A Multigene Approach for Investigating DNA Barcode Lineages in Provisional Cryptic Species of Lepidoptera in Costa Rica

A multigene approach for investigating DNA Barcode lineages in provisional cryptic species of Lepidoptera in Costa Rica

Claudia Bertrand

A Thesis presented to The University of Guelph

In partial fulfilment of requirements for the degree of Master of Science in Integrative Biology

Guelph, Ontario, Canada

ABSTRACT

A multigene approach for investigating DNA barcode lineages in

provisional cryptic species of Lepidoptera in Costa Rica

Claudia Bertrand Advisor:

University of Guelph, 2012 Professor M. Hajibabaei

DNA barcoding has illuminated genetically distinct lineages within what appears to be one morphological species. For example, a large-scale DNA barcode analysis of

Lepidoptera in the Área de Conservación Guanacaste has revealed that 8% of the morphospecies show more than one DNA barcode lineage. To assess the evolutionary significance of five of these lineages I conducted further molecular analyses by sequencing mitochondrial cytochrome b, nuclear Elongation Factor 1 subunit α and ribosomal Internal Transcribed Spacer 2, and compare their gene genealogies with the provisional species tree hypothesized by DNA barcode genetic distances.

Both mitochondrial and nuclear markers support the existence of three species in

Urbanus belli. The lack of corroboration between markers in the four remaining species either suggests that the chosen nuclear markers have not diverged since speciation, or there has been recent hybridization between lineages. In the case of Eacles imperialis, hybridization is strongly suggested.

TABLE OF CONTENTS

ABSTRACT ...... I

TABLE OF CONTENTS ...... III

LIST OF TABLES ...... VI

LIST OF FIGURES...... VIII

ACKNOWLEDGEMENTS ...... X

LIST OF ABBREVIATIONS ...... XII

INTRODUCTION ...... 1

1 MULTIGENE ANALYSIS OF INTRASPECIFIC DNA BARCODE LINEAGES OF

THREE EXEMPLAR LEPIDOPTERA SPECIES WITH NO APPARENT

MORPHOLOGICAL AND ECOLOGICAL DIFFERENCES ...... 4

1.1 INTRODUCTION ...... 6

1.2 METHODS ...... 11

1.2.1 Specimens ...... 11

1.2.2 Phylogenetic analysis of COI, cytb, EF1α and ITS2 ...... 11

1.2.3 Next Generation sequencing of ITS2 ...... 13

1.2.4 Non-metric multidimensional scaling (nMDS) ...... 15

1.2.5 Wolbachia assay ...... 16

1.3 RESULTS ...... 16

1.4 DISCUSSION ...... 18

iii

1.4.1 Incomplete lineage sorting of nuclear loci ...... 19

1.4.2 Hybridization upon secondary contact ...... 21

1.4.3 Under-detected pseudogenes ...... 22

1.5 CONCLUSIONS ...... 23

2 MITOCHONDRIAL AND NUCLEAR GENETIC DIVERGENCE UNDERSCORE

MORPHOLOGICALLY CRYPTIC SPECIES OF URBANUS BELLI (LEPIDOPTERA:

HESPERIIDAE) WITHIN THE ÁREA DE CONSERVACIÓN GUANACASTE ...... 41

2.1 INTRODUCTION ...... 43

2.2 METHODS ...... 46

2.2.1 Specimens ...... 46

2.2.2 Molecular analysis ...... 46

2.2.3 ITS2 secondary structure and compensatory base change analysis ..... 48

2.3 RESULTS ...... 49

2.3.1 Phylogenetic analysis of COI, cytb and EF1α ...... 49

2.3.2 Analysis of ITS2 sequences ...... 49

2.3.3 ITS2 secondary structure & compensatory base changes ...... 50

2.3.4 Wolbachia Assays ...... 51

2.4 DISCUSSION ...... 51

3 INTROGRESSION THROUGH MALE GENE FLOW BETWEEN CRYPTIC

LINEAGES OF THE IMPERIAL MOTH (EACLES IMPERIALIS) IN THE ÁREA DE

CONSERVACIÓN GUANACASTE: EVIDENCE FROM MORPHOLOGY, ECOLOGY

AND MULTIPLE GENE REGIONS...... 71

3.1 INTRODUCTION ...... 72

3.2 METHODS ...... 75

3.2.1 Sampling ...... 75

3.2.2 Molecular analysis ...... 76

3.3 RESULTS ...... 78

3.4 DISCUSSION ...... 79

CONCLUSION ...... 110

REFERENCES ...... 112

APPENDICES ...... 123

APPENDIX A: CHAPTER 1 SUPPLEMENTARY TABLES ...... 123

APPENDIX B: CHAPTER 2 SUPPLEMENTARY TABLES AND MATERIALS ...... 129

Table B.2 Sequence-types of ITS2 sequences from U.belli specimens used in

the ITS2 secondary structure and compensatory basepair change analysis.

...... 145

Nucleotide and secondary structure alignments of ITS2 sequence-types used

in the ITS2 secondary structure and compensatory basepair change analysis.

...... 147

APPENDIX C: CHAPTER 3 SUPPLEMENTARY TABLES ...... 170

APPENDIX D: METHODOLOGY SUPPLEMENTARY TABLES AND MATERIAL ...... 184

Table D.1Description of primers used in this study...... 184

Macherey-Nagel (MN) Extraction Protocol ...... 185

LIST OF TABLES

Table 1.1 Larval food-plant data for barcode lineages of the three morpho-species used in this study……………………………………………………………………………………..25

Table 1.2 Taxonomic sampling of the butterflies and moths used in this study………...27

Table 1.3 Parameters used in Bayesian analyses of phylogeny for each moth or butterfly species and marker region…………………………………………………………31

Table 1.4 Results of Pyrosequencing ITS2 from three morpho-species of moths and butterfly. ………………………………………………………………………………………..32

Table 2.1 Urbanus belli species complex reared from wild-caught caterpillars in the

ACG showing larval food-plant and ecosystems.…………………………………………..58

Table 2.2 Taxonomic sampling of U.belli and gene region success……………………..59

Table 2.3 Parameters used in Bayesian analyses of phylogeny for U.belli for each marker region. …………………………………………………………………………………61

Table 2.4 Results of Pyrosequencing ITS2 from the U. belli complex…………………...62

Table 2.5 CBC matrix showing the number of compensatory base changes within and between each provisional species…………………………………………………………...64

Table 2.6 Wolbachia BLAST results from the wsp and MLST database for the five markers: coxA, hpcA, gatB, fstZ, and fbpA…………………………………………………64

Table 3.1 Eacles imperialisspecimens reared from wild-caught caterpillars in the ACG showing larval food-plant and ecosystems……………….…………………………………85

Table 3.2 Taxonomic sampling and sequencing success………………………………87

Table 3.3 Results of Pyrosequencing ITS2 from E.imperialis specimens collected in the

ACG…..………………………………………………………………………………..……...96

Table 3.4 Parameters used in Bayesian phylogenetic analyses of E. imperialis in the

ACG and in the analysis comprised of geographically distributed individuals…………99

Table 3.5 Mean within and between pairwise sequence divergences for the COI, Cytb,

EF1α, andITS2….…..……………………………………………………………………….100

Table 3.6 Mean pairwise genetic distances between groupings of E. imperialis…..…101

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LIST OF FIGURES

Figure 1.1 Mimoides clusoculis NJ-tree generated using K2P method in BOLD………34

Figure 1.2 Bardaxima perses NJ-tree generated using K2P method in BOLD…………35

Figure 1.3 Eumorpha satellitia NJ-tree generated using K2P method in BOLD…….…36

Figure 1.4 Bayesian trees constructed from COI, cytb, and EF1α, sequences of

Mimoides clucsoculis………………………………………………………………………….37

Figure 1.5 Bayesian trees constructed from COI, cytb, and EF1α, sequences of

Bardaxima perses………………………………………………………………………….….38

Figure 1.6 Bayesian trees constructed from COI, cytb, and EF1α, sequences of

Eumorpha satellitia……………………………………………………………………………39

Figure 1.7 NJ analyses of full ITS2 sequence-types based on p-distances and nMDS distances among ITS2 intra-individual sequence-types of the 3 morpho-species….….40

Figure 2.1 NJ-tree of 299 Urbanus belliCOI sequences from BOLD…………………….65

Figure 2.2 A map of a part of the ACG showing life zones and the distribution of the

U.belli complex. …………………………………………………………………………….…66

Figure 2.3 Bayesian trees constructed from COI, cytb, and EF1α sequences of Urbanus

belli……………………………………………………………………………………………..67

Figure 2.4 nMDS graph showing the intra-individual variation of ITS2 in the U.belli

complex.………………………………………………………………………………………68

viii

Figure 2.5 Maximum Parsimony cladogram constructed from ITS2 sequences of the

U.belli complex.………………………………………………………………………………..69

Figure 2.6 Conserved ITS2 secondary structure for full-length sequence-types of the

Urbanus belli complex..……………………………………………………………………….70

Figure 3.1 The Área de Conservación Guanacaste life zone map showing the distribution of the two E.imperialis lineages.………………………………………..……..102

Figure 3.2 Bayesian trees constructed from mitochondrial and nuclear sequences from

Eacles imperialis. ..…………………………………………………………………….…….103

Figure 3.3 nMDS distances among ITS2 intra-individual sequence-types of the two

E.imperialis lineages. ………………………………………………………………………..104

Figure 3.4 Bayesian tree and map constructed from mitochondrial sequences of E. imperialis populationsthat are geographically distributed throughout the species range…………………………………………………………………………………..………105

Figure 3.5 Bayesian tree constructed from EF1α haplotype sequences of E. imperialis populationsthat are geographically distributed throughout the species range……….. 106

Figure 3.6 Character based analysis between successfully sanger-sequenced individuals of E. imperialis across the species range. …………………………...………107

ACKNOWLEDGEMENTS

Firstly, I would like to thank the Natural Sciences and Engineering Research

Council of Canada and Genome Canada through the Ontario Genomics Institute for financially supporting this research.

I would like to extend much gratitude to my advisor Dr. Mehrdad Hajibabaei for his guidance, motivation and support throughout my Master’s degree. Mehrdad, I am thankful for every opportunity you have given me to present my work to our academic community, network with colleagues, and think critically about science. I would also like to thank my committee members Dr. Teresa Crease and Dr. Alex Smith for helping to shape my thesis with their brilliance, patience and dedication.

I would also like to give thanks to my past and present colleagues and lab mates

Saina Taidi, Steve Konynenburg, Jenn Spall, Stephanie Boilard, Ian King, Joel Gibson,

Jessica Grice, Shannon Eagle, Kara Layton, Monica Young, Liz Boyle, Connor Warne,

Stephanie deWaard, Jeremy deWaard, Sujeevan Ratnasingham, Megan Milton and

Mallory Van Wyngaarden for their support, contribution of ideas and making my work environment enthusiastic and enjoyable. I would like to give a special thanks to Shadi

Shokralla for his kindness, dedication to excellence and help with lab protocols. A special thanks is also given to Dr. Rodolphe Rougerie for providing specimens and performing morphological analysis of Eacles imperialisDHJ01 and Eacles

imperialisDHJ02. Much gratitude is given to the staff of the CCDB and Genomics facility for making my project a priority.

I also need to give special acknowledgements to my collaborators Dr. Dan

Janzen and Dr. Winnie Hallwachs. Working with the two of you has changed the way I think about biology and the world. I am grateful to have had the opportunity to collaborate and learn from both of you; it has been a life changing experience.

Lastly, I am in debt to my family for their unwavering support and praise. To my friends who distracted and laughed with me. Most importantly, I need to thank my partner Karan. Karan this would not have been possible without your patience; encouragement and love. Thank you.

LIST OF ABBREVIATIONS

ACG Área de Conservación Guanacaste

COI 658bp region of Cytochrome c oxidase subunit I cytb 500bp region of Cytochrome b

EF1α 1030bp region of Elongation factor subunit I alpha

ITS2 Internal transcribed spacer region II

ITS1 Internal transcribed spacer region I

CBC Compensatory basepair change

MID Multiple Identifier Tag

Wsp Wolbachia surface-protein marker coxA 402bp region of Cytochrome c oxidase subunit I

hpcA Conserved hypothetical protein

Gln Glutamyl-tRNA gatB amidotransferase subunit B fstZ Cell division protein fbpA Fructose-bisphophate aldolase.

MLST Multi-locus sequence typing

BOLD Barcode of Life Data Systems

NJ Neighbor-Joining

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INTRODUCTION

A major goal of systematic biology is to discover and describe species. Species delimitation, the process of determining species boundaries and discovering new species (Wiens 2007), has resurged in systematic research because of accelerated threats to biodiversity from anthropogenic activities. Historically, phenetic methods based on morphological similarity delimited species. As technology advanced through the 20th century, phylogenetic methods based on genomic data augmented phenetic approaches to species delimitation. DNA barcoding has become an international initiative which has combined phenetic and genomic tools to identify species diversity in a standardized fashion. DNA barcoding uses the sequence variation in a short, standardized gene region to identify organisms to species (Hebert et al. 2003a). In animal life, the DNA barcode is a 658 bp region of cytochrome c oxidase I (COI), a mitochondrial protein coding gene (Hebert et al. 2003b). Traditionally, distance based methods that create and compare similarity matrices are used to calculate intra and inter-specific sequence divergences.

Higher inter-specific divergence than intra-specific divergence between DNA barcode lineages create a “barcode gap” used for species delimitation. Sequence divergence thresholds have also been applied, for instance a 2% threshold of DNA barcode divergences has been used to evaluate species boundaries that have been defined morphologically (Hebert et al. 2003b). In most DNA barcode studies that apply thresholds, species that show higher than 1.5-2% sequence divergence are “flagged” as potentially cryptic species. This type of analysis can flag cryptic species but additional

evidence is required to support the hypothesis that this intra-specific variation represents provisional cryptic species.

This thesis examines cases of morphologically defined species that show distinct, non-overlapping intraspecific clusters of COI sequences in a Neighbor-joining

(NJ) tree that have a range of 1.5%-8% genetic divergence, for the presence of cryptic species. I focus on an ecologically and economically important group in forest ecosystems, the Order Lepidoptera. I chose five species, from five families, of moths and butterflies that have been collected from the Área de Conservación Guanacaste,

Costa Rica. The five species, Mimoides clusoculis (Papilionidae), Bardaxima perses

(Notodontidae), Eumorpha satellitia (Sphingidae), Eacles imperialis (Saturniidae) and

Urbanus belli (Hesperiidae) also exhibit varying levels of host-plant associations, distribution patterns and habitat preferences within the ACG. An integrative approach is used to investigate the provisional cryptic lineages in this study. Previously collected natural history and DNA barcode data are augmented by three additional gene regions including; an additional mitochondrial marker cytochrome b (cytb); and two independent nuclear loci, Elongation Factor 1α (EF1α) and ribosomal Internal Transcribed Spacer 2

(ITS2) . Bayesian analyses, non-metric multidimensional scaling and in one instance maximum parsimony are used to create and compare gene trees and clustering patterns. I also include a test for the presence of Wolbachia because these obligate endosymbionts are known to manipulate host reproduction and facilitate speciation.

The data chapters to follow examine the same overall research question but focus on different species that possess varying levels of natural history data including

habitat preferences and larval food-plant differences, as well as shallow to deep (1.5-

8%) COI sequence divergence data.

Chapter 1 investigates three species, Mimoides clusoculis (Papilionidae),

Bardaxima perses (Notodontidae), and Eumorpha satellitia (Sphingidae) that show between ~1.5-4% DNA barcode intra-specific sequence divergence, sympatric distribution patterns and overlapping larval-food plants. Chapter 2 focuses on Urbanus belli (Hesperiidae) which is composed of three distinct, non-overlapping DNA barcode lineages that have between ~3-5% sequence divergence and share larval-food plants, and overlapping distributions, with the exception of one lineage being restricted to rain forest habitat. Chapter 3 is focused on Eacles imperialis (Saturniidae) which is composed of two lineages that are also distinct and non-overlapping and show up to

~8% COI divergence. The two lineages have strong habitat and larval host-plant preferences. In Chapter 3, I expand sampling of E. imperialis to include individuals from the species Nearctic-Neotropical distribution.

In combination, the three chapters of this thesis show that detecting cryptic species using this integrative approach can discover unappreciated species diversity in

Lepidoptera, yet it still has limitations. This work demonstrates the complexity of delineating cryptic species, especially when species are recently diverged. Analytical techniques focused on the recently diverged species are of prime focus for future work on the species in this study. This thesis also highlights the need for future work focused on delimiting species that hybridize upon secondary contact.

1 Multigene analysis of intraspecific DNA barcode lineages of three exemplar

Lepidoptera species with no apparent morphological and ecological differences

Abstract

DNA barcoding has illuminated genetically distinct lineages within what appears to be one morphological species. For example, large-scale DNA barcode analysis coupled with the Lepidoptera inventory of the Área de Conservación Guanacaste (ACG) in northwest Costa Rica has revealed that 8% of morpho-species of Lepidoptera show more than one DNA barcode lineage. Further studies have revealed larval-food plant and/or overlooked morphological correlates supporting the discovery of cryptic species diversity. To assess the evolutionary significance of three of these cases I conducted further molecular analyses in three species from three families of Lepidoptera containing distinct, non-overlapping DNA barcode lineages with ~1-5% sequence divergence: Mimoides clusoculis (Papilionidae), Bardaxima perses (Notodontidae), and

Eumorpha satellitia (Sphingidae). I sequence cytochrome b (cytb), nuclear Elongation

Factor 1α (EF1α) and ribosomal Internal Transcribed Spacer 2 (ITS2) and compare their gene trees with the species tree hypothesized from patterns of DNA barcode clusters in neighbor-joining (NJ) tree. In the case of ITS2, intra-individual variation is analyzed using non-metric multidimensional scaling (nMDS) and clustering patterns are observed.

The results indicate that shallow DNA barcode lineages (i.e. with less than 2% sequence divergence) are paraphyletic when analyzed using a Bayesian phylogenetic method. In addition, both EF1α and ITS2 supported only a single lineage in all cases. I

discuss possible causes for the absence of nuclear variation in light of evident mitochondrial variation, including incomplete lineage sorting of nuclear loci, interbreeding upon secondary contact and the inadvertent sequencing of nuclear- mitochondrial pseudogenes (NUMTS). I eliminated NUMTs as a likely cause for discordance between mitochondrial and nuclear loci and propose either incomplete lineage sorting or hybridization as more likely causes. I suggest future avenues of research including expanding sampling regimes, and highlight newly developed analytical methods that can shed light on gene tree discordance.

1.1 Introduction

The identification and delineation of species is crucial for all branches of biological science. Today’s biodiversity crisis calls for standardized, cost effective, and robust measures of the planet’s biodiversity and its linkage to critical socioeconomic issues from agriculture to public health and environmental management. Consequently, the development of new technologies for species identification, such as DNA barcoding, plays an important role in addressing this dilemma. The DNA barcode for animals —a

658bp region of the mitochondrial cytochrome c oxidase I (COI) gene—has corroborated taxonomically defined species in extremely diverse groups of invertebrates, and vertebrates (Hebert et al. 2004b, Hajibabaei et al. 2006, Costa et al.

2007, Kerr et al. 2007), including hyper-diverse and taxonomically problematic groups like ants (Smith et al. 2005) and most recently in environmental assemblages like benthos and soil invertebrates (Rougerie et al. 2009, Hajibabaei et al. 2011). DNA barcoding has gained support in an international initiative of 28 collaborating countries worldwide (http://ibol.org/). Although DNA barcoding has been successful in identifying morphologically defined species, the use of DNA barcodes discovering new species- level diversity is currently debated (Hebert et al. 2004a, Moritz and Cicero 2004, Will and Rubinoff 2004, Rubinoff 2006, Song et al. 2008, Ebach 2011, Jinbo et al. 2011,

Mitchell 2011). Morphologically cryptic species are one example of unrecognized diversity that DNA barcode studies have highlighted, but only in a few cases have these studies actually elevated to provisional or described species status (Kerr et al. 2007,

Ward et al. 2008, Chang et al. 2009, Kerr et al. 2009, Robinson et al. 2009, Rougerie et al. 2009, Radulovici et al. 2010, Burns et al. 2008; Clare 2011; Dasmahapatra et al.

2010; Hebert et al. 2004a; Smith et al. 2008; Smith et al. 2007; Smith et al. 2006).

The DNA barcode alone is insufficient for delimiting unrecognized species diversity because of phenomena such as introgression, maternal inheritance, lack of recombination, and mitochondrial nuclear pseudogenes (NUMT). The aforementioned properties of mtDNA can misrepresent species relationships and mislead researchers when investigating species boundaries using DNA barcodes alone (Ballard and

Whitlock 2004). However, a number of studies have used DNA barcodes to identify previously under-described species diversity by combining DNA barcode genetic divergence data with additional lines of evidence from different biological properties; including morphology, ecology, behavior and genetics (Hebert et al. 2004a, Smith et al.

2006, Smith et al. 2007, Burns et al. 2008, Smith et al. 2008, Dasmahapatra et al. 2010,

Clare 2011). Integrative approaches to species discovery are crucial because different biological properties (phonetic, ecological or genetic) can develop at different rates and in no particular order, as lineages separate through space and time (de Queiroz 1998).

This can confound species delimitation if any one character is deemed diagnostic over another. For example, the implementation of a species threshold based on a divergence level of a molecular marker, such as 2% variation in COI DNA barcodes that is applied in many studies of DNA barcoding (Hebert et al. 2003a, Hebert et al. 2003b,

Dasmahapatra et al. 2010). Distance thresholds can over- or under-estimate species numbers if species are very recent or have deep population structure. This thesis

focuses on under-estimated diversity thus one example is three pairs of closely related congener Hesperiidae moth species: Polyctor cleta and P. polyctor, Cobalus virbius and

C. fidicula, Neoxeniades luda and N. pluviasilva Burns. The three species pairs show distinct morphological and genitalic differences and occupy dry forest and rain forest habitat types yet fall well below the 2% threshold, containing between one to three nucleotide differences within the 658bp DNA barcode region of COI (Burns et al. 2007).

A summary of results on DNA barcoding Lepidoptera, from the Lepidoptera inventory of the Área de Conservación Guanacaste (ACG), in northwest Costa Rica, illustrates how morphological and ecological characters can be lacking for species identification. Janzen et al. (2009) revealed that 340 of 2810 morpho-species of

Lepidoptera had distinct intra-specific DNA barcode lineages. There was morphological or ecological support for different lineages in 179 cases, but no support for the other

161. This example demonstrates that nearly half of the potentially unrecognized diversity of Lepidoptera in the ACG lack biological or ecological properties for species discovery. Moreover, in Chapter 2 I investigate three COI lineages of Urbanus belli

(Hesperiidae) that lack support from morphology including genitalic scrutiny, and lack larval-food plant differences, yet I show they are a complex of three species. The three

COI lineages were also found in three additional gene regions, providing additional evidence to support the hypothesis that the three lineages are different species. Utilizing different regions of the genome enables us to build independent lines of evidence for species delimitation when other diagnostic properties are absent, such as morphological and genitalic distinctiveness, larval food plant differences and/or habitat preferences.

The ACG has been a study site for testing the applicability of DNA barcoding.

Multiple studies have identified unrecognized diversity within the conservation area

(Hebert et al. 2003a, Hebert et al. 2004a, Hajibabaei et al. 2006, Smith et al. 2006,

Burns et al. 2007, Smith et al. 2007, Burns et al. 2008, Smith et al. 2008, Janzen et al.

2009, Janzen et al. 2011). The inventory has long-standing taxonomic records, as well as reliable and comprehensive ancillary data including collection locality, collector, date of collection, larval food-plant, sex, and parasitoid development

(http:janzen.sas.upenn.edu). I utilized these datasets, in combination with DNA barcode records deposited on the Barcode of Life Data System (BOLD) (Ratnasingham and

Hebert 2007) to select three morphologically defined species of Lepidoptera, Mimoides clusoculis (Papilionidae), Bardaxima perses (Notodontidae), Eumorpha satellitia

(Sphingidae), that have distinct, non-overlapping intra-specific COI lineages that are

~1.0-4% divergent (Figures 1.1-1.3). All of the intra-specific lineages lack distinct morphological differences, have overlapping larval food-plants and sympatric distributions within the ACG. I investigate these three species for provisional cryptic species diversity through a multigene approach.

The multigene approach used in this study utilizes a Bayesian framework to build gene trees for three additional genetic markers and their gene phylogenies are compared with the species tree hypothesized by DNA barcode data through Neighbor-

Joining using Kimura 2 parameter (K2P) model of nucleotide substitution (Figures 1.1-

1.3). Mitochondrial cytochrome b (cytb), nuclear Elongation factor subunit I alpha

(EF1α), and nuclear ribosomal DNA internal transcribed spacer region II (ITS2) are

examined because they represent both nuclear and mitochondrial genomes, as well as coding and non-coding regions of DNA. In the case of ITS2, intra-individual variation is analyzed using non-metric multidimensional scaling (nMDS), this reduces the redundancy in the dataset and clustering patterns are observed. I chose to implement genetic markers traditionally used in phylogenetic analyses rather than microsatellites and AFLP markers, because although they are useful for discovering cryptic species, they differ in their ability to be standardized and robust for large-scale diversity analyses

(Barbara et al. 2007). Mainly, microsatellite and AFLP markers require high developmental investment and few studies have shown cross-species applicability

(Barbara et al. 2007), making their range of re-usability narrow compared with comparative sequence analysis of protein coding and many non-coding nuclear genes.

Lastly, the presense for Wolbachia endosymbionts are tested using the Wolbachia surface protein (wsp) marker (Baldo et al. 2006). Wolbachia can spread by reducing the fitness of their arthropod hosts by parasitizing host reproductive strategies (Bordenstein,

2003). The most commonly reported mechanism is cytoplasmic incompatibility (CI) in which infected males cannot reproduce successfully with uninfected females or females infected by a different strain of Wolbachia (Bordenstein, 2003). Other mechanisms also include male killing and feminization. Any of these mechanisms can contribute to the speciation process of arthropod taxa by sexually-isolating populations and reducing the viability of offspring (Werren et al. 2008).

1.2 Methods

1.2.1 Specimens

The specimens used in this study were wild-caught as caterpillars in the ACG by

Daniel H. Janzen, Winnie Hallwachs and a group of 30 parataxonomists as part of the ongoing inventory of ACG Lepidoptera (Janzen et al. 2009). Caterpillars were reared to adulthood, killed via freezing, oven dried and spread for the ACG Lepidoptera inventory.

The inventory documents locality, collector, date of collection, larval food-plant, sex and parasitoid development for all specimens (http:janzen.sas.upenn.edu) (Table A.1. and

Table 1.1). Ten to thirty individuals, of each COI lineage, from the three morpho- species, were selected from the Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert 2007), for investigation with additional gene regions (Table A.1).

1.2.2 Phylogenetic analysis of COI, cytb, EF1α and ITS2

DNA was extracted from a single leg using Nucleospin Tissue Kits (Macherey-

Nagel). Details on extraction methods can be found in Appendix D. EF1α was amplified using four primer sets that overlapped by 20-30bp (Appendix D, Table D.1). COI, cytb, and each fragment of EF1α were amplified in 25μl reactions containing final concentrations of 0.2 mM of dNTPs, 0.2 μM of each primer, 0.024 U/μl Invitrogen Taq

DNA polymerase, 20μM of Tris-HCl, 50 μM KCl, and 2.5mM MgCl2. The PCR thermal cycling conditions varied by marker. COI and EF1 α followed: hot start for 94 °C for 2 min, followed by 40 cycles of initial denaturation at 94 °C for 30 sec, annealing temperature of 51°C for 40 sec and 72 °C for 1 min. A final extension step was

performed at 72 °C for 5 min. Cytb underwent the following protocol: hot start for 94 °C for 2 min, followed by 35 cycles of initial denaturation at 94 °C for 30 sec, annealing temperature of 48°C for 1 min and 72 °C for 40sec . A final extension step was performed at 72 °C for 1 min.30-100ng of DNA was added to each PCR reaction.

Information about the primers used for each marker is provided in Appendix D.

ITS2 was amplified in 25μl reactions containing final concentrations of 0.2 mM of dNTPs, 0.4 μM of each primer, 0.024 U/μl Invitrogen Taq DNA polymerase, 20μM of

Tris-HCl, 50 μM KCl, and, and 1.5mM MgCl2. The PCR thermal cycling conditions were as follows: initial denaturation at 94 °C for 5 min, followed by 40 cycles of 94 °C for

1min, annealing temperature of 53°C for 1min and 72 °C for 1 min. A final extension step was performed at 72 °C for 10 min. 30-100ng of DNA was added to each PCR reaction.

The PCR results were visualized on a 1.5% agarose gel stained with Ethidium

Bromide. Any PCR products that showed a band on the agarose gel underwent cycle sequencing reactions with the following protocol: 0.25μl of Dye terminator mix v3.1,

1.875μl 5 X Sequencing Buffer, 1 μl of 10μM Primer, and 5.875μl of H20 for a final volume of 9μl which 2.0μl of PCR product was added. The cycle sequencing thermocycling protocol was as follows: Initial denaturation at 96°C for 2 min, followed by

30 cycles of 96°C for 30 sec, annealing at 55°C for 15sec, and extension at 60°C for 4 min, followed by indefinite hold at 4°C

(http://www.ccdb.ca/pa/ge/research/protocols/sequencing). Cycle sequenced products

were resolved on an ABI 3730XL sequencer (Applied Biosystems, Biosystems, Foster

City, CA, USA) using a standard sequencing protocol.

EF1α sequences were heterogeneous, showing double peaks in sequence chromatograms. Consequently, polymorphic bases were scored using the IUPAC code for ambiguous bases (R,M,Y,S). Sequences were edited using CodonCode Sequence

V3.1.5 (CodonCode, Dedham, MA, USA) software, aligned using CLUSTAL W and manual inspection was done in MEGA 5.0 (Tamuraet al. 2007). Outgroups for each phylogenetic analysis were also amplified and sequenced by the protocols mentioned above and are as follows: Mimoides branchus (09-SRNP-44264, 09-SRNP-44263),

Bardaxima lucilinea (09-SRNP-44671, 09-SRNP-444670) and Eumorpha anchemolus

(09-SRNP-105641). Outgroups were chosen because they appeared closely related to the ingroups when observed in a NJ-tree (K2P) analysis on BOLD and tissue was available for molecular analyses. Sequences were exported in Nexus format.

MrModelTest2.3 (Nylander, J. A. A. 2004) was used to find the best nucleotide substitution model prior to Bayesian analysis. MrBayes v3.1.2 (Ronquist and

Huelsenbeck 2003) was used to generate gene trees for each marker. Four Monte

Carlo Markov chains and a temperature of 0.2 were used for each analysis. Trees were sampled every 100 generations.

1.2.3 Next Generation sequencing of ITS2

Fifty four individuals from three morpho-species were selected for the 454- pyrosequencing analysis of ITS2. ITS2 fragments were PCR amplified with Multiple

Identifier (MID) Tags using the same reaction mix as the Sanger sequencing reactions.

The thermal cycling conditions were: initial denaturation at 94 °C for 5min, followed by

40 cycles of 94 °C for 1min, 53 °C for 1 min, and 72 °C for 1 min, and a final extension step of 72 °C for 10min. The MID tag-primers were used to combine all individuals into two 454 lanes in a 16-lane sequencing run. Amplicons of each sample were bi- directionally sequenced on a 454 Genome Sequencer FLX System (Roche Diagnostics

GmbH) following manufacturer’s amplicon sequencing protocols (http://www.454.com/).

