Diversity and Ecological Structure of Northern Biting Flies

Diversity and Ecological Structure in Northern Biting Flies

Patrick Schaefer

A thesis submitted in conformity with the requirements for the degree of Masters of Science Ecology and Evolutionary Biology University of Toronto

Diversity and Ecological Structure in Northern Biting Flies

Patrick Schaefer

Masters of Science Degree

Ecology and Evolutionary Biology University of Toronto

2014 Abstract Contemporary climate change disproportionately impacts northern environments. Understanding these impacts requires knowledge of the ecological structure (e.g. diversity, abundance and distribution) of resident species. Biting flies are among the best-known groups of insects in northern Canada and are excellent sentinels for environmental change. The goals of this thesis are to determine how climate and geographical history affect the ecological structure of black flies and mosquitoes. Assessment of large-scale macroecological patterns revealed contrasts between Arctic and southern assemblages, while highlighting the importance of geographic history in structuring assemblages. Finer-scale sampling and analysis were used to assess the impacts of contemporary climate change on species ranges. A critical threshold temperature for the presence of biting species of black flies was found that approximates minimum requirements for flight and blood-feeding. Finally, mitochondrial DNA markers allowed the assessment of cryptic diversity in a widely distributed assemblage of northern black flies of the genus

Stegopterna.

Acknowledgments

I would like to express my deepest gratitude to my supervisor, Dr. Douglas C. Currie, whose expertise, understanding, and patience have added considerably to my graduate experience. I appreciate his vast knowledge and skills in many areas, as well as his assistance in writing reports. I would also like to thank the other members of my supervisory committee, Dr. Donald Jackson, and Dr. Alan Baker for the assistance they provided at all levels of the research project.

This research would not have been possible without the Northern Biodiversity Program. I acknowledge the contributions of the Northern Biodiversity Programs principle investigators: Dr. Chris Buddle (McGill University), Dr. Terry Wheeler (McGill University/Lyman Museum), Dr. Donna Giberson (Unviersity of Prince Edward Island) and Dr. Douglas C. Currie (University of Toronto/Royal Ontario Museum) for securing initial funding and providing logistical support for the duration of the project. I also acknowledge the collection and processing efforts of other Northern Biodiversity Program members: S. Laboda, K. Sim, L. Timms, A. Solecki, M. Blair and R. Cordero. I am very grateful for assistance provided by Royal Ontario Museum staff from the Entomology Department Brad Hubley and Antonia Guidotti as well as Kristen Choffe from the Laboratory of Molecular Systematics. I also thank Ida Conflitti (University of Toronto), Laura Timms (Royal Ontario Museum/Credit Valley Conservation), Peter Adler (Clemson University), Sally Adamowicz (Guelph University/Biodiversity Institute of Ontario) and Monty Wood (Canadian National Collection of Insects and Arachnids) for their input and guidance at various stages during this research. Finally, I am grateful towards my loving wife Heather for spending many long hours sorting flies with me in the lab and her patience and support in all aspects of my work.

This work was supported by a National Science and Engineering Research Council of Canada (NCERC) Strategic Project Grant (Ecological Structure of Northern Arthropods: Adaptation to a Changing Environment) awarded to C. Buddle, T. Wheeler, and D. Currie, its supporting partners and collaborators, a NSERC Discovery Grant to D.C. Currie and a NSERC – Canada Graduate Scholarship and Ontario Graduate Scholarship awarded to P. Schaefer.

