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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  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.  ii  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,  iii  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  iv  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.  v  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.  vi  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	
   vii  5.1	
   5.2	
   5.3	
   5.4	
    Introduction ........................................................................................................ 69	
   Materials and methods....................................................................................... 70	
   Results ............................................................................................................... 71	
   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	
    viii  10.2	
   10.3	
   10.4	
   10.5	
    Strengths and limitations................................................................................ 174	
   Potential applications ..................................................................................... 177	
   Future research directions ............................................................................. 179	
   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	
    ix  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	
    x  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	
    xi  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	
    xii  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) xiii  -  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)  xiv  -  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.  xv  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 1  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 nonindigenous 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  2  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  3  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:  4  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.  5  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  6  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.  7  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. 8  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.  9  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  10  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  11  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’.  12  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 neighbourjoining 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  13  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). 14  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 nonoverlapping 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  15  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  16  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).  17  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  Xanthorhoe ramaria Swett & Cassino  polyphyletic  formosa (Hulst), hersiliata (Guenée), rutlandia (McD.) 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)  18  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.  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  1/3  4.43  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  Taxon  Hydriomena perfracta (Swett) Macaria colata (Grote)  19  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).  20  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).  21  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.  22  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  23  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  24  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),  25  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 26  (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 highthroughput 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  27  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/;  28  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  29  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 /  30  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  31  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  32  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 33  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  34  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  35  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.  36  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  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 L. bantaizana  LYMAN025  3  2  0.992  3.87 x 10  -5  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  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  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  surveillance species  surveillance subspecies  Risk  37  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)  38  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).  39  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.  40  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.  41  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.  42  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).  43  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. 44  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  45  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  46  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 multigene 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  47  ‘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 48  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. 49  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  50  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 EF1α (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-timereversible 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/raxmlbb/) (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  51  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  52  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  53  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).  54  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  55  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  56  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  57  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 deeplevel 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  58  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 COI5p 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  59  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.  60  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  61  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.  Taxon / relationship  a  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  N  a  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  supports spurious relationship of (Sterrhinae in part + Larentiinae in part) with bootstrap support of 81  62  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  N  b  N  L  L+S  3  91  99  N  a  N  c  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  63  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.  64  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.  65  Figure 4.3 Best-scoring maximum likelihood tree constructed with the complete data set of 176 taxa and 11 gene fragments.  66  67  Figure 4.4 Best-scoring maximum likelihood tree constructed with a reduced data set of 68 taxa and 11 gene fragments.  68  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. 69  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  70  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,  71  Illecillewaet Campgrounds west of Rogers Pass, 51.2648N 117.494W, 24-Jun2005 (K. Pickthorn) [BIOUG, HLC-20175, LBCA175-05]; Glacier National Park, Glacier National Park Compound at Rogers Pass, 51.3032N 117.519W, 16-Jun2005 (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  72  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 lobeshaped, 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.  73  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  74  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  75  al. 2007), genetic screening may soon be more cost- and time-efficient than current morphological methods of biodiversity monitoring.  76  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).  77  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  78  Figure 5.3 Distribution of Lampropteryx suffumata in North America. Black squares denote species records and black circles are place markers.  79  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. 80  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 81  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  82  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 |.  83  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).  84  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  85  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).  86  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 macroLepidoptera) 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  87  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.  88  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.  89  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.  90  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. 91  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  92  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  93  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  94  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  95  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  96  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; UBC2007-0180 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  97  (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  98  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  99  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 intraspecific 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).  100  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  101  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.  102  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  103  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.  104  Table 7.1 Descriptions for four introduced moth species discovered in Stanley Park, Vancouver, Canada in 2007.  Taxonomy  Host plant(s)  Distribution (outside BC)  References  Paraswammerdamia lutarea  Maloideae (cottoneaster,  Europe - widespread  Karsholt and  (Haworth, 1828)  hawthorn, rowan)  Prays fraxinella  Fraxinus excelsior (ash)  (Donovan, 1793)  Dichelia histrionana  Razowski 1996  Europe – widespread, Newfoundland  Picea (spruce) and Abies (fir)  (Frölich, 1828)  1  Karsholt and Razowski 1996  Europe including  Sterling & Ashby  Scandinavia and British  2006  Isles, E to Caucasus  Argyresthia pruniella (Clerck, 1759)  Rosaceae (stone-fruit cultures)  Europe and Asia Minor, Nova Scotia  2  Agassiz 1996; Karsholt and Razowski 1996  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).  105  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.  106  107  108  109  110  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).  111  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.  112  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). Hyperdiverse arthropod assemblages dominate these ecosystems (Southwood et al. 113  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  114  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;  115  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  116  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 northcentral 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  117  (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).  118  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  119  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 fulllength 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  120  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,  121  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  122  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  123  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.  124  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  125  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).  126  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  127  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  128  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 threequarters 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  129  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  130  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  131  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  132  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  133  (Holloway 1980; Gadagkar et al. 1990), and was effective in a similar postdisturbance 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.  134  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.  135  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 Date Ck.  Number of individuals  Sicamous Ck.  Date Ck.  Sicamous Ck.  Argyresthiidae  7  2  141  3  Blastobasidae  1  0  4  0  Coleophoridae  7  1  28  2  17  14  1312  103  Depressariidae  1  1  1  4  Drepanidae  7  2  95  8  Elachistidae  1  0  1  0  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  Crambidae  Erebidae  136  Taxon  Number of species Date Ck.  Momphidae  Number of individuals  Sicamous Ck.  Date Ck.  Sicamous Ck.  1  3  14  6  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  333  206  7978  2926  Noctuidae  Total  137  Table 8.2 Moth diversity and abundance totals for the eight block types  Metric  Date Creek CC  HR  Sicamous Creek  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  150 (7.6)  205 (8.3)  220 (7.4)  204 (7.8)  89 (6.6)  115 (7.0)  96 (5.7)  120 (7.8)  14  14  14  14  13  13  13  13  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)  936  936  936  936  561  561  561  561  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)  19  36  41  43  13  20  17  26  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)  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  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)  140  140  140  140  80  80  80  80  Observed species richness No. of samples Rarified species richness No. of individuals Observed haplotype richness No. of species Rarified haplotype richness No. of species  Rarified phylogenetic diversity No. of species  138  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 B1 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).  139  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.  140  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.  141  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.  142  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.  143  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).  144  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. 145  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  146  (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.  147  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. 148  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 149  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.  150  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.  151  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 wellsupported 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)  152  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).  153  To evaluate differences in diversity between the two locations, unpaired ttests 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, 154  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).  155  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  156  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 (onetailed 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  157  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 communitywide 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  158  (www.macroecology.ca). In these cases, not only have I provided initial inventories and diversity estimates, but also a DNA barcode library for macromoths 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  159  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  160  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 undersampling (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.  161  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.  162  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 No. of species  Drepanidae  South Okanagan  No. of individuals  No. of species  No. of individuals  0  0  1  1  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  0  0  1  1  Geometridae  49  993  78  670  Ennominae  30  539  46  462  3  51  5  19  Larentiinae  12  156  20  83  Sterrhinae  4  20  7  106  2  12  3  74  135  1981  130  1014  0  0  2  2  14  221  11  119  2  47  1  27  Erebidae  Euteliidae  Geometrinae  Lasiocampidae Noctuidae Acronictinae Amphipyrinae Bryophilinae  163  Taxon  Kamloops No. of species  South Okanagan  No. of individuals  No. of species  No. of individuals  Cuculliinae  1  1  1  1  Dilobinae  0  0  1  1  Heliothinae  2  80  0  0  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  200  8503  239  2358  Noctuinae  Total  164  Table 9.2 Summary of estimated macro-moth diversity at each collection site.  Metric  Kamloops K2 K3  K1 Overall abundance Mean individuals/trap  K4  O1  South Okanagan O2 O3  O4  951 118.9  923 115.4  5338 667.3  1291 161.4  728 91.0  409 51.1  460 57.6  761 95.1  Overall species richness a Rarified species richness  94 (6.5) 61.1 (4.5)  95 (7.0) 75.5 (5.8)  135 (6.5) 65.4 (4.5)  99 (6.3) 58.7 (4.0)  143 (8.5) 93.5 (6.0)  96 (7.9) 95.0 (7.9)  105 (7.5) 98.1 (6.2)  135 (7.3) 105.4 (6.2)  Overall haplotype richness N species (with >6 sequences) b Rarified haplotype richness  61 (7.7) 18 37.3 (4.7)  29 (5.2) 12 26.6 (4.8)  90 (9.4) 33 30.0 (3.1)  50 (6.9) 21 26.2 (3.6)  62.0 (7.7) 20 34.1 (4.3)  44.0 (6.5) 11 44.0 (6.5)  45.0 (6.6) 14 35.4 (5.2)  47.0 (6.7) 16 32.3 (4.6)  Overall phylogenetic diversity c Rarified phylogenetic diversity  9.8 8.7 (0.3)  14.8 13.0 (0.5)  22.5 15.1 (0.7)  9.6 8.2 (0.3)  25.8 16.4 (0.7)  14.0 12.2 (0.3)  17.1 13.8 (0.4)  25.9 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  165  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  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  Stenoporpia pulmonaria  166  Table 9.4 Summary of biological and physical attributes of eight collection sites.  Metric K1 a  mean dbh (standard deviation)  a  Kamloops K2 K3  K4  O1  South Okanagan O2 O3  O4  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) % Douglas-Fir (Fd)  60.2 39.8  73.6 26.4  68.4 31.6  89.8 10.2  64.2 35.8  98.1 1.9  99.1 0.9  78.0 22.0  % of Py with 'green' attack % of Py with 'red' attack % of Py with 'grey' attack % of Py no evidence of attack % of Py mortality  0.7 77.2 0.7 21.3 78.7  7.6 81.3 2.4 8.6 91.4  3.9 70.0 4.2 21.9 78.1  6.7 69.7 7.8 15.9 84.1  0.0 0.0 1.1 98.9 1.1  2.5 2.5 4.8 90.1 9.9  0.1 0.0 0.2 99.6 0.4  0.4 1.7 2.2 95.7 4.3  dbh: diameter at breast height  167  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.  168  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.  169  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.  170  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.  171  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.  172  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 173  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  174  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).  175  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  176  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,  177  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  178  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.  179  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 timeconsuming 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, wellsupported 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  180  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  181  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  182  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.  