Ehrlichia and Rickettsia Tick-Borne Infections Associated with Lone Star Ticks and Under-Sampled Wildlife Hosts in Florida

EHRLICHIA AND RICKETTSIA TICK-BORNE INFECTIONS ASSOCIATED WITH LONE STAR TICKS AND UNDER-SAMPLED WILDLIFE HOSTS IN FLORIDA

JEFFREY CONRAD HERTZ

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2016

To Conrad and Kyra

Pursue dreams. Work hard. Complete goals.

Be happy. Assist others. Enjoy life.

Always check for ticks.

ACKNOWLEDGMENTS

The US Navy’s influence on my life and education cannot be underemphasized.

From my enlistment in 1994, the Navy has provided ample opportunity for me to grow as a Sailor, a person, and an academic. During this privileged opportunity over the last three years, the staff at the Navy Medicine Professional Development Center and

University of Florida’s Naval Reserve Officer’s Training Corps have been extremely supportive and ensured no barriers limited my success in school. Special emphasis must be given to Ms. Patricia Edwards, who handled all finances between the University of Florida and the Navy; Mr. Stephen Fisher, who facilitated a training opportunity in

Carlsbad, CA to supplement my studies; and Mr. Ron Fort, who ensured all administrative requirements were completed locally.

My major advisor, Dr. Phillip E. Kaufman, has been a tremendous mentor and I feel fortunate he was kind enough to take me on as a student. His experience, management acumen, and generosity throughout this process ensured the successful outcomes of this project could be accomplished on an abbreviated military timeline. I am thankful for the continuous support from the members of my graduate committee, Dr.

Sandra Allan, Dr. Cynthia Lord, and Dr. Michael Dark. I am grateful to each of them for their unyielding patience and candid assistance at every stage of this project. Of special note, Dr. Dark provided lab space and coordination with the College of Veterinary

Medicine (CVM) faculty, equipment, and resources – all of which were critical for this research.

The cornerstones of support for this research were the many volunteers, collaborators, and trusted partners we established relationships with at the beginning of this project. To thank everyone individually would be impossible, but please know that

their efforts are duly noted and appreciated. Florida Fish and Wildlife Conservation

Commission (FL FWC) provided access, technical expertise, and sample collection at multiple Wildlife Management Areas (WMAs) throughout the state. Additionally, the staff at FL FWC’s Lovett E. Williams Jr. Wildlife Research Laboratory located in Gainesville was always willing to collect additional samples and provide technical assistance when needed. Dr. Mark Cunningham, Bambi Clemons, Jayde Roofe, Alan Hallman, and

Roger Shields are just a few of the FL FWC staff that provided exceptional support during this project. Another key partner was the National Wild Turkey Federation, which provided technical assistance and distributed collection kits throughout the state. Camp

Blanding Joint Training Center, the St. John’s Water Management District, the Florida

Department of Agriculture and Consumer Services, and the Florida Department of

Environmental Protection kindly provided needed access to sampling locations to conduct this research. Numerous registered hunters voluntarily offered to collect blood and tick samples from their harvests, which allowed for a much larger and diverse sample size. Dr. Rich Robbins from the Armed Forces Pest Management Board generously provided expert confirmatory identification services, which greatly enhanced my confidence in identifying immature stages of Ixodes species. Last and certainly not least, is the unwavering and trusted support of Dr. Katherine Sayler from the University of Florida Department of Wildlife and Ecology Conservation. She has been involved in every facet of this research, and it is doubtful this project could have been completed without her direct involvement. I will forever be indebted for her friendship and generosity.

Several members of the Entomology and Nematology faculty and staff provided mentorship, guidance, and direct support to ensure this research could be completed. In addition to the amount of editing Dr. Jennifer Gillette-Kaufman provided to this dissertation, she had a gift of knowing when I needed a break from whatever task, or stressor, was providing me a hurdle. During these times, her genuine counsel was needed and appreciated. Dr. Emma Weeks sacrificed numerous hours editing drafts of this document and provided frequent statistical consultation over the three-year endeavor, which no doubt had a positive impact on the end product and solidified a lifelong friendship. Drs. James Maruniak, Drion Bucias, and Marjorie Hoy provided excellent formal and informal instruction and guidance on preparing me for the molecular aspects of this research. Dr. Dan Hahn cordially allowed me access to his equipment and liquid nitrogen, which were paramount to all of the DNA extractions performed herein. Drs. Phil Koehler and Roberto Pereira always welcomed me into their lab, continued to check in on my timelines, and encouraged me along the way. Finally, I really appreciated that Ruth Brumbaugh, Nancy Sanders, Elena Alyanaya, Jane

Medley, Lyle Buss, and Nick Hostettler always had time to assist me no matter the circumstances or time of day.

Members of the Kaufman Veterinary Lab are a remarkable team to work with. My fellow graduate students provided healthy competition, meaningful edits, and invaluable scientific discussions that I hope will continue for years to come. I will always strive to repay Maj. Tim Davis, Dr. Amanda Eiden, Dr. Karen Prine, CPT Nick Tucker, Bobby

Aldridge, and soon-to-be Dr. Chris Holderman for the many hours of voluntary assistance they provided to my project. I would be remiss if I didn’t thank the numerous

Kaufman lab volunteers and staff that have provided direct and indirect assistance to this project. One volunteer in particular, Nicole Miller, dedicated many hours extracting

DNA and assisting in qPCR and IFA testing of wildlife and tick samples. Dr. Kaufman’s laboratory manager, Lois Wood, ensured my project never stalled due to administrative lapses or supply deficiencies, which was incredibly valued.

Much of the lab work for this project was conducted at the CVM. The facilities and staff at this location were nothing less than exceptional. Dr. Maureen Long provided equipment support, including the use of the qPCR thermocycler. Dr. Long’s lab manager, Sally Beachboard, was crucial in assisting me when the thermocycler failed to initialize during a period of frequent lab testing, resulting in minimal delays. Additional material support and technical assistance came from Anna Lundgren, Liliana Crosby,

Jill Bobel, and Dhani Prakoso.

I would like to close by thanking my family: Karina, Conrad, and Kyra. Your endearing love and unconditional support is inspirational. Thank you for your patience and encouragement, especially during the most challenging times over the past three years. No matter what stress was accumulating with school or in life, it would all disappear the moment I walked through the front door. I hope that in the years to come,

I am able to provide you all the same level of comfort and support.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 10

LIST OF FIGURES ...... 12

ABSTRACT ...... 13

CHAPTER

1 BACKGROUND AND LITERATURE REVIEW ...... 15

Introduction ...... 15 The Lone Star Tick ...... 16 Classification and Taxonomy ...... 17 Distribution ...... 18 Biology...... 19 Life cycle ...... 19 Habitat ...... 20 Seasonality ...... 21 Host preference and host-seeking behavior ...... 22 Public Health and Veterinary Importance ...... 23 Ehrlichia pathogens ...... 23 Rickettsia pathogens ...... 28 Research Objectives ...... 32

2 DISTRIBUTION AND HOST ASSOCIATIONS OF IXODID TICKS COLLECTED FROM FLORIDA WILDLIFE...... 34

Introduction ...... 34 Materials and Methods...... 35 Results ...... 37 Discussion ...... 39

3 EHRLICHIAL AND RICKETTSIAL PATHOGENS ASSOCIATED WITH FLORIDA WILDLIFE ...... 57

Introduction ...... 57 Materials and Methods...... 59 Sample Collection ...... 59 Sample Processing ...... 60 Serology ...... 61 Pathogen Detection ...... 62 Statistical Analysis ...... 63

Results ...... 64 Discussion ...... 65

4 PREVALENCE OF EHRLICHIAL AND RICKETTSIAL PATHOGENS IN HOST- SEEKING LONE STAR TICKS AT FLORIDA STATE PARKS AND WILDLIFE MANAGEMENT AREAS...... 75

Introduction ...... 75 Materials and Methods...... 78 Tick Sampling ...... 78 DNA Extraction and Pathogen Detection ...... 79 Statistical Analysis ...... 81 Results ...... 82 Discussion ...... 85

5 SEASONAL ACTIVITY AND ABUNDANCE OF TICKS, AND TEMPORAL PATTERNS OF EHRLICHIA AND RICKETTSIA INFECTION RATES OF HOST-SEEKING LONE STAR TICKS IN NORTH-CENTRAL FLORIDA ...... 101

Introduction ...... 101 Methods ...... 102 Study Locations ...... 102 Tick Collections ...... 103 DNA Extraction and Pathogen Detection ...... 105 Statistical Analysis ...... 106 Results ...... 107 Discussion ...... 110

6 SUMMARY AND CONCLUSION ...... 131

Introduction ...... 131 Chapter Summaries ...... 132 Final Conclusion ...... 136

APPENDIX

A SAMPLE LOCATION HABITAT AND RECREATION DESCRIPTIONS ...... 139

B SUPPLEMENTARY TABLES ...... 142

C PERMITS AND AUTHORIZATIONS ...... 153

LIST OF REFERENCES ...... 191

BIOGRAPHICAL SKETCH ...... 212

LIST OF TABLES

Table page

2-1 Prevalence (95% CI) of ixodid ticks collected from major wildlife hosts in Florida, 2000-2015...... 48

2-2 Mean intensity (95% CI) of ixodid ticks collected from major wildlife hosts in Florida, 2000-2015...... 49

2-3 Prevalence and mean intensity of ixodid ticks collected from minor wildlife hosts in Florida, 2000-2015...... 50

2-4 Prevalence of ixodid ticks collected from wildlife in different regions of Florida, 2000-2015...... 51

3-1 Collection period of blood and tick samples obtained from wildlife hosts during a tick-borne pathogen survey in Florida...... 71

3-2 Percentage infection (95% CI) of ixodid ticks collected from wildlife hosts in Florida with Ehrlichia chaffeensis, Ehrlichia ewingii, and Rickettsia species...... 72

3-3 Identity of rickettsial species detected in ticks collected from Florida wildlife. .... 73

4-1 Ixodid ticks collected at Florida state parks (SP) and wildlife management areas (WMA)...... 89

4-2 Analysis of variance (ANOVA) comparing life stage densities between collection sites and the paired state parks and wildlife management areas...... 90

4-3 Ehrlichia chaffeensis and Ehrlichia ewingii infection rates of host-seeking lone star ticks, Amblyomma americanum, collected in Florida state parks (SP) and wildlife management areas (WMA) ...... 91

4-4 Rickettsia spp. infection rates of host-seeking lone star ticks, Amblyomma americanum, collected in Florida state parks (SP) and wildlife management areas (WMA)...... 92

4-5 Entomological risk indices for lone star ticks, Amblyomma americanum, infected with Ehrlichia chaffeensis, Ehrlichia ewingii, and spotted fever group Rickettsia at Florida state parks (SP) and wildlife management areas (WMA) ... 93

5-1 Number of lone star ticks, Amblyomma americanum, collected from three North-central Florida recreational areas between July 2014 and April 2016 .... 115

5-2 Minor ixodid species collected from three North-central Florida locations between July 2014 and April 2016...... 116

5-3 Analysis of variance (ANOVA) comparing life stage densities between collection dates and collection locations...... 117

5-4 Ehrlichia chaffeensis minimum infection rates (MIR) in host-seeking lone star ticks, Amblyomma americanum, collected at three North-central Florida recreational areas between July 2014 and February 2016...... 118

5-5 Ehrlichia ewingii minimum infection rates (MIR) in host-seeking lone star ticks, Amblyomma americanum, collected at three North-central Florida recreational areas between July 2014 and February 2016...... 119

5-6 Monthly Rickettsia spp. minimum infection rates (MIR) in host-seeking lone star ticks, Amblyomma americanum, collected at three North-central Florida recreational areas between July 2014 and February 2016...... 120

5-7 Relative risk of exposure to adult lone star ticks, Amblyomma americanum, infected with Ehrlichia chaffeensis, E. ewingii, and spotted fever group Rickettsia in North-central Florida, August 2014 to February 2016...... 121

5-8 Relative risk of exposure to nymphal lone star ticks, Amblyomma americanum, infected with Ehrlichia chaffeensis, E. ewingii, and spotted fever group Rickettsia in North-central Florida, August 2014 to February 2016...... 122

B-1 Summary of microbes, proteins, and toxins detected in, or associated with, lone star ticks, Amblyomma americanum ...... 142

B-2 Geographic coordinates of areas sampled during a tick survey in May 2015 at Florida state parks and wildlife management areas...... 144

B-3 Geographic coordinates of areas sampled during a tick survey between July 2014 and April 2016 at three North-central Florida locations...... 145

LIST OF FIGURES

Figure page

2-1 Collection kit distributed to collaborators for blood and tick samples from surveyed wildlife ...... 52

2-2 Explanation of the study included in each collection kit...... 53

2-3 Geographic distribution of tick samples collected from wildlife in Florida from 2000-2015 ...... 54

2-4 Geographic distribution of wildlife hosts sampled during a tick survey in Florida from 2000-2015...... 55

2-5 Seasonal trend of the major species adult ticks infesting wildlife hosts in Florida, 2000-2015...... 56

3-1 Percentage of wildlife sampled with Ehrlichia-reactive antibodies...... 74

4-1 Locations sampled during a tick survey conducted in May 2015...... 94

4-2 Number of ehrlichiosis and spotted fever group (SFG) rickettsiosis cases reported to Florida Department of Health from 2008-2012 (FL DOH 2016)...... 95

4-3 Lone star tick larval mass on lint roller sheet...... 96

4-4 Lochoosa Wildlife Management Area (WMA) and Marjorie Kinnan Rawlings State Park (SP) adult and nymphal lone star tick density comparisons between May 18, 2015 and May 27, 2015...... 97

4-5 Relative density of lone star tick, Amblyomma americanum, nymphs and adults collected from paired state parks (SP) and wildlife management areas (WMA) at eight sites in Florida from May 18-28, 2015...... 98

4-6 Adult lone star tick density by site...... 99

4-7 Nymphal lone star tick density by site...... 100

5-1 North-central Florida locations sampled during a tick survey conducted between July 2014 and April 2016 ...... 123

5-2 Density of lone star ticks, Amblyomma americanum, in north-central Florida .. 124

5-3 Temporal ehrlichial infection rates of host-seeking lone star ticks, Amblyomma americanum...... 126

5-4 Temporal rickettsial infection rates of host-seeking lone star ticks, Amblyomma americanum...... 129

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

EHRLICHIA AND RICKETTSIA TICK-BORNE INFECTIONS ASSOCIATED WITH LONE STAR TICKS AND UNDER-SAMPLED WILDLIFE HOSTS IN FLORIDA

Jeffrey C. Hertz

August 2016

Chair: Phillip E. Kaufman Major: Entomology and Nematology

Once considered only to be a nuisance because of its aggressive biting behavior, the lone star tick, Amblyomma americanum (L.) (LST) is now recognized as a major

vector of ehrlichial and rickettsial pathogens. The incidence rates of human ehrlichiosis

and spotted fever rickettsiosis, the diseases caused by these pathogens, have seen

dramatic increases over the last decade. There is limited information published on the

infection rates of these pathogens in ticks collected in Florida.

A survey was conducted to identify the ticks associated with under-sampled wildlife and to determine what animals, or associated ticks, are host to these pathogens.

Nine wildlife hosts were sampled and 4,176 ticks of six species were collected from

66% of Florida counties. All wildlife hosts examined using serological techniques had

Ehrlichia-reactive antibodies. Ehrlichial or rickettsial DNA was detected in four animals using molecular techniques. The same techniques were used to detect ehrlichial DNA and R. amblyommii in lone star ticks, and R. parkeri, R. rhipicephali, and rickettsial endosymbionts from the other tick species tested.

The relative risk of being exposed to ehrlichial and rickettsial pathogens was determined at 8 North-central Florida sites, each containing a wildlife management area

(WMA) and a state park (SP). Lone star ticks were collected and molecular techniques were used to determine that 87.5% of the sites had Ehrlichia-infected LSTs and 100%

of the sites had Rickettsia-infected lone star ticks. Paired WMAs and SPs had similar

lone star tick densities, infection rates, and relative risk, however, differences in these

criteria were observed between the 7 sites sampled.

In a longitudinal study, LSTs were sampled at three locations over a 22-mo

period to compare temporal infection rates of these pathogens. Ehrlichial (0-3%) and

rickettsial (40-75%) infection rates were comparable to other areas within the LSTs

range and seasonal fluctuations were observed. Ehrlichial infection rates had cyclical

peaks and were prevalent in all but three months, while rickettsial infections were

detected in every month.

The data presented expands tick-host relationship records of under-sampled hosts, adds to phenology and distribution records, and improves the understanding of ehrlichial and rickettsial pathogen maintenance in Florida.

CHAPTER 1 BACKGROUND AND LITERATURE REVIEW

Introduction

Two revolutionary discoveries led to a new era of science that revealed the role of ticks in disease-causing pathogen transmission (Sonenshine et al. 2002). In 1893,

Smith and Kilbourne linked the cattle tick, Rhipicephalus (Boophilus) annulatus (Say),

with Babesia bigemina, the causative agent of Texas cattle fever (Dennis and Piesman

2005). Later, in 1905, the tick-borne spirochete Borrelia duttoni was identified as the

causative agent of human relapsing fever (Sonenshine et al. 2002). Further scientific

discoveries over the last century have uncovered that ticks transmit a greater variety of

pathogenic microorganisms than any other arthropod vector group (Jongejan and

Uilenberg 2004).

Despite a greater understanding of disease transmission, ticks have been

discounted as important threats to public health because of the global importance of

mosquito-borne diseases (Beerntsen et al. 2000, Dennis and Piesman 2005). In the

temperate climates located in the United States and Europe, far more illnesses are

associated with ticks than any other arthropod vector, including the mosquito (Githeko

et al. 2000). In 2012, 30,000 cases of Lyme disease were reported to the Centers for

Disease Control and Prevention (CDC) in the United States, six times more than the

number of cases of the most reported mosquito-borne encephalitis, West Nile virus

(CDC 2014). The CDC believes that all tick-borne diseases are vastly underreported

and estimates that the actual number of Americans annually infected with Lyme disease

is closer to 300,000 (Hinckley et al. 2014, Nelson et al. 2015).

In the central and southeastern United States, ehrlichiosis and spotted fever rickettsiosis are the most frequently reported tick-borne diseases (Adams et al. 2015).

Their diagnoses have increased dramatically over the last decade, while reported cases of Lyme disease remain relatively stable (CDC 2014). Incidence rates of ehrlichiosis

and spotted fever rickettsiosis in Florida are remarkably lower than most other states in the central and southeastern regions (Drexler et al. 2016, Nichols Heitman et al. 2016), still case reports have continued to increase annually (FL DOH 2015). Without continued research, it is unclear if case reports are accumulating in Florida because of greater exposure to infected ticks or due to more healthcare providers becoming aware of the signs and symptoms of these diseases.

The lone star tick, Amblyomma americanum (L.), is the vector of several ehrlichial pathogens and is implicated in the transmission of rickettsial pathogens

(Childs and Paddock 2003, Goddard 2003, Cohen et al. 2009, Berrada et al. 2011,

Breitschwerdt et al. 2011). The abundance and geographic distribution of this species and its key vertebrate hosts, coupled with increased population growth in rural environments over the last several decades, has created conditions supportive of an increase the incidence of ehrlichiosis and rickettsiosis (Paddock and Yabsley 2007,

Stromdahl and Hickling 2012). The following pages will review the biology of the lone star tick, common ehrlichial and rickettsial pathogens, and the methods used to investigate zoonotic diseases.

The Lone Star Tick

Historically, the lone star tick was widely considered to be the most annoying and pestiferous tick in the United States (Goddard and Varela-Stokes 2009), but over the last two decades it has also become recognized as one of the more significant tick

vectors affecting Americans (Childs and Paddock 2003). It is the most abundant tick in

the southeastern United States and accounts for the majority of human tick bites, often

with multiple concurrent bites (Childs and Paddock 2003, Goddard and Varela-Stokes

2009, Berrada et al. 2011, Stromdahl and Hickling 2012).

Classification and Taxonomy

The lone star tick was first described in 1758 by Charles Linnaeus as Acarus

americanus from a type specimen originating in either Pennsylvania or New Jersey

(Hooker et al. 1912, Cooley and Kohls 1944). It was later reclassified as Ixodes

americanus (L.) by Fabricius in 1805 and then to Amblyomma americanum (L.) by Koch

in 1844 (Cooley and Kohls 1944).

Like all ticks, lone star ticks are mites belonging to the arthropod class

Arachnida, subclass Acari. Members of this subclass all have four pairs of legs as

adults, lack antennae and wings, and have pedipalps and chelicerae. Ticks, and some

mites, are the only parasitic members in Arachnida (Keirans and Durden 2005). Ticks

are differentiated from other mites by their relatively large size, the presence of a

hypostome, a dorsoventrally flattened appearance, and a sensory apparatus on the

tarsus of each foreleg called the Haller’s organ (Keirans and Durden 2005).

There are 896 currently recognized species of ticks divided into three families:

the Ixodidae, or hard ticks, comprised of 702 species; the Argasidae, or soft ticks, with

193 species; and an intermediary family, Nutalliellidae, which consists of one species

with features of both hard and soft ticks (Guglielmone et al. 2010). The genus

Amblyomma species are differentiated from the other 14 genera of Ixodidae by having

eyes, festoons, and an ornate appearance. Amblyomma species have sub-triangular or

comma-shaped spiracular plates, and the palps are generally long (Cooley and Kohls

1944, Guglielmone et al. 2010). Unengorged, adult female lone star ticks range in size

from 2.5 mm to 3.4 mm, making them slightly larger than the 3 mm long males. Lone

star tick nymphs are considerably smaller, measuring a little over 1 mm, and larvae are

difficult to see with the naked eye, measuring only 0.5 mm in length (Cooley and Kohls

1944). Adult lone star ticks are differentiated from the other 129 Amblyomma species by

its 3/3 hypostomal dentition, presence of a single spur on coxae II-IV, and two spurs on

coxae I, with the internal spur half the length of the external (Cooley and Kohls 1944,

Keirans and Litwak 1989). Additionally, adult lone star ticks exhibit sexual dimorphism

characterized by unique silver-colored ornamentation. Females have a prominent spot

on the distal tip of the scutum that other Amblyomma species lack, and the silvery

dorsal ornamentation on males is restricted to six disassociated, symmetrical markings

located on the lateral edges of the scutum. The juvenile stages resemble the adults,

however, they are smaller with larvae possessing six legs instead of the eight legs

found on nymphs and adults and lack ornamentation.

Distribution

Ticks are found on every continent, however, ticks of the genus Amblyomma

(Koch) are confined to the temperate and tropical regions of the world (Keirans and

Durden 2005). Lone star ticks are found only in North America and have historically

been restricted to the eastern and southeastern regions of the United States (Childs and

Paddock 2003). A county-level review published in 2014 suggests that a northward shift

has occurred in the distribution of lone star ticks, especially along the Atlantic Coast and

into the Midwest (Springer et al. 2014). In Florida, lone star ticks are found throughout

the state, but populations are more prevalent in the northern and central regions (Allan

et al. 2001). The limited distribution of lone star ticks in south Florida may be attributed to climate, vegetation, and/or host availability (Allan et al. 2001).

Biology

Lone star ticks are obligate, hematophagous three-host ticks that indiscriminately

blood-feed on a wide variety of birds and mammals for their development (Childs and

Paddock 2003). They have four stages of hemimetabolous development in their life

cycle: eggs, larvae, nymphs, and adults (Sonenshine 2005).

Life cycle

The lone star tick life cycle begins when gravid adult females deposit a clutch of up to 9,000 eggs in a suitable habitat (Drummond et al. 1971). The larvae, or seed ticks, emerge and ascend low vegetation to quest until a host passes. Replete larvae drop from their host and stay hidden in the environment until completion of their first molt

(Kohls and Brennan 1947, Semtner et al. 1973). As with larval ticks, lone star tick

nymphs must ascend vegetation and wait for an encounter with an acceptable host to

obtain a blood meal (Goddard 1989). Nymphs complete feeding and drop from the host

and molt into adults (Kohls and Brennan 1947, Loomis 1961, Troughton and Levin

2007). The adults attach to a third host to take a final blood meal for spermatogenesis in

males and oogenesis in females, and for each sex to find a suitable mate (Gladney and

Drummand 1970).

Mating is regulated by pheromones and occurs on the host (Kiszewski et al.

2001). Gravid lone star tick females drop from the host and lay eggs approximately 2-3

weeks after successfully mating (Troughton and Levin 2007). The lone star tick life cycle

can take 1 or 2 years to complete under natural conditions depending on the prevailing

environmental and climatic conditions (Loomis 1961, Belozerov 1976, Bouzek et al.

2013). However, in controlled laboratory conditions of 22-24°C, the entire lone star tick life cycle can be completed in 7-8 months (Troughton and Levin 2007).

Habitat

In order for ticks to survive, habitats must have favorable living conditions for tick and host survival, and an adequate blood source available to support all developmental tick life stages (Daniel and Dusbábek 1994). Lone star ticks prefer wooded habitats

containing numerous small and large mammals (Bishopp and Trembley 1945,

Sonenshine and Levy 1971). The habitat preferred by white-tailed deer, Odocoileus

virginianus (Zimmerman), is especially important to lone star ticks because deer are

considered a keystone host for all lone star tick developmental stages (Mount et al.

1993). Within a desired habitat, lone star ticks are dispersed in the environment through

diffuse high moisture microhabitats found within the leaf litter and duff layers (Davidson

et al. 1994). Because no terrestrial habitat is homogenous and microhabitat conditions

vary, lone star ticks are never evenly distributed (Daniel and Dusbábek 1994).

The most recently published literature documenting the ecology of ticks in Florida

was a dissertation by Rogers in 1953. He characterized Florida tick habitat into three

types: hardwood hammocks, flatwoods, and sandhills. Hardwood hammocks are any

areas covered by broad-leaf, evergreen forests; they can be further classified as low,

mesophytic, and upland. Flatwoods are low, mostly level areas characterized by

longleaf pine, Pinus palustris Mill., or slash pine, Pinus elliottii Engelm., forests with

saw-palmetto, Serenoa repens (W. Bartram), wire grass, Aristida stricta Michx, and

gallberry, Ilex glabra (L.) A. Gray, undergrowth. Sandhills are relatively elevated areas

of dry sandy soil with longleaf pines and turkey oaks, Quercus laevis Walter. Rogers

(1953) found that lone star ticks in Florida were restricted to hardwood hammocks, and

did not complete their life cycle in the flatwoods or sandhills. Rogers (1953) did collect a few lone star ticks in these areas, but they were restricted to interspersed hardwood hammock ecotones within the flatwood and sandhill habitats. Dramatic reforestation, host expansion, and urbanization have occurred throughout Florida over the past 60 years, which is thought to have broadened the tick habitat structure in the state.

Seasonality

Lone star ticks are active from early spring to late autumn throughout much of their geographic range (Goddard and Varela-Stokes 2009), however, seasonal activity

varies greatly under differing climatologic and environmental conditions, and host

availability (Dennis and Piesman 2005). Adults and nymphs utilize behavioral diapause

as an overwintering survival strategy during adverse environmental conditions, which

results in populations composed of ticks undergoing a 1- or 2-year life cycle (Belozerov

1976).

Goddard and Varela-Stokes (2009) generalized the seasonality of lone star ticks,

stating that adult activity begins in February, with peak populations spiking from May to

June, and diminishing towards the end of July. Nymphs in a population first appear in

March and tend to have a bimodal host-seeking seasonality; the first peak occurs from

May to June and represents nymphs that overwintered from the previous year, while the

second peak represents the in-year population and occurs in August. Larvae are

generally active from June through October with population numbers peaking in August.

Southern populations of lone star ticks, such as those found in Florida, can be

found active on and off hosts throughout the year (Rogers 1953). Two studies have

documented the seasonality of lone star ticks in Florida and each had similar results

(Rogers 1953, Cilek and Olson 2000). Both studies found that host-seeking adults were

active March through August, with a peak activity in May. Nymphs were first collected either in January or February through October, generally with bimodal peaks. The largest peak in the Rogers (1953) study was in May, whereas, Cilek and Olson (2000) collected more nymphs in September, indicating that spatial and temporal differences exist in Florida. Larvae were recovered from tick drags from May through November, peaking in July and August. Additionally, Rogers (1953) collected lone star ticks from cattle throughout the year. The majority of the lone star ticks collected were adults, which was the only life stage collected in every month.

Host preference and host-seeking behavior

Wildlife hosts serve as a food source, mode of transportation, and as a protected area for ticks to mate. Lone star ticks utilize at least three different host animals throughout their life cycle, but not necessarily different host species. Adult lone star ticks primarily feed on medium and large mammals, such as cattle, deer, hogs, foxes, and dogs, while smaller animals like birds, squirrels, and hares are common hosts for nymphs and larvae (Bishopp and Trembley 1945). Notwithstanding, immature lone star ticks often are found on medium and larger animals, especially white-tailed deer.

Rodents and reptiles are not important hosts for any life stage of this tick (Bishopp and

Trembley 1945, Rogers 1953).

Unlike many other ticks, lone star ticks use a combination of active and passive

strategies to find a host (Allan 2010). Host stimulus such as carbon dioxide or

pheromonal cues causes lone star ticks to aggressively crawl towards the host. In the

absence of cues, lone star ticks ascend vegetation and extend their forelegs in an

ambush behavior called questing. In a given area, lone star ticks can detect a carbon

dioxide source up to 23 m away (Wilson et al. 1972) and disperse up to 29 m to find a

host (Smittle et al. 1967).

Public Health and Veterinary Importance

As mentioned, ticks transmit a greater variety of pathogenic microorganisms than

any other arthropod vector group. Lone star ticks are no exception, and are associated

with several bacteria, viruses, and proteins that result in unique medical conditions and

potentially fatal tick-borne diseases (Table B-1). As research into the tick microbiome

improves and clinicians continue to learn more about the role of lone star ticks in public

health, there is little doubt that the list of lone star tick-associated pathogens will

increase. Of the microbes currently known to be associated with lone star ticks, bacteria

in the order Rickettsiales are assumed the most important. This group of gram-negative,

intracellular α-Proteobacteria includes the genera Rickettsia, Orientia, Ehrlichia,

Neorickettsia, and Anaplasma (Macaluso and Paddock 2014). Pathogens in the genus

Ehrlichia and Rickettsia have been associated with lone star ticks, and are the basis of

this study.

Ehrlichia pathogens

The general term, ehrlichiosis, is used to describe an illness caused by ehrlichial

pathogens that affects the health of animals and humans. Human ehrlichiosis in the

United States is caused by at least four pathogenic species: Ehrlichia chaffeensis

(Dawson et al. 1991, Breitschwerdt et al. 1998), E. ewingii (Breitschwerdt et al. 1998,

Buller et al. 1999), an Ehrlichia species provisionally called Panola Mountain Ehrlichia

(PME) (Reeves et al. 2008, Qurollo et al. 2013) and another species known as E. muris-

like (EML) or as sometimes referred to as Ehrlichia spp. Wisconsin (Pritt et al. 2011).

