ABSTRACT Title of Document: THE ROLE OF HOST-PLANT HYBRIDIZATION IN HOST-ASSOCIATED POPULATION DIVERGENCE IN PHYTOMYZA GLABRICOLA (DIPTERA: AGROMYZIDAE). Julie Byrd H?bert, Ph.D. 2012 Directed By: Associate Professor, Dr. David Hawthorne Department of Entomology Phytomyza glabricola (Diptera: Agromyzidae) is a leaf-mining fly native to the eastern United States that mines two sympatric native holly species, Ilex coriacea and I. glabra. Recent work revealed significant genetic divergence between host-associated populations of flies in North and South Carolina, suggesting the populations are host forms and recent work in Ilex phylogenetics hint the two holly hosts may hybridize. In this work, I investigated potential ecological speciation in P. glabricola, hybridization in its host plants, and how the hybridization among host plants may affect gene flow between host forms of the flies. No-choice mating trials in a greenhouse revealed reproductive isolation between host forms of P. glabricola and suggested female flies are capable of making oviposition mistakes resulting in adult offspring on the non-natal host. Based on these results, I used sequences of the nuclear gene EF-1? and AFLPs to genetically confirm host form status of the flies, and identify I. glabra as the ancestral host. In addition, genome scans revealed several loci under divergent selection among the hosts, suggesting the flies may be undergoing ecological speciation. To investigate the role host plants may play in the genetic divergence among flies, I first used AFLPs to confirm hybridization between I. coriacea and I. glabra. Hybridization rates differed across the geographic range of the species, which was also reflected in the morphology of the leaves. There were no general patterns, however, in the phenotypes of hybrid plants, and no single morphological trait that could reliably identify the hybrids. Finally, I combined genetic data of the flies and the plants to determine whether hybrid plants serve as bridges or barriers for the flies. Population comparisons revealed a significant positive relationship between hybridization in the plants and gene flow in the flies, and individual comparisons indicated flies are using the hybrid plants, albeit at low levels. The results suggest hybrids could serve as bridges between parental species, helping explain how a species from a typically monophagous lineage could expand its host range. THE ROLE OF HOST-PLANT HYBRIDIZATION IN HOST-ASSOCIATED POPULATION DIVERGENCE IN PHYTOMYZA GLABRICOLA (AGROMYZIDAE). by Julie Byrd H?bert Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, College Park in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2012 Advisory Committee: Professor David Hawthorne, Chair Dr. Sonja Scheffer Professor Charles Mitter Professor Maile Neel Professor Thomas Kocher, Dean's Rep ? Copyright by Julie Byrd H?bert 2012 ii DEDICATION To my parents, Carol and Edward Byrd, for supporting me through the good and the bad. iii ACKNOWLEDGEMENTS Where to begin? I have had a lot of support in my time here at Maryland, primarily from fellow graduate students and post-docs, but a few faculty along the way as well. First and foremost, I thank my parents for supporting me and never asking ?when are you going to finish?? I thank Colin Hebert for also supporting me, both as a spouse and a financial support system. I thank Joan West for putting up with all of my questions and various eccentricities as we both waded through the Via and Hawthorne labs. I thank Akito Kawahara for helping me push the boundary and think outside of the box, and to vicariously live the life of a post-doc and new faculty member. I think Charlie Mitter for being my solid foundation, especially in my more tumultuous years. I thank Lois Reid for being Lois: the one person who knew everything at UMD. I thank my original BEES recruitment cohort, who despite all the mess we had to wade through, stuck it out together with one another, making the graduate school experience at least less miserable: Gang Chen, Laura Craig Cloud, Dan Fergus, Sheila Reynolds Gupta, Malinda Henry, Silvana Marten-Rodriguez, Jean-Francois Savard, and Colin Studds. I thank the Gruner, Hare, and Shaw labs (plus other misfits), who allowed me to be an unofficial member, attending lab meetings and learning great science: Pedro Barbosa, Patrick Danley, Tagide DeCarvalho, Alex Forde, Jaime Grace, Daniel Gruner, Matthew Hare, Jenna Jadin, Cora Johnston, Nathan Jud, Sky Lesnick, Mayda Nathan, Tamra Mendelson, Sean Mullen, Jenna Murfree, Maria Murray, Jamie Pettingill, Colin Rose, Gwen Shlichta, Kerry Shaw, Natasha Sherman, Brian Thompson, and Erin Wilson. I thank the entomology department for accepting me into their fold. I thank anyone and everyone I?ve play ultimate with, because without you, I would not have kept my sanity (if I can even claim that). I thank iv my committee, past and present, for aiding in my scientific development and giving feedback when it was most needed. I thank PIG for helping me remember the importance of ecology. Finally, I thank the many others who have helped me in various ways, shapes, and forms: Jenny Axe, Rob Ahern, Adam Bazinet, William Bentley, Pete Blank, Mike Braun, Mercedes Burns, Karen Carter, Linda Cendes, Chris Che-Castaldo, Judy Che- Castaldo, Seth Coleman, Brian Coyle, Brian Davidson, Sarah Davies, Chuck Delwiche, Alana Doty, Michele Dudash, Charlie Fenster, Rohan Fernandes, Steve Frank, Angela Fu, Kin-Lan Han, Sarah Hankerson, Greg Hess, Bill Higgins, Jermaine Hinds, Cerruti Hooks, Jeffrey Jensen, Ana Jesovnik, Brett Kent, Sarah Kingston, Abby Kula, Grace Kunkel, Bill Lamp, Hans Lemke, Alan Leslie, Matt Lewis, Eric Lind, Sarah Lombardi, Holly Martinson, Owen McDonough, Raul Medina, Holly Menninger, Jason Munshi- South, Kevin Nyberg, Tammatha O?Brien, Claire O?Quin, Kelly O?Quin, Meenu Perera, David Quan, Mike Raupp, Sarah Rockwell, Armando Rosario-Lebron, Emily Rose, Varnika Roy, Julie Samy, Katie Schneider, Aarisha Shrestha, Paula Shrewsbury, Jennifer Siani, James Sikes, Bob Smith, Jae Sohn, Jeffrey Sosa, Frank Stearns, Elanor Stevens, Chen-Yu Tsao, Dilip Vengopul, Andreanna Welch, Noor White, Gavin Woodruff, and Hsuan-Chen Wu. Oh, and if I forgot anyone, please remember that I had quite a few years to cover. v TABLE OF CONTENTS DEDICATION .................................................................................................................... ii? ACKNOWLEDGEMENTS ............................................................................................... iii? TABLE OF CONTENTS .................................................................................................... v? LIST OF TABLES ........................................................................................................... viii? LIST OF FIGURES ........................................................................................................... xi? CHAPTER 1: NO-CHOICE MATING TRIALS REVEAL THE PRESENCE OF REPRODUCTIVE ISOLATION BETWEEN HOST FORMS OF PHYTOMYZA GLABRICOLA ON ILEX CORIACEA AND I. GLABRA .............................................. 1? ABSTRACT ........................................................................................................................ 1? INTRODUCTION .............................................................................................................. 2? METHODS ......................................................................................................................... 6? Collections .............................................................................................................. 6? Mating trials ............................................................................................................ 6? RESULTS ........................................................................................................................... 7? DISCUSSION ..................................................................................................................... 8? CHAPTER 2: EVIDENCE FOR ECOLOGICAL SPECIATION IN THE HOLLY LEAF-MINER, PHYTOMYZA GLABRICOLA (DIPTERA: AGROMYZIDAE) .... 16? ABSTRACT ...................................................................................................................... 16? INTRODUCTION ............................................................................................................ 17? MATERIALS AND METHODS ...................................................................................... 22? Collections ............................................................................................................ 22? AFLPs ................................................................................................................... 23? Nuclear sequence data ........................................................................................... 25? Geographic scale of host plant associated genetic divergence ............................. 26? Estimation of cross-host plant oviposition and gene flow .................................... 27? Identification of ancestral and novel host plants ................................................... 28? Host-associated divergent selection ...................................................................... 29? Genomic architecture of divergent loci ................................................................. 30? RESULTS ......................................................................................................................... 32? Geographic scale of host plant associated genetic divergence ............................. 33? Identification of ancestral and novel host plants ................................................... 35? Host-associated divergent selection ...................................................................... 36? Genomic architecture of divergent loci ................................................................. 38? vi DISCUSSION ................................................................................................................... 39? Geographic scale of host-associated genetic divergence ...................................... 40? Direction of host range expansion ........................................................................ 42? Asymmetrical gene flow ....................................................................................... 44? Host-associated divergent selection ...................................................................... 45? Genomic architecture of divergent loci ................................................................. 47? Conclusions ........................................................................................................... 49? CHAPTER 3: A GEOGRAPHIC MOSAIC OF HYBRIDIZATION BETWEEN ILEX CORIACEA AND I. GLABRA (AQUIFOLIACEAE) AND ITS EFFECTS ON HYBRID MORPHOLOGY ........................................................................................... 75? ABSTRACT ...................................................................................................................... 75? INTRODUCTION ............................................................................................................ 77? METHODS ....................................................................................................................... 80? Collections ............................................................................................................ 80? AFLPs ................................................................................................................... 81? Genetic Analysis ................................................................................................... 83? Morphometric Analysis ........................................................................................ 85? RESULTS ......................................................................................................................... 88? Genetic analysis .................................................................................................... 88? Morphometric Analysis ........................................................................................ 90? DISCUSSION ................................................................................................................... 93? Geographic mosaic of hybridization ..................................................................... 93? Morphological identification ................................................................................ 97? Patterns of introgression ....................................................................................... 98? Conclusions ......................................................................................................... 100? CHAPTER 4: GENE FLOW BEGETS GENE FLOW: TESTING THE HYBRID BRIDGE HYPOTHESIS AND ITS ROLE IN ECOLOGICAL SPECIATION .... 120? ABSTRACT .................................................................................................................... 120? INTRODUCTION .......................................................................................................... 121? METHODS ..................................................................................................................... 125? Collections .......................................................................................................... 125? AFLPs ................................................................................................................. 126? Analyses .............................................................................................................. 127? RESULTS AND DISCUSSION ..................................................................................... 129? APPENDIX A: Code written in R to calculate linkage disequilibrium between dominant markers ............................................................................................................................ 150? vii APPENDIX B: Summary Data for Phytomyza glabricola ............................................. 154? APPENDIX C: Results of NEWHYBRIDS in Phytomyza glabricola ............................... 162? APPENDIX D: Full results of genome scans ................................................................. 167? APPENDIX E: Classification of plant samples based on the results of NEWHYBRIDS and STRUCTURE analyses ....................................................................................................... 188? APPENDIX F: Estimated hybrid indices of flies ........................................................... 193? APPENDIX G: Estimated hybrid indices of plants ........................................................ 198? BIBLIOGRAPHY ........................................................................................................... 204? viii LIST OF TABLES Table 1.1. Mating trials of Phytomyza glabricola on its host plants, Ilex glabra and I. coriacea. Trials were considered successful if the flies mated, the female oviposited eggs, and the offspring successfully emerged as adults. ..................... 13? Table 1.2. Comparison of mating trials of Phytomyza glabricola in presence versus absence of the natal and non-natal host plant species. Trials were considered successful if the flies mated, the female oviposited eggs, and the offspring successfully emerged as adults. ............................................................................ 13? Table 2.1. AFLP and EF-1? primer sequences. Pst1A was used in combination with each of the EcoRI based primers (EACA-EAGT). ....................................................... 52? Table 2.2. Summary of samples genotyped from each location and year. ....................... 53? Table 2.3. Results from CVHAPLOT. Analyzing flies from each host plant separately yielded a better consensus between the programs. ............................................... 54? Table 2.4. Summary statistics for EF-1? sequence data. ................................................. 55? Table 2.5. Analysis of molecular variance estimated using the ADONIS function for AFLP data from Phytomyza glabricola feeding on either Ilex coriacea or I. glabra. Variation was partitioned (a) among individuals on each host plant species nested within each location, sex of the flies, and the collection year for North and South Carolina populations; (b) among individuals on each host nested within each location and sex of the flies; (c & d) among locations and sex of the flies within each host plant species. All non-significant interactions were removed from the analysis. ................................................................................................................. 56? Table 2.6. Analysis of molecular variance estimated using the ADONIS function for EF-1? sequences from Phytomyza glabricola feeding on either Ilex coriacea or I.glabra. Variation was partitioned (a) among locations, year, and among individuals on each host plant nested within location for North and South Carolina populations (the only populations sampled in more than one year); (b) among locations and host plants nested within location; (c & d) among locations and sex of the flies within each host plant species. All non-significant interactions were removed from the analysis. .................................................................................................. 57? Table 2.7: Estimates of FST from AFLPs and EF-1? based on host plant (total samples), host plant within locations, and among locations within coriacea-flies and glabra- flies (separately). Samples from locations with less than five samples on one of the host plants were removed from all but the host plant comparison. ................. 58? Table 2.8. Summary statistics for AFLPs: a) all loci combined, b) outlier loci only, c) non-outlier loci only.......................................................................................... 59? Table 2.9. Outliers detected using DFDIST from comparisons between all study populations. Dashes indicate the trimmed mean FST was too low a value to run DFDIST. ?Repeated across comparisons indicates? the number of loci with an outlier above 95% in more than one location comparison (number in independent comparisons). ........................................................................................................ 60? Table 2.10. Summary of outlier loci found in host, sex, and geographic comparisons. Posterior probabilities in bold indicate marker found as an outlier in multiple ix independent population comparisons. Dashes indicate non-significant posterior probabilities (using an alpha of 0.05). .................................................................. 61? Table 2.11. Distribution of peaks in host-associated outliers. Numbers represent the number of individuals that have a peak at that locus. ........................................... 63? Table 2.12. Estimates of allele frequencies for host-associated outlier loci treating males and females of each host race separately. Male frequencies were estimated treating males as haploids and as diploids to compare to estimates using female loci. If haploid male estimates are more similar to female estimates than diploid male estimates (see Table 2.13), the locus will be treated as putatively on the X- chromosome. If females have no peaks present (all 0 alleles) and males have peaks, the locus is putatively on the Y-chromosome. ........................................... 64? Table 2.13. T-tests comparing estimated allele frequencies from Table 2.12. Comparisons were made between haploid male frequencies and female frequencies, then between diploid frequencies and female frequencies. Significantly different comparisons are primarily between haploid male estimated frequencies and female frequencies. The remaining significant differences between diploid male estimates and female estimates are also significantly different for haploid estimates as well, with the exception of locus 238. ............. 65? Table 2.14. Allele frequency estimates of sex-associated outliers treating males and females of each host race separately. Male frequencies were estimated treating males as haploids and as diploids to compare estimates using female loci. If haploid male estimates are more similar to female estimates than diploid male estimates (see Supp. Table 10), the locus will be treated as putatively on the X- chromosome. If females have no peaks present (bolded values of all 0 alleles) and males have peaks, the locus is putatively on the Y-chromosome. Bolded outliers were found to be in linkage disequilibrium with host-associated outlier 238. ..... 66? Table 3.1. Summary of collected samples from each population and site. .................... 102? Table 3.2. AFLP primer sequences. ............................................................................... 103? Table 3.3. Landmarks of leaf shape for comparisons of Ilex coriacea and I. glabra. ... 103? Table 3.4. Qualitative measurements of leaves and character coding for Ilex coriacea and I. glabra............................................................................................................... 104? Table 3.5. Quantitative measurements of leaves from Ilex coriacea and I. glabra. ...... 104? Table 3.6. Summary statistics for AFLPs. ..................................................................... 105? Table 3.8. Estimates of pairwise FST. ............................................................................. 106? Table 3.9. Assessment of discriminant functions based on samples separated by regions and for all samples combined. ............................................................................ 107? Table 3.10. Measurements of quantitative variables in Ilex coriacea, I. glabra, and their hybrids................................................................................................................. 108? Table 3.11. Character states of qualitative variables in Ilex coriacea, I. glabra, and their hybrids................................................................................................................. 109? Table 4.1: Genotyped sample sizes from each population. ............................................ 141? Table 4.2. Adjusted hybrid indices for plant populations. The standard hybrid index was adjusted so that all ?parental? individuals have an index of 0 and an index above 0 indicates some level of mixed genotype (see text). Adjusted indices were then averaged over all individuals in a population. .................................................... 142? x Table 4.3. Adjusted hybrid indices for fly populations. The standard hybrid index was adjusted so that all ?parental? individuals have an index of 0 and an index above 0 indicates some level of mixed genotype (see text). Adjusted indices were then averaged over all individuals in a population. .................................................... 142? xi LIST OF FIGURES Figure 1.1: Endemic range of the host plants, Ilex coriacea and I. glabra with collection sites labeled. .......................................................................................................... 14? Figure 1.2: Diagram of mating chamber. A piece of foam surrounds the base of the plant in its pot, sealing the bottom portion of the cup. Fine mesh was held over the cup with a rubber band. Honey was placed on the side of the cup so that flies had a food source. ........................................................................................................... 15? Figure 2.1: Endemic range of the host plants, Ilex coriacea and I. glabra with collection sites labeled. .......................................................................................................... 68? Figure 2.2. Alignment of translated EF-1? from Phytomyza glabricola to EF-1?-100e and EF-1?-48d from Drosophila melanogaster. ................................................... 69? 69? Figure 2.3: Spider diagrams of environmental factors fitted onto the ordination of AFLP data using non-metric multidimensional scaling. Lines connect each individual within a category to the centroid for that category. a) Host plant species; b) Sex of the fly. ................................................................................................................... 70? Figure 2.4. Results of non-metric multidimensional scaling (NMDS) of AFLPs. Yellow represents flies from I. coriacea and blue represent flies collected from Ilex glabra. Squares represent male flies and triangles are female flies. Four samples were genotyped as larvae, therefore their sex is unknown. .................................. 71? Figure 2.5. Haplotype network of EF-1? in P. glabricola. The size of nodes reflects the relative abundance of each haplotype in the total population. Nodes are colored based upon the frequency of flies from each host plant with that haplotype. Nodes are arranged to show size and connections, therefore connection length does not reflect the number of base pair changes between each haplotype. Each connection represents one base pair difference between nodes. The network is rooted by three closely related species: P. ilicis, P. ditmani, and P. ilicicola. .............................. 72? Figure 2.6: Haplotype network of EF-1? in P. glabricola. The size of nodes reflects the relative abundance of each haplotype in the total population. Nodes are colored based upon the frequency of flies from each location with that haplotype. Nodes are arranged to show size and connections, therefore connection length does not reflect the number of base pair changes between each haplotype. Each connection represents one base pair difference between nodes. The network is rooted by three closely related species: P. ilicis, P. ditmani, and P. ilicicola. .............................. 73? Figure 2.7. Results from among host plant comparison in DFDIST. Lines represent the 95% and 99% confidence intervals generated from the trimmed mean FST in DFDIST. .................................................................................................................. 74? Figure 3.1: Endemic range Ilex coriacea and I .glabra with collection sites labeled. ... 110? Figure 3.2. Sample scan of leaves from I. glabra. ......................................................... 111? Figure 3.3. Example of landmarks on an I. coriacea leaf. ............................................. 112? Figure 3.4. FST between Ilex coriacea and I. glabra among sampling locations. Error bars are 95% confidence interval estimates for FST. FST varies in magnitude among locations, but the differences are not statistically significant. ............................ 113? xii Figure 3.5. ?K for structure runs using a K of 1 to 15. A K of 2 was most representative of the data ............................................................................................................ 114? Figure 3.6. Results of STRUCTURE analysis K=2. Yellow corresponds to Ilex coriacea and blue to I. glabra. Each bar represents a single individual with the portion colored representing the posterior probability of the individual belonging to each cluster. Individuals are ordered by population from north to south (left to right). .......... 115? Figure 3.7. Comparison of the frequency of allele presence between Ilex glabra and I. coriacea. Variation among loci indicates a genetic mosaic of divergence among species in these loci. ............................................................................................ 116? Figure 3.8. Procrustes rotations of landmark data. a) I. coriacea, b) I. glabra, c) hybrids, d) mean shape of I. coriacea, I. glabra, and their hybrids superimposed under the same rotation and scaling. Yellow = I. coriacea, Blue = I. glabra, Green = Hybrids. The mean shape of hybrid leaves appear rounder and broader than those of I. coriacea and I. glabra. ................................................................................ 117? Figure 3.9. Plots of first two linear discriminants from discriminant functions based on traditional morphological characters from samples of Ilex coriacea, I. glabra, and hybrids. a-c) Analyses of regional divisions of samples. d) Analysis of all samples combined. Regions were chosen based on geographic proximity, genetic similarity, and presence of hybrids. Individuals are plotted according to their taxonomic classification based on analysis of genetic admixture: yellow represents > 90% I. coriacea, blue represents > 90% I. glabra, and green represents hybrids, all individuals not classified as parental species. The first axis discriminates between parental species and the second axis discriminates the hybrids from parental species. In general, hybrid individuals more closely resemble I. coriacea than I. glabra. .................................................................... 118? Figure 4.1: Endemic range Ilex coriacea and I .glabra with collection sites labeled. ... 143? Figure 4.2. Hypothesized effects of gene flow in plants on gene flow in insects. Ha: If traits important for host use in insects are intermediate in hybrid plants, insects from both parental host plant species could encounter one another on hybrid plants, potentially resulting in gene flow between insects that otherwise would not encounter one another. Therefore, the more hybridization found in a given location with both host plants, the more gene flow that would be expected to be seen between host-associated insect populations or species. Hb: If traits important for host use in insects are novel or transgressive in hybrid plants, they could prevent insects from either parental host plant species from using the novel host, potentially selecting for greater host fidelity, decreasing gene flow between host- associated insect populations or species. Hc: If traits important for host use in insects display a range of phenotypes from parental to intermediate to novel, there may be no association between hybridization in host plants and gene flow in insects. ................................................................................................................. 144? Figure 4.3. Adjusted hybrid index: The hybrid index varies between 0 and 1 where 0 represents an individual from species (or host-associated population) A with no mixed ancestry and 1 represents an individual from species (or host-associated population) B with no mixed ancestry. Individuals with hybrid indices between 0 and 1 represent individuals with some degree of mixed ancestry, where 0.5 would represent an F1 hybrid. If hybrid indices are averaged in a location with both A xiii and B, the average would likely be an intermediate value closer to the species (or host-associated population) with the larger sample size. Therefore, hybrid indices were standardized by subtracting any values greater than 0.5 from 1, resulting in values between 0 and 0.5 where 0 represents parental and 0.5 represents an F1 hybrid. The image on the left contains the original hybrid indices of individuals from NC followed by their adjusted hybrid index on the right. Once values have been standardized, they can be averaged for a population to obtain a comparable estimate of the degree of hybridization within a given population. .................... 146? Figure 4.4. Comparison of hybrid indices of individual flies on their host plants. Hybrid indices were generated based on AFLPs. Shape indicates plant status and color indicates fly status using a 10% threshold to be considered a ?hybrid?. ............. 148? Figure 4.5. Average adjusted hybrid indices of populations. Populations had a minimum of five individuals present. Population CHE was left out of the regression analysis because it is out of the range of I. coriacea. ....................................................... 149? 1 CHAPTER 1: NO-CHOICE MATING TRIALS REVEAL THE PRESENCE OF REPRODUCTIVE ISOLATION BETWEEN HOST FORMS OF PHYTOMYZA GLABRICOLA ON ILEX CORIACEA AND I. GLABRA ABSTRACT Speciation is the process by which taxa are split into independently evolving lineages. Where a given population or species falls on the continuum of divergence between one and two species depends on the degree of gene flow between the taxa. Reproductive isolation between taxa is one way to decrease gene flow between taxa and allow evolution to progress towards eventual speciation. In this study, I used no-choice mating trials to test for the presence of reproductive isolation between host forms of a leaf- mining fly, Phytomyza glabricola, on its two holly host species, Ilex coriacea and I. glabra. I found that reproductive isolation does exist between host forms in a controlled greenhouse setting. In addition, the presence of either host plant does not affect the mating success of the flies. The results indicate host forms of P. glabricola may be well on their way to becoming different species, although field studies are needed to validate these findings. 2 INTRODUCTION How new species evolve, whether through selection or drift, in allopatry or sympatry, gradually or in spurts, has been a subject of much debate, even before the seminal works of Darwin (1858, 1859) and Wallace (1858, 1876). One large part of the debate is how to define a species (Coyne and Orr 2004). At least nine species definitions exist (reviewed in Coyne and Orr 2004), typically applied to studies to which they are most appropriate. As more research has accumulated, we have come to view speciation as a continuum with species definitions falling at different stages in the process (Harrison 1998; Dres and Mallet 2002). Where taxa fall on that continuum hinges on the degree of gene flow among diverging lineages: as gene flow decreases, lineages grow closer to species status. Because specificity to host plants can enforce reproductive isolation, a large number of studies have focused on host-associated populations (Walsh 1864; Diehl and Bush 1984; Waring et al. 1990; Abrahamson et al. 2003; Stireman et al. 2005; Dickey and Medina 2010; Barman et al. 2012), populations with varying degrees of divergence that fall in the middle of the continuum between a single and multiple species (Dres and Mallet 2002; Funk 2012). The majority of these host-associated systems consist of host forms (Funk 1998; Funk et al. 2002; Nosil et al. 2009), populations with host-associated biological variation, but where the kind and degree of variation have not been fully examined (Funk 2012) and host races, incompletely reproductively isolated populations in sympatry that also remain distinct in the face of gene flow due to divergent selection on populations using alternate hosts (Thorpe 1930; Bush 1969; Jaenike 1981; Dres and Mallet 2002). Host forms and host races imply genetically distinct populations that are associated with different hosts, 3 such as in herbivorous insects (Bush 1969; Phillips and Barnes 1975; Feder et al. 1988; Brown et al. 1996; Via 1999; Abrahamson et al. 2003; Diegisser et al. 2006; Scheffer and Hawthorne 2007; Barman et al. 2012), parasites (Hoberg and Brooks 2008; Kempf et al. 2009), and parasitoids (Stireman et al. 2006; Kolaczan et al. 2009). Understanding why these host-associated populations are genetically distinct requires knowledge of the barriers to gene flow: what degree of reproductive isolation exists between host- associated groups? If it does exist, what causes the isolation? If isolation is incomplete or nonexistent, how can divergence persist in the face of gene flow? To address these questions, it is important to determine whether or not reproductive isolation does, in fact, exist. Will individuals from different host forms mate with one another and produce viable offspring? Here, I address this most fundamental question of reproductive isolation using a newly studied host form system of a leaf-mining fly feeding on two species of holly, all of which are endemic to the eastern United States. Phytomyza glabricola Kulp belongs to a radiation of 14 closely related species, most of which are monophagous and all of which feed on hollies in the genus Ilex (Aquifoliaceae) (Kulp 1968; Scheffer and Wiegmann 2000; Lonsdale and Scheffer 2011). Unlike its congeners, P. glabricola feeds on two sister species of holly, Ilex glabra (L.) A. Gray and Ilex coriacea (Pursh) Chapm. Ilex glabra?s range begins in Maine and extends south to Florida and west to northeastern Texas (Figure 1.1). Ilex coriacea?s range is restricted to the southern portion of I. glabra?s range, where it is sympatric and syntopic to I. glabra (Scheffer 2002; JBH pers. obs.). 4 When feeding on I. coriacea, P. glabricola (hereafter ?coriacea-flies?) have a development time of approximately 9-10 months and are univoltine , whereas P. glabricola feeding on I. glabra (?glabra-flies?) have a larval development time of 2-4 weeks and are multivoltine (Kulp 1968; Al-Siyabi and Shetlar 1998; Scheffer 2002; Scheffer and Hawthorne 2007). Despite these phenological differences, adult P. glabricola from both hosts emerge in synchrony in mid-January to mid-February (Scheffer 2002), therefore creating the opportunity for flies originally from the two host plant species to mate. Adult flies that emerge from each host do not differ morphologically in either external characters or genitalia (Scheffer 2002; Lonsdale and Scheffer 2011). Initial work using amplified fragment length polymorphism (AFLP) frequencies revealed that fly populations from North and South Carolina show host-plant based genetic divergence (Scheffer and Hawthorne 2007). However, mitochondrial haplotypes did not cluster by host plant or location, reflecting either a lack of lineage sorting due to recent divergence or introgression via continuing gene flow (Scheffer and Hawthorne 2007). In this study, using no-choice mating trials in a full factorial design (male host, female host, and host plant(s) present) in the greenhouse, I tested same-host and cross- host mate pairs of flies to determine which fly combinations mated and produced viable offspring, and whether the success of matings depended on presence or absence of particular host plant species. I estimated the degree of reproductive isolation by comparing the number of among-host matings (e.g., female coriacea-fly with male glabra-fly) to same-host matings (e.g., female and male coriacea-flies) producing adult offspring. This comparison 5 provided a coarse measure of overall reproductive isolation including prezygotic as well as extrinsic and intrinsic postzygotic barriers encompassing mating, oviposition, larval development, and successful emergence of adult flies. Flies must survive all of these stages in order to be able to pass their genes on to the next generation; therefore all are required for successful gene flow. If coriacea-flies and glabra-flies are completely reproductively isolated, I expected no successful among-host mate pairs to produce viable offspring. If there is partial reproductive isolation between coriacea-flies and glabra-flies, I expected some among-host mate pairs to be successful, but significantly less than same- host mate pairs. Finally, if there is no reproductive isolation between coriacea-flies and glabra-flies, I expected no difference in the success rate of among-host and same-host mate pairs. Varying host plant species in the mating chambers allowed me to assess the importance of the physical presence of the host plant species in mate choice and mating success. If flies have a mating preference based on presence of the natal host plant, I expected more successful matings when the natal host was present than when the natal host was absent. In addition, I included trials with both host species and observed the presence/absence of leaf-mines (successful larval development) and from which mines adult flies emerge on each host plant species. I then used differences in the presence of leaf-mines, from which leaf-mines adult flies emerged, and the time taken to develop within the leaf-mine, to identify the role of host plant species on the success of mate pairs and the basis of differences in development time. 6 METHODS Collections Flies were collected in January and February of 2006 from Croatan National Forest in North Carolina and Francis Marion National Forest in South Carolina (Figure 1.1). Leaves containing well-developed leaf-mines were removed from host plants and placed into plastic bags labeled for site and host plant species. Abundance of leaf-mines and rates of parasitism varied between locations, leading to unequal sample sizes among populations. Pupae were dissected from mines and placed individually in 0.5 mL Eppendorf tubes and stored in a moist chamber until the emergence of adults. Mating trials No-choice mating experiments were performed in modified 16 ounce plastic cups surrounding small propagated host plants in the greenhouse (Figure 1.2). A total of 107 trials were conducted using every combination of male fly and female fly (from I. coriacea or I. glabra) placed in mating chambers with either I. glabra, I. coriacea, or both host plants present (Table 1.1, Figure 1.2). As flies only live a few days in the greenhouse, mate pairs were generated as soon as a male and female fly eclosed from the same location. The host plant(s) on which they were tested was randomized. Each trial was observed twice a day to note formation of leaf-mines and the emergence of adults from pupae. Dead parental flies were removed from the cup, placed in 100% ethanol, and stored at -80?C. Trials were considered unsuccessful if no leaf-mine was formed after three months. A Pearson?s chi-squared contingency test was used to determine if there was a significant difference in the success rate between same-host and among-host mating 7 trials, allowing me to determine whether different host forms of P. glabricola were capable of producing adults that could potentially allow introgression of alleles among host forms. Hence, a mating trial was considered successful if the mate pair produced offspring that eventually emerged as an adult from at least one of the mines inside the mating chamber. First, I compared the number of successful and unsuccessful trials for same-host versus among-host mate pairs to test for overall reproductive isolation. Next, I compared the number of successful and unsuccessful trials in presence and absence of the natal host plant species to test whether the natal host species is required for mating success. Last, I compared the number of successful and unsuccessful trials in presence versus absence of the non-natal host to test whether the non-natal host prevents successful mating. Tests were performed in the statistical package R (v2.7.2, R Development Core Team, 2010). P-values were computed using a Monte Carlo test (Hope, 1968) with 107 replicates to compensate for a potential lack of power due to small sample sizes. To address whether differences in development time in the wild are only under genetic control, means and standard errors were calculated for development time on each host. In addition, a 2-sample heteroscedastic t-test was conducted in R to test whether development time differed between offspring from different parental combinations. RESULTS Only 12 of the 107 trials successfully resulted in adult offspring, all of which were same-host trials (Table 1.1). Despite the low number of successful matings, significantly more same-host trials were successful than among-host trials (?2 = 7.44, 8 p < 0.01). Because no among-host trials produced offspring, the remaining results refer to same-host trials only. Host plant species presence had no effect on mating success. The presence of the natal host did not appear to increase mating success in either coriacea-flies (?2 = 4.8081, p = 0.06977) or glabra-flies (glabra-flies: ?2 = 0.0845, p = 1; Table 1.2). In addition, the non-natal host did not decrease mating success (coriacea-flies: ?2 = 0.4444, p = 0.6561; glabra-flies: ?2 = 1.712, p = 0.3127; Table 1.2). Interestingly, adult offspring emerged from both host plant species for both coriacea-fly and glabra-fly same-host matings. Offspring emerged from coriacea-fly same-host trials on I. coriacea alone as well as trials with both host plant species present (Table 1.1). For the latter, adults emerged from leaf- mines on I. coriacea as well as from I. glabra. Offspring from glabra-fly same-host trials emerged from trials on I. coriacea alone and trials on I. glabra alone (Table 1.1). Finally, all offspring emerged from each host plant species within two months of the start of the trial. Offspring produced from coriacea-fly mate pairs took 45 ? 2.0 days to emerge whereas flies from glabra-fly same-host mate pairs emerged in 54 ? 