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4-7-2014 Spatiotemporal Distribution of Genus Culex (Diptera: Culicidae) in USF Ecopreserve, Hillsborough County, Florida Emily Schwartz University of South Florida, [email protected]
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Spatiotemporal Distribution of Genus Culex (Diptera: Culicidae) in USF Ecopreserve,
Hillsborough County, Florida
by
Emily Schwartz
A thesis submitted in partial fulfillment of the requirements for degree of Masters of Public Health Department of Global Health College of Public Health University of South Florida
Major Professor Robert Novak, Ph.D. Benjamin Jacob, Ph.D. Thomas Unnasch, Ph.D.
Date of Approval: April 7, 2014
Keywords: Eastern Equine Encephalitis Virus, West Nile Virus, St. Louis Encephalitis Virus, Arbovirus, Ecology
Copyright 2014, Emily Schwartz
ACKNOWLEDGMENTS
I would like to thank Dr. Robert Novak for being a mentor who provided me with an abundance of tools for my future in public health. He has the passion and dedication, which
I hope to reflect in my own career someday. Not only has he passed on knowledge and skills, but also helped guided by professional development by challenging me every step of the way. Also, Dr. Ben Jacob for his expertise and advice regarding statistics and modeling.
I want to give special thanks for my colleague Ryan Tokarz showing me the way when I first started at the University of South Florida. He was always a source of moral support and wealth of knowledge. I cannot forget the other Ryan; Ryan Ortega deserves a big applause for his help with using SAS.
Additionally, I acknowledge Dr. Fox and the USF Ecopreserve Research Committee for giving me permission to conduct my research.
TABLE OF CONTENTS
List of Tables ...... ii
List of Figures ...... iii
Abstract ...... iv
Chapter One: Introduction ...... 1
Chapter Two: Materials and Methods ...... 11 Site Description ...... 11 Site Ecology ...... 12 Site Selection ...... 12 Adult Sampling Technique ...... 14 Egg Collection Technique ...... 15 Gravid Collection Technique ...... 16 Larval Sampling Collection ...... 17 Data Collection ...... 18 Analysis ...... 19
Chapter Three: Results ...... 20 Larval Sampling ...... 20 Gravid Sampling ...... 20 Egg Collection ...... 22 Adult Sampling ...... 24 Statistical Analysis ...... 34
Chapter Four: Discussion ...... 36 Egg Sampling Considerations ...... 36 Gravid Sampling Analysis ...... 38 Adult Sampling Population and Trends ...... 39
List of References ...... 44
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LIST OF TABLES
Table 1: Percentage of egg rafts by species according to distance ...... 24
Table 2: Summation of adult catches by distance ...... 25
Table 3: Paired Student t-test for Culex erraticus catches by distances ...... 35
Table 4: Paired Student t-test for Culex nigripalpus by distances ...... 35
Table 5: Paired student t-test for total Culex catches by distances ...... 35
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LIST OF FIGURES
Figure 1: Example of urban wetland and residential interface ...... 9
Figure 2: Satellite imagery of sampling points ...... 13
Figure 3: Statistical representation of zero-inflated Poisson regression for gravid Culex spp. at 50 meters ...... 21
Figure 4: Gravid Culex species at 50 Meters ...... 21
Figure 5: Gravid Culex species at 100 Meters ...... 22
Figure 6: Zero meter egg collection ...... 22
Figure 7: Fifty meter egg collection...... 23
Figure 8: Hundred meter egg collection ...... 23
Figure 9: Adult catches of Culex erraticus by spatial point ...... 26
Figure 10: Adult catches of Culex nigripalpus by spatial point ...... 27
Figure 11: Adult Culex erraticus compared to rainfall: 0 meters ...... 28
Figure 12: Adult Culex erraticus compared to rainfall: 50 meter ...... 29
Figure 13: Adult Culex erraticus compared to rainfall: 100 meters ...... 30
Figure 14: Adult Culex nigripalpus compared to rainfall: 0 meter ...... 31
Figure 15: Adult Culex nigripalpus compared to rainfall: 50 meter ...... 32
Figure 16: Adult Culex nigripalpus compared to rainfall: 100 meter ...... 33
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ABSTRACT
Within the state of Florida, there are three arboviruses of public health importance that can cause neuroinvasive disease in humans: West Nile Virus, Saint Louis Encephalitis Virus, and Eastern
Equine Encephalitis Virus. Mosquitoes (Diptera: Culicidae) within the genus Culex are known and suspected vectors of these diseases. The vectors of these diseases can be present in urban wetland habitats that allow for exposure to residential communities. Vector ecology must be investigated in order to understand the dynamics of disease transmission. In Hillsborough County, Florida the spatial and temporal distribution of these vectors are not well established. An ecological study was conducted in the University of South Florida’s Ecopreserve using trapping methodologies to sample the adult and gravid females as well as collect the egg population. Collections were made at three spatial points for the duration of July through December 2013 and compared to meteorological variables. Culex erraticus, a proposed bridge vector of Eastern Equine Encephalitis, was the most abundant adult species and gravid female captured. Culex nigripalpus, primary Floridian vector of
Saint Louis Encephalitis and bridge vector of West Nile Virus, was the second most abundant adult species caught as well as the majority of eggs collected. Based on the results collected, the presence of Culex erraticus and Culex nigripalpus was confirmed. The majority of Culex erraticus adults were collected in September and October and Culex nigripalpus adults were the highest in July and August.
The results of the gravid and egg collection generated crucial insight regarding methodology for studying vector ecology within this urban wetland habitat. However, modeling at spatial points based on meteorological variables yielded inconsistent results that illicit further investigation regarding these arboviral vectors of disease.
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CHAPTER ONE:
INTRODUCTION
In Florida, there are three arboviral encephalitides of medical importance of which mosquito
(Diptera: Culicidae) species within the genus Culex are involved in crucial and potential roles of transmission (R. W. Chamberlain, Sudia, Coleman, & Beadle, 1964; Ottendorfer, Ambrose, White,
Unnasch, & Stark, 2009; Vitek, Richards, Mores, Day, & Lord, 2008; G. S. White et al., 2011).
Within the virus family Flaviviridae, viruses within the genus Flavivirus cause Saint Louis Encephalitis
(SLE) and West Nile Encephalitis (WNE) and a virus in genus Alphavirus in the family Togaviridae causes Eastern Equine Encephalitis (EEE) (Viruses, 2011). These arboviral encephalitides each have a medical impact upon Florida, which validates the clinical, epidemiological, ecological, and entomological premises of research investigation in the state.
Saint Louis Encephalitis Virus (SLEV) has been present in the Tampa Bay area for decades with notable epidemics in 1959, 1961, 1962, 1977 and 1990 (R. W. Chamberlain et al., 1964;
Jonathan F Day & Stark, 2000; Shaman, Day, & Stieglitz, 2002). As of 2010, Florida boasts the fifth- highest number of reported cases of Saint Louis Encephalitis neuroinvasive disease cases within in the United States with 380 cases ("St. Louis Encephalitis Virus Neuroinvasive Disease Cases*
Reported by State, 1964-2010,"). During one of the more recent epidemics of 1990-1991, out of the affected counties in Florida the attack rate was 2.25 per 100,000 and as high as 21/100,000 cases in
Indian River County with a case fatality rate of 6.3% (Meehan et al., 2000). Saint Louis Encephalitis disproportionality affects the older population with a median age of 54 in the 1991 epidemic in
Florida (Meehan et al., 2000). Clinical symptoms of SLE are consistent with similar arboviral
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infections such as fever, nausea, abnormal pain, nuchal rigidity, and tremors (Naidech, Elliott,
Naidech, & Elliott, 1999; Southern, Smith, Luby, Barnett, & Sanford, 1969). Major complications persist when SLE develops into the neuroinvasive disease form with inflammation of the meninges and major neurological complications (Johnson, 1998; Solomon, Winter, Solomon, & Winter, 2004).
The convalescent period of SLE can last months after infection with complications that have shown to lead to death (Southern et al., 1969), but the extent of the sequela of SLE is not as well understood. A study of five-year effects of SLE patients from an epidemic in Pinellas county,
Florida from 1964 indicated that a possible sequela might lead to emotional problems and psychological instabilities, but further investigation and statistical support needs to be found
(Lawton, Rich, McLendon, Gates, & Bond, 1970; Lawton, Seabury, Branch, Azar, & Bond, 1966).
