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Forest biomonitoring, biosecurity and DNA barcoding deWaard, Jeremy Ryan 2010

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FOREST BIOMONITORING, BIOSECURITY AND DNA BARCODING  by  Jeremy Ryan deWaard  B.Sc., The University of Guelph, 2000 M.Sc., The University of Guelph, 2004  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY  in  The Faculty of Graduate Studies  (Forestry)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  DECEMBER 2010  ©Jeremy Ryan deWaard, 2010  ii Abstract   The economic, social and biological value of our forests makes their sustainability essential to our well-being. To ensure their long-term health, it is critical to regularly and effectively monitor their inhabitants, as well as to detect non-indigenous species early and accurately.  These programs rely on the precise diagnosis of species, which can be complicated for terrestrial arthropods by sizeable trap samples, damaged specimens, immature life stages and incomplete taxonomy.  The recent advent of DNA barcoding, a technique that differentiates species using sequence variation in a standard gene region, shows tremendous promise for circumventing these obstacles. This dissertation evaluates the integration of barcoding into forest arthropod biomonitoring and biosurveillance programs with several investigations of nocturnal moths (Lepidoptera) in British Columbia, Canada.  Barcode reference libraries are constructed for looper moths (Geometridae) and Lymantria (Erebidae) tussock moths, and are determined to successfully discriminate species in over 93% and 97% of cases, respectively.  The libraries demonstrate how barcoding might enhance biosurveillance programs by flagging two new records for geometrid moths, and by successfully diagnosing 32 intercepted tussock moth specimens. These two libraries, and a multi-gene phylogeny constructed for Geometridae, are used to conduct faunal inventories in modified forest systems, and investigate the influence of disturbance on three levels of moth diversity— species, genetic, and phylogenetic. A first level inventory of Stanley Park, Vancouver, produces a preliminary list of 190 species, the detection of four new exotic species, and the discovery of two potentially cryptic species.  Surveys conducted across several harvest treatments at two silvicultural research forests display no evidence of increased diversity at intermediate disturbance levels, but do reveal a correlation between species and genetic diversity.  And lastly, three levels of moth diversity are estimated in ponderosa pine systems that differ widely in attack by Dendroctonus bark beetles, and demonstrate a negative association between species diversity and tree mortality.  In combination, all projects suggest that DNA barcoding provides several advantages over traditional biosurveillance and biomonitoring, including the ability to rapidly sort specimens, a reduction in specialist time, the detection of species at low density, and the ability to appraise multiple levels of diversity.   iii Preface   Nearly all of my thesis chapters were a product of collaborative research with contributions from several colleagues.  In all cases, I was involved in the conception and design of the projects, performed the majority of the fieldwork, completed nearly all the lab work, analyzed the data, and wrote the chapters with input from co-authors.  More details are provided for specific chapters: Chapter 2:  A version of this chapter is in press. deWaard, J.R., Hebert, P.D.N., and Humble, L.M. (2011).  A comprehensive DNA barcode library for the looper moths (Lepidoptera: Geometridae) of British Columbia, Canada. PLoS ONE.  In press.  Jeremy deWaard conceived and designed the study, performed the museum and lab work, analyzed the data, and wrote the manuscript with input from Paul Hebert and Leland Humble. Chapter 3: A version of this chapter has been published. deWaard, J.R., Mitchell, A., Keena, M.A., Gopurenko, D., Boykin, L.M., Armstrong, K.F., Pogue, M.G., Lima, J., Floyd, R., Hanner, R.H. and Humble, L.M. (2010). Towards a global barcode library for Lymantria (Lepidoptera: Lymantriinae) tussock moths of biosecurity concern.  PLoS ONE 5: e14280. Jeremy deWaard, Andrew Mitchell, Robert Hanner and Leland Humble conceived and designed the experiments; Jeremy deWaard, David Gopurenko, Jaoa Lima and Leland Humble performed the experiments; Jeremy deWaard, Andrew Mitchell, David Gopurenko, Jaoa Lima and Leland Humble analyzed the data; Jeremy deWaard, Andrew Mitchell, Melody Keena,  iv David Gopurenko, Laura Boykin, Karen Armstrong, Michael Pogue, Jaoa Lima, Robin Floyd, Robert Hanner, and Leland Humble contributed reagents, materials, and analysis tools; and Jeremy deWaard wrote the paper with input from Andrew Mitchell, Melody Keena, David Gopurenko, Laura Boykin, Robin Floyd, and Leland Humble. Chapter 4: A version of this article will be submitted for publication.  deWaard, J.R., Mitter, C., Hausmann, A., and Humble, L.M. The ‘barcode approach’ to combining molecular datasets: Reconstructing the phylogeny of North America’s Geometridae as an example.  Jeremy deWaard, Charlie Mitter, and Axel Hausmann conceived and designed the study and provided specimens; Jeremy deWaard performed the museum and lab work, analyzed the data, and wrote the manuscript with input from Leland Humble. Chapter 5: A version of this chapter has been published. deWaard, J.R., Schmidt, B.C., Anweiler, G.G., and Humble, L.M. (2008). First Canadian records of Lampropteryx suffumata ([Denis & Schiffermüller], 1775) (Geometridae: Larentiinae). Journal of the Entomological Society of BC. 105: 19–25. Jeremy deWaard conceived the study; Jeremy deWaard, Chris Schmidt, and Gary Anweiler performed the museum and lab work; Jeremy deWaard analyzed the data and wrote the manuscript with input from Chris Schmidt, Gary Anweiler and Leland Humble. Chapter 6: A version of this chapter has been published. deWaard, J.R., Schmidt, B.C.S., and Humble, L.M.  (2010).  DNA barcoding flags the first  v North American records of a Eurasian moth, Eupithecia pusillata (Denis & Schiffermüller, 1775) (Lepidoptera: Geometridae). Journal of the Entomological Society of BC. 107: 1–7. Jeremy deWaard and Leland Humble conceived and designed the study, performed the museum and lab work, and analyzed the data.  Jeremy deWaard wrote the manuscript with input from Chris Schmidt and Leland Humble. Chapter 7: A version of this chapter has been published. deWaard, J.R., Landry, J.-F., Schmidt, B.C., Derhousoff, J., McLean, J.A. and Humble, L.M. (2009). In the dark in a large urban park: DNA barcodes illuminate cryptic and introduced moth species.  Biodiversity and Conservation 18: 3825– 3839.  John McLean, Leland Humble and Jeremy deWaard conceived and designed the study; Jennifer Derhousoff and John McLean performed the fieldwork; Jeremy deWaard performed the lab work and analyzed the data; Jeremy deWaard, Jean-Francois Landry and Chris Schmidt performed the museum work; Jeremy deWaard wrote the manuscript with input from Jean-Francois Landry, Chris Schmidt, John McLean, and Leland Humble. Chapter 8: A version of this article will be submitted for publication. deWaard, J.R., Landry, J.-F., and Humble, L.M.  Effect of harvest type on three levels of moth diversity in research forests of British Columbia. Jeremy deWaard conceived and designed the study, performed the lab work, and analyzed the data; Jeremy deWaard and Jean-Francois Landry did the museum work; Jeremy deWaard wrote the manuscript with input from Leland Humble.  vi Chapter 9: A version of this article will be submitted for publication. deWaard, J.R., Vyse, A., and Humble, L.M.  Influence of a native pest outbreak on the moth diversity of British Columbia’s ponderosa pine forests. Jeremy deWaard conceived and designed the study, performed the museum and lab work, analyzed the data, and wrote the manuscript with input from Leland Humble.  Alan Vyse provided access to the experimental sites and mensuration data. No ethics approval was required for this research.  vii Table of contents   Abstract ................................................................................................................ ii	
   Preface ................................................................................................................ iii	
   Table of contents...............................................................................................vii	
   List of tables ........................................................................................................x	
   List of figures......................................................................................................xi	
   Acknowledgements..........................................................................................xiii	
   1 	
   Introduction...................................................................................................1	
   1.1	
   Forest health and DNA barcoding........................................................................ 1	
   1.2	
   Research objectives and summary of chapters ................................................... 3	
   2	
   A comprehensive DNA barcode library for the looper moths (Lepidoptera: Geometridae) of British Columbia, Canada ..............................8	
   2.1	
   Introduction .......................................................................................................... 8	
   2.2	
   Materials and methods....................................................................................... 11	
   2.2.1	
   Sampling ..................................................................................................... 11	
   2.2.2	
   DNA analysis............................................................................................... 13	
   2.2.3	
   Data analysis............................................................................................... 13	
   2.3	
   Results and discussion ...................................................................................... 14	
   3	
   Towards a global barcode library for Lymantria (Lepidoptera: Lymantriinae) tussock moths of biosecurity concern...................................22	
   3.1	
   Introduction ........................................................................................................ 23	
   3.2	
   Materials and methods....................................................................................... 26	
   3.3	
   Results ............................................................................................................... 29	
   3.4	
   Discussion.......................................................................................................... 33	
   3.5	
   Conclusion ......................................................................................................... 36	
   4	
   The ‘barcode approach’ to combining molecular datasets: Reconstructing the phylogeny of North America’s Geometridae as an example ..............................................................................................................44	
   4.1	
   Introduction ........................................................................................................ 44	
   4.2	
   Materials and methods....................................................................................... 48	
   4.2.1	
   Taxon sampling........................................................................................... 48	
   4.2.2	
   Gene sampling ............................................................................................ 49	
   4.2.3	
   DNA analysis and data matrix construction ................................................ 49	
   4.2.4	
   Phylogenetic analysis.................................................................................. 51	
   4.3	
   Results and discussion ...................................................................................... 53	
   4.3.1	
   Phylogenetic analysis: contributions, conflict and congruence ................... 53	
   4.3.2	
   Strategies for combining data with large datasets ...................................... 56	
   4.3.3	
   Phylogenetic relationships of North America’s Geometridae ...................... 59	
   5	
   First Canadian records of Lampropteryx suffumata ([Denis & Schiffermüller], 1775) (Geometridae: Larentiinae) .........................................69	
    viii 5.1	
   Introduction ........................................................................................................ 69	
   5.2	
   Materials and methods....................................................................................... 70	
   5.3	
   Results ............................................................................................................... 71	
   5.4	
   Discussion.......................................................................................................... 74	
   6	
   DNA barcoding flags the first North American records of a Eurasian moth, Eupithecia pusillata (Denis & Schiffermüller, 1775) (Lepidoptera: Geometridae) .....................................................................................................80	
   6.1	
   Introduction ........................................................................................................ 80	
   6.2	
   Materials and methods....................................................................................... 81	
   6.3	
   Results ............................................................................................................... 83	
   6.4	
   Discussion.......................................................................................................... 86	
   7	
   In the dark in a large urban park: DNA barcodes illuminate cryptic and introduced moth species..................................................................................91	
   7.1	
   Introduction ........................................................................................................ 91	
   7.2	
   Materials and methods....................................................................................... 93	
   7.3	
   Results ............................................................................................................... 96	
   7.4	
   Discussion.......................................................................................................... 99	
   7.4.1	
   Barcode recovery and success ................................................................... 99	
   7.4.2	
   Inventory progress .................................................................................... 101	
   7.4.3	
   Highlights of the nocturnal lepidopteran fauna of Stanley Park ................ 102	
   7.4.4	
   Conclusions............................................................................................... 104	
   8	
   Effect of harvest type on three levels of moth diversity in research forests of British Columbia ............................................................................113	
   8.1	
   Introduction ...................................................................................................... 113	
   8.2	
   Materials and methods..................................................................................... 117	
   8.2.1	
   Description of experimental sites .............................................................. 117	
   8.2.2	
   Moth sampling........................................................................................... 119	
   8.2.3	
   DNA analysis............................................................................................. 120	
   8.2.4	
   Data analysis............................................................................................. 121	
   8.3	
   Results ............................................................................................................. 124	
   8.4	
   Discussion........................................................................................................ 128	
   8.4.1	
   DNA barcoding for inventorying and monitoring ....................................... 128	
   8.4.2	
   Inventories of two British Columbia research forests ................................ 131	
   8.4.3	
   Effect of harvest type on moth diversity .................................................... 132	
   8.4.4	
   Interplay of three levels of moth diversity.................................................. 134	
   9	
   Influence of a native pest outbreak on the moth diversity of British Columbia’s ponderosa pine forests ..............................................................145	
   9.1	
   Introduction ...................................................................................................... 145	
   9.2	
   Materials and methods..................................................................................... 148	
   9.2.1	
   Experimental sites and sampling .............................................................. 148	
   9.2.2	
   DNA barcode and data analysis................................................................ 149	
   9.3	
   Results ............................................................................................................. 154	
   9.4	
   Discussion........................................................................................................ 158	
   9.4.1	
   Completion of two macro-moth inventories............................................... 158	
   9.4.2	
   Effect of pine beetle outbreak on moth diversity ....................................... 160	
   10	
   Conclusions .............................................................................................173	
   10.1	
   Overall analysis.............................................................................................. 173	
    ix 10.2	
   Strengths and limitations................................................................................ 174	
   10.3	
   Potential applications ..................................................................................... 177	
   10.4	
   Future research directions ............................................................................. 179	
   10.5	
   Concluding statement .................................................................................... 182	
   References .......................................................................................................184	
   Appendices ......................................................................................................214	
   Appendix A: Supplementary material for Chapter 2.................................................. 214	
   Appendix B: Supplementary figure for Chapter 2. .................................................... 230	
   Appendix C: Supplementary table for Chapter 3. ..................................................... 254	
   Appendix D: Supplementary figure for Chapter 3. .................................................... 277	
   Appendix E: Supplementary table for Chapter 4....................................................... 282	
   Appendix F: Supplementary table for Chapter 4. ...................................................... 289	
   Appendix G: Supplementary table for Chapter 7. ..................................................... 290	
   Appendix H: Supplementary figure for Chapter 8. .................................................... 296	
   Appendix I: Supplementary table for Chapter 8. ....................................................... 297	
   Appendix J: Supplementary table for Chapter 8. ...................................................... 306	
   Appendix K: Supplementary figure for Chapter 9. .................................................... 312	
   Appendix L: Supplementary table for Chapter 9. ...................................................... 313	
   Appendix M: Supplementary table for Chapter 9. ..................................................... 318	
       x List of tables   Table 2.1 Geometrid species not distinguishable by DNA barcodes. .................18	
   Table 2.2 Geometrid species with high intraspecific COI variation. ....................19	
   Table 3.1 Assignment of random and surveillance individuals to species. .........37	
   Table 4.1 The recovery and bootstrap support for ten selected clades using different partitions of data.............................................................................61	
   Table 4.2 The recovery and bootstrap support for ten selected clades following ‘partition addition bootstrap alteration’ (PABA) tests. ...................................62	
   Table 4.3 The recovery and bootstrap support for ten selected clades using the six approaches to combining datasets evaluated in the analysis.................63	
   Table 7.1  Descriptions for four introduced moth species discovered in Stanley Park, Vancouver, Canada in 2007. ............................................................105	
   Table 8.1 Summary of moths from each collection site.....................................136	
   Table 8.2 Moth diversity and abundance totals for the eight block types..........138	
   Table 9.1 Summary of macro-moths from the two collection localities. ............163	
   Table 9.2 Summary of estimated macro-moth diversity at each collection site. 165	
   Table 9.3 Abundance and sampling of 14 macro-moth species known to feed on ponderosa pine as larvae in British Columbia. ...........................................166	
   Table 9.4 Summary of biological and physical attributes of eight collection sites. ...................................................................................................................167	
     xi List of figures   Figure 2.1 Combined histograms of pairwise Kimura 2-parameter (K2P) sequence variation. ......................................................................................20	
   Figure 2.2 The relationship between mean intra-specific divergence and the number of individuals analyzed. ...................................................................21	
   Figure 3.1  Collection of specimens through a pheromone-based gypsy moth surveillance program....................................................................................38	
   Figure 3.2 Barcode region of the cytochrome oxidase I (COI) gene. ..................39	
   Figure 3.3 Maximum likelihood tree for 36 species of Lymantria. .......................40	
   Figure 3.4 Combined histograms of pairwise Kimura 2-Parameter (K2P) sequence variation. ......................................................................................41	
   Figure 3.5 Neighbour-joining tree of the gypsy moth Lymantria dispar. ..............42	
   Figure 3.6  Simulated gel electrophoresis for two restriction fragment length polymorphism assays...................................................................................43	
   Figure 4.1 Phylogenies proposed for the Geometridae by recent studies. .........64	
   Figure 4.2 Strategy for taxon and gene sampling. ..............................................65	
   Figure 4.3 Best-scoring maximum likelihood tree constructed with the complete data set of 176 taxa and 11 gene fragments................................................66	
   Figure 4.4 Best-scoring maximum likelihood tree constructed with the reduced data set of 68 taxa and 11 gene fragments..................................................68	
   Figure 5.1  Neighbour-joining tree of Lampropteryx suffumata and related species. ........................................................................................................77	
   Figure 5.2 Adult male of Lampropteryx suffumata. .............................................78	
   Figure 5.3 Distribution of Lampropteryx suffumata in North America..................79	
   Figure 6.1   Neighbour-joining tree of Eupithecia pusillata and two closely related species, E. niphadophilata and E. interruptofasciata. ..................................89	
   Figure 6.2   Morphology of Eupithecia pusillata. .................................................90	
   Figure 7.1  Neighbour-joining tree of the nocturnal Lepidoptera collected in Stanley Park, Vancouver, Canada in 2007. ...............................................106	
   Figure 7.2  Distance summary of the 925 COI barcodes generated for the Stanley Park moth specimens....................................................................111	
   Figure 7.3 Species richness and inventory completeness estimates. ...............112	
   Figure 8.1 Experimental sites. ...........................................................................139	
   Figure 8.2 Combined histograms of Kimura 2-Parameter (K2P) pairwise sequence divergence for a) Date Creek and b) Sicamous Creek. .............140	
   Figure 8.3 Species accumulation curves for a) Date Creek, b) Sicamous Creek. ...................................................................................................................141	
   Figure 8.4 Estimated species accumulation curves of the four block types in a) Date Creek, b) Sicamous Creek. ...............................................................142	
   Figure 8.5 Plots of three levels of diversity for the four block types. .................143	
   Figure 8.6 The strength of association between levels of diversity. ..................144	
   Figure 9.1 Location of field collection sites in south-central British Columbia. ..168	
    xii Figure 9.2 Combined histograms of Kimura 2-Parameter (K2P) pairwise sequence divergence for a) Kamloops and b) S. Okanagan. ....................169	
   Figure 9.3 Species accumulation curves for a) Kamloops and b) S. Okanagan. ...................................................................................................................170	
   Figure 9.4  Species accumulation curves for the eight sites in a) Kamloops and b) S. Okanagan. .............................................................................................171	
   Figure 9.5  Plots of diversity for the 8 sites the eight sites in Kamloops and S. Okanagan...................................................................................................172	
      xiii Acknowledgements   This dissertation would not have been possible without the financial support provided by the following agencies, organizations, and institutions: - Natural Sciences and Engineering Research Council of Canada - Forest Investment Account - Royal British Columbia Museum - Pacific Forestry Centre - Genome Canada - Canadian Barcode of Life Network - Ontario Genomics Institute - University of British Columbia - UBC Faculty of Forestry - Ministry of Forests and Range - Canadian Food and Inspection Agency - Vancouver Parks and Recreation I am also very grateful to the numerous curators, collection managers, fellow reearchers, and others who kindly provided access to specimens or samples, and in many cases, assistance and guidance as well: - Claudia Copley, Rob Cannings, and Kelly Sendall (RBCM) - Axel Hausmann (Zoological State Collection Munich) - Charlie and Kim Mitter (University of Maryland) - Karen Needham (UBCZ) - Gary Anweiler, Danny Shpeley, and Felix Sperling (UASM), - Jean-François Landry, Chris Schmidt, and Don Lafontaine (CNC) - Alex Borisenko (BIOUG) - Greg Pohl (NFRC) - Rich Zack (WSU-JEC)  xiv - Frank Merickel (WFBARR) - Patricia Gentili-Poole (USNM) - Chris Schmidt and Bruce Gill (Canadian Food Inspection Agency) - Scott Miller (Smithsonian Institution) - Alexander Schintlmeister (Dresden) - Paul W. Schaefer (retired, USDA) - Paul Opler, Gary McDonald, and Richard Wilson - Marko Mutanen (University of Oulu) I was very fortunate to receive other assistance, in many different forms, from a variety of colleagues and I thank them for that: - Kim Mitter (University of Maryland) - Allison Shaver (Agriculture and Agri-Food Canada) - Stephanie Kirk, Sujeevan Ratnasingham, Evgeny Zakharov, Natalia Ivanova and other staff at the Canadian Centre for DNA Barcoding - Jane Seed, Sava Barudzija, and Gurp Thandi (Natural Resources Canada, Canadian Forest Service) - Jason Dombroskie and Lisa Lumley (University of Alberta) - Doug Steventon (BC-MOFR) - Jenny Heron (BC-MOE)  I would like to acknowledge my co-authors of several chapters—I have learned immensely from them, and their help and collaboration vastly improved my dissertation: - Jean-François Landry and Chris Schmidt (CNC) - Axel Hausmann (Zoological State Collection, Munich) - Charlie Mitter (University of Maryland) - Gary Anweiler (UASM) - Leland Humble (Natural Resources Canada, Canadian Forest Service)  xv - Paul Hebert, Jaoa Lima, Robin Floyd, and Bob Hanner (University of Guelph) - John McLean and Jennifer Derhousoff (UBC) - Andrew Mitchell (Australian Museum) - Melody Keena (United States Department of Agriculture) - David Gopurenko (Wagga Wagga Agricultural Institute) - Laura Boykin and Karen Armstrong (Bio-Protection Research Centre) - Michael Pogue (USNM) - Alan Vyse (BC-MOFR) I am also grateful to my supervisors and committee members who provided invaluable support and guidance throughout my four years: - Yousry El-Kassaby - John McLean - Leland Humble  And finally, I am forever indebted to my family and friends for their support and encouragement.  My parents, and more recently, my soon to be in-laws, have all stood behind me in my seemingly never-ending scholastic pursuits.  And last but most significantly, I am tremendously grateful to my partner Stephanie for her unwaivering, generous, and patient support, without which, none of this would have been possible.      1 1  Introduction   1.1 Forest health and DNA barcoding The economic, social and biological value of our forests makes their sustainability essential to our well-being.  To ensure their long-term health, it is critical to regularly and effectively monitor forest ecosystems, particularly when disturbed, to prevent or mitigate events that threaten their sustainability.  Forest disturbances including fire, windthrow, native pest outbreaks, logging and cattle grazing, are frequent events and even beneficial in many instances (Oliver 1981; Kimmins 1996; Franklin et al. 2002).  Some disturbances on the other hand, should be avoided at all costs, such as the establishment of invasive species, particularly those known to impart damage elsewhere and are consequently regulated.  But for all types of disturbance, an understanding of their processes and consequences is vital to guarantee the long-term provision of services from forest ecosystems. While satellite-based remote sensing has revolutionized our capability to monitor disturbances and appraise forest biodiversity at larger spatial scales (e.g. Kerr and Ostrovsky 2003), we remain limited below the ecosystem level.  Here our knowledge rests primarily on studies of vertebrates, plants and other ‘indicator’ species (Andelman and Fagan 2000), while the bulk of forest inhabitants, terrestrial arthropods, is understudied or ignored.  This is due in a large part to several roadblocks that inhibit two critical steps in biodiversity monitoring and surveillance projects—specimen sorting and species  2 identification.  Sizeable trap samples, damaged specimens, immature life stages and a lack of taxonomic resources and expertise severely hinder our ability to efficiently and accurately sort and diagnose forest arthropods (Smith et al. 2005, 2009; Caesar et al. 2006; Hajibabaei et al. 2007; Smith and Fisher 2009). Fortunately, the recent advent of DNA barcoding may provide a valuable tool to circumvent these obstacles and facilitate monitoring of forest arthropods, including the appraisal of disturbance events and the surveillance of non- indigenous species. DNA barcoding uses the sequence variation in a short, standardized DNA fragment (Hebert et al. 2003a) to identify organisms to species (or higher taxonomic category) by comparing test sequences against a reference library. Proof of principle studies have established a 658 base pair segment of the mitochondrial gene cytochrome c oxidase subunit 1 (COI) as the standard region for animals, and this has proven effective at differentiating species in a wide range of taxa (see Hebert et al. 2003b; Vogler and Monaghan 2007; Waugh 2007; Frezal and Leblois 2008; Mitchell 2008; Floyd et al. 2009).  The applications of barcoding are broad, ranging from monitoring the illegal trade of bushmeat (Eaton et al. 2010) to seafood authenticity testing (Wong and Hanner 2008) and gut content analysis (Clare et al. 2009) to quality control in laboratory experiments (Bely and Weisblat 2006).  Despite few prior investigations (e.g. Armstrong and Ball 2005; Smith et al. 2005; Floyd et al. 2010), forest biomonitoring and biosurveillance are disciplines that could potentially benefit greatly by incorporating this innovative approach.  In particular, the application of  3 DNA barcoding to detecting and monitoring anthropogenic disturbances to forest ecosystems, such as the invasion of non-indigenous species or silviculture practices, and monitoring natural modifications, such as native pest outbreaks, could possibly transform the field.  1.2 Research objectives and summary of chapters My dissertation aims to comprehensively examine the application of DNA barcoding to forest arthropod biomonitoring and biosurveillance.  This investigation uses an ecologically dominant and economically important component of nearly all forest ecosystems, the Lepidoptera (moths and butterflies), and is conducted in several forest settings in British Columbia, Canada. It will not only test the efficacy of DNA barcodes for rapidly and accurately diagnosing species in a hyper-diverse assemblage, but also evaluate its utility for detecting invasive species, combining datasets in phylogenetic reconstruction, generating regional and local faunal checklists, and assessing multiple levels of diversity in disturbed forest systems.  Several useful tools will be constructed in the process, including two reference barcode libraries, four community phylogenies, one regional checklist, and five local species inventories. The data chapters to follow are independent projects written as manuscripts for publication.  Each one examines a distinct element of the overall research theme, but redundancy is unavoidable in, for instance, introductory  4 discussions and their review of the literature.  Furthermore, in isolation, the chapters might seem unrelated and eclectic.  I hope the summary of chapters below, as well as a brief synopsis to open each chapter, will help readers keep track of how each chapter contributes to the overarching research objective.  The thesis can be roughly divided into three sections: the first three chapters involve the development and evaluation of tools; the middle two chapters describe interesting discoveries made in the development of tools and illustrate their utility; and the final three data chapters employ the tools for generating preliminary species inventories and exploring the effects of disturbance on multiple levels of moth diversity. Chapter 2 is the first of three chapters that evaluate the application of DNA barcoding to biodiversity health monitoring and biosurveillance, while simultaneously developing tools employed in later chapters.  Here I construct a comprehensive reference library for the looper moths (Geometridae) of British Columbia, which present a challenging case for species discrimination via DNA barcoding due to their considerable diversity and limited taxonomic treatment.  In addition to assessing the efficacy of this library to diagnose species, a regional checklist of the geometrid fauna is presented.  Geometrid moths are typically the first or second most species-rich and abundant family in temperate forest inventories, and as such, this library will be critical to facilitate species identifications in the last 3 data chapters. In Chapter 3, I similarly construct and evaluate a reference barcode library, in this case, for the tussock moth genus Lymantria L. (Erebidae:  5 Lymantriinae) that among other significant world wide forestry pests, includes the gypsy moth.   I test the utility of DNA barcoding as a diagnostic method for this group, both for species/subspecies assignment and for determination of geographic provenance of populations. Chapter 4 develops a necessary component of estimating phylogenetic diversity (Faith 1992) — a phylogenetic tree with reliable branch lengths.  Using the DNA barcode region as an ‘adhesive’, I combine a portion of the large LepTree dataset (Regier et al. 2009) with a newly generated matrix with expanded taxonomic coverage, to elucidate the higher relationships of North America’s Geometridae.  In Chapters 8 and 9, this phylogeny will be combined with previous working hypotheses on the interrelationships of Lepidoptera to form a backbone phylogeny.   The construction of community phylogenies will be constrained by this backbone phylogeny, and will provide the topology and branch lengths required for the estimation of phylogenetic diversity. In Chapters 5 and 6, I present new records for two species that were flagged by DNA barcoding during the construction of reference libraries.  The first Canadian records of the holarctic Lampropteryx suffumata (Denis & Schiffermüller) and first North American records of the Eurasian Eupithecia pusillata (Denis & Schiffermüller) were detected and are diagnosed here.  These two cases demonstrate how barcoding can enhance the construction of regional inventories and aid in routine biosurveillance and forest insect surveys to increase the rate of detection of non-indigenous species.  6 Chapter 7 is the first of three chapters that employ the tools developed in earlier chapters to conduct faunal inventories in disturbed forest systems.  Here I perform a survey of post-windstorm Stanley Park, using DNA barcoding for the rough sorting of all material and for tentative species identifications.   The result is a preliminary park checklist for nocturnal Lepidoptera, which includes four new introductions and two potential cryptic species. I evaluate the assistance that barcoding presents for faunal inventories, from reducing specialist time to facilitating the detection of native and exotic species at low density. In Chapter 8, I utilize the barcode library and molecular phylogeny generated in earlier chapters to explore the effect of harvest type on three levels of moth diversity.  Experiments are conducted at two silvicultural research forests with similar harvest treatments that span the continuum of forest modification imposed by silviculture, from unmodified primary forest to clear-cut stands. Species, genetic and phylogenetic diversity will be compared across treatments and used to test hypotheses on the effects on diversity of intermediate levels of disturbance (Connell 1978) and the association of different levels of diversity following disturbance (Vellend 2003). Chapter 9 investigates the effects of the recent mountain pine beetle outbreak on the moth diversity of British Columbia’s ponderosa pine forests.  As with the previous chapter, barcode libraries and molecular phylogenies permit the estimation of three levels of moth diversity, and are employed at sites that differ widely in attack by Dendroctonus bark beetles.  I test hypotheses concerning  7 forest biodiversity and its response to perturbation, while conducting faunal inventories for two more locations. In the tenth and final chapter, I provide an overall analysis and synthesis of my dissertation research and draw some conclusions in reference to my research objectives.  In addition, I discuss the strengths and limitations of my research, propose some potential applications, and suggest some possible avenues for future work on the topic.         8 2 A comprehensive DNA barcode library for the looper moths (Lepidoptera: Geometridae) of British Columbia, Canada1   Synopsis: The construction and evaluation of comprehensive reference libraries is essential to foster the development of DNA barcoding as a tool for monitoring biodiversity and detecting invasive species.  This is the first of three chapters that establish tools to be used later in the dissertation for exploring the effects of disturbance on moth diversity.  Here I build and test a barcode library for the geometrid moths, a diverse and important component of temperate forest ecosystems.  2.1 Introduction  For monitoring biodiversity and detecting invasive species, knowing what species exist in a given location is paramount.  However, the subtle morphological characters that separate closely related species often demand expert interpretation (e.g. Packer et al. 2009), forcing studies to either limit their taxonomic scope, or to only identify specimens to a higher taxonomic category (e.g. family, genus).  DNA barcoding can circumvent these limits by transforming the often lengthy chore of identifying specimens to a rapid, accurate and  1 A version of this chapter is in press. deWaard, J.R., Hebert, P.D.N., and Humble, L.M. (2011).  A comprehensive DNA barcode library for the looper moths (Lepidoptera: Geometridae) of British Columbia, Canada. PLoS ONE.  In press.  9 unbiased task (Armstrong and Ball 2005; Janzen et al. 2005; Smith et al. 2005). For the identification of arthropods in particular, where high diversity and low access to taxonomic expertise complicate the job, DNA barcoding has proven capable of the task in numerous groups, including collembolans (Hogg and Hebert 2004), spiders (Barrett and Hebert 2005), tephritid fruit flies (Armstrong and Ball 2005), mosquitoes (Cywinska et al. 2006), tachinid flies (Smith et al. 2006), aphids (Foottit et al. 2008), ants (Smith and Fisher 2009), bees (Sheffield et al. 2009), wood wasps (Wilson and Schiff 2010), black flies (Rivera and Currie 2009), mayflies, stoneflies and caddisflies (Zhou et al. 2009).  Lepidoptera has seen the most studies of barcode performance to date, and results suggest barcodes permit correct identification in >90% of previously recognized taxa (Hajibabaei et al. 2006a, Hebert et al. 2010, Lukhtanov et al. 2009, Chapter 7).  To continue the development of DNA barcoding as a tool for biodiversity monitoring and invasive species detection, it is necessary to both construct complete reference libraries and assess their efficacy for discriminating species. The taxa for which barcoding delivers results that are discordant with current taxonomy are of particular interest — they generally warrant further investigation as they may contain overlooked species (Smith et al. 2007, Elias-Gutierrez and Valdez-Moreno 2008, Gibbs 2009), species that are hybridizing, cases of synonymy or situations that require a secondary barcode marker for species diagnosis.  It is also worthwhile to explore the effect of sampling density on estimates of genetic variation, both in terms of number of samples (Hubert et al.  10 2008, Kerr et al. 2009) and their geographic coverage (Hebert et al. 2010, Lukhtanov et al. 2009).  The loopers or inchworm moths (Lepidoptera: Geometridae) are one of the largest insect families, composed of about 23,000 species worldwide (Minet and Scoble 1999; Scoble and Hausmann 2007) and approximately 1400 in North America (Ferguson 1983).    They are an abundant, diverse component of most forest ecosystems — this, along with their generally weak flight ability and low propensity to migrate (Nieminen 1986, Doak 2000), make them excellent indicators of environmental quality (Scoble 1992). A large proportion of the species are also important defoliators, including native species such as the fall cankerworm (Alsophila pometaria (Harris)) and invasive pests such as the winter moth (Operophtera brumata (L.)). Because most larvae and adults possess cryptic coloration, they are a notoriously tough group in which to discriminate species.  To further complicate matters, most North American geometrid genera are in need of revision. This latter gap is now being addressed through an ‘integrative approach’ (Padial et al. 2010) that employs DNA barcodes to accelerate the revisionary process in both North America (e.g. Ferris and Schmidt 2010, Pohl et al. 2010) and elsewhere (e.g. Hausmann et al. 2009, Huemer and Hausmann 2009).  The geometrids of British Columbia (BC), Canada present a challenging case for DNA barcoding. There are presently 349 species known from the province — a large fauna with varying levels of taxonomic maturity (see Appendix A for species list and discussion). In this study, I assemble  11 representatives of nearly all these species, from BC and the surrounding region, and from geographically separated populations, to examine patterns of barcode divergence. I test the hypothesis that the barcode region is able to reliably discriminate geometrid species as demonstrated in other taxa (see Savolainen et al. 2005, Vogler and Monaghan 2007, Waugh 2007, Mitchell 2008) and determine which species merit further investigation of their taxonomic status. The result is a reliable identification library with immediate application for monitoring looper moth biodiversity and detecting invasive species in BC.  2.2 Materials and methods 2.2.1 Sampling I chose the province of British Columbia as the primary scope of my library; its boundary does not correspond with the limits of particular biomes. However, this regional focus was chosen to maximize the development of a barcode library that would have high value for biodiversity monitoring and invasive species detection in the province. Appendix A provides an annotated list of species for BC that I compiled.  Although BC is primarily in the Western Cordillera biome, it includes some plains, maritime and subarctic ecosystems (Marshall and Schut 1999) so the fauna has considerable overlap with surrounding provinces, territories and states.  Since the ranges of many geometrid moths are poorly known, and many are expected to shift with climate change, I also sampled selected taxa from adjacent regions, including the Yukon  12 Territory and Alberta in Canada and Washington and Idaho in the United States, but did not attempt to sample their entire faunas. I also included Callizzia amorata Packard (Epipleminae), the sole BC representative of the Uraniidae, the sister group to the Geometridae (e.g. Regier et al. 2009) within the Geometroidea. I selected specimens from eight regional and national insect collections: Canadian National Collection of Insects and Arachnids (Ottawa, ON), Royal BC Museum (Victoria, BC), Pacific Forestry Centre (Victoria, BC), University of British Columbia’s Spencer Collection (Vancouver, BC), Washington State University’s James Entomological Collection (Pullman, WA), University of Idaho’s WFBARR Collection (Moscow, ID), Northern Forestry Centre (Edmonton, AB) and University of Alberta’s Strickland Collection (Edmonton, AB).  An effort was made to sample at least five geographically distinct specimens for each species, to best appraise the genetic variation across its range.  Specimens less than 30 years old were chosen when possible to avoid problems associated with DNA degradation.  Some of the specimens may have been misidentified due to the difficulty of the group and lack of an expert curator in most of the collections. Species identifications were corrected prior to or following DNA analysis where taxonomic resources permitted.  In addition, a few specimens were freshly collected on targeted collecting trips, or by making requests to entomologists in the region.  All specimens were databased and imaged and made publicly available on the Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert 2007) in the project ‘GOBCL – Geometridae of BC Library’.  13 2.2.2 DNA analysis One or two legs were removed from each dried specimen and stored in an individual tube of a 96-tube sample box (Matrix Technologies) or an individual well of a microplate. DNA extraction, amplification, and sequencing of the barcode region of the mitochondrial cytochrome c oxidase I (COI) gene followed a variety of high-throughput techniques recently developed at the Canadian Centre for DNA Barcoding (Hajibabaei et al. 2005; Ivanova et al. 2006; deWaard et al. 2008a) (see Chapter 7 for detailed protocol).  The full-length primers LepF1 and LepR1 (Hebert et al. 2004) were attempted first, but amplification and sequencing using the ‘Lep mini primers’ (MLepF1, MLepR1) (Hajibabaei et al. 2006a) was necessary for most of the older material. The electropherograms were edited and aligned in Seqscape v. 2.5 (Applied Biosystems), then deposited along with the edited sequences to BOLD and GenBank. In the 61 instances where I was unable to successfully sequence a desired species from BC, sequences were obtained from specimens collected in other regions. 2.2.3 Data analysis To investigate the efficacy of barcodes to differentiate geometrid species, sequence divergence within and between species was calculated using the Kimura 2-parameter model (Kimura 1980), and analyzed using the neighbour- joining algorithm (Saitou and Nei 1987), and non-parametric bootstrapping as implemented in BOLD and MEGA4 (Tamura et al. 2007).  I first tallied the proportion of species that form monophyletic clusters, enabling their differentiation by this distance-based analysis.  I also determined which species  14 displayed sequence diversity >3%, an arbitrary threshold that generally falls within the so-called ‘barcode gap’ (i.e. the lack of overlap between intra- and inter-specific divergence, sensu Meyer and Paulay 2005).  And lastly, to ascertain the potential of sampling bias, I tested the significance of the relationship between mean intra-specific divergence and the number of individuals analyzed by performing a linear regression in SPSS v17 (IBM).  2.3 Results and discussion A total of 2392 COI sequences were generated in this study, providing coverage for 400 species and 125 genera.  