2401 Ygalia - - N .D.P. - 1 Oceana county 2 Manistee county 3 Saginaw county 4 SWMREC- Southwest Michigan Research and Extension Center 36 Table 3D. Second flight initiation and peak activity of European corn borers caught at each site in 1992. Site 2nd Flight Accumulated 2nd Flight Peak Accumulated Initiation DD50 Moths/trap/week DD 50 Charter August 6 1660 7.0 2131 Collins August 20 1608 102.0 1914 Deka August 13 1512 47.6 1725 Dykstra August 13 1477 5.0 1623 Evans - - N.D.P. - Fleming August 13 1428 14.0 1790 Graham August 20 1525 81.0 1816 Hemmeter September 3 1657 4.0 1739 Hort Farm August 20 1608 24.6 1914 Karnematt August 20 1406 30.5 1754 Miedema - - N.D.P. - Morse - - N.D.P. - Morrison August 17 1593 8.3 1798 Razjer - - N .D.P. - Ramey - - N.D.P. - Roberts August 20 1525 48.0 1816 Schoub August 20 1525 24.0 1816 Strouse cherry August 20 1525 8.3 1645 Strouse bells August 20 1525 9.0 1816 SWMRECI - - N.D.P. - VanderBand August 13 1395 215.0 1735 Vermeesch - - N.D.P. - Yagalia - - N.D.P. - N .D.P. - No Distinguishable Peak 1 SWMREC-Southwest Michigan Research and Extension Center 37 number of degree days, were assumed to be third flight. In 1992, peak flight activity ranged from 4 to 215 moths per trap per week at various sites. The cool weather in 1992 seemed to contribute to the delayed emergence and low population levels, preventing them from developing easily defined peaks in several cases. At various sites throughout all years of the study, no distinguishable peaks of activity were apparent. In addition to the flight initiation and peak activity at each site in the study, sites were grouped into climatological regions and eventually statewide levels to observe trends in these two events. The lowest DD 50 accumulation on a regional basis for second flight initiation was 1406 in 1992, and the highest was 1939 DD50 in 1991 (Tables 4-7). The lowest DD50 accumulation on a regional basis for the second flight peak was 1711: 62, with the highest at 2296 (Tables 4-7). A seasonal statewide estimate of flight initiation and peak activity was generated for 1990, 1991, and 1992 (Table 8). Only the flight peak range from 1991 and 1992 overlap, which is interesting because they were essentially opposite seasons in terms of total heat accumulation. Why 1990 second flight peak does not overlap with 1991 or 1992 is difficult to explain, because physiologically the developmental time should be constant from year to year. When looking at the combined totals for 1990-1992 (Table 8), the second flight initiation is approximately equal to Apple's (1952) estimate of 1716 i 79 DD50 and Jarvis and Brindley‘s (1965) estimate of 1652 DD50 , This near overlap of flight initiation compared to findings of other researchers in the rrridwest confirms that our degree day estimates of these events were fairly accurate. As more information about both initiation and peak activity is gathered over time, these initial estimates may be further refined. 38 Table 4. Mean 1: S. E. of second flight initiation and peak activity for 1990. Climatological Flight initiation x i SE. Peak activity x i S. E. Divisions DD50 DD50 4 West Central LP 1513 i 15 1823 i 66 5 Central LP N .A. N.A. 6 East Central LP 1541 i 23 1973 i 25 7 Southwest LP 1673 i 0 2197 j; 143 8 South Central LP N.A. N.A. 9 Southeast LP 1812; 86 2101: 0 N .A. - Not Available Table 5. Mean 1: S. E. of second flight initiation and peak activity for 1991. Climatological Flight initiation x i S. E. Peak activity x i S. E. Divisions DD50 DD50 4 West Central LP 1513 i 47 1743 i 37 5 Central LP 1533 i 0 1852 -_l-_ 32 6 East Central LP 15111 18031 7 Southwest LP 1689 i 25 1887 :1; 100 8 South Central LP 1688 2000 9 Southeast LP 19391 22961 1 Only one site available Table 6. Mean i S. E. of third flight initiation and peak activity for 1991. Only one site available Climatological Flight initiation x i: S. E. Peak activity x i S. E. Divisions DD50 DD50 3 Northwest LP 21331 23111 4 West Central LP 2118 i 73 2494 i 67 5 Central LP 2291: 0 2519 i 78 6 East Central LP 2423 i 35 2708 i 0 7 Southwest LP 2320 i 58 2708 j; 40 8 South Central LP 23751 29161 9 Southeast LP 2416 if 78 2824 :2 46 1 39 Table 7. Mean i S. E. of second flight initiation and peak activity for 1992. Climatological Flight initiation x -_t-_ S. E. Peak activity x i: S. E. Divisions DD50 DD50 4 West Central LP 14061 17541 5 Central LP 1509 1:15 1783 i 26 6 East Central LP 1657 1739 7 Southwest LP 1535 i 41 1711 i 62 8 South Central LP 16081 19141 9 Southeast LP 1586 ..—+_ 52 1928 g 144 1 Only one site available Table 8. Mean i S. E. of second and third flight initiation and peak activity at the statewide level for 1990, 1991, and 1992. Temperature for flight initiation was accumulated from March 1 and May 14 to account for photoperiod differences. A mean for all sites involved during 1990-92 is also shown. Mean i S.E. (DD50) Statewide Flight initiation Flight initiation Peak flight (since May 14) (since March 1) 1990 1330: 38 1635 i 51 2013 i 63 1991 1312 i 35 1607 i 40 1873 i 48 1991 (3rd Flight) N. A. 2272 j; 41 2616 i 44 1992 1338 j; 15 1531 i 21 1802 i 30 1990—92 1327 -i- 17 158]; 22 1878 i 30 N. A. - Not Applicable Table 9. Mean :1; S. E. of second flight initiation and peak activity at multi-year sites from 1990 - 1992. Multi-Year Sites Flight initiation x i S. E. Peak activity x i: S. E. DD50 DD50 Collins 1648 i 28 1957 i 30 Dykstra 14771 16231 Evans 1573 i; 58 1738 i 6 Hemmeter 1559 i 40 1850 :t 66 Morrison 1663 