Molecular Discrimination of Phytoseiids Associated with the Red Palm Mite Raoiella Indica (Acari: Tenuipalpidae) from Mauritius and South Florida

Home , Amblyseius, Amblyseius largoensis, Brevipalpus phoenicis, Cecidophyopsis, Cydnoseius, Dypsis lutescens

MOLECULAR DISCRIMINATION OF PHYTOSEIIDS ASSOCIATED WITH THE RED PALM MITE RAOIELLA INDICA (ACARI: TENUIPALPIDAE) FROM MAURITIUS AND SOUTH FLORIDA

HEIDI MARIE BOWMAN

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2010

To my family and friends who have supported me throughout my academic endeavors

ACKNOWLEDGMENTS

I thank my advisor and chair of my graduate committee, Dr. Marjorie Hoy, for providing scientific guidance and financial support. I thank my committee members Dr.

Jorge Peña and Dr. Amy Roda for their professional and academic advice, their

contributions to my research proposal, and for reviewing this thesis. I would like to

acknowledge Dr. A. Jeyaprakash for his guidance in the laboratory and phylogenetic

analysis. I would like to extend appreciation to Dr. Denmark and Dr. Welbourn for their

taxonomic assistance. I would like to acknowledge Daniel Carrillo and Dr. Jorge Peña

for their assistance in collecting phytoseiid specimens in South Florida. I thank Michael

Dornburg, Karol Krey, Ryan Tanay, and Reggie Wilcox for their assistance in rearing

and maintaining the phytoseiid and prey colonies. I thank my family for their constant

support and encouragement of my academic endeavors. I also wish to give thanks to

Robert Cating for being an excellent friend, motivating labmate, and inspiration. Finally,

I wish to acknowledge my partner, Jorge Pérez Gallego, for his steadfast patience, love,

and support. Funding for this research has been provided by the USDA-APHIS and the

Davies, Fisher, and Eckes Endowment for Biological Control to Dr. M. A. Hoy.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS...... 4

LIST OF TABLES...... 7

LIST OF FIGURES...... 8

ABSTRACT ...... 9

CHAPTER

1 LITERATURE REVIEW ...... 11

Introduction ...... 11 The Red Palm Mite Raoiella indica (Acari: Tenuipalpidae)...... 13 RPM Dispersal and Range...... 13 RPM Hosts and Symptomology...... 14 RPM Description and Development ...... 15 U.S.A. RPM Regulatory Response...... 17 RPM Biological Control ...... 18 RPM Natural Enemies...... 19 Classical Biological Control and the Phytoseiidae ...... 20 The Phytoseiidae ...... 22 Phytoseiid Biology ...... 22 Amblyseius...... 24 Arthropod Identification...... 26 Species Concepts...... 26 Taxonomic...... 28 Biological...... 29 Phylogenetic...... 31 Molecular Markers ...... 33 The Mitochondrial Genome ...... 34 The Nuclear Genome ...... 35 Rate of Evolution ...... 36 Single-Copy Genes ...... 37 Availability of Related Sequence Data and Primer Design...... 38 Molecular Markers of Interest for This Study ...... 38 12S rRNA ...... 38 Cytochrome Oxidase I (COI) ...... 39 Elongation Factor-I Alpha (EF-I)...... 40 Random Amplified Polymorphic DNA (RAPD) PCR ...... 42 Research Objectives...... 45 Research Aim...... 45 Main Objectives...... 45

2 MOLECULAR DISCRIMINATION OF PHYTOSEIIDS ASSOCIATED WITH THE RED PALM MITE FROM MAURITIUS AND SOUTH FLORIDA ...... 59

Introduction ...... 59 Methods...... 62 Phytoseiid Collection and Colony Maintenance...... 62 DNA Extractions ...... 63 Amplification and Sequencing of Partial Mitochondrial 12S rRNA and Nuclear EF-I Genes ...... 64 Sequence Editing and Alignment ...... 65 Phylogenetic Analysis ...... 66 Pairwise Distance Analysis...... 67 High-fidelity-RAPD-PCR...... 67 Mitochondrial 12S rRNA Population-Specific Primers ...... 69 Results...... 70 ‘Amblyseius largoensis’ Bayesian Analysis and Sequence Divergence ...... 70 12S rRNA Sequences...... 70 Elongation Factor-I Alpha Sequences...... 73 High-fidelity-RAPD-PCR Analysis of ‘A. largoensis’ Populations...... 76 Mitochondrial 12S rRNA Population-Specific Primers ...... 77 Discussion ...... 77

APPENDIX: PERSPECTIVES...... 112

LIST OF REFERENCES ...... 114

BIOGRAPHICAL SKETCH...... 136

LIST OF TABLES

Table page

1-1 A list of Raoiella indica hosts reported in Florida...... 47

1-2 A list of viruses transmitted by Brevipalpus mites to their host plants...... 48

1-3 List of South Florida Amblyseius 'largoensis' collection sites...... 49

1-4 The partial 12S rRNA sequences from Phytoseiulus spp. submitted by Tixier et al. (2009) to GenBank ...... 50

1-5 Corrected pairwise distances between the partial 12S rRNA sequences from Phytoseiulus spp. submitted by Tixier et al. (2009) to GenBank...... 51

2-1 List of molecular markers used and expected PCR product size...... 82

2-2 List of GenBank accession numbers for clones and taxa included in the 12S rRNA Bayesian analysis...... 83

2-3 List of GenBank accession numbers for clones and taxa included in the EF- I Bayesian analysis...... 86

2-4 Corrected pairwise distances between unique mitochondrial 12S rRNA sequences obtained from the Mauritius and S. Florida ‘A. largoensis’ populations* with additional phytoseiid GenBank accessions using PAUP 4.0b8 with Kimura 2-parameter and among-site rate variation distance settings...... 88

2-5 BLAST searchs performed for the EF-Iα consensus tree clade-1 and clade-2 nucleotide sequences using the discontiguous megablast and the megablast algorithms in the GenBank database...... 89

2-6 List of GenBank accession numbers for clones and taxa included in the putative EF-I Bayesian analysis ...... 90

2-7 List of GenBank accession numbers for clones and taxa included in the ‘unknown elongation factor’ sequence group ...... 91

2-8 Corrected pairwise distances between the Mauritius and S. Florida ‘A. largoensis’ clones* putative EF-Iα amino acid and nucleotide sequences with additional phytoseiid GenBank accessions using PAUP 4.0b8...... 92

LIST OF FIGURES

Figure page

1-1 Map of current Raoiella indica range in Florida (Saeger 2010)...... 53

1-2 Map of Mauritius Amblyseius 'largoensis' collection sites...... 54

1-3 CLUSTAL X DNA alignment for partial 12S rRNA sequences from Phytoseiulus spp. submitted by Tixier et al. (2009) to GenBank...... 55

2-1 CLUSTAL X DNA alignment for partial mitochondrial 12S rRNA gene sequences from the S. Florida and Mauritius ‘A. largoensis’ populations with additional phytoseiid GenBank accessions ...... 93

2-2 CLUSTAL X amino acid alignment translated from partial nuclear EF-Iα gene sequences from the S. Florida and Mauritius ‘A. largoensis’ populations with additional phytoseiid GenBank accessions for the EF-Iα Bayesian analysis ...... 98

2-3 CLUSTAL X DNA alignment for partial nuclear EF-Iα gene sequences from the S. Florida and Mauritius ‘A. largoensis’ populations with additional phytoseiid GenBank accessions for the EF-Iα Bayesian analysis ...... 100

2-4 The 12S rRNA concensus tree was inferred using the MCMC method in MrBayes ...... 107

2-5 The EF-I concensus tree was inferred using the MCMC method in MrBayes with the assumption that all sequences represent a single gene...... 108

2-6 The putative EF-I concensus tree was inferred using the MCMC method in MrBayes assuming two different genes are present...... 109

2-7 The evolutionary history obtained from the high-fidelity-RAPD-PCR markers 196 and 199 for S. Florida and Mauritius ‘Amblyseius largoensis’ populations was inferred using the Neighbor-Joining method in PAUP 4.0b10 ...... 110

2-8 High-fidelity PCR products obtained from the Mauritius and S. Florida colonies using 12S rRNA population-specific primers ...... 111

Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science

MOLECULAR DISCRIMINATION OF PHYTOSEIIDS ASSOCIATED WITH THE RED PALM MITE RAOIELLA INDICA (ACARI: TENUIPALPIDAE) FROM MAURITIUS AND SOUTH FLORIDA

Heidi Marie Bowman

May 2010

Chair: Marjorie A. Hoy Major: Entomology

Since the red palm mite invasion into South Florida and the Caribbean, endemic phytoseiids have been unable to suppress populations or spread of this damaging pest.

In response, phytoseiids were imported from Mauritius for evaluation for a classical biological control program. The Mauritius and Florida phytoseiid populations were both morphologically identified as Amblyseius largoensis Muma. Bayesian analysis and sequence divergence calculations of the mitochondrial 12S rRNA and nuclear EF-Iα genes and Neighbor-Joining analysis of High-fidelity-RAPD-PCR markers were used to discriminate between the two populations. Variability within the 12S gene also was used

to develop population-specific primers for identifying the Mauritius phytoseiid in the

event it is released in South Florida. Bayesian and sequence divergence analyses of

the 12S rRNA sequences suggest that the Mauritius and S. Florida populations

represent two different species. These results were supported by the High-fidelity-

RAPD-PCR markers that indicate the two populations’ genomes are genetically distinct.

However, the EF-Iα gene Bayesian analysis places the two populations within the same

clade. The degenerate EF-Iα primers used to survey the phytoseiids amplified two

different elongation factor sequences with distinct amino acid translations identified as the putative EF-Iα and an unknown elongation factor. As a result of the incongruence

between the 12S, EF-Iα, and RAPD analyses, a conclusion cannot be made as to

whether the Mauritius and S. Florida populations are cryptic species or biotypes of ‘A. largoensis’ without weighing the results of one analysis as more significant than the other.

CHAPTER 1 LITERATURE REVIEW

Introduction

The globalization of trade and travel has resulted in an increased movement of

exotic pestiferous arthropods on infested plant materials into America’s major ports of

entry (US Bureau of the Census 1998; Bryan 1999; Pimentel et al. 2000). In 2004, the

red palm mite (RPM) Raoiella indica Hirst (Acari: Tenuipalpidae) was detected for the first time in the Western Hemisphere on the Caribbean Island of Saint Lucia (Kane et al.

2005). It subsequently spread rapidly throughout the Caribbean and was detected in

South Florida in 2007. The RPM is a destructive pest known to attack numerous species of commercial and ornamental palms, plantains, bananas, and gingers

(Welbourn 2009). Feeding damage results in reduced commodity yield and value

(Borchert and Morgosian 2007) and, as a quarantinable pest, its spread within the

Caribbean and Florida has resulted in the loss of domestic and foreign markets for nursery stock and propagative materials (Meissner et al. 2009).

In response to the threat of RPM to the USA and Puerto Rico, a Red Palm Mite

Technical Working Group was developed. The group consists of experts in biological control, acarology and regulation, with the mission to provide scientific and technical information for surveying, detection, identification, and management of the RPM (DeFeo

2006). An integrated approach including biological control was determined to be the

best option for widescale mitigation (Roda et al. 2008). Peña et al. (2009) conducted

surveys of natural enemies associated with the pest in the Caribbean and South Florida

and identified the entomopathenogenic fungus Hursutella, several phytoseiids, and

generalist arthropod natural enemies. A classical biological control approach also was

adopted and Dr. Marjorie A. Hoy collected phytoseiid populations associated with the

RPM on coconut palms on the island of Mauritius where it is not known as a pest. The

Mauritius phytoseiids and the South Florida phytoseiid populations associated with the

RPM on coconut palms were identified using morphological characters as Amblyseius largoensis Muma by taxonomists Dr. Cal Welbourn (Florida Department of Agriculture and Consumer Services (FDACS), Division of Plant Industry (DPI), Gainesville, Florida) and Dr. H. A. Denmark.

Correct identification of candidate organisms in classical biological control programs is critical. Misidentifications within the Phytoseiidae can occur due to the presence of relatively few taxonomic characters and cryptic species (McMurtry et al.

1976; Hoying and Croft 1977; Da Silva Noronha and de Moraes 2004; Nijhout 2003;

Tixier et al. 2006a, 2008b). Therefore, it was proposed that the imported Mauritius phytoseiid populations’ morphological identification should be followed by other methods of identification, such as reproductive compatibility and molecular markers. If the Mauritius phytoseiid populations are able to feed, survive and reproduce on a diet consisting only of RPM, and found to be more efficacious RPM predators than the phytoseiids currently in South Florida, then methods for discriminating between two

morphologically similar populations must be developed to evaluate their establishment,

dispersal, and efficacy in the field (de León et al. 2006).

The objective of this research is to discriminate between phytoseiids associated

with the red palm mite on coconut palms from Mauritius and South Florida using partial

sequences from the mitochondrial 12S gene and a nuclear gene, elongation factor-1

(EF-I), to evaluate Random Amplified Polymorphic DNA-PCR markers as tools for

discriminating between the two populations, and to develop a molecular marker for identifying the Mauritius phytoseiid populations in the event they are released in South

Florida.

The Red Palm Mite Raoiella indica (Acari: Tenuipalpidae)

RPM Dispersal and Range

RPM females are more mobile than other life stages and are considered to be

mainly responsible for dispersal (Kane et al. 2005). It is believed that the RPM dispersed throughout the Caribbean through movement of nursery material, seed coconuts, and handicrafts constructed from infested coconut leaves for the tourist industry on Caribbean islands (Mendonca et al. 2005; Peña et al. 2006; Welbourn

2009). The RPM also is believed to disperse on the wind so that a strong tropical storm or hurricane could distribute the RPM over a wide area (Hoy et al. 2006; Peña et al.

2006).

The RPM occurs mostly in tropical and subtropical climates (Dowling et al. 2008).

The RPM was first described from India in 1924 from coconut palms and is found

throughout the Asiatic region (India, Egypt, Israel, the Philippines, Mauritius, Reunion,

Malaysia, Sudan, Oman, Pakistan, and the United Arab Emirates) (Hirst 1924; Kane et

al. 2005; Hoy et al. 2006; Dowling et al. 2008; Roda et al. 2008). Dowling et al. (2008)

hypothesize that the genus Raoiella originated in the Australasian region, spread to

occupy the Middle East, and that the United Arab Emirates and Iran may be the origin of

the species R. indica.

The RPM was first detected in the Western Hemisphere during survey work on the

Caribbean islands of Martinique and St. Lucia in 2004 and by 2005 it was detected on

the neighboring island of Dominica (Kane et al. 2005; Peña et al. 2009). In 2006, RPM

was reported in the Dominican Republic, Puerto Rico (Rodrigues et al. 2007),

Guadeloupe, St. Martin, and Trinidad-Tobago (Kane et al. 2005; Etienne and

Fletchmann 2006). Uncontrolled, this pest continued to spread and, by 2007, it was detected in Grenada, Venezuela, the US Virgin Islands, Haiti, and Florida’s Palm Beach counties (Peña et al. 2006). Since 2007, it has been detected in Cuba and Bahamas,

Brazil, and Venezuela (Roda et al. 2008; Vasquez et al. 2008; Jorge Peña, pers. comm). As of September 2009, the RPM has been found in 439 sites in six Florida counties: Broward, Lee, Martin, Monroe, Miami-Dade, and Palm Beach (Figure 1-1)

(Caps surveys 2010; Welbourn 2009). It is predicted that the reported host range for the

RPM limits their potential spread to areas with a USDA Plant Hardiness Zone of 9 or greater. Within the USA, Lousiana, Arizona, Texas, Alabama, Mississippi, South

Carolina, Georgia, Nevada, and California may be at risk (Borchert and Morgosian

2007). Mexico, Southern and Central America also are suitable for a RPM invasion

(Borchert and Morgosian 2007).

RPM Hosts and Symptomology

The RPM is primarily found on the abaxial surface of host leaves along the midrib

(Jepson et al. 1975; Etienne and Fletchmann 2006; Rodrigues et al. 2007). It attacks 27 known palm hosts (Palmaceae) including the areca palm (Dypsis lutescens H.

Wetland), coconut palm (Cocos nucifera L.), canary island date palm (Phoenix

canariensis Chabaud), date palm (Phoenix dactylifera L.), as well as bananas, plantains

(Musaceae: Musa spp.), and gingers (Zingiberaceae: Zingiber spp.) in the Caribbean

and South Florida (Welbourn 2009) (Table 1-1).

On coconut, there is a higher density of the RPM on older (lower) leaves, with

infestations sometimes reaching 4,000 individuals of all life stages per leaflet (Kane et

al. 2005; Peña et al. 2009). Feeding by RPM on healthy coconut fronds results in bright green leaflets turning to pale green; yellow spots soon appear, next chlorotic spots coalesce, and eventually the leaflets develop large copper-brown necrotic spots

(Rodrigues et al. 2007). Depending on the severity of infestation, the bronzing symptoms can be exhibited within two to three months of RPM feeding on coconut

(Roda et al. 2008). Kane et al. (2005) suggest that plants infested with RPM exhibit symptoms similar to plants with nutrient deficiencies or lethal yellowing. It is unknown whether the RPM can vector plant pathogens; however, several species belonging to the genus Brevipalpus (Tenuipalpidae), are associated with plant viruses in the family

Rhabdoviridae (Table 1-2) (Childers et al. 2003; Rodrigues et al. 2004; Kitajima et al.

2003). This suggests that the potential of the RPM as a virus vector needs to be investigated.

RPM Description and Development

All life stages of the RPM, including eggs, are varying shades of red, although the

adult females exhibit dark patches on their dorsum after feeding. The RPM has a flat

body with long, spatulate, and slightly serrate dorsal setae on both sexes. The body of

the adult RPM does not have striae and is smooth except for the presence of punctae

(Sayed 1942). The first pair of dorsocentral hysterosomal setae is longer than the

others; the fourth pair of dorsosublateral setae is shorter than the first pair (Sayed 1942;

Peña et al. 2006; Hoy et al. 2006). A droplet of fluid produced at the tip of dorsal setae

can be observed on immature and adult RPM (Welbourn 2009). The function of these

droplets is unknown but, anecdotally, is believed to be repellent to predators. The

female is approximately 0.32 mm long (245 microns), 0.18 mm wide (182 microns) and

oval in shape (Nageshachandra and Channabasavanna 1984). The male is distinctly

smaller than the female and triangular in shape. Larvae are 0.18 to 0.20 mm long and the nymphs are 0.18 to 0.25 mm long. The larval stage has 3 pairs of legs in contrast to the protonymph and adults, which have 4 (Welbourn 2009). Eggs of the RPM are ovoid with one end slightly broadened and smooth, averaging 0.1 mm in length (100 microns) and 0.08 mm (80 microns) in width (NageshaChandra and ChannaBasavanna 1984;

Hoy et al. 2006). They are deposited in patches of 110-330 eggs on the abaxial leaf surface (Moutia 1958; Kane et al. 2005; Peña et al. 2006). The egg is attached directly to the leaf surface and a slender white stipe, as long as or longer (170-210 m) than the egg and with a coiled tip, is located on the free end of the egg (Nageshachandra and

Channabasavanna 1984). Like the setae of the adults, a droplet of fluid may be present on the tip of the egg stipe. It is not known if the egg produces the droplet or if the adult female provides it during oviposition. The incubation period averages 8 days for fertilized and 7.3 days for unfertilized eggs (Hoy et al. 2006; Welbourn 2009).

Studies of RPM development and ecology on the coconut palm were published by

Moutia (1958), Nageshachandra and Channabasavanna (1984), and Zaher et al.

(1969). Nageshachandra and Channabasavanna (1984) propose that the RPM genetic system is arrhenotoky, which they described as mated females producing only female progeny and unmated females producing only males. In Egypt, the RPM developed all year with a generation time of 3 to 4 weeks at 23 to 28C (Gerson et al. 1983). The development time for females from egg to adult is 23 to 28 days and the adult life span is approximately 30 days at 23.9-25.7C. Mated females have a 5 to 6 day preoviposition period, can lay on average 28 to 38 eggs (Zaher et al. 1969), and oviposit over 47 days under laboratory conditions. Unmated females have a 2-day preoviposition

period, can deposit on average 18 eggs, and oviposit for 40 days. The development time for males from egg to adult is 20 to 22 days, with a life span of approximately 26.5 days at 23.9-25.7C (Nageshachandra and Channabasavanna 1984; Hoy et al. 2006;

Welbourn 2009).

U.S.A. RPM Regulatory Response

In response to the threat of RPM to the USA and Puerto Rico, a Red Palm Mite

Technical Working Group, consisting of experts in biological control, acarology and

regulation, was created in 2006 (DeFeo 2006). It was given the task of developing a

protocol for surveying RPM distribution and a plan for mitigating its spread and damage.

The group determined that eradication was not a viable option, but, instead, an

integrated management plan including biological control and limited use of pesticides

would be the most appropriate and feasible management strategy.

The United States Department of Agriculture’s Animal and Plant Health Inspection

Service (USDA-APHIS) Center for Plant Health Science and Technology (Plant Pest

Quarantine) and Cooperative Agricultural Pest Survey (CAPS) conducted field surveys

in nurseries, residential areas, marinas, and maritime ports in Florida (only here).

Surveys involved visual inspection of hosts for damage and presence of RPM colonies,

as well as sample collection for identification by Dr. Cal Welbourn (FDACS-DPI).

Permanent survey sites (Sentinel Sites) were developed in high-risk areas and totaled

579 sites in 11 Florida counties (CAPS surveys 2008). Once RPM is detected in an

area, delimiting surveys of the environment and host nurseries are conducted.

As of 2009, once RPM is detected in a Florida nursery or a plant broker site, a

Compliance Agreement (required for handling regulated material) must be signed and

followed (Bronson 2009). A low-level RPM tolerance approach has been adopted because complete control using acaricides is no longer considered feasible due to pressures from RPM-infested palms in the areas surrounding south Florida nurseries. A combination of approved acaricide treatment(s) and biological control is suggested to

reduce RPM populations (Bronson 2009). Chemical control tactics and a clean

certification are required for the movement of host plants to a non-infested state

(Bronson 2009; Peña et al. 2009). For instance, the miticides approved by Texas for

RPM treatment are bifenazate, spiromesifen, acequinocyl, efoxazole, and milbemectin

(Bronson 2009).

RPM Biological Control

The RPM Technical Working Group determined biological control was the best option for widescale mitigation of the pest (Roda et al. 2008). Biological control of

arthropod pests is the reduction of populations by their natural enemies, thereby

reducing the environmental, human health, and application costs associated with

pesticide application(s) (Van Drieshe and Bellows 2001). The three approaches

commonly used in biological control programs are conservation of natural enemies,

classical biological control, and augmentation (McMurtry 1982; Van Drieshe and

Bellows 2001; Naranjo 2001). Multiple studies of natural enemies have been conducted

throughout the range of the RPM within the Eastern and Western Hemispheres (Daniel

1981; Somchoudhury and Sarkar 1987; Gassouma 2006; Peña et al. 2009). In addition,

a classical biological control approach utilizing phytoseiid populations collected in

Mauritius (by M. A. Hoy) is being evaluated. Augmentation has been considered, but multiple releases of commercially available phytoseiid predators may not be economically feasible for widescale mitigation efforts, especially in the landscape.

RPM Natural Enemies

In the Eastern Hemisphere, surveys of local natural enemies associated with the pest have been conducted (Daniel 1981; Somchoudhury and Sarkar 1987; Gassouma

2006). In the United Arab Emirates, two arthropods are considered to do an excellent

job in suppressing the RPM, a phytoseiid mite Cydnoseius negevi Swirski-Amitai that is

active all year and a neuropteran (Chrysopa sp.) that is active during the winters

(Gassouma 2006). In 1958, Moutia observed that Amblyseius caudatus Berlese was an

important predator of RPM eggs on coconut palms in Mauritius. Somchoudhury and

Sarkar (1987) found Oligota sp. (Coleoptera: Staphylinidae), Phytoseiulus sp. (Acari:

Phytoseiidae), and Amblyseius sp. (Acari: Phytoseiidae) to be the prevalent RPM

natural enemies on coconut palms in India. Daniel (1981) considered a phytoseiid,

Amblyseius channabasavanni Gupta, and a coccinellid beetle, Stethorus keralicus

Kapur, to be the most important predators of the RPM on palms in India.

Once the RPM was detected in the Western Hemisphere, its range rapidly

increased throughout the Caribbean. During survey work, indigenous natural enemies in

Puerto Rico and Trinidad and Tobago were observed feeding on the RPM on coconut

palms (Peña et al. 2009). These include Amblyseius spp. (Phytoseiidae), the thrips

Aleurodothrips fasciapennis Franklin (Thysanoptera: Phlaeothripidae), cecidomyiid

(Diptera) larvae, the coccinellid Telsimia ephippiger Chapin (Coleoptera), lacewings

(Neuroptera), and entomopathogenic fungi (Hirsutella) (Peña et al. 2009). In Trinidad and Tobago, Amblyseius largoensis (Muma) populations were found to increase in response to the RPM population increases as well as follow the movement of the pest within coconut palm canopies (Roda et al. 2008; Peña et al. 2009). The predatory mite

A. largoensis also has been found in association with the RPM in Puerto Rico, but it has

not been shown to reduce RPM infestations to an acceptable level (Peña et al. 2009) and the RPM continues to increase its population density and range throughout the

Caribbean (Roda et al. 2009). Therefore, it may be surmised that the natural enemies

found associated with the RPM in the Caribbean are not doing an adequate job in

suppressing the RPM at this time.

In anticipation of the RPM entering Florida, Peña et al. (2009) surveyed

predacious arthropods inhabiting palms and bananas in the Homestead area between

December 2006 and January 2008. He found Amblyseius largoensis, Bdella distincta

Baker and Balock (Acari: Bdellidae), Stethorus utilis Horn (Coleoptera: Coccinellidae),

an unidentified cecidomyiid, and an unidentified predaceous thrips (Phaeothripidae)

associated with the RPM. Peña et al. (2009) question the capability of A. largoensis to

maintain the RPM at low densities in S. Florida. Subsequently, Dr. Peña and Daniel

Carrillo have been studying the efficacy of Florida A. largoensis populations as control

agents of the RPM.

The observed inability of local natural enemies in the Caribbean to control the

RPM populations to date raises concerns as to whether Florida’s natural enemies will

be sufficient. In the situation where the endemic natural enemy species are unable to

control the RPM, a classical biological control program could provide additional control.

Classical Biological Control and the Phytoseiidae

Classical biological control involves importation of natural enemies believed to have coevolved with the pest and, therefore, are believed to be effective at controlling the

pest populations (Van Driesche and Bellows 2001). To determine where to collect a

candidate for biological control, one must look to where the pest is not considered a

problem. This is because, in theory, the natural enemies that have evolved with them

keep the pest populations in check. Phytoseiid predators are considered an appropriate choice for biological control due to their small size and ease of rearing. Of the 1000 phytoseiid species known, approximately 30 have been successfully utilized to control tetranychid mites in agronomic systems such as greenhouses, vineyards, citrus, cassava, apple, almonds, cotton, corn and strawberries (McMurtry and Croft 1997;

Logan 1981; Hoy 1982, 1985). To determine whether a phytoseiid or phytoseiid

complex will provide adequate control of a pest, several characteristics must be

considered: the intrinsic rate of increase should be higher than that of the pest; habitat

and prey preferences should be appropriate; and ability to disperse and persist in the

new environment is essential (Kiritani and Dempster 1973; Luck et al. 1988; Herren and

Neuenschwander 1991; Bellows et al. 1992; Yaninek et al. 1992; Yaninek 2007).