Most sequences were derived from specimens from BC (n=1390) or surrounding provinces, territories and states (n=966).  The remainder was collected in other North American regions (N=35) and from a single German specimen (of the biological control agent Minoa murinata (Scopoli, 1763)).  Of the 349 species listed for BC (Appendix A), only Hydrelia brunneifasciata (Packard, 1876) was not successfully barcoded.  Most species were represented by multiple samples (mean = 6.0 individuals/species; maximum = 46), but 62 species had only a single COI barcode.  All but nine sequences were greater than 500 bp (mean = 648 bp, range = 238 to 658bp) and therefore meet the ‘BARCODE data standard’ (see Hubert et al. 2008).  The assembly of this comprehensive dataset reveals the important role that natural history collections possess for barcode library construction, both in terms of access to entire regional faunas and to specimens conducive to DNA analysis (e.g. Meusnier et al. 2008).  15  The neighbour-joining analysis resulted in a tree with most species forming distinct, cohesive units displaying minimal sequence variation (Appendix B).  I found 27 species (6.8%) with undifferentiated or overlapping barcodes (Table 2.1), whereas the remaining 374 (93.2%) formed non-overlapping monophyletic clusters.  Taxa that have undergone recent taxonomic revision appeared to have a higher proportion of species with diagnostic barcodes e.g. Eupithecia spp. (revised in Bolte 1990) – 55 of 55 species formed non- overlapping monophyletic clusters; spp. in the tribe Macariini (Ferguson 2008) – 53/54; and Tetracis spp. (Ferris and Schmidt 2010) – 6/6.  Conversely, taxa known to be in need of revision were often comprised of several species that could not be differentiated by barcodes, such as Lobophora (noted in Pohl et al. 2010) where 3 of 5 species lacked diagnostic barcodes. There was also a single case, the species pair of Probole alienaria/amicaria Herrich-Schäffer, [1855], where the COI data were unable to differentiate the two taxa, corroborating unpublished revisionary work by Tomon (2008) who considers it a single, highly variable species.  The rate of species-level identification in the present dataset is slightly lower than in most previous barcoding studies on Lepidoptera (Hajibabaei et al. 2006a, Hebert et al. 2010, Lukhtanov et al. 2009, Chapter 7), but it is likely to increase with further taxonomic investigation of this fauna.  As the mean interspecific divergence between congeneric taxa (9.17%; range = 0 to 17.27%) was 16-fold higher than mean intraspecific variation (0.56%; range = 0 to 8.73%), the distributions of intra- and interspecific divergences showed limited overlap (Figure 2.1).  There was no significant  16 association between mean intra-specific distance and sample size (Figure 2.2, linear regression, R2=0.09, P=0.07) suggesting my sampling strategy was representative for all taxa. There were 26 instances of high intra-specific divergence (>3%) among the 338 species with multiple samples (Table 2.2).  Of these, 22 cases involved two distinct clusters and 4 involved three clusters. These deep divergences and discrete clusters may indicate the presence of cryptic species, as barcoding has proven invaluable for flagging other species that have gone previously unrecognized  (e.g. Hebert et al. 2004, Witt et al. 2006, Smith et al. 2007, 2008, Gibbs 2009, Locke et al. 2010).  Five of the taxa potentially harbouring cryptic species are also listed in Table 2.1 as taxa indistinguishable by barcodes, raising the number of BC geometrid species highlighted by DNA barcoding that require further taxonomic scrutiny to 48. In summary, two tangible products have arisen from the current study. First, a comprehensive reference library was constructed for the Geometridae of British Columbia that can be employed immediately for biodiversity monitoring and invasive species detection.  This library provides species-level resolution in over 93% of cases, and resolution to a congeneric species pair or group in the remaining cases.  This small proportion of recognized taxa that do not possess diagnostic barcodes, as well the fraction of species potentially housing cryptic species, constitutes the second product — a catalog of taxa that require taxonomic investigation.  Moreover, this catalog includes the materials necessary to facilitate the investigations — a database of specimens vouchered in permanent collections, each linked to publicly available genetic and collateral  17 data.  Used in combination, these components can accelerate integrative taxonomic studies (Miller 2007, Smith et al. 2007) and help define the ‘taxonomy of the future’ (Penev et al. 2008).   18 Table 2.1 Geometrid species not distinguishable by DNA barcodes. The 27 taxa in bold font cannot be diagnosed by COI based on one of five conditions: paraphyletic with respect to one congener; polyphyletic with two or three congeners; share an identical COI haplotype with a congener; haplotypes of one taxon do not form distinct clusters and overlap with haplotypes of congeners; and a combination of the latter two conditions.  Taxon Condition Congener involved  Caripeta divisata Walker paraphyletic angustiorata Walker Eufidonia discospilata (Walker) paraphyletic convergaria (Walker) Hydriomena edenata Swett paraphyletic crokeri Swett Macaria signaria (Hübner) paraphyletic oweni (Swett) Hydriomena furcata (Thunberg) paraphyletic quinquefasciata (Packard) Dysstroma hersiliata (Guenée) paraphyletic rutlandia McDunnough Eustroma semiatrata (Hulst) paraphyletic fasciata Barnes & McD. Epirrita autumnata (Borkhausen) paraphyletic undulata (Harrison)  Lobophora magnoliatoidata (Dyar) polyphyletic nivigerata Walker, simsata Swett Dysstroma colvillei Blackmore polyphyletic formosa (Hulst), hersiliata (Guenée), rutlandia (McD.) Xanthorhoe ramaria Swett & Cassino polyphyletic lagganata Swett & Cassino, baffinensis McDunnough  Lobophora simsata Swett identical barcodes nivigerata Walker Cabera exanthemata (Scopoli) identical barcodes erythemaria Guenée Drepanulatrix falcataria (Packard) identical barcodes carnearia (Hulst) Xanthotype urticaria Swett identical barcodes sospeta (Drury) Orthofidonia exornata (Walker) identical barcodes tinctaria (Walker)  Probole amicaria (Herrich-Schäffer) overlapping barcodes alienaria Herrich-Schäffer Chlorosea banksaria Sperry overlapping barcodes nevadaria Packard  Rheumaptera subhastata (Nolcken) identical and overlapping barcodes hastata (Linnaeus)  19 Table 2.2 Geometrid species with high intraspecific COI variation. The number of specimens per cluster is separated by a forward slash (/) with two numbers indicating cases with two distinct clusters and three numbers indicating three clusters.  The mean sequence diverence calculated for each species was caluculated using the Kimura 2-parameter distance model.  Taxon Individuals per lineage Mean sequence divergence (%)  Aethalura intertexta (Walker) 1/9 5.31 Dichorda rectaria (Grote) 1/2 3.37 Digrammia irrorata (Packard) 4/3 4.87 Dysstroma colvillei (Guenée) 2/2 3.37 Ectropis crepuscularia (Denis & Schiffermüller) 1/20 4.61 Eupithecia annulata (Hulst) 2/12 3.13 Eupithecia lachrymosa (Hulst) 3/9 3.71 Eupithecia longipalpata Packard 1/2 4.08 Eustroma atrifasciata (Hulst) 1/1 3.20 Eustroma semiatrata (Hulst) 2/4/3 4.28 Hydriomena perfracta (Swett) 1/3 4.43 Macaria colata (Grote) 1/7/1 5.04 Macaria decorata (Hulst) 2/8 7.56 Mesoleuca gratulata (Walker) 8/1 4.39 Nemoria unitaria (Packard) 1/1/7 4.45 Plataea trilinearia (Packard) 4/4 3.59 Plemyria georgii  Hulst 1/5 7.31 Probole alienaria Herrich-Schäffer 1/5 3.63 Rheumaptera hastata (Linnaeus) 1/2/3 5.73 Rheumaptera subhastata (Nolcken) 1/7 5.05 Sicya macularia (Harris) 5/6 3.25 Spodolepis danbyi (Hulst) 1/11 3.94 Synchlora aerata (Fabricius) 2/8 3.64 Synchlora bistriaria (Packard) 1/36 5.75 Triphosa haesitata (Guenée) 1/9 3.64 Xanthorhoe lacustrata (Guenée) 1/6 4.58    20 Figure 2.1 Combined histograms of pairwise Kimura 2-parameter (K2P) sequence variation. Solid triangles indicate interspecific divergences between 116 congeneric taxa (70,580 comparisons) while the open squares indicate intraspecific divergences in the 339 species with multiple samples (11,949 comparisons).     21 Figure 2.2 The relationship between mean intra-specific divergence and the number of individuals analyzed. The linear regression is not significant (P=0.07).     22 3 Towards a global barcode library for Lymantria (Lepidoptera: Lymantriinae) tussock moths of biosecurity concern2   Synopsis: Detecting and controlling the movements of invasive species, such as insect pests, relies upon rapid and accurate species identification in order to initiate containment procedures by the appropriate authorities.  In this chapter, I continue to construct reference barcode libraries that hold potential as important tools for species identification in biosurveillance, as well as for conducting biodiversity surveys.  I concentrate on the gypsy moth (Lymantria dispar L.) and other species of Lymantria (Erebidae: Lymantriinae) that are of biosecurity concern. Barcodes are assembled and generated from previous studies, museum collections, and intercepted specimens obtained from surveillance programs in British Columbia. I test the utility of DNA barcoding as a diagnostic method for the assignment of species and subspecies in this genus, as well as for the determination of geographic provenance.     2 A version of this chapter has been published. deWaard, J.R., Mitchell, A., Keena, M.A., Gopurenko, D., Boykin, L.M., Armstrong, K.F., Pogue, M.G., Lima, J., Floyd, R., Hanner, R.H. and Humble, L.M. (2010). Towards a global barcode library for Lymantria (Lepidoptera: Lymantriinae) tussock moths of biosecurity concern.  PLoS ONE 5: e14280.   23 3.1 Introduction Invasive, non-indigenous insects and the pathogens they harbour have an overwhelming ecological, socio-economic, and evolutionary impact on the forest ecosystems they invade (Liebhold et al. 1995, Mooney and Cleland 2001, Gurevitch and Padilla 2004, Pimentel et al. 2005, Lovett et al. 2006, Brockerhoff et al. 2010).  The rapid initiation of containment and eradication programs is imperative to prevent the establishment and spread of adventive populations or individuals, which in turn relies on early detection and accurate identification of non-indigenous species as they enter a new region (Allen and Humble 2001). Surveillance and monitoring at or near sites considered high risk (e.g. ports, airports, cargo facilities) serve this function, but current practices have proven insufficient, as evidenced by the alarming increase in non-indigenous insect establishments in recent decades (e.g. Humble and Allen 2006).  Species identification in particular is a vulnerable step in the surveillance process, as suggested by studies documenting the identification rate of port interceptions (e.g. 40-100% incomplete identifications across families of Coleoptera (Haack 2006)).  To aid in the inherently difficult task of species identification for biosecurity, several molecular approaches are described in the recent standard released by the International Plant Protection Convention on the diagnostic protocols for regulated pests (FAO 2006).  In contrast to the many ad-hoc protocols recognized in this standard (e.g. allozymes, restriction/amplified fragment length polymorphism analysis, microsatellites—techniques reviewed in  24 Le Roux and Wieczorek (2008)), DNA barcoding provides a standardized and generic platform while still meeting and exceeding the rigorous standards of data quality and transparency (reviewed by Floyd et al. (2010)).  Several studies demonstrate the efficacy of the approach as applied to invasive species detection and determination of native provenance, including work on leeches (Siddall and Budinoff 2005), agromyzid leafminers (Scheffer et al. 2006), tephritid fruit flies (Armstrong and Ball 2005; Barr 2009), siricid wasps (Wilson and Schiff 2010), true bugs (Nadel et al. 2010), the cactus moth (Simonsen et al. 2008), the European poplar shoot borer (Humble et al. 2009), and nocturnal moths (Chapter 7).  The integration of DNA barcoding into national biosurveillance programs has been protracted, but acceptance by certain agencies is apparent (e.g. see LBAM ID, which incorporates barcoding into the diagnostics of light brown apple moth and related species in California; Gilligan and Epstein 2009).   The tussock moth genus Lymantria L. (Lepidoptera: Noctuoidea: Erebidae: Lymantriinae) has been the focus of numerous investigations of molecular diagnostic tools, predominantly on Lymantria dispar L., to separate the North American, European and Asian gypsy moth “races” (e.g. Bogdanowicz et al. 1993, 1997, 2000; Pfeifer et al. 1995; Garner and Slavicek 1996; Reineke and Zebitz 1999; Koshio et al. 2002; Armstrong et al. 2003; Keena et al. 2008).  The intensity of research effort is certainly warranted – few groups of insects rival the tussock moths in number of undesirable, potentially invasive species and the destruction they wreak on native and non-native forests (Pogue and Schaefer 2007).  This invasive potential is the product of several undesirable life history  25 traits including long overwintering period in the egg stage, polyphagy in the larval stage, attraction of adults to artificial light sources (e.g. of ports and cargo vessels), and oviposition by females on inanimate surfaces (Wallner et al. 1995; Pogue and Schaefer 2007; Keena et al. 2008).  Invasive species identification for this group is complicated by the propensity for immatures (egg masses) to be the stage of translocation, providing few characters for morphological diagnosis. Furthermore, when the adults are targeted, as is the case with traps employing synthetic sex pheromone attractants, lures may inadvertently attract more than one species (e.g. Ross 2005), and individuals may be severely damaged by the trapping mechanism (e.g. sticky traps; see Figure 3.1) confounding species identification.  Two previous studies (Armstrong and Ball 2005, Ball and Armstrong 2006) initiated a DNA barcode library for Lymantria (and other tussock moth genera) and results suggested remarkable potential for biosurveillance and species identification.  The present study builds upon this solid foundation, to further populate the library with additional species, test that its utility remains with comprehensive sampling within species, and employ the reference library to assign intercepted specimens from quarantine and monitoring programs in British Columbia, Canada.  In addition, I compare the DNA barcoding approach to a diagnostic assay based on the same gene region, herein called the ‘NB system’ (see below), routinely-used in surveillance programs to assess the gross geographic provenance of Lymantria dispar (Bogdanowicz et al. 1993, 2000),  26 and suggest a simple transition for monitoring programs to adopt the barcoding approach with its improved reliability and resolution. 3.2 Materials and methods An effort was made to expand the taxonomic and geographic coverage of the DNA barcode library for the tussock moth genus Lymantria, with particular attention to those at high risk of being transported in cargo or on vessels to new habitats where they could become invasive pests, recently reviewed by Pogue and Schaefer (2007).  Samples and sequences were obtained from four sources. Firstly, sequences were obtained from several previous studies that analyzed all or part of the barcode region: Armstrong and Ball 2005 (76 samples), Ball and Armstrong 2006 (5), Bogdanowicz et al. 2000 (74), Hebert et al. 2010 (12), and Yamaguchi et al. unpublished (Tokyo University of Pharmacy and Life Science) (8).  Secondly, 146 samples were analyzed from vouchered material in publicly accessible collections, namely the Agricultural Scientific Collections Trust (ASCT, New South Wales, Australia), Biodiversity Institute of Ontario (Guelph, Canada), Pacific Forestry Centre (Victoria, Canada), Smithsonian National Museum of Natural History (Washington D.C., United States), and University of Maryland Alcohol Tubes of Lepidoptera collection (College Park). Thirdly, 165 specimens were analyzed from the USDA Forest Service Northern Research Station (Hamden, United States) which included representatives from all 46 strains of Lymantria dispar analyzed in Keena et al. (2008).  Finally, 32 specimens were acquired from surveillance programs in British Columbia, Canada.  Thirty of these specimens were collected in sticky traps baited with L. dispar pheromone  27 (Figure 3.1) around the province during 2006 and 2009 and two individuals were reared from egg masses removed from a Russian cargo vessel in the port of Vancouver in 1992. DNA extraction, amplification, and sequencing of the barcode region of the mitochondrial cytochrome c oxidase I (COI) gene followed standard high- throughput DNA barcoding methods described previously (Hajibabaei et al. 2005; deWaard et al. 2008a).  The primers LepF1 and LepR1 (Hebert et al. 2004) were used in most instances, but amplification and sequencing using the ‘Lep mini primers’ (MLepF1, MLepR1) (Hajibabaei et al. 2006a) was necessary for a few older specimens. Molecular work performed in Australia used the COI primers and amplification methods described in Cho et al. (2008). All sequences are publicly available from the Barcode of Life Data Systems (BOLD) (www.boldsystems.org; Ratnasingham and Hebert 2007) and GenBank (see Appendix C for accession numbers). The 658 base pair (bp) barcode region encompasses most of the 378 bp amplicon and the two restriction enzyme sites of the ‘NB system’ of Bogdanowicz et al. (1993) that is routinely used for gypsy moth diagnostics (Figure 3.2).  The four possible haplotypes in this system are N+B+, N-B+, N+B-, and N-B-, reflecting presence (+) or absence (-) of NlaIII and BamHI restriction sites. To explore the utility of the barcode region for species diagnosis in Lymantria, a maximum likelihood tree was constructed in Garli 1.0 (Zwickl 2006), using the best-fit model as determined by ModelTest 3.7 (Posada and Crandall 1998) under the Akaike Information Criterion.  The general-time-reversible  28 substitution model was chosen, with among-site-rate-heterogeneity modeled according to a gamma distribution, and an estimated proportion of invariant sites. Analysis used default settings with Orgyia antiqua (L.) (BOLD ProcessID XAG647-05, GenBank Accession GU091296) included as an outgroup; branch support was estimated using 100 bootstrap replicates.  The levels of genetic variation within and between species were calculated in MEGA 4 (Tamura et al. 2007) using pairwise Kimura 2-parameter (K2P) distances (Kimura 1980) and the pairwise deletion option. To investigate subspecies delimitation in Lymantria dispar using the COI gene, I reduced the dataset to the 244 sequences > 600 bp.  A neighbour-joining (NJ) tree was constructed in MEGA 4 with K2P distances and the pairwise deletion option.  Specimens were classified to subspecies based on the geographic distribution limits provided by Pogue and Schaefer (2007) where sufficient locality data were available. For both the species and subspecies level, Bayesian assignment tests were performed using the ‘segregating sites’ algorithm of Abdo and Golding (2007; see also Lou and Golding 2010).  For all species with three or more individuals, one randomly-chosen COI sequence was removed from the dataset and used as the query sequence for the test, as in Taveres and Baker (2008). This procedure was subsequently repeated for all haplotypes of the 32 surveillance specimens. The number of segregating sites, the posterior probability of correct assignment, and the risk of mis-assignment were calculated with the program Assigner (available at http://info.mcmaster.ca/TheAssigner/;  29 Abdo and Golding 2007).  The assignment of species and subspecies (and potential for determining geographic provenance and female flight ability) with the COI barcode region was compared against the commonly employed ‘NB system’ (Bogdanowicz et al. 1993).  3.3 Results COI barcodes were obtained from 518 individuals and 36 species of Lymantria, originating from 35 countries (Appendix C).  Sixteen species were represented by a single sample sequence while the remaining species ranged from 2 to 308 sequences (mean excluding L. dispar = 5.8 sequences/species). The average sequence length was 597 bp despite several shorter sequences obtained from previous studies (e.g. sequences from Bogdanowicz et al. 2000 are 375-378 bp).  Four species (L. singapura Swinhoe, L. semperi Schintlmeister, L. todara Moore, and L. subrosea Swinhoe) had sequences shorter than half the barcode region due to specimen age and/or preservation.  There was no evidence of insertions, deletions or stop codons detected, suggesting that psuedogenes were absent from the dataset.  The ML tree for the 36 species revealed relatively long branches among terminal clusters of closely related haplotypes (Figure 3.3, Appendix D).  In only one case did a terminal cluster not correspond to known species limits: L. sinica Moore (n=3) was paraphyletic with respect to the single specimen of L. nebulosa Wileman, with the deep split in L. sinica equalling 2.9% K2P sequence  30 divergence (LYMAN070-08, locality: China split from LYMAN065-08 and LYMAN066-08, locality: Taiwan).  Eighteen of the 20 species clusters with multiple individuals had high bootstrap support (>80%); the remaining two species, L. umbrosa (Butler) and L. dispar, which was considered conspecific until recently (Pogue and Schaefer 2007) and which respond to the same pheromone lure (Ross 2005), had bootstrap support of 69% and <50%, respectively.  The mean K2P sequence divergence between species (x = 14.02%; SD = 3.47%; range = 2.68 – 37.61%) was approximately 21-fold higher than within species variation (0.66%; SD = 0.50%; range = 0 – 3.38%) and formed disjunct distributions (Figure 3.4).  Only 157 of 50,390 intraspecific comparisons and 2 of 630 interspecific comparisons fell within a small range of overlap, between 2 and 4%.  The former cases involved L. mathura Moore, L. sinica, L. obfuscata Walker, and L. dispar (only those comparisons involving one or two short GenBank sequences) and the latter involved the pairs L. dispar / umbrosa and L. xylina Swinhoe / schaeferi Schintlmeister.  The NJ tree of COI sequence divergences in L. dispar indicated a clear delineation between the L. d. dispar subspecies and the two Asian subspecies asiatica Vnukovskii and japonica (Motschulsky) (Figure 3.5).  The tree also revealed that all North American L. d. dispar individuals clustered together along with two sequences from France (LYMMK049-09, LYMMK054-09).  The 32 specimens caught in surveillance programs in British Columbia, Canada comprised four COI haplotypes.  Two of these haplotypes clustered within the North American L. d. dispar, while the other two clustered in the asiatica /  31 japonica group—in all 32 cases, there is perfect correspondence with the subspecies designations deduced from morphology and the origin/pathway of introduction.  The tests of assignment in a Bayesian statistical framework resulted in correct assignment to species and subspecies in all instances (Table 3.1).  The posterior probabilities of assignment for most species (with adequate sample size) were relatively high, and the risks of mis-assignment were quite low.  The assignment of surveillance specimens to L. dispar and their respective subspecies displayed substantially lower posterior probabilities and higher risks, likely a product of the close association of L. dispar with L. umbrosa, as well as the nonmonophyly of L. d. asiatica and japonica.  The haplotypes of the ‘NB system’ were inferred based on the COI sequence present at the two restriction sites (Appendix B) rather than by restriction endonuclease digests.  As in Keena et al. (2008), the three haplotypes N+B+, N-B- and N+B- were present in L. dispar.  All 3 haplotypes were also found in at least one other species—one  species possessed N+B+, five species had N-B-, and 16 species scored as N+B-.  Currently it is unclear exactly which species will generate a COI amplicon with the primers of Bogdanowicz et al. (1993, 2000), but previous work has successfully assayed L. albescens Hori & Umeno (L. dispar albescens in Bogdanowicz et al. (2000)), L. umbrosa (L. dispar hokkaidoensis in Bogdanowicz et al. (2000)), and L. monacha (L.) (LMH, unpublished data of male from Russian Far East).   This suggests that misidentification of species prior to the ‘NB system’ assay could have serious  32 ramifications.  For example, the heavily regulated nun moth (L. monacha), if captured in North America and inadvertently assayed as L. dispar, would be determined to possess the N+B- haplotype (Appendix C), and mistakenly diagnosed as European gypsy moth, L. dispar dispar.  In respect to tracing geographic origins, the 3 NB haplotype states remain mostly informative as originally characterized (Bogdanowicz et al. 1993), but with limited resolution and outliers that could also be misleading (e.g. BOGDA004-08, from Ontario, Canada has the N+B- haplotype characteristic of Europe).  In contrast, the COI sequence data consisted of 91 haplotypes within L. dispar and 142 haplotypes across all species, none of which were shared between species.  Moreover, the haplotype data recovered clusters of L. d. dispar, North American L. d. dispar, and L. d. asiatica/japonica.  The presence of multiple barcode-determined haplotypes in several regions (e.g. 6 haplotypes from 7 individuals in the Indre-et-Loire department of France; 5 haplotypes from 9 individuals from the Ticino Canton in Switzerland) suggests the potential for determining native provenance (and associated traits that may increase the likelihood of successful establishment and long-distance dispersal, such as female flight ability) by analyzing haplotype frequencies across the native and introduced range (e.g. Simonsen et al. 2008, Weese and Santos 2009, Nadel et al. 2010).  Although the sampling density in the present study was not adequate for these analyses, the presence of two haplotypes from France which clustered within the North American L. d. dispar is consistent with the well-documented introduction of the species in 19th century Massachusetts by Leopold Trouvelot of  33 France (Liebhold et al. 1989) (note that although the likely source population was within France, this has never been confirmed). 3.4 Discussion This study has clearly demonstrated the efficacy of DNA barcodes for diagnosing species of Lymantria and has reinforced the view that the approach is an untapped resource with substantial potential for biosecurity and surveillance (Floyd et al. 2010).  The observed 21-fold difference between mean intra- and interspecific variation, with very minimal overlap between the two distributions, resulted in well-supported, cohesive clusters of sequences corresponding with named species.  In only one case—the paraphyly of L. sinica relative to L. nebulosa—did the COI barcodes fail to correctly distinguish species, providing a success rate of 97.2% among 36 morphologically defined Lymantria species. This high success rate is comparable to three recent barcode studies of Lepidoptera: 100% success observed in a temperate, local study of 190 species (Chapter 7); 97.9% in a tropical, regional study of 521 species (Hajibabaei et al. 2006a); and 99.3% in a temperate, continental study of 1,327 species (Hebert et al. 2010).  It remains possible that the deep split in L. sinica is genuine and reflects the allopatric divergence between the nominal species and a misidentified or undescribed species, or that L. sinica and L. nebulosa compose a single entity with atypically variable COI.  In any case, further investigation is warranted.  A deep COI divergence revealed within L. mathura in the study of Ball and Armstrong (2006) pointed to a possible cryptic species subsequently described  34 as L. flavida by Pogue and Schaefer (2007), explaining previous mixed responses to a synthetic pheromone lure by these moths.  In addition, my data set has identified another potentially cryptic species within L. mathura, which I have treated as L. sp. nr mathura, pending a more thorough taxonomic study of this complex. In these ways, DNA barcoding provides secondary benefits to biosecurity applications—taxonomic insights and implications for detection and monitoring in the field.  It also validates a fundamental practice in barcoding projects, the retention of voucher specimens (Floyd et al. 2010), to facilitate future taxonomic examination and to avoid the proliferation of incorrect identifications or ‘error cascades’ (Bortolus 2008).  The positive results of the species and sub-species assignment tests, calculated for both reference and surveillance specimens, demonstrates the future potential for the application of DNA barcoding to biosecurity.  An actively curated and validated reference library is queried with the DNA barcode obtained from a surveillance or quarantine specimen; within a robust statistical framework, species assignments are calculated along with measures of confidence; where sufficient coverage exists, additional assignments are computed (e.g. subspecies identification, native provenance, characteristics related to invasiveness), which can be corroborated with additional molecular markers where necessary; voucher specimens are retained to facilitate morphological confirmation and future taxonomic enquiry.  While the infrastructure is in place for this at the present time (i.e. BOLD, Ratnasingham and Hebert 2007), further benchmarking of statistical assignment programs is necessary (e.g. Lou and Golding 2010), as  35 is the continued construction and maintenance of reference barcode libraries. For the latter, participation by multiple national biosecurity research and monitoring programs is imperative.  To this end, my comparison of the commonly used ‘NB system’ (Bogdanowicz et al. 1993) with the COI barcode approach clearly indicates that higher resolution and generality would be achieved by Lymantria monitoring programs should they adopt DNA barcoding.  I have demonstrated instances when the ‘NB system’ would provide misleading results that could have serious consequences, whereas COI barcodes provide reliable subspecies and broad geographic information.  Moreover, recent studies (e.g. Simonsen et al. 2008, Weese and Santos 2009, Nadel et al. 2010) indicate that higher sampling density should allow more precise tracing of source populations, which in turn will predict female flight ability, the key trait of interest (Keena et al. 2008).  Because the same COI gene region underlies both approaches, the transition for monitoring agencies could be seamless.  Instead of amplifying the 378 bp fragment of Bogdanowicz et al. (1993), the 658 bp barcode region could be amplified with the universal LepF/LepR primers (Hebert et al. 2004).  Assays of the NlaIII and BamHI enzyme digests could continue to be performed, producing slightly different banding patterns (Figure 3.6), but providing a rapid initial assessment as with the ‘NB system’.  The amplicon could then be sequenced for definitive species and broad geographic information.  The increased sampling density would continually develop a baseline from which progressively finer levels of information could be gleaned, potentially replacing the need for other marker  36 systems (e.g. FS1, Garner and Slavicek 1996 or microsatellites, Bogdanowicz et al. 1997).  3.5 Conclusion In this study I have shown that DNA barcoding is an effective tool for discriminating species of Lymantria. Furthermore, my comparison of this system against the NB restriction digest system—commonly employed at present by biomonitoring agencies for this purpose—suggests that the informational value provided by barcoding (species resolution, general applicability) is significantly greater. DNA barcoding also has the potential to provide novel taxonomic insights, facilitated by its rigorous standards of record-keeping and permanent archiving of voucher specimens. As the DNA barcode reference library continues to increase in coverage, both for Lymantria and other taxa of international regulatory concern, its utility as part of a diagnostic/monitoring system will continue to expand.   37 Table 3.1 Assignment of random and surveillance individuals to species. Provided are the three query types, query taxon, BOLD Process ID assigned, number of individuals in query taxon, diagnostic sites, posterior probability of correct assignment, and risk of mis-assignment.  Query Query taxon Process ID No. of individuals No. of diag. sites Posterior probability Risk  species L. mathura LYMAN019 26 14 0.998 3.29 x 10-5  L. monacha LYMMK174  58 13 0.974 2.75 x 10-4  L. antennata LYMAN174 3 5 0.987 6.09 x 10-5  L. sinica LYMAN066 3 11 0.997 8.73 x 10-5  L. obfuscata LYMAN074 8 13 0.897 2.86 x 10-3  L. dissoluta LYMAN055 3 2 0.960 1.21 x 10-4  L. sp. nr. mathura LYMAN025 3 2 0.992 3.87 x 10-5  L. bantaizana GBGL1580 4 2 0.986 1.09 x 10-4  L. lucescens GBGL1613 4 0 0.994 0  L. atemeles LYMAN042 5 3 0.984 4.73 x 10-5  L. xylina GBGL1587 5 5 0.85 9.14 x 10-4  L. flavida LYMAN028 6 6 0.983 1.25 x 10-4  L. fumida GBGL1589 6 1 0.993 9.92 x 10-6  L. plumbalis LYMAN108 9 0 0.998 0  L. albescens LYMAN033 13 5 0.697 1.85 x 10-3  L. umbrosa LYMMK095 21 12 0.572 3.26 x 10-3  surveillance - species L. dispar LMHRG001  308 49 0.727 3.35 x 10-3  L. dispar LMHRG008  308 49 0.766 3.23 x 10-3  L. dispar LBCH7981  308 49 0.694 5.17 x 10-3  L. dispar LYMMK013  308 49 0.694 5.17 x 10-3  surveillance - subspecies L. d. dispar LMHRG001  203 29 0.593 3.10 x 10-3  L. d. dispar LMHRG008  203 29 0.656 3.15 x 10-3  L. d. asiatica LBCH7981  54 6 0.462 3.28 x 10-3  L. d. asiatica LYMMK013  54 2 0.302 1.06 x 10-3  38 Figure 3.1  Collection of specimens through a pheromone-based gypsy moth surveillance program. A, Pheromone trap and B, trapped and damaged Lymantria dispar specimen (LMHRG001-06) (image A from USDA APHIS PPQ Archive, USDA APHIS PPQ, Bugwood.org)    39  Figure 3.2 Barcode region of the cytochrome oxidase I (COI) gene. The barcode region spans 658 base pairs near the 5’ end of the COI gene and includes the two diagnostic restriction enzyme sites of the ‘NB system’ of Bogdanowicz et al. (1993), referred to as N and B.  An additional monomorphic NlaIII site is found in the 5’ region of the barcode gene fragment and therefore a NlaIII enzyme digest of the barcode region would result in two (N-) or three (N+) bands (instead of 1 or 2 bands).    40 Figure 3.3 Maximum likelihood tree for 36 species of Lymantria. Tree was constructed with the barcode region of the COI gene for 518 individuals. The number of specimens collapsed into a single node is given in parentheses after the taxon name.  Bootstrap support values >50% are listed above the corresponding node. Width of the triangles represents the sequence divergence within the cluster.  Scale refers to number of substitutions per site. See Appendix D for full tree.   41 Figure 3.4 Combined histograms of pairwise Kimura 2-Parameter (K2P) sequence variation. Blue vertical bars show intraspecific divergences for the 20 species of Lymantria with multiple individuals and green vertical bars show the interspecific divergences between all 36 species.    42 Figure 3.5 Neighbour-joining tree of the gypsy moth Lymantria dispar. Tree was constructed with 244 sequences of the COI barcode region.  BOLD process IDs and collection localities are provided for each sequence. Surveillance specimens are denoted by a moth symbol.   43 Figure 3.6  Simulated gel electrophoresis for two restriction fragment length polymorphism assays. The barcode region assay amplifies a ~690 bp fragment, whereas the Bogdanowicz et al. (2003) assay amplifies ~380bp.  The presence (+) or absence (-) of the NlaIII and BamHI restriction sites are provided for each assay, as described in the text.  The digest and electrophoresis simulations were performed with New England BioLabs NEBcutter V2.0 (http://tools.neb.com/NEBcutter2).     44 4 The ‘barcode approach’ to combining molecular datasets: Reconstructing the phylogeny of North America’s Geometridae as an example3   Synopsis: Phylogenetic diversity (PD), a measure of the evolutionary heritage of a group of species, is a level of diversity often underappreciated and overlooked. In order to estimate PD, it is necessary to construct a phylogeny of the group that contains reliable branch lengths.  In this chapter I construct another tool to be employed later in this thesis — a multi-gene phylogeny of the Geometridae of North America.  This tree will be used to construct community phylogenies and permit the investigation of the effects of disturbance on three levels of moth diversity, including PD.  4.1 Introduction The inchworm moths or loopers (Lepidoptera: Geometridae) are one of the largest insect families, comprising nearly 23,000 species worldwide (Minet and Scoble 1999; Scoble and Hausmann 2007) and roughly 1400 in North America (Ferguson 1983).  They are distinguished from other macro-moths by their unique tympanal structures at the base of the abdomen as adults, and their measured looping motion as larvae, due to the lack of prolegs on the third to fifth  3 A version of this article will be submitted for publication.  deWaard, J.R., Mitter, C., Hausmann, A., and Humble, L.M. The ‘barcode approach’ to combining molecular datasets: Reconstructing the phylogeny of North America’s Geometridae as an example.  45 abdominal segments in most species.  Most larvae feed externally on leaves, flowers and fruits of trees, shrubs or herbs, but a few species are detritivores (Powell and Opler 2009) and even predators (Hawaiian Eupithecia: Montgomery 1982).  Geometrids are a substantial component of temperate forest ecosystems, and include several serious defoliators, both native (e.g. hemlock looper, Lambdina fiscellaria (Guenée)) and introduced (e.g. winter moth Operophtera brumata (L.)).  Despite their ecological and economic significance, a robust phylogeny of the family still remains to be deciphered, particularly for the North American fauna.  Previous studies have attempted to elucidate deep geometrid relationships using morphology (Holloway 1997; Minet and Scoble 1999; Nakamura 2004), DNA sequence data (Abraham et al. 2001; Young 2006) or both (Young 2008).  While they provide good working hypotheses, all suffered from lack of resolution, generally due to the small number of variable characters considered per taxon.  More recent studies have concentrated on using modern phylogenetic techniques on large molecular data sets and the resolution has improved.  Yamamota and Sota (2007) provided a comprehensive analysis of several markers for Japanese taxa (Figure 4.1a), as did Wahlberg et al. (2010) for Palearctic species focusing on the origins of female flightlessness (Figure 4.1d).  More recently, Regier et al. (2009) and Mutanen et al. (2010) released preliminary results of two massive ‘tree of life’ projects reconstructing the phylogeny of the order Lepidoptera, each with significant coverage in the Geometridae and related families (Figure 4.1b,c).  These studies, in combination  46 with more focused projects (Sihvonen and Kaila 2004, Sihvonen 2005, Snall et al. 2007, Viidalepp et al. 2007, Canfield et al. 2008, Õunap et al. 2008; Õunap and Viidalepp, 2009), strongly support a number of interrelationships: the four major subfamilies are arranged with Larentiinae and Sterrhinae as sister group to the remaining Geometridae; Alsophilinae (Alsophilini here) almost certainly falls within Ennominae; and the heterogeneous Oenochrominae is composed of at least two distantly related lineages.  But many more questions of interrelationships exist, such as: the exact relationship of Larentiinae and Sterrhinae; the placement and monophyly of the minor subfamilies Archiearinae, Desmobathrinae, and Orthostixinae; and the monophyly of Ennominae.  The present situation in geometrid systematics highlights the common state for many groups of organisms.  The flood of ‘tree-of-life’-scale projects has produced an excess of character data for exemplars of the deep, major branches (e.g. ordinal level and above), and is rapidly elucidating their affinities.  At lower taxonomic categories (e.g. families, tribes) however, progress is more sluggish, often hampered by incongruence among molecular markers chosen (Caterino et al. 2000).  Furthermore, it becomes more difficult to locate non-degraded samples of exemplars the closer you get to the periphery of the tree of life, limiting marker choice even further (e.g. fresh/frozen samples are generally required for reverse transcriptase PCR of nuclear protein-coding genes).  Not surprisingly, substantial research has examined how to combine seemingly distinct datasets or phylogenetic trees, for instance using supermatrix or supertree approaches (reviewed by de Queiroz and Gatesy 2007).  An often  47 under-appreciated requirement of the resultant phylogenies for many applications is the derivation of meaningful branch lengths; some examples include the estimation of phylogenetic diversity (Faith 1992), the use of community phylogenies for understanding ecological communities (e.g. Webb et al. 2006), and the dating of divergence events (e.g. Drummond et al. 2006; Rutschmann 2006).  In the latter case, only supermatrix approaches with overlapping characters will suffice.  Opportunely, another source of sequence data is rapidly being developed—the Barcode of Life Initiative—that is surveying one or few standard genes for large swaths of taxa, like the gene cytochrome c oxidase subunit 1 (COI) for all animals.  It would be useful to explore the potential of the COI gene to act as a core region to concatenate datasets for constructing phylogenies.  This ‘barcode approach’, an instance of the supermatrix approach, could effectively combine existing deep-level data matrices with newly generated, shallow-level datasets.  This study therefore has two objectives.  The first is to construct a multi- gene phylogeny for North America’s Geometridae, including exemplars for all suprageneric taxa known to occur here.  In addition to providing a valuable backbone topology to construct community phylogenies, this will contribute a North American perspective to a growing and significant body of literature on deep geometrid systematics.  The second is to explore different strategies for building upon existing deep-level and large-scale molecular datasets that use this phylogenetic signal for tree construction at shallower levels.  I propose a  48 ‘barcode approach’ to combining phylogenetic datasets for this purpose, using the COI gene to concatenate disparate datasets. 4.2 Materials and methods 4.2.1 Taxon sampling My sampling strategy was to select taxa to represent all 53 suprageneric taxa found in North America.  The majority of samples were taken from the extensive Alcohol Tubes of Lepidoptera (ATOLep) collection housed at the University of Maryland in College Park, MD.  Additional specimens, particularly rare or rarely collected exemplars of North American tribes, were acquired from several institutions and collections, including the Zoological State Collection of Munich (Germany), Smithsonian National Museum of Natural History (Washington DC, United States), Canadian National Collection of Insects and Arachnids (Ottawa, ON), Biodiversity Institute of Ontario (Guelph, Canada), and the Area de Conservación Guanacaste collection of Dan Janzen and Winnie Hallwachs (Costa Rica). In addition, I sampled 25 taxa analyzed by Regier et al. (2009) that include all their Geometridae and several outgroup taxa from their LepTree of Life (LTOL) project (http://www.leptree.net/). Not all specimens sampled were originally collected or are known to occur in North America—the priority was maximizing taxonomic breadth with the specimens available. Specimen age ranged from 1 year to 31 years, but the majority was collected in the last 10 years.  Overall, 284 specimens were analyzed, later pruned down to a final set of 176 taxa (see below) (Appendix E).  The ingroup was composed of 7 subfamilies, 61 tribes, and 152 genera, including all 53 suprageneric taxa of  49 North America, and 15 tribes not found here.  The outgroup selected was extensive, consisting of 6 families, 12 subfamilies, and 24 genera, based on the results of recent studies (Yamamota and Sota 2007; Wahlberg et al. 2010; Regier et al. 2009; Mutanen et al. 2010). 4.2.2 Gene sampling The 25 taxa previously analyzed by Regier et al. (2009) yielded sequence data for 5 nuclear protein-coding genes that totaled 6633 base pairs (bp): CAD (2828 bp) (Moulton and Wiegmann 2003), DDC (1281 bp) (Fang et al. 1997), enolase (1134 bp) (Farrell et al. 2001), period (888 bp) (Re), and wingless (402 bp) (Brower and DeSalle 1998).  I refer to this dataset here as ‘LTOL5x25’.  To maximize congruence with the former and other previous systematic studies of Lepidoptera (Caterino et al. 2000), I attempted to amplify and sequence a variety of gene regions, nuclear and mitochondrial, and protein-coding and ribosomal. 4.2.3 DNA analysis and data matrix construction Samples in three 96-well plates were brought to the Canadian Centre for DNA Barcoding in Guelph, Canada for the molecular analyses. A proteinase K lysis buffer was added to each well and the plates were incubated overnight. The following day, the lysate was processed following the glass-fibre protocol of Ivanova et al. (2006) on a Biomek FXP liquid handler (Beckman Coulter). A 2 µl aliquot of this resultant DNA extract was added to each well of a premade PCR plate stored at -20°C and containing 2 ul of H2O, 6.25 µl of 10% trehalose, 1.25 µl of 10X buffer, 0.625 µl of 50 mM MgCl2, 0.0625 µl of 10 mM dNTPs, 0.06 µl of Platinum Taq polymerase (Invitrogen) and 0.125 µl of each of the 10 µM primers.  50 In addition to the COI barcode region, I used 15 primer sets to attempt to amplify nine gene regions: COI-3p–COII, 16S, 18S, 28S-D2, EF-1α (4 primer sets), Wingless, CAD (4 primer sets) DDC, and IDH (see Appendix F for primers, thermocycling conditions, and references).  The E-Gel 96 agarose electrophoresis system (Invitrogen) was used to visualize the PCR reactions and determine the success rate of gene fragments and samples.  Only amplification of the regions COI-3p–COII , 16S, 18S, 28S-D2, and EF-1α resulted in a high proportion of single-banded products suitable for sequencing. Sequencing reactions contained 0.25 µl of Dye terminator mix v3.1 (Applied Biosystems), 1.875 µl of 5X sequencing buffer, 5 µl of 10% trehalose, and 1 µl of the respective 10 µM PCR primer.  These reactions were run at an initial denaturation at 96°C for 2 min, followed by 30 cycles of 96°C for 30 sec, annealing at 55°C for 15 sec, and extension at 60°C for 4 min.  The reactions were cleaned up using the CleanSEQ system (Agencourt Bioscience) on a Biomek FXP liquid handler before being run on a 3730XL DNA Analyzer (Applied Biosystems), all following manufacturer’s instructions. Bidirectional contigs were assembled, edited and aligned using CodonCode Aligner (CodonCode Corporation).  All automated alignments were checked visually and adjusted manually where necessary.  I used Gblocks v.1.81 (Castresana 2000) with stringent default settings to eliminate ambiguous positions in the ribosomal alignments.  The COI barcode fragment successfully sequenced for all specimens was used to confirm identifications with the Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert 2007) identification  51 engine (BOLD-ID) as in Regier et al. (2009) and Wahlberg et al. (2010).  At this point, the dataset was condensed to 176 taxa after removing specimens with only a single gene region, specimens that were potentially misidentified, and redundant taxa.  Concatenating the LTOL5x25 dataset (6633 bp) with COI (658 bp), COI-3p–COII (919bp), 16S (340bp), 18S (612bp), 28S-D2 (249bp), and EF- 1α (924bp) for all 176 taxa resulted in a final data matrix of 10,335 bp (Figure 4.2a).  The average proportion of missing characters for the new 6 gene regions is 28.0%, or 66.4% for all 11 regions (mean = 3613 bp per taxon).  The sequences, trace files, and GenBank accession numbers for all 11 gene regions, as well as the images, voucher information, and collateral data for all 176 taxa, are publicly available on BOLD in the project ‘NAGEO - Phylogeny of the North American Geometridae’. 4.2.4 Phylogenetic analysis  Phylogenetic trees were constructed using the maximum likelihood (ML) criterion and the best-fit model as determined by ModelTest 3.7 (Posada and Crandall 1998) under the Akaike Information Criterion. The general-time- reversible substitution model was selected, with among-site-rate-heterogeneity modeled according to a gamma distribution, and an estimated proportion of invariant DNA sites.  Trees were constructed using RAxML v.7.2 (Stamatakis 2006), both online at the BlackBox web server (http://phylobench.vital-it.ch/raxml- bb/) (Stamatakis et al. 2008) and offline.  For each run, I specified the length of each gene region for estimation of partition-specific parameters to perform a partitioned ML analysis, and then branch supports were estimated using 100  52 bootstrap replicates.  Input files were created using the toolset at the Los Alamos HCV Sequence Database (http://hcv.lanl.gov/content/sequence/hcv/ToolsOutline.html) (Kuiken et al. 2005) and trees were visualized with FigTree v. 1.3.1 (Drummond and Rambaut 2007) and Dendroscope v. 2.7.4 (Huson et al. 2007).  When comparing trees derived from different partitions or subsets of data, I contrasted the recovery and bootstrap support for 10 relatively deep divergences (Table 4.1) from the ML analysis of the full dataset. I considered branches with bootstrap values >50% to be minimally supported, >70% to be well supported and >90% to be strongly supported.  