Lone star ticks are the primary vectors for transmitting E. chaffeensis, E. ewingii, and

presumably PME (Yabsley 2010); EML is transmitted by the blacklegged tick, Ixodes

scapularis Say (Karpathy et al. 2016).

Based on the number of cases reported since 1999, the most important species

for human ehrlichiosis infection in the United States is E. chaffeensis (CDC 2014). In

endemic areas, the prevalence of E. chaffeensis infection in adult lone star ticks tested

by PCR varies from about 2% to 25%, and nymphal infection rates are almost always

lower (Childs and Paddock 2003, Paddock and Yabsley 2007, Gaines et al. 2014,

Killmaster et al. 2014).

Ehrlichia ewingii infection has been reportable in the United States since 2008,

but has been reported at very low levels. The highest number of E. ewingii cases were

reported to the CDC was 17 in 2012, compared to 1,128 cases of E. chaffeensis

infection reported in the same year (CDC 2014). A 2016 report suggests E. ewingii may be under-diagnosed, and its geographic distribution and incidence may be greater than

currently reflected in morbidity data (Harris et al. 2016). Infection prevalence of E.

ewingii in host-seeking lone star ticks has ranged from 0-15% (Paddock and Yabsley

2007, Gaines et al. 2014).

Only one case of human PME infection has been reported, and that report

indicated the infection was mildly pathogenic (Reeves et al. 2008). Despite this, PME is

of considerable interest due to its close phylogenetic relationship with the causative

agent of heartwater disease, E. ruminantium (Sayler et al. 2015). Infection rates of PME

in natural lone star tick populations have not exceeded 3% in studies to date (Loftis et

al. 2008, Gaines et al. 2014, Killmaster et al. 2014, Harmon et al. 2015).

The first four human cases of EML were reported in 2009 (Pritt et al. 2011). The number of cases increased to close to 70 by the end of 2013, all of which have been reported from the Great Lakes region (CDC 2013). The novelty of this pathogen has left many questions unanswered, but research on this topic is being aggressively pursued in the upper Midwest. The distribution and prevalence of this pathogen outside of the upper Midwest is unknown.

Reservoir hosts are critical to the survival and transmission of Ehrlichia pathogens, as no transovarial transmission is thought to occur (Paddock and Childs

2003). Lone star tick larvae are believed to acquire the pathogen during feeding on an

infected host, and maintain the pathogen transstadially (Childs and Paddock 2003). The

white-tailed deer has been found to be the most competent natural reservoir of E.

chaffeensis and E. ewingii (Childs and Paddock 2003). White-tailed deer do not

demonstrate clinical manifestations of the disease, but seroconvert in as little as 10

days and are capable of maintaining a persistent bacteremia for months (Yabsley

2010). Many other species are exposed to E. chaffeensis and infection has been

documented in domestic animals, including dogs and goats, and various wildlife such as coyotes and ring-tailed lemurs (Yabsley 2010). The known reservoirs for E. ewingii are

domestic dogs, white-tailed deer, and goats (Paddock and Yabsley 2007, Meichner et

al. 2015, Starkey et al. 2015). Less is known about PME, but it is assumed that white-

tailed deer serve an important role in their maintenance (Loftis et al. 2008, Wormser and

Pritt 2015). Mice, Mus musculus, have been implicated as important reservoirs for EML

(Karpathy et al. 2016). As with other tick-borne pathogens, it is probable that multiple

species of wildlife are involved in the maintenance of these pathogens (Childs and

Paddock 2003).

It remains unclear what role other tick species have in the transmission of human

ehrlichial pathogens. It is important to note that detecting pathogen DNA in a tick does not implicate that particular species as a vector of the pathogen until verification by transmission studies can be made. Ehrlichia chaffeensis has been detected in the

American dog tick, Dermacentor variabilis (Say), the Pacific Coast tick, D. occidentalis

Marx, and the western blacklegged tick, Ixodes pacificus (Say) (Kramer et al. 1999,

Steiert and Gilfoy 2002, Holden et al. 2003), but transmission studies have not been

conducted. Panola Mountain Ehrlichia has been detected in host-seeking Gulf Coast

tick, Amblyomma maculatum Koch, and transmission studies have confirmed that it and

the lone star tick are competent vectors (Loftis et al. 2016). The blacklegged tick is the

only confirmed vector of EML (Karpathy et al. 2016), however, as with the other

ehrlichial pathogens, other under-sampled tick species may have a role in the

maintenance and transmission of these agents.

Human ehrlichiosis has been reported from 41 of Florida’s 67 counties since it

became a notifiable disease in 1999 (FL DOH 2016). Areas surrounding Leon County in

the panhandle and the counties lining the northeastern shore down through the Ocala

National Forest have reported more cases than the remainder of the state from 2000 to

2013. Alachua County reported 25 cases during the same time period, the most in

Florida. All of the human ehrlichiosis cases reported in Florida have been attributed to

E. chaffeensis. However, some cases may be due to another Ehrlichia species because

patients present with similar symptoms and all ehrlichial pathogens are indistinguishable by the serological methods commonly used for clinical diagnosis (FL DOH 2013).

Unfortunately, in Florida there is no standardized surveillance program for

identifying ehrlichial infections in tick populations, making it impossible to determine the

spatial and temporal variation associated with the pathogens or human case reporting.

Although no routine surveillance is being conducted, efforts are being made to

characterize the distribution and prevalence of ehrlichial pathogens in Florida. Surveys

conducted in Florida have detected E. chaffeensis, E. ewingii and PME in host-seeking

lone star ticks (Paddock and Childs 2003, Mixson et al. 2006, Loftis et al. 2008). The

most recent survey in north-central Florida as of this writing found 14.6, 15.6, and 2% of

host-seeking ticks collected from 2010-2012 were positive for E. chaffeensis, E. ewingii,

and PME, respectively (Sayler et al. 2016).

Examining tick hosts is another method of characterizing the distribution and

prevalence of ehrlichial pathogens, and there have been limited efforts in Florida for this

method of surveillance. Yabsley et al. (2005) predicted the endemic areas of E.

chaffeensis across the southeast using serological data obtained from white-tailed deer.

In both the kriging and logistic regression models used, all but the southernmost

counties of Florida were considered potentially endemic for E. chaffeensis. The

aforementioned study by Sayler et al. (2016) reported approximately 45% of white-tailed

deer specimens had antibodies to Ehrlichia spp., and 7.3% and 6.0% of the deer were

PCR positive for E. chaffeensis or E. ewingii, respectively (Sayler et al. 2016). Another

seroprevalence survey conducted in Florida examined dogs using species-specific

Ehrlichia antibodies (Beall et al. 2011). Their results showed a similar distribution for E.

chaffeensis to what Yabsley et al. (2015) reported and found that more E. ewingii

positive animals were concentrated in the central region of the state. However, the

sample distribution for this study was biased toward areas surrounding major

universities, which included the University of Florida. An Ehrlichia prevalence study with

a focus on raccoons, Procyon lotor (Linnaeus 1758), at six Florida field sites reported a

wide array of seroprevalence rates ranging from 0-91% (Comer et al. 2000).

Experimental inoculation studies in raccoons resulted in brief or absent infections, which

suggest that raccoons may not be important reservoirs in nature, but until tick-

transmission studies are conducted this cannot be confirmed (Yabsley 2010).

Rickettsia pathogens

Rickettsioses are among the earliest recorded and most recognized tick-

associated diseases. More than 20 species of Rickettsia have been identified or

presumptively connected with ticks and human disease globally, and an additional 50

rickettsial species have been identified with unknown pathogenicity (Parola et al. 2013).

Rickettsia rickettsii, the causative agent of Rocky Mountain spotted fever (RMSF), was

believed to be the only tick-borne rickettsioses endemic to the United States until 2004,

when a male patient from Virginia was diagnosed with a newly recognized spotted fever

illness caused by Rickettsia parkeri (Paddock et al. 2004). Four years later, the first

human infection with Rickettsia philipii (strain 364D) was reported from California

(Shapiro et al. 2010). Rickettsia africae, the causative agent for African tick bite fever, is

not endemic in the continental United States, but is reported in cattle and ticks

throughout the Caribbean including from the U.S. Virgin Islands (Kelly 2006, Kelly et al.

2010). Three cases of African tick bite fever have been diagnosed in Florida since 2010,

but all patients had reported travel to Africa (FL DOH 2015).

The association between lone star ticks and Rickettsia has been known since the early 1900s, but only indirect or circumstantial evidence has been published to support lone star tick competency as a vector of any pathogenic Rickettsia (Goddard and

Varela-Stokes 2009). Early research linked lone star ticks to the transmission of R. rickettsii by experimentally infecting recently emerged larvae on infected guinea pigs, allowing them to molt, and feeding the newly infected nymphs on a naïve guinea pig causing typical symptoms and death (Maver 1911). This claim came into question because most lone star tick pathogen surveys have failed to detect the pathogen in natural lone star ticks populations (Childs and Paddock 2003). However, R. rickettsii

DNA was amplified from a lone star tick removed from a North Carolina patient in 2011 and reinvigorated the debate regarding the competency of lone star ticks to vector R. rickettsii (Breitschwerdt et al. 2011). Berrada et al. (2011) strengthened the argument that lone star ticks are plausible vectors of the pathogen because they found R. rickettsia infection rate of lone star ticks, 0.46%, was greater than the infection rate of the American dog tick, Dermacentor variabilis (Say), 0.0%, the principal vector of this pathogen in Kansas. Despite this, they concluded that exposure to R. rickettsii is rare and a person would be 28 times more likely to encounter a lone star tick with R. amblyommii (Berrada et al. 2011). The authors further proposed that the low infection rates observed in lone star ticks may be due to a “dominant template bias,” in which

PCR preferentially amplifies a more abundant rickettsial template (e.g. R. amblyommii),

thereby masking a less abundant organism (e.g. R. rickettsii) and making it more

difficult to detect through current protocols.

Other Rickettsia species have been associated with lone star ticks, with the most common being Rickettsia amblyommii. Surveys of questing adult lone star ticks collected across the eastern United States reported average R. amblyommii infection rates of 13% to 66% (Parola et al. 2013). The only survey conducted of host-seeking lone star ticks in found R. amblyommii infection rates of lone star ticks were higher, ranging from 39.8% to 75% (Sayler et al. 2014). This species has been attributed to mild illness in humans (Billeter et al. 2007, Apperson et al. 2008), but because culture isolation has not been achieved from a mammalian species the pathogenicity is still unclear (Sayler et al. 2014). It is believed that exposure to this species confers some immunity to more virulent species (Dahlgren et al. 2016).

Perhaps the most puzzling rickettsial-like organism associated with lone star ticks is Rickettsia texiana, the presumptive cause of the Bullis fever outbreak of military personnel in 1942 (Goddard 1989, Childs and Paddock 2003). The predominant tick in the area was the lone star tick, but entomologists could not definitively link the illness to the vector (Goddard and Varela-Stokes 2009). No laboratory isolates of the putatively named Rickettsia texiana exist today, nor has the disease been reported again (Childs and Paddock 2003). It has been suggested that Bullis fever may have been due to an E. chaffeensis infection rather than an infection with a novel Rickettsia pathogen (Bavaro et al. 2005).

Rickettsia parkeri is primarily vectored by the Gulf Coast tick, but lone star ticks co-feeding with R. parkeri-infected Gulf Coast ticks are able to acquire the pathogen and transstadially maintain the infection (Wright et al. 2015). Recent tick pathogen surveys have found R. parkeri DNA in lone star ticks collected in Tennessee, Georgia,

and Virginia (Cohen et al. 2009, Gaines et al. 2014). No human infection by this pathogen has been linked directly to lone star ticks to date, but Goddard (2003) experimentally showed that lone star ticks inoculated with R. parkeri could infect naive guinea pigs.

Rickettsia montanensis and R. massiliae have been detected in lone star ticks

(Clay et al. 2008, Moncayo et al. 2010). Rickettsia montanensis has been associated with a mild human rickettsial infection following the bite of an American dog tick

(McQuiston et al. 2012). Rickettsia massiliae has been reported as pathogenic in other countries (Vitale et al. 2006) and has been detected in brown dog ticks, Rhipicephalus sanguineus (Latreille), in California and Arizona (Eremeeva et al. 2006, Beeler et al.

2011), however no human infections have been reported in the United States. The prevalence and distribution of these organisms in lone star ticks is unknown.

In the United States, the primary vectors for spotted fever pathogens are considered to be the American dog tick, the Gulf Coast tick, Amblyomma maculatum

Koch, the brown dog tick, and the Rocky Mountain wood tick, Dermacentor andersoni

Stiles (CDC 2013). Of these vectors, the Rocky Mountain wood tick is the only species not found in Florida. Lone star ticks should be considered as vectors of spotted fever group pathogens until definitive evidence can preclude it from having a role in the dramatic increase of rickettsiosis cases reported across its distribution.

As with the other tick vectors, lone star ticks are capable of transmitting rickettsial bacteria transovarially and transstadially, which makes them an efficient reservoir host for the bacteria (Macaluso and Azad 2005). Transovarial transmission eliminates the need for vertebrate hosts in order for the bacterium to survive. However, vertebrates are

needed to amplify the bacteria and distribute the infection throughout a tick population

(Sonenshine et al. 2002, Macaluso and Azad 2005). Ground rodents and lagomorphs are commonly parasitized by R. rickettsii-infected ticks and may serve as amplification hosts (Parola et al. 2005). One study in Florida examining four tick species collected from 18 black bear, Ursus americanus Pallas, found that 36 ticks had detectable levels of Rickettsia spp. DNA (Yabsley et al. 2009). All of the lone star ticks that tested positive for Rickettsia spp. (n=5) were further characterized by sequencing and identified as R.

amblyommii. The pathogen maintenance status of other vertebrate tick hosts remains

unclear, and this is especially true in Florida where surveys are not conducted routinely.

More than half of the human Rocky Mountain spotted fever infections in the

United States are reported from the South-Atlantic region (CDC 2014). Of the 22 human cases reported from Florida in 2013, 68% were acquired within the state (FL DOH

2015). Infections have been reported every month of the year in Florida, with no identifiable peak in transmission. Most cases of spotted fever rickettsiosis have been reported from the north and north-central regions of the state where lone star ticks are most abundant.

Research Objectives

In this chapter an attempt has been made to review the literature regarding the bionomics of lone star ticks and the importance of this tick species as a vector of pathogens in the United States. While I was able to gather a considerable amount of information on this species, relatively little information is available from Florida. Because ticks and their pathogens have been shown to be temporally and spatially variable, it is important to continue proactive, surveillance-based research to expand upon what is known about ticks and their pathogens in order to better communicate risk and prevent

future tick-borne diseases. The overall goal of this project is to gain a greater understanding of the emerging Ehrlichia and Rickettsia pathogens associated with lone star ticks. The following studies are proposed:

1. Identify which wildlife in Florida are hosts to lone star ticks, and determine if distribution differs spatially among different Florida regions.

2. Determine prevalence of Ehrlichia and Rickettsia pathogens in Florida by sampling wildlife hosts for infected lone star ticks and exposure to these pathogens.

3. Compare state parks and wildlife management areas to determine relative risk of exposure to lone star tick-transmitted Ehrlichia and Rickettsia pathogens.

4. Seek to understand the temporal infection dynamics of Ehrlichia and Rickettsia pathogens in host-seeking lone star ticks.

CHAPTER 2 DISTRIBUTION AND HOST ASSOCIATIONS OF IXODID TICKS COLLECTED FROM FLORIDA WILDLIFE.

Introduction

Ticks are significant vectors of a wide variety of infectious agents that adversely affect human and animal health (Sonenshine 2013). Ticks, and their associated pathogens, are supported in nature through complex zoonotic networks, often involving a variety of wildlife hosts (Childs and Paddock 2003). These wildlife hosts provide blood meals for ticks, serve as reservoirs for pathogens, and disperse ticks and their associated pathogens across geographic regions. Thus, routine surveillance of wildlife is an efficient way to monitor for the introduction of foreign and exotic ticks, track changes in the distribution of native ticks, and determine the prevalence of tick- associated pathogens.

Florida’s rich biodiversity of both native and invasive wildlife supports a wide variety of tick species. Excellent book reviews of the tick collection records associated with Florida mammals (Forrester 1992) and birds (Forrester and Spalding 2003) are available. More recent records of tick-host associations on companion animals

(Burroughs et al. 2016), reptiles (Corn et al. 2011), and other mammals (Wehinger et al.

1995, Durden et al. 2000, Allan et al. 2001, Foster et al. 2003, Yabsley et al. 2009) have

been published and add to the Florida tick collection records.

Although extensive tick-host relationship data exists for select species in Florida,

tick collection records are still lacking from some common Florida wildlife. For example,

Forrester (1992) discusses the internal parasites of coyotes, Canis latrans Say, but

gives little detail to the external parasites found on these animals. Foster et al. (2003)

reported that the Gulf Coast tick, Amblyomma maculatum Koch, and the American dog

tick, Dermacentor variabilis (Say), were recovered from coyotes in three North-central

Florida counties but these records likely are not representative of all ticks found on coyotes in other regions of the state nor did the authors report any details on the prevalence or intensity of infestation of these animals.

Wild turkey, Meleagris gallopavo L., is another example of a wildlife species for which Florida tick records are lacking. Forrester and Spalding (2003) reported that only the lone star tick, Amblyomma americanum (L.), was recovered from wild turkey in

Florida, but in very low numbers. They concluded that wild turkeys are not commonly infested with ticks in Florida, however this conclusion was based on only eight turkeys examined from north Florida. More recent publications in Kansas (Mock et al. 2001),

California (Lane et al. 2006), and Tennessee (Scott et al. 2010) suggest that wild turkeys may be very important hosts to a variety of tick species including lone star ticks.

The objectives of our study were to identify which tick species occur naturally on

wildlife hosts in Florida and determine if tick species distribution differs spatially among

different Florida regions.

Materials and Methods

Ticks were acquired through two collection sources: 1) a collection kit (CK)

program organized by the University of Florida Veterinary Entomology Laboratory and

2) archived samples from the Florida Fish and Wildlife Conservation Commission Lovett

E. Williams Jr. Wildlife Research Laboratory (FL FWC) located in Gainesville, FL. The

CK program focused on ticks collected from wild turkey, feral swine, Sus scrofa L., and

white-tailed deer, Odocoileus virginianus (Zimmermann), although opportunistic samples from other wildlife were received through this program. The collection kits were distributed to collaborators prior to Florida’s 2014 spring wild turkey hunting season and

were replenished, as requested, through the conclusion of the 2015 fall general hunting season. Collaborators included individual hunters, FL FWC biologists, and hunter check

station volunteers. Each collection kit (Figure 2-1) contained an explanation of the study

(Figure 2-2), a data collection envelope, an 8-mL plastic snap-top collection vial, a small

resealable plastic bag, and a postage-paid return envelope. Collaborators were

instructed to collect as many ticks as possible, by hand or with forceps, from recently

deceased animals and record the animal species, age and sex, as well as harvest date,

location, and tick attachment sites on the data collection envelope before returning all

materials to our laboratory in the postage-paid envelope. Ticks provided by FL FWC

were collected opportunistically from a variety of wildlife by FL FWC biologists during necropsy investigations and other ongoing research programs, which included tick collections from game harvests reported at hunter check stations. These samples were stored in at least 70% isopropyl alcohol at room temperature until identification. All wildlife sample collection was approved under University of Florida Institutional Animal

Care and Use Committee protocols #201308183 and #201408189.

Ticks were identified to species and quantified by life stage and sex using published keys (Clifford et al. 1961, Keirans and Litwak 1989, Keirans and Durden

2004), and representative samples are maintained in the research collection of the

University of Florida Veterinary Entomology Laboratory. Tick collections across Florida were grouped into three geographic regions (north, central and south) based on ecosystem descriptions by Myers and Ewel (1990) and for comparison to Allan et al.

(2001) (Figures 2-2 and 2-3).

Tick quantification is reported following the guidelines of Rózsa et al. (2000).

Prevalence was calculated as the proportion of infested hosts by a tick species among

all hosts examined of the same host species. Mean intensity was calculated as the

number of individuals of a tick species divided by the total number of infested hosts of

the same species. Confidence intervals (95%) were calculated following the Sterne’s

Exact Interval for prevalence, and a bias-corrected and accelerated (BCa) method with

2000 bootstrap replications for mean intensity (Sterne 1954, Efron 1987, Reiczigel

2003). Prevalence and mean intensity calculations were performed using QPweb

(Reiczigel et al. 2015). Seasonal trends in tick prevalence were estimated by dividing the monthly collection totals of each tick species by the total number of samples received per month. Determination of a significant difference in relative occurrence of tick species by region was evaluated using a Fisher’s Exact test with the Bonferroni correction (McDonald 2014). Prevalence and mean intensity data were not statistically analyzed because sample collection was not standardized across wildlife.

Results

A total of 4,176 ticks were identified to species from 695 samples collected from

American black bear, Ursus americanus (Pallus), bobcat, Lynx rufus (Schreber), coyote, feral swine, Florida panther, Puma concolor coryi Bangs, gray fox, Urocyon

cinereoargenteus (Schreber), raccoon, Procyon lotor (Linnaeus), white-tailed deer, and

wild turkey. Geographic distributions of the samples by tick species and wildlife host can be found in Figures 2-3 and 2-4, respectively. Seventy-one percent of the samples were obtained through the CK program during 2014-2015. The FL FWC samples had collection dates with the following distribution: 2000-2010 (n = 20; 11%), 2011-2012 (n =

41; 22%), and 2013-2014 (n = 124; 67%). The combined samples represented every

month of the year, although the majority (37%) of the samples were collected in March

(Figure 2-5).

Of the six tick species represented in the samples, lone star ticks were the most

abundant (75%), followed by blacklegged ticks, Ixodes scapularis Say (14%), Gulf

Coast ticks (8%), and American dog ticks (3%). Collections of Ixodes affinis Neumann

and Ixodes texanus Banks equaled less than 1.0% of the total number of ticks received.

The only immature ticks collected from the wildlife surveyed were lone star tick larvae

and nymphs, which comprised 56% of the identified ticks.

The prevalence and mean intensity of ticks infesting major (Tables 2-1 and 2-2)

and minor (Table 2-3) wildlife hosts likely did not represent total tick populations

infesting the individual wildlife. Therefore, the data should be considered as minimum

prevalence and mean intensity values. Table 2-4 lists the relative occurrence of the tick

species infesting each wildlife host by region. All hosts, except bobcats and wild

turkeys, were associated with three or more tick species. Lone star ticks were found on

all wildlife except bobcats and Florida panthers, and were most frequently collected

from wild turkeys (n = 1,796). The highest prevalence (94%) and mean intensity (16.1)

for lone star ticks was from black bear. Gulf Coast ticks and American dog ticks were

collected from six of the nine hosts examined. Although more Gulf Coast ticks were

collected from white-tailed deer (n = 169) than any other host animal, the highest

prevalence (27%) and mean intensity (7.5) was associated with coyotes. American dog

ticks were collected most from black bears (n = 62), and had the highest prevalence

(68%) and the greatest mean intensity (3.0). The blacklegged tick was collected from all

hosts except raccoons, and most frequently removed from feral swine (n = 247).

However, the highest prevalence (47%) and mean intensity (5.6) for the blacklegged tick was from coyotes. The few I. affinis samples were collected from white-tailed deer

(n = 20), with the exception of one female I. affinis recovered from a Florida panther.

Raccoons were the only host found with I. texanus (n = 1).

Discussion

In this study, ticks were collected from wildlife to better understand host

relationships and distribution patterns of ticks on medium and large host species in

Florida. The lone star tick was the most common tick infesting wildlife in this survey. The

frequency in which the lone star tick was collected was anticipated because this tick

species is the most abundant tick found throughout the southeastern United States and

is known to have aggressive, generalist feeding habits (Merten and Durden 2000,

Goddard and Varela-Stokes 2009). The lone star tick is a vector of several ehrlichial

pathogens, Francisella tularensis, Rickettsia rickettsii, and is linked with a red meat

allergy and a disease of unknown etiology called Southern Tick-Associated Rash Illness

(STARI) (Goddard and Varela-Stokes 2009, Commins et al. 2011). Southern

populations of lone star ticks can be found on hosts throughout the year (Rogers 1953),

as was seen in our survey. December was the only month adult ticks were not

recovered, which was not unexpected considering off-host peak adult activity occurs

between March and August (Cilek and Olson 2000, Rogers 1953). Nymphs were

recovered in every month in this survey, but larvae were not recovered from the wildlife

in February, May, or July. Off-host peak larval activity occurs throughout the year in

Florida except during the coldest months (Rogers 1953), which may account for why no

larval ticks were recovered during February. The lack of larval collections in May and

July from this study was likely due to the low volume of samples received in those

months (11 and 5, respectively), and because larval ticks are difficult to find by the collector.

In our survey, 94% of the lone star ticks collected were from black bear, white- tailed deer, and wild turkey. The prevalence of this tick on black bear in our study is at least 40 percentage points higher than what has been reported previously from black bears in the southern United States (Forrester 1992, Yabsley et al. 2009, Leydet and

Liang 2013). The reason for this disparity is unclear, but could be due to higher lone star

tick densities in the habitat where the black bear samples originated.

Lone star tick prevalence on white-tailed deer has been reported as high as

100% in some areas throughout this tick’s distribution (Childs and Paddock 2003). In

Florida, lone star tick prevalence on white-tailed deer has been reported near 30-35%,

but varies greatly based on the geographic location of the white-tailed deer (Allan et al.

2001). Allan et al. (2001) stated that white-tailed deer in the southern regions of Florida

were not infested with lone star ticks, while white-tailed deer in the northern regions had

prevalence values above 17%. Indeed, no lone star ticks were collected in this survey

from white-tailed deer or any wildlife south of Pasco County, except for four adult lone

star ticks recovered from two coyotes harvested in Highlands County. Allan et al. (2001)

credits the difference in climate and vegetation found in south Florida as the likely

reasons that restrict the lone star tick distribution to the northern regions of the state.

Although no significant differences were seen in lone star tick prevalence on white-tailed

deer in Allan et al. (2001), our study had significantly more lone star ticks submitted

from the north region of the state. An increase in the number of lone star tick

submissions for the north region does not necessarily indicate that lone star tick

densities are greater in this region, but further studies should investigate what ecological conditions affect lone star tick populations across Florida’s diverse ecosystems and climatic conditions.

Lone star tick prevalence on turkey was very similar to that of white-tailed deer in our study. This indicates that lone star ticks are more common on turkeys in Florida than previously reported (Forrester and Spalding 2003), and, perhaps, the prevalence of this tick on turkeys is more similar to what has been observed in other areas where the tick and this host are sympatric (Kellogg et al. 1969, Mock et al. 2001, Scott et al. 2010).

Some turkeys from our study were heavily infested, supporting a great number of larvae

(n = 138), nymphs (n = 81), and total ticks (n = 160) from individual birds. It is likely that these numbers did not represent the absolute number of ticks infesting the individual birds, but clearly demonstrate that wild turkeys are favored by immature lone star tick life stages. Only three adult ticks, one male and one female lone star tick and one female blacklegged tick, were recovered from wild turkeys. To our knowledge, this is the first collection record of adults from these species reported from wild turkeys. Only seven turkey samples were submitted outside of the spring wild turkey hunting season.

It is likely that other ixodid ectoparasites infest wild turkeys throughout the year, and

future studies should investigate this temporal effect to establish host relationships that

may be important in zoonotic cycles.

The blacklegged tick, the second most collected tick in our survey, is the principal

vector for the pathogens that cause Lyme borreliosis, anaplasmosis, and human

babesiosis (Nelder et al. 2016). Although the blacklegged tick is collected frequently in

Florida, the diseases associated with this vector are reported less frequently in the

southeast as compared to other areas throughout this tick’s distribution (Adams et al.

2015). The blacklegged tick was collected only from samples taken between October and March in our survey, which corresponds to the peak activity period of the adult life stage in Florida (Taylor 1951). Immatures of this tick were not recovered because these life stages preferentially feed on smaller animals such as native mice and lizards, which were not sampled during this survey (Keirans et al. 1996).

The blacklegged tick was collected on all wildlife except raccoons, however, this tick has been recorded from Florida raccoons previously (Forrester 1992) and our exception likely is due to the low numbers of raccoon samples received. The blacklegged tick was most frequently collected from feral swine, white-tailed deer, and coyote. The prevalence rate of this tick on feral swine (35%) and white-tailed deer

(23%) in this survey is nearly half of the statewide prevalence rate for these species

reported by Allan et al. (2001). Our survey and the survey conducted by Allan et al.

(2001) differed in sample distributions. For example, no feral swine samples were

received from the southern region of the state in our study while the majority of samples

from the Allan et al. study did. Similarly, the majority of deer samples in our study were

received from the north region, while the majorities in the Allan et al. (2001) study were

received from the central region. These differences in sample distributions may

correspond with unique habitat utilization of the wildlife hosts represented, potentially

resulting in variable infestation levels of distinct tick species. Blacklegged ticks were not

reported from the coyotes surveyed in Florida by Foster et al. (2003), which also made

no mention of the month the coyotes were sampled. Blacklegged ticks have been

collected from coyotes in other regions of the country, but small sample sizes make

interpretation of the reported prevalence rates difficult to compare (Pence et al. 1981,

Kollars et al. 2000). One survey in North Carolina, consisting of 37 coyotes, found 47% to be infested with blacklegged ticks (Chitwood et al. 2015).

Gulf Coast ticks were the third most abundant tick collected in our survey.

Historically, these ticks were thought to be of concern because of the economic impact caused to livestock due to the soft tissue reactions the animals developed from the tick bites (Teel et al. 2010). Now this tick species is considered an important vector of human pathogens because of its efficiency in transmitting the spotted fever pathogen

Rickettsia parkeri (Paddock and Goddard 2015). Collections of this tick were made in all months except April, May, and June in our survey, and only adults were collected. Gulf

Coast tick larvae and nymphs prefer feeding on small animals, especially birds (Bishopp and Hixson 1936). No Gulf Coast ticks were submitted from any of the wild turkey samples, despite the immature stages being active during March and April, the peak months when wild turkeys were sampled (Delany and Forrester 1997, Cilek and Olson

2000). Wild turkeys do not appear to be an important host for this tick species, however information on the phenology and host associations of this tick in Florida is scarce and should be further investigated to confirm.

The greatest numbers of Gulf Coast ticks were recovered from black bear, coyote, and white-tailed deer. Of these, coyote had the highest prevalence of infestation

(29%), which was lower than what has been reported in North Carolina (47%) and

Oklahoma (42-100%) (Barker et al. 2004, Chitwood et al. 2015). The only report to our knowledge of the ectoparasites from coyotes in Florida did not quantify the abundance or prevalence of Gulf Coast ticks recovered (Foster et al. 2003). Three coyotes in our

survey had greater than 10 Gulf Coast ticks per animal indicating that high infestation rates of this tick may be common. The 23% statewide prevalence of Gulf Coast ticks on white-tailed deer was lower than the 32-36% rates previously reported in the state by

Allan et al. (2001). Prevalence rates between the two surveys were similar in the southern region (60.2% in Allan et al. compared to 62.5% in our study), but varied in the north and central regions (11% compared to approximately 28% reported by Allan et al.). Similarly, Gulf Coast tick prevalence rates on black bears (13%) were lower in our study compared to the 30% prevalence rate reported by Forrester (1992) and 22% reported by Yabsley et al. (2009). Unlike the variation seen in the white-tailed deer sample distribution, most of the black bears harvested in this study and the Yabsley et al. (2009) and Forrester (1992) studies were from north and central Florida, however county location data varied between each study. It is clear from the results of Allan et al.