Data was filtered using an in-house process with a 10-5-15 sliding window-phred score approach (Ewing and Green 1998, Ewing et al. 1998). The approach starts by analyzing the first 10 nucleotides from the 5’ end of the sequence for a phred score of above 10. If the phred score is above 10, the window of analysis shifts 5 bases towards the 3’ end of the sequence. The analysis repeats until a phred score of less than 10 is retrieved and the sequence is cut at this location. Sequences that passed this initial quality filtering underwent further filtering using PRINSEQ webserver (Schmieder and

Edwards 2011) to remove sequences below 200bp as well as any sequences with base ambiguities. I chose a 200bp cut off because little sequence variation was observed before 200bp. Chimera detection was performed in UCHIME using the de novo option which utilizes abundance information (Edgar et al. 2011). The algorithm is based on the assumption that chimeras are less abundant than their parents because they must have undergone fewer rounds of amplification (Edgar et al. 2011). Sequences that matched chimera sequences by 100% were eliminated from the analysis. The remaining filtered sequences were sorted by MID tag using the online platform BioSculpt

(http://www.ibarcode.org/steve/sculpt.cgi). Forward and reverse direction sequences

were reduced to sequence-types by collapsing sequences that were 100% identical to each other, using the CD-HIT webserver (Li and Godzik 2006). As a last quality control,

I only included sequence-types that had 2 or more collapsed sequences. Only forward direction ITS2 sequences were used in downstreen ordination analyses because reverse sequence-types, after filtering, were minimal (between 1-3). Forward direction sequence-types were aligned in MEGA 5.0 (Tamura et al. 2007) using Clustal W with alignment gap opening = 7 and gap extension =3, followed by manual editing.

Forward and reverse direction sequence-types of ITS2 that had at least 95% match in a 20bp overlap were assembled. ITS2 sequences have been shown to accumulate indels and nucleotide substitutions relatively rapidly and as a result, greater than expected divergence, as well as uncertainty in sequence alignment between ingroups and outgroups has occurred in plants and invertebrates (Baldwin et al. 1995,

Kim and Jansen 1996, Alvarez and Wendel 2003, Moussalli et al. 2009). Unreliable outgroup to ingroup alignment was found in all species, with outgroups showing a lack of nucleotide similarity, variation in sequence length and large indels. NJ-trees (paiwise distances) were therefore used to cluster ITS2 sequences. NJ- trees were generated in

MEGA5.0 using pairwise deletion and nodal support is based on 1000 bootstrap replicates.

1.2.4 Non-metric multidimensional scaling (nMDS)

The sheer abundance of ITS2 data called for non-tree based methods of visualization, thus ordination by non-metric multidimensional scaling (nMDS) was used to create a graphical representation of the intra-individual and inter-specific variation of

ITS2. nMDS plots the data in a non-hierarchical way which allows visualization of other possible patterns of genetic variation, like reticulate patterns (Lessa 1990). nMDS was performed in PRIMER v6 (Clarke, 2006) using the Bray‐Curtis similarity measure (Bray and Curtis 1957). Every position in the sequence-type alignment was treated as a separate character and nucleotides were coded arbitrarily as A = 0, C = 1, G = 2, T = 3,

(Hebert et al. 2003a) and gaps were treated as a fifth character, gap =4, in the matrix.

1.2.5 Wolbachia assay

The presence of Wolbachia was established by a PCR test for the Wolbachia surface protein (wsp) from DNA that was extracted from leg tissue. Primer sequences can be found in Appendix D, Table D.1 and the PCR reaction mix is the same as mentioned previously for cytb and EF1α. The PCR thermal cycling protocol was as follows: denaturation step of 94 °C for 2 min followed by 36 cycles of 94 °C for 30 sec, with an optimal annealing temperature of 59 °C for 45 sec and 72 °C for 1.5 min, and an elongation step of 70 °C for 10 min and a final hold at 4 °C. The PCR amplicons were visualized on a 1.5% agarose gel stained with Ethidium Bromide.

1.3 Results

Twenty-one (100%) COI sequences (Table1.2) of M. clusoculis were used in the

Bayesian analysis (Table 1.3). The topology of the COI Bayesian tree shows paraphyly of the two provisional lineages observed in the NJ-tree (K2P) of M. clusoculis which had an average COI divergence of (1.4% SE =0.47). However, the cytb gene region shows reciprocal monophyly for the two COI lineages (Figure 1.3). Cytb was difficult to amplify with the 40F and 560R primers and had relatively low success of 57% (12/21) (Table

1.2). Twenty sequences (Table 1.2) of the EF1α gene region (95%) were used in the

Bayesian analysis which revealed a single lineage (Figure 1.3).

Fifty-three (98%) and fifty-four (100%) COI and cytb sequences of B. perses specimens were used in the Bayesian analysis (Table 1.3).The Bayesian tree topologies of COI and cytb of B. perses showed reciprocal monophyly for the two COI

NJ-tree lineages (Figure 1.5). However, the EF1α gene tree showed very little genetic variation and the fifty three EF1α sequences (100%) used in the Bayesian analysis revealed a single lineage (Figure 1.5).

Twenty-four (100%) and twenty-three (96%) COI and cytb sequences of E. satellitia specimens were used in the Bayesian analysis (Table 1.2).The tree topology of the COI and cytb Bayesian trees showed reciprocal monophyly of E. satellitiaDHJ01 and paraphyly of E. satellitiaDHJ02 to E. satelittiaDHJ03 (Figure 1.6) compared to the

NJ-tree analysis of E. satellitia (Figure 1.3) which had an average COI divergence between the lineages of (1.7% SE =0.46). Twenty-one sequences (Table 1.2) of the

EF1α gene region (84%) were used in the Bayesian analysis. For the EF1α marker sequences less than 500bp were removed from the analysis because sequences with between 300-500bp clustered together and confounded the tree topology. EF1α gene tree shows a single lineage (Figure 1.6) and had little sequence variation.

ITS2 Sanger-sequencing results are not included in this study because of their sequence heterogeneity and consequently imprecise base calling. ITS2 results are therefore analyzed using pyrosequencing analysis. Pyrosequencing of ITS2 from fifty- four individuals produced 3,955 sequence reads which consisted of three 348

sequence-types, after filtering (Table 1.4). NJ-trees were generated from sequence- types of the entire ITS2 region for M. clusoculis and E. satellitia. However, forward and reverse ITS2 sequence-types of B. perses were unable to overlap because forward and reverse sequences did not possess enough nucleotides (Figure 1.7). Therefore, the NJ- tree based on ITS2 sequences of B. perses is comprised of forward direction sequence- types only (Figure 1.4). All of the tree-based analyses showed a single cluster on the

NJ-tree.The non-metric multidimensional scaling plots (Figure 1.7) lack distinct clusters and each provisional cryptic lineage shares sequence-types with one or both of the other mitochondrial lineages.

Wsp PCR bands were absent in all specimens in this study. The lack of wsp PCR products can be due to Wolbachia being absent in leg tissue and therefore I do not conclude on the presence or absence of Wolbachia in the specimens used in this study.

1.4 Discussion

The three morpho-species investigated in this study showed varying levels of

COI divergences, ranging from 1-4%. The two COI lineages of M. clusoculis and DHJ02 and DHJ03 in E.satellitia have the lowest percentage of inter-lineage sequence divergence, at about 1.5% and 1.7%, respectively. In both cases, NJ-trees resolved these lineages but Bayesian methods showed paraphyly. In the case of M.clusoculis,

Bayesian analysis of COI showed M. clusoculisDHJ02 to be paraphyletic to M. clusoculisDHJ01, but showed cytb to be congruent with the COI NJ-tree, which indicated that there are two lineages. Overall, COI, EF1α and ITS2 markers, when analyzed using a phylogenetic framework, supported a single lineage for M.clusoculis.

In the case of E.satellitia both mitochondrial markers show E.satellitiaDHJ03 to be paraphyletic to E.satellitiaDHJ02. Therefore two lineages of the three are supported at mitochondrial loci under Bayesian methods and none are supported at nuclear markers.

There is support for two lineages of B.perses based on both mitochondrial loci, but not with the two nuclear loci.

The absence of nuclear variation in light of evident mitochondrial variation can be due to three 3 major processes: 1) Incomplete lineage sorting of variation at nuclear loci; 2) hybridization between lineages upon secondary contact; or 3) undetected pseudogenes. I discuss how each process can influence our ability to delineate species.

I present evidence that eliminates NUMTs as a likely cause for the genetic patterns observed in each morpho-species. However, given the data and analyses performed to date, I cannot with certainty determine whether incomplete lineage sorting or hybridization is responsible for the relationship of genetic divergence patterns found at different loci. Thus, I highlight future avenues of research that can improve the delineation of cryptic species, especially when they are recently diverged.

1.4.1 Incomplete lineage sorting of nuclear loci

Discordance between mitochondrial and nuclear divergence patterns can occur when rates of speciation are greater than coalescent times of nuclear genes but not mitochondrial genes, leading to the retention of ancestral polymorphisms at nuclear loci

(Elias et al. 2007). Discordance is more likely if speciation is very recent (Knowles

2009), if speciation rates are high, or if populations have large with stable effective population sizes (Pamilo and Nei 1988). The animal mitochondrial genome, with few

exceptions, is maternally inherited, haploid and has poor repair mechanisms (Birky

2001). These characteristics reduce the effective population size of the mitochondrial genome to ¼ that of nuclear genes and results in higher mutation rates (Ballard and

Whitlock 2004). The mitochondrial genome’s reduced population size can lead to faster coalescent times, compared with diploid or multi-copy nuclear genes. In past studies, nuclear loci have shown little variation relative to DNA barcode data (Dasmahapatra et al. 2010, Clare 2011). Thus, the task of delineating recently radiated species by comparing lineages of nuclear and mitochondrial gene trees becomes less promising when species are recently diverged. As well as, discerning incomplete lineage sorting from hybridization becomes increasingly challenging when these species are also morphologically indistinguishable.

The identification of species that lack diagnostic morphological or ecological traits relies heavily on genetic data. If nuclear loci show polyphyletic or paraphyletic gene trees because of incomplete lineage sorting as well as lack morphological and natural history data, then there will be more support for a single species based on multiple independent lines of evidence. Several studies have shown that nuclear loci have actually represented taxonomically defined species more accurately than mitochondrial loci. For instance, five well-defined species of blue butterflies (Ithomiinae), in the

Amazonian basin, were polyphyletic when DNA barcoded, but showed reciprocal monophyly with respect to the EF1α gene region (Elias et al. 2007). Another example is within the genus Mechantis (Nymphalidae) (Dasmahapatra et al. 2010). Four cryptic species were proposed by DNA barcodes in this genus and wide-spread discordance

was found between two nuclear loci. However, AFLP data showed accordance with wing pattern morphology in one of the four provisional species and the authors concluded that DNA barcode divergences were not always biologically meaningful

(Dasmahapatra et al. 2010).

Many other studies have attempted to reduce this ambiguity in recently radiated species by using nuclear genetic markers often used in population genetics, like microsatellites and AFLP markers (Dasmahapatra et al. 2010, Hausdorf et al. 2011).

However, gene tree discordance can still exist even when using multi-locus approaches

(Pollard et al. 2006, Heckman et al. 2007). The difficulty in finding a suitable nuclear marker for recently radiated species has been augmented by statistical approaches, using coalescent theory, that estimate species trees despite incomplete lineage sorting of gene trees (Maddison& Knowles 2006).

1.4.2 Hybridization upon secondary contact

The process of speciation, in sexually reproducing organisms, can be linked to demographic factors and geological events. The segregation of populations by vicariance events or isolation by distance can create barriers to gene flow allowing populations to diverge by genetic drift and natural selection through time (Avise 2000).

As geological and ecological patterns change, so too can population structure.

Ecological or geological releases on migration can lead to historically allopatric populations becoming sympatric in current environments; these environments are recognized as secondary contact zones. If populations acquire traits that prevent gene flow (through pre or post-zygotic incompatibilities), then once conspecific populations

can become different species. If these same populations can reproduce viable, fit offspring upon secondary contact, stable hybrid zones, new hybrid species, or convergence into a single population can occur (Avise 2004). The use of mitochondrial

DNA for species delimitation is a double-edged sword; the same properties that enable faster coalescent times can also be misinterpreted to represent current reproductive isolation. Mitochondrial genomes, being haploid, maternally inherited and without recombination (in the majority of cases), retain levels of genetic divergence that accumulated in allopatry, despite current interbreeding in sympatry or parapatry.

Consequently, studying the nuclear genome is vital for understanding speciation- convergence processes. However, determining between current interbreeding and incomplete lineage sorting becomes increasingly more challenging when species are recently diverged. The statistical approaches utilizing coalescent theory mentioned previously are also being extended to differentiate between the two (Joly et al. 2009).

1.4.3 Under-detected pseudogenes

The comparison of paralogs, instead of orthologs, in DNA barcoding should be avoided (Moritz and Cicero 2004, Rubinoff 2006). The inadvertent amplification and sequencing of NUMTs can result in false sequence variation that can be mistaken for orthologous genetic divergence. Recent work on grasshoppers, a group with high levels of NUMTs, has revealed the potential for co-amplification of NUMTs in DNA barcoding (Song et al. 2008). NUMTs are almost always non-functional and can be removed from analyses by identifying obvious signs of non-functionality, such as stop codons and frameshift mutations (Buhay 2009) . However, if NUMTs are recently

derived they may still show functional signatures and can be misinterpreted as shallow genetic divergence. Functional signatures, in combination with PCR primer bias, especially if primers are degenerate, increase the possibility of targeting and analyzing

NUMTs as orthologous barcode sequences. One way to lower the probability of misinterpreting pseudogenes as orthologs is to sequence an additional mitochondrial marker that is distant to COI. To date, 90% of detected pseudogenes are below 500bp

(Richly and Leister 2004) making the amplification of a pseudogene that spans the

15,000-17,000bp mitochondrial genome rare. The 500bp cytb and 658bp COI fragments included in this study are about 7500bp apart from each other in the mitochondrial genome, which in Lepidoptera is approximately ~15,500bp (Liao et al. 2010). The fact that both gene regions show three lineages of U.belli increases the likelihood that orthologous, rather than paralogous, sequences are being analyzed in this study.

1.5 Conclusions

I found a lack of support from nuclear genes for multiple lineages identified using

DNA barcodes, although another mitochondrial marker supported the presence of separate lineages in most cases. The results to date do not support the hypothesis that

NUMTs are the cause for the observed mitochondrial-nuclear discordance. However, future avenues of research utilizing deep sequencing methodologies, like 454- pyrosequencing, is an additional way to identify and remove young pseudogenes from genetic analyses. If different mitochondrial sequence-types, hypothesized to be orthologous, are found within a single individual, this suggests sequence-types to be

NUMTs or mitochondrial heteroplasmy. Distinguishing between NUMTs and

mitochondrial heteroplasmy is beyond the scope of this study, but ultimately neither represents species-level diversity.

Further evidence is required to determine if incomplete lineage sorting or interbreeding upon secondary contact is the cause for discordance between divergence patterns at different loci. Additional sampling, encompassing the species’ ranges can shed light on the relationships of populations and past isolation events. For example, including all the populations of a given species can highlight if mtDNA lineages are more closely related to other allopatric populations than to each other in sympatry or parapatry. If this is the case, then secondary contact seems more likely than incipient speciation within the given environment. Before continuing the search for additional lines of evidence, either from different genetic markers or natural history characters, ensuring that sampling encompasses as much of a species range should be a priority.

Even so, distinguishing between incomplete lineage sorting and hybridization becomes increasingly more challenging as time of divergence decreases, especially when species lack intermediate morphology.

Several techniques are being developed to distinguish between incomplete lineage sorting and hybridization, such as Maximum Likelihood estimates and coalescent-based models (Joly et al. 2009,Cranston et al. 2009, McCormack et al.

2009). These techniques are promising avenues for research focused on recently diverged species and are of interest for future work on the species examined in this study.

Table 1.1 Larval food-plant data for barcode lineages of the three morpho-species of moths and butterfly used in this study.

Number of caught caterpillars in ACG food Morpho-species Larval food-plant plant summary Bardaxima persesDHJ02 Ochnaceae Cespedesia spathulata 55 Ouratea lucens 36 Quiinaceae Quiina amazonica 2 Bardaxima persesDHJ03 Ochnaceae Cespedesia spathulata 51 Ouratea lucens 32 Quiinaceae Quiina amazonica 2 Quiina macrophylla 1 Quiina schippii 2 Mimoides clusoculisDHJ01 Annonaceae Rollinia membranacea 29 Mimoides clusoculisDHJ02 Annonaceae Annona pruinosa 1 Annonaceae15017 1 Rollinia membranacea 19 Eumorpha satellitiaDHJ01 Vitaceae Cissus alata 10 Cissus fuliginea 12

Vitis tiliifolia 2 Eumorpha satellitiaDHJ02 Vitaceae Cissus alata 3 Cissus fuliginea 6 Cissus verticillata 2 Vitis tiliifolia 5 Eumorpha satellitiaDHJ03 Vitaceae Cissus alata 9 Cissus fuliginea 22 Cissus verticillata 1 Vitis tiliifolia 3

Table 1.2 Taxonomic sampling of the butterflies and moths used in this study. The table shows gene region success including sequence length and number of ambiguous bases and/or polymorphic positions [n].

cytb EF1α N/ COI Seq. Seq. Polymo Voucher Code Identification Seq. N N Lengt Lengt r Length h h phism 09-SRNP-44671 Bardaxima lucilinea 658 0 499 0 0 0 09-SRNP-44670 Bardaxima lucilinea 658 0 499 0 703 5 10-SRNP-73087 Bardaxima perses 658 0 499 0 751 1 10-SRNP-32297 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32272 Bardaxima perses 658 0 499 0 751 1 10-SRNP-32270 Bardaxima perses 658 0 499 0 751 1 10-SRNP-32269 Bardaxima perses 658 2 499 0 751 2 10-SRNP-32139 Bardaxima perses 658 0 499 0 0 0 10-SRNP-32138 Bardaxima perses 658 0 499 0 751 1 10-SRNP-32135 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32060 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32059 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32057 Bardaxima perses 658 0 499 0 751 1 10-SRNP-32052 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32051 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32050 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32044 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32043 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32031 Bardaxima perses 658 0 499 0 751 1 10-SRNP-32030 Bardaxima perses 658 0 499 0 751 1 10-SRNP-32028 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32027 Bardaxima perses 0 0 492 0 751 2 10-SRNP-32026 Bardaxima perses 643 0 492 0 751 1

10-SRNP-32025 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32024 Bardaxima perses 658 1 499 0 751 1 10-SRNP-32023 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32022 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32021 Bardaxima perses 658 0 499 0 751 2 10-SRNP-32020 Bardaxima perses 658 0 499 0 751 1 10-SRNP-32008 Bardaxima perses 658 0 499 0 751 1 10-SRNP-31979 Bardaxima perses 658 0 492 0 751 0 10-SRNP-31978 Bardaxima perses 658 0 499 0 751 2 10-SRNP-31946 Bardaxima perses 658 0 499 0 751 1 10-SRNP-31945 Bardaxima perses 658 0 499 0 751 1 10-SRNP-31905 Bardaxima perses 658 0 499 0 751 1 10-SRNP-31904 Bardaxima perses 658 0 499 0 751 2 07-SRNP-40778 Bardaxima persesDHJ02 658 0 390 0 751 2 07-SRNP-58689 Bardaxima persesDHJ02 658 0 499 0 751 2 07-SRNP-24022 Bardaxima persesDHJ02 658 0 499 0 751 2 07-SRNP-24082 Bardaxima persesDHJ02 658 0 437 0 751 2 07-SRNP-24059 Bardaxima persesDHJ02 658 2 499 0 751 2 07-SRNP-24080 Bardaxima persesDHJ02 658 0 436 0 751 1 08-SRNP-560 Bardaxima persesDHJ02 658 0 499 0 902 3 07-SRNP-23577 Bardaxima persesDHJ02 658 0 499 0 751 2 07-SRNP-66191 Bardaxima persesDHJ02 658 0 499 0 751 3 07-SRNP-24019 Bardaxima persesDHJ02 619 0 499 0 751 2 07-SRNP-58443 Bardaxima persesDHJ03 658 0 387 0 751 1 06-SRNP-40813 Bardaxima persesDHJ03 658 0 499 0 751 1 06-SRNP-5396 Bardaxima persesDHJ03 658 0 499 0 272 0 06-SRNP-23006 Bardaxima persesDHJ03 658 0 499 0 751 1 07-SRNP-40319 Bardaxima persesDHJ03 655 0 363 1 751 2 07-SRNP-58820 Bardaxima persesDHJ03 658 0 499 0 751 3 07-SRNP-58438 Bardaxima persesDHJ03 658 0 428 0 751 2 07-SRNP-58821 Bardaxima persesDHJ03 658 0 499 0 751 2 07-SRNP-23976 Bardaxima persesDHJ03 658 0 499 0 751 1 07-SRNP-59078 Bardaxima persesDHJ03 658 0 499 0 751 3 09-SRNP- Eumorpha anchemolus 658 0 475 0 367 4 105641

06-SRNP-15793 Eumorpha satellitiaDHJ01 658 0 0 0 1045 3 06-SRNP-56730 Eumorpha satellitiaDHJ01 658 0 499 0 1045 2 06-SRNP-15789 Eumorpha satellitiaDHJ01 658 0 499 0 367 1 06-SRNP-15726 Eumorpha satellitiaDHJ01 658 0 499 0 541 1 06-SRNP-15807 Eumorpha satellitiaDHJ01 658 0 499 0 541 2 06-SRNP-15761 Eumorpha satellitiaDHJ01 658 0 499 0 577 0 06-SRNP-56280 Eumorpha satellitiaDHJ01 658 0 499 0 872 3 06-SRNP-15995 Eumorpha satellitiaDHJ01 658 0 499 0 751 3 08-SRNP-13101 Eumorpha satellitiaDHJ01 658 0 499 0 1045 0 08-SRNP-13452 Eumorpha satellitiaDHJ01 658 0 499 0 751 1 05-SRNP-45896 Eumorpha satellitiaDHJ02 658 0 499 0 1045 2 05-SRNP-46265 Eumorpha satellitiaDHJ02 658 0 451 0 1045 4 05-SRNP-45880 Eumorpha satellitiaDHJ02 658 0 499 0 928 2 05-SRNP-45879 Eumorpha satellitiaDHJ02 658 0 499 0 1045 4 06-SRNP-56489 Eumorpha satellitiaDHJ02 658 0 499 0 873 4 03-SRNP-15400 Eumorpha satellitiaDHJ02 636 1 479 0 137 6 02-SRNP-9758 Eumorpha satellitiaDHJ02 645 0 499 0 541 4 05-SRNP-13504 Eumorpha satellitiaDHJ03 641 0 499 0 465 2 02-SRNP-16193 Eumorpha satellitiaDHJ03 658 0 499 0 316 0 06-SRNP-15739 Eumorpha satellitiaDHJ03 656 0 499 0 541 2 06-SRNP-15686 Eumorpha satellitiaDHJ03 658 0 499 0 494 0 05-SRNP-14107 Eumorpha satellitiaDHJ03 617 0 499 0 541 1 06-SRNP-16005 Eumorpha satellitiaDHJ03 658 0 499 0 1045 0 08-SRNP-13097 Eumorpha satellitiaDHJ03 658 0 499 0 751 0 09-SRNP-44264 Mimoides branchus 658 0 478 0 0 0 09-SRNP-44263 Mimoides branchus 658 0 0 0 610 4 09-SRNP-31201 Mimoides clusoculisDHJ01 658 0 247 0 541 1 08-SRNP-21563 Mimoides clusoculisDHJ01 658 0 478 0 541 0 08-SRNP-35020 Mimoides clusoculisDHJ01 658 0 0 0 541 0 08-SRNP-21739 Mimoides clusoculisDHJ01 658 0 0 0 541 0 05-SRNP-57568 Mimoides clusoculisDHJ01 658 0 0 0 541 0 03-SRNP-5827 Mimoides clusoculisDHJ01 658 0 499 0 541 1 03-SRNP-4163 Mimoides clusoculisDHJ01 658 0 0 0 541 0 03-SRNP-3155 Mimoides clusoculisDHJ01 658 0 0 0 541 0 05-SRNP-2206 Mimoides clusoculisDHJ01 658 0 0 0 541 0

05-SRNP-35079 Mimoides clusoculisDHJ01 658 0 0 0 1045 5 05-SRNP-35212 Mimoides clusoculisDHJ01 658 0 499 0 541 0 08-SRNP-1806 Mimoides clusoculisDHJ02 658 0 246 0 895 0 08-SRNP-2295 Mimoides clusoculisDHJ02 658 0 499 0 427 0 07-SRNP-55685 Mimoides clusoculisDHJ02 655 0 477 0 541 0 06-SRNP-56419 Mimoides clusoculisDHJ02 658 0 499 0 541 2 06-SRNP-56553 Mimoides clusoculisDHJ02 626 0 478 0 541 1 00-SRNP-9489 Mimoides clusoculisDHJ02 658 0 0 0 0 0 00-SRNP-9501 Mimoides clusoculisDHJ02 658 0 416 0 541 0 03-SRNP-3023 Mimoides clusoculisDHJ02 658 0 499 0 541 0 03-SRNP-3580 Mimoides clusoculisDHJ02 658 0 541 0

04-SRNP-1845 Mimoides clusoculisDHJ02 658 0 499 0 615 2

Table 1.3 Parameters used in Bayesian analyses of phylogeny for each moth or butterfly species and marker region. no.seq = number of sequences, ngen = number of generations until convergence, conv = standard deviation of split frequencies, burnin = number of trees discarded for consensus tree (25%).

Species COI Cytb EF1α Mimoides clusoculis no. seq 23 13 21 model HKY+I+G HKY JC+I+G ngen 1x10^6 1x10^6 1x10^6

conv <0.01 <0.01 <0.01 burnin 5000 5000 5000

Bardaxima perses no. seq 55 55 54 model GTR GTR+I F81 ngen 1x10^6 1x10^6 3.1X10^6 conv <0.01 <0.01 <0.01 burnin 5000 5000 155000

Eumorpha satellitia no. seq 25 24 24 model GTR+G HKY+G HKY+G

ngen 1x10^6 1x10^6 3.1X10^6 conv <0.01 <0.01 <0.01

burnin 5000 5000 155000

Table 1.4 Results of Pyrosequencing ITS2 from three morpho-species of moths and butterfly.

# unique # sequence- # sequences in sequence- types (>2 sequence-types (>2 MID Sample ID Species #Sequences types seq) seq) 1 05-SRNP-2206 Mimoides clusoculisDHJ01 94 63 7 31 3 05-SRNP-35212 Mimoides clusoculisDHJ01 79 43 10 36 4 03-SRNP-3155 Mimoides clusoculisDHJ01 104 68 9 36 5 03-SRNP-5827 Mimoides clusoculisDHJ01 65 41 7 24 6 03-SRNP-4163 Mimoides clusoculisDHJ01 125 92 12 33 7 05-SRNP-57568 Mimoides clusoculisDHJ01 171 107 13 64 8 08-SRNP-21739 Mimoides clusoculisDHJ01 60 39 7 21 11 09-SRNP-31201 Mimoides clusoculisDHJ01 143 82 21 61 13 03-SRNP-3580 Mimoides clusoculisDHJ02 186 96 19 90 14 03-SRNP-3019 Mimoides clusoculisDHJ02 80 53 8 27 16 06-SRNP-56553 Mimoides clusoculisDHJ02 152 105 11 47 17 00-SRNP-9501 Mimoides clusoculisDHJ02 74 55 8 19 18 00-SRNP-9489 Mimoides clusoculisDHJ02 176 122 13 54 19 07-SRNP-55685 Mimoides clusoculisDHJ02 128 72 17 56 20 06-SRNP-56419 Mimoides clusoculisDHJ02 72 41 11 31 21 08-SRNP-2295 Mimoides clusoculisDHJ02 46 30 3 16 totals 1755 1109 176 76 08-SRNP-13101 Eumorpha satellitiaDHJ01 62 60 1 20 78 06-SRNP-15789 Eumorpha satellitiaDHJ01 69 50 8 19 79 06-SRNP-15726 Eumorpha satellitiaDHJ01 84 73 5 11 80 06-SRNP-15807 Eumorpha satellitiaDHJ01 123 95 13 28 81 06-SRNP-15761 Eumorpha satellitiaDHJ01 102 69 10 33 83 06-SRNP-56280 Eumorpha satellitiaDHJ01 91 68 8 23 84 06-SRNP-15995 Eumorpha satellitiaDHJ01 74 64 5 10 85 06-SRNP-56489 Eumorpha satellitiaDHJ02 101 79 9 22 86 05-SRNP-45880 Eumorpha satellitiaDHJ02 91 69 9 22 89 05-SRNP-45879 Eumorpha satellitiaDHJ02 162 128 12 34

90 02-SRNP-9758 Eumorpha satellitiaDHJ02 148 112 16 36 91 03-SRNP-15400 Eumorpha satellitiaDHJ02 41 34 3 7 92 05-SRNP-13504 Eumorpha satellitiaDHJ03 66 60 3 6 93 08-SRNP-13097 Eumorpha satellitiaDHJ03 44 40 2 4 94 05-SRNP-14107 Eumorpha satellitiaDHJ03 84 60 8 24 96 06-SRNP-15686 Eumorpha satellitiaDHJ03 140 114 10 26 97 06-SRNP-15739 Eumorpha satellitiaDHJ03 130 108 9 22 98 06-SRNP-16005 Eumorpha satellitiaDHJ03 187 134 20 53 total 1799 1417 151 79 10-SRNP-31945 Bardaxima perses 28 25 1 3 80 10-SRNP-32020 Bardaxima perses 7 6 0 1 81 10-SRNP-32021 Bardaxima perses 24 18 2 6 82 10-SRNP-32022 Bardaxima perses 39 38 0 1 83 10-SRNP-32023 Bardaxima perses 26 22 1 4 84 10-SRNP-32028 Bardaxima perses 12 9 1 3 85 10-SRNP-32030 Bardaxima perses 32 22 3 10 87 10-SRNP-32050 Bardaxima perses 33 28 2 5 88 10-SRNP-32051 Bardaxima perses 18 13 2 5 89 10-SRNP-32052 Bardaxima perses 9 6 1 3 90 10-SRNP-32057 Bardaxima perses 30 29 0 1 91 10-SRNP-32059 Bardaxima perses 39 24 6 15 92 10-SRNP-32060 Bardaxima perses 44 35 4 9 93 10-SRNP-32135 Bardaxima perses 13 10 1 3 94 10-SRNP-32138 Bardaxima perses 17 10 3 7 97 10-SRNP-32270 Bardaxima perses 11 8 1 0 98 10-SRNP-32272 Bardaxima perses 19 18 0 1 total 401 321 21

Figure 1.1 NJ-tree of 46 Mimoides clusoculis COI sequences from BOLD. Sequence divergence was estimated using the Kimura two-parameter substitution model. Nodal support is based on 1000 bootstrap replicates. Numbers in parentheses indicate the number of individuals within each haplotype. COI lineages are represented by DHJ01and DHJ02 interm names.

Mimoides clusoculisDHJ01 (3) 65

56 Mimoides clusoculisDHJ01(3)

97 Mimoides clusoculisDHJ01(21)

71 Mimoides clusoculisDHJ01(1)

Mimoides clusoculisDHJ01 (2)

Mimoides clusoculisDHJ02 (14)

Mimoides clusoculisDHJ02 (1) 98 Mimoides clusoculisDHJ02 (1)

Mimoides branchus

0.01

Figure 1.2 NJ-tree of 130 Bardaxima perses COI sequences from BOLD. Sequence divergence was estimated using the Kimura two-parameter substitution model. Nodal support is based on 1000 bootstrap replicates. Numbers in parentheses indicate the number of individuals within each haplotype. COI lineages are represented by DHJ01and DHJ02 interm names.