In addition to the 11 gene – 176 taxon dataset, I also pruned taxa to create a reduced dataset to explore the effect of missing characters on tree reconstruction.  I selected 68 species that included single exemplars for all tribes, and included all taxa from the minor subfamilies; it resulted in a data matrix with 58.9% missing characters. For investigating the relative contribution of different partitions to the overall phylogenetic signal, I also divided the data into a) nuclear vs. mitochondrial, and b) ribosomal vs. protein-coding genes.  Furthermore, I also performed ‘partition addition bootstrap alteration’ (PABA) tests (Struck et al. 2008), where 11 datasets were constructed, each lacking a single gene region in turn, then compared for estimated bootstrap support.  To evaluate different strategies for expanding upon large ‘tree of life’ studies (see Introduction), I created 6 subsets of the data matrix by adding different sets of gene regions and taxa to the LTOL5x25 dataset: 1) added the  53 COI barcode region for the 25 LTOL taxa (Figure 4.2b); 2) added 6 new gene regions for the 25 LTOL taxa (Figure 4.2c); 3) added the COI barcode region for the 151 new taxa (Figure 4.2d); 4) added 6 new gene regions for the 151 new taxa (Figure 4.2e); 5) added the COI barcode region to all 176 taxa (Figure 4.2f); and 6) added the COI barcode fragment for all 176 taxa and 5 new genes for the new 151 new taxa (i.e. the ‘barcode approach’) (Figure 4.2g).  The trees constructed with these subsets were compared to the ML analysis of the full dataset.  4.3 Results and discussion 4.3.1 Phylogenetic analysis: contributions, conflict and congruence I combined a portion of the large LepTree dataset of Regier et al. (2009) (25 geometrid and outgroup taxa; 5 genes) with a newly generated dataset representing all 53 suprageneric taxa found in North America (151 taxa, 6 different genes including the COI barcode region).  The best-scoring maximum likelihood tree (lnL = -159290.2) constructed is shown in Figure 4.3.  The lack of resolution, evidenced by the small number of bootstrap support values over 50%, was surprising.  The paucity of support was not limited to a particular level (e.g. tribe and below), but instead appeared to be associated with the number of taxa in a clade.  The outgroup families and small geometrid subfamilies demonstrated a considerable proportion of branches with moderate and high support. Conversely, the large subfamily Ennominae demonstrated only 15 of 71  54 branches with minimal or higher bootstrap support.  While the increased taxon sampling and data matrix of 10,335 characters seems sufficient for reconstructing the relationship of species-poor taxa, elucidating affinities in the larger groups such Ennominae and Larentiinae will require further data. The maximum likelihood tree of the reduced dataset (lnL = -91253.9), which comprised exemplars of all geometrid tribes and minor subfamilies, displayed comparable results (Figure 4.4) to the tree derived from the full dataset.  The reduction in the proportion of missing characters (from 66.4% to 58.9%) resulted in an overall weaker support of clades.  I explored this further by summarizing the recovery and bootstrap support for ten selected clades using the full dataset, the reduced dataset, and different partitions thereof (Table 4.1). The reduced dataset lowered node support in four cases and resulted in a slightly altered topology (the relationship of Larentinae and Sterrhinae). When the full dataset was partitioned into nuclear DNA (nucDNA), mitochondrial DNA (mtDNA), protein-coding genes (PCGs) and ribosomal DNA (rDNA), there was an even more pronounced drop in resolution and support (Table 4.1). Individually, these partitions are not major contributors, with perhaps the exception of PCGs to deep divergences in the tree (roots of Geometroidea and Geometridae). These results do not offer a recommendation for which partition contributed the most, or which type would be beneficial for further gene sampling, but it is however, an example of the synergistic effect of combining gene partitions (Reed and Sperling, 1999) where ‘the whole exceeds the sum of the parts’ (Wortley et al. 2005).  55  The ‘partition addition bootstrap alteration’ (PABA) tests (Struck et al. 2008) similarly provided a perspective on the contribution of partitions, in this case, individual genes (Table 4.2).  An increase in bootstrap support for a node when a particular gene is removed, relative to the tree derived from the full dataset, indicated the gene conflicted with the node; on the other hand, a decrease in bootstrap support, or absence of the node altogether, was evidence the gene provided support for the node.  The gene COI-3p–COII provided the largest contribution, since analysis without this partition resulted in decreased support for seven nodes.  CAD was nearly as important, since its removal resulted in decreased support for five nodes as well as strong support for a conflicting arrangement of node 3 (91% support for Sterrhinae on a basal branch relative to Larentiinae, as opposed to L+S).   The genes 18S, 28S, and COI-5p all made similar contributions (for 5, 5, and 4 nodes, respectively) and were a net benefit to analysis, whereas the genes enolase and 16S provided no net benefit (each contributed to 3 nodes and conflicted with 3 nodes), and the genes DDC, period, wingless and EF-1α provided more conflict than positive phylogenetic signal.  There are some limitations to this analysis, for instance it fails to account for the sequence length or frequency of the fragments in the data matrix, but it does validate at least four (COI-3p–COII, COI-5p, 18S, 28S) of the six gene fragments in my newly generated dataset.  Moreover, it may provide useful guidance for gene choice in subsequent deep-level systematic studies of Geometridae and other Lepidoptera.  Those studies would also be wise to consider other factors when selecting gene fragments, namely the ease of  56 amplification and sequencing (see Materials and Methods), incidence of indels, introns or paralogous copies that might complicate isolation or analysis (Wilson 2010), and congruence of marker choice with previous studies in the given taxon (Caterino et al. 2000). 4.3.2 Strategies for combining data with large datasets For evaluating hypothetical strategies for expanding upon large ‘Tree of Life’ studies, to channel this phylogenetic signal for shallower tree construction, I created subsets of the full data matrix that replicated several scenarios.  As with the partitions above, I compared the recovery and bootstrap support for ten selected clades against the best-scoring maximum likelihood tree constructed with the full dataset.  The first strategy tested was simply adding the COI barcode region for the 25 LTOL taxa only (Figure 4.2b).  Such a scenario would require access to the archived specimens or extracted DNA of the original study, a practice that is becoming commonplace in systematics (Hanner and Gregory 2007).  While the different number of taxa prevents a true comparison with the best-scoring tree, this method does provide high support and resolution (Table 4.3).  Many large-scale ‘Tree of Life’ studies are now using COI barcodes, either incorporating the sequence data into their data matrix (Mutanen et al. 2010) or using it to confirm identifications (Regier et al. 2009).  The second strategy was similar, but instead added six new gene regions for the 25 LTOL taxa only (Figure 4.2c).  Compared with the first scenario (Table 4.3), this marginally improves overall node support, but without increased taxa, it provides limited benefit for the expended resources.  The third and fourth strategies tested  57 involved adding the COI barcode region (Figure 4.2d) and adding the 6 new gene regions for the 151 new taxa (Figure 4.2e), respectively.  Using the phylogenetic methods here, these two strategies would not be recommended under any circumstances; the lack of overlap requires an alternative supermatrix approach (de Queiroz and Gatesy 2007) but they were included for demonstration.  In both cases, there is a complete lack of resolution and actually support for spurious relationships (based on the current consensus of phylogenetic relationships within Geometridae).  While this strategy does allow for added taxon sampling and does not require access to archived material from the large-scale study, only the topology will be meaningful, which may suffice for some applications.  The final two strategies assessed provide novel approaches to merging new datasets with previous large-scale studies and should provide meaningful branch lengths for applications such as phylogenetic diversity estimation and divergence dating.  They do require access to archived specimens or DNA, or that the prior study sequenced the COI barcode region (as above).  The fifth strategy tested involved adding the COI barcode region to the 25 LTOL taxa and the new 151 taxa (Figure 4.2f).  The result was a tree with predominantly unresolved polytomies, including the ten selected nodes of comparison (Table 4.3).  It is apparent that the 658 bp overlapping fragment contains insufficient phylogenetic signal for nodes it alone contributes to (i.e. among the 151 new taxa alone), and additively does not possess the necessary signal for nodes reconstructed with all partitions.  It is unclear if this is a result of the specific properties of this data set, but analysis following this strategy in another family of  58 Lepidoptera, the Coleophoridae, revealed similar substandard resolution (V. Nazari, unpublished).  Follow up work is necessary to determine if these observations will be characteristic of this approach, as well as the interplay of factors such as the taxon and gene sampling of the initial dataset, the length of sequence overlap, and shape of the tree. The sixth and final strategy is what I term the ‘barcode approach’ to combining datasets, for the purpose of joining new datasets with existing deep- level molecular datasets to allow reconstruction of shallow phylogenetic relationships.  This involves generating a new dataset, concentrating on gene and taxon coverage that addresses the phylogenetic level of interest, and ensuring that the barcode fragment is sequenced for all new and previous taxa. This approach is advantageous since the genes used in previous studies are not always suitable to resolve the shallower divergences sought, and the sequence data for these genes may be difficult or impossible to recover due to limitations imposed by the samples.  For example, the nuclear protein-coding genes used in Regier et al. (2009) were isolated using reverse transcriptase PCR from fresh and frozen specimens, and these fragments may prove to be too conserved for very recent divergences (but see Kawahara et al. 2009).  My test of this approach involved combining the five gene fragments for the 25 LTOL taxa, the 5 newly sequenced gene fragments for 151 new taxa, and the COI barcode region for all 176 taxa (Figure 4.2g).  The resulting tree was nearly identical in topology to the best-scoring tree using the full dataset, and recovered all ten of the selected nodes (Table 4.3), but only two of these nodes had bootstrap support  59 greater than 50%.  While superficially this approach may appear deficient, the best-scoring tree compared to also has limited node support for a majority of the clades.  I interpret that the recovery of a near-identical topology, in addition to lower but comparable overall branch support, suggests this approach is promising and certainly warrants further evaluation.  Subsequent investigation with large datasets that produce well-resolved and well-supported phylogenies, that have included the barcode fragment for all taxa, and are free of confounding factors such as missing characters in the data matrix, would provide ideal opportunities for assessment.  My results from the evaluation of partitions also suggests that the COI-3p–COII fragment, downstream and adjacent to the COI- 5p barcode region, holds substantial signal (this study; Roe and Sperling 2007) and it would be worthwhile to explore the advantages of using a larger fragment of COI–COII (~1600 bp) for the ‘barcode approach’ of combining datasets. 4.3.3 Phylogenetic relationships of North America’s Geometridae  Bearing in mind the limited node support for many clades, it is possible to extract several useful conclusions concerning the phylogenetic relationships of North America’s Geometridae (Figure 4.3).  First of all, the root of the superfamily Geometroidea had moderate support, with Epicopeiidae + Sematuridae as its sister clade.  This is congruent with Regier et al. (2009), a novel finding relative to the working hypothesis of Kristensen 1999, and contrary to Mutanen et al. (2010) who found Geometroidea paraphyletic with respect to Sematuridae.  The monophyly of Geometridae had high support in both the full and reduced dataset analyses, consistent with recent studies (Yamamota and Sota 2007; Wahlberg et  60 al. 2010; Regier et al. 2009; Mutanen et al. 2010) and has never effectively been refuted (Minet and Scoble 1999).  Within Geometridae, and consistent with recent work, the four major subfamilies are arranged with Larentiinae and Sterrhinae as sister group to the remaining Geometridae, the polyphyly of Oenochrominae is well-supported, and Alsophilini groups within Ennominae.  In the latter case, the best-scoring tree suggests Alsophilini has an affinity with Gonodontini and Campaeini, as in Yamamota and Sota (2007) and Wahlberg et al. (2010).  The present analysis includes more comprehensive sampling for most of the minor subfamilies, which resulted in some unique hypotheses that will require further examination.  Both tribes of Desmobathrinae were analyzed for the first time and the inclusion of one tribe (Desmobathrini) in the Sterrhinae clade (along with Ergavia: Oenochrominae) is a new finding.  Likewise, only Holarctic Archiearinae has been analyzed previously, generally placing it on a basal branch to (Ennominae + Geometrinae) (e.g. Wahlberg et al. 2010), but my addition of Neotropical Archiearinae (Lachnocephala) revealed it to be polyphyletic in this analysis.  Interestingly, Young (2006) noted the Neotropical Archiearinae show affinities with Tasmanian Archiearinae, a taxon she deems “probably misplaced”.  Above all, these discoveries of rampant non-monophyly in the minor subfamilies, at least according to this present analysis, provide the most important conclusion — that increased taxon and gene sampling of the minor subfamilies is necessary before we can elucidate the interrelationships of the major subfamiles, and the bulk of the diversity in Geometridae.  61 Table 4.1 The recovery and bootstrap support for ten selected clades using different partitions of data. The ten branches are indicated on Figures 4.3 and 4.4 by the numbers provided here.  Values given are bootstrap support for the given branch.  N denotes branch is not present and L denotes branch is present but bootstrap support <50%.  Taxon / relationship Branch Full Reduced nucDNA(8) mtDNA(3) PCGs(8) rDNA(3)  Geometroidea 1 83 N L/N N 60 N Geometridae 2 99 98 L/N N 62 N L + S 3 50 N L/N L L/N N L (incl. A1) 4 93 80 L/N L L/N N S (incl. D1 & O1) 5 88 70 L/N L L/N N (O2,D2)+(A2,O3,G,E) 6 95 85 L/N N L/N N A2+(O3,G,E) 7 L L L/N N L/N N O3+G 8 L 52 L/N N L/N N G 9 96 99 L/N 70 61 N E 10 L L L/N N L/N N   62 Table 4.2 The recovery and bootstrap support for ten selected clades following ‘partition addition bootstrap alteration’ (PABA) tests. See Materials and Methods for details of tests. The ten branches are indicated on Figures 4.3 and 4.4 by the numbers provided here.  Values given are bootstrap support for the given branch.  N denotes branch is not present and L denotes branch is present but bootstrap support <50%.  Spurious results are indicated by a footnote.   a supports spurious relationship of (Sterrhinae in part + Larentiinae in part) with bootstrap support of 81  Taxon / relationship Branch -CAD -DDC -Enolase -Period -Wingless -COI5P -COI3P -EF1a -18S -28S -16S  Geometroidea 1 55 87 67 88 90 97 L 99 66 88 96 Geometridae 2 91 95 99 95 99 97 L 95 69 91 97 L + S 3 Na 68 80 81 89 63 L 75 77 67 75 L (incl. A1) 4 87 94 99 93 94 94 L 95 82 80 98 S (incl. D1 & O1) 5 81 92 91 92 89 82 L 88 86 66 86 (O2,D2)+(A2,O3,G,E) 6 L L L L L L L L L L L A2+(O3,G,E) 7 L L L L L L L L L L L O3+G 8 L L L L L L L L L L L G 9 96 96 95 97 93 92 L 98 98 91 96 E 10 L L L L L L L L L L L  63 Table 4.3 The recovery and bootstrap support for ten selected clades using the six approaches to combining datasets evaluated in the analysis. See Materials and Methods for details of analysis. The ten branches are indicated on Figures 3 and 4 by the numbers provided here.  The column headers 4.2b to 4.2g denote the different approaches illustrated in Figure 4.2. Values given are bootstrap support for the given branch.  N denotes branch is not present and L denotes branch is present but bootstrap support <50%. Spurious results are indicated by footnotes.  Taxon / relationship Branch 4.2b 4.2c 4.2d 4.2e 4.2f 4.2g  Geometroidea 1 L 98 L/N N N L Geometridae 2 100 98 L/N Nb N L L + S 3 91 99 Na Nc L L L (incl. A1) 4 100 100 N N L L S (incl. D1 & O1) 5 L 91 N N L L (O2,D2)+(A2,O3,G,E) 6 100 100 N N N 53 A2+(O3,G,E) 7 70 L N N N L O3+G 8 72 96 N N L L G 9 100 100 N N L 58 E 10 100 99 N N N L  a supports spurious relationship of (Sterrhinae in part + Larentiinae in part) with bootstrap support of 81 b supports spurious relationship of (Sterrhinae in part + Uraniidae in part) with bootstrap support of 68 c supports spurious relationship of (Sterrhinae in part + Larentiinae in part) with bootstrap support of 78    64 Figure 4.1 Phylogenies proposed for the Geometridae by recent studies. Shown are a) Yamamota and Sota 2007, b) Regier et al. 2009, c) Mutanen et al. 2010, and d) Wahlberg et al. 2010.       65 Figure 4.2 Strategy for taxon and gene sampling. a) Specific details of the taxon and gene sampling of the complete dataset.  The six subsets of the data matrix created to simulate strategies of combining datasets are shaded in black in b) to g). They were created by adding different sets of gene regions and taxa to the LTOL5x25 dataset (box in white): b) added the COI barcode region for the 25 LTOL taxa; c) added 6 new gene regions for the 25 LTOL taxa; d) added the COI barcode region for the 151 new taxa; e) added 6 new gene regions for the 151 new taxa; f) added the COI barcode region to all 176 taxa; and g) added the COI barcode fragment for all 176 taxa and 5 new genes for the new 151 new taxa (i.e. the ‘barcode approach’).  The trees constructed with these subsets were compared to the maximum likelihood analysis of the full dataset.   66 Figure 4.3 Best-scoring maximum likelihood tree constructed with the complete data set of 176 taxa and 11 gene fragments.   67     68 Figure 4.4 Best-scoring maximum likelihood tree constructed with a reduced data set of 68 taxa and 11 gene fragments.       69 5 First Canadian records of Lampropteryx suffumata ([Denis & Schiffermüller], 1775) (Geometridae: Larentiinae)4   Synopsis: The first Canadian records of the Holarctic species Lampropteryx suffumata (Denis & Schiffermüller, 1775) are documented, based on collections from Alberta and British Columbia.  The specimens were originally detected while constructing the DNA barcoding library for the Geometridae of British Columbia in Chapter 2.  This is the first of two chapters that demonstrate how genetic methods can enhance the construction of regional inventories and aid in surveillance for invasive species.  5.1 Introduction The genus Lampropteryx Stephens includes ten species, most of which are restricted to Asia, with two species also occurring in Europe (Scoble 1999). The black-banded carpet Lampropteryx suffumata ([Denis & Schiffermüller], 1775), described from Vienna, Austria, occurs from western Europe and the northern Mediterranean region to northern Scandinavia, east through the Tien Shan and Altai mountain ranges of south-central Asia to the Kamchatka Peninsula, Russia and Hokkaido, Japan (Skou 1986; Beljaev and Vasilenko  4 A version of this chapter has been published. deWaard, J.R., Schmidt, B.C., Anweiler, G.G., and Humble, L.M. (2008). First Canadian records of Lampropteryx suffumata ([Denis & Schiffermüller], 1775) (Geometridae: Larentiinae). Journal of the Entomological Society of BC. 105: 19-25.  70 2002). Previously known in North America only from Alaska (Choi 2000), I report here historical and contemporary records in British Columbia and Alberta, flagged by DNA barcoding.  5.2 Materials and methods During the course of documenting the molecular diversity of western Canadian geometrid moths from museum and field collections using standard DNA barcoding methods (Hajibabaei et al. 2005; deWaard et al. 2008a), it became evident that a number of specimens variously identified as Antepirrhoe Warren or Xanthorhoe Hübner were highly divergent compared to other congeners. Using the identification engine of the Barcode of Life Database (BOLD) (Ratnasingham and Hebert 2007), their cytochrome oxidase I (COI) sequences were a nearly identical match to those of Lampropteryx suffumata ([Denis & Schiffermüller], 1775) specimens from Bavaria, Germany (Figure 5.1). Although many larentiines are very similar in habitus and are difficult to identify when the wing pattern is abraded, subsequent genitalic examination of the suspect Antepirrhoe and Xanthorhoe specimens showed unequivocally that they are in fact L. suffumata. To determine the Canadian distribution, and whether or not the species is likely native, I examined historical and contemporary Antepirrhoe and Xanthorhoe specimens from various Canadian collections.  I identified specimens in the Royal British Columbia Museum, Victoria, BC (RBCM), the E.H. Strickland  71 Entomological Museum, University of Alberta, Edmonton, AB (UASM) the Canadian National Collection of Insects, Agriculture and Agri-Food Canada, Ottawa, ON (CNC), and the Biodiversity Institute of Ontario, University of Guelph, Guelph, ON (BIOUG) as L. suffumata. The collections of the Pacific Forestry Centre, Canadian Forest Service, Victoria, BC (PFCA), the Spencer Entomological Museum, University of British Columbia, Vancouver, BC (UBCZ), and the Northern Forestry Centre, Canadian Forest Service, Edmonton, AB (NFRC) do not contain any specimens of L. suffumata.  5.3 Results Specimens examined (all specimens are single, pinned adults; the BOLD accession number (italicized) is provided for specimens that have been barcoded): AB: Hillcrest, 49.568N 114.377W, 20-vi-1919 (K. Bowman) [UASM, UASM10792]; West Castle River, W Castle R. Rd., 15 km SW, 49.294N 114.273W, 23-v-1999 (B.C. Schmidt) [CNC, CNCLEP00033310, GWNC311-07]; BC: Elkford, 35 km north, 50.266N 114.921W, 12-Jun-1988 (C.S. Guppy) [RBCM, ENT991-006550, GWNR470-07]; Glacier National Park, Abandoned Rails Trail west of Rogers Pass Centre, 51.2902N 117.516W, 04-Jul-2005 (K. Pickthorn) [BIOUG, HLC-20568, LBCA568-05]; Glacier National Park, Glacier National Park Compound at Rogers Pass, 51.3032N 117.519W, 28-Jun-2005 (K. Pickthorn) [BIOUG, HLC-20320, LBCA320-05]; Glacier National Park,  72 Illecillewaet Campgrounds west of Rogers Pass, 51.2648N 117.494W, 24-Jun- 2005 (K. Pickthorn) [BIOUG, HLC-20175, LBCA175-05]; Glacier National Park, Glacier National Park Compound at Rogers Pass, 51.3032N 117.519W, 16-Jun- 2005 (K. Pickthorn) [BIOUG, HLC-20022, LBCA022-05]; Trinity Valley Field Station, 50.400N 118.917W, 18-May-1961 (W.C. McGuffin) [CNC, CNCLEP00054030]. Identification: A medium-sized, broad-winged moth with a wingspan of 2.5–3.2 cm (Figure 5.2a.). The forewing basal and median bands are dark, varying from red-brown to black, being dark brown in most specimens. The median band has a jagged proximal and distal margin, with the distal margin extending towards the base just below the median area, such that the median band is narrower along the anal third than on the upper half. The apex is also darkened, divided by a white apical dash. There is a subterminal line of white spots or wedges, and the fringe is checkered. It is very similar to Antepirrhoe semiatrata (Hulst), but can be readily separated by the following characters: forewing pale antemedian band faintly bordered with two whitish lines both proximally and distally (only one pale border line in A. semiatrata); forewing subapical dark patch bordered towards costal margin by contrasting pale line (indistinctly so in A. semiatrata). The dorsal markings on the abdomen are the most reliable external features for diagnosing L. suffumata, which has a row of black triangles along the midline (Fig. 5.2a), whereas Antepirrhoe species have two black dots broken at the midline by a pale line/spot. Some specimens may be melanic and lack the contrasting white forewing bands present in most  73 specimens. Xanthorhoe species are superficially similar, but lack the combination of broad, dark basal and median bands with a contrastingly bordered subapical dark patch that extends to the distal wing margin. Genitalic examination of L. suffumata will easily segregate this species: the male valve is simple and lobe- shaped, costa lacking apical process; socii prominent, about half as long as valve, with bundle of apical setae as long as socius; aedeagus uncurved, vesica with two cornuti (Figure 5.2b,c). Identification through genitalic examination of males can usually be made by brushing away the terminal abdominal scales to reveal the apical portion of the valve which lacks the pointed, dorsally projecting costal process of A. semiatrata, in addition to the long tubular socii (stout and triangular without apical hair pencils in A. semiatrata). Male genitalic structure of Xanthorhoe species is very different, with a comparatively massive costal process that extends beyond the valve apex and is variously enlarged, broadened and/or armed with spines. Distribution and habitat: Great Britain and northern Europe east to southern Siberia, Kamchatka and Japan (Skou 1986; Beljaev and Vasilenko 2002); in North America, known from two areas: Alaska (Choi 2000) and southwestern British Columbia and adjacent Alberta (Figure 5.3).  It is likely that this species occurs in intervening regions of northern British Columbia and the Yukon, but these areas have not been adequately surveyed. The single historical collection from Hillcrest, Alberta, coupled with the fact that L. suffumata occurs in relatively remote, mountainous habitats but has not been recorded near the international shipping ports of the coastal Pacific Northwest, suggests that L.  74 suffumata is native to Canada.  Furthermore, it likely expanded over Beringia during the Pleistocene, a common pattern in the western Canadian arthropod fauna, as evident by present ranges and fossil evidence of past ranges (Danks et al. 1997).  Its habitat appears to be open wooded areas, edges and meadows. Life history and notes: There is a single annual brood, with adults in late May to early July. Adults are nocturnal and come to light. The only reported larval hosts are bedstraw species (Galium sp.), particularly G. aparine Linnaeus (Skou 1986).  The pupa overwinters underground (Skou 1986). Based on the scarcity of specimens in Canadian collections, I conclude the species is rarely collected and likely rare. The COI barcode sequences are publicly available in the Barcode of Life Database and GenBank (accession nos. FJ376631–FJ376643).  5.4 Discussion The recent discovery of a relatively large and conspicuous native macromoth in Western North America is surprising, but I believe it can be explained simply by the paucity of taxonomic expertise and literature on the group.  The Canadian larentiines are notoriously hard to discriminate, due in part to the lack of a treatment of this subfamily in McGuffin’s ‘Guide to the Geometridae of Canada’ series (1967, 1972, 1977, 1981, 1987, 1988).  While a few larentiine genera have been revised (Hydriomena Hübner: McDunnough 1954; Eupithecia Curtis: Bolte 1990; Entephria Hübner: Troubridge 1997), most are in dire need of revision, and the Xanthorhoini in particular contain a number  75 of genera that need attention, with cryptic and previously unrecognized species awaiting description (e.g., Psychophora Kirby, Xanthorhoe and Zenophleps Hulst: B.C.S. unpublished data; Antepirrhoe: J.R.D. et al. unpublished data).  It is reasonable to assume that the few specimens of this rarely collected (and presumably rare) species could go unnoticed due to the lack of reliable guides and keys for the group. Although L. suffumata is in all likelihood native, its discovery clearly illustrates how DNA barcoding can assist in the detection and surveillance of nonindigenous organisms (Armstrong and Ball 2005; Chown et al. 2008).  A monitoring program that incorporates DNA barcoding can flag potential introduced species in one of two ways.  First, as in this study, a barcode match is made with one or more specimens collected from the native range.  The potential nonindigenous specimens can then be verified by morphological examination or further genetic analysis.  At that point, national and regional collections can be examined for historical and contemporary specimens in the new range to determine if the species is native or introduced.  Secondly, with a barcode library for a regional fauna broadly representative (e.g., Geometridae of British Columbia – Chapter 2), any barcoded specimens that do not match the database are flagged as potentially nonindigenous and again warrant further examination. Using genetic methods for this initial screening has numerous advantages, most notably the ability to differentiate species objectively across all life stages as well as using damaged specimens.  It is also apparent that with the current costs of genetic analysis steadily dropping and new technologies emerging (Hajibabaei et  76 al. 2007), genetic screening may soon be more cost- and time-efficient than current morphological methods of biodiversity monitoring.  77 Figure 5.1  Neighbour-joining tree of Lampropteryx suffumata and related species. Tree was reconstructed with the barcode fragment of the COI gene.  Sequences shaded in grey are derived from specimens previously misidentified as Antepirrhoe or Xanthorhoe spp.  Scale indicates percent substitutions per site. The 13 sequences are publicly available in the Barcode of Life Database and GenBank (accession nos. FJ376631–FJ376643).   78 Figure 5.2 Adult male of Lampropteryx suffumata. a) dorsal view with diagnostic row of black triangle markings on abdomen indicated by white arrow, b) genital capsule, and c) aedeagus   79 Figure 5.3 Distribution of Lampropteryx suffumata in North America. Black squares denote species records and black circles are place markers.   80 6 DNA barcoding flags the first North American records of a Eurasian moth, Eupithecia pusillata (Denis & Schiffermüller, 1775) (Lepidoptera: Geometridae)5   Synopsis: The first North American records of the juniper pug moth, Eupithecia pusillata (Denis & Schiffermüller, 1775) are presented, a non-indigenous introduction flagged by DNA barcoding.  As in the previous chapter, specimens were detected during the earlier construction of reference libraries and a regional species checklist.  I discuss the integration of DNA barcoding into routine biosurveillance and forest insect surveys to prevent the delayed recognition of non-indigenous species—in this case, 34 years.  6.1 Introduction DNA barcoding has repeatedly demonstrated its utility as a molecular diagnostic technique that merits integration into national biosurveillance programs (Armstrong and Ball 2005; Ball and Armstrong 2006; Chapter 3, 5, 7). In contrast to other molecular tools commonly employed for species identification of intercepted organisms, DNA barcoding is a generic and standardized approach that still meets and surpasses international standards of data quality and transparency (reviewed by Floyd et al. (2010)).  Several studies have  5 A version of this chapter has been published. deWaard, J.R., Schmidt, B.C.S., and Humble, L.M.  (2010).  DNA barcoding flags the first North American records of a Eurasian moth, Eupithecia pusillata (Denis & Schiffermüller, 1775) (Lepidoptera: Geometridae). Journal of the Entomological Society of BC 107:1–7.  81 demonstrated the efficacy of this platform for detecting non-indigenous species and determining native provenance, for example in leeches (Siddall and Budinoff 2005), agromyzid leafminers (Scheffer et al. 2006), tephritid fruit flies (Armstrong and Ball 2005; Barr 2009), siricid wasps (Wilson and Schiff 2010), true bugs (Nadel et al. 2010), and numerous taxa of moths (Ball and Armstrong 2006; Simonsen et al. 2008; Humble et al. 2009; Gilligan and Epstein 2009; Armstrong 2010; Chapter 3, 5, 7).  Here I report the first North American records of the juniper pug moth, Eupithecia pusillata (Denis & Schiffermüller, 1775) flagged by DNA barcoding.  6.2 Materials and methods  While compiling a DNA barcode library for the Geometridae of British Columbia (Chapter 2), the cytochrome c oxidase subunit I (COI) sequences derived from two Eupithecia specimens were found to be divergent from known native Eupthecia.  The two sequences were compared to a reference barcode database of Lepidoptera barcodes using the identification engine (BOLD-ID) of the Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert 2007), and tentatively identified as Eupithecia pusillata.  The reference barcode database for Geometridae used by BOLD-ID is continually validated by specialists to ensure accurate identifications, and is particularly well parameterized due to a global campaign to barcode the nearly 23,000 species of the family (see http://www.lepbarcoding.org/geometridae/index.php).  The sequences with identical and near-identical matches from Europe were obtained from Axel  82 Hausmann (Zoological State Collection, Munich, Germany) and Marko Mutanen (University of Oulu, Oulu, Finland) and combined with related North American specimens (according to Bolte 1990).  A neighbour-joining tree was constructed on BOLD using the Kimura-2-parameter distance method (Figure 6.1).   The two putative E. pusillata specimens were obtained from the RBCM (Royal British Columbia Museum, Victoria, BC) and PFCA (Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre, Victoria, BC), and dissections were completed following the methods detailed by Lafontaine (2004). Images were taken using a Leica M205C microscope equipped with a Leica DFC490 camera kit and Leica LAS Montage system that assembles multiple images in successive planes of focus into a single image with a large depth of field. The specimens were verified by comparison of genitalic structure with specimens held in the CNC (Canadian National Collection of Insects, Arachnids and Nematodes, Ottawa, ON), and figures of E. pusillata in Skou (1986) and Mironov (2003).  Related species in the E. niphadophilata Dyar, 1904 group (Bolte 1990) were ruled out by genitalic comparison to specimens in the CNC, as were other North American species. All historical data associated with the specimens was compiled from specimen labels and Forest Insect and Disease Survey (FIDS) records.  The single specimen from PFCA collected as part of FIDS is uniquely identified by a registration number (e.g. 76-9-0019-01) that links the specimen to a FIDS sampling form, completed at the time of sample collection, as well as a rearing  83 record documenting the status of laboratory rearings. These records are held on file at PFC. 6.3 Results Specimens examined: 1♂ – label data (handwritten information in italics, individual lines separated by comma, multiple labels separated by ‘|’): No. 76-9-0019-01, Date 19 vii, F.I.[D.]S.1976 | c. juniper, Port, Coquitlam BC | Ac. No. PFC, 2007-0271. The specimen was initially identified as Eupithecia unicolor (Hulst). The FIDS records document that this specimen was one of two adults reared from five larvae and five pupae (10 individuals in total) collected by the B.C. Forest Service on Mt. Burke, Port Coquitlam (UTM 10 53 546 [49.3, -122.7], Elevation 09[00] ft), on 15 May 1976.  The host recorded was common juniper (Juniperus communis L.); Remarks & Symptoms state “Attacking several ornamentals with moderate damage”. The date recorded on the specimen label is the date of adult eclosion. While the Rearing Record indicates a second adult eclosed on 8.vii.76 and was subsequently spread, the specimen could not be found in the reference PFC collection. 1♀ – label data: BC, N. Vancouver, 5 AUG 1986, C.S. Guppy | ROYAL BRITISH, COLUMBIA MUSEUM, ENT991-12573 |.  84 This specimen was identified as Eupithecia sp. in the collection before tentative assignment to Eupithecia intricata taylorata Swett by JRD.  Diagnosis: Eupithecia pusillata is most similar to E. niphadophilata and particularly E. interruptofasciata, but a number of Eupithecia species are superficially very similar and identification should be based on genitalic examination. Compared to E. interruptofasciata, which is structurally most similar, the male the 8th sternite apical prongs are narrower, more blunt and the apical cleft is shallower; the base of the sternite is also narrower overall with a shallower medial invagination. The basal half of the male vesica is armed with one spine, not two as in E. interruptofasciata. In the female genitalia, the large spines on the left side of the ductus bursae do not extend beyond the mid-point of the ductus, but extend beyond the midpoint in both E. interruptofasciata and E. niphadophilata. Description: A small moth with a wingspan of 16–22 mm (Mironov 2003) (Figure 6.2a,e).  Forewing narrow, mostly shades of light brown with black transverse lines and oblong discal spot.  Hindwing pale grey-brown with weakly marked transverse lines and variable discal spot.  Abdomen pale grayish brown with narrow black lateral stripes.  Male genitalia (Figure 6.2d) composed of broad valva with small ventral process, heavily sclerotized sacculus, vesica with three horn-like cornuti, simple aedeagus (Figure 6.2c) and elongate 8th sternite with two narrow apical processes (Figure 6.2b).  Female genitalia composed of elongate and sclerotized bursa copulatrix (Figure 6.2h) with small spines at base and larger spines at margin.  Ovipositor is simple with long setae (Figure 6.2f).  85 Terminal segment of pupal case is stout with prominent lateral lobes and cremaster bearing four pairs of hook-like setae  (Figure 6.2h,i). Distribution and habitat: In its native European range, the nominate subspecies is widely distributed from southern Europe, its range extends to the Mediterranean from eastern Spain to mainland Greece and Romania, then extends north and west across northern Ukraine into western Russia. With the exception of Corsica, it has not been recorded from the islands of the Mediterranean. To the north it is present in the British Isles, through central Europe, north to northern Scandinavia, and into western Russia across the southern Kola Peninsula (Skou 1986; Mironov 2003; Karsholt and van Nieukerken 2010). A disjunct population of E. pusillata is present in the Caucasus Mountains (Mironov 2003). In Asia, its range extends across Russia from Sahkalin through Siberia, the Altai and Caucasus regions (Skou 1986). The subspecies E. pusillata scoriata Staudinger, 1857 has been recorded only from Iceland and south-western Greenland (Mironov 2003).  Mironov et al. (2008) recently described a third subspecies, E. pusillata kashmirica Mironov and Ratzel from the Himalayas.  In natural settings, E. pusillata can be found in heaths, forest edges, rocky cliffs, and similar habitats where the primary host grows.  In cosmopolitan areas, it can be common in gardens.  It is known from 0 m up to about 2,500 m above sea level in the Sierra Nevada (Spain) and the Alps (Weigt 1993; Mironov 2003). Life history and notes: The following data are based on European populations, and it is expected that flight times, voltinism and larval hosts will be  86 similar in North America, should extant populations be discovered. Univoltine, with larval stage from late April to mid-June and adult flight period from mid-July to late September (Skou 1986; Mironov 2003).  As its common name implies, the primary host of E. pusillata is common juniper, Juniperus communis L. (Cupressaceae) (Skou 1986), of which it feeds on young needles and flowers.  It is generally regarded as monophagous (Mironov 2003), although it has also been recorded feeding on Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco (Pinaceae) in France (Roques et al. 2006), where this North American tree is cultivated. The host of the subspecies scoriata and kashmirica is not known, but is presumed to also be Juniperus.  Eupithecia pusillata overwinters in the egg stage and pupates in a loose web in the ground (Skou 1986).  It is attacked by a variety of ichneumonid and braconid species listed in Mironov (2003). It is unknown if other native or ornamental species of Juniperus are suitable hosts in British Columbia.  6.4 Discussion Eupithecia Curtis is a large genus with about 1400 described species (Scoble 1999), and about 160 species in North America (Powell and Opler 2009). The North American species were revised by McDunnough (1949), and the Canadian fauna was revised by Bolte (1990). Eupithecia pusillata is part of the niphadophilata species group, which includes two Nearctic and one Palearctic species (Bolte 1990), all feeding primarily on junipers (Skou 1986; Bolte 1990).  87 Although I currently have only two records of Eupithecia pusillata in North America, I can extract a great deal of information from the associated data documentation.  First of all, the collections were made in a heavily urbanized area, greater Vancouver, BC, suggesting the species was introduced.  The lack of records, particularly from inland B.C. (which is well-surveyed for macro- Lepidoptera) and the Yukon Territory and Alaska, lead us to conclude that the species is not naturally Holarctic like some Eupithecia (see Skou 1986, Bolte 1990).  Furthermore, the six Eupithecia species considered Holarctic all show at least 1% COI sequence divergence (data not shown) indicative of separation in the Pleistocene (Knowlton and Weigt 1998).  Secondly, the locality of the first collection (Mt. Burke), the number of individuals collected (ten), and the damage observations in the FIDS record, all indicate that there was an established E. pusillata population in BC in 1976 (but note this is the only FIDS record of a Eupithecia on juniper from greater Vancouver).  And lastly, the 1986 collection from North Vancouver suggests that the population has persisted, or it did for at least a decade.  Subsequent surveys, initially in the Vancouver area, are required to determine the contemporary status of this species.  The excellent documentation of the Forest Insect and Disease Survey that enabled inferences about the status of E. pusillata is unfortunately a relict of the past; the program ceased in 1996 after almost 50 years of operation due to budgetary cut-backs (Van Sickle et al. 2001).  The program’s termination was unfortunate, but perhaps foreseeable as it was simultaneously a) a tremendous resource for managers, foresters and scientists, and b) reliant on tremendous  88 resources itself, particularly in terms of highly qualified personnel.  The program was undoubtedly taxed by the necessity to rear the agents of damage in most cases—immatures—to diagnose species (which was not always accurate even when a specimen was successfully reared, as in the present case).   For the same reasons that DNA barcoding makes an invaluable tool for biosurveillance, it would revolutionize any regional or national biomonitoring program of similar scope to FIDS.  Barcoding could not only identify immature stages (Ahrens et al. 2007) making rearing nonobligatory, it could also identify the plant meal of gut contents (Miller et al. 2007), identify parasitoids (Rougerie et al. submitted), and trace complex food webs (Smith et al. submitted).  Decreasing costs and increasing capabilities of sequencing (e.g. Shokralla et al. 2010) are certain to make species diagnosis in this form time- and cost-effective.  Furthermore, most years of the FIDS program predated electronic databases, so it would also be better served by modern and online relational databases such as BOLD (Ratnasingham and Hebert 2007).  With this tool in place, the tremendous resource of overview surveys such as FIDS could once again be realized, and without having to expend it as a cost.  It would also, without question, speed the time of non-indigenous species detection—from years (34 in the case of E. pusillata) to days.   89 Figure 6.1   Neighbour-joining tree of Eupithecia pusillata and two closely related species, E. niphadophilata and E. interruptofasciata. Tree was reconstructed with the barcode fragment of the cytochrome oxidase I (COI) gene.  Sequences shaded in grey are from two individuals collected in Vancouver, Canada.  Abbreviations: DE – Germany, FI – Finland, IT – Italy, CA – Canada, BC – British Columbia, AB – Alberta.     90 Figure 6.2   Morphology of Eupithecia pusillata. a) male, dorsal view, b) male, 8th sternite (the narrow and blunt prongs, indicated by a black arrow, are diagnostic), c) male, aedeagus, d) male, genital capsule e) female, dorsal view, f) female, ovipositor, g) female, bursa copulatrix (the large spines do not extend beyond the mid-point, indicated by a black arrow – a diagnostic characteristic) h) pupa, terminal segment, dorsal view, i) pupa, terminal segment, lateral view.  Scale bars: a, e = 5 mm; b–d, f–i = 0.5 mm.     91 7 In the dark in a large urban park: DNA barcodes illuminate cryptic and introduced moth species6   Synopsis: This is the first of three chapters that employ the tools developed in earlier chapters to facilitate faunal inventories in disturbed forest systems. Following the devastating windstorms of the 2006–2007 winter, I conducted a first level inventory of nocturnal Lepidoptera in Stanley Park, Vancouver.  I employed high-throughput DNA barcoding for the rough sorting of all material and for tentative species identifications, where possible.  I report a preliminary species list of 190, the detection of four new exotic species, and the discovery of two potentially cryptic species.  I evaluate the assistance that barcoding presents for faunal inventories, both in terms of reducing specialist time and facilitating the detection of native and exotic species at low density.  7.1 Introduction The biodiversity inventory, in all but a few taxa, and at all but the shallowest levels, is inherently a formidable task.  For the vast majority of terrestrial arthropods, enumerating and naming all residents of a community or assemblage is onerous and requires a substantial investment of resources. Large samples, damaged specimens, immature stages—all of these may be  6 A version of this chapter has been published. deWaard, J.R., Landry, J.-F., Schmidt, B.C., Derhousoff, J., McLean, J.A. and Humble, L.M. (2009). In the dark in a large urban park: DNA barcodes illuminate cryptic and introduced moth species.  Biodiversity and Conservation 18: 3825–3839.  92 commonplace when conducting surveys of hyper-diverse groups, and they all can provide a substantial barrier to the cornerstone of biodiversity studies: the accurate diagnosis of species.  To compound this problem, the lack of trained professional systematists and taxonomists, and the subsequent lack of usable keys and modern nomenclature (Gotelli 2004), threatens the extinction of the faunal inventory for all but a few well-known groups (e.g. butterflies, tiger beetles, and dragonflies).  The establishment of DNA barcoding (Hebert et al. 2003a) holds significant promise to overcome some of the obstacles of biodiversity inventories. In particular, barcoding can transform the often lengthy and tedious chore of identifying specimens to a rapid, accurate and unbiased task (Janzen et al. 2005; Smith et al. 2005).  Even when a comprehensive database is unavailable, it can still assist with the rough sorting of specimens, guide morphological determinations, and populate the database for future surveys.  This may free time for specialists and highly qualified personnel, fostering improved inventories and repeated monitoring.  In the wake of the three windstorms of the 2006–2007 winter that caused significant destruction in Stanley Park, Vancouver, Canada (see Vancouver Park Board 2007), it became apparent that the biodiversity data necessary to appraise the effects were lacking.  Furthermore, concern mounted over the forest’s increased susceptibility to exotic species, particularly within various terrestrial arthropod groups.  To remedy this, baseline surveys and monitoring projects in several insect groups were established (McLean et al. 2009a, b), including the  93 initiation of a first level inventory of the nocturnal Lepidoptera assemblage.  To aid with the latter, I conducted high-throughput DNA barcoding for rough sorting of all material and for assigning tentative species identifications where possible.  I evaluate this ‘wedding’ of barcoding and inventories (Janzen et al. 2005) and its effectiveness for the initial screening of a faunal inventory in a hyper-diverse group, as well as its ability to flag exotic and cryptic species.  7.2 Materials and methods Specimens were collected by mercury-vapour light at two sites in Stanley Park, Vancouver, Canada: the west side of the park, near the ‘Hollow Tree’ (49.306N 123.153W, 13m) and on the eastern half, near the Vancouver Aquarium (49.301N 123.128W, 52m).  The sampling effort consisted of eight collections made between May and August 2007 beginning at dusk for roughly 5 hours.  Specimens were hand-collected live and killed by freezing or ammonium hydroxide just prior to mounting and spreading (Landry and Landry 1994).  