An historic example of a successful classical biological control program utilizing a

phytoseiid predator is that of the cassava green mite Mononychellus tanajoa (Bondar)

(Acari: Tetranychidae) (Yaninek and Herren 1988). The cassava green mite was a

devastating introduced pest of cassava (Manihoti esculenta Crantz (Euphorbiaceae)) in

Africa. The pest was responsible for direct losses of 60% within a short period of time

after its introduction and created a famine (Gutierrez et al. 1988; Yaninek and Herren

1988; Löhr et al. 1990; Herren and Neuenschwander 1991). In several regions of South

America the cassava green mite was not considered a significant pest of cassava.

Those areas were surveyed for candidate natural enemies, resulting in the discovery of

over 50 phytoseiids associated with the pest. Of those 50, three species became

established in Africa, two of which spread beyond the original release sites (Yaninek et

al. 1992). One, Typhlodromalus aripo DeLeon, was found to be an effective predator of

the cassava green mite and became established in over 20 countries (Yaninek 2007).

Onzo et al. (2003) determined T. aripo was the best predator because of its ability to establish, disperse, and persist due partially to its ability to use cassava leaf tips as refugia.

The Phytoseiidae

The family Phytoseiidae Berlese (Acari: Mesostigmata or Gamasida) has a

worldwide distribution and consists of approximately 1,984 valid species within 89

genera and three subfamilies (de Moraes et al. 2004b; Keiter and Tixier 2006; Chant

and McMurtry 2007; Tixier and Kreiter 2009). The Phytoseiidae have been studied at

great length with over 4000 publications between the years 1960 to 1994 (Kostiainen

and Hoy 1996). Most of these publications focused on their role as biological control

agents of phytophagous mites (McMurtry 1982; Helle and Sabelis 1985; Pickett and

Gilstrap 1986; James et al. 1995; McMurtry and Croft 1997; Gerson et al. 2003; de

Moraes et al. 2004a).

Phytoseiid Biology

The chromosome number of phytoseiids may vary (2n=6 or 8) and most are

parahaploid (Hoy 1979; Nelson-Rees et al. 1980; Hoy 1985). The life stages include:

egg, larva, protonymph, deutonymph, and adult female or male. The sex ratio varies

between species and is affected by population density and food availability, but tends to

be female biased. Male phytoseiids select female mates through contact with sex

pheromones (Hoy and Smilanick 1979) emitted from macropores located on the dorsal

shield of protonymphs, deutonymphs, adult virgins, and gravid females (Rock et al.

1976). Males can be observed hovering over females selected for reproduction and

mating occurs with males venter to venter with females (Rock et al. 1976; Hoy and

Smilanick 1979).

Females will oviposit in clutches (Nagelkerke et al. 1996). Egg production is

affected by temperature and substrate, species, biotype, number and species of prey

consumed, prey stage consumed, species of pollen and/or combination of plant-animal

diet and their relative seasonal availability and abundance (Ragusa and Swirski 1977;

Bruce-Oliver and Hoy 1990; Gnanavossou et al. 2003; Emmert et al. 2008). The

developmental period for most studied phytoseiid species averages 6.08 days at 27°C

and, depending on the abundance of food, a single female may produce 2-4 eggs /

female / day (Ragusa and Swirski 1977; Tanigoshi 1981; Bruce-Oliver and Hoy 1990;

Gnanavossou et al. 2003; Emmert et al. 2008). If optimal conditions are present, this

translates to ca. 50 generations in one year.

Prey preference and biology will differ between species of the Phytoseiidae

(McMurtry and Croft 1997) and also may occur between feral and colonized strains

(Knipling 1984; Mwansat 2001). Searching for prey is elicited by physical and chemical cues (kairomones, excreta, exuviae) (Hislop et al. 1978; Hoy and Smilanick 1981).

Phytoseiid populations may be locally adapted to certain hosts, host plants, and climatic

regimes (Hoy 1975a, 1975b, 1984).

The Phytoseiidae may be composed of local populations, perhaps because they

have a relatively low mobility and rely on wind currents and movement of plant materials

by natural or human means. These characteristics make phytoseiids susceptible to local

selection pressures from the natural environment and agricultural practices (Hoy and

Knop 1979; Hoy et al. 1979). Local populations may exhibit varying degrees of pesticide

resistance and differences in mating behaviors (Hoy and Cave 1985). With this in mind,

it may be more useful to approach the utility of phytoseiids as biological control agents

by population characteristics instead of the traditional species approach.

Amblyseius

Amblyseius species are used as biological control agents in organic and IPM

systems to control broad mites (Polyphagotarsonemus latus (Banks), Acari:

Tarsonemidae) (Jovicich 2007), two-spotted spider mite (Tetranychus urticae Koch),

chili thrips (Scriptothrips dorsalis Hood) (Arthurs et al. 2009), flower thrips (Frankliniella

occidentalis Pergande) (Ship and Wang 2003), greenhouse whitefly (Trialeurodes

vaporariorum (Westw.)), and tobacco whitefly (Bemisia tabaci Gennadius) (Nomikou et al. 2001).

The placement, status, and content of the genus Amblyseius have been in debate

for the past 35 years (Denmark and Muma 1989). The genus Amblyseius (Amblyseius)

Berlese (Phytoseiidae: Amblyseiinae) contains 295 species organized into 16 species

groups (and one unassigned species group) and is the largest genus within the

subfamily Amblyseiinae Muma (Chant and McMurtry 2006; Tixier et al. 2008a). The

Neotropical region (South and Central America, Caribbean islands, and Florida) has the

highest percentage of total endemic Amblyseiinae species and therefore, is

hypothesized as the center of origin for the subfamily (Chant and McMurtry 2006; Tixier

et al. 2008a).

Amblyseius largoensis. Native populations of phytoseiid mites associated with

the RPM in Florida, Trinidad, Tobago, and Puerto Rico have been morphologically

identified as A. largoensis. It is considered to be a type-III generalist predator,

consuming prey, pollen, and nectar (Yue and Tsai 1996; McMurtry and Croft 1997). In

addition to association with the RPM in Florida and the Caribbean, it has been observed preying on two pests of coconut palm, Aceria guerreronis Keifer (Acari: Eriophyidae) in

Brazil (Yue and Tsai 1996) and Rarosiella cocosae Rimando, a synonym of R. indica,

(Acari: Tenuipalpidae) in the Philippines (Peña et al. 2009).

The Amblyseius largoensis species group is geographically widespread and includes 11 closely related species: A. largoensis, A. sakalava Blommers, A. herbicoloides McMurtry and de Moraes, A. herbicolus (Chant), A. nambourensis

Schicha, A. phillipsi McMurtry and Schicha, A. fletcheri Schicha, A. vazimba Blommers,

A. adhatodae Muma, and A. ankaratrae Blommers (Denmark and Muma 1989). This species group is distinguished morphologically by slight differences in setal lengths, shapes of spermathecal cervices, and the posterior margin of the sternal shield

(McMurtry and de Moraes 1984; Denmark and Muma 1989). In 1952, M. H. Muma collected the A. largoensis female holotype from key lime leaves in Key Largo, Florida, but its original geographic range is unknown. The species A. sakalava (female holotype,

Madagascar) is the most morphologically similar species to A. largoensis among the species currently within the largoensis group but differs in having the spermatheca approximately 1/3 longer and the L2 setae twice as long (Denmark and Muma 1989).

Amblyseius largoensis and A. herbicolus (female holotype, Portugal) are the only two species within the largoensis group that are considered cosmopolitan in distribution

(McMurtry and de Moraes 1984; de Moraes et al. 2004b), which could be due to movement of plants by humans. Some distribution overlap is known for A. largoensis and A. herbicolus because both have confirmed records in Florida (USA) (Denmark and

Muma 1989). However, the range of A. herbicolus is considered to extend to higher

latitudes (confirmed in CA, USA) than A. largoensis and, although both are reported in

Florida, they have not been reported together at the same site (McMurtry and de

Moraes 1984).

Arthropod Identification

In biological control, identification is an essential step to selecting the most

suitable natural enemy, evaluating establishment, and improving mass production (Mahr and McMurtry 1979; Gordh and Beardsley 1999; de León et al. 2006). In 2007, M. A.

Hoy collected phytoseiid populations associated with the RPM on coconut palms on the island of Mauritius (Figure 1-2). These populations were identified as ‘Amblyseius largoensis’ Muma by Dr. Cal Welbourn (FDACS-DPI, Gainesville, Florida) and Dr. H. A.

Denmark using morphological characters. Populations of phytoseiid predators associated with the RPM also were collected from several sites in South Florida (Table

1-2) and identified as ‘A. largoensis’ by Dr. Cal Welbourn and Dr. H. A. Denmark.

Interestingly, the RPM is not considered a pest in Mauritius but in South Florida, its population and range has increased since its detection in 2007. This may suggest that the Mauritius populations are more efficient predators of the RPM than the S. Florida populations. If so, the Mauritius and Florida populations could be biotypes or cryptic species but cannot be discriminated using morphological characters alone. An approach utilizing reproductive compatibility as well as morphological and molecular techniques may be best, especially in discerning biotypes and cryptic species (de León et al. 2006), but first, we must answer the question, how do we define a species?

Species Concepts

A definition of “species” is considered essential for testing biological theories. A species is the basic unit of taxonomy and is made up of evolutionarily distinct

populations. However, defining a species may not be as easy as identifying a definitive morphological character, reproductive isolation, or distinguishable genotypes or

genomic homology (Mallet 2006). This is because evolution is constant and events such

as introgression, hybridization, and cryptic species (phenotypically similar species which

do not interbreed) occur (King and Stansfield 1985; Prowell et al. 2004; Rubinoff and

Holland 2005; Buckley et al. 2006).

Taxonomic, biological, and phylogenetic operational species definitions are just a

few of the many used today (King and Stansfield 1985). All three species concept

approaches require the taxonomist to judge how similar or different populations must be

to be considered a species. In the end, the definition of a species can be different from

scientist to scientist, resulting in some being considered "splitters" and some "lumpers".

Each definition has its strengths and limitations, however.

There are three types of systematic errors inherent in every species concept:

overestimation and underestimation of the number of species, and misrepresenting their

phylogenetic relationships (Adams 1998). The first two errors are, simply, incorrect

estimations of the number of species. The third occurs when an interpretation of

phylogenetic relationships among species is incongruent with recovered evolutionary

history (Adams 1998). If two populations are determined separate species, it is

predicted that they are on independent evolutionary trajectories that will continue to be

independent in the future (i.e. hybridization will not occur) (Adams 1998). To avoid

making such predictions, some scientists approach the definition of a species as only a

snapshot of constant evolutionary change and that haplogroups may represent

evolutionary lineages (Williams et al. 2006; Coleman 2009). In summation, all operational species definitions have advantages, caveats, and appropriate applications.

Taxonomic

The taxonomic species concept is based on morphological or phenetic characters and consists of phenotypically distinguishable groups of coexisting organisms.

Distinguishable morphological characters develop when divergent natural selection

leads to gaps in the distribution of at least one or more morphological traits (Darwin

1859). Characters such as dorsal seta length, leg chaetotaxy, spermatheca shape, and

cheliceral dentition typically are used to identify the Phytoseiidae to species (Chant and

McMurtry 1994, 2006). However, there are disagreements between taxonomists on

what morphological characters should be used as the major criteria for species

distinction and genus status (Tixier et al. 2008b, 2008c). In addition, taxonomists may

have opposing views on how similar organisms must be to be defined a species. The

Phytoseiidae have relatively few morphological characteristics to differentiate between

closely related or cryptic species (Edwards and Hoy 1993; Hoy et al. 2000; Da Silva

Noronha and de Moraes 2004; Tixier et al. 2006a, 2006c). Identification can be tedious

because the time required for morphological identification of taxa scales inversely with

body size (Lawton 1998). The lack of discriminating morphological characters within a

group can lead to an underestimation of species diversity (Fukami et al. 2004).

Furthermore, polyphenisms (intraspecies or population variation) within a species can

lead to misidentifications (McMurtry et al. 1976; Hoying and Croft 1977; Da Silva

Noronha and de Moraes 2004; Nijhout 2003; Tixier et al. 2006a, 2008b) with negative

consequences (Miller and Rossman 1995; Unruh and Woolley 1999).

Following the taxonomic species concept, the S. Florida and Mauritius populations belong to the species ‘A. largoensis’ because specimens from both populations were identified as such by two taxonomists Dr. Cal Welbourn and Dr. H. A. Denmark.

However, concerns arise when the characters used to discern between the A. largoensis populations are few. In such situations, utilizing the biological and phylogenetic species concepts in addition to the taxonomic may help discriminate between the populations.

Biological

The biological species concept was proposed by Mayr (1942) and is based partially on work completed by Dobzhansky (1940). It states that a “biological (genetic) species is a group of naturally interbreeding populations that are reproductively isolated from other such species“, (King and Stansfield 1997). Reproductive isolation is the combined effect of all barriers to gene flow between divergent populations that are in contact and includes prezygotic and postzygotic isolating mechanisms (Hoy and Cave

1988; Mallet 2006). Hybrid sterility, hybrid inviability, and assortative mating will result in partial reproductive isolation. Thus, the loss of interbreeding potential reproductively isolates clades, results in phylogenetically distinct taxa, and may lead to greater divergence (Mallet 2006). There are several caveats to the biological species concept.

For example, there are varying degrees of reproductive isolation, and instances of hybridization and introgression do occur, especially under laboratory conditions in no- choice situations (Mantovani and Scali 1992; Salzburger et al. 2002). Also, there are limitations to testing reproductive compatibility in taxa with complex, irregular, or unknown interbreeding and mating behaviors (Adams 1998).

Hybridization studies have been conducted to determine the species status of phytoseiid populations (Croft 1970; McMurtry et al. 1976; McMurtry 1980; McMurtry and

Baddi 1989; Da Silva Noronha and de Moraes 2004). Within the phytoseiids reproductive incompatibility can lead to shriveled eggs, reduced oviposition rates, increased mortality in immature stadia, or reproductive sterility of progeny (Amano and

Chant 1978; Mahr and McMurtry 1979; McMurtry 1980; Hoy and Knop 1981; Hoy and

Standow 1982; Hoy and Cave 1988). Incompatibility may vary within a population. For instance, some individuals may reproduce while others may not (Mahr and McMurtry

1979). In some instances unidirectional incompatibility may occur so that while one reciprocal cross (population 1 female x population 2 male) produces viable progeny, the reverse (population 2 female x population 1 male) will not (Hoy and Knop 1981).

Incompatibility between populations can develop rapidly, sometimes in as few as 1 or 2 years of reproductive isolation, among phytoseiids (Hoy and Knop 1981; Tanigoshi

1981).

In addition to genetic isolation, reproductive incompatibility within the Acari can also be caused by the vertically and horizontally transmitted -proteobacteria Wobachia pipientis (A and B) (Hoy and Jeyaprakash 2005). This type of incompatibility is coined

‘Cytoplasmic Incompatibility’ (CI) (Werren et al. 1995; Bandi et al. 1998) and can be uni- or bi-directional. Unidirectional CI occurs when a cross between an infected male and uninfected female result in mortality of the embryos. Bidirectional CI occurs when a male and female of the same species are incompatible due to infection by different

Wobachia strains (Stouthamer et al. 1999). In addition, the incompatibility phenotype will depend on the host’s genetic system. Within the parahaploid system found in most

phytoseiids, Wobachia will cause reduced numbers of diploid females (Johanowicz and

Hoy 1998).

Returning to the biological species definition, if the Mauritius and S. Florida populations are found reproductively incompatible (do not mate or mate but do not produce viable progeny) and are not infected with CI-inducing Wobachia, they could be considered separate morphologically similar species (cryptic species). If they are reproductively compatible or exhibit slight incompatibility, it is possible that they are biotypes within the same species and have not undergone complete biological speciation (reproductive isolation). For instance, reproductive incompatibility in conjunction with differences in morphology, developmental rate, and RH tolerance between two populations of Amblyseius addoensis van der Merwe and Ryke from South

Africa (McMurty 1980) was considered sufficient to justify subspecific (biotype) names

(Tanagoshi 1981).

Phylogenetic

With the advent of molecular systematics (phylogenetics) a new definition of

species has evolved. A species will have distinguishable genotypic or genomic clusters

(i.e. populations or genetic entities) that are stable in sympatry (spatially overlapping

populations) or hybrid zones between parapatric forms (two geographic entities that

abut at the boundaries to their range) (Packer and Taylor 1997; Williams et al. 2006;

Mallet 2006). Phylogenetics has been used to identify cryptic species, used to avoid

problems associated with hybridization and the biological species concept, and used to

expand our view of the level of taxonomic diversity present in nature (Williams et al.

2006; Condon et al. 2008). The phylogenetic species concept utilizes percentage

sequence divergence to discriminate between species. The percentage sequence

divergence calculated may vary between taxa and the genes examined and, therefore,

must be examined on a case-by-case basis (Hoy et al. 2000; Jeyaprakash et al. 2003;

Hoy and Jeyaprakash 2005). Within bacteria, an arbitrary 3% sequence divergence in

the 16S ribosomal RNA gene is considered sufficient to confirm species-level

differences (Stackebrandt and Goebel 1994; Jeyaprakash et al. 2003). Within the

Coleoptera, sequence variation of <0.8 % within the COI mitochondrial gene has been

used to establish haplotype differences (Evans et al. 2000; Evans and Lopez 2002).

There are several caveats to the phylogenetic species concept. The availability of

sequence information and availability of primers will limit the type and number of genes

examined in a project. In addition, the cost of equipment and reagents, special training,

and availability and quality of DNA can limit the feasibility of phylogenetic projects.

However, the cost of analysis and specialized training may be justified in biological

control projects when identifying a potential classical biological control organism,

discriminating biotypes or cryptic species, or identifying the origin of an invasive pest for

natural enemy exploration (Dowling 2008).

In this study, the phylogenetic species concept will be applied in addition to the

taxonomic species concept. The phylogenetic relationship between the Mauritius and S.

Florida A. largoensis populations will be evaluated using sequence divergence estimates and Bayesian analysis. Firstly, we will determine sequence divergence from taxa within the same genus or closely related genera of phytoseiids available in

GenBank. Next, we will infer evolutionary relationships based on sequence homology

using Bayesian phylogenetic analysis software.

Molecular Markers

To conduct a phylogenetic analysis, molecular markers appropriate to the question

posed must be determined. Molecular markers are useful for identifying or

distinguishing taxa that are not well-studied, are very small, are members of cryptic species complexes (Jeyaprakash and Hoy 2002; Tixier et al. 2006a, 2008; Rowley et al.

2007; Smith et al. 2008), are different geographical populations of the same species

(Croft 1970; McMurtry 1980; Abou-Setta et. al. 1991; Navajas et al. 1992, 1994; Hoy et al. 2000; Navajas and Fenton 2000; Williams et al. 2006; Coleman 2009), or are present only in immature stages (Zahler et al. 1995). The molecular diagnostic tool used will depend on the type of question, the cost, ease of use, and the sample size (Hoy 2003).

The genome and genome region to be analyzed will depend on the level of taxonomic resolution desired (Hillis and Moritz 1990; Avise 1994; Navajas and Fenton 2000;

Cruickshank 2002).

Caterino et al. (2000) suggested evaluating the most widely used molecular markers to create a standard compilation of taxa sequence information for insect systematics. These include mitochondrial genes: cytochrome oxidase subunit I (COI),

the large mitochondrial ribosomal subunit (16S); and nuclear genes: the small nuclear

ribosomal subunit (18S) and elongation factor-I alpha (EF-I) (Djernaes and Damgaard

2006). When approaching a taxonomic question it is important to choose the correct

gene(s) or ‘marker(s)’ for your taxa. There are several helpful reviews of molecular

markers used in acarology (Navajas and Fenton 2000; Cruickshank 2002). Cruickshank

(2002) identifies characteristics that should be considered when deciding what gene(s)

or gene regions to use in a phylogenetic or taxonomic analysis: rate of

evolution/mutation, single-copy genes, ease of alignment, sufficient number of informative sites (points of mutation, deletion, and inversions), availability of universal

primers, and availability of sequence data from related taxa for comparison. At present,

the number of useful genes is limited in the Acari but whole-genome sequencing of taxa

currently in progress could change that.

The Mitochondrial Genome

Kocher et al. (1989) found that mitochondrial DNA (mtDNA) could be utilized in

phylogenetic evolution/inference in animals. Since then, mtDNA has been used in

taxonomic and population studies of mites and insects (Navajas et al. 1996; Navajas

and Fenton 2000; Toda et al. 2000, 2001; Cruickshank 2002; Evans and Lopez 2002;

Jeyaprakash and Hoy 2002; Brown 2004; Tixier et al. 2008c). There are several

advantages to using mtDNA in taxonomic studies: (1) high copy number within the cell

makes mt genes easier to amplify by the PCR (Tixier et al. 2008c); (2) almost strict maternal inheritance (see Sunnucks and Hales (1996) and Zhang and Hewitt (1996) for examples of nuclear copies of mitochondrial genes) (Cummins et al. 1997; Schwartz and Vissing 2002; Cruickshank 2002); and (3) high levels of sequence divergence for species and biotype or population level resolution due to a high transitional mutation rate (Harrison 1989; Loxdale and Lushai 1998; Moriyama and Powell 1997; Norris et al.

1999; Cruickshank 2002).

The mitochondrial genome base content in chelicerates tends to be A+T rich: 80% in the honeybee mite Varroa destructor (Navajas et al. 2002), 76.9% in the phytoseiid

M. occidentalis (Jeyaprakash and Hoy 2007), and 64.5% in the scorpion Centruoides limpidus (Davila et al. 2005). The mitochondrial gene order varies in arachnids (Qiu et al. 2005), Varroa mite (Navajas et al. 2002), in metastriate and prostriate ticks (Black

and Roehrdanz 1998), and in the phytoseiid M. occidentalis (Jeyaprakash and Hoy

2007). The mitochondrial genome of M. occidentalis is 25 Kb and has one unique region, one duplicated, and one triplicated region (Jeyaprakash and Hoy 2007). In addition, the genome may be missing two genes (ND3 and ND6) when compared to other chelicerates (Jeyaprakash and Hoy 2007). By contrast, the mitochondrial genome of Pseudocellus pearsei (Chelicerata: Ricinulei) is 15.1 Kb in size (Fahrein et al. 2007) and the oribatid mite Steganacarus magnus (Acari: Oribatida) is 13.8 Kb in size (Domes et al. 2008).

The Nuclear Genome

Nuclear genes may have slower mutation rates than mitochondrial genes (Lin and

Danforth 2003) due to selection for codon usage (Moriyama and Powell 1997). Nuclear

protein-coding genes can have problems such as heterozygosity and low copy number

(Djernaes and Damgaard 2006). To date several nuclear genome sequencing projects

are proposed or in various stages of completion, including several soft and hard ticks

(Parasitiformes: Ixodidae and Argasidae) (Stuart et al. 2007), Tetranychus urticae

(Acariformes) (Grbic et al. 2007), M. occidentalis (Parasitiformes) (Jeyaprakash and

Hoy 2009a), and Leptotrombidium spp. (Acariformes) (Van Zee et al. 2007). The

nuclear genome of M. occidentalis is quite small at 88-90  5 Mb (Jeyaprakash and Hoy

2009a) and that of T. urticae, at 75 Mbp, is even smaller (Dearden et al. 2002; Grbic et

al. 2007). At the other end of the size spectrum, the haploid genome size of Ixodes

scapularis was determined to be 2262 Mbp (Geraci et al. 2006) and is one-third to twice

the size of the human genome (Venter et al. 2001). The Ixodida (soft and hard ticks)

have inter- and intra- familial variation in genome size and variation within species

(Geraci et al. 2006). The large size of most tick genomes is considered a result of an excessive amount of duplicated and repetitive sequences, with 30 to 35% consisting of low-copy nuclear genes (Nene 2009; Van Zee et al. 2007). Until a phytoseiid nuclear genome is sequenced, only a complete inactive mariner transposable element

(Jeyaprakash and Hoy 1995) and the ITSI, 5.8S, and ITS2 gene sequences (Navajas et

al. 1999) are available from phytoseiids for phylogenetic studies. Sequencing acarine

genomes, and especially species in the Parasitiformes, will provide the information

necessary to produce new primers for phytoseiid nuclear molecular markers.

Rate of Evolution

Each gene or gene region evolves at different rates that are dependent on the

effect of changes to the function of the region (selection pressure) as well as the

genome. For instance, non-coding regions will tolerate more transitional mutations and

indels (insertions and deletions) than coding genes or rDNA stem regions (Hoy 2003)

and insect mitochondrial genes are known to have a higher transitional mutation rate

than nuclear genes (Moriyama and Powell 1997). With this in mind, it is important to

consider how much variation occurs within a gene or gene region (slow or fast mutation)

because this characteristic will affect the ability to produce accurate alignments among

taxa and conduct phylogenetic analysis (Webber and Gunasekaran 1993; Hoy 2003).

The rate of gene evolution/mutation will determine the level of resolution obtained for a

phylogeny. For example, a gene with a higher rate will be better for resolving genus,

species, and biotype differences, while a gene with a slower rate will help resolve higher

taxonomic questions (Kocher et al. 1989; Webber and Gunasekaran 1993; Cruickshank

2002; Hoy 2003). Therefore, variability in gene sequences can be a double-edged

sword. If a very high level of sequence variability exists, an accurate alignment may not

be feasible. If a gene has a low level of variability, the level of taxonomic resolution will be low.

The level of resolution a gene may provide will vary within genes, from gene to gene, and among taxa. The nuclear ribosomal RNA genes 18S, 5.8S, and 28S and their

internal transcribed spacers (ITS-1 and ITS-2) are commonly used for phylogenetic

resolution at the genus, species, and biotype or population levels (Hillis and Dixon 1991;

Wesson et al. 1993; Vogler and DeSalle 1994; Fenton et al. 1998; Gotoh et al. 1998;

Navajas and Fenton 2000; Santos et al. 2007; Coleman et al. 2009). However, the phytoseiid nuclear ITS-1, 5.8, and ITS-2 regions are much smaller (<0.6 kb) in size and have low nucleotide divergence at the species level in comparison to other arthropods

(Navajas et al. 1999; Jeyaprakash and Hoy 2002). Therefore, this region cannot be

used to answer questions requiring species and biotype resolution within phytoseiids.

Single-Copy Genes

In phylogenetic analysis and genotyping studies it is important to know how many

copies of a gene exist within the organisms examined. The goal is to compare

orthologous (homologous sequences separated by a speciation event) genes between

taxa and produce an accurate phylogeny based on gene-sequence homologies.

However, paralogous genes occur when homologous sequences are separated by a

duplication event within a genome. In population surveys, paralogous gene sequences

can lead to an over estimation of species diversity when the gene sequences in question are orthologous. They can also produce incongruent phylogenetic trees when two gene phylogenies are compared or concatenated (sequence data combined to produce a more robust analysis than the two genes alone). The presence and number of genome duplication events will vary between order and even genera (Geraci et al.

2006). It is difficult to predict whether a gene will be single-copy or multi-copy in taxa when little is known about their genomes.

Availability of Related Sequence Data and Primer Design

Problems in phylogenetic analysis of the Phytoseiidae arise when searching for gene sequences of related taxa for comparison or for primer design. Currently (Dec.