j; 31 1620 i 55 Razjer 1664 i 7 1840 j: 66 Ramey 13451 16541 Yagalia 15741 19381 1 Only one year with flight initiation and peak data 40 Table 10. Mean 3; S. E. of second flight initiation and peak activity by climatological division from 1990-92. Temperature for flight initiation accumulated from March 1 and May 14 to account for photoperiod differences. ' Mean £8. E. (DD50) Climatological Flight initiation Flight initiation Peak activity Divisions (since May 14) (since March 1) 4 West Central LP 1243 i: 33 1500 _+_ 32 1765 j; 31 5 Central LP 1315 i 17 1515 j; 12 1800 i 23 6 East Central LP 1281 i 51 1563 i: 30 1872 i 53 7 Southwest LP 1351 i 30 1617 i 41 1856 i 78 8 South Central LP 1373 i 10 1635 i 22 1943 -_i-_ 23 9 Southeast LP 1431 i 42 1747 =4; 68 2071 _i: 77 41 With such a diversity of flight initiation and peak activities, it is difficult to reliably predict flight events even between sites separated by only a few miles. This has the implication that each individual site (field) can have flight events that are usually similar to others in a given county in terms of size and occurrence of the flight, but may differ from other sites (fields) as the distance between them increases. Therefore an argument can be made that every field needs to be monitored individually, due to intra and inter- regional variation. ' Multi-Site Variation (Between Years) Only two of the eight multi-year sites, Razjer and Hemmeter, have flight peaks within the range of the 1990-92 statewide peak estimate (T ables 8 & 9). Four of the six remaining sites peak below the three year average range and the remaining two sites peak above it. Given this spread, statewide estimates may not be accurate enough to time pest management decisions. This means it is important to understand flight initiation and peak activities at a greater resolution, perhaps the regional level or even events that are peculiar to a specific site. At the regional level, there appears to be a trend of higher accumulations of DD50 needed for flight initiation in the southern compared to the northern regions (Table 10). This may be due to a photoperiod - temperature interaction which determines when overwintering corn borer fifth instars can begin to pupate. Mutchmor and Beckel (1959) determined at latitudes near 43' (approximately Lansing, MI), that the photoperiod in the second week of May (14.5 hours) is sufficient to trigger pupation. Since DD50 are usually accumulated starting March 1, this results in additional heat accumulation in southern regions which essentially goes unused due to photoperiod inadequacy. By accumulating DD50 from May 14, subsequent initiation times have been generated at the 42 regional and state level (Table 8) which have reduced activity windows and perhaps increased their timing accuracy. Comparing multi-year site means (Table 9) with their respective three year regional means (Table 10), shows six of the eight sites are within the DD50 range estimates provided at the regional level. This supports the idea that regional means are fairly representative of flight activity at multi-year sites within their borders. Using degree days (accumulated since March 1) to compare flight initiation finds only the East Central and Southwest lower peninsula regions (Table 10) to overlap with the 1990- 92 statewide estimate (Table 8). This would seem to suggest there are sufficient differences between estimates at those two levels to preferentially use regional estimates if available. Flight initiation at individual sites compared to the 1990-92 regional estimates (Table 10) yielded 3 out of 8 sites in 1990 (Table 3A), 1 out of 13 sites in 1991 (Table 3B), and 6 out of 15 sites in 1992 (Table 3D) to haverange overlaps. This would seem to indicate that flight activity information at the site (field) level is more reliable than regional estimates. There were several sites in 1991 and 1992 that were within :1; 10 DD50 of the regional mean, which shows that regional estimates do encompass most sites and have merit for general use when nothing else is available. Spearmans rank correlation test was, performed on the second flight peak of the multi- year sites to look for a pattern of high or low peak catches at these sites relative to each other. There was no consistency between peak size at multi-year sites. The warmest season did not produce the highest peak, and the coolest season did not produce the lowest peak. There appears to be a random appearance of peak size. The most apparent 43 trend was a tendency for an additional generation in the warmest year, 1991. In seasons with average to below average temperature accumulation, we observe on average two peak flights; one in early June and the other in mid August. In seasons above average temperature accumulation (1991), we observe two to three peak flights; early June, late July, and early September. The number of peaks may also serve as a function of what voltine strain is present; with univoltine strains having one less peak than bivoltine strains. Some areas may have a mix of both strains, making individual peak interpretation precarious at best. By collecting larvae and following their fate under certain lab conditions, voltinism can be determined based on their developmental response. Voltinism information coupled with empirical Observation over time may present us with a window of expected flight peaks at the county, regional, or state level. Another aspect of peak prediction is understanding