A synoptic collection was made for each night, retaining no more than 5 individuals per morphospecies.  Specimens were labeled, photographed and all collateral data and images were uploaded to the project ‘Lepidoptera of Stanley Park’ (LBCS) in the Barcode of Life Database (BOLD) (Ratnasingham and Hebert 2007). From each specimen, one or two legs were removed and stored in an individual tube of a 96-tube sample box (Matrix Technologies).  Subsequent  94 analysis followed standard high-throughput DNA barcoding methods (Hajibabaei et al. 2005; deWaard et al. 2008a) with a few modifications.  Tissue was placed in a 96-well plate of proteinase K lysis buffer and incubated for roughly 18 hours. The lysate was then processed following the glass-fibre protocol of Ivanova et al. (2006) on a Biomek FXP liquid handler (Beckman Coulter).  For PCR amplification, 2 µl of DNA extract was added to each well of a premade PCR plate stored at -20°C and containing 2 ul of H2O, 6.25 µl of 10% trehalose, 1.25 µl of 10X buffer, 0.625 µl of 50 mM MgCl2, 0.0625 µl of 10 mM dNTPs, 0.06 µl of Platinum Taq polymerase (Invitrogen) and 0.125 µl of each of the 10 µM primers LepF1 and LepR1 (Hebert et al. 2004). The thermocycling conditions consisted of an initial denaturation at 94°C for 1 min, five cycles of 94°C for 30 sec, annealing at 45°C for 40 sec, and extension at 72°C for 1 min, followed by 35 cycles of 94°C for 30 sec, 51°C for 40 sec, and 72°C for 1 min, with a final extension at 72°C for 10 min.  The PCR reactions were visualized with the E-Gel 96 agarose electrophoresis system (Invitrogen) before performing the sequencing reactions, again in premade and frozen plates.  Both the forward and reverse direction plates contained 0.25 µl of Dye terminator mix v3.1 (Applied Biosystems), 1.875 µl of 5X sequencing buffer, 5 µl of 10% trehalose, and 1 µl of the respective 10 µM PCR primer.  Sequencing reactions were run at an initial denaturation at 96°C for 2 min, followed by 30 cycles of 96°C for 30 sec, annealing at 55°C for 15 sec, and extension at 60°C for 4 min.  The reactions were purified using the CleanSEQ system (Agencourt Bioscience) on a Biomek FXP liquid handler before being run on a 3730XL DNA Analyzer (Applied  95 Biosystems), all following manufacturer’s instructions.  Electropherograms were edited and aligned in Seqscape v. 2.5 (Applied Biosystems) and the resultant sequences were uploaded to BOLD. The identification engine of BOLD (BOLD-ID) was used for assigning tentative identifications, where possible, for all sequences. The reference barcode database for Lepidoptera used by BOLD-ID is continually validated by specialists ensuring accurate determinations (see http://www.lepbarcoding.org/campaign_nth_am.php for details).  An identification was considered definitive if a similarity score of 98.5–100% was obtained, and the match was with a single monophyletic species.  These barcode-assigned determinations were subsequently confirmed morphologically with comparison to reference specimens in regional insect collections (see below). Cases that were not assigned a definitive identification were keyed to species, performing genitalic dissections where necessary.  All specimens were deposited in the Royal British Columbia Museum, Victoria, BC (RBCM), Pacific Forestry Centre, Canadian Forest Service, Victoria, BC (PFCA), the Spencer Entomological Museum, University of British Columbia, Vancouver, BC (UBCZ), and the Canadian National Collection of Insects, Agriculture and Agri-Food Canada, Ottawa, ON (CNC). In order to explore the completeness of my inventory, I calculated accumulation curves using incidence-based methods.  Firstly, I used the method of Colwell et al. (2004) and Mao et al. (2005) to interpolate the curve for expected total and singleton species caught; the proportion of singletons can be indicative  96 of the completeness of the census (Longino et al. 2002).  Secondly, I calculated two robust (e.g. Chazdon et al. 1998; Summerville and Crist 2005) nonparametric estimators of species richness, the ICE (Lee and Chao 1994) and Chao 2 (Chao 1987) estimators.  The program EstimateS v. 8.0 (Colwell 2006) was employed for all analyses, computing curves as the mean of 1000 randomized species accumulation curves without replacement.  7.3 Results The 8 collections ranged from 41 to 225 moths per night for a total of 925 specimens.  The first attempt at barcoding the samples resulted in 912 being successfully amplified and sequenced; the sequences for the remaining 13 were obtained by simply repeating the procedures from extraction onwards.  A total of 895 specimens provided the full 658 base pair (bp) barcode region and the remaining samples ranged from 119 to 646 bp in sequence length.  The sequences and electropherograms are publicly available on BOLD and GenBank (accession nos. FJ412108–FJ413032), while DNA extracts are archived at -80°C at the Canadian Centre for DNA Barcoding in Guelph, Canada to allow validation and facilitate future biodiversity and genomic research (Hanner and Gregory 2007). The aligned sequences resulted in ~190 clusters with <3% sequence divergence (see below; Figure 7.1).  BOLD-ID unequivocally assigned 124 of these to species based on the complete BOLD database (Appendix H), and a  97 further 61 were tentatively placed to genus.  The length of sequence generated was not inhibitive for species assignment, as demonstrated previously (Hajibabaei et al. 2006b); the two shortest sequences (UBC-2007-0320 – 119 bp and UBC-2007-0322 – 172 bp) were both reliably assigned to Batia lunaris.  For the identifications assigned by barcoding, three generic assignments were later corrected to sister genera after morphological examination (UBC-2007-0481 to 0482 assigned to Pandemis sp., corrected as Argyrotaenia dorsalana; UBC- 2007-0180 to 0182, 0261 to 265, and 0485 to 0489: assigned to Clepsis sp., corrected as Argyrotaenia provana; and UBC-2007-0871 assigned to Battaristis sp., corrected as Coleotechnites sp. nr. coniferella).  For the 66 clusters not assigned to species or genus by BOLD-ID, 25 were identified by brief comparison with reference material, and the final 41 were identified following genitalic preparation. Following the barcoding and morphological examination, 190 species (or sub-generic taxa) representing 21 families were determined (Appendix G).  Due to incomplete taxonomy in some groups, particularly in the Microlepidoptera, 15 taxa have been given interim names (e.g. Acleris JFL01, Macaria signaria complex, Homosetia n. sp. nr. costisignella). Represented as a taxon-ID tree from BOLD (Figure 7.1), it is apparent that barcodes clearly delimit all species. The mean divergence between congeneric species is 9.50% (range = 1.541 - 15.327%, SE = 0.061%) and within species is 0.258% (range = 0 - 3.596%, SE = 0.007%) (Figure 7.2).   If an arbitrary threshold of 3% (Kimura 2-parameter distance) is set (Hebert et al. 2003a), all but 2 species pairs can be differentiated  98 (Dioryctria pseudotsugella/reniculelloides and Chionodes periculella/abella), and only 2 species display intraspecific divergences >3% (Perizoma grandis and Dasypyga alternosquamella) that would potentially inflate the estimation of species number. As is nearly universal in biodiversity inventories, a high prevalence of dominance and rarity was revealed by the identified collection.  Roughly two thirds of the species and individuals collected belong to 3 dominant families: the Geometridae (47 spp. / 338 specimens), Tortricidae (37/189), and Noctuidae (33/102).  On the other end of the spectrum, 93 species were collected in a single sample (uniques).  Similarly, 29 species are represented by only two specimens (doubletons) and 71 are represented by a single individual (singletons).  This large proportion of rare individuals indicates that the inventory likely remains incomplete. There is also a fairly high incidence of nonindigenous species: 31 introduced species that have evidently or presumably established were identified in the collection.  Among these, three species represent new records for North America (Argyresthia pruniella, Dichelia histrionana, and Paraswammerdamia lutarea) and one species has not been previously detected in BC (Prays fraxinella) (Table 7.1).  In the latter case, BOLD-ID indicated a close match between the single specimen (UBC-2007-0308) and two Eurasian Prays spp. (P. oleae – Spain; P. epsilon – South Korea).  Examination of genitalia indicated that the specimen was P. fraxinella, making it the second record for North America (the first was in Newfoundland in 1975; specimen held in CNC).  In addition to  99 these discoveries, two instances of potentially cryptic species were discovered: Dasypyga alternosquamella (3.27-3.60% divergence between clusters) and Nycteola sp. nr. cinereana (4.56-4.72% divergent from N. cinereana). The estimated incidence-based accumulation curves indicate that the number of species may be starting to approach an asymptote (Figure 7.3).  The two nonparametric estimators of total species richness (including the unsampled portion) intersected at a near-identical value: Chao 2 = 307, ICE = 309.  This represents a conservative, minimum estimate of richness (Longino et al. 2002), suggesting that the total nocturnal species present in the two collection localities may be over 60% higher than measured.  7.4 Discussion 7.4.1 Barcode recovery and success  The DNA barcoding of the fresh specimens was straightforward and the recovery of a sufficient fragment of COI for identification was made for all specimens.  A large proportion of the steps from specimen collection to identified material can be completed by non-specialists for three reasons.  Firstly, limited training and supervision is required for a technician or parataxonomist to collect insect specimens in the field, roughly separate them into morphospecies, prepare the specimens for museum deposition, and sample them for DNA analysis. Furthermore, if trapping methods (e.g. UV light traps, pitfall traps, flight interception traps) are employed, and specimens are not sorted to  100 morphospecies, the process becomes even further routine.  Secondly, the laboratory protocols are now highly refined, rapid, and undemanding (Hajibabaei et al. 2005; deWaard et al. 2008a) and many steps can be automated where laboratory infrastructure permits (e.g. Ivanova et al. 2006).  This allows technicians with minimal training and supervision to perform all necessary steps, and to complete them in small laboratory facilities.  And lastly, the process of barcoding itself not only identifies specimens that already exist in the sequence database, but they also limit and guide the downstream work of specialists by sorting unidentified specimens into operational taxonomic units (OTUs) that require examination and may provide higher taxonomic assignments (e.g. genus).  In the present study, 94% of individuals were placed to genus or better prior to a taxonomic specialist viewing the material. The present study demonstrates not only the successful recovery of barcodes, but the successful utility of barcodes for differentiating species of Lepidoptera, particularly at a small regional scale.  Although two species pairs display shallow inter-specific divergence and two species display deep intra- specific divergence, in all cases the barcode groups are distinct and monophyletic, and would not prevent a successful species assignment by COI. This perfect success rate is comparable to two recent studies on Lepidoptera, a 97.9% success rate in a tropical, regional study of 521 species (Hajibabaei et al. 2006a), and the 98.5% observed in a temperate, continental study of 1327 species (Hebert et al. 2010).   101 7.4.2 Inventory progress Facilitated by DNA barcoding, a first level inventory of Stanley Park is now complete.  While the list contains 190 species, several lack proper species epithets, and the nonparametric estimators suggest that a minimum of roughly 120 additional species remain to be sampled in the assemblage.  This is undoubtedly a conservative estimate as collecting was limited to two sites and several nights.  Moreover, Grimble et al. (1992) conducted a comparable inventory in the Pacific Northwest region and tallied 383 nocturnal moth species. Therefore, several recommendations can be made for further developing the inventory. First of all, continued work on the 15 taxa with interim names should reveal their identity.  Revisions for a few of the difficult groups are underway or completed (e.g. macarine geometrids – Ferguson 2008) and others are under examination as part of a continental campaign to barcode all North American Lepidoptera species (see http://www.lepbarcoding.org/campaign_nth_am.php). Secondly, with the asymptote in species number still not reached, it appears worthwhile to continue the barcode-assisted survey in the park.  Future surveys would be best suited to record but not analyze the common and distinctive species (e.g. Noctua pronuba, Gabriola dyari, Habrosyne scripta, Enypia packardata) and increase the sampling of difficult groups (e.g. Tortricidae) where singletons may be hidden in assumed morphospecies (e.g. Clepsis JFL01 within UBC-2007-0854 to UBC-2007-0858).  Other sampling methods should be added aimed at recovering species typically poorly attracted to light traps, particularly in  102 the Microlepidoptera.  Furthermore, sampling with light traps could be expanded to sample early spring and autumn flying species not sampled during this study, in addition to sampling unique microhabitats which likely harbour species not found at the two sampled sites. And lastly, specimens and species previously collected in the park and deposited in the regional and national insect collections can be verified and added to the checklist.  These recommendations would improve the taxonomic completeness of the survey, but the returns would diminish rapidly with increased effort.  However, for the purpose of producing a baseline on which to measure the effects of storms and other disturbances, the sampling design and effort are sufficient. 7.4.3 Highlights of the nocturnal lepidopteran fauna of Stanley Park  One interesting (and perhaps alarming) finding that can be drawn from the preliminary inventory is the high incidence of non-native species.  Nearly one in every 6 species encountered is exotic.  As surprising as this is, particular guilds might be even more skewed—Doğanlar and Beirne (1978) found that introduced species comprised 5 of the 6 most common and 8 of the 11 total species of leafrollers in Vancouver, Canada.  It is rather distressing that four new exotics were detected in a single collecting season.  This might be the product of the park’s close proximity to shipping ports, the high diversity of ornamental plants and other non-native hosts, and the disturbed condition of the park following the windstorms that allowed the populations to increase to a level that could be detected.   Another contributing factor could simply be the addition of DNA barcoding to the arsenal of detection (Armstrong and Ball 2005; Chown et al.  103 2008; Floyd et al. 2010; Chapter 5).  Typically an introduced species persists at low population densities before becoming established (Tilman 2004) so it is expected that few if any individuals will be collected.  Barcoding ensures these few individuals are not overlooked or lumped in with native species, by either matching an existing record in the database (e.g. Chapter 5), receiving a generic (or higher level) assignment (e.g. Prays fraxinella, this study) or by merely flagging the individuals as unique and requiring further scrutiny. The inventory has also brought another interesting finding to light—two instances that might represent previously overlooked species.  The first case, Nycteola sp. nr. cinereana is nearly 5% divergent from the typical ‘form’ of N. cinereana Neumoegen & Dyar and only ~1.5% divergent from one of the two forms of this species complex in Colorado (J.D. Lafontaine, pers. comm.).  The slight colouration and size differences of the two forms are not coupled with genitalic variation, nor are they in the two forms studied here.  The lack of genitalic differences does not necessarily suggest that these belong to a single species, but it does indicate that a single species with an ancient COI polymorphism is a viable hypothesis that requires further study.  Similarly, the second split representing a potentially cryptic species, that in Dasypyga alternosquamella Ragonot, 1887, is not paralleled with noticeable genitalic differences between the two distinct COI groups.  Interestingly, Heinrich (1956) reports that when Ragonot described D. alternosquamella, he also described with it a “variety” (considered a subspecies by the International Code of Zoological Nomenclature) that he called D. alternosquamella stictophorella. The  104 difference was a minor one in the forewing pattern which Heinrich considered a mere individual variant.  Pending further examination, it remains to be seen whether one of the groups represents Ragonot’s variety, a new species, or a COI polymorphism. 7.4.4 Conclusions  Biodiversity inventories must be rapid, reliable, and inexpensive (Coddington et al. 1996) but this ideal remains elusive for terrestrial arthropods. This study has demonstrated the accuracy and speed that DNA barcoding can contribute, as well as its potential for increased sensitivity for invasive and cryptic species detection, particularly at low densities.  In light of the dropping costs of DNA barcoding and the emergence of new technologies (Hajibabaei et al. 2007), incorporating genetic methods into faunal inventories will soon be more cost and time-effective than current morphological methods.  105 Table 7.1  Descriptions for four introduced moth species discovered in Stanley Park, Vancouver, Canada in 2007.   1 One unpublished record in the CNC from 1975 reared from ash. 2 Following its detection in BC, a series from Nova Scotia from the 1960s was discovered in the USNM (Washington).  Taxonomy Host plant(s) Distribution (outside BC) References  Paraswammerdamia lutarea  Maloideae (cottoneaster, Europe - widespread  Karsholt and (Haworth, 1828)   hawthorn, rowan)   Razowski 1996  Prays fraxinella  Fraxinus excelsior (ash) Europe – widespread,  Karsholt and (Donovan, 1793)   Newfoundland1  Razowski 1996  Dichelia histrionana  Picea (spruce) and Abies (fir) Europe including Sterling & Ashby (Frölich, 1828)   Scandinavia and British 2006    Isles, E to Caucasus  Argyresthia pruniella  Rosaceae (stone-fruit cultures)  Europe and Asia Minor,  Agassiz 1996; (Clerck, 1759)    Nova Scotia2  Karsholt and     Razowski 1996   106 Figure 7.1  Neighbour-joining tree of the nocturnal Lepidoptera collected in Stanley Park, Vancouver, Canada in 2007. Two specimens are excluded (UBC-2007-0320 and UBC-2007-0322) due to short COI sequence length.  The number of specimens collapsed into a single node is given in parentheses after the taxon name.  107  108  109  110   111 Figure 7.2  Distance summary of the 925 COI barcodes generated for the Stanley Park moth specimens.  a) histogram of intraspecific divergences for the 190 species (or subgeneric taxa), and b) histogram of congeneric distances for 441 individuals (3175 comparisons).   112 Figure 7.3 Species richness and inventory completeness estimates. Observed species richness, observed singletons and ICE and Chao 2 estimators as a function of sampling effort (collection nights) for the inventory of nocturnal Lepidoptera in Stanley Park, Vancouver, Canada conducted in 2007.        113 8 Effect of harvest type on three levels of moth diversity in research forests of British Columbia   Synopsis: In this chapter, I use the barcode library and molecular phylogeny generated earlier in the dissertation to investigate the effect of logging methods on three levels of moth diversity.  Experiments are conducted at two silvicultural research forests with similar harvest treatments that span the gradient of disturbance imposed by silviculture, from unmodified primary forest to clear-cut treatments.  Species, genetic and phylogenetic diversity are compared across treatments and used to test hypotheses on the impacts on diversity of intermediate levels of disturbance and the correlation of different levels of diversity following disturbance.  8.1 Introduction If we are to have any hope of halting the accelerating loss of terrestrial biodiversity resulting from anthropogenic modification and degradation of forest ecosystems, it is essential that we refine and retool our approaches to inventorying and assessing forest biodiversity.  While satellite-based remote sensing has transformed our abilities to appraise biodiversity at the level of ecosystems (e.g. Kerr and Ostrovsky 2003), we remain severely limited at finer scales where our knowledge rests primarily on studies of vertebrates, plants and other ‘indicator’ or ‘umbrella’ species (Andelman and Fagan 2000).  Hyper- diverse arthropod assemblages dominate these ecosystems (Southwood et al.  114 1979, Stork 1988), but only a select few—those easily identified (dragonflies, butterflies) or in well-studied systems (e.g. ants, carabid beetles)—are routinely subjects of inventories and assessments.  The barriers inhibiting the inclusion of other arthropod taxa are well documented (e.g. Smith et al. 2005, 2009; Caesar et al. 2006; deWaard et al. 2009; Packer et al. 2009; Smith and Fisher 2009): large samples, damaged specimens, a disproportionate number of species at low density, lack of taxonomic expertise, and inadequate taxonomic resources. These factors primarily restrain two critical stages, sorting and identification, which generally far surpass the length of all other stages combined (Marshall et al. 1994).  Fortunately the recent application of DNA barcoding has proven invaluable for accelerating these stages by providing informed sorting and species identifications, consequently reducing specialist time and enhancing sensitivity at low density (Janzen et al. 2005; Caesar et al. 2006; deWaard et al. 2009).  Following the sorting and discrimination of species, it is then possible to construct species inventories for sampled regions and quantify numerous species diversity metrics such as richness, abundance, and turnover. Furthermore, the barcode sequence data may also provide measures for other levels of biodiversity often neglected, namely genetic and phylogenetic diversity, each with their own unique importance to ecosystems.  Increased genetic diversity enhances population performance (e.g. Booy et al. 2000), increases species survival under changing environmental conditions (Spielman et al. 2004), and decreases a species’ extinction risk (Newman and Pilson 1997).  Higher  115 phylogenetic diversity relates to more ancient evolutionary heritage (since species vary dramatically in their evolutionary isolation) and has been proposed as an important metric for conservation prioritization (Faith 1992; Faith and Baker 2006) and future utility (Forest et al. 2007).  Employing DNA barcoding as a tool for inventories and assessments thus opens the door to a more complete approach to measuring biodiversity in these ecosystems.  Investigations of the response of forest ecosystems to disturbance, such as fire, severe windthrow or logging, could benefit greatly from this holistic barcode approach to measuring diversity of hyper-diverse taxa.  First of all, there is a heavy bias in most studies towards low to moderately diverse groups (e.g. Prendergast et al. 1993, but see Lawton et al. 1998), to vertebrates, plants and other indicator taxa (Howard et al. 1998; Ford et al. 2000; Moore et al. 2003; Noss 1999), or a tendency to assign taxa to morphospecies or higher taxonomic ranks (e.g. family) (e.g. Robinson and Tuck 1993; Balmford et al. 1996; Summerville and Crist 2002). These practices may be providing under- or overestimates of the whole forest community (Lawton et al. 1998; Ferrier et al. 2004; Krell 2004), which would in turn, prevent generalizing these perceived perturbation effects to other taxa.  Secondly, the ability to estimate multiple levels of diversity is important for exploring their inter-relationships.  There is substantial evidence suggesting species and genetic diversity are correlated following disturbance (Vellend 2003; Cleary et al. 2006) but that phylogenetic diversity and species diversity may (Rodrigues and Gaston 2002; Pérez–Losada and Crandall 2003; Prado et al. 2010) or may not be decoupled (Faith 1992; Forest et al. 2007;  116 Moritz and Faith 1998).  The ability to use one level as a proxy for one or more other diversity levels would be advantageous (Smith and Fisher 2009).  Finally, it would be valuable for investigations of forest disturbance to increase their capacity to inventory over space and time, for instance, to improve statistical power or cover the entirety of ecological succession.  While follow-up inventories using a morphological approach would not see a marked improvement in ease or efficiency, the barcoding approach scales well (Smith et al. 2005), increasing in efficiency as the reference database is parameterized.  Moreover, barcoding is particularly amenable to next generation sequencing technology (Hudson 2008), which should increase the scale of efficiency by orders of magnitude.  All of these potential benefits can result in post-disturbance research with both a finer scale and expanded scope, a necessary first step to mitigating forest biodiversity loss.  In the present study, I employ the barcode approach to inventory and assess the effects of forest disturbance in the hyper-diverse Lepidoptera. I measure moth diversity in two disparate research forests with similar experimental treatments that span the continuum of forest modification imposed by silviculture, from unmodified primary forest to clear-cut stands. The barcode database previously parameterized (see Chapter 2,3) allows for informed sorting and species-level identification, providing tallies of species abundance and richness; the barcode sequenced for each individual, provides a measure of genetic diversity (e.g. haplotype diversity); and community phylogenies (constructed using a backbone phylogeny to constrain the COI sequence data) provide an estimator of phylogenetic diversity. These three levels of diversity will  117 be calculated for each treatment and analyzed to test two hypotheses; first, that a moderate increase of modification to the forest ecosystem results in an increase in diversity (e.g. Connell 1978; reviewed in Sousa 1984); and second, that the effects on different levels of diversity are correlated following disturbance (Vellend 2003; Cleary et al. 2006).  My study thus has three objectives: 1) construct preliminary species inventories and DNA barcode libraries for two research forests, b) explore the effects of harvest types on three levels of diversity, and c) investigate the interplay between the three levels.  8.2 Materials and methods 8.2.1 Description of experimental sites Two silvicultural research forests were chosen for the post-disturbance experiments: the Date Creek Silvicultural Systems site near Hazelton in north- central BC and the Sicamous Creek Silvicultural Systems site near Sicamous in south-central interior BC (Figure 8.1a). Date Creek is contained within the moist cold subzone of the Interior Cedar–Hemlock (ICH) biogeoclimatic zone (Pojar et al. 1987).  It is a rolling morainal landscape at approximately 450m above sea level where western hemlock (Tsuga heterophylla [Raf.] Sarg.) dominates, but is mixed with western redcedar (Thuja plicata Donn ex D. Don in Lamb), subalpine fir (Abies lasiocarpa [Hook.] Nutt.), lodgepole pine (Pinus contorta var. latifolia Engelm.), and the hybrid complex of white spruce (Picea glauca [Moench] Voss) and Sitka spruce  118 (P. sitchensis [Bong.] Carr.).  Experimental blocks of roughly 20 ha were harvested in 1992–93 and eight blocks were sampled in the present study (Figure 8.1b): A-3 and B-4 are clearcut (CC) treatments where all merchantable trees were harvested; B-2 and B-3 are heavy removal (HR) treatments where ~60% of basal area was removed in small patch cuts; A-2 and B-5 are light removal (LR) treatments where ~30% of basal area was removed in single or small groups of stems; and A-4 and B-1 are no harvest (NH) controls of ~150– 370 year old undisturbed forest. A detailed description of the harvest treatments and associated research is provided by Coates et al. (1997). Sicamous Creek falls within the wet cold subzone of the Engelmann Spruce – Subalpine Fir (ESSF) biogeoclimatic zone (Pojar et al. 1987).  It is a subalpine forest at an altitude of approximately 1650m, exemplified by low temperatures, high winds, and deep snowfalls. It is dominated by two conifer species, subalpine fir (Abies lasiocarpa [Hook.] Nutt.) and Engelmann spruce (Picea engelmanni Parry ex Engelm.), and governed by a short growing season. Experimental blocks of roughly 30 ha were harvested in 1994–95 and eight blocks were sampled in this study (Figure 8.1c): A-4 and C-3 are clearcut (CC) treatments where one 10 ha opening was cut; A-2 and B-1 are heavy removal (HR) treatments where 0.1 ha patch cuts were made; A-3 and C-3 are light removal (LR) treatments where individual tree selection was employed; and A-1 and B-2 are no harvest (NH) controls of ~150–350 year old undisturbed forest.  A summary of the harvest treatments and research conducted at Sicamous Creek is given by Huggard and Vyse (2003).  119 8.2.2 Moth sampling  Lepidoptera diversity was assessed for the eight blocks at each of the two sites i.e. two CC blocks, two HR blocks, two LR blocks, and two NH control blocks (16 blocks in total).  I sampled nocturnal, phototactic moths using 22 W ultraviolet light traps (model 2851; BioQuip, Gardena, CA) powered by a 12 V (26 Ah) sealed lead acid battery (Discover Energy Corp., Vancouver, BC).  Traps were placed near the centre of the treatment, >100m from any block edge, at roughly 1 m above the ground.  Moths that entered the trap through the funnel were killed by ethyl acetate, dispensed through evaporation using a mason jar and sponge wick. One trap was placed in each of the eight blocks, and all traps in one site (i.e. Date Creek or Sicamous Creek) were run on the same evening from dusk until dawn.  Preliminary collections were made in 2008, and comprehensive sampling was done tri-weekly from May (Date Creek) or June (Sicamous Creek) until September 2009, which should have encompassed the flight period for nearly all nocturnal moth species.  This sampling strategy was chosen to standardize sampling effort and facilitate comparisons between harvest treatments, as opposed to an ‘optimized protocol’ that would provide a more comprehensive species inventory (Cardoso et al. 2009).  Trap samples were kept at -20ºC until processing.  Specimens were sorted to morphospecies and a proportion was pinned, imaged, and databased on Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert 2007).  For each trap, a synoptic sample (i.e. a single specimen of each morphospecies) was selected for barcode analysis and the abundance of each was recorded.  In  120 cases where delimiting morphospecies was ambiguous (e.g. many micromoth families, Eupithecia geometrids, Diarsia noctuids) all specimens were analyzed. Additionally, in morphospecies with eight or more individuals, eight specimens were selected for analysis to permit estimates of genetic diversity. 8.2.3 DNA analysis  DNA barcoding followed standard protocols, the details of which can be found in Hajibabaei et al. (2005), Ivanova et al. (2006), and deWaard et al. (2008a).  In short, a small tissue sample was removed from each specimen and placed in an individual well of a 96-well microplate. DNA extraction, amplification, and sequencing of the barcode region of the mitochondrial cytochrome c oxidase I (COI) gene were then completed at the Canadian Centre for DNA Barcoding in Guelph, Canada.  Amplification and sequencing was successful with the full- length primers LepF1 and LepR1 (Hebert et al. 2004) for nearly all specimens, but the ‘Lep mini primers’ MLepF1 and MLepR1 (Hajibabaei et al. 2006a) were used in cases where they were not. The electropherograms were edited and aligned in Seqscape v. 2.5 (Applied Biosystems) before being deposited along with the edited sequences to BOLD and GenBank.  Each resultant sequence was run through the identification engine of BOLD (BOLD-ID; http://www.barcodinglife.org/views/idrequest.php) for tentative species determinations.  Identifications were considered definitive if a similarity score of 98.5–100% was obtained, and the match was with a single monophyletic species. The database provided species identifications for nearly all specimens (exact proportion not recorded), but unique sequences and ambiguous cases  121 were determined to species morphologically.  All tentative identifications were confirmed morphologically by brief comparison with reference specimens in regional and national insect collections.  I followed the nomenclature of Lafontaine and Schmidt (2010) for the Noctuoidea and Powell and Opler (2009) for the remaining taxa.  Voucher specimens were deposited in the Canadian National Collection of Insects, Arachnids and Nematodes (Ottawa, ON), Royal British Columbia Museum (Victoria, BC), Pacific Forestry Centre (Victoria, BC), and University of British Columbia’s Spencer Collection (Vancouver, BC). 8.2.4 Data analysis Upon completion of the species identifications, I tallied the number of species and number of individuals per species for each collecting event.  This data was then entered into the program EstimateS v. 8.0 (Colwell 2006) to explore the completeness of the two inventories—for Date Creek and for Sicamous Creek.  I calculated accumulation curves for species observed, species estimated (Chao 1 estimator; Chao 1987), and singleton species by computing 1,000 randomized accumulation curves without replacement, following the method of Colwell et al. (2004) and Mao et al. (2005). For measuring and comparing three levels of moth diversity, I pooled data from the 16 blocks into eight block types: 1) Date Creek – clearcut (CC), 2) Date Creek – heavy removal (HR), 3) Date Creek – light removal (LR), 4) Date Creek – no harvest (NH), 5) Sicamous Creek – CC, 6) Sicamous Creek – HR, 7) Sicamous Creek – LR, and 8) Sicamous Creek – NH.  Rarified diversity values,  122 along with measures of variance, were calculated for each block type for each level of diversity. Estimates of species diversity were measured by tabulating the number of species and individuals for each collecting event within the block types. EstimateS v 8.0 (Colwell 2006) was used for rarefaction by generating species accumulation curves for each block type, which in turn, were used to interpolate mean species richness values at the largest common sample size for each site (n = 936 individuals for Date Creek, n = 561 for Sicamous Creek). The COI barcode fragment sequenced for each individual was used to provide a measurement of genetic diversity for each block type.  First, the species that had seven or more full-length COI sequences within a block type were determined, and all sequences from these species were assembled into eight FASTA files, one for each block type.  The unique haplotypes were determined and tabulated using FaBox (Villesen 2007), then compiled for input into EstimateS v. 8.0 (Colwell 2006).  As above, accumulation curves were computed to interpolate mean haplotype richness values at the largest common sample size for each site (n = 19 species for Date Creek, n = 13 for Sicamous Creek). Phylogenetic diversity was calculated using species tallies and COI-based community phylogenies.  For each of the eight block types, I estimated a maximum-likelihood phylogeny using the COI sequences of each resident species.  Because any single gene has limited phylogenetic signal, and COI may  123 be inadequate at deep evolutionary levels (Wilson 2010), the trees were constrained by well-supported phylogenetic relationships (Appendix H) based on several previous studies (Kristensen and Skalski 1999; Regier et al. 2009; Mutanen et al. 2010; Zahiri et al. in press; Chapter 4).  Trees were generated in Garli 1.0 (Zwickl 2006) using the general-time-reversible substitution model with among-site-rate-heterogeneity modeled according to a gamma distribution, and an estimated proportion of invariant sites.  Newick tree files containing the topological constraints were assembled using FigTree v. 1.3.1 (Drummond and Rambaut 2007) and a text editor.  The resultant trees provided the reference topologies and branch lengths to calculate total phylogenetic diversity (Faith 1992) for each block type, as implemented in R version 2.8.1 (R Development Core Team 2008) and the packages APE (Paradis et al. 2004) and CAIC (Orme et al. 2008).  Phylogenetic diversity was rarified using the procedure of Zhou et al. (2009) using 1000 bootstraps at a common sample size for each site (n = 140 species for Date Creek, n = 80 for Sicamous Creek). With all three diversity measures calculated, one-way analysis of variance (ANOVA) followed by Tukey’s HSD post hoc tests were used to evaluate differences in diversity according to the independent variable of block type.  Each measure of diversity (species, genetic, and phylogenetic) was analyzed separately against block type, which had 4 subcategories: clear-cut, heavy removal, light removal, and no harvest.  To explore the strength of association between a) species and genetic diversity, b) species and phylogenetic diversity, and c) genetic and phylogenetic diversity, Pearson Product Moment correlation  124 tests were employed on rarified diversity estimates sampled spatially as in Cleary et al. (2006).  All statistical analyses, unless noted, were conducted in SPSS v17 (IBM), and the level of significance was set at P = 0.05.  Charts were plotted with SigmaPlot (Systat Software Inc.).  8.3 Results A total of 7978 moths were collected at Date Creek over seven nights of trapping and 56 trapping events.  Considerably fewer individuals were caught at Sicamous Creek—2926 total moths from seven nights and 52 samples.  Trap samples averaged roughly 142 individuals at Date Creek (range = 0 – 1281) and roughly 56 (range = 0 – 260) at Sicamous Creek.  The 108 trap samples were individually sorted to morphospecies and 6117 specimens were selected for labeling, imaging, vouchering and DNA analysis.  Of the 6117 specimens, 98.1% were successfully amplified and sequenced with the full-length primers on the first attempt.  A second attempt using the ‘lep mini-primers’ resulted in only 16 specimens (0.03%) that were not successfully barcoded. All but ten sequences were greater than 500 bp and meet the ‘BARCODE data standard’ (see Hubert et al. 2008).  The sequences, trace files, images, voucher information, collateral data, and GenBank accession numbers are publicly available on BOLD in the projects ‘LBCDC Lepidoptera of BC - Date Creek’ and ‘LBCSC Lepidoptera of BC - Sicamous Creek’.  The DNA extracts are archived at -80°C at the Canadian Centre for DNA Barcoding in Guelph, Canada.  125  Tentative identifications were assigned by BOLD-ID to 342 of the roughly 440 clusters/morphospecies and were subsequently confirmed morphologically. Representatives of the remaining clusters were brought to the Canadian National Collection of Insects, Arachnids, and Nematodes for comparison with the reference collection.  This comprised 11 morphospecies of macromoths (8 of which were Euxoa spp., a notoriously difficult genus with 183 species in North America (Lafontaine and Troubridge 2010)), and ~88 species of Microlepidoptera.  Brief comparison to reference material provided identifications for 22 of these taxa, while the remainder required further investigation and dissections.  Presently, 63 species have interim taxonomic assignments (e.g. Elachista sp. JFL01, Scrobipalpa sp. nr. atriplicella, and Choristoneura occidentalis group) due to incomplete taxonomy, inadequate literature for identification, and pending descriptions and revisions.  The identified collections resulted in 441 total species from both sites. Only a single species was not clearly delimited by DNA barcodes, the species Antepirrhoe (=Eustroma) semiatrata (Hulst) was paraphyletic with respect to Antepirrhoe fasciata Barnes & McDunnough. For Date Creek, the mean divergence between congeneric species was 4.79% (range = 0.30 – 17.09%, n = 143) and within species was 0.29% (range = 0 – 8.56%, n = 224), a 16.5-fold difference (Figure 8.2a).  For Sicamous Creek, the congeneric divergence averaged 8.42% (0.92 – 15.31%, n = 78) compared to the average intraspecific divergence of 0.073% (0 – 8.29%, n = 121), a 115-fold difference (Figure 8.2b). The mean number of barcodes per species was 11.6 for Date Creek (109  126 species with one barcode; max = 360, Diarsia dislocata Smith) and 10.9 for Sicamous Creek (84 species with one barcode; max = 370 barcodes for Eulithus destinata Möschler).  The total of 441 species inventoried are a diverse assemblage representing 29 families (Table 8.1).  The Date Creek inventory (Table 8.1, Appendix I) is composed of 333 species from 27 families, the Sicamous Creek inventory (Table 8.1, Appendix J) has 206 species from 24 families, and 98 species are found at both sites.  Even single traps were often extremely diverse — a single trap at Date Creek (A-3, light removal) collected 96 species in one evening.  The dominant families of Noctuidae, Geometridae and Tortricidae have the highest diversity of species; in terms of abundance, Crambidae and Phyllocnistidae uncharacteristically exceed Tortricidae, due to large numbers of the two species Scoparia biplagialis Walker and Phyllocnistis populiella Chambers, respectively.  The two sites also have a large proportion of species caught only once — Date Creek has 106 singletons and Sicamous Creek has 82. This suggests the inventories are incomplete, which the accumulation curves corroborate by failing to reach asymptotes (Figure 8.3).  The estimators indicate the inventories are no more than 68.1% (Chao 1 estimate for Date Creek = 489, 95% CI = 426 – 595) and 60.1% (Chao 1 estimate for Sicamous Creek = 343, 95% CI = 281 – 455) complete, respectively. Moreover, most of the block types appear to be under sampled and have not reached an asymptote, with the possible exception of the CC and LR treatments at Sicamous Creek (Figure 8.4).  127  Species diversity, represented by rarified mean species richness, varied substantially between block types (Table 8.2). The effect of block type at Date Creek, when interpolated to the subsample size of 936 individuals, was significant (ANOVA, F[3,4] = 26.2, p < 0.01) with CC higher than HR and LR, which in turn, were higher than NH (Tukey’s HSD, p < 0.05) (Figure 8.5a). The effect of block type was not significant for Sicamous Creek (ANOVA, F[3,4] = 1.9, p > 0.1) (Figure 8.5b). The pattern for observed (i.e. non-rarified) species richness was nearly opposite (Figure 8.5a,b).   Genetic diversity, as calculated by haplotype diversity, did not reveal marked differences between block types (Table 8.2). The effect of block type on rarified haplotype diversity, interpolated to the subsample sizes of 19 and 13, respectively, was not significant for Date Creek (ANOVA, F[3,4] = 2.8, p > 0.1) (Figure 8.5c) or Sicamous Creek (ANOVA, F[3,4] = 1.2, p > 0.1) (Figure 5d). Observed haplotype richness closely paralleled the pattern of observed species richness (Figure 8.5c,d).  Phylogenetic diversity estimates, computed sensu Faith (1992), displayed sizeable differences between block types (Table 8.2).  The effect of block type on rarified phylogenetic diversity was significant for Date Creek (ANOVA, F[3,4] = 191.8, p < 0.001) with the NH control having higher phylogenetic diversity than the CC treatment, which in turn were higher than LR and HR (Tukey’s HSD, p < 0.05) (Figure 8.5e).  There was also a significant effect of block type on rarified phylogenetic diversity for Sicamous Creek (ANOVA, F[3,4] = 36.7, p < 0.01), but with an unexpected pattern of CC with a significantly higher value than LR, and  128 the NH control significantly lower than all three treatments (Tukey’s HSD, p < 0.05) (Figure 8.5d).  The pattern of observed phylogenetic diversity resembled that of the rarified estimates (Figure 8.5e,f).  Exploring the strength of association between levels of diversity revealed a significant correlation between species diversity and genetic diversity (Pearson Product Moment correlation test, n = 8, R = 0.77, p = 0.02) (Figure 8.6a).  This correlation remained significant when the two NH controls were removed (Pearson Product Moment correlation test, n = 6, R = 0.84, p = 0.03).  There was no significant correlation between species diversity and phylogenetic diversity (Pearson Product Moment correlation test, n = 8, R = 0.45, p = 0.3) (Figure 8.6b) or genetic diversity and phylogenetic diversity (Pearson Product Moment correlation test, n = 8, R = 0.44, p = 0.3) (Figure 8.6c).  8.4 Discussion 8.4.1 DNA barcoding for inventorying and monitoring  The extent to which DNA barcoding can assist with terrestrial arthropod inventories and repeated surveys of multiple sites cannot be overstated.  In the present study, two preliminary inventories of a difficult, species-rich fauna were completed in parallel with repeated surveys of 16 sites.  The sorting was straightforward and conservative, and errors were undoubtedly avoided by my being able to barcode all ambiguous specimens.  This is critical for Lepidoptera in particular, as morphological species diagnosis is generally accomplished  129 through forewing characters that are easily ‘rubbed’ away in nature, collection, or preparation.  In the near future, it will become unnecessary to sort specimens prior to genetic analysis, but instead homogenize entire trap samples and analyze them with next generation sequencing protocols (Hudson 2008).  The laboratory stage of my study was also routine and the use of well-tested universal primers provided near-perfect barcode recovery.  The identification engine of BOLD provided tentative species determinations for over three- quarters of the species, drastically reducing specialist time (Caesar et al. 2006; deWaard et al. 2009).  It also permitted identifications of species at low density, which may be too damaged or not prepared appropriately for morphological determination (Packer et al. 2009).  This is particularly noteworthy for Microlepidoptera where diagnostic characters are often not found on the forewings, but on hindwings and mouthparts, necessitating careful spreading that would have increased the time of specimen preparation by at least an order of magnitude.  It is evident that the 145 singleton species observed in my study (not to mention the entire 441 species), would not have been detected or diagnosed morphologically without an overwhelming increase in time, resources and expertise.  The utility of DNA barcodes was once again assessed in the present study, and produced positive results.  Only a single species did not form a distinct and monophyletic barcode cluster, but is contained within a genus currently under revision (Antepirrhoe, JRD unpublished).  The high success rate of barcoding, due to the observed pattern of distinct distributions of intra- and  130 interspecific divergence with minimal overlap, can now be considered typical of regional studies, particularly in Lepidoptera (Hajibabaei et al. 2006a, deWaard et al. 2009, Hebert et al. 2010, Lukhtanov et al. 2009).  An interesting outcome from this divergence analysis was the discrepancy between the two collection sites with respect to congeneric divergence.  There was significantly higher divergence between congeneric species at Sicamous Creek (8.42%) than at Date Creek (4.79%) (Welch’s unpaired t-test, t = 336.0559, df = 145, p < 0.0001).  One possible explanation for this is the ~1200m difference in elevation between the two sites.  Ecological and physiological constraints that restrict species distributions and dispersal across altitudinal gradients may increase genetic differentiation with elevation (Ghalambor et al. 2006; Rodríguez-Castañeda et al. 2009).  This requires further investigation, but highlights one of the ancillary benefits of DNA barcoding—insights into molecular evolution (Costa and Carvalho 2010).  The additional estimates of two levels of diversity that DNA barcoding facilitates is a vital improvement to forest biodiversity and post-disturbance science.  It has long been appreciated that biological diversity encapsulates a hierarchy that spans from genes to ecosystems (Wilson 1988; McNeely et al. 1990).  Conservation biologists above all, when allotting limited efforts and resources, for example when prioritizing protection of natural areas, must consider all levels of diversity to maximize gains and future options (Humphries et al. 1995).  The present study proposes a DNA barcode-based methodology that allows the assessment of three levels of diversity with negligible increased  131 effort.  Subsequent studies will need to comprehensively evaluate the utility of COI for estimating these two new levels, directly comparing them with estimates derived from other genetic markers and approaches.  In the event that this single-gene perspective is biased or inaccurate, it will be necessary to supplement the COI gene with one or more markers that are rapidly–evolving (e.g. mitochondrial control region, internal transcribed spacer, nuclear introns) for genetic diversity estimates and more conserved (e.g. nuclear protein-coding genes) for phylogenetic diversity estimates, perhaps in a multiplex amplification approach (Henegariu et al. 1997). 8.4.2 Inventories of two British Columbia research forests  The completion of two preliminary lepidopteran inventories is a significant achievement relative to the few completed in the Pacific Northwest to date.  