2009), there are a limited number of mitochondrial gene sequences in GenBank

available for constructing phylogenies of the Phytoseiidae: one whole genome

(Jeyaprakash and Hoy 2007), eight taxa for the 12S sequence (Jeyaprakash and Hoy

2002; Pham et al. unpub.; Tixier et al. unpub.; Xia et al. unpub.), one taxa for the 16S

(Roy et al. 2009), 12 taxa for COI (Tixier et al. 2006b; Jeyaparakash and Hoy 2007;

Tixier et al. 2008c; Roy 2009; Tixer et al unpub.), and three taxa for Cytb (Tixier et al.

unpub.). Nuclear gene sequences available (Dec. 2009) include: one taxa for Actin

genes 1-4 (Jeyaprakash and Hoy 2009a), one taxa for 18S (Pham et al. unpub.; Xia et

al. unpub.), one for 28S (Cruickshank and Thomas 1999), seven taxa for ITS-1, 5.8S,

and ITS-2 (Navajas et al. 1999; Ramadan et al. unpub.; Xia et al. unpub.), and one taxa

for elongation factor-1α (EF-I) (Jeyaprakash and Hoy 2009a).

Molecular Markers of Interest for This Study

12S rRNA

The small mitochondrial ribosomal subunit (12S) has become an ideal tool for

phylogenetic resolution of species within the phytoseiids. It is known to be fast evolving

with higher sequence divergence (9.5-45%) than the ITS-2 region (1.2-23%) (Navajas et

al. 1999; Jeyaprakash and Hoy 2002, 2009b). Jeyaprakash and Hoy (2002) detected

high sequence divergences in a portion of the mitochondrial 12S rRNA gene and

subsequently utilized this diversity to create diagnostic primers for species

discrimination of 6 commercially available phytoseiids. Results of this study suggest the rRNA 12S gene may have great potential for species resolution. In 2009, Tixier et al. submitted partial 12S sequences to GenBank obtained from Phytoseiulus persimilis

Athias-Henriot, P. macropilis (Banks), and P. fragariae Denmark & Schicha populations found in the United Kingdom, Argentina, France, and Spain. For this thesis, these sequences were aligned, the 5’ and 3’ ends trimmed to a uniform length (Figure 1-3), and the percentage pairwise differences calculated (Table 1-5); species differences between P. fragariae and P. persimilis and P. macropilis ranged from 4 to 22%. The population pairwise differences ranged from none to 1% in P. persimilis, zero in P. macropilis, and 1 to 7% in P. fragariae (Table 1-5). Considering these pairwise difference scores, the mitochondrial 12S gene appears to be informative for species resolution within the phytoseiids (Norris et al. 1999; Murrell et al. 2000; Jeyaprakash and Hoy 2002). Phytoseiulus intraspecies population pairwise differences (Table 1-5) varied from species to species and it is unclear how valuable the 12S gene will be to discriminate between populations or biotypes.

There are several advantages to utilizing the 12S rRNA gene in our study to discriminate between possible biotypes or cryptic species: (1) availability of universal primers; (2) it may be possible to obtain resolution at the species, biotype or population levels; (3) availability of sequence data from other phytoseiid genera in GenBank for sequence comparisons and species divergence comparisons.

Cytochrome Oxidase I (COI)

The mitochondrial protein-coding gene cytochrome oxidase I (COI) has been used

in taxonomic and population studies (barcoding project) of arthropods (Simon et al.

1994; Roehrdanz and Degrugillier 1998) as well as for genus and species resolution in

spider mite, tick, and phytoseiid phylogenetic studies (Navajas et al. 1996; Navajas and

Fenton 2000; Toda et al. 2000, 2001; Cruickshank 2002; Evans and Lopez 2002;

Salomone et al. 2002; Walter and Campbell 2003; Tixier et al. 2006c). The universal

COI primers designed for arthropods by Kambhampati and Smith (1995) do not anneal due to variability at the priming site in phytoseiids (Jeyaprakash and Hoy 2007; Tixier et al. 2008c). Interestingly, Tixier et al. (2006b, 2008c, 2009) utilized COI primers designed by Navajas et al. (1996) for Tetranychus urticae Koch as a genotyping tool for species

within the phytoseiid genus Kampimodromus. They obtained sequences approximately

430 bp in length that had average pairwise distances of 6, 18, and 20%. The usefulness

of the primers designed by Navajas et al. (1996) for this study was examined using

high-fidelity PCR, but no COI amplification products were obtained from Neoseiulus

californicus (McGregor), N. cucumeris Oudemans, and ‘A. largoensis’ DNA, although an

amplification product was obtained from A. swirskii (Athias-Henriot) (Bowman, unpub.).

These results indicate that the COI primers designed by Navajas et al. (1996) cannot be used for this study to survey the ‘A. largoensis’ populations. Instead, if COI is to be used, new primers must be designed from regions that are less variable or degenerate primers must be designed.

Elongation Factor-I Alpha (EF-I)

The nuclear gene encoding the elongation factor-I alpha (EF-I) protein is a likely

candidate for phylogenetic analysis of phytoseiids (Klompen 2000; Cruickshank 2002).

The EF-I protein is involved in the GTP-dependent binding of charged tRNAs to the acceptor site of the ribosome during translation (Webster 1985; Maroni 1993). It is known to be orthologus (single-copy) in some arthropods and sequences are easier to

align among taxa because, as a protein-coding gene, it has a slower rate of

mutation/evolution than rDNA or non-coding regions. Therefore, EF-I has been

discussed as a possible tool for resolution at the genus level (Friedlander et al. 1992,

1994; Brower and DeSalle 1994, Mitchell et al. 1997; Cruickshank 2002; Arensburger et

al. 2004). However, the use of EF-I for phylogenetic resolution is still novel in the Acari

and has only been sequenced in a limited number of mite taxa. We are interested in

exploring its usefulness for phylogenetic resolution within the phytoseiids. The possible

advantages of utilizing EF-I are: (1) it is considered a single-copy nuclear gene in

Acari; (2) it is possible to obtain resolution at the genus and species level; (3) there are

degenerate primers available that may work for phytoseiids (Jeyaprakash and Hoy

2009a); (4) some sequence data are available from other phytoseiid genera in

GenBank. One concern, however, is whether EF-I is actually a single-copy gene in

phytoseiids.

The genome of Drosophila melanogaster Meigen is known to have two EF-I

genes (EF-I F1 and EF-I F2) with 93.3% amino acid and 90.5% nucleotide similarity

between the paralogs suggesting an ancient duplication (Hovemann et al. 1988; Maroni

1993). The Drosophila EF-I F2 reading frame is interrupted by two introns while EF-I

F1 has only one intron in the leader sequence and none in the coding sequence

(Walldorf et al. 1985; Hovemann et al. 1988; Maroni 1993). Currently, other arthropod

taxa known to have duplicated EF-I sequences include the honeybee (Apis mellifera

L.) with a 25% difference between paralogs and two introns in the F2 reading frame

(Walldorf and Hovemann 1990; Danforth and Ji 1998), ambrosia beetles (Xyleborini)

with a ~7% paralog sequence difference (Jordal 2002), and Scolytine weevils (Normark

1996). Danforth and Ji (1998) consider EF-I to be a candidate model system for

investigating gene duplication within insects. Within the Phytoseiidae, however, only

one EF-I gene is known from Metaseiulus occidentalis (Nesbitt) thus far (GenBank

accession no. FJ527739) (Jeyaprakash and Hoy 2009a). In addition, EF-I paralogs

have not been identified in the tick genome. Only one EF-I sequence has been

deposited into GenBank (accession no. XM_002411102) from the Ixodes scapularis

Say (black-legged tick) genome project (Jason Meyer, pers. comm.). It is important to note that some of the I. scapularis genome did not make it into the assembly and it is still in the process of annotation. Therefore, no conclusions can be made at this time as

to whether EF-I paralogous sequences exist in the I. scapularis genome. Further

investigations into the utility of this gene for genotyping members of the Acari need to

be conducted.

Random Amplified Polymorphic DNA (RAPD) PCR

In 1990, J. Welsh and M. McClelland developed Random Amplified Polymorphic

DNA (RAPD) PCR as a technique to detect genome-wide variability. It can be used to

determine biotypes or species or cryptic species identity, assess kinship, analyze paternity, estimate genetic variation within populations, and monitor colonization

(Hadrys et al. 1992, 1993; Landry et al. 1993; Edwards and Hoy 1995a, 1995b;

Edwards et al. 1997; Yli-Mattila et al. 2000; Hoy et al. 2000; Hoy 2003; Karam et al.

2008). The biggest advantage to RAPD-PCR is that no prior knowledge of sequence

information is required and therefore, it can be used to develop markers for any species

(Hoy 2003). RAPD-PCR is based on the ability of single primers (10-mers) to randomly

prime and amplify throughout a genome (including both single-copy genes and

repetitive DNA) resulting in several DNA fragments, which are separated in an agarose gel. The banding pattern generated shows genetic differences and the presence or absence of specific amplified DNA fragments determines polymorphisms.

Fifty-five RAPD primers were tested by Haymer (1994) and found to be informative when tested with insect DNA (Hoy 2003). Edwards and Hoy (1993) found 92 out of 120

RAPD primers to be informative when testing genetic variation in the parasitoids Trioxys

pallidus (Haliday) and Diglyphus begini (Ashm.). Later, Edwards et al. (1997) were able

to discriminate two morphologically similar phytoseiids Typhlodromalus limonicus

(Garman and McGregor) and T. manihoti de Moraes, using RAPD banding patterns.

The advantages of RAPDs are: (1) no prior sequence knowledge is needed; (2) small amounts of DNA (25 ng/reaction) are required; (3) the lab set-up is easy and cheap; (4) it does not require radioactive detection; and (5) there are many potential markers. There are also disadvantages to using RAPDs: (1) there are several possible mechanisms that may lead to an absence of a band (ranging from mutations to too high a concentration of DNA in the reaction); (2) there can be homology issues; (3) reliable bands are only from dominant Mendelian traits, therefore, recessive traits are not considered except in haploid males (Peener et al. 1993; Edwards and Hoy 1993,

MacPherson et al. 1993; Hoy 2003).

Steps can be taken to avoid the RAPD-PCR concerns listed above. Firstly, replicate reactions should always be run to identify variations in band intensities due to concentration differences in the template DNA (Black 1993; Edwards et al. 1997).

Secondly, consistent reaction concentrations of DNA, primers, MgCl2, and DNA

polymerases must be maintained to avoid variations in banding patterns (Black 1993;

Ellesworth et al. 1993; MacPherson et al. 1993; Edwards et al. 1997). Inconsistency also can be caused by DNA degradation so fresh material should always be used

(Edwards et al. 1997). Differences in banding patterns due to dominant genes can be

avoided by using haploid males in a haploid-diploid genetic system. Lastly, results will

vary due to differences in thermocyclers and the brand of DNA polymerase used so

results may not be fully comparable between laboratories (MacPherson et al. 1993;

Schierwater and Ender 1993; Edwards et al. 1997).

The use of the RAPD-PCR technique on single mites has been limited due to the

quality and quantity of DNA extractions from single mite specimens (Edwards et al.

1997; Jeyaprakash and Hoy 2002). Several studies included DNA from several

individuals, which can result in biased banding patterns (Mitchelmore et al. 1991;

Hadrys et al. 1992; Edwards et al. 1997). However, Jeyaprakash and Hoy (in press) integrated the use of High-fidelity PCR (Hf-PCR) (Barnes 1994; Jeyaprakash and Hoy

2000; Hoy et al. 2001) and RAPD markers to amplify small amounts of DNA extracted from single mites using a soaking technique modified from protocol outlined by Boom et al. (1990). Utilizing this technique, the Hf-RAPD PCR protocol could possibly be performed on as little as 10.9-20.0 ng/l of nucleic acids of good quality. However, it is important to note that there is more mtDNA (high copy number in the cell) than nuclear

DNA in the sample and therefore, the nuclear genome may not be as well represented as in a cleaner and more highly concentrated DNA preparation.

The phylogenetic species concept can enable discrimination between arthropod biotypes or cryptic species in biological control programs. Cryptic species or biotype identification through phylogenetic analysis may assist later morphological analysis by

increasing detection of slight, but significant, character differences. A combination of phylogenetic analysis, whole genome analysis (RAPD-PCR) (Edwards et al. 1997), reproductive compatibility, and intensive morphological study (taxonomic identification)

(Tixier et al. 2006a) may be considered an effective approach to identify the Mauritius and S. Florida populations as cryptic species or biotypes (Mendelson and Shaw 2002;

Arensburger 2004).

Research Objectives

Research Aim

The aim of this research was to determine if the phytoseiids associated with the

RPM from Mauritius and S. Florida, morphologically identified as ‘Amblyseius

largoensis’, are biotypes of the same species or cryptic species.

Main Objectives

The main objective was to determine if the phytoseiid populations associated

with the RPM from Mauritius and South Florida could be discriminated using the

mitochondrial 12S rRNA gene and the nuclear EF-Iα gene. Hf-PCR with population- specific primers and random amplified polymorphic DNA (RAPD) primers are two methods that will be tested to determine if they can be used to discriminate between the

Mauritius and South Florida populations. The main objective was tested through four experiments:

1. Determine if it is possible to discriminate between phytoseiids associated with the RPM from Mauritius and S. Florida using the 12S mitochondrial rRNA gene.

2. Determine if the EF-Iα nuclear gene allows discrimination of phytoseiids associated with the RPM from Mauritius and S. Florida.

3. Evaluate five RAPD markers using Hf-PCR to discriminate between the Mauritius and S. Florida phytoseiid populations.

4. Evaluate 12S rRNA sequences obtained from the Mauritius and S. Florida populations to develop population-specific primers.

Table 1-1. A list of Raoiella indica hosts reported in Florida (Welbourn 2009). Family Genus and species Common name(s) Palmae Adonidia merrilli (Becc.) Becc. (=Veitchia H.A. Wendl.) * Manila palm, Christmas palm Palmae Aiphanes caryotifolia (H.B.K.) H.A. Wendl. Coyure palm, Ruffle palm, Spine palm Palmae Archontophoenix alexandrae (F. Muell.) H.A. Wendl. & Drude Alexander palm, King palm Palmae Beccariophoenix madagascariensis Jum. & H. Perrier Giant windowpane palm Palmae Butia capitata (Mart) Becc. Pindo palm, Jelly palm Palmae Coccothrinax miraguama (H.B.K.) Becc. Miraguama palm Palmae Cocos nucifera L. * Coconut palm Palmae Corypha umbraculifera L. Talipot palm Palmae Livistona chinensis (Jacq.) R. Br. ex Mart. Chinese fan palm Palmae Phoenix canariensis Hort. ex Chabaud Canary Islands date palm Palmae Phoenix dactylifera L. Date palm Palmae Phoenix reclinata Jacq. Senegal date palm Palmae Phoenix roebelenii O’Brien Pygmy date palm, Roebelenii palm Palmae Pritchardia pacifica B.C. Seem. & H.A. Wendl. Fiji fan palm Palmae Pseudophoenix sargentii H.A. Wendl. ex Sarg. Buccaneer palm, Sargent’s cherry palm Palmae Ptychosperma elegans (R. Br.) Blume Solitaire palm, Alexander palm Palmae Ptychosperma macarthurii (H.A. Wendl.) Nichols Macarthur palm Palmae Schippia concolor Burret Silver pimento palm Palmae Syagrus romanzoffiana (Cham.) Glassman Queen palm Palmae Thrinax radiata Lodd. ex J.A. & J.H. Schultes Florida thatch palm Palmae Veitchia spp. H.A. Wendl. Manila palm Palmae Washingtonia robusta H.A. Wendl. * Mexican fan palm Palmae Wodyetia bifurcata A.K. Irvine Foxtail palm Musaceae Heliconia spp. None Musaceae Musa spp. Banana, Plantain Zingiberaceae Alpinia zerumbet (Pers.) B.L. Burtt & R.M. Sm. Shell ginger, Pink porcelain lily * Denotes hosts with observed high populations (Farzan Husin, unpub. data referenced in Roda et al. 2008).

Table 1-2. A list of viruses transmitted by Brevipalpus mites to their host plants (Acari: Tenuipalpidae) (Kitajima et al. 2003). Host Virus Brevipalpus spp. Orange, mandarin (Citrus spp.) Leprosis californicus obovatus phoenicis Coffee (Coffea arabica) L. Ringspot phoenicis Orchids Fleck, Ringspot californicus phoenicis Ligustrum sp. Ringspot obovatus Green spot phoenicis Passiflora edulis Sims, F. flavicarpa Degener Green spot phoenicis Hibiscus rosa-sinensis L. Green spot phoenicis Chlorotic spots phoenicis Hibiscus syriacus L. Green spot phoenicis Hibiscus schizopetalus Hook f. Green spot phoenicis Turk’s hat (Malvaviscus arboreus Cavanilles) Ringspot phoenicis Solanum violaefolium Schott Ringspot phoenicis Solanum actinophylla Harms Ringspot phoenicis Ivy (Hedera canariensis Willdenow) Green spot phoenicis Bleeding heart (Clerodendrum speciosum Guerke) Chlorotic spots phoenicis Ball from dragon (Clerodendrum thomsonae Balfour) Green spot phoenicis Brunfelsia sp. Green spot phoenicis Night jasmine (Cestrum nocturnum L.) Chlorotic spots phoenicis Pelargonium (Pelargonium sp.) Green spot phoenicis King’s mantle (Thunbergia erecta (Bentham) T. Anderson) Green spot phoenicis Mexican sage (Salvia leucantha Cavanilles) Green spot phoenicis Pittosporum sp. Ringspot phoenicis

Table 1-3. List of South Florida Amblyseius 'largoensis' collection sites. Date Plant host Location GPS coordinates Colony 01/ 2007 Banana Lake Worth 26.620764, -80.058891 Florida 1 03/ 2007 Coconut palm Lake Worth 26.569519, -80.050936 Florida 2 04/ 2007 Coconut palm Lake Worth 26.615649, -80.048417 Florida 3 04/ 2008 Coconut palm Hollywood 26.047855, -80.164667 Florida 4

Table 1-4. The partial 12S rRNA sequences from Phytoseiulus spp. submitted by Tixier et al. (2009) to GenBank. Species include P. persimilis Athias-Henriot, P. macropilis (Banks), and P. fragariae Denmark & Schicha individuals from populations in the United Kingdom (UK), Argentina (AR), France (FR), and Spain (SP) Phytoseiulus spp. Isolate GenBank accession fragariae Argentina (AR) 29 FJ985124 “ AR 30 FJ985125 “ AR 31 FJ985126 “ AR 32 FJ985127 “ AR 33 FJ985128 macropilis AR 34 FJ985129 “ AR 35 FJ985130 “ AR 36 FJ985131 “ AR 37 FJ985132 “ AR 38 FJ985133 persimilis France (FR) 10 FJ985106 “ FR 12 FJ985107 “ FR 13 FJ985108 “ FR 14 FJ985109 “ FR 15 FJ985110 “ FR 16 FJ985111 “ FR 17 FJ985112 “ FR 18 FJ985113 “ Spain (SP) 1 FJ985096 “ SP 2 FJ985097 “ SP 3 FJ985098 “ SP 4 FJ985099 “ SP 5 FJ985100 “ SP 6 FJ985101 “ SP 7 FJ985102 “ SP 8 FJ985103 “ SP 9 FJ985104 “ SP 11 FJ985105 “ United Kingdom (UK) 19 FJ985114 “ UK 20 FJ985115 “ UK 21 FJ985116 “ UK 22 FJ985117 “ UK 23 FJ985118 “ UK 24 FJ985119 “ UK 25 FJ985120 “ UK 26 FJ985121 “ UK 27 FJ985122 “ UK 28 FJ985123

Table 1-5. Corrected pairwise distances between the partial 12S rRNA sequences from Phytoseiulus spp. submitted by Tixier et al. (2009) to GenBank. Phytoseiulus persimilis, P. macropilis, and P. fragariae individuals from populations in the United Kingdom (UK), Argentina (AR), France (FR), and Spain (SP) using PAUP 4.0b8 with Kimura 2-parameter and Among-site rate variation distance settings. Distance measured by using a scale of 0 - 1.

Table 1-5. Continued.

Figure 1-1. Map of current Raoiella indica range in Florida (Saeger 2010).

Figure 1-2. Map of Mauritius Amblyseius 'largoensis' collection sites (http://www.bwinternships.com/jo/images/stories/mauritius%20map.jpg).

10 20 30 40 50 60 70 80 90 ......

P. fragariae AR29 CTTTTTAAATATCTTAGAGGAA-TTTATTCTG-TAAAGGATT-TAACACCAACAATCTTACTTTTGTTTGTATTTAAACAATTTACATAC “ “ AR30 CTTTTTAAATATCTTAGAGGAA-TTTATTCTG-TAAAGGATTCTAACACCAACAATCTTACTTTTGTTTGTATTTAAACAATTTACACAC “ “ AR31 CTTTTTAAATATTTTAGAGGAA-TTTATTCTG-TAAAGGATT-TAACACCAACAATCTTACTTTTGTTTGTATTTAAACAATTTACACAC “ “ AR32 CTTTTTAAATATTTTAGAGGAA-TTTATTCTG-TAAAGGATT-TAACACCAAAA-TCTTACTTTTGTTTGTATTTAAACAATTTACATAC “ “ AR33 CTTTTTAAATATTTTAGAGGAA-TTTATTCTG-TAAAGGATT-TAACACCAA-AATCTTACTTTTGTTTGTATTTAAACAATTTACATAC P. macropilis AR34 CTTTTTAAATATTTTAGAGGAA-TTTATTCTG-TAAAGGATT-TGACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ AR36 CTTTTTAAATATTTTAGAGGAA-TTTATTCTG-TAAAGGATT-TGACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ AR37 CTTTTTAAATATTTTAGAGGAA-TTTATTCTG-TAAAGGATT-TGACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ AR38 CTTTTTAAATATTTTAGAGGAA-TTTATTCTGGTAAAGGATT-TGACACCAAAAATCTTACTTTTATTTGTATTAAAACAGTTTACATAC P. persimilis FR10 CTTTTTAAATATTTTAGAGGAAATTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ FR12 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ FR13 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ FR14 CTTTTTAAATATTTTAGAAGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ FR15 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ FR16 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ FR17 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ FR18 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP1 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP2 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP3 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP4 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP5 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP6 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP7 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATCC “ “ SP8 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP9 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ SP11 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACAT-C “ “ UK19 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ UK20 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ UK21 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ UK22 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ UK23 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ UK25 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ UK26 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ UK27 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC “ “ UK28 CTTTTTAAATATTTTAGAGGAA-TTTATTCTA-TAAAGGATT-TAACACCAAAA-TCTTACTTTTATTTGTATTAAAACAGTTTACATAC

Figure 1-3. CLUSTAL X DNA alignment for partial 12S rRNA sequences from Phytoseiulus spp. submitted by Tixier et al. (2009) to GenBank. Species include P. persimilis Athias-Henriot, P. macropilis (Banks), and P. fragariae Denmark & Schicha individuals from populations in the United Kingdom (UK), Argentina (AR), France (FR), and Spain (SP).

100 110 120 130 140 150 160 170 180 ......

P. fragariae AR29 CTCTATTTTAAAATATCTTA-GATATATTTTAGCAATACTTTTATATGAAGTAGGTTTTTAGGTAAAGGTGTAGTTTATACAAAAAGAAT “ “ AR30 CTCTATTTTAAAATATt-TA-GATATATTTTAGCAATACTTTTATATGAAGTAGGTCTTTAGGTAAAGGTGTAGTTTATACAAAGAGAAT “ “ AR31 CTCTATTTTAAAATATt-TA-GATATATTTTAGCAATACTTTTATATGAAGTAGGTTTTTAGGTAAAGGTGTAGTTTATACAAAGAGAAT “ “ AR32 CTCTATTTTAAAATATT-TA-GATATATTTTAGCAATACTTTTATATGAAGTAGGTTTTTAGGTAAAGGTGTAGTTTATACAAAAGAA-T “ “ AR3 CTCTATTTTAAAATATt-TA-GATATATTTTAGCAATACTTTTATATGAAGTAGGTTTTTAGGTAAAGGTGTAGTTTATACAAA-AGAAT P. macropilis AR34 CTCTATTTTAGAATATT-TA-GATATATTCTAATAATACTATTATCTATAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ AR36 CTCTATTTTAGAATATT-TA-GATATATTCTAATAATACTATTATCTATAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ AR37 CTCTATTTTAGAATATTCTACGATATATTCTAATAATACTATTATCTATAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAAGT “ “ AR38 CTCTATTTTAGAATATT-TACGATATATTCTAATAATACTATTATCTATAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAAGT P. persimilis FR10 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ FR12 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ FR13 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ FR14 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ FR15 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ FR16 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ FR17 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ FR18 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP1 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP2 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP3 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP4 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP5 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP6 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP7 CTCTATTTTAAAATATT-CA-A-TATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-- “ “ SP8 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP9 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ SP11 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-- “ “ UK19 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ UK20 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ UK21 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ UK22 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ UK23 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ UK25 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ UK26 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ UK27 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T “ “ UK28 CTCTATTTTAAAATATT-TA-AATATATTTTATTAATACTATTATTT-TAGTAATTTTTTAGGTAAAGGTGTAGCTTATATAAAAGAA-T

Figure 1-3. Continued.

190 200 210 220 230 240 250 260 270 ......

P. fragariae AR29 GAAATAAATGTATATTAATTATTATTTAGT--AACGAGATTTGAATGTAAACTAAACATTAAGTAAAATTTCAAA-GTAAAATTAGTTTA “ “ AR30 GAAATAAATGTATATTAATTATTATTTAGGTAAGCGAGATTTGAATGTAACCAAAACAGTAAGTAAAACTTCAAA-GTAAAATTAGTTTC “ “ AR31 GAAATAAATGTATATTAATTATTATTTAGT--AACGAGATTTGAATGTAACCTAAAAATTAAGTAAAACCTCAAAAGTAAAATTAGTTTA “ “ AR32 GAAATAAA-TTATATTAATTATTATTTAG--TAACGAGATTTGAATGTAAATAAAA-ATTAAGTAAAATTTAAAA-GTAAAATTAGTTTA “ “ AR33 GAAATAAA-TTATATTAATTATTATTTAGT--AACGAGATTTGAATGTAAATAAAA-ATTAAGTAAAATTTAAAA-GTAAAATTAGTTTA P. macropilis AR34 GAAATAAA-TTATAATAATTTTAATT-ATTTTAACAAAATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ AR36 GAAATAAA-TTATAATAATTTTAATT-ATTTTAACAAAATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTAGA “ “ AR37 GAAATAAACTTATAATAATTTTAATT-ATTTTAACAAAATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ AR38 GAAATAAACTTATAATAATTTTAATT-ATTTTAACAAAATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA P. persimilis FR10 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ FR12 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ FR13 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ FR14 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ FR15 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ FR16 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ FR17 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ FR18 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP1 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP2 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP3 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP4 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP5 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP6 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP7 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP8 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP9 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ SP11 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK19 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK20 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK21 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK22 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK23 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK25 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK26 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK27 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA “ “ UK28 GAAATAAA-TTATAATAATTTTTATT-ATTTTAACGAGATTTAAATGTAAATAATA-ATTTAGTAAAATTTAAAA-GTAAAATTAGTATA

Figure 1-3. Continued.

280 290 300 . . .