how the size ofwone peak may effect the size of the next generation. There currently is no predictability between peak size during the same season or peak size from year to year. This may be due to a variety Of environmental (weather conditions), biological (parasitism, pathogens, host plant abiosis), and cultural (spraying, location) interactions. County Level Field Corn Effects Regressing the total number of corn borers caught at each site against the acreage of field corn planted in that county yielded R2 values of 0.103(n=13, F=1.268, p=0.284), 0.006(n=24, F=0.126, p=0.726), and 0.059(n=23, F=1.318, p=0.264) for 1990, 1991, and 1992 respectively (Figure 3). All regressions were non significant (p>0.05). Regressing the peak number of moths caught during the second flight against field corn acreage at eligible sites yielded R2 values of 0.471(n=8, F=5.349, p=0.060) and 0.077(n=16, F=1.168, p=0.298) for 1990 and 1992 respectively (Figure 4), both being weakly positively correlated but neither beingisignificant (p>0.05). In 1991, both second and Total no. ECB trapped during the season Total no. ECB trapped during the season Total no. ECB trapped during the season 44 600 1990 ‘ A RA2=0.103 4001 » A 200- ‘ . 1 ‘ . . . ‘AA 0 " F ' t Y t ‘ f fi ' 0 20000 40000 60000 80000 100000 3000 1991 RAZ=0.006 zoom . A A A A 1000a ‘ ~ A i ‘ A A A “ ‘ A ‘ A o v 1 V f‘ ‘ I i I ' 0 20000 40000 60000 80000 100000 800 ; 1992 ‘ ‘ A 600, R2=0.059 A A 400- 200~ A ., A o A g ‘ AA A A 0 20000 40000 60000 80000 100000 Field corn acreage / County Figure 3. Linear regression of total number of European corn borer trapped during the season against total number of field corn acres in 1990, 1991, and 1992. None are significant (p>0.05). 45 .331: 88:23... a :3 a 33: “8:83 2: 3:0 .33.“ :30 20: .3 Lon—Ezz .33. amp—Ewe .33 .5 .33 .33 E 2E :23 3 Asa—:3 ESE .83.. 58 52.9.3.— ..e EwE 8:8.— PE: 33 2:58 .8 .868qu :35.— .v 3:»; 19:28 \ omeOa Eco 20E oooooF ocoow occcc ococv ooocu o t ‘ U u b p h t p b o . 4 . 8. . .ccw G whodum b t L - ‘ O . G G G . G G . .oop 4 v . G room G . .con . Taco N3 .OHN<~— "may . com OGOOOP I ccooa .958 \ omens“ E8 26E ooooo P @6009 P 1? ccoou o G G G G G G mmmdum1 cocoa cacao b ocoov r L 2.35 an acocu o G. 4. . o 4 _ hvdum0.05). However, Lee (198 8) contends there is a greater number of egg masses in the interior of fields (corn), and Shelton et a1. (1986) states there is a random distribution of egg masses throughout the fie1d(corn). Assuming each field was a fairly homogeneous distribution of plants, I had expected to find more egg masses near the edge because these are the areas immediately adjacent to the mating and resting areas. It would seem a female moth stands less of a chance of predation, disorientation, or being blown away from the field, the closer to the mating or resting area she oviposits. If there is a suitable place to oviposit nearby her daily refuge, there should be no advantage to search for plants in areas farther away. The 50 bell pepper fruit collected from Strouses' field in 1991 revealed a 10% larval infestation rate. This is an unacceptable level of damage, since most processing pepper growers strive to get as close to 0% infestation as possible. Two factors that differed from previous years was the heightened flight activity peaks and temperatures, which were certainly more intense than 1990 or 1992. There appeared initially to be a 59 Table 13 A. Weekly European corn borer egg mass per plant sampling results from August 5 to September 2, 1991. ECB Egg Masses / Plant / Week Site and Crop 8/5 8/ 12 8/25 9/2 Strouse-Banana 0.24 0. 12 0.04 0.04 Strouse-Bell 0 0.07 0. 12 0. 16 Strouse-Cherry 0.12 0.12 0.16 0.08 Morrison-Bell 0.08 0.07 0.2 0.07 Morrison- 0.28 0.12 1.4* 0.24 Sweet corn Razjer- 0.24 0 0.07 H Sweet corn SWMREC 1 NS. 0.04 1.12* 0.08 Sweet corn 1 Southwest Michigan Research and Extension Center *-Significantly different from other row values, Fisher's Protected LSD (p<0.05) H-Field Harvested N.S.-Not Sampled Table 13 B. P and F values of weekly egg mass means at all sites from August 5 to September 4, 1991. Only Morrison and SWMREC are significant (One way ANOVA, p<0.05). Site and Crop P-Value F-Value d.f. Strouse - cherry peppers 0.19 1.79 3 Strouse - bell peppers 0.52 0.80 3 Strouse - banana peppers 0.20 1.72 3 Morrison - bell peppers 0.56 0.71 3 Morrison - sweet corn 0.004 6.53 3 Razjer - sweet corn 0.29 1.40 2 SWMREC 1 - sweet corn 0.0001 24.24 2 1 Southwest Michigan Research and Extension Center 6O connection between the flight activity and egg mass deposition. Accompanying the increased flight activity, were apparently more egg masses being deposited than normal and greater larval survivorship, causing several pepper fields to be plowed under due to excessive damage (Tim Wilkinson, pers. comm). Many fields in Michigan suffered higher larval infestation than normal even using the narrowest spray intervals possible (unpublished data). Flight Activity and Egg Mass Sampling - 1992 In 1992, the peak flight activity was much lower than 1991, ranging from 8.3 to 30.5 moths per trap per week, with no third flight (Figure 6). The flight at those sites was erratic in general, with no consistent increase and decrease of flight activity after a peak. The growers responded to the low levels of flight activity by delaying their spray schedules as long as the trap counts remained low, even though we did not have evidence to recommend this course of action. Of the 24705 pepper plants inspected