183  References  Abdo, Z. and Golding, G.B. 2007. A step toward barcoding life: a model-based, decision-theoretic method to assign genes to pre-existing species groups. Systematic Biology 56: 44–56. Abraham, D., Ryrrholm, N., Wittzell, H., Holloway, J.D., Scoble, M.J., and Lofstedt, C. 2001. Molecular phylogeny of the superfamilies in Geometridae (Geometroidea: Lepidoptera). Molecular Phylogenetics and Evolution 20: 65–77. Agassiz, D.J.L. 1996. Yponomeutidae. In: Emmet A.M. (ed), The Moths and Butterflies of Great Britain and Ireland, vol. 3. Harley Books, Colchester, England, pp. 39–110. Ahrens, D., Monaghan, M.T., and Vogler, A.P. 2007. DNA-based taxonomy for associating adults and larvae in multi-species assemblages of chafers (Coleoptera: Scarabaeidae). Molecular Phylogenetics and Evolution 44: 436–449. Allen, E.A. and Humble, L.M. 2001. Nonindigenous species introductions: a threat to Canada’s forests and forest economy. Canadian Journal of Plant Pathology 24: 103–110. Andelman, S.J. and Fagan, W.F. 2000. Umbrellas and flagships: efficient conservation surrogates or expensive mistakes? Proceedings of the National Academy of Sciences, USA 97: 5954–5959. Anderson, S.J., Dawson, D.A., and Freeland, J.A. 2006. Isolation and characterization of highly polymorphic microsatellite loci for the garden tiger moth Arctia caja (Lepidoptera: Arctiidae). Molecular Ecology Notes 6: 104106. Armstrong, K.F. 2010. DNA barcoding: a new module in New Zealand’s plant biosecurity diagnostic toolbox. EPPO Bulletin 40: 91–100. Armstrong, K.F. and Ball, S.L. 2005. DNA barcodes for biosecurity: invasive species identification. Philosophical Transactions of the Royal Society B: Biological Sciences 360: 1813–1823. Armstrong, K.F., McHugh, P., Chinn, W., Frampton, E.R., and Walsh, P.J. 2003. Tussock moth species arriving on imported used vehicles determined by DNA analysis. New Zealand Plant Protection 56: 16–20. Ayres, M. P. and Lombardero, M. J. 2000. Assessing the consequences of global change for forest disturbance from herbivores and pathogens. Sci. Total Environ. 262: 263–286. 184  Ball, S.L. and Armstrong, K.F. 2006. DNA barcodes for insect pest identification: a test case with tussock moths (Lepidoptera: Lymantriidae). Canadian Journal of Forest Research 36: 337–350. Balmford, A., Green, M.J.B., and Murray, M.G. 1996. Using higher-taxon richness as a surrogate for species richness. I. Regional tests. Proceedings of the Royal Society of London B 263: 1267–1274. Barr, N.B. 2009. Pathway analysis of Ceratitis capitata (Diptera: Tephritidae) using mitochondrial DNA. Journal of Economic Entomology 102: 401–411. Barrett R.D.H. and Hebert, P.D.N. 2005. Identifying spiders through DNA barcodes. Canadian Journal of Zoology 83: 481–491. Beccaloni, G.W. and Gaston, K.J. 1995. Predicting the species richness of Neotropical forest butterflies: Ithnomiinae (Lepidoptera: Nymphalidae) as indicators. Biol. Conserv 71: 77–86. Beljaev, E.A. and Vasilenko, S.V. 2002. An annotated checklist of geometrid moths (Lepidoptera: Geometridae) from the Kamchatka Peninsula and adjacent islands. Entomologica Fennica 13: 195–235. Bely, A.E. and Weisblat, D.A. 2006. Lessons from leeches: a call for DNA barcoding in the lab. Evolution and Development 8: 491–501. Bogdanowicz, S.M., Mastro, V.C., Prasher, D.C., and Harrison, R.G. 1997. Microsatellite DNA variation among Asian and North American gypsy moths (Lepidoptera: Lymantriidae). Annals of the Entomological Society of America 90: 768–775. Bogdanowicz, S.M., Schaefer, P.W., and Harrison, R.G. 2000. Mitochondrial DNA variation among worldwide populations of gypsy moths, Lymantria dispar. Molecular Phylogenetics and Evolution 15: 487–495. Bogdanowicz, S.M., Wallner, W.E., Bell, J., Odell, T.M., and Harrison, R.G. 1993. Asian gypsy moths (Lepidoptera: Lymantriidae) in North America: evidence from molecular data. Annals of the Entomological Society of America 86: 710–715. Bolte, K.B. 1990. Guide to the Geometridae of Canada (Lepidoptera). VI. Subfamily Larentiinae. 1. Revision of the genus Eupithecia. Memoirs of the Entomological Society of Canada 151: 1–253. Booy, G., Hendriks, R.J.J., Smulders, M.J.M., van Groenendael, J.M., and Vosman, B. 2000. Genetic diversity and the survival of populations. Plant Biology 2: 379–395. Bortolus, A. 2008. Error cascades in the biological sciences: The unwanted consequences of using bad taxonomy in ecology. AMBIO: A Journal of the Human Environment 37: 114–118. 185  Bowden, J. 1982. An analysis of the factors affecting catches of insects in light traps. Bulletin of Entomological Research 72: 536–556. Brehm, G. and Fiedler, K. 1999. Diversity and community structure of geometrid moths of disturbed habitat in a montane area in the Ecuadorian Andes. J Res Lepidoptera 38: 1–14. Brockerhoff, E.G., Barratt, B.I.P., Beggs, J.R., Fagan, L.L., Kay, N., Phillips, C.B., and Vink, C.J. 2010. Impacts of exotic invertebrates on New Zealand’s indigenous species and ecosystems. New Zealand Journal of Ecology 34: 158–174. Brower, A.V.Z. and DeSalle, R. 1998. Mitochondrial vs. nuclear DNA sequence evolution among nymphalid butterflies: the utility of Wingless as a source of characters for phylogenetic inference. Insect Molecular Biology 7: 1–10. Cadotte, M. W., Davies, T. J., Regetz, J., Kembel, S., Cleland, E. and Oakley, T.H. 2010. Phylogenetic diversity metrics for ecological communities: integrating species richness, abundance and evolutionary history. Ecology Letters 13: 96–105. Caesar, R.M., Sorensson, M. and Cognato, A.I. 2006. Integrating DNA data and traditional taxonomy to streamline biodiversity assessment: an example from edaphic beetles in the Klamath ecoregion, California, USA. Diversity and Distributions 12: 483–489. Canfield, M. R., Greene, E., Moreau, C. S., Chen, N. and Pierce, N. E. 2008. Exploring phenotypic plasticity and biogeography in emerald moths: A phylogeny of the genus Nemoria (Lepidoptera: Geometridae). Molecular Phylogenetics and Evolution 49: 477–487. Cannings, R.A. and Scudder, G.G.E. 2007. Checklist: Order Lepidoptera in British Columbia. http://www.geog.ubc.ca/biodiversity/efauna/documents/Lepidoptera2008Ca nnings.pdf Cardoso, P., Crespo, L.C., Carvalho, R., Rufino, A.C., and Henriques, S.S. 2009. Ad-hoc vs. standardized and optimized arthropod diversity sampling. Diversity 1: 36–51. Castresana, J. 2000. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17: 540–552. Caterino, M.S., Cho, S., and Sperling, A.H. 2000. The current state of insect molecular systematics: a thriving tower of Babel. Annual Review of Entomology 45: 1–54. Chao, A. 1987. Estimating the population size for capture-recapture data with unequal catchability. Biometrics 43: 783–791.  186  Chazdon R.L., Colwell R.K., Denslow J.S. and Guariguata M.K. 1998. Statistical methods for estimating species richness of woody regeneration in primary and secondary rain forests of northeastern Costa Rica. In: Dallmeier F. and Comisky J.A. (eds), Forest Biodiversity Research, Monitoring, and Modeling: Conceptual Background and Old World Case Studies. Parthenon Publishing, Paris, pp. 285–309. Cho, S., Mitchell, A., Mitter, C., Regier, J., Matthews, M., and Robertson, R. 2008. Molecular phylogenetics of heliothine moths (Lepidoptera: Noctuidae: Heliothinae), with comments on the evolution of host range and pest status. Systematic Entomology 33: 581–594. Choi, S.-W. 1998. Taxonomy of the genus Plemyria Hübner (Lepidoptera, Geometridae, Larentiinae). Entomologica Fennica 9: 185–196. Choi, S.-W. 2000. The occurrence of Lampropteryx suffumata (Denis and Schiffermüller) (Lepidoptera: Geometridae) in North America. Pan-Pacific Entomologist 76: 123–125. Choi, S.-W. 2001. Phylogeny of Eulithis Hübner and related genera (Lepidoptera: Geometridae), with an implication of wing pattern evolution. American Museum Novitates 3318: 1–37. Chown, S.L., Sinclair, B.J. and Jansen van Vuuren, B.J. 2008. DNA barcoding and the documentation of alien species establishment on sub-Antarctic Marion Island. Polar Biology 31: 651–655. Clare, E.L., Fraser, E.E., Braid, H.E., Fenton, M.B. and Hebert, P.D.N. 2009. Species on the menu of a generalist predator, the eastern red bat (Lasiurus borealis): using a molecular approach to detect arthropod prey. Molecular Ecology 18: 2532–2542. Cleary, D.F.R., Fauvelot, C., Genner, M.J., Menken, S.B.J., and Mooers, A.O. 2006. Parallel responses of species and genetic diversity to ENSO-induced environmental destruction. Ecology Letters 9: 304–310. Cleary, D.F.R., Mooers, A.O., Eichhorn, K.A.O., van Tol, J., de Jong, R. and Menken, S.B.J. 2004. Diversity and community composition of butterflies and odonates in an ENSO-induced fire affected habitat mosaic: a case study from East Kalimantan, Indonesia. Oikos 105: 426–446. Coates, K.D., Banner, A., Steventon, J.D., LePage, P., and Bartemucci, P. 1997. The Date Creek Silvicultural Systems Study in the Interior Cedar-Hemlock Forests of Northwestern British Columbia: Overview and Treatment Summaries. BC Ministry of Forest and Range Report. 129 p. Available online at http://www.for.gov.bc.ca/hfd/pubs/docs/Lmh/Lmh38.pdf  187  Coddington, J.A., Young, L.H. and Coyle, F.A. 1996. Estimating spider species richness in a southern Appalachian cove hardwood forest. Journal of Arachnology 24: 111–128. Colwell, R.K. 2006. EstimateS: Statistical estimation of species richness and shared species from samples. Available at http://viceroy.eeb.uconn.edu/estimates. Colwell, R.K., Mao, C.X, and Chang, J. 2004. Interpolating, extrapolating, and comparing incidence-based species accumulation curves. Ecology 85: 2717–2727. Condit, R., Pitman, N., Leigh, E.G. Jr., Chave, J., Terborgh, J., Foster, R.B., Núòez, P.V., Aguillar, S., Valencia, R., Villa, G., Muller-Landau, H.C., Losos, E. and Hubbell, S.P. 2002. Beta-diversity in tropical forest trees. Science 295: 666–669. Connell, J.H. 1978. Diversity in tropical rain forests and coral reefs – high diversity of trees and corals is maintained only in a non-equilibrium state. Science 199: 1302–1310. Costa, F.O. and Carvalho, G.R. 2010. New insights into molecular evolution: prospects from the Barcode of Life Initiative (BOLI). Theory Biosci. 129: 149–157. Covell, C.V. Jr 1970. A revision of the North American species of the genus Scopula (Lepidoptera, Geometridae). Transactions of the American Entomological Society 96: 101–221. Covell, C.V. Jr., Ferguson, D.C., and Straley, G.B. 1986. Ennomos alniaria (Lepidoptera: Geometridae), a European moth recently discovered in British Columbia. Can. Ent. 118:499–501. Craft, K.J., Pauls, S.U., Darrow, K., Miller, S.E., Hebert, P.D.N., Helgen, L.E., Novotny, V., and Weiblen, G.D. 2010. Population genetics of ecological communities with DNA barcodes: An example from New Guinea Lepidoptera. Proceedings of the National Academy of Sciences 107: 5041– 5046. Culverhouse, P.F., Williams, R., Reguera, B., Herry, V., and González-Gil, S. 2003. Do experts make mistakes? Mar. Ecol. Prog. Ser. 247: 17-25. Cywinska, A., Hunter, F.F., and Hebert, P.D.N. 2006. Identifying Canadian mosquito species through DNA barcodes. Medical and Veterinary Entomology 20: 413–424. Daily, G. 1997. Nature's Services: societal dependence on natural ecosystems. Washington (DC): Island Press.  188  Daly, D., Waltham, K., Mulley, J., Watts, P.C., Rosin, A., Kemp, S.J., and Saccheri, I.J. 2004. Trinucleotide microsatellite loci for the peppered moth (Biston betularia). Molecular Ecology Notes 4: 179-181. Danks, H.V., Downes, J.A., Larson, D.J. and Scudder, G.G.E. 1997. Insects of the Yukon: characteristics and history. In Insects of the Yukon (Eds: H.V. Danks and J.A. Downes; Biological Survey of Canada (Terrestrial Arthropods), Ottawa). Pp. 963–1013. de Queiroz, A., and Gatesy J. 2007. The supermatrix approach to systematics. Trends Ecol. Evol. 22: 34–41. deWaard J.R., Landry, J.-F., Schmidt, B.C., Derhousoff, J., McLean, J.A., 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. deWaard, J.R., Ivanova, N.V, Hajibabaei, M. and Hebert, P.D.N. 2008a. Assembling DNA barcodes: analytical protocols. In: Martin C. (ed), Methods in Molecular Biology: Environmental Genetics. Humana Press Inc., Totowa, USA, pp. 275–293. deWaard, J.R., Schmidt, B.C., Anweiler, G.G. and Humble, L.M. 2008b. First Canadian records of Lampropteryx suffumata ([Denis & Schiffermüller], 1775) (Geometridae: Larentiinae). Journal of the Entomological Society of British Columbia 105: 19–25. Doak, P. 2000. Population consequences of restricted dispersal for an insect herbivore in a subdivided habitat. Ecology 81: 1828–1841. Doğanlar, M. and Beirne, B.P. 1978. Fruit tree leafrollers (Lepidoptera) and parasites (Hymenoptera) introduced in the Vancouver district, British Columbia, Canada. Journal of the Entomological Society of British Columbia 75: 23–24. Doğanlar, M. and Beirne, B.P. 1979. Hemithea aestivaria, a geometrid new to North America, established in British Columbia (Lepidoptera: Geometridae: Geometrinae). Can. Ent. 11:1121-1126. Drever, M.C., and K. Martin. 2010. Response of woodpeckers to changes in forest health and harvest: implications for conservation of avian biodiversity. Forest Ecology Management 259: 958-966. Drummond, A.J. and Rambaut, A. 2007. BEAST V1.4.5 (and Associated Programs). Available from URL: http://beast.bio.edsac.uk/Main_Page. Drummond, A.J., Ho, S.Y.W., Phillips, M.J., and Rambaut, A. 2006. Relaxed phylogenetics and dating with confidence. PLoS Biology 4:699-710.  189  Duncan, R.W. 2006. Conifer Defoliators of British Columbia. Natural Resources Canada. Canadian Forest Service, Pacific Forestry Centre. Victoria, BC. 359 pp. Dyer, L.A., Singer, M.S., Lill, J.T., Stireman, J.O., Gentry, G.L., Marquis, R.J., Ricklefs, R.E., Greeney, H.F., Wagner, D.L., Morais, H.C., Diniz, I.R., Kursar, T.A., and Coley, P.D. 2007. Host specificity of Lepidoptera in tropical and temperate forests. Nature 448: 696–700. Eaton, M.J., Meyers, G.L., Kolokotronis, S.-O., Leslie, M.S., Martin, A.P., and Amato, G. 2010. Barcoding bushmeat: molecular identification of Central African and South American harvested vertebrates. Conservation Genetics 11: 1389–1404. Elias-Gutierrez, M., and Valdez-Moreno, M. 2008. A new cryptic species of Leberis Smirnov, 1989 (Crustacea, Cladocera, Chydoridae) from the Mexican semi-desert region, highlighted by DNA barcoding. Hidrobiologica 18: 63–74. Evanno, G., Castella, E., Antoine, C., Paillat, G., and Goudet J. 2009. Parallel changes in genetic diversity and species diversity following a natural disturbance. Molecular Ecology 18: 1137–1144. Evans, D.E. 1960. A revision of the genus Enypia (Lepidoptera: Geometridae). Annals of the Entomological Society of America 53: 560–574. Faith, D.P. 1992. Conservation evaluation and phylogenetic diversity. Biological Conservation 61: 1–10. Faith, D.P. and Baker, A. 2006. Phylogenetic diversity (PD) and biodiversity conservation: some bioinformatics challenges. Evolutionary Bioinformatics 2: 121–128. Fang, Q., Cho, S., Regier, J., Mitter, C., Matthews, M., Poole, R., Friedlander, T., and Zhao, S. 1997. A new nuclear gene for insect phylogenetics: Dopa decarboxylase is informative of relationships within Heliothinae (Lepidoptera: Noctuidae). Systematic Biology 46: 269–283. Farrell, B.D., Sequeira, A.S., O'Meara, B., Normark, B.B., Chung, J.H., and Jordal, B.H. 2001.The evolution of agriculture in beetles (Curculionidae: Scolytinae and Platypodinae). Evolution 55: 2011–2027. Feldman, R.M. and Manning, R.B. 1992. Crisis in systematic biology in the ‘‘Age of Biodiversity.’’ J. Paleontol. 66: 157–158. Ferguson, D.C. 1983. Geometridae. In: Hodges, R.W., Dominick, T., Davis, D.R., Ferguson, D.C., Franclemont, J.G., Munroe, E.G., and Powell, J.A. (Eds) Check list of the Lepidoptera of America north of Mexico. E.W. Classey Ltd. and Wedge Entomological Research Foundation, London, UK, 88–107.  190  Ferguson, D.C. 1985. Geometroidea: Geometridae: Geometrinae. Fasc. 18.1. In: Dominick, R.B., Ferguson, D.C., Franclemont, J.G., Hodges, R.W., Munroe, E.G. (Eds) The moths of America north of Mexico. Wedge Entomological Research Foundation, Washington, D.C., 131 pp. Ferguson, D.C. 1993. A revision of the species of Nematocampa (Geometridae: Ennominae) occurring in the United States and Canada. Journal of the Lepidopterists’ Society 47: 60–77. Ferguson, D.C. 2008. Geometroidea: Geometridae (part): Ennominae (part) — Abraxini, Cassymini, Macariini. Fasc. 17.2. In The Moths of America North of Mexico. (Eds: Dominick, R.B., Ferguson, D.C., Franclemont, J.G., Hodges, R.W., Munroe, E.G.; Wedge Entomological Research Foundation, Washington, D.C.). 576 pp. Ferguson, D.C. and Mello, M.J. 1996. The introduction and spread of Chloroclystis rectangulata (L.) (Geometridae), and its first reported occurrences in the United States. J. Lepid. Soc. 50: 145-148. Ferrier, S., Powell, G.V.N., Richardson, K.S., Manion, G., Overton, J.M., Allnutt, T.F., Cameron, S.E., Mantle, K., Burgess, N.D., Faith, D.P., Lamoreux, J.F., Kier, G., Hijmans, R.J., Funk, V.A., Cassis, G.A., Fischer, B.L., Flemons, P., Lees, D., Lovett, J.C. and Van Rompaey, R.S. 2004. Mapping more of terrestrial biodiversity for global conservation assessment. Bioscience 54: 1101–1109. Ferris, C.D. and Schmidt, B.C. 2010. Revision of the North American genera Tetracis Guenée and synonymization of Synaxis Hulst with descriptions of three new species (Lepidoptera: Geometridae: Ennominae). Zootaxa 2347: 1–36. Fisher, A.I., Shepard, J.H. and Guppy, C.S. 2000. Macrolepidoptera Inventory of the Chilcotin District. Unpublished report. 24 pp. Fletcher, D.S. 1954. A revision of the genus Eubaphe (Lepidoptera: Geometridae). Zoologica 39: 153–166. Floyd, R., Lima, J., deWaard, J.R., Humble, L.R. and Hanner, R.H. 2010. Common goals: incorporating DNA barcoding into international protocols for identification of arthropod pests. Biological Invasions 12: 2947–2954. Floyd, R., Wilson, J.J., and Hebert, P.D.N. 2009. DNA barcodes and insect biodiversity. In: Footit, R.G. and Adler, P.H. (Eds) Insect Biodiversity: Science and Society. Blackwell Publishing, Oxford, 417–431. Food and Agriculture Organization (FAO) 2006. International Standards for Phytosanitary Measures No. 27, Diagnostic protocols for regulated pests. 11 pp.  191  Foottit, R.G., Maw, H.E.L., von Dohlen, C.D., and Hebert, P.D.N. 2008. Species identification of aphids (Insecta: Hemiptera: Aphididae) through DNA barcodes. Molecular Ecology Resources 8: 1189–1201. Ford, W.M., Odom, R.H., Hale, P.E., and Chapman, B.R. 2000. Stand-age, stand characteristics, and landform effects on understory herbaceous communities in southern Appalachian cove-hardwoods. Forest Ecology and Management 93: 237–246. Forest, F., Grenyer, R., Rouget, M., Davies, T.J., Cowling, R.M., Faith, D.P., Balmford, A., Manning, J.C., Proches, S., van der Bank, M., Reeves, G., Hedderson, T.A.J., and Savolainen, V. 2007. Preserving the evolutionary potential of floras in biodiversity hotspots. Nature 445: 757–760. Franklin, J.F., Spies, T.A., Van Pelt, R., Carey, A.B., Thornburgh, D.A., Berg, D.R., Lindenmayer, D.B., Harmon, M.E., Keeton, W.S., Shaw, D.C., Bible, K., and Chen, J.Q. 2002. Disturbances and structural development of natural forest ecosystems with silvicultural implications, using Douglas-fir forests as an example. For. Ecol. Manage. 