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Table of Contents

Acknowledgments ...... ii

Table of Contents ...... iv

List of Tables ...... vi

List of Figures ...... vii

Chapter 1 - General Introduction ...... 1

1.1 References ...... 4

Chapter 2 - Environmental and historical determinants of mosquito (Culicidae) and black fly (Simuliidae) assemblage structure in northern Canada ...... 6

2.1 Abstract ...... 6 2.2 Introduction ...... 6 2.3 Materials and Methods ...... 9 2.3.1 Biological Data ...... 9 2.3.2 Explanatory Variables ...... 10 2.3.3 Analytical Methods ...... 11 2.4 Results ...... 13 2.5 Discussion ...... 15 2.5.1 Assemblage Structure and the Importance of Predictor Variables ...... 15 2.5.2 Macrodistributional Patterns ...... 17 2.5.3 Patterns of Species Richness ...... 18 2.6 References ...... 21 2.7 Tables ...... 31 2.8 Figures ...... 36

Chapter 3 - Climate-induced changes in Arctic black fly communities ...... 45

3.1 Abstract ...... 45 3.2 Introduction ...... 46 3.3 Materials and Methods ...... 47 3.3.1 Study Sites ...... 47

3.3.2 Climate and Species Assemblages ...... 48 3.4 Results ...... 50 3.4.1 Historical and Contemporary species records ...... 50 3.4.2 Temperature Thresholds for Bloodsucking Species ...... 51 3.4.3 Patterns of Species Richness ...... 51 3.5 Discussion ...... 52 3.5.1 Distinguishing Inadequate Baseline Data from Bona Fide Examples of Range Expansion...... 52 3.5.2 Factors Limiting the Distribution of Bloodsucking Black Flies ...... 54 3.5.3 Species Richness and Community Saturation ...... 55 3.5.4 Implications of a Northward Migration of Bloodsucking Black Flies...... 56 3.6 References ...... 60 3.7 Tables ...... 64 3.8 Figures ...... 68

Chapter 4 - Cryptic diversity in northern Nearctic Stegopterna Enderlein (Diptera: Simuliidae)...... 75

4.1 Abstract ...... 75 4.2 Introduction ...... 75 4.3 Materials and Methods ...... 77 4.3.1 Samples and laboratory procedures ...... 77 4.3.2 Data Analysis ...... 78 4.4 Results ...... 79 4.4.1 mtDNA Sequence Diversity and Barcoding Analysis ...... 79 4.4.2 Phylogenetic Structure ...... 80 4.5 Discussion ...... 80 4.6 References ...... 85 4.7 Tables ...... 89 4.8 Figures ...... 91

Chapter 5 - General conclusion ...... 99

List of Tables

Chapter 2

Table 1. Location of the 11 sampling localities, species richness, and predictor variables used in this study ...... 31 Table 2. Relative variable importance calculated with Akaike Information Criterion (AIC) and corrected Akaike Information Criterion (AICc) ...... 32 Supplementary Table 1. Black fly species included in the present study...... 33 Supplementary Table 2. Mosquito species included in the present study ...... 35

Chapter 3

Table 1. Summary of black fly occurrence on Banks, Victoria and Baffin Islands, with indication of distributional category, feeding habits and vector status ...... 64 Table 2. Estimates of local and regional species richness ...... 65 Supplementary Table 1. Black fly collection sites ...... 66

Chapter 4

Table 1. List of black fly species examined in the present study ...... 89

List of Figures

Chapter 2

Figure 1. Location of 11 sampling localities in northern Canada ...... 36 Figure 2. CCA ordination scatterplot of black fly assemblages and correlations with predictor variables...... 37 Figure 3. CCA ordination scatterplot of mosquito assemblages and correlations with predictor variables...... 38 Figure 4. Variation partitioning of black fly and mosquito assemblage structure via pCCA .... 39 Figure 5. Cluster analysis of black fly assemblages and ordered community data matrix ...... 40 Figure 6. Cluster analysis of mosquito assemblages and ordered community data matrix ...... 41 Figure 7. Relative importance of predictor variables in determining species richness calculated with LMG methods ...... 42 Supplemental Figure 1. CCA ordination scatterplots of black fly and mosquito assemblages with the inclusion of rare species and correlations with predictor variables ...... 43 Supplemental Figure 2. pCCA ordination scatterplots of black fly and mosquito assemblages44