for egg masses only five egg masses were found during the entire 1992 season (one at Karnematt's, one at the Morse's, and three at Strouse's bell pepper site). The low number of egg masses does not allow further discussion about the temporal or spatial distribution of egg masses. In 1992, of the four sites inspected for infested fruit, only one corn borer larva was found out of 495 fruit. The lone larva was found at Strouse's bell pepper field. One amazing aspect of this figure is that the grower only applied insecticides twice during the 61 10 Moths / Trap / Week —0— Strouse-bells + Strouse-cherry 1 180 200 220 240 260 280 (O O l N O l —L O Moths / Trap / Week —O'— Karnematt-bells 0 1 Moths / Trap / Week [0 O ‘0 co 0 Figure 6. ‘7 j 40 160 180 200 220 240 260 280 _a O C —O—' Morse-hananaE + Morse-banana W 220 240 260 Julian Date 200 280 1992 Seasonal flight activity curves for European corn borer in Gratiot (A), Newaygo (B), and Kent (C) counties. 62 entire season, instead of the usual 5-7 day schedule once the fruit sets. The reduced insecticides on peppers in 1992 was a trend followed by all the growers we worked with. The abnormally low numbers of both egg masses and larvae‘may be speculated to be related to low flight activity and cool summer temperatures. The cool evenings may have curtailed night time ovipositional flights due to cool weather physiological restraints. Loughner and Brindley (1971) suggests a temperature drop of up to 8°C in the evening increases mating activity in corn borer, but they do not comment on any flight inhibition . associated with cooler temperatures. Showers et al. (1974b) also noted that a drop in evening temperature of 6-12°C leads to increased mating activity. Temperature drop does not directly relate to how low temperatures would affect flight and mating behavior. Flight Activity and Ovipositional Relationship Flight activity was not correlated to egg mass density data showed significant correlations (Table 14 A, p>0.05). The same was true for pooled pepper and sweet corn data (Table 14 A, p>0.05). When the flight data from all the sites was log transformed (not shown) or lagged a week behind the egg mass sampling, there was still no significant relationship except at the SWMREC site (Table 14 B, p<0.05). This result is suspect though, due to both the small number of sample dates and only one pheromone trap at that site. The best correlation between flight activity and egg mass density was obtained by pooling all sweet corn sites and using the flight observed this week with last weeks egg mass density (Table 14 B, p<0.05). Justification for off setting the flight data by one week is supported by Oloumi-Sadeghi et al. (1975) who contends that female calling interferes with the pheromone traps and may delay the effectiveness of the traps. Due to the lack of egg masses found in 1992, linear regression between flight activity and egg mass sampling was not possible. 63 Table 14 A. Correlation of flight activity against egg mass laying at all sites in 1991. None were significant (p>0.05). Site and Crop P-Value F-Value R2 n Strouse - banana 0.65 0.29 0.13 4 Strouse - bell 0.87 0.03 0.02 4 Strouse - cherry 0.48 0.76 0.28 4 Morrison - bell 0.75 0.13 0.06 4 Morrison - sweet corn 0.66 0.27 0.12 4 Razjer - sweet corn 0.70 0.27 0.21 3 SWMREC 1 ‘ sweet corn 0.67 0.33 _ 0.25 3 All pepper sites 0.78 0.08 0.01 16 All sweet corn sites 0.89 ' 0.02 0.01 10 1 Southwest Michigan Research and Extension Center Table 14 B. Correlation of flight activity lagged one week against egg mass density at all sites in 1991. Site and Crop P-Value F-Value R2 n Strouse - banana 0.95 0.01 0.01 4 Strouse - bell 0.99 . 0.0 0.0 4 Strouse - cherry 0.70 0.19 0.09 4 Morrison - bell 0.20 3.61 0.64 4 Morrison - sweet corn 0.17 4.53 0.70 4 Razjer - sweet corn 0.76 0.15 0.13 3 SWMREC 1 ' sweet corn 0.025 655.58 0.998 3 All pepper sites 0.45 0.61 0.04 16 All sweet corn sites 0.006 13.49 0.628 10 1 Southwest Michigan Research and Extension Center 64 Looking for consistency between flight activity and oviposition with these two years of data in terms of establishing spray guidelines based on trap thresholds presents some interesting questions. During the egg mass sampling period of 1991, there were relatively low levels of flight in (0.6 to 29.3 moths per trap per week), low to high egg mass densities ( 0 to 1.4 per plant per week) resulting in higher than average fruit damage (10% infestation). In 1992, during the egg mass sampling period, these same levels of flight activity were recorded (0 to 30.5 moths per trap per week) followed by extremely low levels of oviposition (0 to 0.05 egg masses per plant per week) resulting in nearly undetectable damage (0.8% infestation). It seems like flight activity surrounding a field is not the best measure of oviposition and eventual damage given the results of 1991 and 1992. Is it prudent to develop a trap catch threshold from one (the Massachusetts threshold) to several (< 30 moths per trap per week) for advising growers when to begin spraying without really knowing how temperature and flight relate to oviposition? It is probably best not to try to establish such specific guidelines at this point, but as more information about the system becomes known, perhaps pheromone traps can be used for this purpose. The decision to modify trap thresholds must also account for the crop involved, because sweet corn can tolerate more damage than peppers without suffering equal economic loss. The parameters to indicate when a trap threshold can be revised with confidence or is at the appropriate level hinges on several factors, such as environmental and temperature cues that are still beyond our immediate means of assessability. Perhaps with the use of modeling, some of these subtleties can be identified, allowing a more accurate and reliable description of conditions under which modification of trap thresholds is justified. 