The first detection of West Nile Virus (WNV) in the United States was in 1999 in New York
City (Nash et al., 2001) and has subsequently spread to forty-eight states within the United States, including Florida. WNV has been a target for public health due the upward mobility of the disease throughout North America. From 1999-2008, the United States had 28,961 cases of confirmed and suspected cases of WNV (Lindsey, Staples, Lehman, & Fischer, 2010). While the majority of cases are estimated to be asymptomatic, the cases that present symptoms are similar to a febrile illness with fever, fatigue, head and back pain, and myalgia, which can persist, into diarrhea, vomiting, and rash (Dauphin & Zientara, 2007; Sambri et al., 2013). In Florida, 52 cases of neuroinvasive WNV were reported, and the incidence rate for neuroinvasive disease in the state was 0.01–0.24 per
100,000 (CDC, 2014c). Less than 1% of symptomatic patients have neurological symptoms; however, when an infection becomes neuroinvasive symptoms can include tremors, rigidity, postural instability, and bradykinesia (Diamond, 2009; Sejvar et al., 2003). The neuroinvasive symptoms of the disease are the major medical concern, and present in four broad pathophysiological ways: meningitis, encephalitis, acute flaccid-like paralysis, and ocular complications (Diamond, 2009).
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Due to the infrequent human contraction of Eastern Equine Encephalitis Virus (EEEV), less public health emphasis has been pursued in comparison to the similar arboviruses WNV and
SLE. When EEEV is acquired, the virus can develop into a serious form of neuroinvasive disease with high mortality. EEEV has shown a significant burden upon Florida compared to other states;
70 cases of neuroinvasive disease since 1964 in Hillsborough County, along with an annual incidence of 0.01-0.04 per 100,000 people (CDC, 2014a; CDC, 2014b). In humans, when EEE develops into the neuroinvasive form, symptoms are consistent with stiff neck, tremors, high fever, vomiting, and convulsions. EEE disproportionately affects the younger population, with the mortality rate in children under 10 years old around 75%, and those that do survive show significant neurologic sequela (Deresiewicz, Thaler, Hsu, & Zamani, 1997; Feemster & Haymaker, 1958).
As encephalitis viruses, SLEV, WNV, and EEEV exhibit similar clinical presentation with varying degrees of public health incidence, yet all warrant investigation in terms of vector and transmission dynamics. The transmission cycle of SLEV, WNV, and EEV share known competent vectors, as well potential vectors within the genus Culex (Apperson et al., 2004; R. W. Chamberlain et al., 1964; Eddie W Cupp, Klingler, Hassan, Viguers, & Unnasch, 2003; J. F. Day & Stark, 1996a;
W. K. Reisen et al., 2005; Wellings, Lewis, & Pierce, 1972). Consequently, these vectors share some similarities in regards to ecological transmission, which allows for concurrent study of vector ecology for multiple arboviral transmissions. These arboviral encephalitides have a generalized cycle of an avian host that maintains the viruses within the environment, which are then spread by the arthropod vector with the family Culicidae (Diptera) ("Arboviral Encephalitides," 2005). The arboviruses become a public health concern when the vector bites, and consequently infects, a human or animals of economic importance such as horses, both of which are dead-end hosts
(Bunning et al., 2001; A. N. Clements, 2011; Tsai & Mitchell, 1988).
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The transmission of SLEV aligns with arboviruses such as West Nile Virus and Eastern
Equine Encephalitis Virus. In Florida, the transmission cycle is primarily enzootic with peridomestic avian host from the order Passeriformes, especially nestlings, that includes the house sparrow (Passer domesticus), house finch (Carpodacus mexicanus), cardinal (Cardinalis cardinalis), and blue jay (Cyanocitta cristata) (J. F. Day & Stark, 1999; Jennings, 1969; Mahmood, Chiles, Fang, Barker, & Reisen, 2004;
Reisen, Fang, & Martinez, 2005). Additionally, there is a rural cycle where hosts are birds such as woodthrush (Hylocichla mustelina) and bobwhite (Colinus virginianus) where Culex restauns and Culex salinarius are the principal vectors (McLean et al., 1985; Scott & McLean, 1979). Mammalians may serve as a secondary host in smaller rodents (McLean et al., 1985) but incidental hosts in many cases
(Rosa et al., 2013). Saint Louis Encephalitis Virus has been isolated in multiple species within the genus Culex, with the majority of isolations being Culex nigripalpus, Culex quinquefaciatus, Culex pipiens, and Culex tarsalis (R. W. Chamberlain et al., 1964; J. F. Day & Stark, 1996b; Godsey Jr et al., 2005;
Nelson et al., 1983). Under experimental conditions, these Culex vectors are competent vectors
(Hammon & Reeves, 1943; Sudia, 1959; Sudia & Chamberlain, 1964).
As the WNV spread across the United States, it became apparent that the transmission cycle for the New York Strain WNV was similar to its international transmission cycle (C. G. Hayes,
2001). Aves within the order Passeriformes such as the house sparrow (Passer domesticus), blue jay
(Cyanocitta cristata), common grackle (Quiscalus quiscula), and American crow (Corvus brachyrhynchos) are proven to be the main amplifying hosts (Komar et al., 2001; Komar et al., 2003; Komar et al., 2005).
Culex vectors have been implicated in the field as the main vector for WNV, such as Culex restauns,
Culex salinarius, Culex pipiens, (Anderson et al., 2001; Andreadis, Anderson, & Vossbrinck, 2001; D. J.
White et al., 2001) and experimentally determined competent vectors include Culex tarsalis, Culex quinquefaciatus, Culex salinarius, Culex pipiens (Colton et al., 2005; Sardelis, Turell, Dohm, & O'Guinn,
2001; Turell et al., 2006; Turell, O'Guinn, Dohm, & Jones, 2001; Turell, Sardelis, Dohm, &
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O'Guinn, 2001). As WNV expanded into the south, new Culex vectors were implicated in Florida;
Culex nigripalpus has been positive for WNV in field studies and shown to have a high enough competence to allow infectivity (Blackmore et al., 2003; Godsey Jr et al., 2005; Turell, Sardelis, et al.,
2001; Vitek et al., 2008).
EEEV exhibits many similarities to avian arboviruses like that of WNV, SLE, and it’s regional counterpart Western Equine Encephalitis. EEEV is an enzootic disease with an avian to mosquito transmission cycle that circulates in passerine birds and herons (Estep et al., 2011; Komar
& Spielman, 1994; Morris, 1988; Scott & Weaver, 1989). Ornithophilic mosquitoes, mainly Culiseta melunura (Chamberlain, Rubin, Kissling, & Eidson, 1951; Scott & Weaver 1989), serves as the primary vector, with speculation of bridge vectors like Aedes vexans, Coquillettidia perturbans, Culex erraticus and Culex salinarius (Armstrong, Andreadis, Armstrong, & Andreadis, 2010; Roy W.
Chamberlain, 1958; Eddie W Cupp et al., 2003; Vaidyanathan, Edman, Cooper, & Scott, 1997).
A common ecosystem in the state of Florida is hardwood swamps surrounded by floodplain landscape. Some Culex vectors share an affinity for this habitat, which permeates approximately 42% of the USF Ecopreserve in Hillsborough County, FL (Schmidt, 2005). Culex nigripalpus inhabits cypress swamps and other hardwoods swamps (M. W. Provost, 1969), urban forest and forest ecotones (Salas et al., 2001; J. Smith et al., 2009). Culex erraticus frequently have been found in hardwood swamps with permanent bodies of water (Eddie W Cupp et al., 2003; W. E. Horsfall,
1955). In Florida, EEEV had a positive relationship with tree plantations and forested wetland mixed habitats (Vander Kelen et al., 2012). Both of these proposed vectors are present in this cypress swamp, as shown by mosquito surveillance (Novak, 2013b). These vectors are of particular importance because of their potential involvement as bridge vectors. Culex erraticus feeds largely on aves; however, as an opportunistic feeder it will feed on reptiles, amphibians, and mammals if encountered (Cohen et al., 2009; John D. Edman, 1979; Lewis C. Robertson, Stephen Prior, Charles
5
S. Apperson, & William S. Irby, 1993). It has been observed that mammal feeding by Culex erraticus occurs in shift later in the summer from aves to some mammals, which implicates Culex erraticus as a possible bridge vector during these times (Nathan D. Burkett-Cadena, Hassan, Eubanks, Cupp, &
Unnasch, 2012; J. D. Edman & Taylor, 1968; Kilpatrick et al., 2006; Oliveira et al., 2011). Culex erraticus has an average dispersal of 0.61 km (Laura K Estep, Nathan D Burkett-Cadena, Geoffrey E
Hill, Robert S Unnasch, & Thomas R Unnasch, 2010; Morris, Larson, & Lounibos, 1991), which if infected would allow for it to travel out of its habitat to seek a blood meal, possibly resulting in host infection of EEEV. Although its involvement in WNV and SLE is not clear, isolations of WNV and
SLE in Culex erraticus have been found, and due to similarities in transmission cycle between SLEV,
WNV and EEEV it is proposed they may play role (E. W. Cupp et al., 2007; E. W. Cupp et al., 2004;
Hribar, 2007). This pattern is similar to Culex nigripalpus, which feeds primarily on aves during the winter and spring, shifting to opportunistic feeding including mammals in the fall (John D. Edman,
1974; Molaei et al., 2007). Culex nigripalpus are likely to travel out of woods to seek mammalian hosts
(Edman 1979), which could possibly be in adjacent developments that border the urban wetlands.