155: 399–423. Frezal, L. and Leblois, R. 2008. Four years of DNA barcoding: current advances and prospects. Infect Genet Evol 8: 727–736. Gadagkar, R., Chandrashekara, K., and Nair, P. 1990. Insect species diversity in the tropics: sampling methods and a case study. Journal of the Bombay Natural History Society 87: 337–353. Garner, K. and Slavicek, J.M. 1996. Identification and characterization of a RAPD-PCR marker for distinguishing Asian and North American gypsy moths. Insect Molecular Biology 5: 81–91. Gaston, K.J. and Fuller, R.A. 2007. Biodiversity and extinction: losing the common and the widespread. Progress in Physical Geography 31: 213– 225. Ghalambor, C.K., Huey, R.B., Martin, P.R., Tewksbury, J.J. and Wang, G. 2006. Are mountain passes higher in the tropics? Janzen’s hypothesis revisited. Integr. Comp. Biol. 46: 5–17. Gibbs, J. 2009. Integrative taxonomy identifies new (and old) species in the Lasioglossum (Dialictus) tegulare (Robertson) species group (Hymenoptera, Halictidae). Zootaxa 2032: 1–38. Gilligan, T.M., and Epstein, M.E. 2009. LBAM ID, Tools for diagnosing light brown apple moth and related western U. S. leafrollers (Tortricidae: Archipini). Colorado State Univeristy, California Department of Food and Agriculture, and Center for Plant Health Science and Technology, USDA, APHIS, PPQ.  192  Godfray, H.C.J. 2002. Challenges for taxonomy. Nature 417: 17–19. Gotelli, N.J. 2004. A taxonomic wish-list for community ecology. Transactions of the Royal Society of London B 359: 585–597. Gotelli, N, and Colwell, R.K. 2001. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecology Letters, 4: 379–391. Grant, J.B. and Bogdanowicz, S.M. 2006. Isolation and characterization of microsatellite markers from the panic moth, Saucrobotys futilalis L. (Lepidoptera: Pyralidae: Pyraustinae). Molecular Ecology Notes 6: 353– 355. Grimble, D.G, Beckwith, R.C., and Hammond, P.C. 1992. A survey of the Lepidoptera fauna from the Blue Mountains of eastern Oregon. Journal of Research on the Lepidoptera 31: 83–102. Gurevitch, J. and Padilla, D.K. 2004. Are invasive species a major cause of extinctions? Trends in Ecology and Evolution 19: 470–474. Haack, R.A. 2006. Exotic bark- and wood-boring Coleoptera in the United States: recent establishments and interceptions. Canadian Journal of Forest Research 36: 269–288. Hajibabaei, M., deWaard, J.R., Ivanova, N.V., Ratnasingham, S., Dooh, R., Kirk, S.L., Mackie, P.M. and Hebert, P.D.N. 2005. Critical factors for the high volume assembly of DNA barcodes. Philosophical Transactions of the Royal Society B 360: 1959–1967. Hajibabaei, M., Janzen, D.H., Burns, J.M., Hallwachs, W. and Hebert, P.D.N. 2006a. DNA barcodes distinguish species of tropical Lepidoptera. Proceedings of the National Academy of Sciences of the United States of America 103: 968–971. Hajibabaei, M., Singer, G.A., Clare, E.L. and Hebert P.D.N. 2007. Design and applicability of DNA arrays and DNA barcodes in biodiversity monitoring. BMC Biology 5: 24. Hajibabaei, M., Smith, M.A., Janzen, D.H, Rodriguez, J.J., Whitfield, J.B. and Hebert, P.D.N. 2006b. A minimalist barcode can identify a specimen whose DNA is degraded. Molecular Ecology Notes 6: 959–964. Hamer, K.C., Hill, J.K., Lace, L.A., and Langan, A.M. 1997. Ecological and biogeographical effects of forest disturbance on tropical butterflies of Sumba, Indonesia. Journal of Biogeography 24: 67–75. Hanner, R.H. and Gregory, T.R. 2007. Genomic diversity research and the role of biorepositories. Cell Preservation Technology 5: 93–103.  193  Hausmann, A., Hebert, P.D.N., Mitchell, A., Rougerie, R., Sommerer, M., and Young, C.J. 2009. Revision of the Australian Oenochroma vinaria Guenée, 1858 species-complex (Lepidoptera: Geometridae, Oenochrominae): DNA barcoding reveals cryptic diversity and assesses status of type specimen without dissection. Zootaxa 2239: 1–21. He, T.H., Lamont, B.B., Krauss, S.L., Enright, N.J., and Miller, B.P. 2008. Covariation between intraspecific genetic diversity and species diversity within a plant functional group. Journal of Ecology 96: 956–961. Hebert, P.D.N., Cywinska, A., Ball, S.L. and deWaard, J.R. 2003a. Biological identifications through DNA barcodes. Proceedings of the Royal Society of London B 270: 313–321. Hebert, P.D.N., deWaard, J.R., and Landry, J.-F. 2010. DNA barcodes for 1/1000 of the animal kingdom. Biology Letters 6: 359–362. Hebert, P.D.N., Penton, E.H., Burns, J.M., Janzen, D.H. and Hallwachs, W. 2004. Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator. Proceedings of the National Academy of Sciences of the United States of America 101: 14812– 14817. Hebert, P.D.N., Ratnasingham, S., and deWaard, J.R. 2003b. Barcoding animal life: Cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society of London. Series B. 270: S596– S599. Heinrich, C. 1956. American moths of the subfamily Phycitinae. Bulletin of the United States National Museum 207: 1–581. Henegariu, O., Heerema, N.A., Dlouhy, S.R., Vance, G.H., and Vogt, P.H. 1997. Multiplex PCR: Critical parameters and step-by-step protocol. Biotechniques 23: 504–511. Hogg, I.D. and Hebert, P.D.N. 2004. Biological identification of springtails (Hexapoda, Collembola) from the Canadian Arctic, using mitochondrial DNA barcodes. Canadian Journal of Zoology 82: 749–754. Holloway, J.D. 1980. Insect surveys - an approach to environmental monitoring. Atti XII Congresio Nazionale Italiana Entomologia, Roma. pp. 239–261. Holloway, J.D. 1985. Moths as indicator organisms for categorizing rainforest and monitoring changes and regeneration processes. In: Pullin, A. (Ed.), Tropical Rainforest: the Leeds Symposium. Leeds Symposium, London, pp. 235–242. Holloway, J.D. 1997. The Moths of Borneo. Part 10: Geometridae, Sterrhinae, Larentiinae. Malayan Nat. J. 51: 1–242.  194  Hooper, D.U., Chapin, F.S., III, Ewel, J.J., Hector, A., Inchausti, P., Lavorel, S., Lawton, J.H., Lodge, D.M., Loreau, M., Naeem, S., Schmid, B., Setala, H., Symstad, A.J., Vandermeer, J., and Wardle, D.A. 2005. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecological Monographs 75: 3–35. Howard, P.C., Viskanic, P., Davenport, T.R.B., Kigenyi, F.W., Baltzer, M., Dickinson, C.J., Lwanga, J.S., Matthews, R.A., and Balmford, A. 1998. Complementarity and the use of indicator groups for reserve selection in Uganda. Nature 394: 472–475. Hubert, N., Hanner, R., Holm, E., Mandrak, N.E., Taylor, E., Burridge, M., Watkinson, D., Dumont, P., Curry, A., Bentzen, P., Zhang, J., April, J. and Bernatchez, L. 2008. Identifying Canadian freshwater fishes through DNA barcodes. PLoS ONE 3: e2490. Hudson, M.E. 2008. Sequencing breakthroughs for genomic ecology and evolutionary biology. Mol Ecol Res 8: 3–17. Huemer, P. and Hausmann, A. 2009. A new expanded revision of the European high mountain Sciadia tenebraria species group (Lepidoptera, Geometridae). Zootaxa 2117: 1–30. Huggard, D.J. and Vyse, A. 2003. Site Preparation Alternatives in the Wet, Cold ESSF: Results from Sicamous Creek. BC Ministry of Forest and Range Report. Ext. Note 65. 10p. Available online at www.for.gov.bc.ca/hfd/pubs/docs/En/EN65.pdf. Humble, L. M., deWaard, J.R., and Quinn, M. 2009. Delayed recognition of the European poplar shoot borer, Gypsonoma aceriana (Duponchel) (Lepidoptera: Tortricidae) in Canada. Journal of the Entomological Society of BC 106: 61–70. Humble, L.M. and Allen, E.A. 2006. Forest biosecurity: alien invasive species and vectored organisms. Canadian Journal of Plant Pathology 28: S256–S269. Humphries, C.J., Williams, P.H., and Wright, R.I.V. 1995. Measuring biodiversity value for conservation. Annual Review of Ecology and Systematics. 26: 93– 111. Huson, D.H., Richter, D.C., Rausch, C., Dezulian, T., Franz, M. and Rupp, R. 2007. Dendroscope - An interactive viewer for large phylogenetic trees. BMC Bioinformatics 8: 460. Intachat, J., Holloway, J.D., and Speight, M.R. 1997. The effects of different forest management practices on geometrid moth populations and their diversity in peninsular Malaysia. Journal of Tropical Forest Science 9: 411– 430.  195  Ivanova, N.V., deWaard, J.R. and Hebert, P.D.N. 2006. An inexpensive, automation-friendly protocol for recovering high-quality DNA. Molecular Ecology Notes 6: 998–1002. Janzen, D.H., Hajibabaei, M., Burns, J.M., Hallwachs, W., Remigio, E. and Hebert, P.D.N. 2005. Wedding biodiversity inventory of a large and complex Lepidoptera fauna with DNA barcoding. Philosophical Transactions of the Royal Society B 360: 1835–1845. Jaspars, M. 1998. Tough time for taxonomy. Nature 394: 413. Karsholt, O. and Razowski J. 1996. The Lepidoptera of Europe. A distributional checklist. Apollo Books, Stenstrup, Denmark, 380 pp. Karsholt, O. and van Nieukerken, E.J. 2010. Fauna Europaea: Geometridae. Fauna Europaea version 2.2, Available online at http://www.faunaeur.org [accessed 24 August 2010]. Kawahara, A.Y., Mignault, A.A., Regier, J.C., Kitching, I.J. and Mitter, C. 2009. Phylogeny and biogeography of hawkmoths (Lepidoptera: Sphingidae): evidence from five nuclear genes. PLoS ONE 4: e5719. Kawakita, A., Takimura, A., Terachi, T. Sota, T. and Kato, M. 2004. Cospeciation analysis of an obligate pollination mutualism: Have Glochidion trees (Euphorbiaceae) and pollinating Epicephala moths (Gracillariidae) diversified in parallel? Evolution 58: 2201–2214. Keena, M.A., Cote, M.-J., Grinberg, P.S., and Wallner, W.E. 2008. World distribution of female flight and genetic variation in Lymantria dispar (Lepidoptera: Lymantriidae). Environmental Entomology 37: 636–649. Kerr, J.T. and Ostrovsky, M. 2003. From space to species: ecological applications for remote sensing. Trends in Ecology and Evolution 18: 299– 305. Kerr, K.C.R., Lijtmaer, D.A., Barreira, A.S., Hebert, P.D.N., and Tubaro, P.L. 2009. Probing evolutionary patterns in Neotropical birds through DNA barcodes. PLoS ONE 4: e4379. Kimmins, J.P, 1996. Forest Ecology, 2nd Edition. Upper Saddle River, PrenticeHall, Englewood Cliffs, NJ, 596 pp. Kimura, M. 1980. A simple method for estimating evolutionary rate of base substitution through comparative studies of nucleotide sequences. Journal of Molecular Evolution 16: 111–120. Kitching, R.L., Orr, A.G., Thalib, L., Mitchell, H., Hopkins, M.S., and Graham, A.W. 2000. Moth assemblages as indicators of environmental quality of Australian rain forest. J. Appl. Ecol. 37: 284–297.  196  Klenner, W. and Arsenault, A. 2009. Ponderosa pine mortality during a severe bark beetle (Coleoptera: Curculionidae, Scolytinae) outbreak in southern British Columbia and implications for wildlife habitat management. Forest Ecology and Management 258: S5–S14. Knowlton, N. and Weigt, L.A. 1998. New dates and new rates for divergence across the Isthmus of Panama. Proc R Soc Lond B 265: 2257−2263. Koshio, C., Tomishima, M., Shimizu, K., Kim, H.-S., and Takenaka, O. 2002. Microsatellites in the gypsy moth, Lymantria dispar L. (Lepidoptera: Lymantriidae). Applied Entomology and Zoology 37: 309–312. Krell, F.T. 2004. Parataxonomy vs. taxonomy in biodiversity studies - pitfalls and applicability of ‘morphospecies’ sorting. Biodiversity and Conservation 13: 795–812. Kristensen, N.P. 1999. (Ed): Handbuch der Zoologie, a Natural History of the Phyla of the Animal Kingdom, Vol. IV, Arthropoda: Insecta, Part 35, Lepidoptera, Moths and Butterflies, Vol. 1: Evolution, Systematics, and Biogeography Berlin & New York: Walter de Gruyter. Kristensen, N.P. and Skalski, A.W. 1999. Phylogeny and palaeontology. In Handbook of zoology, vol. IV, Arthropoda: Insecta, part 35, Lepidoptera, moths and butterflies, vol. 1 (ed. N.P. Kristensen), pp. 7 – 25. Berlin, Germany: Walter de Gruyter. Kuiken, C., Yusim, K., Boykin, L. and Richardson, R. 2005. The Los Alamos HCV sequence database. Bioinformatics 21: 379–384. Lafontaine J.D. and Troubridge J.T. 1998. Moths and Butterflies (Lepidoptera) in Smith, I.M., and Scudder, G.G.E., eds. Assessment of species diversity in the Montane Cordillera Ecozone. Burlington: Ecological Monitoring and Assessment Network, 1998. Lafontaine, J.D. 2004. Noctuoidea: Noctuidae (part), Noctuinae (part – Agrotini). In Hodges RW, ed. The moths of North America, fasc. 27.1. Washington, DC: Wedge Entomological Research Foundation 1–385. Lafontaine, J.D. and Schmidt, B.C. 2010. Annotated check list of the Noctuoidea (Insecta, Lepidoptera) of North America north of Mexico. ZooKeys 40: 1– 239. Lafontaine, J.D. and Troubridge, J.T. 2010. Two new species of the Euxoa westermanni species-group from Canada (Lepidoptera, Noctuidae, Noctuinae). ZooKeys 39: 255–262. Landry, J.-F. and Landry, B. 1994. A technique for setting and mounting Microlepidoptera. Journal of the Lepidopterists' Society 48: 205–227.  197  Lawton, J.H., Bignell, D.E., Bolton, B., Bloemers, G.F., Eggleton, P., Hammond, P.M., Hodda, M., Holt, R.D., Larsen, T.B., Mawdsley, N.A., Stork, N.E., Srivastava, D.S. and Watt, A.D. 1998. Biodiversity inventories, indicator taxa and effects of habitat modification in tropical forest. Nature 391: 72–76. Le Roux, J.J. and Wieczorek, A.M. 2009. Molecular systematics and population genetics of biological invasions: towards a better understanding of invasive species management. Annals of Applied Biology 154: 1–17. Leberg, P.L. 2002. Estimating allelic richness: effects of sample size and bottlenecks. Mol. Ecol. 11: 2445–2449. Lee, S.-M. and Chao, A. 1994. Estimating population size via sample coverage for closed capture-recapture models. Biometrics 50: 88–97. Liebhold, A., Mastro, V., and Schaefer, P.W. 1989. Learning from the legacy of Leopold Trouvelot. Bulletin of the Entomological Society of America 35: 20– 21. Liebhold, A.M., Macdonald, W.L., Bergdahl, D., and Mastro, V.C. 1995. Invasion by exotic forest pests: A threat to forest ecosystems. Forest Science Monographs 30. 49 p. Llewellyn Jones, J.R.J. 1951. An annotated check list of the macrolepidoptera of British Columbia. Entomological Society of British Columbia Occasional paper No. 1. 148 pp. Locke, S.A., McLaughlin, J.D., Dayanandan, S., and Marcogliese, D.J. 2010. Diversity and specificity in Diplostomum spp. metacercariae in freshwater fishes revealed by cytochrome c oxidase I and internal transcriber spacer sequences. International Journal of Parasitology 40: 333–343. Longino, J., Coddington, J.A. and Colwell, R.K. 2002. The ant fauna of a tropical rainforest: estimating species richness three different ways. Ecology 83: 689–702. Lou, M., and Golding, G.B. 2010. Assigning sequences to species in the absence of large interspecific differences. Molecular Phylogenetics and Evolution 56: 187–194. Lovett, G.M., Canham, C.D., Arthur, M.A., Weathers, K.C., and Fitzhugh, R.D. 2006. Forest ecosystem responses to exotic pests and pathogens in eastern North America. BioScience 56: 395–405. Lukhtanov, V., Sourakov, A., Zakharov, E.V., and Hebert, P.D.N. 2009. DNA barcoding Central Asian butterflies: increasing geographical dimension does not significantly reduce the success of species identification. Molecular Ecology Resources 9: 1302–1310.  198  MacArthur, R.H. and Wilson, E.O. 1967. The Theory of Island Biogeography. Princeton University Press, Princeton, NJ. Maclauchlan, L., Cleary, M., Rankin, L., Stock, A., Buxton, K., 2008. Overview of Forest Health in The Southern Interior Forest Region. BC Ministry of Forests and Range, Kamloops, BC. , In: http://www.for.gov.bc.ca/rsi/ForestHealth/overview_reports/Overview_2008. html. MacLeod, N., Benfield, M. and Culverhouse P. 2010. Time to automate identification. Nature 467: 154-155. Magurran, A.E. 2004. Measuring Biological Diversity (Oxford: Blackwell Science). Mao, C.X., Colwell, R.K. and Chang, J. 2005. Estimating the species accumulation curve using mixtures. Biometrics 61: 433–441. Marshall, I.B., Schut, P.H. 1999. A national ecological framework for Canada. Environment Canada, Ecosystems Science Directorate, and Agriculture and Agri-Food Canada, Research Branch, Ottawa, ON. Marshall, S.A., Anderson, R.S., Roughley, R.E., Behan-Pelletier, V. and Danks, H.V. 1994. Terrestrial arthropod biodiversity: planning a study and recommended sampling techniques. A brief. Bulletin of the Entomological Society of Canada 26 Supplement. 33 pp. Martin, K., Norris, A., and Drever, M., 2006. Effects of mountain pine beetle outbreaks on avian biodiversity in the British Columbia interior: Implications for critical habitat management. BC Journal of Ecosystems and Management 7: 10–24. McClay, A.S., Cole, D.E., Harris, P., and Richardson, C.J. 1995. Biological control of Leafy Spurge in Alberta: progress and prospects. Alberta Environmental Centre, Vegreville, AB, Report AECV95-R2, 63 pp. McDunnough, J.H. 1946. The species of the truncata group of the genus Dysstroma (Lepidoptera, Geometridae). The Canadian Entomologist 78: 71–78. McDunnough, J.H. 1949. Revision of the North American species of the genus Eupithecia (Lepidoptera, Geometridae). Bulletin of the American Museum of Natural History 93: 533-728. McDunnough, J. 1954. The species of the genus Hydriomena occurring in America north of Mexico (Lepidoptera: Geometridae) American Museum Novitates. No. 1592. 17 pp.  199  McFarland, N. 1963. The macroheterocera (Lepidoptera) of a mixed forest in western Oregon. Master’s Thesis (Unpublished). Dept. Entomol., Oregon St. Univ., Corvallis. 152 p. McGuffin, W.C. 1958. Larvae of the nearctic Larentiinae (Lepidoptera: Geometridae). Memoirs of the Entomological Society of Canada 8: 1–104. McGuffin, W.C. 1967. Guide to the Geometridae of Canada (Lepidoptera). I. Subfamily Sterrhinae. Memoirs of the Entomological Society of Canada 50: 1–67. McGuffin, W.C. 1972. Guide to the Geometridae of Canada (Lepidoptera). II. Subfamily Ennominae. 1. Memoirs of the Entomological Society of Canada 86: 1–159. McGuffin, W.C. 1977. Guide to the Geometridae of Canada (Lepidoptera). III. Subfamily Ennominae. 2. Memoirs of the Entomological Society of Canada 101: 1–191. McGuffin, W.C. 1981. Guide to the Geometridae of Canada (Lepidoptera). IV. Subfamily Ennominae. 3. Memoirs of the Entomological Society of Canada 117: 1–153. McGuffin, W.C. 1987. Guide to the Geometridae of Canada (Lepidoptera). V. Subfamily Ennominae. 4. Memoirs of the Entomological Society of Canada 138: 1–182. McGuffin, W.C. 1988. Guide to the Geometridae of Canada (Lepidoptera). III, IV, and V. Subfamilies Archiearinae, Oenochrominae, and Geometrinae. Memoirs of the Entomological Society of Canada 145: 1–56. McNeely, J.A., Miller, K.R., Reid, W.V.C. and Mittermeier, R.A. 1990. Conserving the World's Biological Diversity. IUCN/WRI/WWF/World Bank, Washington D.C. 193 pp. Meusnier, I., Singer, G., Landry, J.-F., Hickey, D., Hebert, P.D.N., and Hajibabaei, M. 2008. A universal DNA mini-barcode for biodiversity analysis. BMC Genomics 9: 214. Meyer, C.P. and Paulay, G. 2005. DNA barcoding: error rates based on comprehensive sampling. PLoS Biology 3: 2229–2238. Miller, M.A., Müller, G.C., Kravchenko, V.D., Junnila, A., Vernon, K.K., Matheson, C.D. and Hausmann, A. 2007. DNA-based identification of Lepidoptera larvae and plant meals from their gut content. Russian Entomological Journal 15: 427–432. Miller, S.E. 2007. DNA barcoding and the renaissance of taxonomy. Proceedings of the National Academy of Sciences of the United States of America 104: 4775–4776. 200  Minet, J. and Scoble, M.J. 1999. The drepanoid/geometroid assemblage. In Lepidoptera: Moths and Butterflies. 1. Evolution, Systematics, and Biogeography. Handbook of Zoology Vol. IV. Part 35 (Ed: Kristensen NP; De Gruyter, New York). Pp. 301–320. Ministry of Forests and Range [MOFR] 2009a. Biological Control Agent: Minoa murinata (Scop.). <http://www.for.gov.bc.ca/hfp/biocontrol/agents/Minoa_murinata.htm> Ministry of Forests and Range [MOFR] 2009b. Biological Control Agent: Aplocera plagiata L. <http://www.for.gov.bc.ca/hfp/biocontrol/agents/Aplocera_plagiata.htm> Mironov, V. 2003. Larentiinae II (Perizomini and Eupitheciini). [In:] A. Hausmann (ed.): The Geometrid Moths of Europe 4: 1–463. Mironov, V.G., Galsworthy, A.C. and Ratzel, U. 2008. A survey of the Eupithecia fauna (Lepidoptera, Geometridae) of the Western Himalayas: Part II. Transactions of the Lepidopterological Society of Japan 59: 117–143. Mitchell, A. 2008. DNA barcoding demystified. Australian Journal of Entomology 47: 169–173. Montgomery, S.L. 1982. Biogeography of the moth genus Eupithecia in Oceania and the evolution of ambush predation in Hawaiian caterpillars (Lepidoptera: Geometridae). Entomologia Generalis, 8, 27–34. Mooney, H.A. and Cleland, E.E. 2001. The evolutionary impact of invasive species. Proceedings of the National Academy of Sciences of the United States of America 98: 5446–5451. Moore, J. L., Balmford, A., Brooks, T., Burgess, N. D., Hansen, L. A., Rahbek, C. and Williams, P. H. 2003. Performance of sub-Saharan vertebrates as indicator groups for identifying priority areas for conservation. Conserv. Biol. 17: 207–218. Moritz, C. and Faith, D.P. 1998. Comparative phylogeography and the identification of genetically divergent areas for conservation. Molecular Ecology 7: 419–429. Moulton, J.K. and Wiegmann, B.M. 2003. Evolution and phylogenetic utility of CAD (rudimentary) among Mesozoic-aged eremoneuran Diptera (Insecta). Mol Phylogenet Evol 31:363–378. Munroe, E. 1963. The gilvarius group of Aspilates [sic: Aspitates] Treitschke (Lepidoptera: Geometridae). The Canadian Entomologist 95: 260–287. Mutanen, M., Wahlberg, N. and Kaila, L. 2010. Comprehensive gene and taxon coverage elucidates radiation patterns in moths and butterflies. Proc R Soc B, 277: 2839–2848. 