The Influence of Environmental Factors on Aedes Triseriatus Breeding and Egg-Laying

Tree-hole Mosquito Surveillance and Control: The Influence of Environmental Factors on Aedes triseriatus Breeding and Egg-laying

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Public Health in the Graduate School of The Ohio State University

Pei-Yu Chiang

Graduate Program in Public Health

The Ohio State University

2012

Master's Examination Committee:

Dr. Qinghua Sun, Advisor

Dr. Song Liang

Dr. Jianrong Li

Pei-Yu Chiang

2012

Abstract

A nine-week field work was conducted during summer 2010 (July 19 to September 17) to better understand the distribution of the eastern tree-hole mosquito, Aedes triseriatus, with emphasis on the potential environmental factors that may have impacts on its breeding and egg-laying behaviors. Five neighborhoods of Franklin County, Ohio were chosen and ten oviposition traps were set at each location. To examine mosquito preference to habitats, two different elevations and six substrate types were selected and included into the weekly egg surveys. Eggs were then hatched and reared into emergence in the mosquito control facility, followed by identification to species.

Weekly total number of eggs among all five locations showed the highest count (6561) in mid August (week 5). Egg counts for Gahanna and Green Lawn Cemetery peaked (471 and 3169, respectively) in week 5 as well. Egg counts for Obetz Memorial Park peaked

(2981) a week earlier, while those for Prairie and Hilliard Municipal Park peaked (1764 and 298, respectively) one or two weeks later. Green Lawn and Obetz had significantly more eggs deposited than the others (p= 0.004). No significant difference in mean egg counts among ovitrap sites (of the same location) was observed; however, ovitraps placed at ground level (rather than those at elevation) in Hilliard received significantly more eggs (p=0.004). Seasonal factors such as temperature and other environmental

ii factors in response to the seasonal effects were suggested from the observed variations of egg counts over the nine weeks. Only Green Lawn and Obetz showed positive relationship between temperature and egg-laying. Substrates with darker color showed more egg deposition though not statistically supported. Total 793 Aedes triseriatus and 1480 Aedes albopictus were identified and positive associations in abundance of these two species were observed mostly. Evidence accumulated provides insights to the site selection for local mosquito surveillance and control.

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This document is dedicated to my family.

Acknowledgements

I would like to thank Paul Rosile, the former Environment Health Director and Assistant

Health Commissioner at Franklin County Board of Health, for accepting me to take part in the development and operation of their La Crosse virus surveillance program. For field sampling and collection of the specimens, I would like to thank Dr. Daniel

Markowski of the Vector Disease Control International (VDCI), and his crew members

John Grubbs, Matt Bolenbaugh, Ryan Fielden, Justin Fielden, and Gina Fanelli. For the assistance and guidance in mosquito rearing, I would like to thank Yoshio Ikeda, a PhD candidate of the Ohio State Biochemistry Program, who is experienced in maintaining

Aedes, Anopheles, and Culex mosquito colonies in the laboratory. I would also like to thank Dr. Donald Dean at the Biochemistry Department for his generosity allowing me to use his lab space and equipment for adult mosquito identification and storage. Last, but not the least, I would like to thank Drs. Qinghua Sun, Song Liang, and Jianrong Li for reviewing this work and to thank Paul Rosile again for valuable discussion during the preparation of this report.

Vita

2001 ...... B.S. Soil and Environmental Sciences, National Chung-Hsing University, Taichung, Taiwan

2009 to present ...... M.P.H. Environmental Health Sciences, The Ohio State University, Columbus, OH

Publications

Chiang, P.-Y., Goodeman, P., Ergun, A. (Sept 2011). Community Based Food System. In Revisioning Weinland Park (Volume 2) (pp.14-15). Columbus, OH: The Ohio State University, Knowlton School of Architecture.

Chiang, P.-Y., Arroyo-Rodriguez, A., Evans-Cowley, J., et al. (Sept 2011). Savor the Coast: A Recipe for a Sustainable Coast. Columbus, OH: The Ohio State University.

Chiang, P.-Y., Arroyo-Rodriguez, A., Evans-Cowley, J., et al. (Sept 2011). Mississippi Gulf Coast Food System Stakeholder Analysis. Columbus, OH: The Ohio State University.

Chiang, P.-Y., Arroyo-Rodriguez, A., Evans-Cowley, J., et al. (Sept 2011). Mississippi Gulf Coast Food System Assessment. Columbus, OH: The Ohio State University.

Fields of Study

Major Field: Public Health Specialization: Environmental Health Sciences

Table of Contents

Abstract ...... ii

Acknowledgements...... v

Vita ...... vi

Publications ...... vi

Fields of Study ...... vi

List of Tables ...... xi

List of Figures ...... xii

1. Introduction and Background ...... 1

Arboviral Encephalitis ...... 1

La Crosse Encephalitis ...... 2

Mosquito Aedes triseriatus ...... 4

Environmental Factors ...... 5

Gaps & Objectives ...... 7

2. Materials and Methods ...... 8

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2.1 Study Area and Sites Selection ...... 8

2.2. Field Sampling ...... 9

2.2.1. Egg Surveys by Oviposition Traps ...... 9

2.2.2. Larval Surveillance ...... 10

2.2.3. Adult Surveillance ...... 10

2.3. Mosquito Rearing ...... 11

2.3.1. Equipping and Operating the Insectary ...... 11

2.3.2. Collecting, Handling, and Hatching Eggs ...... 12

2.3.3. Larval Rearing ...... 13

2.3.4. Handling, Counting, and Separating Pupae ...... 13

2.4. Adult Mosquito Collection and Identification ...... 13

2.5. LAC Viral Assay/ Virus Detection ...... 15

2.6. Geographic Information System (GIS) Modeling ...... 16

2.7. Statistical Analysis ...... 16

3. Results ...... 18

3.1. Total Egg Counts and Weekly Patterns ...... 18

3.2. Elevation Preference ...... 22

3.3. Substrate Preference ...... 25

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3.5 Adult Mosquito Species ...... 28

4. Discussions ...... 32

4.1. Temperature and Weather Effects ...... 32

4.2. Habitat Preference ...... 37

4.3. Sensitive Male Embryos and Larval Inhibition ...... 44

4.4. Ochlerotatus triseriatus vs. Aedes albopictus: Abundance and Correlation ...... 44

4.5. Quality of the Data ...... 46

5. Concluding Remarks ...... 49

References ...... 50

Appendix A: Aerial Views of the LAC Virus Surveillance Locations ...... 57

Appendix B: Oviposition Traps: Sites and the Setups ...... 60

Appendix C: Tallies on Ovitrap Preference ...... 64

Appendix D: Temperature Data Analyses ...... 66

Appendix E: Egg Survey/Habitat Preference Data Analyses ...... 68

I. Egg Counts vs. Locations ...... 68

II. Egg Counts vs. Ovitraps (Sites) ...... 70

Gahanna ...... 70

Green Lawn Cemetery ...... 73

Hilliard ...... 75

Obetz ...... 78

Prairie ...... 81

III. Egg Counts vs. Substrates...... 83

List of Tables

Table 1. Heights of the oviposition cups at surveillance locations...... 23

Table 2. Tallies on ovitrap preference…………………………………………………………………………..65

List of Figures

Figure 1. California Serogroup Virus Neuroinvasive Disease Cases Reported from 1964 to

2010 in Ohio...... 4

Figure 2. Egg survey over the nine weeks...... 20

Figure 3. Weekly oviposition eggs among five surveillance locations...... 21

Figure 4. Total egg counts over the nine weeks for the five locations...... 21

Figure 5. Egg integrity count diverges from the general weekly total...... 22

Figure 6. Mosquito preference to the level of elevation...... 24

Figure 7. Mosquito preference to substrates with dark color over light color...... 26

Figure 8. Mosquito preference to different types of substrate...... 27

Figure 9. Emerged adult mosquitoes over the nine weeks of collection...... 29

Figure 10. Quantitation and identification of adult mosquitoes for each surveillance location...... 30

Figure 11. Weekly numbers of emerged adult mosquitoes over the nine weeks...... 31

Figure 12. VDCI insectary temperature record...... 33

Figure 14. Scatterplot analyses on the relationship between temperature and egg counts.

...... 35

Figure 15. Individual Value Plot of the five sampling locations...... 38

xii

Figure 18. Scatterplot of Aedes albopictus vs. Ochlerotatus triseriatus ...... 46

Figure 19. Graphical Summaries of the Temperature Data ...... 67

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1. Introduction and Background

While global warming remains an issue of debate, evidence of its effects on increases of emerging or changes in patterns of re-emerging infectious diseases have been observed

(Gould & Higgs, 2009; World Health Organization, 2012). Vector-borne diseases are a great proportion of the emerging and re-emerging infectious diseases (Leisnham &

Juliano, 2012). One of the well-known arboviruses, West Nile virus (WNV), has emerged and caused epidemics in North America. Though availability of competent vector species and susceptible species of migratory birds were the most important factors that contributed to local outbreaks in 1999 rather than climate change, it is believed that environmental conditions such as local temperature and rainfall were very important determinants in WNV transmission, and that mild winter and early spring and summer were the causes for the recent 2012 outbreak (Gould & Higgs, 2009; Jaslow, 2012). In view of this, it is necessary to understand the biology, ecology, and interactions of the arboviruses and their vectors and hosts, and to have a standardized surveillance and control program in place, which is predictive, proactive, and efficient in arbovirus detection, isolation, and its disease reporting.

Arboviral Encephalitis

Arboviruses, or arthropod-borne viruses, maintain in nature through biological transmission between vertebrate hosts and blood feeding arthropod vectors such as 1 mosquitoes (Centers for Disease Control and Prevention, 2005). They occur throughout the world, but each type of virus has its geological distribution determined by the range of its vector(s) (Blair, Adelman, & Olson, 2000). Occurrence of disease in humans or clinical illness in domestic animals results from the blood feeding behavior of the infected vector escaping from its natural focus. It tends to be seasonal and mostly occurs from June through September. Although human infections are usually asymptomatic, they may lead to encephalitis with a fatal outcome (Centers for Disease

Control and Prevention, 2005). With the emergence of arbovirus diseases, it is a serious public health concern under the circumstances that no effective antiviral drugs or human vaccines available for the arboviral encephalitides in the United States.

La Crosse Encephalitis

La Crosse (LAC) virus appears to be the primary cause of arboviral encephalitis in the U.S. for children under 16 years old (B. J. Beaty, Rayms-Keller, Borucki, & Blair, 2000). It is distributed throughout the eastern half of the U.S. and is endemic in the Great Lakes states (Gabitzsch, Blair, & Beaty, 2006). The principle vector of LAC virus is the eastern tree-hole mosquito Aedes triseriatus. In nature, the virus cycles mostly in woodland habitats between its invertebrate vector (eastern tree-hole mosquitoes) and vertebrate hosts (squirrels and chipmunks) (Gabitzsch, Blair, & Beaty, 2006). Maintenance and transmission of the virus occurs when its primary vector and the amplification hosts are in close contact and when persons enter the areas and are bitten by infected mosquitoes (Haddow, Jones, & Odoi, 2009). LAC encephalitis is predominantly a

2 pediatric disease with average age of 8 years. Human infections may result in severe illness though the mortality rate is low (<1%) (Ohio Department of Health, 2008; Ohio

Department of Health, 2012). Every year from late spring through early fall, about 80-

100 LAC encephalitis cases are reported in the U.S, and among which more of the cases in recent years are from mid-Atlantic and southeastern states, as compared with the historic records which were mostly from upper mid-western states (Minnesota,

Wisconsin, Iowa, Illinois, Indiana, and Ohio) (Centers for Disease Control and Prevention,

2011b). From 1963 to 2010, there were 1050 serologically documented cases in Ohio, more than any other state in the U.S. Seven fatalities, all children, have been documented. Number of cases in Ohio can be seen in Figure 1 (Centers for Disease

Control and Prevention, 2011a). As of April 2012, the cumulative 2011 data posted and compiled by U.S. Geological Survey and Centers for Disease Control and Prevention (CDC) indicates that there were 130 national cumulative human disease cases reported, and about 38.5% were from Ohio (50 cases). It was the year with the new height in cases and those were from 34 counties including Franklin County (2 cases) (US Geological

Survey, 2012).

30 Cases 20

1980 2002 1964 1966 1968 1970 1972 1974 1976 1978 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2004 2006 2008 2010 Years

Figure 1. California Serogroup Virus Neuroinvasive Disease Cases Reported from 1964 to 2010 in Ohio. Data were extracted from CDC case report.