65 Conclusions Trying to find a relationship between egg mass levels and pheromone trapped males over the past two years in Michigan has met with very little success. What I expected to find was a relationship where increased flight activity led to an increase in egg masses found at that site, with potentially more fruit damage. The converse should be true as well, with low ECB flight activity leading to fewer egg masses and less damage. Although we were unable demonstrate a connection between flight and oviposition, by improving our ability to monitor and interpret male flight through more research, it may be feasible to utilize pheromone traps as management tools in the future. The ability to use pheromone traps to track corn borer populations ultimately for the purpose of management, is a fascinating concept, yetthe appropriate method for doing so remains elusive. Realistically, the traps are only a relative measure of activity, and a more direct method measure of the population activity may be what is needed. There are many variables that cause the pheromone traps to vary in their effectiveness, including trap placement (Derrick et al. 1992, Lee 1988) and female competition (Oloumi-Sadeghi 1975), thereby affecting the ability of traps to reflect the true activity in that vicinity, confounding our predictions of ovipositional activity. Given the variability of the system, it is our challenge to find the correct application of pheromone trapping for use as a management tool. Pheromone traps can be used to monitor populations but are not suitable for directly indexing oviposition. If we cannot adequately produce crops at the same standard under IPM practices as we can using conventional methods, then perhaps finding alternative uses of slightly damaged fruit should be a priority. The idea that variably infested pepper loads may be earmarked for certain types of processing (e. g. clean peppers get pickled whole, higher damage peppers made into relish) is good in theory, but may have some logistical problems attached to it. 66 The processing lines at this time are dedicated for only a certain type of processing during one time frame, and are not flexible enough to accommodate various quality peppers and pack several products at the same time. The need for high quality produce is one of the most important factors driving the vegetable processing companies, the other is a reduction of chemical inputs. By using pheromone traps to monitor corn borer populations is the first step toward a stronger IPM solution. CONCLUSIONS The European corn borer is an economic pest through out the corn belt, midwest, and eastern seaboard states. Part of its success is related to a complex life history; different voltine strains, pheromone races, and widespread polyphagy, which make this insect very ‘ challenging to manage. The other component of its success is a readily available food supply of both field and vegetable crops. We can take advantage of its unique biology to help us manage it in the long run. When Klun and Brindley (1970) first synthesized ll-tetradecenyl acetate, the active compound in corn borer pheromone, a new tool was developed to explore the behavior of this insect. The pheromone trap is that tool; and like any other tool, we must first understand how to properly use it to unlock its full potential. Pheromone monitoring of corn borer has been attempted by several researchers with varying levels of success. Durant et al. (1986), Derrick et al. (1992), and Ferro and Fletcher-Howell (1985) all support the use of pheromone traps to monitor populations, but none have tried to correlate moth captures to egg mass levels. Kennedy and Anderson (1980) do not support the use of pheromone traps for the purpose of timing insecticide applications in potatoes in North Carolina. In Minnesota, Legg and Chiang (1984, 1984b) attempted to couple a correlation between pheromone trapped (PT) males and black light trapped (BLT) females with a correlation between the BLT females and oviposition, leading to a two step predictive model of egg mass density based on PT males. This last relationship is the essence of what we tried to accomplish in Michigan, using pheromone trap catch 67 n’vvaf 68 activity as an indicator of potential egg mass laying in various vegetable fields, to ultimately establish action guidelines for growers to follow . Our original hypothesis stated that increased pheromone trap catches were the result of increased population emergence and activity, which should correlate to a higher number of egg masses being deposited. During bouts of lower trap catches, the insects activity is thought to be lower with fewer egg masses being deposited. By finding a level of flight activity that corresponded to zero egg masses laid, or a level that the crop could tolerate, growers could delay their initial spray until the trap activity exceeded this threshold. Determining how low this threshold is, if it exists, can have a substantial impact on management because a very large proportion of all