5.4 days. The time to emergence did not significantly differ between coriacea-fly and glabra-fly same-host crosses (t = 1.55, df = 6.35, p = 0.17). DISCUSSION When studying speciation, it is important to determine the degree of gene flow between potentially reproducing populations. In this study, I demonstrated the presence of reproductive isolation between host-associated populations of P. glabricola on its host plants, I. coriacea and I. glabra. I found host plant species presence had no effect on 9 mating success. My results suggest host forms of P. glabricola may be well on their way to becoming distinct species. The lack of viable offspring from any among-host mate pairs suggests the presence of prezygotic or postzygotic barriers to gene flow. No mating behavior was observed and I could not detect oviposition unless a leaf-mine formed, so I was unable to separate premating isolation from among-host inviability. The apparent reproductive barriers indicate that genetic signatures of gene flow (Scheffer & Hawthorne 2007, Chapter 2) are more likely due to incomplete lineage sorting than to ongoing gene flow. There were a low number of successful trials, possibly due to performing the experiments in the greenhouse rather than the natural environment. Conditions in the greenhouse were optimal for plant growth (temperature, light, and water controlled with fertilizer), and are likely different from conditions in their natural pocosin habitat (sandy soil over peat, acidic, low in nutrients such as nitrogen and phosphorus, and often poorly drained although seldom standing water; Smith et al. 1956; Wilbur and Christensen 1983; Richardson 1991; Mitchell et al. 1995). The increased nutrient levels in the green house could have changed important traits such as plant volatiles, physiological chemistry, and secondary metabolites (Kainulainen et al. 1996; Gaston et al. 2004; Scutareanu and Loxdale 2006; Nell et al. 2009; Olson et al. 2009; Winter and Rostas 2010; Ibrahim et al. 2011), all of which could affect the willingness of flies to mate and oviposit (Feder et al. 1995; Nishida et al. 1996; Gouinguene and Stadler 2005; Joyce et al. 2008; Cook et al. 2011) and the ability of offspring to complete their life cycle (Potter 1992; Melo et al. 2006). For example, Diptera are known to use pheromones derived from nutrition sources (Tillman et al. 1999) for signaling during courtship (reviewed in Wicker-Thomas 2007). 10 Changes to the chemistry of their host could change the pheromone composition, preventing the completion of copulation. In addition, the small containers may have interfered with visual courtship displays commonly found in flies, including agromyzids (Ota and Nishida 1966; Carriere and McNeil 1988). Two species of Phytomyza have also been found to use substrate-borne courtship songs (Kanmiya 2006); the vibrations from fans and other equipment in the greenhouse could disrupt such acoustic signaling. Future work should focus on the rates of same-host and across-host matings in natural conditions. Flies from the same host plant successfully mated and success did not depend on which host plant species was present, suggesting host plant presence does not affect mating success (either as an attractant or a deterrent). In addition, offspring from these mate pairs were able to emerge from both I. coriacea and I. glabra, regardless of the parents? natal host. Therefore, it is possible that females could make oviposition ?mistakes?, laying eggs on non-natal hosts, and if the offspring can survive on the non- natal host, as suggested here, these mistakes could lead to gene flow among host forms. Again, the lack of a difference could be due to the greenhouse setting. Changes in plant chemistry and general substrate could affect mating preferences. Furthermore, these were no-choice trials, so females could have oviposited on the non-natal host out of necessity, whereas in normal conditions, they would not. Field work is needed to determine whether host plants affect mating success, females oviposit on the non-natal host, and if larvae and pupae of flies can survive in wild populations. Unexpectedly, all offspring of successful mate-pairs emerged within two months, irrespective of what host plant they emerged from. Flies from I. coriacea typically take 11 nine months to develop in the wild, as opposed to two months for flies from I. glabra (Scheffer 2002). The reduction in development time suggests there is at least some environmental component to the flies? rate of development on each host plant species. Insect development can depend on how well host plants are defended: insects tend to have more generations on plants that are less well defended (Hunter and McNeil 1997; Steinbauer et al. 2004; van Asch and Visser 2007), and host plant quality can influence the induction of diapause (Hunter and McNeil 1997; Ito 2003; Ishihara and Ohgushi 2006; Ito and Saito 2006; Takagi and Miyashita 2008). Foliar nitrogen content is known to vary with soil nutrients (Marschner 1995) and can directly affect the growth rate of phytophagous insects (White 1993; Cornelissen and Stiling 2006). The addition of fertilizer in the greenhouse could explain more rapid development if I. glabra is better able to obtain nitrogen than I. coriacea in natural populations. The mechanisms underlying reproductive isolation in these flies warrants further investigation. I do not yet know the specific mating behavior of these flies, so I may have missed key features important for mating success such as space for flies to move in, additional mates to choose from, day length, or external temperatures. In addition, changes in nutrient content could affect plant volatiles and nutrition, which could play a role in oviposition choice and mating behavior. Future work should focus on replicating natural conditions to determine whether or not complete reproductive isolation exists between host forms of P. glabricola. I have now established that reproductive isolation exists between host forms of P. glabricola, so I can begin to investigate what ecological, behavioral, and/or genetic factors serve as barriers to gene flow in this system. It is important to use recently 12 diverged populations and species to study these barriers, as the original factors causing divergence may disappear over time (Coyne and Orr 2004). Using populations in the ?grey area? of species status will allow us to determine what elements are the most important drivers of speciation, and therefore understand how the great biodiversity we see today originally arose. In conclusion, my study suggests populations of P. glabricola are closer to the species end of the speciation continuum between populations and species. My mating trials indicate a large degree of reproductive isolation exists among populations of P. glabricola on its two host plant species, corresponding to previous molecular work demonstrating significant genetic divergence between the host forms (Scheffer and Hawthorne 2007). I found that female flies will oviposit on both host plant species and offspring are capable of surviving on the parental non-natal host in greenhouse conditions. In addition, I found no evidence that flies must mate in the presence of their natal host or the absence of the non-natal host, indicating migration may be possible between host forms. However, because no cross-host mating pairs produced viable offspring, I have no indication that migration will result in gene flow between host forms of the flies. 13 Table 1.1. Mating trials of Phytomyza glabricola on its host plants, Ilex glabra and I. coriacea. Trials were considered successful if the flies mated, the female oviposited eggs, and the offspring successfully emerged as adults. Male fly Female fly Host-plant species present # Successful Trials Total # of Trials Glabra Glabra Glabra 3 12 Glabra Glabra Coriacea 2 12 Glabra Glabra Both 0 11 Glabra Coriacea Glabra 0 5 Glabra Coriacea Coriacea 0 5 Glabra Coriacea Both 0 4 Coriacea Glabra Glabra 0 8 Coriacea Glabra Coriacea 0 8 Coriacea Glabra Both 0 8 Coriacea Coriacea Glabra 0 12 Coriacea Coriacea Coriacea 3 11 Coriacea Coriacea Both 4 11 Total 12 107 Table 1.2. Comparison of mating trials of Phytomyza glabricola in presence versus absence of the natal and non-natal host plant species. Trials were considered successful if the flies mated, the female oviposited eggs, and the offspring successfully emerged as adults. Natal present Natal absent Non-natal present Non-natal absent Coriacea-Coriacea mate pairs Successful 7 0 4 3 Unsuccessful 15 12 19 8 Glabra-Glabra mate pairs Successful 3 2 2 3 Unsuccessful 20 10 21 9 14 Figure 1.1: Endemic range of the host plants, Ilex coriacea and I. glabra with collection sites labeled. Ilex glabra Ilex coriacea & Ilex glabra Croatan, NC Francis Marion, SC 15 Figure 1.2: Diagram of mating chamber. A piece of foam surrounds the base of the plant in its pot, sealing the bottom portion of the cup. Fine mesh was held over the cup with a rubber band. Honey was placed on the side of the cup so that flies had a food source. 16 CHAPTER 2: EVIDENCE FOR ECOLOGICAL SPECIATION IN THE HOLLY LEAF-MINER, PHYTOMYZA GLABRICOLA (DIPTERA: AGROMYZIDAE) ABSTRACT Evolutionary radiations have been well documented in plants and insects, but we have yet to determine the relative impact of genetic drift and natural selection underlying these radiations. If the radiations are adaptive, the diversity of species could be due to ecological speciation in these lineages. Agromyzid flies are known to have repeated host- associated radiations, so I take advantage of previously identified host forms of P. glabricola associated with Ilex coriacea and I. glabra to test whether the species undergoing ecological speciation. Using AFLPs and nuclear sequence data, I found a geographic mosaic of genetic divergence between host forms across the range of these flies. Flies on I. glabra are multivoltine whereas flies on I. coriacea are univoltine, and voltinism is at least partially controlled by the environment, suggesting plant-mediated genetic divergence could lead to host race formation without the evolution of host preference. The data also suggest the flies expanded from I. glabra to I. coriacea and are now experiencing divergent selection. Genome scans revealed several loci under divergent selection in multiple populations of these flies. It appears P. glabricola is in the process of ecological speciation, suggesting ecological speciation could be at least partially responsible for host-associated radiations in these flies. 17 INTRODUCTION Understanding the evolution of biotic diversity is one of the primary aims of biology. Phytophagous insects are known to be extremely diverse, making up over 25% of the total terrestrial biodiversity (Strong et al. 1984; Price 2008). Much of the diversity was generated by radiations of phytophagous insects onto a number of host plant taxa, particularly angiosperms (Mitter et al. 1988; Farrell 1998; Winkler and Mitter 2008). The wide variety of chemical and morphological defenses of plants combined with a number of plant modules (e.g., leaves, stems, flowers, and fruits) provide many adaptive zones (Simpson 1949, 1953) in which phytophagous insects can specialize (Ehrlich and Raven 1964; Price 2008). Ehrlich and Raven (1964) described how evolutionary radiations of plant lineages could result from the evolution of novel defensive chemistry, followed by evolutionary radiations of phytophagous insects from reciprocal changes to adjust to that chemistry (i.e., ?escape and radiate?). Evolution of key innovations, such as the ability to digest plant defensive chemicals combined with dispersal into a new habitat (e.g. a host plant range expansion) provide ecological opportunities needed for adaptive radiations (Simpson 1949, 1953; Mitter et al. 1991; Schluter 2000; Yoder et al. 2010). If insects mate on their host plant, specialization to a host plant species can result in reproductive isolation and can eventually lead to speciation (Ehrlich and Raven 1964; Wheat et al. 2007; Janz and Nylin 2008). Although patterns of host-associated radiations have been well-documented (Mitter et al. 1988; Farrell 1998; Winkler and Mitter 2008; Yoder et al. 2010), our understanding of the speciation processes and host specialization that give rise to these 18 patterns remains contentious (Coyne and Orr 2004). Darwin first connected speciation with adaptive divergence to different habitats (Darwin 1859). Conceptual models shifted to allopatry with neutral accumulated changes (Mayr 1963; Nosil 2008) followed by sympatric models where fitness and reproduction were associated with habitat preference (Bush 1969; Felsenstein 1981; Rice and Hostert 1993; Hawthorne and Via 2001; Schluter 2001; Via 2001; Feder et al. 2005). More recently, studies of speciation have shifted away from a focus on geographic distribution towards an emphasis on ecologically-based adaptive divergence causing reproductive isolation in either allopatry or sympatry, termed ?ecological speciation? (Futuyma and Moreno 1988; Rundle et al. 2000; Schluter 2000). In phytophagous insects, adaptation to different host plants can decrease gene flow between host-associated populations of insects, especially if the insects reproduce on the host (Smith 1966; Diehl and Bush 1984; Schluter 2001; Turelli et al. 2001; Via 2002). Specific host-associated systems such as host forms (Funk 1998; Funk et al. 2002), populations with an unknown kind and/or degree of host-associated biological variation (Funk 2012) and host races (Thorpe 1930; Bush 1969; Jaenike 1981; Dres and Mallet 2002) demonstrate intermediate steps in speciation, representing the evolution of ecological divergence. Still, ecological divergence is not synonymous with speciation, and we have yet to determine the relative impact of divergent selection versus genetic drift on whether or not speciation proceeds to completion. To determine whether ecological speciation could be responsible for radiations of phytophagous insects on host plants, we need to focus currently diverging or recently evolved taxa within adaptive radiations and determine whether ecological speciation can account for the divergence. 19 The Agromyzidae (leaf-mining flies) show considerable evidence of repeated host-associated radiations (Spencer 1990; Scheffer and Wiegmann 2000; Winkler et al. 2009b). The genus Phytomyza is the largest Agromyzid genus, and is comprised of a large number of host-associated radiations primarily associated with the Ranunculaceae and families within the Asteridae (Winkler et al. 2009a; Winkler et al. 2009b). Phytomyza glabricola Kulp, a species endemic to the eastern United States, belongs to a radiation of 14 closely related species, all of which feed on hollies in the genus Ilex (Aquifoliaceae) and most of which are monophagous (Kulp 1968; Scheffer and Wiegmann 2000; Lonsdale and Scheffer 2011). Unlike its monophagous congeners, P. glabricola feeds on two sister species of holly, Ilex glabra (L.) A. Gray and Ilex coriacea (Pursh) Chapm, both of which are also endemic to the eastern United States (Selbach-Schnadelbach et al. 2009; Manen et al. 2010). Ilex glabra and I. coriacea are found in baygall and pocosin habitats in the coastal plains of the eastern United States (Caughey 1945; Richardson 1983, 1991; Brooks et al. 1993). Ilex glabra is present from Maine south to Florida and west to northeastern Texas (Figure 2.1). Ilex coriacea is sympatric with I. glabra (Scheffer 2002), but it has a much smaller distribution, limited to the southern portion of I. glabra?s range. It also has a patchier distribution than I. glabra, likely due to lower tolerance of dry conditions (Mohlenbrock 1976; Brooks et al. 1993). Where sympatric, the plants are often also syntopic, with leaves from one plant commonly in contact with leaves of the other species. In addition, the two species likely hybridize in nature (Robert K. Godfrey Herbarium 2012, Specimens 000016759-000016766) Hybridization is not surprising considering Ilex species are often very genetically similar to one another (Cuenoud et al. 20 2000; Setoguchi and Watanabe 2000; Manen et al. 2002; Manen 2004; Manen et al. 2010), as evidenced by the many ornamental Ilex cultivars that have been generated by interspecific hybridization (Galle 1997). In the field, when feeding on I. glabra, P. glabricola (hereafter ?glabra-flies?) have a development time of approximately 2-4 weeks and are multivoltine, whereas P. glabricola feeding on I. coriacea (?coriacea-flies?) have a development time of 9-10 months and are univoltine (Kulp 1968; Al-Siyabi and Shetlar 1998; Scheffer 2002; Scheffer and Hawthorne 2007). Despite these phenological differences, adult P. glabricola from each host emerge in synchrony in mid-January to mid-February (Scheffer 2002). Adult flies that emerge from each host do not differ morphologically in either external characters or genitalia (Scheffer 2002; Lonsdale and Scheffer 2011). On greenhouse grown plants, female flies will oviposit on the non-natal host, and the offspring can develop into adult flies (Scheffer pers. comm.; Chapter 1). Mating trials also indicate the presence of reproductive isolation between flies from the two host plant species (Chapter 1). Initial work revealed that fly populations from North and South Carolina show host plant-based genetic divergence based on amplified fragment length polymorphism (AFLP) frequencies (Scheffer and Hawthorne 2007). However, mitochondrial haplotypes did not cluster by host plant or location, reflecting either a lack of lineage sorting due to recent divergence or introgression via continuing gene flow (Scheffer and Hawthorne 2007). Whether divergence exists throughout the range of these insects and their host plants has not been examined and could differ for several reasons. The host plant ranges 21 do not fully coincide, so there may be different degrees of divergence in locations supporting only I. glabra. The host plant range spans a very wide latitudinal gradient possibly altering intrinsic and extrinsic factors such as developmental patterns and natural enemy abundances. In addition, as mentioned above, the host plants likely hybridize in nature, and initial morphological observations suggest hybridization rates differ among locations (see Chapter 3). Because hybridization could produce plants with mixed traits, it could change the distribution of insects on the host plants in different locations, potentially affecting the degree of gene flow in flies among host plant species (see Chapter 4). In this study, I first asked is the degree of genetic divergence across the natural range of P. glabricola similar to the results of Scheffer and Hawthorne (2007)? I used DNA sequence data from the nuclear protein-coding gene Elongation Factor-1? (EF-1?) as well as AFLP data to test for host-associated genetic divergence from populations spread across the sympatric range of the host plant species. I also used this data to examine the amount and direction of gene flow between host forms of P. glabricola by identifying migrants and offspring of cross-host matings. If host-associated radiations of agromyzids, particularly in Phytomyza species feeding on Ilex, are a result of host expansions followed by ecological speciation, I expected to find a pattern of a host range expansion where flies from one host plant species are ancestral to flies from the other species, and genetic signatures of divergent natural selection. First, to determine the direction of the initial host range expansion, I estimated diversity and genetic structure using the EF-1? dataset. I expected more genetic variation and older haplotypes in flies from the ancestral host plant (Harrison 1991; 22 Brown et al. 1996), whereas there should be no difference in the diversity and relative age of haplotypes if both host forms of flies arose at the same time, such as from an additional host. Finally, I asked whether the genetic divergence is due to natural selection or genetic drift associated with vicariance. I used genome scans of AFLPs to detect genetic patterns of divergent selection among genomes of coriacea-flies and glabra-flies then tested for linkage disequilibrium between outliers. If divergent selection reduced gene flow between host forms, the genomic architecture of selected loci, such as physical linkage or sex-chromosome linkage, would increase the likelihood of eventual ecological speciation in P. glabricola. MATERIALS AND METHODS Collections Flies were collected in January and February of 2006 from Croatan National Forest in North Carolina and Francis Marion National Forest in South Carolina, and again in 2007 with additional samples from Cape Henlopen State Park, DE, the Great Dismal Swamp National Wildlife Refuge, VA, Crooked River State Park, GA, Etoniah Creek State Forest, FL, and Apalachicola National Forest, FL (Figure 2.1). Ilex glabra was found at every collection site; however I. coriacea was absent from the most northern sites (NY, NJ, DE, MD) which are outside the plant?s geographic range, and from the GA and Archibold, FL sites. Leaves containing well-developed leaf-mines, and visible larvae, were removed from host plants and placed into plastic bags labeled for site and host plant species. Pupae were dissected from mines and placed individually in 0.5 mL Eppendorf 23 tubes and stored in a moist chamber until adults emerged. Adult flies were placed in 100% ethanol and stored at -80?C. AFLPs Genomic DNA was extracted from 183 individual flies (96 coriacea-flies and 87 glabra-flies) following the animal tissue protocol of the Qiagen DNeasy kit (Qiagen, Valencia, CA). DNA concentrations were standardized to 12.5 ng/?L. AFLP constructs were assembled in a single-tube reaction by mixing 30.0 ?L of genomic DNA, 5.0 ?L 10 X NEBuffer 3 [100 mM NaCl, 50 mM Tris-HCl, 10 mM MgCl2, 1 mM dithiothreitol (DTT)] (New England Biolabs, Ipswich, MA), 0.5 ?L 100X bovine serum albumen (BSA), 5.0 ?L 10mM ATP, 5 units PstI, 5 units EcoRI, 100 units T4 DNA ligase (Genscript, Piscataway, NJ), and 1 ?L each of 5 ?M double-stranded EcoRI and PstI adapters (Hawthorne 2001). The reactions were incubated at 37 C for 5 hours and then 80 C for 20 minutes. Each reaction was then diluted 1:10 with ultrapure H2O and stored at -20 C. A two-step amplification was used (Vos et al. 1995): the preamplification step used one selective base on each primer (EcoRI-A and PstI-A) in a 10 ?L reaction [1.5 mM MgCl2, 0.125 mM dNTPs, and 0.5 units Taq DNA polymerase (Genscript, Piscataway, NJ) combined with 0.25 ?M primers and 2.0 ?L of template DNA]. The reaction was cycled 21 times for 30 sec at 95 C, 1 min at 56 C, and 1 min 72 C with an additional extension period of 5.5 min at 72 C. Preamplification products were diluted 1:40 with ultrapure H2O and stored at -20 C. The selective amplification was performed using the same 10 ?L cocktail, but with a fluorescein amidite (FAM)-labeled primer with additional selective bases in place of EcoRI-A (Table 2.1). A touchdown-PCR was used 24 starting with an annealing temperature of 65 C which was decreased by 1 C for 8 rounds of amplification, followed by 22 rounds of amplification at an annealing temperature of 58 C, and an additional extension period of 7 min at 72 C. PCR products were separated with an ABI 3730 DNA Analyzer (Applied Biosystems, Carlsbad, CA) using MapMarker X-Rhodamine (ROX) labeled 1000bp ladder (BioVentures, Murfreesboro, TN). Electropherograms were scored using GENEMAPPER v.3.7 (Applied Biosystems, Carlsbad, CA). Fragments between 76 and 800 base pairs were first scored using the automated procedure and secondarily checked by eye. To measure the repeatability of peaks, six individuals were repeated across plates and an additional ten individuals replicated within each plate. Negative controls (H2O template) were included at every step of the process. A genotyping error rate was estimated as the ratio of electropherogram peak mismatches among the replicates to the total number of replicated markers (Pompanon et al. 2005). Loci with peak mismatches among repeated samples were removed from the analysis as were loci occurring at the same sizes as peaks observed in the negative controls. Mismatches were not equally distributed among loci: some loci had only a single individual with a mismatch whereas others showed mismatches in a large number of individuals. Therefore, the percentage of loci removed due to mismatches was much higher than the overall genotyping error rate. Finally, because a significant negative correlation of fragment frequency and fragment size may be caused by excessive homoplasy, I estimated that correlation using AFLPSURV (Vekemans et al. 2002). 25 Nuclear sequence data A 910-bp DNA fragment of the nuclear protein-coding gene Elongation Factor-1? (EF-1?) was amplified from genomic DNA of 236 flies (122 coriacea-flies and 114 glabra-flies) collected in 2006 and 2007, and 46 flies (25 coriacea-flies and 21 glabra- flies) from a previous study (Scheffer and Hawthorne 2007) using the primers found in Table 2.1. A standard amplification protocol was used to amplify the fragments, with initial denaturation at 95?C for 2 min followed by 12 cycles of 92?C for 15 s, 56?C for 30 s, and 70?C for 1 min 30 s, then 32 cycles of 92 ?C for 10 s, 55 ?C for 15 s, and 72 ?C for 1 min 30 s, with a final extension at 72 ?C for 10 min. PCR products were purified using either the QIAquick PCR purification kit or the QIAquick gel extraction kit (Qiagen, Inc.). Purified PCR product was used in sequencing reactions with BigDye sequencing kits (Applied Biosystems, Foster City, CA) and the products generated using an ABI-3130 automated sequencer (Applied Biosystems). Diploid sequencing was conducted using nested primers to ensure overlap of at least two amplifications for each sample (Table 2.1). Sequence contigs were assembled and aligned using CODONCODE ALIGNER (v.2.0 CodonCode Corp., Dedham, MA). Heterozygous states were identified as dual peaks. The reading frame of the final consensus sequence was determined by comparison with EF-1?100E and EF-1?48D in Drosophila melanogaster. Allelic phase for EF-1? sequences was reconstructed using the program CVHAPLOT (v.2.01 Huang et al. 2008; Huang and Zhang 2010). CVHAPLOT runs the sequences through several phase- determining programs, each of which has a different algorithm for phase-determination. The resulting haplotypes are then compared among analyses to check for consensus between programs. CVHAPLOT was run with the entire data set, then with flies from each 26 host plant separately. Separating flies from each host plant gave a better consensus among programs, therefore those results were used. Taking a conservative approach, only samples with agreement in 5 or more programs were included in the following analyses (Huang et al. 2008; Huang and Zhang 2010). Geographic scale of host plant associated genetic divergence Host plant associated genetic differentiation was estimated for the entire data set as well as within geographic locations using both AFLP markers and EF-1? sequence data. For AFLPs, 5000 permutations were run to calculate and test the significance of FST using AFLPSURV (v.1.0 Vekemans et al. 2002). For EF-1? sequence data, ?ST (Excoffier et al. 1992) was estimated using ARLEQUIN (v.3.5 Excoffier et al. 2005). FST (and ?ST) for within-host comparisons among locations were calculated only if at least five individuals were present in a population on a single host plant species; for among-host comparisons, locations were only included if at least five individuals were present on each host plant species. I took two additional approaches to measuring the genetic divergence among flies collected from different plant species and locations: an analysis of molecular variance was performed using a permutational MANOVA via the ADONIS function from the VEGAN package (Oksanen et al. 2010 ) in the statistical package R (v 2.11.1, 2010), and using a clustering method that required no a priori hypotheses of substructure using the AFLP data. The distance matrix for EF-1? was calculated using the F84 model of nucleotide substitution (Kishino and Hasegawa 1989; Felsenstein and Churchill 1996) in DNADIST, part of the PHYLIP package (v.3.69 Felsenstein 2005); Jaccard distances were calculated using the AFLPs because they are based only on the shared presence of peaks. 27 ADONIS models were constructed to test the effects of host plant source and collection site location on the genetic structure of flies from all locations and to test the effects of collection year using only the locations common to all years collected. ADONIS models were also constructed to test the effects of sex of the fly on genetic structure of the flies using AFLP data. Models were run with host plant source nested within location. Models for each analysis were first run with all interactions then interactions were sequentially removed if non-significant. Significance was based on 5000 permutations producing pseudo-F ratios. Second, I performed nonmetric multidimensional scaling (NMDS) on pairwise Jaccard genetic distance estimates between individual genotypes to visualize the data in two dimensions. Using NMDS, I am also able to estimate the correlation of a series of explanatory variables, including host plant source, sex, and year, with genetic distances among individuals. The ordination was generated using the function METAMDS, also part of the VEGAN package in R, and the magnitudes of variance attributable to the categorical explanatory variables were tested using a goodness of fit statistic based on 5000 permutations of environmental variables on the ordination data using the function ENVFIT in R. Estimation of cross-host plant oviposition and gene flow Individuals collected from one host plant that carry a multilocus genotype that predominates in the other may signal a cross-host plant oviposition in which a female deposits an egg into the host plant from which neither she nor her mate emerged. These individuals provide an estimate of the oviposition infidelity of females for their natal host plant. Hybrids or more advanced backcrosses between host plant-specific genotypes 28 indicate cross-host plant gene flow. Hybrid AFLP genotypes (F1 and backcrosses) were identified using NEWHYBRIDS (Anderson and Thompson 2002; Anderson 2008). The choice of prior had no effect on the overall likelihood of the results, so calculations were run without individual-specific assumptions using ?Jeffreys-like? prior for the mixing proportion and a uniform prior for allele frequency. Simulations were run with a burn-in period of 8 x 104 iterations followed by 1.5 x 106 sweeps for sampling from the posterior distribution. Ancestry was determined based on three thresholds: the category with the highest posterior probability for each individual, or with a threshold of 90% or 75% probability of being a parental form with the rest considered ?introgressed? individuals. Identification of ancestral and novel host plants Because a recent divergence of flies from ancestral to novel host plants may result in reduced genetic diversity in leaf-miner populations on the novel host plant, I compared the diversity of EF-1? haplotypes and AFLP genotypes of flies from the two host plant species to infer which is ancestral and which is novel. For EF-1? sequence data, the number of haplotypes (H), polymorphic sites (p),haplotype diversity (Hd, Nei 1987), and nucleotide diversity (?, Tajima 1983) were estimated using ARLEQUIN (v.3.5 Excoffier et al. 2005). The number of singleton haplotypes (Sn) and nucleotide diversity (?, Tajima 1983) were estimated using and DNASP (v.5.1 Librado and Rozas 2009). For AFLPs, Nei?s genetic diversity (HJ) and the average gene diversity within populations (HS) were calculated using AFLPSURV (v.1.0 Vekemans et al. 2002). The topology of a haplotype network can also provide clues to the relative ages of haplotypes. Haplotypes that represent nodes that are relatively internal versus at the tips of a network and haplotypes that are more abundant and geographically widespread are 29 likely to be older (Donnelly and Tavare 1986; Golding 1987; Crandall and Templeton 1993). To visualize the relationships among EF-1? haplotypes found in flies from each host plant I generated a median-joining network using NETWORK (v.4.5.1.6 Bandelt et al. 1999; Polzin and Daneschmand 2003). The network was rooted using EF-1? sequences from three closely related species: P. ilicis, P. ilicicola, and P. ditmani to further inform my inference of the relative ages of haplotypes from different host plants (Winkler et al. 2009b). Host-associated divergent selection Migration, mutation, drift, and inbreeding are expected to affect all loci in a genome in a similar fashion. In contrast, selection should have locus specific effects: selected sites should show lower genetic diversity and increased genetic differentiation among populations with contrasting environments relative to the rest of the genome (Beaumont and Balding 2004; Egan et al. 2008; Nosil et al. 2009). I used genome scans to identify AFLP loci whose divergence exceeds that expected by genetic drift associated processes alone to infer the action of selection in causing genetic divergence among flies using the two host plants. I used two methods to detect outliers in several geographic locations to gain confidence in my results by rejecting false positives that are identified in single comparisons and with different analyses (Luikart et al. 2003; Stinchcombe and Hoekstra 2008). First, I identified AFLP loci using a hierarchical-Bayesian approach in DFDIST (Beaumont and Balding 2004), and then I directly asked which loci were likely diverged by selection using BAYESCAN (v.1.0 Foll and Gaggiotti 2008). To generate a seed for creation of a null distribution of FST in DFDIST, a trimmed mean FST for each population was estimated that excludes the highest and lowest 30% of locus-specific FST 30 estimates in the AFLP data set (Weir and Cockerham 1984; Zhivotovsky 1999; Bonin et al. 2006). Using this seed, DFDIST creates a distribution of FST for individual loci given assumptions of neutrality and independent evolution of loci (loose linkage). Thresholds identifying exceptionally divergent or constrained allele frequencies found in comparisons of different populations can then be determined using that distribution. Here, loci with an FST in the upper 95% and 99% confidence intervals of the simulated distributions were labeled ?outliers? and are candidates for divergent selection. DFDIST was run using the total data set, then for NC, SC, and eastern Florida populations, as loci repeatedly identified in more than one location are considered especially robust (Campbell and Bernatchez 2004; Bonin et al. 2006; Egan et al. 2008; Nosil et al. 2008; Hohenlohe et al. 2010). Unlike DFDIST, BAYESCAN estimates the posterior probability of a given locus under two models, evolving neutrally or under selection, using a reversible MCMC approach in which FIS is allowed to vary between 0 and 1. BAYESCAN was run starting with a burn-in period of 20 pilot runs, each with a length of 104 iterations. The burn-in was followed by 40 thinning intervals each with 104 iterations for a total of 400 000 iterations. Outliers were identified as loci with posterior probabilities of being under selection at the ?strong? (0.91-0.97), ?very strong? (0.97-0.99), and ?decisive? (>0.99) levels. Genomic architecture of divergent loci Recent studies in flies have found divergent loci located within chromosomal inversions (Noor et al. 2001; Coluzzi et al. 2002; Feder et al. 2003; Brown et al. 2004; Ayala and Coluzzi 2005), which are expected to show differences faster than normally 31 recombining regions. Inversions are common in Phytomyza (Block 1969a, 1974), so I estimated linkage disequilibrium among host-associated divergent loci to determine whether the loci were clustered with one another suggesting close physical linkage. Because my calculations of LD assume the populations are in Hardy-Weinberg equilibrium, LD was estimated separately for flies from each host plant. Separate analyses also prevented confounding loci in LD because of selection or shared history with those in LD because of physical linkage. Estimates of allele frequencies and LD between AFLP markers were performed as described by Hill (1974) using the statistical package R (v2.11.1, 2010; Appendix A; code available upon request). A chi-square test with one degree of freedom was used as an approximation of the likelihood ratio of LD to no LD to infer significance of LD comparisons (Hill 1974). I used a correction for multiple comparisons based on false discovery rates (Pike 2011) for all tests of LD to account for multiple non-independent comparisons. Sex chromosomes are often associated with speciation because they are expected to show differences in FST faster than other parts of the genome (Muller 1942; Charlesworth et al. 1987; Haldane 1992). Agromyzids have been shown to have an XX/XY sex chromosome system (Block 1969a, b, 1974, 1975a, b, 1976), allowing me to compare allele frequencies of male and female flies within hosts to predict whether host- associated outliers may be located on the X- or Y-chromosome. I estimated allele frequencies and variation in these estimates for each host-associated locus for male and female coriacea-flies, and male and female glabra-flies, using the same iterative model used for estimating LD (Hill 1974). In addition, I estimated allele frequencies for each host-associated locus in male coriacea-flies and male glabra-flies using a haploid model. 32 If a host-associated outlier was located on the Y-chromosome, I expected an absence of peaks in female flies and the presence of peaks in male flies at that locus. If a host- associated outlier is located on the X-chromosome, I expected the allele frequency estimates of that locus for female coriacea-flies to be more similar to estimated allele frequencies of male coriacea-flies calculated using a haploid model than those using a diploid model. I used a t-test with one degree of freedom to compare estimates of female allele frequencies to estimates of male allele frequencies using the haploid model and again for the diploid model. RESULTS A total of 656 AFLP markers were scored from 183 flies giving an initial error rate of 5.5% (Table 2.2, Appendix B). An additional 258 markers were removed due to discrepancies across repeated samples. No plate effect was found, however linkage disequilibrium analyses resulted in patterns of linked markers of the same size from different primer pairs, indicating non-specific primer binding occurred in the samples. There was a higher probability of non-specific primer binding in this study due to one primer being used in all primer-pair combinations. Where identified, all but one locus were discarded to eliminate replicated markers, resulting in a total of 305 markers. Finally, using a more conservative cutoff than the typical 5%, any markers where only one individual contained the rarer allele were discarded, giving a final total of 265 markers. The size range of the AFLP markers was 78-792bp, and 92% had a fragment size above 200 bp. The Pearson correlation coefficient between fragment sizes and fragment frequencies was not significant (r = -0.0137, p = 0.82310), indicating a low risk of homoplasy due to small fragment sizes (Vekemans et al. 2002). 