Although Culex nigripalpus generally are not distance feeders in dispersal studies 17.6 % were found
0.4-1.2 km from release point and some even as far as 5 km (Dow, 1971; Nayar, Provost, & Hansen,
1980). Besides being one of the primary SLE vectors in Florida, Culex nigripaplus may have a role in the spread of EEEV, as it account for 27% of the virus isolations in Tampa Bay, and has been isolated in pools as far as Trinidad (Downs, Aitken, & Spence, 1959; Wellings et al., 1972). It’s shifting catholic feeding habits in summer and fall, along with the increasing cases of human infection in late summer and early May, have a contributing factor as a bridge vector in WNV
(Artsob et al., 2009; Barrera et al., 2010; Blackmore et al., 2003; John D. Edman, 1974). The feeding habitats and dispersal habitats support the idea of Culex nigripalpus and Culex erraticus as bridge vectors.
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The dynamics of vector ecology for Culex vectors begins with the identification of viable aquatic resources where Culex may oviposit their egg floats (A. Clements, 1999; W. E. Horsfall,
1955; Klowden, 1990). Survey of an aquatic habitat can indicate multiple points of Culex bionomics that can aid in vector surveillance and research. Using adult trapping techniques, adult populations may be measured, and male trapping numbers assess the site as a viable breeding ground (Silver &
Service, 2008). The adult male population numbers within these catches can indicate if breeding is taking place since females are attracted to male swarms (Klowden, 1990). Females are more likely to mate with males two days old or younger so male mosquitoes do not disperse great distances from oviposition site, thus, the male populations indicate a viable aquatic habitat for larval development
(Klowden, 1990; Novak, 2013a). Additionally, egg collections can indicate what Culex species are present within the environment, assessing the environments as a suitable area for oviposition
(Klowden, 1990). Gravid collection can indicate that what Culex females are seeking an oviposition site and have found an attractant to cue to the oviposition (Bentley & Day, 1989; Reiskind &
Wilson, 2004).
When investigating the ecology of these vectors, many meteorological variables play a role in vector bionomics, which affect transmission. These variables need to be accounted to be when sampling vector populations. One crucial variable is rainfall due to its influence on suspected bridge vectors. Studies have show Culex nigripalpus have increased flight activity the night after rainfall due to increased humidity (W. L. Bidlingmayer, 1974; J. K. Nayar, 1982; O'Meara, Cutwa-Francis, & Rey,
2010; Maurice W Provost, 1974), and there is negative correlation between rainfall and gravid females (J. F. Day et al., 1990). In contrast, an increase of Culex erraticus numbers has been seen when water levels are low due to decreased rainfall (Lewis C. Robertson et al., 1993). Additionally, temperature can affect flight behavior but due to the seasonally warm temperature in Florida it is probable that only minimum temperatures thresholds affect flight behavior. Concerning
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temperature, (W. L. Bidlingmayer, 1985) set the minimum threshold temperatures for morning and evening catches was placed at 22°C to investigate the differences in catches. Culex nigripalpus and
Culex erraticus have decreased catches with lower night temperatures (W. L. Bidlingmayer, 1985; N.
D. Burkett-Cadena et al., 2011; Gray, Burkett-Cadena, Eubanks, & Unnasch, 2011) For each degree below 20°C, the catch decreases by 14% for Culex nigripalpus and 13% for Culex melaconin (W. L.
Bidlingmayer, 1985). Another variable worth investigation is the degree of daylight minutes due to the influence photoperiods has shown to have on flight behavior and feeding, and thus affecting oviposition and abundance (Beck & Stanley, 1980).
Furthermore, environmental modifications to vectors habitats can change transmission dynamics for vector-borne diseases. Among these modifications, anthropogenic changes have shown to increase vector-borne infections (Norris, 2004; Patz, Graczyk, Geller, & Vittor, 2000). In
Florida, wetlands represent a healthy portion of Florida ecological land coverage ("Development of a Cooperative Land Cover Map: Final Report," 2010). Due to increasing suburbanization, residential development can encroach upon these wetlands. Destruction of such wetland can cause fragmentation of habitats, which create heterogeneous aquatic habitats affecting vector-borne disease transmission (D. L. Smith et al., 2004). Such developments create alterations such as can decreasing buffer zones between aquatic habitats and residential areas, creating new habitats, destroying current habitats or altering existing habitats (Norris, 2004). These environmental modifications can change vector density, shift vector-host dynamics, and alter the cycle of the infectious agent (Patz et al., 2000). Spatial analysts literature, including land cover, have investigated
WNV cases and vector dynamics among fragmented land and urban landscape with interesting findings. Higher numbers of WNV cases have an association to urban areas with high vegetation indexes (Brownstein et al., 2002). In Louisiana, a negative correlation between increased wetland and
WNV cases (Ezenwa et al., 2007) indicates that smaller urban wetlands may increase WNV cases.
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Additionally, the pattern of smaller borders between natural habitats and residential areas shows a pattern of lowered avian diversity and increased transmission of WNV (Brown, Childs, Diuk-
Wasser, & Fish, 2008; Ezenwa, Godsey, King, & Guptill, 2006; Morales-Betoulle et al., 2008).
Figure 1: Example of urban wetland and residential interface
Similarly, for risk assessment of avian malaria, spatial analysis of land cover has shown that land fragmentation has increased vector catches of Culex quinquefaciatus (M. E. Reiter & LaPointe,
2007). With reduced wetland and residential interface, the opportunistic feeding of catholic vectors such as Culex nigripalpus and Culex erraticus (John D. Edman, 1974, 1979; Oliveira et al., 2011) could potentially feed on humans in close proximity which is supported by vector-borne modeling which predicts that human biting rate (HBR) is greatest at the edges of towns (D. L. Smith et al., 2004).
Bridge and enzootic vectors within the Culex genus have been shown to be spatially separated, with bridge vectors being more inclined to inhabitant highly vegetative spaces within residential communities (Brown et al., 2008).
The premise of this study was to investigate the entomological aspect of the arboviral vectors
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within the Culex genus with focus on Culex nigripalpus and Culex erraticus in Florida. Within
Hillsborough County, many urban wetlands are the product of residential development around naturally occurring wetlands or conservations ("Development of a Cooperative Land Cover Map:
Final Report," 2010), creating heterogeneous environments for mosquito breeding and feeding activity. Similar disease transmission for EEEV, WNV, and SLEV arboviruses suggests that fragmented wetland and reduced land wetland coverage could potentially change dynamics to allow for potential vectors to increase infectivity. Due to the predominant wetland ecology that Florida possesses, infringement of these wetlands upon residential communities merits an investigation into these potential Culex vectors focusing on potential risks of bridge vectors. A temporal analysis of three points with 50-meter buffers from a wetland water source was performed to test a hypothesis that Culex vector quantity will differ at each spatial creating a spatial trend from the aquatic habitat according to four premises of local abundance, male population, oviposition, and gravid females.
The temporal period chosen was from mid-July to mid-December to investigate the relationship between vector quantities in accordance to temporal epidemiology of arboviral encephalitides. West
Nile Virus has the majority of cases occurring in the late summer to early fall with 92% of reported annual cases from July to September but southern states can have cases reported later in the year due to delayed overwintering activity of vectors and hosts (E. B. Hayes et al., 2005; Lindsey et al.,
2010). Equally, SLEV also follows a similar seasonality pattern, which peaks in August and
September; whereas EEEV peaks earlier in the year but there is a significant number of cases in July through December (Bigler et al., 1976; Shroyer & Rey, 1990). Meteorological data was collected because it was hypothesized that high rainfall, increased daylight hours, and raised minimum temperature would coincide with fluctuations in vector population and oviposition. Since no published data in Hillsborough County concentrating on Culex vectors exists, to the author’s knowledge, this study will serve as a baseline account for these suspected Culex vectors.