P. fragariae AR29 TC-CGGCGAATTTGAATATAATTTTAT-AAGTGTACATA “ “ AR30 CCACGGCGAATTTGAGTATAATTTTAT-AAGTGTACATA “ “ AR31 CCACGGCGAATTTGAATATAATTTTAT-AAGTGTACATA “ “ AR32 TC-AGGCGAATTTGAATATAATTTTAT-AAGTGTACATA “ “ AR33 TC-AGGCGAATTTGAATATAATTTTAT-AAGTGTACATA P. macropilis AR34 TT-TAGCTGATTTGAATTAGATTTTAT-AAGTGTACATA “ “ AR36 TT-TAGCTGATTTGAATTAGATTTTAT-AAGTGTACATA “ “ AR37 TT-TAGCTGATTTGAATTAGATTTTAT-AAGTGTACATA “ “ AR38 TT-TAGCTGATTTGAATTAGATTTTAT-AAGTGTACATA P. persimilis FR10 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ FR12 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ FR13 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ FR14 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACCTA “ “ FR15 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ FR16 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ FR17 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ FR18 TT-TAGCCAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP1 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP2 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP3 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP4 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP5 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP6 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP7 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP8 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP9 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ SP11 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ UK19 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ UK20 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ UK21 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ UK22 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ UK23 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ UK25 TT-TAGCTAATTTGAATTAGATTTTATTAAGTGTACATA “ “ UK26 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ UK27 TT-TAGCTAATTTGAATTAGATTTTAT-AAGTGTACATA “ “ UK28 TT-TAGCTAATGTGAATTAGATTTTAT-AAGTGTACATA

Figure 1-3. Continued.

CHAPTER 2 MOLECULAR DISCRIMINATION OF PHYTOSEIIDS ASSOCIATED WITH THE RED PALM MITE FROM MAURITIUS AND SOUTH FLORIDA

Introduction

The red palm mite (RPM), Raoiella indica Hirst (Acari: Tenuipalpidae), is an invasive pest occurring mostly in tropical and subtropical climates. It was originally

described from coconut palms in Coimbatore India (Hirst 1924) but is believed to have

dispersed from the Middle East (Dowling et al. 2008). The RPM was first detected in the

Western Hemisphere during survey work on the Caribbean islands of Martinique and St.

Lucia in 2004 (Kane et al. 2005) and by 2007 it spread throughout the Caribbean and was detected in Florida’s Palm Beach county (Peña et al. 2006). As of 2009, the RPM has been detected in six South Florida counties: Broward, Lee, Martin, Miami-Dade,

Monroe, and Palm Beach (Welbourn 2009). A menace to banana and coconut production in the Caribbean and the ornamental horticulture and landscape industries in

Florida, the RPM is known to attack 27 palm hosts (Palmaceae) including the areca palm (Dypsis lutescens H. Wetland), coconut palm (Cocos nucifera L.), canary island date palm (Phoenix canariensis Chabaud), date palm (Phoenix dactylifera L.), as well

as bananas, plantains (Musaceae: Musa spp.), and gingers (Zingiberaceae: Zingiber

spp.) (Welbourn 2009).

The native natural enemies in South Florida have not provided adequate

suppression of the RPM (Peña et al. 2009). A classical biological control program could

provide additional control. In 2007, Dr. M. A. Hoy collected phytoseiid populations

preying on the RPM on coconuts from different climatic regions of Mauritius for importation and study in quarantine in the Department of Entomology and Nematology,

University of Florida, Gainesville. The island of Mauritius was chosen for natural enemy

collection for several reasons, the RPM is not considered an economic pest, and the

climactic conditions are similar to South Florida and the Caribbean, and the cooperation

by government officials. The imported Mauritius predator populations were morphologically identified as ‘Amblyseius largoensis’ Muma by taxonomists Dr. Cal

Welbourn (FDACS-DPI, Gainesville, Florida) and Dr. H. A. Denmark. Native populations of phytoseiid mites associated with the RPM in South Florida, Trinidad, Tobago, and

Puerto Rico also have been morphologically identified as A. largoensis (Peña et al.

2009) yet they are not considered to provide adequate control.

Amblyseius largoensis is considered cosmopolitan in distribution (McMurtry and de

Moraes 1984; de Moraes et al. 2004b) and is a type-III generalist predator (consumes

prey, pollen, and nectar) (Yue and Tsai 1996; McMurtry and Croft 1997). The largoensis

group consists of 11 closely related species distinguished morphologically by slight

differences in setal lengths, shapes of spermathecal cervices, and the posterior margin

of the sternal shield (McMurtry and de Moraes 1984; Denmark and Muma 1989). In

biological control, correct identification is an essential step for conducting biological

studies and selecting the most suitable natural enemy (Mahr and McMurtry 1979; de

León et al. 2006) and incorrect taxonomic identification of phytoseiid species is not

uncommon (McMurtry et al. 1976; Hoying and Croft 1977; Miller and Rossman 1995;

Unruh and Woolley 1999; Da Silva Noronha and de Moraes 2004; Nijhout 2003; Tixier

et al. 2006a, 2008b).

The populations of phytoseiids associated with the RPM from Mauritius and S.

Florida were identified as ‘A. largoensis’ using morphological characters. However,

there are few taxonomic characters available to identify Amblyseius species (McMurtry

and de Moraes 1984; Denmark and Muma 1989) and cryptic species are known to occur within the Acari (Tixier et al. 2006c). In such instances, investigations

incorporating informative molecular markers with morphological taxonomy can provide additional characters for comparing taxa (Navajas and Fenton 2000; Toda et al. 2000;

Navajas et al. 2002; Walton et al. 2004; Tixier et al. 2006a, 2006b). In this investigation, sequence divergences and Bayesian analysis of partial 12S rRNA and EF-Iα gene sequences were used to infer phylogenetic relationships between the two populations

(Jeyaprakash and Hoy 2002; Mallett et al. 2005; Dabert 2006; Laumann et al. 2007).

The 12S gene is known to be fast evolving with high sequence divergence (9.5-45%) compared to the commonly used ITS-2 (1.2-23%) mitochondrial gene (Navajas et al.

1999) and has potential for species resolution within the Phytoseiidae (Jeyaprakash and

Hoy 2002, 2009b). The nuclear protein-coding gene EF-I is considered to be a single-

copy gene within the chelicerates and may be useful to resolve genus- and species-

level questions (Cruickshank, 2002; Jeyaprakash and Hoy, 2009a). In addition to

sequence analysis, Neighbor-Joining analysis of High-fidelity-RAPD-PCR was

performed to characterize the ‘whole genome’ of the Mauritius and the S. Florida

populations (Edwards and Hoy 1993, 1995a, 1995b; Edwards et al. 1997). To evaluate

the degree of divergence in 12S rRNA and EF-Iα sequences in other phytoseiid mites,

sequence divergences were calculated using data available in GenBank. In addition, we

utilized the variability between the 12S rRNA Mauritius and S. Florida colonies to

develop population-specific primers to provide a rapid and easy method for evaluating

the establishment, dispersal, and efficacy of the phytoseiid should it be released (de

León et al. 2006). Utilizing the quickly evolving 12S mitochondrial gene, the single-copy

EF-I nuclear gene, and RAPD-PCR markers may provide strong species- and genus-

level resolution to the phylogenetic comparison of the Mauritius and S. Florida

‘Amblyseius largoensis’ populations.

Methods

Phytoseiid Collection and Colony Maintenance

Five Amblyseius populations found associated with the RPM were collected with a permit (#P526P-07-04232, USDA-APHIS-Plant Protection and Quarantine) by M. A.

Hoy from three climactic regions within Mauritius in October 2007, including Flic en Flac

(-20.270088, 57.375069), North of Port Louis (-20.144595, 57.504845), and three within

Trou de Douce (-20.231597, 57.788429) (Figure 1-2). Amblyseius populations associated with the RPM also were collected from four locations within South Florida’s

Broward and Palm Beach counties (Table 1-3) and were identified as A. largoensis. In addition, A. swirskii, Neoseiulus californicus, N. cucumeris (Syngenta Bioline Inc.,

Oxnard, CA), and Metaseiulus occidentalis (a cultured colony originally from the western U.S.A., Dr. M. A. Hoy laboratory, Gainesville, Florida), were collected in 100%

EtOH, and stored at -80ºC for DNA extraction and served as comparisons of phytoseiid genetic diversity.

The Florida and Mauritius colonies were maintained on paraffin-coated arenas that were placed on wet cotton with a water moat in a plastic dish. Due to difficulties in rearing large populations of R. indica in quarantine, Tetranychus urticae Koch nymphs and adults were used as a primary food source, but all stages of R. indica were provided periodically as well. Cattail (Typha latifolia L.) pollen and tissue paper strips

(Kimwipes, Kimberly-Clark Corp., Irving, TX) soaked with diluted honey were provided as alternative food sources. The T. urticae were cultured on pinto bean (Phaseolus

vulgaris L.) plants grown in a greenhouse maintained at 28-30ºC at 30-40% RH.

Raoiella indica mites were collected with a permit from the Florida Division of Plant

Industry, Department of Agriculture and Consumer Services from four sites within

Broward and Palm Beach counties and reared in the University of Florida’s Department

of Entomology and Nematology quarantine facilities (Gainesville, Florida) on cut

coconut palm leaves placed on wet cotton in plastic dishes at 23-28ºC and a 55-60%

RH, with a 16L: 8D photoperiod. Excess RPM were provided to the Mauritius and S.

Florida colonies when available.

DNA Extractions

Clean genomic DNA was extracted from a pool of 30 starved (Johanowicz and

Hoy 1996) adult females from each of the five Mauritius and the four S. Florida

‘Amblyseius largoensis’ colonies separately, as well as A. swirskii, Neoseiulus

californicus, N. cucumeris (obtained from Syngenta Bioline Inc., CA), and Metaseiulus occidentalis (cultured colony, Dr. M. A. Hoy laboratory, Gainesville, Florida). DNA was extracted using Puregene reagents (QIAGEN, Valencia, CA) and purified using a Tip-20

DNA Purification Kit (QIAGEN, Valencia, CA) following the procedures outlined by the manufacturer. DNA was extracted from the Mauritius and S. Florida populations as needed over the course of 1 year and 10 months, which translates to approximately 92 generations. The quantity and quality of purified extracted nucleic acids was examined using a BioPhotometer (Eppendorf North America, Westbury, NY) by measuring the absorbance at 260 and 280 nM wavelengths.

Amplification and Sequencing of Partial Mitochondrial 12S rRNA and Nuclear EF- I Genes

High-fidelity PCR was performed on each pooled DNA sample using universal

12S and EF-I primers. The primers used to amplify the partial 12S rRNA sequences

were: SR-J-14199 5’-TACTATGTTACGACTTAT-3’ (18-mer) and SR-N-14194 5’-

AAACTAGGATTAGATACCC-3’ (19-mer) (Table 2-1) (Kambhampati and Smith 1995).

The degenerate primers used to amplify the partial EF-I gene sequences were forward

5’-GAYTTYATHAARAAYATGAT-3’ (20-mer) and reverse 5’-GCYTCRTGRTGCATYTC-

3’ (17-mer) (Table 2-1) (Jeyaprakash and Hoy 2009a). The EF-I degenerate primers

used were chosen from several designed by Jeyaprakash and Hoy (2009a) after testing

combinations of forward and reverse primers. The High-fidelity PCR protocol

incorporated three linked profiles; (i) 1 cycle of denaturation at 94°C for 2 min, (ii) 10

cycles of denaturation at 94°C for 10 sec, annealing at 43°C for 30 sec, and extension

at 68°C for 1 min, and (iii) 25 cycles of denaturation at 94°C for 10 sec, annealing at

43°C for 30 sec, and extension at 68°C for 1 min, plus an additional 20 sec added for

every consecutive cycle. The EF-I PCR products (507 bp) were gel purified using the

QIAGEN QIAquick Gel Extraction Kit (QIAGEN Inc., Valencia, CA) to avoid preferential

ligation of primer-dimers during cloning. The 12S PCR products (369 bp) were cleaned

using a QIAGEN column following the procedure suggested by the manufacturer

(QIAGEN Inc., Valencia, CA). Next, A-tailing reactions with purified PCR products as

template were performed to increase the efficiency of cloning reactions. The A-tailed

PCR products were cloned using the Invitrogen pCR2.1 TOPO F’ Cloning Kit

(Invitrogen, Carlsbad, CA) following the protocol recommended by the manufacturer.

Plasmid DNA was extracted using the QIAGEN Mini Plasmid Prep Kit according to

procedures outlined by the manufacturer (QIAGEN, Valencia, CA). Restriction digestions were performed on the pCR2.1 TOPO plasmids extracted to confirm positive transformation with the sequence of interest. Plasmids containing the correct inserts were submitted five at a time from each Mauritius and S. Florida location for Sanger sequencing by the University of Florida Interdisciplinary Core Facility for Biotechnology

Research (ICBR) (Gainesville, Florida). A total of 20 plasmids containing the partial 12S rRNA gene and 10 plasmids for the partial EF-I gene were sequenced for each of the

five Mauritius and four S. Florida colonies.

Sequence Editing and Alignment

The 12S and EF-I gene sequences obtained from the ICBR were checked for

errors by eye and by using the sequence analysis program MacDNASIS version 3.7

(Hitachi, San Bruno, CA, USA). The sequences were compared with similar sequences

in the GenBank database using the BLAST (Basic Alignment Search Tool) search

program (Altschul et al. 1997). The most similar sequences obtained from the GenBank

BLAST results were included in the alignment for constructing the phylogenies (Tables

2-3, 2-4, 2-7, 2-8) (Hall 2001; Hoy 2003). The percentage A-T content of sequences

was calculated using the online Oligo Calc: Oligonucleotide properties calculator (Kibbe

2007). The partial EF-I DNA sequences were translated into amino acids to confirm

the presence of the open reading frame (ORF) and aligned (Figure 2-2) (to achieve

maximum levels of conservation for assessing the degree of similarity and homology)

after setting the parameters for pairwise alignment (gap opening = 15, gap extension =

6.66) and multiple alignments (gap opening = 15, gap extension = 6.66) and protein

weight matrix (Gonnet) (Hall 2001). The resulting alignment was checked for deletions

using CLUSTALX multi-sequence alignment software (Larkin et al. 2007). The 12S and

EF-I nucleotide data sets were aligned using CLUSTAL X v. 1.83 (Thompson et al.

1997) (Figures 2-1 and 2-3) to achieve maximum levels of identity for assessing the degree of similarity and the possibility of homology after setting the parameters for pairwise alignment (gap opening = 15, gap extension = 6.66) and multiple alignments

(gap opening = 15, gap extension = 6.66) (Hall 2001). To ensure a clearly resolved

phylogenetic tree, the alignments created by CLUSTALX were examined and, if necessary, edited manually using the MacClade software package.

Phylogenetic Analysis

Phylogenetic analysis to obtain posterior probabilities was performed using

MrBayes 3.1.2 software package for Bayesian Markov chain Monte Carlo analysis

(MCMC) (Huelsenbeck and Ronquist 2001; Ronquist and Huelsenbeck 2003).

Modeltest 3.7 (Posada and Crandall 1998) was used to select a best-fit model for

alignments from gene data sets. The hierarchal Likelihood Ratio Tests (hLRTs) and

Akaike Information Criterion (AIC) parameters obtained for each dataset was used to

preset the analyses in MrBayes. The hLRTs and AIC parameters generated for the 12S

rRNA best-fit model (TVM + I + G) were [Base = (0.4212 0.1098 0.0851) Nst = 6 Rmat =

(2.8564 10.5542 4.4554 1.2205 10.5542) Rates = gamma Shape = 1.3408 Pinvar =

0.0905]. The hLRTs and AIC parameters generated for the first EF-I best-fit model

(TIMef + I + G) were [Base = equal Nst = 6, Rmat = (1.0000 2.3823 1.5549 1.5549

4.5442) Rates = gamma Shape = 1.4683 Pinvar = 0.4559]. The hLRTs and AIC

parameters generated for the second EF-I best-fit model (TrN + G) were [Base =

(0.2375 0.2836 0.2641) Nst = 6 Rmat = (1.0000 2.0910 1.0000 1.0000 7.1734) Rates =

gamma Shape = 0.2752 Pinvar = 0] and the hLRTs and AIC parameters generated for the unknown EF best-fit model (TIMef + I + G) were [Base = (equal) Nst = 6 Rmat =

(1.0000 3.3897 1.9950 1.9950 6.6086) Rates = gamma Shape = 0.7516 Pinvar =

0.3351]. The posterior probabilities obtained from 1,000,000 generations were used to

support each branch in the Bayesian trees.

Pairwise Distance Analysis

Pairwise distances were calculated for the 12S and EF-I sequence alignments using the PAUP 4.0b10 software package (Swofford 2003). The 12S rRNA sequence pairwise distances were calculated with optimality criteria set at [Rates = gamma,

Shape = 1.3408, Kimura-2 parameters]. Pairwise distances were calculated for EF-I nucleic acid sequences with optimality criteria set at [Rates = gamma, Shape = 1.4683,

Kimura-2 parameters] and amino acid pairwise distances were analyzed with distance settings at mean character difference and Among-site rate variation (Jeyaprakash and

Hoy 2002).

High-fidelity-RAPD-PCR

A preliminary test of five random primers (UBC Biotechnology Laboratory,

Vancouver, BC, Canada) (Table 2-1) for production of distinctive and consistent

banding patterns was conducted on pooled extracted DNA from each of the five

Mauritius (25 mites total) and of each of the four S. Florida Amblyseius populations (20 mites total) using a High-fidelity RAPD-PCR (Hf-RAPD-PCR) protocol designed by

Jeyaprakash and Hoy (in press). Three Hf-RAPD-PCRs of the five primers were

conducted on the 2 pooled DNA samples as well as DNA from M. occidentalis, A.

swirskii, N. californicus, and N. cucumeris, to evaluate whether the banding patterns

were repeatable and consistent for each species or colony. Hf-RAPD-PCR was performed in 50 mM Tris (pH 9.2), 16 mM ammonium sulfate, 1.75 mM MgCl2, 350 µM

each of dATP, dGTP, dTTP, and dCTP, and 400 pM of the 10-mer primer, 1 U of

Accuzyme, and 5 U of Taq DNA polymerase. The Hf-RAPD-PCR was performed

incorporating three linked profiles; (i) one cycle of denaturation at 94°C for 2 min, (ii) 10

cycles of denaturation at 94°C for 10 sec, annealing at 36°C for 30 sec, and extension

at 68°C for 2 min, and (iii) 25 cycles of denaturation at 94°C for 10 sec, annealing at

36°C for 30 sec, and extension at 68°C for 2 min, plus an additional 20 sec added for

every consecutive cycle. Electrophoresis was performed using a 2% TBE (Tris-borate-

EDTA) agarose gel (14 cm x 10.2 cm) and 1% TBE electrophoresis buffer containing

ethidium bromide to separate and stain DNA amplicons. The DNA molecular weight

marker XIV (Roche Diagnostics, Indianapolis, IN) (100 bp to 2650 bp) was used to

determine band size. Bands were visualized and photographed under UV illumination.

The two informative primers that gave distinctive and consistent banding patterns

in the preliminary analysis were each employed in three independent replicated Hf-

RAPD PCR reactions using three different freshly extracted DNA pools from 30 starved

and pooled females from each of the five Mauritius colonies and four S. Florida colonies

(for a total of 10 reactions from the Mauritius colonies X 3 replicates and 8 reactions

from the S. Florida colonies X 3 replicates). In addition, on each of the three days the

replicates were conducted, duplicate reactions were conducted (pseudoreplication) to

further confirm the consistency of the results. Only distinct brightly stained bands (400

to 2650 bp) were scored as 1 (present) or 0 (absent) for the analysis. The evolutionary

history of taxa was inferred using the Neighbor-Joining method (Saitou and Nei 1987) in

PAUP 4.0b10 (Swofford 2003). The posterior probabilities tree is inferred from

1,000,000 generations.

Mitochondrial 12S rRNA Population-Specific Primers

The mitochondrial 12S rRNA sequences obtained from the five Mauritius and

four S. Florida populations were used to design population-specific forward primers

(Table 2-1). The population-specific primers for Mauritius (SR-J-MU, 5’ -

GCCTAATTAGCAAATATTACTTTT - 3’) and S. Florida (SR-J-S.FL, 5’ -

GCTTAAAAATTTTACTTTTA - 3’) were designed in variable regions of the 12S gene.

The specificity was tested with Amblyseius swirskii, Neoseiulus californicus, N.

cucumeris, and Metaseiulus occidentalis (Nesbitt) DNA. The population-specific primers

in combination with the universal 12S reverse primer SR-N-14594 (Kambhampati and

Smith 1995) should amplify a 406-bp fragment for the S. Florida populations and a 330-

bp fragment for the Mauritius populations.

The specificity of the two population-specific primers was tested using a High-

fidelity PCR protocol with clean DNA extracted by Puregene reagents (QIAGEN,

Valencia, CA) from aliquots taken from pools of DNA isolated from 30 starved females

from each of the five Mauritius colonies and DNA pools from all four S. Florida colonies.

DNA extracted from 30 pooled females from A. swirskii, N. californicus, N. cucumeris,

and M. occidentalis was tested as controls. To test the consistency of these reactions, duplicate PCRs were run for each primer and colony source (pseudoreplication). The

High-fidelity PCR protocol incorporated three linked profiles; (i) 1 cycle of denaturation at 94°C for 2 min, (ii) 10 cycles of denaturation at 94°C for 10 sec, annealing at 49°C for

30 sec, and extension at 68°C for 1 min, and (iii) 25 cycles of denaturation at 94°C for

10 sec, annealing at 49°C for 30 sec, and extension at 68°C for 1 min, plus an

additional 20 sec added for every consecutive cycle. Reaction products were separated using electrophoresis 2% TBE (Tris-borate-EDTA) agarose gel (14 cm x 10.2 cm) and

1% TBE electrophoresis buffer containing ethidium bromide. Bands were visualized and photographed under UV illumination. The DNA molecular weight marker XIV (Roche

Diagnostics, Indianapolis, IN) (100 bp to 2650 bp) was used to determine band size.

The gels were scored for the presence or absence of products and product sizes were estimated for each of the reactions.

Results

‘Amblyseius largoensis’ Bayesian Analysis and Sequence Divergence

A total of 20 clones each from the five Mauritius and four South Florida colonies

(180 clones total) were sequenced for the 12S rRNA gene and 10 clones each were

sequenced from the five Mauritius and four South Florida colonies (90 clones total) for

the EF-Iα gene. The 12S rRNA (Table 2-2) and EF-Iα (Table 2-3) unique gene sequences obtained from the Mauritius and S. Florida colonies, including sequences from taxa in GenBank, were used in the Bayesian analysis.

12S rRNA Sequences

All of the 12S rRNA sequences in this study aligned well (Figure 2-1). The 12S

rRNA sequences obtained from the S. Florida ‘A. largoensis’ populations had an A-T

content of ~ 75% and were ~ 410 bp in length. The Mauritius ‘A. largoensis’ populations

had an A-T content of ~ 76% and were ~ 407 bp in length. These are similar to the A-T

content in the same region of DNA in other phytoseiids such as A. swirskii (68%,

GenBank accession GU1284606), Neoseiulus californicus (78%, GenBank accession

AY099367), N. cucumeris (72%, GenBank accession GU198153), N. fallacis (79%,

GenBank accession AY099364), and M. occidentalis (77%, GenBank accession

AY099363). Three clones from two Mauritius colonies, Flic en Flac 1 (FNF1), Trou

d’Eau Douce 6 (TDD6) and Trou d’Eau Douce 7 (TDD7)) (Table 2-3, Figure 2-4),

differed from the majority of sequences obtained, with an A-T content of 69% and length

of 390 bp.

A Bayesian consensus tree was created in which the S. Florida and the Mauritius

colony clones resolved into two distinctly separate clades (Figure 2-4). The S. Florida

clade (clade-1) is supported by 99% posterior probability, and the Mauritius clade

(clade-2) is supported by 94% posterior probability. Three Mauritius clones (FNF1,

TDD6, and TDD7) separated out from the two main clades as a sister clade to N.

cucumeris and were supported by 100% posterior probability scores.

There is a 98.4% or higher DNA sequence similarity within the S. Florida clade-1 clones and 99.2 to 100% DNA sequence similarity within the Mauritius clade-2 clones.

The 12S rRNA corrected nucleotide sequence similarity between the Mauritius clade-2

clones and S. Florida clade-1 clones are 91 to 93% (Table 2-4), indicating that these

two populations are more similar to each other than they are to the other phytoseiid

species examined. The 12S rRNA sequences from Neoseiulus californicus are 62 to

64% similar to the Mauritius clade-2 clones and 61 to 62% similar to the S. Florida

clade-1 clones. The 12S rRNA sequences from Neoseiulus fallacis are 63 to 64%

similar to the Mauritius clade-2 clones and 63 to 64% similar to the S. Florida clade-1

clones; N. cucumeris sequences are only 18 to 22% similar to the Mauritius clade-2

clones and 19 to 22% similar to the S. Florida clade-1 clones. Amblyseius swirskii 12S

rRNA sequences are 64 to 66% similar to the Mauritius clade-2 clones and 61 to 63%

similar to the S. Florida clade-1 clones (Table 2-4).

If we compare 12S rRNA sequences obtained from GenBank of three Neoseiulus spp., three Phytoseiulus spp., and three Amblyseius spp., we find 12S rRNA sequence similarities of 59 to 91% for the Neoseiulus spp., 78 to 96% sequence similarities for the

Phytoseiulus spp. and 64 to 66% similarities for the Amblyseius sequences we examined (Jeyaprakash and Hoy 2002; Tixier et al. unpub.). The 91 to 93% sequence similarity observed in the Mauritius and S. Florida populations fall within the range of those observed between other phytoseiid species (Table 2-4).

In comparing intra-species similarities (Table 1-5) the four S. Florida populations exhibit 98.4% 12S rRNA sequence similarities. The five Mauritius populations exhibit

99.2% sequence similarity in the same gene. Sequence data from populations of three

Phytoseiulus spp. (Tixier et al. unpub.) indicate that there is 95 to 100% sequence similarity within each of the three P. persimilis populations, 96 to 100% sequence similarity within one P. macropilis population, and 93 to 99% sequence similarity within one P. fragariae population (Tixier et al. unpub.). Thus, intaspecific variation in the

Mauritius and S. Florida populations are similar to variation found in 12S rRNA sequences in GenBank from other phytoseiid species.

Three clones from the Mauritius colonies, FNF1, TDD6, and TDD7 (Table 2-3,

Figure 2-4), were not consistent with the majority of 12S rRNA sequences obtained from

Mauritius. In the Bayesian analysis, they resolved into a sister clade to N. cucumeris supported by 100% posterior probability scores (Figure 2-4). Further analysis of the sequences indicated they were only 29 to 34% similar to the Mauritius and S. Florida ‘A. largoensis’ clades and 62 to 63% similar to N. cucumeris. These outlier sequences

could not be identified, and could be the result of contamination or represent another phytoseiid species within the Flic en Flac and Trou d’Eau Douce colonies.

Elongation Factor-I Alpha Sequences

None of the EF-Iα sequences obtained from the ‘A. largoensis’ colonies and

reference taxa (A. swirskii, N. californicus, and N. cucumeris) contained indels or stop

codons (Figure 2-3). All nucleotide and inferred amino acid (Figure 2-2) sequences

aligned well with the acarine sequences, as well as the insect, spider, and Limulus

sequences obtained from GenBank. All ‘A. largoensis’ sequences had an open reading

frame (ORF) that was 568 bp in length. The G-C content of ‘A. largoensis’ sequences

separated into two groups with 58% and 60% G-C ratio, which is similar to that of M.

occidentalis (58%, GenBank accession FJ527739).