Chapter 3

Figure 1. Historical collections of black flies in northern Canada ...... 68 Figure 2. Distribution of black flies on Victoria Island relative to mean summer temperature ...... 69 Figure 3. Relationship between temperature and presence of bloodsucking species of black fly ...... 70 Figure 4. Relationship between temperature and species richness ...... 71 Figure 5. Relationship between local and regional species richness ...... 72 Figure 6. Predicted future distribution of bloodsucking black flies on the Canadian Arctic Archipelago ...... 73 Figure 7. Nesting female snowy owl (Bubo scandiacus) after attacks by black flies in Karasjok, Norway ...... 74

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Chapter 4

Figure 1. Map of study region showing sampling sites and known distributions of three northern Stegopertna species ...... 91 Figure 2. Frequency distribution of intraspecific and interspecific K2P distances for five Stegopterna BINs ...... 92 Figure 3. NJ tree of COI sequences generated using K2P distances ...... 93 Figure 4. Phylogenetic relationships recovered with Bayesian methods of Stegopterna COI sequences ...... 94 Figure 5. NJ tree of COI + COII sequences generated using T92 distances ...... 95 Figure 6. Phylogenetic relationships recovered with Bayesian methods of among Stegopterna COI+COII sequences ...... 96 Figure 7. Map of study region showing distributions of Stegopertna BINs ...... 97 Figure 8. A) Pupa of undescribed Stegopterna from Iqaluit showing length of common gill trunk...... 98

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Chapter 1 General Introduction

Northern ecosystems are among the most fragile on earth; they are also under threat as the rate of climate warming is double that for the world as a whole (IPCC 2013). The impacts of warming have already been observed in changes to forest productivity (Beck et al., 2011), northward range shifts (Itämies et al., 2011) and altered host-parasite dynamics (Zamora-Vilchis et al., 2012). Unfortunately, the vastness of the territory, coupled with the logistical problems associated with fieldwork in the far north, means that baseline data are lacking for most organisms. A better understanding of their ecological structure (i.e. abundance, diversity and range) is needed to understand the full impact of climate on the northern biota. Arthropods serve as excellent models to assess environmental change because of their abundance, rapid population growth, and ability to respond to changing conditions. This thesis examines broad-scale ecological structure and biodiversity patterns in two of the most prominent families of biting flies in northern Canadian — black flies (Simuliidae) and mosquitoes (Culicidae).

The Canadian Arctic covers 4.8 million square kilometers (Marshall et al., 1999), supporting an estimated 23,500 insect species — 22,000 of which are residents of the Boreal ecoclimatic zone (Danks & Foottit, 1989) and 1,500 of which live in the treeless Arctic zone (Danks, 1981). Black flies and mosquitos are worldwide in distribution, but are especially prominent at northern latitudes where the bloodsucking habits of adult females can impose both economical and ecological challenges. Economically, biting flies can greatly impact humans and livestock through haematophagy; they are also vectors of parasitic diseases to a wide variety of domestic and wild animals. Ecologically, black flies can occur in astronomical numbers in Canada’s north, with the immature and adult stages forming an important part of the aquatic and terrestrial food-webs, respectively (Stephenson, 2007). Both black flies and mosquitoes rely on water to complete their development — the former needing running water and the latter standing water. Northern regions are particularly well endowed with such habitats because of poor drainage from the presence of bedrock or permafrost immediately below the soil. Furthermore, conditions are ideal for the maintenance of huge populations of biting flies. For example, Jenkins (1948) estimated that streams in central Alaska could support larval populations of black flies in excess of a million larvae per square meter of stream bottom. Mosquitoes also occur in

2 impressive numbers, with more than 2,000 larvae reported per square meter in subarctic pools (Haufe, 1957), and 12.5 million adult mosquitoes per hectare in the Hudson Bay Lowland near Churchill, Manitoba (Wood, 1985).