Bardaxima persesDHJ01 (1)

Bardaxima persesDHJ01 (1) 77 Bardaxima persesDHJ01 (1)

Bardaxima persesDHJ01(1) 100 Bardaxima persesDHJ01 (60)

Bardaxima persesDHJ01 (1)

Bardaxima persesDHJ02(1)

Bardaxima persesDHJ02(4) 82 Bardaxima persesDHJ02 (1) 55

85 Bardaxima persesDHJ02 (34)

78 Bardaxima persesDHJ02 (25)

Bardaxima lucilinea

100 Bardaxima lucilinea

0.01

Figure 1.3 NJ-tree of 103 Eumorpha satellitia COI sequences from BOLD. Sequence divergence was estimated using the Kimura two-parameter substitution model. Nodal support is based on 1000 bootstrap replicates. Numbers in parentheses indicate the number of individuals within each haplotype. COI lineages are represented by DHJ01, DHJ02 and DHJ03 interm names. Eumorpha satellitiaDHJ03 (10) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (2) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (3) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (1) 81 Eumorpha satellitiaDHJ03 (5) Eumorpha satellitiaDHJ03 (1) Eumorpha satellitiaDHJ03 (2) 99 Eumorpha satellitiaDHJ03 (2) Eumorpha satellitiaDHJ02 (10) Eumorpha satellitiaDHJ02 (1) Eumorpha satellitiaDHJ02 (1) 97 Eumorpha satellitiaDHJ02 (4) Eumorpha satellitiaDHJ02 (1) Eumorpha satellitiaDHJ02 (1) Eumorpha satellitiaDHJ01 (1) Eumorpha satellitiaDHJ01 (1)

99 Eumorpha satellitiaDHJ01 (1) Eumorpha satellitiaDHJ01 (1) Eumorpha satellitiaDHJ01 (21) Eumorpha satellitiaDHJ01 (4) Eumorpha anchemolus

0.010.01 36

Figure 1.4 Bayesian trees constructed from COI, cytb, and EF1α, sequences of Mimoides clucsoculis. Posterior probabilities are presented >70% and scale bars represent number of substitutions per site.

a) COI b) cytb c) EF1a

77 66

94 M. clusoculisDHJ01 72 71

85 98 100

M. clusoculisDHJ02

0.01 0.05

0.05

Fig 1.1 Bayesian trees constructed from CO1, cytb, and EF1a, sequences Mimoides clucsoculis 37 showing the relationship between mitochondrial and nuclear markers. Posterior probabilities are presented >70% and scale bars represent number of substitutions per site. Figure 1.5 Bayesian trees constructed from COI, cytb, and EF1α, sequences of Bardaxima perses. Posterior probabilities are presented >70% and scale bars represent number of substitutions per site.

a) COI b) cytb c) EF1a

B. persesDHJ02 100 73

100

B. persesDHJ02 98

100

0.01

0.01 0.01 0.01

Fig 1.2 Bayesian trees constructed from CO1, cytb, and EF1a, sequences of Bardaxima perses 38 showing the relationship between mitochondrial and nuclear markers. Posterior probabilities are presented >70% and scale bars represent number of substitutions per site. Figure 1.6 Bayesian trees constructed from COI, cytb, and EF1α, sequences of Eumorpha satellitia. Posterior probabilities are presented >70% and scale bars represent number of substitutions per site.

a) COI b) cytb c) EF1a

84 E. satellitiaDHJ01

98 E. satellitiaDHJ02

95 74 E. satellitiaDHJ03

0.05 0.005

0.05

39 Fig 1.3 Bayesian trees constructed from CO1, cytb, and EF1a, sequences of Eumorpha satellitia showing the relationship between mitochondrial and nuclear markers. Posterior probabilities are presented >70% and scale bars represent number of substitutions per site. Figure 1.7 NJ analyses of full ITS2 sequence-types based on p-distances and nMDS distances among ITS2 intra-individual sequence-types of the 3 morpho-species. a) M. clusoculis b).B. perses c) E. satellitia. Provisional cryptic lineages are presented as blue (DHJ01), red (DHJ02) and green (DHJ03) circles. * B. perses NJ analysis is composed of forward direction sequences ranging from 250-400bp

0.001

0.001 Fig. 1.4 NJ analyses of full ITS2 sequence-types* based on p-distances and nMDS distances 40 among ITS2 intra-individual sequence-types of the 3 morpho-species; a) M. clusoculis b).B. perses c) E. satellitia. Putative cryptic lineages are presented as blue (DHJ01), red (DHJ02) and green (DHJ03) circles.

* B. perses NJ analysis is composed of forward direction sequences ranging from 250-400bp. 2 Mitochondrial and nuclear genetic divergence underscore morphologically cryptic species of Urbanus belli (Lepidoptera: Hesperiidae) within the Área de

Conservación Guanacaste

Abstract

The combination of DNA barcodes, morphology and natural history data has revealed several cases of cryptic species within Skipper butterflies. In this study, I investigate three distinct, non-overlapping DNA barcode lineages of Urbanus belli, in the

Área de Conservación Guanacaste (ACG), northwest Costa Rica. A multigene approach is applied which combines evidence from mitochondrial and nuclear genetic markers including; mitochondrial cytochrome b (cytb), nuclear Elongation Factor 1α

(EF1α) and ribosomal Internal Transcribed Spacer 2 (ITS2). I also test for the presence of the bacterial endosymbiont Wolbachia, known to manipulate reproduction in their arthropod hosts. I use the parallel sequencing capability of 454-pyrosequencing to identify ITS2 intra-individual variants and present the intra and inter-lineage relationships of ITS2 sequence-types of U.belli through non-metric multidimensional scaling.

I observed reciprocal monophyly for the three provisional lineages from cytb and

EF1α markers and polyphyly of two of the lineages based on ITS2 sequence-types due to intra-individual variation of ITS2 in two individuals. Wolbachia infections in two of the three lineages were discovered through multi-locus sequence typing, and highlight the potential for endosymbiosis to be a contributor to cryptic speciation. I also find several

inter-lineage compensatory basepair changes (CBC) within the secondary structure of

ITS2 which have been shown to corroborate sexually isolated species. Support from three additional loci, inter-lineage CBCs, habitat localization of one lineage and

Wolbachia infections suggest Urbanus belli is a cryptic complex of three species.This study shows the utility of using a multi-marker approach coupled with next-generation sequencing, as well as structural data analysis and interpretation methods to detect cryptic species.

2.1 Introduction

Identifying cryptic species is essential for not only socio-economic grounds but also for biodiversity estimates and conservation practices. Our inability to accurately detect cryptic species has led to costly invasive species outbreaks and sub-optimal conservation practices for species at risk (Geller 1999, Bidochka et al. 2001, Bickford et al. 2007). The identification of morphologically cryptic species requires integrative approaches that highlight species level relationships. The integration of various independent lines of evidence such as ecological distinctiveness, behavioral differences, and genetic divergences has underscored numerous cases of otherwise unrecognized species. Specifically, since the introduction of DNA barcoding in 2003 to a long-standing morphological and ecological inventory of the Área de Conservación

Guanacaste (ACG), northwest Costa Rica, numerous cases of cryptic species within the skipper butterfly family (Hesperiidae) have been discovered (Janzen et al. 2011).

Key discoveries in the Hesperiidae family include one of the most highly cited studies using DNA barcoding (Hebert et al. 2004a). For example, the Astraptes fulgerator species complex, comprised of 10 named cryptic species was discovered through the integration of DNA barcode divergences, distinct food-plants, caterpillar morphology and ecological preferences (Hebert et al. 2004a). Another interesting example is Perichares philetes which is now divided into four species described by DNA barcode divergences as well as differences in caterpillar and pupae morphology, and food-plants (Burns et al. 2008). Most recently, Burns et al (2010) discovered crypsis within Porphyrogenes peterwegei using DNA barcode divergences, caterpillar

developmental changes, food-plant conservatism and host-specific parasitism. The above discoveries were made possible because the ACG Lepidoptera inventory is comprehensively collecting and cataloging acilliary data, including DNA barcodes, host plants, fine-scale geographic and life zone data, and adult and caterpillar morphology

(http:janzen.sas.upenn.edu). In the examples above, natural history traits are key diagnostic characters in the verification and delimitation of cryptic species. What about species that show distinct, non-overlapping intraspecific DNA barcode lineages but do not show corroborating natural history traits? Are these barcode lineages simply intra- specific variation or do different lines of evidence need to be implemented to uncover these cryptic complexes? Urbanus belli (Hesperiidae) is an example of such a species in the ACG.

The genus Urbanus is currently polyphyletic (Steinhauser 1987, Warren et al.

2008). A phylogeny of the Eudamini tribe revealed two species U.dorantes and U. simplicius to have sister relationships with Thorybes pylades and (Autochoton longipennis + Achalarus albociliatus (U. dorantes + T. pylades))) respectively (Warren et al. 2008). However, the species U. belli is well categorized taxonomically and ecologically as a species that has become specialized on Asteraceae (daisy) host plants (Janzen et al. 2011). Urbanus belli constitutes three distinct DNA barcode lineages U.belliDHJ01, U.belliDHJ02, U.belliDHJ03 (Table B.1., Figure 2.1) separated from each other by ~3-5% sequence divergences at the COI barcode locus. However, these three DNA barcode lineages lack apparent diagnostic morphological and natural history characters. Adults of each lineage have overlapping morphological characters

including genitalic variation. In addition, host plant use overlaps and all three lineages exhibit sympatric ecological distributions with the exception of U.belliDHJ03, which is restricted to rain forest habitat (Table B.1 and Figure 2.2).

To investigate if U.belli is a complex of three cryptic species as suggested by the three COI lineages in the Neighbour-joining (NJ) tree that have between ~3-5% K2P sequence divergence (Figure 2.1), gene trees are generated from three additional molecular markers: a mitochondrial gene (cytochrome b; cytb), a protein-coding nuclear gene (elongation factor subunit I alpha; EF1α), and a nuclear ribosomal region (internal transcribed spacer region II; ITS2) and lineage patterns are compared on phylogenetic trees. Given the properties of ITS2, like high copy number and degree of concerted evolution acting on internal transcribed spacer heterogeneity (Onyabe and Conn 1999), pyrosequencing is utilized to sequence ITS2 and non-metric multidimensional scaling

(nMDS) is used to characterize intra-individual variation. Further analyses are performed using compensatory base changes (CBCs) in ITS2 secondary structure.

CBCs—when both nucleotides of a paired site mutate while the pairing itself is maintained (G-C to A-U) (Gutell et al. 1994) — have been shown to corroborate with sexual incompatibility of species (Mueller et al. 2007). If observed CBCs can also support these provisional species being sexually isolated. Lastly, the presense of

Wolbachia endosymbionts are tested using the Wolbachia surface protein (wsp) marker followed by Multi Locus Sequencing Typing (MLST) to identify the strain of Wolbachia

(Baldo et al. 2006).The MLST assay targets five gene regions from the Wolbachia genome; Cytochrome c oxidase subunit I (coxA), Conserved hypothetical protein(hpcA),

Glutamyl-tRNA(Gln), amidotransferase subunit B(gatB), Cell division protein(fstZ), and

Fructose-bisphophate aldolase (fbpA). The allele types at each locus are defined using the MLST database and combined to identify the type strain (http://www.mlst.net/).

Wolbachia are known to influence insect evolution by manipulating host reproduction.

The most commonly reported mechanism is cytoplasmic incompatibility (Bordenstein,

2003), which is the inability of infected males to reproduce successfully with uninfected females. A bi-directional infection of Wolbachia, in which different populations are fixed for different strains of Wolbachia, can act as a complete barrier to gene flow (Werren et al. 2008).

2.2 Methods

2.2.1 Specimens

Lepidoptera specimens were collected from the ACG as pupae on food-plants and were reared to adulthood and added to an on-going, comprehensive inventory of

Lepidoptera with ancilliary data including locality, host-plant species, sex, and parasitoid development (http:janzen.sas.upenn.edu). Fifty individuals of U.belli were selected from the Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert 2007) (Table B.1) for investigation with additional gene regions.

2.2.2 Molecular analysis

DNA was extracted from 52 specimens and specific protocols can be found in

Appendix D. PCR amplification and sequencing was performed for three markers; cytb,

EF1α and ITS2. All primer details can be found in Appendix D, Table D.1. Details of

PCR and Sanger sequencing protocols are provided in Chapter 1.

V3.1.5 (CodonCode, Dedham, MA, USA) software, aligned using CLUSTAL W and further manual inspection was done in MEGA 5.0 (Tamura et al. 2007). Sequences were exported in Nexus format. MrModelTest2.3 (Nylander, J. A. A. 2004) was used to find the best nucleotide substitution model prior to Bayesian analysis. Sequences from

Urbanus proteus, Urbanus esmeraldus, Urbanus evona, and Urbanus esta were generated using the same protocol as Chapter 1 and were used as outgroups (Table

B.1)

MrBayes v3.1.2 (Ronquist and Huelsenbeck 2003) was used to generate gene trees for each marker. Four Monte Carlo Markov chains and a temperature of 0.2 were used for each analysis. Trees were sampled every 100 generations and Bayesian posterior probabilities were estimated for each node.

Thirty-nine individuals were selected for 454-pyrosequencing analysis of ITS2.

For pyrosequencing protocols and ordination analysis details refer to Chapter 1.

Forward and reverse direction sequence-types of ITS2 that had at least 95% match in a

20bp overlap were assembled. Full length ITS2 sequences were aligned using MEGA

5.0 and maximum parsimony (MP) trees were generated in PAUP 4b 1.0 (Swofford, D.

L. 2003) with and without gaps as a fifth base. A heuristic search was performed with

tree bisection reconnection (TBR) branch swapping and 1,000 random taxon addition replicates, saving no more than 100 equally parsimonious trees per replicate. One thousand bootstrap replicates were performed and 50% majority rule trees were created. Nodes were collapsed below the 50% confidence interval and only bootstrap values above 50% confidence interval were included.

2.2.3 ITS2 secondary structure and compensatory base change analysis

Full length ITS2 intra-individual sequence-types were collapsed by 100% identity to reduce redundancy of the dataset using the CD-HIT web-server (Li and Godzik 2006)

(Appendix B). Secondary structure was determined for unique ITS2 sequence-types using the Vienna RNAfold Webserver (http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi). A

DNA parameter suggested by David Matthews (2004) was used with the default setting of a folding temperature at 37°C allowing for dangling energies on both sides of a helix in any case, using minimum free energy and partition function fold algorithms. The program 4SALE (Seibel et al. 2008) was used to align secondary structure and DNA sequences and estimate compensatory base changes (CBCs) between sequence- types.

2.2.4 Wolbachia assay

The presence of Wolbachia infection was established by a PCR test for the

Wolbachia surface protein (wsp) in leg tissue (Baldoet al. 2006). Refer to Chapter 1 for details on wsp PCR amplification and sequencing. If wsp PCR bands were present in some or all individuals, all specimens from that lineage underwent the more extensive

Multilocus Sequence Typing (MLST) assay developed by Baldo et al (2006) in order to identify the specific Wolbachia strain. The primers for the MLST loci can be found in

Appendix D, Table D.1. The same PCR reaction mix was used as the wsp marker and each marker was amplified using protocols provided in Baldo et al (2006). PCR band checks and Sanger sequencing protocols and editing are the same as described in

Chapter 1.

2.3 Results

2.3.1 Phylogenetic analysis of COI, cytb and EF1α

ITS2 Sanger-sequencing results are not included in this study because of their sequence heterogeneity and consequently imprecise base calling. ITS2 results are therefore analyzed using pyrosequencing analysis only (below). Table 2.2 summarizes specimen details and Table 2.3 provides the parameters used in each Bayesian analysis. The results of the Bayesian analyses of COI, cytb and EF1α show three, highly supported clades (Figure2.3). These clades are congruent with the proposed species boundaries suggested by neighbor-joining analysis of DNA barcodes

(Figure2.1). EF1α sequences less than 500bp were removed from the analysis because they clustered together and confounded the tree topology.

2.3.2 Analysis of ITS2 sequences

The 39 individuals successfully pyrosequenced for ITS2 produced 5,315 sequence reads which consisted of 303 sequence-types, after filtering (Table 2.4). The nMDS plot (Figure 2.4) shows distinct separation of U.belliDHJ02 from U.belliDHJ01

and U.belliDHJ03. Two clusters are observed for U.belliDHJ01, which highlights the level of intra-specific variability that is found within this lineage (also reflected in MP trees). Two individuals, 06-SRNP-46887_a, 06-SRNP-46891_d, of U.belliDHJ03 possess sequence-types that fall into the U.belliDHJ01 clusters. The alignment of ITS2 sequences with gaps treated as missing data had 28 parsimony informative characters

(Figure2.5a) while the ITS2 alignment with gaps treated as a fifth character had 41 parsimony-informative characters (Figure2.5b).The MP tree that includes gaps as fifth characters (CI = 0.853, RI 0.937) had 144 most parsimonious trees and the 50% majority-rule tree supports reciprocal monophyly of U.belliDHJ02 and shows

U.belliDHJ03 to be paraphyletic to U.belliDHJ01. The paraphyly is caused by the 2 sequence-types two mentioned above, 06-SRNP-46887_a and 06-SRNP-46891_d

(Figure 2.5b). When gaps are not considered as a fifth base the MP tree had 770 most parsimonious trees (CI =0.861, RI = 0.954) and the 50% majority-rule tree shows less than 50% support for the U.belliDHJ01 node (Figure 2.5a).

2.3.3 ITS2 secondary structure & compensatory base changes

The secondary structures of Urbanus belli sequence-types show the conserved

ITS2 structure found in Eukaryotic life including four helices (labeled I-IV Figure 2.6),

Helix III is the longest with a 5’ end GGU motif, as well as the U-U mismatch associated with ITS2 II helix in most Eukaryotes (Schultz et al. 2005)(Figure2.6). The CBC analysis identified 10-14 compensatory base pair changes among the three U.belli lineages in helices II and III (Table 2.5, Appendix B). Four CBCs were found between a single ITS2 sequence-type from individual 06-SRNP-46891_a of U.belliDHJ03 in helix III and four

other sequence-types 06-SRNP-46887_c, 05-SRNP-41753, 05-SRNP-42394, 06-

SRNP-46891_d (Table 2.5). The sequence-type 06-SRNP-46891_a, mentioned above, also clusters within the U. belliDHJ01 clade in the MP trees (Figure 2.5a,b).

2.3.4 Wolbachia Assays

16 individuals were positive for the wsp and MLST markers. This included 40%

(4/10) of individuals of U.belliDHJ01, 100% (12/12) of the individuals of U.belliDHJ03 and 0% (0/13) of U.belliDHJ02. I sequenced all PCR bands for wsp and MLST markers.

Sequences generated by extending the reverse primers for gatB, coxA, ftsZ, fbpA and wsp showed heterogeneous sequence chromatograms for both U.belliDHJ01 and

U.belliDHJ03. The hcpA marker showed heterogeneous sequence chromatograms for both forward and reverse primer sequences. In all cases, the homogeneous sequence read or the highest peak was used as the consensus sequence to search the wsp and

MLST database. The allele identities found from a BLAST search of each locus in the database were recorded in Table 2.6. All six loci matched known allelic profiles by 98%-

100% identity and the allelic profile resulted in Wolbachia strain 108 of Supergroup B.

Strain 108 was previously found in the Brangas felderi butterfly (Lycaenidae) in Morona-

Santiago, Ecuador (Behere et al. 2007, Russell et al. 2009).

2.4 Discussion

Complementary mitochondrial and nuclear evidence has been found for three lineages of Urbanus belli in the ACG (Figure 2.3., Figure 2.5). These results strongly suggest that U.belli is a cryptic complex of three species. Each lineage has reduced

gene flow to the point that mitochondrial and nuclear markers lack shared haplotypes between lineages, with a few exceptions of shared intra-individual sequence-types in

ITS2 (see below). The fact that all three lineages are geographically sympatric strengthens the case for species-level status because each lineage has the opportunity to interbreed yet does not. The members of the U.belli complex lack diagnostic morphological and natural history characters typically used for species discrimination.

However, members of the complex do possess other distinguishing traits such as the presence of Wolbachia infections and compensatory basepair changes in helices II and

III of the secondary structure of ITS2. Wolbachia infections can highlight possible factors contributing to the speciation process in this complex while ITS2 CBCs provide an additional line of evidence for sexual incompatibility between the lineages.

The number, size and location of rDNA arrays can vary within species and individuals (Alvarez and Wendel 2003) and therefore impact the marker’s phylogenetic utility. Concerted evolution is thought to homogenize rDNA arrays and strip out variability between repeats (Arnheim et al. 1980b, Hershkovitz et al. 1999). Internal transcribed spacer region 1 (ITS1) has confirmed COI lineages in provisional species of parasitoid flies (Diptera, Tachinidae) (Smith et al. 2006, Smith et al. 2007) and

Malagasy ants (Fisher and Smith 2008). In contrast, intra-individual variation has been observed in ITS1 sequences of the Belvosia Woodley provisional species complex and the Anochetus goodmani provisional species complex (Smith et al. 2006, Fisher and

Smith 2008). Both studies compare ITS1 and COI lineage patterns and conclude either hybridization or the retention of a shared ancestral polymorphism. Likewise, intra- individual variation was observed in sequences of ITS2 from all the U.belli specimens

used in this study. Previous studies have utilized cloning experiments to separate heterogeneous ITS2 sequences (Mayol and Rossello 2001) and in this sense pyrosequencing can be compared to a massive scale cloning experiment. A benefit to using pyrosequencing is the massive amount of sequences acquired. I obtained over

5000 sequences after filtering, which were between 200-400bp in length and resulted in over 300 sequence-types of ITS2.

Pyrosequencing, through the 454-Roche platform is not without limitations. One major drawback is the over and under base calling and delayed base calling which can lead to sequencing inaccuracies (Kircher and Kelso 2010). These inaccuracies are difficult to separate from the natural tendency of ITS2—as a non-coding region—to accumulate indels. I have used a rigorous filtering process to help eliminate pyrosequencing errors. Additionally, I only included sequence-types with two or more identical sequences in my analyses to ensure exclusion of random sequence errors. In addition, sequencing success was low from the reverse primer direction. I suspect this is due to the preferential sequencing of primer dimers or to secondary structure issues of ITS2. This limited the interpretation of ~250bp sequences in the forward direction for intra-individual variability and reduced the number of full length ITS2 sequence-types that could be used in the MP and CBC analysis. However, the nMDS results suggest that the ~250bp sequences adequately illustrate the level of genetic variability of ITS2 reflected in the MP analysis. The nMDS analyses identified sequence-types from the two individuals of U.belliDHJ03 (06-SRNP-46887_a, 06-SRNP-46891_d) that fall into the U.belliDHJ01cluster. This pattern is also reflected in the MP analyses. This overlap and polyphyly can be due to hybridization or incomplete lineage sorting of rDNA arrays.

The lack of complete homogenization of rDNA arrays is one major reason why studies aimed at analysis of cryptic species should not rely solely on ITS data (Alvarez and

Wendel 2003). For example, if an ancestral population is stable for multiple rDNA variants and a speciation event occurs, the effective population size of ITS2 in the descendent lineages can be very large because of the number of rDNA copies within an individual. Without concerted evolution, the time to coalescence for each descendent species would take much longer than single-copy nuclear markers or mitochondrial markers.Consequently, I am not surprised to find shared alleles of ITS2 when examining deep intra-individual variability. However, the support for three genetically divergent lineages based on EF1α suggests that the few overlapping ITS2 sequence- types represent ancestral polymorphisms rather than recent hybridization.

The presence of a single Wolbachia strain in U.belliDHJ01 andU.belliDHJ03, but absence of infection in U.belliDHJ02 suggests that unidirectional cytoplasmic incompatibility (uniCI) (Bordenstein, 2003) is a possible mechanism contributing to the speciation process between these lineages. As mentioned, uniCI is the inability of infected males to reproduce successfully with uninfected females. Theoretically, uniCI can only be a contributing factor to reproductive isolation because infected females can mate freely with uninfected males making uniCI unstable to migrants and insufficient to prevent gene flow (Werren et al. 2008). It is widely accepted that speciation arises due to the accumulation of multiple reproductive barriers (Coyne and Orr 1997).

Consequently, other factors contributing to reproductive isolation, such as ecological adaptations or mating behaviors caused by natural and sexual selection in conjunction

with uniCI can lead to speciation (Werren et al. 2008). The observation that

U.belliDHJ03 is ecologically restricted to rain forest could also be a contributing factor, in conjunction with Wolbachia infection, to the reproductive isolation of U.belliDHJ03 from U.belliDHJ01 and U.belliDHJ02, which inhabit dry and rain forest habitats. It has also been hypothesized that uniCI can reduce gene flow between populations indirectly.

Indirect evolutionary changes caused by CI include CBCs in the host nuclear genome, mitochondrial hitch-hicking and chromosome rearrangements (Bordenstein, 2003). All of these mechanisms reciprocally alter the genetic makeup of populations infected with

Wolbachia and can lead to pre or post-mating incompatibilities between infected and uninfected populations (Jaenike et al. 2006, Bordenstein 2003). However, it should be noted that the absence of Wolbachia can be the result of using somatic tissue, instead of reproductive tissue, as the primary source of DNA, which may decrease detection of

Wolbachia. As a result U.belliDHJ02 could be infected, but the somatic material tested could incorrectly test as ‘absent’. To date, somatic infections have been reported in species including Drosophila (Dobson et al, 1999) and have been proposed to increase the likelihood of horizontal transmission routes (Werren et al, 1995), There have been reported cases of infection being isolated to reproductive tissues in G. morsitans females (Dobson et al, 1999). To further investigate the role of Wolbachia and speciation within this complex, reproductive as well as somatic tissue should be analyzed.

Evidence for CBCs in II and III helices of ITS2 was found between U.belliDHJ01,

U.belliDHJ02, and U.belliDHJ03 (Table 2.5). As well as, four CBCs were found within the sequence-types of U.belliDHJ03 (Table 2.5). CBCs are crucial to preserve the

pairings required for helices that make up the core of the ITS2 secondary structure

(Coleman 2003). CBCs most likely have little causal relationship to speciation but they may indicate that adequate evolutionary time has elapsed to make a speciation event more likely (Coleman 2003). The number of CBCs between lineages depends on the degree of divergence, the sequence length, and on the CBC rate per site (Coleman

2003). As expected, the accumulation of CBCs in ITS2 secondary structure helices has been shown to correlate with closely related taxa being reproductively incompatible

(Coleman 2003, Mueller et al. 2007, Coleman 2009). The CBCs observed between the provisional species of U.belli support previous studies showing CBCs between two cryptic species of Altica (Coleoptera) and three new species in Paramacrobiotus

(Tardigrada) (Ruhl et al. 2010, Schill et al. 2010). The use of CBCs as a biological species identifier has been proposed in the literature (Coleman 2009), however CBCs have been absent in certain taxa, including the blue butterflies of the subgenus

Agrodiaetus, nine cryptic species of Anopheles longirostris, three species of

Euryakaina, and only 5.1% of 34 provisional species supported by ITS2 and COI data

(Wiemers et al. 2009, Alquezar et al. 2010,Miller et al. 2010, Smith et al. 2011). I conclude that the detection of CBCs in the U.belli complex is a distinguishing characteristic for species delineation, but CBCs cannot be used as a necessary criterion for species boundaries.The four CBCs found between ITS2 sequence-types within

U.belliDHJ03 correspond to the same two individuals (06-SRNP-46887_a, 06-SRNP-

46891_d) that also cluster into the U.belliiDHJ01 nMDS plot. As mentioned previously, this intra-individual variation is suggested to be due to the retention of ancestral

polymorphisms because the EF1α gene tree resulted in reciprocally monophyly of

U.belliDHJ01 and U.belliDHJ03.

Making use of the DNA barcode library to generate hypotheses for provisional boundaries of unrecognized species can allow researchers to allocate their resources efficiently. The discovery of the U.belli complex shows that by building upon DNA barcode data by comparing multiple gene trees, ITS2 secondary structure analysis and tests for the presence of Wolbachia endosymbionts; researchers can provide adequate evidence to detect provisional cryptic species.

Table 2.1 Urbanus belli species complex reared from wild-caught caterpillars in the Área de Conservación Guanacaste showing larval food-plant and ecosystems.

Characters U. belliDHJ01 U. belliDHJ02 U. belliDHJ03 Larval food plant

Asteraceae

C. Moraga 1658 1

Asteraceae 14541 3 1

Asteraceae 16762 1

Baltimora recta 2

Calea urticifolia 10 2

Clibadium leiocarpum 3 1 2 Clibadium pittieri 16 3 8 Clibadium surinamensis 3 1 2 Lasianthaea fruticosa 1

Melanthera aspera 68 40 3 Melanthera nivea 2 1

Otopappus verbesinoides 3

Salmea scandens 5 1

Verbesina ovatifolia 5

Vernonia tortuosa 1

Vernonia patens 1

Fabaceae

Viguiera dentata 1

Zexmenia virgulta 73 22 19 Clitoria falcata 1

Dry and rain Ecosystem Dry and rain forest Rain forest forest

Table 2.2 Taxonomic sampling of U.belli and gene region success.Sequence length and number of ambiguous bases and/or polymorphic positions [n] are included for each specimen.