With the assumption that EF-Iα is a single-copy gene, a Bayesian consensus tree

was created (Figure 2-5). The resulting tree indicated two clades supported by 100%

posterior probability scores with the S. Florida and Mauritius populations intermixed. All

S. Florida colonies (1-4) are represented in the two clades. The Mauritius Trou d'Eau

Douce colony was represented in both clades while clones obtained from the North of

Port Louis colony were only found in clade-2 and Flic en Flac clones in clade-1. By

contrast, within the 12S dataset, the S. Florida clones all fall within a single clade, which

is distinctly separate from the Mauritius clones. EF-Iα is a protein-coding gene and

considered to be more conserved than the 12S rRNA gene. Therefore, the phylogenetic

inference from EF-Iα Bayesian analysis should not be divergent from the relationships

inferred with the 12S rRNA gene.

To explore the possibility that the putative EF-Iα sequence dataset represents two

genes instead of one (as is the case with some insects), the EF-Iα sequences were

reanalyzed. A set of BLAST searches were performed using the discontiguous

megablast algorithm (Ma et al. 2002) (more dissimilar sequences, i.e. deeper divergent

taxa are compared) against the Drosophila melanogaster genome, which is known to

have two copies of the EF-Iα gene, F1 and F2 (Hovemann 1988) (Table 2-5). The D.

melanogaster EF-I F2 ORF is interrupted by two introns while the F1 copy has none

(Hovemann 1988) and they share 90.5% nucleotide and 93.3% amino acid similarities.

The sequences for the two ‘A. largoensis’ clades are 82-38% and 95% similar in nucleotide and amino acid sequences, respectively. The BLAST search comparisons are scored by E score and maximum percentage identity (sequence similarity). The E score is defined by GenBank as the number of different alignments with scores equivalent to or better than those that are expected to occur in a database search by chance; thus, the lower the E value, the more significant the score. The sequences in clade-1 had a 77% (E = 2e-120) identity to the D. melanogaster EF-Iα F1 gene and the clade-2 sequences had a 76% (E = 2e-101) identity to the EF-Iα F2 gene (Table 2-5).

The primary reason why clade-2 and clade-1 cannot be considered equivalent to the D. melanogaster EF-Iα F1 and F2 is the lack of introns in the clade-1 sequences. However, it is possible that introns are lacking or lost in the F2 copy of EF-Iα in mites. An alternative hypothesis to explain the presence of two EF-I sequences is that the

Mauritius and S. Florida colonies each contain more than one species, but this is less

likely.

A second BLAST search using the megablast algorithm (Zang et al. 2000) (for

highly similar sequences, i.e. closely related taxa are compared) in the GenBank

nucleotide database was performed for the clade-1 and clade-2 sequences and yielded

primarily acarine taxa (Table 2-5). Consistently, the sequences in clade-2 had higher percentage (91 to 80%) maximum identity (similarity) and E scores with the acarine EF-

Iα sequences than the clade-1 sequences (85 to 79%) (Table 2-5), indicating the two

sequences may represent two different genes. In addition to the Mauritius and S.

Florida clones, the reference phytoseiid clones from A. swirskii, N. californicus, and N.

cucumeris were examined using the megablast algorithm and sorted according to their

respective percentage maximum identity (Tables 2-6, 2-7). The five clones sequenced

from A. swirskii had a 91% maximum identity (E = 0) to the EF-Iα from M. occidentalis.

Five clones were sequenced for N. californicus, four of which had a 91% (E = 0)

maximum identity to M. occidentalis EF-Iα and the remaining clone had an 82% (E = 1e-

129) maximum identity to the nest mite Dermanyssus hirundinis putative EF-Iα

sequence (GenBank accession AM930860). Of 15 clones sequenced for N. cucumeris

only one clone with an ORF was obtained, and BLAST search of this sequence returned

an 81% (E = 1e-130) maximum identity to the feather mite, Pterolichus obtusus Robin,

putative EF-Iα sequence (GenBank accession, EU152765). With these scores we may

infer that the sequences in clade-2 are putative EF-Iα sequences (Table 2-6) and the

sequences in clade-1 are an unknown elongation factor (ukn EF) or a second EF-Iα

gene (Table 2-7). The reference phytoseiids were sorted as follows: A. swirskii

(GenBank accession GU198152) and N. californicus (to be submitted) were placed in

the EF-Iα sequence group (Table 2-6), N. californicus (GenBank accession GU198153)

and N. cucumeris (GenBank accession GU198151) in the ukn EF sequence group

(Table 2-7). The putative EF-Iα (Table 2-6) sequences were aligned using CLUSTALX,

and examined through a second EF-Iα Bayesian analysis to obtain posterior

probabilities for the ‘true’ EF-Iα sequences in ‘A. largoensis’ and related phytoseiids.

The resulting consensus tree (Figure 2-6) reveals that the ‘true’ EF-Iα clones obtained from the Mauritius and S. Florida populations resolve into a single clade, which is to be expected if this gene is only informative at the genus level in phytoseiids.

The corrected nucleotide and amino acid divergences for the ‘A. largoensis’ EF-

Iα clade-2 and the ukn EF clade-1 (or potential second EF-Iα gene) sequences were

calculated (Table 2-8). The EF-Iα nucleotide divergences between the Mauritius and S.

Florida populations and the reference phytoseiids Amblyseius swirskii and Neoseiulus

californicus are 5 to 6%. The EF-Iα nucleotide divergences between Amblyseius swirskii

and Neoseiulus cucumeris are 2%. An analysis of the same region of EF-Iα in

Dermanyssus species (D. carpathicus, D. gallinae, and D. hirundinis; GenBank

accessions AM930872, AM930879, and AM930860) (Table 2-8) reveals 2, 3 and 4%

nucleotide divergences. When compared to the nucleotide divergences calculated

between species and genera of the Acari, the high degree of similarity between the

Mauritius and S. Florida populations ‘true’ EF-Iα sequences (99.6 to 99.8%) suggests

they are the same species.

High-fidelity-RAPD-PCR Analysis of ‘A. largoensis’ Populations

High-fidelity-RAPD-PCR was performed on the five Mauritius and four S. Florida colonies using two RAPD markers. Consistently, 19 bands were scored. A consensus tree was inferred using the Neighbor-Joining method. The unrooted consensus tree

(Figure 2-7) indicates the Mauritius and S. Florida colonies fall within two distinctly separate groups. The S. Florida clade is supported by a high (100%) bootstrap value in comparison to the relatively low bootstrap values for the Mauritius clade (67%). The least support was found for the Flic en Flac colony that fell below 50% resulting in a

collapsed branch. The Neighbor-joining analysis of High-fidelity-RAPD scores places

the two populations into separate clades suggesting that they are genetically distinct.

Mitochondrial 12S rRNA Population-Specific Primers

The 12S rRNA population-specific primers designed for the Mauritius and for the

S. Florida ‘A. largoensis’ populations each resulted in a product of the expected size

(Figure 2-8). No amplicons of the expected size were obtained from the control taxa (A.

swirskii, N. californicus, N. cucumeris, and M. occidentalis).

Discussion

Bayesian analysis of the Mauritius and S. Florida 12S rRNA sequences places the clones into two distinct clades (Figure 2-4) and is supported by 91 to 93% sequence similarities between the two populations (Table 2-4), comparable to sequence similarities between other phytoseiid species. Additional phytoseiid 12S rRNA

sequences would confirm whether this gene is informative at the species level in all

phytoseiid genera. The outlier sequences obtained from the Mauritius Flic en Flac and

Trou d’Eau Douce colonies suggest that they are mixed populations. This may indicate that a cryptic species complex was collected from Mauritius with one ‘species’ out- competing the other for resources in culture or may be a product of contamination while in culture.

Using the 12S rRNA sequence data obtained from the phylogenetic analysis,

Mauritius ‘A. largoensis’ population-specific primers were designed to for a rapid method for detecting these predators in field-collected samples if it were to be released

(Figure 2-8A). In addition, S. Florida population-specific primers were created to detect

contamination by the Florida predators in the cultured Mauritius colonies (Figure 2-8B).

The use of population-specific primers designed from variable regions within the 12S rRNA gene may prove useful in other phytoseiid biological control projects.

The incongruence between the initial EF-Iα (Figure 2-5) and the 12S rRNA

(Figure 2-4) Bayesian analyses led us to question whether the partial EF-Iα sequences are representatives of one or two genes. Through examination of the sequence similarity between the cloned partial EF-Iα sequences with D. melanogaster and M. occidentalis EF-Iα sequences in GenBank (Table 2-5), we were able to separate the two clades into EF-Iα (clade-2) (Table 2-6) and an unknown elongation factor that may represent a second copy of EF-Iα (Table 2-7). A second analysis of the Mauritius and S.

Florida putative EF-Iα clones resolved the two populations into a single clade supported by posterior probabilities score of 100 (Figure 2-6). When compared to the sequence divergences observed between other phytoseiids and those between Dermanyssus

species (Table 2-8), the high similarity between the sequences from Mauritius and S.

Florida populations (99.6 to 99.8%) suggest that they are the same species. However,

this is a highly conserved gene and may not be suitable for species discrimination in

these mites. The presence of both the EF-Iα and the ukn elongation factor gene in the

same genome was confirmed using EF-Iα and ukn elongation factor-specific primers

Mauritius and one S. Florida isoline. PCR products from both primer sets were obtained

from each of the two isolines tested. This indicated that both copies are present in

individuals of the Mauritius and the S. Florida phytoseiids tested and the two sequences

are not indicative of contamination.

Both the ukn elongation factor sequences and the EF-Iα sequences were the result of using degenerate primers to survey the two populations. In future work, care should be taken when using EF-Iα degenerate primers because this gene is not always a single-copy gene and confusion can occur if more than one EF gene is amplified. An

investigation of acarine EF-Iα sequence data in GenBank revealed that the putative EF-

Iα sequences were also obtained from degenerate primers (Roy et al. unpub;

Lekveishvili and Klompen 2004). It is possible that some of these sequences may be incorrectly identified as EF-Iα and, as a result, incorrect phylogenetic inferences may have been proposed.

The results of the RAPD analysis (Figure 2-8) indicate the Mauritius and S. Florida populations are in two distinct genetic groups. These results support the 12S rRNA

Bayesian analysis that also places the two populations into two separate and distinct clades. Future analysis with additional RAPD primers could provide additional support.

In addition, it would be useful to evaluate other closely related taxa in order to produce a rooted Neighbor-joining analysis for RAPD markers.

In this study, the 12S rRNA gene in phytoseiids has proven to be informative at the species level and may be useful in future phylogenetic studies that require species resolution. Although no firm conclusions can be made on the informative nature of the

EF-Iα gene, its use as a marker for species resolution is questionable. Unfortunately, prior to conducting a phylogenetic analysis in groups for which little genetic information is available, there is no way to predict what genes will be informative. The task of finding informative genes in phytoseiids is especially problematic when limited primers and so little sequence information is available. At present, only sequences for mitochondrial

genes, a mariner transposable element, Actin genes 1-4 (Jeyaprakash and Hoy 2009a),

18S (Pham et al. unpub.; Xia et al. unpub.), 28S (Cruickshank and Thomas 1999), the

ITS-1 and ITS-2 complex (Navajas et al. 1999; Ramadan et al. unpub.; Xia et al. unpub.), and the EF-Iα gene (Jeyaprakash and Hoy 2009a; Bowman et al. unpub.) are

known for a limited number of phytoseiid taxa. Genome sequencing of one or more

phytoseiid species could provide more informative genetic markers and could make

phylogenetic analyses more effective. As a result of the incongruence between the

12S, EF-Iα, and RAPD analyses, a conclusion cannot be made as to whether the

Mauritius and S. Florida populations are cryptic species or biotypes of ‘A. largoensis’ without weighing the results of one analysis as more significant than the other. The incongruent results do not provide enough information to determine whether the

Mauritius phytoseiid should be released as a biological control agent of the RPM in S.

Florida. In order to determine the species status of the Mauritius and S. Florida populations, additional genes could be analyzed in conjunction with reproductive compatibility tests. If the two populations are reproductively incompatible, biological assays to determine whether the Mauritius phytoseiid can feed, survive, and reproduce on a diet consisting only of RPM should be conducted. In addition, tests should be conducted to determine whether the Mauritius populations are likely to be more efficacious predators of the RPM than the S. Florida phytoseiids. If the Mauritius and S.

Florida populations hybridize and produce viable progeny, releasing the Mauritius

phytoseiid into the Florida environment as a biological control agent of the RPM may not

be justified. However, release may be justified if the Mauritius phytoseiids are

determined to be more efficacious RPM predators and the populations’ hybrids are considered equally efficacious.

Table 2-1. List of molecular markers used and expected PCR product size. Marker Primer Sequence Expected product size (bp) Author(s)

12S SR-J-14199 5'-TACTATGTTACGACTTAT-3' 390 - 408 Kambhampati and Smith 1995

SR-N-14594 5'-AAACTAGGATTAGATACCC-3' “ “

SR-J-MU 5’-GCCTAATTAGCAAATATTACTTT-3’ 330 For this study

SR-J-S.FL 5’-GCTTAAAAATTTTACTTTTA-3’ 406 “ “

EF-Iα Deg-EF1a-F2 5'-GAYTTYATHAARAAYATGAT-3' 605 Jeyaprakash and Hoy 2009a

Deg-EF1a-R1 5'-GCYTCRTGRTGCATYTC-3' “ “ UBC Biotechnology Laboratory Hf-RAPD 122 5'-GTAGACGAGC-3' 400 - 2650 (Vancouver, BC, Canada) 183 5'-CGTGATTGCT-3' 400 - 2650 “ “

188 5'-GCTGGACATC-3' 400 - 2650 “ “

196 5'-CTCCTCCCCC-3' 600 - 2650 “ “

199 5'-GCTCCCCCAC-3' 400 - 2650 “ “

Table 2-2. List of GenBank accession numbers for clones and taxa included in the 12S rRNA Bayesian analysis. The clone source or GenBank sequence authors are included. The S. Florida (FL) and Mauritius (MU) ‘A. largoensis’ clones are from pooled colonies. Clone or taxa Colony source or author(s) GenBank accession

FL 1 Hollywood, FL GU807437 FL 2 Lake Worth, FL GU807438 FL 3 Lake Worth, FL GU807439 FL 4 Lake Worth, FL GU807440 FL 5 Lake Worth, FL GU807441 FL 6 Lake Worth, FL GU807442 FL 7 Lake Worth, FL GU807443 FL 8 Lake Worth, FL GU807444 FL 9 Lake Worth, FL GU807445 FL 10 Hollywood, FL GU807446

FF 1 Flic en Flac, MU GU807447 FF 2 Flic en Flac, MU GU807448 FF 3 Flic en Flac, MU GU807449 FF 4 Flic en Flac, MU GU807450 FF 5 Flic en Flac, MU GU807451

NPL 1 North of Port Louis, MU GU807452 NPL 2 North of Port Louis, MU GU807453 NPL 3 North of Port Louis, MU GU807454 NPL 4 North of Port Louis, MU GU807455 NPL 5 North of Port Louis, MU GU807456 NPL 6 North of Port Louis, MU GU807457 NPL 7 North of Port Louis, MU GU807458 NPL 8 North of Port Louis, MU GU807459 TDD 1 Trou d'Eau Douce (Colony 1), MU GU807460 TDD 2 Trou d'Eau Douce (Colony 1), MU GU807461 * Number following a colony source location indicates the clone number.

Table 2-2. Continued. Clone or taxa Colony source or author(s) GenBank accession TDD 3 Trou d'Eau Douce (Colony 1), MU GU807462

TDD 4 Trou d'Eau Douce (Colony 1), MU GU807463

TDD 5 Trou d'Eau Douce (Colony 1), MU GU807464

TDD 6 Trou d'Eau Douce (Colony 1), MU GU807465

TDD 7 Trou d'Eau Douce (Colony 1), MU GU807466

TDD 8 Trou d'Eau Douce (Colony 1), MU GU807467

TDD 9 Trou d'Eau Douce (Colony 2), MU GU807468

TDD 10 Trou d'Eau Douce (Colony 2), MU GU807469

TDD 11 Trou d'Eau Douce (Colony 2), MU GU807470

TDD 12 Trou d'Eau Douce (Colony 2), MU GU807471

TDD 13 Trou d'Eau Douce (Colony 2), MU GU807472

TDD 14 Trou d'Eau Douce (Colony 2), MU GU807473

TDD 15 Trou d'Eau Douce (Colony 3), MU GU807474

TDD 16 Trou d'Eau Douce (Colony 3), MU GU807475

TDD 17 Trou d'Eau Douce (Colony 3), MU GU807476

TDD 18 Trou d'Eau Douce (Colony 3), MU GU807477

TDD 19 Trou d'Eau Douce (Colony 3), MU GU807478

TDD 20 Trou d'Eau Douce (Colony 3), MU GU807479 Drosophila melanogaster Meigen Lewis et al. 1995 NC_001709 Habronattus oregonensis (Peckham & Peckham) Hedin and Maddison 2001 AF359082 Iphiseius degenerans (Berlese) Jeyaprakash and Hoy 2002 AY099368

Ixodes hexagonus Leach Black and Roehrdanz 1998 NC_002010

Limulus polyphemus Latr. Lavrov et al. 2000 AF216203

Locusta migratoria (L.) Flook et al. 1995 NC_001712 * Number following a colony source location indicates the clone number.

Table 2-2. Continued. Clone or taxa Colony source or author(s) GenBank accession

Metaseiulus occidentalis (Nesbitt) Jeyaprakash and Hoy 2002 AY099363

Neoseiulus californicus (McGregor) Jeyaprakash and Hoy 2002 AY099367

N. cucumeris Oud. Jeyaprakash and Hoy 2002 AY099366

N. fallacis (Garman) Jeyaprakash and Hoy 2002 AY099364

A. swirskii (Athias-Henriot) Syngenta Bioline Inc. CA GU1284606

Nephila clavata Koch Lee et al. unpub. NC_008063

Ornithoctonus huwena Wang et al. Qiu et al. 2005 NC_005925

Phytoseiulus fragariae Denmark and Schicha Tixier et al. unpub. FJ985128

P. longipes Evans Tixier et al. unpub. FJ952535

P. persimilis Athias-Henriot Tixier et al. unpub. FJ985122

Rhipicephalus sanguineus (Latreille) Black and Roehrdanz 1998 NC_002074

Tetranychus urticae Koch Jeyaprakash and Hoy 2002 AY099365

Varroa destructor Oud. Evans and Lopez 2002 AY163547 * Number following a colony source location indicates the clone number.

Table 2-3. List of GenBank accession numbers for clones and taxa included in the EF- I Bayesian analysis. The clone source or GenBank sequence authors are included. The S. Florida (FL) and Mauritius (MU) ‘A. largoensis’ clones are from pooled colonies. Clone or taxa Colony source or author(s) GenBank accession

FL 1 Lake Worth, FL GU198155

FL 2 Lake Worth, FL GU198156

FL 3 Lake Worth, FL GU198157

FL 4 Lake Worth, FL GU198158

FL 5 Lake Worth, FL GU198163

FL 6 Lake Worth, FL GU198162

FL 7 Hollywood, FL GU198164

FL 8 Hollywood, FL GU198149

FF 2 Flic en Flac, MU GU198161

FF 3 Flic en Flac, MU GU198160

NPL 1 North of Port Louis, MU GU814633

TDD 1 Trou d'Eau Douce colony 1, MU GU198168

TDD 2 Trou d'Eau Douce colony 2, MU GU198167

TDD 3 Trou d'Eau Douce colony 2, MU GU198169

TDD 4 Trou d'Eau Douce colony 3, MU GU198166

Amblyomma sp. Shultz and Regier unpub. AF240836

Amblyseius swirskii Syngenta Bioline Inc. CA GU198152

Aphonopelma chalcodes Chamberlin Regier and Shultz 1997 ACU90045

Dermanyssus hirundinis (Hermann) Roy et al. unpub. AM930860

Drosophila melanogaster Hoskins et al. 2007 NM_206593

Dysdera crocata Koch Regier and Shultz 1997 DCU90047 * Number following a colony source location indicates the clone number.

Table 2-3. Continued. Clone or taxa Colony source or author(s) GenBank accession Euzercon latum Lekveishvili and Klompen unpub. AY624008

Limulus polyphemus Regier and Shultz 1997 LPU90051

Locusta migratoria Zhou et al. 2002 AY077627

Metaseiulus occidentalis Jeyaprakash and Hoy 2009a FJ527739

Neacarus texanus Chamberlin & Mulaik Shultz and Regier unpub. AF240849

Neoseiulus californicus Syngenta Bioline Inc. CA GU198153

N. cucumeris Syngenta Bioline Inc. CA GU198151

Raoiella indica Hollywood, Florida GU198150

Tetranychus urticae Cultured colony, Gainesville, FL GU198154

Locusta migratoria Zhou et al. 2002 AY077627 * Number following a colony source location indicates the clone number.

Table 2-4. Corrected pairwise distances between unique mitochondrial 12S rRNA sequences obtained from the Mauritius and S. Florida ‘A. largoensis’ populations* with additional phytoseiid GenBank accessions (24-27) using PAUP 4.0b8 with Kimura 2-parameter and among-site rate variation distance settings. Distance measured by using a scale of 0 - 1.

* Number following a colony source location indicates the clone number.

Table 2-5. BLAST searches performed for the EF-Iα consensus tree clade-1 and clade-2 nucleotide sequences (Figure 2- 5) using the discontiguous megablast (more dissimilar sequences) and the megablast (for highly similar sequences) algorithms in the GenBank database. Consistently, a higher % maximum identity (similarity) and a lower expectation value or E score were obtained for the clade-2 sequence group. Clade-1 (lacks intron) Clade-2 GenBank Maximum % Maximum % Taxa accession E value identity E value identity Discontiguous megablast search: Drosophila melanogaster EF-Iα F1 NM_165850.2 2e-120 77 7e-138 79 Drosophila melanogaster EF-Iα F2 (contains intron) X06870 2e-101 76 2e-94 74 Drosophila melanogaster EF-Iα F1 * NM_165850.2 - - 2e-138 79 Drosophila melanogaster EF-Iα F2 (contains intron)* X06870 - - 2e-95 75 Megablast search: (Acari lack introns) Metaseiulus occidentalis FJ527739 4e-180 85 0 91 Androlaelaps casalis (Berlese) AM930875 1e-162 82 0 85 Dermanyssus longipes Berlese & Trouessart AM930873 5e-160 82 0 85 Macronyssidae sp. AM930881 2e-159 82 0 85 Dermanyssus gallinae (De Geer) AM930878 2e-158 82 0 85 Dermanyssus carpathicus Dugès AM930872 1e-155 81 6e-178 84 Dermanyssus hirundinis AM930860 1e-154 81 2e-172 83 Megisthanus floridanus AY624009 1e-154 81 2e-164 82 Euzercon latum AY624008 4e-142 80 1e-155 81 Ixodes scapularis Say XM_002411102 2e-134 79 2e-145 80 * Clone NPL 1 has a 1% nucleotide sequence divergence from all other clade-2 clones (Table 2-8), and was compared to the D. melanogaster EF-Iα F1 and F2 sequences.

Table 2-6. List of GenBank accession numbers for clones and taxa included in the putative EF-I Bayesian analysis. The clone* source or GenBank sequence authors are included. The S. Florida (FL) and Mauritius (MU) ‘A. largoensis’ clones are from pooled colonies. Clone or taxa Colony source or author(s) GenBank accession FL 1 Lake Worth, FL GU198155 FL 4 Lake Worth, FL GU198158 FL 6 Lake Worth, FL GU198162 FL 7 Hollywood, FL GU198164 TDD 1 Trou d'Eau Douce colony 1, MU. GU198168 TDD 3 Trou d'Eau Douce colony 2, MU GU198169 NPL 1 North of Port Louis, MU GU814633

Amblyseius swirskii Syngenta Bioline Inc. CA GU198152 Apis mellifera Danforth and Ji 1998 NM_001014993 Dermanyssus hirundinis Roy et al. unpub. AM930860 Drosophila melanogaster Hovemann et al. 1988 X06869 Euzercon latum Lekveishvili and Klompen 2004 AY624008 Megasthanus floridanus Lekveishvili and Klompen 2004 AY624009 Metaseiulus occidentalis Jeyaprakash and Hoy 2009a FJ527739 Neoseiulus californicus Syngenta Bioline Inc. CA To be submitted Raoiella indica Hollywood, FL GU198150 Tetranychus urticae Cultured colony, Gainesville, FL GU198154 * Number following a colony source location indicates the clone number.

Table 2-7. List of GenBank accession numbers for clones and taxa included in the ‘unknown elongation factor’ sequence group. The clone* source or GenBank sequence authors are included. The S. Florida (FL) and Mauritius (MU) ‘A. largoensis’ clones are from pooled colonies. Clone or taxa Colony source or author(s) GenBank accession

FL 2 Lake Worth, FL GU198156 FL 3 Lake Worth, FL GU198157 FL 5 Lake Worth, FL GU198163 FL 8 Hollywood, FL GU198149 TDD 2 Trou d'Eau Douce colony 2, MU GU198167 TDD 4 Trou d'Eau Douce colony 3, MU GU198166 FF 2 Flic en Flac, MU GU198161 FF 3 Flic en Flac, MU GU198160 Neoseiulus californicus Syngenta Bioline Inc. CA GU198153 N. cucumeris Syngenta Bioline Inc. CA GU198151 * Number following a colony source location indicates the clone number.

Table 2-8. Corrected pairwise distances between the Mauritius and S. Florida ‘A. largoensis’ clones* putative EF-Iα amino acid (above diagonal) and nucleotide (below diagonal) sequences with additional phytoseiid GenBank accessions using PAUP 4.0b8. Distance measured by using a scale of 0 - 1. No. Clone or Taxa 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. S. Florida 1 - 0 0 0 0 0 0 0.01 0.01 0.02 0.05 0.05 0.05 0.20

2. S. Florida 4 0 - 0 0 0 0 0 0.01 0.01 0.02 0.05 0.05 0.05 0.20

3. S. Florida 6 0 0 - 0 0 0 0 0.01 0.01 0.02 0.05 0.05 0.05 0.20

4. S. Florida 7 0 0 0 - 0 0 0 0.01 0.01 0.02 0.05 0.05 0.05 0.20

5. N. of Port Louis 1 0 0 0 0 - 0 0 0.01 0.01 0.02 0.05 0.05 0.05 0.20

6. Trou d'Eau Douce 1 0 0 0 0 0.01 - 0 0.01 0.01 0.02 0.05 0.05 0.05 0.20

7. Trou d'Eau Douce 3 0 0 0 0 0.01 0 - 0.01 0.01 0.02 0.05 0.05 0.05 0.20

8. Amblyseius swirskii 0.06 0.06 0.06 0.06 0.06 0.06 0.06 - 0.01 0.02 0.05 0.05 0.05 0.20

9. Neoseiulus californicus 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.02 - 0.02 0.06 0.06 0.06 0.21

10. Metaseiulus occidentalis 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.09 0.09 - 0.06 0.06 0.06 0.20

11. Dermanyssus carpathicus 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.18 0.19 0.18 - 0.01 0 0.21

12. D. gallinae 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.18 0.18 0.18 0.03 - 0.01 0.21

13. D. hirundinis 0.18 0.18 0.18 0.18 0.19 0.18 0.18 0.19 0.2 0.17 0.02 0.04 - 0.21

14. Drosophila melanogaster 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.27 0.25 0.29 0.27 0.29 - * Number following a colony source location indicates the clone number.