My thesis research is part of the Northern Biodiversity Program (NBP) — a collaborative research initiative that aims to document changes to the northern arthropod fauna. The approach is to compare contemporary collections of northern arthropods with those collected during the 1947-1962 Northern Insect Survey (NIS). The NIS was an unprecedented initiative that sampled diversity at 72 sites throughout northern North America at a time when climate change was not yet of global concern. The focus of my research is on biting flies; more specifically, how climate and geographical history have shaped (and continue to shape) the diversity and distribution of these insects.

I was responsible for the biting fly component of the NBP, assisting in the development of collection protocols for mosquitoes (Culicidae), black flies (Simuliidae) and horse- and deer flies (Tabanidae). Specimens of these three families were initially sorted to lowest taxonomic level possible using morphological keys (typically to species or species group). Exemplars of known species complexes of black flies were sent to Peter Adler (Clemson University) for cytological screening. DNA barcoding was conducted primarily by myself in the Laboratory of Molecular Systematics at the Royal Ontario Museum; in some instances, DNA was sent to the Canadian Center for DNA Barcoding for sequencing. Nearly 50,000 specimens of biting flies were identified and curated as part of this research, including larvae, pupae and adults. Three hundred and sixty one of these were selected for DNA barcoding, and their sequences are now available in the Barcode of Life Database. Detailed analyses on horse- and deer flies were not undertaken because they do not occur on the Canadian Arctic Archipelago and collections elsewhere varied markedly in terms of numbers collected. In addition to my work on biting flies, I contributed to the NBP generally by participating in qualitative- and quantitative collecting protocols for terrestrial and aquatic arthropods at six NBP sites. I visited Moosonee ON, Churchill MB and Iqaluit NU during the summer of 2010, and Yellowknife NT, Kugluktuk NU and Cambridge Bay NU during the summer of 2011.

In Chapter 2, I investigate large-scale patterns of species richness and assemblage structure in northern mosquitoes and black flies. This set the stage for Chapter 3, wherein I focus

3 on how climate change has (and is) promoting a northward expansion of black fly species ranges. Finally, chapter 4 addresses how to more effectively assess biodiversity in remote and inaccessible terrain, like Canada’s north. Mitochondrial DNA markers were used to assess cryptic diversity in enigmatic and little-studied populations of northern species in the black fly genus Stegoptera. Collectively, these three chapters are intended to shed important new insights about the diversity and distributional patterns of mosquitoes and black flies in northern Canada, providing a more solid framework for documenting adaptations to ongoing ecological change.

1.1 References

Beck, P.S.A., Juday, G.P., Alix, C., Barber, V.A., Winslow, S.E., Sousa, E.E., et al. (2011) Changes in forest productivity across Alaska consistent with biome shift. Ecology Letters, 14, 373–379.

Danks, H. (1981) Arctic Arthropods: A review of systematics and ecology with particular reference to the North American fauna. Entomological Society of Canada, Ottawa, Canada.

Danks, H. & Foottit, R. (1989) Insects of the boreal zone of Canada. The Canadian Entomologist, 121, 625–690.

Haufe, W. (1957) Physical environment and behaviour of immature stages of Aedes communis (Deg.)(Diptera: Culicidae) in subarctic Canada. The Canadian Entomologist, 89, 120–139.

Itämies, J.H., Leinonen, R. & Meyer-Rochow, V.B. (2011) Climate Change and Shifts in the Distribution of Moth Species in Finland, with a Focus on the Province of Kainuu. In Climate Change - Geophysical Foundations and Ecological Effects. InTech, Croatia, pp. 273–296.

IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp.

Jenkins, D.W. (1948) Ecological observations on the blackflies and punkies of Central Alaska. Mosquito News, 8, 148–54.