COI cytb EF1α n/ Voucher Code Identification Seq. n Seq. n Seq. polymor- Length Length Length phism 08-SRNP-4727 Urbanus belliDHJ01 658 0 499 0 0 06-SRNP-47955 Urbanus belliDHJ01 658 0 499 0 316 0 06-SRNP-46570 Urbanus belliDHJ01 657 0 499 0 1030 5 06-SRNP-47304 Urbanus belliDHJ01 632 0 499 0 316 2 07-SRNP-41187 Urbanus belliDHJ01 642 1 499 0 316 2 08-SRNP-23800 Urbanus belliDHJ01 658 0 475 0 315 2 08-SRNP-5848 Urbanus belliDHJ01 658 0 456 0 316 5 08-SRNP-65935 Urbanus belliDHJ01 658 0 443 0 1045 2 08-SRNP-1439 Urbanus belliDHJ01 658 0 499 0 1030 1 08-SRNP-65153 Urbanus belliDHJ01 658 0 441 0 1045 1 07-SRNP-65582 Urbanus belliDHJ01 658 0 475 0 1045 8 07-SRNP-33232 Urbanus belliDHJ01 658 0 429 0 1045 5 07-SRNP-1119 Urbanus belliDHJ01 658 0 476 0 1045 2 07-SRNP-42421 Urbanus belliDHJ01 658 0 475 0 1045 2 07-SRNP-45090 Urbanus belliDHJ01 658 0 499 0 933 7 06-SRNP-47801 Urbanus belliDHJ02 597 0 499 0 1030 0 07-SRNP-30615 Urbanus belliDHJ02 658 0 465 0 541 3 07-SRNP-20318 Urbanus belliDHJ02 658 0 444 0 0 0 06-SRNP-18276 Urbanus belliDHJ02 658 0 499 0 0 0 07-SRNP-57868 Urbanus belliDHJ02 658 0 445 0 541 0 03-SRNP-12634.1 Urbanus belliDHJ02 658 0 499 0 0

06-SRNP-47816 Urbanus belliDHJ02 658 0 499 0 1030 2 07-SRNP-45071 Urbanus belliDHJ02 655 0 499 0 316 0 01-SRNP-4475 Urbanus belliDHJ02 658 0 499 0 316 1 06-SRNP-3621 Urbanus belliDHJ02 658 0 499 0 0

07-SRNP-40856 Urbanus belliDHJ02 658 0 499 0 930 0

07-SRNP-56547 Urbanus belliDHJ02 658 0 443 0 260 3 07-SRNP-56829 Urbanus belliDHJ02 658 0 446 0 0 0 07-SRNP-30613 Urbanus belliDHJ02 658 0 499 0 541 3 07-SRNP-40676 Urbanus belliDHJ02 658 0 474 0 541 1 06-SRNP-47817 Urbanus belliDHJ02 658 0 499 0 0

06-SRNP-46460 Urbanus belliDHJ02 657 0 499 0 316 0 06-SRNP-46639 Urbanus belliDHJ02 658 0 499 0 541 1 06-SRNP-6511 Urbanus belliDHJ02 657 0 499 0 316 1 06-SRNP-46572 Urbanus belliDHJ02 658 0 499 0 1030 3 05-SRNP-1832 Urbanus belliDHJ02 658 0 499 0 0

02-SRNP-954 Urbanus belliDHJ02 658 0 499 0 316 1 06-SRNP-65065 Urbanus belliDHJ03 649 0 499 0 1045 4 07-SRNP-33182 Urbanus belliDHJ03 648 0 499 0 1045 3 08-SRNP-65993 Urbanus belliDHJ03 658 0 499 0 1045 1 08-SRNP-66028 Urbanus belliDHJ03 658 0 499 0 1045 4 07-SRNP-33183 Urbanus belliDHJ03 658 0 499 0 541 0 07-SRNP-33184 Urbanus belliDHJ03 658 0 499 0 1045 5 07-SRNP-287 Urbanus belliDHJ03 658 0 499 0 316 0 07-SRNP-40761 Urbanus belliDHJ03 655 0 499 0 1045 1 06-SRNP-46887 Urbanus belliDHJ03 657 0 499 0 316 5 06-SRNP-46891 Urbanus belliDHJ03 657 0 499 0 1030 11 05-SRNP-40545 Urbanus belliDHJ03 658 0 499 0 541 0 05-SRNP-41753 Urbanus belliDHJ03 658 0 499 0 316 3 06-SRNP-43129 Urbanus belliDHJ03 381 0 499 0 1030 2 07-SRNP-57988 Urbanus evona 658 0 499 0 1030 2 08-SRNP-71742 Urbanus proteus 658 0 499 0 313 0 04-SRNP-15286 Urbanus evona 658 0 499 1 1030 3 05-SRNP-66411 Urbanus evona 658 0 499 0 1030 0 06-SRNP-1984 Urbanus esta 658 0 499 0 1030 6 07-SRNP-1369 Urbanus proteus 658 0 499 0 316 2 07-SRNP-56430 Urbanus esta 658 0 499 0 1030 3 07-SRNP-57861 Urbanus esmeraldus 658 0 499 0 888 3 07-SRNP-57862 Urbanus esmeraldus 658 0 499 0 316 1 08-SRNP-71995 Urbanus proteus 658 0 499 0 888 4

Table 2.3 Parameters used in Bayesian analyses of phylogeny for U.belli for each marker region. no.seq = number of sequences, ngen = number of generations until convergence, conv = standard deviation of split frequencies, burnin = number of trees discarded for consensus tree (25%).

COI cytb EF1α no. seq 56 54 23 model GTR+G GTR+G K80+G ngen 1x10^6 1x10^6 1x10^6 conv <0.01 <0.01 <0.01 burnin 1250 1250 1250

Table 2.4 Results of Pyrosequencing ITS2 from the U. belli complex.

# unique # sequences in # sequence- # sequence- sequence-types (>2 MID Sample ID Species Sequences types types (>2 seq) seq) 22 07-SRNP-30614 Urbanus belliDHJ01 133 117 7 16 24 07-SRNP-33232 Urbanus belliDHJ01 147 136 6 11 26 08-SRNP-1439 Urbanus belliDHJ01 207 172 15 35 27 08-SRNP-65935 Urbanus belliDHJ01 66 46 8 20 28 08-SRNP-5848 Urbanus belliDHJ01 174 150 11 24 29 08-SRNP-23800 Urbanus belliDHJ01 142 117 9 25 30 08-SRNP-24278 Urbanus belliDHJ01 183 137 18 46 52 07-SRNP-41187 Urbanus belliDHJ01 120 91 13 29 53 06-SRNP-47304 Urbanus belliDHJ01 80 63 8 17 54 06-SRNP-47955 Urbanus belliDHJ01 170 117 23 53 55 06-SRNP-46570 Urbanus belliDHJ01 143 115 13 28 56 08-SRNP-4727 Urbanus belliDHJ01 43 36 3 7 31 06-SRNP-18276 Urbanus belliDHJ02 106 90 8 16 32 06-SRNP-46572 Urbanus belliDHJ02 151 120 14 31 33 07-SRNP-30615 Urbanus belliDHJ02 179 132 20 47 34 07-SRNP-30613 Urbanus belliDHJ02 233 189 17 44 37 07-SRNP-20318 Urbanus belliDHJ02 30 24 3 6 38 07-SRNP-57868 Urbanus belliDHJ02 56 50 3 6 39 07-SRNP-56547 Urbanus belliDHJ02 82 73 4 9 40 07-SRNP-56829 Urbanus belliDHJ02 322 266 23 56 57 07-SRNP-45071 Urbanus belliDHJ02 129 109 8 10 61 06-SRNP-46572 Urbanus belliDHJ02 149 109 11 40 64 06-SRNP-47801 Urbanus belliDHJ02 240 166 30 74 65 06-SRNP-46460 Urbanus belliDHJ02 147 115 14 32 68 05-SRNP-1832 Urbanus belliDHJ02 4 4 0 0 69 01-SRNP-4475 Urbanus belliDHJ02 74 68 3 6

41 05-SRNP-41753 Urbanus belliDHJ03 164 125 17 39 42 05-SRNP-40545 Urbanus belliDHJ03 108 88 7 20 43 06-SRNP-65065 Urbanus belliDHJ03 11 11 0 0 45 07-SRNP-40761 Urbanus belliDHJ03 144 93 21 51 46 07-SRNP-33184 Urbanus belliDHJ03 169 118 18 51 47 07-SRNP-33183 Urbanus belliDHJ03 101 74 11 27 48 07-SRNP-33182 Urbanus belliDHJ03 117 80 17 37 49 08-SRNP-66028 Urbanus belliDHJ03 106 76 10 30 50 08-SRNP-65993 Urbanus belliDHJ03 156 126 13 30 70 06-SRNP-43129 Urbanus belliDHJ03 134 91 17 34 71 06-SRNP-46891 Urbanus belliDHJ03 190 156 11 34 72 06-SRNP-46887 Urbanus belliDHJ03 293 237 26 56 73 05-SRNP-42394 Urbanus belliDHJ03 112 87 11 25

Table 2.5 CBC matrix showing the number of compensatory base changes within and between each provisional species.

DHJ01 DHJ02 DHJ03 DHJ01 0 DHJ02 17 0 DHJ03 10 12 4

Table 2.6 Wolbachia BLAST results from the wsp and MLST database for the five markers: coxA, hpcA, gatB, fstZ, and fbpA. The chart includes the allele type that was found in the BLAST search and the percentage identity match in the databases resulting in the Wolbachia strain 108 of Supergroup B.

% Identity Match in WSP & MLST Marker Allele Database wsp 115 100% gatB 71 98% coxA 67 100% ftsZ 65 99% hcpA 74 99% fbpA 6 98%

Figure 2.1 NJ-tree of 299 Urbanus belli COI sequences from BOLD. Sequence divergence was estimated using the Kimura two-parameter substitution model. Nodal support is based on 1000 bootstrap replicates. Numbers in parentheses indicate the number of individuals within each haplotype. Detailed data for specimens can be found in Table 2.1.

Urbanus belliDHJ01 (4) Urbanus belliDHJ01 (4) Urbanus belliDHJ01 (2) Urbanus belliDHJ01 belliDHJ01 (2) (11) Urbanus belliDHJ01 (167) 99 Urbanus belliDHJ01 (3)

87 Urbanus belliDHJ01 (2)

Urbanus belliDHJ03 (1) Urbanus belliDHJ03 (28) 98 Urbanus belliDHJ03 (2) 78 Urbanus belliDHJ03 (1) Urbanus belliDHJ03 (1) Urbanus belliDHJ02 (1) Urbanus belliDHJ02 (1) 99 Urbanus belliDHJ02 (9) Urbanus belliDHJ02 (1) Urbanus belliDHJ02 (1) Urbanus belliDHJ02 (4) Urbanus belliDHJ02 (53) Urbanus belliDHJ02 (1) Urbanus belliDHJ02 (2) Urbanus belliDHJ02 (1) Urbanus belliDHJ02 (1) Urbanus proteus Urbanus esta 98 Urbanus evona

0.01

Figure 2.2 A map of a part of the ACG showing life zones and the distribution of the Urbanus belli complex. The map shows U.belliDHJ03 to be restricted to rain forest habitat.

U. belliDHJ01 U. belliDHJ02 U. belliDHJ03 Tropical submontane evergreen forest Evergreen seasonal lowland forest subtropical Rain – Cloud forest Coastal rainforest Lowland deciduous forest Semi deciduous –deciduous forest Lowland semi deciduous forest Mangrove forest Herbaceous marshes Marshes and reed beds of typha Open savanna grasses Wooded savannah Shrub vegetation with isolated clumps Alluvial tropical rainforest vegetation

Figure 2.3 Bayesian trees constructed from COI, cytb, and EF1α sequences of Urbanus belli. Posterior probabilities >70% are presented and scale bars represent substitutions per site.

(a)COI (b) Cytb (c) EF1a

100 100 100 DHJ02

100 100 100 DHJ01

100

DHJ03 100 100 0.02 0.2

0.2 0.2 0.2 0.2

Figure 2.4 nMDS graph showing the intra-individual variation of ITS2 in the U.belli complex. The plot shows the distinct cluster of U.belliDHJ02, the two clusters of U.belliDHJ01 and shared sequence-types betweenU.belliDHJ03with U.belliDHJ01.

U.belliDHJ01 U.belliDHJ02 U.belliDHJ03

Figure 2.5 Maximum Parsimony cladogram constructed from ITS2 sequences of the U.belli complex. Lineages are presented as blue (DHJ01), red (DHJ02), and yellow (DHJ01) circles. Bootstrap values above 70% are indicated. (a) gaps are coded as a fifth character. (b) gaps are not considered.The inclusion/exclusion of gaps has little impact on topology but does affect the level of node support.

Figure 2.6 The conserved ITS2 secondary structure for full-length sequence-types of the Urbanus belli complex. Helices are numbered from I-IV. The U-U mismatch typically found in Eukaryotes is outlined with a black circle in helix II. The complete structure represents the 51% consensus of aligned structures with gaps.Degree of secondary structure conservation is displayed in colour gradesfrom green (conserved) to red (not conserved).

3 Introgression through male gene flow between cryptic lineages of the

Imperial Moth (Eacles imperialis) in the Área de Conservación Guanacaste:

Evidence from morphology, ecology and multiple gene regions.

Abstract

DNA barcodes have underscored cryptic species diversity in numerous taxa that also have ecological, behavioral and molecular support. This study examines a provisional pair of cryptic Eacles imperialis species that show deep DNA barcode divergences, habitat preferences and minute morphological differences within the Área de Conservación Guanacaste. Phylogenetic analyses of several gene regions from specimens collected throughout the species Nearctic-Neotropical distribution illustrate that the two provisional cryptic lineages within the ACG have most likely interbred after secondary contact. I propose several explanations for the on-going relationship between mitochondrial lineages and habitat preferences despite gene flow. I propose that this relationship is maintained by male-dispersal biases and linkages between the mitochondrial genome and female inherited traits for oviposition preference.

3.1 Introduction

The mitochondrial genome (mtDNA) has played a vital role in the study of species-level phylogenies, phylogeography and taxonomy. MtDNA is appealing for such analyses because it is fast evolving compared to nuclear loci and is easy to PCR amplify. Moreover, the mitochondrial genome is thought to have ¼ the coalescence time of nuclear genes because of its haploid, maternal inheritance (Ballard and Whitlock

2004). In addition, high copy number and conserved mt-gene regions allow for nearly universal primer design for PCR amplification. However, mtDNA can mislead researchers interested in delimiting species if processes such as nuclear-mitochondrial pseudogenes (NUMTs), introgressive hybridization and incomplete lineage sorting are not recognized. Interestingly, these processes, when recognized, can delimit species and shed light on evolutionary pathways of speciation (McGuire et al. 2007).

The DNA barcode for animal life is a 658 bp region of the cytochrome c oxidase I

(COI) gene from the mitochondrial genome (Hebert et al. 2003b). DNA barcodes have been widely successful as a taxonomic tool in identifying specimens belonging to described species. However, the use of DNA barcodes to identify unrecognized species is limited, mainly for the reasons state above, that under certain conditions, mtDNA may not reflect species boundaries (Skibinski et al. 1994, Bensasson et al. 2001, Ballard and

Whitlock 2004, McGuire et al. 2007). Nonetheless, intraspecific barcode lineages have underscored unrecognized species diversity in many taxa including, but not limited to bats, fish, flies, and butterflies and moths (Hebert et al. 2004a, Smith et al. 2007, Ward et al. 2008, Clare 2011). These previously unrecognized species were identified through corroboration of DNA barcode divergences with a combination of other biological

properties such as overseen morphological distinctiveness, habitat preferences, larval- food plant differences and genetic divergence patterns.

Many of the aforementioned investigations were done in the Área de

Conservación Guanacaste (ACG) in northwest Costa Rica and as a result the ACG has become a central site for studying unappreciated biodiversity (Janzen et al. 2009).The

ACG is a 163,000 ha UNESCO World Heritage Reserve (Janzen et al. 2005). The conservation project has restored primary and secondary forests from 9 Life Zones, including dry, rain and cloud forest. The conservation area covers 2% of the country and contains approximately 230,000 species, which is about 65% of species in Costa Rica and 2.6% of the world’s biodiversity (Janzen et al. 2009). The diversity of habitat types and relatively recent colonization of species can result in distinct lineages being confined to small areas and elevation zones. This adds to the complexity of investigating hidden species diversity in the ACG.

Since 1978, a comprehensive inventory has been created to catalog Lepidoptera species, their larval food plants, and parasitoids (Janzen et al. 2009). In 2003, this long- standing inventory became a major test project for the utility of DNA barcoding (Hebert et al. 2004a, Hajibabaei et al. 2006). Subsequently, DNA barcoding has been integrated into the inventory workflow to catalog biodiversity (Janzen et al. 2005, Janzen et al.

2009). In 2009, a comprehensive review of DNA barcode results from this inventory showed that 12% (340/2810) of lepidopteran morpho-species have intraspecific COI lineages. Approximately 53% (179 /340) of these lineages have morphological or ecological support which in many cases has been used to discover new provisional

species (Janzen et al. 2009). For example, Astraptes fulgerator (Hesperiidae), initially a single morpho-species, is now 10 named species based on DNA barcode divergences, distinct food-plants, caterpillar morphology and ecological preferences (Hebert et al.

2004a, Brower 2010). Perichares philetes (Hesperiidae) is another example of a single morpho-species that is now divided into four provisional species based on DNA barcode divergences, caterpillar morphology and distinct food-plants (Burns et al. 2008).

In the present study I investigate a provisional cryptic species complex of

Lepidoptera collected in the ACG, Eacles imperialis (Saturniidae). DNA barcodes show deep sequence divergence (7.4%) between two major E. imperialis lineages that are also linked to distinct larval-food plants and dry forest and rain forest habitat types

(Figure 3.1). The two lineages, E. imperialisDHJ01 (rain forest type) and E. imperialisDHJ02 (dry forest type) also differ with respect to their mass of male genitalia

(Rodolphe Rougerie, unpublished data). Eacles imperialis is a well studied, morphologically polymorphic species that has a broad, Neactic-Neotropical distribution

(Lemaire 1988). Many subspecies have been described based on wing pattern morphology and geographic locality (Lemaire 1988). The objective of this study is to determine the relationship between the two ACG lineages. In light of the species’ broad distribution, I also expand my sampling to encompass allopatrically distributed populations of E. imperialis.Given the level of COI sequence divergence, ecological preferences and minute morphological differences, I predict reproductive isolation and a lack of gene flow between the two ACG lineages. This study investigates additional gene regions to determine if the two COI lineages are reflected in the mitochondrial and nuclear genome. I examine an additional mitochondrial locus, cytochrome b (cytb) and

two bi-parentally inherited nuclear loci, Elongation factor I subunit alpha (EF1α) and ribosomal internal transcribed spacer region II (ITS2) ) and lineage patterns are compared on phylogenetic trees A test for the presence of Wolbachia endosymbionts is performed using Wolbachia surface protein (wsp) marker (Baldo et al. 2006). Wolbachia can cause reproductive incompatibility between infected and uninfected lineages or lineages infected with different Wolbachia strains. This can contribute to the speciation process of arthropod hosts by causing sexual isolation among populations (Werren et al. 2008).

3.2 Methods

3.2.1 Sampling

Specimens used in this study were wild-caught as caterpillars and reared to adulthood as a part of the Lepidoptera Inventory of the ACG. ACG specimens were collected by Dan Janzen, Winnie Hallwachs and 30 parataxonomists. Leg tissue from

40 specimens, 20 from each E. imperialisDHJ01 and E. imperialisDHJ02, were selected for DNA sequence analyses in this study (Table C.1). E. imperialis were collected from dry and rain forest habitats in the ACG (Figure 3.1, Table C.1). I also selected 167 E. imperialis individuals from allopatrically distributed populations for which there was archived DNA or leg tissue at the Canadian Center for DNA Barcoding (CCDB). All specimens can be found on the Barcode of Life Data Systems (BOLD)

(www.barcodinglife.org). The 167 adult specimens were collected by light trapping.

Available collection data for all specimens used in this study can be found in Table C.1.

3.2.2 Molecular analysis

For our initial investigation of E. imperialis from the ACG, I sequenced EF1α and

ITS2 from 40 individuals from rain forest and dry forest, respectively and a subset of 20 individuals were amplified for cytb (Table 3.2). All primer details can be found in

Appendix D, Table D.1. Details on PCR protocols including reaction mixtures, thermocycling conditions, as well as agarose gel PCR checks and Sanger sequencing protocols are described in Chapter 1.

The initial analysis focused solely on ACG specimens. EF1α sequences were heterogeneous, showing double peaks in sequence chromatograms. Consequently polymorphic bases were scored using the IUPAC code for ambiguous bases (R,M,Y,S).

ITS2 sequences showed intra-individual heterogeneity and low quality, and are not included in this study. Instead, the evolutionary patterns of ITS2 were investigated using next-generation pyrosequencing technology and non-metric multidimensional scaling.

Protocols for next-generation sequencing and non-metric multidimensional scaling can be found Chapter 1.

Sequences were edited using CodonCode Sequence V3.1.5 (CodonCode,

Dedham, MA, USA) software, aligned using CLUSTAL W and manually inspected in

MEGA 5.0 (Tamura et al. 2007). Mean number of Kimura-2-parameter distances within and between groups were calculated in MEGA 5.0 for COI, cytb, EF1α and pairwise distances within and between groups were calculated for ITS2 (Tamura et al. 2007).

Groups were chosen based on COI divergence, locality and previously defined subspecies. Two specimens of Eacles masoni (07-SRNP-110342, 08-SRNP-105092)

were chosen as outgroups because the species is closely related and had available tissue for molecular analysis. Sequences were exported in Nexus format.

MrModelTest2.3 (Nylander, J. A. A. 2004) was used to find the best nucleotide substitution model for each Bayesian analysis. MrBayesv3.1.2 (Ronquist and

Huelsenbeck 2003) was used to generate phylogenetic trees for each marker. Four

Monte Carlo Markov chains and a temperature of 0.2 were used for each analysis.

Trees were sampled every 100 generations.

To further understand the evolutionary relationship between the two ACG lineages of E. imperialis, sampling was expanded to include allopatrically distributed populations of this species (Table C.1). EF1α and ITS2 were sequenced using Sanger sequencing mentioned previously. PHASE 2.1 (Stephens et al. 2001) was used to reconstruct haplotypes from unphased genotypes of EF1α. PHASE2.1 uses a Markov chain–Monte Carlo (MCMC) algorithm to reconstruct haplotypes. Default settings were

100 main iterations, 1 thinning interval, 100 burn-in iterations and a confidence probability threshold of 0.80 (Table 3.2). Mean number of Kimura-2-parameter distances within and between groups were calculated in MEGA 5.0 for COI, and EF1α.

ITS2 sequence heterogeneity was observed in all individuals of E. imperialis regardless of geographical locality. Sequences were trimmed when nucleotides became ambiguous. Consequently, character-based analysis was utilized to determine the level of similarity/differences between sequences.

3.3 Results

The first analysis focused solely on specimens from the ACG. The same two lineages were identified with both COI and cytb and had similar levels of inter-lineage sequence divergence; approximately 7.4% and 7.8%, respectively (Table 3.5).

However, individuals from the two mitochondrial lineages showed very little sequence divergence at EF1α, approximately 0.1%.(Figure 3.2). Sixty-three individuals from the

ACG were successfully pyrosequenced for ITS2 and produced 4,478 sequence reads which consisted of 318 sequence-types, after filtering (Table3.3). ITS2 sequences from individuals in different mtDNA lineages also showed little sequence divergence, approximately 0.72% (Table 3.5). This pattern is also reflected in the nMDS plot which shows a single cluster of sequence-types (Figure 3.3). In addition, wsp PCR bands were absent in all specimens in this study and I cannot make conclusions about the presence of Wolbachia in these specimens.

When I extended my analysis to include allopatrically distributed populations, the

COI phylogeny showed that populations from North America and South America form two major groups (Figure 3.4). In addition, most lineages within each group have limited geographical distributions and corresponed to previously described subspecies.

Overall, mean sequence divergence was 0.05 +/- 0.005 nucleotide substitutions per site or approximately 5% sequence divergence. The greatest COI sequence divergence was

7.7%, between the E. imperialis decoris population from Guatemala and E. imperialisDHJ02 from the ACG (Table 3.6). The two ACG lineages fall into separate

North (E. imperialisDHJ01—rain forest form) and South (E. imperialisDHJ02 – dry forest

form) American groups (Figure 3.4), demonstrating long-standing COI divergence between the two lineages.

There was lower genetic variation in EF1α compared to COI (Table 3.6). No clear

North and South American groupings are observed between geography and lineages identified using EF1α although E. imperialis imperialis from the USA and Canada form a separate cluster as does E. imperialis magnifica/opaca from Brazil and Argentina

(Figure 3.5). The ITS2 sequences that were long enough to be informative in this study showed character differences between North and South American groups as suggested by COI, except for E. imperialisDHJ02 and E. imperialis puirensis lineages, which showed more similarity to North American individuals (Figure 3.6).

3.4 Discussion

The two ACG lineages of E. imperialis differ in habitat type, larval food plants, and mass of male genitalia. These characteristics as well as deep COI divergences suggest unrecognized species diversity. Thus, I expected congruent genetic divergence patterns for these two lineages in the nuclear loci, EF1α and ITS2. However, our results showed little variation at either locus, with shared haplotypes between lineages and low sequence divergence.

When the analysis was expanded to include allopatric populations of E. imperialis, the COI phylogeny revealed highly supported North and South American groupings, as well as associations between most subspecies classifications, COI divergences and geographical locality (Figure 3.4). I discovered that COI sequences of

E. imperialisDHJ02 and E. imperialisDHJ01 fell separately into North and South

American groupings showing that the two lineages are not sister taxa, and suggests that they were once separated geographically. The bridging of North and South America by the rising of the Isthmus of Panama is one potential geological event that could bring these lineages into secondary contact in Central America. The Isthmus of Panama, between Guatemala and Colombia, has only been an inhabitable land mass for approximately 9-3 million years (Coates 1996). The Isthmus of Panama serves as a land bridge between North and South America, permitting movements of plant and animal species both northward and southward (Coates 1996). Future work investigating coalescent times of lineages in combination with the timing of geological events can shed light on this phylogeographic hypothesis.

Allopatric populations of E.imperialis showed little sequence variation at the EF1α locus, suggesting that the lack of sequence variation found between the two ACG lineages could be due to incomplete lineage sorting (Figure 3.5). However, some structure is observed and if E.imperialisDHJ02 and E. imperialis piurensis are ignored, the South American group becomes paraphyletic to the North American group. In either case, EF1α is discordant with the COI tree which shows deep North and South

American groupings. On the contrary, the preliminary ITS2 results corroborate an ancestral North and South American split, but shows E.imperialisDHJ01,

E.imperialisDHJ02 and E. imperialis piurensis to be most similar to ITS2 sequences from individuals found in North America. These results suggest that the two ACG lineages are in secondary contact in the ACG and interbreeding, rather than evolving parapatrically in the absence of lineage sorting at the ITS2 locus. The similarity of

E.imperialisDHJ02 and E. imperialis piurensis ITS2 sequences to the ITS2 sequences

of North American individuals suggests that E.imperialisDHJ01 ITS2 alleles are introgressing into E.imperialisDHJ02 and E. imperialis piurensis populations. Both

E.imperialisDHJ02 and E. imperialis piurensis populations inhabit dry forest habitat and

I suggest the two lineages to be linked through a dry forest corridor northwest of the

Andean ridge. E. imperialis piurensis is also on average 3.4% (Table 3.6) divergent the at COI locus from other Peruvian individuals collected from the Amazonian rain forest region of Peru, providing further evidence for a dry forest adaptation in individuals northwest of the Andean ridge. Denser sampling in the proposed corridor can shed light on levels of connectivity between these subspecies/populations.

If interbreeding is the most parsimonious explanation for discordance genetic divergence patterns between the two ACG lineages then an explanation is required to explain how mitochondrial sequence divergence maintained and is linked to habitat type. The mitochondrial genome is maternally inherited and is therefore linked to female evolutionary history (Ballard and Whitlock 2004). Female Lepidoptera are also the heterogametic sex, possessing the WZ chromosomes (males most often possess

ZZ) (Goldsmith 2009). Taking into consideration maternal inheritance of mtDNA and female heterogamety in Lepidoptera, W or Z-linkage of traits for habitat differentiation, like oviposition preference, can explain the maintenance of mitochondrial divergence and habitat preferences despite gene flow.

If oviposition preference is maternal or W-linked and the two ACG lineages interbreed, female hybrid would still lay eggs in their respective habitat types while hybrid males would be free to disperse, mate, and introgress autosomal and Z-linked

traits between habitat types. Male Saturniidae moths are also known to have higher vagility than females, providing another variable for male dispersal bias and gene flow between habitat types. However, to date no genes have been reported on the W- chromosome. Research has shown however that in Ephestia (Pyralidae) half the W- chromosome is non-functional (Traut et al. 1986) but recent research has found DNA sequences that are W-chromosome specific in Ephestia kuehniella, Plodia interpunctella, and Galleria mellonella (Vitkova et al. 2007). Future research focused on the molecular composition of the W-chromosome is of interest to this study.

Haldane’s Rule– that the heterogametic sex will be at a greater fitness disadvantage in hybrid progeny –(Haldane 1922) can also maintain distinct mtDNA and

W-linked genes while introgressing autosomal loci through male dispersal. Also, in past studies examining Lepidoptera traits related to speciation, 67% of traits for mating behavior and oviposition preference genes were Z-linked (Bush 1975). Z-linkage of oviposition preference in combination with female heterogamety can also explain mitochondrial linkage to habitat type through male dispersal biases.

The Z-linked model was first proposed by Prowell in 1998. The first condition of the model is that habitat choice is determined by females, which is the case for ovipositing female insects. The second condition is that fitness genes associated with habitat use must be on the Z-chromosome. Several studies have shown fitness traits to be Z-linked, such as pupal weight (Campbell 1962) and larval/pupal development

(Campbell 1962, Grula and Taylor 1980). The model also assumes that caterpillars are most fit when they possess alleles that are adapted to the habitat in which they occur. I

illustrate the model using the ACG dry forest (DHJ02) and rain forest (DHJ01) lineages.

When heterogametic DHJ02 females interbreed with DHJ01 males, DHJ02 females will lay eggs in dry forest, because they have the oviposition alleles for this habitat type.

First generation progeny however, will have the Z-chromosome from the DHJ01 male and as a result will possess the DHJ01 allele types for habitat choice and fitness genes for rain forest habitat. The F1 female progeny is therefore less fit in their current environment, decreasing their chances of survivorship or ovipositing. Hybrid male progeny may also be at a fitness disadvantage, being heterozygous for traits. Fitness also depends on the inheritance of genes that are in linkage disequilibrium with genes linked to habitat preference and mitochondrial function (Prowell 1998). However, if hybrid males survive to interbreed with females from either habitat type but hybrid females have a lower fitness, this could result in male driven gene flow between the two lineages, yet would maintain linkage between mtDNA and habitat type. The preliminary

ITS2 data and EF1α lineage patterns suggest that rain forest alleles at these loci are introgression into dry forest individuals with little evidence of bi-directional introgression.

Future work focused on breeding and backcrossing experiments would be an asset to this system.

The extention of DNA barcodes, through a multigene approach, to investigate provisional cryptic species boundaries has led to the discovery of a wide-spread and complicated species complex that can be used as a model system to investigate the maintenance of ecological traits despite gene flow in a stable hybrid zone. Future work aimed at sequencing the genomes of E. imperialisDHJ01 and E. imperialisDHJ02 would provide the initial steps to identifying the genes linked to larval food plant, oviposition

preferences and mtDNA in this complex. Overall, this study shows that even deep levels of mitochondrial divergence are not always reflected in the nuclear genome. A lack of corroboration between mitochondrial and nuclear divergence patterns can be due to incomplete lineage sorting of nuclear loci or interbreeding upon secondary contact.

Sampling regimes that encompass geographical distribution of species are necessary to shed light on which processes are responsible for discordant patterns, enabling researchers to investigate historical divergences and sister relationships. Lastly, the data from this study can also be extended to future work focused on population structure analyses and historical vicariance in the Americas.

Table 3.1 Eacles imperialisspecimens reared from wild-caught caterpillars in the ACG showing larval food-plant and ecosystems (http://janzen.sas.upenn.edu/).