Mosquito Aedes triseriatus

Aedes triseriatus, now Ochlerotatus triseriatus, live in areas where temporary pools of stagnant water can be established such as tree holes, tires, or gutters. Artificial containers are also common habitats. Only females take blood meals and lay eggs close to the shallow pool of water. Eggs hatch when the pool is flooded and when the conditions are right. Larvae are fed by leaf debris, other organic materials, and microorganisms in pools (B. Moore, 2001). Pupae are the last aquatic stage of the mosquito life cycle followed by emergence into adults. Adult Ae. triseriatus have dark palps and proboscis; their wing scales are dark and hind legs are dark without white bands. The most distinguishable characteristics are the dark scutum without lines or patterns but with patches of silver white scales along sides and on thorax, and with

4 lateral basal pale patches on abdomen (Cutwa-Francis & O'Meara, 2008). Female Ae. triseriatus get infected with LAC virus when taking blood meals on the infected vertebrates. The virus can be transovarially transmitted and overwinter (diapause) in eggs or horizontally transmitted through mating to males by the infected females.

Though some study models predicted that transovarial transmission (TOT) alone is insufficient for LAC virus maintenance in nature, others showed that TOT is an extraordinary method of amplification and could affect viral amplification and maintenance (Reese, Beaty, Gabitzsch, Blair, & Beaty, 2009; Reese et al.,

2010) .

Environmental Factors

Many studies have examined how environmental factors could have impacts on mosquito communities -- its geographical distribution and reproduction behavior.

Evidence has been observed demonstrating that climate, land use, and biological invasion affect mosquito communities, particularly their immature stages (eggs and larvae) (Conley, Watling, & Orrock, 2011; Gould & Higgs, 2009; Khatchikian, Dennehy,

Vitek, & Livdahl, 2009; Leisnham & Juliano, 2012). One study on frequency of occurrence for Ae. triseriatus at different elevation, in different months of the year, and in specific types of larval habitats for LAC encephalitis in West Virginia (WV) showed that larvae are equally distributed across all elevation and predisposed to shaded habitats

(Joy & Hildreth-Whitehair, 2000). Another study on various habitat parameters for LAC virus in an enzootic area in WV presented that Ae. triseriatus population densities were

5 higher in sugar maple/red maple than in hemlock/mixed hardwood habitats, and sites containing artificial containers had higher population than those without (Nasci et al.,

2000). Container-type habitats are generally divided into natural (such as tree holes) and man-made or artificial (such as water tanks/bottles, tires, etc). Aedes albopictus and

Oc. triseriatus were two of the 31 species reported breeding in artificial containers within cemeteries around the world (Vezzani, 2007), and Ae. albopictus being an invasive species was found more frequently than Oc.. triseriatus (Juliano, Lounibos, &

O’Meara, 2004). Studies suggest that cemeteries be good habitats for artificial container-breeding mosquitoes mainly because of the environmental characteristics they would provide, such as sugar substances from vegetation, blood from human visitors and caretaker or small animals, shelter area inside house or rodent burrows under man-made structures, amongst grass or other vegetation, etc (Vezzani, 2007).

Also, land use and distribution of infected mosquitoes have been studied for Jamestown

Canyon virus (categorized as California serogroup as same as LAC virus) in Connecticut but showed no difference between selected rural and urban areas (Andreadis, Anderson,

Armstrong, & Main, 2008). Besides, a study on habitat preferences of tree-hole or container mosquitoes in southwestern Virginia showed that Ae. albopictus preferentially oviposits in the yard surrounding the home (open residential areas) over forested area, but no preference was observed for Oc.triseriatus (Barker, Paulson, Cantrell, & Davis,

2003). Moreover, local factors such as water volume, leaf litter mass and top predator density have been examined showing strong influence on mosquito species presence and density (Paradise et al., 2008). 6

Gaps & Objectives

Though LAC virus transmission is known to be broadly associated with hardwood forests, the influence of habitats and factors that define habitats on virus distribution and transmission is not fully understood. No recent study has been conducted specifically for niches in Ohio in terms of the relationship between environmental factors and Ae. triseriatus mosquito distribution. Therefore, the ultimate goal of this project is to develop and/or improve LAC virus surveillance and control program for the Ohio local health department. To achieve the goal, we aimed at studying the environmental factors that are necessary for, or have effects on, the vector Ae. triseriatus breeding and egg-laying. It is expected that through this study, we could gain a better understanding of the impacts of environmental factors on the life cycle of LAC viruses and other arboviruses, to determine optimal protocol to efficiently detect LAC virus before mosquitoes even emerge from larvae. It is believed that the study will provide knowledge that could be used to design a new or strengthen the current LAC virus surveillance to fit local capabilities and needs.

2. Materials and Methods

2.1 Study Area and Sites Selection

The study area includes 50 sites within 5 locations of adjacent neighborhoods of Franklin

County, Ohio, excluding the jurisdiction of City of Columbus (Appendix A, B). Gahanna,

Hilliard, Obetz, and Prairie were 4 of the neighborhoods chosen, where residential areas are close-by and surrounded with overgrown vegetation and heavily wooded areas.

They are also routinely under West Nile Virus surveillance. Green Lawn was newly chosen mainly for the purpose of this tree-hole mosquito (Ae. triseriatus) surveillance project. It is occupied by a 164-year-old cemetery over 1.5 km2 and has many artificial containers suitable for mosquito breeding, such as implanted flower pots or discarded bottles. Five locations were inspected before the site selection was finalized. Ten sites for each location were selected based on the characteristics of the surrounding environment such as tree-holes or tree-hole-liked structures, shaded and wooded spots, evidence of presence of small animals and humans, etc. Depending on the size of the location, sites could be 1 m as close to each other or about 100 m as far.

2.2. Field Sampling

2.2.1. Egg Surveys by Oviposition Traps

Ae. triseriatus eggs were collected by oviposition traps from the above mentioned 50 sites during mid July till early September of 2010. The oviposition trap was made by a

12-ounce (355 ml) black plastic cup with a draining hole on the wall about half way up and a strip of a substrate (canvas or other selected materials) clipped on the side of the cup. At each location, 5 oviposition traps were attached to the tree above the ground

(Elevated) ranging from 50-200 cm in height depending on the site condition, and the other five oviposition traps were set at ground level (Low) (Table 1; settings are shown in Appendix B). Once the trap were attached or set, purposely-made stagnant water, which was made by storing a tank of mixture of tap water and fallen leaves under sun over the weekend, was used to fill up the cup till the height of the draining hole submerging the substrate attached. Lastly, some dead leaves or off-the-branch green leaves and/or wood sticks or flakes were added. The traps were left unattended at the sites for 1 week except for the first week which was only four days. It was during the one-week sampling that mosquitoes lay eggs above and near the waterline. Then the substrate cloths (canvas strip with or without egg deposits) were picked up and replaced with new cloths every Friday followed by drying and hatching procedures. Mosquitoes’ preference to different substrates was tested at certain ovitrap sites during two different weeks. In addition to the original cloths, 6 more substrates with different

9 colors and textures were tested: Chipotle napkin, shipping stuffing brown/grey paper, light brown shipping paper, white paper towel, and blue cloth.

2.2.2. Larval Surveillance

Larval surveillance was carried out as a pre-ovitrapping inspection in conjunction with the site analyses to determine appropriate sites for oviposition sampling. We used inexpensive equipment such as a long handled dipper (for dipping into pools or holes), a turkey baster (for transferring sample), and several whirl-pack/Ziploc bags or collection bottles for containing samples to bring back to lab or office. Larval samples then were allowed to mature to adult stage in an emerging chamber for identification.

2.2.3. Adult Surveillance

Traditional CDC light traps and gravid traps are successfully used for West Nile (WN) virus surveillance to collect adult Culex mosquitoes for identification and virus detection

(US Department of Health and Human Services, 2003). However, because it is difficult to catch adult Ae. triseriatus mosquitoes, current LAC virus surveillance is mostly based on oviposition trapping, which takes advantage of their egg-laying behaviors and characteristics. It has proven to be a useful tool for mosquito detection and population size estimation in particular habitats (Obenauer, Kaufman, Allan, & Kline, 2009b). The adult mosquitoes reared from field-collected eggs were used for detecting virus. A trial run was set up using tea traps, made with fresh water and tree leaves, for adult mosquito surveillance when oviposition egg-laying events went low. The traps were

10 collected daily for consecutive 4 days between September 13 and 17, 2010. The result will not be discussed due to insufficient data.

2.3. Mosquito Rearing

2.3.1. Equipping and Operating the Insectary

The insectary was constructed on-site within the Franklin County Board of Health/

Vector Disease Control International (VDCI) mosquito control facility based on the manual published by American Mosquito Control Association (Gerberg, 1979a). The photoperiod of the insectary affects the life cycle of mosquitoes in different stages and was set to a cycle of 14 hours of light and 10 hours of darkness without interfering normal working hours. However, the temperature and humidity, the two most important factors in successful rearing of mosquitoes, were relatively loosely controlled due to a lack of appropriate equipment. The temperature was controlled to target for

80°F (±5°F) or 27°C (±3°C) by turning on a heater in the morning then off before leaving in the evening. Degree Fahrenheit was recorded at least twice a day when operating the heater and that at an additional time point around noon was also recorded. The insectary or VDCI unit did not maintain 7-day operations; therefore, the temperature over the weekend was close to ambient, while 14-10 day-night cycle remained. The insectary temperature over the whole period of time handling eggs, larvae, and mosquitoes was monitored and documented. Standard restaurant hygiene was followed to ensure clean and sanitary condition for healthy larvae and mosquitoes (MR4

Staff, 2011) . 11

2.3.2. Collecting, Handling, and Hatching Eggs

Wet egg cloths collected back from the field were laid separately in the designated container and air dried over the weekend in the insectary for 4 days for embryonic development (Gerberg, 1979b; Gerberg, 1979c). Some cloths, mostly those collected in earlier 1 or 2 weeks, were left for more than 4 days until almost completely dry; however, pieces of wet paper towel were kept with un-entirely dried cloths in Ziploc bags in the following most of the weeks to keep the eggs moist until ready to hatch.

Before hatching, counting by brushing off the semi-dry eggs had been tried but decided not to be continued due to the annoying static electricity interfering the handling procedure. The eggs therefore were counted directly on the cloth or substrate and identified to species by color, shape, and surface texture to the best extent (Ross &

Horsfall, 1965). For the substrates with very few eggs, bare-eye counting was sufficient.

However, for those with massive amount of eggs, dissection microscope was used together with estimation, if necessary. After eggs were counted in situ (on the substrate), they were again sealed within Ziploc bags with pieces of wet paper providing the moisture to prevent eggs from drying out until ready to hatch. To hatch the eggs, substrate cloth deposited with eggs were immersed into dechlorinated and reduced or deoxygenated water, made by submerging glass jars into boiling water, capping under water, and then cooling to ambient temperature (Gerberg, 1979b). The jar was recapped with cloths and eggs inside. Generally, if successful, enclosion begins in minutes; however, hatching rate varies due to different conditions of the eggs and may last for about an hour or even longer (Gerberg, 1979c). 12

2.3.3. Larval Rearing

Ideally, Ae. triseriatus larvae are suggested to be seeded into trays at a density of 0.9 larva per ml in medium depth of 1.5 cm (Gerberg, 1979c). Density for other species may vary from 1 larva per ml to 1.4 larvae per ml and medium depth varies from 1.5 to 2 cm

(Gerberg, 1979b). However, since it was relatively difficult to accurately estimate the larvae in massive amount, and with different time frame for hatching and to cover all cloths, around 5-10 cm of dechlorinated (but not deoxygenated) water was used in the clear Sterilite 6-quart storage box with dimensions of 34.6 cm (length) x 22.5 cm (weight) x 35.6 cm (height). More clean dechlorinated water may have to be added from time to time to compensate the evaporation. Goldfish food (TetraMin Tropical Flakes) was used to feed the larvae; the amount used depends on the size and the numbers of the larvae.

2.3.4. Handling, Counting, and Separating Pupae

The pupae were picked and transferred into smaller plastic containers for emerging within 48 hours. The containers were either placed uncovered inside the mosquito cage or left outside the cage covered with home-made net to contain the adult mosquitoes.

2.4. Adult Mosquito Collection and Identification

Adult mosquitoes were kept inside the cage provided with damp paper towel for water and halved grape as food source if the emerging event happened during the weekend.

Otherwise, mosquitoes were collected by an electric aspirator as soon as they fully emerged. They were frozen down to -20°C immediately afterward (before counting and

13 recording). Adult mosquitoes were transferred from VDCI lab to Dr. Donald Dean’s lab in Department of Biochemistry at the Ohio State University and kept frozen at -80°C until ready for identification. Only 2 or 3 vials of the samples were taken out each time to the room temperature for microscopic examination. A dissecting microscope (a low power stereoscopic microscope) of 10 X 10 magnifications was used to identify mosquitoes. Generally, the specimens were first sorted to get rid of non-mosquito debris. Then females (with simple antenna) were separated from males (with feather- like bushy antenna), and only females need to be documented because they are the ones that feed on blood and carry the virus. However, for the purpose of getting a better understanding of the mosquito population and its progeny, both sexes were documented in preparing the thesis. The female mosquitoes were then identified based on the keys illustrating characteristics of different genera and species (Cutwa-Francis &

O'Meara, 2008; Thielman & Hunter, December 2007). Genera were first identified and confirmed, and then species within the genera were followed. For those which could only be identified to the genus, say Aedes, and could not be identified further to species because of the lost of their characteristics due to damages, they were documented into the group Aedes spp. Adult mosquitoes were pooled into different vials by different species and documented by counts, species, and conditions. Immediately afterward, they were stored back to -80°C until ready for viral assays in the future.