(2001) and our survey that latitudinal variability exists in the Florida Gulf Coast tick population, with greater densities found in the southern region. It is unclear, however, if sample collection variability or differences in unique habitat utilization by the host animals resulted in the prevalence differences between these studies.

The American dog tick is one of the most recognized ticks in the United States

(Rogers 1953). It is a vector of Francisella tularensis (Reese et al. 2011) and various spotted fever group pathogens, including Rickettsia rickettsii (Parola et al. 2013). This tick was the fourth most collected tick species. As with most of the other ticks collected in this survey, only adult American dog ticks were recovered from the host animals surveyed. The immature stages of this tick feed on rodents, which were not sampled.

The adult ticks were collected from hosts in every month of the year in this survey, consistent with previous reports from Florida (Rogers 1953).

The majority of American dog ticks from our survey were collected from black bear, coyote, and Florida panthers. Black bear and Florida panthers had similar prevalence rates, 68% and 70% respectively, while only 29% of coyotes carried infestations. Previous surveys reported prevalence rates on black bears ranging from

39-75% (Forrester 1992, Yabsley et al. 2009) and 75-92% on Florida panthers

(Forrester 1992, Wehinger et al. 1995). American dog ticks were recovered from

coyotes surveyed in Florida by Foster et al. (2003), but as previously mentioned no

remarks were made regarding the tick abundance or prevalence. Chitwood et al. (2015)

found that 17% of the coyotes surveyed in North Carolina to be infested with this tick.

Interestingly, relatively few (5%) feral swine were infested with American dog ticks in our

study. This contrasts with the earlier reports by Greiner et al. (1984) and Allan et al.

(2001) despite the similar collection periods between the three studies. Nearly all of the

feral swine examined in southern Florida by Greiner et al. (1984) had American dog

ticks (>99%), whereas Allan et al. (2001) reported infestation on approximately 57% of

the feral swine examined in the central and southern regions of the state. Most of the

feral swine harvested in our survey were from the central region, and 68% were

received from either the Green Swamp West Unit Wildlife Management Area (WMA) or

Tosohatchee WMA. Sampling by Greiner et al. (1984) was restricted to one location

while Allan et al. (2001) had several locations, including Green Swamp West Unit WMA.

There have been suggestions that American dog tick populations are being displaced

by other tick species, namely the lone star tick, in other regions of the United States

(Stromdahl and Hickling 2012). Unfortunately, we can only speculate whether this phenomenon may be occurring in the locations where our samples originated. Further investigation is warranted to determine if displacement is occurring in areas where sympatric populations of these ticks occur in Florida.

Only 21 I. affinis were collected in our survey, and the collected adults originated from white-tailed deer and Florida panthers. Ixodes affinis are competent hosts of

Borrelia pathogens, including B. burgdorferi s.s. and B. bissettii, but are not known to bite humans (Maggi et al. 2010). Therefore, they are considered to be an insignificant public health risk, but may be more important than I. scapularis in maintaining the enzootic cycles of these pathogens (Oliver et al. 2003). This tick has not been studied in depth in Florida but may have a phenology comparable to other areas of the southeast.

In Georgia, Virginia, and North Carolina, adult activity of this tick occurred from April to

November (Oliver et al. 1987, Harrison et al. 2010, Nadolny et al. 2011). In our study, two I. affinis ticks were collected in July and more abundantly from September through

November, with the most being collected in October.

Only one adult female I. texanus was collected in our study. This tick is not considered an important vector of human pathogens because of the low frequency in which they feed on humans, however R. rickettsii has been detected in these ticks

(Angeloni 1994). Ixodes texanus likely occurs statewide in Florida (Rogers 1953), but is reported rarely and few studies focusing on this species have been conducted. As a result, the phenology is unknown in Florida. In Missouri and Virginia, I. texanus have been recovered from host animals in all months of the year (Sonenshine 1979, Kollars and Oliver 2003) .

All six species of ticks collected in this study have been reported previously from mammals and birds in Florida (Forrester 1992, Forrester and Spalding 2003). The lone

star tick, the American dog tick, and the blacklegged tick had the broadest host range

while the American dog tick, the blacklegged tick, and the Gulf Coast tick had the widest

geographic distribution. The data presented here greatly expands tick collection state

records from coyote and wild turkey, but information gaps still exist for numerous wildlife

found in Florida. Tick-host association records are often influenced by prevalence of the

host species and the importance of the hosts to humans such as game animals, pests,

and livestock. Surveys of under-sampled hosts may reveal new host associations and

pathogen maintenance systems not previously known.

Table 2-1. Prevalence (95% CI) of ixodid ticks collected from major wildlife hosts in Florida, 2000-2015. Species Black Bear Coyote Feral Swine White-tailed Deer Wild Turkey Life stage (N=31) (N=49) (N=130) (N=139) (N=326) Amblyomma americanum Adults 90 (75-97) 18 (10-32) 32 (25-41) 37 (30-45) 0.3 (0-2) Nymphs 42 (26-60) 4 (1-14) 7 (4-13) 30 (23-39) 42 (37-48) Larvae 10 (3-26) 0 (NC) 1 (0-4) 9 (5-15) 19 (15-23) All Stages 94 (79-99) 20 (11-34) 35 (27-43) 45 (37-54) 44 (38-49) Amblyomma maculatum Adults 13 (5-29) 27 (16-41) 5 (3-11) 23 (17-31) 0 (NC) Dermacentor variabilis Adults 68 (50-83) 29 (17-43) 4 (2-9) 0 (NC) 0 (NC) Ixodes affinis Adults 0 (NC) 0 (NC) 0 (NC) 7 (3-12) 0 (NC) Ixodes scapularis Adults 29 (16-47) 47 (34-61) 35 (28-44) 23 (17-31) 0.3 (0-2) Ixodes texanus Adults 0 (NC) 0 (NC) 0 (NC) 0 (NC) 0 (NC)

All ticks 100 (89-100) 88 (76-95) 63 (54-71) 76 (68-83) 44 (39-49) Prevalence = % of hosts with a particular tick species, 95% confidence interval (CI) were calculated using Sterne’s Exact Interval (Sterne 1954) with QPweb (Reiczigel et al. 2015); NC = not calculable. N = number of host samples.

Table 2-2. Mean intensity (95% CI) of ixodid ticks collected from major wildlife hosts in Florida, 2000-2015. Species Black Bear Coyote Feral Swine White-tailed Deer Wild Turkey Life stage (N=31) (N=49) (N=130) (N=139) (N=326) Amblyomma americanum Adults 12.6 (9.6-17.4) 2.8 (1.9-4.1) 2.6 (2.0-3.5) 5.5 (4.0-7.7) 2.0 (NC) Nymphs 8.2 (3.4-17.7) 1.0 (NC) 2.4 (1.2-5.7) 4.9 (3.8-6.2) 7.0 (5.5-9.4) Larvae 2.7 (2.0-2.7) 0 (NC) 13.0 (NC) 14.2 (4.9-37.6) 13.7 (9.3-21.7) All Stages 16.1 (11.8-24.7) 2.7 (1.8-4.1) 3.2 (2.3-5.1) 10.4 (7.9-16.0) 12.6 (9.8-17.3) Amblyomma maculatum Adults 8.5 (2.3-19.5) 7.5 (3.8-12.2) 2.0 (1.3-2.4) 5.3 (3.7-7.8) 0 (NC) Dermacentor variabilis Adults 3.0 (2.1-4.6) 2.3 (1.4-3.8) 1.2 (1.0-1.4) 0 (NC) 0 (NC) Ixodes affinis Adults 0 (NC) 0 (NC) 0 (NC) 2.2 (1.8-3.3) 0 (NC) Ixodes scapularis Adults 3.2 (1.7-5.7) 5.6 (4.1-7.9) 5.4 (4.0-7.6) 4.2 (2.8-7.7) 1.0 (NC) Ixodes texanus Adults 0 (NC) 0 (NC) 0 (NC) 0 (NC) 0 (NC)

All ticks 19.1 (14.5-27.6) 6.16 (5.1-8.6) 5.0 (4.0-6.7) 9.3 (7.4-12.4) 12.6 (9.9-17.4) Mean intensity = mean number of ticks per infested hosts; 95% confidence interval (CI) calculated using the bias-corrected and accelerated method (Efron 1987) with 2000 bootstrap replications using QPweb (Reiczigel et al. 2015); NC = not calculable. N = number of host samples.

Table 2-3. Prevalence and mean intensity of ixodid ticks collected from minor wildlife hosts in Florida, 2000-2015. Speciesa Bobcat (N=2) Fox (N=3) Panther (N=10) Raccoon (N=5) Prevalence Mean Intensity Prevalence Mean Intensity Prevalence Mean Intensity Prevalence Mean Intensity Life stage (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) A.a. Adults 0 (NC) 0 (NC) 33 (2-87) 3.0 (NC) 0 (NC) 0 (NC) 20 (1-66) 1.0 (NC) Nymphs 0 (NC) 0 (NC) 0 (NC) 0 (NC) 0 (NC) 0 (NC) 40 (8-81) 9.0 (3.0-9.0) Larvae 0 (NC) 0 (NC) 0 (NC) 0 (NC) 0 (NC) 0 (NC) 20 (1-66) 1.0 (NC) All Stages 0 (NC) 0 (NC) 33 (2-87) 3.0 (NC) 0 (NC) 0 (NC) 40 (8-81) 10.0 (3.0-10.0) A.m. Adults 0 (NC) 0 (NC) 33 (2-87) 3.0 (NC) 10 (1-45) 1.0 (NC) 0 (NC) 0 (NC) D.v. Adults 0 (NC) 0 (NC) 33 (2-87) 2.0 (NC) 70 (38-91) 2.9 (1.6-4.3) 40 (8-81) 1.5 (1.0-1.5) I.a. Adults 0 (NC) 0 (NC) 0 (NC) 0 (NC) 10 (1-45) 1.0 (NC) 0 (NC) 0 (NC) I.s. Adults 100 (22-100) 5.5 (1-5.5) 33 (2-87) 6.0 (NC) 40 (15-71) 10.0 (1.5-24.8) 0 (NC) 0 (NC) I.t. Adults 0 (NC) 0 (NC) 0 (NC) 0 (NC) 0 (NC) 0 (NC) 20 (1-66) 1.0 (NC)

All ticks 100 (22-100) 5.5 (1-5.5) 100 (37-100) 4.7 (2.0-6.0) 100 (71-100) 6.2 (2.2-17.1) 100 (50-100) 4.8 (1.4-13.8) Prevalence = % of hosts with a particular tick species, 95% confidence interval (CI) were calculated using Sterne’s Exact Interval (Sterne 1954) with QPweb (Reiczigel et al. 2015); Mean intensity = mean number of ticks per infested hosts; 95% confidence interval (CI) calculated using the bias-corrected and accelerated method (Efron 1987) with 2000 bootstrap replications using QPweb (Reiczigel et al. 2015); NC = not calculable. a A.a. = Amblyomma americanum; A.m. = Amblyomma maculatum; D.v. = Dermacentor variabilis; I.a. = Ixodes affinis; I.s. = Ixodes scapularis; I.t. = Ixodes texanus N = number of host samples received.

Table 2-4. Prevalence of ixodid ticks collected from wildlife in different regions of Florida, 2000-2015. % of hosts infested by tick speciesb Region Na Amblyomma Amblyomma Dermacentor Ixodes Ixodes Ixodes americanum maculatum variabilis affinis scapularis texanus North 244 56.2a 8.6b 9.4a 3.7ax 22.5a 0.4a Central 385 37.7b 4.2b 3.9b 0.0bx 14.3b 0.0a South 47 0.0c 44.7a 14.9a 2.1ab 8.5ab 0.0a Combined 676 41.7x 8.6 6.7 1.5 16.9 0.2

No. ticksc 4,176 3,114 317 125 21 592 1 Hostd T,D,BB, D,C,BB, BB,C,P, D,P H,D,C,P R H,C,R,F H,F,P H,R,F BB,B,F,T aN = number of hosts sampled; 19 samples excluded because host location data not provided. bNumbers with the same column followed by the same letter are not significantly different (Bonferroni corrected P<0.017). cTotal number of ticks recovered from wildlife. dHosts within a column are arranged by relative occurrence. BB = American black bear, Ursus americanus; B = Lynx rufus; C = Canis latrans; D = white-tailed deer, Odocoileus virginianus; F = gray fox, Urocyon cinereoargenteus; H = feral swine, Sus scrofa; P = Florida panther, Puma concolor coryi; R = raccoon, Procyon lotor; T = wild turkey, Meleagris gallopavo

Figure 2-1. Collection kit distributed to collaborators for blood and tick samples from surveyed wildlife. Collection kit included a study information sheet, an 8-mL plastic snap-top collection vial for tick samples, two Nobuto filter strips for blood samples, a #5.5 coin envelope used as a data card, a small resealable plastic bag for containment of the samples, and a postage-paid return envelope. Photo courtesy of author.

Figure 2-2. Explanation of the study included in each collection kit.

Figure 2-3. Geographic distribution of tick samples collected from wildlife in Florida from 2000-2015. A) Lone star tick, Amblyomma americanum, B) Gulf coast tick, Amblyomma maculatum, C) American dog tick, Dermacentor variabilis, D) Ixodes affinis, E) Blacklegged tick, Ixodes scapularis, F) Raccoon tick, Ixodes texanus.

Figure 2-4. Geographic distribution of wildlife hosts sampled during a tick survey in Florida from 2000-2015. A) American black bear, Ursus americanus, B) Bobcat = Lynx rufus, C) Coyote = Canis latrans, D) Gray fox, Urocyon cinereoargenteus, E) Feral swine, Sus scrofa, F) Florida panther, Puma concolor coryi, G) Raccoon = Procyon lotor, H) Eastern and Osceola wild turkey, Meleagris gallopavo, I) White-tailed deer, Odocoileus virginianus.

12.0 300 Hosts with no ticks Hosts with ticks Amblyomma americanum 10.0 Amblyomma maculatum 250 Dermacentor variabilis Ixodes scapularis

8.0 200

6.0 150

4.0 100 No. wildlife of host sampled

2.0 50 No. of ticks recovered per wildlife host wildlife per recovered ticks of No.

0.0 0

Figure 2-5. Seasonal trend of the major species adult ticks infesting wildlife hosts in Florida, 2000-2015. The primary y- axis line data represent the number of ticks recovered from the wildlife hosts in a given month. The secondary y-axis column data represent the number of Florida wildlife hosts examined for ticks in a given month. All life stages of Amblyomma americanum data were recovered, while only adults of the other tick species were recovered.

CHAPTER 3 EHRLICHIAL AND RICKETTSIAL PATHOGENS ASSOCIATED WITH FLORIDA WILDLIFE

Introduction

Ehrlichiosis and spotted fever group (SFG) rickettsiosis are the two most important tick-transmitted diseases in the central and southeastern region of the United

States (Adams et al. 2015). From 2008-2012, infection rates of these diseases in the

United States have seen dramatic 4-fold and 7-fold increases, respectively (Drexler et al. 2016, Nichols Heitman et al. 2016). In Florida, the incidence of ehrlichiosis and rickettsiosis during the same time period was lower than many of the central and southeastern states (Drexler et al. 2016, Nichols Heitman et al. 2016), however, reported cases in Florida increased by 47% and 33%, respectively (FL DOH 2016). It is anticipated that the incidence rates of these diseases will continue to increase throughout the region (Stromdahl and Hickling 2012).

Human ehrlichioses in this region are caused by the obligate intracellular pathogens Ehrlichia chaffeensis and Ehrlichia ewingii (Anderson et al. 1991, Buller et al.

1999). A third potential pathogen, ‘Panola Mountain’ Ehrlichia (PME), has caused one human illness (Reeves et al. 2008). The tick-borne pathogens that cause human SFG rickettsioses in this region are believed to be Rickettsia rickettsii and Rickettsia parkeri

(Parola et al. 2013). It is believed that less pathogenic Rickettsiae, such as Rickettsia massiliae, Rickettsia montanensis, and Rickettsia amblyommii, may also be responsible for human infections (Dahlgren et al. 2016).

Several tick species have been associated with ehrlichiosis and rickettsiosis in this region. The predominant tick species and the most likely tick to bite humans is the lone star tick, Amblyomma americanum (L.) (Goddard and Varela-Stokes 2009,

Stromdahl and Hickling 2012). This tick is the principal vector of E. chaffeensis, E. ewingii, and PME, and has been associated with several rickettsial species including R. amblyommii (Mixson et al. 2006, Billeter et al. 2007), R. massiliae (Vitale et al. 2006,

Clay et al. 2008), R. parkeri (Goddard 2003, Cohen et al. 2009, Gaines et al. 2014), and

R. rickettsii (Berrada et al. 2011). The Gulf Coast tick, Amblyomma maculatum Koch, is

the primary vector for R. parkeri and is considered a vector of PME (Loftis et al. 2016).

The American dog tick, Dermacentor variabilis (Say), often was associated with SFG

rickettsioses in the United States due to the vector’s historical association with R.

rickettsii, the causative agent for Rocky Mountain spotted fever. However, more

contemporary surveys have reported that other rickettsial agents, such as R.

amblyommii, R. montanensis, R. rhipicephali are more commonly encountered in this

tick (Moncayo et al. 2010, Stromdahl et al. 2011, Parola et al. 2013). Ehrlichial DNA,

including E. chaffeensis and E. ewingii, have been detected in American dog ticks but

the importance of this tick as a vector of these pathogens is unknown (Steiert and Gilfoy

2002, Yabsley 2010). The blacklegged tick, Ixodes scapularis Say, has been associated

with several rickettsial species, mostly endosymbionts, however the pathogenic R.

parkeri was reported in blacklegged ticks recovered from black bears in Louisiana

(Leydet and Liang 2013, Nelder et al. 2016).

Ticks and their pathogens are maintained in nature by a wide variety of wildlife

that serve as reservoirs for the bacteria, as sources of blood for tick vectors, or as both

(Childs and Paddock 2003). The principal vertebrate reservoir for ehrlichial pathogens is

the white-tailed deer, Odocoileus virginianus (Zimmerman) (Paddock and Yabsley

2007). Vertebrate hosts for rickettsial bacteria are not well understood, but current

knowledge suggests that these pathogens are primarily maintained in nature by their tick vectors (Parola et al. 2013). However, some rickettsial bacterial require vertebrate hosts for amplification to guarantee their survival if the transovarial transmission rate in their tick host is low (Parola et al. 2013). In order to gain a better understanding of the reservoir complexes that maintain these pathogens in Florida, a survey was conducted to determine which ticks and mammalian and avian wildlife support ehrlichial and

rickettsial pathogens.

Materials and Methods

Sample Collection

Tick and blood samples were collected from 549 wildlife hosts from June 2012

through March 2016 (Table 3-1). All wildlife blood samples, except coyote, Canis latrans

Say, and most of the tick samples were collected through the collection kit (CK) program described in Chapter 2. The Florida Fish and Wildlife Conservation

Commission Lovett E. Williams Jr. Wildlife Research Laboratory (FWC) in Gainesville,

FL provided blood samples on Nobuto filter strips and ticks from all coyote, two black

bears, Ursus americanus, (Pallus), and two white-tailed deer. Tick samples from two white-tailed deer were collected by private citizens and provided directly to the laboratory. Upon receipt of the samples, ticks were identified using standard keys

(Clifford et al. 1961, Keirans and Litwak 1989, Keirans and Durden 2004) and stored at -

80°C, either dry or in 95% ethanol, until DNA extraction. Nobuto filter strips were stored in a sealed container with desiccants at 4°C until antibody elution and DNA extraction

(Curry et al. 2014). All wildlife sample collection was approved under University of

Florida Institutional Animal Care and Use Committee protocols #201308183 and

#201408189.

Sample Processing

Ticks samples were processed from 243 wildlife hosts, consisting of 11 black bear, 26 coyote, 47 feral swine, 15 white-tailed deer, and 144 wild turkeys. DNA was extracted using the Quick-gDNA™ MiniPrep kit (Zymo Research #D3025, Irvine, CA).

Individual adult ticks and pooled immature ticks (pool size: nnymphs ≤ 15; nlarvae ≤ 60)

were removed from -80ºC and transferred to 2.0 ml microcentrifuge tubes (Fisherbrand

#02-681-344, Pittsburgh, PA) containing three 2.0 mm zirconia beads (Biospec

#11079124zx, Bartlesville, OK). The microcentrifuge tubes, containing the ticks and the

beads, were flash frozen in liquid nitrogen for no longer than 5 min before running the

samples for 45 sec in a FastPrep® FP120 cell disrupter (Qbiogene, Inc., Carlsbad, CA)

at a speed of 5.5 m/sec. The tick homogenate was suspended in 500 µl of Zymo

Genomic Lysis Buffer with 0.5% (v/v) beta-mercaptoethanol added (GLB), vortexed, and incubated at room temperature for 5 min before following the remaining steps in the manufacturer’s solid tissue extraction protocol. DNA was eluted in 50 µl of elution buffer and held at -20°C until pathogen testing.

DNA was extracted from blood samples by cutting a 5-mm2 section of the blood-

infused Nobuto filter paper using a clean razor blade, halving it, and placing the two

pieces into 400 µl GLB. Samples were incubated overnight at room temp, then vortexed

before following the remaining steps in the manufacturer’s whole blood extraction

protocol. Blood DNA was eluted in 50 µl of elution buffer and held at -20°C until

pathogen testing.

To elute antibodies from the Nobuto filter strips, the manufacturer’s protocol was

modified. One 5-mm2 piece of Nobuto filter strip, containing 0.02 ml of dried whole

blood, was cut using a clean razor blade and halved, then placed in 175 µl of phosphate

buffered saline (PBS; pH: 7.4) and soaked for at least 3 hours at room temperature to yield an approximate 1:25 serum dilution. The eluted samples were stored at -20ºC until

IFA testing.

Serology

Serum samples were tested for antibodies reactive to Ehrlichia chaffeensis using an indirect immunofluorescence antibody (IFA) for coyote (N = 31), feral swine (N =

114), white-tailed deer (N = 35), and wild turkey (N = 211). Twelve-well, teflon-coated, glass slides were prepared as previously described (Dawson et al. 1994) with highly infected (>90%) canine histiolytic, DH82, cells (CRL-10389™, ATCC, Manassas, VA) that had been passaged 21 times or fewer. The Ehrlichia-infected cells were centrifuged at 1,000 x g for 10 min, supernatant removed, and the pellet resuspended in sterile PBS

(pH 7.4). Five microliters of this cell solution were loaded onto each well on the glass slides, air-dried for 30 min, acetone-fixed for 10 min and stored at -80°C until use.

The stored sample sera were brought to room temperature and diluted using 1% heat-inactivated fetal bovine serum in PBS (pH 7.4) to a final serum dilution of 1:64.

Fluorescein isothiocyanate (FITC)-labeled anti-dog, anti-swine, anti-turkey, or anti-deer

(#02-19-06, #02-14-06, #02-31-06, #02-26-06 Kirkegaard & Perry Laboratories, Inc.) immunoglobulin G (IgG) diluted in sterile PBS (pH 7.4) to a final dilution of 1:75 was used as the secondary antibody conjugate based on the sample source: coyote, feral swine, white-tailed deer, or wild turkey, respectively. Each 12-well slide had one positive and one negative control well to compare against non-specific sample fluorescence using the same dilution ratios using 1% heat-inactivated fetal bovine serum in PBS (pH

7.4) for the control sera and using PBS (pH 7.4) for the secondary antibodies. Ehrlichia chaffeensis-positive serum (#P-ECHG, Biocell Diagnostics) was used as the primary

antibody for the positive control well, and a universal negative control serum (#N-UNIV,

Biocell Diagnostics) was used in the negative control well. FITC-labeled anti-human IgG

(#02-10-06, Kirkegaard & Perry Laboratories, Inc.) was used as the secondary conjugate in both control wells. Individual wells were covered with 3µl of mounting medium (#71-00-16, Kirkegaard & Perry Laboratories, Inc.) or ProLong Diamond

Antifade Mountant w/ DAPI (4',6-diamidino-2-phenylindole) (#P3962, Life Technologies) was used to reduce the effects of fluorescence bleaching. A coverslip was placed over the wells and samples were through a 470/40 nm fluorescence filter using 40x magnification on an ultraviolet scope (Leica DMI4000B, Leica Microsystems, Wetzlar

Germany). Any sample sera with distinct fluorescent staining of the ehrlichial organisms were considered positive (Dawson et al. 1990, Mueller-Anneling et al. 2000).

Nine black bear serum samples were tested for Ehrlichia-reactive antibodies using the SNAP 4Dx Plus test (IDEXX Laboratories, Westbrook, ME) according to manufacturer instructions. Briefly, the 175µl of sample serum was mixed with four drops of the kit-provided conjugate and dispensed into the sample well of the test device. The device activator was pushed once the sample contents were observed in the activation circle of the device, and results were recorded after 8 min. The kit uses an internal positive control, and the company reports a 97% sensitivity and 95% specificity.

Pathogen Detection

Tick DNA extracts and blood DNA extracts were analyzed with a multiplex real- time polymerase chain reaction protocol that simultaneously detects the16s rRNA gene of E. chaffeensis and E. ewingii, and a conserved region of the 17-kD gene targeting

Spotted Fever Group Rickettsia spp. (Sayler et al. 2016). Using the same primer and probe concentrations as Killmaster et al. (2014), 20µl reactions were run on the ABI

7500 Fast Real-Time PCR system (Life Technologies, Grand Island, NY) with Brilliant III

Ultra-Fast QPCR Master Mix (Agilent Technologies, La Jolla, CA) for an initial denaturation at 95°C for 10 min, followed by 40 cycles of denaturation at 95°C for 15 sec, and annealing-extension at 57°C for 1 min. Ehrlichia- and Rickettsia-positive controls were from the same sources reported by Sayler et al. (2016) and distilled water was used as negative controls.

A subset of Rickettsia-positive ticks, by tick species and host, were randomly selected and sequenced to identify the rickettsial species. Original DNA extracts from the Rickettsia-positive samples were amplified using conventional PCR by targeting a

632bp fragment of the OmpA gene (Fournier et al. 1998). To confirm identity, amplicons were sequenced unidirectionally by the University of Florida Interdisciplinary Center for

Biotechnology Research (ICBR) using Sanger methods after being enzymatically purified. Sequences were edited using 4Peaks (Griekspoor et al. 2015), then examined using the National Center for Biotechnology Information (NCBI) Basic Local Alignment

Sequence Tool (BLAST) and the top result was recorded.

Statistical Analysis

A Fisher’s Exact test with the Bonferroni adjustment was used to make pairwise comparisons of the serology data between the five wildlife hosts tested. P-values were two-tailed and p < 0.05 was considered significant. A Microsoft Excel® add-on

(PooledInfRate, ver. 4.0, Centers for Disease Control and Prevention) was used to

calculate a maximum-likelihood estimation (MLE) with a 95% confidence interval (CI) to

approximate E. chaffeensis, E. ewingii, and Rickettsia spp. infection prevalence.

Results

Ehrlichia-reactive antibodies were detected in sera of all hosts examined, with positive samples ranging from 16.1-66.7% (Figure 3-1). Black bears had the highest percentage of samples with Ehrlichia-reactive antibodies, but fewer samples were screened compared to the number of samples tested by IFA. Thus, the only significant differences among host groups were between feral swine and coyotes (P = 0.0004), and between feral swine and wild turkeys (P < 0.0001).

Ehrlichial and rickettsial DNA were detected in few host animal blood samples.

One white-tailed deer blood sample was positive for E. chaffeensis and one wild turkey blood sample was positive for E. ewingii. Rickettsia amblyommii (100% identity to

GenBank Accession No. CP012420.1) was detected in one feral swine and one wild turkey blood sample. No black bear (9), coyote (31), or any of the remaining feral swine

(114), white-tailed deer (34), or wild turkey (321) blood samples were positive by qPCR.

A total of 1,771 ticks from four species were tested by qPCR. Ehrlichial DNA

(Table 3-2) was found only in lone star ticks, and E. chaffeensis (0.2%) and E. ewingii

(0.4%) infection rates were similar. Overall, E. ewingii was more prevalent as it was detected in ticks collected from black bear, coyote, and white-tailed deer compared to E. chaffeensis, which was only detected in ticks collected from wild turkey.

Rickettsial DNA (Table 3-2) was detected from every tick species tested, and associated with every wildlife host. The highest rickettsial infection rates were found in blacklegged ticks (68.5%), followed by lone star ticks (42.5%), Gulf Coast ticks (29.6%), and American dog ticks (20.6%). Rickettsial species’ identities are presented in Table 3-

3. Rickettsia amblyommii was the only species identified in lone star ticks, however one

Gulf coast tick collected from a feral swine and one blacklegged tick recovered from a

white-tailed deer also carried this parasite. Rickettsia parkeri was identified in every Gulf

Coast tick besides the aforementioned Gulf Coast tick infected with R. amblyommii. The

American dog tick rickettsial sequences were identified as R. rhipicephali. The

blacklegged ticks sequenced were associated primarily with rickettsial endosymbionts.

Discussion

The wildlife sampled in this survey are common in Florida and the role of these

animals as hosts of ixodid ticks has been documented (Chapter 2). The information

presented here increases our knowledge about these animals’ role in tick-borne disease

cycles in Florida. Each of the animals examined had some role in the maintenance of

these parasites.

To our knowledge this is the first Ehrlichiae seroprevalence survey of black bears

in the southern United States. Although our study was limited in sample size, it was

surprising that 67% of the 12 black bears were positive for Ehrlichia-reactive antibodies.

Seroprevalence studies in Maryland did not detect any E. canis-reactive antibodies in

63 black bears tested (Bronson et al. 2014), but a larger survey of 381 black bears in

Pennsylvania found 21% were exposed to granulocytic Ehrlichia (Schultz et al. 2002).

Pathogen studies of ticks associated with black bears have been conducted in Florida,

Georgia, and Louisiana (Yabsley et al. 2009, Leydet and Liang 2013). These studies

concluded that black bears may not be important hosts of ehrlichial pathogens because

only one of the 28 lone star ticks tested from the three states were positive for ehrlichial

pathogens. The E. chaffeensis-positive lone star tick was collected from a black bear in

Charlton County, Georgia (Yabsley et al. 2009). The E. ewingii-positive lone star tick in

our survey was collected from a black bear in Putnam County. The high

seroprevalence, lack of ehrlichial DNA evidence in the blood, and low association of

Ehrlichia-infected ticks continues to suggest that black bears in Florida may not be important hosts of these pathogens (Yabsley et al. 2009). However, black bears were host to multiple Gulf Coast ticks positive for R. parkeri and other tick species positive for

R. rhipicephali. The aforementioned surveys in the three southern states detected

multiple rickettsial species in the ticks collected from black bears (Yabsley et al. 2009,

Leydet and Liang 2013). The only recognized pathogenic rickettsial species detected in

these studies was R. parkeri, which was detected in 66% of the Gulf Coast ticks tested

in Louisiana and 17% of the Gulf Coast ticks tested in Georgia. Considering the small

sample size of black bears in our study, further investigation is warranted in Florida to

determine if black bears are important reservoirs of these bacterial agents.