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CHAPTER TWO:
MATERIALS AND METHODS
Site Description
The study site was located within the USF Ecopreserve in Tampa, Hillsborough County,
Florida and the specific sampling site was based on ecological premises with regards to sampling methodology. One consideration was the proximity to aquatic habitat and its relation to other aquatic habitat. The chosen study site is located at a maximum distance from other permanent aquatic habitats, which serves as a buffer to reduce sampling bias from competing larval habitats.
The aquatic habitat is situated at a location in close proximity to the entrance of the Ecopreserve so materials were easily transported and water could be changed out. All study points were chosen inclusively within the ecotone of the aquatic habitat so the difference in ecotone would not influence the sampling.
Site Ecology
The ecology of the study site serves as a representation of a common Floridian ecosystem
("Development of a Cooperative Land Cover Map: Final Report," 2010). The habitat of the site is a semi-permanent flood plain, which transitions to a flatwood plain at the outer ecotone. Flooding in this semi-permanent flood plain will generally last six months from June to February with residual standing water for the whole year in some parts, but will depend on annual rainfall and drought period (Schmidt, 2005). The soil is described as black, organic soil with chobee sandy soil type
(Schmidt, 2005). The canopy is well developed with mainly deciduous trees and some coniferous trees with buttresses for water absorption during flooding. The high canopy is developed with 11
Swamp Cypress (Taxodium ditichum), Swamp maple (Acer rubrum), Water locust (Gleditsia aquatica),
Swamp tupelo (Nyssa sylvatica var. biflora), and American elm (Ulmus americanais) (Schmidt, 2005, p.
31). The mid-canopy is thinner composed of mainly Coastal plain willow (Salix caroliniana), some
Meadow holly (Ilex decidua), Dahoon holly (Ilex cassine), and Southern bayberry (Myrica cerifera), along with sub-canopy species Florida bully (Sideroxylon reclinatum) and Walter’s viburnum (Viburnum obovatum ) (Schmidt, 2005). Common grass species in the flood plain are American barnyard grass
(Echinochloa muricata), Giant Sedge (Carex gigante), Maidencane (Panicum hemitomon), Grayshortbristle horned beaksedge (Rhynchospora corniculata ), and Southern beaksedge (Rhynchospora microcarpa)
(Schmidt, 2005). Typical fauna includes mammalian species such as Hispid cotton rat (Sigmodon hispidu), Virgina opposum (Didelphis virginiana), White-tailed deer (Odocoileus virginianus), wild boar
(Sus scrofa), reptiles and amphibian species such as Southern Toad (Bufo terrestri), Rat snake (Elaphe alleghaniensis), Gopher tortoise (Gopherus polyphemuss) and a broad diversity of species in class Aves including Red-bellied Woodpecker (Melanerpes carolinus), Northern Cardinal (Cardinalis cardinalis)
Yellow-rumped Warbler (Dendroica coronate), Blue-headed Vireo (Vireo solitaries) ("Fauna," 1999; "USF
Eco Preserve: Current Bird List,") .
Site Selection
The spatial component of this study determined that three distinct points were selected with respect to the aquatic habitat. The zero meter point serves as the reference point for the aquatic habitat. Due to seasonal flooding, the aquatic habitat has an indistinct boundary that varies annually.
In the July, the periphery of the flood line was mapped using a global position satellite device and visualized in Arcmap 10.1 (ESRI, Redlands, CA). The zero meter point was chosen because of its positions on the tip of the periphery of the flood line. Additionally, the point was chosen so in the case of extreme flooding there could be a lateral movement of the sampling site so the spatial
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distances were not affected. Stakes were placed in between the waterline and zero meter point and photograph documentation was compiled for each sampling day.
From the zero reference point, two other spatial points at 50 and 100 meters were mapped using a gps handheld device. The two sampling sites were considered based on several ecological and meteorological considerations. Adequate canopy coverage was a consideration for the sampling points due to the illumination effect of the moon. Illumination from moonlight has been found to reduce the effectiveness of the trap by diminishing the effect of the artificial light source when using
New Jersey light traps (W. L. Bidlingmayer, 1967). Reduced trap effectiveness due to lunar interference gains further support by the finding that more mosquitoes were caught during a new moon than full moon (Costantini et al., 1996; William R Horsfall, 1943). All chosen sampling sites had trees that were in a random, staggered positions for minimal visual competition and bias because
W. L. Bidlingmayer and Hem (1980) found that mosquitoes are more attracted to traps at the ends of rows of objects.
Figure 2: Satellite imagery of sampling points
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Adult Sampling Technique
The species within the genus Culex under investigation are nocturnal feeders, meaning adult populations needed to be sampled during the night (W. L. Bidlingmayer, 1974; Gray et al., 2011;
Reisen, Lothrop, & Meyer, 1997). A standard adult sampling technique used in Culicidae surveillance and research is the CDC New Jersey light trap (LT) (John W. Hancock, Gainesville, FL). Light traps are commonly used in surveillance to capture a high quantity of specimens for abundance and dispersal studies (Silver & Service, 2008). Additionally, light traps have been used to detect seasonal changes as well as fluctuations over space and time (Miller, Stryker, Wilkinson, & Esah, 1977). The operation of the CDC LT is best utilized for appetential flight, which is the flight cued by physiological cues. The light serves as this cue and works by creating three zones: inhibition, repulsion, and dazzle (W. L. Bidlingmayer, 1985). Once the adult makes it into the first zone, either the light repels the adult or it may enter the third zone where it becomes disoriented and leads into the trap (W. L. Bidlingmayer, 1985). CDC LTs can yield variable results regarding species so a carbon dioxide attractant supplemented the CDC LTs. Carbon dioxide has been shown to expand the range of attracted mosquitoes (Silver & Service, 2008; Snow, 1970) as well as the quantity caught
(Silver & Service, 2008). The carbon dioxide can stimulate mosquitoes in appetential flight to switch to consumatory flight toward the light trap (W. L. Bidlingmayer, 1985).
A standard CDC New Jersey LT was used at each testing point and hung from a branch at
1.5 meters from the ground for collection purposes. Standard mailing envelope insulated with bubble lining was hung with string so the envelope rested upon the upper shelter (Novak, 2013a).
The traps were set out twice a week at 16:00 to 18:00 hours depending on seasonal sunset variability, because setting out carbon dioxide before dusk has shown to attract an enhanced diversity of crepuscular mosquitoes (Silver & Service, 2008). Approximately one pound of dry ice (Airgas USA,
LLC, Kennesaw, GA) was placed in the mailing envelope and sealed thoroughly so a small, steady
14
stream of carbon dioxide was visibly escaping until after dawn. The light trap was powered by 12V motorcycle battery (Power Sonic, San Diego, California) and all changes of batteries were documented to ensure power supply was adequate for the collection period. The following morning, the trap containers were collected between 8:00-10:00 AM so specimens did not desiccate, similar to mosquito collecting in the Florida Keys (Leal & Hribar, 2010). Collecting nets were brought into the lab and specimens were killed by placement in the freezer. Based on each distance, Culex species were separated from the other Culicidae genus and a random aliquot of twenty-five of the catch was mounted and identified to improve mounting skills and observational abilities. All collected adults were identified under the microscope according to “Keys to the adult females and fourth instar larvae of the Mosquitoes of Florida (Diptera, Culicidae)” (Darsie & Morris, 2000).
Egg Collection Technique
The genus Culex lays eggs on the surface of the water in the form of egg floats (W. E.
Horsfall, 1955). For egg collection for Culex, artificial containers containing various infusions are common for surveillance of oviposition sites and quantifying of population dynamics. For this study, oviposition containers were fashioned from 3.5 gallon plastic buckets (Ropak Packaging, Fountain
Valley, CA). To drain and prevent overflow, eight two-inch holes were drilled around the circumference of the bucket 15.25 cm from the base of the bucket. Then the buckets were spray painted black due to mosquitoes increased attraction to dark colors such as black or green (Allan &
Kline, 2004). The buckets were first conditioned with tap water for 48 hours to remove any excess paint chemicals. The buckets were filled with 6 liters of tap water infused with sod grass plugs 23 cm x 23 cm with 125 grams of rabbit chow since sod infusion has shown dependability in sampling for
Culex eggs (Lampman & Novak, 1996; Paul Reiter, Gubler, Gubler, & Kuno, 1997). Each infusion was fortified with 50 grams of rabbit chow every Friday as to allow for fermentation over the
15
weekend to recondition the buckets due to high volumes of rainfall. Rabbit chow has shown to sustain attraction for Culex for a longer period of time (Lee & Kokas, 2004).