Characters E. imperialisDHJ01 E. imperialisDHJ02

Larval food plant

Anacardiaceae

Mosquitoxylum jamaicense 1 0 Astronium graveolens 0 7 Mangifera indica (introduced) 0 1 Spondias mombin 0 49 Bixaceae Bixa orellana (introduced) 1 1 Cochlospermum vitifolium 0 1158 Burseraceae

Bursera simaruba 0 15 Bursera tomentosa 0 1 Cannabaceae

Trema micrantha 1 2 Combretaceae Terminalia oblonga 0 1 Cupressaceae

Cupressus lusitanica (introduced) 4 0 Euphorbiaceae

Mabea occidentalis 0 3 Fabaceae

Erythrina costaricensis 1 0 Dalbergia retusa 0 5 Gliricidia sepium 0 4 Haematoxylum brasiletto 0 1 Hymenaea courbaril 0 16 Inga vera 0 1 Lonchocarpus acuminatus 0 2 Lonchocarpus felipei 0 2 Lonchocarpus guatemalensis 0 1 Lonchocarpus minimiflorus 0 1 Mimosa xanti 0 1 Myrospermum frutescens 0 2 Fagaceae Quercus oleoides 0 57 Lauraceae Nectandra hihua 1 0 Ocotea veraguensis 0 1 Persea americana (introduced) 0 2 Malvaceae Guazuma ulmifolia 0 1 Trichospermum grewiifolium 1 0 85

Meliaceae Guarea kegelii 1 0 Cedrela odorata 0 18 Swietenia macrophylla 0 5 Myristicaceae Virola koschnyi 1 0 Myrtaceae Eucalyptus deglupta (introduced) 1 0 Psidium guajava (introduced) 38 0 Proteaceae Roupala montana 0 1 Rubiaceae Calycophyllum candidissimum 0 17 Guettarda macrosperma 0 1 Sapindaceae Thouinidium decandrum 0 4 Billia rosea 1 0 Nephelium lappaceum (introduced) 2 0 Verbenaceae Gmelina arborea (introduced) 24 0 Rehdera trinervis 0 4 Viscaceae Phoradendron quadrangulare 0 1

Ecosystems Rain forest Dry forest

Table 3.2 Taxonomic sampling and sequencing success. Sequence length and number of ambiguous bases and/or polymorphic positions [n] is provided for each specimen and marker. * Sequences that were successfully phased using the program PHASE

(Stephenset al. 2001).

COI cytb EF1α Sample ID Identification Seq. N Seq. N Seq. N Length Length Length 09-SRNP-14253 Eacles imperialisDHJ01 658 0 499 0 1030 14 09-SRNP-14248 Eacles imperialisDHJ01 610 0 499 0 751 2 09-SRNP-14252 Eacles imperialisDHJ01 658 0 499 0 1030 2 09-SRNP-14254 Eacles imperialisDHJ01 621 0 499 0 354 3 09-SRNP-14251 Eacles imperialisDHJ01 658 0 499 0 1030 3 09-SRNP-14250 Eacles imperialisDHJ01 658 0 499 0 1030 3 09-SRNP-14259 Eacles imperialisDHJ01 658 0 499 0 1030 2 09-SRNP-14264 Eacles imperialisDHJ01 658 0 499 0 751 1 09-SRNP-14238 Eacles imperialisDHJ01 638 0 219 0 1030 3 09-SRNP-65584 Eacles imperialisDHJ01 658 0 0 0 0 0 09-SRNP-65576 Eacles imperialisDHJ01 658 0 0 0 1030 16 09-SRNP-65583 Eacles imperialisDHJ01 658 0 0 0 1030 1 09-SRNP-65921 Eacles imperialisDHJ01 658 0 0 0 0 0 09-SRNP-66001 Eacles imperialisDHJ01 658 0 0 0 1030 6 09-SRNP-66007 Eacles imperialisDHJ01 658 0 0 0 1030 2 09-SRNP-32539 Eacles imperialisDHJ01 658 0 0 0 1030 5 09-SRNP-5507 Eacles imperialisDHJ01 658 0 0 0 0 0 09-SRNP-32535 Eacles imperialisDHJ01 658 0 0 0 1030 3 09-SRNP-32536 Eacles imperialisDHJ01 658 0 0 0 1030 7 09-SRNP-15415 Eacles imperialisDHJ01 612 0 0 0 1030 2

09-SRNP-15416 Eacles imperialisDHJ01 658 0 0 0 0 0 09-SRNP-15418 Eacles imperialisDHJ01 658 0 0 0 1030 6 09-SRNP-15419 Eacles imperialisDHJ01 628 0 0 0 1030 3 09-SRNP-15417 Eacles imperialisDHJ01 639 0 0 0 1030 1 09-SRNP-66006 Eacles imperialisDHJ01 658 0 0 0 1030 2 09-SRNP-66004 Eacles imperialisDHJ01 658 0 0 0 1030 2 09-SRNP-66003 Eacles imperialisDHJ01 658 0 0 0 1030 3 09-SRNP-66008 Eacles imperialisDHJ01 658 0 0 0 1030 0 09-SRNP-66002 Eacles imperialisDHJ01 658 0 0 0 1030 5 09-SRNP-66005 Eacles imperialisDHJ01 658 0 0 0 1030 4 09-SRNP-15323 Eacles imperialisDHJ01 658 0 0 0 1030 1 09-SRNP-15325 Eacles imperialisDHJ01 658 0 0 0 1030 6 09-SRNP-65588 Eacles imperialisDHJ01 658 0 0 0 1030 2 09-SRNP-44170 Eacles imperialisDHJ01 658 0 0 0 1030 3 09-SRNP-65574 Eacles imperialisDHJ01 658 0 0 0 1030 1 09-SRNP-15324 Eacles imperialisDHJ01 658 0 0 0 1030 5 09-SRNP-65573 Eacles imperialisDHJ01 658 0 0 0 1030 13 09-SRNP-65615 Eacles imperialisDHJ01 658 0 0 0 1030 4 09-SRNP-65587 Eacles imperialisDHJ01 658 0 0 0 1030 14 09-SRNP-65585 Eacles imperialisDHJ01 658 0 0 0 1030 2 09-SRNP-14313 Eacles imperialisDHJ02 658 0 499 0 1030 3 09-SRNP-14295 Eacles imperialisDHJ02 658 0 499 0 1030 13 09-SRNP-14298 Eacles imperialisDHJ02 658 0 499 0 1030 13 09-SRNP-14307 Eacles imperialisDHJ02 635 0 499 0 1030 5 09-SRNP-14343 Eacles imperialisDHJ02 647 0 499 0 1030 1 09-SRNP-14311 Eacles imperialisDHJ02 658 0 499 0 1030 5 09-SRNP-14296 Eacles imperialisDHJ02 658 0 499 0 851 5 09-SRNP-14308 Eacles imperialisDHJ02 658 0 499 0 1030 5 09-SRNP-14310 Eacles imperialisDHJ02 658 0 0 0 1030 3 09-SRNP-14309 Eacles imperialisDHJ02 658 0 499 0 1030 3

10-SRNP-12111 Eacles imperialisDHJ02 658 0 0 0 1030 0 10-SRNP-12069 Eacles imperialisDHJ02 658 0 0 0 1030 3 10-SRNP-12096 Eacles imperialisDHJ02 658 0 0 0 1030 4 10-SRNP-12091 Eacles imperialisDHJ02 658 0 0 0 1030 2 10-SRNP-12086 Eacles imperialisDHJ02 658 0 0 0 1030 7 10-SRNP-12100 Eacles imperialisDHJ02 658 0 0 0 1030 5 10-SRNP-12099 Eacles imperialisDHJ02 658 0 0 0 1030 6 10-SRNP-12080 Eacles imperialisDHJ02 658 0 0 0 0 0 10-SRNP-12055 Eacles imperialisDHJ02 658 0 0 0 1030 7 10-SRNP-12032 Eacles imperialisDHJ02 658 0 0 0 0 0 10-SRNP-12036 Eacles imperialisDHJ02 658 0 0 0 0 0 10-SRNP-12066 Eacles imperialisDHJ02 658 0 0 0 1030 7 10-SRNP-12034 Eacles imperialisDHJ02 658 0 0 0 1030 4 10-SRNP-12054 Eacles imperialisDHJ02 658 0 0 0 1030 4 10-SRNP-12025 Eacles imperialisDHJ02 658 0 0 0 1030 6 10-SRNP-12160 Eacles imperialisDHJ02 658 0 0 0 1030 2 10-SRNP-12154 Eacles imperialisDHJ02 658 0 0 0 1030 2 10-SRNP-12152 Eacles imperialisDHJ02 658 0 0 0 1030 4 10-SRNP-12156 Eacles imperialisDHJ02 658 0 0 0 1030 5 10-SRNP-12185 Eacles imperialisDHJ02 658 0 0 0 1030 6 10-SRNP-12159 Eacles imperialisDHJ02 658 0 0 0 1030 2 10-SRNP-12039 Eacles imperialisDHJ02 658 0 0 0 1030 2 10-SRNP-12038 Eacles imperialisDHJ02 658 0 0 0 1030 6 10-SRNP-12157 Eacles imperialisDHJ02 658 0 0 0 1030 5 10-SRNP-12153 Eacles imperialisDHJ02 658 0 0 0 1030 3 10-SRNP-12155 Eacles imperialisDHJ02 658 0 0 0 1030 7 10-SRNP-12059 Eacles imperialisDHJ02 658 0 0 0 0 0 10-SRNP-12162 Eacles imperialisDHJ02 658 0 0 0 1030 1 05-NCCC-551 Eacles imperialis 658 0 N/A N/A 1030 0 06-FLOR-0238 Eacles imperialis 658 0 N/A N/A 0 0

06-FLOR-0304 Eacles imperialis 658 0 N/A N/A 1030* 0 06-FLOR-0305 Eacles imperialis 656 0 N/A N/A 0 0 06-FLOR-0510 Eacles imperialis 658 0 N/A N/A 1030* 0 06-FLOR-0511 Eacles imperialis 658 0 N/A N/A 1030* 0 06-FLOR-0942 Eacles imperialis 658 0 N/A N/A 1030 0 06-FLOR-1163 Eacles imperialis 585 0 N/A N/A 0 0 06-FLOR-1393 Eacles imperialis 658 0 N/A N/A 1030 0 06-FLOR-1739 Eacles imperialis 658 0 N/A N/A 0 0 06-FLOR-1740 Eacles imperialis 658 0 N/A N/A 0 0 06-NCCC-1139 Eacles imperialis 658 0 N/A N/A 1030* 0 2006-ONT-0963 Eacles imperialis 658 0 N/A N/A 0 0 2006-ONT-0964 Eacles imperialis 658 0 N/A N/A 0 0 2006-ONT-0965 Eacles imperialis 658 0 N/A N/A 1030* 0 2006-ONT-0966 Eacles imperialis 658 0 N/A N/A 0 0 barcode SNB 1160 Eacles imperialis 658 0 N/A N/A 0 0 BC-CGCM 23.763 Eacles imperialis 658 0 N/A N/A 1030 0 BC-Dec0113 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-Dec0114 Eacles imperialis cacicus 399 0 N/A N/A 0 0 BC-Dec0115 Eacles imperialis tucumana 658 0 N/A N/A 0 0 BC-Dec0116 Eacles imperialis tucumana 632 0 N/A N/A 1030 0 BC-Dec0117 Eacles imperialis tucumana 388 1 N/A N/A 0 0 BC-Dec0118 Eacles imperialis 658 0 N/A N/A 0 0 BC-Dec0119 Eacles imperialis 658 0 N/A N/A 1030 0 BC-Dec0120 Eacles imperialis 658 0 N/A N/A 1030 0 BC-Dec0121 Eacles imperialis anchicayensis 658 0 N/A N/A 0 0 BC-Dec0122 Eacles imperialis anchicayensis 635 0 N/A N/A 1030* 0 BC-Dec0126 Eacles imperialis tucumana 658 0 N/A N/A 0 0 BC-Dec0129 Eacles imperialis oslari 658 0 N/A N/A 0 0 BC-Dec0130 Eacles imperialis oslari 658 0 N/A N/A 0 0 BC-Dec0145 Eacles imperialis opaca 658 0 N/A N/A 1030 0

BC-Dec0146 Eacles imperialis opaca 658 0 N/A N/A 1030 0 BC-Dec0149 Eacles imperialis decoris 658 0 N/A N/A 1030 0 BC-Dec0150 Eacles imperialis decoris 658 0 N/A N/A 1030 0 BC-Dec0155 Eacles imperialis magnifica 658 0 N/A N/A 0 0 BC-Dec0156 Eacles imperialis magnifica 658 0 N/A N/A 1030 0 BC-Dec0333 Eacles imperialis magnifica 658 0 N/A N/A 1030 0 BC-Dec0445 Eacles imperialis magnifica 658 0 N/A N/A 1030 0 BC-Dec0446 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-Dec0448 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-Dec0452 Eacles imperialis magnifica 658 0 N/A N/A 1030 0 BC-Dec1104 Eacles imperialis decoris 658 0 N/A N/A 1030 0 BC-Dec1105 Eacles imperialis hallwachsae 658 0 N/A N/A 1030 0 BC-Dec1106 Eacles imperialis hallwachsae 658 0 N/A N/A 1030 0 BC-Dec1506 Eacles imperialis piurensis 658 0 N/A N/A 1030 0 BC-Dec1507 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-Dec1508 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-Dec1623 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-Dec1652 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-Dec1682 Eacles imperialis cacicus 658 0 N/A N/A 1030* 0 BC-Dec1696 Eacles imperialis cacicus 658 0 N/A N/A 1030 0 BC-Dec1697 Eacles imperialis cacicus 658 0 N/A N/A 1030 0 BC-EST0153 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-EST0154 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-EST0155 Eacles imperialis cacicus 632 0 N/A N/A 0 0 BC-EST0156 Eacles imperialis cacicus 280 0 N/A N/A 0 0 BC-EST0157 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-EST0158 Eacles imperialis cacicus 639 0 N/A N/A 0 0 BC-EST0159 Eacles imperialis cacicus 634 0 N/A N/A 0 0 BC-EST0160 Eacles imperialis cacicus 639 0 N/A N/A 0 0 BC-EST0161 Eacles imperialis cacicus 283 0 N/A N/A 0 0

BC-EST0162 Eacles imperialis cacicus 639 0 N/A N/A 0 0 BC-EvS 1848 Eacles imperialis anchicaensis 658 0 N/A N/A 1030 0 BC-EvS 1849 Eacles imperialis anchicaensis 658 0 N/A N/A 1030 0 BC-EvS 1850 Eacles imperialis anchicaensis 658 0 N/A N/A 1030 0 BC-EvS 1856 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-EvS 1859 Eacles imperialis imperialis 658 0 N/A N/A 0 0 BC-EvS 1861 Eacles imperialis imperialis 658 0 N/A N/A 0 0 BC-EvS 1862 Eacles imperialis imperialis 596 0 N/A N/A 1030* 0 BC-EvS 1864 Eacles imperialis pini 658 0 N/A N/A 0 0 BC-EvS 1865 Eacles imperialis pini 658 0 N/A N/A 0 0 BC-EvS 1866 Eacles imperialis oslari 658 0 N/A N/A 1030* 0 BC-EvS 1867 Eacles imperialis oslari 658 0 N/A N/A 0 0 BC-EvS 1869 Eacles imperialis hallwachsae 658 0 N/A N/A 1030* 0 BC-EvS 1871 Eacles imperialis magnefica 658 0 N/A N/A 0 0 BC-EvS 1872 Eacles imperialis magnefica 658 0 N/A N/A 1030* 0 BC-EvS 1873 Eacles imperialis opaca 613 0 N/A N/A 1030 0 BC-EvS 1875 Eacles imperialis opaca 658 0 N/A N/A 0 0 BC-EvS 1876 Eacles imperialis opaca 658 0 N/A N/A 0 0 BC-EvS 1878 Eacles imperialis opaca 658 0 N/A N/A 1030 0 BC-EvS 1879 Eacles imperialis opaca 658 0 N/A N/A 1030 0 BC-EvS 1925 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-EvS 1926 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-EvS 1934 Eacles imperialis 658 0 N/A N/A 1030 0 BC-EvS 1936 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-EvS 1937 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-EvS 1938 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-EvS 1949 Eacles imperialis tucumana 658 0 N/A N/A 1030 0 BC-EvS 1950 Eacles imperialis tucumana 658 0 N/A N/A 1030 0 BC-EvS 1965 Eacles imperialis 658 0 N/A N/A 1030 0 BC-FMP-1049 Eacles imperialis tucumana 658 0 N/A N/A 1030 0

BC-FMP-1050 Eacles imperialis tucumana 658 0 N/A N/A 1030 0 BC-FMP-1051 Eacles imperialis opaca 658 0 N/A N/A 1030* 0 BC-FMP-1052 Eacles imperialis anchicayensis 658 0 N/A N/A 1030* 0 BC-FMP-1053 Eacles imperialis magnifica 658 0 N/A N/A 0 0 BC-FMP-1054 Eacles imperialis magnifica 658 0 N/A N/A 1030* 0 BC-FMP-1055 Eacles imperialis pini 399 0 N/A N/A 0 0 BC-FMP-1056 Eacles imperialis imperialis 658 0 N/A N/A 1030 0 BC-FMP-1058 Eacles imperialis oslari 658 1 N/A N/A 0 0 BC-FMP-1059 Eacles imperialis cacicus 580 0 N/A N/A 0 0 BC-FMP-1060 Eacles imperialis cacicus 658 0 N/A N/A 1030 0 BC-FMP-1061 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-FMP-1062 Eacles imperialis cacicus 658 0 N/A N/A 1030* 0 BC-FMP-1064 Eacles imperialis decoris 658 0 N/A N/A 0 0 BC-FMP-1065 Eacles imperialis typica 658 0 N/A N/A 1030 0 BC-FMP-1427 Eacles imperialis imperialis 658 0 N/A N/A 0 0 BC-FMP-1428 Eacles imperialis piurensis 658 0 N/A N/A 1030* 0 BC-FMP-1429 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-FMP-1431 Eacles imperialis tucumana 658 0 N/A N/A 1030 0 BC-FMP-2132 Eacles imperialis quintanensis 658 0 N/A N/A 1030 0 BC-FMP-2473 Eacles imperialis decoris 658 0 N/A N/A 1030 0 BC-Her0458 Eacles imperialis cacicus 658 0 N/A N/A 1030 0 BC-Her1235 Eacles imperialis 658 0 N/A N/A 1030 0 BC-Her1253 Eacles imperialis 658 0 N/A N/A 1030 0 BC-Her1364 Eacles imperialis quintanensis 658 0 N/A N/A 1030 0 BC-Her1366 Eacles imperialis quintanensis 658 0 N/A N/A 1030 0 BC-Her1368 Eacles imperialis quintanensis 658 0 N/A N/A 1030 0 BC-Her1370 Eacles imperialis quintanensis 658 0 N/A N/A 1030 0 BC-Her1704 Eacles imperialis tucumana 658 0 N/A N/A 0 0 BC-Her1764 Eacles imperialis quintanensis 658 0 N/A N/A 1030* 0 BC-Her1807 Eacles imperialis oslari 658 0 N/A N/A 0 0

BC-Her1819 Eacles imperialis 658 0 N/A N/A 0 0 BC-Her1853 Eacles imperialis 658 0 N/A N/A 1030 0 BC-Her1855 Eacles imperialis 650 0 N/A N/A 0 0 BC-Her2286 Eacles imperialis 649 0 N/A N/A 1030 0 BC-Her3539 Eacles imperialis 658 0 N/A N/A 1030 0 BC-RBP 4604 Eacles imperialis tucumana 658 0 N/A N/A 1030 0 BC-RBP 4605 Eacles imperialis tucumana 658 0 N/A N/A 1030 0 BC-RBP 4606 Eacles imperialis magnifica 658 0 N/A N/A 1030 0 BC-RBP 4607 Eacles imperialis magnifica 658 0 N/A N/A 1030 0 BC-RBP 4609 Eacles imperialis tucumana 658 0 N/A N/A 1030* 0 BC-RBP 4610 Eacles imperialis piurensis 658 0 N/A N/A 1030 0 BC-RBP 4611 Eacles imperialis piurensis 658 0 N/A N/A 1030 0 BC-RBP 4612 Eacles imperialis typica 658 0 N/A N/A 0 0 BC-RBP 4613 Eacles imperialis decoris 658 0 N/A N/A 1030 0 BC-RBP 4614 Eacles imperialis decoris 658 0 N/A N/A 0 0 BC-RBP 4615 Eacles imperialis decoris 658 0 N/A N/A 1030 0 BC-RBP 4616 Eacles imperialis hallwachsae 658 0 N/A N/A 0 0 BC-RBP 4617 Eacles imperialis hallwachsae 658 0 N/A N/A 0 0 BC-RBP 4618 Eacles imperialis hallwachsae 658 0 N/A N/A 0 0 BC-RBP 4619 Eacles imperialis decoris 658 0 N/A N/A 1030 0 BC-RBP 4620 Eacles imperialis decoris 658 0 N/A N/A 1030* 0 BC-RBP 4621 Eacles imperialis decoris 658 0 N/A N/A 1030 0 BC-Roug0157 Eacles imperialis 658 0 N/A N/A 0 0 BC-Roug0158 Eacles imperialis 381 0 N/A N/A 0 0 BC-Roug0159 Eacles imperialis 658 0 N/A N/A 0 0 BC-Roug0160 Eacles imperialis opaca 658 0 N/A N/A 0 0 BC-Roug0161 Eacles imperialis opaca 658 0 N/A N/A 0 0 BC-Roug0162 Eacles imperialis opaca 658 0 N/A N/A 1030* 0 BC-Roug0344 Eacles imperialis anchicayensis 658 0 N/A N/A 0 0 BC-Roug0345 Eacles imperialis opaca 658 0 N/A N/A 0 0

BC-Roug0346 Eacles imperialis oslari 658 0 N/A N/A 0 0 BC-Roug0347 Eacles imperialis oslari 658 0 N/A N/A 0 0 BC-Roug0350 Eacles imperialis oslari 609 0 N/A N/A 0 0 BC-Roug0351 Eacles imperialis oslari 609 0 N/A N/A 0 0 BC-TDMPEG0052 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-TDMPEG0053 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-TDMPEG0054 Eacles imperialis cacicus 658 0 N/A N/A 0 0 BC-TDMPEG0347 Eacles imperialis cacicus 638 0 N/A N/A 1030 0 CLV10710 Eacles imperialis cacicus 658 0 N/A N/A 1030 0 CLV12610 Eacles imperialis cacicus 658 0 N/A N/A 1030 0 HLC-16993 Eacles imperialis 658 0 N/A N/A 1030 0 HLC-16994 Eacles imperialis 658 0 N/A N/A 0 0 NS-RR0657 Eacles imperialis cacicus 658 0 N/A N/A 0 0 NS-RR1685 Eacles imperialis cacicus 658 0 N/A N/A 0 0 NS-RR1705 Eacles imperialis cacicus 658 0 N/A N/A 1030* 0 07-SRNP-110342 Eacles masoni 658 0 499 0 286 3 08-SRNP-105092 Eacles masoni 658 0 499 0 536 5

Table 3.3 Results of Pyrosequencing ITS2 from E.imperialis specimens collected in the ACG.

# # unique haplotypes # sequences in Tag # Sample ID Species #Sequences haplotypes (>2 seq) haplotypes (>2 seq) MID-1 09-SRNP-65584 Eacles imperialisDHJ01 81 65 5 16 MID-2 09-SRNP-32535 Eacles imperialisDHJ01 63 40 8 23 MID-3 09-SRNP-66004 Eacles imperialisDHJ01 59 44 6 15 MID-4 09-SRNP-65921 Eacles imperialisDHJ01 44 27 3 17 MID-5 09-SRNP-66001 Eacles imperialisDHJ01 35 32 1 3 MID-6 09-SRNP-66007 Eacles imperialisDHJ01 67 39 13 28 MID-7 09-SRNP-32539 Eacles imperialisDHJ01 43 26 16 17 MID-8 09-SRNP-5507 Eacles imperialisDHJ01 47 30 7 17 MID-10 09-SRNP-65576 Eacles imperialisDHJ01 81 56 8 25 MID-11 09-SRNP-32536 Eacles imperialisDHJ01 70 55 5 15 MID-13 09-SRNP-15415 Eacles imperialisDHJ01 64 46 5 18 MID-14 09-SRNP-15416 Eacles imperialisDHJ01 72 60 4 12 MID-15 09-SRNP-15418 Eacles imperialisDHJ01 53 34 6 19 MID-16 09-SRNP-15419 Eacles imperialisDHJ01 69 34 5 35 MID-17 09-SRNP-15417 Eacles imperialisDHJ01 49 24 7 25 MID-18 09-SRNP-66006 Eacles imperialisDHJ01 51 31 8 20 MID-19 09-SRNP-65583 Eacles imperialisDHJ01 60 36 8 24 MID-20 09-SRNP-66003 Eacles imperialisDHJ01 54 44 3 10

MID-21 09-SRNP-66008 Eacles imperialisDHJ01 40 29 5 11 MID-22 09-SRNP-66002 Eacles imperialisDHJ01 45 37 3 8 MID-23 09-SRNP-66005 Eacles imperialisDHJ01 60 39 8 21 MID-24 09-SRNP-15323 Eacles imperialisDHJ01 125 79 12 46 MID-25 09-SRNP-15325 Eacles imperialisDHJ01 30 21 4 9 MID-26 09-SRNP-65588 Eacles imperialisDHJ01 150 76 22 74 MID-28 09-SRNP-65574 Eacles imperialisDHJ01 60 40 7 20 MID-29 09-SRNP-15324 Eacles imperialisDHJ01 86 59 6 27 MID-30 09-SRNP-65573 Eacles imperialisDHJ01 59 49 4 10 MID-31 09-SRNP-65615 Eacles imperialisDHJ01 84 52 12 32 MID-32 09-SRNP-65587 Eacles imperialisDHJ01 90 64 9 26 MID-33 09-SRNP-65585 Eacles imperialisDHJ01 114 75 11 39 MID-35 10-SRNP-12162 Eacles imperialisDHJ02 73 52 9 21 MID-36 10-SRNP-12059 Eacles imperialisDHJ02 66 50 7 16 MID-37 10-SRNP-12155 Eacles imperialisDHJ02 69 48 7 21 MID-38 10-SRNP-12153 Eacles imperialisDHJ02 82 71 4 11 MID-39 10-SRNP-12157 Eacles imperialisDHJ02 61 35 10 26 MID-40 10-SRNP-12038 Eacles imperialisDHJ02 58 32 9 26 MID-41 10-SRNP-12039 Eacles imperialisDHJ02 84 44 12 40 MID-42 10-SRNP-12159 Eacles imperialisDHJ02 56 35 7 21 MID-43 10-SRNP-12185 Eacles imperialisDHJ02 131 76 16 55 MID-44 10-SRNP-12156 Eacles imperialisDHJ02 51 35 6 16 MID-45 10-SRNP-12152 Eacles imperialisDHJ02 135 103 12 32 MID-46 10-SRNP-12154 Eacles imperialisDHJ02 61 50 4 11 MID-47 10-SRNP-12160 Eacles imperialisDHJ02 72 46 9 26 MID-48 10-SRNP-12025 Eacles imperialisDHJ02 65 46 7 19

MID-49 10-SRNP-12054 Eacles imperialisDHJ02 43 30 5 13 MID-50 10-SRNP-12034 Eacles imperialisDHJ02 58 45 4 13 MID-51 10-SRNP-12066 Eacles imperialisDHJ02 77 65 5 12 MID-52 10-SRNP-12036 Eacles imperialisDHJ02 72 56 6 16 MID-54 10-SRNP-12032 Eacles imperialisDHJ02 78 53 9 25 MID-55 10-SRNP-12055 Eacles imperialisDHJ02 105 61 15 44 MID-56 10-SRNP-12080 Eacles imperialisDHJ02 37 25 12 12 MID-57 10-SRNP-12099 Eacles imperialisDHJ02 33 15 4 18 MID-58 10-SRNP-12100 Eacles imperialisDHJ02 120 79 15 41 MID-59 10-SRNP-12086 Eacles imperialisDHJ02 76 57 6 19 MID-60 10-SRNP-12091 Eacles imperialisDHJ02 68 39 11 29 MID-62 10-SRNP-12069 Eacles imperialisDHJ02 56 40 6 16 MID-64 10-SRNP-12111 Eacles imperialisDHJ02 96 57 11 39 MID-65 09-SRNP-14238 Eacles imperialisDHJ01 56 48 3 8 MID-66 09-SRNP-14248 Eacles imperialisDHJ01 88 50 14 38 MID-67 09-SRNP-14249 Eacles imperialisDHJ01 118 78 14 40 MID-69 09-SRNP-14296 Eacles imperialisDHJ02 49 33 7 16 MID-70 09-SRNP-14308 Eacles imperialisDHJ02 56 43 5 13 MID-71 09-SRNP-14309 Eacles imperialisDHJ02 88 57 12 31

Table 3.4 Parameters used in Bayesian phylogenetic analyses of E. imperialis in the ACG and in the analysis comprised of geographically distributed individuals. no.seq = number of sequences, ngen = number of generations until convergence, conv = standard deviation of split frequencies, burnin = number of trees discarded for consensus tree (25%).

ACG

COI cytb EF1α no. seq 83 20 65 model GTR + I GTR+G JC ngen 5x10^6 1x10^6 1.5x10^6 conv 0.025 0.01 0.01 burnin 12500 2500 3750

ACG + Allopatric populations

COI EF1α no. seq 175 174(hap) model GTR + I JC ngen 1x10^6 1x10^7 conv 0.016 0.015 burnin 2500 25000

Table 3.5 Mean within and between pairwise sequence divergences for the COI, Cytb,EF1α, and

ITS2 . Standard deviations calculated from 1000 bootstrap iterations.

Mean within pairwise Mean between pairwise Gene sequence divergence sequence divergence +/- region Groups +/- Stand. Dev Stand. Dev

COI Eacles imperialisDHJ01 0.001 +/- 0.001 Eacles imperialisDHJ02 0.001 +/- 0.001 0.074 +/- 0.010 Cytb Eacles imperialisDHJ01 0.0004 +/- 0 Eacles imperialisDHJ02 0 0.077 +/- 0.016 EF1α Eacles imperialisDHJ01 0.001 +/- 0.001 Eacles imperialisDHJ02 0.001 +/- 0.001 0.001 +/- 0.00 ITS2 Eacles imperialisDHJ01 0.0086 +/- 0.0027

Eacles imperialisDHJ02 0.0053 +/- 0.0035 0.0072 +/-0.003

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Table 3.6 Mean pairwise genetic distances between groupings of E. imperialis. Groupings are based COI lineages, locality and on subspecies classifications,) for 658bp of the COI gene (below diagonal) and 1030bp of the EF1αgene (above diagonal).

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

E. imperialis anchicayensis: Panama/ 1 Columbia 0.016 0.015 0.015 0.014 0.012 0.01 0.013 0.012 0.014 0.012 0.016 E. imperialis opacamaginific a:Argentina/ 2 Brazil 0.053 0.014 0.014 0.013 0.01 0.016 0.013 0.012 0.012 0.011 0.013 E. imperialis cacius:French 3 Guiana 0.018 0.054 0.006 0.014 0.013 0.015 0.015 0.015 0.016 0.014 0.017 E.imperialis:ce ntralamazonian 4 rain forest 0.041 0.044 0.041 0.012 0.012 0.015 0.014 0.014 0.014 0.013 0.017 E. imperialis 5 tucuma:Bolivia 0.042 0.043 0.04 0.017 0.01 0.013 0.012 0.011 0.012 0.01 0.016

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/Argentina E. imperialis piurensis:Peru 6 Piura 0.044 0.052 0.046 0.034 0.032 0.012 0.005 0.005 0.005 0.003 0.009 E. imperialis hallwachsea: 7 CostaRica 0.048 0.055 0.05 0.04 0.036 0.016 0.013 0.013 0.014 0.012 0.018 E.imperialisDHJ 02:CostaRica 8 dry forest 0.047 0.053 0.05 0.04 0.037 0.02 0.028 0.005 0.004 0.004 0.009 E.imperialisDHJ 01/decoris: CostaRica 9 /Nicaragua 0.058 0.061 0.061 0.058 0.053 0.049 0.054 0.074 0.004 0.004 0.009 E. imperialis decoris:Guate 10 mala 0.072 0.069 0.07 0.069 0.064 0.07 0.076 0.077 0.041 0.005 0.008 E. imperialis decoris 0.0 11 Nicaragua 0.073 0.067 0.074 0.073 0.068 0.072 0.072 0.075 0.043 17 0.009 Eacles imperialis 0.0 12 oslari: Mexico 0.063 0.057 0.067 0.064 0.059 0.062 0.065 0.068 0.06 58 0.052 13 Eacles 0.057 0.056 0.057 0.053 0.049 0.052 0.057 0.058 0.056 0.0 0.054 0.0

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imperialis 52 38 typica: Mexico E. imperialis quintanensis:G 0.0 0.0 0.0 14 uatemala 0.061 0.06 0.062 0.063 0.058 0.067 0.071 0.073 0.057 51 0.046 44 39 E. imperialis imperialis:USA/ 0.0 0.0 0.0 15 Canada 0.067 0.059 0.065 0.061 0.056 0.057 0.066 0.063 0.059 5 0.049 45 32 0.049

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Figure 3.1 The Área de Conservación Guanacaste life zone map showing the distribution of the two E.imperialis lineages. The lineages are found in areas of dry forest and rain forest habitat types, as well as a small overlap zone where caterpillars were found in Rain forest/subtropical Rain – Cloud forest. Circles represent the number of specimens collected in the different sectors of the ACG.