trap catches occur under low flight activity conditions (Chapter 1, Figures 1 & 2). We were not able to establish a direct correlation between male flight and oviposition, or define a consistent flight activity range where zero egg masses (and very low damage) were found. This may be due to several sources of variation such as the weather, geographic location, diversity of action sites, and female calling interference. Thus our intention of using pheromone traps to measure flight activity to index potential damage via egg mass prediction, was not reliable. I feelit is important to note that the field and sampling conditions under which these experiments were carried out, may have limited our ability to establish such a relationship. Sampling was carried out only during the latter part of 1991 due to logistics, and during 1992, low flight activity and scarce egg mass data, left many of our hypotheses untestable. I feel the flight and oviposition interaction needs to be investigated for another two field seasons before concluding there is no relationship. The flight data that was collected has produced several positive findings in spite of not supporting the major objective. 69 Although pheromone trap catches cannot directly predict egg masses, by observing increasing or decreasing male flight activity at several sites in the network, trends occurring on a regional or state level could be revealed. The ability to see a flight initiate, reach peak activity, and then start to decline provides valuable information to researchers, pest managers, and growers, cueing them into how the population is changing. Using the flight activity curves generated over the past three years, degree day (base 50° F) windows of second flight initiation and peak activity have been calculated at the local, regional and state level. It is pertinent to note that these values include extreme , conditions seen in 1991(hot) and 1992 (cold). This should enable growers to anticipate when these flight events are likely to occur under a range of weather conditions, allowing them time to better prepare a management strategy. In a monitoring capacity, the pheromone traps have been a success by demonstrating that insect activity does fluctuate throughout the season. Educating the grower to better understand the insects biology will allow them to move away from conventional scheduled control and apply their knowledge of pest management to novel deve10pments. As the options for insect management and control become limited due to increased resistance and decreased chemical products, monitoring insect populations and understanding economic thresholds will become more important to successful growers. There are other interesting aspects of this insect that were not directly a part of this research project. The first is how the two different pheromone races of corn borer, New York and Iowa, might impact or change current insect management practices in Michigan. Though‘we trapped for both races in 1990 and 1992, we detected very few New York type moths. These trapped moths in fact may be Iowa type moths that happened to bumble into the wrong trap. Morphologically, the two types are indistinguishable, but electrophoretically, there is an allozyme which allows researchers 70 to identify both strains (pers. comm., Mark Scriber). Having trapped only a few suspected New York type moths, is undoubtedly a relief to Michigan growers. It is documented that this strain has a vast fruit and vegetable host range in comparison with the Iowa type, which is narrower but perhaps expanding. The second interesting aspect of corn borer biology that could not be tested by this research design, is determining where univoltine and bivoltine populations of corn borer exist. Michigan, according most recently to Palmer et al. (1985) and Showers et al. (1989), is divided into three voltine zones; the first in southern lower peninsula is bivoltine, the second in central lower peninsula is transition between univoltine and -__. -—-—. bivoltine, and from there northward only univoltine corn borers. This is corroborated for the most part in the seasonal flight activity graphs in the Appendix. However, the traps are not voltine specific, leaving some interpretation of the graphs as far as when peaks are possible single or mixtures of voltine emergences. It is possible to have sympatric populations of distinct voltine corn borers in the same county. By using pheromone traps alone in cases of overlap to determine voltinism, is subjective to say the least. Knowing how manygenerations to expect in an area can certainlyaid in developing a management plan. In future research efforts, I would recommend that a much more rigorous site selection process be instituted, trying to standardize sites for comparison in a nearby locality. Characteristics such as field size, crop, neighboring crops, similar action site areas, placement of traps in those areas, history of infestations, and current management practices, can all effect trap catch results. The growers chosen for this "on farm" research need to be supporting and aware of the basic goals to be accomplished, and willing to make small sacrifices of either time or resources to help meet the goals outlined. By looking at how activity can vary between nearby sites, while at the same time looking at 71 how activity varies across the state, may provide pest management insight beyond the scope of this study. What also needs to be considered is a