201  Nadel, R.L., Slippers, B., Scholes, M.C., Lawson, S.A., Noack, A.E., Wilcken, C.F., Bouvet, J.P., and WIngfield, M.J. 2010. DNA bar-coding reveals source and patterns of Thaumastocoris peregrinus invasions in South Africa and South America. Biological Invasions 12: 1067–1077. Naeem, S. 2002. Ecosystem consequences of biodiversity loss: the evolution of a paradigm. Ecology 83: 1537–1552. Naeem, S., Chapin, F.S., Costanza, R., Ehrlich, P.R., Golley, F.B., Hooper, D.U., Lawton, J.H., O’Neill, R.V., Mooney, H.A., Sala, O.E., Symstad, A.J., and Tilman, D. 1999. Biodiversity and ecosystem functioning: maintaining natural life support processes. Issues in Ecology 4: 1–12. Nakamura, M. 2004. A morphological and phylogenetic study on the pupae of Geometridae (Insecta: Lepidoptera) from Japan. The Japan heterocerists’ society, Tokyo. Newman, D. and Pilson, D. 1997. Increased probability of extinction due to decreased genetic population size: experimental populations of Clarkia pulchella. Evolution 51: 354–362. Nieminen, M. 1986. Migration of a moth species in a network of small islands. Oecologia 108: 643–651. Norris, A. R. and Martin, K. 2008. Mountain pine beetle presence affects nest patch choice of red-breasted nuthatches. J. Wildlife Manage. 72: 733–737. Norris, A. R. and Martin, K. 2010. The perils of plasticity: dual resource pulses increase facilitation but destabilize populations of small-bodied cavitynesters. Oikos 119: 1126–1135. Noss, R.F. 1999. Assessing and monitoring forest biodiversity: a suggested framework and indicators. For. Ecol. Manag. 115: 135–146. Novotny, V., Miller, S.E., Hulcr, J., Drew, R.A.I., Basset, Y., Janda, M., Setliff, G.P., Darrow, K., Stewart, A. J.A., Auga, J., Isua, B., Molem, K., Manumbor, M., Tamtiai, E., Mogia, M. and Weiblen, G.D. 2007. Low beta diversity of herbivorous insects in tropical forests. Nature 448: 692–695. Odat, N., Hellwig, F.H., Jetschke, G. and Fischer, M. 2010. On the relationship between plant species diversity and genetic diversity of Plantago lanceolata (Plantaginaceae) within and between grassland communities. J Plant Ecol. In press. Oliver, C.D. 1981. Forest development in North America following major disturbances. For. Ecol. Manage. 3: 153–168. Orme, D., Freckleton, R., Gavin, T.G., and Thomas, P.T. 2008. CAIC: Comparative Analyses using Independent Contrasts. [http://r-forge.rproject.org/projects/caic/]. 202  Õunap, E. and Viidalepp, J. 2009. Description of Crypsiphona tasmanica sp. nov. (Lepidoptera: Geometridae: Geometrinae), with notes on limitations using DNA barcodes for delimiting species. Aust. J. Entomol. 48: 113–124. Õunap, E., Viidalepp, J., Saarma, U., 2008. Systematic position of Lythriini revised: transferred from Larentiinae to Sterrhinae (Lepidoptera, Geometridae). Zool. Scr. 4: 405–413. Packer, L., Gibbs, J., Sheffield, C.S. and Hanner, R. 2009. DNA barcoding and the mediocrity of morphology. Molecular Ecology Resources 9: 42–50. Padial, P.M., Miralles, A., De la Riva, I., and Vences, M. 2010. The integrative future of taxonomy. Frontiers in Zoology 7: 16. Paradis, E., Claude, J., and Strimmer, K. 2004. APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics 20: 289–290. Parsons, G.L., Cassis, G., Moldenke, A.R., Lattin, J.D., Anderson, N.H., Miller, J.C., Hammond, P. and Schowalter, T.D. 1991. Invertebrates of the H.J. Andrews Experimental Forest, Western Cascade Range, Oregon. V: An annotated list of insects and other arthropods. PNW-GTR-290. Forest Service. U.S. Department of Agriculture, Washington, D.C. 168 p. Parsons, M.S., Scoble, M.J., Honey, M.R., Pitkin, L.M. and Pitkin, B.R. 1999. The Catalogue. In: Scoble, M. J., ed. Geometrid Moths of the World: a Catalogue (Lepidoptera, Geometridae). Collingwood: CSIRO Publishing, 1016 pp. Penev L., Erwin, T., Thompson, F.C., Sues, H.-D., Engel, M.S., Agosti, D., Pyle, R., Ivie, M., Assmann, T., Henry, T., Miller, J., Ananjeva, N.B., Casale, A., Lourenco, W., Golovatch, S., Fagerholm, H-P., Taiti, S., and AlonsoZarazaga, M. 2008. ZooKeys, unlocking Earth’s incredible biodiversity and building a sustainable bridge into the public domain: From “print- based” to “web-based” taxonomy, systematics, and natural history. ZooKeys 1: 1–7. Pérez-Losada, M. and Crandall, K. 2003. Can taxonomic richness be used as a surrogate for phylogenetic distinctness indices for ranking areas for conservation? Animal Biodiversity and Conservation 26: 77–84. Pfeifer, T.A., Humble, L.M., Ring, M., and Grigliatti, T.A. 1995. Characterization of gypsy moth populations and related species using a nuclear DNA marker. Canadian Entomology 127: 49–58. Pimentel, D., Zuniga, R., and Morrison, D. 2005. Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecological Economics 52: 273–288. Pogue, M.G. and Schaefer, P.W. 2007. A review of selected species of Lymantria (Hübner [1819]) (Lepidoptera: Noctuidae: Lymantriinae) from  203  subtropical and temperate regions of Asia including the description of three new species, some potentially invasive to North America. Publication FHTET-2006–2007, United States Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team, Fort Collins, Colorado. Pohl, G.R., Anweiler, G.G., Schmidt, B.C. and Kondla, N.G. 2010. An annotated list of the Lepidoptera of Alberta, Canada. ZooKeys 38: 1–549. Pojar, J., Klinka, K., and Meidinger, D.V. 1987. Biogeoclimatic classification in British Columbia. For. Ecol. Manage. 22: 119–154. Poole, R.W. 1987. A taxonomic revision of the New World moth genus Pero (Lepidoptera: Geometridae). United States Department of Agriculture, Agricultural Research Service, Technical Bulletin No. 1698, 257 pp. Posada, D. and Crandall, K.A. 1998. ModelTest: testing the model of DNA substitution. Bioinformatics 14: 817–818. Powell, J.A. and Opler, P.A. 2009. Moths of western North America. University of California Press, Berkeley, 369 pp. Prado, A., Hawkins, J. A., Yesson, C. and Bárcenas, R. T. 2010. Multiple diversity measures to identify complementary conservation areas for the Baja California peninsular cacti. Biological Conservation 143: 1510–1520. Prendergast, J.R., Quinn, R.M., Lawton, J.H., Eversham, B.C. and Gibbons, D.W. 1993. Rare species, the coincidence of diversity hotspots and conservation strategies. Nature 365: 335–337. R Development Core Team. 2008. R: A Language and Environment for Statistical Computing. [http://www.R-project.org]. R Foundation for Statistical Computing, Vienna, Austria. Ratnasingham, S. and Hebert, P.D.N. 2007. BOLD: The Barcode of Life Data System (http://www.barcodinglife.org). Molecular Ecology Notes 7: 355– 364. Raupach, M., Astrin, J.J. Hannig, K., Peters, M.K., Stoeckle, M.Y. and Wägele, J.-W. 2010. Molecular species identification of Central European ground beetles (Coleoptera: Carabidae) using nuclear rDNA expansion segments and DNA barcodes. Frontiers in Zoology 7:26. Razowski, J. 2002. Tortricidae (Lepidoptera) of Europe. Volume 1. Tortricinae and Chlidanotinae. Frantisek Slamka Publisher, Bratislava, 247 pp. Reed, R. D. and Sperling F.A.H. 1999. Interaction of process partitions in phylogenetic analysis: An example from the swallowtail butterfly genus Papilio. Mol. Biol. Evol. 16: 286–297.  204  Regier, J.C. 2008. Protocols, Concepts, and Reagents for preparing DNA sequencing templates. Version 12/4/08. www.umbi.umd.edu/users/jcrlab/PCR_primers.pdf Regier, J.C., Fang, Q.Q., Mitter, C., Peigler, R.S., Friedlander, T.P., Solis, M.A. 1998. Evolution and phylogenetic utility of the period gene in Lepidoptera. Mol Biol Evol 15:1172–1182. Regier, J.C., Zwick, A., Cummings, M.P., Kawahara, A.Y., Cho, S., Weller, S., Roe, A., Baixeras, J., Brown, J.W., Parr, C., Davis, D.R., Epstein, M., Hallwachs, W., Hausmann, A., Janzen, D.H., Kitching, I.J., Solis, M.A., Yen, S.-H., Bazinet, A.L., and Mitter, C. 2009. Toward reconstructing the evolution of advanced moths and butterflies (Lepidoptera: Ditrysia): an initial molecular study. BMC Evolutionary Biology 9: 280. Reineke, A. and Zebitz, C.W. 1999. Suitability of polymerase chain reactionbased approaches for identification of different gypsy moth (Lepidoptera: Lymantriidae) genotypes in central Europe. Annals of the Entomological Society of America 92: 737–741. Remigio, E. and Hebert, P.D.N. 2003. Testing the utility of partial COI sequences for phylogenetic estimates of gastropod relationships. Mol. Phylogenet. Evol. 29: 641–647. Rhode, K. 1992. Latitudinal gradients in species diversity: the search for the primary cause. Oikos 65: 514–527. Rindge, F.H. 1949. A revision of the geometrid moths formerly assigned to Drepanulatrix (Lepidoptera). Bulletin of the American Museum of Natural History 94: 231–298. Rindge, F.H. 1950. A revision of the geometrid genus Sericosema (Lepidoptera). American Museum Novitates 1468: 1–30. Rindge, F.H. 1955. A revision of some species of the genus Pero from the western United States (Lepidoptera; Geometridae). American Museum Novitates 1750: 1–33. Rindge, F.H. 1956. A revision of the American species of Deilinia (Lepidoptera: Geometridae). American Museum Novitates 1810: 1–31. Rindge, F.H. 1964. A revision of the genera Melanolophia, Pherotesia, and Melanotesia (Lepidoptera: Geometridae). Bulletin of the American Museum of Natural History 126: 241–434. Rindge, F.H. 1966. A revision of the moth genus Anacamptodes (Lepidoptera: Geometridae). Bulletin of the American Museum of Natural History 132: 175–244.  205  Rindge, F.H. 1967. The North American moths of the genus Earophila Gumppenberg (Lepidoptera: Geometridae). American Museum Novitates 2306: 1–12. Rindge, F.H. 1968. A revision of the moth genus Stenoporpia (Lepidoptera: Geometridae). Bulletin of the American Museum of Natural History 140: 65– 134. Rindge, F.H. 1974a. A revision of the moth genus Gabriola (Lepidoptera: Geometridae). American Museum Novitates 2550: 1–24. Rindge, F.H. 1974b. A revision of the moth genus Hesperumia (Lepidoptera: Geometridae). American Museum Novitates 2561: 1–24. Rindge, F.H. 1975. A revision of the new world Bistonini (Lepidoptera: Geometridae). Bulletin of the American Museum of Natural History 156: 69– 155. Rindge, F.H. 1976. A revision of the moth genus Plataea (Lepidoptera: Geometridae). American Museum Novitates 2595: 1–27. Rindge, F.H. 1978. A revision of the moth genus Xanthotype (Lepidoptera: Geometridae).American Museum Novitates 2659: 1–24. Rindge, F.H. 1979. A revision of the North American moths of the genus Lomographa (Lepidoptera: Geometridae). American Museum Novitates 2673: 1-18. Rindge, F.H. 1981. A revision of the moth genera Meris and Nemeris (Lepidoptera, Geometridae). American Museum Novitates 2710: 1-28. Rivera, J. and Currie, D.C. 2009. Identification of Nearctic black flies using DNA Barcodes (Diptera: Simuliidae). Molecular Ecology Resources, 9 (Suppl. 1): 224–236. Robinson, G.S. and Tuck, K.R. 1993. Diversity and faunistics of small moths (microlepidoptera) in Bornean rainforest. Ecological Entomology 18: 385– 393. Rodrigues, A. and Gaston, K. 2002. Maximizing phylogenetic diversity in the selection of networks of conservation areas. Biological Conservation 105: 103–111. Rodríguez-Castañeda, G., Dyer, L.A., Brehm, G., Connahs, H., Forkner, R.E., Walla, T.R. 2010. Tropical forests are not flat: how mountains affect herbivore diversity. Ecology Letters. In press. Roe, A.D. and Sperling, F.A. 2007. Patterns of evolution of mitochondrial cytochrome c oxidase I and II DNA and implications for DNA barcoding. Mol Phylogenet Evol 44: 325–345.  206  Roques, A., Auger-Rozenberg, M.A. and Boivin, S. 2006. A lack of native congeners may limit colonization of introduced conifers by indigenous insects in Europe. Canadian Journal of Forest Research 36: 299–313. Ross, M.G. 2005. Response to a gypsy moth incursion within New Zealand. Wellington, New Zealand: Ministry of Agriculture and Forestry. Rougerie, R., Smith, M.A., Fernandez-Triana, J., Lopez-Vaamonde, C., Ratnasingham, S. and Hebert, P.D.N. Molecular Analysis of Parasitoid Linkages (MAPL): gut contents of adult parasitoid wasps reveal larval host. Submitted. Rutschmann, F. 2006. Molecular dating of phylogenetic trees: a brief review of current methods that estimate divergence times. Divers Distribut 12: 35–48. Safranyik, L., Shrimpton, D.M., and Whitney H.S., 1974. Management of lodgepole pine to reduce losses from the mountain pine beetle. Forestry Technical Report 1. Canadian Forest Service, Pacific Forestry Centre. Victoria, BC. Saitou, N, and Nei, M. 1987. The neighbour-joining method: a new method for reconstructing evolutionary trees. Molecular Biology and Evolution 4: 406– 425. Samyn, Y. and Massin, C. 2002. Taxonomists’ requiem? Science 295: 276–277. Sato, R. and Kameda, M. 1997. Discovery of Lampropteryx suffumata (Denis & Schiffermüller) (Geometridae: Larentiinae) from Hokkaido, Japan. Yugato 148: 33–37. Saux, C., Fisher, B.L., and Spicer, G.S. 2004. Dracula ant phylogeny as inferred by nuclear 28S rDNA sequences and implications for ant systematics (Hymenoptera: Formicidae: Amblyoponinae). Molecular Phylogenetics and Evolution 33: 457–468. Savolainen, V., Cowan, R.S., Vogler, A.P., Roderick, G.K. and Lane, R. 2005. Towards writing the encyclopedia of life: an introduction to DNA barcoding. Philosophical Transactions of the Royal Society B 360: 1805–1811. Scheffer, S.J., Lewis, M.L., and Joshi, R.C. 2006. DNA barcoding applied to invasive leafminers (Diptera: Agromyzidae) in the Philippines. Annals of the Entomological Society of America 99: 204–210. Schmidt, B.C and Roland, J. 2006. Moth diveristy in a fragmented habitat: Importance of functional groups and landscape scale in the boreal forest. Annals of the Entomological Society of America 99: 1110-1120. Schowalter, T.D. 1985. Adaptations of insects to disturbance. pp. 235–252, In: Pickett, S.T.A. and White. P.S. (Eds.) The Ecology of Natural Disturbance and Patch Dynamics. Academic Press, New York. 207  Scoble, M.J. 1992. The Lepidoptera. Form, Function and Diversity. Oxford University Press, Oxford, UK. Scoble, M.J. (Ed) 1999. Geometrid moths of the world: a catalogue (Lepidoptera: Geometridae). Natural History Museum, London, UK and CSIRO Publishers, Collingwood, Australia, 1016 pp. Scoble, M.J. and Hausmann A. [updated 2007]: Online list of valid and available names of the Geometridae of the World [http://www.lepbarcoding.org/geometridae/species_checklists.php] Sheffield, C.S., Hebert, P.D.N., Kevan, P. and Packer, L. 2009. DNA barcoding a regional bee (Hymenoptera: Apoidea) fauna and its potential for ecological studies. Molecular Ecology Resources 9: 196–207. Shokralla, S., Singer, G.A.C., and Hajibabaei, M. 2010. Direct PCR amplification and sequencing of specimens’ DNA from preservative ethanol. Biotechniques 48: 305–306. Siddall, M.E. and Budinoff, R.B. 2005. DNA-barcoding evidence for widespread introductions of a leech from the South American Helobdella triserialis complex. Conservation Genetics 6: 467–472. Sihvonen, P. 2005. Phylogeny and classification of the Scopulini moths (Lepidoptera: Geometridae, Sterrhinae). Zoological Journal of the Linnean Society 143: 473–530. Sihvonen, P. and Kaila, L. 2004. Phylogeny and tribal classification of Sterrhinae with emphasis on delimiting Scopulini (Lepidoptera: Geometridae). Systematic Entomology 29: 324–358. Simon, C. Frati, F., Beckenbach, A., Crespi, B., Liu, H. and Flook, P. 1994. Evolution, weighting, and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Ann. Entomol. Soc. Am. 87: 651–701. Simonsen, T.J., Brown, R.L. and Sperling, F.A.H. 2008. Tracing an invasion: phylogeography of Cactoblastis cactorum (Lepidoptera: Pyralidae) in the United States based on mitochondrial DNA. Annals of the Entomological Society of America 101: 899–905. Skou, P. 1986. The Geometroid Moths of North Europe (Lepidoptera: Drepanidae and Geometridae). Scandinavian Science Press. 348 pp. Smith, M.A. and Fisher, B.L. 2009. Invasions, DNA barcodes, and rapid biodiversity assessment using ants of Mauritius. Frontiers in Zoology 6: 31. Smith, M.A., Eveleigh, E.S., McCann, K.S. , McCarthy, P.C. and Van Rooyen, K.I. Barcoding a quantified food web: crypsis, concepts, ecology. Submitted. 208  Smith, M.A., Fernandez-Triana, J., Roughley, R., and Hebert, P.D.N. 2009. DNA barcode accumulation curves for understudied taxa and areas. Molecular Ecology Resources. 9s1: 208–216. Smith, M.A., Fisher, B.L., and Hebert, P.D.N. 2005. DNA barcoding for effective biodiversity assessment of a hyperdiverse arthropod group: the ants of Madagascar. Philosophical Transactions of the Royal Society B: Biological Science 360: 1825–1834. Smith, M.A., Rodriguez, J.J., Whitfield, J.B., Deans, A.R., Janzen, D.H., Hallwachs, W., and Hebert, P.D.N. 2008. Extreme diversity of tropical parasitoid wasps exposed by iterative integration of natural history, DNA barcoding, morphology, and collections. Proceedings of the National Academy of Sciences of the United States of America 105: 12359–12364. Smith, M.A., Woodley, N.E., Janzen, D.H., Hallwachs, W., and Hebert, P.D.N. 2006. DNA barcodes reveal cryptic host-specificity within the presumed polyphagous members of a genus of parasitoid flies (Diptera: Tachinidae). Proceedings of the National Academy of Sciences of the United States of America 103: 3657–3662. Snäll, N., Tammaru, T., Wahlberg, N., Viidalepp, J., Ruohomäki, K., Savontaus, M.L., Huoponen, K., 2007. Phylogenetic relationships of the tribe Operophterini (Lepidoptera, Geometridae): a case study of the evolution of female flightlessness. Biol. J. Linn. Soc. 92: 241–252. Sousa, W.P. 1984. The role of disturbance in natural communities. Annual Review of Ecology and Systematics 15: 353–391. Southwood, T.R.E., Brown, V.K. and Reader, T.C. 1979. The relationship of plant and insect diversities in succession. Biological Journal of the Linnean Society 12: 327–348. Spielman, D., Brook, B.W. and Frankham, R. 2004. Most species are not driven to extinction before genetic factors impact them. Proc. Natl. Acad. Sci. USA 101: 15261–15264. Spitzer, K., Jaros, J., Havelka, J., and Leps, J. 1997. Effect of small-scale disturbance on butterfly communities of an indochinese montane rainforest. Biological Conservation 80: 9–15. Stamatakis, A. 2006. RAxML-VI-HPC: Maximum Likelihood- based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22: 2688–2690. Stamatakis, A., Hoover, P. and Rougemont, J. 2008. A rapid bootstrap algorithm for the RAxML web-servers. Systematic Biology 75: 758–771.  209  Sterling, P.H. and Ashby, M. 2006. Dichelia histrionana (Frölich, 1828) (Lepidoptera: Tortricidae) new to the British Isles. Entomologist's Record and Journal of Variation 118: 19–22. Stone, E.W. 1995. The impact of a mountain pine beetle epidemic on wildlife habitat and communities in post-epidemic stands of a lodgepole pine forest in northern Utah. PhD thesis. Utah State University, Ann Arbor, Michigan. Stork, N.E. 1988. Insect diversity: facts, fiction, and speculation. Biological Journal of the Linnean Society 35: 321–337. Struck, T.H., Purschke, G., and Halanych, K.M. 2006. Phylogeny of Eunicida (Annelida) and exporing data congruence using a partition addition bootstrap alteration (PABA) approach. Systematic Biology 55: 1–20. Summerville, K.S. and Crist, T.O. 2002. Effects of timber harvest on forest Lepidoptera: community, guild, and species responses. Ecol. Appl. 12: 820– 835. Summerville, K.S. and Crist, T.O. 2005. Temporal scaling of species accumulation in forest Lepidoptera. Biodiversity and Conservation 14: 3393–3406. Summerville, K.S., Ritter, L.M., and Crist, T.O. 2004. Forest moth taxa as indicators of lepidopteran richness and habitat disturbance: a preliminary assessment. Biol Conserv 116: 9–18. Tamura, K., Dudley, J., Nei, M., and Kumar, S. 2007. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Molecular Biology and Evolution 24: 1596–1599. Taylor, S.W., Carroll, A.L., Alfaro, R.I. and Safranyik, L. 2006. In: The Mountain Pine Beetle: A Synthesis of Biology, Management and Impacts in Lodgepole Pine (eds Safranyik, L. and Wilson, B.) 67–94 (Natural Resources Canada, Canadian Forest Service, Victoria). Tilman, D. 2004. Niche tradeoffs, neutrality, and community structure: A stochastic theory of resource competition, invasion, and community assembly. Proceedings of the National Academy of Sciences of the United States of America 101: 10854–10861. Tomon, T.T. 2007. A revision of the genus Probole Herrich-Schäffer (Lepidoptera: Geometridae) [abstract]. Entomological Society of America, 2007 Annual Meeting, 9–12 December 2007, San Diego, CA. Entomological Society of America, Lanham, MD. (http://esa.confex.com/esa/2007/techprogram/paper_31679.htm)  210  Troubridge, J.T. 1997. Revision of the Nearctic species of the genus Entephria Hübner (Lepidoptera: Geometridae, Larentiinae). Entomologica Scandinavica 28: 121–139. Troubridge, J.T., and Fitzpatrick, S.M. 1993. A revision of the North American Operophtera (Lepidoptera: Geometridae). The Canadian Entomologist 125: 379–397. Usher, M.B., and Keiller, S.W.J. 1998. The macrolepidoptera of farm woodlands: determinants of diversity and community structure. Biodivers Conserv 7: 725–748. Van Sickle, A., Fiddick, R.L., and Wood, C.S. 2001. The forest insect and disease survey in the Pacific Region. Journal of the Entomological Society of British Columbia 98: 169–176. Vancouver Park Board 2007. Stanley Park Restoration Plan. 53p. Available at <www.vancouverparks.ca> Vellend, M. 2003. Island biogeography of genes and species. American Naturalist 162: 358–365. Vellend, M. 2004. Parallel effects of land-use history on species diversity and genetic diversity of forest herbs. Ecology 85: 3043–3055. Vellend, M. 2005. Species diversity and genetic diversity: parallel processes and correlated patterns. American Naturalist 166: 199–215. Viidalepp, J., Tammaru, T., Snäll, N., Ruohomäki, K., and Wahlberg, N., 2007. Cleorodes Warren, 1894 does not belong in the tribe Boarmiini (Lepidoptera: Geometridae). Eur. J. Entomol. 104: 303–309. Villesen, P. 2007. FaBox: an online toolbox for fasta sequences. Molecular Ecology Notes 7: 965–968. Vogler, A.P. and Monaghan, M.T. 2007. Recent advances in DNA taxonomy. Journal of Zoological Systematics and Evolutionary Research 45: 1–10. Wahlberg, N. and Wheat, C.W. 2008. Genomic outposts serve the phylogenomic pioneers: Designing novel nuclear markers for genomic DNA extractions of Lepidoptera. Systematic Biology 57: 231–242. Wahlberg, N., Snäll, N., Viidalepp, J., Ruohomäki, K., and Tammaru, T. 2010. The evolution of female flightlessness among Ennominae of the Holarctic forest zone (Lepidoptera, Geometridae). Molecular Phylogenetics and Evolution 55: 929–938. Wallner, W.E., Humble, L.M., Levin, R.E., Baranchikov, Y.N., and Carde, R.T. 1995. Response of adult lymantriid moths to illumination devices in the Russian Far East. Journal of Economic Entomology 88: 337–342.  211  Walpole, M.J. and Sheldon, I.R. 1999. Sampling butterflies in tropical rainforest: an evaluation of a transect walk method. Biol. Conserv. 87: 85–91. Waugh, J. 2007. DNA barcoding in animal species: progress, potential and pitfalls. Bioessays 29: 188–197. Webb, C.O. 2000. Exploring the phylogenetic structure of ecological communities: an example for rain forest trees. Amer Nat 156: 145–155. Webb, C.O., Losos, J.B. and Agrawal, A.A. 2006. Special feature: Integrating phylogenies into community ecology. Ecology 87: S1-S2. Weese, D.A. and Santos, S.R. 2009. Genetic identification of source populations for an aquarium-traded invertebrate. Animal Conservation 12: 13–19. Weigt, H.-J. 1993. Die Blütenspanner Mitteleuropas (Lepidoptera, Geometridae: Eupitheciini). Teil 5. - Dortmunder Beitrage zur Landeskunde 27: 5–108. Wheeler TA. 2003. The role of voucher specimens in validating faunistic and ecological research. Biological Survey of Canada (Terrestrial Arthropods) Document Series 9: 1-21. Wiegmann, B. M., Regier, J.C., Mitter, C., Friedlander, T.P., Wagner, D.L. and Nielsen, E.S. 2000. Nuclear genes resolve Mesozoic-aged divergences in the insect order Lepidoptera. Molecular Phylogenetics and Evolution 15: 242–259. Willott, S.J., Lim, D.C., Compton, S.G. and Sutton, S.L. 2000. Effects of selective logging on the butterflies of a Bornean rainforest. Conserv. Biol., 14: 1055– 1065. Wilson, A.D., and Schiff, N.M. 2010. Identification of Sirex noctilio and native North American woodwasp larvae using DNA barcodes. Journal of Entomology 7: 60–79. Wilson, E.O. 1988. Biodiversity. National Academy Press, Washington, DC. Wilson, J.J. 2010. Assessing the value of DNA barcodes and other priority gene regions for molecular phylogenetics of Lepidoptera. PLoS ONE 5: e10525. Witt, J.D.S., Threloff, D.L., and Hebert, P.D.N. 2006. DNA barcoding reveals extraordinary cryptic diversity in an amphipod genus: implications for desert spring conservation. Molecual Ecology 15: 3073–3082. Wong, E.H.K. and Hanner, R.H. 2008. DNA barcoding detects market substitution in North American seafood. Food Research International 41: 828–837.  212  Wortley, A., Rudall, P., Harris, D., and Scotland, R. 2005. How much data are needed to resolve a difficult phylogeny? Case study in Lamiales. Systematic Biology 54: 697–709. Yamamoto, S. and Sota, T. 2007. Phylogeny of the Geometridae and the evolution of winter moths inferred from a simultaneous analysis of mitochondrial and nuclear genes. Molecular Phylogenetics and Evolution 44: 711–723. Young, C.J. 2006. Molecular relationships of the Australian Ennominae (Lepidoptera: Geometridae) and implications for the phylogeny of the Geometridae from molecular data. Zootaxa 1264: 1–147. Young, C.J. 2008. Characterization of the Australian Nacophorini using adult morphology, and phylogeny of the Geometridae based on morphological characters. Zootaxa 1736: 1–141. Zahiri, R., Kitching, I.J., Lafontaine, J.D., Mutanen, M., Kaila, L., Holloway, J.D. and Wahlberg, N. A new molecular phylogeny offers hope for a stable family-level classification of the Noctuoidea (Insecta: Lepidoptera). Molecular Phylogenetics and Evolution. In press. Zhang, D.-X. 2004. Lepidopteran microsatellite DNA: redundant but promising. Trends in Ecology and Evolution 19: 507–509. Zhou, X., Adamowicz, S.J., Jacobus, L.M., DeWalt, R.E. and Hebert, P.D.N. 2009. Towards a comprehensive barcode library for Arctic life— Ephemeroptera, Plecoptera, and Trichoptera of Churchill, Manitoba, Canada. Frontiers in Zoology 6: 30. Zhou, Y.H., Gu, H.N. and Dorn, S. 2005. Isolation of microsatellite loci in the codling moth, Cydia pomonella (Lepidoptera: Tortricidae). Mol. Ecol. Notes 5: 226–227. Zwickl, D.J. 2006. Genetic algorithm approaches for the phylogenetic analysis of large biological sequence datasets under the maximum likelihood criterion. Ph.D. dissertation, The University of Texas at Austin.  213  Appendices  Appendix A: Supplementary material for Chapter 2. Revised species checklist of the looper moths (Geometridae) of British Columbia  This revised checklist for the Geometridae of British Columbia includes 349 species and incorporates recent changes in nomenclature and an improved overall understanding of the fauna. 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); 214  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  215  or removed from past checklists, b) undergone recent taxonomic changes, and c) introduced to BC.  Checklist Larentiinae  Cidariini 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22.  Dysstroma citrata (Linnaeus, 1761) Dysstroma sobria Swett, 1917 Dysstroma ochrofuscaria Ferguson, 1983 Dysstroma truncata (Hufnagel, 1767) Dysstroma walkerata (Pearsall, 1909) Dysstroma hersiliata (Guenée, [1858]) Dysstroma formosa (Hulst, 1896) Dysstroma colvillei Blackmore, 1926 Dysstroma brunneata (Packard, 1867) Dysstroma mancipata (Guenée, [1858]) Eulithis propulsata (Walker, 1862) Eulithis testata (Linnaeus, 1761) Eulithis destinata (Möschler, 1860) Eulithis flavibrunneata (McDunnough, 1943) Eulithis xylina (Hulst, 1896) Eurhinosea flavaria Packard, 1873 Antepirrhoe semiatrata (Hulst, 1881)7 Antepirrhoe fasciata Barnes & McDunnough, 1918 Antepirrhoe atrifasciata (Hulst, 1888) Ecliptopera silaceata ([Denis & Schiffermüller], 1775) Colostygia circumvallaria Hübner, [1799]8 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. 216  23. 24. 25. 26.  Thera juniperata (Linnaeus, 1758)9 Thera otisi (Dyar, 1904) Ceratodalia gueneata Packard, 1876 Lampropteryx suffumata ([Denis and Schiffermüller], 1775)10  Hydriomenini 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54.  Hydriomena exculpata Barnes & McDunnough, 1917 Hydriomena expurgata Barnes & McDunnough, 1918 Hydriomena irata Swett, 1910 Hydriomena perfracta Swett, 1910 Hydriomena marinata Barnes & McDunnough, 1917 Hydriomena edenata Swett, 1909 Hydriomena divisaria (Walker, 1860) Hydriomena renunciata (Walker, 1862) Hydriomena albimontanata McDunnough, 1939 Hydriomena nevadae Barnes & McDunnough, 1917 Hydriomena californiata Packard, 1871 Hydriomena crokeri Swett, 1910 Hydriomena ruberata (Freyer, [1831]) Hydriomena macdunnoughi Swett, 1918 Hydriomena furcata (Thunberg, 1784) Hydriomena quinquefasciata (Packard, 1871) Hydriomena albifasciata (Packard, 1874) Hydriomena speciosata (Packard, 1874) Hydriomena morosata Barnes and McDunnough, 191711 Hydriomena nubilofasciata (Packard, 1871) Hydriomena manzanita Taylor, 1906 Triphosa haesitata (Guenée, [1858]) Coryphista meadii (Packard, 1874) Rheumaptera undulata (Linnaeus, 1758) Rheumaptera hastata (Linnaeus, 1758) Rheumaptera subhastata (Nolcken, 1870) Entephria multivagata (Hulst, 1881) 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). 217  55. 56. 57. 58. 59. 60. 61. 62. 63. 64. 65. 66. 67.  Entephria lagganata (Taylor, 1908) Entephria kidluitata (Munroe, 1951) Mesoleuca ruficillata (Guenée, [1858]) Mesoleuca gratulata (Walker, 1862) Spargania magnoliata Guenée, [1858] Spargania luctuata ([Denis & Schiffermüller], 1775) Perizoma basaliata (Walker, 1862) Perizoma grandis (Hulst, 1896) Perizoma curvilinea (Hulst, 1896) Perizoma costiguttata (Hulst, 1896) Perizoma custodiata (Guenée, [1858]) Anticlea vasiliata Guenée, [1858] Anticlea multiferata (Walker, 1863)  Stamnodini 68. 69. 70. 71. 72.  Stamnodes blackmorei Swett, 1915 Stamnodes topazata (Strecker, 1899) Stamnoctenis morrisata (Hulst, 1887) Stamnoctenis pearsalli (Swett, 1914) Stamnodes marmorata (Packard, 1871)  Xanthorhoini 73. 74. 75. 76. 77. 78. 79. 80. 81. 82. 83. 84.  Xanthorhoe labradorensis (Packard, 1867) Xanthorhoe packardata McDunnough, 1945 Xanthorhoe abrasaria (Herrich-Schäffer, [1855]) Xanthorhoe iduata (Guenée, [1858]) Xanthorhoe macdunnoughi Swett, 1918 Xanthorhoe ramaria Swett & Cassino, 1920 Xanthorhoe lagganata Swett & Cassino, 192012 Xanthorhoe baffinensis McDunnough, 1939 Xanthorhoe dodata Swett & Cassino, 1920 Xanthorhoe pontiaria Taylor, 1906 Xanthorhoe fossaria Taylor, 1906 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. 218  85. 86. 87. 88. 89. 90. 91. 92. 93. 94. 95. 96. 97. 98. 99. 100.  Xanthorhoe alticolata Barnes & McDunnough, 1916 Xanthorhoe defensaria (Guenée, [1858]) Xanthorhoe ferrugata (Clerck, 1759) Xanthorhoe borealis Hulst, 1896 Xanthorhoe lacustrata (Guenée, [1858]) Xanthorhoe clarkeata Ferguson, 1987 Epirrhoe alternata (Müller, 1764) Epirrhoe plebeculata (Guenée, [1858]) Epirrhoe sperryi Herbulot, 1951 Euphyia intermediata (Guenée, [1858]) Enchoria lacteata (Packard, 1876) Zenophleps lignicolorata (Packard, 1874) Zenophleps alpinata Cassino, 1927 Psychophora phocata (Möschler, 1862) Psychophora suttoni Heinrich, 194213 Costaconvexa centrostrigaria (Wollaston, 1858)  Asthenini 101. 102. 103. 104. 105. 106. 107. 108.  Hydrelia albifera (Walker, 1866) Hydrelia brunneifasciata (Packard, 1876) Venusia cambrica Curtis, 1839 Venusia duodecemlineata (Packard, 1873) Venusia obsoleta (Swett, 1916) Venusia pearsalli (Dyar, 1906) Trichodezia albovittata (Guenée, [1858]) [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 219  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. 118. 119. 120. 121. 122. 123. 124. 125. 126. 127. 128. 129. 130. 131. 132. 133. 134. 135. 136. 137. 138. 139. 140. 141. 142. 143. 144. 145.  Horisme intestinata (Guenée, [1858]) Horisme incana Swett, 1918 Eupithecia palpata Packard, 1873 Eupithecia lafontaineata Bolte, 1990 Eupithecia sharronata Bolte, 1990 Eupithecia ornata (Hulst, 1896) Eupithecia columbiata (Dyar, 1904) Eupithecia maestosa (Hulst, 1896) Eupithecia longipalpata Packard, 1876 Eupithecia placidata Taylor, 1908 Eupithecia unicolor (Hulst, 1896) Eupithecia pseudotsugata MacKay, 1951 Eupithecia misturata (Hulst, 1896) Eupithecia bryanti Taylor, 1906 Eupithecia regina Taylor, 1906 Eupithecia borealis (Hulst, 1898) Eupithecia subfuscata (Haworth, 1809) Eupithecia tripunctaria Herrich-Schäffer, 1852 Eupithecia lariciata (Freyer, 1841) Eupithecia harrisonata MacKay, 1951 Eupithecia casloata (Dyar, 1904) Eupithecia rotundopuncta Packard, 1871 Eupithecia intricata (Zetterstedt, [1839]) Eupithecia satyrata (Hübner, [1813]) Eupithecia nimbicolor (Hulst, 1896) Eupithecia assimilata Doubleday, 1856 Eupithecia absinthiata (Clerck, 1759) Eupithecia cretaceata (Packard, 1874) Eupithecia behrensata Packard, 1876  220  146. 147. 148. 149. 150. 151. 152. 153. 154. 155. 156. 157. 158. 159. 160. 161. 162. 163. 164. 165. 166. 167. 168. 169.  Eupithecia gelidata Möschler, 1860 Eupithecia multistrigata (Hulst, 1896) Eupithecia perfusca (Hulst, 1898) Eupithecia annulata (Hulst, 1896) Eupithecia olivacea Taylor, 1906 Eupithecia lachrymosa (Hulst, 1900) Eupithecia interruptofasciata Packard, 1873 Eupithecia niphadophilata (Dyar, 1904) Eupithecia pusillata (Denis & Schiffermüller, 1775)16 Eupithecia tenuata Hulst, 1880 Eupithecia agnesata Taylor, 1908 Eupithecia niveifascia (Hulst, 1898) Eupithecia johnstoni McDunnough, 194617 Eupithecia albicapitata Packard, 1876 Eupithecia mutata Pearsall, 1908 Eupithecia spermaphaga (Dyar, 1917) Eupithecia gilvipennata Cassino & Swett, 1922 Eupithecia anticaria Walker, 1862 Eupithecia graefii (Hulst, 1896) Eupithecia nevadata Packard, 1871 Eupithecia ravocostaliata Packard, 1876 Prorella leucata (Hulst, 1896) Prorella mellisa (Grossbeck, 1908) Pasiphila rectangulata (Linnaeus, 1758)18  Lobophorini 170. 171. 172. 173. 174. 175. 176.  Carsia sororiata (Hübner, [1813]) Aplocera plagiata (Linnaeus, 1758)19 Acasis viridata (Packard, 1873) Cladara limitaria (Walker, 1860) Cladara atroliturata (Walker, [1863]) Lobophora nivigerata Walker, 1862 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. 221  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. 186. 187. 188. 189. 190. 191. 192. 193. 194. 195.  Scopula ancellata (Hulst, 1887) Scopula fuscata (Hulst, 1887) Scopula junctaria (Walker, 1861) Scopula quinquelinearia (Packard, 1870)22 Scopula quadrilineata (Packard, 1876) Scopula frigidaria (Möschler, 1860) Scopula siccata McDunnough, 1939 Scopula septentrionicola McDunnough, 1939 Scopula inductata (Guenée, [1858])23 Scopula luteolata (Hulst, 1880) 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 222  196. Scopula sentinaria (Geyer, 1837) 197. Leptostales rubromarginaria (Packard, 1871) Geometrinae Nemoriini 198. 199. 200. 201. 202.  Chlorosea nevadaria Packard, 1873 Chlorosea banksaria Sperry, 1944 Nemoria unitaria (Packard, 1873) Nemoria darwiniata (Dyar, 1904) 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 223  210. Leucobrephos brephoides (Walker, 1857) Cassymini 211. Nematocampa resistaria (Herrich-Schäffer, [1856]) 212. Protitame subalbaria (Packard, 1873) 213. Protitame virginalis (Hulst, 1900) Macariini 214. 215. 216. 217. 218. 219. 220. 221. 222. 223. 224. 225. 226. 227. 228. 229. 230. 231.  Eumacaria madopata (Guenée, [1858])27 Speranza occiduaria (Packard, 1874)28 29 Speranza amboflava (Ferguson, 1953)30 Speranza brunneata (Thunberg, 1784) Speranza boreata Ferguson, 200831 Speranza quadrilinearia (Packard, 1873) Speranza loricaria (Eversmann, 1837) Speranza exauspicata Walker, 1861 Speranza plumosata (Barnes & McDunnough, 1917) Speranza bitactata (Walker, 1862) Speranza decorata (Hulst, 1896) Speranza colata (Grote, 1881) Epelis truncataria (Walker, 1862)32 Macaria lorquinaria (Guenée, [1858]) Macaria perplexata (Pearsall, 1913) Macaria atrimacularia Barnes & McDunnough, 1913 Macaria ulsterata (Pearsall, 1913) Macaria adonis Barnes & McDunnough, 1918  27  Formerly E. latiferrugata (Walker), Ferguson (2008) designated it a synonym. 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. 28  224  232. 233. 234. 235. 236. 237. 238. 239. 240. 241. 242. 243. 244. 245. 246. 247. 248. 249. 250.  Macaria masquerata Ferguson, 200833 Macaria sexmaculata Packard, 1867 Macaria submarmorata Walker, 1861 Macaria signaria (Hübner, [1809])34 Digrammia setonana (McDunnough, 1927) Digrammia curvata (Grote, 1880) Digrammia nubiculata (Packard, 1876) Digrammia denticulata (Grote, 1883) Digrammia delectata (Hulst, 1887) Digrammia ubiquitata Ferguson, 2008 Digrammia muscariata (Guenée, [1858]) Digrammia respersata (Hulst, 1880) Digrammia californiaria (Packard, 1871) Digrammia decorata (Grossbeck, 1907) Digrammia triviata (Barnes & McDunnough, 1917) Digrammia rippertaria (Duponchel, 1830) Digrammia irrorata (Packard, 1876) Digrammia neptaria (Guenée, [1858]) Digrammia subminiata (Packard, 1873)  Boarmiini 251. 252. 253. 254. 255. 256. 257. 258. 259. 260. 261. 262. 263. 264.  Dasyfidonia avuncularia (Guenée, [1858]) Orthofidonia exornata (Walker, 1862) Hesperumia sulphuraria Packard, 1873 Hesperumia latipennis (Hulst, 1896) Neoalcis californiaria (Packard, 1871) Glena nigricaria (Barnes & McDunnough, 1913) Stenoporpia pulmonaria (Grote, 1881) Stenoporpia separataria (Grote, 1883) Stenoporpia excelsaria (Strecker, 1899) Aethalura intertexta (Walker, 1860) Anavitrinelia addendaria (Grossbeck, 1908) Iridopsis clivinaria (Guenée, [1858]) Iridopsis larvaria (Guenée, [1858]) 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). 225  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. 272. 273. 274. 275. 276. 277.  Biston betularia (Linnaeus, 1758) Lycia ursaria (Walker, 1860) Lycia rachelae (Hulst, 1896) Hypagyrtis unipunctata (Haworth, 1809) Hypagyrtis piniata (Packard, 1870) Phigalia plumogeraria (Hulst, 1888) Erannis vancouverensis Hulst, 1896  Baptini 278. Lomographa semiclarata (Walker, 1866) Caberini 279. 280. 281. 282.  Sericosema juturnaria (Guenée, [1858]) Sericosema wilsonensis Cassino & Swett, 1922 Cabera exanthemata (Scopoli, 1763) 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). 226  283. 284. 285. 286. 287. 288. 289. 290. 291. 292. 293.  Cabera variolaria Guenée, [1858] Cabera borealis (Hulst, 1896) Eudrepanulatrix rectifascia (Hulst, 1896) Drepanulatrix unicalcararia (Guenée, [1858]) Drepanulatrix quadraria (Grote, 1882) Drepanulatrix foeminaria (Guenée, [1858]) Drepanulatrix carnearia (Hulst, 1888) Drepanulatrix falcataria (Packard, 1873) Drepanulatrix secundaria Barnes & McDunnough, 1916 Apodrepanulatrix litaria (Hulst, 1887) Ixala desperaria (Hulst, 1887)  Angeronini 294. 295. 296. 297. 298. 299. 300.  Aspitates aberrata (Edwards, 1884) Euchlaena johnsonaria (Fitch, 1869) Euchlaena madusaria (Walker, 1860) Euchlaena marginaria (Minot, 1869) Euchlaena tigrinaria (Guenée, [1858]) Xanthotype sospeta (Drury, 1773) Xanthotype urticaria Swett, 191836  Azelini 301. 302. 303. 304. 305.  Pero honestaria (Walker, 1860) Pero morrisonaria (Edwards, 1881) Pero mizon Rindge, 1955 Pero behrensaria (Packard, 1871) 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. 227  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. 316. 317. 318. 319. 320. 321. 322. 323.  Selenia alciphearia Walker, 1860 Selenia kentaria (Grote & Robinson, 1867) Metanema inatomaria Guenée, [1858] Metanema determinata Walker, 1866 Metarranthis duaria (Guenée, [1858]) Probole alienaria Herrich-Schäffer, [1855] Probole amicaria (Herrich-Schäffer, [1855]) Plagodis phlogosaria (Guenée, [1858]) Plagodis pulveraria (Linnaeus, 1758)  37  Introduced; first recorded in Vancouver, BC by Covell et al (1986). 