3 4 16 5 2 2 18 33 14 25 26 1 55 E. imperialisDHJ01 2 E. imperialisDHJ02 Tropical submontane evergreen forest Evergreen seasonal lowland forest subtropical Rain – Cloud forest 5 Coastal rainforest Lowland deciduous forest Semi deciduous –deciduous forest Lowland semi deciduous forest Mangrove forest Herbaceous marshes Marshes and reed beds of typha Open savanna grasses Wooded savannah Shrub vegetation with isolated clumps Alluvial tropical rainforest vegetation

Figure 3.1 Area de Conservacion Guanacaste life zone map showing the distribution of the two E.imperialis forms in areas of dryforest and rainforest habitat types, as well as a small overlap zone where caterpillars were found in Rainforest/subtropical Rain – Cloud forest. Circles represent the number of specimens collected in the different sectors of the ACG. This figure was created using the program Phylogeoviz (Tsai 2011)

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Figure3.2 Bayesian trees constructed from mitochondrial and nuclear sequences from Eacles imperialis. Posterior probabilities are presented above the 70% confidence interval.

a) COI b) cytb c) EF1a

100

E. imperialisDH01 100

100

0.1 E. imperialisDHJ02 100

0.5

0.02

Figure 3.2 Bayesian trees constructed from mitochondrial and nuclear sequences, showing mitochondrial-nuclear discordance for two ACG forms. Posterier probability are presented above the 70% confidence interval. 105

Figure 3.3 nMDS distances among ITS2 intra-individual sequence-types of the two E.imperialis lineages. Lineages are presented as blue (DHJ01), red (DHJ02) circles.

Fig. 3.3 nMDS distances among ITS2 intra-individual sequence-types of the two E.imperialis lineages. Lineages are presented as blue (DHJ01), red (DHJ02)

circles.

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Figure 3.4 Bayesian tree and map constructed from mitochondrial sequences of E. imperialis populations that are geographically distributed throughout the species range. The tree shows a North and South Figure 3.4 Bayesian tree and map constructed from mitochondrial sequences of E. imperialis American lineage with the two ACG forms clustering in separate lineages. Posterior probabilities above populations that are geographically distributed throughout the species range. The tree shows a North70% andare indicatedSouth American on the tree. lineage Colours with therepresent two ACG groupings forms clustering based on mitochondrialin separate lineages. lineages, Posterier probabilitysubspecies are classifications presented aboveand locality. the 70% confidence interval. Colours represent groupings based on mt lineages, subspecies classifications and locality.

Figure 3.5 Bayesian tree constructed from EF1α sequences from E. imperialis populationsthat are geographically distributed throughout the species range. The tree shows two groups that are congruent with clusters in treesbased on analysis of COI. E. imperialis imperialis was sampled from the USA and FigureCanada 3.4 Bayesian while E. treeimperialis constructed magnifica/opaca from EF1a haplotype was sampledsequences from ofBrazil E. imperialis and Argentina.populations Posterior that are geographically distributed throughout the species range. The tree shows two groups to probabilities above70% are included on the tree. Colours represent the same groupings as the COI tree. show congruent clustering patterns with COI, E. imperialis imperialis from the USA/Canada as well as E. imperialis magnifica/opaca from Brazil and and Agentina. Posterier probability are presented above the 70% confidence interval. Colours represent the same groupings as the COI tree.

outgroup 100 100 100 E. Imperialis imperialis: EF1a USA/Canada

100

100 E. Imperialis maginifica/opaca Brazil/Argentina

99 100

0.0020.002 108

Figure 3.6 Character based analysis of ITS2 from individuals of E. imperialis across the species range. The analysis demonstrates that the two ACG forms as well as E. imperialis piurensis from Piura Peru are most similar to individuals in North American. South American individuals show numerous nucleotide and indel differences.

80 116-126 141 155 163 164 178 170-175 177 232-242 – – – – – – – 09-SRNP-14309 A T ~ ------~ G ~ A ~ G ~ G ~ C ~ C ------~ G A ~ G C T G G C A A G G C 09-SRNP-14310 A T ~ ------~ G ~ A ~ G ~ G ~ C ~ C ------G A ~ G C T G G C A A G G C ACG forms ~ 09-SRNP-65576 A T ~ ------G A ~ G ~ A ~ G ~ G ~ C ~ C ------~ G A ~ G C T G G C A A G G C 09-SRNP-14238 A T ~ ------~ G ~ A ~ G ~ G ~ C ~ C ------~ G A ~ G C T G G C A A G G C 2006-ONT-0966 A T ~ ------~ G ~ A ~ G ~ G ~ C ~ C ------~ G A 2006-ONT-0965 A T ~ ------~ G ~ A ~ G G 06-FLOR-0238 A T ~ ------G A ~ G ~ A ~ G 06-FLOR-0305 A T ~ ------~ 06-FLOR-0511 A T ~ ------~ G ~ A ~ G ~ G 06-FLOR-0304 A T ~ ------~ G ~ A ~ G ~ G 06-FLOR-1393 A T ~ ------~ North BC-Her1855 A T ------~ G ~ A ~ G ~ G BC-Her1235 ~ America A T ------G A ~ G G BC-Her1853 ~ ~ ~ ~ A T ------BC-Her1253 ~ ~ G ~ A ~ G BC-Dec1104 A T ~ ------~ G ~ A ~ G BC-Her1366 A T ~ ------~ G ~ A ~ G ~ G BC-Her1364 A T ~ ------~ G ~ A ~ G ~ G BC-Her1370 A T ~ ------~ G ~ A ~ G ~ G BC-EvS 1936 A T ~ ------~ G ~ A ~ G ~ G BC-FMP-1428 A T ~ ------~ G ~ A ~ G ~ G Peru Piura BC-RBP 4611 A T ~ ------~ G ~ A ~ G ~ G BC-Dec1506 A T ~ ------~ G ~ A ~ G ~ G BC-Dec0446 - - ~ G ------~ BC-Her0458 - - ~ G A A GGG - G GA G ~ A ~ G ~ C ~ C ~ G ~ G CG C C CC ~ - - ~ A C G T C G C G A C G BC-Dec0448 - - ~ G A T GGG - G T A G ~ A ~ G ~ C ~ C ~ G ~ G CG C C CC ~ - - ~ A C G T C G C G A C G South BC-Dec0445 - - ~ G - - GGG - G T A G ~ A ~ G ~ C ~ C ~ G ~ G CG C C T C ~ - - ~ A C G T C G C G A C G America BC-RBP 4604 - - ~ G A G GGGT G AA G ~ A ~ G ~ C ~ C ~ G ~ G CG C C CC ~ - - ~ A C G T C G C G A C G BC-Her1704 - - ~ G A T GGG - G T A G ~ A ~ G ~ C ~ C ~ G ~ G CG C C CC ~ - - ~ A C G T C G C G A C G BC-Dec0146 - - ~ G A ------BC-Dec0333 - - ~ G A ------Figure 3.5 Presents a character based analysis between successfully sanger-sequenced individuals of E. imperialis across the species range. The analysis demonstrates that the two ACG forms as well as the E. imperialis piurensis from Piura Peru are most similar to individuals in North American, while South American individuals show numerous nucleotide and indel differences.

109

CONCLUSION

The objective of this thesis was to investigate five provisional cryptic species of

Lepidoptera that were initially predicted by DNA barcode lineages and examined further using an integrative approach that combined three additional loci and natural history data. I constructed and compared single gene phylogenies that were subsequently used to delineate three cryptic species from the Hesperiidae family and revealed secondary introgression of the broadly distributed Imperial moth (Saturniidae). My findings do not suggest a pattern between the detection of cryptic species and level of DNA barcode divergence. Similarly, my thesis demonstrates that mitochondrial lineages can be discordant with nuclear loci even when mitochondrial divergences are large, shown to be due to secondary introgression. Consequently, this work reiterates the insufficiency of a single gene region for species delineation.

Several strengths and weaknesses became evident while completing this research. Notable strengths include the use of existing collections like BOLD and the

Lepidoptera Inventory of the ACG, as well as implementing an integrative approach that uses multiple lines of evidence to make inferences. Particular limitations of this work were narrow sampling breadth and the comparatively low rates of molecular evolution in nuclear loci. This thesis also highlights the need for future research that regards speciation as a continuous process which can create or eliminate species. Future avenues of research focused on delimiting lineages that are currently introgressing is of particular interest.

110

The decline of species numbers due to habitat fragmentation, degradation and global climate change haspromoted the study biodiversity (Walther et al. 2002, Gaston and Fuller 2007). Discovering unappreciated biodiversity is at the forefront of this research because it will provide more robust species estimates and is crucial for conservation strategies, public health and agricultural practices (Paterson 1991, Geller

1999, Schonrogge et al. 2002, Stuart et al. 2006). This thesis demonstrates that DNA barcode divergences can be used as a framework for integrative approaches to build upon when investigating cryptic species. In addition, this work shows that implementing integrative molecular methods is an asset for cryptic species that lack diagnostic natural history characters.

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APPENDICES

Appendix A: Chapter 1 Supplementary Tables

Table A.1 Supportive collection data for the 104 specimens the butterflies and moths used in this study.

Life Sample ID Country Province Region Sector Exact Site Lat Lon Elev Stage Costa 09-SRNP-44671 Rica Alajuela ACG Llanura Estacion Llanura 10.93 -85.25 135 A Costa 09-SRNP-44670 Rica Alajuela ACG Llanura Estacion Llanura 10.93 -85.25 135 A Costa 10-SRNP-73087 Rica Guanacaste ACG Sector Pitilla Estacion Quica 11 -85.40 470 A Costa 10-SRNP-32297 Rica Guanacaste ACG Sector Pitilla Sendero Naciente 10.99 -85.43 700 A Costa 10-SRNP-32272 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32270 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32269 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32139 Rica Guanacaste ACG Sector Pitilla Sendero Naciente 10.99 -85.43 700 A Costa 10-SRNP-32138 Rica Guanacaste ACG Sector Pitilla Sendero Naciente 10.99 -85.43 700 A Costa 10-SRNP-32135 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32060 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32059 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A 10-SRNP-32057 Costa Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A

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Rica Costa 10-SRNP-32052 Rica Guanacaste ACG Sector Pitilla Sendero Laguna 10.99 -85.42 680 A Costa 10-SRNP-32051 Rica Guanacaste ACG Sector Pitilla Sendero Laguna 10.99 -85.42 680 A Costa 10-SRNP-32050 Rica Guanacaste ACG Sector Pitilla Sendero Laguna 10.99 -85.42 680 A Costa 10-SRNP-32044 Rica Guanacaste ACG Sector Pitilla Sendero Laguna 10.99 -85.42 680 A Costa 10-SRNP-32043 Rica Guanacaste ACG Sector Pitilla Sendero Laguna 10.99 -85.42 680 A Costa 10-SRNP-32031 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32030 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32028 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32027 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32026 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32025 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32024 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32023 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32022 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32021 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32020 Rica Guanacaste ACG Sector Pitilla Cabrera 11.01 -85.41 500 A Costa 10-SRNP-32008 Rica Guanacaste ACG Sector Pitilla Estacion Pitilla 10.99 -85.43 675 A Costa 10-SRNP-31979 Rica Guanacaste ACG Sector Pitilla Sendero Laguna 10.99 -85.42 680 A Costa 10-SRNP-31978 Rica Guanacaste ACG Sector Pitilla Sendero Laguna 10.99 -85.42 680 A

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Costa 10-SRNP-31946 Rica Guanacaste ACG Sector Pitilla Estacion Pitilla 10.99 -85.43 675 A Costa 10-SRNP-31945 Rica Guanacaste ACG Sector Pitilla Loaiciga 11.02 -85.41 445 A Costa 10-SRNP-31905 Rica Guanacaste ACG Sector Pitilla Estacion Pitilla 10.99 -85.43 675 A Costa 10-SRNP-31904 Rica Guanacaste ACG Sector Pitilla Estacion Pitilla 10.99 -85.43 675 A Costa 07-SRNP-40778 Rica Alajuela ACG Rincon Rain forest Sendero Rincon 10.9 -85.28 430 A Costa Sector Mundo 07-SRNP-58689 Rica Guanacaste ACG Nuevo Vado Miramonte 10.77 -85.43 305 A Costa 07-SRNP-24022 Rica Guanacaste ACG Sector Del Oro Tangelo 11.02 -85.45 410 A Costa 07-SRNP-24082 Rica Guanacaste ACG Sector Del Oro Quebrada Trigal 11.03 -85.49 290 A Costa 07-SRNP-24059 Rica Guanacaste ACG Sector Del Oro Quebrada Trigal 11.03 -85.49 290 A Costa 07-SRNP-24080 Rica Guanacaste ACG Sector Del Oro Quebrada Trigal 11.03 -85.49 290 A Costa Sector San 08-SRNP-560 Rica Alajuela ACG Cristobal Luna Azul 10.02 -85.71 450 A Costa 07-SRNP-23577 Rica Guanacaste ACG Sector Del Oro Quebrada Lajosa 11.03 -85.42 400 A Costa 07-SRNP-66191 Rica Alajuela ACG Brasilia Brisanta 11.03 -85.33 290 A Costa 07-SRNP-24019 Rica Guanacaste ACG Sector Del Oro Tangelo 11.02 -85.45 410 A Costa Sector Mundo 07-SRNP-58443 Rica Guanacaste ACG Nuevo Vado Miramonte 10.77 -85.43 305 A Costa 06-SRNP-40813 Rica Alajuela ACG Rincon Rain forest Sendero Llano 10.9 -85.29 400 A Costa Sector San 06-SRNP-5396 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa 06-SRNP-23006 Rica Guanacaste ACG Sector Del Oro Tangelo 11.02 -85.45 410 A Costa 07-SRNP-40319 Rica Alajuela ACG Rincon Rain forest Rio Francia Arriba 10.9 -85.29 400 A

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Costa Sector Mundo 07-SRNP-58820 Rica Guanacaste ACG Nuevo Quebrada Tibio Perla 10.76 -85.43 330 A Costa Sector Mundo 07-SRNP-58438 Rica Guanacaste ACG Nuevo Vado Miramonte 10.77 -85.43 305 A Costa Sector Mundo 07-SRNP-58821 Rica Guanacaste ACG Nuevo Quebrada Tibio Perla 10.76 -85.43 330 A Costa 07-SRNP-23976 Rica Guanacaste ACG Sector Del Oro Quebrada Trigal 11.03 -85.50 290 A Costa Sector Mundo 07-SRNP-59078 Rica Guanacaste ACG Nuevo Quebrada Tibio Perla 10.76 -85.43 330 A 09-SRNP- Costa Sector Mundo 105641 Rica Guanacaste ACG Nuevo Manta Canon 10.77 -85.37 700 A Costa 06-SRNP-15793 Rica Guanacaste ACG Sector Santa Rosa Cuesta Canyon Tigre 10.82 -85.64 270 A Costa Sector Mundo 06-SRNP-56730 Rica Guanacaste ACG Nuevo Vado Ficus 10.77 -85.43 375 A Costa 06-SRNP-15789 Rica Guanacaste ACG Sector Santa Rosa Cuesta Canyon Tigre 10.82 -85.64 270 A Costa 06-SRNP-15726 Rica Guanacaste ACG Sector Santa Rosa Cuesta Canyon Tigre 10.82 -85.64 270 A Costa 06-SRNP-15807 Rica Guanacaste ACG Sector Santa Rosa Cuesta Canyon Tigre 10.82 -85.64 270 A Costa 06-SRNP-15761 Rica Guanacaste ACG Sector Santa Rosa Cuesta Canyon Tigre 10.82 -85.64 270 A Costa Sector Mundo 06-SRNP-56280 Rica Guanacaste ACG Nuevo Quebrada Tibio Perla 10.76 -85.43 330 A Costa 06-SRNP-15995 Rica Guanacaste ACG Sector Santa Rosa Luces 10.85 -85.61 300 A Costa 08-SRNP-13101 Rica Guanacaste ACG Sector Santa Rosa Sendero Natural 10.84 -85.61 290 A Costa 08-SRNP-13452 Rica Guanacaste ACG Sector Santa Rosa Area Administrativa 10.84 -85.62 295 A Costa 05-SRNP-45896 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 05-SRNP-46265 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 05-SRNP-45880 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A

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Costa 05-SRNP-45879 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa Sector Mundo 06-SRNP-56489 Rica Guanacaste ACG Nuevo Mamones 10.77 -85.43 365 A Costa 03-SRNP-15400 Rica Guanacaste ACG Sector Del Oro Quebrada Trigal 11.03 -85.50 290 A Costa 02-SRNP-9758 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 05-SRNP-13504 Rica Guanacaste ACG Sector Santa Rosa Luces 10.85 -85.61 300 A Costa 02-SRNP-16193 Rica Guanacaste ACG Sector El Hacha Finca Araya 11.02 -85.51 295 A Costa 06-SRNP-15739 Rica Guanacaste ACG Sector Santa Rosa Cuesta Canyon Tigre 10.82 -85.64 270 A Costa 06-SRNP-15686 Rica Guanacaste ACG Sector Santa Rosa Cuesta Canyon Tigre 10.82 -85.64 270 A Costa 05-SRNP-14107 Rica Guanacaste ACG Sector Santa Rosa Luces 10.85 -85.61 300 A Costa 06-SRNP-16005 Rica Guanacaste ACG Sector Santa Rosa Luces 10.85 -85.61 300 A Costa 08-SRNP-13097 Rica Guanacaste ACG Sector Santa Rosa Sendero Natural 10.84 -85.61 290 A Costa Sectpr Rincon Rain 09-SRNP-44264 Rica Alajuela ACG Forest Estacion Llanura 10.93 -85.25 135 A Costa Sectpr Rincon Rain 09-SRNP-44263 Rica Alajuela ACG Forest Estacion Llanura 10.93 -85.25 135 A Costa 09-SRNP-31201 Rica Guanacaste ACG Sector Pitilla Loaiciga 11.02 -85.41 445 A Costa 08-SRNP-21563 Rica Guanacaste ACG Sector El Hacha Estacion Los Almendros 11.03 -85.53 290 A Costa 109 08-SRNP-35020 Rica Guanacaste ACG Sector Cacao Sendero Nayo 10.92 -85.47 0 A Costa 08-SRNP-21739 Rica Guanacaste ACG Sector Del Oro Quebrada Trigal 11.03 -85.50 290 A Costa Sector Mundo 05-SRNP-57568 Rica Guanacaste ACG Nuevo Vado Zanja Tapada 10.77 -85.38 550 A Costa Sector San 03-SRNP-5827 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A 03-SRNP-4163 Costa Guanacaste ACG Sector Cacao Estacion Cacao 10.93 -85.47 115 A

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Rica 0 Costa 109 03-SRNP-3155 Rica Guanacaste ACG Sector Cacao Sendero Nayo 10.92 -85.47 0 A Costa Sector San 05-SRNP-2206 Rica Alajuela ACG Cristobal Puente Palma 10.92 -85.38 460 A Costa 109 05-SRNP-35079 Rica Guanacaste ACG Sector Cacao Sendero Nayo 10.92 -85.47 0 A Costa 118 05-SRNP-35212 Rica Guanacaste ACG Sector Cacao Sendero Circular 10.93 -85.47 5 A Costa Sector San 08-SRNP-1806 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Sector San 08-SRNP-2295 Rica Alajuela ACG Cristobal Puente Palma 10.92 -85.38 460 A Costa Sector Mundo 07-SRNP-55685 Rica Guanacaste ACG Nuevo Vado Chamaedorea 10.78 -85.40 570 A Costa Sector Mundo 06-SRNP-56419 Rica Guanacaste ACG Nuevo Vado Licania 10.77 -85.41 470 A Costa Sector Mundo 06-SRNP-56553 Rica Guanacaste ACG Nuevo Vado Huacas 10.76 -85.39 490 A Costa 109 00-SRNP-9489 Rica Guanacaste ACG Sector Cacao Sendero Nayo 10.92 -85.47 0 A Costa 118 00-SRNP-9501 Rica Guanacaste ACG Sector Cacao Sendero Circular 10.93 -85.47 5 A Costa 03-SRNP-3023 Rica Guanacaste ACG Sector Cacao Sendero Maritza 10.94 -85.48 760 A Costa 115 03-SRNP-3580 Rica Guanacaste ACG Sector Cacao Estacion Cacao 10.93 -85.47 0 A Costa Sector San 04-SRNP-1845 Rica Alajuela ACG Cristobal Puente Palma 10.92 -85.38 460 A

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Appendix B: Chapter 2 Supplementary Tables and Materials

Table B.1 Supportive data on the collection of all 299 Urbanus belli complex specimens found in the DNA barcode COI library (associated with Figure 2.1).

Life Sample ID Country Province Region Sector Exact Site Lat Lon Elev Stage Costa Sector Santa Casa Potrero 04-SRNP-15160 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15153 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15679 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15149 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15189 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15161 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15155 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15147 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15146 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15154 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15137 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15162 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15150 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A 04-SRNP-15674 Costa Guanacaste ACG Sector Santa Casa Potrero 10.85 -85.77 17 A

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Rica Elena Grande Costa Sector Santa Casa Potrero 04-SRNP-15680 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15677 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa 04-SRNP-48641 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 04-SRNP-48028 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 04-SRNP-48033 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 04-SRNP-47563 Rica Guanacaste ACG Sector Cacao Gongora Bananal 10.89 -85.48 600 A Costa Sector Santa Casa Potrero 04-SRNP-14307 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-14390 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-14389 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Rincon Rain Camino Rio 04-SRNP-41681 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain Camino Rio 04-SRNP-41680 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa 04-SRNP-48639 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 04-SRNP-47956 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 04-SRNP-47824 Rica Guanacaste ACG Sector Cacao Gongora Bananal 10.89 -85.48 600 A Costa 04-SRNP-14108 Rica Guanacaste ACG Potrerillos Rio Azufrado 10.81 -85.54 95 A Costa Rincon Rain 01-SRNP-5310 Rica Alajuela ACG forest Rio Francia Arriba 10.9 -85.29 400 A Costa Rincon Rain 01-SRNP-5311 Rica Alajuela ACG forest Rio Francia Arriba 10.9 -85.29 400 A Costa Sector San 01-SRNP-3745 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Sector San 01-SRNP-3404 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A

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Costa Rincon Rain Camino Rio 01-SRNP-23060 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Sector Santa Vado Quebrada 02-SRNP-13670 Rica Guanacaste ACG Elena Calera 10.87 -85.65 305 A Costa Sector San 02-SRNP-2246 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa 02-SRNP-28991 Rica Guanacaste ACG Sector Del Oro Camino Mangos 11.01 -85.48 480 A Costa Sector Santa 02-SRNP-32169 Rica Guanacaste ACG Elena Vado Calliandra 10.86 -85.66 290 A Costa Sector Santa Vado Quebrada 02-SRNP-11533 Rica Guanacaste ACG Elena Calera 10.87 -85.65 305 A Costa Sector Santa Vado Quebrada 02-SRNP-13111 Rica Guanacaste ACG Elena Calera 10.87 -85.65 305 A Costa Sector San 02-SRNP-1028 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Sector Santa 02-SRNP-13671 Rica Guanacaste ACG Elena Vado Calliandra 10.86 -85.66 290 A Costa Sector San 02-SRNP-163 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa 04-SRNP-33067 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa 04-SRNP-21152 Rica Guanacaste ACG Sector Del Oro Quebrada Lajosa 11.03 -85.43 400 A Costa 04-SRNP-31053 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa 04-SRNP-22913 Rica Guanacaste ACG Sector Del Oro Puente Mena 11.05 -85.46 280 A Costa 04-SRNP-45034 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 04-SRNP-20680 Rica Guanacaste ACG Sector Del Oro Quebrada Lajosa 11.03 -85.43 400 A Costa 04-SRNP-20872 Rica Guanacaste ACG Sector Del Oro Margarita 11.03 -85.44 380 A Costa 04-SRNP-20925 Rica Guanacaste ACG Sector Del Oro Quebrada Lajosa 11.03 -85.43 400 A Costa 10-SRNP-103604 Rica Alajuela ACG Leiva Protrero Chaves 10.94 -85.32 433 A 01-SRNP-3403 Costa Alajuela ACG Sector San Rio Blanco Abajo 10.9 -85.37 500 A

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Rica Cristobal Costa Rincon Rain 02-SRNP-21477 Rica Alajuela ACG forest Sendero Rincon 10.9 -85.28 430 A Costa Rincon Rain Camino Rio 03-SRNP-12581.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain 03-SRNP-12948.1 Rica Alajuela ACG forest Finca Melina 10.89 -85.29 410 A Costa Rincon Rain 07-SRNP-41928 Rica Alajuela ACG forest Puente Rio Negro 10.9 -85.30 340 A Costa Sector San 08-SRNP-4727 Rica Alajuela ACG Cristobal Sendero Huerta 10.93 -85.37 527 A Costa Sector Mundo 06-SRNP-59672 Rica Guanacaste ACG Nuevo Vado Ocotea 10.76 -85.38 565 A Costa Sector Santa Casa Potrero 04-SRNP-14305 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Rincon Rain 06-SRNP-40146 Rica Alajuela ACG forest Sendero Juntas 10.91 -85.29 400 A Costa 07-SRNP-20167 Rica Guanacaste ACG Sector Del Oro Puente Mena 11.05 -85.46 280 A Costa 04-SRNP-47963 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 07-SRNP-45088 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa Rincon Rain 07-SRNP-40762 Rica Alajuela ACG forest Sendero Juntas 10.91 -85.29 400 A Costa 07-SRNP-30617 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa Sector Mundo 06-SRNP-60091 Rica Guanacaste ACG Nuevo Vado Miramonte 10.77 -85.43 305 A Costa 06-SRNP-47955 Rica Guanacaste ACG Sector Cacao Sendero Pajarito 10.89 -85.47 600 A Costa Sector Mundo 06-SRNP-59197 Rica Guanacaste ACG Nuevo Vado Licania 10.77 -85.41 470 A Costa Quebrada 06-SRNP-46570 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa 06-SRNP-46180 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-46176 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A

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Costa 06-SRNP-47233 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa Sector San 06-SRNP-7474 Rica Alajuela ACG Cristobal Rio Areno 10.91 -85.38 460 A Costa Sector San 06-SRNP-6164 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Quebrada 06-SRNP-46703 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa Sector San 06-SRNP-7378 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa 06-SRNP-46183 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-46487 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-46333 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Rincon Rain 06-SRNP-43281 Rica Alajuela ACG forest Vado Rio Francia 10.9 -85.29 400 A Costa 06-SRNP-32923 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa 06-SRNP-46181 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Sector San 06-SRNP-5512 Rica Alajuela ACG Cristobal Camino Brasilia 10.93 -85.37 500 A Costa 06-SRNP-30699 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa Sector San 06-SRNP-3004 Rica Alajuela ACG Cristobal Sendero Palo Alto 10.88 -85.38 570 A Costa Sector San 06-SRNP-2656 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Rincon Rain 05-SRNP-43001 Rica Alajuela ACG forest Puente Rio Negro 10.9 -85.30 340 A Costa Rincon Rain 06-SRNP-40981 Rica Alajuela ACG forest Rio Francia Arriba 10.9 -85.29 400 A Costa Sector San 06-SRNP-2074 Rica Alajuela ACG Cristobal Sendero Perdido 10.88 -85.39 620 A Costa Sector San 06-SRNP-2199 Rica Alajuela ACG Cristobal Finca San Gabriel 10.88 -85.39 645 A 06-SRNP-30737 Costa Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A

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Rica Costa Rincon Rain Camino Rio 05-SRNP-40888 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa 05-SRNP-45196 Rica Guanacaste ACG Sector Cacao Sendero Guayabal 10.89 -85.48 500 A Costa Rincon Rain 05-SRNP-42399 Rica Alajuela ACG forest Sendero Juntas 10.91 -85.29 400 A Costa Rincon Rain 05-SRNP-40898 Rica Alajuela ACG forest Sendero Parcelas 10.91 -85.29 375 A Costa 05-SRNP-47058 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Rincon Rain Quebrada 05-SRNP-42700 Rica Alajuela ACG forest Guarumo 10.9 -85.28 400 A Costa 05-SRNP-47229 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa 05-SRNP-20694 Rica Guanacaste ACG Sector Del Oro Margarita 11.03 -85.44 380 A Costa 05-SRNP-47232 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa Sector San 04-SRNP-4302 Rica Alajuela ACG Cristobal Puente Palma 10.92 -85.38 460 A Costa 04-SRNP-21913 Rica Guanacaste ACG Sector Del Oro Quebrada Lajosa 11.03 -85.43 400 A Costa Rincon Rain Camino Rio 03-SRNP-12633.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain Camino Rio 03-SRNP-12657.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain Camino Rio 03-SRNP-12627.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain 03-SRNP-12947.1 Rica Alajuela ACG forest Finca Melina 10.89 -85.29 410 A Costa Rincon Rain 03-SRNP-11566 Rica Alajuela ACG forest Finca Aurita 10.88 -85.26 460 A Costa Rincon Rain Camino Rio 03-SRNP-12345.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain Camino Rio 03-SRNP-10529 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain 03-SRNP-12298.1 Rica Alajuela ACG forest Sendero Juntas 10.91 -85.29 400 A

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Costa Rincon Rain Camino Rio 03-SRNP-11211 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa 04-SRNP-21912 Rica Guanacaste ACG Sector Del Oro Quebrada Lajosa 11.03 -85.43 400 A Costa Rincon Rain 01-SRNP-23117 Rica Alajuela ACG forest Sendero Parcelas 10.91 -85.29 375 A Costa Rincon Rain 02-SRNP-7107 Rica Alajuela ACG forest Sendero Anonas 10.9 -85.28 405 A Costa 01-SRNP-1028 Rica Alajuela ACG El Ensayo Camino Ensayo 10.95 -85.37 500 A Costa Sector San 01-SRNP-22505 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Sector San 00-SRNP-22025 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa 99-SRNP-2440 Rica Guanacaste ACG Sector Del Oro Quebrada Serrano 11 -85.46 585 A Costa Sector San 02-SRNP-590 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Rincon Rain Camino Rio 02-SRNP-7734 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain Camino Rio 01-SRNP-5700 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Sector San 00-SRNP-1534 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa 00-SRNP-2200 Rica Guanacaste ACG Sector El Hacha Sendero Bejuquilla 11.03 -85.53 280 A Costa Sector San 00-SRNP-22026 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Sector Santa 02-SRNP-12992 Rica Guanacaste ACG Elena Quebrada Chiquita 10.88 -85.69 410 A Costa Quebrada 04-SRNP-49712 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa Quebrada 04-SRNP-49960 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa Quebrada 04-SRNP-49714 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa Quebrada 04-SRNP-49963 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A 04-SRNP-49713 Costa Guanacaste ACG Sector Cacao Quebrada 10.89 -85.49 390 A