control area where spraying is not permitted, to see how pesticides interfere with the relationship between flight and oviposition, by repelling or killing corn borers. If this is accomplished, there is still the concern of how to appropriately deal with immigration and emigration of adult moths to and from the monitored field. The understanding of corn borer movement between fields is a substantial component in developing a relationship between flight activity and egg mass laying. Lack of accounting of this component may explain why the relationship could not be established. APPENDIX ECB / Trap / Week ECB / Trap / Week 72 12 A 2460 9 ~ —0_ SWMREC-Sweet Corn 160 180 200 220 ‘7 240 ‘ V I 260 280 B —O— Thome-NA 160 180 200 220 Julian Date 240 260 Figures 7 A & B. 1990 Seasonal flight activity curves for European corn borer in Berrien (A) and Kent (B) counties. Degree day acccumulation (base 50 F) shown beside second flight peaks. ECB / Trap / Week ECB / Trap / Week 73 ‘ C —O— Klutchey-Sweet Corn 3- + Oliver-Peppers 2101 - 180 200 220 240 260 280 3 D 2101 2' - 1— .— 0 . . , . . . . 180 200 220 240 260 280 JulianDate Figures 7 C & D. 1990 Seasonal flight activity curves for European corn borer in Macomb (C) and Monroe (D) counties. Degree day accumulation (base 50 F) shown beside second flight peaks. ECB / Trap / Week ECB / Trap / Week 74 50 A —0— Van der Band-Sweet Corn _ 40 " 2693 " 30' ' 20‘ b 10' ' 1 j 240 260 280 1 o . . . . . 160 180 200 220 2M) B |—-O— SWMREC-Sweet Corn 2744 1 00 - 2050 O . u . r - T ' I 160 180 200 220 240 fi f 260 280 Julian Date Figures 8 A & B. 1991 Seasonal flight activity curves for European corn borer in Allegan (A) and Berrien (B) counties. Degree day accumulations (base 50 F) shown beside second and third flight peaks. ECB / Trap / Week ECB / Trap / Week 75 200 C 1807 ‘—0_ Strouse-Peppers + Strouse-Peppers 100 ' . o - 160 180 200 220 240 260 280 D [—0— Morse-Peppers 2623 + Miedema-Sweet Corn fi 160 180 200 220 240 260 280 Julian Date Figures 8 C & D. 1991 Seasonal flight activity curves for European corn borer in Gratiot (C) and Kent (D) counties. Degree day accumulation (base 50 F) shown beside second and third flight peaks. ECB / Trap / Week ECB / Trap / Week 76 200 E —0_ DeCock-Sweet Corn , + Krause-Field Corn ‘ 2767 160. 180 200 220 240 260 280 600 F [—0— Cooper-Sweet Corn 7 2311 450' . -l 300‘ 150‘ 0 . 1 . . . , I _ 160 180 200 220 240 260 280 Julian Date Figures 8 E & F. 1991 Seasonal flight activity curves for European corn borer in Macomb (E) and Manistee (F) counties. Degree day accumulation (base 50 F) shown beside third flight peak. ECB / Trap / Week ECB / Trap / Week 77 "'0'— Heck-Sweet Corn J 180 200 220 240 260 280 200 H l—O— Farr- Sweet Corn 2887 100‘ 180 200 220 240 260 280 Julian Date Figures 8 G & H. 1991 Seasonal flight activity curves for European corn borer in Monroe (G) and Muskegon (H) counties. Degree day accumulation (base 50 F) shown beside the second and third flight peaks. ECB / Trap / Week ECB / Trap / Week 78 300 I —O— Vogel-Sweet Corn 2401 200 ‘ 100' 180 - 260 280 J —0_ Cooper-Field Corn + Cooper-Sweet Corn 180 200 220 240 Julian Date Figures 8 I & J. 1991 Seasonal flight activity curves for European corn borer in Newaygo (I) and Oceana (J) counties. Degree day accumulation (base 50 F) shown beside second and third flight peaks. ECB / Trap / Week ECB / Trap / Week 79 300 71 —O— Vlasic-Peppers N O o r _L O O l 2548 210 220 230 240 2550 2(50 , f 27W) 80 . L —O— Vlasic-Peppers 60' 40' 20‘ 2708 O ' r ' l ' 210 220 230 r 2110 2550 Julian Date j 2(50 1 2713 Figures 8 K & L. 1991 Seasonal flight activity curves for European corn borer in Oceana (K) and Saginaw (L) counties. Degree day accumulation (base 50 F) shown beside third flight peak. ECB / Trap / Week ECB / Trap / Week 80 300 A —O— Vander Band-Sweet Corn 200‘ 100‘ 0 ' . 140 160 Y 180 200 220 1735 240 'V I 260 280 B [—0— SWMREC- Sweet Corn j 140 160 180 200 220 Julian Date 240 260 280 Figures 9 A & B. 1992 Seasonal flight activity curves for European corn borer in Allegan (A) and Berrien (B) counties. Degree day accumulation (base 50 F) shown beside second flight peak. 81 1 00 . 1816 % 80 _ C _O_ Shoub-Peppers _ é) . + Graham-Sweet Corn \ 60 - _‘U— Roberts-Peppers - Q—l . . S F - \ CG 0 :— LL] 160 180 200 220 240 260 280 10 _0_ Strouse-Bells 1645 1816 § 8 - C + _ Strouse-Cherry <1) 3 \ 6 - On 8 [-1 4 - \ 6'3 LL] 2 0 . . . _fi 180 200 220= 240 260 280 Julian Date Figure 9 C. 1992 Seasonal flight activity curves for European corn borer in Gratiot (C) county. Degree day accumulation (base 50 F) shown beside second flight peak. ECB /Trap / Week ECB / Trap / Week 82 30 D —O— Horticulture Farm-Peppers I 1914 20 " ' 1 0 " f o . r u I l 160 180 200 220 240 260 280 20 E '43— Meidema-Sweet Corn —0- Morse-Peppers + Morse-Peppers 10 " ” o -—~D>U4D==D-l-D—-—cr—c1—a—G . a; . 160 180 200 220 240 260 280 Julian Date Figures 9 D & E. 1992 Seasonal flight activity curves for European corn borer m Ingham (D) and Kent (E) counties. , Degree day accumulation (base 50 F) shown beside second flight peak. ECB / Trap / Week ECB / Trap / Week 83 F —O— Decock-Sweet Corn 60 " 1725 ' 140 160 180 200 220 240 260 280 20 G —O— Fleming-NA 1790 + Vermeesch-NA t 10" ’ 0 ' I - I .. ,. .,A r . I . 