Feral swine are present in every county in Florida with a statewide population

estimated to exceed 500,000 individuals (Giuliano 2010), yet little attention has been

directed toward what tick-borne pathogens are associated with these animals in the

state. The Ehrlichia seroprevalence in feral swine reported here (57.3%) is much higher

than that reported in Mississippi (32.8%) and Texas (13.2%) (Castellaw et al. 2011,

Sanders 2011). This may be due to sample bias because 73% of the samples that we

tested were submitted from two WMAs, Green Swamp West WMA and Tosohatchee

WMA, which had individual seroprevalence rates of 58% and 65%, respectively. One

study reported that ticks removed from feral swine had the highest infection prevalence

of E. chaffeensis and E. ewingii compared to ticks collected from a variety of other hosts

in Kentucky (Fritzen et al. 2011). We did not detect ehrlichial DNA in blood or from ticks

collected from feral swine, similar to Sanders (2011) and Castellaw (2011), but we did

detect R. amblyommii from one feral swine blood sample. Sanders (2011) and

Castellaw (2011) failed to amplify rickettsial DNA from their samples despite finding that

almost 30% of the feral swine that they tested contained Rickettsia-reactive antibodies.

Rickettsia amblyommii and R. rhipicephali were the only rickettsial agents detected in the tick samples collected from feral swine in our study. Taken together, the data

suggest that feral swine may not serve as important hosts of these zoonotic tick-borne pathogens.

The seroprevalence rate of white-tailed deer (34.3%) reported here is lower than the statewide rates (44.5%) reported by Sayler et al. (2016). Our sample size (35) was much smaller than the 393 samples tested in their study and had a more condensed

distribution. Interestingly, the combined seroprevalence rate from white-tailed deer

collected at Green Swamp West WMA and Tosohatchee WMA was 40%, representing

one-third of the white-tailed deer tested for Ehrlichia-reactive antibodies. One white-

tailed deer blood sample from a deer harvested in Upper Hillsborough WMA was

positive for E. chaffeensis and two other white-tailed deer, one harvested at Big Bend

WMA and the other at Camp Blanding WMA, hosted lone star ticks that were positive

for E. ewingii. This suggests that E. chaffeensis and E. ewingii are widespread

throughout this region in Florida, and combined with the feral swine results, the areas

around Green Swamp West WMA and Tosohatchee WMA may represent ‘hot spots’ for

ehrlichial pathogens.

This is the only study that has examined tick-borne pathogens associated with

wild turkeys in Florida. Wild turkey in Florida are heavily parasitized by lone star ticks

(Chapter 2), and it has been postulated that their range expansion and population

growth over the last century may have contributed to the increased incidence of lone

star tick-associated diseases (Childs and Paddock 2003). Indeed, in some areas it has been reported that wild turkey provide about twice as many blood meals to lone star

ticks as white-tailed deer (Harmon et al. 2015). Moreover, wild turkey have been

indirectly associated with ehrlichial pathogens through blood meal analysis (Harmon et

al. 2015). We report evidence that wild turkey may have a limited role in the

maintenance of ehrlichial pathogens in Florida. Over a quarter of the wild turkey blood

samples had Ehrlichia-reactive antibodies, including one sample from Caravelle Ranch

WMA that also tested positive for E. ewingii DNA. To our knowledge, this is the first

report of an ehrlichial agent detected from wild turkey blood. Despite finding an E.

ewingii-infected blood sample from a wild turkey, only one of the 1,432 lone star ticks

collected from wild turkey was found Ehrlichia-positive by qPCR. The infected lone star tick was collected as a blood-fed nymph and allowed to molt to an adult prior to DNA extraction and qPCR analysis. This does not implicate wild turkey as a reservoir for this pathogen because E. chaffeensis is transstadially maintained and this tick may have become infected from its larval blood meal, which may have not been a wild turkey

(Childs and Paddock 2003). Rickettsia amblyommii was detected in one wild turkey

blood sample and in each of the Rickettsia-positive lone star ticks sequenced from wild turkey. We believe this to be a novel detection of a rickettsial agent from wild turkey blood. It is unclear if this is a persistent or transient rickettsemia, and further studies should be undertaken to explore this observation further.

Coyotes have been reported in Florida since the 1960’s and are now present in all 67 counties (McCown and Scheick 2007). Seroprevalence and PCR data from south- central states suggest that coyotes are important reservoirs of Ehrlichia pathogens. For

example, greater than 60% of coyotes sampled in Oklahoma and Texas had Ehrlichia- reactive antibodies (Starkey et al. 2013), and a separate survey in Oklahoma reported that 71% of coyotes to be infected with E. chaffeensis, indicating a potential important reservoir for this pathogen (Kocan et al. 2000). The seroprevalence results (16%) reported here were much lower, and we were unable to detect ehrlichial DNA in the 41 coyote blood samples. However, one lone star tick collected from a coyote in Alachua

County was positive for E. ewingii. Ehrlichia ewingii was the most common Ehrlichia

species in coyotes from the Starkey et al. (2013) study, and is the most common

ehrlichial species reported from companion dogs in Florida (Beall et al. 2011).

Importantly, R. parkeri was detected in Gulf Coast ticks collected from three different

coyotes in this study. This may indicate an important relationship between the coyote

and pathogen, and should be studied further.

This study was the culmination of efforts by multiple volunteer collaborators, and

as such, sampling bias could not be avoided. The collected ticks do not comprise the

total tick population on each wildlife host in Florida, nor is it likely that all life stages of

each tick species infesting individual wildlife hosts were captured during tick sampling.

Additionally, ticks were received at different levels of engorgement ranging from flat,

(presumably detached and unfed) to fully engorged. Therefore, positive qPCR results

suggesting a tick is infected with an ehrlichial or rickettsial pathogen do not necessarily

indicate that a naïve tick acquired the pathogen from that infected host. It is as likely

that the ticks acquired ehrlichial and rickettsial infections from a previous blood meal,

through direct transmission by co-feeding infected ticks, or transovarial transmission

(Rickettsia only).

The wildlife surveyed in this study are of particular concern to public health officials because of the frequency these animals enter rural and suburban areas (Pfäffle et al. 2013). This direct interaction of these animals with the shared landscape potentially increases the risk of ehrlichial and rickettsial pathogen transmission to susceptible humans and domestic animals. Future studies should investigate the frequency that tick-borne pathogens are imported into suburban areas by transient rural, under-sampled wildlife.

Table 3-1. Collection period of blood and tick samples obtained from wildlife hosts during a tick-borne pathogen survey in Florida. Hosta N Collection Period Black bear 12 August 2013 - May 2015 Coyote 41 June 2012 - February 2015 Feral swine 117 October 2014 - November 2015 White-tailed deer 40 September 2013 - November 2015 Wild turkey 339 March 2014 - March 2016

Combined 549 June 2012 - March 2016 a Black bear = American black bear, Ursus americanus; Coyote = Canis latrans; Dog = Canis lupus familiaris; Feral swine = Sus scrofa; White-tailed deer = Odocoileus virginianus; Wild turkey = Eastern and Osceola wild turkey, Meleagris gallopavo.

Table 3-2. Percentage infection (95% CI) of ixodid ticks collected from wildlife hosts in Florida with Ehrlichia chaffeensis, Ehrlichia ewingii, and Rickettsia species. Speciesa Hostb Pools Ticks E. chaffeensis E. ewingii Rickettsia spp. Lone star tickc Black bear 28 46 0.0 (0.0-6.9) 2.3 (0.1-11.0) 45.0 (27.6-64.1) Coyote 12 12 0.0 (0.0-24.3) 8.3 (0.5-33.8) 50.0 (23.8-76.2) Feral swine 78 101 0.0 (0.0-3.5) 0.0 (0.0-3.5) 56.2 (45.2-66.7) White-tailed deer 34 54 0.0 (0.0-6.0) 5.4 (1.5-13.3) 60.6 (43.7-75.7) Wild turkey 260 1432 0.3 (0.1-0.7) 0.0 (0.0-0.3) 36.9 (32.4-42.0) All hosts 422 1655 0.2 (0.1-0.6) 0.3 (0.1-0.7) 42.5 (38.4-47.0) Gulf Coast tick Black bear 14 14 0.0 (0.0-21.5) 0.0 (0.0-21.5) 28.6 (10.1-55.0) Coyote 20 20 0.0 (0.0-16.1) 0.0 (0.0-16.1) 25.0 (10.0-46.7) Feral swine 11 11 0.0 (0.0-25.9) 0.0 (0.0-25.9) 27.3 (7.8-57.1) White-tailed deer 9 9 0.0 (0.0-29.9) 0.0 (0.0-29.9) 44.4 (16.6-75.3) All hosts 58 58 0.0 (0.0-6.6) 0.0 (0.0-6.6) 29.6 (18.7-42.7) American dog tick Black bear 19 19 0.0 (0.0-16.8) 0.0 (0.0-16.8) 10.5 (1.9-30.2) Coyote 10 10 0.0 (0.0-27.8) 0.0 (0.0-27.8) 30.0 (8.7-61.3) Feral swine 5 5 0.0 (0.0-43.5) 0.0 (0.0-43.5) 40.0 (8.1-80.5) All hosts 46 46 0.0 (0.0-10.2) 0.0 (0.0-10.2) 20.6 (9.6-36.4) Blacklegged tick Black bear 1 1 0.0 (0.0-79.4) 0.0 (0.0-79.4) 100.0 (NC) Coyote 10 10 0.0 (0.0-27.8) 0.0 (0.0-27.8) 60.0 (29.8-85.3) Feral swine 4 4 0.0 (0.0-49.0) 0.0 (0.0-49.0) 100.0 (NC) White-tailed deer 22 22 0.0 (0.0-8.8) 0.0 (0.0-8.8) 63.6 (42.7-81.3) Wild turkey 1 1 0.0 (NC) 0.0 (NC) 100.0 (NC) All hosts 40 40 0.0 (0.0-9.2) 0.0 (0.0-9.2) 68.4 (52.6-81.5) Infection was determined by qPCR using genus-specific16S rRNA primers with species-specific dual-labeled hydrolysis probes for Ehrlichia chaffeensis and E. ewingii and genus-specific primers and probe that target the 17-kDa antigen gene for Rickettsia spp (Killmaster et al. 2014, Sayler et al. 2016). a Lone star tick = Amblyomma americanum; Gulf Coast tick = A. maculatum; American dog tick = Dermacentor variabilis; Blacklegged tick = Ixodes scapularis. b Black bear = American black bear, Ursus americanus; Coyote = Canis latrans; Feral swine = Sus scrofa; White-tailed deer = Odocoileus virginianus; Wild turkey = Eastern and Osceola wild turkey, Meleagris gallopavo. c Includes all life stages; lone star tick larvae or nymphs were collected from black bear, coyote, feral swine, wild turkey, and white-tailed deer. Adult ticks were tested individually and immature ticks were in pools ≤ 15 for nymphs and ≤ 60 for larvae.

Table 3-3. Identity of rickettsial species detected in ticks collected from Florida wildlife. Tick Speciesa Hostb Nc % Identity GenBank Accession Lone star tick Feral swine 9 99-100 Rickettsia amblyommii strain Ac37 (CP012420.1) Wild turkey 19 White-tailed deer 1 100 Rickettsia amblyommii strain Ac37 (CP012420.1)

Gulf Coast tick Black bear 3d 100 Rickettsia parkeri clone S2AM3 (KC003476.1) Coyote 2e 100 Rickettsia parkeri str. Portsmouth (CP003341.1) 1 100 Rickettsia parkeri clone S2AM3 (KC003476.1) 1 100 Rickettsia parkeri clone S2AM3 (KC003476.1) Feral swine 1 100 Rickettsia amblyommii strain Ac37 (CP012420.1) White-tailed deer 1 100 Rickettsia parkeri clone S2AM3 (KC003476.1)

American dog tick Black bear 1 100 Rickettsia rhipicephali str. 3-7-female6-CWPP (CP003342.1) Coyote 1 100 Rickettsia rhipicephali str. 3-7-female6-CWPP (CP003342.1) Feral swine 1 99 Rickettsia rhipicephali str. 3-7-female6-CWPP (CP003342.1)

Black-legged tick Black bear 1 99 Rickettsia rhipicephali str. 3-7-female6-CWPP (CP003342.1) Coyote 2 99-100 Ixodes scapularis endosymbiont clone FLAC3 (KX001997.1) 1 99 Ixodes scapularis endosymbiont isolate TX136 (EF689737.1) White-tailed deer 2 99 Ixodes scapularis endosymbiont clone FLAC3 (KX001997.1) 1 100 Ixodes scapularis endosymbiont isolate TX136 (EF689737.1) 3f 99 Ixodes scapularis endosymbiont clone FLAC3 (KX001997.1) 1f 99 Rickettsia amblyommii strain Ac37 (CP012420.1) Rickettsial infection was determined initially by qPCR using genus-specific primers and probe that target the 17-kDa antigen gene for Rickettsia spp. (Killmaster et al. 2014, Sayler et al. 2016). Then, original DNA extracts from the Rickettsia-positive samples were amplified using conventional PCR by targeting a 632bp fragment of the OmpA gene (Fournier et al. 1998). Unidirectional sequencing was performed by the University of Florida Interdisciplinary Center for Biotechnology Research (ICBR) using Sanger methods after being enzymatically purified. Sequences were edited using 4Peaks (Griekspoor et al. 2015), then examined using the National Center for Biotechnology Information (NCBI) Basic Local Alignment Sequence Tool (BLAST). a Lone star tick = Amblyomma americanum; Gulf Coast tick = Amblyomma maculatum; American dog tick = Dermacentor variabilis; Blacklegged tick = Ixodes scapularis b Black bear = American black bear, Ursus americanus; Coyote = Canis latrans; Feral swine = Sus scrofa; White-tailed deer = Odocoileus virginianus; Wild turkey = Eastern and Osceola wild turkey, Meleagris gallopavo. c Number of individual ticks sequenced. d Two ticks collected from same black bear. e Collected from same coyote. f Collected from same white-tailed deer.

AB B

Figure 3-1. Percentage of wildlife sampled with Ehrlichia-reactive antibodies. Antibodies for coyote, Canis latrans, feral swine, Sus scrofa, white-tailed deer, Odocoileus virginianus, and wild turkey, Meleagris gallopavo, were detected by indirect immunofluorescence assay. Antibodies for black bear, Ursus americanus, were detected using the SNAP 4Dx Plus test according to manufacturer instructions. Feral swine had significantly more Ehrlichia-reactive antibodies than coyotes (P = 0.0004) and wild turkeys (P < 0.0001).

CHAPTER 4 PREVALENCE OF EHRLICHIAL AND RICKETTSIAL PATHOGENS IN HOST- SEEKING LONE STAR TICKS AT FLORIDA STATE PARKS AND WILDLIFE MANAGEMENT AREAS.

Introduction

The lone star tick, Amblyomma americanum (L.), is the most common tick species encountered in Florida, particularly in the central and northern regions. They are extremely pestiferous due to their high population densities and aggressive biting behavior. Moreover, they are an important vector in the southeastern and south-central

United States because of their competency to transmit multiple human pathogens

(Goddard and Varela-Stokes 2009). Of particular concern, is the ability of lone star ticks to potentially transmit the pathogens causing human ehrlichiosis and spotted fever rickettsiosis (Apperson et al. 2008, Goddard and Varela-Stokes 2009, Breitschwerdt et al. 2011).

Reported ehrlichiosis cases have increased 4-fold from 2000-2012 in the United

States (Nichols Heitman et al. 2016). Ehrlichia chaffeensis is the most important ehrlichial pathogen that has been associated with lone star tick transmission. Infection by E. chaffeensis causes a moderate to severe illness that can be fatal if not treated

and is responsible for the majority of cases of ehrlichiosis (Dahlgren et al. 2011). The

two other ehrlichial pathogens, Ehrlichia ewingii and ‘Panola Mountain’ Ehrlichia,

transmitted by lone star ticks are reported less frequently and cause a similar but

relatively mild illness (Reeves et al. 2008, Nichols Heitman et al. 2016). A recent study

suggested that E. ewingii may be responsible for more cases of ehrlichiosis than the 2%

currently attributed this pathogen nationally (Harris et al. 2016). The Harris et al. (2016) study reexamined 4,177 Ehrlichia- and Anaplasma-positive samples with species-

specific qPCR primers and found E. ewingii was the causative agent in 10% of the reported ehrlichiosis cases. The nine Ehrlichia-positive Florida samples reexamined from this study did not demonstrate any ehrlichial agents by qPCR, but this could be a result of specimen collection timing and limited sensitivity of the assay (Harris et al.

2016). Panola Mountain Ehrlichia has been implicated in only one human illness

(Reeves et al. 2008). Each of these ehrlichial pathogens have been detected in host-

seeking ticks in Florida (Childs and Paddock 2003, Mixson et al. 2004, Loftis et al.

2008), but only E. chaffeensis reportedly has caused illness in the state (FL DOH 2016).

Reported cases of spotted fever rickettsiosis in the United States have increased

7-fold from 2000-2012 (Drexler et al. 2016). Spotted fever rickettsioses are caused by

multiple species of Rickettsia. The association between lone star ticks and the most

virulent rickettsial pathogen, Rickettsia rickettsii, has been known since 1920 but the

importance of lone star ticks in this pathogens transmission cycle has been debated

(Goddard and Varela-Stokes 2009, Berrada et al. 2011, Breitschwerdt et al. 2011).

Rickettsia parkeri (Goddard 2003, Cohen et al. 2009) and Rickettsia massiliae (Vitale et

al. 2006, Heise et al. 2010) are pathogenic species that have been detected in lone star

ticks but it is unknown if lone star ticks are capable of human transmission. The most

common rickettsial agent associated with lone star ticks is Rickettsia amblyommii, a

bacterium considered mildly or non-pathogenic to humans (Billeter et al. 2007,

Apperson et al. 2008, Ponnusamy et al. 2014, Dahlgren et al. 2016). To our knowledge,

R. amblyommii has been the only species of Rickettsia detected in lone star ticks

collected in Florida (Mixson et al. 2006, Sayler et al. 2014).

Compared to other southeastern and south-central states, Florida has relatively few reported cases of ehrlichiosis and rickettsiosis. In 2013, Florida represented only

1.6% and 0.8% of the total ehrlichiosis and spotted fever rickettsiosis cases reported from those regions, respectively (Adams et al. 2015). Nevertheless, there is a discernable area in the north-central and northwestern regions of Florida where these diseases are reported most frequently in the state (FL DOH 2013). Two of the groups at greatest risk for acquiring a tick-borne illness are outdoor recreationalists and natural resource workers, e.g. forestry and game management personnel, who frequent tick- infested habitats (Chapman et al. 2006, IOM 2011).

Florida has one of the United States’ largest state park (SP) and wildlife management area (WMA) systems available to the public. These lands are managed under different philosophies, such as habitat management including fire suppression, wildlife management, including hunting access, and development for public access and use (FL DEP 2014, FL FWC 2014). Habitat management practices such as fire

suppression (Gleim et al. 2014), vegetation reduction (Bloemer et al. 1990), and wildlife

management, specifically deer reduction/exclusion (Bloemer et al. 1986), have been

shown to reduce lone star tick populations and may affect lone star tick-associated

pathogen prevalence. Taken together, such publicly available land provides ample,

yearlong opportunities for the aforementioned activities in potentially high-risk tick

areas. The goals of this study were to compare select Florida SPs and WMAs in terms

of lone star tick density, tick infection by E. chaffeensis, E. ewingii, and potential

Rickettsia spp. pathogens, and the exposure risk infected ticks pose on workers and

recreationalists in this area.

Materials and Methods

Tick Sampling

Eight paired sites (Figure 4-1), each consisting of a SP and a WMA, were

sampled for host-seeking ticks from May 18-27, 2015 between the hours of 0700-1500.

These sites were chosen based on habitat descriptions, geographic proximity to one

another, and their inclusion within an area of increased ehrlichiosis and rickettsiosis

transmission (Figure 4-2) (FL DOH 2016). One paired site (SP and WMA) was sampled on each day starting with Lochloosa WMA followed by sampling at Marjorie Kinnan

Rawlings SP. The order in which the two location types at each site were sampled

alternated daily to reduce temporal sampling variability between SPs and WMAs. No

tick sampling was performed on May 22, then daily sampling resumed on May 23.

Paired site #1 (Figure 4-1) was sampled twice, once on May 18 and again on May 27, to

provide a measure of sampling conditions across the sampling period.

Ticks were sampled by slowly dragging a 1-m2 white polyester cloth (Anti-pill fleece, #060311140, Jo-Anne Stores LLC, Hudson, OH) weighted on the distal end with an aluminum flat bar (1/16” x 3/4", The Hillman Group, Cincinnati, OH). The cloth was drug over leaf litter and low vegetation (< 1 m high) in similar habitat at each SP and

WMA for a total of 400 m of continuous terrain (Table B-2). Ticks were removed from the cloth every 10 m using a lint roller (Scotch Brite™, 3M, St. Paul, MN). Lint roller sheets with adhered ticks were removed, covered by a Kimwipe™ (Kimtech Science ™

#34120, Kimberly-Clark Professional, Roswell, GA), and stored in zippered plastic bags in a cooler with ice packs until species identification was made. At the conclusion of the collection session at each SP and WMA, ticks found on the back of the fleece cloth

were kept as extra specimens and used in pathogen analysis. Clean cloths were used at each SP and WMA.

Ticks were identified to species and individually counted at the end of each day

by examining the lint roller sheet using a dissecting microscope and standard keys

(Clifford et al. 1961, Keirans and Litwak 1989, Keirans and Durden 2004). High-density

areas on the lint roller sheet (e.g. larval tick masses) were carefully subdivided into

smaller areas using an ultra-fine tip permanent marker to improve accuracy (Figure 4-

3). Ixodes spp. immatures were reexamined at the veterinary entomology laboratory

using Durden and Keirans (1996) and submitted to Dr. Rich Robbins of the Armed

Forces Pest Management Board for species confirmation. Only lone star tick nymphs

and adults were analyzed for infection with ehrlichial and rickettsial agents and

subsequent statistical analysis. Pools (n ≤ 5) of nymphs or individual adults were placed

in 2.0 ml microcentrifuge tubes (Fisherbrand™ #02-681-344, Pittsburgh, PA) containing

three 2.0 mm zirconia beads (Biospec #11079124zx, Bartlesville, OK) and stored on ice

until return to the veterinary entomology laboratory, then were stored at -80°C until DNA

extraction.

DNA Extraction and Pathogen Detection

DNA was extracted using the Quick-gDNA™ MiniPrep kit (Zymo Research

#D3025, Irvine, CA). Ticks were mechanically homogenized by flash freezing the 2.0 ml

microcentrifuge tubes in liquid nitrogen for no longer than 5 min prior to running the

samples for 45 sec in a FastPrep® FP120 cell disrupter (Qbiogene, Inc., Carlsbad, CA)

at a speed of 5.5 m/sec. The homogenate was suspended in 500 µl of Zymo Genomic

Lysis Buffer with 0.5% (v/v) beta-mercaptoethanol added, vortexed, and incubated at

room temperature for 5 min before following the manufacturer solid tissue sample

protocol. DNA was eluted in 50 µl of elution buffer and held at -20°C until pathogen testing.

DNA extracts were subjected to a multiplex real-time polymerase chain reaction protocol that simultaneously detects Ehrlichia chaffeensis, E. ewingii, and Rickettsia spp. The assay was optimized with the Brilliant III Ultra-Fast QPCR Master Mix (Agilent

Technologies, La Jolla, CA) using the same primer and probe concentrations listed in

Table 1 of Killmaster et al. (2014) to a final reaction volume of 20 µl (Sayler et al. 2016).

Ehrlichia chaffeensis and E. ewingii primers detect a genus-specific region of the ehrlichial 16S rRNA while the dual-labeled hydrolysis probes identify the species.

Rickettsia spp. primers and probe detect a conserved region of the 17-kDa outer membrane antigen gene, which allows for detection of all spotted fever group

Rickettsiae. Samples were analyzed on the ABI 7500 Fast Real-Time PCR system (Life

Technologies, Grand Island, NY) using the following program: initial denaturation at

95°C for 10 min, followed by 40 cycles of denaturation at 95°C for 15 sec, and annealing-extension at 57°C for 1 min. DNA for the Ehrlichia positive controls were generated from E. chaffeensis (Arkansas str.) cultured in DH82 canine histiocytic cells and from E. ewingii extracted from a naturally-infected dog whole blood sample (Sayler et al. 2016). Rickettsia conorii DNA was used as the Rickettsia spp. positive control and distilled water was used as negative controls (Sayler et al. 2016).

A subsample (n = 45) of the qPCR Rickettsia-positive samples per location were

randomly selected and analyzed using conventional PCR by targeting a 631 bp

fragment of the rompA gene to identify the rickettsial species (Fournier et al. 1998).

Bands were visualized on a 2% agarose gel with ethidium bromide. Amplicons were

enzymatically cleaned and sequenced at the University of Florida Interdisciplinary

Center for Biotechnology Research (ICBR) core laboratory. Nucleotide comparisons were made using the National Center for Biotechnology Information (NCBI) Basic Local

Alignment Sequence Tool (BLAST), and the top result was used.

Statistical Analysis

Density was defined as the number of ticks per 10 m2. A Fisher’s Exact test was

used to compare May 18 and 28 density data at site 1, Marjorie Kinnan Rawlings SP

and Lochloosa WMA, by life stage. A factorial analysis of variance model that included

the treatment effects of collection site (1-8) and paired location types (SP and WMA), as

well as the interaction of the two effects was applied separately to the adult and

nymphal tick density data to determine if life stage densities differed significantly

between the geographic location of the collection sites or between the paired SP and

WMA within a collection site (JMP®, Version 12.0.1, SAS Institute Inc., Cary, NC, 1989-

2015). Differences in main effects were further analyzed using Tukey’s HSD and the

interaction effect was analyzed using JMP® ‘Test Slices’ function. This ‘Test Slices’

function jointly tests all pairwise comparisons involving each treatment effect using an

F-ratio (SAS Institute Inc. 2015). Minimum infection rates (MIR), for individual adults and pooled nymphs, and maximum-likelihood estimation (MLE), for pooled nymphs, were calculated as a percentage (PooledInfRate, ver. 4.0, Microsoft Excel® add-on, Centers

for Disease Control and Prevention). The MIR assumes that each positive pool of

nymphs contains only one infected tick, therefore underestimating the nymphal infection

rate (Biggerstaff 2014). The MLE values calculated by the software does not require this

assumption, and infection rates and 95% confidence interval (CI) are estimated by

taking in consideration the number of pools, the number of ticks per pool, and the

number of positive pools (Biggerstaff 2014). Adult infection rates by paired site and location type were compared using the Fisher’s Exact test for ehrlichial infections due to the low number of positive results and Pearson’s Chi-square test for rickettsial infections. All p-values were two-tailed, and p < 0.05 was considered significant. Post- hoc pairwise comparisons were corrected using the Bonferroni adjustment. An entomological risk index (ERI) was used to compare relative risk between sites and location type. The ERI represents the number of infected ticks per 10 m2. The ERI was

calculated as the product of the combined adult and nymphal density and the

site/location-specific MLE infection rate (Mather 1993).

Results

Five ixodid tick species consisting of 8,590 individuals were collected at Florida

SPs and WMAs in a total area of over a 9 collection-days in May 2015 (Table 4-1). Lone

star ticks made up the vast majority (99.9%) of the collected ticks. Adult and immature

stages of the American dog tick, Dermacentor variabilis (Say), the rabbit tick,

Haemaphysalis leporispalustris (Packard), the blacklegged tick, Ixodes scapularis Say,

and Ixodes minor Neumann, accounted for the remaining ticks collected. There were no

significant differences in lone star tick adult and nymphal densities between May 18 and

May 27 at Marjorie Kinnan Rawlings State Park (Adults: p = 1.00; Nymphs: p = 0.06)

and Lochloosa WMA (Adults: p = 0.86; Nymphs: p = 0.84) (Figure 4-4). The larger

change in nymphal density, although not significant (P = 0.06), at Marjorie Kinnan

Rawlings State Park between the two dates can be attributed to encountering more ‘hot

spots’ as indicated by the larger SEM. Ticks are recognized as being heterogeneously

displaced in the environment due to host movement and behavior, which can vary by

life stage (Van Buskirk and Ostfeld 1998). Considering that tick densities were

decreasing at sites collected after May 21 (Figure 4-5), we concluded that there was no evidence of large changes in tick abundance over the sampling period. Therefore, data

from May 27 was excluded from the remaining analyses to facilitate a balanced design.

Densities ranged from 0.05-0.73 adults (mean = 0.27) and 0.35-3.05 nymphs

(mean = 1.42) per 10 m2 from the SPs and WMAs (Figure 4-5). On average, nymphs

outnumbered adults at each location 7:1 (range 2-20 nymphs per adult). Significant

differences were observed between the eight collection sites for adult lone star tick

density (Figure 4-6) and nymphal density (Figure 4-7), but not observed within life stage

density comparisons between the paired SPs and WMAs (Table 4-2). There was no

interaction effect for the adult density, however nymphal tick densities differed

significantly between the paired SPs and WMAs depending on the collection site (Table

4-2). Further examination of this interaction effect revealed that nymphal densities

varied significantly between the paired SPs and WMAs at site 4 (F1,624 = 4.4324, P =

0.0357), Fort Cooper SP (mean: 3.1 ± 0.75/10m2) and Flying Eagle WMA (mean: 2.0 ±

2 0.29/10m ), and site 6 (F1,624 = 5.58, P = 0.0185), De Leon Springs SP (mean: 0.65 ±

0.13/10m2) and Dexter/Mary Farms WMA (mean: 1.8 ± 0.41/10m2). It is likely that this

variability is also due to the heterogenetic dispersal of ticks in the environment as

previously discussed.

Ehrlichial DNA was detected in adult lone star ticks at four of the eight collection

sites and four of the sixteen locations surveyed and detected in nymphal lone star ticks

at six of the eight collection sites and eight of the sixteen locations surveyed (Table 4-3).

Site 3 was the only site where we did not detect ehrlichial DNA in lone star ticks. The E.

chaffeensis MIR ranged from 0-5% (mean = 0.9%) in adults and 0-4% (mean = 0.8%) in

nymphs at all locations surveyed. The E. ewingii MIR was lower, ranging from 0-25%

(mean = 0.9%) in adults and 0-1.2% (mean = 0.2%) in nymphs at all locations. Ehrlichial

MIRs were not statistically different in adult lone star ticks between the eight collection

sites or between SPs and WMAs.