Marshall, I., Schut, P. & Ballard, M. (1999) A national ecological framework for Canada: attribute data. Environmental Quality Branch, Ecosystems Science Directorate, Environment Canada and Research Branch, Agriculture and Agri-Food Canada, Ottawa/Hull.

Stephenson, S.. (2007) Fishes of the Thomsen River, Banks Island, Northwest Territories. Canadian Manuscript Repository - Fish and Aquatic Sciences, 2944, 1–44.

Wood, D.M. (1985) Biting flies attacking man and livestock in Canada. Agriculture Canada, Ottawa, Canada.

Zamora-Vilchis, I., Williams, S.E. & Johnson, C.N. (2012) Environmental Temperature Affects Prevalence of Blood Parasites of Birds on an Elevation Gradient: Implications for Disease in a Warming Climate. PLoS ONE, 7, e39208.

Chapter 2 Environmental and historical determinants of mosquito (Culicidae) and black fly (Simuliidae) assemblage structure in northern Canada

2.1 Abstract

Both ecological and historical factors interact to shape contemporary communities. Northern Canada is an ideal region for studying the interplay between these factors due to large ecological gradients and recent historical influences from Pleistocene glaciations. In this study I use geographical and ecological data to examine patterns of species richness and assemblage structure among mosquito and black fly populations in northern Canada. Historical and contemporary species data were used to ensure that communities were accurately documented throughout the study area. The data suggest that mosquito and black fly assemblages from the Arctic Ecoclimatic region differ markedly from those of the Boreal and Subarctic Ecoclimatic regions, with temperature being the primary determining factor. Temperature is also the largest contributor to patterns of species richness in both families. In the Boreal and Subarctic Ecoclimatic regions, black fly assemblages exhibit significant differences between eastern and western sites, whereas mosquito assemblages depend more on ecological factors and show weaker geographical patterns. The east-west difference in black fly community structure is attributed mainly to historical factors — probably the result of different refugia during the Wisconsin glaciation.

2.2 Introduction

A fundamental goal of ecology is to understand the patterns and processes governing the distribution of species. Traditionally, ecologists viewed variation among assemblages as being driven predominantly by environmental factors, without much consideration to the effect of historical processes (i.e. McArthur, 1972; Cody, 1975). However, biogeographers have argued that historical factors such as dispersal, vicariance, and extinction are crucial for understanding species distributions (Cracraft, 1994; Tuomisto et al., 2003; Wiens & Donoghue, 2004).

Subsequent incorporation of these phenomena into ecological studies has significantly improved our understanding of biodiversity patterns (Ricklefs & Schluter, 1993; Graham et al., 2005, 2006; Webb et al., 2006; Ricklefs & Jenkins, 2011).

Recent studies examining the effects of historical processes on communities have related geographic distance between communities to differences in species richness and/or assemblage structure (Ribera et al., 2003; Legendre et al., 2005; Baselga & Jimenez-Valderde, 2007; Hof et al., 2008; Keil et al., 2008; Kamilar, 2009). Across broad geographic scales, limited dispersal results in similar species assemblages among geographically proximate locations, with differences increasing with distance (Legendre et al., 2005). Conversely, geographically proximate sites may support vastly different assemblages if historical processes such as vicariance/extinction events or dispersal barriers strongly influenced the distribution of taxa. Determining the relative importance of environmental and spatial factors in structuring biotic assemblages is critical for understanding the origin of biodiversity and how taxa respond to changes in climate and landscapes.