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. 38  228  Ourapterygini 324. 325. 326. 327. 328. 329. 330. 331. 332. 333. 334. 335. 336. 337. 338. 339. 340. 341. 342. 343. 344. 345. 346. 347. 348. 349.  Neoterpes trianguliferata (Packard, 1871) Caripeta divisata Walker, [1863] Caripeta aequaliaria Grote, 1883 Caripeta angustiorata Walker, [1863] Caripeta sp. nr. aequaliaria39 Meris suffusaria McDunnough, 1940 Besma quercivoraria (Guenée, [1858]) Lambdina fiscellaria (Guenée, [1858]) Nepytia umbrosaria (Packard, 1873) Nepytia phantasmaria (Strecker, 1899) Nepytia freemani Munroe, 1963 Sicya macularia (Harris, 1850) Plataea trilinearia (Packard, 1873) Tetracis jubararia (Hulst, 1886)40 Tetracis pallulata (Hulst, 1887) Tetracis cervinaria (Packard, 1871) Tetracis formosa (Hulst, 1896) Tetracis pallidata Ferris, 200941 Tetracis cachexiata Guenée, [1858] Prochoerodes amplicineraria (Pearsall, 1906) Prochoerodes forficaria (Guenée, [1858]) Prochoerodes lineola (Göze, 1781) Sabulodes edwardsata (Hulst, 1886) Enypia venata (Grote, 1883) Enypia griseata Grossbeck, 1908 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). 229  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.  230  231  232  233  234  235  236  237  238  239  240  241  242  243  244  245  246  247  248  249  250  251  252  253  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.  Lymantria albescens  BOGDA065-08  Bogda-JA11-65  N/A  Lymantria albescens  GBGL4530-07  AF075274  Lymantria albescens  LYMAN031-08  Lymantria albescens  1  Country  Locality  Publication  NB Haplotype  Japan  Okinawa  Bogdanowicz et al. 2000  N+  B-  AF075274  Japan  Okinawa  Bogdanowicz et al. 2000  N+  B-  ww01229  HM775520  Japan  Okinawa  Present study  N+  N/A  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  254  Identification  BOLD ID  Specimen ID  Genbank No.  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+  1  Japan  Ibaraki Pref.  Bogdanowicz et al. 2000  N+  B+  Lymantria dispar  BOGDA046-08  Bogda-JA5-46  N/A  Country  Locality  Publication  NB Haplotype  255  Identification  BOLD ID  Specimen ID  Genbank No.  Lymantria dispar  BOGDA047-08  Bogda-JA5-47  N/A  Lymantria dispar  BOGDA048-08  Bogda-JA5-48  N/A  Lymantria dispar  BOGDA049-08  Bogda-JA5-49  N/A  Country  Locality  Publication  NB Haplotype  1  Japan  Ibaraki Pref.  Bogdanowicz et al. 2000  N+  B+  1  Japan  Ibaraki Pref.  Bogdanowicz et al. 2000  N+  B+  1  Japan  Ibaraki Pref.  Bogdanowicz et al. 2000  N+  B+  1  Japan  Ibaraki Pref.  Bogdanowicz et al. 2000  N+  B+  1  Japan  Ibaraki Pref.  Bogdanowicz et al. 2000  N+  B+  1  Japan  Hokkaido  Bogdanowicz et al. 2000  N+  B+  Lymantria dispar  BOGDA050-08  Bogda-JA5-50  N/A  Lymantria dispar  BOGDA051-08  Bogda-JA5-51  N/A  Lymantria dispar  BOGDA064-08  Bogda-JA10-64  N/A  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  N+  B+  British Columbia  Yamaguchi et al. unpublished Present study  N+  B+  Hokkaido 2  Lymantria dispar  LBCH7981-10  10-JDWBC-7981  HM775700  Canada  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-  Russia  Irkutskaya Oblast'  Bogdanowicz et al. 2000  N+  B+  Lymantria dispar asiatica  BOGDA016-08  Bogda-RA2-16  N/A  1  256  Identification  BOLD ID  Specimen ID  Genbank No.  Lymantria dispar asiatica  BOGDA017-08  Bogda-RA2-17  N/A  Lymantria dispar asiatica  BOGDA018-08  Bogda-RA3-18  N/A  Lymantria dispar asiatica  BOGDA019-08  Bogda-RA3-19  N/A  Lymantria dispar asiatica  BOGDA020-08  Bogda-RA3-20  N/A  Lymantria dispar asiatica  BOGDA021-08  Bogda-RA3-21  N/A  Lymantria dispar asiatica  BOGDA022-08  Bogda-RA3-22  N/A  Lymantria dispar asiatica  BOGDA023-08  Bogda-RA3-23  N/A  Lymantria dispar asiatica  BOGDA024-08  Bogda-RA3-24  N/A  Lymantria dispar asiatica  BOGDA025-08  Bogda-RA3-25  N/A  Lymantria dispar asiatica  BOGDA026-08  Bogda-RA4-26  N/A  Lymantria dispar asiatica  BOGDA027-08  Bogda-RA4-27  N/A  Lymantria dispar asiatica  BOGDA028-08  Bogda-CH1-28  N/A  Lymantria dispar asiatica  BOGDA029-08  Bogda-CH1-29  N/A  Lymantria dispar asiatica  BOGDA030-08  Bogda-CH2-30  N/A  Lymantria dispar asiatica  BOGDA031-08  Bogda-CH2-31  N/A  Lymantria dispar asiatica  BOGDA032-08  Bogda-CH3-32  N/A  Lymantria dispar asiatica  BOGDA033-08  Bogda-CH3-33  N/A  Lymantria dispar asiatica  BOGDA034-08  Bogda-CH4-34  N/A  Lymantria dispar asiatica  BOGDA035-08  Bogda-CH4-35  N/A  Country  Locality  Publication  NB Haplotype  1  Russia  Irkutskaya Oblast'  Bogdanowicz et al. 2000  N+  B+  1  Russia  Primorskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  Russia  Primorskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  Russia  Primorskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  Russia  Primorskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  Russia  Primorskiy Kray  Bogdanowicz et al. 2000  N-  B-  1  Russia  Primorskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  Russia  Primorskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  Russia  Primorskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  Russia  Khabarovskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  Russia  Khabarovskiy Kray  Bogdanowicz et al. 2000  N+  B+  1  China  Heilongjiang Sheng  Bogdanowicz et al. 2000  N+  B+  1  China  Heilongjiang Sheng  Bogdanowicz et al. 2000  N+  B+  1  China  Liaoning  Bogdanowicz et al. 2000  N+  B+  1  China  Liaoning  Bogdanowicz et al. 2000  N+  B+  1  China  Hebei  Bogdanowicz et al. 2000  N+  B+  1  China  Hebei  Bogdanowicz et al. 2000  N+  B+  1  China  Beijing Shi  Bogdanowicz et al. 2000  N+  B+  1  China  Beijing Shi  Bogdanowicz et al. 2000  N+  B+  1  South Korea  Seoul  Bogdanowicz et al. 2000  N+  B+  1  South Korea  Seoul  Bogdanowicz et al. 2000  N+  B+  Lymantria dispar asiatica  BOGDA036-08  Bogda-KOR-36  N/A  Lymantria dispar asiatica  BOGDA037-08  Bogda-KOR-37  N/A  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+  257  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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+  NB Haplotype  258  Identification  BOLD ID  Specimen ID  Genbank No.  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  Lymantria dispar dispar  BOGDA001-08  Bogda-US1-01  N/A  Lymantria dispar dispar  BOGDA002-08  Bogda-US2-02  N/A  Lymantria dispar dispar  BOGDA003-08  Bogda-CAN-03  N/A  Lymantria dispar dispar  BOGDA004-08  Bogda-CAN-04  N/A  Lymantria dispar dispar  BOGDA005-08  Bogda-FRA-05  N/A  Lymantria dispar dispar  BOGDA006-08  Bogda-FRA-06  N/A  Lymantria dispar dispar  BOGDA007-08  Bogda-GER-07  N/A  Lymantria dispar dispar  BOGDA008-08  Bogda-GER-08  N/A  Lymantria dispar dispar  BOGDA009-08  Bogda-SAR-09  N/A  Lymantria dispar dispar  BOGDA010-08  Bogda-SLO-10  N/A  Lymantria dispar dispar  BOGDA011-08  Bogda-SLO-11  N/A  Lymantria dispar dispar  BOGDA012-08  Bogda-RA1-12  N/A  Country  Locality  Publication  NB Haplotype  Russia  Primorskiy Kray  Present study  N+  N/A  1  United States  New Jersey  Bogdanowicz et al. 2000  N-  B-  1  United States  Vermont  Bogdanowicz et al. 2000  N-  B-  1  Canada  Ontario  Bogdanowicz et al. 2000  N-  B-  1  Canada  Ontario  Bogdanowicz et al. 2000  N+  B-  1  France  Provence-Alpes-Cote d`Azur  Bogdanowicz et al. 2000  N+  B-  1  France  Provence-Alpes-Cote d`Azur  Bogdanowicz et al. 2000  N+  B-  1  Germany  Baden-Wuerttemberg  Bogdanowicz et al. 2000  N+  B-  1  Germany  Baden-Wuerttemberg  Bogdanowicz et al. 2000  N+  B-  1  Italy  Sardinia  Bogdanowicz et al. 2000  N+  B-  1  Slovakia  Kurinec  Bogdanowicz et al. 2000  N+  B-  1  Slovakia  Kurinec  Bogdanowicz et al. 2000  N+  B-  1  Russia  Moscow City  Bogdanowicz et al. 2000  N+  B-  1  Russia  Moscow City  Bogdanowicz et al. 2000  N+  B-  1  Tunisia  Jendouba  Bogdanowicz et al. 2000  N+  B-  1  Tunisia  Jendouba  Bogdanowicz et al. 2000  N+  B-  Canada  Ontario  Armstrong & Ball 2005  N-  B-  Lymantria dispar dispar  BOGDA013-08  Bogda-RA1-13  N/A  Lymantria dispar dispar  BOGDA014-08  Bogda-TUN-14  N/A  Lymantria dispar dispar  BOGDA015-08  Bogda-TUN-15  N/A  Lymantria dispar dispar  GBGL1515-06  Ly23  DQ116098  259  Identification  BOLD ID  Specimen ID  Genbank No.  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  Lymantria dispar dispar  LMHRG002-06  SPI C-02-02 A  HM775748  Country  Canada  Lymantria dispar dispar  LMHRG004-06  SPI C-03-17 A  HM775747  Canada  Lymantria dispar dispar  LMHRG006-06  SPI I-3-17 A  HM775746  Canada  Lymantria dispar dispar  LMHRG007-06  SPI L-2-5 A  HM775745  Canada  Lymantria dispar dispar  LMHRG008-06  SPI V-23-8 A  HM775732  Canada  Lymantria dispar dispar  LMHRG009-06  SPI V-23-8 B  HM775731  Canada  Lymantria dispar dispar  LMHRG010-06  SPI V-24-3 A  HM775730  Canada  Lymantria dispar dispar  LMHRG011-06  SPI V-25-5 A  HM775729  Canada  Lymantria dispar dispar  LMHRG012-06  SPI V-26-5 A  HM775728  Canada  Lymantria dispar dispar  LMHRG014-06  SPI V-90-2 B  HM775727  Canada  Lymantria dispar dispar  LMHRG015-06  SPI V-90-2 A  HM775726  Canada  Lymantria dispar dispar  LMHRG016-06  SPI V-90-3 A  HM775725  Canada  Lymantria dispar dispar  LMHRG019-06  SPI V-92-1 B  HM775724  Canada  Lymantria dispar dispar  LMHRG020-06  SPI V-92-1 C  HM775723  Canada  Lymantria dispar dispar  LMHRG021-06  SPI V-92-1 D  HM775722  Canada  Lymantria dispar dispar  LMHRG022-06  SPI V-92-1 E  HM775721  Canada  Lymantria dispar dispar  LMHRG023-06  SPI V-92-3 A  HM775720  Canada  Locality  Publication  NB Haplotype  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  260  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Lymantria dispar dispar  LMHRG024-06  SPI V-92-3 B  HM775719  Canada  Lymantria dispar dispar  LMHRG025-06  SPI V-93-1 A  HM775718  Canada  Lymantria dispar dispar  LMHRG026-06  SPI V-93-2 A  HM775717  Canada  Lymantria dispar dispar  LMHRG027-06  SPI V-93-2 B  HM775716  Canada  Lymantria dispar dispar  LMHRG029-06  SPI V-94-1 B  HM775715  Canada  Lymantria dispar dispar  LMHRG030-06  SPI V-94-1 C  HM775714  Canada  Lymantria dispar dispar  LMHRG031-06  SPI V-94-1 D  HM775713  Canada  Lymantria dispar dispar  LMHRG032-06  SPI V-98-2 A  HM775712  Canada  Lymantria dispar dispar  LMHRG033-06  SPI W-17-1 A  HM775711  Canada  Lymantria dispar dispar  LMHRG035-06  SPI X-39-1 A  HM775710  Canada  Locality  Publication  NB Haplotype  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  2  British Columbia  Present study  N-  B-  Lymantria dispar dispar  LMHRG036-06  KAM DAB-9 A  HM775709  Canada  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-  261  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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-  NB Haplotype  262  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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-  NB Haplotype  263  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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-  NB Haplotype  264  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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-  NB Haplotype  265  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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-  NB Haplotype  266  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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-  NB Haplotype  267  Identification  BOLD ID  Specimen ID  Genbank No.  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  Lymantria dispar japonica  BOGDA038-08  Bogda-JA1-38  N/A  Lymantria dispar japonica  BOGDA039-08  Bogda-JA1-39  N/A  Lymantria dispar japonica  BOGDA040-08  Bogda-JA2-40  N/A  Lymantria dispar japonica  BOGDA041-08  Bogda-JA2-41  N/A  Lymantria dispar japonica  BOGDA042-08  Bogda-JA3-42  N/A  Lymantria dispar japonica  BOGDA043-08  Bogda-JA4-43  N/A  Lymantria dispar japonica  BOGDA044-08  Bogda-JA4-44  N/A  Lymantria dispar japonica  BOGDA052-08  Bogda-JA6-52  N/A  Lymantria dispar japonica  BOGDA053-08  Bogda-JA6-53  N/A  Lymantria dispar japonica  BOGDA054-08  Bogda-JA7-54  N/A  Lymantria dispar japonica  BOGDA055-08  Bogda-JA8-55  N/A  Lymantria dispar japonica  BOGDA056-08  Bogda-JA8-56  N/A  Country  Locality  Publication  NB Haplotype  Canada  Ontario  Present study  N-  B-  1  Japan  Kyushu-chiho  Bogdanowicz et al. 2000  N+  B+  1  Japan  Kyushu-chiho  Bogdanowicz et al. 2000  N+  B+  1  Japan  Kyushu-chiho  Bogdanowicz et al. 2000  N+  B+  1  Japan  Kyushu-chiho  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B-  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  1  Japan  Honshu  Bogdanowicz et al. 2000  N+  B+  Lymantria dispar japonica  BOGDA057-08  Bogda-JA9-57  N/A  Lymantria dispar japonica  BOGDA058-08  Bogda-JA9-58  N/A  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+  268  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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  NB Haplotype  269  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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  Present study  N-  B-  Lymantria mathura  LYMAN030-08  ww01228  HM775785  Japan  nr. Soraksan NP Campground 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-  NB Haplotype  270  Identification  BOLD ID  Specimen ID  Genbank No.  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  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  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-  1  Country  Locality  Honshu  Publication  NB Haplotype  271  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Lymantria monacha  GBGL1549-06  Ly396  DQ116132  Japan  Lymantria monacha  GBGL1551-06  Ly68  DQ116134  Czech Republic  Lymantria monacha  GBGL1552-06  Ly238  DQ116135  Japan  Lymantria monacha  GBGL1554-06  Ly401  DQ116137  Japan  Lymantria monacha  GBGL1560-06  Ly64  DQ116143  Lymantria monacha  GBGL1561-06  Ly65  Lymantria monacha  GBGL1562-06  Lymantria monacha  Locality  Honshu  Publication  NB Haplotype  Armstrong & Ball 2005  N+  B-  Armstrong & Ball 2005  N+  B-  Honshu  Armstrong & Ball 2005  N+  B-  Honshu  Armstrong & Ball 2005  N+  B-  Poland  Armstrong & Ball 2005  N+  B-  DQ116144  Poland  Armstrong & Ball 2005  N+  B-  Ly202  DQ116145  South Korea  Kangwon-do  Armstrong & Ball 2005  N+  B-  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-  272  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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-  NB Haplotype  273  Identification  BOLD ID  Specimen ID  Genbank No.  Country  Locality  Publication  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  HM775823  Eastern Highlands  Present study  N+  B-  Lymantria ninayi  HCHL035-04  Papua New Guinea Papua New Guinea India  Eastern Highlands  Present study  N+  B-  Kashmir  Bogdanowicz et al. 2000  N+  B-  NB Haplotype  Lymantria obfuscata  BOGDA067-08  USNM ENT 196233 USNM ENT 196232 Bogda-OBF-67  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  HM775824 N/A  1  274  Identification  BOLD ID  Specimen ID  Genbank No.  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  Lymantria umbrosa  BOGDA059-08  Bogda-JA10-59  N/A  Lymantria umbrosa  BOGDA060-08  Bogda-JA10-60  N/A  Lymantria umbrosa  BOGDA061-08  Bogda-JA10-61  N/A  Lymantria umbrosa  BOGDA062-08  Bogda-JA10-62  N/A  Country  Locality  Publication  NB Haplotype  Taiwan  Pilushi  Present study  N-  N/A  1  Japan  Hokkaido  Bogdanowicz et al. 2000  N+  B-  1  Japan  Hokkaido  Bogdanowicz et al. 2000  N+  B-  1  Japan  Hokkaido  Bogdanowicz et al. 2000  N+  B-  1  Japan  Hokkaido  Bogdanowicz et al. 2000  N+  B-  1  Japan  Hokkaido  Bogdanowicz et al. 2000  N+  B-  Lymantria umbrosa  BOGDA063-08  Bogda-JA10-63  N/A  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-  275  Identification  BOLD ID  Specimen ID  Genbank No.  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  N+  B-  Lymantria umbrosa  GBGL4424-07  AB244667  AB244667  Japan  Hokkaido  N+  B-  Lymantria umbrosa  GBGL4425-07  AB244666  AB244666  Japan  Hokkaido  N+  B-  Lymantria umbrosa  GBGL4426-07  AB244664  AB244664  Japan  Hokkaido  N+  B-  Lymantria umbrosa  GBGL4427-07  AB244661  AB244661  Japan  Hokkaido  N+  B-  Lymantria umbrosa  GBGL4429-07  AB244652  AB244652  Japan  Hokkaido  N+  B-  Lymantria umbrosa  GBGL4431-07  AB244657  AB244657  Japan  Hokkaido  N+  B-  Lymantria umbrosa  GBGL4531-07  AF075273  AF075273  Japan  Hokkaido  Yamaguchi et al. unpublished Yamaguchi et al. unpublished Yamaguchi et al. unpublished Yamaguchi et al. unpublished Yamaguchi et al. unpublished Yamaguchi et al. unpublished Yamaguchi et al. unpublished 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  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  Country  Locality  Publication  NB Haplotype  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  276  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.  277  278  279  280  281  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.  LTOL5  COI-3COII  18S  6633  919  612  919  612  249  612  249  658  612  249  658  919  612  249  340  916  612  249  340  NAGEO018-09  919  612  249  340  NAGEO123-09  919  612  Cymatophora approximaria  NAGEO154-09  789  612  Euchlaena johnsonaria  NAGEO260-09  919  Angeronini*  Lytrosis unitaria  NAGEO153-09  919  612  Angeronini*  Xanthotype urticaria  NAGEO017-09  919  612  Azelinini*  Pero mizon  NAGEO045-09  919  612  249  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  Bistonini*  Biston betularia$  NAGEO031-09  866  612  249  Bistonini*  Cochisea paula  NAGEO118-09  919  612  Bistonini*  Phigalia plumigera  NAGEO080-09  919  612  Subfamily / family  Tribe / subfamily  Species  BOLD-ID  Archiearinae*  Archiearinae*  Archiearis parthenias$  NAGEO020-09  Archiearinae*  Lachnocephala vellosata  NAGEO189-09  Desmobathrini*  Ametris nitocris  NAGEO147-09  Eumeleini#  Eumelea ludovicata  NAGEO076-09  848  Abraxini*  Abraxas latifasciata  NAGEO107-09  Abraxini*  Ligdia wagneri  NAGEO096-09  Alsophilini*  Alsophila pometaria  Angeronini*  Aspitates forbesi  Angeronini* Angeronini*  Desmobathrinae  Ennominae  6633  28S  16S  EF1a  COI5P  658 340  658  924  658 658  726  340  658 658 658 658  249  340 340  249  658 825  658  726  658  658 340  924  658  340  820  658  340  924  658  282  Subfamily / family  LTOL5  COI-3COII  18S  28S  723  612  249  Tribe / subfamily  Species  BOLD-ID  Boarmiini*  Iridopsis sp.  NAGEO078-09  Boarmiini*  Anavitrinella ocularia  NAGEO083-09  Boarmiini*  Glaucina sp.  NAGEO082-09  884  Boarmiini*  Hesperumia latipennis  NAGEO282-09  919  Boarmiini*  Hulstina imitatrix  NAGEO086-09  764  Boarmiini*  Melanchroia sp.  NAGEO130-09  570  Boarmiini*  Orthofidonia flavivenata  NAGEO199-09  919  Boarmiini*  Protoboarmia porcelaria  NAGEO272-09  919  Boarmiini*  Pterotaea lamiaria  NAGEO077-09  864  Boarmiini*  Stenoporpia sp.  NAGEO252-09  919  Caberini*  Cabera erythemaria  NAGEO150-09  Caberini*  Episemasia solitaria  Caberini*  Eudrepanulatrix rectifascia  Caberini*  16S  EF1a  658  612 612  658 249  658  249 612  COI5P  658  249  825  249  658 658 658  249  658  612  249  658  919  612  249  NAGEO161-09  830  612  NAGEO087-09  919  612  Sericosema sp.  NAGEO209-09  919  Caberini*  Stergamataea sp.  NAGEO012-09  Campaeini*  Campaea perlata$  NAGEO064-09  Cassymini*  Nematocampa brehmeata  Cassymini*  Protitame virginalis  Cassymini* Ennomini*  658 340  658 658  340  816  658 658  919  612  249  919  612  249  NAGEO042-09  919  612  249  340  NAGEO159-09  917  612  249  340  Taeniogramma odrussa  NAGEO146-09  912  612  249  340  726  658  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  Eutoeini#  Luxiaria emphatica  NAGEO106-09  919  612  Gnophini*  Gnophos macguffini  NAGEO132-09  903  612  Gonodontini*  Colotois pennaria  NAGEO137-09  919  612  Hypochrosini*  Metarranthis indeclinata  NAGEO162-09  919  612  Hypochrosini*  Nothomiza formosa  NAGEO114-09  919  Hypochrosini*  Omiza lycoraria  NAGEO105-09  875  6633  658  340  924  658  924  658 658  658 658 658  249  340  612  249  340  612  249  658 658 658 658  283  Subfamily / family  LTOL5  COI-3COII  18S  28S  16S  EF1a  COI5P  6633  919  612  233  340  924  658  884  612  249  NAGEO190-09  919  612  Thallophaga hyperborea  NAGEO125-09  865  612  Chiasmia clathrata  NAGEO070-09  919  612  Macariini*  Heliomata cycladata  NAGEO026-09  919  612  Macariini*  Digrammia curvata  NAGEO242-09  919  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  Nacophorini*  Amelora megalocephala  NAGEO187-09  859  612  249  658  Nacophorini*  Animomyia smithii  NAGEO079-09  919  612  249  658  Nacophorini*  Ceratonyx permagnaria  NAGEO202-09  919  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  Ourapterygini*  Eutrapela clemataria  NAGEO089-09  919  Ourapterygini*  Nepytia sp.  