10 20 30 40 50 60 70 80 90 ......

South Florida 1 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 2 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 3 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 4 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 5 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 6 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 7 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 8 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 9 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT “ “ 10 CT---TTGC------TCAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATCTAAATAAGAAT Flic en Flac 1 CT-ATCAAAA------GAGTGACGGG-CGATATGTACTCCTGCTTAAA---AACTA-AC-CAGCAACAG “ “ 2 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 3 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 4 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 5 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT North Port Louis 1 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 2 CT---TTAC------ACAAGAGTGGCGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 3 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 4 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 5 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 6 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 7 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 8 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ACAAA----TAAAATTTAAATAAGCCT Trou d’Eau Douce 1 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 2 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 3 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 4 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 5 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 6 CT-ATCAAAA------GAGTGACGGG-CGATATGTACTCCTGCTTAAA---AACTA-AC-CAGCAACAG “ “ 7 CT-ATCAAAA------GAGTGACGGG-CGATATGTACTCCTGCTTAAA---AACTA-AC-CAGCAACAG “ “ 8 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 9 CT---TTAC------ACAGGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 10 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAGATAAGCCT “ “ 11 CT---T-AC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 12 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 13 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 14 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 15 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 16 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 17 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 18 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 19 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT “ “ 20 CT---TTAC------ACAAGAGTGACGGG-CGATATGTACACAA-ATAAA----TAAAATTTAAATAAGCCT Iphiseius degenerans CT---CTAA------AAGAGAGTGACGGG-CAATATGTACACAT-CTAAAA---TTTTATTCAAATAAACAA Amblyseius swirskii CT---C-AAA------AAGAGAGTGACGGG-CGATATGTACACATACTGAAA---AGAAATTCAAATTAACCT Neoseiulus californicus CT---CTAAT------AAGAGAGTGACGGG-CAATATGTACACTT-CTAAAA---ACTAATTCAAATTAGCAA Neoseiulus cucumeris CT-ATCAAAA------GAGTGACGGG-CGATATGTACTTTCACCAAAA---ATCCACAT-CAATAAGAA Neoseiulus fallacis CT---CTAAT------AAGAGAGTGACGGG-CAATATGTACACTT-CTAAAA---ACTAATTCAAATTAGAAT Phytoseiulus fragariae CT---CTAAA------AAGAGAGCGACGGG-CAATATGTACACTT-ATAAAA---TTATATTCAAATTCGCCT Phytoseiulus longipes CT---CTAAT------AAGAGAGTGACGGG-CAATATGTACACTT-TTAAAA---TCACATTCAACCAAGCTT Phytoseiulus persimilis CT---CTAAA------AAGAGAGTGACGGGGCAATATGTACACTT-ATAAAA---TCTAATTCAAATTAGCTA Metaseiulus occidentalis CT---CTTA------GAGAATGACGGG-CAATATGTACACTTAAAATTT---TTTTATTCAAATTTATTT Varroa destructor TTCATTTTAC------TGAAAGTGACGGG-CGATATGTACACATTTTAGAG---CTTATTTCAAATATTTAT Rhipicephalus sanguineus CT--TATAA------AAGAGTGACGGG-CGATATGTACATATTTTAGAG---CTTAATTCAAATTGACAT Iphiseius hexagonus CT--CAAAAT------TGAGAGCGACGGG-CGATATGTGCATATTCTAGAG---CTTAATTCAATTATCCAT Tetranychus urticae TTCATTTTAAA------AATGAAAGTGATGGG-CAATATGTACATAAAATAATTATTTCATAATCATTTTTATAA Habronattus oregonensis CTTATTTTGT------AATAAGGGTGACGGG-CGATATGTGCACTTCCGTAAA----GAAATTCAAGTTAA-AA Ornithoctonus huwena CTCATCTTTG------GACGAGGGTGACGGG-CGATATGTACACCTTT-TTAG----CTTTTTCATAAAAA-AT Nephila clavata CTTGCCTTAG------GGAAAGGGTGACGGG-CGATATGTGCACATTTATTAT----CATGTTCAAATTTA-AA Limulus polyphemus CTCACCTAAAA------GCGAGAGCGACGGG-CGATGTGTACATGCCTTAGAG---CCCTATTCACAATTACAT Locusta migratoria CTCATATTAAAAGATATAAAATTTTAATCAATAACGAGAGTGACGGG-CGATGTGTACACACTTCAGAG---CCAATATCAGTTAAATTA Drosophila melanogaster CTTACCTTAA------TAATAAGAGCGACGGG-CGATGTGTACATATTTTAGAG---CTAAAATCAAATTATTAA

Figure 2-1. CLUSTAL X DNA alignment for partial mitochondrial 12S rRNA gene sequences from the S. Florida and Mauritius ‘A. largoensis’ populations with additional phytoseiid GenBank accessions. Number following a colony source location indicates the clone number. Hyphen denotes deletion.

100 110 120 130 140 150 160 170 180 ......

South Florida 1 AATTAGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTATATAAT “ “ 2 AATTAGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTATATAAT “ “ 3 AATTCGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTATATAAT “ “ 4 AATTCGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTATATAAT “ “ 5 AATTCGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTATATAAT “ “ 6 AATTAGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTACATAAT “ “ 7 AATTAGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTGTATAAT “ “ 8 AATTCGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTATATAAT “ “ 9 GATTCGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTATATAAT “ “ 10 AATTCGCTTAAAAATTTTACTTTTAAATTTTTCTTTAATTCC---TTATTAAAAAAAAACTATAGTTA---AATAATAAT-TTATATAAT Flic en Flac 1 ATTTAAAC--AACTGCTTACTTTCAAATCCATTTTTAT------TGAGAATTACTTCACAAA--AATAATAAA----AGTAGC “ “ 2 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 3 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 4 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT Flic en Flac 5 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT North Port Louis 1 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 2 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 3 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 4 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 5 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 6 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 7 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 8 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT Trou d’Eau Douce 1 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 2 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 3 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 4 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 5 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 6 ATTTAAAC--AACTGCTTACTTTCAAATCCATTTTTAT------TGAGAATTACTTCACAAA--AATAATAAA----AGTAGC “ “ 7 ATTTAAAC--AACTGCTTACTTTCAAATCCATTTTTAT------TGAGAATTACTTCACAAA--AATAATAAA----AGTAGC “ “ 8 AATTAGC----AAATATTACTTTTAAATTTCTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 9 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 10 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 11 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 12 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 13 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 14 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 15 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 16 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 17 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 18 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 19 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT “ “ 20 AATTAGC----AAATATTACTTTTAAATTTTTCTTTAATCTC---TTATTAAAAAGAAATTATAGTTA---AATAATAAT-TCATATAAT Iphiseius degenerans AATTTAT-----TATTTTACTTTTAAATTCTTCTATACTTATAA-TTATTACAATATAAAGACAGTTA---AATAAAAAT-TTATGTAAT Amblyseius swirskii AATAAACC----AATTTTACTTTTAAATTTTAAATATTAAAA---T-ATTACAAAAACTA-ATTTTTAA--AATAAAAAT-TAATAAAAC Neoseiulus californicus AATATACT----AATATTACTTTTAAATTCTATTTTTAAACT---TTATTACAAAAATAA-ATCATTAA--A-TACTAAT-TAATGAAAC Neoseiulus cucumeris ATTCAATT--TCTTATTTACTATCAAATCCAATTTCAA------ATAAAATTAATTTTATAC--AA----AAA----AGTAGC Neoseiulus fallacis AATATACT----AATATTACTTTTAAATTCTATTTTTTATTT---TTATTACAAAAATAA-ATTATTAA--A-TTTTAAT-TAATGAAAC Phytoseiulus fragariae GATAAACT----AATTTTACTTTTAAATTTTACTTAATTTTTAT-TTACA-TTCAAATCTCGTTACTA---AATAATAAT-TAATATAAT Phytoseiulus longipes AATATACT----TAATTTACTTTTAAATTTTACTAAATTTTAGA-TTACAACTAAAATATTGTTATTA---A-TAATAAT-TAATATAAT Phytoseiulus persimilis AATATACT----AATTTTACTTTTAAATTTTACTAAATTATTAT-TTACA-TTTAAATCTCGTTAAAAT--AATAAAAAT-TATTATAAT Metaseiulus occidentalis TATAGAT----AAATTTTACTTTTAAATTTTTCTTATTTTGA---TTATTTCAAATTTTCAATTTTTGTGAGATTTTAATCTGGTATAAT Varroa destructor AATTTAA----ATATTTTACTTTTAAATCTTTCTTTATAAAA---TTATTTAAAAATTCATATTGTTA---AAAATTAAT-TAATATAAT Rhipicephalus sanguineus TCTATTTC----AATTTTACTTTCAAATCCTAAATGTTATTT------AAATTTCTCTCTCTA---AAAAGAAAT-----GTAAT Iphiseius hexagonus CATATTAA----TAATTTACTTTTAAATCCTAATCTCATCTT------TCAACATATTTAATC---AAAATCAAT-----GTAAT Tetranychus urticae TTCTATTT---A----TTACTATTAAATTCTTTTTTA---AA----ATATTTTTTTTTTGTGTCTAAAT------TAAA Habronattus oregonensis TATTATTA---AGTTTATACTTATAAATCCTTTTTCTAAAAA----TCTTTAGATTATAATGTCCTTAAA---TTTGGTT-TGATGTAAC Ornithoctonus huwena TATTAATA---ATTTATTACTATTAAATCCTTGACTCTTGAA----TGTTTGGAAAGAAGAATG-TAAAT---AAAGAGT-ATAAGTAAC Nephila clavata TATTGTTT---AAATATTACTAATAAATCCTTTTTGTAAAAA----AAATTTTTTTTTT-TCTCCTTAAT---TTTTTTT-TAAAGTAAC Limulus polyphemus ATTTAA-T--AAAAAATTACTTTCAAATCCACCTTCAATTCTATCCTTTCAATAAAACATCCGTATTAA--TAAATTAAT----TGTAAT Locusta migratoria AATAATTT---AA--ATTACTATCAAATCCACCTTCATTAAA----ATATTACAAAATTAAATCCATAATAAAAAAAAAT-TATTGTAAC Drosophila melanogaster TCTTTATA---AT--TTTACTACTAAATCCACTTTCAA-AAA----TTTTTTCATAATTTTATTCATAT--AAATAAATT-TATTGTAAC

Figure 2-1. Continued.

190 200 210 220 230 240 250 260 270 ......

South Florida 1 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 2 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 3 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 4 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 5 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 6 TTATTTCAATCTTTAAAATAAGCTGGACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 7 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 8 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 9 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- “ “ 10 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACACCACTA---ACCTTAGAGAAAA--AAA--TAAATTTACAC--ATAAT- Flic en Flac 1 TCAATTTATCCATTAG-ATATTCTACACATTGACCTGAATTAAGATAAAATTATTTTTAGGAA---TAAGCTGTATCTTAAA--ACTTA- “ “ 2 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--A-AA-TAAACTTACAT--ATAGT- “ “ 3 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAA-TAAACTTACAT--ATAGT- “ “ 4 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAAATAAACTTACAT--ATAGT- “ “ 5 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AGAA-TAAACTTACAT--ATAGT- North Port Louis 1 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAA--TAAACTTACAT--ATAGT- “ “ 2 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AA---TAAACTTACAT--ATAGT- “ “ 3 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--A-AA-TAAACTTACAT--ATAGT- “ “ 4 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAA--TAAACTTACAT--ATAGT- “ “ 5 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--GAAA-TAAACTTACAT--ATAGT- “ “ 6 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAAATAAACTTACAT--ATAGT- “ “ 7 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAA-TAAACTTACAT--ATAGT- “ “ 8 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAAATAAACTTACAT--ATAGT- Trou d’Eau Douce 1 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAA--TAAACTTACAT--ATAGT- “ “ 2 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA----AA-TAAACTTACAT--ATAGT- “ “ 3 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAAATAAACTTACAT--ATAGT- “ “ 4 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAA--TAAACTTACAT--ATAGT- “ “ 5 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAA-TAAACTTACAT--ATAGT- “ “ 6 TCAATTTATCCATTAG-ATTTTCTACACATTGACCTGAATTAAGATAAAATTATTTTTAGGAA---TAAGCTGTATCTTAAA--ACTTA- “ “ 7 TCAATTTATCCATTAG-ATTTTCTACACATTGACCTGAATTAAGATAAAATTATTTTTAGGAA---TAAGCTGTATCTTAAA--ACTTA- “ “ 8 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGACAAAA--AAAA-TAAACTTACAT--ATAGT- “ “ 9 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAA--TAAACTTACAT--ATAGT- “ “ 10 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAA--TAAACTTACAT--ATAGT- “ “ 11 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--A-AA-TAAACTTACAT--ATAGT- “ “ 12 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAA--TAAACTTACAT--ATAGT- “ “ 13 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA----AA-TAAACTTACAT--ATAGT- “ “ 14 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAA-TAAACTTACAT--ATAGT- “ “ 15 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAAATAAACTTACAT--ATAGT- “ “ 16 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAA--TAAACTTACAT--ATAGT- “ “ 17 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAA-TAAACTTACAT--ATAGT- “ “ 18 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAA-TAAACTTACAT--ATAGT- “ “ 19 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AAAA-TAAACTTACAT--ATAGT- “ “ 20 TTATTTCAATCTTTAAAATAAGCTGAACCTTAACCTAAAACATCACTA---ACTCTAGAAAAAA--AGAA-TAAACTTACAT--ATAGT- Iphiseius degenerans TTATCTCAATCTTTTCCATAAGCTGCATCTTTACCTAAAATATTATTA---TGTTTAAGCTAAA--TAAAATATATCTTTAC--ATTTT- Amblyseius swirskii TTATTTCAAACTTTTTCATTAACCGCACCTTTCCCTAAAATTTAACTT--TCCAAAAAAAGTTA--AATACTATTTTTTATAAAATAAT- Neoseiulus californicus TTATTTCATCCTTTTTTATTATCCACACCTTTCCCTAAAATTTA------TCTAAAAAAAGCTA---AATTTATAATTAAACTAGTAATC Neoseiulus cucumeris TCATTAAAACCACTTT-ATGATTTACACATTGACCTGAATTAAAACACTAACGTAAAAAGCAA---TAACCTGTATGTTAAA--ACTTA- Neoseiulus fallacies TTATTTCATTCTTTTTTATAATCCACACCTTTCCCTAAAATTTA------TCTAAATAATTAGA--CAATTTGTAATTAAACTAATAATT Phytoseiulus fragariae TTATTTCATTCTTTTGTATAAACTACACCTTTACCTAAAAACCTACTTCATATAAAAGTATTGC--TAAAATATATCTAAAT--ATTTT- Phytoseiulus longipes TTATTTCATTCTTTTGTATAAACTACACCTTTACCTAAAATTTTACT----ATAAAAGTATTAT--TAAAATATATTTAAAT--ATTTT- Phytoseiulus persimilis TTATTTCATTCTTTTATATAAGCTACACCTTTACCTAAAAAATTACTA-AAATAATAGTATTAA--TAAAATATATTTAAAT--ATTTT- Metaseiulus occidentalis TTATTTCAGACTTGCGCATTAGCTGCACTTTGCCCTAAAAATTCTTTT----TAAAAACATTTA--AAAATTTTTTATAAA---ATTTT- Varroa destructor TCATAATAACCTTAAATATCAACTATATCTTGATTTAAAATATTTTTT--TTAATTAAAATTTC--TATTTTATATCTAAATAAAATAT- Rhipicephalus sanguineus TCACTTCATTCTTAAATTTTTACTGCACCTTGACTTAATATAACTTAA--TTTAATAAATTTTAACAATTGAAGTTATTAATT-GTTTTT Iphiseius hexagonus TCACTTCATTCATAATTTTATATTGCACCTTGACTTAATATAATTCTT--TATAAAAAAATCT--TAAATATAATTATTTAAT-ATAATT Tetranychus urticae CTTTGAT---TTTAATTATATCTTGACCTGTAATCTTTAA-AATTTTTTTTTAATTAAAATTAA--TATTTT------ATTTT- Habronattus oregonensis TCATTAGTTTCTTTAATATAGACTGCACCTTGACCTAACTTTTTA--TAATTTATTGAGAGAAA--TTTTTG------AAAATAT-TTC Ornithoctonus huwena TCGGC--TCCCTTTTTCATTGGTTTTATCTCGACCTGACGTGAAAAGTTTTTTTATTTTGAAAT--GGAATT------TTATCGATTTC Nephila clavata CCACTA-TAACTTTTATGTGGTCTACACCTTTACCTAACTTATTAGATGATCTTTTTAGAAAAA--AATATG------AAAATAAATTC Limulus polyphemus CCACTTCAACCTTTACCATAAGCTGCACCTTGACCTGACATAAAAAATAAATTTTAAACGATAGCTTTAACTCTATAAAGGC--AATCA- Locusta migratoria CCATCATACACTTAACTATAAGCTGCACCTTGACCTGAAATAAATTTTAATAAAAAAACAAGAA--AATTTTTTCTCCAAAAAGATTTTC Drosophila melanogaster CCATTAT-TACTTAAATATAAGCTACACCTTGATCTGATATAAATTTTTATTAAAATTATTGAA--TATTATTATTCTTATAAAATATTC

Figure 2-1. Continued.

280 290 300 310 320 330 340 350 360 ......

South Florida 1 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 2 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 3 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 4 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 5 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 6 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 7 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 8 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 9 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC “ “ 10 --TAAATAGCGGTAGACAAACTGT------AAATACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTTATAG-AATAAATTC Flic en Flac 1 --A---CAGCCGCACATAAA------AATACTA-AAGGTGAAGATAAAGGAGGGGTATCAGGTTATAAAATCAAGCTC “ “ 2 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 3 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 4 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 5 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC North Port Louis 1 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 2 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAGAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 3 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 4 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 5 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 6 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 7 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 8 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC Trou d’Eau Douce 1 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 2 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 3 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 4 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 5 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 6 --A---CAGCCGCACATAAA------AATACTA-AAGGTGAAGATAAAGGAGGGGTATCAGGTTATAAAATCAAGCTC “ “ 7 --A---CAGCCGCACATAAA------AATACTA-AAGGTGAAGATAAAGGAGGGGTATCAGGTTATAAAATCAAGCTC “ “ 8 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 9 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 10 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 11 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 12 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 13 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 14 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 15 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 16 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 17 --TAAATAGCGGTAGACAAACTGT------AGGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 18 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 19 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC “ “ 20 --TAAATAGCGGTAGACAAACTGT------AAGTACAATTTAAAGT-AAGATTTTGGTGTTTTATC-CTTAATAG-AATAAATTC Iphiseius degenerans --TCAATAGCGATATACAAACTAA------AATTACAAGAAAAAGT-AAGATTTTGGTGTTGCATC-CTTTATAG-GATAAATTC Amblyseius swirskii --AAAATAGAGGTATACGAGCTGAAAT------TTACATTAAAAAGT-AAGATATTGGGGTCATATC-CTTTATAG-AATAAGTTT Neoseiulus californicus AAAAGATAGAGGTATATGAAATGTAATGTATTAAATTATACAAAAAAAAGT-AAGATTTTGGGGTTGACTC-CTTTAAAG-AATAAATTT Neoseiulus cucumeris --A---CAGCCGTACATAAA------AACAAAA-GTGGTGAAATTAAAAGGGGGTTATCAAATTAAATTAACAAGCTC Neoseiulus fallacies AAAAAATAGAGGTATATGAAATGTTAT-----AACTAATACAAAAAAAAGT-AAGATACTGGTGTCAACTC-CTTTAAAG-AATAAGTTT Phytoseiulus fragariae --AAAATAGAGGTATGTAAATTGTTTA------AA-TACAAACAAAAGT-AAGATTTTGGTGTTAAATC-CTTTACAG-AATAAATTC Phytoseiulus longipes --AAAATAGAGGTATGTAAATTGTTGA------AAATACAAACAAAAGT-AAGATACTGGTGTCAAATC-CTTTATAG-AATAAATTC Phytoseiulus persimilis --AAAATAGAGGTATGTAAACTGTTTT------AA-TACAAATAAAAGT-AAGATTTTGGTGTTAAATC-CTTTATAG-AATAAATTC Metaseiulus occidentalis --TAAATAGAGGTATACAAACTGTAGA------AGTTTACTAACGTAAGT-AAGATTAAGGGGTTTTATC-CATTACAG-AATAAATTC Varroa destructor ---AAATAACGATATATAAATTGA------CTTTCAAATTTAAGT-AAGATATCGGCGTTTTATC-CCTTACTT-TACAAATTC Rhipicephalus sanguineus -----TAGTGGTATACAAATTGA------ATTTACAAATTTAAGT-AAGATTAAG-TGTTTTATC-CATTAAAG-AACAAATTC Iphiseius degenerans A-AATATAGTGGTATACAAATTGA------TTTAACCAAATTAAGT-AAGATCAAGGCGTTTTATC-CATTACAG-AGCAAATTC Tetranychus urticae -----ACGGAGATAAATAAATTAAA------AATCTTAAGTTTTTTTTAATGTGTATTTTCT-ATAAATA-ATCAAGACC Habronattus oregonensis TTTAGATGGCGATATACAAATTTTC------TTTTAAAGTGAAATTTATCGGGGGTTGTCG-ATTATAC-AACAAGTTC Ornithoctonus huwena TTTAGACGGCGATATAAAGGCTTTG------AGAAAAAGATAAATTTAACGGGGATTATCGGATTAAGA-TACGAGTTC Nephila clavata TTAAGATGGAGGTATATAAAATTTA------AATAAAAGTAAAAATTAACGTGGATTATCG-ATTATTT-AGCAGGTTC Limulus polyphemus --AAGACGGCGGTATACAAACTGT------AATAACAAAATAAAGTAAAATTAAACGAGGACCATC-GATTACAG-AGCAGATTC Locusta migratoria TGATAACGGAGATATACAAACAAAT------AAATTAAGTAAAGTAAATCGTGTACTATCA-ATCATGA-GATAGGTTC Drosophila melanogaster TGATAACGACGGTATATAAACTGATT------ACAAATTTAAGTAAGGTCCATCGTGGATTATCG-ATTAAAA-AACAGGTTC

Figure 2-1. Continued.

370 380 390 400 410 420 430 440 450 ......

South Florida 1 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA “ “ 2 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA “ “ 3 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA “ “ 4 CTCTGAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA “ “ 5 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA “ “ 6 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA “ “ 7 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA “ “ 8 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA “ “ 9 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACGCCTA--CTACCTCACATT------CGTACAC-CTAATA “ “ 10 CTCTAAAAAATTTAAAAAGCCGCCAATAAATT--TAAGTTTCATGCACAACACCTA--CTACCTAACATT------CGTACAC-CTAATA Flic en Flac 1 CTCTGA--AGAAAAACAGGCCGCCAGAAAGGT--TAAGTTTTTTAATTATTAATTACTACCTTAAAGTA------TCCACATCATAATA “ “ 2 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 3 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 4 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 5 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA North Port Louis 1 CTCTAAAAAATTTATATAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 2 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 3 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 4 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACCTA--CTACCTAACATT------CATACAC-CTAATA “ “ 5 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 6 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 7 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 8 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA Trou d’Eau Douce 1 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 2 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 3 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 4 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCAAACATT------CATACAC-CTAATA “ “ 5 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 6 CTCTGA--AGAAAAACAGGCCGCCAGAAAGGT--TAAGTTTTTTAATTATTAATTACTACCTTAAAGTA------TCCACATCATAATA “ “ 7 CTCTGA--AGAAAAACAGGCCGCCAGAAAGGT--TAAGTTTTTTAATTATTAATTACTACCTTAAAGTA------TCCACATCATAGTA “ “ 8 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 9 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAGTA “ “ 10 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 11 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 12 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 13 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 14 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 15 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 16 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 17 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 18 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTCA--CTACCTAACATT------CATACAC-CTAATA “ “ 19 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA “ “ 20 CTCTAAAAAATTTATAAAGCCGCCAATAAATT--TAAGTTTCATGTATAACACTTA--CTACCTAACATT------CATACAC-CTAATA Iphiseius degenerans CTCTAAAAAATTTAAAAAGCCGCCAATTAATT--TTAGTTTCATGTTATTCAACTA--CTACTAAATGTT------ATTTAATACTAATA Amblyseius swirskii CTCTAAAAAATTCATATAGCCGCCAATTTATT--TTAGTTTCATGAAAATCACTTA--CTACTAAATATA------AAAAATTTCTAATA Neoseiulus californicus CTCTAAGATATTTAAAAAGCCGCCAATTAATT--TTAGTTTCATGTTTTTCACTTA--CTACTAAATTTT------CTAAATTTATAATA Neoseiulus cucumeris CTCTGCT-AGAGTAGTGAACCGCCAGAAGAAT--TAAGTTTAGAAAAAATAATTTACTACTTTAAAGCA------ATCTTTAAATAGTA Neoseiulus fallacies CTCTAATATATTTAAAAAGCCGCCAATTAATT--TTAGTTTCATGCATTACACTTA--CTACTAAATATA------CTAATATTATAATA Phytoseiulus fragariae CTCTAAAATATTTAAAAAGCCGCCAATTAATT--TTAGTTTCATGAAAACCACTTA--CTACTAAATATT------AAATATGACTAATA Phytoseiulus longipes CTCTAAAATATTTAAAAAGCCGCCAATTAATT--TTAGTTTCATGAATATCACTTA--CTACTAAATCTT------AAAATTATCTAATA Phytoseiulus persimilis CTCTAAAATATTTAAAAAGCCGCCAATTAATT--TTAGTTTCATGTTCAACACTTTACCTACTAAATTTT------AAATGTAACTAATA Metaseiulus occidentalis CTCTAAAATTATTTTA-AGCCGCCAATTTTTT--TTAGTTTCGTGATTTTCATTTA--CTACTAATTTTT------ATATTTT---AATA Varroa destructor CTCTAATAAGAATAAAATGCCGCCATTTGACT--TTAATTTCAAAAAATTC---TA--CTCCTAATCTTT------GTTTAAGTATAATA Rhipicephalus sanguineus CTCTGAAAAGCTTAAAATACCGCCATAATTTT--TTGCTTTCGTAATTTTTATTTA--CTAACAATATTTA------CCTCTTAAATAATA Iphiseius hexagonus CTCTAAAAAGCTTAAAATACCGCCAAAATCTT--ATGATTTCATAATCATTATATA--CTAACAACATATA------GCT-TAAAATAATA Tetranychus urticae CTTTAACTATAATATTTTACCGCCAAAAATTT--CTAGTTTAA----CTT---TATAAGTTTATTACTAAAAAA---TTT---TTT----TACTT Habronattus oregonensis CTCTAA-TGAAATGAAA-GCCGCCATTTTATAATTAGGTTTTAA-----TAATTATTACTTCC-TAAGATGAT------TGTAGTATACTA Ornithoctonus huwena CTCTAA-TAAGATGTAAGGCCGCCAAAGGGCA--TGGGTTTTCA-----TAATTTGTAATTTC--CTTATAAT------TCTAGAATAAAA Nephila clavata CTCTAA-TATGAAAAAATGCCGCCAAACTACA--TAAGTTTTGA-----TAAAAAGTTCTACTACTTTTTTAT------TTAGATATAAAA Limulus polyphemus CTCTGAACAGCTTAAAGCACCGCCAAATTTTT--TAGGTTTCATGATCAACAATTACTACCCTAATTTCCTTTAC------ACCTTAAAATAACA Locusta migratoria CTCTGAATGGAATGAAATACCGCCAAATTCTT--TGGGTTTAAAGACCTTAACTAATAATACCCAGGTAAAACAAAATTTACATTT-AAATAATA Drosophila melanogaster CTCTAGATAGACTAAAATACCGCCAAATTTTT--TAAGTTTCAAGAACATAACTATTACTACTTTAGCAATTTA---TTTACATTTTAAATAATA

Figure 2-1. Continued.