The vast territory of northern Canada is an ideal setting for investigating factors that influence species distributions (Danks, 1981; Weider & Hobaek, 2000). First, communities at northern latitudes are typically simpler than those farther south, and are therefore easier to evaluate. Secondly, there is marked variation among the three Ecoclimatic regions that dominate the Canadian north. For example, the Arctic Ecoclimatic region is characterized by colder temperatures, shorter summers, stronger winds and sparser vegetation than the Subarctic- and Boreal Ecoclimatic regions (Danks & Foottit, 1989). Consequently, the Arctic is beyond the physiological limit of many organisms (Danks, 1981). In addition to contemporary ecological factors, historical (Pleistocene-aged) glacial events also played a role in shaping the northern biota (Weider & Hobaek, 2000). During the last (i.e., Wisconsin) glaciation, most of northern Canada was covered in thick layers of ice. With the retreat of continental glaciers just ~8-12 kya, present-day assemblages in previously glaciated regions are considerably younger than those of adjacent refugial areas (e.g., Beringia). Together, these ecological- and historical traits make northern Canada an ideal setting to study the relative contribution of contemporary ecological and historical factors that structure biological communities.

Mosquitoes (Culicidae) and black flies (Simuliidae) are numerous and conspicuous members of the northern biota. They are especially renowned for the bloodsucking habit of adult bloodsucking habit of females and transmission of parasitic diseases to hosts (Kramer et al., 2008; Adler et al., 2010). Consequently, these two families are among the most completely studied groups of insects in North America. Mosquitoes and black flies attain their greatest population densities at northern latitudes, and can have significant negative impacts on humans and wild and domestic animals. For instance, Caribou herds are driven onto harsh windswept mountains and ridges in an effort to escape swarms of biting flies (Toupin et al., 1996). Similarly, black flies are a blight on northern birds, having been implicated in deaths of juvenile Great Horned Owls (Hunter et al., 1997), Snowy Owls (Solheim et al., 2013) and Peregrine Falcons (Alasdair Franke, Pers. Comm.). Biting flies achieve their great abundance because of the prominence of favorable breeding sites in northern Canada. Permafrost results in poor drainage, which in turn leads to the formation of ponds and streams — the larval habitat of mosquitoes and black flies, respectively.

Patterns of species richness and distribution relate directly to economic the impact of biting flies, and are influenced by both biotic and abiotic factors (e.g., Grillet et al., 2001; Andreadis et al., 2004). Previous studies on mosquitoes and black flies investigated patterns on a regional scale — appropriate for the management of local pest species and disease vectors. However, such studies provide little information about the macro-distribution of species that constitute the local species pool. Investigating causal factors that influence the distributions of biting flies represents an important avenue of investigation. Factors that influence the distribution of biting flies can be grouped into 2 broad categories: historical and environmental. Historical factors, such as the Pleistocene glaciation, are known to influence the present-day distributions of biting flies and other organisms (Currie, 1997; Brant & Orti, 2003; Drovetski & Ronquist, 2003; Adler et al., 2004; Galbreath & Cook, 2004). Environmental factors include climate and habitat features. Climatic variables, especially temperature, have been shown to significantly influence species growth and development (Colbo & Porter, 1981; Merritt et al., 1982; Ross & Merritt, 1987; Shipp et al., 1988; Beketov et al., 2010), and have potential to limit the northernmost distributions of species. Other habitat characteristics that can influence species distributions include geology, vegetation and elevation. Areas with greater elevational

9 heterogeneity offer a wider variety of habitats, which may influence distributions and biodiversity patterns.

Using a combination of contemporary and historical collection data, we describe patterns of biodiversity in northern Canadian black flies and mosquitoes. Specifically, we assess patterns of species richness and assemblage structure in terms of environmental and historical factors as well as determine the relative contributions of each factor to the observed biodiversity patterns.