Egg floats were collected between 08:00 and 10:00 AM Monday through Friday. A moist cotton ball was dipped in the bucket to extract the eggs from the surface of the water. The eggs were directly taken back to the lab to be reared for identification. Each egg float was placed in a separate casserole dish with deionized water and fed fish tetrad (Novak, 2013a). The larvae were incubated in an environmental chamber (Thermo Fisher Scientific, model 3759, Waltham, MA) under cycles of
12 light hours and 12 dark hours until the larvae reached third or fourth instar. Once fourth instar was reached, the larvae were killed with hot water (not boiling) and preserved in ethyl alcohol
(Decon Labs, King Prussia, PA). The larvae were identified under the microscope using Darsie’s taxonomic key “Keys to the adult females and fourth instar larvae of the mosquitoes of Florida
(Diptera, Culicidae)” (Darsie & Morris, 2000). All unhatched eggs floats were examined for classification as previously hatched or unfertilized eggs.
Gravid Collection
Gravid female mosquito collection is common for arboviral surveillance because the blood can be extracted and tested for viral DNA. Gravid traps can capture the local Culex population in search of suitable oviposition habitats. The classic Reiter trap was developed for this purpose and the Reiter trap design has had modifications to increase catches with fewer disturbances from predators and improved specimen quality (P. Reiter, 1987; P. Reiter, Jakob, Francy, & Mullenix,
1986). CDC Gravid Trap Model 1712 (John W. Hancock Company, Gainesville, FL) was used for the purpose of this study, which has been shown to have no difference between other CDC gravid traps made from other manufacturers (Allan & Kline, 2004). The infusion was made from 4 liters of tap water with sod grass of 23 cm by 23 cm with fortification of 200 grams of rabbit chow (Kaytee’s,
16
Chilton, WI). This infusion reflects the same infusion used for egg sampling of the population to keep sampling methodology consistent.
Two gravid traps at 50 m and 100 m were set out twice a week between 16:00 to 18:00 hours depending on seasonal sunset variability to ensure nocturnal Culex were captured before the first periodicity of activity (W. L. Bidlingmayer, 1967; Gray et al., 2011). The collecting chamber from the gravid trap was collected between 08:00 and 10:00 AM hours and placed in refrigerator at 4 degrees Celsius to knock out for collection. The specimens were extracted from the freezer to kill the specimens. All gravid mosquitoes were identified under a microscope and classified as gravid or non-gravid. All Culex were speciated using Darsie’s taxonomic key “Keys to the adult females and fourth instar larvae of the mosquitoes of Florida (Diptera, Culicidae)” (Darsie & Morris, 2000).
Larval Sampling
Larval sampling can prove that environments at a local sampling site of standing water or aquatic habitat can be hospitable for larval growth and development. Egg collection shows that the environment was a viable oviposition site but larvae detection indicates the environmental variables are conducive to growth and the possibility of adult emergence (Silver & Service, 2008). For the purpose of this study and the flood plain, larval sampling was conducted along the periphery of the waterline at the reference point. Larval sampling was conducted once a week using a standard larval dipper (Bioquip, catalog no .1132) for twenty-five dips with different dip techniques. The following four dipping techniques were used to sample for all types of Culex due to different reactions to stimulation and disturbances. The simple scoop technique required a forty-five degree angle and allowed to fill; another technique used was the complete submersion method to gather fast moving larvae (O'Malley, 1989; Silver & Service, 2008). Two other techniques were used to target species hiding within the organic debris on the bottom of the aquatic floor. The flow-in method was
17
executed by placing the dipper flat against the mud floor and allowed to fill completely; an additional technique used was the scraping method that involves scraping the dipper at a forty-five degree angle along the vegetation of the mud floor (O'Malley, 1989).
While along the water line, disturbances were avoided by choosing a position that did not cast a shadow over the water. Sampling in deeper water required a moment of non-activity to allow larvae to reemerge to the surface. The number of larvae were noted per dip and then put into a vial for transportation in the laboratory. The larvae were killed using hot (not boiling) water and stored in ethanol alcohol (Decon Labs, King Prussia, PA). The larvae were then identified using a standard microscope using Darsie’s taxonomic key “Keys to the adult females and fourth instar larvae of the mosquitoes of Florida (Diptera, Culicidae)” (Darsie & Morris, 2000).
Data Collection
Multiple meteorological and environmental covariates were used for the data analysis for this study collected from external sources. For daylight hours, data was extracted from the United States
Naval Observatory database. Daylight hours were taken from the zero meter reference point from coordinates 28’4 North and 82’23 from July through December. The data was exported into a
Microsoft Excel 2011 and formatted for analysis. Minimum temperature and daily rainfall was collected from a weather station in Pleasant Terrace North, Station KFLTEMPL2, with geocoordinates: Latitude: N 28 ° 3 ' 41 '' ( 28.061 ° ) Longitude: W 82 ° 23 ' 55 '' (-82.399 °), which is located 1.513 km from the zero reference sampling point. Data was accessed through the Citizen
Underground Weather project. The data points from July to December were requested and compiled into Microsoft Excel 2011. Rainfall was summed to two days before the catch night as well as five days before the catch night for the entire period.
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Analysis
The analysis for the program was divided into two categories: statistical analysis and graphical representation. For the statistical analysis of the adult sampling, a stepwise multiple linear regression with meteorological covariates: rainfall, minimum temperature, and daylights hours for the temporal period. Each spatial point had the regression run for the species of interest.
Additionally, a student’s t test was run between the different spatial points to find significant difference between species. For the gravid mosquitoes and egg sampling, a zero inflated Poisson model was conducted due to low sampling numbers. The zero Poisson model was used to detect any pattern within the low sampling populations.
Concerning graphical representation, adult target species for each spatial point were graphed to show temporal trends. With table visualizations, all the adults’ species were displayed according to spatial points over the temporal period. Gravid samples and egg collections were charted according to each spatial point for the duration of the sampling period.
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CHAPTER THREE:
RESULTS
Larval Sampling
All larval sampling was collected weekly; out of twenty-three weeks collected only two weeks yielded larval sampling. The first two weeks of collection, 7/16/14 and 7/30/13, yielded 8 and 17 larvae, with an average larvae per dip of 0.04 and 0.85, respectively. The cumulative rainfall the weeks before July 16th and July 30th was 3.0226 cm and 4.2672 cm, respectively. Identified larvae were Culex restauns, Culex nigripalpus, and Culex coronator.
Gravid Sampling
Three species were caught in the gravid traps: Culex erraticus, Culex nigripalpus, and Culex spp.
4.2672, which were species within the subgenus Culex (Culex). At 50 meters, of the total catch of 25 females 40% were Culex spp, 48% were Culex erraticus, and 12% Culex nigripalpus, with the majority of collections within the temporal period: 7/18- 9/13. At 100 meters, of the total catch of 27 gravid females 50 % were Culex spp., 48.15% Culex erraticus, and 3.85% Culex nigripalpus with the majority of the collection between July through September. Additionally, at 50 meters, 54 non-gravid females were caught: 6 Culex nigripalpus, 36 Culex erraticus, 17 Culex spp, and 2 Culex coronator. Five males were caught throughout the sampling period: 1 Culex nigripalpus, 3 Culex erraticus, and 1 Culex spp. At 100 meters, non-gravid females: 9 Culex nigripalpus, 51 Culex erraticus, 25 Cules spp were caught, with 7 males: 6 Culex erraticus males and 1 Culex nigripalpus males. For statistical analysis, a zero inflated regression analysis was run according to distance for Culex catches by date with covariates of rainfall,
20
minimum temperature, and daylight minutes. All regression models yielded were invalid due to violation of model parameters, which invalidates model findings. The following figure of Culex spp. at fifty meters is a representation of the statistical output that violated these parameters.