10 20 30 40 50 60 70 80 90 ......

South Florida 2 TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 3 TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 5 TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 8 TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI Flic en Flac 2 TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 3 TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI Trou D’Eau Douce 2 TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 4 TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI South Florida 1 TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 4 TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 6 TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 7 TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI North of Port Louis 1 TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI Trou d’Eau Douce 1 TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI “ “ 3 TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI Amblyseius swirskii TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI Neoseiulus californicus TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSESRYEEIKKEVSSYIKKIGYNPATVPFVPI Neoseiulus cucumeris TGTSQADCAILICPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEPRFEEIKKEVSSYIKKIGYNPATVPFVPI Metaseiulus occidentalis TGTSQADCAILVCPAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEARFEEIKKEVSSYIKKIGYNPATVPFVPI Dermanyssus hirundinis TGTSQADCAILVCPAGTGEFEAGISQNGQTREHALLAYTLGVKQMIVGVNKMDTSEPPYSEDRFEEIKKEVSLYIKKIGYNPNSVPFVPI Euzercon latum TGTSQADCAVLICAAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTTEPPFSQPRFEEIQKEVTSYIKKIGYNPATVPFVPI Amblyomma sp. TGTSQADCAVLIVAAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTTEPPFSQSRFEEIQKEVSAYIKKIGYNPATVPFVPI Neacarus texanus TGTSQADCAVLIVAAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTTEPPFSQARFEEIQKEVSAYIKKIGYNPATVPFVPI Tetranychus urticae TGTSQADCAVLICAAGVGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDSAEPKYSQARYEEITKEVSSYIKKIGYNPATVPFVPI Raoiella indica TGTSQADCAVLIVAAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTTEPKFSQARFEEISKEVSNYIKKIGYNPATVPFVPI Aphonopelma chalcodes TGTSQADCAVLVVAAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTTEPPFSESRFEEIKKEVSAYIKKIGYNPATVPFVPI Dysdera crocata TGTSQADCAVLIVAAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTTEPPFSESRFEEIKKEVSAYIKKIGYNPATVPFVPI Limulus polyphemus TGTSQADCAVLIVAAGTGEFEAGISKNGQTREHALLAYTLGVKQMIVGVNKMDTTEPPYSEKRFEEIQKEVSAYIKKIGYNPATVAFVPI Locusta migratoria TGTSQADCAVLIVAAGTGEFEAGISKNGQTREHALLAFTLGVKQLIVGVNKMDSTEPPYSEARFEEIKKEVSNYIKKIGYNPVAVAFVPI Drosophila melanogaster TGTSQADCAVLIVAAGTGEFEAGISKNGQTREHALLAFTLGVKQLIVGVNKMDSTEPPYSEARYEEIKKEVSSYIKKIGYNPASVAFVPI

Figure 2-2. CLUSTAL X amino acid alignment translated from partial nuclear EF-Iα gene sequences from the S. Florida and Mauritius ‘A. largoensis’ populations with additional phytoseiid GenBank accessions for the EF-Iα Bayesian analysis. Number following a colony source location indicates the clone number. Hyphen denotes deletion.

100 110 120 130 140 150 160 170 180 ......

South Florida 2 SGWCGDNMLEPSPNMTWYKGWTIERGGTKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV “ “ 3 SGWCGDNMLEPSPNMTWYKGWTIERGGTKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV “ “ 5 SGWCGDNMLEPSPNMTWYKGWTIERGGTKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV “ “ 8 SGWCGDNMLEPSPNMTWYKGWTIERGGTKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV Flic en Flac 2 SGWCGDNMLEPSPNMTWYKGWTIERGGTKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV “ “ 3 SGWCGDNMLEPSPNMTWYKGWTIERGGTKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV Trou d’Eau Douce 2 SGWCGDNMLEPSPNMTWYKGWTIERGGTKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV “ “ 4 SGWCGDNMLEPSPNMTWYKGWTIERGGTKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV South Florida 1 SGWAGDNMLEPSPNMGWYKGWQIERKGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV “ “ 4 SGWAGDNMLEPSPNMGWYKGWQIERKGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV “ “ 6 SGWAGDNMLEPSPNMGWYKGWQIERKGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV “ “ 7 SGWAGDNMLEPSPNMGWYKGWQIERKGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV North of Port Louis 1 SGWAGDNMLEPSPNMGWYKGWQIERKGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV Trou d’Eau Douce 1 SGWAGDNMLEPSPNMGWYKGWQIERKGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV “ “ 3 SGWAGDNMLEPSPNMGWYKGWQIERKGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV Amblyseius swirskii SGWAGDNMLEPSPNMPWYKGWQIERKGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV Neoseiulus californicus SGWCGDNMLEPSPNMTWYKGWTIERSGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV Neoseiulus cucumeris SGWCGDNMLEPSPNMTWYKGWTIERQGQKFEGKTLLQALDVMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPAHITTEVKSV Metaseiulus occidentalis SGWAGDNMLEPSPNMTWYKGWQIERKNQKFEGKTLLQALDVMEPPTSPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV Dermanyssus hirundinis SGWAGDNMLEVSANMPWYKGWQIERKGSKFEGKTLLQALDVMEPPARPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPSNLTTEVKSV Euzercon latum SGWNGDNMLEPSTNMPWYKGWSIERKGAKFEGKTLLQALDVMEPPSRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPANLTTEVKSV Amblyomma sp. SGWNGDNMLEPSQNMPWYKGWSIERKSGKSEGKTLLQALDAMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPANLTTEVKSV Neacarus texanus SGWNGDNMLDASSNMPWFKGWSIERKSGKSEGKTLLQALDAMEPPTRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPCNLTTEVKSV Tetranychus urticae SGWHGDNMIEPSPNMPWYKGWSIEKKGAKLEGKTLLQALDAMDPPSRPVDKALRLPLQDVYKIGGIGTVPVGRVETGTIKPGMIVTFAPVNLTTEVKSV Raoiella indica SGWNGDNMLEPSDNMPWFKGWQIEKKGSKLEGKTLLQALDAMDPPSRPVDKPLRLPLQDVYKIGGIGTVPVGRVETGVIKPGMVVTFAPVGITTEVKSV Aphonopelma chalcodes SGWNGDNMLEPSTNMPWYKGWNIERKSSKSDGKTLLQALDAMEPPSRPLDRPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGMVVTFAPVNLTTEVKSV Dysdera crocata SGWNGDNMLEPSTNMPWYKGWNIERKSGKNDGKTLLQALDAMEPPSRPLDKPLRLPLQDVYKIGGIGTVPVGRVETGVMKPGMVVTFAPVNITTEVKSV Limulus polyphemus SGWNGDNMLEASPNTPWFKGFKIERKGQTTEGKTLLQALDCAEPPSRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGVLKPGTVVTFAPAMITTEVKSV Locusta migratoria SGWHGDNMLEHSDKMSWFKGWSIERNEGKAEGKTLIEALDAILPPNRPTEKPLRLPLQDVYKIGGIGTVPVGRVETGILKPGMVVTFAPANLTTEVKSV Drosophila melanogaster SGWHGDNMLEPSEKMPWFKGWSVERKEGKAEGKCLIDALDAILPPQRPTDKPLRLPLQDVYKIGGIGTVPVGRVETGLLKPGMVVNFAPVNLVTEVKSV

Figure 2-2. Continued.

10 20 30 40 50 60 70 80 90 ......

South Florida 1 CACCGGAACTTCGCAGGCCGATTGTGCCATCCTCGTCTGCCCCGCCGGTACCGGTGAATTCGAAGCCGGTATCTCGAAGAACGGCCAGAC “ “ 2 CACCGGAACTTCTCAAGCCGACTGCGCTATTCTCATCTGCCCTGCGGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAAAACGGCCAAAC “ “ 3 CACCGGAACTTCTCAAGCCGACTGCGCTATTCTCATCTGCCCTGCGGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAAAACGGCCAAAC “ “ 4 CACCGGAACTTCGCAGGCCGATTGTGCCATCCTCGTCTGCCCCGCCGGTACCGGTGAATTCGAAGCCGGTATCTCGAAGAACGGCCAGAC “ “ 5 CACCGGAACTTCTCAAGCCGACTGCGCTATTCTCATCTGCCCTGCGGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAAAACGGCCAAAC “ “ 6 CACCGGAACTTCGCAGGCCGATTGTGCCATCCTCGTCTGCCCCGCCGGTACCGGTGAATTCGAAGCCGGTATCTCGAAGAACGGCCAGAC “ “ 7 CACCGGAACTTCGCAGGCCGATTGTGCCATCCTCGTCTGCCCCGCCGGTACCGGTGAATTCGAAGCCGGTATCTCGAAGAACGGCCAGAC “ “ 8 CACCGGAACTTCTCAAGCCGACTGCGCTATTCTCATCTGCCCTGCGGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAAAACGGCCAAAC Flic en Flac 2 CACCGGAACTTCTCAAGCCGACTGCGCTATTCTCATCTGCCCTGCGGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAAAACGGCCAAAC “ “ 3 CACCGGAACTTCTCAAGCCGACTGCGCTATTCTCATCTGCCCTGCGGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAAAACGGCCAAAC North of Port Louis 1 CACCGGAACTTCGCAGGCCGATTGTGCCATCCTCGTCTGCCCCGCCGGTACCGGTGAATTCGAAGCCGGTATCTCGAAGAACGGCCAGAC Trou d’Eau Douce 1 CACCGGAACTTCGCAGGCCGATTGTGCCATCCTCGTCTGCCCCGCCGGTACCGGTGAATTCGAAGCCGGTATCTCGAAGAACGGCCAGAC “ “ 2 CACCGGAACTTCTCAAGCCGACTGCGCTATTCTCATCTGCCCTGCGGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAAAACGGCCAAAC “ “ 3 CACCGGAACTTCGCAGGCCGATTGTGCCATCCTCGTCTGCCCCGCCGGTACCGGTGAATTCGAAGCCGGTATCTCGAAGAACGGCCAGAC “ “ 4 CACCGGAACTTCTCAAGCCGACTGCGCTATTCTCATCTGCCCTGCGGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAAAACGGCCAAAC Amblyseius swirskii CACCGGTACTTCCCAGGCTGATTGTGCCATCCTTGTCTGCCCCGCCGGTACCGGAGAATTCGAAGCCGGTATCTCGAAGAACGGCCAGAC Neoseiulus californicus CACAGGAACTTCCCAAGCCGACTGCGCGATCCTCATCTGCCCCGCCGGAACCGGCGAGTTCGAGGCCGGAATCTCCAAGAACGGCCAAAC Neoseiulus cucumeris CACGGGAACTTCTCAGGCCGACTGCGCTATTCTCATCTGCCCTGCCGGAACCGGCGAGTTCGAAGCCGGCATTTCCAAGAATGGACAAAC Metaseiulus occidentalis CACCGGAACTTCCCAGGCCGATTGTGCCATCCTTGTCTGTCCCGCCGGTACCGGAGAATTCGAGGCCGGTATCTCCAAGAACGGTCAGAC Dermanyssus hirundinis CACGGGAACGTCGCAGGCCGACTGCGCCATCCTCGTCTGTCCGGCCGGTACCGGCGAATTCGAAGCTGGTATCTCGCAGAACGGCCAGAC Euzercon latum CACGGGAACATCTCAGGCTGATTGCGCTGTTCTCATCTGCGCCGCCGGTACCGGTGAATTCGAAGCCGGTATTTCTAAGAACGGCCAGAC Amblyomma sp. CACTGGAACGTCGCAGGCTGACTGTGCTGTGCTGATTGTGGCTGCCGGTACCGGCGAGTTCGAGGCTGGTATCTCCAAGAACGGCCAGAC Neacarus texanus CACAGGAACATCACAGGCTGACTGTGCTGTCTTAATTGTTGCTGCTGGTACTGGTGAATTTGAAGCTGGTATCTCAAAGAACGGACAGAC Raoiella indica TACTGGAACTTCACAGGCCGACTGTGCAGTTCTGATCGTTGCTGCCGGTACTGGTGAATTTGAAGCTGGTATATCTAAGAACGGCCAGAC Tetranychus urticae TACTGGTACTTCTCAAGCTGATTGTGCTGTATTGATTTGTGCTGCTGGTGTTGGTGAATTCGAAGCTGGTATCTCTAAGAACGGTCAAAC Aphonopelma chalcodes TACGGGAACTTCACAAGCTGACTGTGCAGTCTTAGTAGTGGCAGCAGGAACAGGTGAATTTGAAGCAGGTATCTCAAAGAATGGACAAAC Dysdera crocata TACAGGAACCTCGCAGGCCGATTGTGCTGTCCTGATTGTGGCTGCAGGTACTGGTGAGTTTGAGGCTGGTATCTCCAAGAACGGACAGAC Limulus polyphemus TACTGGAACATCCCAGGCTGATTGTGCTGTTCTGATTGTGGCTGCTGGCACTGGTGAATTTGAAGCTGGAATTTCCAAAAATGGCCAGAC Locusta migratoria TACAGGAACGTCACAGGCTGACTGTGCAGTGTTGATCGTAGCAGCTGGTACAGGTGAATTTGAAGCCGGTATTTCTAAGAACGGACAAAC Drosophila melanogaster TACCGGTACCTCTCAGGCCGATTGTGCGGTGCTGATCGTCGCCGCCGGAACTGGAGAGTTCGAGGCCGGGATCTCGAAGAACGGCCAGAC

Figure 2-3. CLUSTAL X DNA alignment for partial nuclear EF-Iα gene sequences from the S. Florida and Mauritius ‘A. largoensis’ populations with additional phytoseiid GenBank accessions for the EF-Iα Bayesian analysis. Number following a colony source location indicates the clone number. Hyphen denotes deletion.

100

100 110 120 130 140 150 160 170 180 ......

South Florida 1 TCGTGAACACGCTCTGCTCGCCTACACCCTCGGTGTGAAGCAGATGATCGTCGGTGTCAACAAGATGGACACTTCGGAGCCTCCCTACTC “ “ 2 GCGTGAGCACGCTCTTCTCGCTTACACTCTCGGTGTCAAGCAGATGATCGTCGGTGTCAACAAGATGGACACCTCCGAGCCTCCGTACTC “ “ 3 GCGTGAGCACGCTCTTCTCGCTTACACTCTCGGTGTCAAGCAGATGATCGTCGGTGTCAACAAGATGGACACCTCCGAGCCTCCGTACTC “ “ 4 TCGTGAACACGCTCTGCTCGCCTACACCCTCGGTGTGAAGCAGATGATCGTCGGTGTCAACAAGATGGACACTTCGGAGCCTCCCTACTC “ “ 5 GCGTGAGCACGCTCTTCTCGCTTACACTCTCGGTGTCAAGCAGATGATCGTCGGTGTCAACAAGATGGACACCTCCGAGCCTCCGTACTC “ “ 6 TCGTGAACACGCTCTGCTCGCCTACACCCTCGGTGTGAAGCAGATGATCGTCGGTGTCAACAAGATGGACACTTCGGAGCCTCCCTACTC “ “ 7 TCGTGAACACGCTCTGCTCGCCTACACCCTCGGTGTGAAGCAGATGATCGTCGGTGTCAACAAGATGGACACTTCGGAGCCTCCCTACTC “ “ 8 GCGTGAGCACGCTCTTCTCGCTTACACTCTCGGTGTCAAGCAGATGATCGTCGGTGTCAACAAGATGGACACCTCCGAGCCTCCGTACTC Flic en Flac 2 GCGTGAGCACGCTCTCCTCGCTTACACTCTCGGTGTCAAGCAGATGATCGTCGGTGTCAACAAGATGGACACCTCCGAGCCTCCGTACTC “ “ 3 GCGTGAGCACGCTCTTCTCGCTTACACTCTCGGTGTCAAGCAGATGATCGTCGGTGTCAACAAGATGGACACCTCCGAGCCTCCGTACTC North of Port Louis 1 TCGTGAACACGCTCTGCTCGCCTACACCCTCGGTGTGAAGCAGATGATCGTCGGTGTCAACAAGATGGACACTTCGGAGCCTCCGTACTC Trou d’Eau Douce 1 TCGTGAACACGCTCTGCTCGCCTACACCCTCGGTGTGAAGCAGATGATCGTCGGTGTCAACAAGATGGACACTTCGGAGCCTCCCTACTC “ “ 2 GCGTGAGCACGCTCTTCTCGCTTACACTCTCGGTGTCAAGCAGATGATCGTCGGTGTCAACAAGATGGACACCTCCGAGCCTCCGTACTC “ “ 3 TCGTGAACACGCTCTGCTCGCCTACACCCTCGGTGTGAAGCAGATGATCGTCGGTGTCAACAAGATGGACACTTCGGAGCCTCCCTACTC “ “ 4 GCGTGAGCACGCTCTTCTCGCTTACACTCTCGGTGTCAAGCAGATGATCGTCGGTGTCAACAAGATGGACACCTCCGAGCCTCCGTACTC Amblyseius swirskii TCGTGAACACGCTCTTCTCGCCTACACCCTTGGTGTGAAGCAGATGATCGTTGGTGTCAACAAGATGGACACTTCTGAGCCTCCTTACTC Neoseiulus californicus GCGTGAACACGCCCTGCTCGCTTACACTCTCGGTGTGAAGCAAATGATTGTCGGTGTCAACAAGATGGACACTTCCGAGCCTCCGTACTC Neoseiulus cucumeris GCGTGAACACGCTCTGCTCGCGTACACTCTCGGAGTGAAGCAAATGATTGTCGGTGTCAACAAGATGGACACTTCCGAGCCCCCGTACTC Metaseiulus occidentalis TCGTGAGCACGCTCTTCTCGCCTACACCCTTGGTGTGAAGCAGATGATCGTCGGTGTGAACAAGATGGACACCTCTGAGCCGCCGTACTC Dermanyssus hirundinis TCGTGAGCACGCCCTGCTCGCGTACACGCTCGGCGTGAAGCAAATGATTGTCGGCGTCAACAAGATGGACACCTCGGAGCCGCCCTACTC Euzercon latum TAGAGAACACGCTCTTCTTGCCTACACTCTCGGTGTGAAGCAAATGATCGTTGGCGTCAACAAGATGGACACCACCGAGCCTCCTTTCAG Amblyomma sp. CCGAGAGCACGCCCTGCTGGCTTACACCCTTGGCGTGAAGCAGATGATTGTCGGCGTGAACAAGATGGATACCACCGAGCCTCCCTTCTC Neacarus texanus CAGAGAACATGCCCTTCTGGCTTACACTTTGGGTGTGAAGCAGATGATTGTGGGTGTTAACAAGATGGACACTACTGAGCCTCCTTTCAG Raoiella indica TCGAGAACATGCTTTGTTGGCATATACCTTGGGCGTAAAGCAAATGATCGTTGGTGTCAACAAGATGGACACCACTGAGCCAAAATTTAG Tetranychus urticae TCGAGAACATGCTTTGTTGGCATACACCTTGGGTGTAAAACAAATGATTGTAGGTGTTAACAAAATGGATTCAGCTGAGCCAAAATATTC Aphonopelma chalcodes CAGAGAACATGCTTTACTTGCATATACCTTAGGAGTAAAACAAATGATTGTAGGTGTGAACAAGATGGATACCACTGAACCACCCTTCAG Dysdera crocata CAGAGAACACGCTCTGCTTGCCTACACCTTGGGTGTCAAGCAGATGATTGTTGGTGTCAACAAGATGGACACCACTGAACCACCATTCAG Limulus polyphemus CCGTGAACACGCCTTGTTGGCCTACACCCTGGGTGTGAAGCAGATGATTGTGGGAGTGAACAAGATGGACACAACTGAACCTCCTTATAG Locusta migratoria CCGTGAGCATGCCTTGTTGGCTTTCACTTTGGGTGTCAAGCAACTGATTGTGGGTGTGAACAAAATGGATTCGACTGAGCCACCATACAG Drosophila melanogaster CCGCGAGCACGCCCTTCTGGCATTCACGCTGGGCGTGAAGCAGCTTATTGTGGGCGTCAACAAGATGGACTCCACTGAGCCGCCGTACAG

Figure 2-3. Continued.

101

190 200 210 220 230 240 250 260 270 ......

South Florida 1 CGAGCCTCGTTTCGAGGAAATCAAGAAGGAAGTGTCTTCCTACATCAAGAAGATCGGATACAACCCCGCCACCGTTCCGTTCGTCCCGAT “ “ 2 GGAGCCTCGTTTCGAGGAAATCAAGAAGGAGGTGTCCTCCTACATCAAGAAGATCGGTTACAACCCCGCGACTGTGCCATTCGTTCCCAT “ “ 3 GGAGCCTCGTTTCGAGGAAATCAAGAAGGAGGTGTCCTCCTACATCAAGAAGATCGGTTACAACCCCGCGACTGTGCCATTCGTTCCCAT “ “ 4 CGAGCCTCGTTTCGAGGAAATCAAGAAGGAAGTGTCTTCCTACATCAAGAAGATCGGATACAACCCCGCCACCGTTCCGTTCGTCCCGAT “ “ 5 GGAGCCTCGTTTCGAGGAAATCAAGAAGGAGGTGTCCTCCTACATCAAGAAGATCGGTTACAACCCCGCGACTGTGCCATTCGTTCCCAT “ “ 6 CGAGCCTCGTTTCGAGGAAATCAAGAAGGAAGTGTCTTCCTACATCAAGAAGATCGGATACAACCCCGCCACCGTTCCGTTCGTCCCGAT “ “ 7 CGAGCCTCGTTTCGAGGAAATCAAGAAGGAAGTGTCTTCCTACATCAAGAAGATCGGATACAACCCCGCCACCGTTCCGTTCGTCCCGAT South Florida 8 GGAGCCTCGTTTCGAGGAAATCAAGAAGGAGGTGTCCTCCTACATCAAGAAGATCGGTTACAACCCCGCGACTGTGCCATTCGTTCCCAT Flic en Flac 2 GGAGCCTCGTTTCGAGGAAATCAAGAAGGAGGTGTCCTCCTACATCAAGAAGATCGGTTACAACCCCGCGACTGTGCCATTCGTTCCCAT “ “ 3 GGAGCCTCGTTTCGAGGAAATCAAGAAGGAGGTGTCCTCCTACATCAAGAAGATCGGTTACAACCCCGCGACTGTGCCATTCGTTCCCAT North of Port Louis 1 CGAGCCTCGTTTCGAGGAAATCAAGAAGGAAGTGTCTTCCTACATCAAGAAGATCGGATACAACCCCGCCACCGTTCCGTTCGTCCCGAT Trou d’Eau Douce 1 CGAGCCTCGTTTCGAGGAAATCAAGAAGGAAGTGTCTTCCTACATCAAGAAGATCGGTTACAACCCCGCCACCGTTCCGTTCGTCCCGAT “ “ 2 GGAGCCTCGTTTCGAGGAAATCAAGAAGGAGGTGTCCTCCTACATCAAGAAGATCGGTTACAACCCCGCGACTGTGCCATTCGTTCCCAT “ “ 3 CGAGCCTCGTTTCGAGGAAATCAAGAAGGAAGTGTCTTCCTACATCAAGAAGATCGGTTACAACCCCGCCACCGTTCCGTTCGTCCCGAT “ “ 4 GGAGCCTCGTTTCGAGGAAATCAAGAAGGAGGTGTCCTCCTACATCAAGAAGATCGGTTACAACCCCGCGACTGTGCCATTCGTTCCCAT Amblyseius swirskii CGAGCCTCGATTCGAGGAAATCAAGAAGGAAGTGTCTTCCTACATCAAGAAGATCGGATACAACCCCGCCACTGTGCCTTTCGTTCCGAT Neoseiulus californicus GGAGTCCCGATACGAGGAAATCAAGAAGGAGGTGTCTTCTTACATCAAGAAGATCGGCTACAATCCCGCAACCGTGCCATTCGTACCCAT Neoseiulus cucumeris AGAGCCTCGCTTCGAGGAAATCAAGAAGGAAGTGTCCTCTTACATCAAGAAGATCGGTTACAACCCCGCGACCGTGCCATTCGTGCCCAT Metaseiulus occidentalis CGAGGCTCGATTCGAGGAAATCAAGAAGGAGGTCTCGTCGTACATCAAGAAGATCGGATACAACCCCGCCACGGTTCCCTTCGTCCCCAT Dermanyssus hirundinis TGAGGACCGGTTCGAGGAGATCAAGAAAGAGGTGTCGCTGTACATCAAGAAGATCGGCTACAACCCGAACTCTGTGCCGTTTGTGCCCAT Euzercon latum CCAACCTCGCTTTGAAGAAATCCAGAAGGAAGTTACCTCCTACATCAAAAAGATTGGTTACAACCCCGCAACCGTACCCTTTGTGCCAAT Amblyomma sp. TCAGAGCCGTTTCGAGGAAATCCAGAAGGAAGTGTCCGCCTACATCAAGAAGATTGGCTACAACCCTGCTACTGTTCCGTTTGTGCCCAT Neacarus texanus CCAGGCCAGGTTTGAGGAAATCCAGAAGGAAGTGTCTGCCTACATCAAGAAGATTGGATACAACCCTGCCACTGTACCCTTCGTTCCCAT Raoiella indica CCAAGCTAGGTTTGAGGAGATATCTAAAGAAGTAAGCAACTATATTAAAAAAATTGGGTACAACCCTGCCACAGTACCATTTGTGCCCAT Tetranychus urticae TCAAGCTCGTTATGAAGAAATTACCAAGGAAGTTAGCAGTTACATTAAGAAGATTGGTTACAATCCAGCAACTGTACCATTTGTACCAAT Aphonopelma chalcodes TGAGTCAAGATTTGAAGAAATCAAGAAAGAAGTATCTGCTTATATCAAAAAAATTGGCTACAATCCAGCAACTGTACCATTTGTTCCAAT Dysdera crocata TGAGTCTCGATTTGAGGAAATCAAGAAGGAAGTATCCGCTTACATCAAGAAGATTGGTTACAACCCTGCCACCGTACCTTTTGTTCCCAT Limulus polyphemus TGAGAAACGTTTTGAAGAAATCCAGAAGGAAGTTAGTGCCTACATTAAGAAGATAGGCTACAATCCTGCCACTGTTGCCTTTGTGCCAAT Locusta migratoria TGAGGCTCGTTTTGAGGAAATTAAGAAGGAAGTCAGTAACTACATTAAGAAGATTGGTTACAATCCAGTAGCTGTTGCCTTTGTTCCTAT Drosophila melanogaster CGAGGCCCGCTACGAGGAGATCAAGAAGGAGGTGTCCTCGTACATCAAGAAGATCGGCTACAATCCGGCCTCGGTGGCCTTCGTGCCCAT

Figure 2-3. Continued.

102

280 290 300 310 320 330 340 350 360 ......