33 A total of 308 flies were genotyped for a 910 bp sequence of EF-1?, resulting in 27 SNPs (Table 2.2, Appendix B). Only 279 individuals (145 coriacea-flies and 134 glabra-flies) had 5 or more votes in the consensus analysis of CVHAPLOT, reducing the dataset to 75 distinct genotypes and 43 haplotypes with 22 polymorphic sites (Table 2.3). The translated sequence matched that of EF-1?48D (95% match), and all polymorphic sites were in third codon positions (Figure 2.2). Both coriacea-flies and glabra-flies showed signs of recombination between haplotypes (minimum number of recombination events based on the four allele approach, Hudson and Kaplan 1985; Table 2.4; Fu 1997). Geographic scale of host plant associated genetic divergence The mean allele frequencies did not differ between sample years for AFLPs (F = 1.17435, df = 1, p=0.226, Table 2.5) nor EF-1? (F = 2.2811, df = 1, p=0.168, Table 2.6), therefore data were combined among years. Results from the ADONIS function (Tables 2.5 and 2.6) and analyses using FST were similar, therefore only FST is given here. Significant genetic divergence was found among flies from different host plant species using both AFLPs (FST: 0.1247, p < 0.0005) and EF-1? (?ST: 0.50744, p < 0.001; Table 2.7). Host-associated differences were also significant in all three geographic locations, but varied in magnitude among locations (Table 2.7). Estimates of ?ST using EF-1? increased in a southerly direction (Table 2.7). The opposite was seen in AFLPs: the most southern population in eastern Florida had the lowest FST whereas the northern populations (North and South Carolina) had higher values of FST. There were significant, but smaller, differences in allele frequencies among flies from different locations within the same host plant species for AFLPs (coriacea-flies: FST: 0.0482, p = 0.0182 glabra- 34 flies: FST: 0.0178, p = 0.0146; Table 2.7) and EF-1? (coriacea-flies: ?ST: 0.02844, p = 0.00880; glabra-flies: ?ST: 0.01263, p = 0.09677; Table 2.7). Using the AFLP data, the 183 individuals formed four distinct groups on the first two NMDS axes, corresponding to host plant and sex of the fly (Figures 2.3, 2.4). The Kruskal?s stress for the final ordination was 22.9%. Both host plant and sex were significantly correlated with the ordination of the AFLP data (host plant: R2 = 0.4965, p = 0.0002, Figure 2.3a; sex: R2 = 0.3123, p = 0.0002, Figure 2.3b). Visually, flies from each host plant clearly separated along the first axis, and males and females separated along the second axis (Figure 2.4). The differentiation among the sex of the flies likely represents good coverage of the genome, and is likely driven by distances among individuals associated with sex chromosomes and genes that influence sex formation. Location was also significantly associated with the NMDS ordination, (location: R2 = 0.0804, p = 0.0024), but only if the two locations with only glabra-flies included; if they were removed, location was no longer significant (location: R2 = 0.0272, p = 0.3243). The results from NEWHYBRIDS indicated low rates of gene flow between host plants. Using the majority-rules threshold, none of the flies were identified as F1 hybrids, but 18 individuals were classified as backcrosses with coriacea-flies and one individual as a backcross with glabra-flies (Appendix C). Using the 90% threshold, 36 individuals were identified as introgressed individuals in a primarily coriacea-fly genome, and eight as introgressed individuals in a primarily glabra-fly genome (Appendix C). Using the 75% threshold, those numbers dropped to 21 and 2, respectively. Regardless of the 35 threshold used, the introgression patterns indicate bidirectional gene flow with asymmetric movement of glabra-fly alleles to coriacea-fly genomes. Identification of ancestral and novel host plants The mean genetic variability of EF-1? is lower for coriacea-flies than glabra-flies regardless of the measure used (Table 2.4). Coriacea-flies have less haplotype and nucleotide diversity, and fewer average pairwise differences than glabra-flies. In addition, there were 14 haplotypes and only one singleton found in coriacea-flies, whereas glabra- flies had more than twice as many haplotypes (36) and 13 singletons (Figure 2.5). There were 7 haplotypes shared between the flies on the different host plants. The most common haplotype (h13) was found in 126 of the 135 coriacea-flies but only one glabra- fly (Figure 2.5). Unlike host plant, there were no geographic patterns in the network (Figure 2.6). AFLPs revealed a different pattern. Estimates of genetic diversity were fairly similar among host forms. Coriacea-flies had slightly more polymorphic loci than glabra- flies (Table 2.8), but glabra-flies had slightly higher values for Nei?s genetic diversity and Nei?s HS (Table 2.8). Dividing the AFLPs into outlier and non-outlier loci did not change this result. Glabra-flies had slightly higher genetic diversity than coriacea-flies with both outlier and non-outlier loci (Table 2.8) The majority of the haplotypes found in coriacea-flies are found in a cluster distal to the most similar haplotypes found in glabra-flies. This cluster is distinguished by alternative alleles of a single SNP (snp4; Figure 2.5). The SNP was nearly a fixed difference between host forms, however 2.8% of coriacea-flies are homozygous for the glabra-fly allele, 19.3% of coriacea-flies were heterozygous, and 0.7% of glabra-flies 36 were homozygous for the coriacea-fly allele. No glabra-flies were heterozygous at this position. Host-associated divergent selection Genome scans in DFDIST testing for divergent selection between populations on each host plant in each location indicated 32 loci (12.5%) had FST higher than the 95th percentile of the simulation results in at least one comparison (Table 2.9; Appendix D). Of those, 24 (9.3%) were significant outliers in multiple locations. When all populations were combined, 15 (5.7%) outliers were significant among host plants (Figure 2.7; Tables 2.9, 2.10). All but two (loci 200 and 238) of the 15 loci found in the combined comparison were also significant using BAYESCAN (Table 2.10), and all but locus 238 were significant in multiple independent comparisons. These two loci were the closest outliers to the cutoff in DFDIST, so they had a lower likelihood in general of being outliers (Figure 2.7). The values of ?ST in EF-1 ? were very similar to the FST estimates using only outlier AFLP loci (Table 2.7). Given the high FST, but the lack of non-synonymous changes in the DNA sequence, the data suggest EF-1? is likely near a locus under divergent selection. When EF-1? is added to the AFLP outliers present in multiple independent comparisons, there appear to be 15 loci showing signs of divergent selection among host plants in these flies. When I examined the distribution of peaks among populations of coriacea-flies and glabra-flies, no strong patterns emerged (Table 2.11). Both coriacea-flies and glabra- flies had five fixed or nearly-fixed loci, only one of which was shared between them (locus 118): it had nearly a fixed presence in coriacea-flies and a nearly-fixed absence in 37 glabra-flies (Table 2.11). Where populations were nearly fixed, the individuals with the minority allele were typically found in populations from North and South Carolina, where I collected over two years and had larger sample sizes (Tables 2.2, 2.11). Of the outliers with lower support, locus 200 had a fixed absence in glabra-flies, likely driving its identification as an outlier, but was only at mid-level frequencies in coriacea-flies, reducing its likelihood of experiencing divergent selection (Table 2.11). Locus 238 was at higher frequencies in coriacea-flies than glabra-flies, but the difference was not enough to be identified using smaller sample sizes in location comparisons or using the Bayesian approach. Among samples of coriacea-flies collected from different locations, 13 loci (6.4%) were identified as significant outliers in DFDIST (Tables 2.9, 2.10). None of those markers were outliers in more than one independent comparison and only one was identified in BAYESCAN (locus 144 within coriacea-flies; Table 2.10; Appendix D). Two of the 16 outlier loci were also identified as host-associated outliers (locus 70 and locus 72; Table 2.10). Upon further examination, the outlier status appeared to be driven by coriacea-flies in eastern Florida (Table 2.11, Appendix D). These populations lack a fixed absence in locus 70 and a nearly fixed presence in locus 72 found in in all other populations (Table 2.11). Glabra-flies had fewer location-specific outliers: 10 loci (5.1%) were identified at the 95% level in DFDIST (Tables 2.9, 2.10), none of which were significant in BAYESCAN. Two of the among-location outliers identified in glabra-flies were also outliers in coriacea-flies in DFDIST (locus 167 and locus 226; Table 2.10). Within-host location- associated divergence for locus 167 was driven by genetic differences in eastern Florida 38 for both coriacea-flies and glabra-flies (Table 2.11; Appendix D). Locus 226 was more complicated: differences existed between both northern populations and Florida, and between eastern and western Florida populations within coriacea-flies, but differences in glabra-flies were driven by the population in Delaware (Table 2.11; Appendix D). Genomic architecture of divergent loci Two groups of loci were identified in LD among coriacea-flies (70-72 and 115-118-246) and one pair of loci in LD among glabra-flies (242-255; Figure 2.7). Loci 70 and 72 were also identified as host-associated outliers as well as location- associated outliers within coriacea-flies largely due to genetic differences in the population from eastern Florida (Tables 2.10, 2.11; Appendix D). These differences could potentially explain why these loci appear to be in LD within the coriacea-flies as well. I did not detect LD among the remaining host-associated outlier loci. However, six host-associated outliers were in LD with sex-related outliers. In coriacea-flies, host- associated outliers 94 and 115 were in LD with sex-associated locus 188, and host- associated loci 72 and 213 were in LD with sex-associated locus 113. In addition, host- associated locus 238 was in LD with the 8 sex-associated loci (20, 32, 41, 125, 132, 249, 251, and 261). Glabra-flies only had one host-associated locus (231) in LD with a sex- associated locus (188). My estimates of male and female allele frequencies gave no evidence of among- host outliers on the Y-chromosome. All of but one of these loci either had peaks in multiple females, or if no peaks in females, also had no peaks in the males for that population (Table 2.12). The only locus with no peaks in females and peaks in males was 39 locus 231 in glabra-flies; however coriacea-fly females did have peaks (Table 2.12). There was no significant interaction between host plant and sex of the fly, so I have no reason to expect locus 231 to be on a sex chromosome in one host-associated population but not the other. I also did not see strong evidence of the presence of host-associated outliers on the X-chromosome. For most loci, estimates of allele frequencies using a diploid model for male flies more closely resembled female allele frequencies than estimates using a haploid model (Tables 2.13, 2.14). Three loci had significant differences between female allele frequency estimates and those using the diploid male model, but not with estimates using the haploid male model (loci 72, 213, and 238; Table 2.13). Two of those loci, markers 72 and 213, were closer to the diploid male model in glabra-flies but not coriacea-flies (Table 2.13). Locus 238 had more similar allele frequency estimates between females and haploid males in both coriacea-flies and glabra-flies; however, the haploid model was also close to significantly different in both cases (Table 2.13). To clarify whether 238 could be located on the X-chromosome, I examined allele frequency estimates of the sex-associated outliers with females, a haploid male model, and a diploid male model (Table 2.14). All of the sex-associated outliers in LD with host- associated locus 238 showed a pattern of being on a Y-chromosome, not an X- chromosome, making it unlikely locus 238 is located on a sex chromosome in these flies. DISCUSSION The results of this study show Phytomyza glabricola may be in the process of ecological speciation among its two host plant species, Ilex coriacea and I. glabra. Host- associated genetic divergence is present across the geographic range of P. glabricola, 40 although the magnitude varies among locations and among genetic markers. I found evidence of contemporary gene flow, indicating host forms of the flies are likely not yet different species despite previous evidence of reproductive isolation (Chapter 1). The flies likely expanded from I. glabra to I. coriacea, but enough time has passed to eliminate much of the demographic signature of a host range expansion from the genome of coriacea-flies. Instead, genetic divergence appears to be primarily driven by natural selection, as expected if the flies are in the process of ecological speciation. However, I did not detect physical linkage among AFLP outlier loci, nor did the loci appear to be on sex chromosomes, two features often tied to an increased probability of eventual speciation. Still, I cannot completely eliminate the potential presence of inversions or sex-linkage due to the low resolution of AFLP loci in this study. Geographic scale of host-associated genetic divergence Host-associated genetic structure exists across the range of P. glabricola, supporting the previous identification of coriacea-flies and glabra-flies as host forms (Scheffer and Hawthorne 2007; Funk 2012). Divergence among host plants is much larger than divergence among locations within a given host, meaning coriacea-flies from Florida are more genetically similar to coriacea-flies from Delaware than they are to glabra-flies from Florida. In addition, the degree of genetic divergence among host forms varies among locations. The variation in the degree of host-associated genetic divergence could be due to environmental differences between geographic locations. Higher temperatures and increased daylight hours in the south could increase developmental rates of flies in these locations. Flies on I. glabra experience multiple generations in a year, whereas flies on 41 I. coriacea have only a single generation (Scheffer 2002). The additional generations of flies on I. glabra could give more chances for adaptive traits to arise via recombination and mutation in glabra-flies, and selection could more efficiently eliminate slightly deleterious alleles, especially if alleles allowing coriacea-flies to use I. coriacea are maladaptive on I. glabra, increasing the degree of divergent selection on glabra-flies. If so, plant-driven temporal differences without allochronic isolation could result in increased genetic divergence among host forms. A host range expansion from I. glabra to I. coriacea could have immediately resulted in genetic divergence among populations on each host plant species, without a need for preference of a particular host or differences in performance. Environmental differences could also indirectly impact the populations of flies by changing the relative abundances of their host plants. Ilex glabra tolerates a wider range of temperatures than I. coriacea, and is also more tolerant of dry conditions (Mohlenbrock 1976; Brooks et al. 1993). Locations with less rain fall and cooler temperatures may have a higher relative abundance of I. glabra. Much like the increase in the number of generations, an increased population size of glabra-flies could increase the genetic variation in the population, allowing selection to more efficiently eliminate deleterious alleles. However, the abundance of flies is not necessarily tied to the abundance of the host species. Individual I. coriacea plants tend to have a higher density of leaf-mines than do I. glabra (JBH, S.J. Scheffer pers. obs.), even though a given location typically has more I. glabra, so the two could balance out to even the relative population sizes of host forms of the flies. It is also possible the geographic variation in estimates of FST could be a sampling effect as sample sizes from eastern Florida were 42 smaller than those in North and South Carolina, and too small in the other locations to have any confidence in estimates of FST. Direction of host range expansion There are three probable scenarios to explain how P. glabricola has diverged between I. coriacea and I. glabra. Either I. coriacea is the ancestral host and flies expanded to I. glabra, vice versa, or the ancestral flies were originally on a different plant species that they no longer use, and expanded onto I. coriacea and I. glabra from that third ancestral host. Phytomyza glabricola is not found on host plants other than I. coriacea and I. glabra, and most in the clade are monophagous, therefore a shift from one current host to the other appears more likely than a shift to both from an additional species. The combination of the haplotype network and genetic divergence present in host forms points towards I. glabra as the ancestral host. Haplotypes that are relatively internal in a network are likely to be older than haplotypes at the tips of the network (Donnelly and Tavare 1986; Golding 1987; Crandall and Templeton 1993). Closely related taxa used as outgroups for the network were most closely related to primarily glabra-fly haplotypes (Figure 2.5). In addition, the haplotypes most characteristic of coriacea-flies were found within an offshoot of the main network, analogous to a nested clade within a phylogram. The topology suggests either that a subset of flies from I. glabra colonized the novel host plant, bringing along only a small fraction of the ancestral genetic diversity (Harrison 1991; Brown et al. 1996), or natural selection is reducing the genetic variation of either EF-1?, or a locus closely linked to it, in coriacea-flies but not glabra-flies. 43 Coriacea-flies also had less genetic variation in EF-1? than glabra-flies, but roughly equal genomic variation based on AFLPs. There are two main reasons to expect less genetic diversity in coriacea-flies than glabra-flies: either the flies expanded from I. glabra to I. coriacea and coriacea-flies are not yet in mutation selection balance, or coriacea-flies are adapting to a novel environment. Given the high ?ST among host forms (0.51662, Table 2.7) and the presence of only synonymous substitutions, it appears EF-1? may be closely linked to a locus under divergent selection. In addition, if the lowered variation in EF-1? were due to a founder event following a host range expansion, I would expect the AFLPs to show reduced diversity in coriacea-flies as well, as drift should affect all loci similarly (Cavalli-Sforza 1966; Lewontin and Krakauer 1973; Vitalis et al. 2001). Thus, if the flies expanded from I. glabra to I. coriacea, it was long enough ago that additional genetic variation has arisen throughout the genome of coriacea-flies. The differences in development time on each host could also affect the genetic diversity of EF-1? in each host form. If EF-1? is near a locus under divergent selection, I would expect less genetic diversity in glabra-flies due to the increased effect of selection compounded over multiple generations, which does not match the pattern seen. Instead, it appears that the strength of selection on coriacea-flies is stronger than the increased effect of selection due to multiple generations. However, multiple generations could also allow for increased recombination between EF-1? and the selected locus, potentially increasing diversity in EF-1? in glabra-flies, which I cannot eliminate as a possibility with these data. Identifying the ancestral and novel host plant will allow me to investigate factors that may have driven the initial host range expansion. Enemy-free space is a strong 44 possibility (Denno et al. 1990; Gratton and Welter 1999; Murphy 2004), as populations of P. glabricola experience parasitism rates of 50 to 100% (JBH pers. obs.) with a trend of higher parasitism on I. glabra than I. coriacea. Flies could also have expanded to a new host plant species to escape competition on the ancestral host plant or gain a new resource. However, I find many I. coriacea and I. glabra with no leaf-mines on them, and plants do not seem to be saturated with leaf-mines, suggesting a lack of strong competition. More work is needed to elucidate what selection pressures may differ between the host plants, and how those affect genetic divergence between the fly populations. Asymmetrical gene flow Very low rates of gene flow were found among populations of coriacea-flies and glabra-flies. No fixed differences in either AFLPs or EF-1? were found between host forms of P. glabricola. In addition, none of the individual flies were identified as F1 hybrids; but, a number of individuals were identified as backcrosses, indicating either F1 hybrids are present at a low frequency within these populations, or the putative backcrosses are presenting unsorted ancestral polymorphism. Most of the individuals identified as having introgression predominantly had a coriacea-fly genetic background. The asymmetry of gene flow could have several explanations. Flies on I. glabra are multivoltine whereas flies on I. coriacea are univoltine (Scheffer 2002). If voltinism has at least a partial environmental component linked to the host plant (Chapter 1), F1 and backcrossed flies on I. glabra will have multiple generations in which they will likely mate back to the parental glabra-flies, potentially masking bidirectional gene flow by eliminating easily identifiable glabra-fly backcrosses. The additional generations would 45 also allow selection to more efficiently remove slightly deleterious alleles. If selection in the additional generations results in increased specialization to I. glabra, any preference that evolves could potentially reduce the willingness or ability of glabra-flies to use the alternate host plant, I. coriacea. Future work should sample flies from the second generation on I. glabra to determine whether or not F1 and backcrossed individuals are present and eliminated in future generations, or instead, if gene flow is primarily unidirectional from I. glabra into I. coriacea. On the other hand, asymmetrical gene flow may not be directly influenced by the host plant. Expansion to a novel host plant species is associated with changes in host acceptance, host use, and mate choice (Janz and Nylin 2008). If coriacea-flies are less choosy, they may be more likely to migrate to another host plant and may also be less choosy about mates. Previous work in Drosophila species demonstrated asymmetrical mating between ancestral and founding populations where female choose mates based on specific mating behavior (Kaneshiro 1976; Ohta 1978). Males in the founding population putatively lose parts of the polygenic mating ritual via drift and cannot mate with ancestral females, whereas females from the founding population will mate with ancestral males, and potentially as time goes on, with novel males (Kaneshiro 1980). If the same is true for coriacea-flies, coriacea-females may mate with glabra-males and males of mixed ancestry, but glabra-females may not, resulting in a greater number of backcrosses to coriacea-flies. Host-associated divergent selection Ecological speciation is defined as ecologically-based adaptive divergence. To investigate whether the genetic divergence I found between coriacea-flies and glabra-flies 46 shows signatures of divergent selection, I used genome scans to identify several AFLP loci with a higher FST between host-associated populations than expected due to drift processes alone. All but two of these loci were also identified as outliers in multiple independent population comparisons and/or using multiple methods of identification, lending support to their outlier status. The arrangement of presences and absences within an outlier locus among populations pointed to divergent selection on both hosts rather than directional selection on one host and balancing selection on the other. If the latter was the case, I would have expected more outlier loci with near-fixed and fixed differences in the population experiencing directional selection, but the number of outlier loci with fixed and near- fixed differences was equal among host forms. EF-1? was also likely near a locus under divergent selection. The high estimates of ?ST among host forms were more similar to FST estimates using AFLP outliers than to estimates using non-outlier loci across the geographic range of P. glabricola. If EF-1a is physically linked to a locus under divergent selection, the increased number of generations of glabra-flies could explain why the patterns of divergence seen in EF-1a among locations (increasing FST in a southerly direction) differs from the patterns seen with AFLPs (lower FST in Florida relative to North and South Carolina); AFLPs should represent both selection and demographic effects, whereas EF-1a could just represent the strength of divergent selection. If southern populations of glabra-flies have a greater number of generations than northern populations, the increased effects of selection near EF-1a could lead to the increased host-associated genetic divergence in southern locations. 47 Fewer AFLP outlier loci were found when comparing among locations within host plant than among host plants, and only one locus was found to be significant in multiple independent comparisons within DFDIST, indicating divergent selection is much stronger between host plants than local adaptation (Table 2.10). Most location-associated outliers within both glabra-flies and coriacea-flies were due to differences between populations in eastern Florida and the other populations. These differences could be due to environmental conditions in Florida. For example, winter diapause is terminated by high temperatures in a congeneric, P. chaerophylli (Frey 1991). If the same is true for P. glabricola, flies in southern populations could experience earlier diapause, and in the case of glabra-flies, potentially more generations in southern populations. On the other hand, if differences were due to temperature, I would expect to see similar differences associated with the populations from western Florida in coriacea-flies, but this was not the case. More work is needed to determine what is causing flies from eastern Florida to differ from the other populations. Genomic architecture of divergent loci The genomic architecture of host-associated outliers both reflects the past evolution of genetic divergence and will affect how rapidly genetic divergence will continue to evolve between host forms of P. glabricola, therefore affecting the likelihood of speciation in these lineages. LD will accumulate among markers in genomic regions experiencing reduced recombination, such as within chromosomal inversions (reviewed in Hoffmann and Rieseberg 2008) or in regions containing loci under especially strong selection (Beaumont and Balding 2004; Via and West 2008; Nosil et al. 2009). To examine whether ?genomic islands? exist in P. glabricola, I looked for LD between host- 48 associated outliers in coriacea-flies and glabra-flies separately to make a very coarse inference of the genomic architecture of the divergence. I found little evidence for physical linkage among host-associated outliers in these flies. Host-associated outliers found to be in LD within coriacea-flies were not the same as outliers in LD in glabra-flies. Coriacea-flies and glabra-flies could have different adaptive genes, in addition to different alleles, potentially explaining the loci in LD found with coriacea-flies and not glabra-flies, and vice versa (Hawthorne and Via 2001). The differences could also appear to be in LD due to chance. Estimates of LD using dominant markers require the assumption of Hardy Weinberg Equilibrium (HWE), and the outliers clearly do not meet that assumption (Bonin et al. 2004). In addition, by testing for LD within a given host form, outlier loci close to fixation in that host form would have little or no variation with which to detect linkage disequilibrium. However, if host forms were combined, I could not separate LD due to divergent selection (as expected with the outlier loci) from physical linkage. Host-associated outliers found to have LD in one host form, but not the other, could be due to genomic rearrangements in coriacea-flies relative to glabra-flies. Chromosomal inversions have been associated with speciation (reviewed in Hoffmann and Rieseberg 2008), but I expect host-associated outliers within an inversion should be more likely to show up as in LD in both populations, due to a reduced likelihood of recombination in inversions (Hoffmann and Rieseberg 2008; Feder and Nosil 2009). However, given the course genomic resolution of AFLPs and the lack of a linkage map or a sequenced genome on which to map the host-associated outliers, I cannot say for sure that chromosomal rearrangements cannot be associated with the genomic distribution of 49 outliers in these flies. Although evidence of LD among host-associated outliers would have indicated potential islands of speciation, not finding significant LD does not mean markers are not linked or within an inversion. The degree of coverage by AFLP loci here is not enough to negate the potential presence of physical linkage. Sex chromosomes are also expected to show differences in FST faster than other parts of the genome due to a smaller effective population size as a result of Haldane?s rule (Muller 1942; Haldane 1992; Wu and Davis 1993; Turelli and Orr 1995; Wu et al. 1996) and the large X-effect (Charlesworth et al. 1987; Coyne and Orr 1989; Coyne 1992; Masly and Presgraves 2007), and are consequently often associated with speciation. I did not see convincing evidence of X- or Y-linkage of the host-associated outliers. I cannot say for sure that host-associated outliers in P. glabricola are not located on the sex chromosomes because I do not have a linkage map or sequenced genome on which to map the markers. So-called ?speciation genes? have been associated with sex chromosomes in other systems (Wittbrodt et al. 1989; Barbash et al. 2000; Phadnis and Orr 2009), so further work is needed to determine whether or not it could also be the case in P. glabricola. Conclusions Host forms of Phytomyza glabricola show a geographic mosaic of genetic divergence on their host plants, Ilex coriacea and I. glabra. Patterns of genetic divergence associated with differences in voltinism on each host plant suggest genetic divergence could arise among host-associated populations without the evolution of host preference. Differences in development time also likely manifest themselves in asymmetrical bidirectional gene flow, in this case with primarily glabra-fly alleles 50 introgressing into the coriacea-fly background, giving the appearance of unidirectional gene flow. However, I could not eliminate the possibility of unidirectional gene flow associated with the host range expansion of glabra-flies onto I. coriacea, which may have resulted in less fidelity in host acceptance, host use, and mate choice in coriacea-flies. I detected evidence for divergent selection among host forms of P. glabricola associated with both EF-1? and fifteen AFLP outlier loci. Although I would expect stronger selection on coriacea-flies to adapt to the novel host plant environment, I did not see more fixed alleles in coriacea-flies, potentially because the additional generations of glabra-flies allows selection to more efficiently remove slightly deleterious alleles. Regardless, the detection of divergent selection suggests host forms of P. glabricola are in the midst of ecological speciation. Recent studies of speciation have often identified divergent selection in genomic areas of reduced recombination. I did not find evidence of linkage disequilibrim among outliers, as expected if outliers are within an inversion, nor evidence of outliers on sex chromosomes. I cannot, however, eliminate the possibility of LD or sex-linkage due to the low genomic resolution of AFLP loci in this study. The endemic P. glabricola belongs to an adaptive radiation of leaf-mining flies onto Ilex species. Although not guaranteed, it is reasonable to presume the macroevolutionary patterns seen in Phytomyza are due to similar microevolutionary processes. Because P. glabricola is either currently diverging or recently diverged, it is an appropriate species with which to identify the evolutionary processes responsible for an adaptive radiation. It appears that ecological speciation may be that mechanism. Future work will need to determine how other host races and recently diverged species 51 have evolved within this clade of Phytomyza, which has great potential to become a model system for the evolution of new species. Future work should also focus on what trait(s) are under divergent selection, the genetic basis for these traits, and the resulting phenotypes to fully grasp the evolutionary mechanisms driving divergence in these flies. 52 Table 2.1. AFLP and EF-1? primer sequences. Pst1A was used in combination with each of the EcoRI based primers (EACA-EAGT). Primer Sequence AFLP Pst1A 5 ?- GAC TGC GTA CAT GCA GA - 3? EACA 5? - /56-FAM/GAC TGC GTA CCA ATT CAC A - 3? EACT 5? - /56-FAM/GAC TGC GTA CCA ATT CAC T - 3? EAGA 5? - /56-FAM/GAC TGC GTA CCA ATT CAG A - 3? EAGT 5? - /56-FAM/GAC TGC GTA CCA ATT CAG T - 3? EF-1? EF46F * 5' - GAG GAA ATC AAG AAG GAA G - 3' PEF40F 5' - TCG TCA TTG GAC ACG TAG ATT CAG G - 3' PEF61R 5' - GAT GGT TCC AAC ATG TTA TCA C - 3' PEF64R 5' - CGA CAC ATA AAG GCT TGG ATG GCA CC - 3' PEF65R 5' - GTC TCA TGT CAC GCA CAG CGA AAC GAC - 3' *(Cho et al. 1995) Table 2.2. Summary of samples genotyped from each location and year. Coriacea-flies Glabra-flies Ef1alpha AFLP Ef1alpha AFLP State Site Population S&H1 2006 2007 2006 2007 S&H1 2006 2007 2006 2007 FL Apalachicola National Forest Hunters -2 - 6 - 6 - - 1 - 1 Archibold Biological Station Archibold - - - - - 8 - - - - Etoniah Creek State Forest East V - - - - - - - 2 - 0 Stuck in Sand - - 7 - 5 - - 11 - 9 GA Crooked River State Park Crooked River - - - - - - - 4 - 3 SC Francis Marion National Forest Big Ocean Bay 10 17 5 15 4 - 18 6 17 4 Wambaw Trail - 19 10 12 7 - 21 1 16 2 NC Croatan National Forest Catfish Lake - 22 - 18 - - 5 - 3 - Road 152 - 22 10 20 7 - 25 4 19 2 Carolina Beach State Park Carolina Beach 15 - - - - 7 - - - - VA Great Dismal Swamp National Wildlife Refuge Great Dismal Swamp - - 4 - 2 - - 1 - 1 MD Annapolis Annapolis - - - - - 2 - - - - DE Cape Henlopen State Park Cape Henlopen - - - - - - - 15 - 10 NY Long Island Long Island - - - - - 4 - - - - Subtotal 25 80 42 63 31 21 69 45 55 32 Total 147 96 135 87 1Details on samples can be found in Scheffer and Hawthorne (2007). 2 Samples not collected from locations with ?-?. Table 2.3. Results from CVHAPLOT. Analyzing flies from each host plant separately yielded a better consensus between the programs. CV category H S I II III Overall Individuals (combined data) 127 139 13 9 8 296 Individuals (from I. coriacea) 90 53 2 2 1 148 Individuals (from I. glabra) 37 86 11 7 7 148 Number distinct genotypes 10 56 10 9 8 93 Total distinct haplotypes 10 33 14 16 14 57 Number of category-unique haplotypes* 10 25 8 7 7 57 Frequency (%) of category-unique haplotypes in total sample 83.9 11.5 2.2 1.2 1.2 100 Note: All rows following the separate host plant analyses refer to the combined data from those separate analyses. H: homozygous individuals; S: individuals where all programs fully supported the same haplotype; I ? III: number of dissenting consensus votes received in each category (e.g., I means only one program had a different solution than the others); * Haplotypes newly observed in each category. 55 Table 2.4. Summary statistics for EF-1? sequence data. N H p Sn Hd ? Rm Flies from I. coriacea 145 15 10 1 0.4932 0.047474 4 Flies from I. glabra 134 36 22 13 0.7869 0.104536 5 Total flies 279 43 22 12 0.8008 0.114040 6 N: number of phased samples; H: the number of haplotypes; p: the total number of polymorphic SNPs; Sn: the number of singleton haplotypes; Hd: haplotype diversity; ?: nucleotide diversity; Rm: the minimum number of recombination events. 56 Table 2.5. Analysis of molecular variance estimated using the ADONIS function for AFLP data from Phytomyza glabricola feeding on either Ilex coriacea or I. glabra. Variation was partitioned (a) among individuals on each host plant species nested within each location, sex of the flies, and the collection year for North and South Carolina populations; (b) among individuals on each host nested within each location and sex of the flies; (c & d) among locations and sex of the flies within each host plant species. All non-significant interactions were removed from the analysis. Source d.f. SS MS F - model R2 P (>F) a) b) c) d) Location Sex Year Host nested in Location Residuals Total Location Sex Host nested in Location Residuals Total Coriacea-flies Location Sex Residuals Total Glabra-flies Location Sex Residuals Total 1 2 1 2 139 145 6 2 5 169 182 4 2 89 95 6 2 78 86 0.33913 2.72593 0.16667 4.05319 19.72807 27.01300 2.30711 3.23548 5.00615 23.89756 34.44630 1.20764 2.00981 11.77062 14.98807 1.55257 1.63939 11.64781 14.83977 0.33913 1.36296 0.16667 2.02659 0.14193 0.38452 1.61774 1.00123 0.14141 0.30191 1.00491 0.13225 0.25876 0.81969 0.14933 2.38946 9.60317 1.17435 14.27898 - . 2.71925 11.44043 7.08055 - . 2.28281 7.59829 - . 1.73281 5.48911 - . 0.0126 0.1009 0.0062 0.1500 0.7303 1 0.0670 0.0939 0.1453 0.6938 1 0.0806 0.1341 0.7853 1 0.1046 0.1105 0.7849 1 < 0.001 < 0.001 0.226 < 0.001 - . < 0.001 < 0.001 < 0.001 - . < 0.0005 < 0.0005 - . < 0.0005 < 0.0005 - . 57 Table 2.6. Analysis of molecular variance estimated using the ADONIS function for EF-1? sequences from Phytomyza glabricola feeding on either Ilex coriacea or I.glabra. Variation was partitioned (a) among locations, year, and among individuals on each host plant nested within location for North and South Carolina populations (the only populations sampled in more than one year); (b) among locations and host plants nested within location; (c & d) among locations and sex of the flies within each host plant species. All non-significant interactions were removed from the analysis. Source d.f. SS MS F - model R2 P (>F) a) b) c) d) Location Year Host nested in Location Residuals Total Location Host nested in Location Residuals Total Coriacea-flies Location Residuals Total Glabra-flies Location Residuals Total 1 1 2 215 219 9 5 264 278 4 139 143 9 125 134 -0.000003 0.000002 0.000483 0.000165 0.000647 1.381623 4.823749 3.824143 10.029514 0.000012 0.000060 0.000072 0.18877 0.19076 0.37953 -0.000003 0.000002 0.000242 0.000001 0.153514 0.964750 0.014485 0.000003 0.000000 0.020974 0.001526 - 3.9021 2.2811 314.17 - . 10.597825 66.601577 - . 6.8100 - . 13.744 - . - 0.0046 0.0027 0.7465 0.2554 1 0.1378 0.4810 0.3813 1 0.1639 0.8361 1 0.4974 0.5026 1 1 0.1678 < 0.0005 - . < 0.0005 < 0.0005 - . < 0.05 - . < 0.05 - . Table 2.7: Estimates of FST from AFLPs and EF-1? based on host plant (total samples), host plant within locations, and among locations within coriacea-flies and glabra-flies (separately). Samples from locations with less than five samples on one of the host plants were removed from all but the host plant comparison. AFLPs EF-1? AFLP outliers AFLP non-outliers Comparison FST p-value ?ST p-value FST p-value FST p-value Host plant 0.1247 < 0.0005 0.5166 < 0.0001 0.4946 < 0.0005 0.0571 < 0.0005 NC host plant 0.1270 < 0.0005 0.4950 < 0.0001 0.5045 < 0.0005 0.0632 < 0.0005 SC host plant 0.1390 < 0.0005 0.5599 < 0.0001 0.5179 < 0.0005 0.0764 < 0.0005 East-FL host plant 0.0973 0.0032 0.5892 < 0.0001 0.4154 < 0.0005 0.0553 0.0142 Locations of coriacea-flies 0.0482 0.0182 0.0284 0.0088 0.0883 0.0076 0.0312 0.0014 Locations of glabra-flies 0.0178 0.0146 0.0374 0.0968 0.0527 0.0834 0.0158 0.0322 59 Table 2.8. Summary statistics for AFLPs: a) all loci combined, b) outlier loci only, c) non-outlier loci only. Pop n #loc. #poly. loc. HJ HS a) Flies from I. coriacea 96 265 238 0.1559 0.1723 Flies from I. glabra 87 265 232 0.1594 0.1771 Total 183 265 265 0.1662 0.1577 b) Flies from I. coriacea 96 15 12 0.2429 0.2404 Flies from I. glabra 87 15 14 0.2594 0.2444 Total 183 15 15 0.3430 0.2512 c) Flies from I. coriacea 96 250 226 0.1508 0.1590 Flies from I. glabra 87 250 218 0.1535 0.1646 Total 183 250 250 0.1556 0.1521 n: number of samples; #loc.: number of loci; #poly loci.: number of polymorphic loci; HJ: Nei?s gene diversity; HS: average gene diversity within populations. 60 Table 2.9. Outliers detected using DFDIST from comparisons between all study populations. Dashes indicate the trimmed mean FST was too low a value to run DFDIST. ?Repeated across comparisons indicates? the number of loci with an outlier above 95% in more than one location comparison (number in independent comparisons). Outlier loci: 95% (99%) Geographic Distance (km) No. of polymorphic loci Total % Across hosts CNC vs. GDE 430 187 11 (5) 5.9% (2.7%) CNC vs. GNC 0 198 12 (8) 6.1% (4.0%) CNC vs. GSC 312 214 13 (8) 6.1% (3.7%) CNC vs. GE-FL 722 181 8 (2) 4.4% (1.1%) CSC vs. GDE 752 177 10 (5) 5.6% (2.8%) CSC vs. GNC 312 190 10 (8) 5.3% (4.2%) CSC vs. GSC 0 215 13 (10) 6.0% (4.7%) CSC vs. GE-FL 424 172 9 (3) 5.2% (1.7%) CE-FL vs. GDE 1175 115 3 (0) 2.6% (0%) CE-FL vs. GNC 722 143 5 (0) 3.5% (0%) CE-FL vs. GSC 424 170 14 (3) 8.2% (1.8%) CE-FL vs. GE-FL 0 104 6 (0) 5.8% (0%) CW-FL vs. GDE 1284 125 4 (0) 3.2% (0%) CW-FL vs. GNC 870 198 10 (4) 5.1% (2.0%) CW-FL vs. GSC 558 175 13 (7) 7.4% (4.0%) CW-FL vs. GE-FL 264 115 4 (3) 3.5% (2.6%) Combined na 257 15 (11) 5.7% (4.2%) Repeated across comparisons 23 (14) 8.7% (5.3%) Within I. coriacea CNC vs. CSC 312 190 -- -- CNC vs. CE-FL 722 163 8 (5) 4.9% (3.1%) CNC vs. CW-FL 870 165 7 (2) 4.2% (1.2%) CSC vs. CE-FL 424 154 6 (3) 3.9% (1.9%) CSC vs. CW-FL 558 155 6 (1) 3.9% (0.6%) CE-FL vs. CW-FL 264 78 5 (1) 6.4% (1.3%) Combined na 203 13 (7) 6.4% (3.4%) Repeated across comparisons 11 (0) 5.4% (0.0%) Within I. glabra GDE vs. GNC 430 148 -- -- GDE vs. GSC 752 173 5 (2) 2.9% (1.1%) GDE vs. GE-FL 1175 131 2 (1) 1.5% (0.8%) GNC vs. GSC 312 185 -- -- GNC vs. GE-FL 722 192 3 (1) 1.6% (0.5%) GSC vs. GE-FL 424 174 8(4) 4.6% (2.3%) Combined na 197 10 (4) 5.1% (2.0%) Repeated across comparisons 4 (0) 2.0% (0.0%) 61 Table 2.10. Summary of outlier loci found in host, sex, and geographic comparisons. Posterior probabilities in bold indicate marker found as an outlier in multiple independent population comparisons. Dashes indicate non-significant posterior probabilities (using an alpha of 0.05). Between hosts Within I. coriacea Within I. glabra Between sexes Outlier # (name) DFDIST BAYESCAN DFDIST BAYESCAN DFDIST BAYESCAN DFDIST BAYESCAN 2?(eact.140)? ??? ??? ??? ??? ??? ??? 1? 1? 8?(eact.210)? ??? ??? 1? ??? ??? ??? ??? ??? 13?(eact.254.6)? 0.99975? 1? ??? ??? ??? ??? ??? ??? 20?(eact.333.8)? ??? ??? ??? ??? ??? ??? 1? 1? 22?(eact.349.5)? ??? ??? ??? ??? ??? ??? 0.977256? ??? 28?(eact.392)? ??? ??? ??? ??? 0.990752 ??? ??? ??? 32?(eact.407.4)? ??? ??? ??? ??? ??? ??? 1? 1? 41?(eact.457.7)? ??? ??? ??? ??? ??? ??? 1? 1? 43?(eact.472.2)? ??? ??? ??? ??? ??? ??? 0.979505? ??? 51?(eact.537)? ??? ??? 0.979505 ??? ??? ??? ??? ??? 70?(eaca.208.1)? 1? 1? 0.990502 ??? ??? ??? ??? ??? 72?(eaca.219.3)? 0.99975? 1? 0.99975 ??? ??? ??? ??? ??? 74?(eaca.253.3)? ??? ??? ??? ??? 0.990502 ??? ??? ??? 92?(eaca.371.9)? ??? ??? 1? ??? ??? ??? ??? ??? 94?(eaca.388.4)? 1? 1? ??? ??? ??? ??? ??? ??? 99?(eaca.404.8)? ??? ??? ??? ??? ??? ??? 1? ??? 109?(eaca.469.9)? ??? ??? ??? ??? 0.986? ??? ??? ??? 111?(eaca.489.2)? ??? ??? 0.996751 ??? ??? ??? ??? ??? 113?(eaca.505.8)? ??? ??? ??? ??? ??? ??? 0.9915? ??? 115?(eaca.518.8)? 1? 1? ??? ??? ??? ??? ??? ??? 116?(eaca.522.7)? ??? ??? 0.997751 ??? ??? ??? ??? ??? 118?(eaca.532.1)? 1? 1? ??? ??? ??? ??? ??? ??? 122?(eaca.584.8)? ??? ??? 0.976256 ??? ??? ??? ??? ??? 124?(eaca.592.8)? ??? ??? ??? ??? ??? ??? 0.99925? ??? 125?(eaca.623.9)? ??? ??? ??? ??? ??? ??? 1? 1? 132?(eaca.755.4)? ??? ??? ??? ??? ??? ??? 1? 1? 137?(eagt.148)? ??? ??? ??? ??? ??? ??? 0.99975? 0.997? 144?(eagt.226.3)? ??? ??? ??? 0.952? ??? ??? ??? ??? 148?(eagt.236.3)? ??? ??? 0.984004 ??? ??? ??? ??? ??? 167?(eagt.414.1)? ??? ??? 0.994251 ??? 0.997001 ??? ??? ??? 184?(eagt.552.8)? ??? ??? ??? ??? 0.995001 ??? ??? ??? 188?(eagt.654.5)? ??? ??? ??? ??? ??? ??? 0.991252? ??? 191?(eagt.729.2)? ??? ??? ??? ??? ??? ??? 0.990002? ??? 62 Between hosts Within I. coriacea Within I. glabra Between sexes Outlier # (name) DFDIST BAYESCAN DFDIST BAYESCAN DFDIST BAYESCAN DFDIST BAYESCAN 192?(eagt.737.6)? ??? ??? ??? ??? ??? ??? 1? 1? 193?(eagt.739.9)? ??? ??? ??? ??? 0.993252 ??? 1? 0.978? 199?(eaga.186.1)? ??? ??? ??? ??? ??? ??? 0.993252? ??? 200?(eaga.210.2)? 0.983754? ??? ??? ??? ??? ??? ??? ??? 204?(eaga.249.1)? 0.998? 0.961? ??? ??? ??? ??? ??? ??? 213?(eaga.297.7)? 0.994251? 0.989? ??? ??? ??? ??? ??? ??? 225?(eaga.402.1)? ??? ??? 0.995001 ??? ??? ??? ??? ??? 226?(eaga.411.3)? ??? ??? 0.99925 ??? 0.997251 ??? ??? ??? 227?(eaga.425.2)? 0.99925? 0.992? ??? ??? ??? ??? ??? ??? 229?(eaga.432.4)? ??? ??? ??? ??? 0.9995? ??? ??? ??? 231?(eaga.437.4)? 0.993252? 0.956? ??? ??? ??? ??? ??? ??? 238?(eaga.489.5)? 0.976006? ??? ??? ??? ??? ??? ??? ??? 241?(eaga.498.2)? ??? ??? ??? ??? 0.988503 ??? ??? ??? 242?(eaga.499.4)? 0.999251? 0.982? ??? ??? ??? ??? ??? ??? 245?(eaga.517.6)? ??? ??? 0.994501 ??? ??? ??? ??? ??? 246?(eaga.518.5)? 0.99925? 1? ??? ??? ??? ??? ??? ??? 249?(eaga.542.9)? ??? ??? ??? ??? ??? ??? 1? 1? 250?(eaga.543.9)? ??? ??? ??? ??? ??? ??? 1? 0.999? 251?(eaga.583.9)? ??? ??? ??? ??? ??? ??? 1? 1? 255?(eaga.651.2)? 1? 1? ??? ??? ??? ??? ??? ??? 259?(eaga.672.3)? ??? ??? ??? ??? 0.993252 ??? ??? ??? 260?(eaga.681.6)? ??? ??? ??? ??? ??? ??? 1? ??? 261?(eaga.684.6)? ??? ??? ??? ??? ??? ??? 1? 1? 