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Rica Heliconia Costa Quebrada 04-SRNP-49711 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa 05-SRNP-49623 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa Sector San 01-SRNP-22185 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Rincon Rain Quebrada 05-SRNP-43429 Rica Alajuela ACG forest Guarumo 10.9 -85.28 400 A Costa 06-SRNP-31091 Rica Guanacaste ACG Sector Pitilla Ingas 11 -85.42 580 A Costa 06-SRNP-46459 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa 06-SRNP-19690 Rica Guanacaste ACG Potrerillos Rio Azufrado 10.81 -85.54 95 A Costa Sector San 07-SRNP-1053 Rica Alajuela ACG Cristobal Camino Brasilia 10.93 -85.37 500 A Costa 06-SRNP-47304 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 07-SRNP-23883 Rica Guanacaste ACG Sector Del Oro Quebrada Lajosa 11.03 -85.43 400 A Costa 06-SRNP-46173 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-48039 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 98-SRNP-4170 Rica Guanacaste ACG Sector Del Oro Quebrada Serrano 11 -85.46 585 A Costa 05-SRNP-47230 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa Rincon Rain 05-SRNP-42614 Rica Alajuela ACG forest Sendero Bejuco 10.91 -85.28 400 A Costa 07-SRNP-45068 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 06-SRNP-47295 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-31265 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa Sector Santa 05-SRNP-60977 Rica Guanacaste ACG Rosa Quebrada Puercos 10.86 -85.57 155 A

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Costa Rincon Rain 05-SRNP-42873 Rica Alajuela ACG forest Montanya Figueres 10.88 -85.29 460 A Costa Rincon Rain 06-SRNP-40907 Rica Alajuela ACG forest Sendero Bejuco 10.77 -85.60 180 A Costa 07-SRNP-20462 Rica Guanacaste ACG Sector Del Oro Bosque Aguirre 11 -85.44 620 A Costa Sector Santa 96-SRNP-11569 Rica Guanacaste ACG Rosa Las Mesas 10.85 -85.61 305 A Costa Rincon Rain 07-SRNP-41187 Rica Alajuela ACG forest Rio Francia Arriba 10.9 -85.29 400 A Costa Sector Santa Area 92-SRNP-3666 Rica Guanacaste ACG Rosa Administrativa 10.84 -85.62 295 A Costa Sector Santa 93-SRNP-6910 Rica Guanacaste ACG Rosa Tanquetas 10.87 -85.61 295 A Costa Sector Santa 93-SRNP-6785 Rica Guanacaste ACG Rosa Cafetal 10.86 -85.61 280 A Costa Sector Santa 93-SRNP-3897 Rica Guanacaste ACG Rosa Cafetal 10.86 -85.61 280 A Costa Sector Santa Mirador Santa 93-SRNP-3810 Rica Guanacaste ACG Rosa Elena 10.87 -85.61 305 A Costa Sector Rincon 11-SRNP-41167 Rica Alajuela ACG Rain Forest Sendero Juntas 10.91 -85.29 400 A Costa 10-SRNP-32075 Rica Guanacaste ACG Sector Pitilla Ingas 11 -85.42 580 A Costa Sector Mundo 10-SRNP-56022 Rica Guanacaste ACG Nuevo Camino Pozo Tres 10.77 -85.37 733 A Costa Sector Mundo 10-SRNP-56020 Rica Guanacaste ACG Nuevo Camino Pozo Tres 10.77 -85.37 733 A Costa Sector Mundo 10-SRNP-56021 Rica Guanacaste ACG Nuevo Camino Pozo Tres 10.77 -85.37 733 A Costa Sector Rincon 09-SRNP-69873 Rica Alajuela ACG Rain Forest Jacobo 10.94 -85.32 461 A Costa Laguna Agua 08-SRNP-24278 Rica Guanacaste ACG Sector El Hacha Buena 11.03 -85.57 220 A Costa 08-SRNP-23800 Rica Guanacaste ACG Sector El Hacha Vuelta Peligrosa 11.03 -85.54 280 A Costa Sector San 08-SRNP-5848 Rica Alajuela ACG Cristobal Sendero Huerta 10.93 -85.37 527 A 08-SRNP-65935 Costa Alajuela ACG Brasilia Moga 11.01 -85.35 320 A

137

Rica Costa Sector San 08-SRNP-1439 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa 08-SRNP-65153 Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A Costa 07-SRNP-65582 Rica Alajuela ACG Brasilia Piedrona 11.02 -85.36 340 A Costa 07-SRNP-33232 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa Sector San 07-SRNP-1119 Rica Alajuela ACG Cristobal Camino Brasilia 10.93 -85.37 500 A Costa Rincon Rain 07-SRNP-42421 Rica Alajuela ACG forest Sendero Juntas 10.91 -85.29 400 A Costa Rincon Rain 07-SRNP-42423 Rica Alajuela ACG forest Sendero Juntas 10.91 -85.29 400 A Costa 07-SRNP-31148 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa 07-SRNP-31150 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa 07-SRNP-20874 Rica Guanacaste ACG Sector Del Oro Monte Cristo 11.01 -85.43 525 A Costa 07-SRNP-31149 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa 07-SRNP-20875 Rica Guanacaste ACG Sector Del Oro Monte Cristo 11.01 -85.43 525 A Costa 07-SRNP-30807 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa 07-SRNP-30614 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa 07-SRNP-45090 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 04-SRNP-47882 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 04-SRNP-47558 Rica Guanacaste ACG Sector Cacao Gongora Bananal 10.89 -85.48 600 A Costa Sector Santa 93-SRNP-3407 Rica Guanacaste ACG Rosa Cafetal 10.86 -85.61 280 A Costa Sector Santa Area 93-SRNP-4203 Rica Guanacaste ACG Rosa Administrativa 10.84 -85.62 295 A

138

Costa Rincon Rain Camino Rio 04-SRNP-41942 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Sector Santa Casa Potrero 04-SRNP-15157 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa 06-SRNP-47801 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Sector San 02-SRNP-1026 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Sector Mundo 05-SRNP-59447 Rica Guanacaste ACG Nuevo Porton Rivas 10.76 -85.37 570 A Costa Sector Santa 03-SRNP-12592 Rica Guanacaste ACG Elena Mancha 10.85 -85.67 330 A Costa 06-SRNP-46184 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Sector Mundo Quebrada Tibio 07-SRNP-55283 Rica Guanacaste ACG Nuevo Perla 10.76 -85.43 330 A Costa 07-SRNP-30615 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa 07-SRNP-20318 Rica Guanacaste ACG Sector Del Oro Lajosa 11.03 -85.43 400 A Costa Sector 06-SRNP-18276 Rica Guanacaste ACG Horizontes Vado Esperanza 10.79 -85.55 85 A Costa Sector Mundo Cerro Gongora 07-SRNP-57868 Rica Guanacaste ACG Nuevo Pelado 10.76 -85.41 740 A Costa Sector Rincon 10-SRNP-80316 Rica Alajuela ACG Rain Forest Cafecito 10.94 -85.32 455 A Costa Sector Santa Area 93-SRNP-3098 Rica Guanacaste ACG Rosa Administrativa 10.84 -85.62 295 A Costa Sector Santa Area 93-SRNP-4205 Rica Guanacaste ACG Rosa Administrativa 10.84 -85.62 295 A Costa Sector Santa Camino Rosa 93-SRNP-3294 Rica Guanacaste ACG Rosa Maria 10.83 -85.61 285 A Costa 04-SRNP-45491 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Rincon Rain Camino Rio 03-SRNP-12624.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain Camino Rio 03-SRNP-12634.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A 06-SRNP-47816 Costa Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A

139

Rica Costa 07-SRNP-45071 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa 08-SRNP-31826 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa 10-SRNP-31880 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa 10-SRNP-31881 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa 06-SRNP-30895 Rica Guanacaste ACG Sector Pitilla Loaiciga 11.02 -85.41 445 A Costa Sector Santa Area 95-SRNP-10572 Rica Guanacaste ACG Rosa Administrativa 10.84 -85.62 295 A Costa Sector San 01-SRNP-2952 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Rincon Rain Camino Rio 01-SRNP-4475 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Sector San Vado Rio 01-SRNP-487 Rica Alajuela ACG Cristobal Cucaracho 10.87 -85.39 640 A Costa Sector San 06-SRNP-3621 Rica Alajuela ACG Cristobal Camino Brasilia 10.93 -85.37 500 A Costa Sector San 02-SRNP-166 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Rincon Rain 07-SRNP-40856 Rica Alajuela ACG forest Sendero Bejuco 10.77 -85.60 180 A Costa 93-SRNP-6827 Rica Guanacaste ACG Sector Pocosol Torres Centeno 10.89 -85.59 230 A Costa 06-SRNP-47814 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-30896 Rica Guanacaste ACG Sector Pitilla Loaiciga 11.02 -85.41 445 A Costa 06-SRNP-46174 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-46171 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Sector Mundo Quebrada Tibio 06-SRNP-57638 Rica Guanacaste ACG Nuevo Perla 10.76 -85.43 330 A Costa Sector Mundo 07-SRNP-56547 Rica Guanacaste ACG Nuevo Vado Huacas 10.76 -85.39 490 A

140

Costa Sector Mundo 07-SRNP-56829 Rica Guanacaste ACG Nuevo Punta Plancha 10.74 -85.43 420 A Costa 07-SRNP-30613 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa Rincon Rain Camino Rio 07-SRNP-40676 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa 06-SRNP-47817 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-46460 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa 06-SRNP-46639 Rica Guanacaste ACG Sector Cacao Sendero Guayabal 10.89 -85.48 500 A Costa Sector San 06-SRNP-6511 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa 06-SRNP-46315 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-46179 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Quebrada 06-SRNP-46572 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa 06-SRNP-46486 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-46172 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 06-SRNP-2658 Rica Guanacaste ACG Los Angeles Tajo Angeles 10.86 -85.42 540 A Costa Sector Santa 05-SRNP-19630 Rica Guanacaste ACG Elena Vado Coyolito 10.86 -85.68 40 A Costa 06-SRNP-2662 Rica Guanacaste ACG Los Angeles Tajo Angeles 10.86 -85.42 540 A Costa 05-SRNP-47231 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa 05-SRNP-47043 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Sector Mundo 05-SRNP-59444 Rica Guanacaste ACG Nuevo Porton Rivas 10.76 -85.37 570 A Costa Sector Mundo 05-SRNP-59448 Rica Guanacaste ACG Nuevo Porton Rivas 10.76 -85.37 570 A 05-SRNP-1832 Costa Alajuela ACG Sector San Potrero Argentina 10.89 -85.39 520 A

141

Rica Cristobal Costa 04-SRNP-45494 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 03-SRNP-29774 Rica Guanacaste ACG Sector Del Oro Chon 11.05 -85.45 280 A Costa 04-SRNP-45492 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa 04-SRNP-45586 Rica Guanacaste ACG Sector Cacao Quebrada Otilio 10.89 -85.48 550 A Costa Sector San 02-SRNP-1417 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Sector San Vado Rio 02-SRNP-954 Rica Alajuela ACG Cristobal Cucaracho 10.87 -85.39 640 A Costa 95-SRNP-6826 Rica Guanacaste ACG Sector Junquillal Estacion Junquillal 10.97 -85.69 5 A Costa Quebrada 04-SRNP-49377 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa Sector Santa Casa Potrero 04-SRNP-14877 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa Casa Potrero 04-SRNP-15145 Rica Guanacaste ACG Elena Grande 10.85 -85.77 17 A Costa Sector Santa 04-SRNP-15474 Rica Guanacaste ACG Rosa Cafetal 10.86 -85.61 280 A Costa Quebrada 04-SRNP-48357 Rica Guanacaste ACG Sector Cacao Heliconia 10.89 -85.49 390 A Costa 04-SRNP-47954 Rica Guanacaste ACG Sector Cacao Cuesta Caimito 10.89 -85.47 640 A Costa Sector Santa Area 04-SRNP-14569 Rica Guanacaste ACG Rosa Administrativa 10.84 -85.62 295 A Costa Sector Santa 02-SRNP-32172 Rica Guanacaste ACG Elena Vado Calliandra 10.86 -85.66 290 A Costa Sector San Quebrada 02-SRNP-392 Rica Alajuela ACG Cristobal Cementerio 10.87 -85.39 700 A Costa 04-SRNP-20968 Rica Guanacaste ACG Sector Del Oro Quebrada Lajosa 11.03 -85.43 400 A Costa 04-SRNP-20876 Rica Guanacaste ACG Sector Del Oro Margarita 11.03 -85.44 380 A Costa Rincon Rain Camino Rio 03-SRNP-12654.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A

142

Costa Sector San 07-SRNP-1121 Rica Alajuela ACG Cristobal Camino Brasilia 10.93 -85.37 500 A Costa Sector San 07-SRNP-1122 Rica Alajuela ACG Cristobal Camino Brasilia 10.93 -85.37 500 A Costa 06-SRNP-65065 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa 07-SRNP-33182 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa 08-SRNP-65993 Rica Alajuela ACG Brasilia Gallinazo 11.02 -85.37 360 A Costa 08-SRNP-66028 Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A Costa 07-SRNP-33183 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa 07-SRNP-33184 Rica Guanacaste ACG Sector Pitilla Amonias 11.04 -85.40 390 A Costa Sector San 07-SRNP-287 Rica Alajuela ACG Cristobal Camino Brasilia 10.93 -85.37 500 A Costa Rincon Rain 07-SRNP-40761 Rica Alajuela ACG forest Sendero Juntas 10.91 -85.29 400 A Costa 06-SRNP-46887 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa Sector San 06-SRNP-7473 Rica Alajuela ACG Cristobal Rio Areno 10.91 -85.38 460 A Costa 06-SRNP-46891 Rica Guanacaste ACG Sector Cacao Puente Gongora 10.89 -85.47 540 A Costa Sector San 05-SRNP-7209 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Rincon Rain 05-SRNP-40545 Rica Alajuela ACG forest Vochysia 10.87 -85.25 320 A Costa Rincon Rain 05-SRNP-41753 Rica Alajuela ACG forest Sendero Rincon 10.9 -85.28 430 A Costa Rincon Rain Camino Rio 03-SRNP-12629.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain 03-SRNP-10927 Rica Alajuela ACG forest Rio Francia Arriba 10.9 -85.29 400 A Costa Rincon Rain Camino Rio 03-SRNP-12109.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A 03-SRNP-10327 Costa Alajuela ACG Rincon Rain Camino Rio 10.9 -85.29 410 A

143

Rica forest Francia Costa Rincon Rain Camino Rio 03-SRNP-12655.1 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Sector San 99-SRNP-5541 Rica Alajuela ACG Cristobal Sendero Corredor 10.88 -85.39 620 A Costa Rincon Rain Camino Rio 01-SRNP-23227 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain Camino Rio 04-SRNP-42794 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Sector San 01-SRNP-22184 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Rincon Rain Camino Rio 01-SRNP-23228 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Sector San 01-SRNP-2104 Rica Alajuela ACG Cristobal Rio Blanco Abajo 10.9 -85.37 500 A Costa Rincon Rain 02-SRNP-7163 Rica Alajuela ACG forest Sendero Parcelas 10.91 -85.29 375 A Costa 06-SRNP-31264 Rica Guanacaste ACG Sector Pitilla Pasmompa 11.02 -85.41 440 A Costa Rincon Rain Camino Rio 06-SRNP-43129 Rica Alajuela ACG forest Francia 10.9 -85.29 410 A Costa Rincon Rain 05-SRNP-42394 Rica Alajuela ACG forest Sendero Juntas 10.91 -85.29 400 A Costa Sector Mundo 09-SRNP-57089 Rica Guanacaste ACG Nuevo Camino Pozo Tres 10.77 -85.37 733 A

Costa ACG Sector Santa A 04-SRNP-15286 Rica Guanacaste Rosa Bosque Humedo 10.851 -85.608 290

Costa ACG Sector Mundo A 05-SRNP-66411 Rica Guanacaste Nuevo Vado Miramonte 10.772 -85.434 305

Costa ACG Sector San A 06-SRNP-1984 Rica Alajuela Cristobal Suampo Uncaria 11.018 -85.474 370

Costa ACG Sector San A 07-SRNP-1369 Rica Alajuela Cristobal Camino Brasilia 10.93 -85.372 500

144

Costa ACG Sector Mundo A 07-SRNP-56430 Rica Guanacaste Nuevo Vado Miramonte 10.772 -85.434 305

Costa ACG Sector Mundo Cerro Gongora A 07-SRNP-57861 Rica Guanacaste Nuevo Pelado 10.763 -85.413 740

Costa ACG Sector Mundo Cerro Gongora A 07-SRNP-57862 Rica Guanacaste Nuevo Pelado 10.763 -85.413 740

Costa ACG Sector Mundo A 07-SRNP-57988 Rica Guanacaste Nuevo Camino Brisas 10.74 -85.416 380

Costa ACG A 08-SRNP-71995 Rica Guanacaste Sector Pitilla Estacion Quica 10.997 -85.397 470

Table B.2 Sequence-types of ITS2 sequences from U.belli specimens used in the ITS2 secondary structure and compensatory basepair change analysis.

Sequence-types Sample IDs Provisional species Sequence-type 0 05-SRNP-42394 Urbanus belliDHJ03 06-SRNP-43129 Urbanus belliDHJ03 07-SRNP-33183 Urbanus belliDHJ03 07-SRNP-33182 Urbanus belliDHJ03 07-SRNP-33184 Urbanus belliDHJ03 07-SRNP-40761 Urbanus belliDHJ03 08-SRNP-66028 Urbanus belliDHJ03 08-SRNP-65993 Urbanus belliDHJ03

145

Sequence-type 1 06-SRNP-18276_b Urbanus belliDHJ02 06-SRNP-47816_b Urbanus belliDHJ02 07-SRNP-45071 Urbanus belliDHJ02 07-SRNP-30615 Urbanus belliDHJ02 07-SRNP-56829 Urbanus belliDHJ02 07-SRNP-57868 Urbanus belliDHJ02 Sequence-type 2 07-SRNP-65582 Urbanus belliDHJ01 06-SRNP-46570_b Urbanus belliDHJ01 08-SRNP-23800 Urbanus belliDHJ01 08-SRNP-24278_c Urbanus belliDHJ01 Sequence-type 3 07-SRNP-41187_c Urbanus belliDHJ01 07-SRNP-41187_a Urbanus belliDHJ01 06-SRNP-47304 Urbanus belliDHJ01 Sequence-type 4 06-SRNP-47816_a Urbanus belliDHJ02 06-SRNP-47801 Urbanus belliDHJ02 07-SRNP-56547 Urbanus belliDHJ02 Sequence-type 5 07-SRNP-33232 Urbanus belliDHJ01 08-SRNP-5848 Urbanus belliDHJ01 Sequence-type 6 06-SRNP-46460_a Urbanus belliDHJ02 06-SRNP-46572 Urbanus belliDHJ02 Sequence-type 7 06-SRNP-47304_a Urbanus belliDHJ01 Sequence-type 8 06-SRNP-46891_a Urbanus belliDHJ01 Sequence-type 9 08-SRNP-24278_a Urbanus belliDHJ01 Sequence-type 10 01-SRNP-4475 Urbanus belliDHJ02 Sequence-type 11 06-SRNP-18276_a Urbanus belliDHJ01 Sequence-type 12 06-SRNP-46460_b Urbanus belliDHJ01 Sequence-type 13 06-SRNP-46460_c Urbanus belliDHJ01 Sequence-type 14 07-SRNP-20318 Urbanus belliDHJ02 Sequence-type 15 07-SRNP-30613 Urbanus belliDHJ02 Sequence-type 16 08-SRNP-24278_b Urbanus belliDHJ01 Sequence-type 17 06-SRNP-47955 Urbanus belliDHJ01 Sequence-type 18 08-SRNP-1439 Urbanus belliDHJ01 Sequence-type 19 06-SRNP-46570_a Urbanus belliDHJ01 Sequence-type 20 06-SRNP-47304_b Urbanus belliDHJ01 Sequence-type 21 07-SRNP-30614 Urbanus belliDHJ01

146

Sequence-type 22 08-SRNP-4727 Urbanus belliDHJ01 Sequence-type 23 06-SRNP-46887_c Urbanus belliDHJ03 Sequence-type 24 06-SRNP-46891 Urbanus belliDHJ03 Sequence-type 25 05-SRNP-41753 Urbanus belliDHJ03 Sequence-type 26 06-SRNP-46887_a Urbanus belliDHJ03 Sequence-type 27 06-SRNP-46891_c Urbanus belliDHJ01 Sequence-type 28 06-SRNP-46891_d Urbanus belliDHJ01 Sequence-type 29 06-SRNP-46891_b Urbanus belliDHJ01 Sequence-type 30 07-SRNP-41187_b Urbanus belliDHJ01

Nucleotide and secondary structure alignments of ITS2 sequence-types used in the ITS2 secondary structure and compensatory basepair change analysis.

>06-SRNP-46887_c__Urbanus_belliDHJ03

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATTCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGTGTGGACATATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAC-TAAA-

TGCAGTGCGATTTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCC--

CGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATATGTTACGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCTGTCGCACCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

147

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... ((((((.(((....)))))))))((.(((((((((..((((((((...((((((....))))))....))))).))).)))))...)))).))..-...)-

))))(((((((.((((((((((((..((((((((...... (((((((.--(((((.((((((...... ((((...(((((...((((.((((..((((((....)))))).))-))---.))))...)))))...)))).)))).))..))))).)))))))..-

))))))))...))))))))))))....))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>06-SRNP-46891_Urbanus_belliDHJ03

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAT-

GAAA-TACAGTGCGTTTTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCG--

CGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATATGTTACGTGCTTCGGCACGTTAA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))))(((....(((((((((((..((((((((...... ((((((((--(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))..)-))---.))))...)))))...)))).)))).))..)))))))))))))..-

148

))))))))...)))))))))))(((((...... )))))((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... ))))))))))))))..))))).

...... ))......

>05-SRNP-41753_Urbanus_belliDHJ03

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGTGTGGACATATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAC-TAAA-

TGCAGTGCGATTTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCC--

CGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATATGTTACGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGAGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCTGTCGCACCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... ((((((.(((....)))))))))((.(((((((((..((((((((...((((((....))))))....))))).))).)))))...)))).))..-...)-

))))(((((((.((((((((((((..((((((((...... (((((((.--(((((.((((((...... ((((...(((((...((((.((((..((((((....)))))).))-))---.))))...)))))...)))).)))).))..)))))...)))))))-

))))))))...))))))))))))....))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>06-SRNP-46887_a__Urbanus_belliDHJ03

149

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGTGTGGACATATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGGCGTCGG------TCCGTTTAAATATATCAT-GAAA-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TAATACGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... ((((((.(((....)))))))))((.(((((((((..(((...(((..((((((....))))))))).)))------.)))))...)))).))..-...)-

))))))(((....(((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))...-..))).))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...)))))))))))(((((...... )))))((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... ))))))))))))))..))))).

...... ))......

>haplotype 0_05-SRNP-42394_Urbanus_belliDHJ03

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGTGTGGACATATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAC-TAAA-

TGCAGTGCGATTTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATATGTTACGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCTGTCGCACCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

150

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... ((((((.(((....)))))))))((.(((((((((..((((((((...((((((....))))))....))))).))).)))))...)))).))..-...)-

))))(((((((.((((((((((((..((((((((...... (((((((--.(((((.((((((...... ((((...(((((...((((.((((..((((((....)))))).))-))---.))))...)))))...)))).)))).))..))))).)))))))..-

))))))))...))))))))))))....))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>06-SRNP-46891_c_Urbanus_belliDHJ03

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACAGCCAGGACCATTCCTGTCTGAGGGCCGGCTGTATAAAAACAA-

TATCACACTGTTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATA

TATCAT-GAAA-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTTA-TA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCTCTG--

TCGCACCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCAGCGCGCT

CGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACC

CGCCGAATTTA

151

.((((....))))..((.....))(((((.(((...... )))))))).(((((((((((((.((((((((((...... -...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))(((((....(((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.((((..((((((....)))))).))-))---.))))...)))))...)))).)))).))..)))))..))))))))-))))))))...)))))))))))....--

.))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))).))))))((.....))......

>06-SRNP-46891_d_Urbanus_belliDHJ03

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACTACTCCTGTCTGAGGGCCGGCTGTATAAA--

CAAATATCACACTGTTCACTCGAAAGTGTGGACATATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTA

AATATATCAC-TAAA-TGCAGTGCGATTTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATATGTTACGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCTGTCGCACCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCTCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTAT

CGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....)))).(((.....)))((((.((((...... ))))))))..(((((((((((((.((((((((((...--...... ((((((.(((....)))))))))((.(((((((((..((((((((...((((((....))))))....))))).))).)))))...)))).))..-...)-

))))(((((((.((((((((((((..((((((((...... (((((((--.(((((.((((((...... ((((...(((((...((((.((((..((((((....)))))).))-))---.))))...)))))...)))).)))).))..))))).)))))))..-

))))))))...))))))))))))....))))))).....((((((((.(((..((((....(((...((((((((.(((((((((((((...((.((((((...... ))))))))..))).))))))).)))..))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

......

>06-SRNP-46891_b_Urbanus_belliDHJ03

152

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAG-ACCACTCCTGTCTGAGGGCCGGCTGTATAAA--CAA-

TATCACACTGTTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATA

TATCAT-GAAA-TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATATGTTACGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCTGTCGCACCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

...... ((((...((.....))(((((.((((...... )))).-.....((((((((((((.((((((((((...--...-...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))(((((...((((((((((((..((((((((...... (((((((--.(((((.((((((...... ((((...(((((...((((.((((..((((((....)))))).))-))---.))))...)))))...)))).)))).))..))))).)))))))..-

))))))))...))))))))))))...... ))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))).))))).)))

))...... ))))....

>06-SRNP-46891_a_Urbanus_belliDHJ03

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAA-

CAAATATCACACTGTTCACTCGAGAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTA

AATATATCAA-TGAA-

TACAGTGCGAATTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TAATACGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

153

GACGCGTATTTGGCGCGCGCGCGCTCTTTCGCACCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTA

TCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTATC

GTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((....-...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))(((((((.((((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))...-..))).))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...))))))))))))....))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>haplotype 2_07-SRNP-65582_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

GAAA-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))))(((....(((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))..)-))---.))))...)))))...)))).)))).))..)))))..))))))))-

154

))))))))...)))))))))))(((((...... )))))((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... ))))))))))))))..))))).

...... ))......

>haplotype 3_07-SRNP-41187_c_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

TGAA-

TACAGTGCGAATTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TAATACGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))((((((((((((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))...-..))).))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...))))))))))))...)))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>haplotype 5_07-SRNP-33232_Urbanus_belliDHJ01

155

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

TGAA-

TACAGTGCGAATTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TAATACGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCTTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTG

TCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTATC

GTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))(((((((.((((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))...-..))).))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...))))))))))))....))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>08-SRNP-24278_b_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

GAAA-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTTAATA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

156

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))))(((....(((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))...)))---.))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...)))))))))))(((((...... )))))((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... ))))))))))))))..))))).

...... ))......

>06-SRNP-47955_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

TGAA-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))))(((....(((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))..)-))---.))))...)))))...)))).)))).))..)))))..))))))))-

157

))))))))...)))))))))))(((((...... )))))((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... ))))))))))))))..))))).

...... ))......

>08-SRNP-1439_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

GAAT-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((...... ((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... -....-

...))))...... (((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))..)-))---.))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...)))))))))))(((((...... )))))((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))....))))))).)))))))))))))..)))))

...... ))......

>06-SRNP-46570_a_Urbanus_belliDHJ01

158

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAAAAAAAATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

GAAA-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCTTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTG

TCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTATC

GTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))(((((...((((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))..)-))---.))))...)))))...)))).)))).))..)))))..))))))))-

...... ))......

>06-SRNP-47304_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

TGAA-

TACAGTGCGAATTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TAATACGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

159

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))((((((((((((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))...-..))).))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...))))))))))))...)))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>07-SRNP-30614_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

GGAA-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -(((.-

(((.(((((...((((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))..)-))---.))))...)))))...)))).)))).))..)))))..))))))))-

160

))))))))...))))))))))))...... )))))...)))(((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))))..))))))).)))))))))))))..)))))

...... ))......

>08-SRNP-4727_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTACGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

GAAA-

TACAGTGCGTTCTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCATAT

GTTACGTGCTTCGGCACGTTAA-TA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGATCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -...)-

))))(((((.((.(((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))..)-))---.))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...))))))))))))).....))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>06-SRNP-47304_a_Urbanus_belliDHJ01

161

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAAGAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATAACAA--

GAAATACAGTGCGAACTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGC

ATATGTTACGTGCTTCGGCACGTTAA-TAATACGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... --

...)))))((((((((((((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))...-..))).))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...))))))))))))...)))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>08-SRNP-24278_a_Urbanus_belliDHJ01

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGCCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCAA-

TGAAATACAGTGCGAATTGCGCGTGCGCTTTTGCGCGTCGTTCAACGCGCGCGTCCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTG

CATATGTTACGTGCTTCGGCACGTTTAATA---CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCG-

GACGCGTATTTGGCGCGCGCGCGCTCGTTCGCATCGAGTAGGCGGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGT

162

GTCGTCGCTGCCGTAAAAAGCAGCGCGCTCGCACGCGGCGAACGCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCCAATTTTTA

TCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.((((((((((...... (((((((((....)))))))))...(((((..((((((((...((((((....))))))....))))).))).)))))...... -

....)))))((((((((((((((((((((..((((((((...... ((((((((..(((((.((((((...... ((((...(((((...((((.(((...((((((....))))))...)))---.))))...)))))...)))).)))).))..)))))..))))))))-

))))))))...))))))))))))...)))))))).....((((((((.(((..((((....(((...((((((((((((((((((((((...((.((((((...... ))))))))..))).))))))).))).)))))))))...)))...))))..))).))))))))...... )))))))))))))..)))))..

...... ))......

>haplotype 1_06-SRNP-47816_b_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATGA

AACAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGCGCGCGCTCGGTCGCACCGAGTAGGC

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCGGCGCGCTCGCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((...(((((...(((((((((....((((....))))...))-))---

)))))...)))))...)))).)))).))..))))).)))))))...)))))))))..)))))))))))((((((.....))))))((((((((.(((..((((....(((...((((((((((((((((((((((.(((((((((...... ))))))).)).))).))))))).))).)))))))))...)))...))))

..))).))))))))....))))))).)))))))))))))..)))))...... ))......

163

>haplotype 4_06-SRNP-47816_a_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATGA

AATAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGCGCGCGCTCGGTCGCACCGAGTAGGC

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCGGCGCGCTCGCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((...(((((...(((((((((....((((....))))...))-))---

..))).))))))))....))))))).)))))))))))))..)))))...... ))......

>haplotype 6_06-SRNP-46460_a_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATGA

AACAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTCGGCACTTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGCGCGCGCTCGGTCGCACCGAGTAGGC

164

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCGGCGCGCTCGCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((...(((((...(((((((((..((((((....)))))).))-))---

..))).))))))))....))))))).)))))))))))))..)))))...... ))......