Figure 3: Statistical representation of zero-inflated Poisson regression for gravid Culex spp. at 50 meters
Gravid Females by Catch Date: 50 Meter
4 Culex erraticus 3 Culex Nigripalpus 2 1 Culex spp.
0
8/1-8/2 8/8-8/9 9/5-9/6
7/11-7/12 7/18-7/19 7/25-7/26 8/15-8/16 8/21-8/22 8/29-8/30 9/12-9/13 9/19-9/20 9/26-9/27 10/3-10/4 11/6-11/7 12/5-12/6
Number of Gravid Gravid Females Number of
10/31-11/1
10/10-10/11 10/17-10/18 10/24-10/25 11/14-11/15 11/21-11/22 11/26-11/27 12/12-12/13 Catch Night
Figure 4: Gravid Culex species at 50 Meters
21
Gravid Female by Catch Date: 100 Meter
4 Culex erraticus 3 Culex nigripalpus 2 Culex spp. 1
0
8/1-8/2 8/8-8/9 9/5-9/6
Number of Gravid Gravid Females Number of
8/21-8/22 9/26-9/27 7/11-7/12 7/18-7/19 7/25-7/26 8/15-8/16 8/29-8/30 9/12-9/13 9/19-9/20 10/3-10/4 11/6-11/7 12/5-12/6
10/31-11/1
10/10-10/11 10/17-10/18 10/24-10/25 11/14-11/15 11/21-11/22 11/26-11/27 12/12-12/13 Catch Night
Figure 5: Gravid Culex species at 100 Meters
Egg Collection
Egg collections resulted in many zero collections for all three sampling sites but from the eggs collected the majority from Culex nigripalpus at all three spatial points. There were unhatched eggs that could not speciated; 1 at zero meters and 6 at 100 meters.
10 Egg Collection by Week: Zero Meter 9
8
7 Unhatched 6 Culex quinquefaciatus 5 Culex nigripalpus 4
3 Number of Egg RaftsEgg Number of 2 1 0
Figure 6: Zero meter egg collection
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The majority of eggs were collected during July and September with no eggs rafts were collected after 10/18/14 at all three sampling sites. Low sampling numbers inhibited running a regression model against meteorological covariates.
7 Egg Collection by Week: 50 Meter
6
5 Culex quinquefaciatus 4 Culex restauns 3 Culex nigripalpus
2 Numbr of Egg of RaftsEgg Numbr 1
0
Figure 7: Fifty meter egg collection
9 Egg Collection by Week: 100 Meter 8 7 6 Unhatched 5 Culex quinfaciatus 4 Culex restauns 3 Culex nigripalpus
Number of Egg RaftsEgg Number of 2 1 0
Figure 8: Hundred meter egg collection
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Table 1: Percentage of egg rafts by species according to distance
Distance 0 50 100 Culex nigripalpus 38 17 18 Percent 88.40% 77.30% 62.10% Culex restauns 0 2 4 Percent 0 9.10% 13.80% Culex quinquefaciatus 4 3 1 Percent 9.30% 13.60% 3.40% Unhatched 1 0 6 Percent 2.30% 0 20.70% Total 43 22 29
Adult Sampling
For all three spatial distances, the majority of the catches were Culex erraticus with 72.27% and Culex nigripalpus with 15.1% of the cumulative catches. For all three spatial points, there were a total of ten identified species. One hundred meters had the highest number of catches with 42.01% of the catches, 31.76% at zero meters, and 26.23% at fifty meters. Throughout the sampling period there was only two male mosquitoes caught: one Culex erraticus at zero meters on 8/1-8/2 and another Culex erraticus at 50 fifty meters on 9/9-9/10.
The abundance of Culex erraticus peaked during the month of September and the beginning of October, except for 50 meters 9/5-9/6 and 9/23-9/34 where catches are zero due to field errors.
Culex nigripalpus was most abundant during July and August with markedly fewer catches at zero meters. Both Culex erraticus and Culex nigripalpus abundances tapered by the last week in October, however, there was one increase on the night of 11/26. Culex erraticus and Culex nigripalpus for each sampling site were plotted against rainfall. No clear pattern was seen for Culex erraticus but Culex nigripalpus does show a peak in rainfall with a couple days lag with subsequent Culex nigripalpus increases especially in August and September.
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Table 2: Summation of Adult Catches by Distance
Percent of Zero meter Zero Fifty One Hundred Sum Catch Culex erraticus 1366 1004 1699 4069 74.27% Culex nigripalpus 190 275 366 831 15.17% Culex spp. 161 116 177 454 8.29% Culex restauns 12 8 7 27 0.49% Culex coronater 2 3 9 14 0.26% Culex 5 13 2 20 0.37% quinquefaciatus Culex territans 3 7 11 21 0.38% Culex salinarius 1 3 9 13 0.24% Culex peccator 0 2 0 2 0.04% Culex tarsalis 0 5 9 14 0.26% Culex pilosus 0 1 13 14 0.26% Sum by Distance 1740 1437 2302 5479
Percent of Total 31.76% 26.23% 42.01%
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Adult Catches of Culex erraticus by Spatial Point 250
200
150
0 meter 100
50 meter Number of Adults Number of 100 meter
50
0
Catch Night
Figure 7: Adult catches of Culex erraticus by spatial point*
*Notes: Sampling nights 9/5-9/6 and 9/23-9/24 at 50 meters yielded no results due to field errors.
26
Adult Catches of Culex nigripalpus by Spatial Point 50
45
40
35
30
25 0 meter 20
50 meter Number of Adults Number of 15 100 meter
10
5
0
Catch Night
Figure 10: Adult catches of Culex nigripalpus by spatial point*
*Notes: Sampling nights 9/5-9/6 and 9/23-9/24 at 50 meters yielded no results due to field errors.
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Number of Adult Culex erraticus Compared to Rainfall at Zero Meters 6 140
5 120 100 4 Number of Adult Culex erraticus
80 erraticus Culex 3 Rainfall in Centimeters 60
Rainfall (cm) Rainfall 2 40
1 20 Number of Adult Number of
0 0
8/7 9/4
7/10 8/28 12/4 7/17 7/24 7/31 8/14 8/21 9/11 9/18 9/25 10/2 10/9 11/6
10/16 10/30 11/13 11/20 11/27 12/11 12/18 10/23 Figure 11: Adult Culex erraticus compared to rainfall: 0 meters
28
Number of Adult Culex erraticus Compared to Rainfall at Fifty Meters
6 120
5 100
4 80 Number of Adult Culex erraticus 3 60 erraticus Culex Rainfall in centimeters
2 40 Rainfall(cm)
1 20
0 0
Number of Adult Number of
8/7 9/4
7/10 8/28 12/4 7/17 7/24 7/31 8/14 8/21 9/11 9/18 9/25 10/2 10/9 11/6
10/16 10/23 10/30 11/13 11/20 11/27 12/11 12/18 Catch Day
Figure 12: Adult Culex erraticus compared to rainfall: 50 meter
*Notes: Sampling nights 9/5-9/6 and 9/23-9/24 at 50 meters yielded no results due to field errors.
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Number of Adult Culex erraticus Compared to Rainfall at One-Hundred Meters
6 250
5 200
4 150 Number of Adult Culex erraticus 3 erraticus Culex 100 Rainfall in centimeters
2 Rainfall (cm) Rainfall
1 50
0 0
Number of Adult Number of
8/7 9/4
7/10 8/28 12/4 7/17 7/24 7/31 8/14 8/21 9/11 9/18 9/25 10/2 10/9 11/6
10/16 10/23 10/30 11/13 11/20 11/27 12/11 12/18 Catch Day
Figure 13: Adult Culex erraticus compared to rainfall: 100 meters
30
Number of Adult Culex nigripalpus Compared to Rainfall at Zero Meters
6 25
5 20
4 15 3 Number of Adult Culex nigripalpus Culex Culex nigripalpus 10 Rainfall in centimeters
2 Raiinfall Raiinfall(cm) 1 5
0 0
8/7 9/4
7/10 7/17 7/24 7/31 8/14 8/21 8/28 9/11 9/18 9/25 10/2 10/9 11/6 12/4
Numbers of Adults of Numbers
10/16 10/23 10/30 11/13 11/20 11/27 12/11 12/18 Catch Days
Figure 14: Adult Culex nigripalpus compared to rainfall: 0 meters
31
Number of Adult Culex nigripalpus Compared to Rainfall at Fifty Meters
6 50 45
5 40
4 35 30 Number of Adult Culex nigripalpus 3 25 20 nigripalpus Culex Rainfall in centimeters 2 Rainfall(cm) 15 1 10 5
0 0
Number of Adult Number of
8/7 9/4
7/10 7/17 7/24 7/31 8/14 8/21 8/28 9/11 9/18 9/25 10/2 10/9 11/6 12/4
10/30 10/16 10/23 11/13 11/20 11/27 12/11 12/18 Catch Day
Figure 15: Adult Culex nigripalpus compared to rainfall: 50 meters
*Notes: Sampling nights 9/5-9/6 and 9/23-9/24 at 50 meters yielded no results due to field errors.