2.5. LAC Viral Assay/ Virus Detection

Numerous studies have demonstrated use of direct or indirect techniques for detection and/or diagnosis of LAC virus from field-collected mosquitoes, vertebrate hosts, and human clinical specimens (Balfour, Majerle, & Edelman, 1973; B. J. Beaty, Hildreth,

Blenden, & Casals, 1982; B. J. Beaty et al., 1982; B. J. Beaty, Jamnback, Hildreth, &

Brown, 1983; Calisher, Pretzman, Muth, Parsons, & Peterson, 1986; Chandler, Beaty,

Bishop, & Ward, 1989; Chandler et al., 1998; Hildreth, Beaty, Meegan, Frazier, & Shope,

1982; Hildreth & Beaty, 1983; Jamnback, Beaty, Hildreth, Brown, & Gundersen, 1982;

Lambert et al., 2005; L. P. Wasieloski Jr, Rayms-Keller, Curtis, Blair, & Beaty, 1994).

Standard rapid detection by reverse transcriptase-polymerase chain reaction (RT-PCR) assay developed originally for WN virus has also been applied for use in LAC virus detection (Lambert et al., 2005; Lanciotti et al., 2000). However, only one study was identified, for monitoring dengue virus, using RT-PCR technique applied to experimental and field-collected mosquito larvae (Chow et al., 1998).

In order to test for arbovirus infection, a BioSafety Level 2 lab is required. One of the kits available for (LAC) virus is TaqMan One-Step RT-PCR Master Mix Reagent Kit from

Applied Biosystems (recognized and suggested by a previous OSU-CPH-EHS student

Michael Kimbrell). Ae. triseriatus and Ae. albopictus mosquitoes identified will to be scheduled for the virus test by Franklin County Board of Health. However, due to busy routine WNV surveillance during the season and with limited labor, the assay is on queue for whatever time it takes.

2.6. Geographic Information System (GIS) Modeling

Literature reviews on vector-borne disease transmission led to the assumption that numerous environmental factors may be critical for Ae. triseriatus and LAC virus surveillance and control. To assess the environmental risk factors and hot zones for LAC virus infection, geographic information system (GIS) modeling was used, provided with the present field data and the information of variables such as land use, land cover, distribution of forest or wooded area, tree holes, soils, elevation, slope, proximity to roads, proximity to schools and/or recreational parks, proximity to hydrological network

(streams or wetlands), presence of humans or small animals, etc (Cooke, Grala, & Wallis,

2006; Jacob, Morris, Caamano, Griffith, & Novak, 2011). Potential models are landscape-base model and seasonal model (Cooke, Grala, & Wallis, 2006). The analysis has not completed and will not be discussed.

2.7. Statistical Analysis

Data were graphed by Microsoft Excel for visualization and were analyzed by Minitab 16 statistical software for understanding correlations between environmental variables and the abundance and distribution of eggs and/or mosquitoes. Basic descriptive statistics were examined and the output of analyses are displayed (Appendix D, E). One-way analysis of variance (one-way ANOVA) was chosen to perform hypothesis testing for differences in mean egg counts among 5 sampling locations and among 10 oviposition trap sites of each location. The null hypothesis was that there is no difference in mean egg counts between locations, ovitraps (sites), or substrate types. When the p-value

16 was small enough or smaller than the significance level (alpha-value) selected which is

0.05 so that the null was rejected, Fisher’s comparison grouping was performed subsequently, providing confidence intervals to examine the pairwise differences between means.

3. Results

It was observed that eggs were laid above the water line on the substrate which lies against the wall of the ovitrap. For the substrate with very few deposits, eggs were scattered individually; for those with massive amount, eggs lined up and were in layers sometimes showing zigzag pattern.

3.1. Total Egg Counts and Weekly Patterns

Over the nine weeks of sampling by oviposition traps, among all 5 surveillance locations

(Appendix A), Gahanna and Green Lawn Cemetery had about 27% and 34% of the eggs, respectively, collected from week 5 (August 13-20) (Figure 2a, b). Hilliard had about total 62% of the eggs from week 5 and 7 together; each with around 31% (August 13-20 and August 27-September 3) (Figure 2c). However, eggs laid at Obetz peaked (2981) earlier in week 4, accounting for 31% of the eggs (August 6-13), and those at Prairie peaked (1764; 39%) later in week 6 (Aug 20-27) (Figure 2d, e). Overall, the weekly total number of eggs among all 5 locations was plotted (Figure 3), showing a close-to-bell- shape curve with its highest point (6561) in week 5 as well. In terms of the total number of eggs each location obtained during the 9-week surveillance, Obetz and Green Lawn

Cemetery were the highest two (Figure 4). It was also noted that many eggs in week 5

(August 13-20) were halved and opened with empty shells (data not shown).

Considering possible causes due to insects often found along with the damp substrate, the difference in egg counts between those that were intact verses all individual eggs or egg residues were compared (Figure 5).

Gahanna Green Lawn Cemetery 0910-0917 0910-0917 30 15 0903-0910 0 0903-0910 217 0827-0903 411 0827-0903 1112 0820-0827 153 0820-0827 735 0813-0820 471 0813-0820 3169 0806-0813 303 0806-0813 396 0730-0806 361 0730-0806 2025 0723-0730 21 0723-0730 1680 0719-0723 5 0719-0723 a) b)

Hilliard Obetz 0910-0917 9 0910-0917 35 0903-0910 36 0903-0910 518 0827-0903 298 0827-0903 1263 0820-0827 140 0820-0827 72 0813-0820 291 0813-0820 1518 0806-0813 61 0806-0813 2981 0730-0806 0 0730-0806 1517 0723-0730 115 0723-0730 1187 0719-0723 0 0719-0723 568 c) d)

Prairie 0910-0917 8 0903-0910 22 0827-0903 800 0820-0827 1764 0813-0820 1112 0806-0813 410 0730-0806 177 0723-0730 230 0719-0723 38 e)

Figure 2. Egg survey over the nine weeks. a) Gahanna, b) Green Lawn Cemetery, c) Hilliard, d) Obetz, e) Prairie. Week 1: 0719-0723 and Week 9: 0910-0917. Gahanna and Green Lawn had their highest counts in week 5 (0813-0820). Hilliard had its highest count in week 7 (0827-0903). Obetz had it highest count in week 4 (0806- 0813), and Prairie had its highest one in week 6 (0820-0827).

3500 7000 6561 3000 6000

2500 5000

2000 4000

1500 3000 Egg Counts Counts (#) Egg 1000 2000 (#) Total Weekly Gahanna 500 1000 Green Lawn Cemetery 0 0 Hilliard Obetz Prairie Weeks Weekly Total

Figure 3. Weekly oviposition eggs among five surveillance locations. Weekly Total represents the summation of numbers of eggs from Gahanna, Green Lawn Cemetery, Hilliard, Obetz, and Prairie within the same week. The highest egg count occurred in week 5 as 6561; two low points occurred in week 4 and 6.

12000 9659

10000 9349

8000

6000

4000 Total Egg Counts Egg Total 2000

0 Gahanna Green Lawn Hilliard Obetz Prairie Cemetery Oviposition Sampling Locations

Figure 4. Total egg counts over the nine weeks for the five locations. Obetz had the highest number of eggs collected over the nine sampling weeks, followed by Green Lawn Cemetery, Prairie, Gahanna, and Hilliard.

7000

6000

5000

4000

3000

Overall Counts Egg Counts Counts (#) Egg 2000 Intact-Only Counts

1000

Weeks

Figure 5. Egg integrity count diverges from the general weekly total. There are about 2000 counts of difference in week 5 between overall and intact-only records.

3.2. Elevation Preference

At each surveillance location, total 10 oviposition traps were set up half elevated and half grounded to study mosquito preference to specific traps of different height (Table 1 and Appendix B). By analyzing the frequency of the highest counts on the specific trap during the week, oviposition traps #4, #7, #6/8, #5, and #6 of Gahanna, Green Lawn

Cemetery, Hilliard, Obetz, and Prairie, respectively, were found chosen the most by mosquitoes and laid the highest number of eggs on their corresponding substrates

(Appendix C). All those traps were the ones set on the ground level (Table 1). Similar result can be seen demonstrating various distributions of egg counts among ovitraps.

For Gahanna and Hilliard, eggs were only being deposited in certain ovitraps (Figure 6a, c); however, for Green Lawn, Obetz, and Prairie eggs were relatively evenly, in general, being deposited among traps (Figure 6b, d, e).

Table 1. Heights of the oviposition cups at surveillance locations. Oviposition Gahanna Green Lawn Cemetery Hilliard Obetz Prairie Cups

1 E L E E E 2 L L L L L 3 E E E E E 4 L L L L L 5 E E E L E 6 L E L E L 7 E L E L E 8 L E L L L 9 E L E E E 10 L E L E L Note: E stands for elevated cups and L stands for cups placed on the ground level. Those marked red are the cups most chosen by mosquitoes over the 9 weeks and the ones with the highest egg counts.

500 1800 1600

400 1400 1200 300 1000 800

200 600 Egg Counts Counts (#) Egg

Egg Counts (#)Counts Egg 400 100 200 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 a) Oviposition Cups b) Oviposition Cups

1800 500 1600

400 1400

1200 300 1000 800 200

600 Egg Counts Counts (#) Egg 100 400 Egg Counts Counts (#) Egg 200 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 c) Oviposition Cups d) Oviposition Cups

1000 900 800 700 600 500 400

Egg Counts Counts (#) Egg 300 200 100 0 1 2 3 4 5 6 7 8 9 10 e) Oviposition Cups

Figure 6. Mosquito preference to the level of elevation. a) Gahanna, b) Green Lawn Cemetery, c) Hilliard, d) Obetz, e) Prairie. Dates of the weeks are color coded as shown on the bottom right. For Gahanna, eggs were selectively being deposited among trap #1-5. For Hilliard, eggs were in traps #1, 2, 4, 6, 7, 8, and 10. For Green Lawn, Obetz, and Prairie, all 10 traps had egg deposition, though variation in egg counts can still be observed among traps. 24

3.3. Substrate Preference

Majority of the egg surveys in the field were carried out using the canvas cloth; however, in search for better substrates to optimize the oviposition surveillance methods and to study whether those are factors for oviposition egg laying, 6 other materials with different textures and colors were chosen, along the way, to replace the canvas based on the published documented materials, availability, convenience of handling, and the monetary reasons. Four of the 6 substrates (Figure 7a) were first tested in Green Lawn

Cemetery during the week of July 23-29 with duplications. Data show that the grey shipping paper had the highest number of total eggs collected, closely followed by the brown shipping paper, then the brown Chipotle napkin; whereas the white paper towel had the lowest number of eggs deposited (Figure 7b).

Another trial of testing was performed during the week of August 6-13 using 3 substrates; 2 of which were the same brown or grey shipping paper and the third one was another smoother and lighter brown paper (Figure 8a). One ovitrap of each of the 5 locations was selected. Data show that the light brown paper had about 700 eggs and was the highest among the three substrates tested (Figure 8b).

300 400 250 350

300

200 250 150 200 150 1 Egg Counts Egg 100 100 2 50 50 sum 0 0 Brown Brown Grey White Chipotle Shipping Shipping Paper Napkin Stuffing Stuffing Towel Paper b)

Figure 7. Mosquito preference to substrates with dark color over light color. a) Four substrates (brown Chipotle napkin, brown/grey shipping paper, and white paper towel) were tested for the oviposition egg-laying preference; b) The blue and red bars represent the duplicates of the traps placed at site 1 and 2 and data ranges from 26 to 255 counts; the green dots indicate the total number of eggs for the specific type of substrate with maximum value of 337 and minimum value of 26. The order of the two sets of data varies; however, in general, substrates with darker color rather than the light color had more eggs deposited.

800

700 600 500 400 300 200 100

0 Among the Substrates Amongthe Same Brown-light (bsl) Brown-brown Grey (gs)

Total Counts(#) from the the 5 Counts(#)Locations from Total (bsb) Shipping Shipping Shipping Stuffing Paper Stuffing Paper Stuffing b)

Figure 8. Mosquito preference to different types of substrate. a) Three substrates (brown-light, brown-brown, and grey shipping paper) were tested for the oviposition egg-laying preference; b) Result shows that total 696 egg counts were for the brown- light shipping paper, 561 egg counts were for the brown-brown paper, and 445 egg counts were for the grey paper from the 5 locations.