140 160 180 200 220 240 260 280 Julian Date Figures 9 F & G. 1992 Seasonal flight activity curves for European corn borer in Macomb (F) and Midland (G) counties. Degree day accumulation (base 50 F) shown beside second flight peak. ECB / Trap / Week ECB / Trap / Week 84 —O"' Charter-Sweet Corn 160 180 2131 r T j 200 220 240 260 280 4O 30‘ 20‘ 10‘ —0— Karnematt-Peppers 1754 f O 140 160 180 200 220 240 JulianDate 260 280 Figures 9 H & I. 1992 Seasonal flight activity curves for European corn borer in Monroe (H) and Newaygo (I) counties. Degree day accumulations (base 50 F) shown beside second flight peak. ECB / Trap / Week ECB / Trap / Week ECB /Trap / Week 85 80‘ F—D— 1990 Yagalia-Field Corn ] 60‘ 40‘ r 20‘ Y I 240 260 280 o . , v I v I 140 160 180 200 220 ' I 10 C0— 1991 Yagalia-Field Corn I 0 ' I ' Iv ' I V I r I v I v 140 160 180 200 220 240 260 280 , [+ 1992 Yagalia-Field Corn 1 140 160 180 200 220 240 260 280 JulianDate Figure 10 A. 1990, 1991, and 1992 multi-year site seasonal flight activity curves for European corn borer in Bay county. Degree day accumulations (base 50 F) shown beside second flight peaks. ECB /Trap / Week ECB / Trap / Week ECB / Trap / Week 86 10 l—D— r990 Colllns-Fleld Corn 3 o ' I V I r I 140 160 180 200 220 240 17 260 280 80 [—0— 1991 Collins-Field Corn J 60‘ 40‘ 2916 *1 220 240 V 260 280 [—l— 1992 Collins-Field Corn J 90‘ -l 60‘ 30‘ 1914 o . . 140 160 Y 180 200 220 240 Julian Date '— 260 280 Figure 10 B.‘ 1990, 1991, and 1992 multi-year site seasonal flight activity curves for European corn borer in Ingham county. Degree day accumulations (base 50 F) shown beside second and third flight peaks. ECB /Trap / Week ECB / Trap / Week ECB /Trap / Week 87 10 + 1990 Evans-Peppers 160 180 200 220 240 260 280 300 ——O-— 1991 Evans-Peppers .2289 200 ‘ 100* 1746 0" r I 160 180 200 220 240 r 260 280 —U— 1992 Evans-Peppers V 160 180 200 220 240 260 280 Julian Date Figure 10 C. 1990, 1991, and 1992 multi-year site seasonal flight activity curves for the European corn borer in Oceana county. Degree day accumulations (base 50 F) shown beside second and third flight peaks. ECB / Trap / Week ECB [Trap / Week ECB / Trap / Week 88 5 1 ["D— 1990 Ramey-Peppeg] 4‘ - 3r . 2* . 1 .. u- 140 160 180 200 220 240 260 280 400 . 'F0— 1991 Ramey-Peppers] 2289 300‘ ’ 200‘ . 100' ' 1654 o V I V I r v r v . . 140 160 180 200 220 240 260 280 10 + 1992 Ramey-Peppers] 5‘ . o f . - . - . . . . . 140 160 180 200 220 240 260 280 Julian Date Figure 10 D. 1990, 1991, and 1992 multi-year site seasonal flight activity curves for European corn borer in Oceana county. Degree day accumulations (base 50 F) shown beside second and third flight peaks. ECB / Trap / Week ECB / Trap / Week ECB / Trap / Week 89 10 —C}'— 1990 Dykstra-Sweet Corn 160 180 200 220 240 260 280 —0— 1991 Dykstra-Peppers 2 5 69 200 ‘ 160 180 200 220 240 260 280 _+_ 1992 Dykstra-Sweet Corn 160 180 200 220 240 260 280 Julian Date Figure 10 E. 1990, 1991, and 1992 multi-year site seasonal flight activity curves for European corn borer in Ottawa county. Degree day accumulations (base 50 F) shown beside second flight peaks. ECB / Trap / Week ECB /'I‘rap / Week ECB / Trap / Week 90 50 40 l 1990 Heminder-Sweet Corn I 2008 _ l 30 ‘ _ 20 r _ 1O ‘ _ l o V I V f V I I V I V 140 160 180 200 220 240 260 280 4O _. [—0— 1991 Hemmeter-Sweet Corn] 2708 ’ 3O ‘ . 20‘ 1803 . 1 0 ‘ . O I V V I V I v I . v 140 160 180 200 220 240 260 280 10 I+ 1992 Hemmeter-Sweet Corn I 1739 14o réo 180 200 220 240 vzéo '280 Julian Date Figure 10 F. 1990, 1991, and 1992 multi-year site seasonal flight activity curves for European corn borer in Saginaw county. Degree day accumulations (base 50 F) shown beside second and third flight peaks. ECB / Trap / Week [—0— 1991 Morrison-Sweet Corn I 2741 r 80 r . i 60‘ 40‘ ECB /Trap / Week 20‘ [+ 1992 Morrison-Sweet Corn ] 1798 ECB /Trap / Week 150 200 .230- V300 Julian Date Figure 10 G. 1990, 1991, and 1992 multi-year site seasonal flight activity curves for European corn borer in Van Buren county. Degree day accumulations (base 50 F) shown beside second and third flight peaks. ECB / Trap / Week ECB /Trap / Week ECB /Trap / Week 92 40 , “—0— 1990 Raijer-Sweet Corn] 30‘ 20‘ [—0— 1991 Raiier-SW‘!et cm] 2880 30‘ 20‘ 150' . 200' 250 300 + 1992 Raijer-Sweet Corn I 150' ‘ v 7200 250 300 JulianDate Figure 10 H. 1990, 1991, and 1992 multi-year site seasonal flight activity curves for European corn borer in Van Buren county. Degree day accumulations (base 50 F) shown beside second and third flight peaks. 93 Figure 11. Site distribution of the European corn borer monitoring network in Michigan's lower peninsula, 1990-92. The region each site belongs to is also shown on the distribution map. Site Abbreviation Years involved Charter CHA 1992 Collins COL 1990, 91, 92 Cooper COO 1991 DeCock DEC 1991, 92 Dykstra DYK 1990, 91, 92 Evans EVA 1990, 91, 92 Farr FAR 1991 Fleming FLE 1992 Graham GRA 1992 Heck HEC 1991 Hemmeter HEM 1990, 91, 92 Karnematt KAR 1992 Klutchey KLU 1990 Krause KRA 1991 Mathis MAT 1990 Miedema MIE 1991, 92 Morrison MORI 1990, 91, 92 Morse MORS 1991, 92 Oliver OLI 1990 Ramey RAM 1990, 91, 92 Razjer RAZ 1990, 91, 92 Roberts ROB 1992 Schoub SCH 1992 Strouse STR 1991, 92 SWMREC SWM 1990, 91, 92 Thome THO 1990 Vander Band VAN 1991 Vermeesch VER 1992 Vlasic VLA 1991 Vogel VOG 1991 Yagalia 1990, 91, 92 93a C00 coo m “G VL EVA voc VER-JL‘i RAM KAR ’ STR HEM scrr VLA FAR nos , CRA j TL} MORS DYK T110 MIE KLU KRA VAN HOR DEC cor. OLI moat RAz HEC SWM CHA MAT LITERATURE CITED 94 Literature Cited Apple, J. W. 1952. Corn borer development and control in canning corn in relation to temperature accumulation. J. Econ. Ent. 45:877-879. Arbuthnot, KB. 1949. 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