All collection sites and locations had Rickettsia-infected adult and nymphal lone star ticks, with variable prevalence (Table 4-4). All of the 45 Rickettsia-positive lone star ticks sequenced were 99-100% identical to Rickettsia amblyommii (GenBank Accession

No. CP012420.1). The adult tick Rickettsia spp. MIR ranged from 30-100% (mean =

62.8%) and differed significantly among the eight collection sites (χ2 = 58.37, P = <

0.0001), but not between the paired SP or WMA (χ2 = 1.470, P = 0.2254). Post-hoc

pairwise analysis found significantly lower rickettsial infection rates in adult lone star

ticks collected from site 1 compared to site 2 (P = 0.0220), site 5 (P = 0.0006), and site

6 (P = 0.0242), and site 8 compared to site 5 (P = 0.0022). The nymphal Rickettsia spp.

MIR ranged from 17.6-20.0% (19.5%) and the MLE ranged from 18.5-32.5% (49.2%)

from all locations. Unlike the nymphal MIRs, nymphal MLEs at most locations could not

be calculated because all pools tested positive.

The ERI for lone star ticks infected with E. chaffeensis, E. ewingii, and Rickettsia

spp. at Florida SPs and WMAs are listed in Table 4-5. The risk of encountering E.

chaffeensis-infected ticks (ERI: 0.0014/10 m2) was 2.8x greater than the risk posed by

E. ewingii-infected ticks (ERI: 0.005/10 m2) across all sites. Ehrlichia chaffeensis ERI

ranged from 0.000-0.045, with the highest risk being recorded at Flying Eagle WMA.

Fort Cooper SP and Seminole Forest WMA had the highest E. ewingii ERIs, which

ranged from 0.000-0.023. The ERI for Rickettsia spp. was 0.978 infected ticks/10 m2,

with the lowest risk (0.342) recorded at Lochloosa WMA and the highest risk (2.314) at

Andrews WMA.

Discussion

This survey documented the ixodid tick diversity and the relative exposure risk to ehrlichial and rickettsial pathogens in host-seeking lone star ticks at eight distinct geographic sites across Florida. All five tick species collected in this study have been reported in Florida, and the relative abundance of lone star ticks compared to the other species collected is consistent with previous reports (Stromdahl and Hickling 2012).

American dog ticks and blacklegged ticks are well known vectors of multiple pathogens and frequently bite humans (Estrada-Peña and Jongejan 1999), while the rabbit tick and

I. minor rarely bite humans but are believed to be important in enzootic disease cycles

(Oliver et al. 2003, Freitas et al. 2009). The role of these species in tick-borne disease transmission cycles in Florida is unknown and should be further investigated.

Identification of the lone I. minor specimen collected from Rainbow Springs SP, in

Marion county, was confirmed by Dr. Rich Robbins of the Armed Forces Pest

Management Board and appears to be a new county record (Durden et al. 2000). This species is believed to be present statewide, but collections are rare (Rogers 1953).

Lone star tick adult activity peaks in March and bimodal nymphal activity peaks occur in April and August in North-central Florida (Rogers 1953), so it was not surprising to find lone star ticks in abundance during the time of our study. Despite there being no differences in adult and nymphal lone star tick density between the WMAs and SPs, differences were apparent between collection sites indicating that abiotic and biotic factors influence lone star tick phenology and abundance across this geographic area.

Previous studies have reported that host densities (Bloemer et al. 1990), habitat type

(Semtner and Hair 1973), environmental conditions (Semtner et al. 1973), and anthropogenic habitat alteration (Allan 2009) influence lone star tick reproduction and development.

The prevalence of ehrlichial pathogens in host-seeking lone star ticks varied throughout our study region. The overall adult lone star tick infection rates by E. chaffeensis (0.9%) and E. ewingii (0.9%) in our study were lower, but comparable to, what has been reported recently in Georgia (Killmaster et al. 2014), Mississippi

(Castellaw et al. 2010), Tennessee (Cohen et al. 2010), and Virginia (Gaines et al.

2014, Wright et al. 2014). Infection rates (MIR and/or MLE) in those studies ranged between 1.4-7.3% for E. chaffeensis and 0.8-7.8% for E. ewingii. Similarly, of the nymphs tested in many of those studies, infection rates ranged from 0.7-3.4% for E. chaffeensis and 0.8-1.9% for E. ewingii compared to the overall nymphal infection rates of 0.8% for E. chaffeensis and 0.2% for E. ewingii detected in our study. Mixson et al.

(2006) tested adult lone star ticks from three North-central Florida locations and found

2.1% (2 of 94 tested positive; listed incorrectly as 3.0%) were infected with E. ewingii, but none of the 151 ticks tested were found infected with E. chaffeensis. In the Mixson et al. (2006) study, 4.8% of the adult ticks tested from Manatee Springs SP were infected with E. ewingii. We had no E. ewingii detections at Manatee Springs SP, although we did identify one adult lone star tick infected with E. chaffeensis from that location.

Rickettsial infections were detected in host-seeking lone star ticks at every site and prevalence varied greatly across the region. The only rickettsial species that we detected was R. amblyommii, which is the most prevalent rickettsial species in lone star

ticks collected in Florida (Sayler et al. 2014). Previous reports of rickettsial infections in host-seeking adult lone star ticks in North-central Florida averaged 37.1-57.1% (Mixson et al. 2006, Sayler et al. 2014), which is comparable to the 62.8% detected in the adult ticks we evaluated. There are no published comparable studies in North-central Florida

that examined nymphal infection rates, but as expected, our estimates (MIR = 19.5%)

were lower than what was detected in adults. Given the limitations of the MIR

calculation procedure using pooled samples, 19.5% is likely an underestimate of the

true nymphal population infection rate and the MLE (49.2%) is probably a closer

approximation. Future studies would benefit from smaller pools or individual testing of

nymphs in studies evaluating highly prevalent bacteria, such as Rickettsia spp. in lone

star ticks, would allow for better estimates of the true tick infection rate.

Despite the relatively low infection rates of ehrlichial pathogens across the region, there remains a considerable risk of being exposed to these pathogens. On average, one in every 100 lone star ticks encountered in a 10 m2 area throughout North- central Florida was infected with ehrlichial pathogens. Lone star ticks are heterogeneously dispersed in the environment, with numerous lone star ticks being found in a relatively small area. For example, 4,086 adult lone star ticks were collected beneath a small juniper tree during the Bullis Fever epidemic at a Texas military training facility in the 1940s (Goddard 1989). Fortunately, lone star tick populations have never been reported this high in Florida. In our survey, 11% of the lone star ticks collected were in groups of five or more, with the most collected being 25 per 10 m2.

Undoubtedly, there were more ticks within the areas surveyed than what were

recovered.

A person is 51 times more likely to encounter a Rickettsia-infected lone star tick than one infected with ehrlichial pathogens. Fortunately, R. amblyommii accounts for

the vast majority of Rickettsia bacteria found in lone star ticks in this region (Sayler et al.

2014), and was the only species detected in our study. This rickettsial species is mildly

or non-pathogenic (Billeter et al. 2007, Apperson et al. 2008), and may confer immunity

against more pathogenic rickettsial species like R. rickettsii (Blanton et al. 2014,

Dahlgren et al. 2016). Nonetheless lone star ticks are potential vectors of pathogenic

Rickettsia species, including R. rickettsii (Breitschwerdt et al. 2011) and R. parkeri

(Cohen et al. 2009). Field studies have shown that these pathogenic agents are difficult

to detect because their presence can be masked in current diagnostic tests by more

abundant R. amblyommii found in lone star ticks. Of the 870 ticks tested by Berrada et

al. (2009), 90% percent of the pools contained R. amblyommii compared to only 0.46%

containing R. rickettsii. Thus, the failure to detect a pathogenic rickettsial agent in lone

star ticks does not infer that a pathogenic Rickettsia is not present and caution should

be used when communicating risk.

In conclusion, there were no differences in risk of exposure to Ehrlichia- and

Rickettsia-infected lone star ticks between SPs and WMAs, however bacterial groups

were present and varied spatially throughout North-central Florida. Workers and

recreationalists throughout this region should be educated on the risks ticks pose to

their health and be informed on how they can reduce their exposure to ticks and their

pathogens. This includes avoiding areas of known high tick densities, wearing skin and

clothing-based repellents, and conducting thorough body checks daily when transiting

through potential tick habitat.

Table 4-1. Ixodid ticks collected at Florida state parks (SP) and wildlife management areas (WMA) during May 2015. Date Location American Rabbit Ixodes Blacklegged All Lone star tick dog tick tick minor tick Ticks A N L T May 18 Lochloosa WMA 12 31 193 236 0 0 0 0 236 Marjorie Kinnan Rawlings SP 13 40 0 53 0 2N 0 0 55 May 19 Manatee Springs SP 20 87 2 109 0 0 0 0 109 Andrews WMA 29 71 0 100 0 0 0 0 100 May 20 Goethe WMA 2 40 0 42 0 0 0 0 42 Rainbow Springs SP 10 49 323 382 0 0 1N 0 383 May 21 Fort Cooper SP 7 122 0 129 1A 0 0 0 130 Flying Eagle WMA 9 81 3,797 3,887 0 0 0 1A 3,888 May 23 Wekiwa Springs SP 15 101 660 776 0 0 0 0 776 Seminole Forest WMA 22 64 461 547 1N 0 0 1L 549 May 24 Dexter/Mary Farms WMA 8 26 0 34 0 0 0 0 34 De Leon Spring State Park 9 72 0 81 0 0 0 0 81 May 25 Dunns Creek SP 5 55 0 60 0 0 0 0 60 Dunns Creek WMA 3 19 0 22 0 0 0 0 22 May 26 Camp Blanding WMA 7 14 76 97 0 0 0 1L 98 M.R. Gold Head Branch SP 4 34 1,859 1,897 0 0 0 0 1,897 May 27 Marjorie Kinnan Rawlings SP 13 29 0 42 0 0 0 0 42 Lochloosa WMA 13 74 0 87 0 0 0 1N 88

May 18-27 Combined (All sites) 201 1,009 7,371 8,581 2 2 1 4 8,590 Ticks were collected by slowly dragging a 1-m2 fleece cloth over leaf litter and low vegetation (<1 m high) in similar habitat for a total area of 400 m2. No collections were conducted on May 22. A = adults; N = nymphs; L = larvae; T = total. Lone star tick: Amblyomma americanum, American dog tick: Dermacentor variabilis, Rabbit tick: Haemaphysalis leporispalustris, Blacklegged tick: Ixodes scapularis

Table 4-2. Analysis of variance (ANOVA) comparing life stage densities between collection sites and the paired state parks and wildlife management areas. Life Stage Source df Sum of Squares Mean Square F Ratio Prob > F Adults Model 15 20.6734 1.3782 4.563 <0.0001 Error 624 188.4750 0.3020 Combined total 639 209.1484

Model Effects Collection Site (1-8) 7 18.0109 8.5186 <0.0001 Location Type (SP or WMA) 1 0.0125 0.0414 0.8389 Collection Site*Location Type 7 1.6859 0.7974 0.5897

Nymphs Model 15 355.2438 23.6829 4.9957 <0.0001 Error 624 2958.2000 4.7407 Combined total 639 3313.4438

Model Effects Collection Site (1-8) 7 264.2438 7.9628 <0.0001 Location Type (SP or WMA) 1 1.0125 0.2136 0.6441 Collection Site*Location Type 7 84.1938 2.5371 0.0140

Table 4-3. Ehrlichia chaffeensis and Ehrlichia ewingii infection rates of host-seeking lone star ticks, Amblyomma americanum, collected in Florida state parks (SP) and wildlife management areas (WMA) in May 2015. Adults Nymphs Paired Site/Locationa No. tested ECH MIRb EEW MIRb No. pools No. ticks ECH MLEc 95% CI EEW MLEc 95% CI Site #1 38 0.0 (0) 0.0 (0) 19 86 1.2 (1) 0.1-5.6 0.0 (0) 0.0-4.0 Lochloosa WMA 22 0.0 (0) 0.0 (0) 9 36 0.0 (0) 0.0-8.5 0.0 (0) 0.0-8.5 Marjorie Kinnan Rawlings SP 16 0.0 (0) 0.0 (0) 10 50 2.0 (1) 0.1-9.5 0.0 (0) 0.0-6.3 Site #2 45 2.2 (1) 0.0 (0) 32 158 0.6 (1) 0.0-3.0 0.0 (0) 0.0-2.3 Manatee Springs SP 24 4.2 (1) 0.0 (0) 14 69 0.0 (0) 0.0-4.8 0.0 (0) 0.0-4.8 Andrews WMA 21 0.0 (0) 0.0 (0) 18 89 1.1 (1) 0.1-5.3 0.0 (0) 0.0-3.8 Site #3 16 0.0 (0) 0.0 (0) 19 95 0.0 (0) 0.0-3.6 0.0 (0) 0.0-3.6 Goethe WMA 3 0.0 (0) 0.0 (0) 9 45 0.0 (0) 0.0-6.9 0.0 (0) 0.0-6.9 Rainbow Springs SP 13 0.0 (0) 0.0 (0) 10 50 0.0 (0) 0.0-6.3 0.0 (0) 0.0-6.3 Site #4 23 0.0 (0) 0.0 (0) 45 224 0.9 (2) 0.2-2.9 0.4 (1) 0.0-2.1 Fort Cooper SP 13 0.0 (0) 0.0 (0) 17 85 0.0 (0) 0.0-4.0 1.2 (1) 0.1-5.6 Flying Eagle WMA 10 0.0 (0) 0.0 (0) 28 139 1.5 (2) 0.3-4.7 0.0 (0) 0.0-2.6 Site #5 40 2.5 (1) 0.0 (0) 40 200 0.0 (0) 0.0-1.8 0.5 (1) 0.0-2.4 Wekiwa Springs SP 20 0.0 (0) 0.0 (0) 20 100 0.0 (0) 0.0-3.5 0.0 (0) 0.0-3.5 Seminole Forest WMA 20 5.0 (1) 0.0 (0) 20 100 0.0 (0) 0.0-3.5 1.0 (1) 0.1-4.8 Site #6 26 0.0 (0) 0.0 (0) 24 120 0.8 (1) 0.0-4.0 0.0 (0) 0.0-2.9 Dexter/Mary Farms WMA 11 0.0 (0) 0.0 (0) 17 85 0.0 (0) 0.0-4.0 0.0 (0) 0.0-4.0 De Leon Springs SP 15 0.0 (0) 0.0 (0) 7 35 2.9 (1) 0.2-13.5 0.0 (0) 0.0-8.4 Site #7 15 0.0 (0) 6.7 (1) 21 105 3.0 (3) 0.8-7.9 0.0 (0) 0.0-3.3 Dunns Creek SP 11 0.0 (0) 0.0 (0) 16 80 2.6 (2) 0.5-8.2 0.0 (0) 0.0-4.2 Dunns Creek WMA 4 0.0 (0) 25.0 (1) 5 25 4.0 (1) 0.2-18.8 0.0 (0) 0.0-10.8 Site #8 20 0.0 (0) 5.0 (1) 12 56 0.0 (0) 0.0-5.8 0.0 (0) 0.0-5.8 Camp Blanding WMA 10 0.0 (0) 10.0 (1) 4 19 0.0 (0) 0.0-13.2 0.0 (0) 0.0-13.2 M.R. Gold Head Branch SP 10 0.0 (0) 0.0 (0) 8 37 0.0 (0) 0.0-8.1 0.0 (0) 0.0-8.1

All Sites/Locations 223 0.9 (2) 0.9 (2) 212 1044 0.8 (8) 0.4- 1.5 0.2 (2) 0.0- 0.6 ECH = E. chaffeensis; EEW = E. ewingii a Presented in order of tick collection. Locations alternated between WMA and SP for sites 1-4, then SP and WMA for sites 5-8. b Minimum infection rate (MIR) percentage is calculated as number of positive per number of individuals tested. Number of positive individuals in parentheses. c Maximum likelihood estimation (MLE) and 95% confidence interval is the maximum likely infection rate (%) based on the number of pools, number of ticks per pool, and number of positive pools (Biggerstaff 2014). Number of positive pools in parentheses.

Table 4-4. Rickettsia spp. infection rates of host-seeking lone star ticks, Amblyomma americanum, collected in Florida state parks (SP) and wildlife management areas (WMA) in May 2015. Adults Nymphs Paired Site/Locationa No. tested MIRb No. pools No. ticks MIRb MLEc,d 95% CIc Site #1 38 36.8 (14) 19 86 18.6 (16) 32.3 20.0-50.8 Lochloosa WMA 22 31.8 (7) 9 36 19.4 (7) 28.8 13.8-54.6 Marjorie Kinnan Rawlings SP 16 43.8 (7) 10 50 18.0 (9) 32.4 17.1-64.2 Site #2 45 75.6 (34) 32 158 20.3 (32) NC NC Manatee Springs SP 24 66.7 (16) 14 69 20.3 (14) NC NC Andrews WMA 21 85.7 (18) 18 89 20.2 (18) NC NC Site #3 16 56.3 (9) 19 95 20.0 (19) NC NC Goethe WMA 3 100.0 (3) 9 45 20.0 (9) NC NC Rainbow Springs SP 13 46.2 (6) 10 50 20.0 (10) NC NC Site #4 23 56.5 (13) 45 224 20.1 (45) NC NC Fort Cooper SP 13 46.2 (6) 17 85 20.0 (17) NC NC Flying Eagle WMA 10 70.0 (7) 28 139 20.1 (28) NC NC Site #5 40 85.0 (34) 40 200 20.0 (40) NC NC Wekiwa Springs SP 20 100.0 (20) 20 100 20.0 (20) NC NC Seminole Forest WMA 20 70.0 (14) 20 100 20.0 (20) NC NC Site #6 26 80.8 (21) 24 120 28.3 (22) 36.9 24.5-56.7 Dexter/Mary Farms WMA 11 30.0 (10) 17 85 17.6 (15) 32.5 19.8-53.5 De Leon Springs SP 15 73.3 (11) 7 35 20.0 (7) NC NC Site #7 15 60.0 (9) 21 105 20.0 (21) NC NC Dunns Creek SP 11 45.5 (5) 16 80 20.0 (16) NC NC Dunns Creek WMA 4 100.0 (4) 5 25 20.0 (5) NC NC Site #8 20 30.0 (6) 12 56 16.1 (9) 25.3 13.0-45.9 Camp Blanding WMA 10 30.0 (3) 4 19 21.1 (4) NC NC M.R. Gold Head Branch SP 10 30.0 (3) 8 37 13.5 (5) 18.5 7.3-40.2

All Sites/Locations 223 62.8 (140) 212 1044 19.5 (204) 49.2 42.5- 57.3 a Presented in order of tick collection. Locations alternated between WMA and SP for sites 1-4, then SP and WMA for sites 5-8. b Minimum infection rate (MIR) percentage is calculated as number of positive individuals (adults) or pools (nymphs) per number of individuals or pools tested. Number of positive in parentheses. c Maximum likelihood estimation (MLE) and 95% confidence interval is the maximum likely infection rate (%) based on the number of pools, number of ticks per pool, and number of positive pools (Biggerstaff 2014). d NC = non-calculable; All pools tested positive in this group, making it impossible to calculate a MLE for the testing outcome

Table 4-5. Entomological risk indices for lone star ticks, Amblyomma americanum, infected with Ehrlichia chaffeensis, Ehrlichia ewingii, and spotted fever group Rickettsia at Florida state parks (SP) and wildlife management areas (WMA) in May 2015. Densityb Infection Ratec ERId Site/Location a ECH EEW RICK ECH EEW RICK Site #1 1.2 ± 0.15 0.8 0.0 35.1 0.010 0.000 0.421 Lochloosa WMA 1.1 ± 0.23 0.0 0.0 31.1 0.000 0.000 0.342 Marjorie Kinnan Rawlings SP 1.3 ± 0.29 1.5 0.0 39.1 0.020 0.000 0.508 Site #2 2.6 ± 0.25 1.0 0.0 75.7 0.026 0.000 1.968 Manatee Springs SP 2.5 ± 0.32 1.1 0.0 67.0 0.028 0.000 1.675 Andrews WMA 2.7 ± 0.38 0.9 0.0 85.7 0.024 0.000 2.314 Site #3 1.3 ± 0.25 0.0 0.0 58.3 0.000 0.000 0.758 Goethe WMA 1.1 ± 0.31 0.0 0.0 100.0 0.000 0.000 1.100 Rainbow Springs SP 1.5 ± 0.39 0.0 0.0 49.8 0.000 0.000 0.747 Site #4 2.7 ± 0.41 0.8 0.4 60.4 0.022 0.011 1.631 Fort Cooper SP 2.3 ± 0.30 0.0 1.0 51.7 0.000 0.023 1.189 Flying Eagle WMA 3.2 ± 0.75 1.4 0.0 69.3 0.045 0.000 2.218 Site #5 2.5 ± 0.29 0.4 0.4 85.0 0.010 0.010 2.125 Wekiwa Springs SP 2.2 ± 0.35 0.0 0.0 100.0 0.000 0.000 2.200 Seminole Forest WMA 2.9 ± 0.47 0.8 0.8 70.0 0.023 0.023 2.030 Site #6 1.4 ± 0.23 0.7 0.0 59.3 0.010 0.000 0.830 Dexter/Mary Farms WMA 2.0 ± 0.42 0.0 0.0 50.0 0.000 0.000 1.000 DeLeon Springs SP 0.9 ± 0.17 2.0 0.0 73.2 0.018 0.000 0.659 Site #7 1.0 ± 0.25 2.6 0.8 61.3 0.026 0.008 0.613 Dunns Creek SP 1.5 ± 0.48 2.3 0.0 51.4 0.035 0.000 0.771 Dunns Creek WMA 0.6 ± 0.13 3.5 3.2 100.0 0.021 0.019 0.600 Site #8 0.4 ± 0.16 0.0 1.3 27.6 0.000 0.005 0.110 Camp Blanding WMA 0.5 ± 0.13 0.0 3.3 36.6 0.000 0.017 0.183 M.R. Gold Head Branch SP 1.0 ± 0.28 0.0 0.0 22.3 0.000 0.000 0.223

All Sites/Locations 1.7 ± 0.10 0.8 0.3 57.5 0.014 0.005 0.978 ECH: E. chaffeensis; EEW: E. ewingii: RICK: Rickettsia spp. a Presented in order of tick collection. Locations alternated between WMA and SP for sites 1-4, then SP and WMA for sites 5-8. b Combined density of adult and nymphal lone star ticks ± SEM/10 m2 c Maximum likelihood estimation of the adult and nymphal combined infection rate d Entomological Risk Index (ERI) represents the number of infected lone star ticks per 10 m2. It is calculated as the product of the combined density and the proportion of infected ticks.

Figure 4-1. Locations sampled during a tick survey conducted in May 2015. Each location contained one state park paired to a wildlife management area based on geographic proximity and habitat.

Figure 4-2. Number of ehrlichiosis (A) and spotted fever group (SFG) rickettsiosis (B) cases reported to Florida Department of Health from 2008-2012 (FL DOH 2016). All ehrlichiosis cases were reported as Ehrlichia chaffeensis; however, different species of Ehrlichia are indistinguishable from E. chaffeensis by serologic testing. Therefore, some cases may actually be due to E. ewingii or other unspecified Ehrlichia. Spotted fever rickettsiosis is caused by multiple Rickettsia species, which also cross-react with serologic testing. National reporting SFG rickettsiosis standards expanded to include all SFG Rickettsiae in 2010, but Florida’s surveillance case definition remained unchanged throughout 2008-2012.

Figure 4-3. Lone star tick larval mass on lint roller sheet. Larval ticks were removed from the tick drag using a lint roller. A ultra-fine tip permanent marker was used to make divisions on the sheet to ease counting of individual ticks. Photo courtesy of author.

2.5 5/18/15 5/27/15

2 2

1.5

SEM 10 m SEM per 1 ±

Mean Mean 0.5

0 Adults Nymphs Adults Nymphs Lochloosa WMA Marjorie Kinnan Rawlings SP

Figure 4-4. Lochoosa Wildlife Management Area (WMA) and Marjorie Kinnan Rawlings State Park (SP) adult and nymphal lone star tick density comparisons between May 18, 2015 and May 27, 2015. No significant differences were detected in tick densities at Lochloosa WMA (adults: P = 0.86, nymphs: P = 0.84 by Fisher’s Exact Test) or Marjorie Kinnan Rawlings State Park SP (adults: P = 1.00, nymphs: P = 0.06 by Fisher’s Exact Test).

3.5 Nymphs Adults

2.5 SEM per 10 m2 ±

2 Mean

1.5

0.5

Figure 4-5. Relative density of lone star tick, Amblyomma americanum, nymphs and adults collected from paired state parks (SP) and wildlife management areas (WMA) at eight sites in Florida from May 18-28, 2015. Data is presented in order of collection. Ticks were collected by slowly dragging a 1-m2 fleece cloth over 400 m2 area of leaf litter and low vegetation (<1 m high) in similar hardwood hammock, pine forest, or mixed hardwood/pine forest habitat.

0.8

0.7 A 2 0.6 AB 0.5

SEM per 10 m 0.4 AB ± 0.3 BC BC

Mean C C 0.2 C

0.1

0 Site 1 Site 2 Site 3 Site 4 Site 5 Site 6 Site 7 Site 8

Figure 4-6. Adult lone star tick density by site. Ticks were collected by slowly dragging a 1-m2 fleece cloth over 400 m2 area of leaf litter and low vegetation (<1 m high) in similar hardwood hammock, pine forest, or mixed hardwood/pine forest habitat.

3 A

2 2.5 AB AB

BC SEM per 10 m 1.5 BC ± C C

Mean 1 C

0.5

0 Site 1 Site 2 Site 3 Site 4 Site 5 Site 6 Site 7 Site 8

Figure 4-7. Nymphal lone star tick density by site. Ticks were collected by slowly dragging a 1-m2 fleece cloth over 400 m2 area of leaf litter and low vegetation (<1 m high) in similar hardwood hammock, pine forest, or mixed hardwood/pine forest habitat.

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CHAPTER 5 SEASONAL ACTIVITY AND ABUNDANCE OF TICKS, AND TEMPORAL PATTERNS OF EHRLICHIA AND RICKETTSIA INFECTION RATES OF HOST-SEEKING LONE STAR TICKS IN NORTH-CENTRAL FLORIDA

Introduction

The tick-borne diseases ehrlichiosis and rickettsiosis have seen dramatic

increases of reported cases over the last decade in the United States (Drexler et al.

2016, Nichols Heitman et al. 2016). Depending on the pathogenicity of the intracellular

bacteria that cause the diseases, infection can range from asymptomatic or mild illness

to more severe forms that require hospitalization and, in rare cases, death. These

diseases are most frequently reported in areas of the south-central and southeastern

United States where lone star ticks, Amblyomma americanum (L.), are present.

Lone star ticks are the primary vectors for the agents that cause ehrlichiosis and

are suspected to transmit pathogens that cause rickettsiosis (Stromdahl and Hickling

2012). Ehrlichia chaffeensis and E. ewingii are the principal pathogens that cause

human ehrlichiosis in the United States (Harris et al. 2016, Nichols Heitman et al. 2016).

A third species, Panola Mountain Ehrlichia, has been associated with one human illness

(Reeves et al. 2008).

Rickettsia rickettsii was the major pathogen associated with human cases of rickettsiosis in the United States, but novel pathogens such as Rickettsia parkeri and other Rickettsia spp. are now suspected to be more frequently associated with human illness (Dahlgren et al. 2016). Rickettsia rickettsii, R. massiliae, and R. parkeri have been associated with lone star ticks, but their importance as a vector of these pathogens is disputed or unknown (Goddard 2003, Vitale et al. 2006, Cohen et al. 2009,

Heise et al. 2010, Berrada et al. 2011, Breitschwerdt et al. 2011). Rickettsia

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amblyommii, a mildly or non-pathogenic species common in lone star ticks, have infection rates often exceeding 50% (Mixson et al. 2006, Billeter et al. 2007, Gaines et al. 2014, Killmaster et al. 2014, Sayler et al. 2014).

The risk of acquiring one of these pathogens is dependent on tick abundance, tick infection rates, and the extent of human exposure to questing infected ticks

(Randolph 2009). These criteria are dynamic, and previous studies have reported that host densities (Bloemer et al. 1990), habitat type (Semtner and Hair 1973), environmental conditions (Semtner et al. 1973), and anthropogenic habitat alteration

(Allan 2009, Gleim et al. 2014) all influence lone star tick phenology and abundance.

Ehrlichiosis and rickettsiosis have been reported in North-central Florida, but there is limited data available on the seasonal patterns of lone star ticks and even less is known on the temporal dynamics of their associated pathogens. The limited studies investigating temporal dynamics of these pathogens have focused on annual data comparisons (Childs and Paddock 2003, Mixson et al. 2006, Sayler et al. 2016). The aim of this study was to determine the seasonality of lone star ticks in North-central

Florida and monitor ehrlichial and rickettsial infection rates of adult and nymphal lone star ticks across a 22-month period. The ultimate goal is to reveal seasonal fluctuations of pathogen infection rates in questing lone star ticks for public health officials to better communicate exposure risk throughout the region.

Methods

Study Locations

Three study locations in North-central Florida (Figure 5-1) were selected based on historical lone star tick ehrlichial and rickettsial infection prevalence data (Mixson et al. 2006, Sayler et al. 2016), geographic proximity to one another, and similar mixed

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pine/hardwood hammock habitat that favor lone star tick populations (Rogers 1953).

Andrews Wildlife Management Area (AWMA) is located in western Levy County and is composed of 3,501 acres of primarily unaltered contiguous hardwood hammock forests

(FL FWC 2004). O’Leno State Park (OLEN), which included the area surrounding the

O’Leno/River Rise State Park equestrian barn (29°50'54.4"N, 82°38'01.1"W), is located on the border of Alachua and Columbia counties and contains 18 diverse natural communities covering 6,215 acres (FL FWC 2003). San Felasco Hammock Preserve

State Park and San Felasco Gainesville City Park (SANF) in Alachua county is considered the most diverse and complex community in north-central Florida, encompassing 6,927-acres (FL DEP 2005). This study location included areas of suitable tick habitat found near the main hiking trails (29°42'49.7"N, 82°27'40.8"W;

29°43'01.4"N 82°27'38.0"W), east hiking trails (29°42'47.4"N, 82°23'34.4"W), and north hiking trails (29°46'41.2"N, 82°28'46.1"W; 29°46'19.9"N 82°28'06.5"W). Tick collections were approved through Florida Department of Environmental Protection non- commercial research collection permits (#02271410, #02231520, #03241610) for OLEN and SANF, and Florida Fish and Wildlife Conservation Commission special use access permits (#49705, #50095, #50722) for AWMA.

Tick Collections

From July 2014 until April 2016, ticks were collected at randomized sites from each location (AWMA, OLEN, SANF) covering a total area of 200-1,000 m (Table B-3).