2.3 Materials and Methods

2.3.1 Biological data

Contemporary data were derived from the 2010-2012 Northern Biodiversity Program (NBP), which aimed to document arthropod diversity patterns in northern Canada (Ernst & Buddle, 2013; Timms et al., 2013). Arthropods were collected from 12 widely distributed sites in northern Canada, with 4 sites each in the Boreal, Subarctic, and Arctic Ecoclimatic regions (fig. 1, Table 1). Only 3 of 4 Arctic sites are included in the present study as the northernmost site (i.e., Lake Hazen, Ellesmere Island) supported no black flies and only 2 species of mosquito. The other locations were visited at least once during the summers of 2010-2012. Collections were made during a two-week period at each site using standard protocols. A minimum of 10 lentic and 10 lotic habitats were sampled for the immature stages of mosquitoes and black flies, respectively. For black flies, an effort was made to collect a minimum of 30 specimens from each stream, making sure that all available microhabitats were sampled (McCreadie & Adler, 1998; Hamada et al., 2002; McCreadie et al., 2005). Larvae were fixed in 1:3 acetic ethanol (Carnoy’s fixative) and 95% ethanol to facilitate cytological- and molecular analyses, respectively. Adults were collected using sweep nets, aerial nets and malaise traps, with all material fixed in 95% ethanol. Mosquito larvae were collected from a wide variety of prospective breeding sites. Larger-sized habitats (e.g., small lakes, ponds) were sampled using a mosquito dipper. Smaller-sized habitats (e.g., hummock water, rock crevices) were sampled using a small aquarium net or large pipette. Most immature mosquitoes were fixed in 95% ethanol, with selected last-instar larvae and pupae reared to the adult stage. Male and female mosquitoes were also collected using an aerial net, whereas host-seeking females were aspirated selectively from humans. Reared and wild-caught adults were pinned to facilitate morphological

10 identification. All mosquito and black fly material was initially identified to lowest taxonomic level using the morphological keys of Wood et al. (1979) and Adler et al. (2004), respectively. To account for the vagaries of inter-annual variation and the potential for differences in collecting efficacy among field crews, we include historical distributional records to develop as complete a profile as possible for the mosquito and black fly communities at each site. Data come primarily from collections made during the Northern Insect Survey (NIS), which sampled the same 11 sites (and many others) from 1948-1962 (Twinn, 1950; Shewell, 1957). Other sources of historical records include: (Peterson, 1970; Wood, 1978; Wood et al., 1979; Procunier, 1982; Adler et al., 2004; Darsie et al., 2005). Combining historical and contemporary collection data may introduce errors from very recent range expansions (c.f., chapter 3); however, the aim of this study was to investigate the determinants of long-term macrodistributional patterns, which overshadow recent changes.

2.3.2 Explanatory Variables

Because of the relatively small number of observations, only a limited number of predictor variables could be tested. We recognize 2 broad categories as follows:

1) Geographic (Historical): Universal Transverse Mercator coordinates were chosen to represent spatial variables as the true distances between sites. The x (LAT) and y (LON) coordinates of each locality were included in analysis as a proxy for historical factors including dispersal, variance and extinction. 2) Environmental: This category includes 2 factors related to local habitats: a. Climate: A large number of climatic variables were considered for inclusion in this analysis. Nineteen bioclimatic variables were calculated from 1981-2010 normalized climate data (Hijmans et al., 2005, 2011; Mekis & Vincent, 2011; Vincent et al., 2012) for climate stations situated nearest to our sampling localities. A number of techniques were used to select the most appropriate predictors. First, principal component analysis was first used to identify variables that explain similar components of variation. Mean Summer Temperature (MST-Bio10) and Total Annual Precipitation (TAP-Bio12) were minimally correlated and chosen for further analysis — both for the simplicity in their interpretation and their comparability among studies.

b. Elevational Heterogeneity: Areas with greater altitudinal variation offer a wider variety of habitats and — at least among black flies — promote the highest species richness (Adler et al., 2004). Altitudinal variation was classified as the range of elevation (maximum – minimum) occurring within a 1° radius of the sampling site. This provides an estimate of altitudinal variation within the flight range of most species of mosquitoes and black flies.