63 Table 2.11. Distribution of peaks in host-associated outliers. Numbers represent the number of individuals that have a peak at that locus. Locus 13 70 72 94 115 118 200 204 213 227 231 238 242 246 255 Total Coriacea-flies VA 1 0 2 0 2 2 0 0 1 0 1 1 0 2 0 2 NC 39 0 41 7 13 44 23 0 38 0 26 26 1 16 0 45 SC 34 0 36 4 4 38 11 0 30 0 20 26 0 12 0 38 East-FL 4 2 0 0 2 4 0 0 5 0 2 0 1 2 0 5 West-FL 4 0 5 0 2 6 3 0 6 0 0 4 0 2 0 6 Frequency 0.85 0.02 0.88 0.11 0.24 0.98 0.39 0.00 0.83 0.00 0.41 0.59 0.02 0.35 0.00 Glabra-flies DE 3 10 0 10 10 0 0 7 1 2 1 0 7 10 5 10 VA 0 1 0 0 1 0 0 1 0 0 0 0 1 1 1 1 NC 1 20 3 16 24 1 0 11 5 11 1 2 17 24 19 24 SC 2 27 2 36 36 1 0 13 10 23 0 4 18 36 34 39 GA 1 2 0 3 3 0 0 1 2 2 0 2 2 3 1 3 East-FL 1 6 3 8 9 0 0 1 1 4 0 2 2 9 9 9 West-FL 0 1 0 1 1 0 0 0 0 0 0 1 0 1 1 1 Frequency 0.09 0.77 0.09 0.85 0.97 0.02 0.00 0.39 0.22 0.48 0.02 0.13 0.54 0.97 0.80 Frequency: the frequency of peaks within the listed host form (coriacea-flies or glabra- flies). Table 2.12. Estimates of allele frequencies for host-associated outlier loci treating males and females of each host race separately. Male frequencies were estimated treating males as haploids and as diploids to compare to estimates using female loci. If haploid male estimates are more similar to female estimates than diploid male estimates (see Table 2.13), the locus will be treated as putatively on the X-chromosome. If females have no peaks present (all 0 alleles) and males have peaks, the locus is putatively on the Y- chromosome. Coriacea-flies Glabra-flies outliers haploid male female diploid male haploid male female diploid male # Locus Freq. SE Freq. SE Freq. SE Freq. SE Freq. SE Freq. SE 13 eact.254.6 0.8696 0.0025 0.5959 0.0049 0.6388 0.005 0.0952 0.0021 0.0488 0.0011 0.0488 0.0011 70 eaca.208.1 0.0217 0.0005 0.0103 0.0002 0.0109 0.0002 0.9048 0.0021 0.3828 0.0056 0.6914 0.0051 72 eaca.219.3 0.8193 0.0021 0.622 0.0048 0.6703 0.0048 0.0714 0.0016 0.0614 0.0014 0.0364 0.0008 94 eaca.388.4 0.1522 0.0028 0.0417 0.0008 0.0792 0.0016 0.881 0.0025 0.5636 0.0059 0.655 0.0054 115 eaca.518.8 0.3696 0.0051 0.0632 0.0012 0.206 0.0036 1 0 0.7327 0.0047 1 0 118 eaca.532.1 0.9783 0.0005 0.8571 0.0025 0.8526 0.0027 0 0 0.012 0.0003 0 0 200 eaga.210.2 0.413 0.0053 0.1919 0.0032 0.2339 0.0039 0 0 0 0 0 0 204 eaga.249.1 0 0 0 0 0 0 0.3571 0.0055 0.2441 0.0044 0.1982 0.0038 213 eaga.297.7 0.8696 0.0025 0.5482 0.0051 0.6388 0.005 0.1429 0.0029 0.1409 0.0029 0.2763 0.0048 227 eaga.425.2 0 0 0 0 0 0 0.4762 0.0059 0.2763 0.0048 0.2763 0.0048 231 eaga.437.4 0.5 0.0054 0.3149 0.0044 0.2929 0.0045 0.0238 0.0006 0 0 0.012 0.0003 238 eaga.489.5 0.3696 0.0051 0.5482 0.0051 0.206 0.0036 0.0952 0.0021 0.0742 0.0016 0.0488 0.0011 242 eaga.499.4 0.0217 0.0005 0.0103 0.0002 0.0109 0.0002 0.5714 0.0058 0.3274 0.0052 0.3453 0.0054 246 eaga.518.5 0.4348 0.0053 0.1548 0.0027 0.2482 0.0041 1 0 0.7327 0.0047 1 0 255 eaga.651.2 0 0 0 0 0 0 0.7857 0.004 0.5636 0.0059 0.5371 0.0059 Freq.: estimated allele frequency. SE: standard error of allele frequency estimate. Table 2.13. T-tests comparing estimated allele frequencies from Table 2.12. Comparisons were made between haploid male frequencies and female frequencies, then between diploid frequencies and female frequencies. Significantly different comparisons are primarily between haploid male estimated frequencies and female frequencies. The remaining significant differences between diploid male estimates and female estimates are also significantly different for haploid estimates as well, with the exception of locus 238. Coriacea-flies Glabra-flies Outliers haploid male vs. female diploid male vs. female haploid male vs. female diploid male vs. female # locus t s p-value t s p-value t s p-value t s p-value 13 eact.254.6 22.0305 0.0124 0.0007 * 2.9696 0.0144 0.0324 5.3158 0.0087 0.0109 0 0.0072 0.3183 70 eaca.208.1 2.9483 0.0039 0.0328 0.2067 0.0029 0.3053 38.5523 0.0135 0.0002 * 19.3343 0.0160 0.0008 * 72 eaca.219.3 16.4639 0.0120 0.0012 * 3.3958 0.0142 0.0254 1.1832 0.0085 0.1326 3.4542 0.0072 0.0246 94 eaca.388.4 12.5766 0.0088 0.0020 5.2454 0.0071 0.0112 22.4436 0.0141 0.0006 * 5.5723 0.0164 0.0099 115 eaca.518.8 26.3357 0.0116 0.0005 * 14.0876 0.0101 0.0016 * 25.2682 0.0106 0.0005 * 25.2682 0.0106 0.0005 * 118 eaca.532.1 15.4061 0.0079 0.0013 * 0.4296 0.0105 0.2687 4.4900 0.0027 0.0150 4.4900 0.0027 0.0150 200 eaga.210.2 16.4559 0.0134 0.0012 * 3.4283 0.0123 0.0250 0 0 0.3183 0 0 0.3183 204 eaga.249.1 0 0 0.3183 0 0 0.3183 7.3601 0.0154 0.0058 3.2850 0.0140 0.0270 213 eaga.297.7 25.5345 0.0126 0.0005 * 6.2111 0.0146 0.0080 0.1702 0.0118 0.3093 10 0.0135 0.0032 227 eaga.425.2 0 0 0.3183 0 0 0.3183 12.5241 0.0160 0.0020 0 0.0151 0.3183 231 eaga.437.4 12.8595 0.0144 0.0019 1.6061 0.0137 0.0889 6.2969 0.0038 0.0078 4.4900 0.0027 0.0150 238 eaga.489.5 12.1818 0.0147 0.0021 25.3417 0.0135 0.0005 * 2.2374 0.0094 0.0530 3.1679 0.0080 0.0288 242 eaga.499.4 2.9483 0.0039 0.0328 0.2067 0.0029 0.3053 15.0771 0.0162 0.0014 * 1.1267 0.0159 0.1403 246 eaga.518.5 21.4549 0.0131 0.0007 * 7.7771 0.0120 0.0052 25.2682 0.0106 0.0005 * 25.2682 0.0106 0.0005 * 255 eaga.651.2 0 0 0.3183 0 0 0.3183 14.4662 0.0154 0.0015 * 1.5810 0.0168 0.0910 Values in bold font are significantly different at a standard 0.05 level t: the estimated t-value; s: the combined standard deviation. * Significantly different after a Bonferroni correction for multiple comparisons. Table 2.14. Allele frequency estimates of sex-associated outliers treating males and females of each host race separately. Male frequencies were estimated treating males as haploids and as diploids to compare estimates using female loci. If haploid male estimates are more similar to female estimates than diploid male estimates (see Supp. Table 10), the locus will be treated as putatively on the X-chromosome. If females have no peaks present (bolded values of all 0 alleles) and males have peaks, the locus is putatively on the Y-chromosome. Bolded outliers were found to be in linkage disequilibrium with host-associated outlier 238. Table 2.14 Coriacea-flies Glabra-flies outliers haploid male female diploid male haploid male Female diploid male # locus Freq. SE Freq. SE Freq. SE Freq. SE Freq. SE Freq. SE Chromosome 2 eact.140 0.5435 0.0054 0.0206 0.0004 0.3243 0.0048 0.7143 0.0049 0.0364 0.0008 0.4655 0.0059 Y? 20 eact.333.8 0.9348 0.0013 0.0742 0.0014 0.7446 0.0041 1 0 0.0120 0.0003 1 0 Y? 22 eact.349.5 0.0435 0.0009 0.0103 0.0002 0.0220 0.0005 0.2143 0.0040 0 0 0.1136 0.0024 Y? 32 eact.407.4 0.5000 0.0054 0.0311 0.0006 0.2929 0.0045 0.5238 0.0059 0.0120 0.0003 0.3099 0.0051 Y? 41 eact.457.7 0.8043 0.0034 0.0103 0.0002 0.5577 0.0054 0.9286 0.0016 0 0 0.7327 0.0047 Y? 43 eact.472.2 0.7174 0.0044 0.7143 0.0042 0.4684 0.0054 0.9762 0.0006 1 0 0.8457 0.0031 X? 99 eaca.404.8 0.1739 0.0031 0 0 0.0911 0.0018 0.2143 0.0040 0 0 0.1136 0.0024 Y 113 eaca.505.8 0.6304 0.0051 0.7143 0.0042 0.3921 0.0052 0.6667 0.0053 0.5371 0.0059 0.4226 0.0058 X? 124 eaca.592.8 0 0 0.0853 0.0016 0 0 0.0476 0.0011 0.1691 0.0033 0.0241 0.0006 Auto? 125 eaca.623.9 0.9348 0.0013 0 0 0.7446 0.0041 0.9762 0.0006 0 0 0.8457 0.0031 Y 132 eaca.755.4 0.9348 0.0013 0.0103 0.0002 0.7446 0.0041 0.9524 0.0011 0 0 0.7818 0.0041 Y? 137 eagt.148 0.2609 0.0042 0 0 0.1403 0.0026 0.4286 0.0058 0.0120 0.0003 0.2441 0.0044 Y? 188 eagt.654.5 0.9783 0.0005 1 0 0.8526 0.0027 0.8571 0.0029 1 0 0.6220 0.0056 X? 191 eagt.729.2 0.1739 0.0031 0 0 0.0911 0.0018 0.1190 0.0025 0.0120 0.0003 0.0614 0.0014 Y? 192 eagt.737.6 0.7391 0.0042 1 0 0.4892 0.0054 0.7143 0.0049 1 0 0.4655 0.0059 X? 193 eagt.739.9 0.2174 0.0037 0 0 0.1153 0.0022 0.2381 0.0043 0 0 0.1271 0.0026 Y 199 eaga.186.1 0.1739 0.0031 0 0 0.0911 0.0018 0.1429 0.0029 0.0120 0.0003 0.0742 0.0016 Y? 249 eaga.542.9 0.9565 0.0009 0 0 0.7915 0.0036 0.9048 0.0021 0 0 0.6914 0.0051 Y 250 eaga.543.9 0.0217 0.0005 0.4467 0.0050 0.0109 0.0002 0.0238 0.0006 0.0614 0.0014 0.0120 0.0003 Auto? 251 eaga.583.9 0.9130 0.0017 0.0103 0.0002 0.7051 0.0045 0.8095 0.0037 0 0 0.5636 0.0059 Y? 260 eaga.681.6 0.0870 0.0017 0.1548 0.0027 0.0445 0.0009 0.0714 0.0016 0.2929 0.0049 0.0364 0.0008 X? 261 eaga.684.6 0.7391 0.0042 0 0 0.4892 0.0054 0.6429 0.0055 0.0120 0.0003 0.4024 0.0057 Y? 68 Figure 2.1: Endemic range of the host plants, Ilex coriacea and I. glabra with collection sites labeled. Ilex glabra Ilex coriacea & Ilex glabra Cape Henlopen, DE Great Dismal Swamp, VA Croatan, NC Francis Marion, SC Crooked River, GA Etoniah Creek, FL Apalachicola, FL Long Island, NY NJ Annapolis, MD Archibold, FL Carolina Beach, NC F an igure 2.2. A d EF-1?-48 lignment of d from Dro translated E sophila mela F-1? from P nogaster. hytomyza glabricola to EF-1?-100 69 e Figure 2.3: Spider diagrams of environmental factors fitted onto the ordination of AFLP data using non-metric multidimensional scaling. Lines connect each individual within a category to the centroid for that category. a) Host plant species; b) Sex of the fly. -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 -1 -0.8 -0.6 -0.4 -0.2 0.2 0.4 0.6 0.8 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 -1 -0.8 -0.6 -0.4 -0.2 0.2 0.4 0.6 0.8 Centroid Ilex coriacea Ilex glabra NMDS1 N M D S 2 Centroid Female Male N M D S 2 NMDS1 a) b) 71 Figure 2.4. Results of non-metric multidimensional scaling (NMDS) of AFLPs. Yellow represents flies from I. coriacea and blue represent flies collected from Ilex glabra. Squares represent male flies and triangles are female flies. Four samples were genotyped as larvae, therefore their sex is unknown. -0.8 -0.6 -0.4 -0.2 0.2 0.4 0.6 -1 -0.8 -0.6 -0.4 -0.2 0.2 0.4 0.6 0.8NM DS 2 NMDS 1 Unknown sex coriacea-flies Female coriacea-flies Male coriacea-flies Unknown sex glabra-flies Female glabra-flies Male glabra-flies 72 Figure 2.5. Haplotype network of EF-1? in P. glabricola. The size of nodes reflects the relative abundance of each haplotype in the total population. Nodes are colored based upon the frequency of flies from each host plant with that haplotype. Nodes are arranged to show size and connections, therefore connection length does not reflect the number of base pair changes between each haplotype. Each connection represents one base pair difference between nodes. The network is rooted by three closely related species: P. ilicis, P. ditmani, and P. ilicicola. P. ditmani P. ilicicola P. ilicis Collected from I. coriacea Collected from I. glabra SNP4 SNP4 SNP4 73 Figure 2.6: Haplotype network of EF-1? in P. glabricola. The size of nodes reflects the relative abundance of each haplotype in the total population. Nodes are colored based upon the frequency of flies from each location with that haplotype. Nodes are arranged to show size and connections, therefore connection length does not reflect the number of base pair changes between each haplotype. Each connection represents one base pair difference between nodes. The network is rooted by three closely related species: P. ilicis, P. ditmani, and P. ilicicola. P. ditmani P. ilicicola P. ilicis New York New Jersey Delaware Maryland Virginia North Carolina South Carolina Georgia East Florida South FloridaWest Florida 74 Figure 2.7. Results from among host plant comparison in DFDIST. Lines represent the 95% and 99% confidence intervals generated from the trimmed mean FST in DFDIST. Note: Loci connected in yellow were in LD within coriacea-flies. Loci connected in blue were in LD within glabra-flies ?Neutral? 95% 99% 0.00 0.10 0.20 0.30 0.40 0.50 Heterozygosity 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 FST 99% CI 95% CI 118 244 115 72 13 95 211 253 229 240225 202 70 LD in coriacea -flies LD in glabra -flies 94 75 CHAPTER 3: A GEOGRAPHIC MOSAIC OF HYBRIDIZATION BETWEEN ILEX CORIACEA AND I. GLABRA (AQUIFOLIACEAE) AND ITS EFFECTS ON HYBRID MORPHOLOGY ABSTRACT Premise: Interspecific hybridization is common in plants and can cause discordance among phylogenies based on different genes or phenotypes, particularly in taxa with porous genomes such as the genus Ilex. In these taxa, it is important to be able to identify and remove hybrid individuals from phylogenetic studies. I use a pair of sister species to test whether morphological characters can be used to reliably identify parental species and their hybrids. Methods: Leaves were sampled from locations across the sympatric range of I. coriacea and I. glabra. AFLPs were used to genetically identify parental species and their hybrids. Discriminant functions were generated based on morphological characters of leaves to determine whether leaf morphology could reliably recover genetic identities. Key Results: Natural hybrids were found in 3 of the 7 populations sampled, with asymmetric bidirectional gene flow of I. glabra alleles into the I. coriacea genetic background. Discriminant functions based on morphological characters were able to correctly identify all samples, but only if samples were first split into geographic regions, likely reflecting varying rates of hybridization among locations. No single trait could easily differentiate hybrids from parental samples, and each hybrid had a combination of parental, intermediate, and/or transgressive traits. Conclusions: A geographic mosaic of hybridization exists across the range of I. coriacea and I. glabra resulting in a phenotypic mosaic of parental, intermediate, and transgressive 76 traits. The effects of hybridization in Ilex will likely depend on the individuals sampled, the location they are sampled from, and the traits examined. 77 INTRODUCTION Hybridization is a common phenomenon in plants, particularly in outcrossing species with vegetative reproduction (Ellstrand et al. 1996; Rieseberg 1997). Although interspecific hybrids typically constitute less than 0.1% of a given population of hybridizing species, 25% of plant species are known to hybridize with at least one other species (Mallet 2005). Hybrids experience increased genetic variation via new combinations of alleles (Rieseberg and Ellstrand 1993) which can have a variety of outcomes. These combinations are often deleterious, but in some cases they can contribute to adaptability by producing novel phenotypes (Rieseberg and Carney 1998; Rieseberg et al. 1999; Whitham et al. 1999; Rieseberg et al. 2000) and allowing adaptive traits to introgress into a novel genomic background (Morgan et al. 2010). In addition new genetic combinations in hybrids can either decrease or increase differentiation between parental species (Seehausen 2004; Mallet 2005) by either breaking down or reinforcing reproductive barriers (reviewed in Abbott 1992; Rieseberg and Wendel 1993). Hence, hybridization can affect both anagenesis and cladogenesis in plant lineages and given its prevalence across taxa, it likely has been an important influence in plant diversification patterns and processes The effects of hybridization on phylogenetic analysis are likely to be greatest in taxa with porous genomes, i.e., taxa that remain distinct entities despite current gene flow (Lexer et al. 2009). Such taxa are expected to have a ?genetic mosaic? of highly divergent and introgressed genome regions, depending on physical proximity to loci directly or indirectly involved in reproductive isolation (Wu 2001; Smadja et al. 2008; Via and West 2008). Such genetic mosaics should also result in ?phenotypic mosaics? due to 78 interspecific recombination in hybrids and backcrosses (Lexer et al. 2009). These complexities explain why few general patterns have emerged from studies that have examined phenotypes in hybrid plants (reviewed in Rieseberg and Ellstrand 1993). First generation hybrids are no more likely to display morphologically intermediate characters than parental ones, and most hybrids show at least one transgressive (i.e., extreme) phenotype (Rieseberg and Ellstrand 1993; Rieseberg et al. 1999). The variation in both genetic and morphological characters in hybrid samples can be problematic for taxonomic and phylogenetic analysis. Intermediate morphologies can make species characterization difficult, and transgressive phenotypes can lead to long- branch attraction and homoplasy (Kornet and Turner 1999; Vriesendorp and Bakker 2005). Phylogenetic studies can exclude putative hybrids to gain phylogenetic clarity, but to do so, the hybrid individuals must be identified, and most phylogenetic studies do not include more than two or three individuals per species, making identification of hybrids difficult, especially in taxa with porous genomes where hybrids can form between both closely and distantly related taxa (Lexer et al. 2009; Manen et al. 2010). In these systems, more work is needed using multiple specimens of putatively hybridizing species to screen for hybrid individuals and phenotypes and determine whether genetic or morphological data will be more reliable for determining taxonomic relationships. The family Aquifoliaceae (hollies) has emerged as a group with porous genomes. Recent work has revealed high levels of introgression between both closely and distantly related species and a lack of concordance between phylogenies based on different genes or morphological characters (Baas 1978; Cuenoud et al. 2000; Manen et al. 2002; Manen 2004; Selbach-Schnadelbach et al. 2009; Manen et al. 2010). Aquifoliaceae consist of a 79 single extant genus (Powell et al. 2000), Ilex (L.), of approximately 600 species (Loizeau et al. 2005). Taxonomic studies of Ilex noted the overlap in morphological variation among species, suggesting hybridization was likely an important part of evolution in the lineage (Baas 1978). Detailed population level studies of Ilex have identified naturally occurring hybrid individuals (Manen 2004; Lee et al. 2006) and hybrid species (Setoguchi and Watanabe 2000; Joung et al. 2011), indicating hybridization is a common phenomenon in Ilex. To date however, work has focused primarily on documenting the presence of hybrids rather than examining rates of hybridization or characterizing the genetic and morphological traits exhibited. One pair of species, I. coriacea (Pursh) Chapm. and I. glabra (L.) A. Gray are consistently placed as sister taxa (but see Selbach-Schnadelbach et al. 2009) although the placement of this pair relative to other Ilex species varies between plastid and nuclear phylogenies (Manen et al. 2010). These species are evergreen holly shrubs that are native to pine forests on the coastal plain of the eastern United States (Duncan and Duncan 1987; Godfrey 1988). The more cold-tolerant I. glabra grows from Nova Scotia, south to Florida, and along the Gulf of Mexico into eastern Texas whereas I. coriacea has a much smaller range from southern Virginia south to northern Florida and west to Texas (Scheffer 2002; Chapters 1, 2). Throughout the range of I. coriacea, I. glabra is more abundant (Mohlenbrock 1976; Richardson 1983; Brewer 1998; Brockway and Lewis 2003; Clark et al. 2008), but where I. coriacea is found, the two species are sympatric and often syntopic. They are distinguished in the field based on leaf morphology (Gray and Fernald 1950; Lundell 1961; Duncan and Duncan 1987; Godfrey 1988; Lance 2004) but are often mistaken as a single species, particularly in southern populations (Lundell 80 1961). Due to the spatial overlap, the two species have potential to hybridize throughout the overlapping range, and plants with intermediate leaf morphology have been found throughout regions of overlap (Robert K. Godfrey Herbarium 2012, Specimens 000016759-000016766). However the hybrid status of these individuals has not been genetically confirmed. The sympatric distribution, sister species status, and morphological similarities of I. coriacea and I. glabra are particularly suited to test whether morphological characters can be used to reliably identify parental species and their hybrids. For the purposes of this study, I use ?hybrid? to encompassing F1 and backcrossed individuals (i.e., non-parental types). Both I. coriacea and I. glabra are evergreen species and leaves are used to identify and differentiate them year round (Gray and Fernald 1950; Lundell 1961; Duncan and Duncan 1987; Godfrey 1988; Lance 2004). Hence, leaves were collected from multiple populations throughout the range of both species to encompass the full range of genotypic and morphological variation. The objectives of the study were to genetically confirm that I. coriacea and I. glabra naturally hybridize in wild populations and to determine whether hybridization rates vary among locations. In addition, I test whether morphology is a good indicator of hybrid status, especially in phenotypically plastic species. METHODS Collections Plant material for genetic analysis was collected in January and February of 2006 and 2007 from Croatan National Forest, NC and Francis Marion National Forest, SC (Table 3.1). In 2007, additional samples were collected from Cape Henlopen State Park, 81 DE, the Great Dismal Swamp National Wildlife Refuge, VA, Crooked River State Park, GA, Etoniah Creek State Forest, FL, and Apalachicola National Forest, FL (Figure 3.1, Table 3.1). Ilex glabra was found at every collection site, however I. coriacea was not found at two of the sites (DE and GA), the first of which is outside the known geographic range of I. coriacea. Plant material collected in 2007 was also used for morphometric analysis. Collection protocols were developed to represent variation across individuals and locations. Ilex can grow via vegetative reproduction, so the shrubs were selected by moving through a patch and collecting from plants clearly separated by one another by at least a yard between main trunks. The stem closest to the base of the plant with at least five leaves and no new growth was removed from each plant and placed into a plastic bag labeled with site and plant species. After returning to the lab, leaves were removed from the stem and images of both the abaxial and adaxial surfaces of the leaves were recorded using a scanner (Canon CanoScan LiDE 55) at 400 dpi with a ruler included to allow scaling for morphological measurement (Figure 3.2). Immediately after scanning, leaves were placed in labeled envelopes and stored at -80?C. AFLPs Phylogenetic relationships of Ilex species based on nuclear data more closely resemble morphological relationships than do those based on plastid data (Manen et al. 2010); thus I used genomic markers to genetically differentiate each species and their putative hybrids. A total of 202 plants (104 putative I. coriacea and 98 putative I. glabra) were genotyped using AFLPs. For each plant, 35 to 45 mg of leaf material was frozen using liquid nitrogen and ground to a fine powder using a sterilized mortar and pestle. 82 Total genomic DNA was extracted following the plant tissue mini protocol of the Qiagen DNeasy plant kit (Qiagen, Valencia, CA) with a minor adjustment: the lysis step was incubated overnight to increase yield. Following extraction, DNA concentrations were standardized to 12.5 ng/?L. AFLPs were generated using two-step amplification (Vos et al. 1995; Chapter 2). Preamplification and amplification followed procedures in Chapter 2 with only a change in the selective primers used (Table 3.2). PCR products were separated with an ABI 3730 DNA Analyzer (Applied Biosystems, Carlsbad, CA) using MapMarker X-Rhodamine (ROX) labeled 1000bp ladder (BioVentures, Murfreesboro, TN). Electropherograms were scored using GENEMARKER (Soft Genetics, LLC, State College, PA). Fragments between 76 and 949 base pairs were first scored using the automated procedure and secondarily checked by eye. Samples were then examined to determine the fragment size where peak heights became too low to be reliably scored. Final maximum fragment sizes varied from 457 to 720bp across primer pair combinations. AFLPs are known to exhibit problems with repeatability, therefore six individuals were repeated across plates, and ten individuals within each plate to test for repeatability, resulting in 85-136 repeated samples (depending on the optimization needed in each primer-pair combination). In addition, negative controls (H2O template) were run for every step of the process. After scoring, a genotyping error rate was estimated as the ratio of electropherogram peak mismatches among replicated samples to the total number of replicated markers (Pompanon et al. 2005). Using a conservative approach, loci with peaks in the negative controls were removed from the analysis as were loci with peak 83 mismatches among repeated samples. Mismatches are not equally distributed among loci: some loci have only a single individual with a mismatch whereas others show mismatches in a large number of individuals. As a result, the percentage of loci removed due to mismatches is much higher than the overall genotyping error rate. Finally, because a significant negative correlation of fragment frequency and fragment size may be caused by excessive homoplasy, the correlation was estimated using AFLPSURV (Vekemans et al. 2002). Genetic Analysis Local rates of hybridization can differ depending on ecological conditions (Bleeker and Hurka 2001; Williams et al. 2001; Watano et al. 2004; Aldridge and Campbell 2009) so I tested for geographic differences in genetic structure across the range of I. coriacea and I. glabra. Genetic differentiation and diversity were estimated for each species using AFLPs. Nei?s genetic diversity, total gene diversity, Nei?s HS, and Wright?s FST were calculated using AFLPSURV (Vekemans et al. 2002), with 5000 permutations run to test significance for FST. Geographic variation in genetic divergence was addressed using pairwise FST as calculated using AFLPSURV and using an analysis of molecular variance, performed using a permutational MANOVA of Jaccard distances via the ADONIS function from the VEGAN package in R (Oksanen et al. 2010 ). ADONIS models were constructed to test the effects of species and collection site location on the genetic structure of plants from all locations. Models were run with species nested within location to examine whether hybridization rates differed among locations. Significance was based on 5000 permutations producing pseudo-F ratios. 84 To identify rates of hybridization between the Ilex species, I used both a clustering algorithm and an assignment test of the AFLP genotypes. First, I used STRUCTURE (v2.3.3, Pritchard et al. 2000; Falush et al. 2007) to determine the number (K) of genetic groupings the hollies formed. Runs were conducted for K = 1 to 15 to determine whether genetic structure was present among species and sampled locations. I used the population admixture model and independently replicated each run of a given K 10 times with a burn-in of 125 000 iterations followed by 106 iterations of Monte Carlo Markov Chain (MCMC) via grid computing on the Lattice Project at the University of Maryland (Bazinet et al. 2007; Bazinet and Cummings 2008; Myers et al. 2008). To identify the most likely value of K among my samples I used ?K as described in Evanno et al. (2005). The mean of the permutated matrices among replicates was calculated using CLUMPP 1.1.2 (Jakobsson and Rosenberg 2007), then visualized using DISTRUCT 1.1 (Rosenberg 2004). Although the result of STRUCTURE presents a hypothesized mixture of K populations, STRUCTURE does not assign individuals as having parental types or showing introgression associated with either hybridization or backcrossing. Thus, hybrid AFLP genotypes (F1 and backcrosses) were identified using NEWHYBRIDS (Anderson and Thompson 2002; Anderson 2008). Briefly, NEWHYBRIDS uses Bayesian inference to estimate the posterior probability that individuals belong in user-specified categories (e.g., parental, backcross, F1) based on the proportion of loci expected to come from one of two species (Anderson and Thompson 2002), and has been modified to allow inference using dominant markers (Anderson 2008). The choice of prior had no effect on the overall likelihood of the results, so calculations were run without individual-specific 85 assumptions using a ?Jeffreys-like? prior for the mixing proportion and a uniform prior for allele frequency. Simulations were run with a burn-in period of 8 x 104 iterations followed by 1.5 x 106 sweeps for sampling from the posterior distribution. Individuals were classified as parental, F1, backcross, or late backcross depending on the probability of membership in each category. Parental-types were defined as having at least a 90% probability of being a parental form (Vaha and Primmer 2006). Within the hybrids, the category with the highest probability was considered true (F1, backcross to I. coriacea, or backcross to I. glabra). In cases where the individual had the highest probability of being a parental-type, but that probability was less than 90%, the individual was considered a later generation backcross. To determine whether a genetic mosaic of divergence exists for these species, frequencies for the presence of alleles were calculated for each locus for parental-type I. coriacea and separately for I. glabra. The frequencies of each species were visually compared using a scatterplot to determine whether some loci were more divergent than others. Morphometric Analysis To investigate whether vegetative morphological features can reliably differentiate the species and hybrids, I used morphometric analysis to distinguish individuals genotypically classified as I. coriacea, I. glabra, and hybrids. A total of 54 I. coriacea and 62 I. glabra samples were both genotyped and used for morphometric analysis. For each plant, I selected the largest leaf with the least amount of damage with no obvious discernible differences in shape from other leaves from that plant. Once the 86 leaf was chosen, landmarks were placed and stored as x-y coordinates and traditional measurements were made using TPSDIG2 (Rohlf 2005; Figure 3, Tables 3-5). Strictly speaking, landmarks are defined as points at specific anatomical structures and are considered homologous, whereas pseudolandmarks are defined by specifying their position on a structure relative to each other and other landmarks present (Dickinson et al. 1987; Kores et al. 1993), therefore I am using. Pseudolandmarks have been shown to accurately represent shape (Dickinson et al. 1987) and are appropriate for this study because I am not testing for allometric change through time. Landmarks were placed at the base of the petiole, where the blade joined the petiole, and at the apex of the blade (Table 3.3, Figure 3.3). The length between the base and apex of the blade was measured, and landmarks were placed at ?, ?, and ? the length of the blade on the midvein of the leaf. Landmarks were also placed on the edges of the leaf at a 90? angle to the midvein at ?, ?, and ? of the length (Table 3.3, Figure 3.3). Traditional morphological measurements were chosen based on features often used to differentiate these two species (Tables 3.4-3.5). Leaf shape ranges from elliptic to oblong for I. coriacea and obovate to elliptic for I. glabra (Lundell 1961; Godfrey 1988). The apex is described as acute or obtuse for I. coriacea with an acute, sometimes rounded base versus an obtuse apex and acute base in I. glabra (Lundell 1961; Godfrey 1988). In I. coriacea, the leaves are typically spinescent-serrate above the middle often with spinose prickles along the entire margin of the leaf (Gray and Fernald 1950; Duncan and Duncan 1987; Lance 2004). On the other hand, I. glabra leaves are typically crenate or crenate-serrate above the middle of the margin (Gray and Fernald 1950; Duncan and Duncan 1987). In addition, the leaves of I. coriacea tend to be larger than those of 87 I. glabra, and have a greater width relative to the length of the leaf (Lundell 1961; Godfrey 1988; Lance 2004). All of the following analyses were conducted using the statistical package R (v2.11.1, 2010). Individuals were grouped by the resulting classifications from NEWHYBRIDS. Because there were very few individuals identified as hybrids and NEWHYBRIDS has been shown to be more robust at identifying hybrids versus parental individuals than discriminating between hybrid categories (Anderson 2008), all individuals with less than 90% parental membership were pooled as ?hybrids? for the remaining analyses (Vaha and Primmer 2006). For analysis of landmark data, I performed generalized Procrustes analysis (GPA) using the function PROCGPA in the SHAPES package (Dryden 2009). Differences between the mean shapes of I. glabra and I. coriacea, and between parentals and hybrids, were tested using 5000 permutations of the tangent coordinates generated from the GPA?s of each group in the function TESTMEANSHAPES, also in the SHAPES package. The traditional morphological data was used to classify individuals into parental I. coriacea, I. glabra, and their hybrids via a discriminant function analysis (DFA) using the function LDA in the package MASS (Venables and Ripley 2002). Discriminant functions were generated using all of the samples collected, then using subsamples based upon location. Hybrid samples were not present in every location, so nearby locations had to be combined to allow for discrimination among parental species and hybrids. Treating genetic classification as ?truth?, the performance of each of the discriminant functions was assessed using the following measures: 88 1) Efficiency, the power to identify true genotypic status of individuals (sensu Vaha and Primmer 2006; Burgarella et al. 2009): the number of correctly identified individuals for a group divided by the actual number of individuals actually in that group. 2) Accuracy (sensu Yang et al. 2005; Vaha and Primmer 2006; Burgarella et al. 2009): the proportion of individuals correctly assigned to a group divided by the total number of individuals assigned to that group. 3) Type I error: the number of individuals wrongly identified as hybrids over the total number of actual purebreds in a sample. Finally, I examined each morphological trait in individual hybrids to characterize them as parental, intermediate, or transgressive trait states to determine whether a genetic mosaic is indeed tied to a phenotypic mosaic of leaf morphology. Means and standard deviations of each character were calculated for I. coriacea and I. glabra. A t-test for comparing a single observation to the mean was used to determine whether the character state of each hybrid individual fell within the range of I. coriacea, I. glabra, or both parental species(Sokal and Rohlf 1981). Character states significantly outside the range of both species were considered transgressive characters (Cosse et al. 1995). RESULTS Genetic analysis A total of 1034 markers were scored giving an initial error rate of 8.82%. Discarding markers with a single discrepancy between repeated samples resulted in a total of 679 markers. Finally, an initial allele frequency cutoff of 0.5% (corresponding to only a single individual containing the rarer allele) resulted in a significant correlation 89 between fragment size and allele frequency (N = 631, r = 0.0789, p < 0.05). As a result, the frequency cutoff was increased until the correlation was no longer significant (at 3%, N = 427, r = 0.0871, p = 0.07220) to reduce the risk of homoplasy. The size range of the 427 AFLP markers was 76-720 bp and 79% had a fragment size above 200 bp. Overall, there is more genetic diversity in I. glabra than in I. coriacea, with a larger number of polymorphic loci and larger estimates of genetic and gene diversity (Table 3.6). The results of ADONIS (Table 3.7) and analyses using FST yielded similar results, so only FST is given here. Populations of both holly species show small but significant genetic structuring among locations (I. coriacea: FST = 0.0518, p < 0.0005; I. glabra: FST = 0.0290, p < 0.0005; Table 3.6). The degree of divergence between the holly species varied in magnitude among locations with higher values of FST in northern than southern populations (Figure 3.4). Within I. coriacea, pairwise estimates of FST among populations indicated significant differences among all population comparisons except VA with NC, and eastern and western FL (Table 3.8a). Populations of I. glabra were much more similar to one another with significant differences between NC and all but DE, and between VA and western FL (Table 3.8b). When species were combined, the only locations with both host plants that showed significant divergence were eastern FL from NC and SC (Table 3.8c). Using the AFLP data, STRUCTURE clustered the 202 individuals from the seven locations into two distinct groups that corresponded to species identification (Figures 3.5- 3.6). Using a 90% membership cutoff, 97 samples were identified as I. coriacea, 95 as I. glabra, and 10 as hybrids (Appendix E). Only one sample was found to be 90 misidentified, initially identified as being I. glabra but conclusively I. coriacea based on its genotype (Appendix E). The results from NEWHYBRIDS also indicated low rates of gene flow between the holly species. The same 97 individuals were identified as I. coriacea parentals, 95 as I. glabra, and 10 as hybrids (Appendix E). Hybrid individuals were found in NC, SC, and western FL, but not the other four locations. Of the 10 hybrids, 2 were identified as F1, 4 as backcrossed to I. coriacea, 3 as late backcrosses to I. coriacea, and 1 as a late backcross to I. glabra. Although the exact identification of sample status by NEWHYBRIDS may not be correct (Anderson 2008), the combination of population membership resulting from STRUCTURE and the number of individuals identified as backcrosses to I. coriacea give good evidence that gene flow is bidirectional, but asymmetric with primarily I. glabra alleles introgressing into the I. coriacea background. When examining the loci for a genetic mosaic of divergence, the majority of loci were present at relatively high or low frequencies in both species (Figure 3.7). Several loci were absent from one species but present, at varying frequencies, in the others, and roughly 10% were at a high frequency in one location but low in the other, with a difference in frequency of 0.75 or more. A single locus was fixed among species: all I. glabra had a peak whereas all I. coriacea did not. Morphometric Analysis Preliminary analysis suggested I. coriacea and I. glabra could be discriminated based on leaf shape, but hybrids could not. Shapes of leaves based on landmarks were significantly different between parental Ilex species (James T2: 84.35, p < 0.01), but not between parental plants and hybrids (James T2: 561.44, p = 0.387123), the latter likely 91 due to a low number of hybrid plants (7 compared to 109 parental; Figure 3.8).Visual inspection of the mean shapes indicated hybrid leaves were, on the whole, transgressive rather than intermediate relative to the parental species (Figure 3.8d). Discriminant function analyses were run using the full dataset then with combinations of samples that are geographically near one another. Samples from NC, SC, and/or western FL had to be included in each dataset as they were the only locations with individuals identified as hybrids (Appendix E). Because no hybrids were identified in DE or VA, the samples from these locations were combined with those from NC. Pairwise comparisons of FST among I. coriacea populations were significantly different between VA and SC, and NC and SC (Table 3.8a), as were comparisons among I. glabra populations between NC and SC (Table 3.8b), therefore samples from SC were not combined with the DE-VA-NC group. Samples from eastern and western FL were combined due to proximity and genetic similarity (Table 3.8). The GA population was more similar to the population from eastern FL than to SC, so it was combined with the FL populations, resulting in two groups: SC, and GA-FL. The discriminant function based on the total data set did not perform as well as the functions based on the subsets of samples, which had no misclassified samples (Table 3.9, Figure 3.9). In the total combined data, hybrids and I. coriacea were more likely to be incorrectly identified (2 of 48 samples and 2 of 7 samples, respectively) than I. glabra, with only 1 sample misidentified. Similar to the mean shapes based on landmark data, linear discriminant scores of hybrid plants more closely resemble those of I. coriacea than I. glabra (Figure 3.9), potentially explaining why I. glabra was more likely to be correctly identified. 92 Hybrid individuals had character states that ranged from parental to intermediate to transgressive depending on the individual and character in question. No quantitative variables were particularly indicative of hybrid status, and most were intermediate between parental distributions (Table 3.10). Three hybrid individuals showed transgressive characters: one was identified as a backcross to I. coriacea (PHUNC012), one as an F1 (PHUNGE05), and one as somewhere between an F1 and a backcross to I. coriacea (PSOPC005; Appendix E). The three individuals identified as late backcrosses to I. coriacea (P152C288, P152CE02, and PBOBC191) all had a combination of intermediate and I. coriacea-like traits. Interestingly, one of the individuals identified as an F1 was intermediate for all characters (PBOBCE05), but the other had the largest number of transgressive character states (PHUNGE05). Apex shape and leaf margin were the two most discriminatory qualitative characters that appeared representative of species status (Table 3.11). The majority of I. coriacea (37 out of 48 individuals) had complex apices whereas all 61 I. glabra had convex apices. Hybrids were split, 2 with convex apices and 5 with complex. The leaf margin of 40 of the 48 I. coriacea plants had bristles with no crenation whereas 54 of the 61 I. glabra had crenation on the leaf margin lacking bristles (Table 3.11). Hybrids more closely resembled I. coriacea with 6 of the 7 individuals containing bristles but no crenation along their leaf margins. The remaining hybrid, with crenation on the leaf margin, was the F1 individual that also had the majority of the transgressive quantitative traits. 93 DISCUSSION The objectives of this study were to test for hybridization between two species of holly, I. coriacea and I. glabra, examine whether hybridization rates varied among locations, and determine whether or not leaf morphology could be used to differentiate parental species from one another and hybrid plants. I found low rates of hybridization between these two species that varied depending on the location examined. These differences were also reflected in the ability to discriminate between the morphology of leaves of I. coriacea, I. glabra, and their hybrids: discriminant functions based on data divided into geographic regions were better able to correctly identify samples than the function based on the entire dataset. Despite the correct classification, there were no characters that could be used alone to discriminate samples and few patterns emerged regarding the character state of hybrids relative to parental types. Geographic mosaic of hybridization The genetic data match observations of the abundance and distribution of the plant species. Ilex glabra is both more abundant within a given location and has a wider geographic range than I. coriacea, likely generating the higher genetic diversity seen in I. glabra. The differences in genetic structure among the species are likely due to the patchier distribution of I. coriacea, resulting in a higher FST among its populations than among populations of I. glabra. Within a given host species, there was a trend for more northern populations to be similar to one another, but different than southern populations, suggesting different environmental pressures among northern and southern areas of the species? ranges. 94 Genetic data indicated that I. coriacea and I. glabra are naturally hybridizing in native populations. The degree of hybridization varies among geographic locations, with a general trend towards greater gene flow with a decrease in latitude. The genetic data agrees with observational data, where it can be more difficult to identify plants in southern populations (JBH, S. J. Scheffer, personal observation). Work in other systems have also found rates of hybridization can vary depending on ecological conditions such as differences in climate (Williams et al. 2001), pollinators (Chase and Raven 1975), and types of vegetation (Watano et al. 2004). A number of factors could explain the geographic mosaic of hybridization in this system. In southern populations, I. coriacea begins blooming weeks before I. glabra (Godfrey 1988), but the degree of overlap in blooming time for these species is unknown. The plants in this study were sampled over a wide latitudinal range, and flowering times vary by latitude (Duncan and Duncan 1987). If the period of overlap is higher in southern populations than the populations farther north, it could explain the higher levels of gene flow in those locations. In addition, I. glabra is much more abundant in the south, whereas I. coriacea is patchily distributed throughout its range. Even if the degree of overlap in blooming period does not vary among locations, the higher relative abundance of I. glabra in the south could increase interspecific pollination relative to intraspecific pollination in I. coriacea. Both I. coriacea and I. glabra are dioecious and pollinators are required for reproduction (Galle 1997). Abundances of pollinators are known to vary both spatially and temporally among plant populations (Herrera 1988; Schemske and Horvitz 1990; Ashman and Stanton 1991; Eckhart 1992; Cane and Payne 1993; Moeller 2005) due to 95 different geographic ranges of pollinators relative to the plants they pollinate, yearly fluctuations in pollinator population sizes, and variation in the availability of other sources of pollen or nectar in a given location (Thompson 1988; Eckhart 1992; Moeller 2006). Pollinators also vary in their effectiveness at transferring pollen (Primack and Silander 1975; Schemske and Horvitz 1984; Eckhart 1992). Localized adaptation of floral phenotypes in response to varying communities of pollinators could select for floral traits specialized to specialist pollinators (Schemske and Bradshaw 1999; Schluter 2000; Coyne and Orr 2004; Ellis and Johnson 2009), but could also result in increased variation to allow a greater number of generalist species to pollinate flowers. If pollinator communities vary greatly in space and time, interspecific hybridization rates could vary accordingly. Hybrid plants have been shown to be less affected by competition than their parental species (Campbell and Snow 2007; Rose et al. 2009). I observed that surrounding vegetation differed among locations: Southern habitats often consisted of very large populations of I. glabra and Serenoa repens (Bartr.) Small (saw-palmetto) in the understory of long-leaf and slash pine forests. More northern populations had smaller patches of both I. glabra and I. coriacea, and were outside the range of S. repens (McNab and Edwards Jr. 1980). If hybrid plants have better competitive ability against S. repens or other sympatric species relative to the parental species, it could potentially explain why hybridization rates were higher in southern populations. In addition, or in contrast, to environmental conditions, variation in gene flow can be due to evolutionary history or intrinsic genetic incompatibilities. I have no data on the historical distributions of I. coriacea and I. glabra, but it is reasonable to surmise that 96 I. glabra could have been driven south during the Pleistocene (Davis 1981; Delacourt and Delacourt 1984). A longer period of sympatry between I. coriacea and I. glabra in southern populations relative to the more northern distribution would increase the chance that hybridization would occur in the southern part of the distribution. Intrinsic genetic incompatibilities due to chromosomal rearrangements, differences in ploidy levels, or genic incompatibilities, either within or between loci (reviewed in Coyne and Orr 2004) could also cause gene flow to vary. Most Ilex species, including I. glabra are diploid (2N = 40) with a few cases of tetraploidy (Frierson 1959; Galle 1997), but the ploidy level of I. coriacea remains unknown. I saw no difference in the number of peaks seen in the samples of I. coriacea relative to I. glabra, suggesting that I. coriacea is also diploid. Based on phylogenetic studies of the Aquifoliaceae, reproductive barriers are weak in general among Ilex species, and both closely related and distantly related species show signs of hybridization (Manen et al. 2010). Incompatibility can vary with the particular genotypes present in a given location, as well as the species present. Phylogenetic work based on plastids places these species with other North American species whereas nuclear phylogenies place I. coriacea and I. glabra in a different clade, suggesting at least some degree of introgression with other North American species (Manen et al. 2010). Although not tested here, I. ambigua (Michx.) Torr., I. cassine L., I. decidua Walter, I. opaca Aiton, and I. vomitoria Aiton are found within an insect?s cruising range of I. coriacea and I. glabra, and could potentially hybridize with either or both species, further complicating the phylogenetic relationship between Ilex species. 