NAGEO192-09  919  Ourapterygini*  Pherne sperryi  NAGEO014-09  919  Ourapterygini*  Phyllodonta peccataria  NAGEO205-09  919  Ourapterygini*  Sabulodes olifata  NAGEO203-09  919  Ourapterygini*  Sicya macularia  NAGEO044-09  852  612  249  340  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  Tribe / subfamily  Species  BOLD-ID  Hypochrosini*  Plagodis fervidaria$  NAGEO037-09  Lithinini*  Gueneria similaria  NAGEO155-09  Lithinini*  Odontothera sp.  Lithinini* Macariini*  658 340  249  658  340 340  658 924  340  658  249  249  658  340  924  221  612  658  658  249 612  658  658  249  924  658  249  658  249  658  223  658  249  658 658  284  Subfamily / family  Geometrinae  Larentiinae  COI-3COII  18S  NAGEO122-09  361  612  Aracima muscosa  NAGEO091-09  919  612  Dichordophorini*  Dichordophora phoenix  NAGEO024-09  919  Dysphaniini#  Dysphania militaris  NAGEO120-09  919  612  Comibaenini#  Comibaena quadrinotata  NAGEO092-09  849  612  Geometrini#  Geometra papilionaria  NAGEO119-09  919  612  Hemistolini#  Hemistola veneta  NAGEO093-09  919  612  249  Hemitheini*  Chlorochlamys sp.  NAGEO029-09  919  612  249  Hemitheini*  Hemithea aestivaria  NAGEO269-09  919  Hemitheini*  Hethemia pistasciaria  NAGEO182-09  859  612  Hemitheini*  Mesothea incertata  NAGEO128-09  916  612  Nemoriini*  Chlorosea margaretaria$  NAGEO005-09  919  612  Nemoriini*  Dichorda iridaria  NAGEO164-09  919  612  249  Nemoriini*  Nemoria mimosaria  NAGEO166-09  919  612  249  Nemoriini*  Eucyclodes gavissima  NAGEO108-09  919  612  249  Pseudoterpnini#  Dindica polyphaenaria  NAGEO109-09  919  612  249  Pseudoterpnini#  Hypobapta xenomorpha$  NAGEO006-09  919  612  Rhomboristini*  Lophochorista calliope  NAGEO139-09  919  612  249  Synchlorini*  Synchlora aerata  NAGEO027-09  829  612  221  Tribe uncertain#  Agathia curvifiens  NAGEO117-09  919  612  249  Asthenini*  Hydrelia flammeolaria  NAGEO073-09  919  612  249  340  Asthenini*  Laciniodes unistirpis  NAGEO111-09  857  612  249  340  Asthenini*  Trichodezia albovittata  NAGEO009-09  903  612  249  340  Asthenini*  Venusia cambrica  NAGEO251-09  919  Chesiadini*  Aplocera efformata  NAGEO071-09  573  612  Cidariini*  Cidaria fulvata  NAGEO188-09  919  612  Tribe / subfamily  Species  BOLD-ID  Thinopterygini#  Thinopteryx crocopterata  Aracimini#  LTOL5  6633  6633  28S  16S  EF1a  340  COI5P 658  924  658  340  726  658  340  924  658  924  658  249 340  658 672  340  658 658 642  340  658  249  658 340  658 658 658  340  726  658  687  658  894  658  340  658 658 753  658 658 658  924  249  658 658  924 340  658 658  285  Subfamily / family  COI-3COII  18S  NAGEO067-09  919  NAGEO180-09  697  Antepirrhoe (Eustroma) sp.  NAGEO194-09  912  Eudulini*  Eubaphe sp.  NAGEO032-09  919  Euphyiini*  Euphyia intermediata  NAGEO176-09  919  Eupitheciini*  Pasiphila rectangulata  NAGEO280-09  Eupitheciini*  Eupithecia acutipennis$  NAGEO021-09  Hydriomenini*  Coryphista meadii  NAGEO028-09  Hydriomenini*  Hydriomena furcata  NAGEO066-09  919  612  Larentiini#  Spargania magnoliata  NAGEO051-09  626  612  Larentiini#  Anticlea (Earophila) badiata  NAGEO186-09  919  612  Lobophorini*  Cladara limitaria  NAGEO246-09  919  Lobophorini*  Heterophleps triguttaria  NAGEO048-09  877  Lobophorini*  Lobophora nivigerata  NAGEO265-09  919  Lobophorini*  Scelidacantha triseriata  NAGEO049-09  Lobophorini*  Trichopteryx carpinata$  NAGEO003-09  Melanthiini#  Melanthia procellata  Operophterini*  Epirrita autumnata  Operophterini* Perizomini*  Tribe / subfamily  Species  BOLD-ID  Cidariini*  Dysstroma formosa  Cidariini*  Ecliptopera silaceata  Cidariini*  LTOL5  16S  EF1a  COI5P  612  340  798  658  612  340  28S  658  249 195 612  654 340  658  340  658  919 6633  866  632 612  249  340  612  249  340  658 249  837 340  658 658  223 612 612  NAGEO094-09  919  612  NAGEO129-09  919  612  Operophtera brumata  NAGEO232-09  919  Perizoma grandis  NAGEO177-09  919  Rheumapterini*  Rheumaptera undulata  NAGEO273-09  Rheumapterini*  Triphosa haesitata  NAGEO193-09  787  Stamnodini*  Stamnodes marmorata  NAGEO050-09  919  612  Stamnodini*  Stamnoctenis nr. morrisata  NAGEO054-09  919  612  Trichopterygini*  Carige sp.  NAGEO104-09  919  612  Trichopterygini*  Dyspteris abortivaria  NAGEO174-09  919  612  Trichopterygini*  Tyloptera bella  NAGEO095-09  865  612  Xanthorhoini*  Costaconvexa centrostrigaria  NAGEO178-09  893  612  612  658 658  202  919  658 658  612  919 6633  915  249 249  640 340  924  658  340  924  658  340  924  658  340  658  249  658  249  658  249  658  249  658 340  249 193  798  658  340  658  340  658  340  658 658 658  286  Subfamily / family  Oenochrominae*  Sterrhinae  Uraniidae  Tribe / subfamily  Species  BOLD-ID  Xanthorhoini*  Epirrhoe medeifascia  NAGEO204-09  Xanthorhoini*  Orthonama obstipata$  NAGEO019-09  Xanthorhoini*  Psychophora sp. G  Xanthorhoini* Xanthorhoini*  LTOL5  COI-3COII  18S  28S  16S  EF1a  919 6633  COI5P 658  897  612  658  NAGEO131-09  877  612  658  Xanthorhoe lacustrata  NAGEO030-09  919  612  Zenophleps sp.  NAGEO217-09  919  Oenochrominae*  Dichromodes sp.$  NAGEO002-09  6633  919  612  Oenochrominae*  Dinophalus lechriomita group$  NAGEO004-09  6633  919  612  Oenochrominae*  Ergavia carinenta  NAGEO023-09  919  612  Oenochrominae*  Nearcha sp.  NAGEO084-09  919  612  Oenochrominae*  Sarcinodes perakaria  NAGEO121-09  795  612  249  340  Cosymbiini*  Cyclophora nr. dataria$  NAGEO007-09  919  612  235  340  Cosymbiini*  Pleuroprucha insulsaria  NAGEO170-09  919  612  249  Cosymbiini*  Semaeopus gracilata  NAGEO201-09  919  Rhodometrini#  Rhodometra sacraria  NAGEO022-09  866  612  249  340  Scopulini*  Leptostales ferruminaria  NAGEO168-09  919  612  249  340  Scopulini*  Lophosis labeculata  NAGEO169-09  919  612  249  Scopulini*  Pseudasellodes fenestrariaDHJ01  NAGEO034-09  919  612  Scopulini*  Scopula limboundata$  NAGEO001-09  859  612  Cyllopoidini#  Smicropus laeta  NAGEO113-09  919  612  Sterrhini*  Idaea demissaria  NAGEO085-09  919  612  Sterrhini*  Lobocleta peralbata  NAGEO167-09  919  612  Timandrini*  Haematopis grataria  NAGEO053-09  858  612  249  658  Timandrini*  Timandra amaturaria  NAGEO172-09  919  612  249  658  Epipleminae  Calledapteryx dryopterata  NAGEO046-09  866  612  Epipleminae  Callizzia sp.  NAGEO271-09  919  6633  6633  340  900  658 658  340 249  924  658  924  658  924  658 658 658  924  658  726  658 658  249  924  658 658 658  340  924  658  340  843  658 658  249  870 340  340 249  658 658  658 658  287  Subfamily / family  Epicopeiidae Sematuridae  Noctuidae  Drepanidae  Thyatiridae  COI-3COII  18S  NAGEO038-09  864  612  NAGEO068-09  862  612  Phazaca interrupta  NAGEO081-09  919  612  Epipleminae  Schidax squamaria  NAGEO033-09  877  612  Epipleminae  Nedusia sp.  NAGEO056-09  869  612  Epipleminae  Syngria druidaria$  NAGEO058-09  6633  797  612  Microniinae  Acropteris sparsaria$  NAGEO055-09  6633  917  612  Uraniinae  Lyssa zampa$  NAGEO060-09  6633  919  612  Uraniinae  Urania fulgens  NAGEO065-09  919  612  Uraniinae  Urapteroides sp.  NAGEO069-09  865  612  249  Epicopeiinae  Epicopeia hainesii$  NAGEO039-09  6633  865  612  Epicopeiinae  Psychostrophia melangaria$  NAGEO040-09  6633  865  612  Sematurinae  Coronidia orithea  NAGEO013-09  919  612  Sematurinae  Homidiana sp.  NAGEO061-09  919  612  Sematurinae  Sematura luna$  NAGEO063-09  6633  864  612  249  Lymantriinae  Lymantria dispar$  NAGEO059-09  6633  919  612  249  Amphipyrinae  Spodoptera frugiperda$  NAGEO074-09  6633  919  612  249  Plusiinae  Trichoplusia ni$  NAGEO043-09  6633  865  612  180  340  Cyclidiinae  Cyclidia substigmaria$  NAGEO062-09  6633  919  612  249  340  Drepaninae  Drepana bilineata  NAGEO243-09  Oretinae  Oreta rosea$  NAGEO036-09  6633  919  612  249  340  909  658  Thyatirinae  Pseudothyatira cymatophoroides$  NAGEO035-09  6633  919  612  249  340  924  658  Tribe / subfamily  Species  BOLD-ID  Epipleminae  Erosia veninotata  Epipleminae  Metorthocheilus emarginatus  Epipleminae  LTOL5  919  28S  16S  EF1a  340  924  COI5P 658 641 658  249  658 658  249  658 870  658  226  924  658  226  900  658  780  650  340 340 249  658 924  658  726  658 658 658  340  918  658  888  658  870  658  738  658  249  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  288  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 COI-3pCOII 16S 18S 28S EF1a EF1a EF1a EF1a Wingless CAD CAD CAD CAD DDC IDH  LepF1  ATTCAACCAATCATAAAGATATTGG  LepR1  TAAACTTCTGGATGTCCAAAAAATCA  50  Y  1  cos2183 16Sgaf rc18H 28SD2B EF1aLepF2 EF1aLepF1 EF1aLepF3 EF_F LepWg1 CAD_743nF CAD_2F CAD_2F CAD_743nF DDC3.2sF IDHdeg27F  CAACATTTATTTTGATTTTTCGG GTATCTTGTGTATCAGAGTT GCTGAAACTTAAAGGAATTGACGGAAGGGCAC GTCGGGTTGCTTGAGAGTGC ACAAATGCGGTGGTATCGACAA CACATYAACATTGTCGTSATYGG GATATCGCTCTGTGGAAGTTCG GTCACCATCATYGACGC GARTGYAARTGYCAYGGYATGTCTGG GGNGTNACNACNGCNTGYTTYGARCC GTNGTNTTYCARACNGGNATGGT GTNGTNTTYCARACNGGNATGGT GGNGTNACNACNGCNTGYTTYGARCC TGGYTICAYGTIGAYGCNGCNTAYGC GGWGAYGARATGACNAGRATHATHTGG  COI-IIR 16Sgar 18L 28SD3Ar EF1aLepR EF1aLepR EF1aLepR EF1aR LepWg2 CAD_1028R CAD_3R CAD_1028R CAD_3R DDCdegR3 IDHdegR  GTTCAAATTAATTCAATTATTTG CCTGGCTTACACCGGTTTGAA CACCTACGGAAACCTTGTTACGACTT TCCGTGTTTCAAGACGGGTC GATTTACCRGWACGACGRTC GATTTACCRGWACGACGRTC GATTTACCRGWACGACGRTC GATTTACCRGWACGACGRTC ACTICGCARCACCARTGGAATGTRCA TTRTTNGGNARYTGNCCNCCCAT RTGYTCNGGRTGRAAYTG TTRTTNGGNARYTGNCCNCCCAT RTGYTCNGGRTGRAAYTG CCCATNGTNACYTCYTC TTYTTRCAIGCCCANACRAANCCNCC  50 50 50 50 58 58 58 58 50 50 50 50 50 50 55  Y Y Y Y Y N N N N N N N N N N  2 3 4 5 3 3 3 6,7 8 9 10 9 10 11,9 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.  289  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  Crambidae (12)  52  Agriphila straminella ([Denis & Schiffermüller], 1775)  2  M  Catoptria oregonicus (Grote, 1880)  1  B  Chrysoteuchia topiarius (Zeller, 1866)  2  B  Eudonia JFL01  2  M+G  Eudonia JFL02  1  M+G  Eudonia echo (Dyar, 1929)  6  M+G  B  introduced introduced  290  Taxon (no. of species)  Individuals  Identification  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  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  Geometridae (47) Campaea perlata (Guenée, [1858])  Notes  B  introduced  338 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  291  Taxon (no. of species)  Individuals  Identification  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  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  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  Noctuidae (33)  Notes  introduced  introduced  B  102  Acronicta dactylina Grote, 1874  3  B  Adelphagrotis stellaris (Grote, 1880)  1  M  Agrotis ipsilon (Hufnagel, 1766)  3  B  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  seasonal migrant  292  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  Noctua pronuba (Linnaeus, 1758)  27  B  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  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  seasonal migrant introduced  introduced  293  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  Tischeriidae (1)  1  Coptotriche malifoliella (Clemens, 1860)  1  G  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  Ditula angustiorana (Haworth, 1811)  14  B  Epinotia JFL01  1  G  Epinotia JFL02  3  G  Epinotia JFL03  1  G  9  G  introduced; 1st NA record  Epinotia albangulana (Walsingham, 1879)  294  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  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  Paraswammerdamia lutarea (Haworth, 1828)  1  G  Prays fraxinella (Donovan, 1793)  1  M  Swammerdamia caesiella (Hübner, 1796)  1  B  introduced; 1st NA record introduced; 1st NA record introduced; 1st BC record introduced  Swammerdamia pyrella (Villers, 1789)  1  B  introduced  Yponomeuta padella (Linnaeus, 1758)  7  M  introduced  introduced  295  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).  296  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  Argyresthiidae (7)  No. of individuals 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)  Coleophoridae (7)  4 28  Batrachedra praeangusta (Haworth, 1828) Batrachedra striolata Zeller, 1875 Coleophora alnifoliae Barasch, 1934  12 1 11  Coleophora deauratella Lienig & Zeller, 1846  1  Coleophora glaucella Walsingham, 1882  1  Coleophora mayrella (Hübner, [1813])  1  Coleophora sparsipulvella Chambers, 1875 Crambidae (17)  1 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 Udea sp. cf. saxifrage Udea washingtonalis (Grote, 1882)  5 18 1  297  Family  Species  Depressariidae (1)  No. of individuals 1  Agonopterix sp. nr. clemensella Drepanidae (7)  1 95  Ceranemota albertae Clarke, 1938 Ceranemota fasciata (Barnes & McDunnough, 1910) Drepana bilineata (Packard, 1864) Euthyatira lorata (Grote, 1881) Habrosyne scripta (Gosse, 1840) Oreta rosea (Walker, 1855) Pseudothyatira cymatophoroides (Guenée, 1852) Elachistidae (1)  13 8 35 8 10 3 18 1  Elachista sp. JFL01 Erebidae (11)  1 151  Catocala semirelicta Grote, 1874  2  Clemensia albata Packard, 1864  36  Dasychira grisefacta (Dyar, 1911)  7  Eilema bicolor (Grote, 1864) Hypenodes caducus (Dyar, 1907) Hypenodes sombrus Ferguson, 1954 Idia aemula concisa  45 6 1 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  298  Family  Species  Coleotechnites sp. nr. piceaella Coleotechnites starki (T.N. Freeman, 1957)  No. of individuals 1 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) Cabera exanthemata (Scopoli, 1763) Campaea perlata (Guenée, [1858]) Caripeta angustiorata Walker, [1863]  15 5 97 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 Enypia packardata Taylor, 1906 Enypia venata (Grote, 1883)  4 51 7  Epirrita autumnata (Borkhausen, 1794)  45  Eulithis destinata (Möschler, 1860)  18  Eulithis propulsata (Walker, 1862)  12  Eulithis testata (Linnaeus, 1761) Eulithis xylina (Hulst, 1896)  1 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  299  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) Gabriola dyari Taylor, 1904 Hydriomena divisaria (Walker, 1860) Hydriomena furcata (Thunberg, 1784) Hydriomena irata Swett, 1910 Hydriomena renunciata (Walker, 1862) Hydriomena ruberata (Freyer, [1831]) Iridopsis larvaria (Guenée, [1858]) Lambdina fiscellaria (Guenée, [1858])  8 137 1 441 3 22 4 2 109  Lampropteryx suffumata ([Denis & Sch.], 1775)  1  Lobophora nivigerata Walker, 1862  5  Macaria exauspicata Walker, 1861  33  Macaria loricaria (Eversmann, 1837) Macaria signaria (Hübner, [1809])  1 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) Selenia alciphearia Walker, 1860 Sicya macularia (Harris, 1850) Spargania magnoliata Guenée, [1858] Stenoporpia pulmonaria (Grote, 1881)  2 5 175 8 4  Synaxis jubararia (Hulst, 1886)  116  Venusia cambrica Curtis, 1839  294  Venusia pearsalli (Dyar, 1906)  4  Xanthorhoe abrasaria (Herrich-Schäffer, [1855]) Xanthorhoe decoloraria (Esper, [1806])  17 4  Xanthorhoe ferrugata (Clerck, 1759) 8  300  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 Lasiocampidae (1)  1 28  Phyllodesma americana (Harris, 1841) Lyonetiidae (1)  28 9  Lyonetia saliciella Busck, 1904 Momphidae (1)  9 14  Mompha conturbatella (Hübner, [1819]) Noctuidae (68)  14 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) Autographa ampla (Walker, [1858])  1 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 Cryptocala acadiensis (Bethune, 1870) Cucullia intermedia Speyer, 1870 Diarsia calgary (J. B. Smith, 1898)  4 12 1 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  301  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) Polia nimbosa (Guenée, 1852)  1 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 Syngrapha alias (Ottolengui, 1902)  1 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) Xestia oblata (Morrison, 1875) Xestia perquiritata (Morrison, 1874) Xestia smithii (Snellen, 1896)  19 1 4 118  Xestia speciosa (Hübner, [1813]) 55  302  Family  Species  Xylotype arcadia Barnes & Benjamin, 1922 Notodontidae (9)  No. of individuals 1 102  Clostera albosigma Fitch, 1856  16  Clostera apicalis (Walker, 1855)  2  Clostera brucei (Hy. Edwards, 1885) Furcula scolopendrina (Boisduval, 1869) Gluphisia septentrionis Walker, 1855  1 10 9  Nadata gibbosa (J.E. Smith, 1797)  10  Notodonta simplaria Graef, 1881  13  Oligocentria pallida (Strecker, 1899) Pheosia portlandia Hy. Edwards, 1886 Oecophoridae (3)  4 37 4  Denisia haydenella (Chambers, 1877)  1  Eido trimaculella (Fitch, 1856)  1  Polix coloradella (Walsingham, 1888)  2  Phyllocnistidae (2)  1184 Phyllocnistis populiella Chambers, 1875 Phyllocnistis sp. nr. populiella  Plutellidae (1)  1183 1 2  Plutella vanella Walsingham, 1881 Pterophoridae (3)  2 17  Adaina sp. Hellinsia sp. Oxyptilus delawaricus Zeller, 1873 Pyralidae (6)  2 1 14 51  Apomyelois sp. Dioryctria reniculelloides Mutuura & Munroe, 1973  1 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)  Sphingidae (2)  5 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  303  Family  Species  Niditinea orleansella (Chambers, 1873) Tortricidae (60)  No. of individuals 1 565  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) Apotomis removana (Kearfott, 1907)  9 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) Choristoneura occidentalis group Clepsis persicana (Fitch, 1856) Clepsis virescana (Clemens, 1865)  3 121 9 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  304  Family  Species  Epinotia trigonella (Linnaeus, 1758)  5  Gypsonoma sp. cf. salicicolana  2  Hedya ochroleucana (Frölich, 1828)  1  Hedya sp. nr. ochroleucana  2  Notocelia culminana (Walsingham, 1879) Olethreutes castorana (McDunnough, 1922)  7 18  Olethreutes deprecatoria Heinrich, 1926  6  Olethreutes sp. 1  4  Olethreutes sp. 2  4  Olethreutes sp. nr. minaki Pandemis limitata (Robinson, 1869)  3 16  Petrova burkeana (Kearfott, 1907)  1  Phaneta infimbriana (Dyar, 1904)  5  Phaneta sp. 5 Rhopobota naevana (Hübner, [1817]) Taniva albolineana (Kearfott, 1907) Zeiraphera canadensis Mutuura & Freeman, 1967 Zeiraphera sp. cf. pacifica Zeiraphera fortunana (Kearfott, 1907) Uraniidae (1)  4 13 1 37 2 11 96  Callizzia amorata Packard, 1876 Yponomeutidae (1)  96 2  Swammerdamia caesiella (Hübner, 1796) Total (333)  No. of individuals  2 7978  305  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  Argyresthiidae (2)  No. of individuals 3  Argyresthia pygmaeella (Hübner, [1813])  2  Argyresthia sp. 5  1  Coleophoridae (1)  2 Coleophora klimeschiella Toll, 1952  Cosmopterigidae (1)  2 1  Walshia miscecolorella (Chambers, 1875) Crambidae (14)  1 103  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 Gesneria centuriella ([Denis & Schiffermüller], 1775)  9 24  Gesneria sp.  6  Pediasia trisecta (Walker, 1856)  1  Scoparia basalis Walker, 1866  1  Scoparia biplagialis Walker, 1866 Udea sp. 5 Udea sp. cf. saxifrage Udea washingtonalis (Grote, 1882) Depressariidae (1)  4 18 5 26 4  Depressariodes nivalis (Braun, 1921) Drepanidae (2)  4 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  306  Family  Species  Bryotropha similis (Stainton, 1854)  No. of individuals 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) Eupithecia bryanti Taylor, 1906 Eupithecia cretaceata (Packard, 1874) Eupithecia gelidata Möschler, 1860 Eupithecia graefii (Hulst, 1896)  1 3 257 2 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) Macaria lorquinaria (Guenée, [1858])  10 1  Macaria quadrilinearia (Packard, 1873) 1  307  Family  Species  Macaria signaria (Hübner, [1809]) Perizoma grandis (Hulst, 1896) Pero mizon Rindge, 1955 Selenia alciphearia Walker, 1860 Sicya macularia (Harris, 1850) Spargania luctuata ([Denis & Schiffermüller], 1775)  No. of individuals 4 10 1 25 1 171  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 Xanthorhoe ferrugata (Clerck, 1759) Xanthorhoe fossaria Taylor, 1906  17 1 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)  Momphidae (3)  8 6  Mompha conturbatella (Hübner, [1819])  1  Mompha sexstrigella (Braun, 1921)  2  Mompha sp. Noctuidae (64)  3 785  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) Apamea cogitata (J. B. Smith, 1891)  2 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  308  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) Diarsia freemani Hardwick, 1950 Eremobina claudens (Walker, 1857)  1 17 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 Lasionycta mutilata (J. B. Smith, 1898)  2 126  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) Pseudohermonassa flavotincta (J. B. Smith, 1892) Syngrapha alias (Ottolengui, 1902) Syngrapha angulidens (J. B. Smith, 1891)  3 21 4 46  Syngrapha celsa (Hy. Edwards, 1881) 4  309  Family  Species  No. of individuals  Syngrapha octoscripta (Grote, 1874)  2  Syngrapha orophila (Hampson, 1908)  4  Syngrapha viridisigma (Grote, 1874)  1  Xestia fabulosa (Ferguson, 1965) Xestia homogena (McDunnough, 1921) Xestia oblata (Morrison, 1875) Xestia perquiritata (Morrison, 1874) Xestia smithii (Snellen, 1896) Xestia speciosa (Hübner, [1813]) Nolidae (1)  35 106 3 56 5 101 1  Nycteola cinereana Neumoegen & Dyar, 1893 Notodontidae (2)  1 2  Nadata gibbosa (J.E. Smith, 1797)  1  Pheosia portlandia Hy. Edwards, 1886  1  Oecophoridae (2)  2 Denisia haydenella (Chambers, 1877) Polix coloradella (Walsingham, 1888)  Phyllocnistidae (2)  1 1 15  Phyllocnistis populiella Chambers, 1875 Phyllocnistis sp. nr. populiella Plutellidae (1)  14 1 1  Plutella xylostella (Linnaeus, 1758) Pterophoridae (5)  1 16  Adaina sp.  5  Hellinsia pectodactylus (Staudinger, 1859)  1  Platyptilia carduidactyla (Riley, 1869)  1  Platyptilia sp. 1  1  Platyptilia sp. nr. tesseradactyla Pyralidae (6)  8 31  Dioryctria pseudotsugella Munroe, 1959 Dioryctria reniculelloides Mutuura & Munroe, 1973  1 26  Ephestia sp.  1  Ephestiodes gilvescentella Ragonot, 1887  1  Homoeosoma electella (Hulst, 1887)  1  Pyla aequivoca Heinrich, 1956 Scythrididae (1)  1 34  Scythris noricella (Zeller, 1843) Sphingidae (1)  34 1  Hyles gallii (Rottemburg, 1775) Tortricidae (26)  1 389  Acleris britannia Kearfott, 1904  3  Acleris gloveranus (Walsingham, 1879)  1  Agapeta zoegana (Linnaeus, 1767) 1  310  Family  Species  Ancylis sp. nr. myrtillana  3  Archips cerasivorana (Fitch, 1856)  1  Archips grisea (Robinson, 1869)  1  Choristoneura occidentalis group Dichrorampha simulana (Clemens, 1860)  176 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) Phtheochroa sp. 1 Taniva albolineana (Kearfott, 1907)  Total (206)  No. of individuals  11 5 1  Zeiraphera fortunana (Kearfott, 1907)  19  Zeiraphera improbana (Walker, 1863)  6 2926  311  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).  