At the beginning of the study tick collections were done as a ‘pilot’ study and area sampled was very inconsistent (200 – 3050 m) from multiple sites (2-8), but then standardized in 2015 to encompass 1000 m per location consisting of 300-400 m subsamples from three sites (Table B-3). Tick collections were made by slowly dragging

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a 1-m2 white polyester cloth (Anti-pill fleece, #060311140, Jo-Anne Stores LLC,

Hudson, OH) weighted on the distal end with an aluminum flat bar (1/16” x 3/4", The

Hillman Group, Cincinnati, OH). The cloth was drug over leaf litter and low vegetation

(<1-m high) in similar habitat. Every 10 m the cloth was checked and all attached ticks were removed using a lint roller (Scotch Brite™, 3M, St. Paul, MN). Ticks found on the back of the fleece cloth were saved as ‘extra’ ticks and included in the random sampling for pathogen detection, but were excluded from the density calculations. Lint roller sheets with attached ticks were covered by a Kimwipe™ (Kimtech Science™ #34120,

Kimberly-Clark Professional, Roswell, GA), then stored in zippered plastic bags in a cooler with ice packs until quantification and species identification were completed.

Ticks were individually counted and identified by examining the lint roller sheet using a dissecting microscope and standard keys (Clifford et al. 1961, Keirans and

Litwak 1989, Keirans and Durden 2004). High-density areas on the lint roller sheet (e.g. larval tick masses) were carefully subdivided into smaller areas using an ultra-fine tip permanent marker to improve accuracy (Figure 4-3). Occasionally, larval tick counts were estimated by subdividing the high-density areas as before, counting the ticks within those areas, and comparing those counts to subareas too dense to subdivide. In these few instances, conservative estimates were used. In instances when larval ticks could not be identified on the lint roller sheet, a larval subsample was slide mounted, either cleared or uncleared, and identified using a compound microscope. Nymphal and adult lone star ticks were removed from the lint roller sheets and stored in 95% ethanol by location, site, and life stage at -80°C until DNA extraction.

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DNA Extraction and Pathogen Detection

A maximum of 30 individual adults and 30 individual nymphs per location per month, collected between July 2014 and February 2016, were analyzed for ehrlichial and rickettsial pathogens. Ticks were taken from -80°C storage, randomly removed from the 95% ethanol, and allowed to air dry prior to being placed individually into 2.0 ml microcentrifuge tubes (Fisherbrand #02-681-344, Pittsburgh, PA) containing three 2.0 mm zirconia beads (Biospec #11079124zx, Bartlesville, OK). Ticks were mechanically homogenized by flash freezing the 2.0 ml microcentrifuge tubes in liquid nitrogen for 5 min prior to processing the samples in a FastPrep® FP120 cell disrupter (Qbiogene, Inc.,

Carlsbad, CA) for 45 sec at a speed of 5.5 m/sec. DNA was extracted from the sample using the Quick-gDNA™ MiniPrep kit (Zymo Research #D3025, Irvine, CA) by vortexing the homogenate in 500 µl of Zymo Genomic Lysis Buffer with 0.5% (v/v) beta- mercaptoethanol added. This suspension was incubated at room temperature for 5 min before following the manufacturer solid tissue sample protocol. DNA was eluted in 50 µl of elution buffer and held at -20°C until pathogen testing.

DNA extracts were analyzed with a multiplex real-time polymerase chain reaction protocol that simultaneously detects the16s rRNA gene of E. chaffeensis and E. ewingii, and a conserved region of the 17-kD gene targeting Spotted Fever Group Rickettsia spp. (Sayler et al. 2016). Using the same primer and probe concentrations as Killmaster et al. (2014), 20µl reactions were run on the ABI 7500 Fast Real-Time PCR system (Life

Technologies, Grand Island, NY) with Brilliant III Ultra-Fast QPCR Master Mix (Agilent

Technologies, La Jolla, CA) for an initial denaturation at 95°C for 10 min, followed by 40 cycles of denaturation at 95°C for 15 sec, and annealing-extension at 57°C for 1 min.

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Ehrlichia and Rickettsia positive controls were from the same sources reported by

Sayler et al. (2016) and distilled water was used as the negative controls.

A subsample (n = 93) of the positive Rickettsia samples were randomly selected

by month and sequenced to identify rickettsial species. Original DNA extracts from

these samples were amplified using conventional PCR by targeting a 632bp fragment of

the OmpA gene (Fournier et al. 1998). To confirm identity, amplicons were

enzymatically purified and sequenced, unidirectionally, using Sanger methods at the

University of Florida Interdisciplinary Center for Biotechnology Research (ICBR).

Sequences were edited using 4Peaks (Griekspoor et al. 2015), then analyzed using the

National Center for Biotechnology Information (NCBI) Basic Local Alignment Sequence

Tool (BLAST).

Statistical Analysis

Densities were calculated as the mean number of ticks per 10 m2 and combined

each month by life stage excluding collection year. Density calculations included ticks

collected between August 2014 and April 2016 and excluded the ticks collected in July

2014 because only AWMA was sampled during this month. A factorial analysis of variance model that included the treatment effects of collection month (Jan - Dec) and location (AWMA, OLEN, SANF), as well as the interaction of the two effects was applied separately to the density data to determine if life stage densities differed significantly between the collection months and the geographic location of the collection sites (JMP®,

Version 12.0.1, SAS Institute Inc., Cary, NC, 1989-2015). Differences in main effects

were further analyzed using Tukey’s HSD. Minimum infection rates (MIR) were

calculated using lone star ticks collected between July 2014 and February 2016. MIRs

were calculated for nymphal, adult, and total ticks (nymph and adults combined) as the

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percent of pathogen-positive tick samples per number of individual ticks tested each

month. The MIRs, for each site over all collections, were compared by location, life

stage, and collection year using the Fisher’s Exact test for ehrlichial infections or

Pearson’s Chi-square test for rickettsial infections. All p-values were two-tailed, and p <

0.05 was considered significant. Post-hoc pairwise comparisons were corrected using

the Bonferroni adjustment. An entomological risk index (ERI) was used to compare

relative risk between months. The ERI represents the number of infected ticks per 10

m2. The ERI was calculated monthly, by life stage, by taking the density and multiplying

it with the E. chaffeensis, E. ewingii, and Rickettsia spp. infection rates (Mather 1993).

Results

Lone star ticks accounted for 99.8% of the 73,272 ticks collected over the 22- month sampling period at the three recreational areas (Table 5-1). Other species recovered (Table 5-2) were the Gulf Coast tick, Amblyomma maculatum Koch, the gophertortoise tick, A. tuberculatum Marx, the American dog tick, Dermacentor variabilis

(Say), the blacklegged tick, Ixodes scapularis Say, and the rabbit tick, Haemaphysalis leporispalustris (Packard).

Lone star ticks were collected in every month of the year in north-central Florida.

Tick collections, by life stage, significantly varied by collection month due to the seasonality of each life stage (Table 5-3). No significant differences were detected in tick collections between locations, except for adult ticks, which were collected less frequently at SANF than the other two locations (Table 5-3). Adult lone star ticks were

recovered in every month of the year except November and December, and adult

activity peaked in May (Figure 5-2A). Over the course of the study, adult lone star tick

density ranged from 0.0-0.4 ticks/10 m2 (mean = 0.1) with the greatest density recorded

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in May 2015. Lone star tick nymphs were collected during every month of the year and

exhibited a bimodal distribution with peaks occurring in May and September (Figure 5-

2B). Lone star tick nymphal density ranged from 0.0-2.7 ticks/10 m2 (mean = 0.9), and

the greatest density was also recorded in May 2015. Lone star tick larvae were

recovered in every month, but at much lower densities from December to May (Figure

5-2C). February 2015 was the only month lone star tick larvae were not collected. The

peak season for this life stage occurred from June through October with the greatest

abundance occurring in July. Larval density ranged from 0.0-40.9 ticks/10 m2 (mean =

10.9), and the greatest density recorded in July 2015.

Ehrlichial infections of lone star ticks were prevalent in north-central Florida in all

months except November through January. Ehlrichia chaffeensis was detected in lone star tick adults (Figure 5-3A) from February through August, except for March and July, with a peak in August (4.2%). In nymphs, E. chaffeensis was detected in March, May,

August, and September, and the nymphs that were collected in September had the highest infection rate (1.7%). Ehrlichia ewingii was detected in adults (Figure 5-3C) consistently from March until peaking in August (4.2%). Ehrlichia ewingii infections in nymphs (Figure 5-4D) occurred in May, August, and October, with May having the highest E. ewingii-infected nymphs (1.3%).

Ehrlichia chaffeensis MIRs, averaged for each site over all collections, ranged

from 0.5-3.0% in adult lone star ticks and 0.0-1.2% in nymphal ticks at the locations

surveyed (Table 5-4). Total E. chaffeensis MIRs differed significantly between locations

(P = 0.0073). SANF had the highest total E. chaffeensis MIR (1.7%), which was

statistically greater than AWMA’s total MIR (0.1%, P = 0.0073), but was not statistically

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different than OLEN’s total MIR. No statistical differences were found between AWMA

and OLEN E. chaffeensis infection rates. Ehrlichia ewingii MIRs, averaged for each site

over all collections, ranged from 0.9-1.3% for adults and 0.0-0.8% in nymphs (Table 5-

5). There were no statistical differences among total E. ewingii MIRs between locations

(P = 0.2733). No statistical differences were detected among E. chaffeensis MIRs (P =

0.5144) or among E. ewingii MIRs (P = 1.000) by collection year, but there were

significantly differences in MIRs by life stage for E. chaffeensis (Adult: 1.83%, Nymph:

0.50%, P = 0.0173) and E. ewingii (Adult: 1.63%, Nymph: 0.25%, P = 0.0032).

Rickettsia was detected in lone star ticks during every month of the year.

Rickettsia detection in adult ticks was limited to January through September (Figure 5-

4A), whereas, Rickettsia detection in nymphal ticks occurred in every month (Figure 5-

4B). Rickettsial infections, averaged for each site over all collections, ranged from 41.3-

73.4% for adults and 42.2-73.8% for nymphs (Table 5-6). Total rickettsial rates were

significantly different between locations (χ2 = 152.51, P ≤ 0.0001), with AWMA (74.4%)

having significantly higher infection rates compared to OLEN (41.9%; P ≤ 0.0001) and

SANF (46.4%; P ≤ 0.0001). MIRs were not statistically different by life stage (P =0.9571)

or by year (P = 0.647). All 93 of the sequenced Rickettsia positive samples matched R.

amblyommii (99-100% identity to GENBANK accession number: CP012420.1).

The relative exposure risk to ehrlichial- and rickettsial-infected lone staradult and

nymphal ticks are presented in Table 5-7 and Table 5-8, respectively. The adult tick ERI

value, averaged for each site over all collections, for E. chaffeensis and E. ewingii was

0.002. The relative risk of exposure to Ehrlichia chaffeensis-infected adults ranged

between 0.000 to 0.010 monthly, while the relative risk of exposure to E. ewingii ranged

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from 0.000 to 0.005. The peak adult ERI value occurred in May for E. chaffeensis and in

May and September for E. ewingii. The nymphal tick ERI value, averaged for each site over all collections, was higher for E. chaffeensis-infected nymphs (0.005) than E. ewingii-infected nymphs (0.002). Ehrlichia chaffeensis ERI values ranged from 0.000 to

0.034, and E. ewingii ERI values ranged from 0.000-0.033. The peak nymphal ERI value occurred in September for E. chaffeensis, although the May ERI value (0.033) was as high. The peak nymphal ERI value for E. ewingii occurred in May. The combined

Rickettsia spp. ERI value for adults was 0.55, and ranged from 0.000 to 0.183, while for nymphs the value was 0.519, and ranged from 0.024-1.305. The adult Rickettsia spp.

ERI values peaked in May, and the nymphal values peaked in September.

Discussion

This study monitored the seasonal fluctuations of lone star ticks and E. chaffeensis, E. ewingii, and Rickettsia spp. infections of these ticks in north-central

Florida. Lone star ticks were present year-round at all locations, and the phenology recorded in this study agrees with another north-central study conducted at Gulf

Hammock Game Reserve [sic: Gulf Hammock WMA] by Rogers (1953). Rogers (1953) reported lone star tick seasonal activity peaks for larvae in July, bimodal peaks for nymphs in May and August, and the adults in May. A study conducted by Cilek and

Olson (2000), in northwestern Florida, did not identify a clear peak activity period for adult lone star ticks, while nymphal tick activity was unimodal, peaking in September.

Slight differences in lone star tick activity were observed between the locations surveyed in our study. In general, adult lone star tick activity occurred earlier at AWMA and had no discernable peak activity period compared to OLEN and SANF. Additionally, fewer adults were collected at SANF than the other locations. It is likely that lone star

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tick activity varies throughout the state dependent on habitat heterogeneity, host availability, weather patterns, or other biotic or abiotic factors. Further investigation is needed to determine what factors influence lone star tick phenology in north central

Florida. Importantly, this variability in tick density should be considered when making risk predications, as changes in tick density dramatically increase the risk of exposure.

The ehrlichial infection rates reported here are comparable with rates published throughout the lone star tick’s range, including Florida (Mixson et al. 2006, Cohen et al.

2010, Sayler et al. 2016). Interestingly, Sayler et al. (2016) reported unusually high ehrlichial infection rates in lone star ticks collected from OLEN in 2011 (E. ewingii only,

12.0%) and 2012 (E. chaffeensis, 73.6%, and E. ewingii, 64.1%). We did not detect any differences in ehrlichial rates between years in our study, but infection rates in adult and nymphal ticks did fluctuate monthly. In sampled ticks, E. chaffeensis infections had a trimodal frequency distribution with cyclical peaks every 2-3 months with the first peak beginning in February for adults and in March for nymphs. Ehrlichia ewingii infection peaks appeared a month after E. chaffeensis, and were trimodal in nymphs, but bimodal in adults. Interestingly, E. chaffeensis and E. ewingii were not detected in nymphs collected in April and September, respectively. These months represent peak activity periods for this life stage, and the lack of Ehrlichial pathogen detection during these periods is intriguing. Further investigation is warranted to determine if temporal fluctuations are observed in other lone star tick populations, and attempt to determine whether these fluctuations are due to a sampling bias (e.g. host availability or habitat variability), generational prevalence (e.g. overwintered vs. newly emerged), or other factors not readily apparent.

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Rickettsia amblyommii was the only rickettsial species identified in the ticks tested. This species is assumed to be mildly or non-pathogenic (Billeter et al. 2007,

Apperson et al. 2008, Ponnusamy et al. 2014), and may confer some immunity to more virulent rickettsial species (Dahlgren et al. 2016). Rickettsial infections in nymphal and adult ticks had no definitive peaks throughout the year, but higher infection rates were recorded during the colder months, while the lowest rates were during the warmer months. The higher rates in the colder months may be an artifact due to the low sample size relative to the number of samples tested during the warmer months and because the majority of the ticks tested during the colder months were collected from AWMA, which had significantly higher Rickettsia spp. infection rates compared to the other two sites. Despite this, rickettsial infection rates at all three sites fluctuated between 10-20 percentage points throughout the year.

The precise reasons why pathogenic and non-pathogenic bacterial communities in ticks temporally fluctuate temporally are largely unknown. These cyclic variations within the lone star tick’s microbiome may be caused by changes in environmental conditions, molting, aging, population structure, and host choice (Menchaca et al. 2013,

Trout Fryxell and DeBruyn 2016). It is thought that the tick microbiome can influence the vector’s competence or capability to transmit a pathogen (Trout Fryxell and DeBruyn

2016). For example, Gall et al. (2016) reported that an increased proportion of bacterial endosymbionts (Rickettsia belli) were negatively correlated with Anaplasma marginale levels in the Rocky Mountain wood tick, Dermacentor andersoni Stiles. Conversely, interactions with lone star tick endosymbionts (Coxiella spp.) have been shown to be positively correlated with Ehrlichia pathogens (Trout Fryxell and DeBruyn 2016).

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Interestingly, E. chaffeensis and E. ewingii infections were detected only during August

at AWMA compared to persistent detections at OLEN (6 mo and 5 mo, respectively)

and SANF (5 mo each). It would be a worthwhile endeavor to explore the microbiome of

these populations to determine if bacterial species other than Rickettsia spp. differ.

Cases of human ehrlichiosis have been reported from February through

November in Florida, with the most cases occurring in May (FL DOH 2015). This trend

is similar to the exposure risk calculated in this study, which also emphasizes that May

was a month of heightened risk for ehrlichiosis transmission. September also had a

higher ehrlichial risk value, which was attributed to a higher E. chaffeensis infection rate

of nymphs. Overall, nymphal ticks posed a higher risk for ehrlichial pathogens because

their densities were much greater than the adult ticks throughout the entire sampling

period. However, adult ticks, despite their relatively low abundance, were 3.7-fold more

infected with E. chaffeensis and 6.5-fold more infected with E. ewingii. These

differences in infection rates and density translate to vast differences in relative risk. For

example, a person is 3.3- or 6.6-fold more likely to be exposed to an E. chaffeensis- or

E. ewingii- infected nymph, respectively, than an infected adult during May in our study.

However, in the two adjacent months, April and June, that same person would be more

likely to encounter an infected adult. However, as with Lyme disease and other tick- borne diseases, the nymph poses greater risk because of their small size (IOM 2011).

Although adults generally carry a much higher infection rate, they are often found quickly and removed.

Florida-acquired rickettsioses have been reported consistently from April through

November (FL DOH 2015). This trend corresponds to the active season of lone star

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ticks for most of the state and is consistent with the rickettsial infection rates detected

throughout the year in this study. As previously mentioned, we failed to detect Rickettsia

spp. other than R. amblyommii in this study, which suggests that lone star ticks may not

be important in the transmission of more virulent rickettsial species in Florida. However,

failure to detect a pathogen does not necessarily mean the pathogen is truly absent

within a population. Only 0.46% of lone star ticks examined in a Kansas population

contained pathogenic R. rickettsia (Berrada et al. 2011). In the Kansas study, 90% of

the pools were positive for R. amblyommii and two of the samples positive with R.

rickettsii were dual-infected with R. amblyommii. Low infection rates of pathogenic R.

parkeri were found in lone star ticks collected in Georgia and Tennessee (Cohen et al.

2009). Although the relative proportion of R. amblyommii was not reported in this study,

it could be assumed to be comparable to the 40-50% infection rates reported in lone

star ticks in another Tennessee study (Moncayo et al. 2010).

Preventing tick-borne infections is preferred over treating the short- and long-

term effects of disease (IOM 2011). Because tick-borne pathogens are temporally and

spatially variable, continuous proactive surveillance to detect pathogens in host-seeking

ticks is essential to predicting endemic zoonotic transmission cycles and responding to

future emerging pathogens. Public health officials should encourage active surveillance

programs to better communicate exposure risk concerning lone star ticks and their

pathogens in north-central Florida. Future investigations should integrate microbiome

characterization to determine if temporal fluctuations occur in the tick microbiome that may be advantageous or disadvantageous to the survival of tick-borne pathogens.

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Table 5-1. Number of lone star ticks, Amblyomma americanum, collected from three North-central Florida recreational areas between July 2014 and April 2016. Total Area No. Ticks Collected (% total by life stage)b Locations Sampled (m2)a Adults Nymphs Larvae Total Andrews Wildlife Management Area 20,980 318 (40.0)A 2,433 (37.8)A 22,542 (34.2)A 25,293 (34.6) O’Leno State Park 20,650 285 (35.8)A 2,416 (37.5)A 24,442 (37.1)A 27,143 (37.1) San Felasco Hammock Preserve State Park 19,050 192 (24.2)B 1,592 (24.7)A 18,929 (28.7)A 20,713 (28.3)

Locations Combined 60,680 795 6,441 65,913 73,149 Data in columns with different letters are significantly different (α = 0.05). aTicks were collected monthly at each location by slowly dragging a 1-m2 fleece cloth over leaf litter and low vegetation (<1-m high) in similar hardwood hammock, pine forest, or mixed hardwood/pine forest habitat for a total area ranging from 200-1000 m at each location per month. bLone star ticks consisted of 99.8% of the total ticks collected during this period.

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Table 5-2. Minor ixodid species collected from three North-central Florida locations between July 2014 and April 2016. Amblyomma Amblyomma Dermacentor Haemaphysalis Ixodes MMYYYYa Sum (M2)b maculatum tuberculatum variabilis leporispalustris scapularis 07-2014 200 0 0 0 0 0 08-2014 1,800 0 0 0 0 0 09-2014 2,650 0 0 0 0 0 10-2014 2,680 0 0 0 0 0 11-2014 2,300 0 0 0 0 9A 12-2014 3,050 0 0 0 0 10A 01-2015 3,000 0 7L 4L 1N 22A 02-2015 3,000 0 0 0 0 10A 03-2015 3,000 1N 4L 0 0 5A 04-2015 3,000 0 0 0 0 1N 05-2015 3,000 0 0 10A 0 0 06-2015 3,000 0 0 0 1N 0 07-2015 3,000 0 0 0 0 0 08-2015 3,000 0 0 0 0 2N 09-2015 3,000 0 0 0 0 2N 10-2015 3,000 0 0 0 0 5A 11-2015 3,000 0 0 0 0 9A 12-2015 3,000 0 1N, 1L 0 0 2A 01-2016 3,000 0 0 0 0 6A 02-2016 3,000 0 0 0 0 2A 03-2016 3,000 0 0 0 0 1N, 32L 04-2016 3,000 0 0 0 0 2A, 3L

Combined 60,680 1 13 14 2 123 A = adult; N = nymph; L = larvae aTicks were collected monthly at each location by slowly dragging a 1-m2 fleece cloth over leaf litter and low vegetation (<1-m high) in similar hardwood hammock, pine forest, or mixed hardwood/pine forest habitat for a total area ranging from 400-1000 m at each location per month. bTotal area sampled on a given date.

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Table 5-3. Analysis of variance (ANOVA) comparing life stage densities between collection dates and collection locations. Life Stage Sourcea df Sum of Squares Mean Square F Ratio Prob > F Adults Model 35 95.46 2.73 21.40 <0.0001 Error 6012 766.15 0.13 Combined total 6047 861.61

Model Effects Collection Month (Jan-Dec) 11 81.952053 58.4621 <0.0001 Location (AWMA, OLEN, SANF) 2 2.317697 9.0936 0.0001 Collection Month*Location 22 10.935376 3.9005 <0.0001

Nymphs Model 35 4895.931 139.884 8.88 <0.0001 Error 6012 94728.839 15.757 Combined total 6047 99624.770

Model Effects Collection Month (Jan-Dec) 11 3865.4415 22.3020 <0.0001 Location (AWMA, OLEN, SANF) 2 83.3625 2.6453 0.0711 Collection Month*Location 22 845.9268 2.4403 <0.0001

Larvae Model 35 1227234 35063.8 3.70 <0.0001 Error 6012 56959870 9474.4 Combined total 6047 58187104

Model Effects Collection Month (Jan-Dec) 11 954657.70 9.1602 <0.0001 Location (AWMA, OLEN, SANF) 2 2890.66 0.1526 0.8585 Collection Month*Location 22 261976.20 1.2569 0.1881 aAWMA: Andrew’s Wildlife Management Area; OLEN: O’leno State Park; SANF: San Felasco Hammock Preserve State Park

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Table 5-4. Ehrlichia chaffeensis minimum infection rates (MIR) in host-seeking lone star ticks, Amblyomma americanum, collected at three North-central Florida recreational areas between July 2014 and February 2016. AWMA OLEN SANF Month T A N T A N T A N 07-2014 0.0 (37) 0.0 (18) 0.0 (19) NT NT NT NT NT NT 08-2014 2.3 (44) 7.1 (14) 0.0 (30) 2.9 (35) 0.0 (6) 3.4 (29) 0.0 (28) 0.0 (2) 0.0 (26) 09-2014 0.0 (32) 0.0 (2) 0.0 (30) 0.0 (31) 0.0 (1) 0.0 (30) 6.5 (31) 0.0 (1) 6.7 (30) 10-2014 0.0 (30) NT 0.0 (30) 0.0 (32) 0.0 (2) 0.0 (30) 0.0 (20) NT 0.0 (20) 11-2014 0.0 (9) NT 0.0 (9) 0.0 (5) NT 0.0 (5) NT NT NT 12-2014 0.0 (6) NT 0.0 (6) 0.0 (5) NT 0.0 (5) NT NT NT 01-2015 0.0 (35) 0.0 (5) 0.0 (30) 0.0 (12) 0.0 (4) 0.0 (8) NT NT NT 02-2015 0.0 (50) 0.0 (20) 0.0 (30) 0.0 (7) NT 0.0 (7) 0.0 (5) 0.0 (3) 0.0 (2) 03-2015 0.0 (53) 0.0 (23) 0.0 (30) 0.0 (40) 0.0 (10) 0.0 (30) 2.1 (48) 0.0 (18) 3.3 (30) 04-2015 0.0 (59) 0.0 (29) 0.0 (30) 1.7 (60) 3.3 (30) 0.0 (30) 1.8 (56) 3.8 (26) 0.0 (30) 05-2015 0.0 (36) 0.0 (16) 0.0 (20) 1.7 (60) 3.3 (30) 0.0 (30) 3.3 (60) 3.3 (30) 3.3 (30) 06-2015 0.0 (60) 0.0 (30) 0.0 (30) 1.7 (59) 3.4 (29) 0.0 (30) 0.0 (43) 0.0 (13) 0.0 (30) 07-2015 0.0 (44) 0.0 (14) 0.0 (30) 0.0 (60) 0.0 (30) 0.0 (30) 0.0 (50) 0.0 (20) 0.0 (30) 08-2015 0.0 (50) 0.0 (20) 0.0 (30) 0.0 (39) 0.0 (9) 0.0 (30) 4.0 (50) 10.0 (20) 0.0 (30) 09-2015 0.0 (34) 0.0 (4) 0.0 (30) 2.9 (34) 0.0 (4) 3.3 (30) 0.0 (30) NT 0.0 (30) 10-2015 0.0 (30) NT 0.0 (30) 0.0 (30) NT 0.0 (30) 0.0 (22) NT 0.0 (22) 11-2015 0.0 (30) NT 0.0 (30) 0.0 (5) NT 0.0 (5) 0.0 (8) NT 0.0 (8) 12-2015 0.0 (10) NT 0.0 (10) 0.0 (2) NT 0.0 (2) 0.0 (2) NT 0.0 (2) 01-2016 0.0 (12) NT 0.0 (12) 0.0 (2) 0.0 (1) 0.0 (1) 0.0 (1) NT 0.0 (1) 02-2016 0.0 (34) 0.0 (4) 0.0 (30) 3.0 (33) 25.0 (4) 0.0 (29) 0.0 (3) NT 0.0 (3)

Combined 0.1 (695) 0.5 (199) 0.0 (496) 1.1 (551) 2.5 (160) 0.5 (391) 1.8 (457) 3.0 (133) 1.2 (324) MIR = percent of pathogen positive tick samples per number of individual ticks tested (n = total individuals tested); Infection was determined by qPCR using genus-specific16S rRNA primers with species-specific dual-labeled hydrolysis probes for Ehrlichia chaffeensis and E. ewingii (Killmaster et al. 2014, Sayler et al. 2016). AWMA = Andrews Wildlife Management Area; OLEN = O’Leno State Park; SANF = San Felasco Hammock Preserve State Park; T = Total ticks (A+N); A = Adults; N = Nymphs; NT = Not tested; no ticks collected during this sampling period.

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Table 5-5. Ehrlichia ewingii minimum infection rates (MIR) in host-seeking lone star ticks, Amblyomma americanum, collected at three North-central Florida recreational areas between July 2014 and February 2016. AWMA OLEN SANF Month T A N T A N T A N 07-2014 0.0 (37) 0.0 (18) 0.0 (19) NT NT NT NT NT NT 08-2014 2.3 (44) 7.1 (14) 0.0 (30) 0.0 (35) 0.0 (6) 0.0 (29) 0.0 (28) 0.0 (2) 0.0 (26) 09-2014 0.0 (32) 0.0 (2) 0.0 (30) 0.0 (31) 0.0 (1) 0.0 (30) 0.0 (31) 0.0 (1) 0.0 (30) 10-2014 0.0 (30) NT 0.0 (30) 3.2 (32) 0.0 (2) 3.3 (30) 0.0 (20) NT 0.0 (20) 11-2014 0.0 (9) NT 0.0 (9) 0.0 (5) NT 0.0 (5) NT NT NT 12-2014 0.0 (6) NT 0.0 (6) 0.0 (5) NT 0.0 (5) NT NT NT 01-2015 0.0 (35) 0.0 (5) 0.0 (30) 0.0 (12) 0.0 (4) 0.0 (8) NT NT NT 02-2015 0.0 (50) 0.0 (20) 0.0 (30) 0.0 (7) NT 0.0 (7) 0.0 (5) 0.0 (3) 0.0 (2) 03-2015 0.0 (53) 0.0 (23) 0.0 (30) 0.0 (40) 0.0 (10) 0.0 (30) 2.1 (48) 5.6 (18) 0.0 (30) 04-2015 0.0 (59) 0.0 (29) 0.0 (30) 0.0 (60) 0.0 (30) 0.0 (30) 1.8 (56) 3.8 (26) 0.0 (30) 05-2015 0.0 (36) 0.0 (16) 0.0 (20) 1.7 (60) 0.0 (30) 3.3 (30) 1.7 (60) 3.3 (30) 0.0 (30) 06-2015 0.0 (60) 0.0 (30) 0.0 (30) 1.7 (59) 3.4 (29) 0.0 (30) 0.0 (43) 0.0 (13) 0.0 (30) 07-2015 0.0 (44) 0.0 (14) 0.0 (30) 1.7 (60) 3.3 (30) 0.0 (30) 0.0 (50) 0.0 (20) 0.0 (30) 08-2015 2.0 (50) 5.0 (20) 0.0 (30) 2.6 (39) 0.0 (9) 3.3 (30) 2.0 (50) 5.0 (20) 0.0 (30) 09-2015 0.0 (34) 0.0 (4) 0.0 (30) 0.0 (34) 0.0 (4) 0.0 (30) 0.0 (30) NT 0.0 (30) 10-2015 0.0 (30) NT 0.0 (30) 0.0 (30) NT 0.0 (30) 0.0 (22) NT 0.0 (22) 11-2015 0.0 (30) NT 0.0 (30) 0.0 (5) NT 0.0 (5) 0.0 (8) NT 0.0 (8) 12-2015 0.0 (10) NT 0.0 (10) 0.0 (2) NT 0.0 (2) 0.0 (2) NT 0.0 (2) 01-2016 0.0 (12) NT 0.0 (12) 0.0 (2) 0.0 (1) 0.0 (1) 0.0 (1) NT 0.0 (1) 02-2016 0.0 (34) 0.0 (4) 0.0 (30) 0.0 (33) 0.0 (4) 0.0 (29) 0.0 (3) NT 0.0 (3)

Combined 0.3 (695) 1.0 (199) 0.0 (496) 0.9 (551) 1.3 (160) 0.8 (391) 0.9 (457) 3.0 (133) 0.0 (324) MIR = percent of pathogen positive tick samples per number of individual ticks tested (n = total individuals tested); Infection was determined by qPCR using genus-specific16S rRNA primers with species-specific dual-labeled hydrolysis probes for Ehrlichia chaffeensis and E. ewingii (Killmaster et al. 2014, Sayler et al. 2016). AWMA = Andrews Wildlife Management Area; OLEN = O’Leno State Park; SANF = San Felasco Hammock Preserve State Park; T = Total ticks (A+N); A = Adults; N = Nymphs; NT = Not tested; no ticks collected during this sampling period.