>01-SRNP-4475_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATGA

AACAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTCGGCACCTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGCGCGCGCTCGGTCGCACCGAGTAGGC

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCGGCGCGCTCGCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((...(((((...(((((((((....((((....))))...))-))---

..))).))))))))....))))))).)))))))))))))..)))))...... ))......

165

>06-SRNP-18276_a_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATGA

AACAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTTGGGCCTTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGCGCGCGCTCGGTCGCACCGAGTAGGC

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCGGCGCGCTCGCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((...(((((...(((((((((..(((.((.....))))).))-))---

..))).))))))))....))))))).)))))))))))))..)))))...... ))......

>06-SRNP-46460_b_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATGA

AATAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTCGGCACTTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGCGCGCGCTCGGTCGCACCGAGTAGGC

166

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCGGCGCGCTCGCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((...(((((...(((((((((..((((((....)))))).))-))---

..))).))))))))....))))))).)))))))))))))..)))))...... ))......

>06-SRNP-46460_c_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGGATAAAAACAAATATCACACT

GTTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATG

AAATAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTACAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGACGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGCGCGCGCTCGGTCGCACCGAGTAGGC

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCGGCGCGCTCGCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((..((((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((....((((...(((((((((....((((....))))...))-))---

)))))...))))....)))).)))).))..))))).)))))))...)))))))))..)))))))))))((((((.....))))))((((((((.(((..((((....(((...((((((((((((((((((((((.(((((((((...... ))))))).)).))).))))))).))).)))))))))...)))...))))

..))).))))))))....)))))))))))))))))))))..)))))...... ))......

167

>07-SRNP-20318_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATGA

AATAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGTGCGCGCTCGGTCGCACCGAGTAGGC

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGACGTCGCTGCCGTAAAAAGCGGCGCGCTCGCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((...(((((...(((((((((....((((....))))...))-))---

)))))...)))))...)))).)))).))..))))).)))))))...)))))))))..)))))))))))((((((.....))))))((((((((.(((..((((....(((...(((((((((((((((((((..((((((.((((((...... )))))))).)))).))))))).))).)))))))))...)))...))))

..))).))))))))....))))))).)))))))))))))..)))))...... ))......

>07-SRNP-30613_Urbanus_belliDHJ02

ATCGACATTTCGAACGCACATTGCGGTCCGTGGAGAAACATCCAGGACCACTCCTGTCTGAGGGCCGGCTGTATAAAAACAAATATCACACTG

TTCACTCGAAAGAGTGGACAAATGACGGTTCCGCGTCGCTTCGACCCGTTCGGGTCGCCGTCGGCGTCGGTCCGTTTAAATATATCACATGA

AATAAAGTGCGATTTGCGCGTGCGCTTATGCGCGTCGTTCAACGCGCGC--

CCGGAGCCCCCCGTGCTCTCGGCGACCCTTCGGTGTGCGTATGTCGAGTGCTTCGGCACGTTTA-TA---

CGCGCTAAGAGGGCGAGCCGTCGGGTGGATCTCCGTGCGTGTGCGGGACGCGTATTTGGCGCGCGCGCGCTCGGTCGCACCGAGTAGGC

168

GGACTCGACGTCCGAAGTGCGTTTCGACGCCGTCGTCGCCGTGGCGTGTCGTCGCTGCCGTAAAAAGCGGCGCGCTCTCACGCGGCGAAC

GCGCGGCGTCGTATCGCTGACGGATATCGCGTCTGCCTCGAATTTTTATCGTTGGCCTCAGATCAGGGAGGATCACCCGCCGAATTTA

.((((....))))..((...... (((((.((((...... ))))))))).(((((((((((((.(((((...(((((((.....(((.((((((((((((....))))))))....(((((..((((((((...((((((....))))))....))))).))).)))))...... )))).)))..(((((((

((((.(((((((((...... (((((((--.(((((.((((((...... ((((...(((((...(((((((((....((((....))))...))-))---

)))))...)))))...)))).)))).))..))))).)))))))...)))))))))..)))))))))))((((((.....))))))((((((((.(((..((((....(((...(((((((((((((((((((..(((.(((((((...... )))))))))).....))))))).))).)))))))))...)))...)))).

.))).))))))))....))))))).)))))))))))))..)))))...... ))......

169

Appendix C: Chapter 3 Supplementary Tables

Table C.1 Supportive collection data for the 250 E. imperialis specimensused in this study.

Life Sample ID Country/Ocean Province Region Sector Exact Site Lat Lon Elev stage Sector Rincon 09-SRNP-14238 Costa Rica Guanacaste ACG Rain Forest Estacion Leiva 10.94 -85.32 454 A Sector Rincon 09-SRNP-14248 Costa Rica Guanacaste ACG Rain Forest Finca Chaves 10.94 -85.32 454 A Sector Rincon 09-SRNP-14250 Costa Rica Guanacaste ACG Rain Forest Finca Chaves 10.94 -85.32 454 A Sector Rincon 09-SRNP-14251 Costa Rica Guanacaste ACG Rain Forest Finca Chaves 10.94 -85.32 454 A Sector Rincon 09-SRNP-14252 Costa Rica Guanacaste ACG Rain Forest Finca Chaves 10.94 -85.32 454 A Sector Rincon 09-SRNP-14253 Costa Rica Guanacaste ACG Rain Forest Finca Chaves 10.94 -85.32 454 A Sector Rincon 09-SRNP-14254 Costa Rica Guanacaste ACG Rain Forest Finca Chaves 10.94 -85.32 454 A Sector Rincon 09-SRNP-14259 Costa Rica Guanacaste ACG Rain Forest Estacion Leiva 10.94 -85.32 454 A Sector San Estacion San 09-SRNP-14264 Costa Rica Alajuela ACG Cristobal Gerardo 10.88 -85.39 575 A Sector Santa Camino 09-SRNP-15323 Costa Rica ACG Rosa Borrachos 10.84 -85.62 295 A Sector Santa Camino 09-SRNP-15324 Costa Rica ACG Rosa Borrachos 10.84 -85.62 295 A Sector Santa Camino 09-SRNP-15325 Costa Rica ACG Rosa Borrachos 10.84 -85.62 295 A Sector Santa Camino 09-SRNP-15415 Costa Rica Guanacaste ACG Rosa Borrachos 10.84 -85.62 295 A Sector Santa Camino 09-SRNP-15416 Costa Rica Guanacaste ACG Rosa Borrachos 10.84 -85.62 295 A Sector Santa Camino 09-SRNP-15417 Costa Rica Guanacaste ACG Rosa Borrachos 10.84 -85.62 295 A 09-SRNP-15418 Costa Rica Guanacaste ACG Sector Santa Camino 10.84 -85.62 295 A

170

Rosa Borrachos Sector Santa Camino 09-SRNP-15419 Costa Rica Guanacaste ACG Rosa Borrachos 10.84 -85.62 295 A Sector Santa Camino 09-SRNP-32535 Costa Rica Guanacaste ACG Rosa Borrachos 10.84 -85.62 295 A Sector Santa Camino 09-SRNP-32536 Costa Rica Guanacaste ACG Rosa Borrachos 10.84 -85.62 295 A Sector Rincon 09-SRNP-32539 Costa Rica Guanacaste ACG Rain Forest Rio Francia 10.90 -85.29 410 A Sector Rincon 09-SRNP-44170 Costa Rica Alajuela ACG Rain Forest Rio Francia 10.90 -85.29 410 A Sector Rincon 09-SRNP-5507 Costa Rica Alajuela ACG Rain Forest Rio Francia 10.90 -85.29 410 A Sector Rincon 09-SRNP-65573 Costa Rica Alajuela ACG Rain Forest Manta Porton 10.96 -85.28 147 A Sector Rincon 09-SRNP-65574 Costa Rica Alajuela ACG Rain Forest Manta Porton 10.96 -85.28 147 A Sector Rincon 09-SRNP-65576 Costa Rica Alajuela ACG Rain Forest Estacion Leiva 10.94 -85.32 454 A Sector Rincon 09-SRNP-65583 Costa Rica Alajuela ACG Rain Forest Estacion Leiva 10.94 -85.32 454 A Sector Rincon 09-SRNP-65584 Costa Rica Alajuela ACG Rain Forest Manta Porton 10.96 -85.28 147 A Casa Calixto 09-SRNP-65585 Costa Rica Alajuela ACG Santa Cecilia Moraga 11.06 -85.41 335 A Casa Calixto 09-SRNP-65587 Costa Rica Alajuela ACG Santa Cecilia Moraga 11.06 -85.41 335 A Casa Calixto 09-SRNP-65588 Costa Rica Alajuela ACG Santa Cecilia Moraga 11.06 -85.41 335 A Sector Rincon Estacion 09-SRNP-65615 Costa Rica Alajuela ACG Rain Forest Llanura 10.93 -85.25 135 A Sector San Estacion San 09-SRNP-65921 Costa Rica Alajuela ACG Cristobal Gerardo 10.88 -85.39 575 A 09-SRNP-66001 Costa Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-66002 Costa Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-66003 Costa Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-66004 Costa Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A

171

09-SRNP-66005 Costa Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-66006 Costa Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-66007 Costa Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-66008 Costa Rica Alajuela ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14295 Costa Rica ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14296 Costa Rica Guanacaste ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14298 Costa Rica ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14307 Costa Rica ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14308 Costa Rica Guanacaste ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14309 Costa Rica Guanacaste ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14310 Costa Rica Guanacaste ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14311 Costa Rica ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14313 Costa Rica ACG Brasilia Moga 11.01 -85.35 320 A 09-SRNP-14343 Costa Rica ACG Brasilia Moga 11.01 -85.35 320 A Sector Santa Area 10-SRNP-12025 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12030 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12032 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12034 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12036 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12038 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12039 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12054 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12055 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12059 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A

172

Sector Santa Area 10-SRNP-12066 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12069 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12080 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12081 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12086 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12091 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12096 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12099 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12100 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12111 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12152 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12153 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12154 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12155 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12156 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12157 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12159 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12160 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A Sector Santa Area 10-SRNP-12162 Costa Rica ACG Rosa Administrativa 10.84 -85.62 295 A 10-SRNP-12185 Costa Rica ACG Sector Santa Area 10.84 -85.62 295 A

173

Rosa Administrativa Sunset drive Havelock, UV 05-NCCC-551 United States trap 34.87 -76.94 A Etoniah Creek Preservation 06-FLOR-0238 United States Florida Putnam Co. State Forest site 29.74 -81.84 36 A Ocala National nr. Hwys 310 06-FLOR-0304 United States Florida Putnam Co. Forest and 19 29.52 -81.84 19 A Ocala National nr. Hwys 310 06-FLOR-0305 United States Florida Putnam Co. Forest and 19 29.52 -81.84 19 A Etoniah Creek 06-FLOR-0510 United States Florida Putnam Co. State Forest Picnic area 29.76 -81.84 19 A Etoniah Creek 06-FLOR-0511 United States Florida Putnam Co. State Forest Picnic area 29.76 -81.84 19 A Etoniah Creek Preservation 06-FLOR-0942 United States Florida Putnam Co. State Forest site 29.74 -81.84 36 A Archbold 06-FLOR-1163 United States Florida Highlands Co. Biological Station off Main Dr. 27.18 -81.35 51 A Archbold 06-FLOR-1393 United States Florida Highlands Co. Biological Station Jay cottage 27.17 -81.35 55 A Archbold 06-FLOR-1739 United States Florida Highlands Co. Biological Station Red Hill 27.18 -81.34 35 A Archbold 06-FLOR-1740 United States Florida Highlands Co. Biological Station Red Hill 27.18 -81.34 35 A Croatan National 06-NCCC-1139 United States North Carolina Carteret County Forest Rd. 181 34.77 -76.76 A County of Lennox- Thompson Hill 2006-ONT-0963 Canada Ontario Addington Tamworth Rd 44.53 -77.00 A County of Lennox- Thompson Hill 2006-ONT-0964 Canada Ontario Addington Tamworth Rd 44.53 -77.00 A County of Lennox- Thompson Hill 2006-ONT-0965 Canada Ontario Addington Tamworth Rd 44.53 -77.00 A County of Lennox- Thompson Hill 2006-ONT-0966 Canada Ontario Addington Tamworth Rd 44.53 -77.00 A

174

barcode SNB Trinidad and Northern range 1160 Tobago Northern Range forest reserve 10.73 -61.25 700 A BC-CGCM Serra da 23.763 Brazil Ceara Meruoca Meruoca -3.47 -40.50 A BC-Dec0118 Colombia Cundimarca Boqueron 5.07 -74.13 800 A BC-Dec0119 Colombia Cundimarca Boqueron 5.07 -74.13 800 A BC-Dec0120 Colombia Cundimarca Boqueron 5.07 -74.13 800 A BC-EvS 1934 Peru Amazonas Campo Seis -5.28 -78.40 850 A BC-EvS 1965 Peru Amazonas Puente Niera 650 A BC-Her1235 Guatemala Baja Verapaz Santa Rosa 15.24 -90.30 1610 A BC-Her1253 Guatemala Baja Verapaz Santa Rosa 15.24 -90.30 1610 A Finca Firmeza. Cerro Negro BC-Her1819 Guatemala Izabal Norte 15.38 -89.69 950 A BC-Her1853 Guatemala Baja Verapaz Santa Rosa 15.24 -90.30 1610 A Reserva BC-Her1855 Guatemala Suchitepequez Tarrales 14.53 -91.15 1041 A BC-Her2286 Bolivia Nor Yungas 1400 A BC-Her3539 A BC-Roug0157 A BC-Roug0158 United States A BC-Roug0159 A HLC-16993 United States Massachusetts Dukes Co. Martha's Vineyard A HLC-16994 United States Massachusetts Dukes Co. Martha's Vineyard A BC-EvS 1848 Peru Amazonas Puente Niera 650 A BC-EvS 1849 Peru Amazonas Puente Niera 650 A Street to BC-EvS 1850 Peru Amazonas Campo Seis Montenegro -5.27 -78.38 750 A San Jose del BC-Dec0121 Colombia Choco Palmar 4.92 -76.25 1200 A Rd Cali - Buenaventura, BC-Dec0122 Colombia Valle San Cipriano 3.87 -76.85 200 A

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Tolima, Rd. Sanfe de Bogota to Melgar, BC-FMP-1052 Colombia Boqueron 650 A Rd Paramonga to Huaraz, km. BC-Roug0344 Peru Ancash 121 -9.82 -77.79 3500 A - BC-Dec0113 Bolivia La Paz Nor Yungas Inca Huara 16.58 -67.43 1500 A - BC-Dec0114 Bolivia La Paz Nor Yungas Inca Huara 16.58 -67.43 1500 A Serra do Penitente, BC-Dec0446 Brazil Maranhao Balsas -8.75 -46.33 400 A Serra do Penitente, BC-Dec0448 Brazil Maranhao Balsas -8.75 -46.33 400 A Florencia- BC-Dec1623 Colombia Caqueta Florencia CTR308 1.41 -75.54 A Florencia- BC-Dec1652 Colombia Caqueta Florencia CTR309 1.42 -75.53 A Florencia- BC-Dec1682 Colombia Caqueta Florencia CAF119 1.35 -75.82 A Florencia- BC-Dec1696 Colombia Caqueta Florencia CAF121 1.35 -75.82 A Florencia- BC-Dec1697 Colombia Caqueta Florencia CAF119 1.35 -75.82 A PK5 Montagne de fer trail + 3 Km on a trail on BC-EST0153 French Guiana the right 5.30 -53.60 A BC-EST0154 French Guiana PK54 Kaw road 4.52 -52.07 300 A BC-EST0155 French Guiana PK54 Kaw road 4.52 -52.07 300 A BC-EST0156 French Guiana PK54 Kaw road 4.52 -52.07 300 A BC-EST0157 French Guiana PK54 Kaw road 4.52 -52.07 300 A BC-EST0158 French Guiana PK54 Kaw road 4.52 -52.07 300 A

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BC-EST0159 French Guiana PK54 Kaw road 4.52 -52.07 300 A PK19 St Elie BC-EST0160 French Guiana trail 5.25 -53.07 115 A PK19 St Elie BC-EST0161 French Guiana trail 5.25 -53.07 115 A PK3 Crique BC-EST0162 French Guiana valentin trail 5.36 -53.67 113 A Kanton BC-EvS 1856 French Guiana Cayenne Cayenne South Belizon 4.27 -52.64 80 A BC-FMP-1059 Venezuela Carabobo Bejuma 10.18 -68.26 A Piste de Foret de Coralie Est. BC-FMP-1060 French Guiana PK 17 200 A Rd. To Yavisa BC-FMP-1062 Panama El llano 70 A Calabozo, BC-FMP-1429 Venezuela Guarico llanos Farm La Linda 8.92 -67.43 A Rd to Kaw, km. BC-Her0458 French Guiana 37 4.55 -52.15 A BC- Palmares- TDMPEG0052 Brazil Para Palmares BPR1434 -5.87 -49.87 A BC- Palmares- TDMPEG0053 Brazil Para Palmares BPR2447 -5.85 -49.87 A BC- Palmares- TDMPEG0054 Brazil Para Palmares BPR2450 -5.86 -49.86 A BC- Macaranduba- TDMPEG0347 Brazil Para Macaranduba BMB209 -4.78 -49.38 A Nouragues Research CLV10710 French Guiana Station 4.10 -52.68 300 A Nouragues Research CLV12610 French Guiana Station 4.10 -52.68 300 A NS-RR0657 French Guiana Nouragues Inselberg Camp Forest border 4.09 -52.68 160 A Heliport - Drop NS-RR1685 French Guiana Nouragues Inselberg Camp Zone 4.09 -52.68 160 A Heliport - Drop NS-RR1705 French Guiana Nouragues Inselberg Camp Zone 4.09 -52.68 160 A

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Rd Panama city - Yavisa, BC-Dec0149 Panama km143 8.92 -78.29 75 A Rd Panama city - Yavisa, BC-Dec0150 Panama km143 8.92 -78.29 75 A Rd Santiago de Purriscal - Puerto Quepos, km33, Reserva BC-Dec1104 Costa Rica San Jose la Cangreja 9.68 -84.38 265 A BC-FMP-1064 Guatemala Perhulha A El Gobiado Cooperativa BC-FMP-2473 Nicaragua Jinotega `La Herreda` 14.05 -85.11 1310 A BC-RBP 4613 Guatemala Alta Verapaz Coban Chicacnab 15.25 -90.21 1500 A BC-RBP 4614 Guatemala Alta Verapaz Coban Chicacnab 15.25 -90.21 1500 A BC-RBP 4615 Guatemala Alta Verapaz Coban Chicacnab 15.25 -90.21 1500 A BC-RBP 4619 Nicaragua Jinotega El Gobiado Lina Herredia 14.05 -85.11 1280 A BC-RBP 4620 Nicaragua Jinotega El Gobiado Lina Herredia 14.05 -85.11 1280 A BC-RBP 4621 Nicaragua Jinotega El Gobiado Lina Herredia 14.05 -85.11 1280 A Rd Santiago de Purriscal - Puerto Quepos, km33, Reserva BC-Dec1105 Costa Rica San Jose la Cangreja 9.70 -84.41 478 A Rd Santiago de Purriscal - Puerto Quepos, km33, Reserva BC-Dec1106 Costa Rica San Jose la Cangreja 9.70 -84.41 478 A near Santiago de BC-EvS 1869 Costa Rica San Jose Puriscal Canton Puriscal A BC-RBP 4616 Costa Rica Puntarenas P.N. Esquina La Gamba 8.42 -83.12 A BC-RBP 4617 Costa Rica Puntarenas P.N. Esquina La Gamba 8.42 -83.12 A BC-RBP 4618 Costa Rica Puntarenas P.N. Esquina La Gamba 8.42 -83.12 A

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BC-EvS 1859 United States Indiana Elkhad County Elkhard 41.67 -85.85 235 A BC-EvS 1861 United States Indiana Elkhad County Elkhard 41.67 -85.85 235 A BC-EvS 1862 United States Indiana Elkhad County Elkhard 41.67 -85.85 235 A Walker Country, 8 miles S.W. BC-FMP-1056 United States Texas Huntsville 30.47 -95.82 A Walker County, 8 miles S.W. of BC-FMP-1427 United States Texas Huntsville 30.47 -95.82 A Santa - BC-EvS 1871 Brazil Catarina Rio Natal Sao Bento do Sul 26.03 -49.12 400 A Santa - BC-EvS 1872 Brazil Catarina Corupa 26.40 -49.22 200 A Santa Sao Bento do - BC-Dec0155 Brazil Catarina Sul 26.25 -49.38 800 A Santa Sao Bento do - BC-Dec0156 Brazil Catarina Sul 26.25 -49.38 800 A Rd Curitiba - Sao Paulo, km353, - BC-Dec0333 Brazil Sao Paulo Miracatu 24.08 -47.26 340 A Rd Curitiba - Joinville, Guaratuba, Pontal do - BC-Dec0445 Brazil Parana Itatare 25.86 -48.97 884 A Santa Sao Bento do - BC-Dec0452 Brazil Catarina Sul 26.25 -49.38 800 A Rte. Vitoria to Belo Horizonte - BC-FMP-1053 Brazil Espirito Santo km 120 20.30 -41.28 850 A - BC-FMP-1054 Argentina Misiones San Pedro 26.63 -54.13 580 A 100 km NE La - BC-RBP 4606 Bolivia La Paz Paz Caranavi-Coroico 16.20 -67.60 1500 A 100 km NE La - BC-RBP 4607 Bolivia La Paz Paz Caranavi-Coroico 16.20 -67.60 1500 A

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50km of Buenos Aires, - BC-Dec0145 Argentina Buenos Aires Jose C. Paz 34.50 -58.75 25 A 50km of Buenos Aires, - BC-Dec0146 Argentina Buenos Aires Jose C. Paz 34.50 -58.75 25 A BC-EvS 1873 Argentina Corrientes San Gabriel 70 A - BC-EvS 1875 Argentina Corrientes San Gabriel 28.97 -57.20 70 A BC-EvS 1876 Argentina Corrientes San Gabriel 70 A - BC-EvS 1878 Argentina Misiones Dos del Mayo 27.02 -54.68 550 A - BC-EvS 1879 Argentina Misiones Dos del Mayo 27.02 -54.68 550 A - BC-FMP-1051 Argentina Buenos Aires San Miguel 35.45 -58.80 A BC-Roug0160 Argentina A BC-Roug0161 Argentina A BC-Roug0162 Argentina A - BC-Roug0345 Argentina Misiones Dos de Mayo 27.03 -54.65 500 A Rd Yecora - - BC-Dec0129 Mexico Sonora Maycoba, km8 28.35 108.85 1695 A Rd Yecora - - BC-Dec0130 Mexico Sonora Maycoba, km8 28.35 108.85 1695 A Pena Blanca Santa Cruz - BC-EvS 1866 United States Arizona Lake County 31.40 111.08 500 A Pena Blanca Santa Cruz - BC-EvS 1867 United States Arizona Lake County 31.40 111.08 500 A Santa Cruz Conztry, Pena BC-FMP-1058 United States Arizona Lake, Noquales A Hermosillo to Yecora. Km BC-Her1807 Mexico Sinaloa 259 1475 A Dirtroad from - BC-Roug0346 Mexico Zacatecas Momax to San 21.97 103.21 1966 A

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Lorenzo, after San Lorenzo, 'La Manchada' track, km. 2 Road from Teuel de Gonzales to Florencia de Benito Juarez, km. 11.3, dirtroad of Monte Carillos, - BC-Roug0347 Mexico Zacatecas km. 3 21.53 103.50 2114 A Pena Blanca - BC-Roug0350 United States Arizona Lake 31.40 111.08 1100 A Pena Blanca - BC-Roug0351 United States Arizona Lake 31.40 111.08 1100 A BC-EvS 1864 Canada Ontario Fitzroy Harbour 45.47 -78.22 60 A BC-EvS 1865 Canada Ontario Fitzroy Harbour 45.47 -78.22 60 A Atlanta surrounding BC-FMP-1055 United States Atlanta area A BC-Dec1506 Peru Piura Abra Porcuja 1800 A BC-Dec1507 Peru Lambayeque Penachi -6.17 -79.47 1800 A BC-Dec1508 Peru Piura Abra Porcuja 1800 A BC-EvS 1925 Peru Piura Abra Porcuya 1800 A BC-EvS 1926 Peru Lambayeque Penachi -6.17 -79.47 1800 A BC-EvS 1936 Peru Piura Abra Porcuya 1800 A BC-EvS 1937 Peru Piura Abra Porcuya 1800 A BC-EvS 1938 Peru Piura Abra Porcuya 1800 A BC-FMP-1061 Peru Piura Abra Porcuya 1800 A BC-FMP-1428 Peru Piura Abra Porcuya 1800 A Cordillera de Huancabamba BC-RBP 4610 Peru Piura Guamani ptov. La Filadera -5.24 -79.45 870 A BC-RBP 4611 Peru Piura Cordillera de Huancabamba La Filadera -5.24 -79.45 870 A

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Guamani ptov. BC-FMP-2132 Mexico Chiapas Santo Domingo 17.07 -91.46 550 A Reserve BC-Her1364 Guatemala Peten Ixpanpajul 16.87 -89.82 197 A Reserve BC-Her1366 Guatemala Peten Ixpanpajul 16.87 -89.82 197 A Reserve BC-Her1368 Guatemala Peten Ixpanpajul 16.87 -89.82 197 A Reserve BC-Her1370 Guatemala Peten Ixpanpajul 16.87 -89.82 197 A Lago Izabal. Balneario El BC-Her1764 Guatemala Izabal Bosqueton 15.56 -89.28 25 A - BC-Dec0115 Bolivia Santa Cruz Cordillera Gutierrez 19.41 -63.53 1100 A Rd Villamontes - Boyuibe, - BC-Dec0116 Bolivia Chuquisaca Gran Chaco km25 21.03 -63.44 340 A Rd Vacca Guzman - - BC-Dec0117 Bolivia Santa Cruz Cordillera Camiri 19.82 -63.71 1615 A Rd La Vina - Pampa - BC-Dec0126 Argentina Grande, km25 25.65 -65.48 1590 A San Jose de BC-EvS 1949 Bolivia Santa Cruz Chiquitos 600 A San Jose de - BC-EvS 1950 Bolivia Santa Cruz Chiquitos 17.85 -60.75 600 A BC-FMP-1049 Bolivia Tarija 900 A street from Santa Clara to - BC-FMP-1050 Argentina Jujuy La Estrella 24.32 -64.51 1180 A Route Santa Clara to El BC-FMP-1431 Argentina Jujuy Fuente, km 24 1325 A Villa Serrano a Vallegrande km - BC-Her1704 Bolivia Chuquisaca 38 18.92 -64.29 1342 A

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8,5 km W - BC-RBP 4604 Bolivia Santa Cruz Mataral 18.08 -64.17 1660 A 8,5 km W - BC-RBP 4605 Bolivia Santa Cruz Mataral 18.08 -64.17 1660 A 8,5 km W - BC-RBP 4609 Bolivia Santa Cruz Mataral 18.08 -64.17 1660 A San Pedro, BC-FMP-1065 Mexico Oaxaca Teutila 17.98 -96.72 1050 A BC-RBP 4612 Mexico Oaxaca Metates 17.12 -97.99 900 A 07-SRNP- Rincon Rain Estacion 110342 Costa Rica Alajuela ACG forest Caribe (Melina) 10.90 -85.27 391 A 08-SRNP- 105092 Costa Rica Guanacaste ACG Quica Quica 11.00 -85.40 487 A En la luz puerta Sector San casa San 09-SRNP-5508 Costa Rica Alajuela ACG Cristobal Gerardo A

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Appendix D: Methodology supplementary tables and material

Table D.1Description of primers used in this study.

Target F primer Primer sequence (5'-3') R primer Primer sequence (5'-3') bp Ref. Hebert et al. COI LepF ATTCAACCAATCATAAAGATATTGG LepR TAAACTTCTGGATGTCCAAAAAATCA 658 2004a cytb 40F TGAATCTGAGGAGGGTTTGCIGT 560R TCTACTGGGCGGGCTCCAATTCA 499 Shakralla et al EF1α Starsky CACATYATTGTCGTSATYGG Hutch CTTGATGAAATCYCTGTGTCC 238 Cho et al. 1995 EF1α Bo GCTGAGCGYGARCGTGGTATCAC Luke CATRTTGTCKCCGTGCCAKCC 367 Cho et al. 1995 EF1α Laverne GAGGAAATYAARAAGGAAG Verdi GACACCAGTTTCAACTCTGCC 267 Nazari et al. 2007 EF1α BJ CARGACGTATACAAAATCGG Bear GCAATGTGRGCIGTGTGGCA 319 Nazari et al. 2007 Pedro et al/White ITS2 ITS2_d1F GAACTGCAGGACACATGAAC ITS4 TCCTCCGCTTATTGATATGC variable et al. 1990 gatB gatB_F1 GAKTTAAAYCGYGCAGGBGTT gatB_R1 TGGYAAYTCRGGYAAAGATGA 369 Baldo et al. 2006 COI coxA_F1 TTGGRGCRATYAACTTTATAG coxA_R1 CTAAAGACTTTKACRCCAGT 402 Baldo et al. 2006 hpcA hcpA_F1 GAAATARCAGTTGCTGCAAA hcpA_R1 GAAAGTYRAGCAAGYTCTG 444 Baldo et al. 2006 ftsZ ftsZ_F1 ATYATGGARCATATAAARGATAG ftsZ_R1 TCRAGYAATGGATTRGATAT 435 Baldo et al. 2006 fbpA fbpA_F1 GCTGCTCCRCTTGGYWTGAT fbpA_R1 CCRCCAGARAAAAYYACTATTC 429 Baldo et al. 2006 wsp wsp_F1 GTCCAATARSTGATGARGAAAC wsp_R1 CYGCACCAAYAGYRCTRTAAA 546 Baldo et al. 2006

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Macherey-Nagel (MN) Extraction Protocol

Pre-lysis 1. Add 180ul Buffer T1 to each 200ul labelled tube. 2. Add ~3mm tissue (insect) to each tube; put tubes into FastPrep for 20s. 3. Add 25ul of Proteinase K solution to each tube, vortex and short spin tubes. Note: Do not mix Buffer T1 and Proteinase K more than 10-15 min before addition to the samples: Proteinase K tendsto self-digest in Buffer T1 without substrate. 4. Incubate the tubes at 56*C for ~3hours. Use a shaking incubator or vortex occasionally.

Lysis 1. Vortex the samples. Add 200ul of Buffer B3, vortex vigorously and incubate at 70*C for 10min. Vortex briefly. Note: If particles are visible centrifuge for 5 min at high speed and transfer supernatant to new tube.

Adjust DNA binding conditions 1. Add 210ul ethanol (96-100%) to the sample and vortex vigorously.

Bind DNA 1. Place 1 Nucleospin Tissue Column into a collection tube (per sample). Apply the sample to the column. Centrifuge for 1 min at 11,000 x g. Discard the flow- through and place the column back into the Collection tube. Wash silica membrane 1st wash: Add 500ul Buffer BW. Centrifuge for 1 min at 11,000 x g. Discard the flow- through and place the column back into the Collection tube. 2nd wash: Add 600ul Buffer B5 to the column and centrifuge for 1 min at 11,000 x g. Discard the flow-through and place the column back into the Collection tube.

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Dry silica membrane 1. Centrifuge the column for 1 min at 11,000 x g. (Residual ethanol is removed during this step)

Elute highly pure DNA 1. Place the Nucleospin Tissue Column into a 1.5ml tube and add 50ul pre-warmed Elution Buffer BE (water) (70*C). 2. Incubate at room temp for 1 min. Centrifuge 1 min at 11,000 x g.

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