97 Morphological identification Leaf morphology can be used to identify hybrid samples, but there were no easily identifiable characters that could consistently discriminant hybrids from the parental species. Although the discriminant function based on the full dataset performed quite well, five samples were misclassified whereas functions derived from subsets based on geographic proximity and genetic similarity were able to correctly classify all individuals as defined by their genotype. Varying morphology among regions is not surprising given the genetic structure among locations in each species. However, regional differences complicate matters for identifying and removing hybrid individuals from phylogenetic reconstruction. If hybridization commonly varies among locations and the traits used for phylogenetic reconstruction vary accordingly, not only multiple individuals, but multiple individuals from multiple locations will be needed to correctly identify hybrid status. The difficulty identifying hybrids from the full dataset is likely due to the wide variation of morphologies found just among these seven hybrid samples. No characters showed consistent differences between hybrid plants and parental species. Much like patterns seen in the hybrid species Ilex x wahlodensis (Lee et al. 2006; Joung et al. 2011) and hybrids seen between Brahea dulcis and B. nitida (Ramirez-Rodriguez et al. 2011), introgression appeared primarily unidirectional, with the majority of hybrid individuals identified as varying degrees of backcrosses to I. coriacea, and these individuals tended to have a combination of intermediate and I. coriacea-like traits. The most interesting comparison was that of the F1s: one had all intermediate character states, and the other had the majority of transgressive character states as well as intermediate states and ones like one or the other of the parental species. Hybrid F1s are typically expected to have 98 intermediate morphology, whereas F2 individuals are expected to have higher numbers of transgressive traits due to recombination (Whitham 1989; Bangert et al. 2006). I did not test for the F2 category in NewHybrids as it can be tough to differentiate from F1?s particularly when hybridization rates are low, but the morphology suggests that PHUNGE05 may be an F2 individual. If so, it could suggest higher rates of hybridization in western Florida than other locations, particularly given the smaller sample size taken from that location. Patterns of introgression When the traits were combined there was one generality: hybrid individuals tended to look more like I. coriacea than I. glabra, matching the patterns of genetic introgression. Four of the five non-F1 hybrids were identified as being backcrossed to I. coriacea, indicating asymmetrical bidirectional introgression of primarily I. glabra alleles into the I. coriacea background. Similar patterns have been found in cottonwoods, where phytochemical composition and arthropod communities on hybrid trees are most similar to the most genetically similar parental species (Bangert et al. 2006). There are several potential explanations for the asymmetric introgression of alleles from I. glabra into the I. coriacea genetic background. First, the abundance of I. glabra is much larger than I. coriacea, both within a given location and with a larger overall geographic range. Abundance is expected to affect frequency of introgression, where the frequency of alleles from the more abundant species in the genetic background of the less abundant species should be higher than vice versa (Nason et al. 1992; Carney et al. 2000; Burgess et al. 2005). Although F1 individuals are more likely to backcross to the more common species, backcrosses to the less common species will be easier to 99 genetically discern from parental and F1 individuals, resulting in asymmetrical introgression. Because I. glabra is more abundant than I. coriacea, abundance alone could explain the higher number of individuals identified as backcrosses to I. coriacea. In addition to differences in abundance, at least some degree of allochrony exists between I. coriacea and I. glabra (Godfrey 1988). If the temporal divergence is heritable, the blooming period of F1 hybrids could have greater overlap with I. coriacea than I. glabra. Range expansions are also expected to show patterns of unidirectional introgression from the local species into the invading species (Currat et al. 2008; Excoffier et al. 2009). If I. glabra has always had a more northern distribution than I. coriacea, and both species were pushed further south during the Pleistocene, when the species moved back north during post-glaciation, I. coriacea could have moved into the current range, still occupied by I. glabra. Fitness differences can also affect the directionality of introgression. Alleles conferring increased fitness are expected to introgress more often than neutral or deleterious alleles (Barton 2001; Borge et al. 2005; Whitney et al. 2006). Ilex glabra tolerates a wider range of ecological conditions than I. coriacea including soil texture, calcium carbonate, pH, salinity, and temperature (USDA 2012), and is also more tolerant of dry conditions (Mohlenbrock 1976; Brooks et al. 1993). If competition for space and resources is important, introgression of traits allowing greater tolerance of variation in these conditions would be more likely to allow I. coriacea to potentially expand its microhabitat whereas less would be gained by I. glabra, matching the observed pattern in these species. 100 Hybridization not only affects morphological phenotypes, but chemical as well, yielding repercussions that extend to multiple trophic levels (Whitham et al. 1994; Fritz 1999; Fritz et al. 1999; Whitham et al. 1999; Dungey et al. 2000; Hochwender and Fritz 2004; Wimp et al. 2005; Bangert et al. 2006; Bailey et al. 2009; Smith et al. 2011). Genetically more similar plants are more likely to support more similar communities than genetically dissimilar plants (genetic similarity rule, Bangert et al. 2006). Because hybrids have traits of both parental species, they can attract community assemblages from both, resulting in more diverse communities of species (Whitham et al. 1994; Whitham et al. 1999; Dungey et al. 2000; Hochwender and Fritz 2004; Wimp et al. 2005; Bangert et al. 2006; Bailey et al. 2009). In addition, if traits important to interacting organisms such as phytophagous insects are intermediate in hybrids, hybrid individuals can serve as a ?hybrid bridge? allowing the insects to expand their host range (Floate and Whitham 1993). A leaf-mining fly from a highly specialized clade of insects has recently been found to be forming host races on I. coriacea and I. glabra (Scheffer and Hawthorne 2007, Chapters 1-2), suggesting hybrids could have served as a mechanism for the original host shift. More work is needed to determine whether or not this is the case. Conclusions Natural populations of I. coriacea and I. glabra are hybridizing resulting in primarily unidirectional introgression of I. glabra alleles into an I. coriacea background. The morphology of leaves can be used to discriminate parental species and their hybrids and perform best when the samples are divided into regional groupings rather than the entire dataset. The improvement is likely due to genotypic differences, as I identified a geographic mosaic of hybridization in these species. Despite the ability to correctly 101 classify samples using discriminant function analysis, no consistent patterns were found among individual traits in hybrids relative to the parental species; some traits were transgressive, some intermediate, and some similar to parental species, and all three could be found for a single trait or among traits within a single individual. The phenotypic mosaic seen in hybrids makes it difficult to predict how hybrids would affect phylogenetic inference, as it could depend on the individuals sampled, where they are sampled from, and what traits are used. Table 3.1. Summary of collected samples from each population and site. I. coriacea I. glabra 2006 2007 2006 2007 State Site Population Geno1 Geno Both2 Geno Geno Both FL Apalachicola National Forest Sopchoppy 0 5 5 0 1 1 Hunters 0 9 8 0 8 8 Etoniah Creek State Forest East V 0 0 0 0 10 3 Stuck in Sand 0 10 7 0 8 3 GA Crooked River State Park Crooked River 0 0 0 0 10 7 SC Francis Marion National Forest Big Ocean Bay 10 8 6 3 10 4 Wambaw Trail 10 10 9 2 10 6 NC Croatan National Forest Catfish Lake 3 7 3 0 9 8 Road 152 12 11 8 1 9 6 VA Great Dismal Swamp National Wildlife Refuge Great Dismal Swamp 0 9 8 0 9 8 DE Cape Henlopen State Park Cape Henlopen 0 0 0 0 8 8 Total 35 69 54 6 92 62 1Geno: Genotyped; 2Both: In addition to genotyping, leaf samples were morphologically measured and analyzed. 103 Table 3.2. AFLP primer sequences. Primer1 Sequence PAC 5? - GAC TGC GTA CAT GCA GAC - 3? PAG 5? - GAC TGC GTA CAT GCA GAG - 3? PAT 5? - GAC TGC GTA CAT GCA GAT - 3? EACA 5? - /56-FAM/GAC TGC GTA CCA ATT CAC A - 3? EAGA 5? - /56-FAM/GAC TGC GTA CCA ATT CAG A - 3? EACT 5? - /56-FAM/GAC TGC GTA CCA ATT CAC T - 3? EAGT 5? - /56-FAM/GAC TGC GTA CCA ATT CAG T - 3? Note: Four primer pairs were used: EACA-PAG, EAGA-PAT, EACT-PAC, and EAGT- PAC. 1E: EcoRI; P: PstI. Table 3.3. Landmarks of leaf shape for comparisons of Ilex coriacea and I. glabra. Landmark # Description 1 Base of the petiole 2 Where blade joined petiole (base of blade) 3 ? length of blade along the midvein 4 Top edge of leaf at 90? angle to the midvein at point 3 5 Bottom edge of the leaf at 90? angle to the midvein at point 3 6 ? length of blade along midvein 7 Top edge of leaf at 90? angle to midvein at point 6 8 Bottom edge of leaf at 90? angle to midvein at point 6 9 ? length of blade along the midvein 10 Top edge of leaf at 90? angle to midvein at point 9 11 Bottom edge of leaf at 90? angle to midvein at point 9 12 Apex of blade Note: Top and bottom edges are defined with the apex of the blade to the left of the base of the blade. 104 Table 3.4. Qualitative measurements of leaves and character coding for Ilex coriacea and I. glabra. Apex Angle 0 ? Acute 1 ? Obtuse Apex Shape 0 - Cuneate (no significant curvature) 1 - Convex (curves away from midvein) 2 - Complex (more than one inflection point) Base Angle 0 ? Acute 1 ? Obtuse Base Shape 0 - Cuneate (no significant curvature) 1 - Convex (curved away from the midvein) 2 - Concave (curved toward the midvein) 3 - Convex on one side and concave on the other Blade Shape 0 - Elliptic (widest part of blade in middle 1/5 of long axis) 1 - Obovate (widest part of blade in the apical 2/5 of long axis) 2 - Oblong (widest part of blade in middle 1/3 of long axis with opposite margins roughly parallel Extent of Teeth 0 ? No teeth 1 - Apex (apical ? of margin of blade) 2 - Half (along apical ? of margin of blade) 3 - Much (beyond apical ? of margin towards base) Laminar Symmetry 0 ? Symmetrical 1 ? Asymmetrical at base 2 ? Asymmetrical at apex 3 ? Asymmetrical at both apex and base Leaf Margin 0 ? Entire (smooth) 1 ? Crenate lacking bristle 2 ? Crenate with bristle 3 ? Bristle only Table 3.5. Quantitative measurements of leaves from Ilex coriacea and I. glabra. Apex Angle The angle between landmarks 10, 12, and 11 Base Angle The angle between landmarks 3, 2, and 4 Area Area of leaf, including petiole Lower Teeth Number of teeth along lower leaf margin Upper Teeth Number of teeth along upper leaf margin Length of Blade Distance between landmarks 2 and 12 Perimeter Perimeter of leaf including the petiole Width at ? Blade Distance between landmarks 4 and 5 Width at ? Blade Distance between landmarks 7 and 8 Width at ? Blade Distance between landmarks 10 and 11 Note: See Figure 3 and Table 3 for placement of landmarks. 105 Table 3.6. Summary statistics for AFLPs. Pop n #poly. loci HJ HT HS FST Ilex coriacea 105 407 0.16386 0.1840 0.1745 0.0518 I. glabra 97 421 0.17798 0.1940 0.1884 0.0290 Total 202 427 0.20208 0.2518 0.1709 0.3210 Notes: n: number of samples; # poly. loci: number of polymorphic loci; HJ: Nei?s genetic diversity; HT: total gene diversity; Nei?s HS; Wright?s FST. Table 3.7. Analysis of molecular variance estimated using the ADONIS function for AFLP data from Ilex coriacea or I.glabra. Source d.f. SS MS F - model R2 P (>F) a) b) c) Location Species nested in Location Residuals Total Ilex coriacea Location Residuals Total Ilex glabra Location Residuals Total 6 5 190 201 4 100 104 6 90 96 4.00572 13.82695 22.95728 40.78996 1.44967 10.24510 11.69477 1.67066 12.71218 14.38284 0.66762 2.76539 0.12083 0.36242 0.10245 0.27844 0.14125 5.52539 22.88704 . - . 3.53747 . - . 1.97132 . - . 0.0982 0.3390 0.5628 1 0.1240 0.8760 1 0.1162 0.8838 1 < 0.0005 < 0.0005 . - . < 0.0005 . - . < 0.0005 . - . Notes: Variation was partitioned (a) among species nested within each location, then within each species among locations (b, c). Table 3.8. Estimates of pairwise FST. a) VA NC SC East FL West FL VA -- 0.0284 0.0022 * < 0.0001 * < 0.0001 * NC 0.0250 -- < 0.0001 * 0.0008 * 0.0008 * SC 0.0428 0.0365 -- 0.0006 * 0.0004 * East FL 0.0923 0.0610 0.0522 -- 0.0578 West FL 0.0752 0.0614 0.0465 0.0246 -- b) DE VA NC SC GA East FL West FL DE -- 0.0154 0.0062 0.0402 0.0074 0.0052 0.0032 VA 0.0344 -- < 0.0001 * 0.0516 0.0132 0.0056 < 0.0001 * NC 0.0346 0.0569 -- 0.0004 * 0.0006 * < 0.0001 * < 0.0001 * SC 0.0233 0.0144 0.0281 -- 0.1138 0.0070 0.0252 GA 0.0375 0.0125 0.0396 0.0083 -- 0.1214 0.0542 East FL 0.0377 0.0229 0.0523 0.0192 0.0060 -- 0.0594 West FL 0.0528 0.0400 0.0572 0.0227 0.0097 0.0106 -- c) VA NC SC East FL West FL VA -- 0.0214 0.1238 0.0298 0.1138 NC 0.0031 -- 0.0674 0.0014 * 0.0360 SC 0.0079 0.0069 -- 0.0026 * 0.1116 East FL 0.0203 0.0400 0.0324 -- 0.0194 West FL 0.0101 0.0161 0.0071 0.0214 -- Notes: a) Among sampling locations of Ilex coriacea. b) Among sampling locations of I. glabra. c) Among sampling locations with combined I. coriacea and I. glabra. FST is below the diagonal and associated p-values based on resampling are above the diagonal. * Significant at p < 0.5 after Bonferroni correction for multiple comparisons. Table 3.9. Assessment of discriminant functions based on samples separated by regions and for all samples combined. Efficiency Accuracy Type I Error I. coriacea I. glabra hybrids I. coriacea I. glabra hybrids DE, VA, NC 1 1 1 1 1 1 0 SC 1 1 1 1 1 1 0 GA, East FL, West FL 1 1 1 1 1 1 0 All populations 0.958 0.984 0.714 0.958 0.984 0.714 0.018 Notes: See text for definitions of efficiency, accuracy, and type 1 error. Functions based on locational divisions performed better than the function with all samples combined. Hybrids were most often incorrectly assigned, followed by I. coriacea, likely because hybrids more closely resembled I. coriacea than I. glabra. Table 3.10. Measurements of quantitative variables in Ilex coriacea, I. glabra, and their hybrids. Apex angle Base angle Area (mm 2) Left teeth Right teeth Length of blade (mm) Perimeter (mm) Width at ? blade (mm) Width at ? blade (mm) Width at ? blade (mm) Ilex coriacea 73.81 ? 10.08? 64.54 ? 9.83? 912.83 ? 320.61 2.65 ? 1.90 2.58 ? 1.80 53.64 ? 10.66 148.19 ? 28.22 17.06 ? 4.20 24.22 ? 4.85 20.32 ? 4.16 Ilex glabra 70.87 ? 10.48? 58.24 ? 11.04? 498.13 ? 157.77 1.79 ? 0.90 1.80 ? 0.93 41.46 ? 8.11 112.65 ? 20.94 11.51 ? 2.65 16.56 ? 3.52 14.75 ? 3.04 Hybrid Samples P152C288 75.02? 55.77? 802.24 0 ? 1 51.71 142.86 13.59 23.19 19.85 P152CE02 77.70? 65.28? 566.31 3 4 ? 41.95 117.36 13.54 19.84 17.07 PBOBC191 84.67? 77.68? 662.57 0 ? 2 41.23 117.97 16.74 ? 23.31 19.01 PBOBCE05 63.25? 48.81? 499.86 1 3 44.12 125.05 10.25 16.81 14.96 PHUNC012 86.66? 83.72? ? 723.50 4 ? 1 41.93 120.41 19.04 ?? 24.65 ?? 20.11 PHUNGE05 78.12? 77.17? 198.12 * 2 1 23.11 ?** 71.28 ?** 9.50 11.44 ** 9.49 ** PSOPC005 89.58? 85.54? *? 904.29 ? 1 0 46.05 131.30 21.46 ?? 28.29 ?? 23.23 ?? Notes: Means and standard deviations of morphological measurements are listed for each parental species. Hybrid samples are listed individually beneath the parental means. Colored cells represent values with a probability of 90% or less of belonging to a parental distribution based on a t-test to compare a single observation to the mean. Blue represents values outside the distribution of I. coriacea, yellow for values outside the range of I. glabra, and peach for transgressive traits. Symbols indicate significant differences from parental species. I. coriacea: * p < 0.05, ** p < 0.01; I. glabra: ? p < 0.05, ?? p < 0.01. Table 3.11. Character states of qualitative variables in Ilex coriacea, I. glabra, and their hybrids. Apex angle Apex shape Blade shape Base angle Base shape Extent of teeth Laminar symmetry Leaf margin 0 1 0 1 2 0 1 2 0 1 0 1 2 3 0 1 2 3 0 1 2 3 0 1 2 3 Ilex coriacea 45 3 1 10 37 43 4 1 47 1 16 22 6 4 3 14 8 23 14 6 13 15 3 0 5 40 Ilex glabra 59 2 0 61 0 42 14 5 60 1 18 39 1 3 1 42 17 1 20 19 6 16 1 54 6 0 Hybrids 7 0 0 2 5 6 1 0 7 0 4 3 0 0 0 3 3 1 2 2 0 3 0 1 0 6 Notes: Yellow represents individuals with character states that more closely resemble those in I. coriacea than in I. glabra. The reverse is true for boxes highlighted in blue. 110 Figure 3.1: Endemic range Ilex coriacea and I .glabra with collection sites labeled. Ilex glabra Ilex coriacea & Ilex glabra Cape Henlopen, DE Great Dismal Swamp, VA Croatan, NC Francis Marion, SC Crooked River, GA Etoniah Creek, FL Apalachicola, FL F igure 3.2. Sample scan of leaves from I. glabra. 111 112 Figure 3.3. Example of landmarks on an I. coriacea leaf. 1 5 23 4 8 6 710 9 11 12 F ar bu igure 3.4. F e 95% conf t the differe ST between I idence interv nces are no lex coriacea al estimate t statistically and I. glab s for FST. FS significant ra among sa T varies in m . mpling loca agnitude am tions. Error ong locatio 113 bars ns, 114 Figure 3.5. ?K for structure runs using a K of 1 to 15. A K of 2 was most representative of the data De lta K 500 1500 1000 2000 3000 2500 0 K 2 12 141084 6 Figure 3.6. Results of STRUCTURE analysis K=2. Yellow corresponds to Ilex coriacea and blue to I. glabra. Each bar represents a single individual with the portion colored representing the posterior probability of the individual belonging to each cluster. Individuals are ordered by population from north to south (left to right). Cap e H enlo pen , DE Gre at D ism al S wam p, V A 152 - C roat an, NC CAT - C roat an, NC BOB - Fr anci s M ario n, S C WA M - Fra ncis Ma rion , SC Cro oke d R iver , GA EAV - E toni ah C reek , FL SIS - E toni ah C reek , FL HU N - Apa lach icol a, F L SOP - A pala chic ola, FL F co in igure 3.7. C riacea. Var these loci. omparison o iation amon f the freque g loci indica ncy of allel tes a geneti e presence b c mosaic of etween Ilex divergence glabra and among spec 116 I. ies ? F d ro sh igure 3.8. P ) mean shap tation and s ape of hybr a) c) rocrustes ro e of I. coria caling. Yell id leaves ap tations of lan cea, I. glabr ow = I. cori pear rounde dmark data a, and their acea, Blue = r and broade . a) I. coriac hybrids sup I. glabra, G r than those b) d) ea, b) I. gla erimposed u reen = Hyb of I. coriac bra, c) hybr nder the sam rids. The m ea and I. gla 117 ids, e ean bra. 118 Figure 3.9. Plots of first two linear discriminants from discriminant functions based on traditional morphological characters from samples of Ilex coriacea, I. glabra, and hybrids. a-c) Analyses of regional divisions of samples. d) Analysis of all samples combined. Regions were chosen based on geographic proximity, genetic similarity, and presence of hybrids. Individuals are plotted according to their taxonomic classification based on analysis of genetic admixture: yellow represents > 90% I. coriacea, blue represents > 90% I. glabra, and green represents hybrids, all individuals not classified as parental species. The first axis discriminates between parental species and the second axis discriminates the hybrids from parental species. In general, hybrid individuals more closely resemble I. coriacea than I. glabra. 119 Figure 3.9 a) b) c) d) 120 CHAPTER 4: GENE FLOW BEGETS GENE FLOW: TESTING THE HYBRID BRIDGE HYPOTHESIS AND ITS ROLE IN ECOLOGICAL SPECIATION ABSTRACT Interspecific hybridization is common in plants and is known to affect plant resistance to herbivory either positively or negatively depending on the herbivore in question and the phenotype of the hybrids. The relative resistance of hybrids will affect the ability of herbivores to colonize hybrids and move between parental species. When populations of herbivores on different host plant species are genetically differentiated from one another, hybridization between the host plant species could affect how much gene flow occurs between the host forms. Here, I demonstrate that hybrid plants may be serving as ?hybrid bridges? to host forms of a leaf-mining fly, Phytomyza glabricola on its two holly hosts, Ilex coriacea and I. glabra. Hybridization between host plant species and the amount of gene flow between host forms of the fly vary among different locations. As hybridization rates of populations of its host plants increase, so does gene flow between host forms of the insect. Considering the number of plant species that hybridize, it is likely that hybrid bridges and barriers are important for many host form and host race systems. In addition, the presence of hybrid bridges indicates hybrid plants may allow host range expansion in specialized herbivores. Hybrid bridges may be the missing link explaining how adaptive radiations proceed in specialized lineages of herbivorous insects. 121 INTRODUCTION Natural interspecific hybridization, successful matings in nature between two species, occurs in an estimated 25% of plant species (Ellstrand et al. 1996; Arnold 1997; Rieseberg 1997; Mallet 2005). First generation hybrids often share similarities with either parental species depending on the particular combination of alleles passed on from each parent (Lexer et al. 2009), but will also display intermediate and transgressive phenotypes (Rieseberg and Ellstrand 1993; Rieseberg et al. 1999). The resulting genotypic and phenotypic mosaics continues to increase with recombination in advanced generation hybrids (Carney et al. 2000; Travis et al. 2008), particularly between taxa with porous genomes (Lexer et al. 2009). These changes in genotypic and phenotypic diversity not only influence the ecology and evolution of the hybridizing species, but also affect communities of species affiliated with the hybridizing plants (Hochwender and Fritz 2004). A number of studies indicate hybridization can alter plant resistance to herbivorous species, directly and indirectly changing the abundance and community structure of phytophagous species (Whitham et al. 1994; Fritz 1999; Fritz et al. 1999; Whitham et al. 1999; Dungey et al. 2000; Hochwender and Fritz 2004; Wimp et al. 2005; Bangert et al. 2006; Bailey et al. 2009; Smith et al. 2011). Whether hybridization will result in an increase or decrease in species abundance and diversity depends on the particular combination of traits displayed in individual plant hybrids (Bailey et al. 2009). Changes in phenology (e.g., flowering date (Johnson and Agrawal 2005) and budburst (Hunter et al. 1997)), defensive chemistry (e.g., tannins (Bailey et al. 2006), glucosinate (Clauss et al. 2006), and flavonoids (Johnson et al. 2009)), defensive morphology (e.g., 122 trichome density (Clauss et al. 2006; Johnson 2008) and wax (Zalucki et al. 2002)), and nutritive quality (e.g., leaf water content, percent nitrogen (Strong et al. 1984; Huberty and Denno 2006; Johnson 2008)) can all impact the preference, performance, and distribution of beneficial and herbivorous species (Fritz 1999; Fritz et al. 1999; Orians 2000; Carmona et al. 2011). Depending on the fitness of herbivorous species on hybrid plants relative to the parental plant species, hybrids can serve as bridges (Floate and Whitham 1993) or barriers to movement between plant species. If specialized herbivores have moderate fitness on hybrids relative to the natal host plant species, but low fitness on the alternate parental plant species, hybrid plants can serve as ecological and evolutionary bridges allowing the herbivores to gradually adapt to the non-natal species (?hybrid bridge hypothesis?; Floate and Whitham 1993; Whitham et al. 1999). If, on the other hand, herbivores have low to zero fitness on hybrid plants, natural selection should favor avoidance of hybrid plants, potentially resulting in reproductive isolation between populations of herbivores associated with each parental species (Barton 2001). Although plant hybridization has received little attention in regards to the evolution of host-associated differentiation (Dres and Mallet 2002), hybrid bridges and barriers could affect the degree of specialization and genetic divergence among host forms. The role of host plant hybridization in host-associated differentiation, and potentially speciation, has not been tested partially due to a lack of appropriate systems. An effective method requires sympatric host plant species, hybridization between the hosts, and herbivorous species specialized on one or both of the parental plant species. 123 In this study, a native species of leaf-mining fly, Phytomyza glabricola Kulp, and its two native holly hosts, Ilex coriacea (Pursh) Chapman and I. glabra (Linnaeus) Gray were used to study the effects of host plant hybridization on genetic distance in insect host forms, host-associated populations where the kind and degree of host-associated variation have not been fully examined (Funk 2012). Phytomyza (Diptera: Agromyzidae) is a large genus (> 400 species) of flies mainly composed of monophagous leaf-miners (Spencer et al. 1986; Spencer 1990). Phytomyza glabricola belongs to a radiation of 14 closely related species, all of which feed on hollies in the genus Ilex, and most of which are monophagous (Kulp 1968; Scheffer and Wiegmann 2000; Lonsdale and Scheffer 2011). In contrast, P. glabricola feeds on two native species of holly, the ancestral host, I. glabra, and I. coriacea, which are sympatric for much of their range (Scheffer 2002; Chapters 1-3). The adults from each host do not appear to differ morphologically in either external characters or genitalia (Scheffer 2002). The leaf-miners do, however, differ in development time, taking nine months to develop on I. coriacea versus two to four weeks on I. glabra (Kulp 1968; Al-Siyabi and Shetlar 1998; Scheffer 2002). Despite differences in development time among host plant species, adult P. glabricola emerge in synchrony in mid-January to mid-February (Scheffer 2002). The host plants of the leaf-miners, I.coriacea and I. glabra, are members of the family Aquifoliaceae (hollies), that consists of a single extant genus (Powell et al. 2000), Ilex (L.) of approximately 600 species (Loizeau et al. 2005). The two species are evergreen shrubs native to pocosins, hammocks, baygalls, and long-leaf pine forests on the coastal plain of the eastern United States (Duncan and Duncan 1987; Godfrey 1988). The more cold tolerant I. glabra grows from coastal Nova Scotia south to Florida, and 124 along the Gulf of Mexico into eastern Texas (Duncan and Duncan 1987; Figure 1). The range of I. coriacea is completely encompassed within the range of I. glabra, extending from southern Virginia to northern Florida and Texas. Throughout its range, I. coriacea is sympatric and often syntopic with I. glabra (Scheffer 2002; Chapters 1-3), the more abundant of the two species (Mohlenbrock 1976; Richardson 1983; Brewer 1998; Brockway and Lewis 2003; Clark et al. 2008). The two are likely sister species (Manen et al. 2010) and hybridize in the wild (Chapter 3). Although hybridization rates are consistently low, they do vary among locations (Chapter 3). No-choice mating trials have revealed that P. glabricola from the same host plant will mate, oviposit, and develop on either holly species but cross-host mate pairs failed to produce offspring (Chapter 1). The reproductive isolation seen in the mating trials is also expressed as host-plant based genetic structure (Scheffer and Hawthorne 2007), and genome scans of the flies show signs of divergent selection, suggesting they may be in the midst of ecological speciation (Chapter 2). The combination of sympatry throughout the range of I. coriacea, natural variation in rates of hybridization among the Ilex species, and the presence of host forms in P. glabricola allow me to test whether hybrid plants serve as a bridge or barrier for these flies. To examine the relationships between host plant hybridization and gene flow in the insects, I will focus on population-level and individual comparisons of flies and their host plants. I ask how does genetic divergence in host forms of P. glabricola change in relation to the degree of hybridization among I. coriacea and I. glabra? Previous work has demonstrated a geographic mosaic of hybridization and phenotypic divergence among locations of the two Ilex species (Chapter 3) and a geographic mosaic of genetic divergence among host-associated 125 populations of flies (Chapter 2), allowing for population-level comparisons of gene flow between fly populations and gene flow between holly species. In addition, flies were collected as pupae within their leaf-mine allowing for direct genetic comparison of the fly and its host plant. The relationship between genetic divergence in the flies and hybridization in the host plants will depend on the hybrid phenotypes for traits that affect host plant use in the flies. If these traits are intermediate in hybrids, host forms of P. glabricola specialized to each parental species could encounter one another on hybrid plants, potentially increasing gene flow and decreasing genetic divergence between host forms (Floate and Whitham 1993; Gange 1995). If so, I expect a positive relationship between gene flow in the plants and gene flow in the insects (Figure 4.2). On the other hand, if hybrid plants have novel or transgressive traits rendering them unpalatable to the flies, I expect hybrids to serve as ?barriers?, increasing genetic divergence between host forms, resulting in a negative relationship between gene flow in the plants and gene flow in the insects. Finally, there could be no relationship at all between hybridization in host plants and gene flow in insects because of a phenotypic mosaic of important traits, some of which may attract flies from either parental host plant species and some of which may deter flies. METHODS Collections Leaf-mines and leaves were collected in January through March of 2006 from Croatan National Forest, NC and Francis Marion National Forest, SC, and again in 2007 with additional samples from Cape Henlopen State Park, GA, the Great Dismal Swamp National Wildlife Refuge, VA, Crooked River State Park, GA, Etoniah Creek State 126 Forest, FL, and Apalachicola National Forest, FL (Figure 4.1, Table 4.1). Ilex glabra was found at every site, however I. coriacea was not found at two sites (DE and GA), the first of which is outside the known geographic range of I. coriacea. Both years, leaves containing well-developed leaf-mines and visible larvae were removed from host plants and placed into plastic bags labeled with site, date, and putative host plant species. In 2007, in addition to the leaf-mines, the stem closest to the base of the plant with at least five leaves and no new growth was removed from each plant and placed with the collected leaf-mine, if present, or into its own plastic bag labeled with site, date, and putative species if no leaf-mine was present on the plant. Pupae were later dissected from the leaf-mines and placed individually in 0.5 mL Eppendorf tubes and stored in a moist chamber until the emergence of adults, at which point adult flies were placed in 100% ethanol and stored at -80?C. After dissection of mines, leaves were placed in labeled coin envelopes and stored at -80?C. AFLPs A total of 202 plants (97 I. coriacea, 95 I. glabra, and 10 hybrids) and 183 flies (96 from putative I. coriacea, and 87 from putative I. glabra) were genotyped using AFLPs. Methods were as described in Chapters 2 and 3. Briefly, all samples were genotyped using four primer pair combinations (Chapters 2, 3). PCR products were separated with an ABI 3730 DNA Analyzer (Applied Biosystems, Carlsbad, CA) using MapMarker X-Rhodamine (ROX) labeled 1000bp ladder (BioVentures, Murfreesboro, TN). Electropherograms were scored using either GENEMAPPER v.3.7 (Applied Biosystems, Carlsbad) or GENEMARKER (Soft Genetics, LLC, State College, PA) for the flies and plants, respectively. Six individuals were replicated across plates, and ten 127 individuals within plates, to test for repeatability. In addition, negative controls (H2O template) were run for every step of the process. After scoring, loci with peaks in the negative controls were removed from the analysis, as were loci with peak mismatches among repeated samples. Finally, loci with small fragment frequencies were removed to eliminate any negative correlation of fragment frequency and fragment size that may be caused by excessive homoplasy (Vekemans et al. 2002). Analyses The hybrid index was chosen to quantify the degree of hybridization contributing to an individual sample. The hybrid index is an allele-frequency based estimate of the proportion of alleles in an individual that are inherited from one of two parental populations or species (Buerkle 2005). The index ranges from 0 to 1 where, for this study, 0 represents either flies collected from I. coriacea (hereafter ?coriacea-flies?) or samples of I. coriacea and 1 represents either flies collected from I. glabra (hereafter ?glabra-flies?) or samples of I. glabra. Reference samples are needed to estimate hybrid indices, therefore samples were classified as parental if the sample had a 0.99 or greater membership in a parental category as assigned by NEWHYBRIDS (Anderson and Thompson 2002; Anderson 2008; see Chapters 2,3 for details). A total of 30 coriacea- flies and 51 glabra-flies, and 84 I. coriacea and 89 I. glabra were classified as reference samples. Hybrid indices were estimated for each individual using the HINDEX function in the package INTROGRESS (Buerkle 2005; Gompert and Buerkle 2009, 2010) using the statistical package R (R Development Core Team 2010). Although codominant markers are preferred for estimating the hybrid index (Buerkle 2005), dominant markers can be used if enough markers are used with divergent allele frequencies in parental species (van 128 Loo et al. 2008; Bellusci et al. 2010; MacKay et al. 2010; Vereecken et al. 2010; Hrsak et al. 2011; Xu et al. 2011). The resulting hybrid indices were then used in two ways. Direct comparisons were made between the hybrid index of individual flies and plants if both the fly and plant were successfully genotyped. Individual comparisons allowed visual examination of the distribution of coriacea-flies, glabra-flies, and genotypic intermediates on I. coriacea, I. glabra, and their hybrids. The presence of both coriacea-flies and glabra-flies, or of intermediates, on hybrid plants would be an indication hybrid plants are serving as a bridge rather than a barrier to gene flow. If, instead, no flies are found on hybrid plants, plants are likely serving as a barrier to gene flow. Many genotyped samples of plants did not have corresponding genotypes for flies, and vice versa (Table 4.1), therefore hybrid indices were combined to perform population-level comparisons. Rather than using FST, which eliminates much of the information regarding introgression of alleles, mean hybrid index scores were calculated for each population. Previous work with mean hybrid index scores were not corrected for parental identification (Bennuah et al. 2004; Burgess et al. 2005; Zitari et al. 2012), which could result in misleading averages close to 0.5 for populations with roughly equal numbers of samples from each parental species. Therefore, an adjusted hybrid index was created to estimate the amount of introgression present in a given population. Hybrid index estimates above 0.5 were subtracted from 1 to normalize the data (Figure 4.3) resulting in a value of 0 for parental individuals and values between 0 and 0.5 for individuals with mixed ancestry. For populations with a minimum of 5 individuals, the 129 adjusted hybrid indices were averaged across all individuals within a given population to get an estimate of the degree of introgression for that population. A linear regression was used to test whether the mean adjusted hybrid index of fly populations depends on the mean adjusted hybrid index of plant populations. Holly species are much longer lived than the leaf-miners that feed on them, and are more likely to affect gene flow of the flies than vice versa. The flies are not typically present during the blooming periods of their host plants, and are therefore not likely pollinators of the holly species. If hybrid plants are serving as a hybrid bridge, then more flies should be moving between host plants, resulting in a positive relationship between hybridization in plants and gene flow in the flies (Figure 4.2a). If, instead, hybrid plants are serving as a hybrid barrier to gene flow, then greater hybridization in plants should result in lower gene flow among host-associated populations of flies (Figure 4.2b). A non-significant correlation would indicate no relationship between hybridization in the plants and hybridization in the flies (Figure 4.2c). The linear regression was estimated using the function LM using the statistical package R (R Development Core Team 2010). For regressions of a single variable and the response, the function conducts a generalized linear model based on a Gaussian distribution. RESULTS AND DISCUSSION A total of 427 AFLP markers were retained for I. coriacea and I. glabra and a total of 267 markers for coriacea-flies and glabra-flies (Chapters 2, 3). Markers in the plants ranged from 76-720bp in length, with 79% having a fragment size above 200bp. In the flies, markers ranged from 78-792bp in length with 92% of the markers above 200bp. 130 Variation in hybrid indices among populations There was much more variation in the hybrid indices of flies than in the hybrid indices of plants (Figure 4.4, Appendix F, G), which is not surprising given the plants are considered different species, whereas the flies are currently considered host forms (Chapter 2). Previous work revealed reproductive isolation among host forms of P. glabricola (Chapter 1), but genetic data suggests the flies are not yet different species and are likely undergoing ecological speciation (Chapter 2). However, if the flies are different species, there has likely not been enough time for lineage sorting to differentiate neutral loci among the species, reflected here as intermediate hybrid index scores. In both plants and flies, the lowest average adjusted hybrid indices were in Cape Henlopen, as expected as it is outside the range of I. coriacea. In addition, both plant and fly populations had the highest scores in western Florida (Sopchoppy and Hunters populations, respectively), suggesting hybridization is much more prevalent in that area. A number of factors could explain the increased adjusted hybrid index in southern populations. Both I. coriacea and I. glabra are dioecious and pollinators are required for reproduction (Galle 1997). Ilex glabra is much more abundant in the south, whereas I. coriacea is patchily distributed throughout its range, so the higher relative abundance of I. glabra in the south could increase interspecific pollination relative to intraspecific pollination in I. coriacea. In addition, southern populations of I. coriacea begin blooming weeks before I. glabra (Godfrey 1988), but the degree of overlap in blooming time for these species is unknown. If the period of overlap is higher in southern populations than the populations farther north, it could explain the higher levels of gene flow among the plants in those locations. 