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Table 5-6. Monthly Rickettsia spp. minimum infection rates (MIR) in host-seeking lone star ticks, Amblyomma americanum, collected at three North-central Florida recreational areas between July 2014 and February 2016. AWMA OLEN SANF Month T A N T A N T A N 07-2014 62.2 (37) 61.1 (18) 63.2 (19) NT NT NT NT NT NT 08-2014 86.4 (44) 78.6 (14) 90.0 (30) 42.9 (35) 83.3 (6) 34.5 (29) 10.7 (28) 50.0 (2) 7.7 (26) 09-2014 81.3 (32) 50.0 (2) 83.3 (30) 51.6 (31) 0.0 (1) 53.3 (30) 61.3 (31) 100.0 (1) 60.0 (30) 10-2014 80.0 (30) NT 80.0 (30) 34.4 (32) 0.0 (2) 36.7 (30) 35.0 (20) NT 35.0 (20) 11-2014 77.8 (9) NT 77.8 (9) 80.0 (5) NT 80.0 (5) NT NT NT 12-2014 83.3 (6) NT 83.3 (6) 60.0 (5) NT 60.0 (5) NT NT NT 01-2015 68.6 (35) 100.0 (5) 63.3 (30) 75.0 (12) 50.0 (4) 87.5 (8) NT NT NT 02-2015 82.0 (50) 80.0 (20) 83.3 (30) 28.6 (7) NT 28.6 (7) 80.0 (5) 66.7 (3) 100.0 (2) 03-2015 71.7 (53) 60.9 (23) 80.0 (30) 37.5 (40) 40.0 (10) 36.7 (30) 54.2 (48) 44.4 (18) 60.0 (30) 04-2015 76.3 (59) 75.9 (29) 76.7 (30) 43.3 (60) 40.0 (30) 46.7 (30) 44.6 (56) 50.0 (26) 40.0 (30) 05-2015 69.4 (36) 75.0 (16) 65.0 (20) 28.3 (60) 36.7 (30) 20.0 (30) 45.0 (60) 43.3 (30) 46.7 (30) 06-2015 63.3 (60) 66.7 (30) 60.0 (30) 49.2 (59) 51.7 (29) 46.7 (30) 39.5 (43) 38.5 (13) 40.0 (30) 07-2015 81.8 (44) 92.9 (14) 76.7 (30) 28.3 (60) 26.7 (30) 30.0 (30) 42.0 (50) 40.0 (20) 43.3 (30) 08-2015 64.0 (50) 75.0 (20) 56.7 (30) 41.0 (39) 44.4 (9) 40.0 (30) 58.0 (50) 55.0 (20) 60.0 (30) 09-2015 88.2 (34) 100.0 (4) 86.7 (30) 41.2 (34) 50.0 (4) 40.0 (30) 60.0 (30) NT 60.0 (30) 10-2015 63.3 (30) NT 63.3 (30) 50.0 (30) NT 50.0 (30) 54.5 (22) NT 54.5 (22) 11-2015 73.3 (30) NT 73.3 (30) 80.0 (5) NT 80.0 (5) 50.0 (8) NT 50.0 (8) 12-2015 90.0 (10) NT 90.0 (10) 50.0 (2) NT 50.0 (2) 0.0 (2) NT 0.0 (2) 01-2016 66.7 (12) NT 66.7 (12) 50.0 (2) 100.0 (1) 0.0 (1) 0.0 (1) NT 0.0 (1) 02-2016 70.6 (34) 100.0 (4) 66.7 (30) 48.5 (33) 50.0 (4) 48.3 (29) 0.0 (3) NT 0.0 (3)

Combined 74.0 (695) 74.4 (199) 73.8 (496) 41.9 (551) 41.3 (160) 42.2 (391) 46.4 (457) 46.6 (133) 46.3 (324) MIR = percent of pathogen positive tick samples per number of individual ticks tested (n = total individuals tested); Infection was determined by qPCR using genus-specific primers and probe that target the 17-kDa antigen gene for Rickettsia spp. (Killmaster et al. 2014, Sayler et al. 2016). AWMA = Andrews Wildlife Management Area; OLEN = O’Leno State Park; SANF = San Felasco Hammock Preserve State Park; T = Total ticks (A+N); A = Adults; N = Nymphs; NT = Not tested; no ticks collected during this sampling period.

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Table 5-7. Relative risk of exposure to adult lone star ticks, Amblyomma americanum, infected with Ehrlichia chaffeensis, E. ewingii, and spotted fever group Rickettsia in North-central Florida, August 2014 to February 2016. % Infectionb ERIc Month Density (SEM)a n ECH EEW RICK ECH EEW RICK January 0.01 (0.01) 10 0.0 0.0 80.0 0.000 0.000 0.011 February 0.03 (0.01) 31 3.2 0.0 77.4 0.001 0.000 0.025 March 0.12 (0.01) 51 0.0 2.0 51.0 0.000 0.002 0.059 April 0.28 (0.02) 85 2.4 1.2 55.3 0.007 0.003 0.157 May 0.39 (0.04) 76 2.6 1.3 47.4 0.010 0.005 0.183 June 0.25 (0.03) 72 1.4 1.4 55.6 0.004 0.004 0.141 July 0.23 (0.05) 64 0.0 1.6 45.3 0.000 0.004 0.106 August 0.11 (0.02) 71 4.2 4.2 66.2 0.005 0.005 0.076 September 0.02 (0.01) 12 0.0 0.0 66.7 0.000 0.000 0.013 October 0.00 (0.00) 2 0.0 0.0 0.0 0.000 0.000 0.000 November 0.00 (0.00) 0 NT NT NT NC NC NC December 0.00 (0.00) 0 NT NT NT NC NC NC

Combined 0.1 (0.01) 474 1.9 1.7 55.9 0.002 0.002 0.055 ECH: E. chaffeensis; EEW: E. ewingii: RICK: Rickettsia spp., includes non-pathogenic and potentially pathogenic species; NT: None tested, no ticks collected during this sampling period; NC: Not calculable. a Combined mean number of adult lone star ticks per 10 m2 collected from Andrews Wildlife Management Area, O’Leno State Park, and San Felasco Hammock Preserve State Park. b Infection rate of adult lone star ticks collected from all locations. Infection was determined by qPCR using genus-specific16S rRNA primers with species-specific dual-labeled hydrolysis probes for E. chaffeensis and E. ewingii and genus-specific primers and probe that target the 17-kDa antigen gene for Rickettsia spp (Killmaster et al. 2014, Sayler et al. 2016). n = total number of ticks screened individually. c ERI is the entomological risk index and represents the number of pathogen-infected adult lone star ticks per 10 m2. It is calculated as the product of the density and the proportion of infected ticks.

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Table 5-8. Relative risk of exposure to nymphal lone star ticks, Amblyomma americanum, infected with Ehrlichia chaffeensis, E. ewingii, and spotted fever group Rickettsia in North-central Florida, August 2014 to February 2016. % Infectionb ERIc Month Density (SEM)a n ECH EEW RICK ECH EEW RICK January 0.07 (0.02) 52 0.0 0.0 65.4 0.000 0.000 0.043 February 0.18 (0.03) 101 0.0 0.0 62.4 0.000 0.000 0.111 March 1.17 (0.13) 90 1.1 0.0 58.9 0.013 0.000 0.688 April 1.97 (0.24) 90 0.0 0.0 54.4 0.000 0.000 1.073 May 2.66 (0.37) 80 1.3 1.3 41.3 0.033 0.033 1.099 June 0.81 (0.12) 90 0.0 0.0 48.9 0.000 0.000 0.394 July 0.81 (0.09) 90 0.0 0.0 50.0 0.000 0.000 0.406 August 1.20 (0.20) 175 0.6 0.6 49.1 0.007 0.007 0.591 September 2.04 (0.34) 180 1.7 0.0 63.9 0.034 0.000 1.305 October 0.80 (0.17) 162 0.0 0.6 54.3 0.000 0.005 0.435 November 0.14 (0.03) 57 0.0 0.0 71.9 0.000 0.000 0.102 December 0.03 (0.01) 25 0.0 0.0 72.0 0.000 0.000 0.024

Combined 0.92 (0.05) 1192 0.5 0.3 56.1 0.005 0.002 0.519 ECH: E. chaffeensis; EEW: E. ewingii: RICK: Rickettsia spp., includes non-pathogenic and potentially pathogenic species. a Combined mean number of nymphal lone star ticks per 10 m2 collected from Andrews Wildlife Management Area, O’Leno State Park, and San Felasco Hammock Preserve State Park. b Infection rate of nymphal lone star ticks collected from all locations. Infection was determined by qPCR using genus-specific16S rRNA primers with species-specific dual-labeled hydrolysis probes for E. chaffeensis and E. ewingii and genus-specific primers and probe that target the 17-kDa antigen gene for Rickettsia spp. (Killmaster et al. 2014, Sayler et al. 2016). n = total number of ticks screened individually. c ERI is the entomological risk index and represents the number of pathogen-infected nymphal lone star ticks per 10 m2. It is calculated as the product of the density and the proportion of infected ticks.

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Figure 5-1. North-central Florida locations sampled during a tick survey conducted between July 2014 and April 2016

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0.5 A A 0.4 2

B / 10 m 0.3 BC CD SEM ± 0.2 D D Adults Adults 0.1 E E E E E E 0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

4.0 B

2 A 3.0

AB AB

SEM/ 10 m 2.0 ± BC C CD 1.0 CD CD Nymphs Nymphs

D D D D 0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Figure 5-2. Density of lone star ticks, Amblyomma americanum, in north-central Florida. A) adults, B) nymphs, C) larvae. Ticks were collected monthly by slowly dragging a 1-m2 fleece cloth over leaf litter and low vegetation (<1-m high) in similar hardwood hammock, pine forest, or mixed hardwood/pine forest habitat at three locations in north-central Florida for a total area sampled of 60,680 m2. Data from August – December included tick collections made in 2014 and 2015. Data from January – April included tick collections made in 2015 and 2016. Data from May – July included tick collections made in 2016. Bars with different letters are significantly different (α = 0.05).

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60.00 C A 50.00 2

40.00 AB ABC

SEM/ 10 m 30.00 ± ABCD BCD 20.00 CD Larvae 10.00 D D D D D D 0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Figure 5-2. Continued.

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4.5 0.45 A 4.0 0.40

3.5 0.35

3.0 0.30 2

2.5 0.25

2.0 0.20 Adults/ Adults/ 10 m

Infection Rate % Rate Infection 1.5 0.15

1.0 0.10

0.5 0.05

0.0 0.00 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC (10) (31) (51) (85) (76) (72) (64) (71) (12) (2) (0) (0)

Figure 5-3. Temporal ehrlichial infection rates of host-seeking lone star ticks, Amblyomma americanum. A) Ehrlichia chaffeensis-infected adults, B) E. chaffeensis-infected nymphs, (C) E. ewingii-infected adults, D) E. ewingii- infected nymphs. Primary-axis line chart represents the % of infected ticks. Number in parentheses equals number of ticks tested per month. Secondary- axis area chart represents the density of the displayed life stage. Infection was determined by qPCR using genus-specific16S rRNA primers with species-specific dual-labeled hydrolysis probes for E. chaffeensis and E. ewingii (Killmaster et al. 2014, Sayler et al. 2016).

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1.8 3.0 B 1.6 2.5 1.4

1.2 2.0 2

1.0 1.5 0.8 Nymphs/ 10 m

Infection Rate % Rate Infection 0.6 1.0

0.4 0.5 0.2

0.0 0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (52) (101) (90) (90) (80) (90) (90) (175) (180) (162) (57) (25)

4.5 0.5 C 4.0 0.4

3.5 0.4

3.0 0.3 2

2.5 0.3

2.0 0.2 Adults/ Adults/ 10 m

Infection Rate % Rate Infection 1.5 0.2

1.0 0.1

0.5 0.1

0.0 0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (10) (31) (51) (85) (76) (72) (64) (71) (12) (2) (0) (0)

Figure 5-3. Continued.

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1.4 3.0 D

1.2 2.5

1.0

2.0 2 0.8 1.5 0.6 Nymphs/ 10 m

Infection Rate % Rate Infection 1.0 0.4

0.5 0.2

0.0 0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (52) (101) (90) (90) (80) (90) (90) (175) (180) (162) (57) (25)

Figure 5-3. Continued.

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90.0 0.5

80.0 0.4

70.0 0.4

60.0 0.3 2

50.0 0.3

40.0 0.2 Adults/ Adults/ 10 m

Infection Rate % Rate Infection 30.0 0.2

20.0 0.1

10.0 0.1

0.0 0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (10) (31) (51) (85) (76) (72) (64) (71) (12) (2) (0) (0)

Figure 5-4. Temporal rickettsial infection rates of host-seeking lone star ticks, Amblyomma americanum. A) Adults infected with Rickettsia spp., B) Nymphs infected with Rickettsia spp. Primary-axis line chart represents the % of infected ticks. Number in parentheses equals number of ticks tested per month. Secondary-axis area chart represents the density of the displayed life stage. Infection was determined by qPCR using genus-specific primers and probe that target the 17-kDa antigen gene for Rickettsia spp. (Killmaster et al. 2014, Sayler et al. 2016).

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80.0 3.0

70.0 2.5 60.0

2.0 2 50.0

40.0 1.5

30.0 Nymphs/ 10 m

Infection Rate % Rate Infection 1.0 20.0 0.5 10.0

0.0 0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (52) (101) (90) (90) (80) (90) (90) (175) (180) (162) (57) (25)

Figure 5-4. Continued.

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CHAPTER 6 SUMMARY AND CONCLUSION

Introduction

Ticks were the first arthropods to be confirmed as vectors of pathogens, and they

currently are the most important arthropod group to transmit pathogens in the United

States and Europe (Randolph 2010, Adams et al. 2015). Over the last three decades

the number of recognized tick-borne diseases has increased considerably globally (IOM

2011), and has doubled in North America over the same period (Paddock and Yabsley

2007). One of the tick species that has emerged as a significant public health threat in

the United States is the lone star tick, Amblyomma americanum (L.).

The lone star tick is common and aggressively bites hosts, including humans, throughout its distribution (Goddard and Varela-Stokes 2009). The tick is primarily found in the central and southeastern regions of the United States, but has expanded its range to include parts of the Atlantic Coast and Midwestern states (Springer et al. 2014). Two of the most important disease groups associated with the lone star tick include

ehrlichiosis and spotted fever group rickettsiosis. Lone star ticks are the principal vector

for ehrlichial pathogens and evidence suggests that they may play a larger role in the

transmission of rickettsioses than previously assumed (Childs and Paddock 2003,

Dahlgren et al. 2016). These two diseases have seen dramatic 4-fold and 7-fold increases in their respective national incidence rates from 2008-2012 (Drexler et al.

2016, Nichols Heitman et al. 2016). This trend is expected to continue into the future, as well as the probable emergence of additional unknown pathogens associated with this tick (Stromdahl and Hickling 2012). Reported human cases of ehrlichiosis and rickettsiosis in Florida has increased over the last decade and most often occur in areas

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that overlap with the lone star tick distribution (FL DOH 2015). Throughout the lone star

tick’s range in Florida, it can be encountered during most of the year (Rogers 1953).

Florida lacks a standardized surveillance program for identifying ehrlichial and

rickettsial infections in natural tick populations (FL DOH 2012). Instead, the FL DOH relies on passive case reporting to predict high-risk areas and communicate risk.

Studies have been conducted in Florida that provide limited information on the infection rates of ehrlichial and rickettsial pathogens in host-seeking ticks (Mixson et al. 2006,

Sayler et al. 2014, 2016) and in some Florida wildlife hosts (Yabsley et al. 2009, Beall et al. 2011, Sayler et al. 2016). The goal of the studies conducted herein was to expand upon what is known about Ehrlichia and Rickettsia pathogens associated with lone star ticks in order to better communicate risk and prevent future tick-borne diseases.

Chapter Summaries

In Chapter 2, the relative abundance and distribution of ixodid ticks associated

with nine under-sampled wildlife was determined for 66% of Florida counties. A total of

4,176 ticks were identified from black bear, bobcat, coyote, white-tailed deer, gray fox,

Florida panther, raccoon, feral swine, and wild turkey, of which, the vast majority (75%)

were lone star ticks. Other ixodid species of public health importance included the

blacklegged tick, Ixodes scapularis Say, the Gulf Coast tick, Amblyomma maculatum

Koch, the American dog tick, Dermacentor variabilis (Say), and few samples of Ixodes

affinis and Ixodes texanus. The data presented expanded tick-host relationships of

under-sampled hosts in Florida, and provided phenology and distribution records, which

may be of value to the tick-borne disease risk communication programs conducted in

the state. Ixodid tick surveys of wildlife are important studies because they provide a

glimpse of the tick species interactions that may be important to pathogen distribution

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and propagation. Additionally, surveys such as this, are better at collecting relatively rare species (e.g. I. texanus) compared to traditional drag and carbon dioxide sampling methods. Future surveys should target a greater diversity of under-sampled hosts across a wider spatial and temporal scale to provide a more accurate representation of tick species present and geographic distribution.

In Chapter 3, it was demonstrated that Florida wildlife, and associated ixodid ticks, are exposed to or infected with ehrlichial and rickettsial pathogens. Ehrlichia- reactive antibodies were detected in the five wildlife hosts examined using serological techniques, and prevalence ranged from 16.1-66.7%. One feral swine, two wild turkeys and one white-tailed deer were the only blood samples of the 515 wildlife samples tested using molecular techniques to contain ehrlichial or rickettsial DNA. A total of

1,799 ticks collected from the wildlife were subjected to the same molecular testing technique. Ehrlichial DNA was found only in lone star ticks, with E. ewingii (0.4%) being more prevalent and associated with a greater number of hosts than E. chaffeensis

(0.2%). Rickettsial DNA was detected from every tick species tested and was associated with every wildlife host. The highest rickettsial infection rates were found in blacklegged ticks (70.0%), followed by lone star ticks (42.7%), Gulf Coast ticks (29.3%), and American dog ticks (15.2%). Using conventional PCR followed by Sanger sequencing, it was determined that Rickettsia amblyommii, R. parkeri, R. rhipicephali, and rickettsial endosymbionts were the rickettsial species infecting the ticks collected from Florida wildlife. As previously stated, future studies should target a greater diversity of under-sampled hosts across a wider spatial and temporal scale. Additionally, as part of the study design, systems should be incorporated to compare engorged tick pools

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and post-molt tick pools from the same wildlife host. If planned, the data would provide

a better indication on how important one host is on the overall infection rates of ticks in

a given area.

In Chapter 4, a study to determine the relative risk of being exposed to ehrlichial

and rickettsial pathogens was conducted at eight sites throughout North-central Florida,

each containing a wildlife management area (WMA) and a state park (SP). Adult and nymphal lone star ticks were collected at each location and their densities were recorded. Genomic DNA was extracted from the lone star ticks and molecular techniques were used to determine infection with Ehrlichia chaffeensis, E. ewingii, and

Rickettsia spp. All but two sites had evidence of ehrlichial pathogens infecting lone star ticks, and we detected Rickettsia in lone star ticks at every site. The pathogen infection rates were multiplied by the lone star tick densities to compare the relative risk between sites. Overall, WMAs and SPs had similar lone star tick densities, infection rates, and relative risk, however, these data varied statistically between geographic sites. Thus,

Ehrlichia- and Rickettsia-infected lone star ticks are widely distributed throughout North- central Florida and some locations may have a higher risk profile than others. It is possible that an abundance of under-sampled hosts, or other ecological characteristics, may be positively or negatively affecting infection rates of lone star ticks across these geographic areas. Future work should elucidate commonalities in geographic ‘hot spots’ and ‘cold spots’ to see if vulnerabilities or indicators can be exposed. Expanding this work to include multiple WMAs and SPs through a voluntary tick encounter survey may provide another approach in determining pathogen hot spots across the state.

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In Chapter 5, it was determined that ehrlichial and rickettsial pathogens of lone star ticks have seasonal fluctuations in North-central Florida. Ticks were collected monthly over a 22-mo period to determine monthly densities and infection rates in order to compare monthly exposure risk. Infection rates of E. chaffeensis, E. ewingii, and

Rickettsia spp. were determined using molecular techniques. At these locations, lone star ticks were collected in every month of the year, although seasonal activity peaks differed by life stage. Adult activity was limited to between January and October, while both immature stages were collected year-round. Ehrlichial infections of lone star ticks were prevalent in all months except November, December and January, and overall infection rates were comparable to other areas within the lone star tick’s range. Ehrlichia chaffeensis infection rates ranged from 0.5-3.0% in adult lone star ticks and 0.0-1.2% in nymphal ticks at the locations surveyed, while E. ewingii infection rates ranged from 0.9-

1.3% for adults and 0.0-0.8% in nymphs. Similarly, rickettsial infection rates were comparable to other areas and ranged between 40 – 75% between sites. Based on the tick densities and infection rates in the area surveyed, the greatest exposure risk for ehrlichial pathogens occurs in May. Rickettsial exposure risk peaked in April for adult ticks and September for nymphal ticks; however, only R. amblyommii, a mildly or non- pathogenic endosymbiont, was detected using Sanger sequencing. Failure to detect rickettsial pathogens in lone star ticks does not eliminate the possibility of exposure to rickettsial pathogens. Other published works have documented the difficulties of detecting low frequency rickettsial agents in ticks, especially in ticks with prevalent rickettsial endosymbionts. Future studies should continue to explore different multifaceted methods that are able to better differentiate rickettsial species from tick

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samples. Additionally, studies attempting to explore the seasonal fluctuations of pathogens in ticks should make every effort to extend the temporal scale to account for overlapping generations within lone star tick populations. For example, lone star tick populations are composed of within-year and past-year individuals, which likely had different life histories that include alternate host blood meals, differential host disbursement of blood-fed ticks, and the inherent differing pathogen exposures as dictated by host species population infectivity levels.

Final Conclusion

Lone star ticks are important vectors in Florida. Despite the relatively low number of human cases of ehrlichiosis reported in the state, the two most important pathogens that cause the illness, E. chaffeensis and E. ewingii, are common in north central

Florida. Interestingly, E. chaffeensis was more prevalent than E. ewingii in the host- seeking ticks tested; however, the opposite was true in the ticks that were tested from the wildlife. All wildlife species tested had measurable seroprevalence to ehrlichial pathogens, indicating that Ehrlichia-infected ticks are feeding on these wildlife hosts.

Indeed, lone star ticks were the predominant tick on all hosts except coyote. Coyotes also had the lowest seroprevalence rate. Two hosts, black bear and feral swine, had higher than expected Ehrlichia-reactive antibodies but no evidence of active infection

(positive qPCR). We detected E. ewingii from wild turkey, which appears to be the first direct association reported with this wildlife host. Transmission studies should be conducted to make final conclusions about the reservoir status of black bear, feral swine, and wild turkey.

The presence of Rickettsia was more common than Ehrlichia and is ubiquitous in north central Florida, however the majority of the rickettsial species detected are

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considered mildly or non-pathogenic. For both host-seeking lone star ticks and the lone star ticks recovered from the wildlife, only R. amblyommii was identified. Rickettsia amblyommii was also detected in the blacklegged tick and the Gulf Coast tick. It is unclear if these were true infections in these tick species or if the infection was detected

in the host blood meal that had been imbibed. The infected blacklegged tick and Gulf

Coast tick were feeding on a white-tailed deer and feral swine, respectively. The feral

swine was tested for pathogens, but it was negative, although another feral swine and a

wild turkey were positive for R. amblyommii. This is believed to be first reports of R.

amblyommii infection of feral swine and wild turkey. The only pathogenic rickettsial

species detected, R. parkeri, was detected solely in Gulf Coast ticks, however the ticks

were collected from black bear, coyote, and white-tailed deer. The distribution of these

hosts and Gulf Coast ticks in Florida is statewide, however it appears that Gulf Coast

ticks may be more prevalent in south Florida. Further studies should better define the

distribution of the Gulf Coast tick and R. parkeri in Florida, and attempt to understand

the role of wildlife in rickettsial maintenance cycles.

Finally, ehrlichial and rickettsial infections vary spatially and temporally. This

makes the prospect of communicating the true risk of exposure in the state difficult

without continuous surveillance of host-seeking ticks and their wildlife hosts. It is unclear

what abiotic (e.g. sample technique) and biotic (e.g. host movement) ecological factors

influence this spatial and temporal variation. The public health infrastructure should

include funding and/or systems to coordinate clinical and entomological surveillance

efforts across the state in an attempt to better define exposure risk. In doing so, the

general public could make better-informed risk decisions based on the exposure risks in

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their area. Additionally, clinical practitioners could have region-specific clinical flow charts that incorporate the primary tick-borne disease risk in the area, which could decrease diagnosis times and increase accurate reporting of tick-borne disease.

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APPENDIX A SAMPLE LOCATION HABITAT AND RECREATION DESCRIPTIONS

Andrews Wildlife Management Area (FL FWC 2004): Located in western Levy County. It is 3,501 acres of primarily unaltered contiguous hardwood hammock forests with xeric and mesic vegetative communities within close proximity of one another, but also contains areas of hydric communities bordering the Suwannee River. Recreation activities include hunting, fishing, wildlife viewing, biking, hiking, scenic driving, paddling, and picnicking. Ticks during this survey were collected in upland hardwood forest habitat (FL FWCFNAI 2014).

Camp Blanding Wildlife Management Area (FL FWC 2016): Located in Clay County. The 56,197 acres consists primarily of planted pine plantations with remnant mature pines in the northern areas and sandhills in the southern areas. Bottomland hardwood forests occur along the headwaters of Black Creek. This area is used primarily for military training throughout most of the year. Public recreation is allowed for fishing and hunting during specified periods. Ticks during this survey were collected in sandhill and mixed hardwood-coniferous forest habitat (FL FWCFNAI 2014).

DeLeon Springs State Park (FL DEP 2006): Located in Volusia County. The park contains 606 acres, of which 297 acres is wetland. The upland areas surrounding the springs include mixed forest, xeric hammock, and mesic flatwood habitat. The primary recreational activity is swimming in the Ponce De Leon headspring, but other activities include picnicking, hiking, fishing, paddling, power boating and nature observation. Ticks during this survey were collected in mixed wetland forest habitat (FL FWCFNAI 2014).

Dexter Mary Wildlife Management Area (FL AGCS/FFS 2015): Located in Volusia County. This 14,377-acre WMA is located within Lake George State Forest. The area is covered with ecological communities include mesic flatwoods, floodplain wetlands, sandhills, and interspersed cypress and bay depressions. Recreational activities include fishing, hunting, nature study, geo-caching, and hiking, biking, and equestrian trails. Ticks during this survey were collected in mixed wetland forest habitat (FL FWCFNAI 2014).

Dunns Creek State Park (FL DEP 2004a): Located in Putnam County. The park is 6,222 acres and park contains 21 distinct natural communities. Hiking and fishing are the primary recreational activities. Ticks during this survey were collected in sandhill and mixed hardwood habitats (FL FWCFNAI 2014).

Dunns Creek Wildlife Management Area (SJRWMD 2013). Located in Putnam County. The 3,155 acres that comprise this area consists primarily of floodplain swamp and a diverse array of other natural communities dominated by mesic flatwoods. Recreational activities include open to the public for hunting, hiking, bicycling, equestrian activities, and primitive camping. Ticks during this survey were collected in mesic flatwood habitat (FL FWCFNAI 2014).

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Flying Eagle Wildlife Management Area (SWFWMD 2011). Located in west-central Citrus County. The area is comprised of 5,701 acres of mesic hammock and other forested uplands with smaller areas of pasture and other habitat, including wetland communities along the Withlacoochee River. Recreational activities include cycling, birding, backpacking, equestrian riding, hiking, hunting, geocaching, interpretive uses, nature study and photography. Ticks during this survey were collected in sandhill and mixed hardwood-coniferous forest habitats (FL FWCFNAI 2014).

Fort Cooper State Park(FL DEP 2015): Located in Citrus County. This area comprises 734 acres of diverse wildlife habitat, including hardwood hammocks, basin marsh, and sandhill. Recreational activities include swimming, paddling, fishing, picnicking, hiking, nature study, and annual interpretive reenactments of the Second Seminole War. Ticks during this survey were collected in mesic hammock habitat (FL FWCFNAI 2014).

Goethe Wildlife Management Area (FL AGCS/FFS 2013): Located in both Levy and Alachua Counties. This 53,587-acre state forest contains one of the largest longleaf- pine flatwoods communities in Florida, and includes other natural communities such as scrubby flatwoods, dome swamp, sandhill, and basin swamp. Recreation opportunities include an extensive system of equestrian and hiking trails, camping, hunting, fishing and picnicking sites. Ticks during this survey were collected in mesic flatwood habitat (FL FWCFNAI 2014).

Lochloosa Wildlife Management Area (SJRWMD 2007): Located in Alachua County. The 10,338 acres WMA consists primarily of pine plantations, basin marsh, and floodplain swamp. Recreational activities include hiking, biking, camping, wildlife viewing, photography, seasonal hunting and equestrian activities. Ticks during this survey were collected in coniferous plantation forest habitat (FL FWCFNAI 2014).

Mike Roess Gold Head Branch State Park (FL DEP 2010): Located in Clay County. Over 2,366 acres contains 13 distinct natural communities, including a ravine system. The mesic flatwoods and xeric hammock are the primary habitats surrounding the ravine system, but the park consists mostly of sandhill habitat. Recreational activities include nature study and picnicking, hiking, camping, swimming, boating and fishing. Ticks during this survey were collected in upland hardwood forest habitat (FL FWCFNAI 2014).

Manatee Springs State Park (FL DEP 2004b): Located in Levy County. The 2,443 acres of natural communities include bottomland forest, floodplain forest, floodplain swamp and sinkholes. Recreational activities are centered on the developed swimming area in the spring, and boating and fishing on the spring run. Camping sites and hiking trails are located in the upland mixed forest and xeric hammock habitat in the park. Ticks during this survey were collected in mixed hardwood-coniferous forest habitat (FL FWCFNAI 2014).

Marjorie Kinnan Rawlings State Park (FL DEP 2008): Located within Alachua County. This historic homestead sits on 99 acres and contains one of the few remaining

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wooded, undeveloped wildlife corridors between Orange Lake and Lochloosa Lake. Outside the farmyard property, the habitat includes some upland mixed forest, mesic flatwoods, basin marsh, basin swamp and depression marsh communities. The primary recreation use is visiting the house and surrounding grounds, which includes two hiking trails through the woodland community. Ticks during this survey were collected in mixed wetland hardwood and mixed hardwood-coniferous habitats (FL FWCFNAI 2014).

O’leno State Park (FL FWC 2003): Located on the border of Alachua and Columbia Counties, and intersected by the Santa Fe River. Eighteen diverse natural communities comprise the 6,215 acres of O’leno and River Rise Hammock State Park. Recreational activities include nature study, fishing, paddling, camping, and boasts an extensive system of hiking, off-road biking and equestrian trails. The areas sampled in this study were restricted to areas around the O’leno State Park developed area and the areas around the Rivers Rise Hammock State Park horse stables. These areas primarily consisted of upland mixed forest, pine forest, and wetland habitat.