3.5 Adult Mosquito Species

Total 4010 mosquitoes were successfully emerged and identified for all 5 locations over the 9 weeks of collection. Among which, 2386 were female Aedes, 1311 were males, 6 were Culex (grouped into the “Others”), and 307 were damaged or fragmented mosquitoes (Figure 9). Only female mosquitoes were documented into species. To sum up, 793 female Ae. triseriatus were identified, along with 1480 Ae. albopictus, 32 Ae. japonicas, 1 Ae. vexan, and 80 un-identifiable Aedes species (Figure9a). Data show that

Obetz and Gahanna were the top 2 locations where we got 482 and 153 Ae. triseriatus, respectively, followed by Green Lawn Cemetery, Hilliard, and Prairie obtaining 85, 43, and 30 mosquitoes, respectively (Figure 10). Data also demonstrate that the numbers of mosquitoes identified peaked between weeks 4, 5, and 6 depending on the locations

(Figure 11) and this supports the egg survey in the field (Figure 3).

1600 1480

1400 1311 1200 1000 793 800 600

400 307 Mosquitoe Counts Counts (#) Mosquitoe 80 200 32 7 0

Others 0%

Males Ae. 33% albopictus 37%

Oc. Damaged triseriatus 7% Ae. 20% Ae. japonicus vexan Ae. spp. 1% 0% 2% b)

Figure 9. Emerged adult mosquitoes over the nine weeks of collection. a) Bar graph presents numbers and species of adult mosquitoes reared in the lab from eggs collected in the field; b) Pie chart displays the contribution of each category (Aedes species of females, males, others, and integrity) to the total population of mosquito emerged.

600

200 527

180 153 500 160 140 400 120 297 100 89 300 80 200 60 40 85 Mosquito Counts (#)Counts Mosquito 100

Mosquito Counts Counts (#) Mosquito 39 20 0 7 3 0 2 1 0 4 0 0

a) b) 600 200

499 482 495

180 500 160 140 400 120 100 82 300 80 200 43 60 34

40 100 66

Mosquito Counts Counts (#) Mosquito Mosquito Counts Counts (#) Mosquito 20 3 5 4 0 0 11 0 0 0

c) d) 450 420

400 348 350 300 250 198 200 150 100 61

Mosquito Counts Counts (#) Mosquito 21 30 50 1 0 0

Figure 10. Quantitation and identification of adult mosquitoes for each surveillance location. Number of different species (or categories) of emerged mosquitoes were summed up over 9 weeks. a) Gahanna, b) Green Lawn Cemetery, c) Hilliard, d) Obetz, e) Prairie. 30

Gahanna Green Lawn Cemetery

150 500

400 100 300

200 50

100 Number of Mosquitoes of Number 0 Mosquitoes of Numbers 0 0 2 4 6 8 10 0 2 4 6 8 10 a) Weeks b) Weeks

Hilliard Obetz

140

1000 120 800 100 80 600 60 400 40 200

20 Numbers of Mosquitoes of Numbers Numbers of Mosquitoes of Numbers 0 0 0 2 4 6 8 10 0 2 4 6 8 10 c) Weeks d) Weeks

Prairie

600

500

400

300

200

100 Numbers of Mosquitoes of Numbers 0 0 5 10 e) Weeks

Figure 11. Weekly numbers of emerged adult mosquitoes over the nine weeks. a) Gahanna, b) Green Lawn Cemetery, c) Hilliard, d) Obetz, e) Prairie.

4. Discussions

4.1. Temperature and Weather Effects

Data show that the insectary temperature fluctuated between a maximum of 32.6°C to a minimum of 18.1°C and the mean (SD) value was about 26.8°C (2.4) (Figure 12 and

Appendix D). A less fluctuating period of time (within 3°C range between 26°C and 29°C) was during early August to early September (week 4 to 7). It is suspected that the fluctuation was not as drastic due to the impact of the outdoor ambient temperature in a way that higher outdoor temperature heated up the room during the day, and possibly the metal construction and insulation of the mosquito control facility trapped and kept the heat in while the heater was off during the night. On the contrary, temperature dropped more quickly when outdoor ambient temperature was low. From late September to early November, relatively lower temperature and the less attended station resulted in larger jumps in temperature indoor, which may in turn have effects on eggs condition and larvae rearing.

35.0 32.6

30.0

° 25.0 20.0 18.1 15.0

10.0 Tmperature ( Tmperature 5.0 0.0 Duration (Days, Time)

Figure 12. VDCI insectary temperature record. The temperature was monitored 2 or 3 times a day from July 27, 2012 to November 09, 2012. The highest point was recorded as 32.6°C on August 05, 2012 and the lowest point was as 18.1°C on November 09, 2012

As rising awareness on global climate change, public health in terms of pathogen infection and disease transmission is a concern. Temperature changes can easily affect mosquito’s life cycle- the reproduction rate, number of blood meals, breeding and maturation length, etc (Epstein, 2005). It is believed that the geographic spread of diseases and the locations of the outbreaks can be predicted by climatic data (Epstein &

Defilippo, 2001; Epstein, 2005). Therefore, it is worth examining the relationship between local temperature and the Ae. triseriatus egg-laying behavior in terms of egg counts. However, no on-site field temperature data was collected during the sampling period; archived data from National Oceanic and Atmospheric Administration (NOAA) database were therefore extracted and compiled. Generally, the record shows a decreasing tendency in average daily temperature in Ohio (Figure 13). Scatterplot

33 analyses were performed in a hope that any correlation can be identified (Figure 14).

However, no obvious relationship between the egg counts and average record daily temperature can be observed which is probably due to small sample size. The result slightly shows that egg counts from 2 (Green Lawn and Obetz) out of total 5 locations on some of the days of 22.5°C were relatively higher than the counts on the rest of the days

(Figure 14a). Only the data from Green Lawn and Obetz demonstrate positive relationships, implicating higher egg counts with increasing temperature (Figure 14b).

The data from Gahanna show negative correlation, suggesting presence of potential unknown factors whose impact on egg-laying outweigh the temperature effect (Figure

14b).

26.00

25.00

° 24.00 23.00 22.00

21.00 Temperature ( Temperature 20.00 19.00 1 2 3 4 5 6 7 8 9 Weeks

Figure 13. Average record daily highest minimum temperature in Ohio. The data was extracted from the Daily Highest Minimum Temperature records archived in National Oceanic and Atmospheric Administration (NOAA) database. Only the temperature recorded by the station(s) at Franklin County or, if no Franklin record is available, that from all close-by stations were pulled and averaged out over the week.

ScEggatte Countsrplot of vsEg gAverage Counts vRecords Avera Dailyge Re cTemperatureord Daily Tem (°C)pera bytur Weeke (°C)

21.0 22.5 24.0

Gahanna Green Law n C emetery Hilliard Weeks 3000 1 2 3 2000 4 5 1000

s 6 t

n 7

u 0 8 o

C O betz Prairie 21.0 22.5 24.0 9

g 3000

g E

2000

1000

0 21.0 22.5 24.0 Average Record Daily Temperature (°C) a) Panel variable: Locations

ScatteEggrplo tCounts of Egg Cvso uAveragents vs Av Dailyerage Temperature Daily Temper a(°C)ture (°C)

3500 Locations Gahanna 3000 Green Lawn Cemetery Hilliard Obetz

2500 Prairie s

t 2000

o C

1500

g E 1000

500

21 22 23 24 25 Average Daily Temperature (°C) b)

Figure 14. Scatterplot analyses on the relationship between temperature and egg counts. Data were plotted by Minitab 16.

Studies have shown that in the tree-hole mosquito Ae. triseriatus and closely related species, eggs from one batch will not hatch entirely by a hatch stimulus, such as change of oxygen level, because the extreme environment of their natural larval habitats dry out during the summer hatching season (Khatchikian, Dennehy, Vitek, & Livdahl, 2009).

They show hatch delay in response to drought conditions allowing their offspring to

35 emerge and survive over time with reduced risk of reproductive failure. Taking this into consideration, some eggs, given the flattened appearance, may have experienced dry conditions either before collection out in the field or during the storage in the insectary long and strong enough to stimulate hatch delay, resulting in the low hatching rate obtained (Data not shown).

4.2. Habitat Preference

Many environmental factors have been studied regarding the effects on mosquito habitats and oviposition preference. To investigate mosquito distribution and its preferred habitats in Ohio, the relationship between number of eggs collected and the corresponding surveillance locations and ovitrap sites for 5 neighborhoods around

Columbus, Ohio were analyzed. One-way analysis of variance (one-way ANOVA) was performed to test for differences in mean egg counts among 5 locations (Appendix E).

The p-value of 0.004 suggests that at least one of the means was significantly different from the others. Subsequent multiple comparisons using Fisher’s method then indicated that mean egg counts of Green Lawn Cemetery and Obetz Memorial Park differed significantly from that of Gahanna and Hilliard Municipal Park. In addition, the individual value plot shows that mosquitoes deposited relatively similar numbers of eggs over the 9-week periods at Gahanna or Hilliard; however, egg deposition over the same duration for Green Lawn, Obetz, or Prairie showed wide range of variation, suggesting the presence of potential seasonal factors (ex: temperature, weather, etc) or other environmental factors in response to the seasonal effects (ex: shades, wind direction, etc) (Figure 15, 16).

The result of Green Lawn having the highest number of eggs in average could probably be explained by the fact that Green Lawn is resided by wildlife such as deer, woodchucks, red fox, coyote, and albino squirrel, and studies on California encephalitis

(CE) in Ohio have found that arboreal squirrels, chipmunks, and woodchucks have

37 hemagglutination inhibiting and/or neutralizing antibodies to CE virus (Berry et al.,

1975), implicating the susceptibility of specific host animals for virus amplification, and giving the potential for Green Lawn to serve as a transmission hot zone once the virus is introduced.

Individual Value Plot of Five Sampling Locations 3500

3000

2500 s

t 2000

o C

1500

g g E 1168.63 1000 1073.22

500 506.778

195 105.556 0

Gahanna Green Lawn Hilliard Obetz Prairie Locations

Figure 15. Individual Value Plot of the five sampling locations. This plot shows the dispersions of the observed egg counts for all 5 sampling locations, and the blue symbols represent the means of the samples of each location. The mean egg count for Green Lawn Cemetery was generally the highest closely followed by the mean for Obetz. The spread of the data for the 5 locations vary. Data were plotted by Minitab 16.

Gahanna Green Lawn 95% CI for the Mean 95% CI for the Mean 700 250 600 200

500

s s

150 t

t 400

C C

300

100

E E 200 197.875 178 50 52.4444 51.1111 151.75 40.5556 117.5 121.875 31 100 96 82.875 14.7778 77.5 64.625 80.625 0 0.111111 1.11111 0.555556 3.33333 0 0

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 a) Ovitraps (Sites) b) Ovitraps (Sites)

Hilliard Obetz 95% CI for the Mean 95% CI for the Mean 900

150 800 700

600

100

s t

t 500

o o

C 400

g 50

g g

g 300 E 33 30.625 E 15.5556 17.6667 10.25 200 184.778 3.33333 2.88889 159.333 0 0.5 0 0 136.556 135.222 111.556 100 102.889 83.7778 93.625 31.4444 42.7778 0 -50 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 c) Ovitraps (Sites) d) Ovitraps (Sites)

Prairie 95% CI for the Mean

400

300

t n

u 200

g g

E 114 100 72.125 77.25 55 51 57.5 57 36.5714 41.2857 45.8571 0

1 2 3 4 5 6 7 8 9 10 e) Ovitraps (Sites)

Figure 16. Individual Value Plots of the sampling sites. a) Gahanna, b) Green Lawn, c) Hilliard, d) Obetz, and e) Prairie. The plots show the dispersions of the observed egg counts for 10 ovitraps of each location, and the blue symbols represent the means of the samples. Data were plotted by Minitab 16.

Specifically, differences among ovitrap sites within the same location in terms of mosquitoes’ preference in egg-laying were further examined. One-way ANOVA analyses show that for all 5 surveillance locations, the p-value for the means of the 10 ovitraps of the each location was larger than the 0.05 level of significance (Gahanna: 0.126, Green

Lawn: 0.747, Hilliard: 0.263, Obetz: 0.360, and Prairie: 0.943), meaning the observed differences in mean egg counts among different ovitrap sites at the same location were not large enough to rule out the chance as the cause (failure to reject the null) (Figure

16 and Appendix E). In other words, the variations of egg counts among different ovitraps may be simply due to chance alone and happen randomly. However, trees of mesichabitat or other environmental factors such as tree species and trunk diameters

(Ballard, Waller, & Knapp, 1987) have been shown to have impacts on site selection, even though no evidence regarding this aspect is provided in the present report.

Moreover, altitude or height preference for egg-laying has been reported (Joy & Sullivan,

2005; Obenauer, Kaufman, Allan, & Kline, 2009a; Obenauer, Kaufman, Allan, & Kline,

2009b) .