The only other inventories for British Columbia are presented by Fisher et al. (2000) and deWaard et al. (2009; Chapter 9); only three more have been completed in Oregon (McFarland 1963; Parsons et al. 1991; Grimble et al. 1992), although there have been considerably more in surrounding regions (see Pohl et al. 2010; Powell and Opler 2009).  These two should have particular value due to their location in active silvicultural research systems, where providing both a vouchered reference collection in the regional museums and a DNA barcode library will facilitate identifications.  Furthermore it will now be possible to explore moth diversity at the landscape level of temperate forests, and investigate for instance patterns of beta diversity.  Combined with host plant data from the Forest Insect and Disease Survey (Van Sickle et al. 2001), this would be a  132 worthwhile contribution to the ongoing debate on geographic isolation and ecological specialization in temperate versus tropical forest ecosystems (Dyer et al. 2007; Novotny et al. 2007; Craft et al. 2010). 8.4.3 Effect of harvest type on moth diversity Interpretation of the results exploring the influence of harvest type on moth diversity is not straightforward, but several conclusions can be made.  First, there was no support for the intermediate disturbance hypothesis (Connell 1978) at either of the sites, nor at any level of diversity; in all six comparisons (Figure 8.5), the light removal treatment never had the significantly highest value of diversity. For the three comparisons with a significant effect of block type on diversity, the extreme block types, clearcut and no harvest, had the highest diversity values — NH contained the highest phylogenetic diversity at Date Creek, whereas CC contained the highest values for species diversity at Date Creek and phylogenetic diversity at Sicamous Creek. This is in stark contrast to several temperate (Summerville and Crist 2002) and tropical forest studies (Hamer et al. 1997; Intachat et al. 1997; Spitzer et al. 1997; Walpole and Sheldon 1999; Willott et al. 2000; Cleary et al. 2006) that have demonstrated highest species richness in moderately disturbed forest relative to proximate clearcut or unlogged stands.  One explanation for this might be that the results are confounded by the migration and dispersal of ‘tourist species’ from adjacent blocks, perhaps made evident by a large number of potentially transient singleton species (Brehm and Fiedler 1999).  This effect would be minimized by removing singleton species from the analysis (Brehm and Fiedler 1999) or concentrating  133 on taxa with weak flight ability and low propensity to migrate, such as the Geometridae (Nieminen 1986, Doak 2000).  Another possibility is that the sampling within block types was insufficient to detect a consistent pattern, and instead a random fraction of the community was sampled (Cardoso et al. 2009), which may be in line with the species accumulation curves failing to reach asymptotes. The second general conclusion from the analysis of moth diversity is that the estimation and comparison of genetic diversity was inconclusive and perhaps suboptimal.  There was no detectable pattern for rarified estimates of haplotype richness, which suggests that variation in the COI marker (or the measure of it used here) is insufficient to track the true differences in diversity between block types; that migration and gene flow between block populations has homogenized the gene pool; or both. Ostensibly there appears to be ample variation in COI based on the average haplotypes/species (3.57) in the genetic diversity calculations.  And while many species of moths move short distances and rarely colonize patches over one kilometer from their larval host (e.g. Nieminen 1986, Doak 2000), results could again be confounded by migrant taxa with strong flight ability (e.g. noctuids).  In any case, as stated above, it is necessary for future work to further investigate the utility of COI for the function of estimating genetic diversity.  Finally, in light of results contradictory to previous studies, it is necessary to re-evaluate the use of light traps for monitoring the effects of disturbance. While it is undoubtedly one of the best ways to undertake insect surveys  134 (Holloway 1980; Gadagkar et al. 1990), and was effective in a similar post- disturbance appraisal of temperate forest moth diversity (Summerville and Crist 2002), there remains a large number of variables that affect the size and composition of light-trap catches (Bowden 1982) and consequently, many authors feel it is unlikely to provide a true reflection of the fauna (Southwood 1978).  My standardized approach, using identical traps, for identical duration and on the same evenings, should remove most variables, but variation in microhabitat and microclimate were unavoidable.  A comparison of light trap captures with that of flight intercept traps, such as a Malaise trap, would be worthwhile. 8.4.4 Interplay of three levels of moth diversity  Any associations between different levels of diversity can have a direct impact on conservation and management decisions and broaden our understanding of post-disturbance diversity effects.  In the present study, I determined a positive correlation between species and genetic diversity, but not between species and phylogenetic diversity or between genetic and phylogenetic diversity.  The former strongly supports the species-genetic diversity correlation proposed by Vellend (2003), founded on island biogeography theory (MacArthur and Wilson 1967), and previously validated by forest herbs (Vellend 2004), rainforest butterflies (Cleary et al. 2006), sand dune shrubs (He et al. 2008), freshwater snails (Evanno et al. 2009), and grassland herbs (Odat et al. 2010). In contrast to these previous studies that assessed variation in genetic diversity using a single species, I present the first assessment based on multiple species.  135 This association is of significant importance for conservation biologists who must infer the value and distribution of biodiversity to mitigate loss from forest modification and degradation.  This permits the use of one diversity level to act as a surrogate for the other, reducing valuable time and resources.  While species diversity is unquestionably the most commonly assessed level, it may prove advantageous to avoid species diagnosis by adopting a solely molecular diversity assessment, particularly in taxonomically understudied taxa.  Faith and Baker (2006) have indeed suggested this as an application of DNA barcoding, but for the calculation of phylogenetic diversity, and employing it as a surrogate for species diversity.  The lack of association of phylogenetic diversity with the other two levels (as in Faith 1992; Forest et al. 2007; Moritz and Faith 1998) should not discourage its measurement in this fashion, but should caution generalizing its estimates with other levels of diversity.   136 Table 8.1 Summary of moths from each collection site. Classification follows Powell and Opler (2009) with the exception of Noctuoidea (Erebidae, Noctuidae and Nolidae here), which has recently been reorganized (Lafontaine and Schmidt 2010); Erebidae is broken done to the subfamily level to allow comparison with previous studies.  Taxon Number of species Number of individuals  Date Ck. Sicamous Ck. Date Ck. Sicamous Ck.  Argyresthiidae 7 2 141 3 Blastobasidae 1 0 4 0 Coleophoridae 7 1 28 2 Crambidae 17 14 1312 103 Depressariidae 1 1 1 4 Drepanidae 7 2 95 8 Elachistidae 1 0 1 0 Erebidae 11 5 151 11 Arctiinae 2 2 81 3 Lymantriinae 3 1 11 1 Catocalinae 1 0 2 0 Hypeninae 0 1 0 1 Hypenodinae 2 0 7 0 Herminiinae 2 0 49 0 Herminiinae 0 1 0 6 Rivulinae 1 0 1 0 Gelechiidae 24 4 138 74 Geometridae 81 57 2411 1418 Gracillariidae 9 2 10 3 Lasiocampidae 1 2 28 8 Lyonetiidae 1 1 9 8  137 Taxon Number of species Number of individuals  Date Ck. Sicamous Ck. Date Ck. Sicamous Ck.  Momphidae 1 3 14 6 Noctuidae 68 64 1538 785 Nolidae 0 1 0 1 Notodontidae 9 2 102 2 Oecophoridae 3 2 4 2 Phyllocnistidae 2 2 1184 15 Plutellidae 1 1 2 1 Pterophoridae 3 5 17 16 Pyralidae 6 6 51 31 Scythrididae 1 1 5 34 Sphingidae 2 1 55 1 Tineidae 7 0 14 0 Tortricidae 60 26 565 389 Uraniidae 1 0 96 0 Yponomeutidae 1 0 2 0  Total 333 206 7978 2926   138 Table 8.2 Moth diversity and abundance totals for the eight block types    Metric Date Creek Sicamous Creek  CC HR LR NH CC HR LR NH  Overall abundance 936 2039 2250 2753 639 765 561 961 Mean individuals/trap 66.9 145.6 160.7 196.6 49.2 58.8 43.2 73.9  Observed species richness 150 (7.6) 205 (8.3) 220 (7.4) 204 (7.8) 89 (6.6) 115 (7.0) 96 (5.7) 120 (7.8) No. of  samples 14 14 14 14 13 13 13 13  Rarified species richness 150.0 (7.7) 128.6 (5.0) 131.3 (5.0) 100.6 (4.2) 84.0 (6.1) 94.3 (5.9) 96.0 (5.8) 87.5 (5.6) No. of individuals 936 936 936 936 561 561 561 561  Observed haplotype richness 66.0 (8.0) 157.0 (12.5) 165.0 (12.8) 155.0 (12.4) 38.0 (6.0) 64.0 (7.9) 56.0 (7.3) 96.0 (9.7) No. of species 19 36 41 43 13 20 17 26  Rarified haplotype richness 66.0 (8.0) 82.8 (6.6) 76.5 (5.9) 68.5 (5.5) 38.0 (6.0) 41.6 (5.1) 42.8 (5.6) 48.3 (4.9) No. of species 19 19 19 19 13 13 13 13  Observed phylogenetic diversity 56.1 41.9 45.6 78.7 33.1 37.2 30.6 29.6 No. of species 150 205 220 204 89 115 96 120  Rarified phylogenetic diversity 53.1 (0.8) 31.2 (0.9) 32.2 (1.4) 58.7 (2.2) 30.5 (0.6) 28.4 (1.0) 26.6 (0.9) 21.9 (0.8) No. of species 140 140 140 140 80 80 80 80  139 Figure 8.1 Experimental sites. a) Location of field collection sites in British Columbia, Canada.  b) The 8 blocks at the Date Creek Silvicultural Systems site.  A-3 and B-4 are clearcut treatments; B-2 and B-3 are heavy removal treatments (~60% basal area removed); A-2 and B-5 are light removal treatments (~30% basal area removed); and A-4 and B-1 are no harvest controls.  c) The 8 blocks at the Sicamous Creek Silvicultural Systems site.  A-4 and C-3 are 10-ha clearcut treatments; A-2 and B- 1 are heavy removal, 0.1-ha patch cut treatments; A-3 and C-3 are light removal, individual tree selection treatments (~20% basal area removed); and A-1 and B-2 are no harvest controls.  Images modified from Coates et al. (1997) and Huggard and Vyse (2003).   140 Figure 8.2 Combined histograms of Kimura 2-Parameter (K2P) pairwise sequence divergence for a) Date Creek and b) Sicamous Creek. Solid circles indicate interspecifc divergences between congeneric species and open circles indicate intraspecific divergence for species with multiple individuals.    141 Figure 8.3 Species accumulation curves for a) Date Creek, b) Sicamous Creek. Rarefaction curves are given for singletons, observed species and estimated species richness (Chao 1 estimator) for each moth inventory.    142 Figure 8.4 Estimated species accumulation curves of the four block types in a) Date Creek, b) Sicamous Creek. Block types are CC – clearcut, HR – heavy removal, LR – light removal, and NH – no harvest control. Species richness was rarified against number of individuals trapped.     143 Figure 8.5 Plots of three levels of diversity for the four block types. Block types are CC – clearcut, HR – heavy removal, LR – light removal, and NH – no harvest control.  Shown are species diversity at a) Date Creek, and b) Sicamous Creek; genetic diversity at c) Date Creek and d) Sicamous Creek, and phylogenetic diversity at e) Date Creek, and f) Sicamous Creek. Rarified values are presented as shaded bars with one standard deviation indicated by error bars.  A single black circle indicates the non-rarified, observed value. Different letters within each bar represent statistically significant differences (P < 0.05) after an analysis of variance (ANOVA) and a Tukey post hoc test.    144 Figure 8.6 The strength of association between levels of diversity. a) Relationship between mean rarefied species diversity and mean rarefied genetic diversity (haplotype richness); b) Relationship between mean rarefied species diversity and mean rarified phylogenetic diversity (sum of branch lengths); c) Relationship between mean rarefied genetic diversity (haplotype richness and mean rarified phylogenetic diversity (sum of branch lengths).  The asterisk (*) indicates a significant relationship (P < 0.05).    145 9 Influence of a native pest outbreak on the moth diversity of British Columbia’s ponderosa pine forests   Synopsis: This final data chapter investigates the impact of the recent mountain pine beetle outbreak on the moth diversity of British Columbia’s ponderosa pine forests.  As with the previous chapter, earlier constructed barcode libraries and molecular phylogenies permit the estimation of three levels of moth diversity, and are employed at sites that differ widely in attack by Dendroctonus bark beetles.  I test hypotheses concerning forest biodiversity and its response to perturbation, while conducting faunal inventories for two more British Columbia forest ecosystems.  9.1 Introduction The outbreaks of native and invasive forest pests will undoubtedly continue to increase in extent and severity with the ongoing change of global climate (Ayres and Lombardero 2000).  It remains to be determined exactly what the ecological consequences of this increase will be, particularly in relation to the sustainability and maintenance of ecological services.  Many ecological processes have proven a challenge to monitor let alone understand (Daily 1997), but their strong interdependence with biotic diversity is unquestionable.  As such, it is generally accepted that the maintenance of the animal, plant and microbial communities of an ecosystem will likewise maintain, at least in part, the ecological services it provides (Naeem et al. 1999; Naeem 2002; Hooper et al.  146 2005).  It thus appears valuable to explore the effects of ongoing pest outbreaks on resident biotic communities, and in turn, the ecological impact on the forest system.  The recent outbreak of mountain pine beetle (MPB) (Dendroctonus ponderosae Hopkins) in Western Canada is the most extensive and severe epidemic on record (Taylor et al. 2006).  While millions of hectares of the primary host lodgepole pine (Pinus contorta var. latifolia Dougl.) have been devastated over the last decade, the less extensive ponderosa pine (P. ponderosa Laws) forests have more recently come under attack.  These warm and dry forests, found in low elevation slopes and valleys of southern British Columbia, are witnessing significant mortality from mountain pine beetle and its close ally the western pine beetle (D. brevicomis LeConte) (Maclauchlan et al. 2008, Klenner and Arsenault 2009).  The consequences of the death of most mature overstory pine trees have been well-studied for birds (Martin et al. 2006; Norris and Martin 2008, 2010) and other vertebrates (see Klenner and Arsenault 2009 and references therein), but very little has been done to determine what effect the severe change in habitat is having on other animal communities (but see Stone 1995).  Furthermore, the groups studied have generally been strongly associated with the resource pulse of increased bark beetles or infected trees, for instance foraging woodpeckers (Drever and Martin 2010) or cavity-nesting birds (Norris and Martin 2008).  A more impartial perspective on the ecological consequences of the recent outbreak might be achieved through assessing the impact on a neutral taxon.  Apart from a few species that feed on ponderosa pine as larvae  147 (Duncan 2006), macro-moths (Lepidoptera) are not directly linked to the habitat features recently modified, and may be ideal indicators of the ecosystem as a whole, as previous work suggests (Holloway 1985; Beccaloni and Gaston 1995; Kitching et al. 2000; Summerville et al. 2004).  In the present study, I explore the effects of the recent mountain pine beetle outbreak on the moth diversity of ponderosa pine forests in British Columbia.  The recent application of DNA barcoding to inventories and monitoring (Janzen et al. 2005; Smith et al. 2005; Caesar et al. 2006; deWaard et al. 2009; Chapter 8) has greatly simplified the tasks, and can now facilitate studies of hyper-diverse taxa such as Lepidoptera.  I employ DNA barcoding for rough sorting and species identification of specimens collected at eight sites in two locations that differ widely in attack by Dendroctonus spp.   In addition to investigating the effect on species diversity, I use the DNA data to estimate two additional levels of diversity at each site — genetic and phylogenetic diversity. Two hypotheses will be tested; first, that older and more severe MPB attack will negatively affect moth diversity; and second, that the variation of moth diversity between sites can be predicted by one or more biological attributes that gauge the health and structure of the forest stand.   148 9.2 Materials and methods 9.2.1 Experimental sites and sampling  The British Columbia Ministry of Forests and Range (BC-MOFR) have an ongoing project exploring the impact of the recent mountain pine beetle outbreak on the ponderosa pine forests of south-central BC.   Eight of their approximately 22 transects in two locations were chosen for this project — four sites in Thompson Valley in the Kamloops area, and four sites in the southern Okanagan Valley, south of Penticton and near Okanagan Falls (Figure 9.1). Klenner and Arsenault (2009) provided a detailed description of the project and transects, as well as a preliminary overview of monitoring up until 2008. Bark beetle-related mortality of ponderosa pine in the Kamloops region began in 2005, peaked in 2007 and sharply declined in 2008, suggesting the outbreak was fading.  There was evidence of light and moderate attack severity in the South (S.) Okanagan in 2005, but by 2008, tree mortality was continuing to rise, suggesting the outbreak was still in the initial stages in this region.  Sampling in 2009 therefore encompassed both a trailing and leading edge of the bark beetle outbreak in BC’s ponderosa pine forests.  Moth diversity was inventoried at the eight sites, referred to as K1, K2, K3, and K4 for the Kamloops sites, and O1, O2, O3, and O4 for the S. Okanagan sites. Nocturnal, phototactic moths were collected using 22 W ultraviolet light traps (model 2851; BioQuip, Gardena, CA) powered by a 12 V (26 Ah) sealed lead acid battery (Discover Energy Corp., Vancouver, BC). Traps were placed on the transect, over 200m from any one end, and at roughly 1 m above the ground.  149 Moths that entered the trap were knocked down by the killing agent ethyl acetate, dispensed through evaporation using a mason jar and sponge wick.  One trap was placed on each of the four transects in one location (i.e. Kamloops or S. Okanagan) the first evening, and the remaining four transects were sampled the following evening.  Eight nights of collections (64 traps in total) were made roughly tri-weekly from May until September 2009.  Traps were run from dusk until dawn on evenings without strong winds, precipitation, or unfavourable phases of the moon.  Trap samples were frozen immediately after retrieval and stored at -20ºC until processing.  Owing to logistical and time constraints, I only analyzed nocturnal macrolepidoptera, a monophyletic assemblage that in British Columbia constitutes the Bombycoidea, Drepanoidea, Geometroidea, Lasiocampoidea and Noctuoidea.  Specimens were sorted to morphospecies prior to enumerating, pinning, labeling, imaging and databasing. A synoptic sample (i.e. a single specimen of each morphospecies) for each trap was selected for subsequent barcode analysis.  In addition to analyzing a single individual per species for each trap, I also analyzed all ambiguous specimens where delimiting morphospecies was difficult (e.g. Eupithecia geometrids, Euxoa noctuids).  Also, for morphospecies with eight or more individuals, I analyzed eight specimens to permit estimates of genetic diversity. 9.2.2 DNA barcode and data analysis  DNA barcoding followed standard protocols (Hajibabaei et al. 2005; Ivanova et al. 2006; deWaard et al. 2008a) and was completed at the Canadian  150 Centre for DNA Barcoding in Guelph, Canada. Amplification and sequencing of 658 base pairs of cytochrome c oxidase subunit I (COI) was performed with the full-length primers LepF1 and LepR1 (Hebert et al. 2004) in all but a few recalcitrant cases, where the ‘Lep mini primers’ MLepF1 and MLepR1 (Hajibabaei et al. 2006a) were used. The electropherograms were edited and aligned in Seqscape v. 2.5 (Applied Biosystems), then deposited to the Barcode of Life Data Systems (BOLD) and GenBank.  All sequences were run through the identification engine of BOLD (BOLD-ID; http://www.barcodinglife.org/views/idrequest.php) for tentative species identifications.  Specimens that failed to barcode, as well as unique sequences and ambiguous cases, were determined to species morphologically using a variety of taxonomic literature compiled on the Canadian Biodiversity Information Facility ‘Moths of Canada’ website (http://www.cbif.gc.ca/spp_pages/misc_moths/phps/mothindex_e.php). All specimens were confirmed morphologically by comparison with reference specimens in natural history collections where they were subsequently deposited: Canadian National Collection of Insects, Arachnids and Nematodes (CNCI) (Ottawa, ON), Royal British Columbia Museum (Victoria, BC), Pacific Forestry Centre (Victoria, BC), and Spencer Collection, University of British Columbia (Vancouver, BC).  Classification followed Lafontaine and Schmidt (2010) for the Noctuoidea and Powell and Opler (2009) for the remaining superfamilies.  151 The number of species and number of individuals per species were tallied for each trapping event and pooled for the Kamloops and South Okanagan regions.  The data were formatted for the program EstimateS v. 8.0 (Colwell 2006), which was used to calculate the completeness of the two inventories. This program computed accumulation curves for species observed (Mao Tau method), species estimated (Chao 1 estimator; Chao 1987), and singleton species by generating 1,000 randomized accumulation curves without replacement, following the method of Colwell et al. (2004) and Mao et al. (2005).  Three levels of diversity were then estimated for each of the eight sites: K1, K2, K3, K4, O1, O2, O3, and O4.  The outbreak species Douglas fir tussock moth (Orgyia pseudotsugata McDunnough) was removed due to the aberrant results its abundance caused during analysis.  All diversity estimates were rarified — this approach allows for unbiased comparisons of diversity values after accounting for variation in sampling effort (Gotelli and Colwell 2001; Leberg 2002).  Species diversity was estimated by tallying the number of species and abundance of each species for each collection event.  EstimateS v 8.0 (Colwell 2006) was used to rarify estimates for each site by generating species accumulation curves (see above).  The curves were then used to interpolate observed species (Mao Tau method) and associated variance at the largest common sample size of 393 individuals.  152 The haplotype variation in COI allowed the estimation of genetic diversity for each site. For all species that had six or more full-length COI sequences within a site, all sequences were assembled into eight FASTA files, one for each site.  The online software FaBox (Villesen 2007) was used to collapse the sequence alignments into unique haplotypes which were tabulated into ‘Format 3’ (i.e. haplotype number, species, haplotype abundance) for input into EstimateS v. 8.0 (Colwell 2006).  As above, accumulation curves were generated to interpolate haplotype richness at the largest common sample size of 11 species. Phylogenetic diversity was estimated by first constructing community phylogenies (Webb 2000) using the COI data.  For each of the eight sites, I estimated a maximum-likelihood phylogeny using the COI sequences of each resident species.  A gene tree constructed with a single marker is not likely to resemble the true phylogeny, so I used topological constraints based on well- supported phylogenetic relationships (Kristensen and Skalski 1999; Regier et al. 2009; Mutanen et al. 2010; Zahiri et al. in press; Chapter 4) (Appendix K). Constraint files in the Newick tree format were assembled using FigTree v. 1.3.1 (Drummond and Rambaut 2007) and a text editor. These files were read into Garli 1.0 (Zwickl 2006) and a heuristic tree search was executed using the general-time-reversible + gamma + invariant sites substitution model.  The best tree selected for each of the eight sites provided the reference topologies and branch lengths to calculate phylogenetic diversity (Faith 1992).  R version 2.8.1 (R Development Core Team 2008) with the packages APE (Paradis et al. 2004)  153 and CAIC (Orme et al. 2008) installed were used to calculate phylogenetic diversity.  Rarefaction curves following the procedure of Zhou et al. (2009) used 1000 bootstraps to interpolate the phylogenetic diversity and its variance at the common sample size of 80 species. Because geographic variation may confound results, raw and incomplete mensuration data was obtained from the Ministry of Forests and Range to approximate several site attributes for comparison with diversity estimates.  The mean diameter at breast height (dbh) was calculated from raw measurements for between 1 and 12 plots at each site to provide a proxy of stand maturity for each site.  Only ponderosa pine and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) were present at the collection sites, but the proportion of each varied considerably and was calculated from the plot counts.  All trees examined in the plots were examined for external signs of attack by Dendroctonus spp. and were assigned one of four categories that correspond to the sequence of needle colour changes that occur following beetle attack (Safranyik et al. 1974): 1) ‘green attack’ – signs of entry holes, pitch tubes and frass, but with green needles that appeared healthy; 2) ‘red attack’ – needles had turned red following death of the tree, typically one year from initial attack; 3) ‘grey attack’ – all needles lost and tree dead for two or more years; and 4) ‘no attack’ – no evidence of beetle attack. These values were tallied and are reported as percentages of examined trees. Mortality in 2009 was calculated as the percentage of all trees in ‘green’, ‘red’ or ‘grey’ categories, as in Klenner and Arsenault (2009).  154 To evaluate differences in diversity between the two locations, unpaired t- tests were computed for each of the three rarified measures of diversity.  To test if macro-moth species with ponderosa pine as their larval host (Duncan 2006, deWaard et al. unpublished) were reduced in abundance in Kamloops due to the Dendroctonus outbreak, Wilcoxon signed ranks tests were performed on abundance and sample data for these species. For site attributes, linear regressions of the measures mean dbh, % Douglas-fir, and % mortality were calculated individually for the dependent variables of rarified species, genetic, and phylogenetic diversity.  All statistical analyses, unless noted, were conducted in SPSS v17 (IBM), and the level of significance was set at P = 0.05.  Charts were plotted with SigmaPlot (Systat Software Inc.).  9.3 Results The 64 collection events at both locations trapped a total of 10,861 individuals.  The eight nights of trapping in each location resulted in 8503 specimens in Kamloops (median trap sample = 51.5, range = 2 – 4116) and 2358 specimens in S. Okanagan (median trap sample = 53.0, range = 2 – 276).  All specimens were sorted to morphospecies and tallied, and 2878 were imaged, vouchered and sampled for genetic analysis.  These specimens were 99.3% successfully amplified and sequenced, resulting in only 21 individuals lacking COI sequence data.  The mean sequence length was 650 bp (range = 212 – 658 bp) and 2843 were greater than 500 bp, meeting the ‘BARCODE data standard’ (see Hubert et al. 2008). The COI sequences, electropherograms, images,  155 ancillary data, voucher accessions and GenBank accessions are publicly available on BOLD in the project ‘LBCPY Lepidoptera of BC – Py project’.  The DNA extracts are also publicly available for future work (Hanner and Gregory 2007), archived at -80°C at the Canadian Centre for DNA Barcoding in Guelph, Canada.  The species identification of the specimens was generally straightforward. Tentative assignments by BOLD-ID were confirmed morphologically by comparison with reference specimens in the regional collections in BC, and difficult cases (all Euxoa spp. and 15 other noctuoids) were determined at the CNCI.  The 21 specimens without COI barcodes were easily assigned to species by comparing (morphologically) with specimens collected from the same location. DNA barcodes were able to delimit species in 100% of the cases, although sequence divergence was shallow in some genera (e.g. Abagrotis, Euxoa and Panthea).  For the Kamloops sites, mean intraspecific divergence was 0.13% (range = 0 – 3.1%, 24,043 comparisons, n = 135) compared to 4.3% between congeneric species (range = 0.6 – 15.2%, 41874 comparisons, n = 60) (Figure 9.2a); at the S. Okanagan sites, mean intraspecific divergence was 0.22% (range = 0 – 5.3%, 12401 comparisons, n = 145) in contrast to the interspecific mean of 6.0% (range = 0.6 – 15.2%, 11826 comparisons, n = 91) (Figure 9.2b). Two species displayed deep intraspecific divergences (Protolampra rufipectus (Morrison): max distance = 3.1%; Macaria colata Grote 5.25%) that warrant further taxonomic investigation (see Chapter 2).  156  The two inventories constructed are comprised of 325 species in total, 114 of which are found at both locations, and they represent ten macromoth families (Table 9.1).  The Kamloops inventory has 200 species including 60 singletons (Appendix L), and the S. Okanagan inventory comprises 239 species and 84 singletons (Appendix M). The Douglas fir tussock moth (Orgyia pseudotsugata) was extremely abundant, particularly at the Kamloops sites.  It was caught in all 24 traps (2 locations X 4 sites X 3 nights) in August and September, including a single trap (K3 on 4-xiii-2009) that had 3772 individuals.  Excluding Orgyia pseudotsugata, the mean individuals collected per species were 16.1 (SD = 39.2, range = 1 – 327) and 8.6 (SD = 18.5, range = 1 – 134) for Kamloops and S. Okanagan, respectively.  The accumulation curves constructed for each location have not reached asymptotes (Figure 9.3) indicating incomplete inventories — roughly 71.9% complete in the case of Kamloops (Chao 1 estimator = 278 species, 95% CI = 240 – 353) and 68.4% in the case of S. Okanagan (Chao 1 estimator = 349, 95% CI = 302 – 432).  The species accumulation curves for the eight sites individually also failed to reach asymptotes (Figure 9.4).  Species diversity, represented by rarified species richness, ranged from approximately 59 species in site K3 to 105 species in site O4 (Table 9.2).  The mean rarified species richness of Kamloops was 65.2 (SD = 7.4), significantly lower than the mean of 98.0 (SD=0.9) for S. Okanagan (unpaired t-test, t = 7.2, p = 0.0004) (Figure 5a).  For genetic diversity, haplotype richness was estimated from between 11 to 31 species at each site (Table 9.2) and rarified values varied from roughly 26 haplotypes (SD = 3.6) at site K3 to 44 haplotypes (SD = 6.5) at  157 site O2.  The mean rarified haplotype richness at Kamloops (30.0, SD = 5.1) was also lower than at S. Okanagan (36.4, SD = 5.2) (Figure 9.5b), but this difference was not significant (unpaired t-test, t = 1.2, p = 0.28).  Finally, rarified phylogenetic diversity had its lowest value in Kamloops (site K4: combined branch length = 8.2 units, SD=0.3) and highest value in S. Okanangan (site O4: combined branch length = 17.2 units, SD = 0.7).  The mean rarified phylogenetic diversity of Kamloops was 11.3 (SD = 3.4), which was not significantly lower than the mean of 14.9 (SD=2.3) for S. Okanagan (student t-test, t = 1.8, p = 0.12) (Figure 9.5c). Nine of the fourteen macro-moth species with ponderosa pine as larval host in British Columbia were collected (Table 9.3).  In seven of nine species, the number of individuals and samples collected was lower in Kamloops relative to S. Okanagan.  This lower abundance was nearly significant for both individuals (one-tailed Wilcoxon signed ranks tests: Z = -1.38, p = 0.084) and samples (one- tailed Wilcoxon signed ranks tests: Z = -1.63, p = 0.052).  The linear regression analysis of site attributes (Table 9.4) and diversity estimates revealed that approximately 85% of the variance in species diversity is explained by ponderosa pine mortality (% mortality: B = -0.402, p = 0.001, R2 = 0.853).  The other two variables were not significantly associated with species diversity (mean dbh: B = 0.486, p = 0.762; % Douglas-fir: B = -0.017, p = 0.950). General linear regression models including attributes individually or together were not significant for genetic diversity (mean dbh: B = 1.237, p = 0.204; % Douglas-fir: B = 0.038, p = 0.798; % mortality: B = -0.183, p = 0.094) or  158 phylogenetic diversity (mean dbh: B = -0.208, p = 0.691; % Douglas-fir: B = 0.083, p = 0.377; % mortality: B = -0.041, p = 0.456).  9.4 Discussion 9.4.1 Completion of two macro-moth inventories  Using DNA barcoding as a tool for specimen sorting and species identification, I was able to achieve preliminary Lepidoptera inventories for two ponderosa pine systems.  The inventories are limited to nocturnal Macrolepidoptera, but this is true for most inventories, due to the general lack of expertise and taxonomic resources for Microlepidoptera.  The two can still be easily compared with other inventories in the region (see Chapter 8) and furthermore, they still comprise a species-rich fauna and contain nearly all groups considered to be good indicators of species diversity and forest disturbance (e.g. Summerville et al. 2004).  While not strictly baseline inventories, they will nonetheless provide initial species lists and diversity estimates for comparison with current and future studies.  Several other taxonomic groups are currently being inventoried on these transects, which will allow for an empirical community- wide assessment of the impacts of the pine beetle.  Future monitoring of these sites would permit tracking of long-term effects, important since these forest ecosystems will take decades to recover (Klenner and Arsenault 2009). Concurrently, it will be possible to monitor climate change effects, as these transects overlap with the Canada Global Change Transect (CGCT) project  159 (www.macroecology.ca).  In these cases, not only have I provided initial inventories and diversity estimates, but also a DNA barcode library for macro- moths to facilitate species identifications.  The species accumulation curves and abundance-based estimators suggested the inventories are roughly 70% complete.  Adding the remainder of species will be increasingly difficult—multiplied effort will provide diminishing returns (Magurran 2004).  The extent to which this is affecting between-site comparisons was not quantified, but under-sampling can produce spurious results if estimates are based on the initial steep slope of diversity curves (Cardoso et al. 2009).  In this study, all samples collected were sorted and analyzed, and this was performed following the commencement of field collection.  If conversely, samples were collected at a greater frequency, and a fraction were analyzed concurrently with field collection, it would be possible to predict the sampling and specimen analysis necessary for a complete (or nearly complete) inventory.  Two recent studies (Smith et al. 2009; Zhou et al. 2009) demonstrated that accumulation curves generated with barcode-estimated phylogenetic diversity were highly congruent with those based on morphologically derived species diversity.  Such a method allows comparison between sites and provides a measure of sampling efficiency, all prior to placing formalized names on specimens (Smith et al. 2009). Furthermore, this makes no assumptions about species boundaries, and therefore is particularly attractive for surveying organisms lacking a mature taxonomic system (Zhou et al. 2009). Subsequent studies employing DNA barcoding to assess diversity effects across  160 multiple sites would be advised to consider this in situ approach to gauging inventory completion. 9.4.2 Effect of pine beetle outbreak on moth diversity  I investigated the effect the recent epidemic of Dendroctonus bark beetles is having on moth diversity in ponderosa pine forests by estimating three levels of diversity in two locations (and eight sites) varying in level of attack.  Species richness was found to be significantly lower where the beetle outbreak has already peaked and begun to fade, relative to a location at the leading edge of the epidemic.  Moth species with ponderosa pine documented as the larval host, also exhibited a similar trend (although marginally insignificant) but their limited numbers by no means skew the results.  A large proportion of the variance in species diversity was explained by disturbance severity (ponderosa pine mortality), but lack of association with other site attributes does not exclude other confounding factors.  The rapid spread of the outbreak prohibited the investigation of forest blocks varying in outbreak intensity while still in close proximity, and as such, geographic variation in species richness (Rhode 1992) or variable trapping conditions (Southwood et al. 1979) may have introduced biases.  Nonetheless, assuming that I did identify a true biological signal, the results are in accordance with previous studies assessing insect community responses to disturbance (Schowalter 1985); many investigations have documented a decrease in insect species diversity, at least initially, following ecosystem perturbation.  In contrast, Stone (1995) found that insect diversity and abundance, sampled four years post-outbreak, increased linearly with mountain  161 pine beetle infestation in a lodgepole pine system, posited to be a function of the improved structure and composition of understory (successional) vegetation. There is a well-evidenced relationship between Lepidoptera diversity and forest plant species richness (Usher and Keiller 1998), suggesting that the observed depression may be temporary.  There was a similar trend of lower genetic and phylogenetic diversity in the sites where Dendroctonus activity was highest, but this association was not statistically significant.  The likelihood that these results were affected by under- sampling (see above) is high, and it is unfortunate that time and logistical constraints did not permit estimates from additional sites.  Furthermore, spatial scale can greatly influence the magnitude of post-disturbance diversity effects (e.g. Cleary et al. 2004; Condit et al. 2002) and because of this, metrics that incorporate composition and evenness may be more appropriate, and allow the detection of subtle effects.  However, the genetic and phylogenetic analogues of these species diversity indices (e.g. Simpson’s index) are less developed (Cadotte et al. 2010), particularly regarding algorithms and software programs for their computation.  On the other hand, if the observed lack of association is authentic, a disparity between the effect on species diversity and the effect on genetic and phylogenetic diversity is not inconceivable.  Species and phylogenetic diversity can be unlinked (see Chapter 8) and the correlation of species and genetic diversity is not universal.  The latter relationship weakens when the genetic diversity of rare species is measured (Vellend 2005), a possibility in the present study since multiple species were analyzed.  162  The question remains, can we glean anything from these post-disturbance effects on a hyper-diverse moth community that can be generalized to the ecosystem as a whole?  Macro-moths may be comparatively neutral, apart from a few larval defoliators of ponderosa pine, and they have a proven record as indicators of habitat integrity (Holloway 1985; Beccaloni and Gaston 1995; Kitching et al. 2000; Summerville et al. 2004).  Their perceived depression in species richness may therefore be representative of the larger biotic system. The pending work on other taxonomic groups may corroborate this suggestion, and follow-up monitoring in the post-outbreak years would also be informative.  If confirmed, this implies that the maintenance of the biotic communities in this system have been negatively impacted by the Dendroctonus outbreak, if only temporarily, which in turn, will affect the ecological services they provide (Naeem et al. 1999; Naeem 2002; Hooper et al. 2005).  In any case, the ecological consequences of increased pest outbreaks, however acute, cannot be ignored when other natural and human-induced agents of disturbance are likewise increasing, and so much disturbance threatens to become too much disturbance.  163 Table 9.1 Summary of macro-moths from the two collection localities. Classification follows Powell and Opler (2009) with the exception of Noctuoidea (Erebidae, Euteliidae, and Noctuidae here), which has recently been reorganized (Lafontaine and Schmidt 2010).  The larger families of Geometridae, Erebidae, and Noctuidae are divided up into subfamilies.   Taxon Kamloops South Okanagan  No. of species No. of individuals No. of species No. of individuals  Drepanidae 0 0 1 1 Erebidae 10 5748 15 549 Arctiinae 4 428 4 110 Calpinae 1 1 1 1 Erebinae 2 2 5 104 Herminiinae 0 0 2 26 Hypeninae 1 2 1 2 Lymantriinae 1 5300 1 301 Rivulinae 1 6 1 5 Euteliidae 0 0 1 1 Geometridae 49 993 78 670 Ennominae 30 539 46 462 Geometrinae 3 51 5 19 Larentiinae 12 156 20 83 Sterrhinae 4 20 7 106 Lasiocampidae 2 12 3 74 Noctuidae 135 1981 130 1014 Acronictinae 0 0 2 2 Amphipyrinae 14 221 11 119 Bryophilinae 2 47 1 27  164 Taxon Kamloops South Okanagan  No. of species No. of individuals No. of species No. of individuals  Cuculliinae 1 1 1 1 Dilobinae 0 0 1 1 Heliothinae 2 80 0 0 Noctuinae 110 1626 100 791 Oncocnemidinae 4 4 10 67 Pantheinae 1 1 2 3 Plusiinae 1 1 2 3 Notodontidae 1 1 4 7 Saturniidae 1 1 1 2 Sphingidae 2 3 5 39 Uraniidae 0 0 1 1  Total 200 8503 239 2358     165 Table 9.2 Summary of estimated macro-moth diversity at each collection site.  Metric Kamloops South Okanagan  K1 K2 K3 K4 O1 O2 O3 O4  Overall abundance 951 923 5338 1291 728 409 460 761 Mean individuals/trap 118.9 115.4 667.3 161.4 91.0 51.1 57.6 95.1  Overall species richness 94 (6.5) 95 (7.0) 135 (6.5) 99 (6.3) 143 (8.5) 96 (7.9) 105 (7.5) 135 (7.3) Rarified species richnessa 61.1 (4.5) 75.5 (5.8) 65.4 (4.5) 58.7 (4.0) 93.5 (6.0) 95.0 (7.9) 98.1 (6.2) 105.4 (6.2)  Overall haplotype richness 61 (7.7) 29 (5.2) 90 (9.4) 50 (6.9) 62.0 (7.7) 44.0 (6.5) 45.0 (6.6) 47.0 (6.7) N species (with >6 sequences) 18 12 33 21 20 11 14 16 Rarified haplotype richnessb 37.3 (4.7) 26.6 (4.8) 30.0 (3.1) 26.2 (3.6) 34.1 (4.3) 44.0 (6.5) 35.4 (5.2) 32.3 (4.6)  Overall phylogenetic diversity 9.8 14.8 22.5 9.6 25.8 14.0 17.1 25.9 Rarified phylogenetic diversityc 8.7 (0.3) 13.0 (0.5) 15.1 (0.7) 8.2 (0.3) 16.4 (0.7) 12.2 (0.3) 13.8 (0.4) 17.2 (0.7)  a species richness rarified to 393 individuals b haplotype richness rarified to 11 species c phylogentic diversity rarified to 80 species   166 Table 9.3 Abundance and sampling of 14 macro-moth species known to feed on ponderosa pine as larvae in British Columbia. Species listed are from Duncan (2006) and deWaard et al. (unpublished).  Species Kamloops S. Okanagan  abundance samples abundance samples  Caripeta aequaliaria 0 0 1 1 Caripeta n.sp. 1 1 2 2 Stenoporpia pulmonaria 13 5 5 3 Phaeoura mexicanaria 0 0 9 5 Macaria adonis 6 5 4 4 Sabulodes edwardsata 0 0 0 0 Glena nigricaria 14 4 28 7 Tolype dayi 11 4 65 10 Dasychira grisefacta 0 0 0 0 Abagrotis n.sp. 0 0 0 0 Egiria curialis 0 0 0 0 Panthea gigantea 0 0 0 0 Lithophane atara 0 0 1 1 Lithophane ponderosa 0 0 1 1       167 Table 9.4 Summary of biological and physical attributes of eight collection sites.    Metric Kamloops South Okanagan  K1 K2 K3 K4 O1 O2 O3 O4  mean dbha (standard deviation) 26.1 (12.6) 24.2 (14.1) 23.7 (12.3) 24.0 (13.9) 14.2 (6.7) 22.2 (8.3) 16.5 (9.4) 20.8 (12.1)  % ponderosa pine (Py) 60.2 73.6 68.4 89.8 64.2 98.1 99.1 78.0 % Douglas-Fir (Fd) 39.8 26.4 31.6 10.2 35.8 1.9 0.9 22.0  % of Py with 'green' attack 0.7 7.6 3.9 6.7 0.0 2.5 0.1 0.4 % of Py with 'red' attack 77.2 81.3 70.0 69.7 0.0 2.5 0.0 1.7 % of Py with 'grey' attack 0.7 2.4 4.2 7.8 1.1 4.8 0.2 2.2 % of Py no evidence of attack 21.3 8.6 21.9 15.9 98.9 90.1 99.6 95.7 % of Py mortality 78.7 91.4 78.1 84.1 1.1 9.9 0.4 4.3  a dbh: diameter at breast height   168 Figure 9.1 Location of field collection sites in south-central British Columbia. Eight sites near Kamloops and Okanagan Falls used by the BC Ministry of Forest and Range to monitor the effects of MPB outbreak on ponderosa pine forests.      169 Figure 9.2 Combined histograms of Kimura 2-Parameter (K2P) pairwise sequence divergence for a) Kamloops and b) S. Okanagan. Solid circles indicate interspecifc divergences between congeneric species and open circles indicate intraspecific divergence for species with multiple individuals.       170 Figure 9.3 Species accumulation curves for a) Kamloops and b) S. Okanagan. Rarefaction curves are given for singletons, observed species and estimated species richness (Chao 1 estimator) for each moth inventory.     171 Figure 9.4  Species accumulation curves for the eight sites in a) Kamloops and b) S. Okanagan. Species richness was plotted against number of individuals trapped.     172 Figure 9.5  Plots of diversity for the 8 sites the eight sites in Kamloops and S. Okanagan. Shown are a) species diversity, b) genetic diversity, and c) phylogenetic diversity. Rarified values are presented with one standard deviation indicated by error bars.   173 10 Conclusions   10.1 Overall analysis  The overarching research objective was to comprehensively investigate the application of DNA barcoding as a tool for biomonitoring and biosecurity of forest arthropods.  Working with the hyper-diverse Lepidoptera primarily of British Columbia, I constructed two reference barcode libraries and a multi-gene phylogeny, that were subsequently used to detect five non-indigenous species, build five species inventories, and assess community responses in two disturbed forest systems across three levels of moth diversity.  My findings include no evidence of increased diversity at intermediate treatments of harvesting, but did reveal a correlated response of species and genetic diversity.  Similarly, I determined a negative association between species diversity and tree mortality in ponderosa pine forests with differential attack of Dendroctonus bark beetles. Relative to traditional morphological approaches, DNA barcoding evidently provides several key advantages to biosurveillance and biosecurity in forest arthropods.  First of all, the sorting of samples is immensely time-consuming and potentially error-prone for many forest arthropod groups, and the capacity of DNA barcoding to filter them into manageable units is invaluable (Caesar et al. 2006). Secondly, with the number of practicing taxonomists in decline (Jaspars 1998; Samyn and Massin 2002), and their resources increasingly threatened (Feldman and Manning 1992; Godfray 2002), a demonstrated reduction of specialist time via barcoding is critical.  Thirdly, in several instances here, DNA barcoding  174 facilitated the recognition of non-indigenous species at low density, often decades after introduction, overlooked due to the inadequacy of traditional methods (Packer et al. 2009).  Finally, the ability to simultaneously appraise multiple levels of diversity—species, genetic, and phylogenetic—may require validation and refinement (see below) but could be a significant advance for biomonitoring, and for specific purposes such as conservation prioritization (Smith and Fisher 2009).  10.2 Strengths and limitations  Several strengths and weaknesses became apparent during the completion of the dissertation research.  A few notable issues are described in detail below. Archived material  An important strength of this dissertation is the wealth of archived materials that were a byproduct of the research. In total, over 12,800 specimens and nearly 1100 species were DNA barcoded; in each case, the specimen data, image and sequence data are archived online and are publicly accessible.  In addition, purified DNA extracts for every analyzed specimen have been archived at -80°C at the Canadian Centre for DNA Barcoding in Guelph, Ontario to facilitate future molecular investigations (Hanner and Gregory 2007). Over 9900 of these are newly collected specimens and have been deposited in regional and national insect collections, many of which are the first provincial, Canadian, or  175 North American records of a taxon.  The importance of vouchered specimens cannot be overstated — the deposition of vouchers permits long term studies, the correction of published errors, the resolution of species limits, and the confirmation of research results (Wheeler 2003), and failing to do so can lead to errors proliferating in the literature indefinitely (Bortolus 2008). The multiplicity of vouchered and archived materials makes it particularly amenable to confirmation and improves its reproducibility. An integrative approach  A related strength in this study was the adoption of an ‘integrative taxonomic approach’ (see Padial et al. 2010) that uses multiple sources of evidence to make inferences.  Identifications here, and the inventories and experiments based upon them, were supported with both molecules and morphology.  Taxonomy generally lacks a tradition of independent testing and verification of results in terms of species identifications (MacLeod et al. 2010), and blind-test studies have revealed alarming inaccuracy in some cases (e.g. Culverhouse et al. 2003).  