San Felasco Hammock Preserve State Park (FL DEP 2005): Located in Alachua county. Considered the most diverse and complex community in north-central Florida, encompassing 6,927-acres of upland and wetland natural areas, including upland mixed forest, sandhill communities, and pastureland. Recreational activities include hiking, off- road biking, horseback riding, horse carriage events, picnicking and nature study. This area included 189 acres of the City of Gainesville San Felasco Park, which had similar upland and wetland natural areas offering hiking and picnicking recreational activities.

Seminole Forest Wildlife Management Area (FL AGCS/FFS 2011): Located in Lake County. The 27,082 acres contains almost all of the natural communities found in Central Florida, including mesic flatwoods, hydric hammocks, scrub, and sandhill. Recreation activities include hiking, horseback riding, fishing, primitive camping, off-road bicycling, hunting, paddling, and nature study. Ticks during this survey were collected in mesic flatwood habitat (FL FWCFNAI 2014).

Wekiwa Springs State Park (FL DEP 2012): Located in Orange County. Contains five distinct natural communities, with lone star tick habitat consisting primarily of upland mixed woodland and mesic flatwoods. Swimming is a popular recreational activity, but other activities include paddling, nature study, camping, hiking, off-road bicycling, and horseback riding. Ticks during this survey were collected in sandhill and mixed woodland habitat (FL FWCFNAI 2014). .

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APPENDIX B SUPPLEMENTARY TABLES

Table B-1. Summary of microbes, proteins, and toxins detected in, or associated with, lone star ticks, Amblyomma americanuma Group Causative Agent Associated Disease Reference Bacteria Coxiella burnettii Q Fever Parker and Kohls 1943 Ehrlichia chaffeensis Ehrlichia chaffeensis infectionb Ewing et al. 1995 Varela-Stokes 2007 Ehrlichia ewingii Ehrlichia ewingii infection Anziani et al. 1990 Ehrlichia spp., Panola Mountain (PME) Undetermined ehrlichiosis Killmaster et al. 2014 Loftis et al. 2006 Loftis, Levin, et al. 2008 Yabsley et al. 2008 Francisella tularensis Tularemia Hopla 1960 Rickettsia amblyommii Spotted fever rickettsiosis Apperson et al. 2008 Billeter et al. 2007 Rickettsia massilae Spotted fever rickettsiosis Clay et al. 2008 Rickettsia parkeri Spotted fever rickettsiosis Goddard 2003 Gaines et al. 2014 Cohen et al. 2009 Rickettsia rickettsii Spotted fever rickettsiosis Berrada et al. 2011 Burgdorfer and Brinton 1975 Maver 1911 Parker et al. 1933 Rickettsia texianac Bullis Fever Woodland et al. 1943 Unknown Southern Tick-Associated Rash Illness (STARI) Masters et al. 2008

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Table B-1. Continued Group Causative Agent Associated Disease Reference Viruses Bourbon virus Not yet named Kosoy et al. 2015 Dugbe virus Nairobi sheep disease Linthicum et al. 1989 Heartland virus Not yet named Savage et al. 2013 “Long Island tick rhabdovirus” Not implicated Tokarz et al. 2014 Lone star virus Not implicated Kokernot et al. 1969 Tacaribe virus (FL isolate) Not implicated Sayler et al. 2014 Unnamed enterovirus Aseptic meningitis Freundt et al. 2005

Protozoa Babesia cervi (= B. odocoilei) Babesiosis Emerson 1969 Toxoplasma gondii Toxoplasmosis Woke et al. 1953 Theileria cervi Theileriosis Barker et al. 1973 Kuttler et al. 1967 Trypanosoma spp. Not implicated Krinsky and Burgdorfer 1976

Other Tick proteins Red meat allergy Commins et al. 2011 Wolver et al. 2012 Toxins Tick paralysis Swartzwelder and Seabury 1947 a Expanded from Goddard and Varela-Stokes (2009) b Formally Human Monocytic Ehrlichiosis (HME) c No laboratory isolates exist today, nor has the disease reappeared; some believe Bullis Fever was caused by E. chaffeensis (Bavaro et al. 2005)

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Table B-2. Geographic coordinates of areas sampled during a tick survey in May 2015 at Florida state parks and wildlife management areas. Date Location Start Timea End Timeb Cum. Timec Total Area (m2)d Latitudee Longitudef 05/18/15 Lochloosa WMA 9:16 10:22 1:06 400 29.47765 -82.15943 05/18/15 Marjorie Kinnan Rawlings SP 11:40 NA NA NA 29.48143 -82.16289 05/18/15 Marjorie Kinnan Rawlings SP NA 12:30 0:50 400 29.48141 -82.15772 05/19/15 Manatee Springs SP 9:10 10:15 1:05 400 29.48664 -82.97471 05/19/15 Andrews WMA 12:10 13:20 1:10 400 29.55066 -82.94063 05/20/15 Goethe WMA 8:45 9:35 0:50 400 29.30674 -82.60432 05/20/15 Rainbow Springs SP 12:00 12:55 0:55 400 29.09811 -82.43273 05/21/15 Fort Cooper SP 8:47 10:10 1:23 400 28.80707 -82.30696 05/21/15 Flying Eagle WMA 12:00 13:08 1:08 400 28.82137 -82.24725 05/23/15 Weikawa Springs SP 9:20 10:11 0:51 400 28.71384 -81.47918 05/23/15 Seminole Forest WMA 13:00 14:07 1:07 400 28.87595 -81.44307 05/24/15 Dexter/Mary Farms WMA 7:54 8:50 0:56 400 29.13296 -81.49167 05/24/15 De Leon Spring State Park 10:25 11:00 0:35 400 29.13887 -81.37520 05/25/15 Dunns Creek SP 8:33 9:24 0:51 400 29.52146 -81.62534 05/25/15 Dunns Creek WMA 11:00 11:40 0:40 400 29.57099 -81.57852 05/26/15 Camp Blanding WMA 9:48 10:35 0:47 400 29.82368 -82.01035 05/26/15 Mike Roess Gold Head Branch SP 11:30 12:29 0:59 400 29.83980 -81.95337 05/27/15 Marjorie Kinnan Rawlings SP 9:04 NA NA NA 29.48151 -82.16300 05/27/15 Marjorie Kinnan Rawlings SP NA 10:10 1:06 400 29.48124 -82.15746 05/27/15 Lochloosa WMA 11:42 12:30 0:48 400 29.47570 -82.15744 NA = Not applicable a Start time (24-hr clock) for tick collection at specified location. b End time (24-hr clock) for tick collection at specified location. c Cumulative time (h:mm) for tick collection at specified location. d Ticks were collected slowly dragging a 1-m2 fleece cloth over leaf litter and low vegetation (<1-m high) in similar habitat. The fleece cloth was checked every 10 m and all attached ticks were removed. eWorld Geodetic System 1984 Latitude. f World Geodetic System 1984 Longitude.

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Table B-3. Geographic coordinates of areas sampled during a tick survey between July 2014 and April 2016 at three North-central Florida locations. # Collection codea Date Timeb Latitudec Longituded UTM Ee UTM Nf Total Area (M2)g 1 0714AWMA01 7/22/2014 ND ND ND ND ND 100 2 0714AWMA02 7/22/2014 ND ND ND ND ND 100 3 0814AWMA01 8/6/2014 ND ND ND ND ND 100 4 0814AWMA02 8/6/2014 ND ND ND ND ND 100 5 0814AWMA03 8/6/2014 ND ND ND ND ND 100 6 0814AWMA04 8/6/2014 ND ND ND ND ND 100 7 0814AWMA05 8/6/2014 ND ND ND ND ND 100 8 0814AWMA06 8/6/2014 ND ND ND ND ND 100 9 0814AWMA07 8/6/2014 ND ND ND ND ND 100 10 0814AWMA08 8/6/2014 ND ND ND ND ND 100 11 0814OLEN01 8/13/2014 0910 29.90845 -82.58361 347115 3309695 200 12 0814OLEN02 8/13/2014 1000 29.90835 -82.58162 347307 3309681 200 13 0814OLEN03 8/13/2014 1045 29.91348 -82.58136 347340 3310249 200 14 0814SANF01 8/13/2014 1718 29.71208 -82.46061 358715 3287775 200 15 0814SANF02 8/13/2014 1300 29.71156 -82.46028 358746 3287717 200 16 0914AWMA01 9/9/2014 0935 29.56400 -82.94024 312037 3272045 200 17 0914AWMA02 9/9/2014 1025 29.55988 -82.94056 311999 3271589 200 18 0914AWMA03 9/9/2014 1105 29.55798 -82.94615 311453 3271388 100 19 0914AWMA04 9/9/2014 1120 29.55802 -82.94617 311451 3271392 200 20 0914AWMA05 9/9/2014 1150 29.54525 -82.94032 311995 3269967 200 21 0914AWMA06 9/9/2014 1230 29.54182 -82.94798 311246 3269600 200 22 0914SANF01 9/17/2014 ND 29.71228 -82.46069 358707 3287797 200 23 0914SANF02 9/17/2014 ND 29.71149 -82.46020 358754 3287709 200 24 0914SANF03 9/17/2014 1118 29.70991 -82.45692 359069 3287530 200 25 0914OLEN01 9/19/2014 0930 29.91796 -82.59643 345891 3310766 200 26 0914OLEN02 9/19/2014 1025 29.90843 -82.58371 347105 3309692 220 27 0914OLEN03 9/19/2014 1110 29.90842 -82.58152 347316 3309688 200 28 0914OLEN04 9/19/2014 1145 29.91345 -82.58147 347329 3310246 200

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Table B-3. Continued. # Collection codea Date Timeb Latitudec Longituded UTM Ee UTM Nf Total Area (M2)g 29 0914OLEN05 9/19/2014 1220 29.91358 -82.58305 347177 3310262 130 30 1014AWMA01 10/7/2014 0955 29.55966 -82.93115 312910 3271550 200 31 1014AWMA02 10/7/2014 1033 29.55993 -82.93185 312843 3271581 270 32 1014AWMA03 10/7/2014 1130 29.55462 -82.94285 311767 3271010 230 33 1014AWMA04 10/7/2014 1211 29.54685 -82.94035 311995 3270145 210 34 1014AWMA05 10/7/2014 1330 29.54462 -82.93105 312892 3269882 280 35 1014OLEN01 10/16/2014 0946 29.91704 -82.60210 345343 3310671 200 36 1014OLEN02 10/16/2014 1025 29.90890 -82.58324 347151 3309744 200 37 1014OLEN03 10/16/2014 1115 29.90864 -82.58201 347269 3309714 200 38 1014OLEN04 10/16/2014 1156 29.91286 -82.58151 347324 3310180 200 39 1014OLEN05 10/16/2014 1231 29.91871 -82.59249 346273 3310844 200 40 1014SANF01 10/23/2014 1133 29.71336 -82.46115 358664 3287917 110 41 1014SANF02 10/23/2014 1201 29.71348 -82.46229 358554 3287932 100 42 1014SANF03 10/23/2014 1220 29.71383 -82.46310 358476 3287972 100 43 1014SANF04 10/23/2014 1300 29.71238 -82.46071 358706 3287808 180 44 1114AWMA01 11/4/2014 1022 29.55987 -82.92669 313343 3271566 115 45 1114AWMA02 11/4/2014 1049 29.56778 -82.94043 312026 3272465 110 46 1114AWMA03 11/4/2014 1116 29.56431 -82.94021 312041 3272080 100 47 1114AWMA04 11/4/2014 1133 29.55866 -82.94608 311461 3271463 120 48 1114AWMA05 11/4/2014 1210 29.53837 -82.96575 309517 3269246 240 49 1114OLEN01 11/14/2014 1330 ND ND ND ND 200 50 1114OLEN02 11/14/2014 1350 ND ND ND ND 500 51 1114OLEN03 11/14/2014 1500 ND ND ND ND 100 52 1114OLEN04 11/14/2014 1515 ND ND ND ND 100 53 1114OLEN05 11/14/2014 1520 ND ND ND ND 150 54 1114SANF01 11/13/2014 1240 29.77336 -82.47562 357350 3294585 400 55 1114SANF02 11/13/2014 1430 29.71066 -82.39298 365255 3287537 160 56 1214AWMA01 12/3/2014 0958 29.55975 -82.93118 312907 3271560 170 57 1214AWMA02 12/3/2014 1023 29.56037 -82.94019 312035 3271643 210

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Table B-3. Continued. # Collection codea Date Timeb Latitudec Longituded UTM Ee UTM Nf Total Area (M2)g 58 1214AWMA03 12/3/2014 1053 29.55485 -82.94288 311764 3271035 200 59 1214AWMA04 12/3/2014 1119 29.54891 -82.94106 311930 3270374 300 60 1214AWMA05 12/3/2014 1151 29.54341 -82.94007 312016 3269763 120 61 1214OLEN01 12/4/2014 1013 29.91739 -82.59770 345768 3310704 250 62 1214OLEN02 12/4/2014 1047 29.91731 -82.59019 346493 3310685 250 63 1214OLEN03 12/4/2014 1121 29.91165 -82.58572 346916 3310052 200 64 1214OLEN04 12/4/2014 1154 29.90898 -82.58353 347123 3309753 200 65 1214OLEN05 12/4/2014 1229 29.91329 -82.58087 347387 3310227 150 66 1214SANF01 12/16/2014 1030 29.71075 -82.39257 365295 3287546 400 67 1214SANF02 12/16/2014 1143 29.77172 -82.47242 357657 3294399 300 68 1214SANF03 12/16/2014 1400 29.71258 -82.46098 358680 3287831 300 69 0115AWMA01 1/21/2015 1110 29.55985 -82.92364 313638 3271559 300 70 0115AWMA02 1/21/2015 1200 29.55991 -82.93173 312854 3271578 300 71 0115AWMA03 1/21/2015 1305 29.54334 -82.93817 312200 3269752 400 72 0115OLEN01 1/22/2015 1035 29.91288 -82.58305 347175 3310185 300 73 0115OLEN02 1/22/2015 1130 29.91337 -82.58067 347406 3310236 300 74 0115OLEN03 1/22/2015 1225 29.91757 -82.59021 346491 3310714 400 75 0115SANF01 1/14/2015 1400 29.77329 -82.47568 357344 3294577 250 76 0115SANF02 1/14/2015 1455 29.71036 -82.48504 356349 3287614 250 77 0115SANF03 1/14/2015 1545 29.71223 -82.46066 358710 3287792 500 78 0215AWMA01 2/16/2015 1144 29.53327 -82.96585 309498 3268681 350 79 0215AWMA02 2/16/2015 1326 29.55652 -82.94265 311790 3271220 350 80 0215AWMA03 2/16/2015 1430 29.56043 -82.87942 317924 3271553 300 81 0215OLEN01 2/11/2015 1100 29.96882 -82.60155 345476 3316409 350 82 0215OLEN02 2/11/2015 1200 29.91982 -82.59998 345552 3310977 300 83 0215OLEN03 2/11/2015 1240 29.91020 -82.58183 347289 3309886 350 84 0215SANF01 2/12/2015 1048 29.71382 -82.39172 365382 3287885 300 85 0215SANF02 2/12/2015 1125 29.72012 -82.39258 365307 3288585 400 86 0215SANF03 2/12/2015 1247 29.71170 -82.45705 359059 3287728 300

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Table B-3. Continued. # Collection codea Date Timeb Latitudec Longituded UTM Ee UTM Nf Total Area (M2)g 87 0315AWMA01 3/3/2015 1130 29.57468 -82.94026 312055 3273229 350 88 0315AWMA02 3/3/2015 1217 29.56226 -82.94019 312039 3271852 350 89 0315AWMA03 3/3/2015 1322 29.54722 -82.94004 312025 3270185 300 90 0315OLEN01 3/4/2015 0918 29.91939 -82.59000 346514 3310916 350 91 0315OLEN02 3/4/2015 1016 29.91035 -82.58149 347322 3309902 350 92 0315OLEN03 3/4/2015 1128 29.91273 -82.57894 347572 3310163 300 93 0315SANF01 3/17/2015 1026 29.71385 -82.39184 365370 3287889 300 94 0315SANF02 3/17/2015 1159 29.71437 -82.46064 358715 3288029 400 95 0315SANF03 3/17/2015 1319 29.71586 -82.45956 358822 3288193 300 96 0415AWMA01 4/14/2015 1104 29.56166 -82.92355 313650 3271759 350 97 0415AWMA02 4/14/2015 1207 29.55668 -82.94289 311767 3271238 350 98 0415AWMA03 4/14/2015 1324 29.54521 -82.93992 312033 3269962 300 99 0415OLEN01 4/8/2015 0955 29.91485 -82.58287 347196 3310403 300 100 0415OLEN02 4/8/2015 1052 29.91523 -82.58049 347426 3310442 300 101 0415OLEN03 4/8/2015 1242 29.84570 -82.63387 342163 3302808 400 102 0415SANF01 4/11/2015 1114 29.71259 -82.39292 365264 3287751 300 103 0415SANF02 4/11/2015 1214 29.77798 -82.47622 357298 3295097 400 104 0415SANF03 4/11/2015 1342 29.71427 -82.46103 358677 3288018 300 105 0515AWMA01 5/19/2015 1208 29.55059 -82.94081 311957 3270560 400 106 0515AWMA02 5/19/2015 1327 29.55052 -82.94099 311940 3270552 300 107 0515AWMA03 5/19/2015 1426 29.56046 -82.94283 311780 3271657 300 108 0515OLEN01 5/11/2015 1013 29.91895 -82.60171 345383 3310883 300 109 0515OLEN02 5/11/2015 1108 29.91272 -82.57903 347563 3310162 400 110 0515OLEN03 5/11/2015 1215 29.91038 -82.58347 347131 3309908 300 111 0515SANF01 5/7/2015 1016 29.71333 -82.45894 358878 3287911 300 112 0515SANF02 5/7/2015 1125 29.72005 -82.39233 365331 3288577 300 113 0515SANF03 5/7/2015 1235 29.71611 -82.45901 358875 3288220 400 114 0615AWMA01 6/12/2015 1015 29.56197 -82.93144 312886 3271806 400

148

Table B-3. Continued. # Collection codea Date Timeb Latitudec Longituded UTM Ee UTM Nf Total Area (M2)g 115 0615AWMA02 6/12/2015 1144 29.55985 -82.94602 311469 3271595 300 116 0615AWMA03 6/12/2015 1243 29.54654 -82.93102 312898 3270095 300 117 0615OLEN01 6/5/2015 0952 29.92127 -82.59066 346454 3311125 400 118 0615OLEN02 6/5/2015 1117 29.91538 -82.58160 347319 3310460 300 119 0615OLEN03 6/5/2015 1222 29.90831 -82.58291 347182 3309678 300 120 0615SANF01 6/23/2015 0941 29.71555 -82.39193 365364 3288077 300 121 0615SANF02 6/23/2015 1054 29.77374 -82.46916 357975 3294619 300 122 0615SANF03 6/23/2015 1213 29.71675 -82.46366 358426 3288296 400 123 0715AWMA01 7/21/2015 0941 29.56204 -82.93414 312625 3271818 300 124 0715AWMA02 7/21/2015 1028 29.54847 -82.93966 312065 3270323 400 125 0715AWMA03 7/21/2015 1139 29.54503 -82.95627 310449 3269969 300 126 0715OLEN01 7/22/2015 0914 29.91035 -82.58103 347367 3309902 400 127 0715OLEN02 7/22/2015 1125 29.91919 -82.58996 346518 3310893 300 128 0715OLEN03 7/22/2015 1208 29.91947 -82.59021 346494 3310925 300 129 0715SANF01 7/23/2015 1016 29.71176 -82.39197 365355 3287657 300 130 0715SANF02 7/23/2015 1104 29.71434 -82.46098 358682 3288026 400 131 0715SANF03 7/23/2015 1210 29.71780 -82.45652 359118 3288404 300 132 0815AWMA01 8/11/2015 0952 29.54469 -82.93966 312058 3269904 300 133 0815AWMA02 8/11/2015 1049 29.56990 -82.9403 312042 3272699 400 134 0815AWMA03 8/11/2015 1202 29.55330 -82.94225 311823 3270863 300 135 0815OLEN01 8/13/2015 0940 29.91508 -82.58324 347160 3310429 300 136 0815OLEN02 8/13/2015 1048 29.91268 -82.57943 347525 3310158 400 137 0815OLEN03 8/13/2015 1155 29.84898 -82.63297 342255 3303170 300 138 0815SANF01 8/12/2015 0922 29.77525 -82.47549 357365 3294794 300 139 0815SANF01b 8/12/2015 0935 29.77778 -82.47607 357312 3295075 300 140 0815SANF02 8/12/2015 1049 29.71320 -82.45888 358884 3287897 400 141 0815SANF03 8/12/2015 1201 29.71952 -82.46366 358430 3288603 300 142 0915AWMA01 9/14/2015 1028 29.54381 -82.95446 310622 3269831 400

149

Table B-3. Continued. # Collection codea Date Timeb Latitudec Longituded UTM Ee UTM Nf Total Area (M2)g 143 0915AWMA02 9/14/2015 1119 29.56094 -82.94616 311458 3271716 300 144 0915AWMA03 9/14/2015 1311 29.56704 -82.94330 311746 3272387 300 145 0915OLEN01 9/15/2015 0846 29.91930 -82.59826 345717 3310917 400 146 0915OLEN02 9/15/2015 1123 29.91361 -82.58483 347005 3310268 300 147 0915OLEN03 9/15/2015 1215 29.91571 -82.58370 347117 3310499 300 148 0915SANF01 9/21/2015 1011 29.71189 -82.39400 365158 3287674 300 149 0915SANF02 9/21/2015 1113 29.72108 -82.45488 359282 3288765 400 150 0915SANF03 9/21/2015 1226 29.71046 -82.45730 359033 3287591 300 151 1015AWMA01 10/12/2015 1011 29.56266 -82.93770 312281 3271893 300 152 1015AWMA02 10/12/2015 1115 29.55931 -82.94320 311742 3271530 300 153 1015AWMA03 10/12/2015 1212 29.54517 -82.93797 312222 3269955 400 154 1015OLEN01 10/15/2015 1039 29.91047 -82.58171 347301 3309916 300 155 1015OLEN02 10/15/2015 1148 29.91543 -82.58098 347379 3310465 300 156 1015OLEN03 10/15/2015 1308 29.84900 -82.63373 342182 3303174 400 157 1015SANF01 10/20/2015 1054 29.71027 -82.45660 359100 3287569 300 158 1015SANF02 10/20/2015 1152 29.71854 -82.46356 358439 3288494 300 159 1015SANF03 10/20/2015 1407 29.71578 -82.39237 365321 3288103 400 160 1115AWMA01 11/3/2015 1031 29.56517 -82.94007 312056 3272175 300 161 1115AWMA02 11/3/2015 1129 29.54541 -82.94004 312022 3269985 400 162 1115AWMA03 11/3/2015 1229 29.55987 -82.94302 311760 3271592 300 163 1115OLEN01 11/12/2015 0955 29.91902 -82.60192 345363 3310891 300 164 1115OLEN02 11/12/2015 1046 29.91014 -82.58388 347091 3309882 300 165 1115OLEN03 11/12/2015 1203 29.91958 -82.59016 346499 3310937 400 166 1115SANF01 11/18/2015 1045 29.71569 -82.46031 358749 3288175 400 167 1115SANF02 11/18/2015 1139 29.71432 -82.46061 358718 3288023 300 168 1115SANF03 11/18/2015 1250 29.71345 -82.38993 365554 3287842 300 169 1215AWMA01 12/8/2015 1056 29.56183 -82.92366 313640 3271778 300 170 1215AWMA02 12/8/2015 1150 29.54017 -82.96656 309442 3269447 400

150

Table B-3. Continued. # Collection codea Date Timeb Latitudec Longituded UTM Ee UTM Nf Total Area (M2)g 171 1215AWMA03 12/8/2015 1237 29.56849 -82.94016 312053 3272543 300 172 1215OLEN01 12/7/2015 1036 29.91281 -82.57896 347570 3310172 300 173 1215OLEN02 12/7/2015 1134 29.91922 -82.59000 346514 3310897 400 174 1215OLEN03 12/7/2015 1205 29.91942 -82.59012 346503 3310919 300 175 1215SANF01 12/11/2015 1057 29.77272 -82.46879 358009 3294505 300 176 1215SANF02 12/11/2015 1206 29.71178 -82.39186 365365 3287660 300 177 1215SANF03 12/11/2015 1334 29.71750 -82.46370 358424 3288379 400 178 0116AWMA01 1/6/2016 1105 29.56174 -82.93307 312727 3271783 300 179 0116AWMA02 1/6/2016 1142 29.55662 -82.94274 311781 3271231 400 180 0116AWMA03 1/6/2016 1224 29.55615 -82.93797 312242 3271171 300 181 0116SANF01 1/7/2016 1115 29.71397 -82.46098 358681 3287984 300 182 0116SANF02 1/7/2016 1203 29.71519 -82.46114 358667 3288120 400 183 0116SANF03 1/7/2016 1300 29.71258 -82.39280 365275 3287749 300 184 0116OLEN01 1/12/2016 1153 29.84905 -82.63380 342174 3303179 300 185 0116OLEN02 1/12/2016 1253 29.91902 -82.59818 345724 3310885 400 186 0116OLEN03 1/12/2016 1351 29.91041 -82.58341 347136 3309911 300 187 0216SANF01 2/16/2016 1215 29.71856 -82.45573 359195 3288487 400 188 0216SANF02 2/16/2016 1253 29.71519 -82.46218 358567 3288121 300 189 0216SANF03 2/16/2016 1350 29.77824 -82.47630 357290 3295126 300 190 0216AWMA01 2/17/2016 1054 29.56236 -82.94023 312035 3271863 400 191 0216AWMA02 2/17/2016 1148 29.55353 -82.94243 311805 3270888 300 192 0216AWMA03 2/17/2016 1229 29.54545 -82.93952 312072 3269988 300 193 0216OLEN01 2/18/2016 1021 29.91351 -82.58588 346903 3310258 400 194 0216OLEN02 2/18/2016 1133 29.92113 -82.59071 346448 3311109 300 195 0216OLEN03 2/18/2016 1302 29.84452 -82.63126 342413 3302673 300 196 0316AWMA01 3/22/2016 1056 29.54033 -82.96425 309666 3269460 400 197 0316AWMA02 3/22/2016 1155 29.55980 -82.94586 311484 3271588 300 198 0316AWMA03 3/22/2016 1253 29.57222 -82.94023 312053 3272956 300

151

Table B-3. Continued. # Collection codea Date Timeb Latitudec Longituded UTM Ee UTM Nf Total Area (M2)g 199 0316SANF01 3/28/2016 1058 29.71105 -82.46031 358742 3287660 400 200 0316SANF02 3/28/2016 1156 29.71171 -82.45882 358887 3287731 300 201 0316SANF03 3/28/2016 1241 29.71544 -82.46049 358731 3288147 300 202 0316OLEN01 3/31/2016 1025 29.91831 -82.60264 345292 3310812 300 203 0316OLEN02 3/31/2016 1118 29.91461 -82.58130 347347 3310374 300 204 0316OLEN03 3/31/2016 1222 29.90996 -82.58135 347335 3309858 400 205 0416AWMA01 4/13/2016 1117 29.56023 -82.94604 311468 3271636 300 206 0416AWMA02 4/13/2016 1243 29.54637 -82.93087 312912 3270076 400 207 0416AWMA03 4/13/2016 1405 29.55092 -82.94101 311938 3270596 300 208 0416OLEN01 4/18/2016 1053 29.91979 -82.59137 346382 3310961 300 209 0416OLEN02 4/18/2016 1157 29.91524 -82.58067 347408 3310443 400 210 0416OLEN03 4/18/2016 1324 29.84771 -82.63402 342151 3303031 300 211 0416SANF01 4/20/2016 1117 29.71381 -82.39177 365376 3287884 300 212 0416SANF02 4/20/2016 1216 29.77449 -82.47185 357715 3294705 300 213 0416SANF03 4/20/2016 1413 29.71969 -82.46441 358357 3288622 400 ND = No data; not collected #1-10; data lost #22-23; equipment failure #49-53. a Collection Code: DATE_LOCATION_SITEID; Date in MM-YYYY format, site either AWMA (Andrews Wildlife Management Area), OLEN (O’Leno State Park), SANF (San Felasco Hammock Preserve State Park), SITEID is unique location within location where ticks were sampled 01-08. b Start time (24-hr clock) for tick collection at specified location. c World Geodetic System 1984 Latitude. d World Geodetic System 1984 Longitude. e Universal Transverse Mercator 17 Easting. f Universal Transverse Mercator 17 Northing. g Total area sampled. Tick collections began as a ‘pilot’ study (#1-65). Area sampled during this time was very inconsistent (200 – 3050 m) and consisted of multiple sites. Methods standardized (#>65) to encompass 1000 m per location consisting of 300-400 m subsamples from three sites.

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BIOGRAPHICAL SKETCH

Jeffrey Conrad Hertz was born in Peoria, Illinois. He spent his entire childhood in

Fulton County, Illinois, a rural community known for exceptional hunting and fishing

opportunities. In 1994, he graduated Lewistown Community High School and enlisted in

the United States Navy as a Hospital Corpsman. Throughout his enlisted career, he

served with the United States Marine Corps, at Naval Medical Centers, and was

assigned to the Office of Attending Physician at the United States Capitol. He deployed

twice in 1998 with the Marine Expeditionary Unit Service Support Group 26 and Combat

Service Support Detachment 69 supporting Operation Joint Guard in Bosnia and

Operation Fuerte Apoyo in Central America.

He received an Associate of Science degree in laboratory technologies from

George Washington University in 2002 and a Bachelor of Science degree in

interdisciplinary studies with a focus on biology from Mountain State University,

Beckley, West Virginia in 2003. He began a master’s in biodefense program at George

Mason University, but disenrolled after the Navy selected him as the first enlisted Sailor

to study entomology under the Medical Service Corps In-service Procurement Program

(MSC-IPP) in 2004. Under this program, he obtained a Master of Science in entomology at the University of Florida in 2007 under the direction of Dr. Philip G. Koehler studying the potential of insecticide-treated cords and sprayable baits for control of house flies.

He received a commission as a Lieutenant (junior grade) in the Medical Service

Corps following his graduation in August 2007. After attending Officer Indoctrination

School, he was assigned to the Navy Entomology Center of Excellence in Jacksonville,

Florida. He deployed on the USS Boxer (LHD 4) supporting Operation Continuing

Promise in 2008 prior to being reassigned to 3rd Medical Battalion in Okinawa, Japan.

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He was promoted to the rank of full Lieutenant in 2009 and spent much of his Okinawan tour participating in training exercises throughout Southeast Asia. In 2012, he was selected for the Duty Under Instruction by the Medical Service Corps and temporarily reassigned to San Diego, California before beginning his Ph.D. program in August

2013.

He is an active member of the Entomological Society of America and the

Acarological Society of America. Upon graduation, he anticipates assignment to the

Naval Medical Research Center - Asia in Singapore. He and his wife, Karina have two children, Conrad and Kyra, who enjoy travelling and experiencing life together.

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