To examine the effect of elevation on the distribution of eggs, same type of substrates were used within the same surveillance location of the same week, though white paper towels were tested for Green Lawn Cemetery and Obetz in week 6 (August 20-27) and all 5 location substrates were changed to blue cloth in weeks 7, 8, and 9. It can be generally inferred that (1) the higher the frequency (over the nine weeks) of having the highest number of eggs for a specific cup and (2) the higher total egg count falls on the

40 specific trap, the higher preference mosquitoes lay eggs on that trap/cup. The tally data show that mosquitoes prefer to lay eggs on traps which placed on the ground or lower level (Table 1 and Appendix C).

To confirm the inference, one-way ANOVA hypothesis testing was again performed

(Appendix E). However, only the mean egg counts from Hilliard showed statistically significant difference (p-value 0.004) between the elevated (E) and ground-level (L) traps with the ground-level ones having more eggs. The mean egg counts from Obetz will likely differ (p-value 0.074) if a higher significant level of 0.1 is set. Although the inference is not completely statistically supported, studies on ovipositional height preferences of container-inhabiting mosquitoes reported similar findings where Ae. albopictus preferred to oviposit at ground level and its eggs were significantly more often recovered from traps at 1 m, whereas Ae. triseriatus eggs were recovered more at

6 m and have shown a strong preference for tree canopies up to 27 m (Obenauer,

Kaufman, Allan, & Kline, 2009a; Obenauer, Kaufman, Allan, & Kline, 2009b). This could support the present result of higher numbers of eggs collected from the ground-level (L) ovitraps for most of the sampling locations with high Ae. albopictus counts. It could also partially explain why for most of the sampling locations no statistically significant difference was observed between elevated and ground-level traps, because the elevated heights were not extreme enough to show the difference. Variations of egg counts in terms of ovipositional height preference do occur (Figure 17), suggesting presence of potential factors such as availability of artificial containers, abundance of hosts (dogs, cats, and humans), coexisting mosquito species (Aedes hendersoni) that 41 compete with the habitat, etc (Obenauer, Kaufman, Allan, & Kline, 2009b; Richards,

Ponnusamy, Unnasch, Hassan, & Apperson, 2006).

Gahanna Green Lawn 95% CI for the Mean 95% CI for the Mean 700 250 600 200

500

s t 150 t

n 400

300

g g

100 g

E E 200

50 134.375 100 99.35 20.5333 18.4667 0 0

E L E L a) Elevation b) Elevation

Hilliard Obetz 95% CI for the Mean 95% CI for the Mean 180 900

160 800

140 700

120 600

t n

n 100 500

80 400

g E 60 E 300

40 200 134.2 21.1905 20 100 81.9318 0 1.42857 0

E L E L c) Elevation d) Elevation

Prairie 95% CI for the Mean 900

800

700

600

s t

n 500

o C

400

g g

E 300

200 134.2 100 81.9318 0

E L e) Elevation

Figure 17. Individual Value Plots: Egg Counts vs. Elevations. a) Gahanna, b) Green Lawn, c) Hilliard, d) Obetz, and e) Prairie. The plots show the means and dispersions of the observed egg counts for elevated vs. ground- level ovitraps. The blue symbols represent the means of the samples. Data were plotted by Minitab 16.

4.3. Sensitive Male Embryos and Larval Inhibition

Studies have shown that critical day lengths and larval density-dependent feedback could affect sex-ratio imbalance among container mosquito species (Lounibos & Escher,

2008). Scientists have also demonstrated that male embryos of Ae. triseriatus are more sensitive than females to suboptimal hatching stimuli in the laboratory (Shroyer & Craig,

1981) and increasing larval density in natural habitats significantly reduce hatching rate of Ae. triseriatus (T. P. Livdahl & Edgerly, 1987). Therefore, it is hypothesized that the recorded relatively high percentage of male mosquitoes (31-48% individually or 33% in average) (Figure 10, 11) resulted from the combination of the above mentioned two factors in a way that the newly readily hatched male larvae inhibit the unhatched embryos, which may have more females, from hatching.

4.4. Ochlerotatus triseriatus vs. Aedes albopictus: Abundance and

Correlation

As mentioned previously, LAC virus is historically transmitted by the native mosquito Ae. triseriatus (Say), but it is suspected that the invasive Ae. albopictus, which co-exists with

Ae. triseriatus in water-holding containers, may be an important accessory vector in region where LAC encephalitis is an emerging disease (Leisnham & Juliano, 2012). In addition, scientists in Tennessee isolated LAC virus from Ae. albopictus implicating the species as a potential secondary vector (Barker, Paulson, Cantrell, & Davis, 2003).

Studies have shown that Ae. albopictus competes over Oc. triseriatus under laboratory conditions (Aliabadi & Juliano, 2002) . Moreover, Ae. albopictus has been observed with

44 lower abundance in tree-hole sites but greater in cemetery sites with about twice those in tree-holes, while Oc. triseriatus shows in an opposite way having greater abundance in tree holes but rare or absent in cemetery (Kesavaraju, Damal, & Juliano, 2008). The study also suggests that Oc. triseriatus and Ae. albopictus co-exist in tree hole habitats under predation pressure (Kesavaraju, Damal, & Juliano, 2008). These studies support the present result for Green Lawn Cemetery which shows the domination of Ae. albopictus (Figure 10b) and for the relatively similar abundance of the two species in

Hilliard and Obetz (Figure 10c, d). Another aspect which may explain the overall abundance of Ae. albopictus within the sample is that eggs of other Aedes species may have over-dried for prolonged time resulting in increased percent Ae. albopictus because it can survive longer in dry and low temperature (Cooke, Grala, & Wallis, 2006;

Goddard, 2003). Additionally, scatterplot analysis shows that there are positive associations between the abundance of Ae. albopictus and that of Oc. triseriatus in terms of egg counts for the most of the locations (Figure 18).

AedesS albopictcatterpuslo tvs o fOchlerotatus Aedes albo ptriseriatusictus vs O chlerotatus triseriatus 0 200 400 Gahanna Green Lawn Cemetery Hilliard 300 36

200

s 1

u 26 100

t c

i 0 21 p 0 29 01 07 o 1 47 105 7

b 0 l

a Obetz Prairie

300 0 200 400

e d

e 6

A Locations 200 14 Gahanna 473 Green Lawn Cemetery 100 0 014 0 2 Hilliard Obetz 1 20 0 Prairie 0 0 200 400 Ochlerotatus triseriatus Panel variable: Locations

Figure 18. Scatterplot of Aedes albopictus vs. Ochlerotatus triseriatus

Data were plotted by Minitab 16. Values labeled represent the number of Oc. triseriatus.

4.5. Quality of the Data

Ideally, each substrate should be tested along with the original canvas cloth for all 5 surveillance locations for the whole season (9 weeks) so that confounders such as daylight, temperature, and other environmental conditions could be ruled out from factors which influence the number of eggs oviposit and further interfere with the interpretation on mosquitoes’ preference on substrates. However, in consideration of the time constraint and the impact that too many substrates would distract mosquitoes from egg laying and further reduce the sampling size for each substrate, only Green

Lawn Cemetery, where we believed it would provide more eggs because of its segregated woods-shaded environment and scattering artificial containers, was selected for 4-substrate testing (Chipotle napkin, brown/grey shipping stuffing paper, and white

46 paper towel) for only one week (at the end of July). Another set of substrate testing was carried out in week 4 (August 6-13) for the purpose of repeating and confirming the previous test result; however, only 2 of the substrates (brown/grey shipping stuffing paper) were chosen to be re-tested along with another new type of brown paper

(lighter and finer), and only 1 of the total 10 ovitraps at each location was selected to set up additional substrates based on the previous 3 weeks of egg counts. Therefore, a conclusion could not be drawn strictly even if both tests show similar results. Not to mention, the data actually show inconsistency in whether or not mosquitoes prefer brown over grey paper we used. Although data show that the white paper towel had the lowest number of egg deposited (Figure 7), it was not statistically significantly different from other darker substrates in terms of mean egg counts (Appendix E).

Potential reasons could be that the sample size was too small and the experimental design was in favor of summing rather than averaging the data.

During the collection period, there were 2 weeks when different man-power was involved for weekly ovitrap preparation. The white paper towel was introduced for testing again in week 6 (August 20-27) for Green Lawn and Obetz, and the 6th substrate, blue cloth, was introduced in week 7 on August 27 for all 5 locations and had been kept using for the last 3 weeks of egg collection until September 17. However, no other type of substrate was used accompany the white paper or blue cloth within the same weeks for the same locations. Therefore, we hesitate to say that the drop of the weekly total egg counts (Figure 3) was exclusively because of the texture and color of the substrate but not because of other factors such as the lower temperature in late summer season. 47

More studies and field work have to be done with comprehensive and strict experimental design to resolve the doubt. Meanwhile, the data presented here could provide a preliminary view for the development of the surveillance program and to serve as a prototype for better-designed field work.

5. Concluding Remarks

In summary, our data demonstrate how environmental factors such as seasonal timing, local temperature, vegetation and wildlife, altitude, and micro/macro-habitat could have impacts on tree-hole mosquito egg-laying behaviors in terms of the number of eggs deposited. Though the analyses are somewhat inconclusive for all surveillance locations, they do provide some clues for habitat preference to ground-level ovitraps with substrates of natural dark color (brown or grey). The high numbers of eggs collected from Green Lawn Cemetery and Obetz Memorial Park suggest the existence of unique environmental conditions that Ae. albopictus or Ae. triseriatus prefer. These observations can provide insights to the local sampling site selection. The methodology used for egg collection in the field and for mosquito rearing in the self-built insectary can serve as a prototype for LAC virus surveillance and control program targeted for on- going development. Lastly, more work is needed, for better understanding of the association of environmental factors and the behavior of tree-hole mosquito oviposition egg-laying. Meanwhile, it is hoped that virus determination on the sample collected and

GIS mapping for environmental risk factors could proceed to completion in the near future.

References

Aliabadi, B. W., & Juliano, S. A. (2002). Escape from Gregarine Parasites Affects the Competitive Interactions of an Invasive Mosquito Springer Netherlands. doi:10.1023/A:1020933705556

Andreadis, T. G., Anderson, J. F., Armstrong, P. M., & Main, A. J. (2008). Isolations of Jamestown Canyon virus (Bunyaviridae: Orthobunyavirus) from field-collected mosquitoes (Diptera: Culicidae) in Connecticut, USA: a ten-year analysis, 1997- 2006. Vector Borne and Zoonotic Diseases (Larchmont, N.Y.), 8(2), 175-188. doi:10.1089/vbz.2007.0169

Balfour, H. H.,Jr, Majerle, R. J., & Edelman, C. K. (1973). California arbovirus (La Crosse) infections. II. Precipitin antibody tests for the diagnosis of California encephalitis. Infection and Immunity, 8(6), 947-951.

Ballard, E. M., Waller, J. H., & Knapp, F. W. (1987). Occurrence and ovitrap site preference of tree hole mosquitoes: Aedes triseriatus and Aedes hendersoni in eastern Kentucky. Journal of the American Mosquito Control Association, 3(1), 42-44.

Barker, C.,M., Paulson, S.,L., Cantrell,S., & Davis, B.,S. (2003). Habitat Preferences and Phenology of Ochlerotatus triseriatus and Aedes albopictus (Diptera: Culicidae) in Southwestern Virginia. Journal of Medical Entomology, 40(4), 403-410.

Beaty, B. J., Rayms-Keller, A., Borucki, M. K., & Blair, C. D. (2000). La Crosse encephalitis virus and mosquitoes: a remarkable relationship. American Society for Microbiology News, 66, 349-357.

Beaty, B. J., Casals, J., Brown, K. L., Gundersen, C. B., Nelson, D., McPherson, J. T., & Thompson, W. H. (1982). Indirect fluorescent-antibody technique for serological diagnosis of La Crosse (California) virus infections. Journal of Clinical Microbiology, 15(3), 429-434.

Beaty, B. J., Hildreth, S. W., Blenden, D. C., & Casals, J. (1982). Detection of La Crosse (California encephalitis) virus antigen in mouse skin samples. American Journal of Veterinary Research, 43(4), 684-687.

Beaty, B. J., Jamnback, T. L., Hildreth, S. W., & Brown, K. L. (1983). Rapid diagnosis of La Crosse virus infections: evaluation of serologic and antigen detection techniques for the clinically relevant diagnosis of La Crosse encephalitis. Progress in Clinical and Biological Research, 123, 293-302.

Berry, R. L., Parsons, M. A., LaLonde, B. J., Stegmiller, H. W., Lebio, J., Jalil, M., & Masterson, R. A. (1975). Studies on the epidemiology of California encephalitis in an endemic area in Ohio in 1971. The American Journal of Tropical Medicine and Hygiene, 24(6 Pt 1), 992-998.

Blair, C. D., Adelman, Z. N., & Olson, K. E. (2000). Molecular strategies for interrupting arthropod-borne virus transmission by mosquitoes. Clinical Microbiology Reviews, 13(4), 651-661.

Calisher, C. H., Pretzman, C. I., Muth, D. J., Parsons, M. A., & Peterson, E. D. (1986). Serodiagnosis of La Crosse virus infections in humans by detection of immunoglobulin M class antibodies. Journal of Clinical Microbiology, 23(4), 667- 671.