131 The surrounding environment also differs across the geographic distribution of I. coriacea and I. glabra. Populations of I. coriacea and I. glabra differ in the surrounding plant communities; particularly the presence of Serenoa repens (Bartr.) Small (saw-palmetto) in the south. Pollinator communities may also vary spatially and temporally (Herrera 1988; Schemske and Horvitz 1990; Ashman and Stanton 1991; Eckhart 1992; Cane and Payne 1993; Moeller 2005). Differences in competitive ability among hybrid and parental plants against S. repens or other sympatric species, or variation in pollinator communities could potentially explain why hybridization rates were higher in southern populations. However, these factors are not likely to directly influence the degree of gene flow among host forms of the flies. Variation in gene flow can also be heavily influenced by evolutionary history. Although I have no data on the historical distributions of I. coriacea and I. glabra, it is reasonable to surmise that I. glabra could have been driven south during the Pleistocene (Davis 1981; Delacourt and Delacourt 1984). A longer period of sympatry between I. coriacea and I. glabra in southern populations relative to the more northern distribution would increase the chance that hybridization would occur in the southern part of the distribution, and if the flies have been on the plants for that long of a period, they too may have had more chances for gene flow. The variation in the degree of host-associated genetic divergence is expected to be influenced by environmental differences among locations, but is more likely due to indirect effects mediated by the host plant than direct effects from the outside environment. For example, flies on I. glabra experience multiple generations in a year, whereas flies on I. coriacea have only a single generation (Scheffer 2002), and 132 development time is influenced by the environment (Chapter 1), meaning higher temperatures and increased daylight hours in the south could increase developmental rates of flies in these locations. The additional generations in flies emerging from I. glabra would allow selection to more efficiently eliminate slightly deleterious alleles and increase the probability that any hybrid flies present would backcross to glabra-flies, increasing genetic divergence among host forms of the flies. However, I see decreased genetic divergence in southern populations, suggesting differences in development time are not the driving force underlying differences in genetic divergence. Instead, if hybrid plants are influencing the rate of gene flow among host forms of the insects, such as serving as a hybrid bridge, then the increased hybridization rates in the south could allow host forms of the flies to encounter one another via hybrid plants regardless of the cause of variation in hybridization rates among I. coriacea and I. glabra. Hybrid bridge A significant positive relationship was found between the average adjusted hybrid indices of flies and plants among locations with both host forms (R2 = 0.6717, F1,4 = 8.182, p = 0.04591; Figure 4.5). The averages from CHE were not included in the regression analysis because they are outside the range of I. coriacea, but serve as a control because they should have the lowest hybrid indices (Figure 4.5). Populations of plants with the highest scores (and therefore the highest hybridization rates) had the highest rates of gene flow in the flies, and the same was true for the lowest scores (Figure 4.5), matching the expectation for hybrids serving as bridges for flies among host plant species. The correlation is primarily driven by the Hunters population from western Florida, (without HUN, R2 = 0.1313, F1,3 = 0.4535, p = 0.5489), but I believe that point is 133 valid. Plants from populations in Florida are more difficult to identify than plants in the northern populations (JBH, S. J. Scheffer, personal observation), suggesting higher hybridization rates in the south (Chapter 3). Had I sampled from additional southern populations in Alabama, Louisiana, and Mississippi as well as further out the panhandle of Florida, I would have likely found average hybrid indices at or above the level found in Hunters. It was much harder to find a specific pattern from comparisons of individual flies and their hosts, mainly due to low numbers of hybrid plants (Chapter 3), and even lower numbers that also had corresponding genotyped flies (Table 4.1). Of the two plants identified as hybrids, one was associated with a fly with mixed ancestry, and one was associated with a glabra-fly (Figure 4.4), indicating female glabra-flies will oviposit on hybrid plants, and their offspring can survive to adulthood there. In addition, at least one coriacea-fly X glabra-fly offspring survived to adulthood on a hybrid plant, whereas most hybrid flies are found on I. coriacea. Based on these data, I cannot say whether the individual is the result of a glabra-fly female mating with a coriacea-fly male, but given the glabra-fly that emerged from the other hybrid plant, it is a distinct possibility. Further observations are needed to determine which flies are more likely to move among the different holly species and their hybrids, and which are more likely to oviposit on a non- natal host species. Patterns of introgression When introducing the hybrid bridge hypothesis, Floate and Whitham (1993) made specific predictions regarding the movement of taxa between parental plants and their hybrids: as the degree of hybridization and backcrossing to a parental species increases, 134 the number of intermediate steps between that parental species and hybrids should also increase, increasing the likelihood the insects will move to the hybrid plants. Therefore, if hybridization is asymmetrical between parental host species, insects should move primarily in the same direction as the asymmetry. Asymmetrical introgression was found in the plants, with primarily I. glabra alleles in the I. coriacea genetic background (Chapter 3). There are several potential explanations for this asymmetry. First, the abundance of I. glabra is much larger than I. coriacea, both within a given location and over a larger geographic range. Although F1 individuals are more likely to backcross to the more abundant species, backcrosses to the less abundant species will be easier to genetically discern from parental and F1 individuals, resulting in asymmetrical introgression, with primarily alleles from the more abundant species in the genetic background of the less abundant species (Nason et al. 1992; Carney et al. 2000; Burgess et al. 2005). Because I. glabra is more abundant than I. coriacea, abundance alone could explain the higher number of individuals identified as backcrosses to I. coriacea. Alleles conferring increased fitness are expected to introgress more often than neutral or deleterious alleles (Barton 2001; Borge et al. 2005; Whitney et al. 2006). Ilex glabra tolerates a wider range of ecological conditions than I. coriacea including soil texture, calcium carbonate, pH, salinity, and temperature (USDA 2012), and is also more tolerant of dry conditions (Mohlenbrock 1976; Brooks et al. 1993). If competition for space and resources is important, introgression of traits allowing greater tolerance of variation in these conditions would be more likely to allow I. coriacea to potentially 135 expand its microhabitat whereas less would be gained by I. glabra, matching the observed pattern in these species. Range expansions are also expected to show patterns of unidirectional introgression from the local species into the invading species (Currat et al. 2008; Excoffier et al. 2009). If I. glabra has always had a more northern distribution than I. coriacea, and both species were pushed further south during the Pleistocene, when the species moved back north during post-glaciation, I. coriacea could have moved into the current range, still occupied by I. glabra. As predicted by Floate and Whitham (1993), the flies show the same pattern of asymmetrical introgression consisting of primarily glabra-fly alleles in the coriacea-fly genetic background (Chapter 2). Not surprisingly, the morphology of the leaves in I. coriacea x I. glabra hybrids more closely resemble those of I. coriacea than I. glabra (Chapter 3), indicating traits important to host use by the flies could likely show the same pattern. However, the same pattern of asymmetry could also be coincidence. Flies on I. glabra are multivoltine whereas flies on I. coriacea are univoltine (Scheffer 2002). If voltinism has at least a partial environmental component linked to the host plant (Chapter 1), F1 and backcrossed flies on I. glabra will have multiple generations in which they will likely mate back to the parental glabra-flies, potentially masking bidirectional gene flow by eliminating easily identifiable glabra-fly backcrosses. The development time of flies on hybrid plants remains unknown, so I cannot predict how it may differ from that on I. coriacea or I. glabra, if at all. Work is needed to determine the cause of delayed development of P. glabricola on I. coriacea, and how it may change in hybrid plants. 136 Previous work suggests I. glabra was the ancestral host for P. glabricola, and the flies expanded onto I. coriacea (Chapter 2). If a hybrid bridge was responsible for the initial host range expansion and backcrossing increases the number of intermediate steps between parental taxa, current patterns of introgression indicate the initial move from I. glabra to an intermediate likely required more change than from the intermediate to I. coriacea but less of a shift than directly from I. glabra to I. coriacea (Floate and Whitham 1993). This suggests either the initial hybrid host plants (presumably F1) were phenotypically similar to I. glabra in traits that mattered to the flies or that gene flow among I. coriacea and I. glabra has changed since the initial expansion. Hybrids between I. coriacea and I. glabra contain a phenotypic mosaic of parental, intermediate, and transgressive traits (Chapter 3), suggesting multiple hybrid plants could have been colonized by glabra-flies on an evolutionary time scale. In addition, the relative abundance of the two host plant species has likely changed over time, and if abundance is responsible for asymmetrical introgression, introgression may have been more equally bidirectional in the past. Either way, it appears possible that hybrid plants may have allowed the initial host range expansion of flies in this highly specialized lineage. Potential mechanisms Many factors could be affecting the performance of P. glabricola on the hollies and their hybrids. Phytophagous insects are known to respond to the genetic composition of plants via their defensive chemistry (i.e. secondary metabolites; Bangert et al. 2006). Many holly species contain ursolic acid, phenylpropanoids, and arbutin (Choi et al. 2005), all of which have been associated with plant defense (Martin 1964; Levin 1971; 137 Korkina 2007); however I. coriacea and I. glabra have not yet been examined for the presence of these compounds. A recent meta-analysis revealed physical plant traits, rather than chemical ones, have the strongest negative correlation with endophytes, followed by phenological traits and physiological traits such as water content and nitrogen concentration (Carmona et al. 2011). As apparent by their names, I. coriacea and I. glabra are both coriaceous, containing thick, leathery, and highly cutinized leaves (Caughey 1945), and glabrous, without surface ornamentation such as bristles or hairs. The waxy leaves have no effect on transpiration rates (Caughey 1945), but could potentially serve as protection against oviposition from leaf-miners (Zalucki et al. 2002). Phenologically, I. coriacea blooms weeks before I. glabra for at least part of their overlapping range (Godfrey 1988), so the plants could also differ in the timing of new growth. Physiologically, I. glabra is considered less nutritious than other plants found in pocosin habitats (Smith et al. 1956), and its growth is deterred by competing plant species (Hagan et al. 2009, 2010). If nutrition content of hybrid plants differs from parental plants, it could affect host choice and survival of the flies. Plants can also indirectly control herbivory by attracting predators and parasitoids. Parasitoids are likely the highest source of mortality in these flies, with rates varying from 50-100% parasitism among locations (JBH unpublished). Reduced parasitism rates on hybrid plants could allow greater survival, increasing the likelihood coriacea-flies and glabra-flies will survive and encounter one another on the hybrid plants (Fritz et al. 1999). Estimates of parasitism rates on the hybrid plants in this study (60%) appear to be intermediate between rates on I. glabra (64%) and those on I. coriacea 138 (52%). To fully understand how hybrid plants are serving as hybrid bridges, more work needs to be conducted to examine the nature of host plant selection by P. glabricola, and the specific plant traits that affect larval performance on these species and these hybrids. I must point out that not all hybrid plants had leaf-mines (Table 4.4). I have not yet been able to determine whether flies avoid ovipositing on these plants, larvae are unable to survive, or plants drop the leaves with mines. Nonetheless, it indicates that some individual hybrid plants could serve as barriers rather than bridges. Hybrid plants likely represent a phenotypic mosaic of traits (Lexer et al. 2009; Chapter 3), where different combinations of novel, intermediate, and parental traits can be found among hybrid individuals. The particular combination of traits will be controlled by the particular combination of alleles from parental species combined with genetic recombination in backcrosses (Whitham 1989; Fritz 1999; Dungey et al. 2000). The effects of these combinations on herbivores will depend on the particular trait of interest and the composition of hybrids in that location. Having evidence for both hybrid bridges and hybrid barriers is not a paradox, but is just representative of the natural variation present in host plant populations. The evolutionary and ecological influence of hybrid bridges and barriers will likely vary among populations. If some populations have high numbers of hybrids that serve as barriers, herbivores will likely be more adapted to parental species in those populations, and may have increased preference for parental plants to avoid the hybrid barriers (Barton 2001). On the other hand, populations with high numbers of hybrids that serve as bridges will tend have less specialized herbivores and potentially less stringent preferences. The combination of bridges and barriers among locations will likely result in 139 a geographic mosaic of genetic divergence among associated herbivore populations (Thompson 2005; Edelaar and Benkman 2006; Barbour et al. 2009; Thompson 2009; Marsden et al. 2011; Barman et al. 2012). Conclusions Variation in average adjusted hybrid indices among locations indicates a geographic mosaic of hybridization between I. coriacea and I. glabra, and a geographic mosaic of genetic divergence among host forms of P. glabricola. Southern populations of both host plants and the flies had higher average adjusted hybrid indices than northern populations, likely reflecting environmental variation such as differences in relative abundance of I. glabra among locations, which then cascaded through the plants to affect the flies. The positive correlation between host plant hybridization and gene flow between host forms of P. glabricola suggest hybrid plants serve as a bridge for the flies between parental host plant species. Hybrid plants could be responsible for the initial host range expansion from I. glabra to I. coriacea in these flies. Since the initial expansion, differences in development time on each host have resulted in host plant-mediated genetic divergence among populations on each host. Subsequent adaptation to each host is driving ecological speciation among the host forms of the flies. However, the host forms are not yet new species, potentially due to gene flow promoted by hybrid bridges. Much work on plant-insect coevolution has focused on host-range expansions followed by genetic divergence among lineages due to specialization and reproductive isolation on each host (Weintraub et al. 1995; Hawthorne and Via 2001; Ronquist and Liljeblad 2001; Nosil 2002; Janz et al. 2006; Janz and Nylin 2008). Hybrid bridges could 140 help explain how host range expansions in phytophagous insects first occur, particularly in highly specialized insect lineages (Kelley and Farrell 1998; Stireman 2005; Janz and Nylin 2008; Groot et al. 2011), such as Phytomyza (Spencer et al. 1986; Spencer 1990). Hybrids intermediate in traits important for host-use could ease the transition to the new host species (Floate and Whitham 1993). As insects adapt to the new host, genetic divergence is likely to increase due to divergent selection. Variation in hybridization rates among host plants and gene flow among insects and the genetic basis of and strength of selection on host preference and performance would likely result in a geographic mosaic of genetic divergence among host forms of insects, which if coupled with reproductive isolation, could result in a geographic mosaic of speciation (Thompson 2005; Edelaar and Benkman 2006; Barbour et al. 2009; Thompson 2009; Marsden et al. 2011; Barman et al. 2012). Knowing hybridization is common in plants (Ellstrand et al. 1996; Rieseberg 1997), it is likely that hybrid bridges and barriers exist in many plant-insect systems, and could be largely responsible for the high diversity of species in both. The cost and effort required to generate the number and types of markers with the number of individuals needed to detect hybridization are decreasing rapidly (Glenn 2011), improving our ability to test how hybridization affects the evolution of interacting species. Increased effort will likely reveal that plant hybridization is the missing link explaining how adaptive radiations proceed in highly specialized lineages of insects. Table 4.1: Genotyped sample sizes from each population. Ilex coriacea Ilex glabra State Site Population Plants Flies Combo Plants Flies Combo FL Apalachicola National Forest Hunters (HUN) 9 6 4 8 1 1 Sopchoppy (SOP) 5 0 0 1 0 0 Etoniah Creek State Forest East V (EAV) 0 0 0 10 0 0 Stuck in Sand (SIS) 10 5 4 8 9 7 GA Crooked River State Park Crooked River (CRG) 0 0 0 10 3 2 SC Francis Marion National Forest Big Ocean Bay (BOB) 18 19 7 13 21 3 Wambaw Trail (WAM) 20 19 12 12 18 1 NC Croatan National Forest Catfish Lake (CAT) 10 18 0 9 3 0 Road 152 (152) 23 27 14 10 21 1 VA Great Dismal Swamp National Wildlife Refuge Great Dismal Swamp (GDS) 9 2 1 9 1 0 DE Cape Henlopen State Park Cape Henlopen (CHE) 0 0 0 8 10 7 Total 104 96 42 98 87 22 ?Combo? refers to combinations of individual genotyped flies and the genotyped plant from which they were collected. 142 Table 4.2. Adjusted hybrid indices for plant populations. The standard hybrid index was adjusted so that all ?parental? individuals have an index of 0 and an index above 0 indicates some level of mixed genotype (see text). Adjusted indices were then averaged over all individuals in a population. Population N Mean Standard Deviation Standard Error of Mean HUN 17 0.052938 0.132544 0.032147 SOP 6 0.072731 0.143235 0.058475 EAV 10 0.014748 0.028223 0.008925 SIS 18 0.026783 0.04746 0.011187 CRG 10 0.00803 0.013211 0.004178 BOB 31 0.025078 0.085422 0.015342 WAM 32 0.020816 0.059917 0.010592 152 33 0.015237 0.049879 0.008683 CAT 19 0.026697 0.067206 0.015418 GDS 18 0.014552 0.021252 0.005009 CHE 8 0.006347 0.015464 0.005467 Table 4.3. Adjusted hybrid indices for fly populations. The standard hybrid index was adjusted so that all ?parental? individuals have an index of 0 and an index above 0 indicates some level of mixed genotype (see text). Adjusted indices were then averaged over all individuals in a population. Population N Mean Standard Deviation Standard Error of Mean HUN 7 0.278335 0.181328 0.068536 SIS 14 0.172567 0.164555 0.043979 CRG 3 0.121203 0.128849 0.074391 BOB 40 0.094846 0.110644 0.017494 WAM 37 0.104827 0.124812 0.020519 152 48 0.142987 0.151814 0.021912 CAT 21 0.208212 0.142443 0.031084 GDS 3 0.237584 0.244655 0.141252 CHE 10 0.065696 0.092991 0.029406 143 Figure 4.1: Endemic range Ilex coriacea and I .glabra with collection sites labeled. Ilex glabra Ilex coriacea & Ilex glabra Cape Henlopen, DE Great Dismal Swamp, VA Croatan, NC Francis Marion, SC Crooked River, GA Etoniah Creek, FL Apalachicola, FL Long Island, NY NJ Annapolis, MD Archibold, FL Carolina Beach, NC Figure 4.2. Hypothesized effects of gene flow in plants on gene flow in insects. Ha: If traits important for host use in insects are intermediate in hybrid plants, insects from both parental host plant species could encounter one another on hybrid plants, potentially resulting in gene flow between insects that otherwise would not encounter one another. Therefore, the more hybridization found in a given location with both host plants, the more gene flow that would be expected to be seen between host-associated insect populations or species. Hb: If traits important for host use in insects are novel or transgressive in hybrid plants, they could prevent insects from either parental host plant species from using the novel host, potentially selecting for greater host fidelity, decreasing gene flow between host-associated insect populations or species. Hc: If traits important for host use in insects display a range of phenotypes from parental to intermediate to novel, there may be no association between hybridization in host plants and gene flow in insects. Figure 4.2 Ha: Hybrid-bridge hypothesis Hybridization in Hollies G e n e F l o w i n F l i e s . . . . . . Hybridization in Hollies G e n e F l o w i n F l i e s Hc: No effect on gene flow (random) Hybridization in Hollies G e n e F l o w i n F l i e s Hb: Hybrids novel and unused . . . . . . Figure 4.3. Adjusted hybrid index: The hybrid index varies between 0 and 1 where 0 represents an individual from species (or host- associated population) A with no mixed ancestry and 1 represents an individual from species (or host-associated population) B with no mixed ancestry. Individuals with hybrid indices between 0 and 1 represent individuals with some degree of mixed ancestry, where 0.5 would represent an F1 hybrid. If hybrid indices are averaged in a location with both A and B, the average would likely be an intermediate value closer to the species (or host-associated population) with the larger sample size. Therefore, hybrid indices were standardized by subtracting any values greater than 0.5 from 1, resulting in values between 0 and 0.5 where 0 represents parental and 0.5 represents an F1 hybrid. The image on the left contains the original hybrid indices of individuals from NC followed by their adjusted hybrid index on the right. Once values have been standardized, they can be averaged for a population to obtain a comparable estimate of the degree of hybridization within a given population. Figure 4.3 0 0.2 0.4 0.6 0.8 1 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 H y b r i d I n d e x Individuals 0 0.1 0.2 0.3 0.4 0.5 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 A d j u s t e d H y b r i d I n d e x Individuals Figure 4.4. Comparison of hybrid indices of individual flies on their host plants. Hybrid indices were generated based on AFLPs. Shape indicates plant status and color indicates fly status using a 10% threshold to be considered a ?hybrid?. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 * * * Plant I. coriacea I. glabra Hybrid Fly Coriacea-fly Glabra-fly Hybrid * H y b r i d i n d e x o f f l y Hybrid index of plant Figure 4.5. Average adjusted hybrid indices of populations. Populations had a minimum of five individuals present. Population CHE was left out of the regression analysis because it is out of the range of I. coriacea. . 152, NC BOB, SC CAT, NC CHE, DE HUN, westFL SIS, eastFL WAM, SC 0 0.05 0.1 0.15 0.2 0.25 0.3 0 0.01 0.02 0.03 0.04 0.05 0.06 A d j u s t e d A v e r a g e H y b r i d I n d e x o f F l i e s Adjusted Average Hybrid Index of Plants y = 4.3390 x + 0.0458 R2 = 0.06717, adj R2 = 0.5896 p-value = 0.04591 150 APPENDIX A: Code written in R to calculate linkage disequilibrium between dominant markers ######################################################################## # Code for calculating Linkage Disequilibrium between dominant loci based on # equations from Hill 1974. ######################################################################## rm(list=ls()) utils:::setWindowTitle(paste("=",getwd())) ######################### READ ME ############################## # The input file should be a tab-delimited text file # The file should consist of a first column identifying a sample (individual) # followed by the markers # The first row should be the marker names # The markers should all be in binary format. # This is not set up to handle missing data, nor is it set up to handle data # with more than 2 alleles or haplotypes. I may be able to modify this as needed. ###################################################################### cat("\n") # outputs an empty line cat("Enter input file name","\n") # Don't forget the .txt inputfile<-readLines(n=1) cat("Enter output file name","\n") # Don't forget the .txt outputfile<-readLines(n=1) genos<-read.delim(paste(inputfile), header=T, row.names=1) samplenames<-row.names(genos) markernames<-colnames(genos) # The following sets up the table for the LD calculations # markers 1 and 2 are each a column for a marker to be compared # obs is the table which should be the output of the observed values makeobserved<-function(marker, othermarker) { samps<-length(marker) marker1<-marker marker2<-othermarker obsrows<-c("A-","aa","Total") 151 obscols<-c("B-","bb","Total") obs=matrix(data=NA, nrow=3, ncol=3) rownames(obs)<-obsrows colnames(obs)<-obscols AB=0 aB=0 Ab=0 ab=0 for(n in 1:samps){ if(marker1[n]==1){ if(marker2[n]==1) AB=AB+1 if(marker2[n]==0) Ab=Ab+1 } ## These count the number of samples in each if(marker1[n]==0){ ## combination of alleles for the two markers if(marker2[n]==1) aB=aB+1 if(marker2[n]==0) ab=ab+1 } } # There is probably an easier way to do this obs[1,1]=AB # but I'm not shooting for clean code. obs[1,2]=Ab # Here I'm setting up the observed matrix. obs[2,1]=aB obs[2,2]=ab obs[1,3]=sum(obs[1,1:2]) obs[2,3]=sum(obs[2,1:2]) obs[3,1]=sum(obs[1:2,1]) obs[3,2]=sum(obs[1:2,2]) obs[3,3]=sum(obs[3,1:2]) return(obs) } makep<-function(obs) { # obs is the table of observed values obss<-obs sumaa<-obss[2,3] tot<-obss[3,3] pval=1-sqrt((sumaa/tot)) return(pval) } makeq<-function(obs) { obss<-obs sumbb<-obss[3,2] tot<-obss[3,3] qval=1-sqrt((sumbb/tot)) return(qval) } 152 makef22<-function(obs) { obss<-obs aabb<-obss[2,2] tot<-obs[3,3] f22=sqrt(aabb/tot) return(f22) } makeD<-function(obs) { obss<-obs f22<-makef22(obss) sumaa<-obss[2,3] sumbb<-obss[3,2] tot<-obss[3,3] LD=f22-sqrt((sumaa*sumbb))/tot return(LD) } makeK<-function(obs) { obss<-obs LD<-makeD(obss) pval<-makep(obss) if(pval==0) { # removing NAs pval<-0.000001 } qval<-makeq(obss) if(qval==0) { # removing NAs qval<-0.000001 } tot<-obss[3,3] kval=(4*tot*(LD^2))/(pval*(2-pval)*qval*(2-qval)) return(kval) } # for eventually outputting the calculated values fullLD=matrix(data=NA, nrow=1, ncol=11) colnames(fullLD)<-c("Compare","Marker1", "Marker2", "A_B_", "A_bb", "aaB_", "aabb", "p", "q", "D", "k") #samplenames, markernames, genos nummark<-length(markernames) for(i in 1:(nummark-1)){ 153 print("i=") print(i) remaining<-i+1 # the for statements will go through every for(j in remaining:nummark){ # combination of markers marker1<-genos[,i] marker2<-genos[,j] observed<-makeobserved(marker1, marker2) AB<-observed[1,1] Ab<-observed[1,2] aB<-observed[2,1] ab<-observed[2,2] pval<-makep(observed) qval<-makeq(observed) Dval<-makeD(observed) Kval<-makeK(observed) comparename=paste(markernames[i],markernames[j],sep="-") fullLDentry<-c(comparename,markernames[i],markernames[j], AB, Ab, aB, ab, pval, qval, Dval, Kval) fullLD<-rbind(fullLD, fullLDentry) } } rownames(fullLD)<-fullLD[,1] fullLD<-fullLD[2:nrow(fullLD),2:ncol(fullLD)] fullLD<-as.data.frame(fullLD) likeli<-as.numeric(as.vector(fullLD$k)) pvalue<-vector(mode="numeric", length=nrow(fullLD)) for(i in 1:nrow(fullLD)){ if(!is.na(likeli[i])){ pvalue[i]=pchisq(likeli[i], df=1, lower.tail=F) } } fullLD<-cbind(fullLD, pvalue) write.table(fullLD, file=outputfile, quote=F, sep="\t", append=F) 154 APPENDIX B: Summary Data for Phytomyza glabricola Sample Host Sex Population Location Collection AFLP EF-1alpha 152C004 C F 152 NC 2006 X X 152C013 C M 152 NC 2006 X X 152C026 C M 152 NC 2006 X X 152C031 C M 152 NC 2006 X X 152C032 C F 152 NC 2006 X X 152C039 C F 152 NC 2006 X X 152C042 C M 152 NC 2006 X X 152C059 C F 152 NC 2006 X X 152C061 C M 152 NC 2006 X X 152C062 C F 152 NC 2006 X X 152C077 C M 152 NC 2006 X X 152C092 C F 152 NC 2006 X X 152C096 C F 152 NC 2006 X X 152C099 C M 152 NC 2006 X 152C101 C F 152 NC 2006 X 152C102 C M 152 NC 2006 X X 152C123 C F 152 NC 2006 X X 152C127 C F 152 NC 2006 X X 152C130 C M 152 NC 2006 X X 152C142 C M 152 NC 2006 X X 152C143 C F 152 NC 2006 X X 152C190 C F 152 NC 2006 X X 152C223 C M 152 NC 2007 X X 152C234 C M 152 NC 2007 X 152C248 C F 152 NC 2007 X X 152C258 C F 152 NC 2007 X 152C264 C F 152 NC 2007 X X 152C265 C ? 152 NC 2007 X 152C271 C F 152 NC 2007 X X 152C272 C F 152 NC 2007 X 152C273 C M 152 NC 2007 X X 152C280 C M 152 NC 2007 X 152C288 C M 152 NC 2007 X X 152G001 G M 152 NC 2006 X X 152G002 G F 152 NC 2006 X X 152G012 G M 152 NC 2006 X X 152G013 G M 152 NC 2006 X 152G015 G M 152 NC 2006 X X 152G018 G F 152 NC 2006 X X 152G030 G M 152 NC 2006 X 155 Sample Host Sex Population Location Collection AFLP EF-1alpha 152G033 G F 152 NC 2006 X 152G034 G M 152 NC 2006 X X 152G035 G F 152 NC 2006 X X 152G037 G F 152 NC 2006 X X 152G038 G M 152 NC 2006 X X 152G040 G F 152 NC 2006 X X 152G053 G M 152 NC 2006 X 152G066 G M 152 NC 2006 X X 152G068 G F 152 NC 2006 X X 152G075 G F 152 NC 2006 X X 152G086 G F 152 NC 2006 X X 152G093 G M 152 NC 2006 X X 152G096 G F 152 NC 2006 X X 152G098 G M 152 NC 2006 X X 152G109 G F 152 NC 2006 X X 152G116 G F 152 NC 2006 X X 152G123 G F 152 NC 2006 X 152G126 G M 152 NC 2006 X 152G164 G M 152 NC 2007 X X 152G167 G F 152 NC 2007 X 152G183 G M 152 NC 2007 X 152G199 G M 152 NC 2007 X X BOBC006 C M BOB SC 2006 X X BOBC007 C F BOB SC 2006 X X BOBC012 C F BOB SC 2006 X BOBC019 C F BOB SC 2006 X BOBC023 C F BOB SC 2006 X X BOBC037 C F BOB SC 2006 X X BOBC039 C F BOB SC 2006 X X BOBC046 C M BOB SC 2006 X X BOBC047 C M BOB SC 2006 X BOBC049 C F BOB SC 2006 X X BOBC050 C M BOB SC 2006 X BOBC074 C F BOB SC 2006 X BOBC076 C M BOB SC 2006 X X BOBC084 C F BOB SC 2006 X X BOBC127 C M BOB SC 2006 X X BOBC128 C F BOB SC 2006 X X BOBC130 C F BOB SC 2006 X X BOBC134 C M BOB SC 2006 X BOBC149 C F BOB SC 2006 X X BOBC196 C M BOB SC 2007 X X 156 Sample Host Sex Population Location Collection AFLP EF-1alpha BOBC198 C M BOB SC 2007 X X BOBC228 C F BOB SC 2007 X BOBC230 C M BOB SC 2007 X X BOBC241 C F BOB SC 2007 X BOBC243 C F BOB SC 2007 X BOBG001 G M BOB SC 2006 X X BOBG002 G M BOB SC 2006 X X BOBG003 G M BOB SC 2006 X X BOBG004 C F BOB SC 2006 X BOBG005 G M BOB SC 2006 X X BOBG007 G M BOB SC 2006 X X BOBG010 G M BOB SC 2006 X X BOBG034 G M BOB SC 2006 X X BOBG045 G F BOB SC 2006 X X BOBG057 G M BOB SC 2006 X X BOBG067 C M BOB SC 2006 X BOBG090 G F BOB SC 2006 X X BOBG094 G F BOB SC 2006 X X BOBG095 G F BOB SC 2006 X X BOBG104 G F BOB SC 2006 X X BOBG111 G F BOB SC 2006 X BOBG114 G F BOB SC 2006 X X BOBG120 G F BOB SC 2006 X X BOBG128 G M BOB SC 2006 X X BOBG158 G ? BOB SC 2007 X X BOBG159 G ? BOB SC 2007 X BOBG169 G F BOB SC 2007 X X BOBG174 G F BOB SC 2007 X X BOBG190 G M BOB SC 2007 X BOBG198 G M BOB SC 2007 X X CATC004 C F CAT NC 2006 X X CATC010 C M CAT NC 2006 X X CATC049 C F CAT NC 2006 X X CATC051 C F CAT NC 2006 X X CATC076 C F CAT NC 2006 X CATC105 C F CAT NC 2006 X X CATC113 C M CAT NC 2006 X CATC115 C M CAT NC 2006 X X CATC119 C M CAT NC 2006 X X CATC124 C M CAT NC 2006 X X CATC135 C M CAT NC 2006 X X CATC145 C M CAT NC 2006 X X 157 Sample Host Sex Population Location Collection AFLP EF-1alpha CATC148 C F CAT NC 2006 X CATC158 C M CAT NC 2006 X X CATC159 C M CAT NC 2006 X X CATC168 C M CAT NC 2006 X X CATC172 C M CAT NC 2006 X X CATC175 C M CAT NC 2006 X CATC176 C F CAT NC 2006 X X CATC179 C M CAT NC 2006 X X CATC183 C F CAT NC 2006 X X CATC189 C M CAT NC 2006 X X CATG001 G F CAT NC 2006 X CATG013 G F CAT NC 2006 X X CATG025 G M CAT NC 2006 X CATG038 G F CAT NC 2006 X X CATG073 G F CAT NC 2006 X X CHEG005 G ? CHE DE 2007 X CHEG033 G M CHE DE 2007 X X CHEG048 G F CHE DE 2007 X X CHEG049 G M CHE DE 2007 X X CHEG059 G ? CHE DE 2007 X CHEG064 G ? CHE DE 2007 X CHEG088 G F CHE DE 2007 X X CHEG095 G F CHE DE 2007 X X CHEG096 G F CHE DE 2007 X X CHEG106 G F CHE DE 2007 X CHEG107 G M CHE DE 2007 X X CHEG108 G F CHE DE 2007 X CHEG109 G ? CHE DE 2007 X X CHEG114 G M CHE DE 2007 X X CHEG122 G F CHE DE 2007 X X CRGG002 G M CRG GA 2007 X X CRGG007 G F CRG GA 2007 X CRGG008 G F CRG GA 2007 X X CRGG014 G larva CRG GA 2007 X X EAVG001 G larva EAV EAST-FL 2007 X EAVG002 G larva EAV EAST-FL 2007 X GDSC005 C M GDS VA 2007 X GDSC039 C F GDS VA 2007 X GDSC056 C M GDS VA 2007 X X GDSC065 C F GDS VA 2007 X X GDSG012 G M GDS VA 2007 X X HUNC002 C F HUN WEST-FL 2007 X X 158 Sample Host Sex Population Location Collection AFLP EF-1alpha HUNC003 C F HUN WEST-FL 2007 X X HUNC006 C M HUN WEST-FL 2007 X X HUNC007 C F HUN WEST-FL 2007 X X HUNC009 C M HUN WEST-FL 2007 X X HUNC014 C M HUN WEST-FL 2007 X X HUNG002 G M HUN WEST-FL 2007 X X PCo15 C ? BOB SC Scheffer & Hawthorne X PCo16 C ? BOB SC Scheffer & Hawthorne X PCo18 C ? BOB SC Scheffer & Hawthorne X PCo19 C ? BOB SC Scheffer & Hawthorne X PCo21 C ? BOB SC Scheffer & Hawthorne X PCo23 C ? BOB SC Scheffer & Hawthorne X PCo26 C ? BOB SC Scheffer & Hawthorne X PCo27 C ? BOB SC Scheffer & Hawthorne X PCo28 C ? BOB SC Scheffer & Hawthorne X PCo29 C ? BOB SC Scheffer & Hawthorne X PCo30 C ? Carolina Beach NC Scheffer & Hawthorne X PCo31 C ? Carolina Beach NC Scheffer & Hawthorne X PCo33 C ? Carolina Beach NC Scheffer & Hawthorne X PCo34 C ? Carolina Beach NC Scheffer & Hawthorne X PCo35 C ? Carolina Beach NC Scheffer & Hawthorne X PCo36 C ? Carolina Beach NC Scheffer & Hawthorne X PCo37 C ? Carolina Beach NC Scheffer & Hawthorne X PCo38 C ? Carolina Beach NC Scheffer & Hawthorne X PCo39 C ? Carolina Beach NC Scheffer & Hawthorne X PCo40 C ? Carolina Beach NC Scheffer & Hawthorne X PCo41 C ? Carolina Beach NC Scheffer & Hawthorne X PCo42 C ? Carolina Beach NC Scheffer & Hawthorne X PCo43 C ? Carolina Beach NC Scheffer & Hawthorne X PCo44 C ? Carolina Beach NC Scheffer & Hawthorne X PCo45 C ? Carolina Beach NC Scheffer & Hawthorne X PGl14 G ? BOB SC Scheffer & Hawthorne X PGl15 G ? BOB SC Scheffer & Hawthorne X PGl16 G ? BOB SC Scheffer & Hawthorne X PGl17 G ? BOB SC Scheffer & Hawthorne X PGl18 G ? BOB SC Scheffer & Hawthorne X PGl20 G ? BOB SC Scheffer & Hawthorne X PGl21 G ? BOB SC Scheffer & Hawthorne X PGl22 G ? BOB SC Scheffer & Hawthorne X PGl23 G ? BOB SC Scheffer & Hawthorne X PGl24 G ? BOB SC Scheffer & Hawthorne X PGl25 G ? BOB SC Scheffer & Hawthorne X 159 Sample Host Sex Population Location Collection AFLP EF-1alpha PGl26 G ? BOB SC Scheffer & Hawthorne X PGl27 G ? BOB SC Scheffer & Hawthorne X PGl28 G ? BOB SC Scheffer & Hawthorne X PGl31 G ? Carolina Beach NC Scheffer & Hawthorne X PGl39 G ? Carolina Beach NC Scheffer & Hawthorne X PGl40 G ? Carolina Beach NC Scheffer & Hawthorne X PGl41 G ? Carolina Beach NC Scheffer & Hawthorne X PGl42 G ? Carolina Beach NC Scheffer & Hawthorne X PGl44 G ? Carolina Beach NC Scheffer & Hawthorne X PGl45 G ? Carolina Beach NC Scheffer & Hawthorne X PGl46 G ? Archibold SOUTH-FL Scheffer & Hawthorne X PGl47 G ? Archibold SOUTH-FL Scheffer & Hawthorne X PGl48 G ? Archibold SOUTH-FL Scheffer & Hawthorne X PGl49 G ? Archibold SOUTH-FL Scheffer & Hawthorne X PGl50 G ? Archibold SOUTH-FL Scheffer & Hawthorne X PGl51 G ? Archibold SOUTH-FL Scheffer & Hawthorne X PGl52 G ? Archibold SOUTH-FL Scheffer & Hawthorne X PGl53 G ? Archibold SOUTH-FL Scheffer & Hawthorne X PGl54 G ? Long Island NY Scheffer & Hawthorne X PGl55 G ? Long Island NY Scheffer & Hawthorne X PGl56 G ? Annapolis MD Scheffer & Hawthorne X PGl62 G ? Annapolis MD Scheffer & Hawthorne X PGl63 G ? NJ NJ Scheffer & Hawthorne X PGl64 G ? NJ NJ Scheffer & Hawthorne X SISC004 C F SIS EAST-FL 2007 X X SISC014 C M SIS EAST-FL 2007 X X SISC025 C larva SIS EAST-FL 2007 X SISC030 C M SIS EAST-FL 2007 X X SISC040 C M SIS EAST-FL 2007 X X SISC041 C larva SIS EAST-FL 2007 X SISC042 C F SIS EAST-FL 2007 X X SISG003 G M SIS EAST-FL 2007 X X SISG007 G larva SIS EAST-FL 2007 X SISG011 G F SIS EAST-FL 2007 X X SISG032 G M SIS EAST-FL 2007 X X SISG048 G M SIS EAST-FL 2007 X X SISG050 G F SIS EAST-FL 2007 X X SISG054 G M SIS EAST-FL 2007 X SISG066 G M SIS EAST-FL 2007 X X SISG067 G M SIS EAST-FL 2007 X X SISG069 G M SIS EAST-FL 2007 X X SISG076 G M SIS EAST-FL 2007 X X 160 Sample Host Sex Population Location Collection AFLP EF-1alpha WAMC002 C M WAM SC 2006 X X WAMC004 C M WAM SC 2006 X X WAMC014 C M WAM SC 2006 X X WAMC028 C M WAM SC 2006 X WAMC031 C F WAM SC 2006 X X WAMC034 C F WAM SC 2006 X WAMC036 C M WAM SC 2006 X X WAMC040 C F WAM SC 2006 X X WAMC041 C F WAM SC 2006 X WAMC044 C F WAM SC 2006 X WAMC054 C F WAM SC 2006 X X WAMC057 C M WAM SC 2006 X X WAMC063 C F WAM SC 2006 X X WAMC066 C F WAM SC 2006 X WAMC078 C F WAM SC 2006 X WAMC082 C M WAM SC 2006 X X WAMC084 C M WAM SC 2006 X X WAMC090 C M WAM SC 2006 X WAMC092 C M WAM SC 2006 X X WAMC102 C M WAM SC 2007 X WAMC103 C F WAM SC 2007 X X WAMC106 C M WAM SC 2007 X WAMC114 C F WAM SC 2007 X X WAMC121 C F WAM SC 2007 X X WAMC124 C larva WAM SC 2007 X WAMC127 C F WAM SC 2007 X WAMC128 C F WAM SC 2007 X X WAMC141 C ? WAM SC 2007 X X WAMC146 C larva WAM SC 2007 X WAMC148 C F WAM SC 2007 X X WAMG001 G M WAM SC 2006 X X WAMG005 G M WAM SC 2006 X X WAMG008 G M WAM SC 2006 X X WAMG012 G F WAM SC 2006 X X WAMG016 G F WAM SC 2006 X X WAMG020 G M WAM SC 2006 X X WAMG031 G F WAM SC 2006 X X WAMG037 G F WAM SC 2006 X X WAMG038 G F WAM SC 2006 X X WAMG040 G M WAM SC 2006 X X WAMG043 G M WAM SC 2006 X X WAMG050 G F WAM SC 2006 X X 161 Sample Host Sex Population Location Collection AFLP EF-1alpha WAMG052 G F WAM SC 2006 X WAMG055 G F WAM SC 2006 X X WAMG062 G F WAM SC 2006 X X WAMG067 G M WAM SC 2006 X WAMG068 G F WAM SC 2006 X X WAMG069 G M WAM SC 2006 X WAMG073 G M WAM SC 2006 X WAMG075 G F WAM SC 2006 X X WAMG076 G F WAM SC 2006 X WAMG092 G M WAM SC 2007 X X WAMG096 G M WAM SC 2007 X Hosts are host plants Ilex coriacea (C) and I. glabra (G). Sex are sex of the flies: female (F), male (M), larva, or unknown (?). Individuals sampled in 2006 and 2007 are from Cape Henlopen (CHE), Great Dismal Swamp (GDS), Croatan (152 and CAT), Francis Marion (BOB and WAM), Crooked River (CRG), Etoniah Creek (SIS), and Apalachicola (HUN) (see Figure 2.1 for map). Details for individuals not collected in 2006 or 2007 can be found in Scheffer and Hawthorne (2007). 162 APPENDIX C: Results of NEWHYBRIDS in Phytomyza glabricola Highlighted posterior probabilities represent the different cutoffs for introgression: backcross in bold, less than 75% posterior probability of belonging to a parental type in bold italics, and less than 90% posterior probability of belonging to a parental type in italics. Sample Coriacea-fly Backcross-coriacea F1 Backcross-glabra Glabra-fly 152C004 0.69483 0.30506 0.00008 0.00003 0 152C013 0.99535 0.00462 0.00002 0.00002 0 152C026 0.12764 0.84579 0.02624 0.00032 0 152C031 0.1273 0.85883 0.01384 0.00004 0 152C032 0.8078 0.19199 0.0002 0 0 152C039 0.97639 0.02357 0.00003 0.00001 0 152C042 0.97766 0.02227 0.00003 0.00003 0 152C059 0.99719 0.00278 0.00002 0.00001 0 152C061 0.98565 0.0143 0.00004 0 0 152C062 0.99673 0.00325 0.00002 0.00001 0 152C077 0.75451 0.24512 0.00033 0.00004 0 152C092 0.97206 0.0279 0 0.00003 0 152C096 0.98758 0.01239 0.00002 0.00002 0 152C102 0.02938 0.92371 0.04481 0.0021 0 152C123 0.98965 0.01032 0.00002 0.00001 0 152C127 0.6564 0.34341 0.00018 0.00001 0 152C130 0.98347 0.01648 0.00003 0.00002 0 152C142 0.88241 0.11747 0.00008 0.00004 0 152C143 0.99751 0.00247 0.00002 0.00001 0 152C190 0.9926 0.00736 0.00003 0.00001 0 152C223 0.96684 0.03309 0.00003 0.00004 0 152C248 0.99956 0.00042 0.00001 0 0 152C258 0.83909 0.16073 0.00017 0 0 152C264 0.80683 0.19308 0.00008 0.00001 0 152C271 0.97316 0.0268 0.00003 0 0 152C273 0.984 0.01596 0.00002 0.00002 0 152C288 0.09805 0.86949 0.03188 0.00058 0 152G001 0 0.00022 0 0.00116 0.99853 152G002 0 0.00001 0.00144 0.24645 0.75211 152G012 0 0.00021 0.00056 0.05715 0.94208 152G015 0 0 0 0.00064 0.99935 152G018 0 0 0.00001 0.00263 0.99736 152G034 0 0.00036 0.00392 0.14465 0.85106 152G035 0 0.00001 0.00087 0.17271 0.82641 152G037 0 0 0.00001 0.00173 0.99826 152G038 0 0 0 0.00329 0.99671 163 Sample Coriacea-fly Backcross-coriacea F1 Backcross-glabra Glabra-fly 152G040 0 0 0 0.00627 0.99372 152G066 0 0 0 0.00122 0.99878 152G068 0 0.00016 0.00249 0.14035 0.857 152G075 0 0 0 0.00205 0.99795 152G086 0 0 0.00021 0.03859 0.96119 152G093 0 0 0 0.00017 0.99982 152G096 0 0.00018 0.00004 0.00032 0.99947 152G098 0 0 0.00001 0.00947 0.99053 152G109 0 0 0.00001 0.00471 0.99528 152G116 0 0 0.00003 0.01343 0.98654 152G164 0 0 0 0.00034 0.99966 152G199 0 0 0 0.00012 0.99988 BOBC006 0.98802 0.01192 0.00003 0.00003 0 BOBC007 0.99334 0.00663 0.00002 0 0 BOBC012 0.9989 0.00107 0.00002 0.00001 0 BOBC019 0.99545 0.00452 0.00002 0 0 BOBC023 0.99792 0.00206 0.00002 0 0 BOBC037 0.99521 0.00478 0.00001 0 0 BOBC039 0.99689 0.00308 0.00002 0.00001 0 BOBC046 0.99641 0.00354 0.00002 0.00003 0 BOBC049 0.99987 0.0001 0.00002 0 0 BOBC076 0.75172 0.24811 0.00014 0.00003 0 BOBC084 0.99536 0.0046 0.00002 0.00001 0 BOBC127 0.99026 0.0097 0.00002 0.00003 0 BOBC128 0.98369 0.01628 0.00002 0.00002 0 BOBC130 0.9978 0.00217 0.00002 0.00001 0 BOBC149 0.92269 0.07724 0.00004 0.00003 0 BOBC196 0.77289 0.22644 0.00062 0.00005 0 BOBC198 0.98163 0.01832 0.00005 0.00001 0 BOBC230 0.98467 0.01527 0.00001 0.00004 0 BOBC243 0.98683 0.01313 0.00001 0.00002 0 BOBG001 0 0 0 0.00017 0.99982 BOBG002 0 0 0.00002 0.00862 0.99136 BOBG003 0 0 0.00001 0.00615 0.99383 BOBG005 0 0.00006 0.00005 0.00075 0.99914 BOBG007 0 0 0.0005 0.0745 0.92499 BOBG010 0 0 0 0.00023 0.99977 BOBG034 0 0 0 0.00022 0.99977 BOBG045 0 0 0.00001 0.02353 0.97645 BOBG057 0 0.00001 0.00011 0.03298 0.9669 BOBG090 0 0.00086 0.0214 0.45957 0.51817 BOBG094 0 0 0.00004 0.01593 0.98403 164 Sample Coriacea-fly Backcross-coriacea F1 Backcross-glabra Glabra-fly BOBG095 0 0 0.00002 0.01182 0.98816 BOBG104 0 0 0.00002 0.01086 0.98911 BOBG111 0 0 0.00004 0.0102 0.98976 BOBG114 0 0.00004 0.00051 0.04628 0.95317 BOBG120 0 0 0 0.00097 0.99903 BOBG128 0 0 0 0.00133 0.99867 BOBG158 0 0 0.00016 0.08061 0.91923 BOBG169 0 0 0.00002 0.01248 0.9875 BOBG174 0 0 0.00002 0.00132 0.99866 BOBG198 0 0 0 0.00226 0.99773 CATC004 0.99275 0.00722 0.00002 0.00001 0 CATC010 0.82866 0.17081 0.00052 0.00001 0 CATC049 0.99732 0.00265 0.00002 0.00001 0 CATC051 0.98409 0.01588 0.00002 0.00002 0 CATC105 0.99598 0.00399 0.00002 0.00001 0 CATC115 0.91022 0.08967 0.00008 0.00004 0 CATC119 0.45149 0.53159 0.01686 0.00006 0 CATC124 0.9354 0.0645 0.00008 0.00002 0 CATC135 0.6342 0.36477 0.001 0.00003 0 CATC145 0.74724 0.25252 0.00022 0.00002 0 CATC158 0.84137 0.15844 0.00015 0.00004 0 CATC159 0.82206 0.17776 0.00017 0.00002 0 CATC168 0.77915 0.22045 0.00038 0.00003 0 CATC172 0.02232 0.86638 0.0754 0.03589 0 CATC176 0.98656 0.01341 0.00001 0.00002 0 CATC179 0.07718 0.91764 0.00509 0.00009 0 CATC183 0.99745 0.00253 0.00002 0.00001 0 CATC189 0.99546 0.00449 0.00001 0.00004 0 CATG013 0 0 0.00006 0.02188 0.97806 CATG038 0 0 0.00004 0.03677 0.96319 CATG073 0 0 0.0003 0.06826 0.93143 CHEG033 0 0 0 0.00205 0.99795 CHEG048 0 0 0 0.00114 0.99885 CHEG049 0 0 0 0.00024 0.99976 CHEG088 0 0 0.00001 0.0002 0.99979 CHEG095 0 0 0.00011 0.03809 0.96181 CHEG096 0 0 0.00002 0.01153 0.98845 CHEG107 0 0 0 0.0011 0.99889 CHEG109 0 0 0 0.00495 0.99505 CHEG114 0 0 0.0001 0.03494 0.96496 CHEG122 0 0 0.00001 0.00294 0.99705 CRGG002 0 0 0.00001 0.00247 0.99753 165 Sample Coriacea-fly Backcross-coriacea F1 Backcross-glabra Glabra-fly CRGG008 0 0.00001 0.00213 0.18799 0.80988 CRGG014 0 0 0.00001 0.00616 0.99384 GDSC056 0.00921 0.85928 0.12452 0.00699 0 GDSC065 0.3398 0.65794 0.00225 0.00001 0 GDSG012 0 0 0 0.0034 0.9966 HUNC002 0.97846 0.0215 0.00002 0.00001 0 HUNC003 0.95707 0.04289 0.00003 0.00001 0 HUNC006 0.89035 0.10953 0.00009 0.00003 0 HUNC007 0.75733 0.24256 0.00009 0.00002 0 HUNC009 0.06793 0.91389 0.01777 0.00042 0 HUNC014 0.03545 0.87577 0.08584 0.00294 0 HUNG002 0 0 0.00004 0.02079 0.97917 SISC004 0.00633 0.98404 0.00924 0.00039 0 SISC014 0.62245 0.37695 0.00054 0.00005 0 SISC030 0.21185 0.78772 0.00036 0.00007 0 SISC040 0.14824 0.79494 0.04818 0.00863 0.00001 SISC042 0.05308 0.94497 0.00194 0 0 SISG003 0 0 0 0.00556 0.99443 SISG011 0 0 0.00012 0.02969 0.97019 SISG032 0 0 0 0.00028 0.99972 SISG048 0 0 0 0.01391 0.98609 SISG050 0 0.0353 0.13903 0.60432 0.22135 SISG066 0 0 0 0.00075 0.99925 SISG067 0 0 0 0.00096 0.99904 SISG069 0 0 0 0.00351 0.99649 SISG076 0 0 0.00009 0.01654 0.98336 WAMC002 0.16851 0.82209 0.00929 0.00011 0 WAMC004 0.9963 0.00364 0.00001 0.00004 0 WAMC014 0.95987 0.04005 0.00005 0.00003 0 WAMC031 0.97133 0.02863 0.00002 0.00001 0 WAMC036 0.97295 0.02699 0.00003 0.00003 0 WAMC040 0.99281 0.00715 0.00003 0.00001 0 WAMC054 0.59293 0.40519 0.00186 0.00003 0 WAMC057 0.96627 0.03366 0.00004 0.00004 0 WAMC063 0.19328 0.80252 0.00419 0.00001 0 WAMC082 0.99412 0.00583 0.00002 0.00002 0 WAMC084 0.98998 0.00999 0.00002 0.00001 0 WAMC092 0.99469 0.00527 0 0.00004 0 WAMC103 0.90599 0.09395 0.00004 0.00002 0 WAMC114 0.99055 0.00942 0.00002 0.00001 0 WAMC121 0.99527 0.0047 0.00002 0.00001 0 WAMC127 0.97302 0.02694 0.00001 0.00003 0 166 Sample Coriacea-fly Backcross-coriacea F1 Backcross-glabra Glabra-fly WAMC128 0.89917 0.10065 0.00017 0.00001 0 WAMC141 0.97811 0.02186 0 0.00003 0 WAMC148 0.99483 0.00514 0.00003 0 0 WAMG001 0 0 0.00006 0.01718 0.98276 WAMG005 0 0 0.00012 0.05285 0.94703 WAMG008 0 0 0.00001 0.00597 0.99402 WAMG012 0 0 0 0.00164 0.99836 WAMG016 0 0 0.00002 0.00305 0.99692 WAMG020 0 0 0.00001 0.00534 0.99465 WAMG031 0 0.00001 0.00012 0.03445 0.96543 WAMG037 0 0.00001 0.00015 0.06199 0.93785 WAMG038 0 0 0.00001 0.00556 0.99443 WAMG040 0 0 0 0.00131 0.99869 WAMG043 0 0 0.00002 0.00144 0.99854 WAMG050 0 0 0 0.00401 0.99598 WAMG055 0 0 0.00001 0.00108 0.99891 WAMG062 0 0.00002 0.00035 0.10234 0.89729 WAMG068 0 0 0 0.00074 0.99925 WAMG075 0 0 0.00001 0.00003 0.99995 WAMG092 0 0 0.00003 0.01995 0.98003 WAMG096 0 0 0 0.00105 0.99895 APPENDIX D: Full results of genome scans i) Among host comparisons. ii) Within host and among sex comparisons. Under ?Total? the first column is from DFDIST and the second column is from BAYESCAN. All other columns are results from DFDIST. Markers with no polymorphism in a particular subset are labeled as ?rem? for removed. Numbers indicate significance (99%, 95%, or 90% level.) Only markers with 95% or greater probability of being outliers were included as outliers in Chapter 1. i) Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 1 rem 90 rem rem rem rem rem rem rem rem rem rem rem Rem 2 3 rem rem rem rem rem rem rem rem 4 rem rem rem rem rem 5 6 rem rem rem rem 7 rem rem rem rem rem rem rem rem rem rem rem rem rem 8 99 90 95 90 90 9 rem rem rem rem rem rem 10 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 11 rem rem rem rem rem rem rem rem rem 12 rem rem rem rem rem rem rem rem rem 13 99 99 99 99 95 99 99 95 90 95 90 95 14 90 rem rem rem rem rem rem rem rem rem rem rem rem rem 15 rem rem rem rem rem rem rem rem 16 rem rem rem rem rem rem rem rem rem rem rem rem rem 17 18 rem rem rem rem rem rem rem rem rem Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 19 rem rem rem rem rem rem rem rem rem 20 21 rem rem rem rem rem rem rem 22 90 rem rem rem rem 23 rem rem rem rem rem rem rem rem rem rem rem rem rem 24 rem rem rem rem rem rem rem rem rem rem rem rem rem 25 rem rem rem rem rem rem 26 rem rem rem rem rem rem rem 27 rem rem rem rem rem rem rem rem rem rem rem 28 rem 95 rem rem rem rem rem rem rem rem 29 30 rem rem rem rem rem rem rem rem rem rem rem rem rem 31 32 33 rem rem rem rem rem rem rem 34 rem rem rem rem 35 36 37 rem rem rem 38 rem rem rem rem rem rem rem rem rem rem rem rem 39 rem rem rem rem rem rem rem rem rem rem rem rem rem 40 rem rem rem rem rem rem rem rem rem rem rem rem rem 41 42 90 rem rem rem rem rem rem 43 rem rem rem rem rem rem rem rem rem 44 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 45 90 rem rem rem Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 46 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 47 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 48 