South Florida 1 TTCCGGATGGGCCGGAGACAACATGCTCGAGCCCTCTCCCAACATGGGATGGTACAAGGGATGGCAGATCGAGCGCAAGGGCCAGAAGTT “ “ 2 CTCGGGATGGTGTGGAGACAACATGCTGGAGCCCTCGCCAAACATGACCTGGTACAAAGGATGGACCATCGAGCGCGGAGGCACGAAATT “ “ 3 CTCGGGATGGTGTGGAGACAACATGCTGGAGCCCTCGCCAAACATGACCTGGTACAAAGGATGGACCATCGAGCGCGGAGGCACGAAATT “ “ 4 TTCCGGATGGGCCGGAGACAACATGCTCGAGCCCTCTCCCAACATGGGATGGTACAAGGGATGGCAGATCGAGCGCAAGGGCCAGAAGTT “ “ 5 CTCGGGATGGTGTGGAGACAACATGCTGGAGCCCTCGCCAAACATGACCTGGTACAAAGGATGGACCATCGAGCGCGGAGGCACGAAATT “ “ 6 TTCCGGATGGGCCGGAGACAACATGCTCGAGCCCTCTCCCAACATGGGATGGTACAAGGGATGGCAGATCGAGCGCAAGGGCCAGAAGTT “ “ 7 TTCCGGATGGGCCGGAGACAACATGCTCGAGCCCTCTCCCAACATGGGATGGTACAAGGGATGGCAGATCGAGCGCAAGGGCCAGAAGTT “ “ 8 CTCGGGATGGTGTGGAGACAACATGCTGGAGCCCTCGCCAAACATGACCTGGTACAAAGGATGGACCATCGAGCGCGGAGGCACGAAATT Flic en Flac 2 CTCGGGATGGTGTGGAGACAACATGCTGGAGCCCTCGCCAAACATGACCTGGTACAAAGGATGGACCATCGAGCGCGGAGGCACGAAATT “ “ 3 CTCGGGGTGGTGTGGAGACAACATGCTGGAGCCCTCGCCAAACATGACCTGGTACAAAGGATGGACCATCGAGCGCGGAGGCACGAAATT North of Port Louis 1 TTCCGGATGGGCCGGAGACAACATGCTCGAGCCCTCTCCCAACATGGGATGGTACAAGGGATGGCAGATCGAGCGCAAGGGCCAGAAGTT Trou d’Eau Douce 1 TTCCGGATGGGCCGGAGACAACATGCTCGAGCCCTCTCCCAACATGGGATGGTACAAGGGATGGCAGATCGAGCGCAAGGGCCAGAAGTT “ “ 2 CTCGGGATGGTGTGGAGACAACATGCTGGAGCCCTCGCCAAACATGACCTGGTACAAAGGATGGACCATCGAGCGCGGAGGCACGAAATT “ “ 3 TTCCGGATGGGCCGGAGACAACATGCTCGAGCCCTCTCCCAACATGGGATGGTACAAGGGATGGCAGATCGAGCGCAAGGGCCAGAAGTT “ “ 4 CTCGGGATGGTGTGGAGACAACATGCTGGAGCCCTCGCCAAACATGACCTGGTACAAAGGATGGACCATCGAGCGCGGAGGCACGAAATT Amblyseius swirskii TTCCGGATGGGCCGGAGACAACATGCTCGAGCCCTCTCCCAACATGCCCTGGTACAAGGGATGGCAGATTGAGCGCAAGGGTCAGAAGTT Neoseiulus californicus CTCAGGATGGTGTGGAGACAACATGCTGGAACCTTCGCCAAACATGACCTGGTACAAGGGATGGACCATCGAGCGTTCCGGCCAGAAATT Neoseiulus cucumeris TTCGGGATGGTGTGGAGACAACATGCTGGAACCTTCGCCAAACATGACCTGGTACAAGGGATGGACCATCGAGCGTCAGGGCCAGAAATT Metaseiulus occidentalis TTCTGGATGGGCTGGAGACAACATGCTTGAGCCCTCTCCCAACATGACTTGGTACAAGGGATGGCAGATCGAGCGAAAAAATCAGAAGTT Dermanyssus hirundinis CTCCGGCTGGGCTGGCGACAACATGCTTGAGGTGTCGGCCAACATGCCCTGGTACAAGGGATGGCAGATCGAACGAAAGGGCAGCAAGTT Euzercon latum TTCTGGCTGGAATGGAGACAACATGCTCGAGCCGTCTACCAACATGCCGTGGTACAAGGGATGGAGTATTGAACGTAAGGGAGCCAAGTT Amblyomma sp. CTCTGGCTGGAACGGCGACAACATGCTCGAGCCTAGCCAGAACATGCCCTGGTACAAGGGGTGGTCTATTGAGCGCAAGTCTGGCAAGTC Neacarus texanus TTCTGGCTGGAATGGAGACAACATGCTGGATGCCTCTTCCAACATGCCCTGGTTTAAGGGATGGTCTATCGAGAGGAAGTCTGGCAAGTC Raoiella indica CTCCGGCTGGAACGGTGACAACATGCTTGAACCAAGTGATAACATGCCCTGGTTCAAGGGATGGCAAATTGAGAAGAAAGGATCTAAACT Tetranychus urticae TTCTGGATGGCATGGTGACAACATGATTGAACCATCACCTAACATGCCTTGGTATAAGGGATGGTCAATTGAAAAGAAGGGAGCTAAATT Aphonopelma chalcodes TTCTGGCTGGAATGGTGACAACATGTTGGAACCCAGCACAAACATGCCATGGTACAAGGGATGGAACATTGAACGCAAGAGCTCAAAATC Dysdera crocata TTCCGGCTGGAACGGTGACAACATGTTGGAGCCCAGCACCAACATGCCGTGGTACAAGGGATGGAACATCGAACGCAAGAGTGGAAAGAA Limulus polyphemus CTCTGGGTGGAATGGTGACAATATGCTGGAAGCCAGCCCTAACACTCCATGGTTTAAGGGGTTTAAAATTGAACGCAAGGGTCAAACAAC Locusta migratoria TTCTGGATGGCATGGTGACAACATGTTGGAGCATTCTGACAAGATGAGCTGGTTCAAGGGATGGTCTATTGAACGTAACGAAGGAAAGGC Drosophila melanogaster CTCCGGATGGCACGGCGACAATATGCTGGAGCCGTCCGAGAAGATGCCCTGGTTCAAGGGATGGTCCGTGGAGCGCAAGGAAGGCAAGGC

Figure 2-3. Continued.

103

370 380 390 400 410 420 430 440 450 ......

South Florida 1 CGAAGGAAAGACCCTCCTCCAGGCCCTCGACGTCATGGAGCCTCCCACCAGGCCCACCGACAAGCCTCTCCGTCTTCCCCTCCAGGACGT “ “ 2 CGAGGGCAAGACGCTTCTGCAGGCCCTCGATGTCATGGAGCCCCCGACCAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTCCAGGACGT “ “ 3 CGAGGGCAAGACGCTTCTGCAGGCCCTCGATGTCATGGAGCCCCCGACCAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTCCAGGACGT “ “ 4 CGAAGGAAAGACCCTCCTCCAGGCCCTCGACGTCATGGAGCCTCCCACCAGGCCCACCGACAAGCCTCTCCGTCTTCCCCTCCAGGACGT “ “ 5 CGAGGGCAAGACGCTTCTGCAGGCCCTCGATGTCATGGAGCCCCCGACCAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTCCAGGACGT “ “ 6 CGAAGGAAAGACCCTCCTCCAGGCCCTCGACGTCATGGAGCCTCCCACCAGGCCCACCGACAAGCCTCTCCGTCTTCCCCTCCAGGACGT “ “ 7 CGAAGGAAAGACCCTCCTCCAGGCCCTCGACGTCATGGAGCCTCCCACCAGGCCCACCGACAAGCCTCTCCGTCTTCCCCTCCAGGACGT “ “ 8 CGAGGGCAAGACGCTTCTGCAGGCCCTCGATGTCATGGAGCCCCCGACCAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTCCAGGACGT Flic en Flac 2 CGAGGGCAAGACGCTTCTGCAGGCCCTCGATGTCATGGAGCCCCCGACCAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTCCAGGACGT “ “ 3 CGAGGGCAAGACGCTTCTGCAGGCCCTCGATGTCATGGAGCCCCCGACCAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTCCAGGACGT North of Port Louis 1 CGAAGGAAAGACCCTCCTCCAGGCCCTCGACGTCATGGAGCCTCCCACCAGGCCCACCGACAAGCCTCTCCGTCTTCCCCTCCAGGACGT Trou d’Eau Douce 1 CGAAGGAAAGACCCTCCTCCAGGCCCTCGACGTCATGGAGCCTCCCACCAGGCCCACCGACAAGCCTCTCCGTCTTCCCCTCCAGGACGT “ “ 2 CGAGGGCAAGACGCTTCTGCAGGCCCTCGATGTCATGGAGCCCCCGACCAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTCCAGGACGT “ “ 3 CGAAGGAAAGACCCTCCTCCAGGCCCTCGACGTCATGGAGCCTCCCACCAGGCCCACCGACAAGCCTCTCCGTCTTCCCCTCCAGGACGT “ “ 4 CGAGGGCAAGACGCTTCTGCAGGCCCTCGATGTCATGGAGCCCCCGACCAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTCCAGGACGT Amblyseius swirskii CGAGGGCAAGACCCTTCTCCAAGCTCTCGACGTCATGGAGCCTCCCACCAGGCCCACCGACAAGCCCCTTCGTCTTCCCCTCCAGGACGT Neoseiulus californicus CGAGGGCAAAACCCTCCTGCAGGCTCTTGATGTAATGGAGCCTCCCACCAGGCCCACCGACAAGCCTCTGCGTCTGCCACTCCAGGATGT Neoseiulus cucumeris CGAGGGCAAAACCCTCCTCCAGGCTCTCGATGTCATGGAACCGCCTACCAGGCCCACCGACAAGCCTCTCCGTCTGCCTCTGCAGGACGT Metaseiulus occidentalis TGAAGGCAAGACCCTTCTCCAGGCCCTCGATGTCATGGAGCCGCCCACCAGGCCCACCGACAAGCCGCTTCGTCTTCCCCTCCAGGACGT Dermanyssus hirundinis TGAGGGCAAGACGCTGCTGCAGGCCCTCGACGTCATGGAGCCGCCCGCGAGGCCCACCGACAAGCCTCTGCGTCTGCCCCTGCAGGACGT Euzercon latum CGAGGGAAAGACCCTCTTGCAGGCCCTCGATGTCATGGAGCCACCGAGCAGGCCTACCGACAAGCCTCTTCGATTGCCTCTGCAGGATGT Amblyomma sp. TGAGGGCAAGACCCTTCTTCAGGCTCTCGACGCGATGGAGCCCCCGACCCGGCCCACGGACAAGCCCCTCCGACTTCCCCTGCAGGACGT Neacarus texanus TGAAGGCAAGACACTTCTGCAGGCTCTGGATGCCATGGAGCCCCCCACTAGGCCAACTGACAAACCCCTTAGGCTTCCCCTTCAGGATGT Raoiella indica TGAGGGGAAAACTTTGCTCCAAGCTCTTGATGCCATGGACCCACCATCCAGACCGGTTGACAAGCCTCTACGTCTACCACTCCAGGATGT Tetranychus urticae GGAAGGTAAAACATTGTTACAAGCCTTAGATGCTATGGATCCTCCATCTCGACCAGTTGATAAGGCACTTCGACTTCCACTTCAAGATGT Aphonopelma chalcodes TGATGGCAAGACATTATTGCAAGCATTGGATGCTATGGAGCCACCATCTCGACCTCTGGACAGGCCACTCAGGTTGCCTCTTCAGGATGT Dysdera crocata TGACGGCAAGACCTTGTTGCAAGCTTTGGATGCCATGGAGCCACCCTCCAGGCCTTTGGACAAACCTCTTAGATTGCCCCTCCAGGATGT Limulus polyphemus TGAAGGCAAGACTCTCTTGCAAGCTTTGGACTGTGCTGAACCTCCATCTCGTCCCACTGACAAGCCTCTTCGTCTGCCTCTGCAGGATGT Locusta migratoria TGAGGGAAAGACTTTAATTGAAGCTCTCGATGCCATCCTCCCTCCCAACAGGCCAACTGAGAAGCCTCTTAGGCTTCCTCTTCAGGATGT Drosophila melanogaster AGAGGGCAAGTGCTTGATCGACGCGCTGGACGCGATCCTTCCACCCCAGCGTCCCACCGACAAGCCGCTGCGCCTGCCGCTCCAGGACGT

Figure 2-3. Continued.

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460 470 480 490 500 510 520 530 540 ......

South Florida 1 TTACAAGATCGGTGGTATCGGCACAGTGCCCGTCGGTCGTGTCGAAACCGGTGTCATCAAGCCTGGTATGGTGGTCACTTTCGCTCCTTC “ “ 2 CTACAAGATCGGAGGTATCGGAACGGTCCCCGTGGGCCGTGTGGAAACCGGCGTCCTCAAGCCCGGCATGGTGGTCACCTTCGCCCCGGC “ “ 3 CTACAAGATCGGAGGTATCGGAACGGTCCCCGTGGGCCGTGTGGAAACCGGCGTCCTCAAGCCCGGCATGGTGGTCACCTTCGCCCCGGC “ “ 4 TTACAAGATCGGTGGTATCGGCACAGTGCCCGTCGGTCGTGTCGAAACCGGTGTCATCAAGCCTGGTATGGTGGTCACTTTCGCTCCTTC “ “ 5 CTACAAGATCGGAGGTATCGGAACGGTCCCCGTGGGCCGTGTGGAAACCGGCGTCCTCAAGCCCGGCATGGTGGTCACCTTCGCCCCGGC “ “ 6 TTACAAGATCGGTGGTATCGGCACAGTGCCCGTCGGTCGTGTCGAAACCGGTGTCATCAAGCCTGGTATGGTGGTCACTTTCGCTCCTTC “ “ 7 TTACAAGATCGGTGGTATCGGCACAGTGCCCGTCGGTCGTGTCGAAACCGGTGTCATCAAGCCTGGTATGGTGGTCACTTTCGCTCCTTC “ “ 8 CTACAAGATCGGAGGTATCGGAACGGTCCCCGTGGGCCGTGTGGAAACCGGCGTCCTCAAGCCCGGCATGGTGGTCACCTTCGCCCCGGC Flic en Flac 2 CTACAAGATCGGAGGTATCGGAACGGTCCCCGTGGGCCGTGTGGAAACCGGCGTCCTCAAGCCCGGCATGGTGGTCACCTTCGCCCCGGC “ “ 3 CTACAAGATCGGAGGTATCGGAACGGTCCCCGTGGGCCGTGTGGAAACCGGCGTCCTCAAGCCCGGCATGGTGGTCACCTTCGCCCCGGC North of Port Louis 1 TTACAAGATCGGTGGTATCGGCACAGTGCCCGTCGGTCGTGTCGAAACCGGTGTCATCAAGCCTGGTATGGTGGTCACTTTCGCTCCTTC Trou d’Eau Douce 1 TTACAAGATCGGTGGTATCGGCACAGTGCCCGTCGGTCGTGTCGAAACCGGTGTCATCAAGCCTGGTATGGTGGTCACTTTCGCTCCTTC “ “ 2 CTACAAGATCGGAGGTATCGGAACGGTCCCCGTGGGCCGTGTGGAAACCGGCGTCCTCAAGCCCGGCATGGTGGTCACCTTCGCCCCGGC “ “ 3 TTACAAGATCGGTGGTATCGGCACAGTGCCCGTCGGTCGTGTCGAAACCGGTGTCATCAAGCCTGGTATGGTGGTCACTTTCGCTCCTTC “ “ 4 CTACAAGATCGGAGGTATCGGAACGGTCCCCGTGGGCCGTGTGGAAACCGGCGTCCTCAAGCCCGGCATGGTGGTCACCTTCGCCCCGGC Amblyseius swirskii TTACAAGATCGGAGGTATTGGCACAGTGCCCGTAGGTCGTGTCGAAACCGGTGTCATCAAGCCTGGTATGGTCGTCACTTTCGCTCCGTC Neoseiulus californicus TTACAAGATCGGAGGAATCGGAACAGTCCCTGTAGGCCGTGTGGAAACCGGAGTTCTGAAACCCGGCATGGTCGTCACCTTCGCCCCGGC Neoseiulus cucumeris TTACAAGATCGGAGGAATCGGAACAGTTCCTGTGGGCCGTGTTGAAACCGGAGTTCTCAAACCCGGCATGGTGGTCACCTTCGCTCCGGC Metaseiulus occidentalis CTACAAGATCGGCGGTATCGGAACAGTGCCCGTGGGCCGTGTCGAAACCGGTGTCATCAAGCCCGGTATGGTGGTCACCTTCGCGCCGTC Dermanyssus hirundinis CTACAAGATCGGCGGTATTGGTACGGTGCCCGTAGGCCGTGTCGAGACTGGCGTCATCAAGCCCGGCATGGTCGTCACGTTCGCGCCGTC Euzercon latum CTACAAAATTGGAGGTATTGGCACAGTACCCGTGGGTCGTGTTGAAACTGGTGTGCTCAAGCCCGGCATGGTTGTCACGTTTGCACCTGC Amblyomma sp. CTACAAGATTGGTGGCATTGGCACGGTGCCCGTCGGCCGTGTGGAGACCGGCGTTCTCAAGCCCGGCATGGTCGTCACCTTTGCCCCTGC Neacarus texanus GTATAAAATTGGAGGTATTGGAACTGTGCCAGTTGGTAGAGTTGAAACTGGTGTTCTTAAGCCGGGTATGGTGGTTACCTTTGCTCCATG Raoiella indica CTACAAGATTGGTGGTATTGGTACAGTACCTGTTGGTCGTGTCGAAACTGGTGTTATTAAGCCTGGTATGGTCGTTACGTTCGCTCCTGT Tetranychus urticae CTACAAAATCGGTGGTATTGGTACTGTACCAGTTGGTAGAGTTGAAACTGGTACAATTAAGCCAGGTATGATTGTTACATTTGCACCAGT Aphonopelma chalcodes CTACAAAATTGGAGGTATTGGTACTGTTCCTGTTGGCAGAGTTGAAACTGGAGTGTTGAAACCTGGAATGGTTGTTACTTTTGCTCCTGT Dysdera crocata CTACAAAATCGGAGGTATTGGAACTGTCCCAGTCGGCAGAGTGGAAACTGGTGTCATGAAACCTGGTATGGTCGTCACCTTTGCTCCAGT Limulus polyphemus CTACAAAATTGGAGGTATTGGTACTGTACCTGTTGGTAGAGTTGAAACTGGTGTCTTGAAACCTGGCACCGTGGTTACCTTTGCCCCTGC Locusta migratoria GTACAAAATTGGTGGTATTGGAACAGTACCTGTGGGCCGAGTAGAAACAGGTATTCTCAAACCTGGTATGGTTGTGACATTTGCTCCAGC Drosophila melanogaster CTACAAGATCGGAGGCATCGGAACCGTACCAGTAGGTCGTGTGGAGACTGGTCTCCTCAAGCCAGGCATGGTCGTCAACTTTGCGCCGGT

Figure 2-3. Continued.

105

550 560 . .

South Florida 1 CAACCTCACCACTGAAGTCAAGTCCGTC “ “ 2 CCACATCACCACCGAGGTGAAGTCCGTG “ “ 3 CCACATCACCACCGAGGTGAAGTCCGTG “ “ 4 CAACCTCACCACTGAAGTCAAGTCCGTC “ “ 5 CCACATCACCACCGAGGTGAAGTCCGTG “ “ 6 CAACCTCACCACTGAAGTCAAGTCCGTC “ “ 7 CAACCTCACCACTGAAGTCAAGTCCGTC “ “ 8 CCACATCACCACCGAGGTGAAGTCCGTG Flic en Flac 2 CCACATCACCACCGAGGTGAAGTCCGTG “ “ 3 CCACATCACCACCGAGGTGAAGTCCGTG North of Port Louis 1 CAACCTCACCACTGAAGTCAAGTCCGTG Trou d’Eau Douce 1 CAACCTCACCACTGAAGTCAAGTCCGTC “ “ 2 CCACATCACCACCGAGGTGAAGTCCGTG “ “ 3 CAACCTCACCACTGAAGTCAAGTCCGTC “ “ 4 CCACATCACCACCGAGGTGAAGTCCGTG Amblyseius swirskii CAACCTCACCACTGAAGTCAAGTCCGTC Neoseiulus californicus TCACATCACCACTGAAGTGAAGTCCGTG Neoseiulus cucumeris TCACATCACTACCGAAGTGAAGTCCGTG Metaseiulus occidentalis CAACCTCACCACTGAAGTCAAGTCCGTC Dermanyssus hirundinis TAACCTCACCACTGAGGTGAAGTCGGTC Euzercon latum CAACTTGACTACTGAAGTAAAGTCTGTT Amblyomma sp. CAACCTGACCACTGAGGTCAAGTCCGTG Neacarus texanus CAACCTTACAACTGAAGTCAAGTCTGTT Raoiella indica CGGTATTACCACTGAAGTTAAATCAGTC Tetranychus urticae TAACTTGACAACTGAAGTAAAATCAGTT Aphonopelma chalcodes CAACTTAACTACTGAAGTGAAGTCTGTG Dysdera crocata TAACATCACCACTGAAGTAAAATCTGTG Limulus polyphemus TATGATCACCACCGAAGTAAAGTCTGTT Locusta migratoria TAATTTGACGACTGAAGTAAAATCTGTA Drosophila melanogaster CAACCTGGTCACCGAAGTAAAGTCTGTG

Figure 2-3. Continued.

106

Figure 2-4. The 12S rRNA concensus tree was inferred using the MCMC method in MrBayes (Huelsenbeck and Ronquist 2001; Ronquist and Huelsenbeck 2003). The Mauritius and S. Florida 12S clones are in two distinct sister clades. Number following a colony source location indicates the clone number. The posterior probabilities tree inferred from 1,000,000 generations is taken to represent the evolutionary history of the taxa analyzed. Branches corresponding to partitions with less than a posterior probability of 50 are collapsed.

107

Figure 2-5. The EF-I concensus tree was inferred using the MCMC method in MrBayes (Huelsenbeck and Ronquist 2001; Ronquist and Huelsenbeck 2003) with the assumption that all sequences represent a single gene. The Mauritius and S. Florida clones are intermingled between two clades. Number following a colony source location indicates the clone number. The posterior probabilities tree inferred from 1,000,000 generations is taken to represent the evolutionary history of the taxa analyzed. Branches corresponding to partitions with less than a posterior probability of 50 are collapsed.

108

Figure 2-6. The putative EF-I concensus tree was inferred using the MCMC method in MrBayes (Huelsenbeck and Ronquist 2001; Ronquist and Huelsenbeck 2003) assuming two different genes are present. Both the Mauritius and S. Florida clones are grouped together in the same clade when a single putative EF-I gene is used. Number following a colony source location indicates the clone number. The posterior probabilities tree was inferred from 1,000,000 generations is taken to represent the evolutionary history of the taxa analyzed. Branches corresponding to partitions with less than a posterior probability of 50 are collapsed.

109

Figure 2-7. The evolutionary history obtained from the high-fidelity-RAPD-PCR markers 196 and 199 for S. Florida (colonies 1-4) and Mauritius (colonies Flic en Flac, Trou d’Eau Douce (1-3), and North of Port Louis) ‘Amblyseius largoensis’ populations was inferred using the Neighbor-Joining method (Saitou and Nei 1987) in PAUP 4.0b10 (Swofford 2003). The bootstrap consensus tree inferred from 100,000 replicates is taken to represent the evolutionary history of the taxa analyzed (Felsenstein 1985). Branches corresponding to partitions reproduced in less than 50% bootstrap replicates are collapsed.

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Figure 2-8. High-fidelity PCR products obtained from the Mauritius and S. Florida colonies using 12S rRNA population-specific primers. PCR products obtained using the Mauritius forward primer (A) and S. Florida population-specific forward primer (B) indicate the appropriate band size for the Mauritius (330 bp) and the S. Florida (406 bp) populations while products of that band size were not produced from Amblyseius swirskii, Neoseiulus californicus, N. cucumeris, and Metaseiulus occidentalis.

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APPENDIX PERSPECTIVES

First, I would like to express how happy and privileged I feel to be involved with the

Entomology and Nematology department at the University of Florida. It is a wonderful

department composed of insightful faculty members, supportive staff and a vibrant

student body excited about the study of acarology, entomology, and nematology. The

past two years as an M.S. student have greatly enriched my life. I have gained confidence as a scientist had the opportunity to learn innumerable professional and life lessons. Thank you.

“If you can't ride two horses at once, you shouldn't be in the circus” - James

Maxton.

This quote by James Maxton perfectly embodies the expectations placed on graduate students and scientists as a whole. To be successful, I have learned that I must be able to multi-task, efficiently supervise others, work well with a variety of personalities and work styles, be able to clearly communicate ideas to the scientific community and the layman, and maintain a dynamic approach to my research.

Firstly, I learned to work harder and smarter than I thought possible before this experience. I learned to multi-task many layers of my daily life: multiple lab protocol, research and study, writing and lab work, and student life and personal life. Dr. Hoy taught me that the best way to learn a technique is to be taught, to practice, and then to teach someone else. This proved true when I had the opportunity to teach a visiting scientist from Egypt how to set-up a high-fidelity PCR and how to visualize your product.

I was given the opportunity to train and manage two OPS workers while a student in Dr.

M. A. Hoy’s lab. This was a wonderful opportunity to learn management tactics for

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different employee personalities, to observe different working habits between the

‘artisan’ and ‘time management’ personalities, and to gain realistic work expectations.

During my experience as an M.S. student, I learned that communication is critical to the success of any research project. I had a difficult time communicating my thoughts

clearly and concisely when I joined the lab. I was able to improve my communication

skills and confidence though conversations with Dr. Hoy, Dr. Jeyaprakash, and my

fellow students. Through my learning experiences, I have observed that often people

enter a scientific discussion with assumptions that may skew what is being said.

Therefore, in order to gain the most from the experience, it is important to approach every conversation with an open mind as a speaker and as a listener. In addition, when there is a breakdown in communication due to poor skills or personality conflict, the research may still be successful but not to the level of achievement possible.

I learned that in science, it is essential to maintain a dynamic approach to research. It is important to discover to new and creative ways to solve problems in the lab and to answer scientific questions. I have also learned that a hypothesis can be ever changing. If an experiment indicates an original hypothesis incorrect, it is important to adjust accordingly so that the proceeding series of experiments will produce valuable information.

As a M.S. student of Dr. M. A. Hoy’s I learned many valuable skills that I can apply to my personal and future professional life. I am very grateful for the experiences and opportunities to learn while under her tutelage.

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BIOGRAPHICAL SKETCH

Heidi Marie Bowman is a native of the Shenandoah Valley situated under the Blue

Ridge Mountains in Virginia. Upon graduation from Harrisonburg High School in 1997, she began her undergraduate studies at Blue Ridge Community College where she received an Associate’s degree in 2000. She was accepted into the horticulture program at West Virginia University (WVU) (Morgantown, WV) in 2000, and received her B.S. in horticulture in 2002. She then obtained a Master of Agriculture, Forestry and Consumer

Sciences degree at WVU under the guidance of Dr. Sven Verlinden in 2004. In 2005, she enrolled in the interdisciplinary Doctor of Plant Medicine Program at the University of Florida under the supervision of Dr. Robert McGovern. In 2007, she began a concurrent Master of Science program within the Department of Entomology and

Nematology under the supervision of Dr. Marjorie A. Hoy. She is currently a member of the Acarological Society of America, Systematic and Applied Acarology society, The

Florida Entomological Society, and the Entomological Society of America.

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