Centers for Disease Control and Prevention. (2005). Information on Arboviral Encephalitides. Retrieved 9/21, 2012, from http://www.cdc.gov/ncidod/dvbid/arbor/arbdet.htm

Centers for Disease Control and Prevention. (2011a). "California Serogroup Virus Neuroinvasive Disease Cases Reported by State, 1964-2010" In La Crosse Encephalitis: Epidemeology and Geologic Distribution. Retrieved 9/21, 2012, from http://www.cdc.gov/lac/tech/epi.html#map

Centers for Disease Control and Prevention. (2011b). "California Serogroup Virus Neuroinvasive Disease Cases Reported by Year, 1964-2010" In La Crosse Encephalitis: Epidemeology and Geologic Distribution. Retrieved 9/21, 2012, from http://www.cdc.gov/lac/tech/epi.html#map

Chandler, L. J., Beaty, B. J., Bishop, D. H., & Ward, D. C. (1989). Detection of La Crosse and snowshoe hare viral nucleic acids by in situ hybridization. The American Journal of Tropical Medicine and Hygiene, 40(5), 561-568.

Chandler, L. J., Borucki, M. K., Dobie, D. K., Wasieloski, L. P., Thompson, W. H., Gundersen, C. B., . . . Beaty, B. J. (1998). Characterization of La Crosse virus RNA in autopsied central nervous system tissues. Journal of Clinical Microbiology, 36(11), 3332-3336.

Chow, V. T., Chan, Y. C., Yong, R., Lee, K. M., Lim, L. K., Chung, Y. K., . . . Tan, B. T. (1998). Monitoring of dengue viruses in field-caught Aedes aegypti and Aedes albopictus mosquitoes by a type-specific polymerase chain reaction and cycle sequencing. The American Journal of Tropical Medicine and Hygiene, 58(5), 578-586.

Conley, A. K., Watling, J. I., & Orrock, J. L. (2011). Invasive plant alters ability to predict disease vector distribution. Ecological Applications : A Publication of the Ecological Society of America, 21(2), 329-334.

Cooke, W. H.,3rd, Grala, K., & Wallis, R. C. (2006). Avian GIS models signal human risk for West Nile virus in Mississippi. International Journal of Health Geographics, 5, 36. doi:10.1186/1476-072X-5-36

Cutwa-Francis, M. M., & O'Meara, G. F. (2008). Photographic Guide to Common Mosquitoes of Florida. University of Florida, Vero Beach, FL: Florida Medical Entomology Laboratory.

Epstein, P. R., & Defilippo, C. (2001). West Nile Virus and Drought. Global Change & Human Health, 2(2), 105-107. doi:10.1023/A:1015089901425

Epstein, P. R. (2005). Climate Change and Human Health. N Engl J Med, 353(14), 1433- 1436. doi:10.1056/NEJMp058079

Gabitzsch, E. S., Blair, C. D., & Beaty, B. J. (2006). Effect of La Crosse virus infection on insemination rates in female Aedes triseriatus (Diptera: Culicidae). Journal of Medical Entomology, 43(5), 850-852.

Gerberg, E. J. (1979a). I. The Insectary. In D. L. Collins (Ed.), Manual for Mosquito Rearing and Experimental Techniques (Bulletin No. 5 ed., pp. 1-6). Selma, California: American Mosquito Control Association.

Gerberg, E. J. (1979b). II. Maintenance of Mosquito Colonies. In D. L. Collins (Ed.), Manual for Mosquito Rearing and Experimental Techniques (Bulletin No. 5 ed., pp. 7-26). Selma, California: American Mosquito Control Association.

Gerberg, E. J. (1979c). III. Procedures for Laboratory Rearing of Specific Mosquitoes. In D. L. Collins (Ed.), Manual for Mosquito Rearing and Experimental Techniques (Bulletin No. 5 ed., pp. 62-64). Selma, California: American Mosquito Control Association.

Goddard, J. (2003). Setting up a mosquito control program. (). Mississippi State Department of Health: Bureau of General Environmental Services.

Gould, E. A., & Higgs, S. (2009). Impact of climate change and other factors on emerging arbovirus diseases. Transactions of the Royal Society of Tropical Medicine and Hygiene, 103(2), 109-121. doi:10.1016/j.trstmh.2008.07.025

Haddow, A. D., Jones, C. J., & Odoi, A. (2009). Assessing risk in focal arboviral infections: are we missing the big or little picture? PloS One, 4(9), e6954. doi:10.1371/journal.pone.0006954

Hildreth, S. W., & Beaty, B. J. (1983). Application of enzyme immunoassays (EIA) for the detection of La Crosse viral antigens in mosquitoes. Progress in Clinical and Biological Research, 123, 303-312.

Hildreth, S. W., Beaty, B. J., Meegan, J. M., Frazier, C. L., & Shope, R. E. (1982). Detection of La Crosse arbovirus antigen in mosquito pools: application of chromogenic and fluorogenic enzyme immunoassay systems. Journal of Clinical Microbiology, 15(5), 879-884.

Jacob, B. G., Morris, J. A., Caamano, E. X., Griffith, D. A., & Novak, R. J. (2011). Geomapping generalized eigenvalue frequency distributions for predicting prolific Aedes albopictus and Culex quinquefasciatus habitats based on spatiotemporal field-sampled count data. Acta Tropica, 117(2), 61-68. doi:10.1016/j.actatropica.2010.10.002

Jamnback, T. L., Beaty, B. J., Hildreth, S. W., Brown, K. L., & Gundersen, C. B. (1982). Capture immunoglobulin M system for rapid diagnosis of La Crosse (California encephalitis) virus infections. Journal of Clinical Microbiology, 16(3), 577-580.

Jaslow, R. (2012, August 24). What's making the 2012 West Nile viruse outbreak the worst ever? CBS News

Joy, J. E., & Hildreth-Whitehair, A. (2000). Larval habitat characterization for Aedes triseriatus (Say), the mosquito vector of LaCrosse encephalitis in West Virginia. Wilderness & Environmental Medicine, 11(2), 79-83.

Joy, J. E., & Sullivan, S. N. (2005). Occurrence of tire inhabiting mosquito larvae in different geographic regions of West Virginia. Journal of the American Mosquito Control Association, 21(4), 380-386.

Juliano, S. A., Lounibos, L. P., & O’Meara, G. F. (2004). A field test for competitive effects of Aedes albopictus on A. aegypti in South Florida: differences between sites of coexistence and exclusion? Oecologia, 139(4), 583-593.

Kesavaraju, B., Damal, K., & Juliano, S. A. (2008). Do natural container habitats impede invader dominance? Predator-mediated coexistence of invasive and native container-dwelling mosquitoes. Oecologia, 155(3), 631-639. doi:10.1007/s00442-007-0935-4

Khatchikian, C. E., Dennehy, J. J., Vitek, C. J., & Livdahl, T. (2009). Climate and geographic trends in hatch delay of the treehole mosquito, Aedes triseriatus Say (Diptera: Culicidae). Journal of Vector Ecology : Journal of the Society for Vector Ecology, 34(1), 119-128. doi:10.1111/j.1948-7134.2009.00015.x

Lambert, A. J., Nasci, R. S., Cropp, B. C., Martin, D. A., Rose, B. C., Russell, B. J., & Lanciotti, R. S. (2005). Nucleic acid amplification assays for detection of La Crosse virus RNA. Journal of Clinical Microbiology, 43(4), 1885-1889. doi:10.1128/JCM.43.4.1885-1889.2005

Lanciotti, R. S., Kerst, A. J., Nasci, R. S., Godsey, M. S., Mitchell, C. J., Savage, H. M., . . . Roehrig, J. T. (2000). Rapid detection of west nile virus from human clinical specimens, field-collected mosquitoes, and avian samples by a TaqMan reverse transcriptase-PCR assay. Journal of Clinical Microbiology, 38(11), 4066-4071.

Leisnham, P. T., & Juliano, S. A. (2012). Impacts of climate, land use, and biological invasion on the ecology of immature aedes mosquitoes: implications for la crosse emergence. EcoHealth, 9(2), 217-228. doi:10.1007/s10393-012-0773-7

Livdahl, T. P., & Edgerly, J. S. (1987). Egg hatching inhibition: field evidence for population regulation in a treehole mosquito. Ecological Entomology, 12(4), 395- 399. doi:10.1111/j.1365-2311.1987.tb01020.x

Lounibos, L. P., & Escher, R. L. (2008). Sex ratios of mosquitoes from long-term censuses of Florida tree holes. Journal of the American Mosquito Control Association, 24(1), 11-15.

Moore, B. (2001). Aedes triseriatus. Retrieved 9/23, 2012, from http://animaldiversity.ummz.umich.edu/accounts/Aedes_triseriatus/

MR4 Staff. (2011). 1.2 Cleanliness and General Maintenance. Retrieved 9/7, 2012, from http://www.mr4.org/Portals/3/Pdfs/Anopheles/1.2%20Cleanliness%20and%20G eneral%20Maintenance%20v%201.pdf

Nasci, R. S., Moore, C. G., Biggerstaff, B. J., Panella, N. A., Liu, H. Q., Karabatsos, N., . . . Brannon, E. S. (2000). La Crosse encephalitis virus habitat associations in Nicholas County, West Virginia. Journal of Medical Entomology, 37(4), 559-570.

Obenauer, P. J., Kaufman, P. E., Allan, S. A., & Kline, D. L. (2009a). Host-seeking height preferences of Aedes albopictus (Diptera: Culicidae) in north central Florida suburban and sylvatic locales. Journal of Medical Entomology, 46(4), 900-908.

Obenauer, P. J., Kaufman, P. E., Allan, S. A., & Kline, D. L. (2009b). Infusion-baited ovitraps to survey ovipositional height preferences of container-inhabiting mosquitoes in two Florida habitats. Journal of Medical Entomology, 46(6), 1507- 1513.

Ohio Department of Health. (2008). La Crosse Fact Sheet. ().

Ohio Department of Health. (2012). La Crosse Encephalitis Virus Disease. ( No. ODH- IDCM). Columbus, Ohio:

Paradise, C. J., Blue, J. D., Burkhart, J. Q., Goldberg, J., Harshaw, L., Hawkins, K. D., . . . Villalpando, S. (2008). Local and regional factors influence the structure of treehole metacommunities. BMC Ecology, 8, 22. doi:10.1186/1472-6785-8-22

Reese, S. M., Beaty, M. K., Gabitzsch, E. S., Blair, C. D., & Beaty, B. J. (2009). Aedes triseriatus females transovarially infected with La Crosse virus mate more efficiently than uninfected mosquitoes. Journal of Medical Entomology, 46(5), 1152-1158.

Reese, S. M., Mossel, E. C., Beaty, M. K., Beck, E. T., Geske, D., Blair, C. D., . . . Black, W. C. (2010). Identification of super-infected Aedes triseriatus mosquitoes collected as eggs from the field and partial characterization of the infecting La Crosse viruses. Virology Journal, 7, 76. doi:10.1186/1743-422X-7-76

Richards, S. L., Ponnusamy, L., Unnasch, T. R., Hassan, H. K., & Apperson, C. S. (2006). Host-feeding patterns of Aedes albopictus (Diptera: Culicidae) in relation to availability of human and domestic animals in suburban landscapes of central North Carolina. Journal of Medical Entomology, 43(3), 543-551.

Ross, H. H., & Horsfall, W. R. (1965). A synopsis of the mosquitoes of Illinois (Diptera, Culicidae) (Biological Notes No. 52 ed.). Urbana, Illinois: Illinois Natural History Survey.

Shroyer, D.,A., & Craig, G.,B. (1981). Seasonal Variation in Sex Ratio of Aedes triseriatus (Diptera: Culicidae) and Its Dependence on Egg Hatching Behavior. Environmental Entomology, 10(2), 147-152.

Thielman, A. C., & Hunter, F. F. (December 2007). Photographic Key to the Adult Female Mosquitoes (Diptera: Culicidae) of Canada. Canadian Journal of Arthropod Identification, No. 4

US Department of Health and Human Services. (2003). Epidemic/Epizootic West Nile Virus in the United States: Guideline for Surveillance, Prevention, and Control. ().

US Geological Survey. (2012). La Crosse Encephalitis Historical Data. Retrieved 9/21, 2012, from http://diseasemaps.usgs.gov/lac_historical.html

Vezzani, D. (2007). Review: artificial container-breeding mosquitoes and cemeteries: a perfect match. Tropical Medicine & International Health : TM & IH, 12(2), 299- 313. doi:10.1111/j.1365-3156.2006.01781.x

Wasieloski, L. P.,Jr, Rayms-Keller, A., Curtis, L. A., Blair, C. D., & Beaty, B. J. (1994). Reverse transcription-PCR detection of LaCrosse virus in mosquitoes and comparison with enzyme immunoassay and virus isolation. Journal of Clinical Microbiology, 32(9), 2076-2080.