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 49 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 50 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 51 95 rem 52 rem rem rem rem 53 rem rem rem rem rem rem rem rem rem rem rem rem rem 54 rem rem rem rem rem rem rem rem rem rem rem rem 55 rem 90 rem rem rem rem rem rem rem rem 56 rem rem rem rem rem rem rem rem rem rem 57 rem rem rem rem rem rem rem rem rem rem rem rem 58 rem rem rem rem rem rem rem rem rem rem rem rem rem 59 rem rem rem rem rem rem rem rem rem rem rem rem rem rem 60 rem rem rem rem rem rem rem rem rem rem rem rem rem 61 rem rem rem rem rem rem rem rem rem rem rem 62 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 63 rem rem rem rem rem rem rem rem 64 rem rem rem rem rem rem 65 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 66 90 rem rem rem 67 rem rem rem rem rem rem rem rem rem rem rem rem 68 rem rem rem rem rem rem rem rem rem rem rem rem rem 69 90 rem rem 70 95 99 99 99 99 99 95 99 99 99 95 95 95 71 rem rem rem rem rem rem 72 99 99 99 99 99 99 99 99 99 95 rem 95 99 Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 73 90 90 95 95 74 99 rem rem rem 75 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 76 rem rem rem rem rem rem rem rem 77 rem rem rem 78 79 80 rem rem 81 rem rem rem rem rem rem rem rem rem rem rem rem rem 82 rem rem rem 83 rem rem rem rem rem rem rem rem rem rem 84 rem rem rem rem rem rem rem rem rem rem rem rem rem 85 86 rem rem rem rem rem rem rem 87 90 95 95 95 rem rem rem rem rem rem 88 rem 89 rem rem rem rem rem rem rem rem rem rem rem rem 90 rem rem rem rem 91 rem rem rem rem rem rem rem rem rem rem rem rem rem 92 99 rem rem rem rem rem 95 99 99 99 93 rem rem rem rem rem rem rem rem rem rem rem rem rem 94 99 99 99 90 99 95 99 95 99 95 95 99 95 95 99 90 97 rem rem rem rem 98 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 99 rem 100 rem rem rem rem rem rem 101 rem rem rem rem rem rem rem rem rem rem rem rem rem Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 102 103 104 rem rem rem rem rem 105 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 106 107 108 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 109 95 110 111 99 90 rem 90 112 rem rem rem 113 rem 114 rem rem rem rem rem rem rem rem rem rem rem rem rem 115 99 99 99 99 99 95 99 99 99 99 95 95 95 116 99 rem rem rem rem rem rem rem rem 95 rem rem rem rem 117 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 118 99 99 99 99 99 99 99 99 99 99 90 99 90 95 99 99 99 119 rem rem rem rem rem rem rem rem rem rem rem rem rem 120 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 121 rem rem rem rem 122 95 rem rem 123 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 124 rem rem rem 125 126 rem rem rem 127 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 128 rem rem rem rem rem rem rem rem rem rem rem rem rem Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 129 rem rem rem rem rem rem rem rem rem rem rem rem rem 130 rem rem rem rem rem rem rem rem rem rem rem rem rem 131 rem rem 132 134 rem rem rem rem rem rem rem rem rem rem rem rem 135 rem rem rem rem rem rem rem rem rem rem 136 rem rem rem rem rem rem rem rem rem 137 138 139 90 90 140 rem 141 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 142 rem rem rem rem rem rem rem rem rem rem rem rem rem rem 143 rem rem rem rem rem rem rem 144 90 rem 90 90 90 95 99 95 90 95 99 99 145 rem rem rem rem rem rem rem rem rem rem rem rem rem 146 rem rem rem rem rem rem rem rem rem rem rem rem rem 147 rem 90 95 90 148 95 rem rem rem rem rem rem rem rem rem 90 95 149 150 151 152 153 rem rem rem 154 rem rem rem rem 155 rem rem rem rem rem rem rem rem 156 rem Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 157 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 158 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 159 rem rem rem rem rem 160 rem rem rem rem rem rem rem rem rem 161 rem rem rem rem rem rem rem rem rem rem rem rem rem 162 rem rem rem rem 163 rem rem rem rem rem rem rem rem rem rem rem rem rem 164 165 rem 166 rem rem rem rem rem rem rem rem rem rem rem rem 167 95 99 90 90 95 168 rem rem rem rem rem rem rem rem rem rem rem rem 169 rem rem 170 90 171 rem rem 172 rem rem 173 rem rem rem rem rem rem rem rem rem rem rem rem 174 rem rem rem rem 175 rem 176 rem rem rem rem rem rem rem rem rem rem rem 177 178 rem rem rem rem 179 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 180 90 95 181 90 rem 182 rem rem rem rem rem rem rem rem rem rem rem rem rem 183 rem rem rem rem rem rem rem rem rem rem rem Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 184 99 rem rem 185 rem rem rem rem rem rem rem rem rem 186 rem rem rem rem rem rem rem rem rem rem rem rem rem 187 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 188 rem rem rem rem rem rem rem rem rem 189 rem rem rem rem rem rem rem rem rem rem rem 190 rem rem rem rem rem rem rem rem rem rem 191 rem rem rem rem rem 192 rem rem 193 95 rem 194 rem rem rem rem 195 99 rem 196 90 197 rem rem rem rem rem rem rem rem rem rem rem rem rem 199 rem rem rem 200 rem 95 95 90 95 rem rem rem rem 90 95 201 rem rem 202 203 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 204 rem 99 95 95 95 90 rem 95 90 rem rem rem 205 rem rem rem rem rem rem 206 207 rem rem 208 rem rem rem rem rem rem rem rem rem 209 210 rem rem rem 211 Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 212 rem rem rem rem rem rem rem rem rem rem 213 95 95 95 95 90 95 95 95 95 95 90 95 99 95 214 rem rem rem rem 215 rem rem rem rem rem rem rem rem 216 rem rem rem rem rem rem rem rem rem rem rem rem 217 90 218 rem rem rem rem 219 220 rem 221 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 222 rem rem rem rem rem rem rem rem rem 223 rem rem rem rem rem 224 225 99 rem rem rem rem rem rem rem rem rem 95 rem rem rem 226 99 99 95 95 95 227 rem 99 99 95 99 90 90 99 228 rem rem rem 229 99 90 rem 90 rem 230 rem rem 231 95 95 90 95 95 rem rem rem 232 233 rem 234 235 rem rem rem rem rem rem rem rem rem rem rem rem rem 236 95 90 95 95 90 90 237 rem rem rem rem 238 95 90 95 rem 90 90 Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 239 90 95 95 240 95 241 rem 99 rem rem rem rem rem rem rem rem rem rem rem 242 99 95 95 99 90 95 99 90 243 rem rem rem rem rem rem rem rem rem rem rem rem rem 244 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 245 95 95 95 90 rem rem rem 246 99 99 95 99 95 95 95 99 99 95 95 95 95 247 rem rem rem rem rem rem rem rem rem rem rem 248 rem rem rem 249 250 rem rem 251 252 rem rem rem rem rem rem rem rem rem rem rem rem 253 rem 254 rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem rem 255 rem 90 99 99 90 99 99 99 99 99 99 90 99 95 99 99 99 256 rem rem rem rem rem 257 rem rem rem rem rem rem rem rem rem rem rem 258 rem rem rem rem rem rem rem rem rem rem rem rem rem 259 95 95 90 90 90 rem 90 90 95 rem 260 rem 261 262 rem rem rem rem rem rem rem rem rem rem 263 rem rem rem rem rem rem rem rem rem rem rem rem 264 265 Locus coriacea-flies glabra- flies Total NC- DE NC- NC NC- SC NC- EFL SC- DE SC- NC SC- SC SC- EFL EFL- DE EFL- NC EFL- SC EFL- EFL WFL- DE WFL- NC WFL- SC WFL- EFL 266 rem rem 267 rem rem rem rem rem rem 268 269 rem rem rem rem rem rem rem rem rem rem rem ii) Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 1 rem rem rem rem rem rem 90 99 rem 2 99 99 99 99 3 rem rem rem rem rem 4 rem 5 6 rem rem rem 7 rem rem rem rem rem rem rem rem 8 99 rem 99 rem 95 9 rem rem rem 10 rem rem rem rem rem rem rem rem 11 rem rem rem rem rem rem 12 rem rem rem rem rem rem rem 13 14 rem 95 rem 95 rem rem rem rem 15 rem rem rem rem rem 16 rem rem rem rem rem rem rem rem 17 18 rem rem rem rem rem rem Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 19 rem rem rem rem rem 20 99 99 99 99 21 rem rem rem rem 22 rem 90 95 95 23 rem rem rem rem rem rem rem rem 24 rem rem rem rem rem rem rem rem rem 25 rem rem rem rem 26 rem rem rem rem 27 rem rem rem rem rem rem rem 28 rem rem rem rem rem 90 rem 29 90 30 rem rem rem rem rem rem rem rem 31 rem rem 32 99 99 99 99 33 rem rem rem rem rem rem 34 rem rem 35 rem 36 rem 37 rem 38 rem rem rem rem rem rem rem 39 rem rem rem rem rem rem rem rem rem 40 rem rem rem rem rem rem rem rem 41 99 99 99 99 42 rem rem rem rem 43 rem rem rem rem rem 95 rem 95 44 rem rem rem rem rem rem rem rem rem rem rem Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 45 rem 90 rem 90 46 rem rem rem rem rem rem rem rem rem rem 47 rem rem rem rem rem rem rem rem rem rem 48 rem rem rem rem rem rem rem rem rem rem rem 49 rem rem rem rem rem rem rem rem rem rem rem rem 50 rem rem rem rem rem rem rem rem rem rem 51 rem 95 52 rem rem rem rem 90 53 rem rem rem rem rem rem rem rem 54 rem rem rem rem rem rem rem rem 55 rem rem rem rem rem rem 56 rem rem rem rem rem 57 rem rem rem rem rem rem 90 rem 58 rem rem rem rem rem rem rem rem 59 rem rem rem rem rem rem rem rem rem 60 rem rem rem rem rem rem rem rem 61 rem rem rem rem rem rem rem rem 62 rem rem rem rem rem rem rem rem rem rem rem rem 63 rem rem rem rem rem 90 rem 64 rem rem rem rem 65 rem rem rem rem rem rem rem rem rem rem rem rem 66 rem 90 67 rem rem rem rem rem rem rem 68 rem rem rem rem rem rem rem 69 90 95 70 95 rem 90 rem 90 99 Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 71 rem rem rem rem 72 99 99 95 90 73 74 rem 95 75 rem rem rem rem rem rem rem rem rem rem rem 76 rem rem rem 77 rem rem 78 rem 79 rem 80 rem 81 rem rem rem rem rem rem rem rem 82 rem rem rem 83 rem rem rem rem rem 84 rem rem rem rem rem rem rem rem 85 rem rem rem 86 rem rem rem rem rem 87 90 rem rem rem rem 88 rem 90 89 rem rem rem rem rem rem rem rem 90 rem rem rem rem rem rem 91 rem rem rem rem rem rem rem rem 92 99 99 99 rem rem rem rem rem 93 rem rem rem rem rem rem rem rem 94 rem rem 97 rem rem rem rem rem rem 98 rem rem rem rem rem rem rem rem rem rem rem rem Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 99 rem rem 99 95 99 90 100 rem rem rem rem 101 rem rem rem rem rem rem rem rem 102 rem 103 104 rem rem rem rem rem rem 105 rem rem rem rem rem rem rem rem rem 106 107 rem 108 rem rem rem rem rem rem rem rem rem rem 109 90 99 95 95 110 111 rem 99 95 90 90 112 rem 113 rem 99 95 114 rem rem rem rem rem rem rem rem 115 rem rem 90 116 99 rem 95 rem rem rem rem rem rem 117 rem rem rem rem rem rem rem rem rem rem 118 rem rem rem rem rem rem rem rem 119 rem rem rem rem rem rem rem rem 120 rem rem rem rem rem rem rem rem rem rem rem 121 rem rem rem rem 122 95 95 rem 123 rem rem rem rem rem rem rem rem rem rem 124 rem rem 95 99 99 Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 125 99 99 99 99 126 127 rem rem rem rem rem rem rem rem rem rem rem 128 rem rem rem rem rem rem rem rem 129 rem rem rem rem rem rem rem rem 130 rem rem rem rem rem rem rem rem 131 rem rem rem rem rem 132 99 99 99 99 134 rem rem rem rem rem rem rem 135 rem rem rem rem rem rem 136 rem rem rem rem rem rem 137 90 99 99 99 99 138 139 rem rem rem 140 rem 141 rem rem rem rem rem rem rem rem rem rem rem 142 rem rem rem rem rem rem rem rem rem 143 rem rem rem rem 144 90 rem 145 rem rem rem rem rem rem rem rem 146 rem rem rem rem rem rem rem rem 147 rem rem rem rem rem rem 148 rem 95 90 rem rem rem rem rem 149 rem 90 90 150 151 Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 152 153 rem rem 154 rem rem 155 rem rem rem rem rem 156 157 rem rem rem rem rem rem rem rem 158 rem rem rem rem rem rem rem rem rem rem rem 159 rem rem rem 160 rem rem rem rem rem 95 rem 161 rem rem rem rem rem rem rem rem 162 rem rem rem 163 rem rem rem rem rem rem rem rem rem 164 90 165 rem 90 166 rem rem rem rem rem rem rem 167 95 99 90 99 168 rem rem rem rem rem rem 169 rem 170 95 95 171 rem 172 rem 173 rem rem rem rem rem rem rem rem 174 90 rem 175 90 rem 176 rem rem rem rem rem rem rem 177 Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 178 rem rem 179 rem rem rem rem rem rem rem rem rem rem rem 180 99 181 90 182 rem rem rem rem rem rem rem rem 183 rem rem rem rem rem rem 90 rem 184 rem 99 90 185 rem rem rem rem rem rem 186 rem rem rem rem rem rem rem rem rem rem 187 rem rem rem rem rem rem rem rem 188 rem rem rem rem rem rem 95 95 189 rem rem rem rem rem rem rem rem 190 rem rem rem rem rem 191 rem rem 99 95 192 rem 99 99 99 99 193 rem 95 99 99 99 99 95 194 rem rem 195 90 196 90 95 197 rem rem rem rem rem rem rem rem rem rem 199 rem rem 99 95 200 rem rem rem rem rem 201 rem rem rem 202 203 rem rem rem rem rem rem rem rem rem rem rem 204 rem rem rem rem rem rem Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 205 rem rem rem rem 206 rem 207 90 rem 90 208 rem rem rem rem rem rem 209 210 rem rem 211 212 rem rem rem rem rem rem 213 rem 214 rem rem rem rem rem rem 215 rem rem rem rem rem rem 216 rem rem rem rem rem rem rem rem 217 218 rem rem rem 219 220 rem 221 rem rem rem rem rem rem rem rem rem rem 222 rem rem rem rem rem rem rem 223 rem rem rem rem rem 224 225 99 rem 95 rem rem rem rem rem 226 90 95 95 90 90 227 rem rem rem rem rem rem 228 rem rem 229 90 rem 99 99 90 230 rem 95 Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 231 90 95 rem rem rem rem 232 95 233 90 234 95 235 rem rem rem rem rem rem rem rem 236 90 90 rem rem 237 rem rem rem rem rem 238 90 90 90 99 90 239 rem 240 rem 241 rem rem rem rem rem 95 rem rem 242 rem rem rem rem 90 243 rem rem rem rem rem rem rem rem 244 rem rem rem rem rem rem rem rem rem 245 99 90 95 rem rem 246 rem rem 247 rem rem rem rem rem rem rem rem 248 rem 249 90 99 99 99 99 250 rem 99 99 99 251 95 99 99 99 99 252 rem rem rem rem rem rem rem 253 90 254 rem rem rem rem rem rem rem rem rem 255 rem rem rem rem rem rem 256 rem rem rem rem rem rem Within coriacea-flies Within glabra-flies Sex Locus NC-EFL NC-WFL SC-EFL SC-WFL EFL-WFL DE-SC DE-EFL NC-EFL SC-EFL coriacea-flies glabra-flies Total 257 rem rem rem rem rem rem rem 258 rem rem rem rem rem rem rem 259 rem 95 99 260 rem 95 99 99 90 261 99 99 99 99 262 rem rem rem rem rem rem rem 263 rem rem rem rem rem rem rem rem 264 265 266 rem 90 267 rem rem rem 268 269 rem rem rem rem rem rem 188 APPENDIX E: Classification of plant samples based on the results of NEWHYBRIDS and STRUCTURE analyses Highest probabilities are indicated in bold. Using a cutoff of 0.90 for belonging to a parental group, both analyses result in the same the final classification, given in the last column. NEWHYBRIDS STRUCTURE Sample I. coriacea backcross coriacea F1 backcross glabra I. glabra I. coriacea I. glabra Classification P152C012 1 0 0 0 0 0.9999 0.0001 I. coriacea P152C013 1 0 0 0 0 0.999 0.001 I. coriacea P152C014 1 0 0 0 0 0.996 0.004 I. coriacea P152C031 1 0 0 0 0 0.999 0.001 I. coriacea P152C042 1 0 0 0 0 0.999 0.001 I. coriacea P152C077 1 0 0 0 0 0.999 0.001 I. coriacea P152C092 1 0 0 0 0 0.999 0.001 I. coriacea P152C099 1 0 0 0 0 0.9987 0.0013 I. coriacea P152C122 1 0 0 0 0 0.998 0.002 I. coriacea P152C127 1 0 0 0 0 0.999 0.001 I. coriacea P152C130 1 0 0 0 0 1 0 I. coriacea P152C133 1 0 0 0 0 0.9991 0.0009 I. coriacea P152C222 1 0 0 0 0 0.999 0.001 I. coriacea P152C234 1 0 0 0 0 0.999 0.001 I. coriacea P152C240 1 0 0 0 0 0.999 0.001 I. coriacea P152C247 1 0 0 0 0 0.999 0.001 I. coriacea P152C254 1 0 0 0 0 0.994 0.006 I. coriacea P152C271 0.99996 0.00004 0 0 0 0.9877 0.0123 I. coriacea P152C272 1 0 0 0 0 1 0 I. coriacea P152C280 1 0 0 0 0 0.997 0.003 I. coriacea P152C288 0.84829 0.1517 0.00001 0 0 0.8776 0.1224 late Bx I.coriacea P152CE02 0.7758 0.22419 0 0 0 0.833 0.167 late Bx I.coriacea P152CE06 1 0 0 0 0 0.998 0.002 I. coriacea P152G027 0 0 0 0 1 0.001 0.999 I. glabra P152G167 0 0 0 0 1 0.0062 0.9938 I. glabra P152G168 0 0 0 0 1 0.001 0.999 I. glabra P152G172 0 0 0 0 1 0.001 0.999 I. glabra P152G174 0 0 0 0 1 0.001 0.999 I. glabra P152G180 0 0 0 0 1 0.001 0.999 I. glabra P152G183 0 0 0 0 1 0.001 0.999 I. glabra P152G199 0 0 0 0 1 0.001 0.999 I. glabra P152GE01 0 0 0 0 1 0.001 0.999 I. glabra P152GE02 0 0 0 0 1 0.001 0.999 I. glabra PBOBC006 1 0 0 0 0 0.999 0.001 I. coriacea PBOBC016 1 0 0 0 0 0.999 0.001 I. coriacea PBOBC046 1 0 0 0 0 0.999 0.001 I. coriacea PBOBC047 1 0 0 0 0 0.999 0.001 I. coriacea PBOBC048 1 0 0 0 0 0.999 0.001 I. coriacea PBOBC061 1 0 0 0 0 0.998 0.002 I. coriacea PBOBC084 1 0 0 0 0 0.999 0.001 I. coriacea PBOBC092 1 0 0 0 0 1 0 I. coriacea PBOBC142 1 0 0 0 0 0.9992 0.0008 I. coriacea 189 NEWHYBRIDS STRUCTURE Sample I. coriacea backcross coriacea F1 backcross glabra I. glabra I. coriacea I. glabra Classification PBOBC149 1 0 0 0 0 0.999 0.001 I. coriacea PBOBC181 0.99999 0.00001 0 0 0 0.9632 0.0368 I. coriacea PBOBC187 1 0 0 0 0 0.997 0.003 I. coriacea PBOBC191 0.75963 0.24037 0 0 0 0.8573 0.1427 late Bx I.coriacea PBOBC198 1 0 0 0 0 0.9992 0.0008 I. coriacea PBOBC228 1 0 0 0 0 0.999 0.001 I. coriacea PBOBC240 1 0 0 0 0 0.9998 0.0002 I. coriacea PBOBCE04 1 0 0 0 0 0.999 0.001 I. coriacea PBOBCE05 0 0.00662 0.99339 0 0 0.552 0.448 F1 hybrid PBOBG011 0 0 0 0.00009 0.99991 0.0584 0.9416 I. glabra PBOBG028 0 0 0 0 1 0.004 0.996 I. glabra PBOBG067 1 0 0 0 0 0.999 0.001 I. coriacea PBOBG159 0 0 0 0 1 0.001 0.999 I. glabra PBOBG169 0 0 0 0 1 0.007 0.993 I. glabra PBOBG170 0 0 0 0 1 0.001 0.999 I. glabra PBOBG174 0 0 0 0 1 0.006 0.994 I. glabra PBOBG182 0 0 0 0 1 0.005 0.995 I. glabra PBOBG190 0 0 0 0 1 0.001 0.999 I. glabra PBOBG198 0 0 0 0 1 0.001 0.999 I. glabra PBOBG205 0 0 0 0 1 0.003 0.997 I. glabra PBOBGE01 0 0 0 0 1 0.001 0.999 I. glabra PBOBGE17 0 0 0 0 1 0.001 0.999 I. glabra PCATC093 0.99848 0.00152 0 0 0 0.9813 0.0187 I. coriacea PCATC115 0.00001 0.99938 0.00061 0 0 0.7431 0.2569 Bx I. coriacea PCATC185 1 0 0 0 0 0.998 0.002 I. coriacea PCATC197 1 0 0 0 0 0.997 0.003 I. coriacea PCATC204 1 0 0 0 0 0.999 0.001 I. coriacea PCATC212 1 0 0 0 0 0.989 0.011 I. coriacea PCATC219 1 0 0 0 0 0.999 0.001 I. coriacea PCATC225 1 0 0 0 0 0.999 0.001 I. coriacea PCATC240 0.99999 0.00001 0 0 0 0.98 0.02 I. coriacea PCATC245 1 0 0 0 0 0.997 0.003 I. coriacea PCATG107 0 0 0 0 1 0.001 0.999 I. glabra PCATG114 0 0 0 0 1 0.001 0.999 I. glabra PCATG134 0 0 0 0 1 0.005 0.995 I. glabra PCATG137 0 0 0 0 1 0.002 0.998 I. glabra PCATG143 0 0 0 0 1 0.001 0.999 I. glabra PCATG148 0 0 0 0 1 0.001 0.999 I. glabra PCATG151 0 0 0 0 1 0.001 0.999 I. glabra PCATGE09 0 0 0 0 1 0.001 0.999 I. glabra PCATGE17 0 0 0 0 1 0.002 0.998 I. glabra PCHEG003 0 0 0 0 1 0.001 0.999 I. glabra PCHEG033 0 0 0 0 1 0.001 0.999 I. glabra PCHEG047 0 0 0 0 1 0.003 0.997 I. glabra PCHEG058 0 0 0 0 1 0.001 0.999 I. glabra PCHEG089 0 0 0 0 1 0.0226 0.9774 I. glabra PCHEG093 0 0 0 0 1 0.001 0.999 I. glabra PCHEG114 0 0 0 0 1 0.001 0.999 I. glabra PCHEG119 0 0 0 0 1 0.001 0.999 I. glabra PCRGG001 0 0 0 0 1 0.0206 0.9794 I. glabra PCRGG007 0 0 0 0 1 0.002 0.998 I. glabra PCRGG008 0 0 0 0 1 0.001 0.999 I. glabra 190 NEWHYBRIDS STRUCTURE Sample I. coriacea backcross coriacea F1 backcross glabra I. glabra I. coriacea I. glabra Classification PCRGG010 0 0 0 0 1 0.001 0.999 I. glabra PCRGG013 0 0 0 0 1 0.001 0.999 I. glabra PCRGG014 0 0 0 0 1 0.0186 0.9814 I. glabra PCRGG017 0 0 0 0 1 0.008 0.992 I. glabra PCRGGE24 0 0 0 0 1 0.001 0.999 I. glabra PCRGGE32 0 0 0 0 1 0.001 0.999 I. glabra PCRGGE36 0 0 0 0 1 0.001 0.999 I. glabra PEAVG001 0 0 0 0 1 0.001 0.999 I. glabra PEAVG002 0 0 0 0 1 0.001 0.999 I. glabra PEAVG004 0 0 0 0.00012 0.99988 0.0514 0.9486 I. glabra PEAVGE02 0 0 0 0 1 0.004 0.996 I. glabra PEAVGE03 0 0 0 0 1 0.001 0.999 I. glabra PEAVGE06 0 0 0 0 1 0.001 0.999 I. glabra PEAVH003 0 0 0 0.00004 0.99996 0.062 0.938 I. glabra PEAVH004 0 0 0 0 1 0.001 0.999 I. glabra PEAVHE01 0 0 0 0 1 0.001 0.999 I. glabra PEAVHE02 0 0 0 0 1 0.001 0.999 I. glabra PGDSC003 1 0 0 0 0 0.9988 0.0012 I. coriacea PGDSC009 1 0 0 0 0 0.999 0.001 I. coriacea PGDSC012 1 0 0 0 0 0.998 0.002 I. coriacea PGDSC024 1 0 0 0 0 0.996 0.004 I. coriacea PGDSC036 1 0 0 0 0 0.997 0.003 I. coriacea PGDSC055 1 0 0 0 0 0.999 0.001 I. coriacea PGDSC057 1 0 0 0 0 0.999 0.001 I. coriacea PGDSCE01 1 0 0 0 0 0.997 0.003 I. coriacea PGDSCE02 1 0 0 0 0 0.999 0.001 I. coriacea PGDSG018 0 0 0 0.00005 0.99995 0.0565 0.9435 I. glabra PGDSG020 0 0 0 0 1 0.001 0.999 I. glabra PGDSG021 0 0 0 0 1 0.0272 0.9728 I. glabra PGDSG026 0 0 0 0 1 0.002 0.998 I. glabra PGDSG032 0 0 0 0 1 0.006 0.994 I. glabra PGDSG037 0 0 0 0 1 0.001 0.999 I. glabra PGDSG046 0 0 0 0 1 0.007 0.993 I. glabra PGDSGE05 0 0 0 0.00002 0.99998 0.0583 0.9417 I. glabra PGDSGE12 0 0 0 0 1 0.001 0.999 I. glabra PHUNC001 0.99999 0.00001 0 0 0 0.994 0.006 I. coriacea PHUNC003 1 0 0 0 0 0.999 0.001 I. coriacea PHUNC006 0.99996 0.00004 0 0 0 0.9839 0.0161 I. coriacea PHUNC010 1 0 0 0 0 0.998 0.002 I. coriacea PHUNC012 0.00762 0.97475 0.01763 0 0 0.7429 0.2571 Bx I. coriacea PHUNC014 1 0 0 0 0 0.998 0.002 I. coriacea PHUNCE04 1 0 0 0 0 0.999 0.001 I. coriacea PHUNCE06 1 0 0 0 0 0.996 0.004 I. coriacea PHUNCE08 1 0 0 0 0 0.999 0.001 I. coriacea PHUNG002 0 0 0 0 1 0.001 0.999 I. glabra PHUNGE01 0 0 0 0 1 0.009 0.991 I. glabra PHUNGE05 0 0.00008 0.99989 0.00002 0 0.4954 0.5046 F1 hybrid PHUNGE07 0 0 0 0 1 0.001 0.999 I. glabra PHUNGE09 0 0 0 0 1 0.001 0.999 I. glabra PHUNGE11 0 0 0 0 1 0.0019 0.9981 I. glabra PHUNGE14 0 0 0 0 1 0.001 0.999 I. glabra PHUNGE15 0 0 0 0 1 0.001 0.999 I. glabra 191 NEWHYBRIDS STRUCTURE Sample I. coriacea backcross coriacea F1 backcross glabra I. glabra I. coriacea I. glabra Classification PSISC001 1 0 0 0 0 0.998 0.002 I. coriacea PSISC009 0.96664 0.03336 0 0 0 0.9164 0.0836 I. coriacea PSISC010 1 0 0 0 0 0.999 0.001 I. coriacea PSISC013 1 0 0 0 0 0.998 0.002 I. coriacea PSISC025 1 0 0 0 0 0.999 0.001 I. coriacea PSISC026 1 0 0 0 0 0.999 0.001 I. coriacea PSISC028 0.99958 0.00042 0 0 0 0.9851 0.0149 I. coriacea PSISC033 1 0 0 0 0 0.997 0.003 I. coriacea PSISCE36 0.99408 0.00592 0 0 0 0.9033 0.0967 I. coriacea PSISCE37 0.99999 0.00001 0 0 0 0.992 0.008 I. coriacea PSISG006 0 0 0 0 1 0.0016 0.9984 I. glabra PSISG010 0 0 0 0 1 0.002 0.998 I. glabra PSISG032 0 0 0 0.00004 0.99996 0.0484 0.9516 I. glabra PSISG048 0 0 0 0 1 0.001 0.999 I. glabra PSISG057 0 0 0 0 1 0.005 0.995 I. glabra PSISG063 0 0 0 0 1 0.002 0.998 I. glabra PSISG076 0 0 0 0 1 0.001 0.999 I. glabra PSISGE16 0 0 0 0 1 0.001 0.999 I. glabra PSOPC001 1 0 0 0 0 0.997 0.003 I. coriacea PSOPC005 0 0.31468 0.68532 0 0 0.656 0.344 F1 / Bx I. coriacea PSOPCE01 1 0 0 0 0 0.998 0.002 I. coriacea PSOPCE02 0.99879 0.00121 0 0 0 0.9689 0.0311 I. coriacea PSOPCE03 1 0 0 0 0 0.9929 0.0071 I. coriacea PSOPGE02 0 0 0 0 1 0.001 0.999 I. glabra PWAMC013 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC014 1 0 0 0 0 0.997 0.003 I. coriacea PWAMC034 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC036 1 0 0 0 0 0.998 0.002 I. coriacea PWAMC040 0.99999 0.00001 0 0 0 0.994 0.006 I. coriacea PWAMC046 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC057 1 0 0 0 0 0.9956 0.0044 I. coriacea PWAMC063 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC084 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC090 0.01321 0.98544 0.00135 0 0 0.7617 0.2383 Bx I. coriacea PWAMC106 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC113 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC121 0.99999 0.00001 0 0 0 0.983 0.017 I. coriacea PWAMC123 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC128 1 0 0 0 0 0.991 0.009 I. coriacea PWAMC141 1 0 0 0 0 0.999 0.001 I. coriacea PWAMC144 1 0 0 0 0 1 0 I. coriacea PWAMC148 1 0 0 0 0 1 0 I. coriacea PWAMCE04 1 0 0 0 0 0.999 0.001 I. coriacea PWAMCE07 1 0 0 0 0 0.9967 0.0033 I. coriacea PWAMG011 0 0 0.00029 0.10433 0.89538 0.1699 0.8301 late Bx I. glabra PWAMG079 0 0 0 0 1 0.0181 0.9819 I. glabra PWAMG091 0 0 0 0 1 0.001 0.999 I. glabra PWAMG093 0 0 0 0 1 0.001 0.999 I. glabra PWAMG094 0 0 0 0 1 0.002 0.998 I. glabra PWAMG096 0 0 0 0 1 0.001 0.999 I. glabra PWAMG097 0 0 0 0 1 0.002 0.998 I. glabra PWAMG098 0 0 0 0 1 0.001 0.999 I. glabra 192 NEWHYBRIDS STRUCTURE Sample I. coriacea backcross coriacea F1 backcross glabra I. glabra I. coriacea I. glabra Classification PWAMGE02 0 0 0 0 1 0.009 0.991 I. glabra PWAMGE08 0 0 0 0 1 0.001 0.999 I. glabra PWAMGE15 0 0 0 0 1 0.0418 0.9582 I. glabra PWAMGE19 0 0 0 0 1 0.001 0.999 I. glabra 193 APPENDIX F: Estimated hybrid indices of flies Hybrid index calculated using package INTROGRESS using method described in Buerkle (2005). Flies with a 0.99 or higher membership in a parental type using NEWHYBRIDS used as training samples. Values of 0 correspond to coriacea-flies and 1 to glabra-flies. Sample Lower limit 95% CI Hybrid Index Upper limit 95% CI 152C004 0.04024 0.177669 0.367981 152C013 0 0 0.164214 152C026 0.293484 0.485933 0.686612 152C031 0.225633 0.388817 0.569845 152C032 0.041704 0.172718 0.366856 152C039 0 0.067773 0.273666 152C042 0.110608 0.274485 0.472594 152C059 0 0 0.067859 152C061 0.13374 0.268919 0.434151 152C062 0 0 0.097234 152C077 0.225287 0.400157 0.58788 152C092 0.027973 0.105241 0.242405 152C096 0.002934 0.048775 0.177236 152C102 0.264345 0.449763 0.647324 152C123 0.016885 0.095757 0.251175 152C127 0.149408 0.301338 0.482423 152C130 0.072599 0.213317 0.394513 152C142 0.175531 0.347175 0.539385 152C143 0 0 0.116087 152C190 0 0 0.110181 152C223 0.119151 0.290581 0.489884 152C248 0 0 0.068257 152C258 0.04123 0.176185 0.37407 152C264 0.04108 0.141983 0.302539 152C271 0.00786 0.096404 0.276939 152C273 0.017407 0.151249 0.338493 152C288 0.28823 0.481623 0.683161 BOBC006 0.059464 0.203115 0.396588 BOBC007 0 0 0.119467 BOBC012 0 0 0.074828 BOBC019 0 0 0.076621 BOBC023 0 0 0.112447 BOBC037 0 0 0.102516 BOBC039 0 0 0.092464 BOBC046 0 0 0.207053 BOBC049 0 0 0.055993 BOBC076 0.084266 0.243605 0.440171 194 Sample Lower limit 95% CI Hybrid Index Upper limit 95% CI BOBC084 0 0 0.076003 BOBC127 0 0 0.21199 BOBC128 0.014799 0.087033 0.238572 BOBC130 0 0 0.096036 BOBC149 0.019763 0.147619 0.342668 BOBC196 0.120675 0.317181 0.533168 BOBC198 0 0.103105 0.316278 BOBC230 0.023717 0.141591 0.321405 BOBC243 0.048937 0.165948 0.340814 CATC004 0 0 0.107374 CATC010 0.086385 0.254633 0.45814 CATC049 0 0.009359 0.16693 CATC051 0.006038 0.084118 0.256804 CATC105 0 0 0.106245 CATC115 0.099277 0.276397 0.483591 CATC119 0.237448 0.432325 0.636585 CATC124 0.049085 0.209599 0.422755 CATC135 0.105537 0.294366 0.512135 CATC145 0.153612 0.322014 0.518148 CATC158 0.108502 0.294497 0.505593 CATC159 0.04206 0.184082 0.383859 CATC168 0.153744 0.326972 0.527042 CATC172 0.360713 0.541901 0.723648 CATC176 0.027425 0.117041 0.268919 CATC179 0.182266 0.369523 0.573128 CATC183 0 0 0.08571 CATC189 0 0.067461 0.29542 GDSC056 0.291795 0.488745 0.690856 GDSC065 0.092554 0.224007 0.404764 HUNC002 0 0 0.171713 HUNC003 0.036956 0.137402 0.304285 HUNC006 0.226444 0.399493 0.588301 HUNC007 0.07045 0.195317 0.371834 HUNC009 0.280749 0.470731 0.666317 HUNC014 0.282814 0.481214 0.682191 SISC004 0.107627 0.257936 0.455074 SISC014 0.178078 0.355346 0.557794 SISC030 0.14137 0.309233 0.501687 SISC040 0.356086 0.566226 0.77432 SISC042 0.118811 0.253978 0.428405 WAMC002 0.309655 0.484122 0.663118 WAMC004 0 0.074297 0.266229 195 Sample Lower limit 95% CI Hybrid Index Upper limit 95% CI WAMC014 0.106802 0.292092 0.503433 WAMC031 0 0.051036 0.251256 WAMC036 0.041312 0.196237 0.400658 WAMC040 0 0 0.155469 WAMC054 0.034827 0.167643 0.364797 WAMC057 0.067241 0.244578 0.458567 WAMC063 0.101163 0.236751 0.416411 WAMC082 0 0 0.187056 WAMC084 0 0 0.107154 WAMC092 0 0.021512 0.154889 WAMC103 0.114417 0.260649 0.444939 WAMC114 0 0 0.116897 WAMC121 0 0 0.089098 WAMC127 0 0.025753 0.231995 WAMC128 0.009584 0.110593 0.303656 WAMC141 0.066132 0.174396 0.325955 WAMC148 0 0 0.09558 152G001 0.891268 1 1 152G002 0.582556 0.784241 0.942123 152G012 0.74665 0.940946 1 152G015 0.859403 1 1 152G018 0.814837 1 1 152G034 0.579304 0.803845 0.977303 152G035 0.585799 0.797395 0.960696 152G037 0.724972 0.952753 1 152G038 0.826736 1 1 152G040 0.882449 1 1 152G066 0.869392 1 1 152G068 0.385795 0.602523 0.818626 152G075 0.727981 0.960235 1 152G086 0.478255 0.7009 0.924138 152G093 0.931993 1 1 152G096 0.874091 1 1 152G098 0.852013 1 1 152G109 0.675388 0.912916 1 152G116 0.593441 0.816723 1 152G164 0.920002 1 1 152G199 0.929503 1 1 BOBG001 0.922129 1 1 BOBG002 0.801706 0.996334 1 BOBG003 0.830424 1 1 BOBG005 0.911736 1 1 196 Sample Lower limit 95% CI Hybrid Index Upper limit 95% CI BOBG007 0.582248 0.797163 0.964302 BOBG010 0.887584 1 1 BOBG034 0.923174 1 1 BOBG045 0.584187 0.772771 0.922413 BOBG057 0.543372 0.758394 0.956629 BOBG090 0.436498 0.653349 0.860381 BOBG094 0.556715 0.788343 0.99544 BOBG095 0.606299 0.810092 0.987354 BOBG104 0.599669 0.799819 0.95804 BOBG111 0.568403 0.791454 0.989195 BOBG114 0.492276 0.734013 0.959707 BOBG120 0.78981 0.992946 1 BOBG128 0.808458 1 1 BOBG158 0.718429 0.90766 0.993715 BOBG169 0.59672 0.817267 0.981772 BOBG174 0.818717 0.995739 1 BOBG198 0.87337 1 1 CATG013 0.563452 0.773858 0.954803 CATG038 0.620056 0.821377 0.969613 CATG073 0.510752 0.732792 0.927453 CHEG033 0.894356 1 1 CHEG048 0.838917 1 1 CHEG049 0.921617 1 1 CHEG088 0.861569 1 1 CHEG095 0.59017 0.813286 0.982705 CHEG096 0.521086 0.733629 0.91617 CHEG107 0.841466 0.971499 1 CHEG109 0.859295 0.990282 1 CHEG114 0.707317 0.900714 1 CHEG122 0.69541 0.933633 1 CRGG002 0.874063 1 1 CRGG008 0.540341 0.743466 0.922935 CRGG014 0.695741 0.892924 1 GDSG012 0.865858 1 1 HUNG002 0.547733 0.735811 0.888825 SISG003 0.829556 1 1 SISG011 0.635561 0.845318 1 SISG032 0.906714 1 1 SISG048 0.751961 0.915656 1 SISG050 0.355736 0.569317 0.787949 SISG066 0.910902 1 1 SISG067 0.905519 1 1 197 Sample Lower limit 95% CI Hybrid Index Upper limit 95% CI SISG069 0.828042 0.964182 1 SISG076 0.653263 0.899851 1 WAMG001 0.690165 0.908518 1 WAMG005 0.690977 0.876161 0.998092 WAMG008 0.825496 1 1 WAMG012 0.854275 1 1 WAMG016 0.695376 0.934704 1 WAMG020 0.793706 0.995487 1 WAMG031 0.482638 0.695667 0.885341 WAMG037 0.494283 0.702429 0.886004 WAMG038 0.638329 0.869924 1 WAMG040 0.860028 1 1 WAMG043 0.827625 1 1 WAMG050 0.707186 0.946399 1 WAMG055 0.72975 0.925781 1 WAMG062 0.462724 0.67395 0.88104 WAMG068 0.824537 1 1 WAMG075 0.917742 1 1 WAMG092 0.773307 0.932029 0.995833 WAMG096 0.852588 1 1 198 APPENDIX G: Estimated hybrid indices of plants Hybrid index calculated using package INTROGRESS using method described in Buerkle (2005). Flies with a 0.99 or higher membership in a parental type using NEWHYBRIDS used as training samples. Values of 0 correspond to I. coriacea and 1 to I. glabra. Lower limit 95% CI Hybrid Index Upper limit 95% CI P152C012 0 0 0.025698 P152C013 0 0 0.053315 P152C014 0 0.010338 0.088731 P152C031 0 0 0.043222 P152C042 0 0 0.040316 P152C077 0 0 0.033806 P152C092 0 0 0.036663 P152C099 0 0 0.038073 P152C122 0 0.004466 0.052682 P152C127 0 0 0.043644 P152C130 0 0 0.025685 P152C133 0 0 0.027589 P152C222 0 0 0.0296 P152C234 0 0 0.036493 P152C240 0 0 0.028275 P152C247 0 0 0.025766 P152C254 0 0.01984 0.08644 P152C271 0 0.042124 0.12622 P152C272 0 0 0.023759 P152C280 0 0.005776 0.057586 P152C288 0.084275 0.191218 0.312071 P152CE02 0.126972 0.219771 0.326941 P152CE06 0 0.000124 0.043281 PBOBC006 0 0 0.028814 PBOBC016 0 0 0.072876 PBOBC046 0 0 0.027086 PBOBC047 0 0 0.051491 PBOBC048 0 0 0.035279 PBOBC061 0 0 0.09251 PBOBC084 0 0 0.039025 PBOBC092 0 0 0.023988 PBOBC142 0 0 0.027247 PBOBC149 0 0 0.027793 199 Lower limit 95% CI Hybrid Index Upper limit 95% CI PBOBC181 0 0.035257 0.110599 PBOBC187 0 0.011242 0.068153 PBOBC191 0.085477 0.169217 0.269075 PBOBC198 0 0 0.026275 PBOBC228 0 0 0.034426 PBOBC240 0 0 0.026256 PBOBCE04 0 0 0.040278 PBOBCE05 0.335557 0.450678 0.569088 PCATC093 0.010444 0.120739 0.244897 PCATC115 0.176288 0.275032 0.383824 PCATC185 0 0 0.047636 PCATC197 0 0.002171 0.073857 PCATC204 0 0 0.037701 PCATC212 0 0.01814 0.088144 PCATC219 0 0 0.033301 PCATC225 0 0 0.04053 PCATC240 0 0.060716 0.15936 PCATC245 0 0.023525 0.120159 PGDSC003 0 0.001707 0.065924 PGDSC009 0 0 0.029495 PGDSC012 0 0.001237 0.061215 PGDSC024 0 0.031956 0.115365 PGDSC036 0 0.010401 0.079618 PGDSC055 0 0 0.038927 PGDSC057 0 0 0.043521 PGDSCE01 0 0.005507 0.057589 PGDSCE02 0 0 0.04712 PHUNC001 0 0.02963 0.125045 PHUNC003 0 0 0.054668 PHUNC006 0 0.048122 0.143082 PHUNC010 0 0.006221 0.090855 PHUNC012 0.194598 0.301103 0.414193 PHUNC014 0 0 0.067559 PHUNCE04 0 0 0.040135 PHUNCE06 0 0.006985 0.088297 PHUNCE08 0 0 0.045128 PSISC001 0 0 0.050524 PSISC009 0.063424 0.159493 0.271938 200 Lower limit 95% CI Hybrid Index Upper limit 95% CI PSISC010 0 0 0.053521 PSISC013 0 0 0.079916 PSISC025 0 0 0.065409 PSISC026 0 0 0.065497 PSISC028 0 0.084127 0.192921 PSISC033 0 0.007095 0.087982 PSISCE36 0.024638 0.108613 0.215233 PSISCE37 0 0.01682 0.118496 PSOPC001 0 0.009944 0.088487 PSOPC005 0.254694 0.360351 0.470751 PSOPCE01 0 0 0.057405 PSOPCE02 0 0.06609 0.1633 PSOPCE03 0 0 0.075683 PWAMC013 0 0 0.048819 PWAMC014 0 0 0.081011 PWAMC034 0 0 0.030449 PWAMC036 0 0 0.05216 PWAMC040 0 0.035807 0.118286 PWAMC046 0 0 0.032636 PWAMC057 0 0.020926 0.107268 PWAMC063 0 0 0.02808 PWAMC084 0 0 0.062606 PWAMC090 0.19029 0.292752 0.403628 PWAMC106 0 0 0.039684 PWAMC113 0 0 0.043323 PWAMC121 0 0.035198 0.107299 PWAMC123 0 0 0.042134 PWAMC128 0 0 0.065964 PWAMC141 0 0 0.028303 PWAMC144 0 0 0.025341 PWAMC148 0 0 0.024998 PWAMCE04 0 0 0.044783 PWAMCE07 0 0.015259 0.086885 P152G027 0.94886 1 1 P152G167 0.93114 0.990836 1 P152G168 0.971648 1 1 P152G172 0.944232 1 1 P152G174 0.957031 1 1 201 Lower limit 95% CI Hybrid Index Upper limit 95% CI P152G180 0.944899 1 1 P152G183 0.963427 1 1 P152G199 0.951566 1 1 P152GE01 0.966544 1 1 P152GE02 0.957848 1 1 PBOBG011 0.823666 0.931449 1 PBOBG028 0.933788 0.99176 1 PBOBG067 0 0 0.047665 PBOBG159 0.962983 1 1 PBOBG169 0.908178 0.98034 1 PBOBG170 0.957779 1 1 PBOBG174 0.920248 1 1 PBOBG182 0.909803 0.988887 1 PBOBG190 0.970665 1 1 PBOBG198 0.942747 1 1 PBOBG205 0.939187 0.996527 1 PBOBGE01 0.967177 1 1 PBOBGE17 0.956403 1 1 PCATG107 0.967214 1 1 PCATG114 0.963714 1 1 PCATG134 0.934101 0.993083 1 PCATG137 0.93544 1 1 PCATG143 0.960553 1 1 PCATG148 0.952656 1 1 PCATG151 0.964708 1 1 PCATGE09 0.950092 1 1 PCATGE17 0.9382 1 1 PCHEG003 0.955845 1 1 PCHEG033 0.959381 1 1 PCHEG047 0.933861 0.993413 1 PCHEG058 0.97114 1 1 PCHEG089 0.865035 0.955808 1 PCHEG093 0.955865 1 1 PCHEG114 0.955244 1 1 PCHEG119 0.962303 1 1 PCRGG001 0.89625 0.971309 1 PCRGG007 0.932682 1 1 PCRGG008 0.970856 1 1 202 Lower limit 95% CI Hybrid Index Upper limit 95% CI PCRGG010 0.964625 1 1 PCRGG013 0.940418 1 1 PCRGG014 0.893681 0.968683 1 PCRGG017 0.904673 0.979712 1 PCRGGE24 0.960689 1 1 PCRGGE32 0.968973 1 1 PCRGGE36 0.970409 1 1 PEAVG001 0.966078 1 1 PEAVG002 0.96704 1 1 PEAVG004 0.833854 0.931418 0.996201 PEAVGE02 0.925534 0.988188 1 PEAVGE03 0.958 1 1 PEAVGE06 0.951692 1 1 PEAVH003 0.838434 0.932911 0.995173 PEAVH004 0.964382 1 1 PEAVHE01 0.944697 1 1 PEAVHE02 0.953552 1 1 PGDSG018 0.849092 0.940017 0.993682 PGDSG020 0.943189 1 1 PGDSG021 0.880159 0.958813 1 PGDSG026 0.925581 1 1 PGDSG032 0.894918 0.979268 1 PGDSG037 0.956336 1 1 PGDSG046 0.888733 0.973004 1 PGDSGE05 0.844617 0.937768 0.998009 PGDSGE12 0.967166 1 1 PHUNG002 0.95316 1 1 PHUNGE01 0.912115 0.976066 1 PHUNGE05 0.401698 0.516045 0.630666 PHUNGE07 0.943692 1 1 PHUNGE09 0.958852 1 1 PHUNGE11 0.925399 1 1 PHUNGE14 0.952761 1 1 PHUNGE15 0.961249 1 1 PSISG006 0.95581 1 1 PSISG010 0.943579 1 1 PSISG032 0.824217 0.925274 0.998471 PSISG048 0.965583 1 1 203 Lower limit 95% CI Hybrid Index Upper limit 95% CI PSISG057 0.880786 0.968779 1 PSISG063 0.918511 1 1 PSISG076 0.953857 1 1 PSISGE16 0.959009 1 1 PSOPGE02 0.968661 1 1 PWAMG011 0.719095 0.817707 0.900909 PWAMG079 0.905637 0.975597 1 PWAMG091 0.962003 1 1 PWAMG093 0.959671 1 1 PWAMG094 0.93032 1 1 PWAMG096 0.963477 1 1 PWAMG097 0.945043 1 1 PWAMG098 0.972086 1 1 PWAMGE02 0.921292 0.988506 1 PWAMGE08 0.969113 1 1 PWAMGE15 0.867357 0.952031 1 PWAMGE19 0.956112 1 1 204 BIBLIOGRAPHY Abbott, R. J. 1992. Plant invasions, interspecific hybridization and the evolution of new plant taxa. Trends in Ecology & Evolution 7:401-405. Abrahamson, W. G., C. P. Blair, M. D. Eubanks, and S. A. Morehead. 2003. Sequential radiation of unrelated organisms: the gall fly Eurosta solidaginis and the tumbling flower beetle Mordellistena convicta. Journal of Evolutionary Biology 16:781- 789. Al-Siyabi, A. A. K., and D. J. Shetlar. 1998. Inkberry leaf miner, Phytomyza glabricola Kulp (Diptera: Agromyzidae): Life cycle in Ohio. Ohio State Extension Research Special Circular:165-199. Aldridge, G., and D. R. Campbell. 2009. Genetic and morphological patterns show variation in frequency of hybrids between Ipomopsis (Polemoniaceae) zones of sympatry. Heredity 102:257-265. Anderson, E. C. 2008. Bayesian inference of species hybrids using multilocus dominant genetic markers. Philos Trans R Soc Lond B Biol Sci 363:2841-2850. Anderson, E. C., and E. A. Thompson. 2002. A model-based method for identifying species hybrids using multilocus genetic data. Genetics 160:1217-1229. Arnold, M. L. 1997. Natural hybridization and evolution. Oxford University Press, New York. Ashman, T.-L., and M. Stanton. 1991. Seasonal variation in pollination dynamics of sexually dimorphic Sidalcea oregana ssp. spicata (Malvaceae). Ecology 72:993- 1003. Ayala, F. J., and M. Coluzzi. 2005. Chromosome speciation: Humans, Drosophila, and mosquitoes. P Natl Acad Sci USA 102:6535-6542. Baas, P. 1978. Inheritance of foliar and nodal anatomical characters in some Ilex hybrids. Botanical Journal of the Linnean Society 77:41-52. Bailey, J. K., J. A. Schweitzer, F. Ubeda, J. Koricheva, C. J. LeRoy, M. D. Madritch, B. J. Rehill, R. K. Bangert, D. G. Fischer, G. J. Allan, and T. G. Whitham. 2009. From genes to ecosystems: a synthesis of the effects of plant genetic factors across levels of organization. Philos Trans R Soc Lond B Biol Sci 364:1607-1616. Bailey, J. K., S. C. Wooley, R. L. Lindroth, and T. G. Whitham. 2006. Importance of species interactions to community heritability: a genetic basis to trophic-level interactions. Ecology Letters 9:78-85. Bandelt, H. J., P. Forster, and A. Rohl. 1999. Median-joining networks for inferring intraspecific phylogenies. Molecular Biology and Evolution 16:37-48. 205 Bangert, R. K., R. J. Turek, B. Rehill, G. M. Wimp, J. A. Schweitzer, G. J. Allan, J. K. Bailey, G. D. Martinsen, P. Keim, R. L. Lindroth, and T. G. Whitham. 2006. A genetic similarity rule determines arthropod community structure. Molecular Ecology 15:1379-1391. Barbash, D. A., J. Roote, and M. Ashburner. 2000. The Drosophila melanogaster Hybrid male rescue gene causes inviability in male and female species hybrids. Genetics 154:1747-1771. Barbour, R. C., J. M. O'Reilly-Wapstra, D. W. De Little, G. J. Jordan, D. A. Steane, J. R. Humphreys, J. K. Bailey, T. G. Whitham, and B. M. Potts. 2009. A geographic mosaic of genetic variation within a foundation tree species and its community- level consequences. Ecology 90:1762-1772. Barman, A. K., M. N. Parajulee, C. G. Sansone, C. Suh, and R. F. Medina. 2012. Geographic pattern of host-associated differentiation in Pseudatomoscelis seriatus (Reuter). Entomologia Experimentalis et Applicata 143:31-41. Barton, N. H. 2001. The role of hybridization in evolution. Molecular Ecology 10:551- 568. Bazinet, A., D. Myers, J. Fuetsch, and M. Cummings. 2007. Grid Services Base Library: A high-level, procedural application programming interface for writing Globus- based Grid services. Future Generation Computer Systems 23:517-522. Bazinet, A. L., and M. P. Cummings. 2008. The Lattice Project: a Grid research and production environment combining multiple Grid computing models. Rechenkraft.net, Marburg. Beaumont, M. A., and D. J. Balding. 2004. Identifying adaptive genetic divergence among populations from genome scans. Molecular Ecology 13:969-980. Bellusci, F., G. Pellegrino, A. M. Palermo, and A. Musacchio. 2010. Crossing barriers between the unrewarding Mediterranean orchids Serapias vomeracea and Serapias cordigera. Plant Species Biology 25:68-76. Bennuah, S. Y., T. Wang, and S. N. Aitken. 2004. Genetic analysis of the Picea sitchensis ? glauca introgression zone in British Columbia. Forest Ecology and Management 197:65-77. Bleeker, W., and H. Hurka. 2001. Introgressive hybridization in Rorippa (Brassicaceae): gene flow and its consequences in natural and anthropogenic habitats. Molecular Ecology 10:2013-2022. Block, K. 1969a. Chromosomal variation in Agromyzidae I. Phytomyza abdominalis Zett. - two incipient species and their natural hybrid. Hereditas 62:131-152. 206 Block, K. 1969b. Chromosomal variation in Agromyzidae II. Phytomyza crassiseta Zetterstedt - a parthenogenic species. Hereditas 62:357-381. Block, K. 1974. Chromosomal variation in Agromyzidae (Diptera) III. Cerodonta (Butomomyza) eucaricis Nowakowski - two semispecies or sibling species? Hereditas 78:125-140. Block, K. 1975a. Chromosomal variation in Agromyzidae (Diptera) IV. Further observations on natural hybridization between two semispecies within Phytomyza abdominalis. Hereditas 79:199-208. Block, K. 1975b. Chromosomal variation in Agromyzidae (Diptera) V. Amauromyza (Trilobomyza) flavifrons - a polymorphic species. Hereditas 80:205-218. Block, K. 1976. Chromosomal variation in Agromyzidae (Diptera) VI. Comparative chromosome studies. Hereditas 84:177-212. Bonin, A., E. Bellemain, P. Bronken Eidesen, F. Pompanon, C. Brochmann, and P. Taberlet. 2004. How to track and assess genotyping errors in population genetics studies. Molecular Ecology 13:3261-3273. Bonin, A., P. Taberlet, C. Miaud, and F. Pompanon. 2006. Explorative genome scan to detect candidate loci for adaptation along a gradient of altitude in the common frog (Rana temporaria). Molecular Biology and Evolution 23:773-783. Borge, T., K. Lindroos, P. Nadvornik, A. C. Syvanen, and G. P. Saetre. 2005. Amount of introgression in flycatcher hybrid zones reflects regional differences in pre and post-zygotic barriers to gene exchange. Journal of Evolutionary Biology 18:1416- 1424. Brewer, J. S. 1998. Patterns of plant species richness in a wet slash-pine (Pinus elliottii) savanna. Journal of the Torrey Botanical Society 125:216-224. Brockway, D. G., and C. E. Lewis. 2003. Influence of deer, cattle grazing and timber harvest on plant species diversity in a longleaf pine bluestem ecosystem. Forest Ecology and Management 175:49-69. Brooks, A. R., E. X. Nixon, and J. A. Neal. 1993. Woody vegetation of wet creek bottom communities in Eastern Texas. Castanea 58:185-196. Brown, J. M., W. G. Abrahamson, and P. A. Way. 1996. Mitochondrial DNA phylogeography of host races of the goldenrod ball gallmaker, Eurosta solidaginis (Diptera: Tephritidae). Evolution 50:777-786. Brown, K. M., L. M. Burk, L. M. Henagan, M. A. F. Noor, and R. Harrison. 2004. A test of the chromosomal rearrangement model of speciation in Drosophila pseudoobscura. Evolution 58:1856-1860. 207 Buerkle, C. A. 2005. Maximum-likelihood estimation of a hybrid index based on molecular markers. Molecular Ecology Notes 5:684-687. Burgarella, C., Z. Lorenzo, R. Jabbour-Zahab, R. Lumaret, E. Guichoux, R. J. Petit, A. Soto, and L. Gil. 2009. Detection of hybrids in nature: application to oaks (Quercus suber and Q. ilex). Heredity 102:442-452. Burgess, K. S., M. Morgan, L. Deverno, and B. C. Husband. 2005. Asymmetrical introgression between two Morus species (M. alba, M. rubra) that differ in abundance. Molecular Ecology 14:3471-3483. Bush, G. L. 1969. Sympatric host race formation and speciation in frugivorous flies of the genus Rhagoletis (Diptera: Tephritidae). Evolution 23:237-251. Campbell, D., and L. Bernatchez. 2004. Generic scan using AFLP markers as a means to assess the role of directional selection in the divergence of sympatric whitefish ecotypes. Molecular Biology and Evolution 21:945-956. Campbell, L. G., and A. A. Snow. 2007. Competition alters life history and increases the relative fecundity of crop-wild radish hybrids (Raphanus spp.). New Phytologist 173:648-660. Cane, J. H., and J. A. Payne. 1993. Regional, annual, and seasonal variation in pollinator guilds: intrinsic traits of bees (Hymenoptera: Apoidea) underlie their patterns of abundance at Vaccinium ashei (Ericaceae). Ann Entomol Soc Am 86:577-588. Carmona, D., M. J. Lajeunesse, and M. T. J. Johnson. 2011. Plant traits that predict resistance to herbivores. Functional Ecology 25:358-367. Carney, S. E., K. A. Gardner, and L. H. Rieseberg. 2000. Evolutionary changes over the fifty-year history of a hybrid population of sunflowers (Helianthus). Evolution 54:462-474. Carriere, Y., and J. N. McNeil. 1988. Observations on the mating behavior of the alfalfa blotch leafminer, Agromyza frontella (Rondani) (Diptera: Agromyzidae), and evidence of a female sex pheromone. Journal of Insect Behavior 1:291-307. Caughey, M. G. 1945. Water relations of pocosin or bog shrubs. Plant Physiol 20:671- 689. Cavalli-Sforza, L. L. 1966. Population structure and human evolution. Proceedings of the Royal Society of London. Series B, Biological Sciences 164:362-379. Charlesworth, B., J. A. Coyne, and N. Barton. 1987. The relative rates of evolution of sex chromosomes and autosomes. American Naturalist 130:113-146. 208 Chase, V. C., and P. H. Raven. 