Besides providing independent verification, this integrative approach has lead to a number of additional discoveries (e.g. a description of a new species of Caripeta that feeds on ponderosa pine; JRD, unpublished), and the accessibility of online data is critical to linking DNA barcoding with other biodiversity projects, ultimately to contribute to the ‘taxonomy of the future’ (Penev et al. 2008).   176 Guild- and family-specific responses  One noteworthy limitation for Chapters 8 and 9 is that I did not classify species to guilds (e.g. woody plant feeders, herbaceous plant feeders, detrivores) or families for separate analysis due to time constraints.  Previous studies (e.g. Summerville and Crist 2002; Schmidt and Roland 2006) have demonstrated that the diversity patterns within functional groups (such as feeding guilds) can vary dramatically, and may differ from or bias the overall diversity patterns.  It is possible that the unusual diversity patterns observed in Chapter 8 are due to overall diversity measures masking important community changes at the functional level.  Similarly, it would be worthwhile to run the analyses separately for different clades, since they vary widely in biological attributes that might affect diversity patterns (Summerville et al. 2004).  For example, some families such as Geometridae are generally considered poor fliers and demonstrate high ecological fidelity (Nieminen 1986, Doak 2000). Sampling issues The unusual diversity patterns observed at times, are at least in part, the products of incomplete sampling, and this is another notable limitation of the study.  I chose generality (in terms of inventory sites and taxonomic breadth) over replication, and the statistical power of analyses suffered as a consequence. Furthermore, the sampling effort necessary to complete several inventories, and effectively sample each experimental treatment or site, proved greater than originally calculated.  With accumulation curves indicating a failure to approach  177 asymptotes, particularly for genetic diversity, it cannot be ruled out that the estimates are based on the initial steep slope of the diversity curves and hence a random portion of the community was sampled (Cardoso et al. 2009).  Choosing to sacrifice generality would have been one solution to this limitation, perhaps concentrating on a single family and increasing the number of sites and frequency of sampling.  Genetic diversity in particular evidently required increased sampling—this and the suitability of COI for this purpose warrant further investigation (see below).  10.3 Potential applications The objective of this dissertation was to evaluate the application of DNA barcoding to the fields of forest biomonitoring and biosecurity.  As described above, its integration could have tremendous benefits, particularly as sequencing technology continues to improve and decrease in cost.  It is now evident that it would be advantageous for specific programs within these fields to adopt this approach and are discussed below. FIDS or FIDS-like programs  As discussed at length in Chapter 6, the now defunct Forest Insect and Disease Survey (FIDS) was a tremendous resource for managers, foresters and scientists for almost 50 years (Van Sickle et al. 2001).  A reincarnation of this program, likely run at the provincial level, might now be possible with a concerted effort combining the recent advances in remote sensing, relational databasing,  178 and molecular diagnostics, such as DNA barcoding.  In the case of the former, significant capital would be necessary initially for the molecular infrastructure, development of reference libraries, and establishment of protocols for linking incidence of pests and pathogens with damage in the field.  I do not believe it is absurd to envision a forest biomonitoring system as routine as contemporary programs for water and soil-testing, now provided or overseen by provincial agencies. Regional or national biosurveillance programs  A program where the integration of DNA barcoding is more urgent is in regional and national biosurveillance programs, administered for instance by the Canadian Food Inspection Agency at the federal level.  These programs already conduct molecular diagnostic tests for specific intercepted organisms, so the incorporation of DNA barcoding, now recognized in the International Standards for Phytosanitary Measures No. 27 entitled ‘Diagnostic Protocols for Regulated Pests’ (FAO 2006), would be straightforward.  Furthermore, the standardized and generic platform that barcoding offers, while still meeting the standards of data quality and transparency (see Floyd et al. 2010), could provide data ancillary to the identification.  It is possible through analyzing haplotype frequencies across the native and introduced range to determine the native provenance of intercepted specimens (e.g. Simonsen et al. 2008, Weese and Santos 2009, Nadel et al. 2010), information that cannot always be determined by the vessel or mode of entry.  Routine barcoding would develop the baseline databases necessary for such analyses, and ultimately provide a better understanding of the  179 flux and flow of species moving with international trade.  The integration of barcoding into surveillance intercept identification procedures can also be transitional (as I proposed for gypsy moth diagnostics in Chapter 3).  If these programs make vouchering of intercepted specimens compulsory and available to barcoding laboratories, they could be analyzed in parallel or a posteriori, and at the very least provide independent confirmation of the diagnoses. International collaboration will be necessary to construct and validate reference libraries (as was the case for Chapter 3) not merely to ensure comprehensive coverage, but to provide a fair and equal system for all agencies involved. Fortunately, several countries have already begun to integrate DNA barcoding into biosecurity diagnostics, such as the United States (Gilligan and Epstein 2009) and New Zealand (Armstrong 2010).  10.4 Future research directions My investigation into applying DNA barcoding to forest biomonitoring and biosecurity has contributed to a growing body of literature on the topic (Smith et al. 2005; Armstrong and Ball 2005; Humble et al. 2009; Smith and Fisher 2009; Floyd et al. 2010, Wilson and Schiff 2010), answering some questions, but raising others.  I discuss here a few avenues of future research that concentrate on a number of these questions.    180 Phylogenetic diversity and DNA barcoding Faith and Baker (2006) were the first to propose the idea that biodiversity assessments using phylogenetic diversity (PD) estimates would integrate well with DNA barcoding programs.  Assessments using PD sidestep the time- consuming and often impossible necessity for taxonomic species designations that slow progress using traditional techniques, and DNA barcoding would provide the topologies and branch lengths necessary to calculate PD.  Studies have further developed this idea and implemented barcoding for estimating PD in several arthropod groups (Smith et al. 2009; Smith and Fisher 2009; Zhou et al. 2009). However, in each case, simple tree-building (e.g. neighbour-joining algorithm) was conducted using solely the barcode fragment, which is known to have only limited phylogenetic utility (Wilson 2010; Remigio and Hebert 2003).  In Chapter 8 and 9, I used a well-supported but conservative backbone phylogeny of Lepidoptera to constrain maximum likelihood analyses of the barcode fragment for the construction of community phylogenies, then computed PD based on these.  It is assumed this is an improvement to previous simple methods, but in all cases it is unclear if they are reliable surrogates for PD calculated from our best hypothesis of the phylogeny — a well-resolved, well- supported tree constructed with multiple character sources. Whether COI (or other barcode regions) provides a reliable proxy for estimating PD could easily be tested by compiling and reanalyzing previous phylogenetic studies (e.g. Mutanen et al. 2010; Raupach et al. 2010) that use COI as one of their markers, in each case comparing PD estimated by a) the multi-gene tree, b) the COI-only  181 tree, and c) the COI-only tree constructed with topological constraints (as in Chapters 8,9).  The results would indicate how future studies should proceed prudently when using barcode data for PD estimation. Estimating genetic diversity with COI  Similar to the situation for phylogenetic diversity, the estimation of genetic diversity using solely COI, as in this dissertation, warrants further investigation. My attempts to supplement COI with a second rapidly-evolving marker were unsuccessful due to sequencing issues (sequencing of the mitochondrial control region and nuclear internal transcribed spacers 1 and 2 were unsuccessful because of the frequent homopolymers and short tandem repeats; data not shown), but COI alone appeared to provide ample haplotype variation within and between sites.  What needs to be explored is whether this single neutral marker is representative of the actual genetic diversity of a given population. The use of COI enables the averaging of haplotype diversity (or other metric) across multiple species within a community, which is contrary to the standard approach of calculating a diversity metric for a single representative species using multiple neutral markers (e.g. microsatellites, amplified fragment length polymorphisms). Using a combination of these two approaches for a selected number of taxa could determine if COI-derived genetic diversity is representative.  For instance, it would be possible to go back to archived DNA samples from Chapters 7 to 9 and perform secondary molecular assays on a few species.  Although microsatellite loci have been difficult to isolate and characterize in Lepidoptera (Zhang 2004), a few taxa in BC have had markers developed, such as Biston  182 betularia L. (Daly et al. 2004), Saucrobotys futilalis L. (Grant and Bogdanowicz 2006), Cydia pomonella (L.) (Zhou et al. 2005), and Arctia caja (L.) (Anderson et al. 2006), and there are no foreseeable reasons why AFLPs could not be developed.  Such a study could determine if COI alone is a viable option for estimating genetic diversity. Patterns of beta diversity  The completion of five preliminary species inventories permits another interesting avenue for future work—patterns of beta diversity (i.e. rate of change in species composition) in British Columbia’s forest systems.  Combined with host plant data from FIDS and floral inventories of the five locations, it would be possible to explore the association of geographic isolation and ecological specialization, across the continuum from non-specialists (detritivores) to polyphagous to monophagous feeders.  This would allow one to empirically test the hypothesis that contrary to the tropics (Novotny et al. 2007), temperate forests exhibit lower beta diversity between host species and, in turn, lower ecological specialization, providing a mechanism that underlies the disparity between tropical and temperate herbivore species richness (Dyer et al. 2007).  10.5 Concluding statement  With biodiversity disappearing at an unprecedented rate (Gaston and Fuller 2007), and our forests overwhelmed by habitat destruction, fragmentation and degradation, it is critical that we refine our ability to document and appraise  183 forest organisms.  This dissertation suggests DNA barcoding can play a valuable role in forest biomonitoring and biosurveillance, and its adoption by national programs would be advantageous.  Monitoring and maintaining forest diversity requires a diversity of tools, and DNA barcoding is a useful addition to the tool set.  184 References   Abdo, Z. and Golding, G.B. 2007. 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This checklist builds upon the Geometridae component of earlier lists by Llewellyn Jones (1951), Lafontaine and Troubridge (1998), and Cannings and Scudder (2007). Most of the geometrid fauna of BC is fairly well known. Nearly all Canadian species in the subfamilies Sterhinnae, Geometrinae, Archiearinae and Ennominae were treated in McGuffin’s ‘Guide to the Geometridae of Canada’ series (1967, 1972, 1977, 1981, 1987, 1988).  The adult Larentiinae were not revised in this series, but the known larvae were covered earlier (McGuffin 1958). Some larentiine genera found in BC have been revised, namely Anticlea (Rindge 1967), Dysstroma in part (McDunnough 1946), Entephria (Troubridge 1997), Eubaphe (Fletcher 1954), Eupithecia (Bolte 1990), Hydriomena (McDunnough 1954), Operophtera (Troubridge and Fitzpatrick 1993), Plemyria (Choi 1998), and Rheumaptera (Skou 1986).  Within the remaining subfamilies, Scopula (Sterrhinae) was revised by Covell (1970), the Geometrinae by Ferguson (1985), and the following ennomine taxa have been treated (all or in part): Cassymini and Macariini (Ferguson 2008); Hesperumia (Rindge 1974b); Iridopsis (Rindge 1966); Stenoporpia (Rindge 1968); Bistonini (Rindge 1975), Baptini (Rindge 1979);  215 Caberini (Rindge 1949, 1950, 1956); Aspitates (Munroe 1963); Pero (Poole 1987; Rindge 1955); Xanthotype (Rindge 1978); Gabriola (Rindge 1974a); Probole (Tomon 2007); Enypia (Evans 1960); Melanolophia (Rindge 1964); Meris (Rindge 1981); Nematocampa (Ferguson 1993); Plataea (Rindge 1976); and Tetracis (Synaxis) (Ferris and Schmidt 2010).  Pohl et al. (2010) raised the status of several geometrid taxa from subspecies or junior subjective synonyms to valid species, and proposed numerous synonymies or revised synonymies relevant to BC Geometridae. Duncan (2006) documented larvae of the species known to defoliate coniferous trees in BC.  Parsons et al. (1999) compiled a global geometrid checklist, which is updated periodically online (Scoble and Hausmann 2007). The order of taxa in the checklist reflects recent studies that have examined subfamily and tribe relationships (Abraham et al. 2001, Young 2006, Yamamoto and Sota 2007, Regier et al. 2009, Mutanen et al. 2010, Wahlberg et al. 2010, chapter 4) and is congruent with the checklist of Pohl et al. (2010). Within subfamilies and tribes, the order follows the ‘Moths of North America’ checklist of Ferguson (1983) where possible. Each species is presented in italics followed by the author and date of the published description. Parentheses around the author and date indicate that the species was not described in the genus in which it is currently placed. Square brackets around the date indicate that the description was published in a year different from that given in the work.  Square brackets around the authors indicate that the authors were not listed on the original publication. Footnotes are provided for species that have a) been added  216 or removed from past checklists, b) undergone recent taxonomic changes, and c) introduced to BC.  Checklist Larentiinae  Cidariini  1. Dysstroma citrata (Linnaeus, 1761) 2. Dysstroma sobria Swett, 1917 3. Dysstroma ochrofuscaria Ferguson, 1983 4. Dysstroma truncata (Hufnagel, 1767) 5. Dysstroma walkerata (Pearsall, 1909) 6. Dysstroma hersiliata (Guenée, [1858]) 7. Dysstroma formosa (Hulst, 1896) 8. Dysstroma colvillei Blackmore, 1926 9. Dysstroma brunneata (Packard, 1867) 10. Dysstroma mancipata (Guenée, [1858]) 11. Eulithis propulsata (Walker, 1862) 12. Eulithis testata (Linnaeus, 1761) 13. Eulithis destinata (Möschler, 1860) 14. Eulithis flavibrunneata (McDunnough, 1943) 15. Eulithis xylina (Hulst, 1896) 16. Eurhinosea flavaria Packard, 1873 17. Antepirrhoe semiatrata (Hulst, 1881)7 18. Antepirrhoe fasciata Barnes & McDunnough, 1918 19. Antepirrhoe atrifasciata (Hulst, 1888) 20. Ecliptopera silaceata ([Denis & Schiffermüller], 1775) 21. Colostygia circumvallaria Hübner, [1799]8 22. Plemyria georgii Hulst, 1896  7 The North American species of Eustroma were transferred to Antepirrhoe by Choi (2001). 8 Formerly a subspecies of C. turbata (Hübner), Pohl et al (2010) designated it to a valid species.  217 23. Thera juniperata (Linnaeus, 1758)9 24. Thera otisi (Dyar, 1904) 25. Ceratodalia gueneata Packard, 1876 26. Lampropteryx suffumata ([Denis and Schiffermüller], 1775)10  Hydriomenini  27. Hydriomena exculpata Barnes & McDunnough, 1917 28. Hydriomena expurgata Barnes & McDunnough, 1918 29. Hydriomena irata Swett, 1910 30. Hydriomena perfracta Swett, 1910 31. Hydriomena marinata Barnes & McDunnough, 1917 32. Hydriomena edenata Swett, 1909 33. Hydriomena divisaria (Walker, 1860) 34. Hydriomena renunciata (Walker, 1862) 35. Hydriomena albimontanata McDunnough, 1939 36. Hydriomena nevadae Barnes & McDunnough, 1917 37. Hydriomena californiata Packard, 1871 38. Hydriomena crokeri Swett, 1910 39. Hydriomena ruberata (Freyer, [1831]) 40. Hydriomena macdunnoughi Swett, 1918 41. Hydriomena furcata (Thunberg, 1784) 42. Hydriomena quinquefasciata (Packard, 1871) 43. Hydriomena albifasciata (Packard, 1874) 44. Hydriomena speciosata (Packard, 1874) 45. Hydriomena morosata Barnes and McDunnough, 191711 46. Hydriomena nubilofasciata (Packard, 1871) 47. Hydriomena manzanita Taylor, 1906 48. Triphosa haesitata (Guenée, [1858]) 49. Coryphista meadii (Packard, 1874) 50. Rheumaptera undulata (Linnaeus, 1758) 51. Rheumaptera hastata (Linnaeus, 1758) 52. Rheumaptera subhastata (Nolcken, 1870) 53. Entephria multivagata (Hulst, 1881) 54. Entephria takuata (Taylor, 1908)  9 Introduced to Nova Scotia from Europe in 1945 (Prentice, 1963), this species has been collected in BC in recent years 10 Recently documented in BC by deWaard et al. (2008). 11 Added to list based on specimens from Riske Creek, BC held at the Royal BC Museum (RBCM).  218 55. Entephria lagganata (Taylor, 1908) 56. Entephria kidluitata (Munroe, 1951) 57. Mesoleuca ruficillata (Guenée, [1858]) 58. Mesoleuca gratulata (Walker, 1862) 59. Spargania magnoliata Guenée, [1858] 60. Spargania luctuata ([Denis & Schiffermüller], 1775) 61. Perizoma basaliata (Walker, 1862) 62. Perizoma grandis (Hulst, 1896) 63. Perizoma curvilinea (Hulst, 1896) 64. Perizoma costiguttata (Hulst, 1896) 65. Perizoma custodiata (Guenée, [1858]) 66. Anticlea vasiliata Guenée, [1858] 67. Anticlea multiferata (Walker, 1863)  Stamnodini  68. Stamnodes blackmorei Swett, 1915 69. Stamnodes topazata (Strecker, 1899) 70. Stamnoctenis morrisata (Hulst, 1887) 71. Stamnoctenis pearsalli (Swett, 1914) 72. Stamnodes marmorata (Packard, 1871)  Xanthorhoini  73. Xanthorhoe labradorensis (Packard, 1867) 74. Xanthorhoe packardata McDunnough, 1945 75. Xanthorhoe abrasaria (Herrich-Schäffer, [1855]) 76. Xanthorhoe iduata (Guenée, [1858]) 77. Xanthorhoe macdunnoughi Swett, 1918 78. Xanthorhoe ramaria Swett & Cassino, 1920 79. Xanthorhoe lagganata Swett & Cassino, 192012 80. Xanthorhoe baffinensis McDunnough, 1939 81. Xanthorhoe dodata Swett & Cassino, 1920 82. Xanthorhoe pontiaria Taylor, 1906 83. Xanthorhoe fossaria Taylor, 1906 84. Xanthorhoe decoloraria (Esper, [1806])  12 Formerly a subspecies of Xanthorhoe incursata (Hübner, [1813]), X. lagganata is now a valid species (Pohl et al 2010) and true X. incursata is restricted to central Europe.  219 85. Xanthorhoe alticolata Barnes & McDunnough, 1916 86. Xanthorhoe defensaria (Guenée, [1858]) 87. Xanthorhoe ferrugata (Clerck, 1759) 88. Xanthorhoe borealis Hulst, 1896 89. Xanthorhoe lacustrata (Guenée, [1858]) 90. Xanthorhoe clarkeata Ferguson, 1987 91. Epirrhoe alternata (Müller, 1764) 92. Epirrhoe plebeculata (Guenée, [1858]) 93. Epirrhoe sperryi Herbulot, 1951 94. Euphyia intermediata (Guenée, [1858]) 95. Enchoria lacteata (Packard, 1876) 96. Zenophleps lignicolorata (Packard, 1874) 97. Zenophleps alpinata Cassino, 1927 98. Psychophora phocata (Möschler, 1862) 99. Psychophora suttoni Heinrich, 194213 100. Costaconvexa centrostrigaria (Wollaston, 1858)  Asthenini  101. Hydrelia albifera (Walker, 1866) 102. Hydrelia brunneifasciata (Packard, 1876) 103. Venusia cambrica Curtis, 1839 104. Venusia duodecemlineata (Packard, 1873) 105. Venusia obsoleta (Swett, 1916) 106. Venusia pearsalli (Dyar, 1906) 107. Trichodezia albovittata (Guenée, [1858]) 108. [Minoa murinata (Scopoli, 1763)]14  Operophterini  109. Epirrita autumnata (Borkhausen, 1794) 110. Epirrita pulchraria (Taylor, 1907) 111. Operophtera brumata (Linnaeus, 1758)15  13 Added to list based on specimens from Pink Mountain, BC held in the Canadian National Collection (CNC) 14 Released in BC (MOFR 2009a) and AB (McClay et al. 1995) as a biological control agent for leafy spurge (Euphorbia esula), there is no evidence that it has established 15 Introduced; first detected in Victoria, BC in 1976  220 112. Operophtera bruceata (Hulst, 1886) 113. Operophtera danbyi (Hulst, 1896) 114. Operophtera occidentalis (Hulst, 1896)  Eudelini  115. Eubaphe mendica (Walker, 1854) 116. Eubaphe unicolor (Robinson, 1869)  Eupitheciini  117. Horisme intestinata (Guenée, [1858]) 118. Horisme incana Swett, 1918 119. Eupithecia palpata Packard, 1873 120. Eupithecia lafontaineata Bolte, 1990 121. Eupithecia sharronata Bolte, 1990 122. Eupithecia ornata (Hulst, 1896) 123. Eupithecia columbiata (Dyar, 1904) 124. Eupithecia maestosa (Hulst, 1896) 125. Eupithecia longipalpata Packard, 1876 126. Eupithecia placidata Taylor, 1908 127. Eupithecia unicolor (Hulst, 1896) 128. Eupithecia pseudotsugata MacKay, 1951 129. Eupithecia misturata (Hulst, 1896) 130. Eupithecia bryanti Taylor, 1906 131. Eupithecia regina Taylor, 1906 132. Eupithecia borealis (Hulst, 1898) 133. Eupithecia subfuscata (Haworth, 1809) 134. Eupithecia tripunctaria Herrich-Schäffer, 1852 135. Eupithecia lariciata (Freyer, 1841) 136. Eupithecia harrisonata MacKay, 1951 137. Eupithecia casloata (Dyar, 1904) 138. Eupithecia rotundopuncta Packard, 1871 139. Eupithecia intricata (Zetterstedt, [1839]) 140. Eupithecia satyrata (Hübner, [1813]) 141. Eupithecia nimbicolor (Hulst, 1896) 142. Eupithecia assimilata Doubleday, 1856 143. Eupithecia absinthiata (Clerck, 1759) 144. Eupithecia cretaceata (Packard, 1874) 145. Eupithecia behrensata Packard, 1876  221 146. Eupithecia gelidata Möschler, 1860 147. Eupithecia multistrigata (Hulst, 1896) 148. Eupithecia perfusca (Hulst, 1898) 149. Eupithecia annulata (Hulst, 1896) 150. Eupithecia olivacea Taylor, 1906 151. Eupithecia lachrymosa (Hulst, 1900) 152. Eupithecia interruptofasciata Packard, 1873 153. Eupithecia niphadophilata (Dyar, 1904) 154. Eupithecia pusillata (Denis & Schiffermüller, 1775)16 155. Eupithecia tenuata Hulst, 1880 156. Eupithecia agnesata Taylor, 1908 157. Eupithecia niveifascia (Hulst, 1898) 158. Eupithecia johnstoni McDunnough, 194617 159. Eupithecia albicapitata Packard, 1876 160. Eupithecia mutata Pearsall, 1908 161. Eupithecia spermaphaga (Dyar, 1917) 162. Eupithecia gilvipennata Cassino & Swett, 1922 163. Eupithecia anticaria Walker, 1862 164. Eupithecia graefii (Hulst, 1896) 165. Eupithecia nevadata Packard, 1871 166. Eupithecia ravocostaliata Packard, 1876 167. Prorella leucata (Hulst, 1896) 168. Prorella mellisa (Grossbeck, 1908) 169. Pasiphila rectangulata (Linnaeus, 1758)18  Lobophorini  170. Carsia sororiata (Hübner, [1813]) 171. Aplocera plagiata (Linnaeus, 1758)19 172. Acasis viridata (Packard, 1873) 173. Cladara limitaria (Walker, 1860) 174. Cladara atroliturata (Walker, [1863]) 175. Lobophora nivigerata Walker, 1862 176. Lobophora montanata Packard, 1874  16 Introduced; 2 specimens from the Vancouver, BC area have been identified as the Eurasian juniper pug moth, E. pusillata (see Chapter 6). 17 Added to list based on a single specimen collected near Okanagan Falls held at the RBCM. 18 Introduced; first recorded in Victoria, BC in 1968 (Ferguson and Mello 1996). 19 Released in BC (MOFR 2009b) as a biological control agent for St. John's wort (Hypericum perforatum), it has subsequently established in the southern interior.  222 177. Lobophora simsata Swett, 1920 178. Lobophora magnoliatoidata (Dyar, 1904) 179. Lobophora canavestita (Pearsall, 1906)  Sterrhinae  Sterrhini  180. Idaea demissaria (Hübner, [1831]) 181. Idaea rotundopennata (Packard, 1876) 182. Idaea dimidiata (Hufnagel, 1767)  Cosymbiini  183. Cyclophora dataria (Hulst, 1887) 184. Cyclophora pendulinaria (Guenée, [1858])  Scopulini20 21  185. Scopula ancellata (Hulst, 1887) 186. Scopula fuscata (Hulst, 1887) 187. Scopula junctaria (Walker, 1861) 188. Scopula quinquelinearia (Packard, 1870)22 189. Scopula quadrilineata (Packard, 1876) 190. Scopula frigidaria (Möschler, 1860) 191. Scopula siccata McDunnough, 1939 192. Scopula septentrionicola McDunnough, 1939 193. Scopula inductata (Guenée, [1858])23 194. Scopula luteolata (Hulst, 1880) 195. Scopula sideraria (Guenée, [1858])  20 Lobocleta quaesitata (Hulst, 1880) has been removed, as in Pohl et al. (2010), since it was erroneously reported in Canada by McGuffin (1967). 21 Scopula quadrilineata (Packard, 1876) has been removed, as in Pohl et al. (2010), as it has only been recorded as far west as Saskatchewan. 22 Raised from a subspecies of S. junctaria Walker to species status in Pohl et al. (2010) 23 Added to list based on several specimens from several BC localities held in the CNC and RBCM  223 196. Scopula sentinaria (Geyer, 1837) 197. Leptostales rubromarginaria (Packard, 1871)  Geometrinae  Nemoriini  198. Chlorosea nevadaria Packard, 1873 199. Chlorosea banksaria Sperry, 1944 200. Nemoria unitaria (Packard, 1873) 201. Nemoria darwiniata (Dyar, 1904) 202. Nemoria glaucomarginaria (Barnes & McDunnough, 1917)  Synchlorini  203. Dichorda rectaria (Grote, 1877)24 204. Synchlora aerata (Fabricius, 1798) 205. Synchlora bistriaria (Packard, 1876)    Hemitheini  206. Chlorochlamys triangularis Prout, 1912 207. Hemithea aestivaria (Hübner, [1799])25 208. Mesothea incertata (Walker, [1863])  Archiearinae26  209. Archiearis infans (Möschler, 1862)  24 Added to list based on three specimens from BC held at the Smithsonian Institute (SI) 25 Introduced; first reported in Vancouver, BC by Doğanlar and Beirne (1979) 26 Recent phylogenetic analyses (refs) strongly support the inclusion of North American and Eurasian ‘Archiearinae’ within Ennominae, and its demotion to Archiearini  224 210. Leucobrephos brephoides (Walker, 1857)  Cassymini  211. Nematocampa resistaria (Herrich-Schäffer, [1856]) 212. Protitame subalbaria (Packard, 1873) 213. Protitame virginalis (Hulst, 1900)  Macariini  214. Eumacaria madopata (Guenée, [1858])27 215. Speranza occiduaria (Packard, 1874)28 29 216. Speranza amboflava (Ferguson, 1953)30 217. Speranza brunneata (Thunberg, 1784) 218. Speranza boreata Ferguson, 200831 219. Speranza quadrilinearia (Packard, 1873) 220. Speranza loricaria (Eversmann, 1837) 221. Speranza exauspicata Walker, 1861 222. Speranza plumosata (Barnes & McDunnough, 1917) 223. Speranza bitactata (Walker, 1862) 224. Speranza decorata (Hulst, 1896) 225. Speranza colata (Grote, 1881) 226. Epelis truncataria (Walker, 1862)32 227. Macaria lorquinaria (Guenée, [1858]) 228. Macaria perplexata (Pearsall, 1913) 229. Macaria atrimacularia Barnes & McDunnough, 1913 230. Macaria ulsterata (Pearsall, 1913) 231. Macaria adonis Barnes & McDunnough, 1918  27 Formerly E. latiferrugata (Walker), Ferguson (2008) designated it a synonym. 28 Several species of BC Macaria were transferred to Speranza by Ferguson (2008). 29 Speranza andersoni (Swett, 1916) has been synonymized with S. occiduaria (Pohl et al. 2010). 30 Formerly a subspecies of S. sulphurea, which is now delimited as an Eastern species 31 BC specimens of Speranza anataria (Swett, 1913) are attributable to recently described S. boreata. 32 Formerly in Macaria, Ferguson (2008) transferred truncataria to Epelis.  225 232. Macaria masquerata Ferguson, 200833 233. Macaria sexmaculata Packard, 1867 234. Macaria submarmorata Walker, 1861 235. Macaria signaria (Hübner, [1809])34 236. Digrammia setonana (McDunnough, 1927) 237. Digrammia curvata (Grote, 1880) 238. Digrammia nubiculata (Packard, 1876) 239. Digrammia denticulata (Grote, 1883) 240. Digrammia delectata (Hulst, 1887) 241. Digrammia ubiquitata Ferguson, 2008 242. Digrammia muscariata (Guenée, [1858]) 243. Digrammia respersata (Hulst, 1880) 244. Digrammia californiaria (Packard, 1871) 245. Digrammia decorata (Grossbeck, 1907) 246. Digrammia triviata (Barnes & McDunnough, 1917) 247. Digrammia rippertaria (Duponchel, 1830) 248. Digrammia irrorata (Packard, 1876) 249. Digrammia neptaria (Guenée, [1858]) 250. Digrammia subminiata (Packard, 1873)  Boarmiini  251. Dasyfidonia avuncularia (Guenée, [1858]) 252. Orthofidonia exornata (Walker, 1862) 253. Hesperumia sulphuraria Packard, 1873 254. Hesperumia latipennis (Hulst, 1896) 255. Neoalcis californiaria (Packard, 1871) 256. Glena nigricaria (Barnes & McDunnough, 1913) 257. Stenoporpia pulmonaria (Grote, 1881) 258. Stenoporpia separataria (Grote, 1883) 259. Stenoporpia excelsaria (Strecker, 1899) 260. Aethalura intertexta (Walker, 1860) 261. Anavitrinelia addendaria (Grossbeck, 1908) 262. Iridopsis clivinaria (Guenée, [1858]) 263. Iridopsis larvaria (Guenée, [1858]) 264. Anavitrinelia pampinaria (Guenée, [1858])  33 BC specimens of Macaria bicolorata (Fabricius, 1798) are attributable to the recently described M. masquerata 34 Macaria unipunctaria (Wright, 1916) and Macaria marmorata (Ferguson, 1972) has been synonymized with M. signaria (Pohl et al. 2010).  226 265. Ectropis crepuscularia ([Denis and Schiffermüller], 1775) 266. Protoboarmia porcelaria (Guenée, [1858])  Gnophini35  267. Gnophos macguffini Smiles, 1978  Melanolophiini  268. Melanolophia imitata (Walker, 1860) 269. Eufidonia convergaria (Walker, 1860) 270. Eufidonia discospilata (Walker, 1862)  Bistonini  271. Biston betularia (Linnaeus, 1758) 272. Lycia ursaria (Walker, 1860) 273. Lycia rachelae (Hulst, 1896) 274. Hypagyrtis unipunctata (Haworth, 1809) 275. Hypagyrtis piniata (Packard, 1870) 276. Phigalia plumogeraria (Hulst, 1888) 277. Erannis vancouverensis Hulst, 1896  Baptini  278. Lomographa semiclarata (Walker, 1866)  Caberini  279. Sericosema juturnaria (Guenée, [1858]) 280. Sericosema wilsonensis Cassino & Swett, 1922 281. Cabera exanthemata (Scopoli, 1763) 282. Cabera erythemaria Guenée, [1858]  35 The Gnophini is under revision and it is presently unclear whether G. macguffini will remain within Gnophini sensu lato (A. Hausmann, pers. comm).  227 283. Cabera variolaria Guenée, [1858] 284. Cabera borealis (Hulst, 1896) 285. Eudrepanulatrix rectifascia (Hulst, 1896) 286. Drepanulatrix unicalcararia (Guenée, [1858]) 287. Drepanulatrix quadraria (Grote, 1882) 288. Drepanulatrix foeminaria (Guenée, [1858]) 289. Drepanulatrix carnearia (Hulst, 1888) 290. Drepanulatrix falcataria (Packard, 1873) 291. Drepanulatrix secundaria Barnes & McDunnough, 1916 292. Apodrepanulatrix litaria (Hulst, 1887) 293. Ixala desperaria (Hulst, 1887)  Angeronini  294. Aspitates aberrata (Edwards, 1884) 295. Euchlaena johnsonaria (Fitch, 1869) 296. Euchlaena madusaria (Walker, 1860) 297. Euchlaena marginaria (Minot, 1869) 298. Euchlaena tigrinaria (Guenée, [1858]) 299. Xanthotype sospeta (Drury, 1773) 300. Xanthotype urticaria Swett, 191836  Azelini  301. Pero honestaria (Walker, 1860) 302. Pero morrisonaria (Edwards, 1881) 303. Pero mizon Rindge, 1955 304. Pero behrensaria (Packard, 1871) 305. Pero occidentalis (Hulst, 1896)  Nacophorini  306. Phaeoura mexicanaria (Grote, 1883) 307. Gabriola dyari Taylor, 1904   36 Added to the list based on specimens from Charlie Lake, BC held in the RBCM.  228 Campaeini  308. Campaea perlata (Guenée, [1858])  Ennomini  309. Ennomos magnaria Guenée, [1858] 310. Ennomos alniaria (Linnaeus, 1758)37  Epirranthini  311. Spodolepis danbyi (Hulst, 1898)38  Lithinini  312. Philedia punctomacularia (Hulst, 1888) 313. Thallophaga taylorata (Hulst, 1896) 314. Thallophaga hyperborea (Hulst, 1900)  Anagogini  315. Selenia alciphearia Walker, 1860 316. Selenia kentaria (Grote & Robinson, 1867) 317. Metanema inatomaria Guenée, [1858] 318. Metanema determinata Walker, 1866 319. Metarranthis duaria (Guenée, [1858]) 320. Probole alienaria Herrich-Schäffer, [1855] 321. Probole amicaria (Herrich-Schäffer, [1855]) 322. Plagodis phlogosaria (Guenée, [1858]) 323. Plagodis pulveraria (Linnaeus, 1758)    37 Introduced; first recorded in Vancouver, BC by Covell et al (1986). 38 Previously considered a subspecies of S. substriataria Hulst, 1896, S. danbyi (Hulst) it is now considered to be a full species (Pohl et al. 2010) and all BC specimens are attributable to it.  229 Ourapterygini  324. Neoterpes trianguliferata (Packard, 1871) 325. Caripeta divisata Walker, [1863] 326. Caripeta aequaliaria Grote, 1883 327. Caripeta angustiorata Walker, [1863] 328. Caripeta sp. nr. aequaliaria39 329. Meris suffusaria McDunnough, 1940 330. Besma quercivoraria (Guenée, [1858]) 331. Lambdina fiscellaria (Guenée, [1858]) 332. Nepytia umbrosaria (Packard, 1873) 333. Nepytia phantasmaria (Strecker, 1899) 334. Nepytia freemani Munroe, 1963 335. Sicya macularia (Harris, 1850) 336. Plataea trilinearia (Packard, 1873) 337. Tetracis jubararia (Hulst, 1886)40 338. Tetracis pallulata (Hulst, 1887) 339. Tetracis cervinaria (Packard, 1871) 340. Tetracis formosa (Hulst, 1896) 341. Tetracis pallidata Ferris, 200941 342. Tetracis cachexiata Guenée, [1858] 343. Prochoerodes amplicineraria (Pearsall, 1906) 344. Prochoerodes forficaria (Guenée, [1858]) 345. Prochoerodes lineola (Göze, 1781) 346. Sabulodes edwardsata (Hulst, 1886) 347. Enypia venata (Grote, 1883) 348. Enypia griseata Grossbeck, 1908 349. Enypia packardata Taylor, 1906     39 A cryptic species within C. aequaliaria was flagged through DNA barcoding, subsequently corroborated with nuclear markers and genitalic characters, and is now being described (JRD unpublished). 40 The genus Synaxis is synonymized with Tetracis in Ferris and Schmidt (2010). 41 New species described with a single BC record (Trinity Valley) in Ferris and Schmidt (2010).  230 Appendix B: Supplementary figure for Chapter 2. Neighbour-joining tree for 400 species of Geometridae and Uraniidae from British Columbia, Canada and surrounding provinces, territories and states. BOLD process IDs and collection localities are provided for each sequence.   231   232   233   234   235   236   237   238   239   240   241   242   243   244   245   246   247   248   249   250   251   252   253   254 Appendix C: Supplementary table for Chapter 3. Taxonomic sample used in study, including Barcode of Life Database (BOLD) and GenBank accessions.  Also listed is the presence (+) or absence (-) of the NlaIII (N) and BamHI (B) restriction enzyme sites of the ‘NB system’, determined from the sequence data (i.e. not by performing the assay).  Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria albescens BOGDA065-08 Bogda-JA11-65 N/A 1  Japan Okinawa Bogdanowicz et al. 2000 N+ B- Lymantria albescens GBGL4530-07 AF075274 AF075274 Japan Okinawa Bogdanowicz et al. 2000 N+ B- Lymantria albescens LYMAN031-08 ww01229 HM775520 Japan Okinawa Present study N+ N/A Lymantria albescens LYMAN032-08 ww01230 HM775519 Japan Okinawa Present study N+ B- Lymantria albescens LYMAN033-08 ww01231 HM775518 Japan Okinawa Present study N+ N/A Lymantria albescens LYMAN034-08 ww01232 HM775517 Japan Okinawa Present study N+ B- Lymantria albescens LYMAN035-08 ww01233 HM775516 Japan Okinawa Present study N+ B- Lymantria albescens LYMAN036-08 ww01234 HM775515 Japan Okinawa Present study N+ B- Lymantria albescens LYMAN037-08 ww01235 HM775514 Japan Okinawa Present study N+ B- Lymantria albescens LYMAN038-08 ww01236 HM775513 Japan Okinawa Present study N+ B- Lymantria albescens LYMAN039-08 ww01237 HM775512 Japan Okinawa Present study N+ B- Lymantria albescens LYMAN076-08 ww01274 HM775511 Japan Okinawa Present study N+ B- Lymantria albescens LYMAN077-08 ww01275 HM775510 Japan Okinawa Present study N+ N/A Lymantria antennata GBGL1614-06 Lepi477 DQ149570 Australia Queensland Ball & Armstrong 2006 N- B- Lymantria antennata GBGL1615-06 Lepi475 DQ149571 Australia Queensland Ball & Armstrong 2006 N- B- Lymantria antennata GBGL1616-06 Lepi474 DQ149572 Australia Queensland Ball & Armstrong 2006 N- B- Lymantria antennata LYMAN162-08 ww02142 HM775522 Australia New South Wales Present study N- N/A  255 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria antennata LYMAN164-08 ww02144 HM775521 Australia New South Wales Present study N- B- Lymantria antennata LYMAN165-08 ww02145 HM775529 Australia New South Wales Present study N- N/A Lymantria antennata LYMAN166-08 ww02244 HM775528 Australia Queensland Present study N- N/A Lymantria antennata LYMAN167-08 ww02245 HM775527 Australia Queensland Present study N- N/A Lymantria antennata LYMAN168-08 ww02246 HM775526 Australia Queensland Present study N- B- Lymantria antennata LYMAN170-08 ww02248 HM775525 Australia Queensland Present study N- B- Lymantria antennata LYMAN171-08 ww02249 HM775524 Australia Queensland Present study N- B- Lymantria antennata LYMAN172-08 ww02250 HM775523 Australia Queensland Present study N- B- Lymantria antennata LYMAN173-08 ww02251 HM775531 Australia Queensland Present study N- B- Lymantria antennata LYMAN174-08 ww02252 HM775530 Australia Queensland Present study N- B- Lymantria atemeles GBGL1601-06 Lepi453 DQ116184 Thailand Kampaeng Saen Armstrong & Ball 2005 N- B- Lymantria atemeles LYMAN040-08 ww01238 HM775534 Thailand Kampaeng Saen Present study N- N/A Lymantria atemeles LYMAN041-08 ww01239 HM775533 Thailand Kampaeng Saen Present study N- N/A Lymantria atemeles LYMAN042-08 ww01240 HM775532 Thailand Kampaeng Saen Present study N- N/A Lymantria atemeles LYMAN175-08 ww02253 HM775535 Thailand Chantabury Present study N- N/A Lymantria bantaizana GBGL1580-06 Ly230 DQ116163 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria bantaizana GBGL1585-06 Ly231 DQ116168 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria bantaizana GBGL1590-06 Ly232 DQ116173 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria bantaizana GBGL1595-06 Ly228 DQ116178 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria brunneiplaga LTOLB207-09 AYK-04-0840-03 HM775536 Malaysia   Present study N+ B- Lymantria concolor LYMAN081-08 ww01279 HM775537 Nepal Jiri Present study N+ N/A Lymantria dispar BOGDA045-08 Bogda-JA5-45 N/A 1  Japan Oshima Island Bogdanowicz et al. 2000 N+ B+ Lymantria dispar BOGDA046-08 Bogda-JA5-46 N/A 1  Japan Ibaraki Pref. Bogdanowicz et al. 2000 N+ B+  256 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar BOGDA047-08 Bogda-JA5-47 N/A 1  Japan Ibaraki Pref. Bogdanowicz et al. 2000 N+ B+ Lymantria dispar BOGDA048-08 Bogda-JA5-48 N/A 1  Japan Ibaraki Pref. Bogdanowicz et al. 2000 N+ B+ Lymantria dispar BOGDA049-08 Bogda-JA5-49 N/A 1  Japan Ibaraki Pref. Bogdanowicz et al. 2000 N+ B+ Lymantria dispar BOGDA050-08 Bogda-JA5-50 N/A 1  Japan Ibaraki Pref. Bogdanowicz et al. 2000 N+ B+ Lymantria dispar BOGDA051-08 Bogda-JA5-51 N/A 1  Japan Ibaraki Pref. Bogdanowicz et al. 2000 N+ B+ Lymantria dispar BOGDA064-08 Bogda-JA10-64 N/A 1  Japan Hokkaido Bogdanowicz et al. 2000 N+ B+ Lymantria dispar GBGL1529-06 Ly35 DQ116112 Japan   Armstrong & Ball 2005 N+ B+ Lymantria dispar GBGL1536-06 Ly33 DQ116119 Japan   Armstrong & Ball 2005 N+ B+ Lymantria dispar GBGL1537-06 Ly34 DQ116120 Japan   Armstrong & Ball 2005 N+ N/A Lymantria dispar GBGL1538-06 Ly41 DQ116121 Japan   Armstrong & Ball 2005 N+ B+ Lymantria dispar GBGL4430-07 AB244647 AB244647 Japan Hokkaido Yamaguchi et al. unpublished N+ B+ Lymantria dispar LBCH7981-10 10-JDWBC-7981 HM775700 Canada 2  British Columbia Present study N+ B+ Lymantria dispar LYMAN045-08 ww01243 HM775704 Kyrgyzstan Karalma Present study N+ N/A Lymantria dispar LYMAN046-08 ww01244 HM775703 Kyrgyzstan Karalma Present study N+ B- Lymantria dispar LYMAN047-08 ww01245 HM775702 Kyrgyzstan Toktogul Present study N+ N/A Lymantria dispar LYMAN048-08 ww01246 HM775701 Kyrgyzstan Toktogul Present study N+ B- Lymantria dispar LYMMK112-09 LymMk_RB-1 HM775591 Russia Krasnojarsk Present study N+ B- Lymantria dispar LYMMK113-09 LymMk_RB-2 HM775590 Russia Krasnojarsk Present study N+ B- Lymantria dispar LYMMK114-09 LymMk_RB-3 HM775589 Russia Krasnojarsk Present study N+ B- Lymantria dispar LYMMK115-09 LymMk_RBI-1 HM775588 Russia Khakassia Present study N+ B- Lymantria dispar LYMMK116-09 LymMk_RBI-2 HM775586 Russia Khakassia Present study N+ B- Lymantria dispar LYMMK117-09 LymMk_RBI-3 HM775585 Russia Khakassia Present study N+ B- Lymantria dispar asiatica BOGDA016-08 Bogda-RA2-16 N/A 1  Russia Irkutskaya Oblast' Bogdanowicz et al. 2000 N+ B+  257 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar asiatica BOGDA017-08 Bogda-RA2-17 N/A 1  Russia Irkutskaya Oblast' Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA018-08 Bogda-RA3-18 N/A 1  Russia Primorskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA019-08 Bogda-RA3-19 N/A 1  Russia Primorskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA020-08 Bogda-RA3-20 N/A 1  Russia Primorskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA021-08 Bogda-RA3-21 N/A 1  Russia Primorskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA022-08 Bogda-RA3-22 N/A 1  Russia Primorskiy Kray Bogdanowicz et al. 2000 N- B- Lymantria dispar asiatica BOGDA023-08 Bogda-RA3-23 N/A 1  Russia Primorskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA024-08 Bogda-RA3-24 N/A 1  Russia Primorskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA025-08 Bogda-RA3-25 N/A 1  Russia Primorskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA026-08 Bogda-RA4-26 N/A 1  Russia Khabarovskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA027-08 Bogda-RA4-27 N/A 1  Russia Khabarovskiy Kray Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA028-08 Bogda-CH1-28 N/A 1  China Heilongjiang Sheng Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA029-08 Bogda-CH1-29 N/A 1  China Heilongjiang Sheng Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA030-08 Bogda-CH2-30 N/A 1  China Liaoning Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA031-08 Bogda-CH2-31 N/A 1  China Liaoning Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA032-08 Bogda-CH3-32 N/A 1  China Hebei Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA033-08 Bogda-CH3-33 N/A 1  China Hebei Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA034-08 Bogda-CH4-34 N/A 1  China Beijing Shi Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA035-08 Bogda-CH4-35 N/A 1  China Beijing Shi Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA036-08 Bogda-KOR-36 N/A 1  South Korea Seoul Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica BOGDA037-08 Bogda-KOR-37 N/A 1  South Korea Seoul Bogdanowicz et al. 2000 N+ B+ Lymantria dispar asiatica GBGL1523-06 Ly1L DQ116106 Russia Sakhalinskaya Oblast Armstrong & Ball 2005 N+ B+ Lymantria dispar asiatica GBGL1524-06 GP2 DQ116107 Russia Sakhalinskaya Oblast Armstrong & Ball 2005 N+ B+  258 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar asiatica GBGL1567-06 Ly218 DQ116150 South Korea Wontong Armstrong & Ball 2005 N+ N/A Lymantria dispar asiatica GBGL1568-06 Ly219 DQ116151 South Korea Wontong Armstrong & Ball 2005 N+ B+ Lymantria dispar asiatica GBGL1569-06 Ly220 DQ116152 South Korea Wontong Armstrong & Ball 2005 N+ B+ Lymantria dispar asiatica GBGL1586-06 Ly222 DQ116169 South Korea Wontong Armstrong & Ball 2005 N+ B+ Lymantria dispar asiatica LYMAN011-08 ww01209 HM775708 Mongolia Ulaanba-atar Present study N+ B+ Lymantria dispar asiatica LYMAN012-08 ww01210 HM775707 Mongolia Ulaanba-atar Present study N+ N/A Lymantria dispar asiatica LYMAN013-08 ww01211 HM775706 China Liaoning Present study N+ N/A Lymantria dispar asiatica LYMAN014-08 ww01212 HM775705 China Liaoning Present study N+ N/A Lymantria dispar asiatica LYMMK013-09 LymMk_AA-1 HM775695 Canada 2  British Columbia Present study N+ B+ Lymantria dispar asiatica LYMMK014-09 LymMk_AA-2 HM775694 Canada 2  British Columbia Present study N+ B+ Lymantria dispar asiatica LYMMK016-09 LymMk_CB-1 HM775692 China Beijing Shi Present study N+ B+ Lymantria dispar asiatica LYMMK017-09 LymMk_CB-2 HM775691 China Beijing Shi Present study N+ B+ Lymantria dispar asiatica LYMMK018-09 LymMk_CB-3 HM775690 China Beijing Shi Present study N+ B+ Lymantria dispar asiatica LYMMK019-09 LymMk_CH-1 HM775689 China Hebei Present study N+ B+ Lymantria dispar asiatica LYMMK020-09 LymMk_CH-2 HM775688 China Hebei Present study N+ B+ Lymantria dispar asiatica LYMMK021-09 LymMk_CH-3 HM775687 China Hebei Present study N+ B+ Lymantria dispar asiatica LYMMK022-09 LymMk_CL-1 HM775686 China Liaoning Present study N+ B+ Lymantria dispar asiatica LYMMK023-09 LymMk_CL-2 HM775608 China Liaoning Present study N+ B+ Lymantria dispar asiatica LYMMK024-09 LymMk_CL-3 HM775607 China Liaoning Present study N+ B+ Lymantria dispar asiatica LYMMK025-09 LymMk_CS-1 HM775685 China Shandong Present study N+ B+ Lymantria dispar asiatica LYMMK026-09 LymMk_CS-2 HM775605 China Shandong Present study N+ B+ Lymantria dispar asiatica LYMMK027-09 LymMk_CS-3 HM775684 China Shandong Present study N+ B+ Lymantria dispar asiatica LYMMK118-09 LymMk_RM-1 HM775584 Russia Primorskiy Kray Present study N+ B+  259 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar asiatica LYMMK119-09 LymMk_RM-2 HM775583 Russia Primorskiy Kray Present study N+ B+ Lymantria dispar asiatica LYMMK120-09 LymMk_RM-3 HM775582 Russia Primorskiy Kray Present study N+ B+ Lymantria dispar asiatica RFELP029-08 PaA-08-552 HM775618 Russia Primorskiy Kray Present study N+ B+ Lymantria dispar asiatica RFELP030-08 PaA-08-553 HM775617 Russia Primorskiy Kray Present study N+ B+ Lymantria dispar asiatica RFELP031-08 PaA-08-554 HM775616 Russia Primorskiy Kray Present study N+ N/A Lymantria dispar asiatica RFELP032-08 PaA-08-555 HM775615 Russia Primorskiy Kray Present study N+ B+ Lymantria dispar asiatica RFELP033-08 PaA-08-556 HM775614 Russia Primorskiy Kray Present study N+ N/A Lymantria dispar dispar BOGDA001-08 Bogda-US1-01 N/A 1  United States New Jersey Bogdanowicz et al. 2000 N- B- Lymantria dispar dispar BOGDA002-08 Bogda-US2-02 N/A 1  United States Vermont Bogdanowicz et al. 2000 N- B- Lymantria dispar dispar BOGDA003-08 Bogda-CAN-03 N/A 1  Canada Ontario Bogdanowicz et al. 2000 N- B- Lymantria dispar dispar BOGDA004-08 Bogda-CAN-04 N/A 1  Canada Ontario Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA005-08 Bogda-FRA-05 N/A 1  France Provence-Alpes-Cote d`Azur Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA006-08 Bogda-FRA-06 N/A 1  France Provence-Alpes-Cote d`Azur Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA007-08 Bogda-GER-07 N/A 1  Germany Baden-Wuerttemberg Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA008-08 Bogda-GER-08 N/A 1  Germany Baden-Wuerttemberg Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA009-08 Bogda-SAR-09 N/A 1  Italy Sardinia Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA010-08 Bogda-SLO-10 N/A 1  Slovakia Kurinec Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA011-08 Bogda-SLO-11 N/A 1  Slovakia Kurinec Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA012-08 Bogda-RA1-12 N/A 1  Russia Moscow City Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA013-08 Bogda-RA1-13 N/A 1  Russia Moscow City Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA014-08 Bogda-TUN-14 N/A 1  Tunisia Jendouba Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar BOGDA015-08 Bogda-TUN-15 N/A 1  Tunisia Jendouba Bogdanowicz et al. 2000 N+ B- Lymantria dispar dispar GBGL1515-06 Ly23 DQ116098 Canada Ontario Armstrong & Ball 2005 N- B-  260 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar GBGL1520-06 Ly20 DQ116103 Canada Ontario Armstrong & Ball 2005 N- B- Lymantria dispar dispar GBGL1535-06 Ly21 DQ116118 Canada Ontario Armstrong & Ball 2005 N- B- Lymantria dispar dispar GBGL1579-06 Ly161 DQ116162 United States West Virginia Armstrong & Ball 2005 N- B- Lymantria dispar dispar GBGL1602-06 Lepi454 DQ116185 United States   Armstrong & Ball 2005 N- B- Lymantria dispar dispar GBGL4532-07 AF075272 AF075272 United States   Bogdanowicz et al. 2000 N- B- Lymantria dispar dispar LMHRG001-06 SPI B-5-2 A HM775749 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG002-06 SPI C-02-02 A HM775748 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG004-06 SPI C-03-17 A HM775747 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG006-06 SPI I-3-17 A HM775746 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG007-06 SPI L-2-5 A HM775745 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG008-06 SPI V-23-8 A HM775732 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG009-06 SPI V-23-8 B HM775731 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG010-06 SPI V-24-3 A HM775730 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG011-06 SPI V-25-5 A HM775729 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG012-06 SPI V-26-5 A HM775728 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG014-06 SPI V-90-2 B HM775727 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG015-06 SPI V-90-2 A HM775726 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG016-06 SPI V-90-3 A HM775725 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG019-06 SPI V-92-1 B HM775724 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG020-06 SPI V-92-1 C HM775723 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG021-06 SPI V-92-1 D HM775722 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG022-06 SPI V-92-1 E HM775721 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG023-06 SPI V-92-3 A HM775720 Canada 2  British Columbia Present study N- B-  261 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar LMHRG024-06 SPI V-92-3 B HM775719 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG025-06 SPI V-93-1 A HM775718 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG026-06 SPI V-93-2 A HM775717 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG027-06 SPI V-93-2 B HM775716 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG029-06 SPI V-94-1 B HM775715 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG030-06 SPI V-94-1 C HM775714 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG031-06 SPI V-94-1 D HM775713 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG032-06 SPI V-98-2 A HM775712 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG033-06 SPI W-17-1 A HM775711 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG035-06 SPI X-39-1 A HM775710 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LMHRG036-06 KAM DAB-9 A HM775709 Canada 2  British