World Health Organization. (2012). Situation of Dengue/Dengue Haemorrhagic Fever in Soth-East Asia Region. Retrieved 9/21, 2012, from http://www.searo.who.int/en/Section10/Section332_1098.htm

Appendix A: Aerial Views of the LAC Virus Surveillance Locations

Source: Google Earth 2012; Imagery Date: 5/28/2010

T01: Gahanna [40° 2'23.49"N, 82°53'49.52"W] Wooded area and plenty tree holes. T02: Obetz (Memorial Park) [39°53'4.24"N, 82°56'51.71"W] Wooded area with dirt nature trails, fishing pond with largemouth bass, bluegill, and channel catfish, football/soccer fields, and big cover was spotted. T03: Prairie [39°57'34.07"N, 83° 8'1.90"W] Wooded areas with tall/mature trees and piles of logs in the center empty ground. T04: Hilliard (Municipal Park) [40° 1'37.53"N, 83°10'11.03"W] Wooded areas in or by the park with many tree holes of various sizes (a woodpecker was spotted), habitats for the host animals (ex: chipmunks), and human trace (trail). T05: Franklin (Green Lawn Cemetery) [39°56'19.41"N, 83° 2'0.43"W] Wooded area with trees and shrubs, area of prairie grass, wildlife animals, and birds.

T01 T02

T03 T04

T05

Appendix B: Oviposition Traps: Sites and the Setups

Obetz (O)

O1 O2 O3 O4 O5

O6 O7 O8 O9 O10

Green Lawn Cemetery (GL)

GL1 GL2 GL3 GL4 GL5

GL6 GL7 GL8 GL9 GL 10

Appendix C: Tallies on Ovitrap Preference

Table 2. Tallies on ovitrap preference 65

Appendix D: Temperature Data Analyses

Summary for Temperature (°C)

A nderson-Darling Normality Test A -Squared 1.31 P-V alue < 0.005

Mean 26.756 StDev 2.407 V ariance 5.793 Skew ness -0.45048 Kurtosis 1.37733 N 125

Minimum 18.111 1st Q uartile 25.722 Median 26.889 3rd Q uartile 27.944 18 21 24 27 30 33 Maximum 32.611 95% C onfidence Interv al for Mean 26.330 27.183 95% C onfidence Interv al for Median 26.447 27.222 95% C onfidence Interv al for StDev 95% Confidence Intervals 2.141 2.749 Mean

Median

26.2 26.4 26.6 26.8 27.0 27.2 a) Summary for Ave Record Daliy Tempt (°C)

A nderson-Darling Normality Test A -Squared 2.06 P-V alue < 0.005

Mean 22.457 StDev 1.005 V ariance 1.010 Skew ness 1.07689 Kurtosis 1.01837 N 45 Minimum 21.111 1st Q uartile 21.667 Median 22.431 3rd Q uartile 22.778 21 22 23 24 25 Maximum 24.778 95% C onfidence Interv al for Mean 22.155 22.758 95% C onfidence Interv al for Median 22.143 22.619 95% C onfidence Interv al for StDev 9 5 % Confidence Intervals 0.832 1.269 Mean

Median

22.2 22.3 22.4 22.5 22.6 22.7 22.8 b)

Figure 19. Graphical Summaries of the Temperature Data a) Insectary Temperature (site collected) b) Average Record Daily Temperature (extracted and compiled from NOAA records). Values and graphs were produced using Basic Statistics function of the Minitab 16 software.

Appendix E: Egg Survey/Habitat Preference Data Analyses I. Egg Counts vs. Locations

Data Display

Egg Row Locations Counts 1 Gahanna 5 2 Gahanna 21 3 Gahanna 361 4 Gahanna 303 5 Gahanna 471 6 Gahanna 153 7 Gahanna 411 8 Gahanna 0 9 Gahanna 30 10 Green Lawn Cemetery * 11 Green Lawn Cemetery 1680 12 Green Lawn Cemetery 2025 13 Green Lawn Cemetery 396 14 Green Lawn Cemetery 3169 15 Green Lawn Cemetery 735 16 Green Lawn Cemetery 1112 17 Green Lawn Cemetery 217 18 Green Lawn Cemetery 15 19 Hilliard 0 20 Hilliard 115 21 Hilliard 0 22 Hilliard 61 23 Hilliard 291 24 Hilliard 140 25 Hilliard 298 26 Hilliard 36 27 Hilliard 9 28 Obetz 568 29 Obetz 1187 30 Obetz 1517 31 Obetz 2981 32 Obetz 1518 33 Obetz 72 34 Obetz 1263 35 Obetz 518 36 Obetz 35 37 Prairie 38 38 Prairie 230 39 Prairie 177 40 Prairie 410 41 Prairie 1112 42 Prairie 1764 43 Prairie 800 44 Prairie 22 45 Prairie 8 68

One-way ANOVA: Egg Counts versus Locations

Source DF SS MS F P Locations 4 8356484 2089121 4.50 0.004 Error 39 18085945 463742 Total 43 26442429

S = 681.0 R-Sq = 31.60% R-Sq(adj) = 24.59%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------+--- Gahanna 9 195.0 192.2 (------*------) Green Lawn 8 1168.6 1070.4 (------*------) Hilliard 9 105.6 117.9 (------*------) Obetz 9 1073.2 917.0 (------*------) Prairie 9 506.8 605.3 (------*------) ------+------+------+------+--- 0 600 1200 1800

Pooled StDev = 681.0

Grouping Information Using Fisher Method

Locations N Mean Grouping Green Lawn 8 1168.6 A Obetz 9 1073.2 A Prairie 9 506.8 A B Gahanna 9 195.0 B Hilliard 9 105.6 B

Means that do not share a letter are significantly different.

Fisher 95% Individual Confidence Intervals All Pairwise Comparisons among Levels of Locations

Simultaneous confidence level = 72.55%

Locations = Gahanna subtracted from:

Locations Lower Center Upper ------+------+------+------+-- Green Lawn 304.3 973.6 1642.9 (------*-----) Hilliard -738.8 -89.4 559.9 (-----*------) Obetz 228.9 878.2 1527.5 (------*-----) Prairie -337.5 311.8 961.1 (-----*------) ------+------+------+------+-- -1000 0 1000 2000

Locations = Green Lawn subtracted from:

Locations Lower Center Upper ------+------+------+------+-- Hilliard -1732.4 -1063.1 -393.8 (-----*------) Obetz -764.7 -95.4 573.9 (------*------) Prairie -1331.2 -661.8 7.5 (-----*------) ------+------+------+------+-- -1000 0 1000 2000

Locations = Hilliard subtracted from:

Locations Lower Center Upper ------+------+------+------+-- Obetz 318.3 967.7 1617.0 (------*-----) Prairie -248.1 401.2 1050.5 (-----*------) ------+------+------+------+-- -1000 0 1000 2000

Locations = Obetz subtracted from:

Locations Lower Center Upper ------+------+------+------+-- Prairie -1215.8 -566.4 82.9 (-----*------) ------+------+------+------+-- -1000 0 1000 2000

II. Egg Counts vs. Ovitraps (Sites)

Gahanna

Data Display

Ovitraps Egg Row (Sites) Elevation Counts 1 1 E 0 2 1 E 1 3 1 E 0 4 1 E 206 5 1 E 1 6 1 E 9 7 1 E 255 8 1 E 0 9 1 E 0 10 2 L 5 11 2 L 1 12 2 L 111 13 2 L 0 14 2 L 91 15 2 L 3 16 2 L 125 17 2 L 0 18 2 L 29 19 3 E 0 20 3 E 0 21 3 E 0 22 3 E 97 23 3 E 34 24 3 E 2 25 3 E 0 26 3 E 0 27 3 E 0 28 4 L 0 29 4 L 11 30 4 L 250 31 4 L 0 32 4 L 186 70

33 4 L 10 34 4 L 3 35 4 L 0 36 4 L 0 37 5 E 0 38 5 E 0 39 5 E 0 40 5 E 0 41 5 E 153 42 5 E 124 43 5 E 1 44 5 E 0 45 5 E 1 46 6 L 0 47 6 L 0 48 6 L 0 49 6 L 0 50 6 L 1 51 6 L 0 52 6 L 0 53 6 L 0 54 6 L 0 55 7 E 0 56 7 E 5 57 7 E 0 58 7 E 0 59 7 E 0 60 7 E 5 61 7 E 0 62 7 E 0 63 7 E 0 64 8 L 0 65 8 L 0 66 8 L 0 67 8 L 0 68 8 L 5 69 8 L 0 70 8 L 0 71 8 L 0 72 8 L 0 73 9 E 0 74 9 E 3 75 9 E 0 76 9 E 0 77 9 E 0 78 9 E 0 79 9 E 27 80 9 E 0 81 9 E 0 82 10 L 0 83 10 L 0 84 10 L 0 85 10 L 0 86 10 L 0 87 10 L 0 88 10 L 0 89 10 L 0 90 10 L 0

One-way ANOVA: Egg Counts versus Ovitraps (Sites)

Source DF SS MS F P Ovitraps (Sites) 9 39574 4397 1.61 0.126 Error 80 218347 2729 Total 89 257920

S = 52.24 R-Sq = 15.34% R-Sq(adj) = 5.82%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev +------+------+------+------1 9 52.44 101.73 (------*------) 2 9 40.56 52.80 (------*------) 3 9 14.78 32.79 (------*------) 4 9 51.11 96.06 (------*------) 5 9 31.00 61.38 (------*------) 6 9 0.11 0.33 (------*------) 7 9 1.11 2.20 (------*------) 8 9 0.56 1.67 (------*------) 9 9 3.33 8.93 (------*------) 10 9 0.00 0.00 (------*------) +------+------+------+------35 0 35 70

Pooled StDev = 52.24

One-way ANOVA: Egg Counts versus Elevation

Source DF SS MS F P Elevation 1 96 96 0.03 0.857 Error 88 257824 2930 Total 89 257921

S = 54.13 R-Sq = 0.04% R-Sq(adj) = 0.00%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------+- E 45 20.53 56.15 (------*------) L 45 18.47 52.03 (------*------) ------+------+------+------+- 10 20 30 40

Pooled StDev = 54.13

Green Lawn Cemetery

Data Display

Ovitraps Egg Row (Sites) Elevation Counts 1 1 L * 2 1 L 256 3 1 L 127 4 1 L 83 5 1 L 639 6 1 L 0 7 1 L 108 8 1 L 1 9 1 L 0 10 2 L * 11 2 L 170 12 2 L 338 13 2 L 18 14 2 L 349 15 2 L 33 16 2 L 2 17 2 L 30 18 2 L 0 19 3 E * 20 3 E 0 21 3 E 257 22 3 E 61 23 3 E 104 24 3 E 184 25 3 E 13 26 3 E 0 27 3 E 1 28 4 L * 29 4 L 500 30 4 L 8 31 4 L 31 32 4 L 279 33 4 L 130 34 4 L 23 35 4 L 4 36 4 L 0 37 5 E * 38 5 E 32 39 5 E 230 40 5 E 100 41 5 E 111 42 5 E 3 43 5 E 40 44 5 E 1 45 5 E 0 46 6 E * 47 6 E 0 48 6 E 330 49 6 E 17 50 6 E 670 51 6 E 142 52 6 E 192 53 6 E 73 54 6 E 0 73

55 7 L * 56 7 L 601 57 7 L 428 58 7 L 22 59 7 L 135 60 7 L 16 61 7 L 339 62 7 L 35 63 7 L 7 64 8 E * 65 8 E 27 66 8 E 62 67 8 E 50 68 8 E 305 69 8 E 17 70 8 E 142 71 8 E 41 72 8 E 1 73 9 L * 74 9 L 0 75 9 L 85 76 9 L 2 77 9 L 367 78 9 L 140 79 9 L 64 80 9 L 2 81 9 L 3 82 10 E * 83 10 E 94 84 10 E 160 85 10 E 12 86 10 E 210 87 10 E 70 88 10 E 189 89 10 E 30 90 10 E 3

One-way ANOVA: Egg Counts versus Ovitraps (Sites)

Source DF SS MS F P Ovitraps (Sites) 9 149802 16645 0.65 0.747 Error 70 1780292 25433 Total 79 1930093

S = 159.5 R-Sq = 7.76% R-Sq(adj) = 0.00%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev -----+------+------+------+---- 1 8 151.8 215.2 (------*------) 2 8 117.5 149.7 (------*------) 3 8 77.5 97.5 (------*------) 4 8 121.9 180.3 (------*------) 5 8 64.6 79.7 (------*------) 6 8 178.0 229.0 (------*------) 7 8 197.9 228.8 (------*------) 8 8 80.6 100.2 (------*------) 9 8 82.9 125.7 (------*------) 10 8 96.0 81.5 (------*------) 74

-----+------+------+------+---- 0 100 200 300

Pooled StDev = 159.5

One-way ANOVA: Egg Counts versus Elevation

Source DF SS MS F P Elevation 1 24535 24535 1.00 0.319 Error 78 1905558 24430 Total 79 1930093