32
Number of Adult Culex nigripalpus Compared to Rainfall at One-Hundred Meters
6 45 40 5
35
4 30 Number of Adult Culex nigripalpus 25 3 nigripalpus Culex 20 Rainfall in centimeters
2 15 Rainfall (cm) Rainfall 10 1 5
0 0
Number of Adult Number of
8/7 9/4
7/10 7/17 7/24 7/31 8/14 8/21 8/28 9/11 9/18 9/25 10/2 10/9 11/6 12/4
10/30 10/16 10/23 11/13 11/20 11/27 12/11 12/18 Catch Day
Figure 16: Adult Culex nigripalpus compared to rainfall: 100 meters
33
Statistical analysis
Multiple stepwise linear regressions were conducted for the major species: Culex nigripalpus and Culex erraticus as well for the total catch for Culex genus. The meteorological variables were rainfall accumulation for three accumulated rainfall and five day accumulated rainfall, minimum temperature, and minutes of daylight.
For Culex erraticus, the zero-meter trap model was found to be significant for minimum temperature (Partial R-square 0.1703, F-value 8.62, p-value 0.0054) as well at 100 meters (partial R- square 0.1860, F-value 9.82, p-value 0.0031). At the fifty-meter trap, the model found three-day rainfall accumulation (Partial R-square 0.3047, F-value 17.97, p-value 0.0001) was significant.
For Culex nigripalpus, the zero-meter trap model was found to be significant for daylight minutes (Partial R-square 0.3182, F-value 19.60, p-value < .0001) as well 100-meter (partial R-square
0.3054, F-value 9.82, p-value <.0001). Contrastingly, fifty-meter trap model found three-day accumulation (Partial R-square 0.0995, F-value 6.91, p-value 0.0121) and minimum temperature
(partial R-square 0.3245, F-value 19.69, p-value <.0001) significant components of the model.
Considering the total Culex catches at each spatial point, the zero-meter trap model was found to be significant for minimum temperature (Partial R-square 0.2475, F-value 13.82, p-value
0.0006) as well as the 50 minimum temperature (partial R-square 0.3245, F-value 19.69, p-value
<.0001). Daylight minutes were significant in the model at fifty-meter (Partial R-square 0.4023, F- value 27.6, p-value <.0001) and, 100-meter (partial R-square 0.2506, F-value 14.83, p-value <.0005).
A paired student t-test was used for what effect the three distances of zero meter, 50 meter, and 100 meter had on the mean total catches for Culex erraticus, Culex nigripalpus, and total
Culex adult catches. A significant different was found between 50-meter and 100-meter sampling site with for Culex erraticus (p-value 0.0493) and total Culex p-value 0.0266. For Culex nigripalpus, a significant difference (p-value 0.0362) was found between zero-meter and 100-meter sampling sites.
34
Table 3: Paired Student t-test for Culex erraticus catches by distances
Least Means Square for Distance Effect on Dependent Variable: Culex erraticus Pr > |t|for : LS Mean (i)= LS Means (j), <0.05
i/j 0 meters 50 meters 100 meters
0 meters 0.2936 0.3542
50 meters 0.2936 0.0493
100 meters 0.3542 0.0493
Table 4: Paired Student t-test for Culex nigripalpus catches by distances
Least Means Square for Distance Effect on Dependent Variable: Culex nigripalpus Pr > |t|for : LS Mean (i)= LS Means (j), <0.05
i/j 0 meters 50 meters 100 meters
0 meters 0.2567 0.0362
50 meters 0.2567 0.3396
100 meters 0.0362 0.3396
Table 5: Paired student t-test for total Culex catches by distances
Least Means Square for Distance Effect on Dependent Variable: Total Culex Pr > |t|for : LS Mean (i)= LS Means (j), <0.05
i/j 0 meters 50 meters 100 meters
0 meters 0.3805 0.1742
50 meters 0.3805 0.0266
100 meters 0.1741 0.0266
35
CHAPTER FOUR:
DISCUSSION
Investigating vector ecology for vectors of public health requires careful consideration of sampling techniques. Mosquitoes have particular bionomics, which distinguishes them in terms of oviposition site, environment where larval occurs, and feeding habits which affect dispersal patterns
(Horsfall, 1955). Even though the Culex vectors for the arboviral encephalitides share similar habitats and transmission dynamics (Diaz, Quaglia, & Contigiani, 2012) the sampling techniques are chosen for a particular piece of information regarding that vector’s ecology.
Egg Sampling Considerations
Analysis for egg raft collection in terms of statistical analysis was severely limited by lack of sample size. There was a high count of zeroes throughout the temporal period for all spatial points that led to inability run a linear regression with the meteorological variables. The number of excess zeroes within a data set can be, in some cases, treated with a zero inflated data to find a trend among the non-zero data points and zero data points. Possible models to deal with zero-inflated data in ecological research rely heavily upon categorization of zero in the data the research (Martin et al.,
2005). In this study, the uncertainty of the cause of the zeroes supports no statistical analysis due to the lack of support of statistical treatment of these cases in the literature (Martin et al., 2005).
Choosing a model could lead to misinterpreted data inferences and relationships.
The uncertainty of the categorization of zero type within the data lies within two potential explanations that deserve discussion. One explanation relates to the choice of sampling
36
methodology used to target the oviposition for the Culex genus. Whereas, the bucket containers with sod grass and rabbit chow infusion has been successful for Culex egg collection in other studies in other ecosystems (Dennett et al., 2007; Lampman & Novak, 1996); it may be that this sampling methodology was not successful in capturing the oviposition populations in this ecosystem. In this scenario, the explanation for any oviposition activity by Culex nigripalpus is due to their nondiscrimination of oviposition sites (Hribar, 2007; Jai Krishen Nayar, 1982; M. W. Provost, 1969).
The chosen methodology may not been attractive to Culex erraticus since they prefer to oviposit in permanent bodies of water with surface plants (W. E. Horsfall, 1955; William R. Horsfall & Morris,
1952; L. C. Robertson, S. Prior, C. S. Apperson, & W. S. Irby, 1993). Additionally, it must be noted that the lack of oviposition by other species within the genus Culex may be explained by the lack of attractive to the media due to the dilution by the rainfall especially during the hurricane season (Jai
Krishen Nayar, 1982). In contrast, the chosen urban wetland site may not have been a viable oviposition site for the Culex genus. Lack of oviposition may be supported further by the lack of detection of larvae within the aquatic habitat indicating that this site is not a viable habitat. This is supported by the fact that larvae detection indicates that the oviposition site for those species has an environment that provided proper nutrients and aquatic conditions for development (Silver &
Service, 2008).
Future direction is recommended to determine the explanation between these findings. A comparative trapping study needs to be conducted with the methodology used in this study and another oviposition methodology used in Florida involving the Culex genus. The proposed alternative trapping method would use the construction of artificial pooling from a wooden base with lining with an infusion hay and brewer’s yeast, which has been successful in capturing Culex populations in Florida (W. Smith & Jones, 1972). Use of aquatic surface plants could be placed in the pool for attraction for species like Culex erraticus, which are more likely to oviposit with aquatic
37
vegetation. This trapping would need to be extended for at least two active mosquito seasons to establish an adequate data set and account for meteorological fluctuations. If similar zero counts were seen in this comparative study, then a zero inflated ZIP model could be used to account for the excess zeroes within the population because the logistic of a true zero could be validated using a dataset over a longer temporal period (Lambert, 1992).
Gravid Sampling Analysis
Similarly to the egg sampling collection, the gravid traps yielded an excess number of zeroes with the majority of the gravid females trapped being Culex erraticus and Culex nigripalpus. The discussion regarding zero-inflated models in the egg collection applies to the gravid sampling analysis since the exact cause of zero is unknown. The analysis conducted was done solely under the assumption that this was a false zero that means that the species in question was present in the environment but not detected by the observer (Martin et al., 2005). The model used was a zero- inflated binomial regression with a model which accounts for two population distributions to accurately assess the false zeroes; however, when the model revealed that the data had violated one of the limitations of the zero-inflated regression model. This means that any inferences from this model could lead to false ecological premises (Martin et al., 2005).
In order to verify if this was due to sampling methodology or true absence of the vectors, a similar proposition to egg collection would need to be conducted. The hay and rabbit chow infusion would need to be compared with another infusion such as cow manure (Alahmed, 1998), which was successful in capturing gravid Culex in Florida (Allan, Bernier, & Kline, 2005) for two or more active seasons to catch an adequate sample. A significant difference between the two trappings would indicate that this infusion might not have been successful in this environment. On the other hand, if
38
similar numbers were found for both infusions with an absence of catches then this finding may be supported that this species is not actively seeking oviposition within this habitat.