Columbia Present study N- B- Lymantria dispar dispar LYMAN015-08 ww01213 HM775736 United States Virginia Present study N- N/A Lymantria dispar dispar LYMAN016-08 ww01214 HM775735 United States Maryland Present study N- B- Lymantria dispar dispar LYMAN017-08 ww01215 HM775734 United States Maryland Present study N- N/A Lymantria dispar dispar LYMAN018-08 ww01216 HM775733 United States Maryland Present study N- B- Lymantria dispar dispar LYMMK001-09 LymMk_Q-1 HM775587 Austria Vienna Present study N+ B- Lymantria dispar dispar LYMMK002-09 LymMk_Q-2 HM775576 Austria Vienna Present study N+ B- Lymantria dispar dispar LYMMK003-09 LymMk_Q-3 HM775565 Austria Vienna Present study N+ B- Lymantria dispar dispar LYMMK004-09 LymMk_R-1 HM775554 Austria Vienna Present study N+ B- Lymantria dispar dispar LYMMK005-09 LymMk_R-2 HM775543 Austria Vienna Present study N+ B- Lymantria dispar dispar LYMMK006-09 LymMk_R-3 HM775620 Austria Vienna Present study N+ B- Lymantria dispar dispar LYMMK007-09 LymMk_S-1 HM775619 Austria Burgenland Present study N+ B- Lymantria dispar dispar LYMMK008-09 LymMk_S-2 HM775699 Austria Burgenland Present study N+ B-  262 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar LYMMK009-09 LymMk_S-3 HM775698 Austria Burgenland Present study N+ B- Lymantria dispar dispar LYMMK010-09 LymMk_UB-1 HM775697 Bulgaria Sofiya-Grad Present study N+ B- Lymantria dispar dispar LYMMK011-09 LymMk_UB-2 HM775612 Bulgaria Sofiya-Grad Present study N+ B- Lymantria dispar dispar LYMMK012-09 LymMk_UB-3 HM775696 Bulgaria Sofiya-Grad Present study N+ B- Lymantria dispar dispar LYMMK028-09 LymMk_CCL-1 HM775683 Croatia Primorsko-Goranska Zupanjia Present study N+ B- Lymantria dispar dispar LYMMK029-09 LymMk_CCL-2 HM775682 Croatia Primorsko-Goranska Zupanjia Present study N+ B- Lymantria dispar dispar LYMMK030-09 LymMk_CCL-3 HM775681 Croatia Primorsko-Goranska Zupanjia Present study N+ B- Lymantria dispar dispar LYMMK031-09 LymMk_CSL-1 HM775680 Slovenia Sumarija Llrovljani Present study N+ B- Lymantria dispar dispar LYMMK032-09 LymMk_CSL-2 HM775679 Slovenia Sumarija Llrovljani Present study N+ B- Lymantria dispar dispar LYMMK033-09 LymMk_CSL-3 HM775678 Slovenia Sumarija Llrovljani Present study N+ B- Lymantria dispar dispar LYMMK034-09 LymMk_CSN-1 HM775677 Slovenia Sumarija Novska Present study N+ B- Lymantria dispar dispar LYMMK035-09 LymMk_CSN-2 HM775676 Slovenia Sumarija Novska Present study N+ B- Lymantria dispar dispar LYMMK036-09 LymMk_CSN-3 HM775675 Slovenia Sumarija Novska Present study N+ B- Lymantria dispar dispar LYMMK037-09 LymMk_CSO-1 HM775674 Slovenia Sumarija otok Present study N+ B- Lymantria dispar dispar LYMMK038-09 LymMk_CSO-2 HM775673 Slovenia Sumarija otok Present study N+ B- Lymantria dispar dispar LYMMK039-09 LymMk_CSO-3 HM775672 Slovenia Sumarija otok Present study N+ B- Lymantria dispar dispar LYMMK040-09 LymMk_CSS-1 HM775671 Slovenia Sumarija strizovojha Present study N+ B- Lymantria dispar dispar LYMMK041-09 LymMk_CSS-2 HM775670 Slovenia Sumarija strizovojha Present study N+ B- Lymantria dispar dispar LYMMK042-09 LymMk_CSS-3 HM775669 Slovenia Sumarija strizovojha Present study N+ B- Lymantria dispar dispar LYMMK043-09 LymMk_BF-1 HM775668 France Poitou-Charentes Present study N+ B- Lymantria dispar dispar LYMMK044-09 LymMk_BF-2 HM775667 France Poitou-Charentes Present study N+ B- Lymantria dispar dispar LYMMK045-09 LymMk_BF-3 HM775666 France Poitou-Charentes Present study N+ B- Lymantria dispar dispar LYMMK046-09 LymMk_N-1 HM775665 France Indre-et-Loire Present study N+ B-  263 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar LYMMK048-09 LymMk_O-1 HM775664 France Indre-et-Loire Present study N+ B- Lymantria dispar dispar LYMMK049-09 LymMk_O-2 HM775663 France Indre-et-Loire Present study N- B- Lymantria dispar dispar LYMMK050-09 LymMk_O-3 HM775662 France Indre-et-Loire Present study N+ B- Lymantria dispar dispar LYMMK051-09 LymMk_P-1 HM775661 France Indre-et-Loire Present study N+ B- Lymantria dispar dispar LYMMK052-09 LymMk_P-2 HM775660 France Indre-et-Loire Present study N+ B- Lymantria dispar dispar LYMMK053-09 LymMk_P-3 HM775659 France Indre-et-Loire Present study N+ B- Lymantria dispar dispar LYMMK054-09 LymMk_T-1 HM775658 France Alsace Present study N- B- Lymantria dispar dispar LYMMK055-09 LymMk_T-2 HM775657 France Alsace Present study N+ B- Lymantria dispar dispar LYMMK056-09 LymMk_T-3 HM775656 France Alsace Present study N+ B- Lymantria dispar dispar LYMMK057-09 LymMk_A-1 HM775655 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK058-09 LymMk_A-2 HM775654 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK059-09 LymMk_A-3 HM775653 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK060-09 LymMk_B-1 HM775652 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK061-09 LymMk_B-2 HM775651 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK062-09 LymMk_B-3 HM775650 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK063-09 LymMk_C-1 HM775649 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK064-09 LymMk_C-2 HM775648 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK065-09 LymMk_C-3 HM775647 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK066-09 LymMk_D-1 HM775646 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK067-09 LymMk_E-1 HM775645 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK068-09 LymMk_E-2 HM775644 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK069-09 LymMk_E-3 HM775643 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK070-09 LymMk_F-1 HM775642 Germany Baden-Wuerttemberg Present study N+ B-  264 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar LYMMK071-09 LymMk_F-2 HM775641 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK072-09 LymMk_F-3 HM775640 Germany Baden-Wuerttemberg Present study N+ B- Lymantria dispar dispar LYMMK073-09 LymMk_G-1 HM775606 Germany Bavaria Present study N+ B- Lymantria dispar dispar LYMMK074-09 LymMk_G-2 HM775639 Germany Bavaria Present study N+ B- Lymantria dispar dispar LYMMK075-09 LymMk_G-3 HM775638 Germany Bavaria Present study N+ B- Lymantria dispar dispar LYMMK076-09 LymMk_GL-1 HM775637 Germany Hesse Present study N+ B- Lymantria dispar dispar LYMMK078-09 LymMk_GL-3 HM775636 Germany Hesse Present study N+ B- Lymantria dispar dispar LYMMK079-09 LymMk_H-1 HM775635 Germany Bavaria Present study N+ B- Lymantria dispar dispar LYMMK080-09 LymMk_H-2 HM775634 Germany Bavaria Present study N+ B- Lymantria dispar dispar LYMMK081-09 LymMk_H-3 HM775633 Germany Bavaria Present study N+ B- Lymantria dispar dispar LYMMK082-09 LymMk_I-1 HM775632 Germany Hesse Present study N+ B- Lymantria dispar dispar LYMMK083-09 LymMk_I-2 HM775631 Germany Hesse Present study N+ B- Lymantria dispar dispar LYMMK084-09 LymMk_I-3 HM775630 Germany Hesse Present study N+ B- Lymantria dispar dispar LYMMK085-09 LymMk_J-1 HM775629 Germany Hesse Present study N+ B- Lymantria dispar dispar LYMMK086-09 LymMk_J-2 HM775628 Germany Hesse Present study N+ B- Lymantria dispar dispar LYMMK087-09 LymMk_J-3 HM775627 Germany Hesse Present study N+ B- Lymantria dispar dispar LYMMK088-09 LymMk_KG-1 HM775613 Greece Curr Present study N+ B- Lymantria dispar dispar LYMMK089-09 LymMk_KG-2 HM775626 Greece Curr Present study N+ B- Lymantria dispar dispar LYMMK097-09 LymMk_JL-1 HM775603 Lithuania Kuzsin Nezijos Present study N+ B- Lymantria dispar dispar LYMMK098-09 LymMk_JL-2 HM775602 Lithuania Kuzsin Nezijos Present study N+ B- Lymantria dispar dispar LYMMK099-09 LymMk_JL-3 HM775601 Lithuania Kuzsin Nezijos Present study N+ B- Lymantria dispar dispar LYMMK100-09 LymMk_PA-1 HM775600 Poland Poznan Region Present study N+ B- Lymantria dispar dispar LYMMK102-09 LymMk_PA-3 HM775599 Poland Poznan Region Present study N+ B-  265 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar LYMMK103-09 LymMk_PB-1 HM775598 Poland Poznan Region Present study N+ B- Lymantria dispar dispar LYMMK104-09 LymMk_PB-2 HM775597 Poland Poznan Region Present study N+ B- Lymantria dispar dispar LYMMK105-09 LymMk_PB-3 HM775596 Poland Poznan Region Present study N+ B- Lymantria dispar dispar LYMMK106-09 LymMk_PC-1 HM775610 Poland Poznan Region Present study N+ N/A Lymantria dispar dispar LYMMK107-09 LymMk_PC-2 HM775609 Poland Poznan Region Present study N+ N/A Lymantria dispar dispar LYMMK108-09 LymMk_PC-3 HM775595 Poland Poznan Region Present study N+ B- Lymantria dispar dispar LYMMK109-09 LymMk_PP-1 HM775594 Portugal Portalegre Present study N+ B- Lymantria dispar dispar LYMMK110-09 LymMk_PP-2 HM775593 Portugal Portalegre Present study N+ B- Lymantria dispar dispar LYMMK111-09 LymMk_PP-3 HM775592 Portugal Portalegre Present study N+ B- Lymantria dispar dispar LYMMK121-09 LymMk_ESL-1 HM775581 Slovakia Bratislava Present study N+ B- Lymantria dispar dispar LYMMK122-09 LymMk_ESL-2 HM775580 Slovakia Bratislava Present study N+ B- Lymantria dispar dispar LYMMK123-09 LymMk_ESL-3 HM775579 Slovakia Bratislava Present study N+ B- Lymantria dispar dispar LYMMK124-09 LymMk_K-1 HM775578 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK125-09 LymMk_K-2 HM775577 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK126-09 LymMk_K-3 HM775575 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK127-09 LymMk_L-1 HM775574 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK128-09 LymMk_L-2 HM775573 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK129-09 LymMk_L-3 HM775572 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK130-09 LymMk_M-1 HM775571 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK131-09 LymMk_M-2 HM775570 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK132-09 LymMk_M-3 HM775569 Switzerland Ticino Present study N+ B- Lymantria dispar dispar LYMMK133-09 LymMk_NC-1 HM775568 United States North Carolina Present study N- B- Lymantria dispar dispar LYMMK134-09 LymMk_NC-2 HM775567 United States North Carolina Present study N- B-  266 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar LYMMK135-09 LymMk_NC-3 HM775566 United States North Carolina Present study N- B- Lymantria dispar dispar LYMMK136-09 LymMk_CT-1 HM775564 United States Connecticut Present study N- B- Lymantria dispar dispar LYMMK137-09 LymMk_CT-2 HM775563 United States Connecticut Present study N- B- Lymantria dispar dispar LYMMK138-09 LymMk_CT-3 HM775562 United States Connecticut Present study N- B- Lymantria dispar dispar LYMMK139-09 LymMk_CT2-1 HM775561 United States Connecticut Present study N- B- Lymantria dispar dispar LYMMK140-09 LymMk_CT2-2 HM775560 United States Connecticut Present study N- B- Lymantria dispar dispar LYMMK141-09 LymMk_CT2-3 HM775559 United States Connecticut Present study N- B- Lymantria dispar dispar LYMMK142-09 LymMk_LAM-1 HM775558 United States New York Present study N- B- Lymantria dispar dispar LYMMK143-09 LymMk_LAM-2 HM775557 United States New York Present study N- B- Lymantria dispar dispar LYMMK144-09 LymMk_LAM-3 HM775556 United States New York Present study N- B- Lymantria dispar dispar LYMMK145-09 LymMk_LAP-1 HM775555 United States New York Present study N- B- Lymantria dispar dispar LYMMK146-09 LymMk_LAP-2 HM775553 United States New York Present study N- B- Lymantria dispar dispar LYMMK147-09 LymMk_LAP-3 HM775552 United States New York Present study N- B- Lymantria dispar dispar LYMMK148-09 LymMk_LB-1 HM775551 United States New York Present study N- B- Lymantria dispar dispar LYMMK149-09 LymMk_LB-2 HM775550 United States New York Present study N- B- Lymantria dispar dispar LYMMK150-09 LymMk_LB-3 HM775549 United States New York Present study N- B- Lymantria dispar dispar LYMMK151-09 LymMk_LM-1 HM775548 United States New York Present study N- B- Lymantria dispar dispar LYMMK152-09 LymMk_LM-2 HM775547 United States New York Present study N- B- Lymantria dispar dispar LYMMK153-09 LymMk_LM-3 HM775546 United States New York Present study N- B- Lymantria dispar dispar LYMMK154-09 LymMk_LO-1 HM775545 United States New York Present study N- B- Lymantria dispar dispar LYMMK155-09 LymMk_LO-2 HM775544 United States New York Present study N- B- Lymantria dispar dispar LYMMK156-09 LymMk_LO-3 HM775542 United States New York Present study N- B- Lymantria dispar dispar LYMMK157-09 LymMk_MA-1 HM775541 United States Massachusetts Present study N- B-  267 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar LYMMK158-09 LymMk_MA-2 HM775540 United States Massachusetts Present study N- B- Lymantria dispar dispar LYMMK159-09 LymMk_MA-3 HM775539 United States Massachusetts Present study N- B- Lymantria dispar dispar LYMMK160-09 LymMk_WV-1 HM775538 United States West Virginia Present study N- B- Lymantria dispar dispar LYMMK161-09 LymMk_WV-2 HM775622 United States West Virginia Present study N- B- Lymantria dispar dispar LYMMK162-09 LymMk_WV-3 HM775624 United States West Virginia Present study N- B- Lymantria dispar dispar LYMMK164-09 LymMk_LG-2 HM775621 Latvia   Present study N+ B- Lymantria dispar dispar TMNBD445-07 MNBTT-3246 HM775744 Canada New Brunswick Present study N- B- Lymantria dispar dispar TMNBD446-07 MNBTT-3247 HM775743 Canada New Brunswick Present study N- B- Lymantria dispar dispar TMNBD447-07 MNBTT-3248 HM775742 Canada New Brunswick Present study N- B- Lymantria dispar dispar TMNBD448-07 MNBTT-3249 HM775741 Canada New Brunswick Present study N- B- Lymantria dispar dispar TTMNB259-06 MNBTT-259 HM775740 Canada New Brunswick Present study N- B- Lymantria dispar dispar TTMNB260-06 MNBTT-260 HM775739 Canada New Brunswick Present study N- B- Lymantria dispar dispar XAG005-05 2005-ONT-589  GU091217 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG177-05 2005-ONT-761  GU091216 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG214-05 2005-ONT-798  GU091222 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG215-05 2005-ONT-799  GU091219 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG216-05 2005-ONT-800  GU091220 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG217-05 2005-ONT-801  GU091221 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG235-05 2005-ONT-819  GU091223 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG277-05 2005-ONT-861  GU091215 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG307-05 2005-ONT-891  GU091213 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG308-05 2005-ONT-892  GU091214 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAG348-05 2005-ONT-932  GU091218 Canada Ontario Hebert et al. 2010 N- B-  268 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar dispar XAG658-05 2005-ONT-1242  GU091224 Canada Ontario Hebert et al. 2010 N- B- Lymantria dispar dispar XAK267-06 2006-ONT-1262 HM775738 Canada Ontario Present study N- B- Lymantria dispar dispar XAK268-06 2006-ONT-1263 HM775737 Canada Ontario Present study N- B- Lymantria dispar japonica BOGDA038-08 Bogda-JA1-38 N/A 1  Japan Kyushu-chiho Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA039-08 Bogda-JA1-39 N/A 1  Japan Kyushu-chiho Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA040-08 Bogda-JA2-40 N/A 1  Japan Kyushu-chiho Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA041-08 Bogda-JA2-41 N/A 1  Japan Kyushu-chiho Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA042-08 Bogda-JA3-42 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA043-08 Bogda-JA4-43 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA044-08 Bogda-JA4-44 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA052-08 Bogda-JA6-52 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA053-08 Bogda-JA6-53 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B- Lymantria dispar japonica BOGDA054-08 Bogda-JA7-54 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA055-08 Bogda-JA8-55 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA056-08 Bogda-JA8-56 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA057-08 Bogda-JA9-57 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica BOGDA058-08 Bogda-JA9-58 N/A 1  Japan Honshu Bogdanowicz et al. 2000 N+ B+ Lymantria dispar japonica GBGL1527-06 Ly321 DQ116110 Japan Honshu Armstrong & Ball 2005 N+ B+ Lymantria dispar japonica GBGL1528-06 LY323 DQ116111 Japan Honshu Armstrong & Ball 2005 N+ B+ Lymantria dispar japonica GBGL1542-06 Ly332 DQ116125 Japan Honshu Armstrong & Ball 2005 N+ B+ Lymantria dispar japonica GBGL1548-06 Ly326 DQ116131 Japan Honshu Armstrong & Ball 2005 N+ B+ Lymantria dispar japonica GBGL1553-06 Ly328 DQ116136 Japan Honshu Armstrong & Ball 2005 N+ B+ Lymantria dispar japonica GBGL1570-06 Ly337 DQ116153 Japan Honshu Armstrong & Ball 2005 N+ B+  269 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria dispar japonica LYMAN007-08 ww01205 HM775753 Japan Honshu Present study N+ B+ Lymantria dispar japonica LYMAN008-08 ww01206 HM775752 Japan Honshu Present study N+ B+ Lymantria dispar japonica LYMAN009-08 ww01207 HM775751 Japan Honshu Present study N+ N/A Lymantria dispar japonica LYMAN010-08 ww01208 HM775750 Japan Honshu Present study N+ N/A Lymantria dispar japonica LYMMK091-09 LymMk_Hon-1 HM775625 Japan Honshu Present study N+ B+ Lymantria dispar japonica LYMMK092-09 LymMk_Hon-2 HM775611 Japan Honshu Present study N+ B+ Lymantria dispar japonica LYMMK093-09 LymMk_Hon-3 HM775604 Japan Honshu Present study N+ B+ Lymantria dissoluta LYMAN055-08 ww01253 HM775755 China Guangdong Present study N+ N/A Lymantria dissoluta LYMAN071-08 ww01269 HM775754 Hong Kong N.T. Shatin Present study N+ N/A Lymantria dissoluta LYMAN181-08 ww02259 HM775756 China Fujian Present study N+ N/A Lymantria ekeikei LYMAN096-08 ww01294 HM775757 Indonesia Irian Jaya Present study N+ N/A Lymantria flavida GBGL1504-06 Ly144a DQ116087 Japan Okinawa Armstrong & Ball 2005 N+ B- Lymantria flavida GBGL1505-06 Ly166 DQ116088 Japan Okinawa Armstrong & Ball 2005 N+ B- Lymantria flavida LYMAN026-08 ww01224 HM775761 Japan Okinawa Present study N+ B- Lymantria flavida LYMAN027-08 ww01225 HM775760 Japan Okinawa Present study N+ B- Lymantria flavida LYMAN028-08 ww01226 HM775759 Japan Okinawa Present study N+ B- Lymantria flavida LYMAN029-08 ww01227 HM775758 Japan Okinawa Present study N+ B- Lymantria fumida GBGL1589-06 Ly248 DQ116172 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria fumida GBGL1607-06 Lepi679 DQ116190 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria fumida GBGL1608-06 Ly248_2 DQ116191 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria fumida LYMAN075-08 ww01273 HM775764 Japan Iwate Present study N+ B- Lymantria fumida LYMAN085-08 ww01283 HM775763 Japan Honshu Present study N+ B- Lymantria fumida LYMAN086-08 ww01284 HM775762 Japan Honshu Present study N+ N/A  270 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria grisea LYMAN097-08 ww01295 HM775765 India Assam Present study N+ B- Lymantria lucescens GBGL1594-06 Ly184 DQ116177 Japan Honshu Armstrong & Ball 2005 N- B- Lymantria lucescens GBGL1613-06 Lep1114 DQ149569 Japan Honshu Ball & Armstrong 2006 N- B- Lymantria lucescens LYMAN063-08 ww01261 HM775767 Japan Honshu Present study N- N/A Lymantria lucescens LYMAN064-08 ww01262 HM775766 Japan Honshu Present study N- N/A Lymantria mathura GBGL1574-06 Ly99 DQ116157 South Korea Kangwon-do Armstrong & Ball 2005 N- B- Lymantria mathura GBGL1576-06 Ly121 DQ116159 South Korea Kangwon-do Armstrong & Ball 2005 N- B- Lymantria mathura GBGL1577-06 Ly123 DQ116160 South Korea Kangwon-do Armstrong & Ball 2005 N- B- Lymantria mathura GBGL1578-06 Ly125 DQ116161 South Korea Yongau-ri Armstrong & Ball 2005 N- B- Lymantria mathura LYMAN019-08 ww01217 HM775789 Japan Hokkaido Present study N- B- Lymantria mathura LYMAN020-08 ww01218 HM775788 Japan Honshu Present study N- N/A Lymantria mathura LYMAN021-08 ww01219 HM775787 Japan Honshu Present study N- N/A Lymantria mathura LYMAN022-08 ww01220 HM775786 South Korea nr. Soraksan NP Campground Present study N- B- Lymantria mathura LYMAN030-08 ww01228 HM775785 Japan Hokkaido Present study N- B- Lymantria mathura LYRFE002-08 PaA-08-1182 HM775774 Japan Fukushima Present study N- B- Lymantria mathura LYRFE003-08 PaA-08-1183 HM775773 Japan Fukushima Present study N- B- Lymantria mathura LYRFE004-08 PaA-08-1184 HM775772 Japan Fukushima Present study N- B- Lymantria mathura LYRFE005-08 PaA-08-1185 HM775771 Japan Fukushima Present study N- B- Lymantria mathura LYRFE006-08 PaA-08-1186 HM775770 Japan Fukushima Present study N- B- Lymantria mathura LYRFE007-08 PaA-08-1187 HM775769 Japan Fukushima Present study N- B- Lymantria mathura LYRFE008-08 PaA-08-1188 HM775768 Japan Fukushima Present study N- B- Lymantria mathura RFELP001-08 PaA-08-524 HM775784 Russia Primorskiy Kray Present study N- N/A Lymantria mathura RFELP002-08 PaA-08-525 HM775783 Russia Primorskiy Kray Present study N- B-  271 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria mathura RFELP003-08 PaA-08-526 HM775782 Russia Primorskiy Kray Present study N- B- Lymantria mathura RFELP004-08 PaA-08-527 HM775781 Russia Primorskiy Kray Present study N- B- Lymantria mathura RFELP005-08 PaA-08-528 HM775780 Russia Primorskiy Kray Present study N- B- Lymantria mathura RFELP006-08 PaA-08-529 HM775779 Russia Primorskiy Kray Present study N- B- Lymantria mathura RFELP007-08 PaA-08-530 HM775778 Russia Primorskiy Kray Present study N- B- Lymantria mathura RFELP008-08 PaA-08-531 HM775777 Russia Primorskiy Kray Present study N- B- Lymantria mathura RFELP009-08 PaA-08-532 HM775776 Russia Primorskiy Kray Present study N- B- Lymantria mathura RFELP010-08 PaA-08-533 HM775775 Russia Primorskiy Kray Present study N- B- Lymantria minomonis LTOLB230-09 AYK-04-5397 HM775790 Japan Yamanashi-ken Present study N+ B- Lymantria monacha BOGDA071-08 Bogda-MON-71 N/A 1  Japan Hokkaido Bogdanowicz et al. 2000 N+ B- Lymantria monacha GBGL1506-06 Ly247 DQ116089 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1508-06 Ly44_2 DQ116091 Czech Republic   Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1512-06 Ly65_2 DQ116095 Poland   Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1514-06 Ly389 DQ116097 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1518-06 Ly385 DQ116101 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1519-06 Ly392 DQ116102 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1530-06 Ly394 DQ116113 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1531-06 Ly395 DQ116114 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1540-06 Ly69 DQ116123 Czech Republic   Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1541-06 Ly239 DQ116124 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1544-06 Ly43 DQ116127 Poland   Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1546-06 Ly67 DQ116129 Czech Republic   Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1547-06 Ly70 DQ116130 Czech Republic   Armstrong & Ball 2005 N+ B-  272 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria monacha GBGL1549-06 Ly396 DQ116132 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1551-06 Ly68 DQ116134 Czech Republic   Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1552-06 Ly238 DQ116135 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1554-06 Ly401 DQ116137 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1560-06 Ly64 DQ116143 Poland   Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1561-06 Ly65 DQ116144 Poland   Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1562-06 Ly202 DQ116145 South Korea Kangwon-do Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1563-06 Ly203 DQ116146 South Korea Kangwon-do Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1564-06 Ly208 DQ116147 South Korea Kangwon-do Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1565-06 Ly214 DQ116148 South Korea Kangwon-do Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1566-06 Ly217 DQ116149 South Korea Kangwon-do Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1571-06 Ly342 DQ116154 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1572-06 Ly347 DQ116155 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1573-06 Ly343 DQ116156 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL1581-06 Ly240 DQ116164 Japan Honshu Armstrong & Ball 2005 N+ B- Lymantria monacha GBGL4527-07 AF075277 AF075277 Japan Hokkaido Bogdanowicz et al. 2000 N+ B- Lymantria monacha LYMMK172-09 LymMk_CZP-1 HM775818 Czech Republic   Present study N+ B- Lymantria monacha LYMMK173-09 LymMk_CZP-2 HM775817 Czech Republic   Present study N+ B- Lymantria monacha LYMMK174-09 LymMk_CZP-3 HM775816 Czech Republic   Present study N+ B- Lymantria monacha LYMMK175-09 LymMk_CZP-4 HM775791 Czech Republic   Present study N+ N/A Lymantria monacha LYMMK176-09 LymMk_CZP-5 HM775815 Czech Republic   Present study N+ B- Lymantria monacha LYMMK177-09 LymMk_CZP-6 HM775814 Czech Republic   Present study N+ B- Lymantria monacha LYMMK178-09 LymMk_JIP-1 HM775813 Japan   Present study N+ B-  273 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria monacha LYMMK179-09 LymMk_JIP-2 HM775812 Japan   Present study N+ B- Lymantria monacha LYMMK180-09 LymMk_JIP-3 HM775811 Japan   Present study N+ B- Lymantria monacha LYMMK181-09 LymMk_JIP-4 HM775810 Japan   Present study N+ B- Lymantria monacha RFELP011-08 PaA-08-534 HM775807 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP012-08 PaA-08-535 HM775806 Russia Primorskiy Kray Present study N+ N/A Lymantria monacha RFELP013-08 PaA-08-536 HM775805 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP014-08 PaA-08-537 HM775808 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP015-08 PaA-08-538 HM775804 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP016-08 PaA-08-539 HM775803 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP017-08 PaA-08-540 HM775802 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP018-08 PaA-08-541 HM775801 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP019-08 PaA-08-542 HM775800 Russia Primorskiy Kray Present study N+ N/A Lymantria monacha RFELP020-08 PaA-08-543 HM775799 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP021-08 PaA-08-544 HM775798 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP022-08 PaA-08-545 HM775809 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP023-08 PaA-08-546 HM775797 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP024-08 PaA-08-547 HM775796 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP025-08 PaA-08-548 HM775795 Russia Primorskiy Kray Present study N+ N/A Lymantria monacha RFELP026-08 PaA-08-549 HM775794 Russia Primorskiy Kray Present study N+ N/A Lymantria monacha RFELP027-08 PaA-08-550 HM775793 Russia Primorskiy Kray Present study N+ B- Lymantria monacha RFELP028-08 PaA-08-551 HM775792 Russia Primorskiy Kray Present study N+ N/A Lymantria naesigi LYMAN101-08 ww01299 HM775819 Philippines Negros Occidental Present study N+ B- Lymantria narindra LYMAN093-08 ww01291 HM775820 Thailand Near Thongphaphem Present study N- B-  274 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria nebulosa LYMAN104-08 ww01302 HM775821 China Wuzhi Shan Present study N+ B+ Lymantria nephrographa LYMAN094-08 ww01292 HM775822 Australia New South Wales Present study N- N/A Lymantria ninayi HCHL034-04 USNM ENT 196233 HM775823 Papua New Guinea Eastern Highlands Present study N+ B- Lymantria ninayi HCHL035-04 USNM ENT 196232 HM775824 Papua New Guinea Eastern Highlands Present study N+ B- Lymantria obfuscata BOGDA067-08 Bogda-OBF-67 N/A 1  India Kashmir Bogdanowicz et al. 2000 N+ B- Lymantria obfuscata GBGL1603-06 Lepi484 DQ116186 India   Armstrong & Ball 2005 N+ B- Lymantria obfuscata GBGL1604-06 Lepi485 DQ116187 India   Armstrong & Ball 2005 N- B- Lymantria obfuscata GBGL1605-06 Lepi486 DQ116188 India   Armstrong & Ball 2005 N+ B- Lymantria obfuscata GBGL4529-07 OBF AF075275 India Jammu and Kashmir Bogdanowicz et al. 2000 N+ B- Lymantria obfuscata GBGL4970-08 Lepi1024 DQ155599 India Himachal Pradesh Ball & Armstrong 2006 N+ B- Lymantria obfuscata LYMAN073-08 ww01271 HM775826 India Kulu Val Present study N+ B- Lymantria obfuscata LYMAN074-08 ww01272 HM775825 India Kulu Val Present study N+ B- Lymantria panthera LYMAN099-08 ww01297 HM775827 Indonesia Kalimantan Selatan Present study N+ B- Lymantria plumbalis LYMAN106-08 ww01304 HM775836 Thailand Pakchong Present study N- N/A Lymantria plumbalis LYMAN107-08 ww01305 HM775835 Thailand Pakchong Present study N- B- Lymantria plumbalis LYMAN108-08 ww01306 HM775834 Thailand Pakchong Present study N- B- Lymantria plumbalis LYMAN109-08 ww01307 HM775833 Thailand Pakchong Present study N- B- Lymantria plumbalis LYMAN110-08 ww01308 HM775832 Thailand Pakchong Present study N- B- Lymantria plumbalis LYMAN111-08 ww01309 HM775831 Thailand Pakchong Present study N- B- Lymantria plumbalis LYMAN112-08 ww01310 HM775830 Thailand Pakchong Present study N- B- Lymantria plumbalis LYMAN113-08 ww01311 HM775829 Thailand Pakchong Present study N- B- Lymantria plumbalis LYMAN114-08 ww01312 HM775828 Thailand Pakchong Present study N- B- Lymantria pulverea LYMAN082-08 ww01280 HM775838 Taiwan Tayuling Present study N+ N/A  275 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria pulverea LYMAN083-08 ww01281 HM775837 Taiwan Tayuling Present study N+ B- Lymantria rhapdota LYMAN105-08 ww01303 HM775839 Philippines N. Palawan Present study N+ N/A Lymantria schaeferi LYMAN187-08 ww02265 HM775840 China Fujian Present study N+ B- Lymantria semperi LYMAN185-08 ww02263 HM775841 Philippines Mindoro Present study N/A N/A Lymantria singapura LYMAN179-08 ww02257 HM775842 China Yunnan Present study N/A N/A Lymantria sinica LYMAN065-08 ww01263 HM775845 Taiwan T`ao-yuan Chen Present study N+ N/A Lymantria sinica LYMAN066-08 ww01264 HM775844 Taiwan T`ao-yuan Chen Present study N+ B- Lymantria sinica LYMAN070-08 ww01268 HM775843 China Hongkong Present study N+ B- Lymantria sp. nr. mathura LYMAN023-08 ww01221 HM775848 Taiwan Wulai Present study N+ N/A Lymantria sp. nr. mathura LYMAN024-08 ww01222 HM775847 Taiwan Wulai Present study N+ N/A Lymantria sp. nr. mathura LYMAN025-08 ww01223 HM775846 Hong Kong Shek Kong Present study N+ N/A Lymantria subrosea LYMAN068-08 ww01266 HM775849 Sri Lanka Mate. Dist. Present study N/A N/A Lymantria todara LYMAN189-08 ww02267 HM775850 India Trivendrum Present study N/A N/A Lymantria umbrifera LYMAN059-08 ww01257 HM775852 Taiwan Pilushi Present study N- N/A Lymantria umbrifera LYMAN060-08 ww01258 HM775851 Taiwan Pilushi Present study N- N/A Lymantria umbrosa BOGDA059-08 Bogda-JA10-59 N/A 1  Japan Hokkaido Bogdanowicz et al. 2000 N+ B- Lymantria umbrosa BOGDA060-08 Bogda-JA10-60 N/A 1  Japan Hokkaido Bogdanowicz et al. 2000 N+ B- Lymantria umbrosa BOGDA061-08 Bogda-JA10-61 N/A 1  Japan Hokkaido Bogdanowicz et al. 2000 N+ B- Lymantria umbrosa BOGDA062-08 Bogda-JA10-62 N/A 1  Japan Hokkaido Bogdanowicz et al. 2000 N+ B- Lymantria umbrosa BOGDA063-08 Bogda-JA10-63 N/A 1  Japan Hokkaido Bogdanowicz et al. 2000 N+ B- Lymantria umbrosa GBGL1543-06 Ly419 DQ116126 Japan Hokkaido Armstrong & Ball 2005 N+ B- Lymantria umbrosa GBGL1584-06 Ly420 DQ116167 Japan Hokkaido Armstrong & Ball 2005 N+ B- Lymantria umbrosa GBGL1596-06 Ly475 DQ116179 Japan Hokkaido Armstrong & Ball 2005 N+ B-  276 Identification BOLD ID Specimen ID Genbank No. Country Locality Publication NB Haplotype  Lymantria umbrosa GBGL1597-06 Ly477 DQ116180 Japan Hokkaido Armstrong & Ball 2005 N+ B- Lymantria umbrosa GBGL1598-06 Ly479 DQ116181 Japan Hokkaido Armstrong & Ball 2005 N+ B- Lymantria umbrosa GBGL1599-06 Ly480 DQ116182 Japan Hokkaido Armstrong & Ball 2005 N+ B- Lymantria umbrosa GBGL4423-07 AB244668 AB244668 Japan Hokkaido Yamaguchi et al. unpublished N+ B- Lymantria umbrosa GBGL4424-07 AB244667 AB244667 Japan Hokkaido Yamaguchi et al. unpublished N+ B- Lymantria umbrosa GBGL4425-07 AB244666 AB244666 Japan Hokkaido Yamaguchi et al. unpublished N+ B- Lymantria umbrosa GBGL4426-07 AB244664 AB244664 Japan Hokkaido Yamaguchi et al. unpublished N+ B- Lymantria umbrosa GBGL4427-07 AB244661 AB244661 Japan Hokkaido Yamaguchi et al. unpublished N+ B- Lymantria umbrosa GBGL4429-07 AB244652 AB244652 Japan Hokkaido Yamaguchi et al. unpublished N+ B- Lymantria umbrosa GBGL4431-07 AB244657 AB244657 Japan Hokkaido Yamaguchi et al. unpublished N+ B- Lymantria umbrosa GBGL4531-07 AF075273 AF075273 Japan Hokkaido Bogdanowicz et al. 2000 N+ B- Lymantria umbrosa LYMMK095-09 LymMk_JJ-2 HM775853 Japan Hokkaido Present study N+ B- Lymantria umbrosa LYMMK096-09 LymMk_JJ-3 HM775854 Japan Hokkaido Present study N+ B- Lymantria xylina BOGDA069-08 Bogda-XYL-69 N/A 1  Taiwan Taipei Bogdanowicz et al. 2000 N+ B- Lymantria xylina GBGL1575-06 Ly104 DQ116158 Taiwan Kuan-in Armstrong & Ball 2005 N+ B- Lymantria xylina GBGL1587-06 Ly105 DQ116170 Taiwan Kuan-in Armstrong & Ball 2005 N+ B- Lymantria xylina GBGL1588-06 Ly106 DQ116171 Taiwan Kuan-in Armstrong & Ball 2005 N+ B- Lymantria xylina GBGL4528-07 AF075276 AF075276 Taiwan T`ai-pei Hsien Bogdanowicz et al. 2000 N+ B-  1 Only a few representative sequences were deposited in GenBank from Bogdanowicz et al. 2000; the remaining sequences were manually constructed based on their text and figures 2 This specimen was collected as part of a gypsy moth surveillance program and the country and locality refers to this event  277 Appendix D: Supplementary figure for Chapter 3. Complete maximum likelihood tree for 36 species of Lymantria. Full tree from Figure 3.3 displaying haplotype variation within species clusters.  BOLD process IDs and collection localities are provided for each sequence.  Tree was rooted with the outgroup Orgyia antiqua.  278   279   280   281   282 Appendix E: Supplementary table for Chapter 4. Taxonomic sample for phylogenetic analysis.  Shaded boxes indicate a sequence for that gene region was included in analysis, and its sequence length is provided.  Subfamily / family Tribe / subfamily Species BOLD-ID LTOL5 COI-3-COII 18S 28S 16S EF1- a COI- 5P  Archiearinae* Archiearinae* Archiearis parthenias$ NAGEO020-09 6633 919 612       658  Archiearinae* Lachnocephala vellosata NAGEO189-09   919 612 249 340   658  Desmobathrinae Desmobathrini* Ametris nitocris NAGEO147-09     612 249     658  Eumeleini# Eumelea ludovicata NAGEO076-09   848 612 249     658  Ennominae Abraxini* Abraxas latifasciata NAGEO107-09   919 612 249 340 924 658  Abraxini* Ligdia wagneri  NAGEO096-09   916 612 249 340   658  Alsophilini* Alsophila pometaria NAGEO018-09   919 612 249 340 726 658  Angeronini* Aspitates forbesi NAGEO123-09   919 612   340   658  Angeronini* Cymatophora approximaria NAGEO154-09   789 612       658  Angeronini* Euchlaena johnsonaria NAGEO260-09   919         658  Angeronini* Lytrosis unitaria NAGEO153-09   919 612 249 340   658  Angeronini* Xanthotype urticaria NAGEO017-09   919 612   340 825 658  Azelinini* Pero mizon NAGEO045-09   919 612 249   726 658  Azelinini* Stenaspilatodes antidiscaria NAGEO152-09   908 612 249 340   658  Baptini* Lomographa subspersata NAGEO115-09   919 612 249 340   658  Baptini* Synegia hadassa NAGEO075-09   919 612 249     658  Bistonini* Biston betularia$ NAGEO031-09 6633 866 612 249 340 924 658  Bistonini* Cochisea paula NAGEO118-09   919 612   340 820 658  Bistonini* Phigalia plumigera NAGEO080-09   919 612 249 340 924 658  283 Subfamily / family Tribe / subfamily Species BOLD-ID LTOL5 COI-3-COII 18S 28S 16S EF1- a COI- 5P  Boarmiini* Iridopsis sp. NAGEO078-09   723 612 249     658  Boarmiini* Anavitrinella ocularia NAGEO083-09     612       658  Boarmiini* Glaucina sp. NAGEO082-09   884 612 249     658  Boarmiini* Hesperumia latipennis NAGEO282-09   919   249     658  Boarmiini* Hulstina imitatrix NAGEO086-09   764 612 249   825 658  Boarmiini* Melanchroia sp. NAGEO130-09   570   249     658  Boarmiini* Orthofidonia flavivenata NAGEO199-09   919         658  Boarmiini* Protoboarmia porcelaria NAGEO272-09   919   249     658  Boarmiini* Pterotaea lamiaria NAGEO077-09   864 612 249     658  Boarmiini* Stenoporpia sp. NAGEO252-09   919         658  Caberini* Cabera erythemaria NAGEO150-09   919 612 249 340   658  Caberini* Episemasia solitaria NAGEO161-09   830 612       658  Caberini* Eudrepanulatrix rectifascia NAGEO087-09   919 612   340 816 658  Caberini* Sericosema sp. NAGEO209-09   919         658  Caberini* Stergamataea sp. NAGEO012-09   919 612 249     658  Campaeini* Campaea perlata$ NAGEO064-09 6633 919 612 249   924 658  Cassymini* Nematocampa brehmeata NAGEO042-09   919 612 249 340 924 658  Cassymini* Protitame virginalis NAGEO159-09   917 612 249 340   658  Cassymini* Taeniogramma odrussa NAGEO146-09   912 612 249 340 726 658  Ennomini* Ennomos magnaria NAGEO157-09   919 612 249 340 924 658  Ennomini* Selenia bilunaria NAGEO072-09   919 612 207   762 658  Epirranthini* Spodolepis substriataria NAGEO156-09   919 612 249 340   658  Eutoeini# Luxiaria emphatica NAGEO106-09   919 612       658  Gnophini* Gnophos macguffini NAGEO132-09   903 612       658  Gonodontini* Colotois pennaria NAGEO137-09   919 612 249 340   658  Hypochrosini* Metarranthis indeclinata NAGEO162-09   919 612       658  Hypochrosini* Nothomiza formosa NAGEO114-09   919 612 249 340   658  Hypochrosini* Omiza lycoraria NAGEO105-09   875 612 249     658  284 Subfamily / family Tribe / subfamily Species BOLD-ID LTOL5 COI-3-COII 18S 28S 16S EF1- a COI- 5P  Hypochrosini* Plagodis fervidaria$ NAGEO037-09 6633 919 612 233 340 924 658  Lithinini* Gueneria similaria NAGEO155-09   884 612 249     658  Lithinini* Odontothera sp. NAGEO190-09   919 612   340   658  Lithinini* Thallophaga hyperborea NAGEO125-09   865 612 249 340   658  Macariini* Chiasmia clathrata NAGEO070-09   919 612   340 924 658  Macariini* Heliomata cycladata NAGEO026-09   919 612   340   658  Macariini* Digrammia curvata NAGEO242-09   919   249     658  Macariini* Speranza guenearia NAGEO057-09   919 612   340 903 658  Macariini* Fernaldella fimetaria NAGEO041-09   919 612   340 924 658  Melanolophiini* Melanolophia imitata NAGEO249-09   919   249     658  Melanolophiini* Vinemina catalina NAGEO216-09   919   198     658  Nacophorini* Aethaloida packardaria NAGEO008-09   919   249 340 924 658  Nacophorini* Amelora megalocephala NAGEO187-09   859 612 249     658  Nacophorini* Animomyia smithii NAGEO079-09   919 612 249     658  Nacophorini* Ceratonyx permagnaria NAGEO202-09   919   221     658  Nacophorini* Hasodima elegans NAGEO185-09   919 612 249 340 924 658  Nephodiini# Carpella Janzen1 NAGEO090-09   919 612 249 340 924 658  Ourapterygini* Caripeta angustiorata NAGEO183-09   919 612   340 870 658  Ourapterygini* Enypia venata NAGEO228-09   919   249     658  Ourapterygini* Eutrapela clemataria NAGEO089-09   919 612 249   924 658  Ourapterygini* Nepytia sp. NAGEO192-09   919   249     658  Ourapterygini* Pherne sperryi NAGEO014-09   919 612 249     658  Ourapterygini* Phyllodonta peccataria NAGEO205-09   919   223     658  Ourapterygini* Sabulodes olifata NAGEO203-09   919   249     658  Ourapterygini* Sicya macularia NAGEO044-09   852 612 249 340   658  Ourapterygini* Somatolophia ectrapelaria NAGEO088-09   919 612 249 340 924 658  Palyadini* Phrygionis privignaria NAGEO025-09   919 612 249 340 924 658  Sphacelodini* Sphacelodes vulneraria NAGEO010-09   919 612   340 924 658  285 Subfamily / family Tribe / subfamily Species BOLD-ID LTOL5 COI-3-COII 18S 28S 16S EF1- a COI- 5P  Thinopterygini# Thinopteryx crocopterata NAGEO122-09   361 612   340   658  Geometrinae Aracimini# Aracima muscosa NAGEO091-09   919 612     924 658  Dichordophorini* Dichordophora phoenix NAGEO024-09   919     340 726 658  Dysphaniini# Dysphania militaris NAGEO120-09   919 612   340 924 658  Comibaenini# Comibaena quadrinotata NAGEO092-09   849 612 249   924 658  Geometrini# Geometra papilionaria NAGEO119-09   919 612   340   658  Hemistolini# Hemistola veneta NAGEO093-09   919 612 249   672 658  Hemitheini* Chlorochlamys sp. NAGEO029-09   919 612 249 340   658  Hemitheini* Hemithea aestivaria NAGEO269-09   919         642  Hemitheini* Hethemia pistasciaria NAGEO182-09   859 612   340   658  Hemitheini* Mesothea incertata NAGEO128-09   916 612 249     658  Nemoriini* Chlorosea margaretaria$ NAGEO005-09 6633 919 612   340   658  Nemoriini* Dichorda iridaria NAGEO164-09   919 612 249     658  Nemoriini* Nemoria mimosaria NAGEO166-09   919 612 249     658  Nemoriini* Eucyclodes gavissima NAGEO108-09   919 612 249   726 658  Pseudoterpnini# Dindica polyphaenaria NAGEO109-09   919 612 249   687 658  Pseudoterpnini# Hypobapta xenomorpha$ NAGEO006-09 6633 919 612   340 894 658  Rhomboristini* Lophochorista calliope NAGEO139-09   919 612 249 340   658  Synchlorini* Synchlora aerata NAGEO027-09   829 612 221     658  Tribe uncertain# Agathia curvifiens NAGEO117-09   919 612 249   753 658  Larentiinae Asthenini* Hydrelia flammeolaria NAGEO073-09   919 612 249 340   658  Asthenini* Laciniodes unistirpis NAGEO111-09   857 612 249 340   658  Asthenini* Trichodezia albovittata NAGEO009-09   903 612 249 340 924 658  Asthenini* Venusia cambrica NAGEO251-09   919   249     658  Chesiadini* Aplocera efformata NAGEO071-09   573 612     924 658  Cidariini* Cidaria fulvata NAGEO188-09   919 612   340   658  286 Subfamily / family Tribe / subfamily Species BOLD-ID LTOL5 COI-3-COII 18S 28S 16S EF1- a COI- 5P  Cidariini* Dysstroma formosa NAGEO067-09   919 612   340 798 658  Cidariini* Ecliptopera silaceata NAGEO180-09   697 612   340   658  Cidariini* Antepirrhoe (Eustroma) sp. NAGEO194-09   912   249     654  Eudulini* Eubaphe sp. NAGEO032-09   919   195 340   658  Euphyiini* Euphyia intermediata NAGEO176-09   919 612   340   658  Eupitheciini* Pasiphila rectangulata NAGEO280-09   919         632  Eupitheciini* Eupithecia acutipennis$ NAGEO021-09 6633 866 612 249 340 915 658  Hydriomenini* Coryphista meadii NAGEO028-09     612 249 340   658  Hydriomenini* Hydriomena furcata NAGEO066-09   919 612       658  Larentiini# Spargania magnoliata NAGEO051-09   626 612 249   837 658  Larentiini# Anticlea (Earophila) badiata NAGEO186-09   919 612   340   658  Lobophorini* Cladara limitaria NAGEO246-09   919   202     658  Lobophorini* Heterophleps triguttaria NAGEO048-09   877 612       658  Lobophorini* Lobophora nivigerata NAGEO265-09   919   223     640  Lobophorini* Scelidacantha triseriata NAGEO049-09   919 612   340 924 658  Lobophorini* Trichopteryx carpinata$ NAGEO003-09 6633 919 612 249 340 924 658  Melanthiini# Melanthia procellata NAGEO094-09   919 612   340 924 658  Operophterini* Epirrita autumnata NAGEO129-09   919 612 249 340   658  Operophterini* Operophtera brumata NAGEO232-09   919   249     658  Perizomini* Perizoma grandis NAGEO177-09   919 612 249     658  Rheumapterini* Rheumaptera undulata NAGEO273-09       249     658  Rheumapterini* Triphosa haesitata NAGEO193-09   787   249     658  Stamnodini* Stamnodes marmorata NAGEO050-09   919 612   340 798 658  Stamnodini* Stamnoctenis nr. morrisata NAGEO054-09   919 612   340   658  Trichopterygini* Carige sp. NAGEO104-09   919 612 249 340   658  Trichopterygini* Dyspteris abortivaria NAGEO174-09   919 612   340   658  Trichopterygini* Tyloptera bella NAGEO095-09   865 612 193     658  Xanthorhoini* Costaconvexa centrostrigaria NAGEO178-09   893 612       658  287 Subfamily / family Tribe / subfamily Species BOLD-ID LTOL5 COI-3-COII 18S 28S 16S EF1- a COI- 5P  Xanthorhoini* Epirrhoe medeifascia NAGEO204-09   919         658  Xanthorhoini* Orthonama obstipata$ NAGEO019-09 6633 897 612       658  Xanthorhoini* Psychophora sp. G NAGEO131-09   877 612       658  Xanthorhoini* Xanthorhoe lacustrata NAGEO030-09   919 612   340 900 658  Xanthorhoini* Zenophleps sp. NAGEO217-09   919         658  Oenochrominae* Oenochrominae* Dichromodes sp.$ NAGEO002-09 6633 919 612   340 924 658  Oenochrominae* Dinophalus lechriomita group$ NAGEO004-09 6633 919 612     924 658  Oenochrominae* Ergavia carinenta NAGEO023-09   919 612 249   924 658  Oenochrominae* Nearcha sp. NAGEO084-09   919 612       658  Oenochrominae* Sarcinodes perakaria NAGEO121-09   795 612 249 340   658  Sterrhinae Cosymbiini* Cyclophora nr. dataria$ NAGEO007-09 6633 919 612 235 340 924 658  Cosymbiini* Pleuroprucha insulsaria NAGEO170-09   919 612 249   726 658  Cosymbiini* Semaeopus gracilata NAGEO201-09   919         658  Rhodometrini# Rhodometra sacraria NAGEO022-09   866 612 249 340 924 658  Scopulini* Leptostales ferruminaria NAGEO168-09   919 612 249 340   658  Scopulini* Lophosis labeculata NAGEO169-09   919 612 249     658  Scopulini* Pseudasellodes fenestrariaDHJ01 NAGEO034-09   919 612   340 924 658  Scopulini* Scopula limboundata$ NAGEO001-09 6633 859 612 249 340 843 658  Cyllopoidini# Smicropus laeta NAGEO113-09   919 612       658  Sterrhini* Idaea demissaria NAGEO085-09   919 612 249   870 658  Sterrhini* Lobocleta peralbata NAGEO167-09   919 612   340   658  Timandrini* Haematopis grataria NAGEO053-09   858 612 249     658  Timandrini* Timandra amaturaria NAGEO172-09   919 612 249     658  Uraniidae Epipleminae Calledapteryx dryopterata NAGEO046-09   866 612   340   658  Epipleminae Callizzia sp. NAGEO271-09   919   249     658  288 Subfamily / family Tribe / subfamily Species BOLD-ID LTOL5 COI-3-COII 18S 28S 16S EF1- a COI- 5P  Epipleminae Erosia veninotata NAGEO038-09   864 612       658  Epipleminae Metorthocheilus emarginatus NAGEO068-09   862 612   340 924 641  Epipleminae Phazaca interrupta NAGEO081-09   919 612       658  Epipleminae Schidax squamaria NAGEO033-09   877 612 249     658  Epipleminae Nedusia sp. NAGEO056-09   869 612       658  Epipleminae Syngria druidaria$ NAGEO058-09 6633 797 612 249     658  Microniinae Acropteris sparsaria$ NAGEO055-09 6633 917 612     870 658  Uraniinae Lyssa zampa$ NAGEO060-09 6633 919 612 226   924 658  Uraniinae Urania fulgens NAGEO065-09   919 612 226   900 658  Uraniinae Urapteroides sp. NAGEO069-09   865 612 249   780 650 Epicopeiidae Epicopeiinae Epicopeia hainesii$ NAGEO039-09 6633 865 612   340   658  Epicopeiinae Psychostrophia melangaria$ NAGEO040-09 6633 865 612   340 924 658 Sematuridae Sematurinae Coronidia orithea NAGEO013-09   919 612 249   726 658  Sematurinae Homidiana sp. NAGEO061-09   919 612       658  Sematurinae Sematura luna$ NAGEO063-09 6633 864 612 249     658 Noctuidae Lymantriinae Lymantria dispar$ NAGEO059-09 6633 919 612 249 340 918 658  Amphipyrinae Spodoptera frugiperda$ NAGEO074-09 6633 919 612 249   888 658  Plusiinae Trichoplusia ni$ NAGEO043-09 6633 865 612 180 340 870 658 Drepanidae Cyclidiinae Cyclidia substigmaria$ NAGEO062-09 6633 919 612 249 340 738 658  Drepaninae Drepana bilineata NAGEO243-09   919   249     658  Oretinae Oreta rosea$ NAGEO036-09 6633 919 612 249 340 909 658 Thyatiridae Thyatirinae Pseudothyatira cymatophoroides$ NAGEO035-09 6633 919 612 249 340 924 658  * suprageneric taxon of Geometridae found in North America # suprageneric taxon of Geometridae not known from North America $ taxon analyzed by Regier et al. 2009  289 Appendix F: Supplementary table for Chapter 4. Target regions, primer names (F = forward, R = reverse), primer sequences, annealing temperatures, and references.  Target F primer Primer sequence (5' to 3') R primer Primer sequence (5' to 3') Temp. Seq. Ref.  COI-5p LepF1 ATTCAACCAATCATAAAGATATTGG LepR1 TAAACTTCTGGATGTCCAAAAAATCA 50 Y 1 COI-3p- COII cos2183 CAACATTTATTTTGATTTTTCGG COI-IIR GTTCAAATTAATTCAATTATTTG 50 Y 2 16S 16Sgaf GTATCTTGTGTATCAGAGTT 16Sgar CCTGGCTTACACCGGTTTGAA 50 Y 3 18S rc18H GCTGAAACTTAAAGGAATTGACGGAAGGGCAC 18L  CACCTACGGAAACCTTGTTACGACTT 50 Y 4 28S 28SD2B GTCGGGTTGCTTGAGAGTGC 28SD3Ar TCCGTGTTTCAAGACGGGTC 50 Y 5 EF1a EF1aLepF2 ACAAATGCGGTGGTATCGACAA EF1aLepR GATTTACCRGWACGACGRTC 58 Y 3 EF1a EF1aLepF1 CACATYAACATTGTCGTSATYGG EF1aLepR GATTTACCRGWACGACGRTC 58 N 3 EF1a EF1aLepF3 GATATCGCTCTGTGGAAGTTCG EF1aLepR GATTTACCRGWACGACGRTC 58 N 3 EF1a EF_F GTCACCATCATYGACGC EF1aR GATTTACCRGWACGACGRTC 58 N 6,7 Wingless LepWg1 GARTGYAARTGYCAYGGYATGTCTGG LepWg2 ACTICGCARCACCARTGGAATGTRCA 50 N 8 CAD CAD_743nF GGNGTNACNACNGCNTGYTTYGARCC CAD_1028R TTRTTNGGNARYTGNCCNCCCAT 50 N 9 CAD CAD_2F GTNGTNTTYCARACNGGNATGGT CAD_3R RTGYTCNGGRTGRAAYTG 50 N 10 CAD CAD_2F GTNGTNTTYCARACNGGNATGGT CAD_1028R TTRTTNGGNARYTGNCCNCCCAT 50 N 9 CAD CAD_743nF GGNGTNACNACNGCNTGYTTYGARCC CAD_3R RTGYTCNGGRTGRAAYTG 50 N 10 DDC DDC3.2sF TGGYTICAYGTIGAYGCNGCNTAYGC  DDCdegR3 CCCATNGTNACYTCYTC 50 N 11,9 IDH IDHdeg27F GGWGAYGARATGACNAGRATHATHTGG IDHdegR TTYTTRCAIGCCCANACRAANCCNCC 55 N 9  References (Ref.) are 1: Hebert et al. 2004; 2: Simon et al. 1994; 3: Yamamoto and Sota 2007; 4: Wiegmann et al. 2000; 5: Saux et al. 2004; 6: Reed and Sperling 1999; 7: Kawakita et al. 2004; 8: Brower and DeSalle, 1998; 9: Wahlberg and Wheat 2008; 10: Regier 2008; and 11: Fang et al. 1997.   290 Appendix G: Supplementary table for Chapter 7. Species list and incidence data for inventory of nocturnal Lepidoptera conducted in 2007 in Stanley Park, Vancouver, Canada.  The number of individuals is not a measure of abundance since no more than 5 individuals per morphospecies were collected and analyzed.  Species denoted by B were identified using BOLD; those denoted by M were recognized through morphological comparisons of adults; and those denoted by G required genitalic dissections for identification.   