S = 156.3 R-Sq = 1.27% R-Sq(adj) = 0.01%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------+--- E 40 99.3 130.1 (------*------) L 40 134.4 178.7 (------*------) ------+------+------+------+--- 70 105 140 175

Pooled StDev = 156.3

Hilliard

Data Display

Ovitraps Egg Row (Sites) Elevation Counts 1 1 E 0 2 1 E 0 3 1 E 0 4 1 E 0 5 1 E 0 6 1 E 0 7 1 E 30 8 1 E 0 9 1 E 0 10 2 L 0 11 2 L 0 12 2 L 0 13 2 L 8 14 2 L 30 15 2 L 92 16 2 L 0 17 2 L 1 18 2 L 9 19 3 E 0 20 3 E 4 21 3 E 0 22 3 E 0 23 3 E 0 24 3 E 0 25 3 E 0 75

26 3 E 0 27 3 E * 28 4 L 0 29 4 L 0 30 4 L 0 31 4 L 11 32 4 L 0 33 4 L 42 34 4 L 29 35 4 L 0 36 4 L * 37 5 E 0 38 5 E 0 39 5 E 0 40 5 E 0 41 5 E 0 42 5 E 0 43 5 E 0 44 5 E 0 45 5 E * 46 6 L 0 47 6 L 0 48 6 L 0 49 6 L 0 50 6 L 169 51 6 L 0 52 6 L 84 53 6 L 11 54 6 L * 55 7 E 0 56 7 E 0 57 7 E 0 58 7 E 0 59 7 E 0 60 7 E 2 61 7 E 0 62 7 E 24 63 7 E 0 64 8 L 0 65 8 L 111 66 8 L 0 67 8 L 42 68 8 L 92 69 8 L 0 70 8 L 0 71 8 L 0 72 8 L * 73 9 E 0 74 9 E 0 75 9 E 0 76 9 E 0 77 9 E 0 78 9 E 0 79 9 E 0 80 9 E 0 81 9 E * 82 10 L 0 83 10 L 0 84 10 L 0 85 10 L 0 86 10 L 0 76

87 10 L 4 88 10 L 155 89 10 L 0 90 10 L 0

One-way ANOVA: Egg Counts versus Ovitraps (Sites)

Source DF SS MS F P Ovitraps (Sites) 9 11475 1275 1.28 0.263 Error 74 73840 998 Total 83 85316

S = 31.59 R-Sq = 13.45% R-Sq(adj) = 2.92%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev -+------+------+------+------1 9 3.33 10.00 (------*------) 2 9 15.56 30.27 (------*------) 3 8 0.50 1.41 (------*------) 4 8 10.25 16.41 (------*------) 5 8 0.00 0.00 (------*------) 6 8 33.00 62.14 (------*------) 7 9 2.89 7.94 (------*------) 8 8 30.63 46.36 (------*------) 9 8 0.00 0.00 (------*------) 10 9 17.67 51.52 (------*------) -+------+------+------+------20 0 20 40

Pooled StDev = 31.59

One-way ANOVA: Egg Counts versus Elevation

Source DF SS MS F P Elevation 1 8201 8201 8.72 0.004 Error 82 77115 940 Total 83 85316

S = 30.67 R-Sq = 9.61% R-Sq(adj) = 8.51%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------+- E 42 1.43 5.86 (------*------) L 42 21.19 42.97 (------*------) ------+------+------+------+- 0 10 20 30

Pooled StDev = 30.67

Grouping Information Using Fisher Method

Elevation N Mean Grouping L 42 21.19 A E 42 1.43 B 77

Means that do not share a letter are significantly different.

Fisher 95% Individual Confidence Intervals All Pairwise Comparisons among Levels of Elevation

Simultaneous confidence level = 95.00%

Elevation = E subtracted from:

Elevation Lower Center Upper -+------+------+------+------L 6.45 19.76 33.07 (------*------) -+------+------+------+------12 0 12 24

Obetz

Data Display

Ovitraps Egg Row (Sites) Elevation Counts 1 1 E 0 2 1 E 63 3 1 E 71 4 1 E 7 5 1 E 90 6 1 E 0 7 1 E 38 8 1 E 10 9 1 E 4 10 2 L 90 11 2 L 140 12 2 L 132 13 2 L 271 14 2 L 85 15 2 L 39 16 2 L 145 17 2 L 20 18 2 L 4 19 3 E 20 20 3 E 34 21 3 E 31 22 3 E 105 23 3 E 121 24 3 E 0 25 3 E 57 26 3 E 14 27 3 E 3 28 4 L 35 29 4 L 0 30 4 L 276 31 4 L 450 32 4 L 221 33 4 L 0 34 4 L 193 35 4 L 52 36 4 L 2 78

37 5 L 200 38 5 L 258 39 5 L 281 40 5 L 152 41 5 L 329 42 5 L 3 43 5 L 378 44 5 L 60 45 5 L 2 46 6 E 0 47 6 E 27 48 6 E 49 49 6 E 521 50 6 E 85 51 6 E 0 52 6 E 11 53 6 E 57 54 6 E 4 55 7 L 20 56 7 L 266 57 7 L 230 58 7 L 390 59 7 L 111 60 7 L 24 61 7 L 120 62 7 L 43 63 7 L 13 64 8 L 120 65 8 L 143 66 8 L 260 67 8 L 78 68 8 L 140 69 8 L 9 70 8 L 35 71 8 L 216 72 8 L 3 73 9 E 2 74 9 E 196 75 9 E 165 76 9 E 800 77 9 E 271 78 9 E 0 79 9 E 0 80 9 E 0 81 9 E 0 82 10 E 80 83 10 E 60 84 10 E 7 85 10 E 207 86 10 E 63 87 10 E 0 88 10 E 286 89 10 E 46 90 10 E *

One-way ANOVA: Egg Counts versus Ovitraps (Sites)

Source DF SS MS F P Ovitraps (Sites) 9 189081 21009 1.12 0.360 Error 79 1483696 18781 79

Total 88 1672776

S = 137.0 R-Sq = 11.30% R-Sq(adj) = 1.20%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------+--- 1 9 31.4 35.0 (------*------) 2 9 102.9 81.8 (------*------) 3 9 42.8 43.5 (------*------) 4 9 136.6 158.5 (------*------) 5 9 184.8 139.7 (------*------) 6 9 83.8 166.6 (------*------) 7 9 135.2 132.7 (------*------) 8 9 111.6 89.5 (------*------) 9 9 159.3 262.3 (------*------) 10 8 93.6 100.5 (------*------) ------+------+------+------+--- 0 100 200 300

Pooled StDev = 137.0

One-way ANOVA: Egg Counts versus Elevation

Source DF SS MS F P Elevation 1 60778 60778 3.28 0.074 Error 87 1611998 18529 Total 88 1672776

S = 136.1 R-Sq = 3.63% R-Sq(adj) = 2.53%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------+- E 44 81.9 149.4 (------*------) L 45 134.2 121.7 (------*------) ------+------+------+------+- 70 105 140 175

Pooled StDev = 136.1

Grouping Information Using Fisher Method

Elevation N Mean Grouping L 45 134.2 A E 44 81.9 A

Means that do not share a letter are significantly different.

Fisher 95% Individual Confidence Intervals All Pairwise Comparisons among Levels of Elevation

Simultaneous confidence level = 95.00%

Elevation = E subtracted from: 80

Elevation Lower Center Upper -+------+------+------+------L -5.1 52.3 109.6 (------*------) -+------+------+------+------50 0 50 100

Prairie

Data Display

Ovitraps Egg Row (Sites) Elevation Counts 1 1 E * 2 1 E 2 3 1 E 0 4 1 E 41 5 1 E 103 6 1 E 415 7 1 E 4 8 1 E 12 9 1 E 0 10 2 L * 11 2 L 65 12 2 L 0 13 2 L 23 14 2 L 200 15 2 L 180 16 2 L 148 17 2 L 2 18 2 L 0 19 3 E * 20 3 E 0 21 3 E 0 22 3 E 46 23 3 E 4 24 3 E 333 25 3 E 1 26 3 E 1 27 3 E * 28 4 L * 29 4 L 76 30 4 L 25 31 4 L 65 32 4 L 78 33 4 L 1 34 4 L 9 35 4 L 2 36 4 L * 37 5 E * 38 5 E 43 39 5 E 6 40 5 E * 41 5 E 14 42 5 E 293 43 5 E 1 44 5 E 0 45 5 E 0 46 6 L * 47 6 L 0 81

48 6 L 0 49 6 L 152 50 6 L 376 51 6 L 71 52 6 L 195 53 6 L 4 54 6 L * 55 7 E * 56 7 E 38 57 7 E 37 58 7 E 3 59 7 E 1 60 7 E 195 61 7 E 12 62 7 E * 63 7 E 3 64 8 L * 65 8 L 0 66 8 L 38 67 8 L * 68 8 L 2 69 8 L 117 70 8 L 162 71 8 L 0 72 8 L 2 73 9 E * 74 9 E 0 75 9 E 0 76 9 E 1 77 9 E 193 78 9 E 43 79 9 E 220 80 9 E 0 81 9 E 3 82 10 L * 83 10 L 6 84 10 L 68 85 10 L 75 86 10 L 141 87 10 L 116 88 10 L 48 89 10 L 2 90 10 L 0

One-way ANOVA: Egg Counts versus Ovitraps (Sites)

Source DF SS MS F P Ovitraps (Sites) 9 32447 3605 0.37 0.943 Error 64 616710 9636 Total 73 649157

S = 98.16 R-Sq = 5.00% R-Sq(adj) = 0.00%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------+--- 1 8 72.13 142.96 (------*------) 2 8 77.25 85.63 (------*------) 3 7 55.00 123.73 (------*------) 82

4 7 36.57 35.20 (------*------) 5 7 51.00 107.80 (------*------) 6 7 114.00 139.40 (------*------) 7 7 41.29 69.61 (------*------) 8 7 45.86 66.66 (------*------) 9 8 57.50 93.39 (------*------) 10 8 57.00 53.37 (------*------) ------+------+------+------+--- 0 60 120 180

Pooled StDev = 98.16

One-way ANOVA: Egg Counts versus Elevation

Source DF SS MS F P Elevation 1 1962 1962 0.22 0.642 Error 72 647195 8989 Total 73 649157

S = 94.81 R-Sq = 0.30% R-Sq(adj) = 0.00%

Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------+- E 37 55.89 105.22 (------*------) L 37 66.19 83.11 (------*------) ------+------+------+------+- 40 60 80 100

Pooled StDev = 94.81

III. Egg Counts vs. Substrates

One-way ANOVA: Egg Counts versus Substrate Types

Source DF SS MS F P Substrate Types 3 30481 10160 2.48 0.201 Error 4 16400 4100 Total 7 46881

S = 64.03 R-Sq = 65.02% R-Sq(adj) = 38.78%

Level N Mean StDev Brown Shipping Paper 2 157.50 9.19 Chipotle Napkin 2 97.50 31.82 Grey Shipping Paper 2 168.50 122.33 White Paper Towel 2 13.00 18.38

Individual 95% CIs For Mean Based on Pooled StDev Level ------+------+------+------+ Brown Shipping Paper (------*------) Chipotle Napkin (------*------) Grey Shipping Paper (------*------) 83

White Paper Towel (------*------) ------+------+------+------+ 0 120 240 360

Pooled StDev = 64.03

Grouping Information Using Fisher Method

Substrate Types N Mean Grouping Grey Shipping Paper 2 168.50 A Brown Shipping Paper 2 157.50 A Chipotle Napkin 2 97.50 A White Paper Towel 2 13.00 A

Means that do not share a letter are significantly different.

Fisher 95% Individual Confidence Intervals All Pairwise Comparisons among Levels of Substrate Types

Simultaneous confidence level = 84.70%

Substrate Types = Brown Shipping Paper subtracted from:

Substrate Types Lower Center Upper Chipotle Napkin -237.78 -60.00 117.78 Grey Shipping Paper -166.78 11.00 188.78 White Paper Towel -322.28 -144.50 33.28

Substrate Types ------+------+------+------+-- Chipotle Napkin (------*------) Grey Shipping Paper (------*------) White Paper Towel (------*------) ------+------+------+------+-- -200 0 200 400

Substrate Types = Chipotle Napkin subtracted from:

Substrate Types Lower Center Upper Grey Shipping Paper -106.78 71.00 248.78 White Paper Towel -262.28 -84.50 93.28

Substrate Types ------+------+------+------+-- Grey Shipping Paper (------*------) White Paper Towel (------*------) ------+------+------+------+-- -200 0 200 400

Substrate Types = Grey Shipping Paper subtracted from:

Substrate Types Lower Center Upper White Paper Towel -333.28 -155.50 22.28

Substrate Types ------+------+------+------+-- White Paper Towel (------*------) ------+------+------+------+-- -200 0 200 400 84