Although the data was not sufficient to do any significant statistical analysis in relation to spatiotemporal effects of this ecosystem, there were some interesting findings. Gravid trapping did include some male Culex erraticus even more than with the baited carbon dioxide traps. This does support that Culex erraticus are ovipositing in the vicinity of this that ecosystem because males do not disperse far from their emergence (Klowden, 1990; Novak, 2013b). The capture of male Culex erraticus was not large enough to do any sort of analysis, but their presence in the trap supports the idea that the sample methodology was not adequate in this environment. Additionally, the collection of no Culex erraticus eggs but the presence of gravid female Culex erraticus further supports the idea this may be a sampling error. Detection of gravid females signifies that there are females in the environment in flight seeking an oviposition sight. Performing the proposed further research would be able to shed light into these results of this present study.
Adult Sampling Population and Trends
The predominant Culex adults collected were Culex erraticus and Culex nigripalpus, which support previous findings that these potential bridge vectors are found within wetlands (W. E.
Horsfall, 1955; M. W. Provost, 1969; Vander Kelen et al., 2012). One of the main purposes of this study was to address spatiotemporal patterns concerning Culex vectors, which was unfortunately not established due to insignificance of the models. For Culex erraticus the only significant spatial difference was between 50 and 100 meter points, which is against the hypothesis that there would be a spatial difference at each point especially between zero and 100 meter. This was based on the literature that Culex erraticus after oviposition would disperse farther into habitats for feeding (W.
Bidlingmayer, 1971). The spatial significance for Culex nigripalpus between 0 and 100 meter which fits
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the hypothesis that the Culex nigripalpus will have a greater mean catch farther from the aquatic habitat due to their dispersal capabilities (Barrera et al., 2010; Méndez et al., 2001; Nayar et al., 1980;
Nayar & Sauerman Jr, 1973; Salas et al., 2001). The total Culex catches significant difference was 50 and 100 meters, which relates to the question of the impact of this difference. The different of mean catches for all spatial points from the aquatic habitat, especially between 50 and 100 meters need to be further investigated before any speculations are made. It is acknowledged that the sampling points may have been too insignificant considering the dispersal habitats of Culex vectors at the center of this study which can range from average 0.4 km to 5.l km for Culex nigripalpus and an average distance of 0.73 km for Culex erraticus (L. K. Estep, N. D. Burkett-Cadena, G. E. Hill, R. S.
Unnasch, & T. R. Unnasch, 2010; Morris et al., 1991; Nayar et al., 1980).
Unfortunately, the models for Culex erraticus and Culex nigripalpus did not support the hypothesized relationship regarding meteorological variability. The regression model for Culex nigripalpus at zero and 100-meter had a significant correlation for daylight minutes. Since the daylight minutes are consistent at each trapping point, it was hypothesized that it be would found significant at all three distances. Only speculation can be made these findings were influenced by the high occurrence of rain and temperature during months of increased daylight minutes. This inconsistency questions the significance this relationship and needs further investigation. For the 50-meter model, the positive relationship between three-day accumulated rainfalls supports the previous literature regarding that Culex nigripalpus have increased catches after increasing amounts of rainfall due to increased flight activity (W. L. Bidlingmayer, 1974; J. F. Day, Curtis, Day, & Curtis, 1989; M. W.
Provost, 1969). At 50 meters, increases of adults could be attributed to the floodplain increases causing adults to disperse from the zero point to search for food or resting places; however, this does not account for why 100 meter does not have increased catches after increased rainfall and needs further investigation.
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Similar complications arose in findings for the models regarding Culex erraticus. All parameters were excluded from the zero and 100-meter traps except for minimum temperature. This finding is supported by the literature that Culex erraticus catches will decrease as the minimum threshold is reached (W. L. Bidlingmayer, 1985); however, this leads to the question of why this was not seen with Culex nigripalpus since their abundance is more affected by the change in minimum temperature change (W. L. Bidlingmayer, 1985; N. D. Burkett-Cadena et al., 2011). A longer sampling period along with multiple traps would allow for pooling of data to see if the relationship is continually seen.
The total Culex counts regression model indicates that at 50 meters and 100 meters increasing daylights minutes have an increasing number of catches but not at zero meters which is similar to the finding for Culex nigripalpus. To further investigate this relationship, daylight minutes should be compared to catches over a whole annual period to see if this relationship is significant for the whole year. A slight relationship between daylight and increased feeding rates in Culex quinquefaciatus could be one explanation for this finding because with increased feeding there will be increased flight activity (Mogi, 1992). This effect would best be further studied with Culex erraticus and Culex nigripalpus in a laboratory setting examining the photoperiod and flight activity.
Additionally, further recommended studies including dark minutes may be a more appropriate variable to test since it has greater physiological effects on insect populations (Saunders, 2013). With those recommendations, it must be addressed that increased daylight hours could be associated with high temperatures, which was not considered in the model. This was due to the lack of change of mosquito flight activity at an upper threshold in Florida (W.T. Bidlingmayer, 1985).
Overall, one of the limitations of this study was the lack of statistical significance in the models, but many questions were generated from the analysis that can lead to further research and direction. First, due to annual meteorological variation sampling should take place for multiple active
41
seasons to create power within the analysis, which will reduce the chance of finding false significant patterns. Further analysis upon this data regarding meteorological variables could be conducted, however, due to the analysis not being part of the original study design this may lead to false inferences and is beyond the scope of this study. The baited adult catches give an idea about vector presence within this ecosystem. Though analysis of the presence of adult vectors is limited to the relative abundance of adult species but conclusions are subject to limitations without adequate larval and egg data (Service & Silver, 2008).
Even with lack of data extracted from the models, there were some considerable insights into the adult female and male populations within the Culex genus. The sampling numbers by species and temporality gives baseline data for the adult populations within this ecosystem. The results showed that the predominant adult species within this semi-permanent swamp are Culex nigripalpus, which is a principal vector for SLE and potential bridge vector WNV, and Culex erraticus, which suspected bridge vectors for EEEV. The temporal pattern of Culex nigripalpus peaking in July and August was affirmed (Jai Krishen Nayar, 1982; O'Meara et al., 2010) and Culex erraticus numbers peaked in September and October, which is a slight shift from peaks in July through September
(Eddie W Cupp et al., 2003; Molaei et al., 2007; L. C. Robertson et al., 1993). This difference in temporality is probably due to the southern latitude of Florida or simply the pattern for this year, which can be influence by a myriad of environmental factors that fluctuate annually. These vector peaks coincide with the late seasonal epidemiology of SLE and WNE in Florida in late summer and fall. Additionally, other potential vectors of SLE and WNV were caught in the adults including Culex restauns, Culex quinquefaciatus, and Culex salinarius. A substantial portion of the total adult catches at
8.29% was Culex spp., which were species of the genus Culex subgenus Culex that could not be identified. For a better representation of these adults, identification using PCR would be advisable to identify mosquito species in further studies, but was a limitation within this study. Another
42
discussion point concerning the adult trap results was the absence of adult males except one in the baited carbon dioxide LT and few in the gravid traps. This reiterates the discussion that this area may not a suitable mating site nor is it in close proximity to newly emerged adults.
Due to the proximity of this urban wetland with the known presence of Culex vectors and potential Culex bridge vectors, a comprehensive study into these vectors dynamics should be conducted. This would include an avian site survey to detect the arboviral host composition. Also, blood-fed Culex females should be sampled to investigate the proportion of their feedings to determine host-feeding patterns (John D. Edman, 1979; Estep et al., 2011; Molaei et al., 2007).
Additionally, gravid females would be collected and viral detection would be performed to detect pools of arboviruses: WNV, SLEV, EEEV. Adult, larval, and egg collection would be used concurrently to detect vector abundance and oviposition. Suction traps and resting boxes would be beneficial additions to adult trapping to understand a true representation of adults including males
(W. L. Bidlingmayer, 1967; Eddie W Cupp et al., 2003; Silver & Service, 2008). This study should be conducted for multiple seasons to fortify seasonal patterns and establish overwintering patterns. A comprehensive study would allow concurrent studying of vector-host relationships within this particular environment, which would allow for better assessment of risk and surveillance.
Although, the egg collection and gravid sampling for Culex, specifically Culex nigripalpus and
Culex erraticus, did not confirm many significant findings, the study gives insight into this urban wetland ecosystem especially regards to the proposed bridge vector as well as raising a series of questions worth further investigation. Due to the public health impact of WNV, SLEV, and EEEV in Florida, it is advised to execute further studies to investigate these Culex species’ ecology to understand how this plays in transmission dynamics in these particular environments. This study provided baseline information for an urban wetland ecosystem in Hillsborough County that can serve as a platform for further research.
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