312  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 Erebidae (10) Arctiinae Bruceia pulverina Neumoegen, 1893 Eilema bicolor (Grote, 1864) Grammia nevadensis (Grote & Robinson, 1866) Virbia ferruginosa (Walker, 1854) Calpinae Scoliopteryx libatrix (Linnaeus, 1758) Erebinae Catocala briseis W. H. Edwards, 1864 Lygephila victoria (Grote, 1874) Hypeninae Phobolosia anfracta (Hy. Edwards, 1881) Lymantriinae Orgyia pseudotsugata (McDunnough, 1921) Rivulinae Mycterophora longipalpata Hulst, 1896 Geometridae (49) Ennominae Caripeta sp. Digrammia curvata (Grote, 1880) Digrammia denticulata (Grote, 1883) Digrammia neptaria (Guenée, [1858]) Digrammia setonana (McDunnough, 1927) Digrammia triviata (Barnes & McDunnough, 1917) Enypia griseata Grossbeck, 1908 Euchlaena johnsonaria (Fitch, 1869) Eumacaria latiferrugata (Walker, [1863]) Glena nigricaria (Barnes & McDunnough, 1913) Hesperumia sulphuraria Packard, 1873 Macaria adonis Barnes & McDunnough, 1918 Macaria bitactata (Walker, 1862) Macaria brunneata (Thunberg, 1784) Macaria decorata (Hulst, 1896) Macaria exauspicata Walker, 1861 Macaria plumosata (Barnes & McDunnough, 1917) Macaria signaria (Hübner, [1809]) Melanolophia imitata (Walker, 1860) Meris suffusaria McDunnough, 1940 Nematocampa resistaria (Herrich-Schäffer, [1856]) Neoterpes trianguliferata (Packard, 1871) Pero behrensaria (Packard, 1871) Pero morrisonaria (Hy. Edwards, 1881) Pero occidentalis (Hulst, 1896) Plataea trilinearia (Packard, 1873) Protoboarmia porcelaria (Guenée, [1858])  No. of individuals 5739 1 143 283 1 1 1 1 2 5300 6 766 1 327 4 1 15 27 1 2 1 14 1 6 4 13 8 1 11 12 6 2 10 1 26 1 27 1 1  313  Taxon  No. of individuals  Sicya macularia (Harris, 1850) Stenoporpia pulmonaria (Grote, 1881) Synaxis sp. Geometrinae Chlorochlamys triangularis Prout, 1912 Synchlora aerata (Fabricius, 1798) Synchlora bistriaria (Packard, 1876) Larentiinae Dysstroma formosa (Hulst, 1896) Dysstroma truncata (Hufnagel, 1767) Eulithis testata (Linnaeus, 1761) Eupithecia behrensata Packard, 1876 Eupithecia borealis (Hulst, 1898) Eupithecia interruptofasciata Packard, 1873 Eupithecia sp. 11 Eupithecia sp. 22 Hydriomena furcata (Thunberg, 1784) Hydriomena ruberata (Freyer, [1831]) Prorella leucata (Hulst, 1896) Stamnoctenis morrisata (Hulst, 1887) Sterrhinae Idaea demissaria (Hübner, [1831]) Scopula fuscata (Hulst, 1887) Scopula inductata (Guenée, [1858]) Scopula luteolata (Hulst, 1880)  1 13 1  Lasiocampidae (2) Malacosoma californica (Packard, 1864) Tolype dayi Blackmore, 1921  12 1 11  Noctuidae (135) Amphipyrinae Amphipyra tragopoginis (Clerck, 1759) Apamea antennata (J. B. Smith, 1891) Apamea cogitata (J. B. Smith, 1891) Apamea devastator (Brace, 1819) Apamea impulsa (Guenée, 1852) Apamea inordinata (Morrison, 1875) Apamea longula (Grote, 1879) Apamea occidens (Grote, 1878) Apamea spaldingi (J. B. Smith, 1909) Caradrina camina Smith 1894 Caradrina meralis (Morrison, 1875) Caradrina montana (Bremer, 1861) Chytonix divesta (Grote, 1874) Condica discistriga (J. B. Smith, 1894) Bryophilinae Cryphia cuerva (Barnes, 1907) Cryphia olivacea (J. B. Smith, 1891) Cuculliinae Cucullia antipoda group Heliothinae Schinia acutilinea (Grote, 1878) Schinia walsinghami (Hy. Edwards, 1881) Noctuinae  14 2 35 2 3 1 2 5 1 1 95 3 5 4 34 9 2 5 4  1981 1 2 1 5 2 33 2 2 13 32 23 42 6 57 46 1 1 15 65  314  Taxon Abagrotis dodi McDunnough, 1927 Abagrotis forbesi (Benjamin, 1921) Abagrotis hermina Lafontaine, 1998 Abagrotis mirabilis (Grote, 1879) Abagrotis nanalis (Grote, 1881) Abagrotis nefascia (J.B. Smith, 1908) Abagrotis placida (Grote, 1876) Abagrotis reedi Buckett, 1969 Abagrotis scopeops (Dyar, 1904) Abagrotis trigona (J.B. Smith, 1893) Abagrotis vittifrons (Grote, 1864) Actebia balanitis (Grote, 1873) Agrotis venerabilis Walker, [1857] Anaplectoides prasina ([Denis & Schiffermüller], 1775) Anarta columbica (McDunnough, 1930) Anarta crotchii (Grote, 1880) Anarta montanica (McDunnough, 1930) Anarta mutata (Dod, 1913) Andropolia epichysis Grote 1880 Anicla exuberans (J. B. Smith, 1898) Archanara subflava (Grote, 1882) Cosmia elisae Lafontaine & Troubridge, 2003 Diarsia dislocata (J. B. Smith, 1904) Diarsia freemani Hardwick, 1950 Dichagyris variabilis (Grote, 1874) Egira curialis (Grote, 1873) Egira rubrica (Harvey, 1878) Epidemas obscurus J. B. Smith, 1903 Eurois astricta Morrison, 1874 Eurois occulta (Linnaeus, 1758) Euxoa aberrans McDunnough, 1932 Euxoa adumbrata (Eversmann, 1842) Euxoa agema (Strecker, 1899) Euxoa albipennis (Grote, 1876) Euxoa atomaris (J. B. Smith, 1890) Euxoa atristrigata (J. B. Smith, 1890) Euxoa auripennis Lafontaine, 1974 Euxoa bochus (Morrison, 1874) Euxoa brunneigera (Grote, 1876) Euxoa campestris (Grote, 1875) Euxoa castanea Lafontaine, 1981 Euxoa catenula (Grote, 1879) Euxoa cf. setonia Euxoa choris (Harvey, 1876) Euxoa comosa group sp. 1 Euxoa comosa group sp. 2 Euxoa declarata (Walker, 1865) Euxoa difformis (J. B. Smith, 1900) Euxoa divergens (Walker, [1857]) Euxoa excogita (J. B. Smith, 1900) Euxoa flavicollis (J. B. Smith, 1888) Euxoa infracta (Morrison, 1875) Euxoa messoria (Harris, 1841) Euxoa mimallonis (Grote, 1873) Euxoa nevada (J. B. Smith, 1900)  No. of individuals 6 1 1 2 22 1 4 4 1 5 12 4 134 1 10 8 4 1 8 10 1 3 1 1 19 10 1 15 3 3 3 4 8 11 1 3 59 4 1 1 14 31 3 18 3 18 6 6 4 3 2 11 9 9 2  315  Taxon Euxoa obeliscoides (Guenée, 1852) Euxoa oblongistigma (J. B. Smith, 1888) Euxoa perpolita (Morrison, 1876) Euxoa plagigera (Morrison, 1874) Euxoa punctigera (Walker, 1865) Euxoa quadridentata (Grote & Robinson, 1865) Euxoa ridingsiana (Grote, 1875) Euxoa satiens (J. B. Smith, 1890) Euxoa satis (Harvey, 1876) Euxoa servitus (J. B. Smith, 1895) Euxoa silens (Grote, 1875) Euxoa sp. nr. infausta Euxoa sp. nr. satis Euxoa terrenus (J. B. Smith, 1900) Euxoa tessellata (Harris, 1841) Feltia jaculifera (Guenée, 1852) Feltia mollis (Walker, [1857]) Hada sutrina (Grote, 1881) Homorthodes discreta (Barnes & McDunnough, 1916) Homorthodes furfurata (Grote, 1875) Lacinipolia anguina (Grote, 1881) Lacinipolia comis (Grote, 1876) Lacinipolia pensilis group sp. 1 Lacinipolia pensilis group sp. 2 Lacinipolia sp. nr. buscki Lacinipolia stricta (Walker, 1865) Lacinipolia strigicollis (Wallengren, 1860) Lacinipolia vicina group Leucania anteoclara J. B. Smith, 1902 Leucania insueta Guenée, 1852 Leucania multilinea Walker, 1856 Leucania oregona J. B. Smith, 1902 Neoligia invenusta Troubridge & Lafontaine, 2002 Neoligia lillooet Troubridge & Lafontaine, 2002 Neoligia tonsa (Grote, 1880) Orthosia hibisci (Guenée, 1852) Orthosia revicta (Morrison, 1876) Orthosia segregata (J. B. Smith, 1893) Parabagrotis exsertistigma (Morrison, 1874) Parabagrotis sulinaris Lafontaine, 1998 Polia delecta Barnes & McDunnough, 1916 Polia nugatis (J. B. Smith, 1898) Polia piniae Buckett & Bauer, 1967 Polia purpurissata (Grote, 1864) Protolampra rufipectus (Morrison, 1875) Protorthodes curtica (J. B. Smith, 1890) Pseudanarta crocea (Hy. Edwards, 1875) Pseudanarta flava (Grote, 1874) Sideridis rosea (Harvey, 1874) Spaelotis clandestina (Harris, 1841) Tholera americana (J. B. Smith, 1894) Xestia smithii (Snellen, 1896) Xylena cineritia (Grote, 1875) Xylena thoracica (Putnam-Cramer, 1886) Zosteropoda hirtipes Grote, 1874  No. of individuals 20 7 5 60 15 5 4 95 4 44 1 1 3 4 10 130 2 1 1 22 2 1 4 16 12 2 24 4 11 117 1 1 6 7 29 1 3 4 30 5 1 56 1 2 10 158 25 1 2 2 118 1 1 2 2  316  Taxon Oncocnemidinae Apharetra dentata (Grote, 1875) Oncocnemis lacticollis J. B. Smith, 1908 Oncocnemis poliochroa Hampson, 1906 Oncocnemis sp. Pantheinae Panthea acronyctoides (Walker, 1861) Plusiinae Syngrapha orophila (Hampson, 1908)  No. of individuals  1 1 1 1 1 1  Notodontidae (1) Nadata gibbosa (J.E. Smith, 1797)  1 1  Saturniidae (1) Hyalophora euryalus (Boisduval, 1855)  1 1  Sphingidae (2) Smerinthus sp. Sphinx drupiferarum J.E. Smith, 1797  3 1 2  317  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 Drepanidae (1) Drepana bilineata (Packard, 1864) Erebidae (15) Arctiinae Cycnia oregonensis (Stretch, 1873) Grammia nevadensis (Grote & Robinson, 1866) Bruceia pulverina Neumoegen, 1893 Eilema bicolor (Grote, 1864) Calpinae Scoliopteryx libatrix (Linnaeus, 1758) Erebinae Drasteria adumbrata (Behr, 1870) Drasteria divergens (Behr, 1870) Drasteria ochracea (Behr, 1870) Drasteria sabulosa (Hy. Edwards, 1881) Melipotis jucunda (Hübner, 1818) Herminiinae Idia occidentalis (J. B. Smith, 1884) Idia sp. nr. lubricalis Hypeninae Spargaloma sexpunctata Grote, 1873 Lymantriinae Orgyia pseudotsugata (McDunnough, 1921) Rivulinae Mycterophora longipalpata Hulst, 1896 Euteliidae (1) Marathyssa inficita (Walker, 1865) Geometridae (78) Ennominae Anavitrinella pampinaria (Guenée, [1858]) Caripeta aequaliaria Grote, 1883 Caripeta sp. Digrammia californiaria (Packard, 1871) Digrammia curvata (Grote, 1880) Digrammia delectata (Hulst, 1887) Digrammia denticulata (Grote, 1883) Digrammia muscariata (Guenée, [1858]) Digrammia neptaria (Guenée, [1858]) Digrammia ordinata (Walker, 1862) Digrammia respersata (Hulst, 1880) Digrammia triviata (Barnes & McDunnough, 1917)  No. of individuals 1 1 549 4 48 7 51 1 3 1 3 96 1 22 4 2 301 5 1 1 670 3 1 2 1 8 20 7 1 14 21 62 1  318  Taxon Drepanulatrix falcataria (Packard, 1873) Drepanulatrix foeminaria (Guenée, [1858]) Drepanulatrix secundaria Barnes & McDunnough, 1916 Drepanulatrix unicalcararia (Guenée, [1858]) Euchlaena johnsonaria (Fitch, 1869) Euchlaena madusaria (Walker, 1860) Euchlaena tigrinaria (Guenée, [1858]) Eudrepanulatrix rectifascia (Hulst, 1896) Eumacaria latiferrugata (Walker, [1863]) Glena nigricaria (Barnes & McDunnough, 1913) Hesperumia sulphuraria Packard, 1873 Iridopsis clivinaria (Guenée, [1858]) Ixala desperaria (Hulst, 1887) Macaria adonis Barnes & McDunnough, 1918 Macaria bitactata (Walker, 1862) Macaria colata (Grote, 1881) Macaria decorata (Hulst, 1896) Macaria plumosata (Barnes & McDunnough, 1917) Macaria quadrilinearia (Packard, 1873) Macaria sexmaculata Packard, 1867 Macaria signaria (Hübner, [1809]) Melanolophia imitata (Walker, 1860) Pero behrensaria (Packard, 1871) Pero mizon Rindge, 1955 Pero occidentalis (Hulst, 1896) Phaeoura mexicanaria (Grote, 1883) Plagodis phlogosaria (Guenée, [1858]) Plagodis pulveraria (Linnaeus, 1758) Sericosema juturnaria (Guenée, [1858]) Sericosema wilsonensis Cassino & Swett, 1922 Sicya macularia (Harris, 1850) Spodolepis danbyi (Hulst, 1898) Stenoporpia pulmonaria (Grote, 1881) Synaxis cervinaria (Packard, 1871) Geometrinae Chlorochlamys triangularis Prout, 1912 Chlorosea nevadaria Packard, 1873 Nemoria darwiniata (Dyar, 1904) Nemoria glaucomarginaria (Barnes & McDunnough, 1917) Synchlora aerata (Fabricius, 1798) Larentiinae Aplocera plagiata (Linnaeus, 1758) Coryphista meadii (Packard, 1874) Costaconvexa centrostrigaria (Wollaston, 1858) Dysstroma formosa (Hulst, 1896) Dysstroma truncata (Hufnagel, 1767) Eulithis propulsata (Walker, 1862) Eulithis xylina (Hulst, 1896) Eupithecia absinthiata (Clerck, 1759) Eupithecia agnesata Taylor, 1908 Eupithecia behrensata Packard, 1876 Eupithecia maestosa (Hulst, 1896)  No. of individuals 7 8 1 13 2 1 1 8 5 28 5 7 1 4 3 8 13 2 3 1 6 32 3 14 3 9 1 1 110 1 1 1 5 13 1 3 7 2 6 2 1 1 5 1 1 1 2 1 45 1  319  Taxon  No. of individuals  Eupithecia nevadata Packard, 1871 Eupithecia niveifascia (Hulst, 1898) Eupithecia sp. 22 Eustroma semiatrata (Hulst, 1881) Hydriomena renunciata (Walker, 1862) Perizoma costiguttata (Hulst, 1896) Prorella leucata (Hulst, 1896) Stamnodes marmorata (Packard, 1871) Zenophleps alpinata Cassino, 1927 Sterrhinae Idaea demissaria (Hübner, [1831]) Leptostales rubromarginaria (Packard, 1871) Scopula ancellata (Hulst, 1887) Scopula inductata (Guenée, [1858]) Scopula junctaria (Walker, 1861) Scopula luteolata (Hulst, 1880) Scopula quinquelinearia (Packard, 1871)  69 17 3 11 1 1 4  Lasiocampidae (3) Phyllodesma americana (Harris, 1841) Malacosoma californica (Packard, 1864) Tolype dayi Blackmore, 1921  74 8 1 65  Noctuidae (130) Acronictinae Acronicta mansueta J. B. Smith, 1897 Acronicta strigulata J. B. Smith, 1897 Amphipyrinae Apamea acera (J. B. Smith, 1900) Apamea antennata (J. B. Smith, 1891) Apamea devastator (Brace, 1819) Apamea longula (Grote, 1879) Apamea spaldingi (J. B. Smith, 1909) Caradrina meralis (Morrison, 1875) Caradrina montana (Bremer, 1861) Caradrina morpheus (Hufnagel, 1766) Chytonix divesta (Grote, 1874) Condica discistriga (J. B. Smith, 1894) Spodoptera praefica (Grote, 1875) Bryophilinae Cryphia olivacea (J. B. Smith, 1891) Cuculliinae Cucullia eulepis (Grote, 1876) Dilobinae Raphia frater Grote, 1864 Noctuinae Abagrotis apposita (Grote, 1878) Abagrotis discoidalis (Grote, 1876) Abagrotis mirabilis (Grote, 1879) Abagrotis nefascia (J.B. Smith, 1908) Abagrotis placida (Grote, 1876) Abagrotis reedi Buckett, 1969  3 2 1 2 1 1 1 2 9  1014 1 1 1 13 3 1 2 71 10 1 7 9 1 27 1 1 1 1 5 1 2 1  320  Taxon Abagrotis scopeops (Dyar, 1904) Abagrotis trigona (J.B. Smith, 1893) Abagrotis vittifrons (Grote, 1864) Adelphagrotis indeterminata (Walker, 1865) Admetovis oxymorus Grote, 1873 Admetovis similaris Barnes, 1904 Agrotis sp. nr. carolina Agrotis venerabilis Walker, [1857] Anaplectoides prasina ([Denis & Schiffermüller], 1775) Anarta columbica (McDunnough, 1930) Anarta crotchii (Grote, 1880) Anarta decepta (Grote, 1883) Andropolia aedon (Grote, 1880) Dichagyris variabilis (Grote, 1874) Egira crucialis (Harvey, 1875) Egira curialis (Grote, 1873) Egira perlubens (Grote, 1881) Egira simplex (Walker, 1865) Epidemas obscurus J. B. Smith, 1903 Eurois occulta (Linnaeus, 1758) Euxoa agema (Strecker, 1899) Euxoa albipennis (Grote, 1876) Euxoa atomaris (J. B. Smith, 1890) Euxoa auripennis Lafontaine, 1974 Euxoa bicollaris (Grote, 1878) Euxoa bochus (Morrison, 1874) Euxoa castanea Lafontaine, 1981 Euxoa catenula (Grote, 1879) Euxoa cf. setonia Euxoa choris (Harvey, 1876) Euxoa difformis (J. B. Smith, 1900) Euxoa divergens (Walker, [1857]) Euxoa excogita (J. B. Smith, 1900) Euxoa infausta (Walker, 1865) Euxoa infracta (Morrison, 1875) Euxoa messoria (Harris, 1841) Euxoa mimallonis (Grote, 1873) Euxoa obeliscoides (Guenée, 1852) Euxoa olivia (Morrison, 1876) Euxoa plagigera (Morrison, 1874) Euxoa pluralis (Grote, 1878) Euxoa punctigera (Walker, 1865) Euxoa rockburnei Hardwick, 1973 Euxoa satis (Harvey, 1876) Euxoa septentrionalis (Walker, 1865) Euxoa silens (Grote, 1875) Euxoa sp. nr. brunneigera Euxoa sp. nr. excogita Euxoa sp. nr. satis Euxoa terrenus (J. B. Smith, 1900) Euxoa tessellata (Harris, 1841) Feltia jaculifera (Guenée, 1852)  No. of individuals 2 10 2 1 4 1 2 80 1 38 2 5 1 7 1 7 6 2 1 4 1 3 5 1 3 2 3 2 3 1 11 1 1 1 3 2 1 4 2 8 3 9 2 7 1 5 1 1 1 25 7 134  321  Taxon Hadena variolata (J. B. Smith, 1888) Homorthodes discreta (Barnes & McDunnough, 1916) Homorthodes furfurata (Grote, 1875) Lacanobia sp. nr. subjuncta Lacinipolia pensilis group sp. 1 Lacinipolia pensilis group sp. 2 Lacinipolia sp. nr. buscki Lacinipolia stricta (Walker, 1865) Lacinipolia strigicollis (Wallengren, 1860) Lacinipolia vicina group Leucania insueta Guenée, 1852 Leucania oregona J. B. Smith, 1902 Lithophane atara (J. B. Smith, 1909) Lithophane ponderosa Troubridge & Lafontaine, 2003 Mesogona taedata (Harvey, 1874) Neoligia invenusta Troubridge & Lafontaine, 2002 Neoligia lancea Troubridge & Lafontaine, 2002 Noctua pronuba (Linnaeus, 1758) Orthosia revicta (Morrison, 1876) Orthosia segregata (J. B. Smith, 1893) Papestra brenda (Barnes & McDunnough, 1916) Papestra invalida (J. B. Smith, 1891) Parabagrotis exsertistigma (Morrison, 1874) Parabagrotis sulinaris Lafontaine, 1998 Polia delecta Barnes & McDunnough, 1916 Polia piniae Buckett & Bauer, 1967 Pronoctua typica J. B. Smith, 1894 Properigea albimacula (Barnes & McDunnough, 1912) Protolampra brunneicollis (Grote, 1865) Protolampra rufipectus (Morrison, 1875) Protorthodes curtica (J. B. Smith, 1890) Pseudanarta crocea (Hy. Edwards, 1875) Setagrotis pallidicollis (Grote, 1880) Sideridis rosea (Harvey, 1874) Spaelotis bicava Lafontaine, 1998 Spaelotis clandestina (Harris, 1841) Spaelotis unicava Lafontaine, 1998 Tesagrotis corrodera (J. B. Smith, 1907) Tesagrotis piscipellis (Grote, 1878) Tholera americana (J. B. Smith, 1894) Xestia oblata (Morrison, 1875) Zotheca tranquilla Grote, 1874 Oncocnemidinae Homohadena fifia Dyar, 1904 Oncocnemis greyi Troubridge & Crabo, 1998 Oncocnemis parvanigra Blackmore, 1923 Oncocnemis poliochroa Hampson, 1906 Oncocnemis semicollaris J. B. Smith, 1909 Oncocnemis sp. Pleromelloida bonuscula (J. B. Smith, 1898) Pleromelloida sp. Sympistis amun Troubridge, 2008  No. of individuals 2 12 14 6 3 2 7 4 20 9 38 1 1 2 7 1 1 6 1 2 3 1 9 1 13 5 3 9 1 1 117 5 7 4 1 3 3 2 2 17 1 2 5 23 4 1 5 22 2 3 1  322  Taxon  No. of individuals  Sympistis cocytus Troubridge, 2008 Pantheinae Panthea acronyctoides (Walker, 1861) Panthea virginarius (Grote, 1880) Plusiinae Anagrapha falcifera (Wm. Kirby, 1837) Autographa californica (Speyer, 1875)  1  Notodontidae (4) Clostera apicalis (Walker, 1855) Gluphisia septentrionis Walker, 1855 Gluphisia severa Hy. Edwards, 1886 Nadata gibbosa (J.E. Smith, 1797)  7 1 1 1 4  Saturniidae (1) Hyalophora euryalus (Boisduval, 1855)  2 2  Sphingidae (5) Paonias excaecata (J.E. Smith, 1797) Paonias myops (J.E. Smith, 1797) Smerinthus sp. Sphinx perelegans Hy. Edwards, 1874 Sphinx vashti Strecker, 1878  39 1 3 3 8 24  Uraniidae (1) Callizzia sp.  1 2 2 1  1 1  323  

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