Taxon (no. of species)  Individuals Identification Notes  Lepidoptera (190)  925  Arctiidae (5)  20 Clemensia albata Packard, 1864 1 B Lophocampa argentata (Packard, 1864) 2 B Lophocampa maculata Harris, 1841 11 B Lophocampa roseate (Walker, 1866) 3 M Spilosoma virginica (Fabricius, 1798) 3 B  Bucculatricidae (2)  4 Bucculatrix ainsliella Murtfeldt, 1905 2 B Bucculatrix canadensisella Chambers, 1875 2 B  Coleophoridae (7)  15 Asaphocrita aphidiella (Walsingham, 1907) 1 B Coleophora pruniella Clemens, 1861 1 B Coleophora serratella (Linnaeus, 1761) 2 M introduced Coleophora trifolii (Curtis, 1832) 1 B introduced Holcocera chalcofrontella Clemens, 1863 2 M Holcocera immaculella McDunnough, 1930 2 B Hypatopa simplicella (Dietz, 1910) 6 B  Cosmopterigidae (1)  1 Sorhagenia nimbosa (Braun, 1915) 1 B  Crambidae (12)  52 Agriphila straminella ([Denis & Schiffermüller], 1775) 2 M introduced Catoptria oregonicus (Grote, 1880) 1 B Chrysoteuchia topiarius (Zeller, 1866) 2 B introduced Eudonia JFL01  2 M+G Eudonia JFL02  1 M+G Eudonia echo (Dyar, 1929)                                       6 M+G  291 Taxon (no. of species)  Individuals Identification Notes  Eudonia rectilinea (Zeller, 1874)                                     3 B Eudonia spenceri Munroe, 1972 3 M+G Gesneria centuriella ([Denis & Schiffermüller], 1775) 5 B Herpetogramma thestealis (Walker, 1859) 15 G Scoparia biplagialis Walker, 1866 11 B Udea profundalis (Packard, 1873) 1 B  Drepanidae (1)  1 Drepana bilineata (Packard, 1864) 1 B  Gelechiidae (10)  51 Agnippe prunifoliella (Chambers, 1873) 2 B Bryotropha similis (Stainton, 1854) 1 B Chionodes abella (Busck, 1903) 10 G Chionodes lictor Hodges, 1999 7 M Chionodes mediofuscella (Clemens, 1863) 3 B Chionodes periculella (Busck, 1910) 7 G Coleotechnites atrupictella (Dietz, 1900) 3 G Coleotechnites nr. coniferella  1 G Coleotechnites piceaella (Kearfott, 1903) 8 B Recurvaria nanella ([Denis & Schiffermüller], 1775) 9 B introduced  Geometridae (47)  338 Campaea perlata (Guenée, [1858]) 3 B Caripeta aequaliaria Grote, 1883 1 B Caripeta divisata Walker, [1863] 11 B Ceratodalia gueneata Packard, 1876 9 B Cyclophora pendulinaria (Guenée, [1858]) 1 B Dysstroma citrata (Linnaeus, 1761) 21 G Ectropis crepuscularia ([Denis & Sch.], 1775) 5 B Enypia packardata Taylor, 1906                                       19 B Enypia venata (Grote, 1883)                                      7 B Epirrhoe alternata (Müller, 1764)                                     1 M Eulithis destinata (Möschler, 1860) 1 B Euphyia intermediata (Guenée, [1858]) 3 B Eupithecia bryanti Taylor, 1906 1 B Eupithecia columbiata (Dyar, 1904) 1 B Eupithecia graefii (Hulst, 1896) 3 B Eupithecia lariciata (Freyer, 1841) 1 B Eupithecia longipalpata Packard, 1876 19 G Eupithecia maestosa (Hulst, 1896) 2 B Eupithecia misturata (Hulst, 1896) 18 B Eupithecia rotundopuncta Packard, 1871 2 G  292 Taxon (no. of species)  Individuals Identification Notes  Eupithecia sharronata Bolte, 1990 1 B Eupithecia subfuscata (Haworth, 1809) 7 B Eupithecia unicolor (Hulst, 1896) 6 G Eustroma semiatrata (Hulst, 1881) 1 B Gabriola dyari Taylor, 1904 20 B Hemithea aestivaria (Hübner, [1799]) 12 B introduced Hydriomena californiata (Packard, 1871) 4 G Hydriomena marinata Barnes & McDunnough, 1917 19 B Hydriomena renunciata (Walker, 1862) 8 G Idaea dimidiata (Hufnagel, 1767) 3 B Iridopsis larvaria (Guenée, [1858]) 24 B Macaria lorquinaria (Guenée, [1858]) 1 B Macaria signaria complex  31 G Melanolophia imitata (Walker, 1860) 8 B Neoalcis californiaria (Packard, 1871) 7 B Pasiphila rectangulata (Linnaeus, 1758) 7 B introduced Perizoma grandis (Hulst, 1896) 8 B Pero mizon Rindge, 1955 1 B Pero morrisonaria (Hy. Edwards, 1881) 8 B Plagodis phlogosaria (Guenée, [1858]) 1 B Protitame virginalis (Hulst, 1900) 1 B Rheumaptera undulata (Linnaeus, 1758) 1 B Selenia alciphearia Walker, 1860 1 B Spargania magnoliata Guenée, [1858] 1 B Stamnoctenis pearsalli (Swett, 1914) 14 B Venusia cambrica Curtis, 1839 11 B Xanthorhoe defensaria (Guenée, [1858]) 3 B  Gracillariidae (2)  2 Caloptilia alnicolella (Chambers, 1875) 1 G Marmara arbutiella Busck, 1903 1 M  Lasiocampidae (1)  1 Phyllodesma americana (Harris, 1841) 1 B  Noctuidae (33)  102 Acronicta dactylina Grote, 1874 3 B Adelphagrotis stellaris (Grote, 1880) 1 M Agrotis ipsilon (Hufnagel, 1766) 3 B seasonal migrant Anaplectoides prasina ([Denis & Sch.], 1775) 2 B Apamea amputatrix (Fitch, 1857) 8 B Apamea cogitata (J. B. Smith, 1891) 1 B Aseptis adnixa (Grote, 1880) 5 B  293 Taxon (no. of species)  Individuals Identification Notes  Aseptis binotata (Walker, 1865) 1 M Autographa californica (Speyer, 1875) 2 B Autographa corusca (Strecker, 1885) 2 B Caradrina morpheus (Hufnagel, 1766) 1 B Cosmia praeacuta (J. B. Smith, 1894) 2 M Dargida procinctus (Grote, 1873) 10 B Diarsia esurialis (Grote, 1881) 2 M Euplexia benesimilis McDunnough, 1922 1 B Hypena abalienalis Walker, 1859 3 B Hypena bijugalis Walker, 1859 1 B Hypena humuli Harris, 1841 1 B Hypena palparia (Walker, 1861) 1 B Lacinipolia patalis (Grote, 1873) 1 B Lithacodia albidula (Guenée, 1852) 1 B Mamestra configurata Walker, 1856 1 M Mythimna unipuncta (Haworth, 1809) 1 B seasonal migrant  Noctua pronuba (Linnaeus, 1758) 27 B introduced Nycteola cinereana Neumoegen & Dyar, 1893 2 B Nycteola sp. nr. cinereana  1 G Oligia indirecta (Grote, 1875) 1 B Pseudorthodes irrorata (J. B. Smith, 1888) 8 M Scoliopteryx libatrix (Linnaeus, 1758) 2 B Syngrapha celsa (Hy. Edwards, 1881) 2 B Syngrapha rectangula (Wm. Kirby, 1837) 2 M Zale minerea (Guenée, 1852) 2 B Zanclognatha lutalba (J. B. Smith, 1906) 1 M  Notodontidae (2)  7 Nadata gibbosa (J.E. Smith, 1797) 6 B Schizura ipomoeae Doubleday, 1841 1 B  Oecophoridae (5)  31 Batia lunaris (Haworth, 1828) 19 B introduced Brymblia quadrimaculella (Chambers, 1875) 3 G Carcina quercana (Fabricius, 1775) 8 B introduced Hofmannophila pseudospretella (Stainton, 1849) 2 B introduced Polix coloradella (Walsingham, 1888) 1 B  Plutellidae (2)  2 Plutella porrectella (Linnaeus, 1758) 1 B introduced Plutella xylostella (Linnaeus, 1758) 1 B seasonal migrant Pterophoridae (2)  3  294 Taxon (no. of species)  Individuals Identification Notes  Emmelina monodactyla (Linnaeus, 1758) 2 G introduced Hellinsia pectodactylus (Staudinger, 1859) 1 B introduced  Pyralidae (8)  46 Dasypyga alternosquamella Ragonot, 1887 10 G Dioryctria pseudotsugella Munroe, 1959 10 B Dioryctria reniculelloides Mutuura & Munroe, 1973 3 B Ephestiodes gilvescentella Ragonot, 1887 1 B Oreana unicolorella (Hulst, 1887) 3 B Phycitodes reliquellus (Dyar, 1904) 2 B Promylea lunigerella Ragonot, 1887 8 G Vitula serratilineella Ragonot, 1887 9 G  Thyatiridae (2)  31 Habrosyne scripta (Gosse, 1840) 21 B Pseudothyatira cymatophoroides (Guenée, 1852) 10 B  Tineidae (1)  2 Homosetia n. sp. nr. costisignella  2 G  Tischeriidae (1)  1 Coptotriche malifoliella (Clemens, 1860) 1 B  Tortricidae (37)  189 Acleris comariana (Zeller, 1846) 13 B introduced Acleris forsskaleana (Linnaeus, 1758) 5 B introduced Acleris holmiana (Linnaeus, 1758) 1 M introduced Acleris variegana ([Denis & Schiffermüller], 1775) 3 B introduced Aethes JFL01  2 G Apotomis JFL01  1 G Archips argyrospila (Walker, 1863) 1 B Argyrotaenia dorsalana (Dyar, 1903) 2 M Argyrotaenia provana (Kearfott, 1907) 13 G Choristoneura occidentalis T.N. Freeman, 1967                                 20 M Choristoneura rosaceana (Harris, 1841) 5 B Clepsis JFL01  1 M Clepsis virescana (Clemens, 1865) 4 M Dichelia histrionana (Frölich, 1828)  5 G introduced; 1st NA record Ditula angustiorana (Haworth, 1811) 14 B Epinotia JFL01  1 G Epinotia JFL02  3 G Epinotia JFL03  1 G Epinotia albangulana (Walsingham, 1879) 9 G  295 Taxon (no. of species)  Individuals Identification Notes  Epinotia cf. subviridis  1 M Epinotia hopkinsana (Kearfott, 1907)                                   3 G Epinotia solandriana (Linnaeus, 1758)                                   7 B Epinotia transmissana (Walker, 1863)                                     1 B Epinotia tsugana T.N. Freeman, 1967                                 6 G Eulia ministrana (Linnaeus, 1758)                                   5 B Grapholita packardi Zeller, 1875 1 B Hedya nubiferana (Haworth, 1811) 12 B introduced Olethreutes JFL01  1 G Olethreutes appendiceum (Zeller, 1875) 11 B Pandemis cerasana (Hübner, 1786) 7 M introduced Pandemis heparana ([Denis & Schiffermüller], 1775) 10 B introduced Proteoteras aesculana Riley, 1881 2 B Rhopobota naevana (Hübner, [1817]) 6 B introduced Spilonota ocellana ([Denis & Schiffermüller], 1775) 1 B introduced Taniva albolineana (Kearfott, 1907) 1 G Thaumatographa youngiella (Busck, 1922) 4 M Zeiraphera improbana (Walker, 1863) 6 G  Yponomeutidae (9)  24 Argyresthia JFL01  1 G Argyresthia conjugella Zeller, 1839 1 G Argyresthia goedartella (Linnaeus, 1758) 1 B Argyresthia pruniella (Clerck, 1759)  10 G introduced; 1st NA record Paraswammerdamia lutarea (Haworth, 1828) 1 G introduced; 1st NA record Prays fraxinella (Donovan, 1793)  1 M introduced; 1st BC record Swammerdamia caesiella (Hübner, 1796) 1 B introduced Swammerdamia pyrella (Villers, 1789) 1 B introduced Yponomeuta padella (Linnaeus, 1758) 7 M introduced       296 Appendix H: Supplementary figure for Chapter 8. Backbone phylogeny used for estimating phylogenetic diversity of moths collected at Date Creek and Sicamous Creek. Classification follows Powell and Opler (2009) and Lafontaine and Schmidt (2010).  Phylogenetic relationships are based on a variety of sources (Kristensen and Skalski 1999; Regier et al. 2009; Mutanen et al. 2010; Zahiri et al. in press; Chapter 4).     297 Appendix I: Supplementary table for Chapter 8. Inventory of moth species collected at the Date Creek Silvicutural System, near Hazelton, British Columbia in 2008 and 2009. Classification follows Powell and Opler (2009) and Lafontaine and Schmidt (2010).  Family Species  No. of individuals  Argyresthiidae (7)   141  Argyresthia conjugella Zeller, 1839 1  Argyresthia goedartella (Linnaeus, 1758) 2  Argyresthia oreasella Clemens, 1860 2  Argyresthia pygmaeella (Hübner, [1813]) 130  Argyresthia sp. 2  1  Argyresthia sp. 3  2  Argyresthia sp. 4  3 Blastobasidae (1)   4  Hypatopa binotella (Thunberg, 1794) 4 Coleophoridae (7)   28  Batrachedra praeangusta (Haworth, 1828) 12  Batrachedra striolata Zeller, 1875 1  Coleophora alnifoliae Barasch, 1934 11  Coleophora deauratella Lienig & Zeller, 1846 1  Coleophora glaucella Walsingham, 1882 1  Coleophora mayrella (Hübner, [1813]) 1  Coleophora sparsipulvella Chambers, 1875 1 Crambidae (17)   1312  Agriphila ruricolellus (Zeller, 1863) 5  Catoptria latiradiellus (Walker, 1863) 5  Catoptria oregonicus (Grote, 1880) 1  Crambus pascuella (Linnaeus, 1798) 1  Crambus perlella (Scopoli, 1763) 4  Eudonia sp. 1  31  Eudonia sp. 2  2  Eudonia sp. 3  430  Eudonia vivida Munroe, 1972                                       5  Gesneria centuriella ([Denis & Schiffermüller], 1775) 3  Pyrausta nicalis (Grote, 1878) 1  Scoparia biplagialis Walker, 1866 797  Udea sp. 4  2  Udea sp. 5  1  Udea sp. cf. itysalis  5  Udea sp. cf. saxifrage  18  Udea washingtonalis (Grote, 1882) 1  298 Family Species  No. of individuals  Depressariidae (1)   1  Agonopterix sp. nr. clemensella  1 Drepanidae (7)   95  Ceranemota albertae Clarke, 1938 13  Ceranemota fasciata (Barnes & McDunnough, 1910) 8  Drepana bilineata (Packard, 1864) 35  Euthyatira lorata (Grote, 1881) 8  Habrosyne scripta (Gosse, 1840) 10  Oreta rosea (Walker, 1855) 3  Pseudothyatira cymatophoroides (Guenée, 1852) 18 Elachistidae (1)   1  Elachista sp. JFL01  1 Erebidae (11)   151  Catocala semirelicta Grote, 1874 2  Clemensia albata Packard, 1864 36  Dasychira grisefacta (Dyar, 1911) 7  Eilema bicolor (Grote, 1864) 45  Hypenodes caducus (Dyar, 1907) 6  Hypenodes sombrus Ferguson, 1954 1  Idia aemula concisa  43  Idia americalis (Guenée, 1854) 6  Leucoma salicis (Linnaeus, 1758) 3  Mycterophora inexplicata (Walker, [1863]) 1  Orgyia antiqua (Linnaeus, 1758) 1 Gelechiidae (24)   138  Agnippe prunifoliella (Chambers, 1873) 1  Anacampsis innocuella (Zeller, 1873) 2  Aristotelia fungivorella (Clemens, 1864) 1  Bryotropha gemella Rutten & Karsholt, 2004 4  Bryotropha plantariella Tengström 1848 1  Bryotropha similis (Stainton, 1854) 19  Carpatolechia proximella (Hübner, 1796) 34  Caryocolum sp. nr. pullatella  1  Chionodes continuella (Zeller, 1839) 1  Chionodes fictor Hodges, 1999 2  Chionodes sp. JFL01  22  Coleotechnites atrupictella (Dietz, 1900) 7  Coleotechnites blastovora (McLeod, 1962) 9  Coleotechnites florae (T.N. Freeman, 1960)                               3  Coleotechnites sp. 2  1  Coleotechnites sp. 3  2  Coleotechnites sp. 4  1  Coleotechnites sp. nr. blastovora 6  299 Family Species  No. of individuals   Coleotechnites sp. nr. piceaella  1  Coleotechnites starki (T.N. Freeman, 1957)                               13  Gelechia dromicella Busck, 1910 1  Gelechia sp.  1  Scrobipalpa atriplicella Fischer von Röslerstamm 1839 1  Scrobipalpa sp. nr. atriplicella  4 Geometridae (82)   2411  Acasis viridata (Packard, 1873) 1  Anticlea multiferata (Walker, 1863) 6  Anticlea vasiliata Guenée, [1858] 7  Besma quercivoraria (Guenée, [1858]) 2  Biston betularia (Linnaeus, 1758) 15  Cabera exanthemata (Scopoli, 1763) 5  Campaea perlata (Guenée, [1858]) 97  Caripeta angustiorata Walker, [1863] 5  Caripeta divisata Walker, [1863] 22  Ceratodalia gueneata Packard, 1876 28  Cladara atroliturata (Walker, [1863]) 1  Cladara limitaria (Walker, 1860) 3  Cyclophora pendulinaria (Guenée, [1858]) 13  Dysstroma citrata (Linnaeus, 1761) 21  Dysstroma hersiliata (Guenée, [1858]) 4  Dysstroma truncata (Hufnagel, 1767) 126  Dysstroma walkerata (Pearsall, 1909) 7  Ecliptopera silaceata ([Denis & Schiffermüller], 1775) 41  Ectropis crepuscularia ([Denis & Schiffermüller], 1775) 14  Enypia griseata Grossbeck, 1908 4  Enypia packardata Taylor, 1906                                       51  Enypia venata (Grote, 1883)                                      7  Epirrita autumnata (Borkhausen, 1794)                                 45  Eulithis destinata (Möschler, 1860) 18  Eulithis propulsata (Walker, 1862)                                     12  Eulithis testata (Linnaeus, 1761)                                   1  Eulithis xylina (Hulst, 1896)                                      70  Eupithecia absinthiata (Clerck, 1759) 2  Eupithecia albicapitata Packard, 1876 7  Eupithecia assimilata Doubleday, 1856 1  Eupithecia graefii (Hulst, 1896) 6  Eupithecia intricata (Zetterstedt, [1839]) 6  Eupithecia lariciata (Freyer, 1841) 1  Eupithecia palpata Packard, 1873 2  Eupithecia perfusca (Hulst, 1898) 1  Eupithecia satyrata (Hübner, [1813]) 8  300 Family Species  No. of individuals   Eupithecia sharronata Bolte, 1990 1  Eupithecia sp.  1  Eupithecia tripunctaria Herrich-Schäffer, 1852 2  Eustroma fasciata Barnes & McDunnough, 1918 3  Eustroma semiatrata (Hulst, 1881) 8  Gabriola dyari Taylor, 1904 137  Hydriomena divisaria (Walker, 1860) 1  Hydriomena furcata (Thunberg, 1784) 441  Hydriomena irata Swett, 1910 3  Hydriomena renunciata (Walker, 1862) 22  Hydriomena ruberata (Freyer, [1831]) 4  Iridopsis larvaria (Guenée, [1858]) 2  Lambdina fiscellaria (Guenée, [1858]) 109  Lampropteryx suffumata ([Denis & Sch.], 1775) 1  Lobophora nivigerata Walker, 1862 5  Macaria exauspicata Walker, 1861 33  Macaria loricaria (Eversmann, 1837) 1  Macaria signaria (Hübner, [1809]) 26  Macaria submarmorata Walker, 1861 3  Macaria ulsterata (Pearsall, 1913) 1  Melanolophia imitata (Walker, 1860) 20  Mesoleuca ruficillata (Guenée, [1858]) 1  Metanema determinata Walker, 1866 1  Metanema inatomaria Guenée, [1858] 2  Perizoma grandis (Hulst, 1896) 196  Pero morrisonaria (Hy. Edwards, 1881) 1  Plagodis phlogosaria (Guenée, [1858]) 1  Plagodis pulveraria (Linnaeus, 1758) 16  Plemyria georgii Hulst, 1896 29  Probole amicaria (Herrich-Schäffer, [1855]) 1  Protoboarmia porcelaria (Guenée, [1858]) 13  Rheumaptera undulata (Linnaeus, 1758) 15  Scopula frigidaria (Möschler, 1860) 2  Selenia alciphearia Walker, 1860 5  Sicya macularia (Harris, 1850) 175  Spargania magnoliata Guenée, [1858] 8  Stenoporpia pulmonaria (Grote, 1881) 4  Synaxis jubararia (Hulst, 1886) 116  Venusia cambrica Curtis, 1839 294  Venusia pearsalli (Dyar, 1906) 4  Xanthorhoe abrasaria (Herrich-Schäffer, [1855]) 17  Xanthorhoe decoloraria (Esper, [1806]) 4  Xanthorhoe ferrugata (Clerck, 1759) 8  301 Family Species  No. of individuals   Xanthorhoe iduata (Guenée, [1858]) 12  Zenophleps alpinata Cassino, 1927 2 Gracillariidae (9)   10  Acrocercops astericola (Frey & Boll, 1873) 1  Caloptilia alnivorella (Chambers, 1875) 1  Caloptilia sp. nr. strictella  1  Cameraria agrifoliella (Braun, 1908) 1  Parectopa sp. JFL01  1  Parornix sp. DRD30  2  Phyllonorycter sp. 2  1  Phyllonorycter sp. 3  1  Protolithocolletis lathyri Braun, 1929 1 Lasiocampidae (1)   28  Phyllodesma americana (Harris, 1841) 28 Lyonetiidae (1)   9  Lyonetia saliciella Busck, 1904 9 Momphidae (1)   14  Mompha conturbatella (Hübner, [1819]) 14 Noctuidae (68)   1538  Abagrotis placida (Grote, 1876) 2  Acronicta fragilis (Guenée, 1852) 8  Actebia fennica (Tauscher, 1806) 1  Agrochola sp. nr. pulchella  3  Anaplectoides prasina ([Denis & Schiffermüller], 1775) 55  Anaplectoides pressus (Grote, 1874) 41  Apamea cogitata (J. B. Smith, 1891) 20  Apamea indocilis (Walker, 1856) 1  Autographa ampla (Walker, [1858]) 22  Autographa corusca (Strecker, 1885) 3  Autographa mappa (Grote & Robinson, 1868) 2  Autographa sansoni Dod, 1910 2  Celaena reniformis (Grote, 1874) 1  Coenophila opacifrons (Grote, 1878) 2  Cosmia elisae Lafontaine & Troubridge, 2003 4  Cryptocala acadiensis (Bethune, 1870) 12  Cucullia intermedia Speyer, 1870 1  Diarsia calgary (J. B. Smith, 1898) 8  Diarsia dislocata (J. B. Smith, 1904) 419  Diarsia esurialis (Grote, 1881) 172  Diarsia freemani Hardwick, 1950 24  Diarsia rubifera (Grote, 1875) 26  Enargia decolor (Walker, 1858)                                     18  Eremobina claudens (Walker, 1857) 1  302 Family Species  No. of individuals   Eueretagrotis perattentus (Grote, 1876) 4  Euplexia benesimilis McDunnough, 1922 3  Eurois astricta Morrison, 1874 70  Eurois occulta (Linnaeus, 1758) 99  Graphiphora augur (Fabricius, 1775) 92  Hyppa contrasta McDunnough, 1946 3  Ipimorpha nanaimo Barnes, 1905 3  Lacinipolia comis (Grote, 1876) 15  Lithomoia germana (Morrison, 1875) 33  Mythimna oxygala (Grote, 1881) 1  Ochropleura implecta Lafontaine, 1998 4  Oligia illocata (Walker, 1857) 5  Oligia mactata (Guenée, 1852) 1  Orthosia hibisci (Guenée, 1852) 1  Panthea acronyctoides (Walker, 1861) 4  Panthea virginarius (Grote, 1880) 9  Parastichtis suspecta (Hübner, [1817]) 1  Phlogophora periculosa Guenée, 1852 44  Platypolia anceps (Stephens, 1850) 3  Plusia nichollae (Hampson, 1913) 1  Polia detracta (Walker, 1857) 1  Polia nimbosa (Guenée, 1852) 18  Polia purpurissata (Grote, 1864) 1  Protolampra rufipectus (Morrison, 1875) 8  Pseudorthodes irrorata (J. B. Smith, 1888) 3  Pyrrhia exprimens (Walker, 1857) 1  Sunira verberata (J. B. Smith, 1904) 7  Sympistis anweileri Troubridge & Lafontaine, 2008 1  Syngrapha alias (Ottolengui, 1902) 14  Syngrapha celsa (Hy. Edwards, 1881) 4  Syngrapha epigaea (Grote, 1875) 1  Syngrapha interrogationis (Linnaeus, 1758) 1  Syngrapha octoscripta (Grote, 1874) 1  Syngrapha selecta (Walker, [1858]) 1  Syngrapha viridisigma (Grote, 1874) 25  Xanthia tatago Lafontaine & Mikkola, 2003 1  Xestia fabulosa (Ferguson, 1965) 7  Xestia homogena (McDunnough, 1921) 1  Xestia mustelina (J. B. Smith, 1900) 19  Xestia oblata (Morrison, 1875) 1  Xestia perquiritata (Morrison, 1874) 4  Xestia smithii (Snellen, 1896) 118  Xestia speciosa (Hübner, [1813]) 55  303 Family Species  No. of individuals   Xylotype arcadia Barnes & Benjamin, 1922 1 Notodontidae (9)   102  Clostera albosigma Fitch, 1856 16  Clostera apicalis (Walker, 1855) 2  Clostera brucei (Hy. Edwards, 1885) 1  Furcula scolopendrina (Boisduval, 1869) 10  Gluphisia septentrionis Walker, 1855 9  Nadata gibbosa (J.E. Smith, 1797) 10  Notodonta simplaria Graef, 1881 13  Oligocentria pallida (Strecker, 1899) 4  Pheosia portlandia Hy. Edwards, 1886 37 Oecophoridae (3)   4  Denisia haydenella (Chambers, 1877) 1  Eido trimaculella (Fitch, 1856) 1  Polix coloradella (Walsingham, 1888) 2 Phyllocnistidae (2)   1184  Phyllocnistis populiella Chambers, 1875 1183  Phyllocnistis sp. nr. populiella  1 Plutellidae (1)   2  Plutella vanella Walsingham, 1881 2 Pterophoridae (3)   17  Adaina sp.  2  Hellinsia sp.  1  Oxyptilus delawaricus Zeller, 1873 14 Pyralidae (6)   51  Apomyelois sp.  1  Dioryctria reniculelloides Mutuura & Munroe, 1973 19  Meroptera pravella (Grote, 1878) 1  Pyla aequivoca Heinrich, 1956 2  Pyla fusca (Haworth, 1828) 10  Vitula broweri (Heinrich, 1956) 18 Scythrididae (1)   5  Scythris noricella (Zeller, 1843) 5 Sphingidae (2)   55  Smerinthus cerisyi Wm. Kirby, 1837 44  Smerinthus jamaicensis (Drury, 1773) 11 Tineidae (7)   14  Homosetia sp.  1  Hypoplesia sp.  2  Monopis spilotella Tengström, 1848 6  Morophagoides burkerella (Busck, 1904) 1  Nemapogon sp. DRD045  2  Nemapogon tylodes (Meyrick, 1919) 1  304 Family Species  No. of individuals   Niditinea orleansella (Chambers, 1873) 1 Tortricidae (60)   565  Acleris albicomana  84  Acleris britannia Kearfott, 1904 10  Acleris caliginosana (Walker, 1863) 1  Acleris sp. cf. emargana  14  Acleris curvalana (Kearfott, 1907) 11  Acleris robinsoniana (W.T.M Forbes, 1923)                              1  Acleris variana (C.H. Fernald, 1886)                               7  Ancylis sp. nr. myrtillana  1  Ancylis sp. nr. subaequana  1  Ancylis tineana (Hübner, [1799]) 1  Apotomis bifida (McDunnough, 1938) 1  Apotomis capreana (Hübner, [1817]) 13  Apotomis funerea (Meyrick, 1920) 9  Apotomis removana (Kearfott, 1907) 13  Apotomis sp. nr. spinulana  2  Archips dissitana (Grote, 1879) 6  Archips packardiana (C.H. Fernald, 1886) 5  Archips strianus (C.H. Fernald, 1905) 1  Choristoneura conflictana (Walker, 1863) 3  Choristoneura occidentalis group  121  Clepsis persicana (Fitch, 1856) 9  Clepsis virescana (Clemens, 1865) 28  Eana argentana (Clerck, 1759) 2  Eana osseana (Scopoli, 1763) 1  Endothenia hebesana (Walker, 1863)                                     7  Epiblema sp.  1  Epinotia castaneana (Walsingham, 1895)                                 1  Epinotia indecorana (Zetterstedt, 1839)                                1  Epinotia lindana (C.H. Fernald, 1892)                               10  Epinotia momonana (Kearfott, 1907)                                   3  Epinotia nisella (Clerck, 1759)                                     9  Epinotia plumbolineana Kearfott, 1907                                     25  Epinotia rectiplicana (Walsingham, 1879)                                 10  Epinotia signiferana Heinrich, 1923 1  Epinotia solandriana (Linnaeus, 1758)                                   2  Epinotia sp. 1  1  Epinotia sp. 4  1  Epinotia sp. 5  1  Epinotia sp. 6  1  Epinotia sp. 7  1  Epinotia transmissana (Walker, 1863) 3  305 Family Species  No. of individuals   Epinotia trigonella (Linnaeus, 1758)                                   5  Gypsonoma sp. cf. salicicolana  2  Hedya ochroleucana (Frölich, 1828) 1  Hedya sp. nr. ochroleucana  2  Notocelia culminana (Walsingham, 1879) 7  Olethreutes castorana (McDunnough, 1922) 18  Olethreutes deprecatoria Heinrich, 1926 6  Olethreutes sp. 1  4  Olethreutes sp. 2  4  Olethreutes sp. nr. minaki  3  Pandemis limitata (Robinson, 1869) 16  Petrova burkeana (Kearfott, 1907) 1  Phaneta infimbriana (Dyar, 1904) 5  Phaneta sp. 5  4  Rhopobota naevana (Hübner, [1817]) 13  Taniva albolineana (Kearfott, 1907) 1  Zeiraphera canadensis Mutuura & Freeman, 1967                       37  Zeiraphera sp. cf. pacifica  2  Zeiraphera fortunana (Kearfott, 1907) 11 Uraniidae (1)   96  Callizzia amorata Packard, 1876 96 Yponomeutidae (1)   2  Swammerdamia caesiella (Hübner, 1796) 2  Total (333)  7978   306 Appendix J: Supplementary table for Chapter 8. Inventory of moth species collected at the Sicamous Creek Silvicutural System, near Sicamous, British Columbia in 2008 and 2009. Classification follows Powell and Opler (2009) and Lafontaine and Schmidt (2010).   Family Species  No. of individuals  Argyresthiidae (2)   3  Argyresthia pygmaeella (Hübner, [1813]) 2  Argyresthia sp. 5  1 Coleophoridae (1)   2  Coleophora klimeschiella Toll, 1952 2 Cosmopterigidae (1)   1  Walshia miscecolorella (Chambers, 1875) 1 Crambidae (14)   103  Agriphila plumbifimbriellus (Dyar, 1904) 2  Agriphila ruricolellus (Zeller, 1863) 1  Catoptria oregonicus (Grote, 1880) 1  Crambus perlella (Scopoli, 1763) 4  Eudonia alpina (Curtis, 1850) 1  Eudonia sp. 4  9  Gesneria centuriella ([Denis & Schiffermüller], 1775) 24  Gesneria sp.  6  Pediasia trisecta (Walker, 1856) 1  Scoparia basalis Walker, 1866 1  Scoparia biplagialis Walker, 1866 4  Udea sp. 5  18  Udea sp. cf. saxifrage  5  Udea washingtonalis (Grote, 1882) 26 Depressariidae (1)   4  Depressariodes nivalis (Braun, 1921) 4 Drepanidae (2)   8  Ceranemota fasciata (Barnes & McDunnough, 1910) 5  Habrosyne scripta (Gosse, 1840) 3 Erebidae (5)   11  Dasychira grisefacta (Dyar, 1911) 1  Hypena humuli Harris, 1841 1  Idia aemula concisa  6  Neoarctia beanii (Neumoegen, 1891) 1  Platarctia parthenos (Harris, 1850) 2 Gelechiidae (4)   74  Aristotelia rubidella (Clemens, 1860) 2  307 Family Species  No. of individuals   Bryotropha similis (Stainton, 1854) 2  Scrobipalpa sp. 3  66  Syncopacma sp.  4 Geometridae (57)   1418  Anticlea multiferata (Walker, 1863) 1  Aplocera plagiata (Linnaeus, 1758) 1  Ceratodalia gueneata Packard, 1876 2  Cyclophora pendulinaria (Guenée, [1858]) 4  Dysstroma hersiliata (Guenée, [1858]) 9  Dysstroma truncata (Hufnagel, 1767) 55  Dysstroma walkerata (Pearsall, 1909) 28  Ecliptopera silaceata ([Denis & Schiffermüller], 1775) 21  Entephria multivagata (Hulst, 1881)                                      1  Enypia packardata Taylor, 1906                                       1  Enypia venata (Grote, 1883)                                      39  Eulithis destinata (Möschler, 1860) 381  Eulithis propulsata (Walker, 1862)                                     30  Eupithecia absinthiata (Clerck, 1759) 1  Eupithecia bryanti Taylor, 1906 3  Eupithecia cretaceata (Packard, 1874) 257  Eupithecia gelidata Möschler, 1860 2  Eupithecia graefii (Hulst, 1896) 63  Eupithecia lachrymosa (Hulst, 1900) 5  Eupithecia lariciata (Freyer, 1841) 1  Eupithecia misturata (Hulst, 1896) 3  Eupithecia nimbicolor (Hulst, 1896) 7  Eupithecia perfusca (Hulst, 1898) 1  Eupithecia satyrata (Hübner, [1813]) 34  Eupithecia sharronata Bolte, 1990 34  Eupithecia tripunctaria Herrich-Schäffer, 1852 1  Eustroma fasciata Barnes & McDunnough, 1918 11  Eustroma semiatrata (Hulst, 1881) 18  Hydriomena californiata (Packard, 1871) 2  Hydriomena exculpata Barnes & McDunnough, 1917 31  Hydriomena furcata (Thunberg, 1784) 10  Hydriomena renunciata (Walker, 1862) 4  Idaea dimidiata (Hufnagel, 1767) 1  Iridopsis larvaria (Guenée, [1858]) 1  Lobophora nivigerata Walker, 1862 1  Macaria bitactata (Walker, 1862) 1  Macaria decorata (Hulst, 1896) 10  Macaria lorquinaria (Guenée, [1858]) 1  Macaria quadrilinearia (Packard, 1873) 1  308 Family Species  No. of individuals   Macaria signaria (Hübner, [1809]) 4  Perizoma grandis (Hulst, 1896) 10  Pero mizon Rindge, 1955 1  Selenia alciphearia Walker, 1860 25  Sicya macularia (Harris, 1850) 1  Spargania luctuata ([Denis & Schiffermüller], 1775) 171  Spargania magnoliata Guenée, [1858] 65  Thallophaga hyperborea (Hulst, 1900) 1  Thera otisi (Dyar, 1904) 2  Triphosa haesitata (Guenée, [1858]) 1  Venusia cambrica Curtis, 1839 3  Xanthorhoe abrasaria (Herrich-Schäffer, [1855]) 2  Xanthorhoe alticolata Barnes & McDunnough, 1916 17  Xanthorhoe ferrugata (Clerck, 1759) 1  Xanthorhoe fossaria Taylor, 1906 19  Xanthorhoe incursata lagganata (Hübner, [1813]) 9  Xanthorhoe macdunnoughi Swett, 1918 4  Xanthorhoe ramaria Swett & Cassino, 1920 5 Gracillariidae (2)   3  Acrocercops astericola (Frey & Boll, 1873) 1  Caloptilia strictella (Walker, 1864) 2 Lasiocampidae (2)   8  Malacosoma californica (Packard, 1864) 2  Phyllodesma americana (Harris, 1841) 6 Lyonetiidae (1)   8  Lyonetia prunifoliella (Hübner, 1796) 8 Momphidae (3)   6  Mompha conturbatella (Hübner, [1819]) 1  Mompha sexstrigella (Braun, 1921) 2  Mompha sp.  3 Noctuidae (64)   785  Abagrotis scopeops (Dyar, 1904) 1  Agrotis antica Crabo & Lafontaine, 2004 1  Amphipyra tragopoginis (Clerck, 1759) 2  Anaplectoides prasina ([Denis & Schiffermüller], 1775) 6  Anaplectoides pressus (Grote, 1874) 3  Anarta oregonica (Grote, 1881) 2  Apamea cogitata (J. B. Smith, 1891) 33  Apamea devastator (Brace, 1819) 6  Apamea maxima (Dyar, 1904) 2  Autographa corusca (Strecker, 1885) 1  Autographa metallica (Grote, 1875) 2  Autographa sansoni Dod, 1910 9  309 Family Species  No. of individuals   Caradrina morpheus (Hufnagel, 1766) 2  Cosmia elisae Lafontaine & Troubridge, 2003 1  Dargida procinctus (Grote, 1873) 1  Diarsia esurialis (Grote, 1881) 1  Diarsia freemani Hardwick, 1950 17  Eremobina claudens (Walker, 1857)                                     3  Eurois astricta Morrison, 1874 43  Eurois occulta (Linnaeus, 1758) 28  Euxoa altens McDunnough, 1946 1  Euxoa declarata (Walker, 1865) 1  Euxoa divergens (Walker, [1857]) 6  Euxoa intrita (Morrison, 1874) 1  Euxoa lewisi (Grote, 1873) 1  Euxoa messoria (Harris, 1841) 1  Euxoa satis (Harvey, 1876) 1  Euxoa terrenus (J. B. Smith, 1900) 1  Graphiphora augur (Fabricius, 1775) 3  Hada sutrina (Grote, 1881) 8  Hadena ectrapela (J. B. Smith, 1898) 1  Hyppa contrasta McDunnough, 1946 7  Hyppa indistincta J. B. Smith, 1894 9  Lacinipolia comis (Grote, 1876) 3  Lacinipolia olivacea (Morrison, 1874) 1  Lasionycta fergusoni Crabo & Lafontaine, 2009 2  Lasionycta mutilata (J. B. Smith, 1898) 126  Litholomia napaea (Morrison, 1874) 1  Melanchra pulverulenta (J. B. Smith, 1888) 8  Mniotype tenera (J. B. Smith, 1900) 1  Mythimna oxygala (Grote, 1881) 5  Neoligia subjuncta (J. B. Smith, 1898) 1  Ochropleura implecta Lafontaine, 1998 1  Papestra quadrata (J. B. Smith, 1891) 17  Parabagrotis sulinaris Lafontaine, 1998 3  Peridroma saucia (Hübner, [1808]) 1  Phlogophora periculosa Guenée, 1852 2  Polia piniae Buckett & Bauer, 1967 7  Polia propodea McCabe, 1980 9  Protolampra rufipectus (Morrison, 1875) 1  Proxenus miranda (Grote, 1873) 3  Pseudohermonassa flavotincta (J. B. Smith, 1892) 21  Syngrapha alias (Ottolengui, 1902) 4  Syngrapha angulidens (J. B. Smith, 1891) 46  Syngrapha celsa (Hy. Edwards, 1881) 4  310 Family Species  No. of individuals   Syngrapha octoscripta (Grote, 1874) 2  Syngrapha orophila (Hampson, 1908) 4  Syngrapha viridisigma (Grote, 1874) 1  Xestia fabulosa (Ferguson, 1965) 35  Xestia homogena (McDunnough, 1921) 106  Xestia oblata (Morrison, 1875) 3  Xestia perquiritata (Morrison, 1874) 56  Xestia smithii (Snellen, 1896) 5  Xestia speciosa (Hübner, [1813]) 101 Nolidae (1)   1  Nycteola cinereana Neumoegen & Dyar, 1893 1 Notodontidae (2)   2  Nadata gibbosa (J.E. Smith, 1797) 1  Pheosia portlandia Hy. Edwards, 1886 1 Oecophoridae (2)   2  Denisia haydenella (Chambers, 1877) 1  Polix coloradella (Walsingham, 1888) 1 Phyllocnistidae (2)   15  Phyllocnistis populiella Chambers, 1875 14  Phyllocnistis sp. nr. populiella  1 Plutellidae (1)   1  Plutella xylostella (Linnaeus, 1758) 1 Pterophoridae (5)   16  Adaina sp.  5  Hellinsia pectodactylus (Staudinger, 1859) 1  Platyptilia carduidactyla (Riley, 1869) 1  Platyptilia sp. 1  1  Platyptilia sp. nr. tesseradactyla  8 Pyralidae (6)   31  Dioryctria pseudotsugella Munroe, 1959 1  Dioryctria reniculelloides Mutuura & Munroe, 1973 26  Ephestia sp.  1  Ephestiodes gilvescentella Ragonot, 1887 1  Homoeosoma electella (Hulst, 1887) 1  Pyla aequivoca Heinrich, 1956 1 Scythrididae (1)   34  Scythris noricella (Zeller, 1843) 34 Sphingidae (1)   1  Hyles gallii (Rottemburg, 1775) 1 Tortricidae (26)   389  Acleris britannia Kearfott, 1904 3  Acleris gloveranus (Walsingham, 1879) 1  Agapeta zoegana (Linnaeus, 1767) 1  311 Family Species  No. of individuals   Ancylis sp. nr. myrtillana  3  Archips cerasivorana (Fitch, 1856) 1  Archips grisea (Robinson, 1869) 1  Choristoneura occidentalis group  176  Dichrorampha simulana (Clemens, 1860) 1  Eana argentana (Clerck, 1759) 36  Eana niveosana (Packard, 1866) 14  Eana osseana (Scopoli, 1763) 91  Epinotia castaneana (Walsingham, 1895)                                 1  Epinotia plumbolineana Kearfott, 1907                                     6  Eucosma smithiana (Walsingham, 1895)                                 1  Hystrichophora asphodelana (Kearfott, 1907) 1  Lozotaenia rindgei Obraztsov, 1962 3  Notocelia sp. nr. culminana  2  Olethreutes castorana McDunnough, 1922 1  Olethreutes electrofuscum (Heinrich, 1923) 1  Petrova burkeana (Kearfott, 1907) 2  Phaneta corculana (Zeller, 1874) 1  Phaneta elongana (Walsingham, 1879) 11  Phtheochroa sp. 1  5  Taniva albolineana (Kearfott, 1907) 1  Zeiraphera fortunana (Kearfott, 1907) 19  Zeiraphera improbana (Walker, 1863) 6  Total (206)  2926   312 Appendix K: Supplementary figure for Chapter 9. Backbone phylogeny used for estimating phylogenetic diversity of moths collected in ponderosa pine forests in Kamloops and South Okanagan. Classification follows Powell and Opler (2009) and Lafontaine and Schmidt (2010).  Phylogenetic relationships are based on a variety of sources (Kristensen and Skalski 1999; Regier et al. 2009; Mutanen et al. 2010; Zahiri et al. in press; Chapter 4).     313 Appendix L: Supplementary table for Chapter 9. Species inventory for ponderosa pine forests in the Kamloops, BC vicinity. Classification follows Powell and Opler (2009) and Lafontaine and Schmidt (2010).  Taxon  No. of individuals  Erebidae (10)  5739 Arctiinae Bruceia pulverina Neumoegen, 1893 1 Eilema bicolor (Grote, 1864) 143 Grammia nevadensis (Grote & Robinson, 1866) 283 Virbia ferruginosa (Walker, 1854) 1 Calpinae Scoliopteryx libatrix (Linnaeus, 1758) 1 Erebinae Catocala briseis W. H. Edwards, 1864 1 Lygephila victoria (Grote, 1874) 1 Hypeninae Phobolosia anfracta (Hy. Edwards, 1881) 2 Lymantriinae Orgyia pseudotsugata (McDunnough, 1921) 5300 Rivulinae Mycterophora longipalpata Hulst, 1896 6  Geometridae (49)  766 Ennominae Caripeta sp.  1 Digrammia curvata (Grote, 1880) 327 Digrammia denticulata (Grote, 1883) 4 Digrammia neptaria (Guenée, [1858]) 1 Digrammia setonana (McDunnough, 1927) 15 Digrammia triviata (Barnes & McDunnough, 1917) 27 Enypia griseata Grossbeck, 1908 1 Euchlaena johnsonaria (Fitch, 1869)                                      2 Eumacaria latiferrugata (Walker, [1863]) 1 Glena nigricaria (Barnes & McDunnough, 1913) 14 Hesperumia sulphuraria Packard, 1873 1 Macaria adonis Barnes & McDunnough, 1918 6 Macaria bitactata (Walker, 1862) 4 Macaria brunneata (Thunberg, 1784) 13 Macaria decorata (Hulst, 1896) 8 Macaria exauspicata Walker, 1861 1 Macaria plumosata (Barnes & McDunnough, 1917) 11 Macaria signaria (Hübner, [1809]) 12 Melanolophia imitata (Walker, 1860) 6 Meris suffusaria McDunnough, 1940 2 Nematocampa resistaria (Herrich-Schäffer, [1856]) 10 Neoterpes trianguliferata (Packard, 1871) 1 Pero behrensaria (Packard, 1871) 26 Pero morrisonaria (Hy. Edwards, 1881) 1 Pero occidentalis (Hulst, 1896) 27 Plataea trilinearia (Packard, 1873) 1 Protoboarmia porcelaria (Guenée, [1858]) 1  314 Taxon  No. of individuals  Sicya macularia (Harris, 1850) 1 Stenoporpia pulmonaria (Grote, 1881) 13 Synaxis sp.  1 Geometrinae Chlorochlamys triangularis Prout, 1912 14 Synchlora aerata (Fabricius, 1798) 2 Synchlora bistriaria (Packard, 1876) 35 Larentiinae Dysstroma formosa (Hulst, 1896) 2 Dysstroma truncata (Hufnagel, 1767) 3 Eulithis testata (Linnaeus, 1761)                                   1 Eupithecia behrensata Packard, 1876 2 Eupithecia borealis (Hulst, 1898) 5 Eupithecia interruptofasciata Packard, 1873 1 Eupithecia sp. 11  1 Eupithecia sp. 22  95 Hydriomena furcata (Thunberg, 1784) 3 Hydriomena ruberata (Freyer, [1831]) 5 Prorella leucata (Hulst, 1896) 4 Stamnoctenis morrisata (Hulst, 1887) 34 Sterrhinae Idaea demissaria (Hübner, [1831]) 9 Scopula fuscata (Hulst, 1887) 2 Scopula inductata (Guenée, [1858]) 5 Scopula luteolata (Hulst, 1880) 4  Lasiocampidae (2)  12 Malacosoma californica (Packard, 1864) 1 Tolype dayi Blackmore, 1921 11  Noctuidae (135)  1981 Amphipyrinae Amphipyra tragopoginis (Clerck, 1759) 1 Apamea antennata (J. B. Smith, 1891) 2 Apamea cogitata (J. B. Smith, 1891) 1 Apamea devastator (Brace, 1819) 5 Apamea impulsa (Guenée, 1852) 2 Apamea inordinata (Morrison, 1875) 33 Apamea longula (Grote, 1879) 2 Apamea occidens (Grote, 1878) 2 Apamea spaldingi (J. B. Smith, 1909) 13 Caradrina camina Smith 1894 32 Caradrina meralis (Morrison, 1875) 23 Caradrina montana (Bremer, 1861) 42 Chytonix divesta (Grote, 1874) 6 Condica discistriga (J. B. Smith, 1894) 57 Bryophilinae Cryphia cuerva (Barnes, 1907) 46 Cryphia olivacea (J. B. Smith, 1891) 1 Cuculliinae Cucullia antipoda group  1 Heliothinae Schinia acutilinea (Grote, 1878) 15 Schinia walsinghami (Hy. Edwards, 1881) 65 Noctuinae   315 Taxon  No. of individuals  Abagrotis dodi McDunnough, 1927 6 Abagrotis forbesi (Benjamin, 1921) 1 Abagrotis hermina Lafontaine, 1998 1 Abagrotis mirabilis (Grote, 1879) 2 Abagrotis nanalis (Grote, 1881) 22 Abagrotis nefascia (J.B. Smith, 1908)                                 1 Abagrotis placida (Grote, 1876) 4 Abagrotis reedi Buckett, 1969 4 Abagrotis scopeops (Dyar, 1904) 1 Abagrotis trigona (J.B. Smith, 1893)                                 5 Abagrotis vittifrons (Grote, 1864) 12 Actebia balanitis (Grote, 1873) 4 Agrotis venerabilis Walker, [1857] 134 Anaplectoides prasina ([Denis & Schiffermüller], 1775) 1 Anarta columbica (McDunnough, 1930) 10 Anarta crotchii (Grote, 1880) 8 Anarta montanica (McDunnough, 1930) 4 Anarta mutata (Dod, 1913) 1 Andropolia epichysis Grote 1880 8 Anicla exuberans (J. B. Smith, 1898) 10 Archanara subflava (Grote, 1882) 1 Cosmia elisae Lafontaine & Troubridge, 2003 3 Diarsia dislocata (J. B. Smith, 1904) 1 Diarsia freemani Hardwick, 1950 1 Dichagyris variabilis (Grote, 1874) 19 Egira curialis (Grote, 1873) 10 Egira rubrica (Harvey, 1878) 1 Epidemas obscurus J. B. Smith, 1903 15 Eurois astricta Morrison, 1874 3 Eurois occulta (Linnaeus, 1758) 3 Euxoa aberrans McDunnough, 1932 3 Euxoa adumbrata (Eversmann, 1842) 4 Euxoa agema (Strecker, 1899) 8 Euxoa albipennis (Grote, 1876) 11 Euxoa atomaris (J. B. Smith, 1890) 1 Euxoa atristrigata (J. B. Smith, 1890) 3 Euxoa auripennis Lafontaine, 1974 59 Euxoa bochus (Morrison, 1874) 4 Euxoa brunneigera (Grote, 1876) 1 Euxoa campestris (Grote, 1875) 1 Euxoa castanea Lafontaine, 1981 14 Euxoa catenula (Grote, 1879) 31 Euxoa cf. setonia  3 Euxoa choris (Harvey, 1876) 18 Euxoa comosa group sp. 1  3 Euxoa comosa group sp. 2  18 Euxoa declarata (Walker, 1865) 6 Euxoa difformis (J. B. Smith, 1900) 6 Euxoa divergens (Walker, [1857]) 4 Euxoa excogita (J. B. Smith, 1900) 3 Euxoa flavicollis (J. B. Smith, 1888) 2 Euxoa infracta (Morrison, 1875) 11 Euxoa messoria (Harris, 1841) 9 Euxoa mimallonis (Grote, 1873) 9 Euxoa nevada (J. B. Smith, 1900) 2  316 Taxon  No. of individuals  Euxoa obeliscoides (Guenée, 1852) 20 Euxoa oblongistigma (J. B. Smith, 1888) 7 Euxoa perpolita (Morrison, 1876) 5 Euxoa plagigera (Morrison, 1874) 60 Euxoa punctigera (Walker, 1865) 15 Euxoa quadridentata (Grote & Robinson, 1865) 5 Euxoa ridingsiana (Grote, 1875) 4 Euxoa satiens (J. B. Smith, 1890) 95 Euxoa satis (Harvey, 1876) 4 Euxoa servitus (J. B. Smith, 1895) 44 Euxoa silens (Grote, 1875) 1 Euxoa sp. nr. infausta  1 Euxoa sp. nr. satis  3 Euxoa terrenus (J. B. Smith, 1900) 4 Euxoa tessellata (Harris, 1841) 10 Feltia jaculifera (Guenée, 1852) 130 Feltia mollis (Walker, [1857]) 2 Hada sutrina (Grote, 1881) 1 Homorthodes discreta (Barnes & McDunnough, 1916) 1 Homorthodes furfurata (Grote, 1875) 22 Lacinipolia anguina (Grote, 1881) 2 Lacinipolia comis (Grote, 1876) 1 Lacinipolia pensilis group sp. 1  4 Lacinipolia pensilis group sp. 2  16 Lacinipolia sp. nr. buscki  12 Lacinipolia stricta (Walker, 1865) 2 Lacinipolia strigicollis (Wallengren, 1860) 24 Lacinipolia vicina group  4 Leucania anteoclara J. B. Smith, 1902 11 Leucania insueta Guenée, 1852 117 Leucania multilinea Walker, 1856 1 Leucania oregona J. B. Smith, 1902 1 Neoligia invenusta Troubridge & Lafontaine, 2002 6 Neoligia lillooet Troubridge & Lafontaine, 2002 7 Neoligia tonsa (Grote, 1880) 29 Orthosia hibisci (Guenée, 1852) 1 Orthosia revicta (Morrison, 1876) 3 Orthosia segregata (J. B. Smith, 1893) 4 Parabagrotis exsertistigma (Morrison, 1874) 30 Parabagrotis sulinaris Lafontaine, 1998 5 Polia delecta Barnes & McDunnough, 1916 1 Polia nugatis (J. B. Smith, 1898) 56 Polia piniae Buckett & Bauer, 1967 1 Polia purpurissata (Grote, 1864) 2 Protolampra rufipectus (Morrison, 1875) 10 Protorthodes curtica (J. B. Smith, 1890) 158 Pseudanarta crocea (Hy. Edwards, 1875) 25 Pseudanarta flava (Grote, 1874) 1 Sideridis rosea (Harvey, 1874) 2 Spaelotis clandestina (Harris, 1841) 2 Tholera americana (J. B. Smith, 1894) 118 Xestia smithii (Snellen, 1896) 1 Xylena cineritia (Grote, 1875) 1 Xylena thoracica (Putnam-Cramer, 1886) 2 Zosteropoda hirtipes Grote, 1874 2  317 Taxon  No. of individuals  Oncocnemidinae Apharetra dentata (Grote, 1875) 1 Oncocnemis lacticollis J. B. Smith, 1908 1 Oncocnemis poliochroa Hampson, 1906 1 Oncocnemis sp.  1 Pantheinae Panthea acronyctoides (Walker, 1861) 1 Plusiinae Syngrapha orophila (Hampson, 1908) 1  Notodontidae (1)  1 Nadata gibbosa (J.E. Smith, 1797) 1  Saturniidae (1)  1 Hyalophora euryalus (Boisduval, 1855) 1  Sphingidae (2)  3 Smerinthus sp.  1 Sphinx drupiferarum J.E. Smith, 1797 2    318 Appendix M: Supplementary table for Chapter 9. Species inventory for Ponderosa Pine forests in the Okanagan Falls, BC vicinity. Classification follows Powell and Opler (2009) and Lafontaine and Schmidt (2010).  Taxon  No. of individuals  Drepanidae (1)  1 Drepana bilineata (Packard, 1864) 1  Erebidae (15)  549 Arctiinae Cycnia oregonensis (Stretch, 1873) 4 Grammia nevadensis (Grote & Robinson, 1866) 48 Bruceia pulverina Neumoegen, 1893 7 Eilema bicolor (Grote, 1864) 51 Calpinae Scoliopteryx libatrix (Linnaeus, 1758) 1 Erebinae Drasteria adumbrata (Behr, 1870) 3 Drasteria divergens (Behr, 1870) 1 Drasteria ochracea (Behr, 1870) 3 Drasteria sabulosa (Hy. Edwards, 1881) 96 Melipotis jucunda (Hübner, 1818) 1 Herminiinae Idia occidentalis (J. B. Smith, 1884) 22 Idia sp. nr. lubricalis  4 Hypeninae Spargaloma sexpunctata Grote, 1873 2 Lymantriinae Orgyia pseudotsugata (McDunnough, 1921) 301 Rivulinae Mycterophora longipalpata Hulst, 1896 5  Euteliidae (1)  1 Marathyssa inficita (Walker, 1865) 1  Geometridae (78)  670 Ennominae Anavitrinella pampinaria (Guenée, [1858]) 3 Caripeta aequaliaria Grote, 1883 1 Caripeta sp.  2 Digrammia californiaria (Packard, 1871) 1 Digrammia curvata (Grote, 1880) 8 Digrammia delectata (Hulst, 1887) 20 Digrammia denticulata (Grote, 1883) 7 Digrammia muscariata (Guenée, [1858]) 1 Digrammia neptaria (Guenée, [1858]) 14 Digrammia ordinata (Walker, 1862) 21 Digrammia respersata (Hulst, 1880) 62 Digrammia triviata (Barnes & McDunnough, 1917) 1  319 Taxon  No. of individuals  Drepanulatrix falcataria (Packard, 1873) 7 Drepanulatrix foeminaria (Guenée, [1858]) 8 Drepanulatrix secundaria Barnes & McDunnough, 1916 1 Drepanulatrix unicalcararia (Guenée, [1858]) 13 Euchlaena johnsonaria (Fitch, 1869)                                      2 Euchlaena madusaria (Walker, 1860)                                     1 Euchlaena tigrinaria (Guenée, [1858]) 1 Eudrepanulatrix rectifascia (Hulst, 1896)                                      8 Eumacaria latiferrugata (Walker, [1863]) 5 Glena nigricaria (Barnes & McDunnough, 1913) 28 Hesperumia sulphuraria Packard, 1873 5 Iridopsis clivinaria (Guenée, [1858]) 7 Ixala desperaria (Hulst, 1887) 1 Macaria adonis Barnes & McDunnough, 1918 4 Macaria bitactata (Walker, 1862) 3 Macaria colata (Grote, 1881) 8 Macaria decorata (Hulst, 1896) 13 Macaria plumosata (Barnes & McDunnough, 1917) 2 Macaria quadrilinearia (Packard, 1873) 3 Macaria sexmaculata Packard, 1867 1 Macaria signaria (Hübner, [1809]) 6 Melanolophia imitata (Walker, 1860) 32 Pero behrensaria (Packard, 1871) 3 Pero mizon Rindge, 1955 14 Pero occidentalis (Hulst, 1896) 3 Phaeoura mexicanaria (Grote, 1883) 9 Plagodis phlogosaria (Guenée, [1858]) 1 Plagodis pulveraria (Linnaeus, 1758) 1 Sericosema juturnaria (Guenée, [1858]) 110 Sericosema wilsonensis Cassino & Swett, 1922 1 Sicya macularia (Harris, 1850) 1 Spodolepis danbyi (Hulst, 1898) 1 Stenoporpia pulmonaria (Grote, 1881) 5 Synaxis cervinaria (Packard, 1871) 13 Geometrinae Chlorochlamys triangularis Prout, 1912 1 Chlorosea nevadaria Packard, 1873 3 Nemoria darwiniata (Dyar, 1904) 7 Nemoria glaucomarginaria (Barnes & McDunnough, 1917) 2 Synchlora aerata (Fabricius, 1798) 6 Larentiinae Aplocera plagiata (Linnaeus, 1758) 2 Coryphista meadii (Packard, 1874) 1 Costaconvexa centrostrigaria (Wollaston, 1858) 1 Dysstroma formosa (Hulst, 1896) 5 Dysstroma truncata (Hufnagel, 1767) 1 Eulithis propulsata (Walker, 1862)                                     1 Eulithis xylina (Hulst, 1896)                                      1 Eupithecia absinthiata (Clerck, 1759) 2 Eupithecia agnesata Taylor, 1908 1 Eupithecia behrensata Packard, 1876 45 Eupithecia maestosa (Hulst, 1896) 1  320 Taxon  No. of individuals  Eupithecia nevadata Packard, 1871 3 Eupithecia niveifascia (Hulst, 1898) 2 Eupithecia sp. 22  1 Eustroma semiatrata (Hulst, 1881) 2 Hydriomena renunciata (Walker, 1862) 1 Perizoma costiguttata (Hulst, 1896) 1 Prorella leucata (Hulst, 1896) 1 Stamnodes marmorata (Packard, 1871) 2 Zenophleps alpinata Cassino, 1927 9 Sterrhinae Idaea demissaria (Hübner, [1831]) 69 Leptostales rubromarginaria (Packard, 1871) 17 Scopula ancellata (Hulst, 1887) 3 Scopula inductata (Guenée, [1858]) 11 Scopula junctaria (Walker, 1861) 1 Scopula luteolata (Hulst, 1880) 1 Scopula quinquelinearia (Packard, 1871) 4  Lasiocampidae (3)  74 Phyllodesma americana (Harris, 1841) 8 Malacosoma californica (Packard, 1864) 1 Tolype dayi Blackmore, 1921 65  Noctuidae (130)  1014 Acronictinae Acronicta mansueta J. B. Smith, 1897 1 Acronicta strigulata J. B. Smith, 1897 1 Amphipyrinae Apamea acera (J. B. Smith, 1900) 1 Apamea antennata (J. B. Smith, 1891) 13 Apamea devastator (Brace, 1819) 3 Apamea longula (Grote, 1879) 1 Apamea spaldingi (J. B. Smith, 1909) 2 Caradrina meralis (Morrison, 1875) 71 Caradrina montana (Bremer, 1861) 10 Caradrina morpheus (Hufnagel, 1766) 1 Chytonix divesta (Grote, 1874) 7 Condica discistriga (J. B. Smith, 1894) 9 Spodoptera praefica (Grote, 1875) 1 Bryophilinae Cryphia olivacea (J. B. Smith, 1891) 27 Cuculliinae Cucullia eulepis (Grote, 1876) 1 Dilobinae Raphia frater Grote, 1864 1 Noctuinae Abagrotis apposita (Grote, 1878) 1 Abagrotis discoidalis (Grote, 1876) 1 Abagrotis mirabilis (Grote, 1879) 5 Abagrotis nefascia (J.B. Smith, 1908)                                 1 Abagrotis placida (Grote, 1876) 2 Abagrotis reedi Buckett, 1969 1  321 Taxon  No. of individuals  Abagrotis scopeops (Dyar, 1904) 2 Abagrotis trigona (J.B. Smith, 1893)                                 10 Abagrotis vittifrons (Grote, 1864) 2 Adelphagrotis indeterminata (Walker, 1865) 1 Admetovis oxymorus Grote, 1873 4 Admetovis similaris Barnes, 1904 1 Agrotis sp. nr. carolina  2 Agrotis venerabilis Walker, [1857] 80 Anaplectoides prasina ([Denis & Schiffermüller], 1775) 1 Anarta columbica (McDunnough, 1930) 38 Anarta crotchii (Grote, 1880) 2 Anarta decepta (Grote, 1883) 5 Andropolia aedon (Grote, 1880) 1 Dichagyris variabilis (Grote, 1874) 7 Egira crucialis (Harvey, 1875) 1 Egira curialis (Grote, 1873) 7 Egira perlubens (Grote, 1881) 6 Egira simplex (Walker, 1865) 2 Epidemas obscurus J. B. Smith, 1903 1 Eurois occulta (Linnaeus, 1758) 4 Euxoa agema (Strecker, 1899) 1 Euxoa albipennis (Grote, 1876) 3 Euxoa atomaris (J. B. Smith, 1890) 5 Euxoa auripennis Lafontaine, 1974 1 Euxoa bicollaris (Grote, 1878) 3 Euxoa bochus (Morrison, 1874) 2 Euxoa castanea Lafontaine, 1981 3 Euxoa catenula (Grote, 1879) 2 Euxoa cf. setonia  3 Euxoa choris (Harvey, 1876) 1 Euxoa difformis (J. B. Smith, 1900) 11 Euxoa divergens (Walker, [1857]) 1 Euxoa excogita (J. B. Smith, 1900) 1 Euxoa infausta (Walker, 1865) 1 Euxoa infracta (Morrison, 1875) 3 Euxoa messoria (Harris, 1841) 2 Euxoa mimallonis (Grote, 1873) 1 Euxoa obeliscoides (Guenée, 1852) 4 Euxoa olivia (Morrison, 1876) 2 Euxoa plagigera (Morrison, 1874) 8 Euxoa pluralis (Grote, 1878) 3 Euxoa punctigera (Walker, 1865) 9 Euxoa rockburnei Hardwick, 1973 2 Euxoa satis (Harvey, 1876) 7 Euxoa septentrionalis (Walker, 1865) 1 Euxoa silens (Grote, 1875) 5 Euxoa sp. nr. brunneigera  1 Euxoa sp. nr. excogita  1 Euxoa sp. nr. satis  1 Euxoa terrenus (J. B. Smith, 1900) 25 Euxoa tessellata (Harris, 1841) 7 Feltia jaculifera (Guenée, 1852) 134  322 Taxon  No. of individuals  Hadena variolata (J. B. Smith, 1888) 2 Homorthodes discreta (Barnes & McDunnough, 1916) 12 Homorthodes furfurata (Grote, 1875) 14 Lacanobia sp. nr. subjuncta  6 Lacinipolia pensilis group sp. 1  3 Lacinipolia pensilis group sp. 2  2 Lacinipolia sp. nr. buscki  7 Lacinipolia stricta (Walker, 1865) 4 Lacinipolia strigicollis (Wallengren, 1860) 20 Lacinipolia vicina group  9 Leucania insueta Guenée, 1852 38 Leucania oregona J. B. Smith, 1902 1 Lithophane atara (J. B. Smith, 1909) 1 Lithophane ponderosa Troubridge & Lafontaine, 2003 2 Mesogona taedata (Harvey, 1874) 7 Neoligia invenusta Troubridge & Lafontaine, 2002 1 Neoligia lancea Troubridge & Lafontaine, 2002 1 Noctua pronuba (Linnaeus, 1758) 6 Orthosia revicta (Morrison, 1876) 1 Orthosia segregata (J. B. Smith, 1893) 2 Papestra brenda (Barnes & McDunnough, 1916) 3 Papestra invalida (J. B. Smith, 1891) 1 Parabagrotis exsertistigma (Morrison, 1874) 9 Parabagrotis sulinaris Lafontaine, 1998 1 Polia delecta Barnes & McDunnough, 1916 13 Polia piniae Buckett & Bauer, 1967 5 Pronoctua typica J. B. Smith, 1894 3 Properigea albimacula (Barnes & McDunnough, 1912) 9 Protolampra brunneicollis (Grote, 1865) 1 Protolampra rufipectus (Morrison, 1875) 1 Protorthodes curtica (J. B. Smith, 1890) 117 Pseudanarta crocea (Hy. Edwards, 1875) 5 Setagrotis pallidicollis (Grote, 1880) 7 Sideridis rosea (Harvey, 1874) 4 Spaelotis bicava Lafontaine, 1998 1 Spaelotis clandestina (Harris, 1841) 3 Spaelotis unicava Lafontaine, 1998 3 Tesagrotis corrodera (J. B. Smith, 1907) 2 Tesagrotis piscipellis (Grote, 1878) 2 Tholera americana (J. B. Smith, 1894) 17 Xestia oblata (Morrison, 1875) 1 Zotheca tranquilla Grote, 1874 2 Oncocnemidinae Homohadena fifia Dyar, 1904 5 Oncocnemis greyi Troubridge & Crabo, 1998 23 Oncocnemis parvanigra Blackmore, 1923 4 Oncocnemis poliochroa Hampson, 1906 1 Oncocnemis semicollaris J. B. Smith, 1909 5 Oncocnemis sp.  22 Pleromelloida bonuscula (J. B. Smith, 1898) 2 Pleromelloida sp.  3 Sympistis amun Troubridge, 2008 1  323 Taxon  No. of individuals  Sympistis cocytus Troubridge, 2008 1 Pantheinae Panthea acronyctoides (Walker, 1861) 1 Panthea virginarius (Grote, 1880) 2 Plusiinae Anagrapha falcifera (Wm. Kirby, 1837) 2 Autographa californica (Speyer, 1875) 1  Notodontidae (4)  7 Clostera apicalis (Walker, 1855) 1 Gluphisia septentrionis Walker, 1855 1 Gluphisia severa Hy. Edwards, 1886 1 Nadata gibbosa (J.E. Smith, 1797) 4  Saturniidae (1)  2 Hyalophora euryalus (Boisduval, 1855) 2  Sphingidae (5)  39 Paonias excaecata (J.E. Smith, 1797) 1 Paonias myops (J.E. Smith, 1797) 3 Smerinthus sp.  3 Sphinx perelegans Hy. Edwards, 1874 8 Sphinx vashti Strecker, 1878 24  Uraniidae (1)  1 Callizzia sp.  1   

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