1975. Evolutionary and ecological relationships between Aquilegia formosa and A. pubescens (Ranunculaceae), two perennial plants. Evolution 29:474-486. Cho, S. W., A. Mitchell, J. C. Regier, C. Mitter, R. W. Poole, T. P. Friedlander, and S. W. Zhao. 1995. A highly conserved nuclear gene for low-level phylogenetics - Elongation Factor-1? recovers morphology-based tree for heliothine moths. Molecular Biology and Evolution 12:650-656. Choi, Y. H., S. Sertic, H. K. Kim, E. G. Wilson, F. Michopoulos, A. W. Lefeber, C. Erkelens, S. D. Prat Kricun, and R. Verpoorte. 2005. Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis. J Agric Food Chem 53:1237-1245. Clark, M. A., J. Siegrist, and P. A. Keddy. 2008. Patterns of frequency in species-rich vegetation in pine savannas: Effects of soil moisture and scale. Ecoscience 15:529-535. Clauss, M. J., S. Dietel, G. Schubert, and T. Mitchell-Olds. 2006. Glucosinolate and trichome defenses in a natural Arabidopsis lyrata population. J Chem Ecol 32:2351-2373. Coluzzi, M., A. Sabatini, A. della Torre, M. A. Di Deco, and V. Petrarca. 2002. A polytene chromosome analysis of the Anopheles gambiae species complex. Science 298:1415-1418. Cook, M. A., S. N. Ozeroff, S. M. Fitzpatrick, and B. D. Roitberg. 2011. Host-associated differentiation in reproductive behaviour of cecidomyiid midges on cranberry and blueberry. Entomologia Experimentalis et Applicata 141:8-14. Cornelissen, T., and A. Stiling. 2006. Does low nutritional quality act as a plant defence? An experimental test of the slow-growth, high-mortality hypothesis. Ecological Entomology 31:32-40. Cosse, A. A., M. G. Campbell, T. J. Glover, C. E. Linn, J. L. Todd, T. C. Baker, and W. L. Roelofs. 1995. Pheromone behavioral responses in unusual male European corn borer hybrid progeny no correlated to electrophysiological phenotypes of their pheromone-specific antennal neurons. Cellular and Molecular Life Sciences 51:809-816. Coyne, J. A. 1992. Genetics and speciation. Nature 355:511-515. Coyne, J. A., and H. A. Orr. 1989. Two rules of speciation. Pp. 180-207 in D. Otte, and J. Endler, eds. Speciation and its Consequences. Sinauer Associates, Sunderland, Mass. Coyne, J. A., and H. A. Orr. 2004. Speciation. Sinauer Associates, Inc., Sunderland, M.A. 209 Crandall, K. A., and A. R. Templeton. 1993. Empirical tests of some predictions from coalescent theory with applications to intraspecific phylogeny reconstruction. Genetics 134:959-969. Cuenoud, P., M. A. del Pero Martinez, P. A. Loizeau, R. Spichiger, S. Andrews, and J. F. Manen. 2000. Molecular phylogeny and biogeography of the genus Ilex L. (Aquifoliaceae). Annals of Botany 85:111-122. Currat, M., M. Ruedi, R. J. Petit, and L. Excoffier. 2008. The hidden side of invasions: massive introgression by local genes. Evolution 62:1908-1920. Darwin, C. 1858. On the tendency of species to form varieties; and on the perpetuation of varieties and species by natural means of selection. I. Extract from an unpublished work on species, II. Abstract of a letter from C. Darwin, Esq., to Prof. Asa Gray. Biological Journal of the Linnean Society 3:45-53. Darwin, C. 1859. On the Origin of Species by Means of Natural Selection. J. Murray, London. Davis, M. B. 1981. Quaternary history and the stability of forest communities. Pp. 132- 177 in D. C. West, H. H. Shugart, and D. B. Botkin, eds. Forest Succession. Springer-Verlag, New York. Delacourt, H. R., and P. A. Delacourt. 1984. Ice age haven for hardwoods. Natural History 93:22-25. Denno, R. F., S. Larsson, and K. L. Olmstead. 1990. Role of enemy-free space and plant quality in host-plant selection by willow beetles. Ecology 71:124-137. Dickey, A. M., and R. F. Medina. 2010. Testing host-associated differentiation in a quasi- endophage and a parthenogen on native trees. Journal of Evolutionary Biology 23:945-956. Dickinson, T. A., W. H. Parker, and R. E. Strauss. 1987. Another approach to leaf shape comparisons. Taxon 36:1-20. Diegisser, T., A. Seitz, and J. E. S. Johannesen. 2006. Phylogeographic patterns of host- race evolution in Tephritis conura (Diptera: Tephritidae). Molecular Ecology 15:681-694. Diehl, S. R., and G. L. Bush. 1984. An evolutionary and applied perspective of insect biotypes. Annual Review of Entomology 29:471-504. Donnelly, P., and S. Tavare. 1986. The ages of alleles and a coalescent. Advances in Applied Probability 18:1-19. Dres, M., and J. Mallet. 2002. Host races in plant-feeding insects and their importance in sympatric speciation. Philos T R Soc B 357:471-492. 210 Dryden, I. 2009. shapes: Statistical shape analysis. R package version 1.1-3. http://CRAN.R-project.org/package=shapes. Duncan, W. H., and M. B. Duncan. 1987. The Smithsonian Guide to Seaside Plants of the Gulf and Atlantic Coasts from Louisiana to Massachusetts, Exclusive of Lower Peninsular Florida. Smithsonian Institution Press, Washington, D.C. Dungey, H. S., B. M. Potts, T. G. Whitham, and H. F. Li. 2000. Plant genetics affects arthropod community richness and composition: evidence from a synthetic eucalypt hybrid population. Evolution 54:1938-1946. Eckhart, V. M. 1992. Spatio-temporal variation in abundance and variation in foraging behavior of the pollinators of gynodioecious Phacelia linearis (Hydrophyllaceae). Oikos 64:573-586. Edelaar, P., and C. W. Benkman. 2006. Replicated population divergence caused by localized coevolution? A test of three hypotheses in the red crossbill-lodgepole pine system. Journal of Evolutionary Biology 19:1651-1659. Egan, S. P., P. Nosil, and D. J. Funk. 2008. Selection and genomic differentiation during ecological speciation: isolating the contributions of host association via a comparative genome scan of Neochlamisus bebbianae leaf beetles. Evolution 62:1162-1181. Ehrlich, P. R., and P. H. Raven. 1964. Butterflies and plants: a study in coevolution. Evolution 18:586-608. Ellis, A. G., and S. D. Johnson. 2009. The evolution of floral variation without pollinator shifts in Gorteria diffusa (Asteraceae). American Journal of Botany 96:793-801. Ellstrand, N. C., R. Whitkus, and L. H. Rieseberg. 1996. Distribution of spontaneous plant hybrids. Proceedings of the National Academy of Sciences 93:5090-5093. Evanno, G., S. Regnaut, and J. Goudet. 2005. Detecting the number of clusters of individuals using the software structure: a simulation study. Molecular Ecology 14:2611-2620. Excoffier, L., M. Foll, and R. J. Petit. 2009. Genetic consequences of range expansions. Annual Review of Ecology, Evolution, and Systematics 40:481-501. Excoffier, L., G. Laval, and S. Schneider. 2005. Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform Online 1:47-50. Excoffier, L., P. E. Smouse, and J. M. Quattro. 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479-491. 211 Falush, D., M. Stephens, and J. K. Pritchard. 2007. Inference of population structure using multilocus genotype data: dominant markers and null alleles. Molecular Ecology Notes 7:574-578. Farrell, B. D. 1998. "Inordinate fondness" explained: why are there so many beetles? Science 281:555-559. Feder, J. L., C. A. Chilcote, and G. L. Bush. 1988. Genetic differentiation between sympatric host races of the apple maggot fly Rhagoletis pomonella. Nature 336:61-64. Feder, J. L., and P. Nosil. 2009. Chromosomal inversions and species differences: when are genes affecting adaptive divergence and reproductive isolation expected to reside within inversions? Evolution 63:3061-3075. Feder, J. L., K. Reynolds, W. Go, and E. C. Wang. 1995. Intraspecific and interspecific competition and host race formation in the apple maggot fly, Rhagoletis pomonella (Diptera, Tephritidae). Oecologia 101:416-425. Feder, J. L., J. B. Roethele, K. Filchak, J. Niedbalski, and J. Romero-Severson. 2003. Evidence for inversion polymorphism related to sympatric host race formation in the apple maggot fly, Rhagoletis pomonella. Genetics 163:939-953. Feder, J. L., X. Xie, J. Rull, S. Velez, A. Forbes, B. Leung, H. Dambroski, K. E. Filchak, and M. Aluja. 2005. Mayr, Dobzhansky, and Bush and the complexities of sympatric speciation in Rhagoletis. Proc Natl Acad Sci U S A 102 Suppl 1:6573- 6580. Felsenstein, J. 1981. Skepticism towards Santa Rosalia, or why are there so few kinds of animals? Evolution 35:124-138. Felsenstein, J. 2005. PHYLIP (Phylogeny Inference Package) version 3.6. in D. b. t. author, ed. Department of Genome Sciences, University of Washington,, Seattle. Felsenstein, J., and G. A. Churchill. 1996. A Hidden Markov Model approach to variation among sites in rate of evolution. Molecular Biology and Evolution 13:93-104. Floate, K. D., and T. G. Whitham. 1993. The "hybrid bridge" hypothesis: host shifting via plant hybrid swarms. American Naturalist 141:651-662. Foll, M., and O. Gaggiotti. 2008. A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180:977-993. Frey, J. E. 1991. Voltinism and diapause in the oligophagous leafminer Phytomyza chaerophylli (Kaltenbach) (Dipt., Agromyzidae). Journal of Applied Entomology 112:99-106. 212 Frierson, J. L. 1959. Cytotaxonomic Study of Selected Indigenous and Introduced Species of the Genus Ilex Commonly Grown in the United States. PhD Thesis. University of South Carolina, Columbia. Fritz, R. S. 1999. Resistance of hybrid plants to herbivores: genes, environment, or both? Ecology 80:382-391. Fritz, R. S., C. Moulia, and G. Newcombe. 1999. Resistance of hybrid plants and animals to herbivores, pathogens, and parasites. Annual Review of Ecology and Systematics 30:565-591. Fu, Y. X. 1997. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147:915-925. Funk, D. J. 1998. Isolating a role for natural selection in speciation: host adaptatation and sexual isolation in Neochlammisus bebbianae leaf beetles. Evolution 52:1744- 1759. Funk, D. J. 2012. Of ?host forms? and host races: terminological issues in ecological speciation. International Journal of Ecology 2012:1-8. Funk, D. J., K. E. Filchak, and J. L. Feder. 2002. Herbivorous insects: model systems for the comparative study of speciation ecology. Genetica 116:251-267. Futuyma, D. J., and G. Moreno. 1988. The evolution of ecological speciation. Annual Review of Ecology, Evolution, and Systematics 19:207-233. Galle, F. C. 1997. Hollies: the Genus Ilex. Timber Press, Portland, Oregon. Gange, A. C. 1995. Aphid performance in an alder (Alnus) hybrid zone. Ecology 76:2074-2083. Gaston, K. J., D. R. Genney, M. Thurlow, and S. E. Hartley. 2004. The geographical range structure of the holly leaf-miner. IV. Effects of variation in host-plant quality. J. Anim. Ecol. 73:911-924. Glenn, T. C. 2011. Field guide to next-generation DNA sequencers. Molecular Ecology Resources 11:759-769. Godfrey, R. K. 1988. Trees, Shrubs, and Woody Vines of Northern Florida and Adjacent Georgia and Alabama. University of Georgia Press, Athens. Golding, G. B. 1987. The detection of deleterious selection using ancestors inferred from a phylogenetic history. Genetics Research 49:71-82. Gompert, Z., and C. A. Buerkle. 2009. A powerful regression-based method for admixture mapping of isolation across the genome of hybrids. Molecular Ecology 18:1207-1224. 213 Gompert, Z., and C. A. Buerkle. 2010. introgress: a software package for mapping components of isolation in hybrids. Molecular Ecology Resources 10:378-384. Gouinguene, S. P. D., and E. Stadler. 2005. Comparison of the sensitivity of four Delia species to host and non-host plant compounds. Physiol. Entomol. 30:62-74. Gratton, C., and S. C. Welter. 1999. Does "enemy-free space" exist? Experimental host shifts of an herbivorous fly. Ecology 80:773-785. Gray, A., and M. L. Fernald. 1950. Manual of Botany; A Handbook of the Flowering Plants and Ferns of the Central and Northeastern United States and Adjacent Canada. American Book Co., New York,. Groot, A. T., A. Classen, O. Inglis, C. A. Blanco, J. Lopez, Jr., A. Teran Vargas, C. Schal, D. G. Heckel, and G. Schofl. 2011. Genetic differentiation across North America in the generalist moth Heliothis virescens and the specialist H. subflexa. Molecular Ecology 20:2676-2692. Hagan, D. L., S. Jose, M. Thetford, and K. Bohn. 2009. Production physiology of three native shrubs intercropped in a young longleaf pine plantation. Agroforestry Systems 76:283-294. Hagan, D. L., S. Jose, M. Thetford, and K. Bohn. 2010. Partitioning of applied (15)N fertilizer in a longleaf pine and native woody ornamental intercropping system. Agroforestry Systems 79:47-57. Haldane, J. B. S. 1992. Sex ratio and unisexual sterility in hybrid animals. Journal of Genetics 12:101-109. Harrison, J. K. 1998. Linking evolutionary pattern and process: the relevance of species concepts for the study of speciation. Pp. 19-31 in D. J. Howard, and S. H. Berlocher, eds. Endless Forms : Species and Speciation. Oxford University Press, New York. Harrison, R. G. 1991. Molecular changes at speciation. Annual Review of Ecology, Evolution, and Systematics 22:281-308. Hawthorne, D. J. 2001. AFLP-based genetic linkage map of the Colorado potato beetle Leptinotarsa decemlineata: sex chromosomes and a pyrethroid-resistance candidate gene. Genetics 158:695-700. Hawthorne, D. J., and S. Via. 2001. Genetic linkage of ecological specialization and reproductive isolation in pea aphids. Nature 412:904-907. Herrera, C. M. 1988. Variation in mutualisms: the spatio-temporal mosaic of a pollinator assemblage. Biological Journal of the Linnean Society 35:95-125. 214 Hill, W. G. 1974. Estimation of linkage disequilibrium in randomly mating populations. Heredity 33:229-239. Hoberg, E. P., and D. R. Brooks. 2008. A macroevolutionary mosaic: episodic host- switching, geographical colonization and diversification in complex host-parasite systems. Journal of Biogeography 35:1533-1550. Hochwender, C. G., and R. S. Fritz. 2004. Plant genetic differences influence herbivore community structure: evidence from a hybrid willow system. Oecologia 138:547- 557. Hoffmann, A. A., and L. H. Rieseberg. 2008. Revisiting the impact of inversions in evolution: from population genetic markers to drivers of adaptive shifts and speciation? Annual Review of Ecology, Evolution, and Systematics 39:21-42. Hohenlohe, P. A., P. C. Phillips, and W. A. Cresko. 2010. Using population genomics to detect selection in natural populations: key concepts and methodological considerations. International Journal of Plant Sciences 171:1059-1071. Hrsak, V., S. Brana, Z. Sedlar, and I. Pejic. 2011. Morphometric and molecular (RAPD) analysis of six Serapias taxa from Croatia. Biologia 66:55-63. Huang, Z. S., Y. J. Ji, and D. X. Zhang. 2008. Haplotype reconstruction for scnp DNA: a consensus vote approach with extensive sequence data from populations of the migratory locust (Locusta migratoria). Molecular Ecology 17:1930-1947. Huang, Z. S., and D. X. Zhang. 2010. CVhaplot: a consensus tool for statistical haplotyping. Molecular Ecology Resources 10:1066-1070. Huberty, A. F., and R. F. Denno. 2006. Consequences of nitrogen and phosphorus limitation for the performance of two planthoppers with divergent life-history strategies. Oecologia 149:444-455. Hudson, R. R., and N. L. Kaplan. 1985. Statistical properties of the number of recombination events in the history of a sample of DNA sequences. Genetics 111:147-164. Hunter, M. D., and J. N. McNeil. 1997. Host-plant quality influences diapause and voltinism in a polyphagous insect herbivore. Ecology 78:977-986. Hunter, M. D., G. C. Varley, and G. R. Gradwell. 1997. Estimating the relative roles of top-down and bottom-up forces on insect herbivore populations: A classic study?revisited. Proceedings of the National Academy of Sciences 94:9176-9181. Ibrahim, M. H., H. Z. Jaafar, A. Rahmat, and Z. A. Rahman. 2011. Effects of nitrogen fertilization on synthesis of primary and secondary metabolites in three varieties of kacip fatimah (Labisia pumila Blume). International Journal of Molecular Sciences 12:5238-5254. 215 Ishihara, M., and T. Ohgushi. 2006. Reproductive inactivity and prolonged developmental time induced by seasonal decline in host plant quality in the willow leaf beetle Plagiodera versicolora (Coleoptera: Chrysomelidae). Environmental Entomology 35:524-530. Ito, K. 2003. Effect of leaf condition on diapause induction of a Kanzawa spider mite Tetranychus kanzawai Kishida (Acari: Tetranychidae) population on tea plants. Applied Entomology and Zoology 28:559-563. Ito, K., and Y. Saito. 2006. Effects of host-plant species on diapause induction of the Kanzawa spider mite, Tetranychus kanzawai. Entomologia Experimentalis et Applicata 121:177-184. Jakobsson, M., and N. A. Rosenberg. 2007. CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801-1806. Janz, N., and S. Nylin. 2008. The oscillation hypothesis of host-plant range and speciation. Pp. 203-215 in K. J. Tilmon, ed. Specialization, Speciation, and Radiation : the Evolutionary Biology of Herbivorous Insects. University of California Press, Berkeley. Janz, N., S. Nylin, and N. Wahlberg. 2006. Diversity begets diversity: host expansions and the diversification of plant-feeding insects. BMC Evolutionary Biology 6:4. Johnson, M. T. J. 2008. Bottom-up effects of plant genotype on aphids, ants, and predators. Ecology 89:145-154. Johnson, M. T. J., and A. A. Agrawal. 2005. Plant genotype and environment interact to shape a diverse arthropod community on evening primrose (Oenothera biennis) Ecology 86:874-885. Johnson, M. T. J., A. A. Agrawal, J. L. Maron, and J. P. Salminen. 2009. Heritability, covariation and natural selection on 24 traits of common evening primrose (Oenothera biennis) from a field experiment. Journal of Evolutionary Biology 22:1295-1307. Joung, Y. H., D. Picton, J. O. Park, and M. S. Roh. 2011. Molecular evidence for the interspecific hybrid origin of Ilex ? wandoensis. Horticulture, Environment, and Biotechnology 52:516-523. Joyce, A. L., R. E. Hunt, J. S. Bernal, and S. B. Vinson. 2008. Substrate influences mating success and transmission of courtship vibrations for the parasitoid Cotesia marginiventris. Entomologia Experimentalis et Applicata 127:39-47. Kainulainen, P., J. Holopainen, V. Palomaki, and T. Holopainen. 1996. Effects of nitrogren fertilization on secondary chemistry and ectomycorrhizal state of Scots pine seedlings and on growth of grey pine aphid. J Chem Ecol 22:617-636. 216 Kaneshiro, K. Y. 1976. Ethological isolation and phylogeny in the Planitibia subgroup of Hawaiian Drosophila. Evolution 30:740-745. Kaneshiro, K. Y. 1980. Sexual isolation, speciation, and the direction of evolution. Evolution 34:437-444. Kanmiya, K. 2006. Communication by vibratory signals in Diptera. Pp. 381-396 in S. Drosopoulos, and M. F. Claridge, eds. Insect Sounds and Communication: Physiology, Behaviour, Ecology, and Evolution. Taylor and Francis, Boca Raton. Kelley, S. T., and B. D. Farrell. 1998. Is specialization a dead end? The phylogeny of host use in Dendroctonus bark beetles (Scolytidae). Evolution 52:1731-1743. Kempf, F., T. Boulinier, T. De Meeus, C. Arnathau, and K. D. McCoy. 2009. Recent evolution of host-associated divergence in the seabird tick Ixodes uriae. Molecular Ecology 18:4450-4462. Kishino, H., and M. Hasegawa. 1989. Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in hominoidea. J Mol Evol 29:170-179. Kolaczan, C. R., S. B. Heard, K. A. Segraves, D. M. Althoff, and J. D. Nason. 2009. Spatial and genetic structure of host-associated differentiation in the parasitoid Copidosoma gelechiae. Journal of Evolutionary Biology 22:1275-1283. Kores, P. J., M. Molvray, and S. P. Darwin. 1993. Morphometric variation in three species of Cyrtostylis (Orchidaceae). Systematic Botany 18:274-282. Korkina, L. G. 2007. Phenylpropanoids as naturally occurring antioxidants: from plant defense to human health. Cellular and Molecular Biology (Noisy-le-Grand, France) 53:15-25. Kornet, D. J., and H. Turner. 1999. Coding polymorphism for phylogeny reconstruction. Systematic Biology 48:365-379. Kulp, L. A. 1968. The taxonomic status of dipterous holly leaf miners (Diptera: Agromyzidae). University of Maryland Agriculture Experiment Station Bulletin A-155:1-42. Lance, R. 2004. Woody plants of the Southeastern United States : a Winter Guide. University of Georgia Press, Athens. Lee, N., S. Yeau, J. Park, and M. Roh. 2006. Molecular evidence for hybridization of Ilex x wandoensis (Aquifoliaceae) by RAPD analysis. Journal of Plant Biology 49:491-497. Levin, D. A. 1971. Plant phenolics: an ecological perspective. American Naturalist 105:157-181. 217 Lewontin, R. C., and J. Krakauer. 1973. Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics 74:175-195. Lexer, C., J. Joseph, M. van Loo, G. Prenner, B. Heinze, M. W. Chase, and D. Kirkup. 2009. The use of digital image-based morphometrics to study the phenotypic mosaic in taxa with porous genomes. Taxon 58:349-364. Librado, P., and J. Rozas. 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25:1451-1452. Loizeau, P. A., G. Barriera, J.-F. Manen, and O. Broennimann. 2005. Towards an understanding of the distribution of Ilex L. (Aquifoliaceae) on a world-wide scale. Pp. 501-520 in I. Friis, and H. Balslev, eds. Plant Diversity and Complexity Patterns. Local, Regional, and Global Dimensions. Biologiske Skrifter. Lonsdale, O., and S. J. Scheffer. 2011. Revision of Nearctic holly leafminers in the genus Phytomyza (Diptera: Agromyzidae), including descriptions of four new species. Ann Entomol Soc Am 104:1183-1206. Luikart, G., P. R. England, D. Tallmon, S. Jordan, and P. Taberlet. 2003. The power and promise of population genomics: from genotyping to genome typing. Nature Reviews Genetics 4:981-994. Lundell, C. L. 1961. Flora of Texas. Texas Research Foundation, Renner,. MacKay, R., S. Reid, R. William, and N. M. Hill. 2010. Genetic evidence of introgressive invasion of the globally imperiled Scirpus longii by the weedy Scirpus cyperinus (Cyperaceae) in Nova Scotia. Rhodora 112:34-57. Mallet, J. 2005. Hybridization as an invasion of the genome. Trends in Ecology & Evolution 20:229-237. Manen, J. F. 2004. Are both sympatric species Ilex perado and Ilex canariensis secretly hybridizing? Indication from nuclear markers collected in Tenerife. BMC Evolutionary Biology 4:46. Manen, J. F., G. Barriera, P. A. Loizeau, and Y. Naciri. 2010. The history of extant Ilex species (Aquifoliaceae): evidence of hybridization within a Miocene radiation. Molecular Phylogenetics and Evolution 57:961-977. Manen, J. F., M. C. Boulter, and Y. Naciri-Graven. 2002. The complex history of the genus (Aquifoliaceae): evidence from the comparison of plastid and nuclear DNA sequences and from fossil data. Plant Systematics and Evolution 235:79-98. Marschner, H. 1995. Mineral nutrition of higher plants. Academic Press, London. Marsden, C. D., Y. Lee, C. C. Nieman, M. R. Sanford, J. Dinis, C. Martins, A. Rodrigues, A. J. Cornel, and G. C. Lanzaro. 2011. Asymmetric introgression between the M 218 and S forms of the malaria vector, Anopheles gambiae, maintains divergence despite extensive hybridization. Molecular Ecology 20:4983-4994. Martin, J. T. 1964. Role of cuticle in the defense against plant disease. Annual Review of Phytopathology 2:81-100. Masly, J. P., and D. C. Presgraves. 2007. High-resolution genome-wide dissection of the two rules of speciation in Drosophila. Plos Biol 5:e243. Mayr, E. 1963. Animal Species and Evolution. Belknap Press of Harvard University Press, Cambridge,. McNab, W. H., and M. B. Edwards Jr. 1980. Climatic factors related to the range of saw- palmetto (Serenoa repens (Bartr.) Small). American Midland Naturalist 103:204- 208. Melo, G. A., M. M. Shimizu, and P. Mazzafera. 2006. Polyphenoloxidase activity in coffee leaves and its role in resistance against the coffee leaf miner and coffee leaf rust. Phytochemistry 67:277-285. Mitchell, M. S., K. S. Karriker, E. J. Jones, and R. A. Lancia. 1995. Small mammal communities associated with pine plantation management of pocosins. The Journal of Wildlife Management 59:875-881. Mitter, C., B. Farrell, and D. J. Futuyma. 1991. Phylogenetic studies of insect-plant interactions: insights into the genesis of diversity. Trends in Ecology & Evolution 6:290-293. Mitter, C., B. D. Farrell, and B. Wiegmann. 1988. The phylogenetic study of adaptive zones: has phytophagy promoted insect diversification? American Naturalist 132:107-128. Moeller, D. 2005. Pollinator community structure and sources of spatial variation in plant?pollinator interactions in Clarkia xantiana ssp. xantiana. Oecologia 142:28- 37. Moeller, D. A. 2006. Geographic structure of pollinator communities, reproductive assurance, and the evolution of self-pollination. Ecology 87:1510-1522. Mohlenbrock, R. H. 1976. Woody plants of the Ocala National Forest, Florida. Castanea 41:309-319. Morgan, K., Y. M. Linton, P. Somboon, P. Saikia, V. Dev, D. Socheat, and C. Walton. 2010. Inter-specific gene flow dynamics during the Pleistocene-dated speciation of forest-dependent mosquitoes in Southeast Asia. Molecular Ecology 19:2269- 2285. 219 Muller, H. J. 1942. Isolating mechanisms, evolution, and temperature. Biological Symposia 6:71-125. Murphy, S. M. 2004. Enemy-free space maintains swallowtail butterfly host shift. . Proceedings of the National Academy of Sciences 101:18048-18052. Myers, D. S., A. L. Bazinet, and M. P. Cummings. 2008. Expanding the Reach of Grid Computing: Combining Globus- and BOINC-Based Systems. John Wiley & Sons, New York. Nason, J. D., N. C. Ellstrand, and M. L. Arnold. 1992. Patterns of hybridization and introgression in populations of oaks, manzanitas, and irises. American Journal of Botany 79:101-111. Nei, M. 1987. Molecular Evolutionary Genetics. Columbia University Press, New York. Nell, M., M. Votsch, H. Vierheilig, S. Steinkellner, K. Zitterl-Eglseer, C. Franz, and J. Novak. 2009. Effect of phosphorus uptake on growth and secondary metabolites of garden sage (Salvia officinalis L.). J Sci Food Agric 89:1090-1096. Nishida, R., S. Schulz, C. S. Kim, H. Fukami, Y. Kuwahara, K. Honda, and N. Hayashi. 1996. Male sex pheromone of a giant danaine butterfly, Idea leuconoe. J Chem Ecol 22:949-972. Noor, M. A. F., K. L. Grams, L. A. Bertucci, and J. Reiland. 2001. Chromosomal inversions and the reproductive isolation of species. Proceedings of the National Academy of Sciences 98:12084-12088. Nosil, P. 2002. Transition rates between specialization and generalization in phytophagous insects. Evolution 56:1701-1706. Nosil, P. 2008. Ernst Mayr and the integration of geographic and ecological factors in speciation. Biological Journal of the Linnean Society 95:26-46. Nosil, P., S. P. Egan, and D. J. Funk. 2008. Heterogeneous genomic differentiation between walking-stick ecotypes: "isolation by adaptation" and multiple roles for divergent selection. Evolution 62:316-336. Nosil, P., D. J. Funk, and D. Ortiz-Barrientos. 2009. Divergent selection and heterogeneous genomic divergence. Molecular Ecology 18:375-402. Ohta, A. T. 1978. Ethological isolation and phylogeny in the grimshawi species complex of Hawaiian Drosophila. Evolution 32:485-492. Oksanen, J., F. G. Blanchet, R. Kindt, P. Legendre, R. B. O'Hara, G. L. Simpson, P. Solymos, M. H. H. Stevens, and H. Wagner. 2010 vegan: Community Ecology Package. R package version 1.17-2. http://CRAN.R-project.org/package=vegan. 220 Olson, D. M., A. M. Cortesero, G. C. Rains, T. Potter, and W. J. Lewis. 2009. Nitrogen and water affect direct and indirect plant systemic induced defense in cotton. Biological Control 49:239-244. Orians, C. M. 2000. The effects of hybridization in plants on secondary chemistry: implications for the ecology and evolution of plant-herbivore interactions. American Journal of Botany 87:1749-1756. Ota, A. K., and T. Nishida. 1966. A biological study of Phytobia (Amauromyza) maculosa (Diptera: Agromyzidae). Ann Entomol Soc Am 59:902-911. Phadnis, N., and H. A. Orr. 2009. A single gene causes both male sterility and segregation distortion in Drosophila hybrids. Science 323:376-379. Phillips, P. A., and M. M. Barnes. 1975. Host race formation among sympatric apple, walnut and plum populations of Cydia pomonella. Ann Entomol Soc Am 68:1053-1060. Pike, N. 2011. Using false discovery rates for multiple comparisons in ecology and evolution. Methods in Ecology and Evolution 2:278-282. Polzin, T., and S. V. Daneschmand. 2003. On Steiner trees and minimum spanning trees in hypergraphs. Operations Research Letters 31:12-20. Pompanon, F., A. Bonin, E. Bellemain, and P. Taberlet. 2005. Genotyping errors: causes, consequences and solutions. Nature Reviews Genetics 6:847-859. Potter, D. A. 1992. Abundance and mortality of a specialist leafminer in response to experimental shading and fertilization of American holly. Oecologia 91:14-22. Powell, M., V. Savolainen, P. Cu?noud, J. F. Manen, and S. Andrews. 2000. The mountain holly (Nemopanthus mucronatus: Aquifoliaceae) revisited with molecular data. Kew Bulletin 55:341-347. Price, P. W. 2008. Adaptive radiation: phylogenetic constraints and ecological consequences. Pp. 174-187 in K. J. Tilmon, ed. Specialization, Speciation, and Radiation : the Evolutionary Biology of Herbivorous Insects. University of California Press, Berkeley. Primack, R. B., and J. A. Silander. 1975. Measuring the importance of different pollinators to plants. Nature 277:294-297. Pritchard, J. K., M. Stephens, and P. Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics 155:945-959. R Development Core Team. 2010. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 221 Ramirez-Rodriguez, R., E. Tovar-Sanchez, J. Jimenez Ramirez, K. Vega Flores, and V. Rodriguez. 2011. Introgressive hybridization between Brahea dulcis and Brahea nitida Arecaceae) in Mexico: evidence from morphological and PCR-RAPD patterns. Botany 89:545-557. Rice, W. R., and E. E. Hostert. 1993. Laboratory experiments on speciation - what have we learned in 40 years? Evolution 47:1637-1653. Richardson, C. J. 1983. Pocosins: vanishing wastelands or valuable wetlands? Bioscience 33:626-633. Richardson, C. J. 1991. Pocosins: an ecological perspective. Wetlands 11:335-354. Rieseberg, L. H. 1997. Hybrid origins of plant species. Annual Review of Ecology and Systematics 28:359-389. Rieseberg, L. H., M. A. Archer, and R. K. Wayne. 1999. Transgressive segregation, adaptation, and speciation. Heredity 83:363-372. Rieseberg, L. H., S. J. Baird, and K. A. Gardner. 2000. Hybridization, introgression, and linkage evolution. Plant Molecular Biology 42:205-224. Rieseberg, L. H., and S. E. Carney. 1998. Plant hybridization. New Phytologist 140:599- 624. Rieseberg, L. H., and N. C. Ellstrand. 1993. What can molecular and morphological markers tell us about plant hybridization? Critical Reviews in Plant Sciences 12:213-241. Rieseberg, L. H., and J. F. Wendel. 1993. Introgression and its consequences in plants. Pp. 70-109 in R. Harrison, ed. Hybrid Zones and the Evolutionary Process. Oxford University Press, New York. Robert K. Godfrey Herbarium, F. S. U. 2012. Online Database. Biology Department. http://herbarium.bio.fsu.edu/database.php. Rohlf, F. J. 2005. TpsDig Version 2.04. Department of Ecology and Evolution, State University of New York at Stony Brook, New York. Ronquist, F., and J. Liljeblad. 2001. Evolution of the gall wasp-host plant association. Evolution 55:2503-2522. Rose, C. W., R. J. Millwood, H. S. Moon, M. R. Rao, M. D. Halfhill, P. L. Raymer, S. I. Warwick, H. Al-Ahmad, J. Gressel, and C. N. Stewart. 2009. Genetic load and transgenic mitigating genes in transgenic Brassica rapa (field mustard) x Brassica napus (oilseed rape) hybrid populations. BMC Biotechnology 9:93. 222 Rosenberg, N. A. 2004. distruct: a program for the graphical display of population structure. Molecular Ecology Notes 4:137-138. Rundle, H. D., L. Nagel, J. Wenrick Boughman, and D. Schluter. 2000. Natural selection and parallel speciation in sympatric sticklebacks. Science 287:306-308. Scheffer, S. J. 2002. New host record, new range information, and a new pattern of voltinism: Possible host races within the holly leafminer Phytomyza glabricola Kulp (Diptera : Agromyzidae). P Entomol Soc Wash 104:571-575. Scheffer, S. J., and D. J. Hawthorne. 2007. Molecular evidence of host-associated genetic divergence in the holly leafminer Phytomyza glabricola (Diptera : Agromyzidae): apparent discordance among marker systems. Molecular Ecology 16:2627-2637. Scheffer, S. J., and B. M. Wiegmann. 2000. Molecular phylogenetics of the holly leaf miners (Diptera : Agromyzidae : Phytomyza): Species limits, speciation, and dietary specialization. Molecular Phylogenetics and Evolution 17:244-255. Schemske, D. W., and H. D. Bradshaw, Jr. 1999. Pollinator preference and the evolution of floral traits in monkeyflowers (Mimulus). P Natl Acad Sci USA 96:11910- 11915. Schemske, D. W., and C. C. Horvitz. 1984. Variation among floral visitors in pollination ability: a precondition for mutualism specialization. Science 225:519-521. Schemske, D. W., and C. C. Horvitz. 1990. Spatiotemporal variation in insect mutualists in a neotropical herb. Ecology 71:1085-1097. Schluter, D. 2000. The Ecology of Adaptive Radiation. Oxford University Press, Oxford. Schluter, D. 2001. Ecology and the origin of species. Trends in Ecology & Evolution 16:372-380. Scutareanu, P., and H. D. Loxdale. 2006. Ratio of nutrient and minerals to defensive compounds indicative of plant quality and tolerance to herbivory in pear trees. Journal of Plant Nutrition 29:629-642. Seehausen, O. 2004. Hybridization and adaptive radiation. Trends in Ecology & Evolution 19:198-207. Selbach-Schnadelbach, A., S. S. Cavalli, J.-F. Manen, G. C. Coelho, and T. T. De Souza- Chies. 2009. New information for Ilex phylogenetics based on the plastid psbA- trnH intergenic spacer (Aquifoliaceae). Botanical Journal of the Linnean Society 159:182-193. Setoguchi, H., and I. Watanabe. 2000. Intersectional gene flow between insular endemics of Ilex (Aquifoliaceae) on the Bonin Islands and the Ryukyu Islands. American Journal of Botany 87:793-810. 223 Simpson, G. G. 1949. Tempo and Mode in Evolution. Columbia University Press, New York. Simpson, G. G. 1953. The Major Features of Evolution. Columbia University Press, New York. Smadja, C., J. Galindo, and R. Butlin. 2008. Hitching a lift on the road to speciation. Molecular Ecology 17:4177-4180. Smith, D. S., J. K. Bailey, S. M. Shuster, and T. G. Whitham. 2011. A geographic mosaic of trophic interactions and selection: trees, aphids and birds. Journal of Evolutionary Biology 24:422-429. Smith, F. H., K. C. Beeson, and W. E. Price. 1956. Chemical composition of herbage browsed by deer in two wildlife management areas. The Journal of Wildlife Management 20:359-367. Smith, J. M. 1966. Sympatric speciation. American Naturalist 100:637-650. Sokal, R. R., and F. J. Rohlf. 1981. Biometry. W. H. Freeman and Company, San Francisco. Spencer, K. A. 1990. Host Specialization in the World Agromyzidae (Diptera). Kluwer Academic Publishers, Dordrecht, The Netherlands. Spencer, K. A., G. C. Steyskal, and United States. Agricultural Research Service. 1986. Manual of the Agromyzidae (Diptera) of the United States. U.S. Dept. of Agriculture, Washington, D.C. Steinbauer, M. J., D. J. Kriticos, Z. Lukacs, and A. R. Clarke. 2004. Modelling a forest lepidopteran: phenological plasticity determines voltinism which influences population dynamics. Forest Ecology and Management 198:117-131. Stinchcombe, J. R., and H. E. Hoekstra. 2008. Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits. Heredity 100:158-170. Stireman, J. O. 2005. The evolution of generalization? Parasitoid flies and the perils of inferring host range evolution from phylogenies. Journal of Evolutionary Biology 18:325-336. Stireman, J. O., J. D. Nason, and S. B. Heard. 2005. Host-associated genetic differentiation in phytophagous insects: General phenomenon or isolated exceptions? Evidence from a goldenrod-insect community. Evolution 59:2573- 2587. 224 Stireman, J. O., J. D. Nason, S. B. Heard, and J. M. Seehawer. 2006. Cascading host- associated genetic differentiation in parasitoids of phytophagous insects. P Roy Soc B-Biol Sci 273:523-530. Strong, D. R., J. H. Lawton, and R. Southwood. 1984. Insects on Plants : Community Patterns and Mechanisms. Harvard University Press, Cambridge, Mass. Tajima, F. 1983. Evolutionary relationship of DNA sequences in finite populations. Genetics 105:437-460. Takagi, S., and T. Miyashita. 2008. Host plant quality influences diapause induction of Byasa alcinous (Lepidoptera: Papilionidae). Ann Entomol Soc Am 101:392-396. Thompson, J. N. 1988. Variation in interspecific interactions. Annual Review of Ecology and Systematics 19:65-87. Thompson, J. N. 2005. The Geographic Mosaic of Coevolution. University of Chicago Press, Chicago. Thompson, J. N. 2009. The coevolving web of life. American Naturalist 173:125-140. Tillman, J. A., S. J. Seybold, R. A. Jurenka, and G. J. Blomquist. 1999. Insect pheromones - an overview of biosynthesis and endocrine regulation. Insect Biochemistry and Molecular Biology 29:481-514. Travis, S., J. Baggs, and J. Maschinski. 2008. Disentangling the role of hybridization in the evolution of the endangered Arizona cliffrose (Purshia subintegra; Rosaceae): a molecular and morphological analysis. Conservation Genetics 9:1183-1194. Turelli, M., N. H. Barton, and J. A. Coyne. 2001. Theory and speciation. Trends in Ecology & Evolution 16:330-343. Turelli, M., and H. A. Orr. 1995. The dominance theory of Haldane's rule. Genetics 140:389-402. USDA, N. 2012. The PLANTS Database (http://plants.usda.gov). National Plant Data Team, Greensboro, NC. Vaha, J. P., and C. R. Primmer. 2006. Efficiency of model-based Bayesian methods for detecting hybrid individuals under different hybridization scenarios and with different numbers of loci. Molecular Ecology 15:63-72. van Asch, M., and M. E. Visser. 2007. Phenology of forest caterpillars and their host trees: the importance of synchrony. Annual Review of Entomology 52:37-55. van Loo, M., J. A. Joseph, B. Heinze, M. F. Fay, and C. Lexer. 2008. Clonality and spatial genetic structure in Populus x canescens and its sympatric backcross parent P. alba in a Central European hybrid zone. New Phytol 177:506-516. 225 Vekemans, X., T. Beauwens, M. Lemaire, and I. Roldan-Ruiz. 2002. Data from amplified fragment length polymorphism (AFLP) markers show indication of size homoplasy and of a relationship between degree of homoplasy and fragment size. Molecular Ecology 11:139-151. Venables, W. N., and B. D. Ripley. 2002. Modern Applied Statistics with S. Springer, New York. Vereecken, N. J., S. Cozzolino, and F. P. Schiestl. 2010. Hybrid floral scent novelty drives pollinator shift in sexually deceptive orchids. BMC Evolutionary Biology 10:103. Via, S. 1999. Reproductive isolation between sympatric races of pea aphids. I. Gene flow restriction and habitat choice. Evolution 53:1446-1457. Via, S. 2001. Sympatric speciation in animals: the ugly duckling grows up. Trends in Ecology & Evolution 16:381-390. Via, S. 2002. The ecological genetics of speciation. American Naturalist 159:S1-S7. Via, S., and J. West. 2008. The genetic mosaic suggests a new role for hitchhiking in ecological speciation. Molecular Ecology 17:4334-4345. Vitalis, R., K. Dawson, and P. Boursot. 2001. Interpretation of variation across marker loci as evidence of selection. Genetics 158:1811-1823. Vos, P., R. Hogers, M. Bleeker, M. Reijans, T. van de Lee, M. Hornes, A. Frijters, J. Pot, J. Peleman, M. Kuiper, and et al. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23:4407-4414. Vriesendorp, B., and F. T. Bakker. 2005. Reconstructing patterns of reticulate evolution in angiosperms: what can we do? Taxon 54:593-604. Wallace, A. R. 1858. On the tendency of species to form varieties; and on the perpetuation of varieties and species by natural means of selection. III. On the tendency of varieties to depart indefinitely from the original type. Biological Journal of the Linnean Society 3:53-62. Wallace, A. R. 1876. The Geographical Distribution of Animals. Macmillan, London. Walsh, B. 1864. On phytophagic varieties and phytophagic species. Proceedings of the Entomological Society of Philadelphia 3:403-430. Waring, G. L., W. G. Abrahamson, and D. J. Howard. 1990. Genetic differentiation among host-associated populations of the gallmaker Eurosta solidaginis (Diptera, Tephritidae). Evolution 44:1648-1655. 226 Watano, Y., A. Kanai, and N. Tani. 2004. Genetic structure of hybrid zones between Pinus pumila and P. parviflora var. pentaphylla (Pinaceae) revealed by molecular hybrid index analysis. American Journal of Botany 91:65-72. Weintraub, J. D., J. H. Lawton, and M. J. Scoble. 1995. Lithinine moths on ferns - a phylogenetic study of insect-plant interactions. Biological Journal of the Linnean Society 55:239-250. Wheat, C. W., H. Vogel, U. Wittstock, M. F. Braby, D. Underwood, and T. Mitchell- Olds. 2007. The genetic basis of a plant-insect coevolutionary key innovation. P Natl Acad Sci USA 104:20427-20431. White, T. C. R. 1993. The inadequate environment : nitrogen and the abundance of animals. Springer-Verlag, Berlin ; New York. Whitham, T. G. 1989. Plant hybrid zones as sinks for pests. Science 244:1490-1493. Whitham, T. G., G. D. Martinsen, K. D. Floate, H. S. Dungey, B. M. Potts, and P. Keim. 1999. Plant hybrid zones affect biodiversity: tools for a genetic-based understanding of community structure. Ecology 80:416-428. Whitham, T. G., P. A. Morrow, and B. M. Potts. 1994. Plant hybrid zones as centers of biodiversity: the herbivore community of two endemic Tasmanian eucalypts. Oecologia 97:481-490. Whitney, K. D., R. A. Randell, and L. H. Rieseberg. 2006. Adaptive introgression of herbivore resistance traits in the weedy sunflower Helianthus annuus. American Naturalist 167:794-807. Wicker-Thomas, C. 2007. Pheromonal communication involved in courtship behavior in Diptera. Journal of Insect Physiology 53:1089-1100. Wilbur, R. B., and N. L. Christensen. 1983. Effects of fire on nutrient availability in a North Carolina coastal plain pocosin. American Midland Naturalist 110:54-61. Williams, J. H., W. J. Boecklen, and D. J. Howard. 2001. Reproductive processes in two oak (Quercus) contact zones with different levels of hybridization. Heredity 87:680-690. Wimp, G. M., G. D. Martinsen, K. D. Floate, R. K. Bangert, and T. G. Whitham. 2005. Plant genetic determinants of arthropod community structure and diversity. Evolution 59:61. Winkler, I. S., and C. Mitter. 2008. The phylogenetic dimension of insect-plant interactions: a review of recent evidence. Pp. 240-266 in K. J. Tilmon, ed. Specialization, Speciation, and Radiation : the Evolutionary Biology of Herbivorous Insects. University of California Press, Berkeley. 227 Winkler, I. S., C. Mitter, and S. J. Scheffer. 2009a. Repeated climate-linked host shifts have promoted diversification in a temperate clade of leaf-mining flies. P Natl Acad Sci USA 106:18103-18108. Winkler, I. S., S. J. Scheffer, and C. Mitter. 2009b. Molecular phylogeny and systematics of leaf-mining flies (Diptera: Agromyzidae): delimitation of Phytomyza Fall?n sensu lato and included species groups, with new insights on morphological and host-use evolution. Syst Entomol 34:260-292. Winter, T. R., and M. Rostas. 2010. Nitrogen deficiency affects bottom-up cascade without disrupting indirect plant defense. J Chem Ecol 36:642-651. Wittbrodt, J., D. Adam, B. Malitschek, W. Maueler, F. Raulf, A. Telling, S. M. Robertson, and M. Schartl. 1989. Novel putative receptor tyrosine kinase encoded by the melanoma-inducing Tu locus in Xiphophorus. Nature 341. Wu, C. I. 2001. The genic view of the process of speciation. Journal of Evolutionary Biology 14:851-865. Wu, C. I., and A. W. Davis. 1993. Evolution of postmating reproductive isolation: the composite nature of Haldane's rule and its genetic basis. American Naturalist 142:187-212. Wu, C. I., N. A. Johnson, and M. F. Palopoli. 1996. Haldane's rule and its legacy: Why are there so many sterile males? Trends in Ecology & Evolution 11:281-284. Xu, S., P. M. Schl?ter, G. Scopece, H. Breitkopf, K. Gross, S. Cozzolino, and F. P. Schiestl. 2011. Floral isolatioin is the main reproductive barrier among closely related sexually deceptive orchids. Evolution 65:2606-2620. Yang, B. Z., H. Zhao, H. R. Kranzler, and J. Gelernter. 2005. Practical population group assignment with selected informative markers: characteristics and properties of Bayesian clustering via STRUCTURE. Genet Epidemiol 28:302-312. Yoder, J. B., E. Clancey, S. Des Roches, J. M. Eastman, L. Gentry, W. Godsoe, T. J. Hagey, D. Jochimsen, B. P. Oswald, J. Robertson, B. A. Sarver, J. J. Schenk, S. F. Spear, and L. J. Harmon. 2010. Ecological opportunity and the origin of adaptive radiations. Journal of Evolutionary Biology 23:1581-1596. Zalucki, M. P., A. R. Clarke, and S. B. Malcolm. 2002. Ecology and behavior of first instar larval Lepidoptera. Annual Review of Entomology 47:361-393. Zitari, A., G. Scopece, A. N. Helal, A. Widmer, and S. Cozzolino. 2012. Is floral divergence sufficient to maintain species boundaries upon secondary contact in Mediterranean food-deceptive orchids? Heredity 108:219-228.