2.3.3 Analytical Methods

The large spatial scales of the present study present difficulties for analysis. Among aquatic organisms, the distinction between local and regional assemblages are unclear, though the regional unit is often considered to provide species for the local scale (Angermeier & Winston, 1998; Johnson et al., 2004). Consequently, individual streams and lakes are often considered as the local scale, and regional assemblages are considered the sum of all species from local collections in that region (e.g. McCreadie & Adler, 1998; Lake, 2000; Ribera et al., 2003; Johnson et al., 2004; Belmaker & Jetz, 2011). The individual localities in the present study represent regional species pools that are variously distributed throughout multiple ecoclimatic regions. As a result, the overall analysis is on a continental scale which is beyond the spatial scale of many methods of describing biodiversity patterns (e.g. nestedness and beta-diversity). Other studies investigating patterns on these spatial scales simplify their data and/or analysis with a priori assumptions, often grouping assemblages into regional subsets (e.g. Ribera et al., 2003; Bossenbroek et al., 2005; Qian & Ricklefs, 2007; Hof et al., 2008; Keil et al., 2008). Due to the relatively limited number of sites in the present study, we use broader methods that are relatively free of assumptions relating to spatial scale.

Ordination analysis was used to explore relationships between predictor variables and assemblage structure for each family. Canonical Correspondence Analysis (CCA) was used for assessing patterns of assemblage structure relative to predictor variables (Neff & Jackson, 2011). This method was chosen as it presumes a unimodal response of species abundance and occurrence to underlying gradients. A partial CCA (pCCA) was further used to assess the influence of environmental factors after accounting for geographical parameters (Borcard & Legendre, 1994; Borcard et al., 2004). In Canonical Correspondence Analysis, the sum of canonical eigenvalues divided by the total inertia of species data relates to the amount of

12 explained variation (Legendre et al., 2005). The variation in assemblage structure was thereby attributed to pure and shared components of environmental, elevational and spatial components. Correlations between predictor variables and resulting 2 dimensional ordinations were calculated to determine the relative importance of each in determining assemblage structure. Analyses were performed using the vegan 2.0-9 package (Oksanen et al., 2013) for R 3.0.2 (R Core Development Team, 2013).

A hierarchical clustering analysis was performed to delineate major faunal groupings. Ward’s minimum variance method was applied to Bray-Curtis distances of the faunal data. Cluster diagrams are displayed in relation to species by site matrices to qualitatively illustrate macrodistributional patterns. Analyses were performed using the vegan 2.0-9 package (Oksanen et al., 2013) for R 3.0.2 (R Core Development Team, 2013).

We investigate the relationship between predictor variables and species richness using multiple linear regressions. The relative contribution of each predictor variable to the multiple regression models was assessed using the unweighted averaging-over-orders technique (LMG) in the R package relaimpo (Grömping, 2006). A limitation of standard multiple regression is its dependence on the order in which variables are added in the equation. In this study, LAT is highly correlated with MST, and only one or the other will be significant in a standard regression equation. However, each variable has its own biological interpretation (i.e., dispersal limitation vs. physiological limitation), and both can act simultaneously. Relative Importance analysis estimates the contribution of a predictor variable by averaging its r2 across all possible combinations of the regression equation. The benefit of this approach is that it estimates the relative contribution each regressor makes to r2, considering both its direct effects and its effects when combined with the other variables in the regression equation (Johnson & LeBreton, 2004). Bootstrap confidence intervals were calculated based on 10,000 replicates. For comparative purposes an AIC method of relative variable importance was also used from the R package MuMIn (Barton, 2013). A variety of techniques were used including using AIC and AICc, as well as averaging over all possible models or a subset of the top 5 models.

2.4 Results

Contemporary collections yielded a total of 32 species or species complexes of black flies and 20 species of mosquitoes. Addition of historical distributional records increased the black fly data matrix to 55 species or species complexes; however, 10 rare species (i.e., those that occurred at just one site) were excluded from ordinations because of their disproportionate influence on ordination analysis (Poos & Jackson, 2012) (suppl. fig. 1). Addition of historical distributional records increased the mosquito matrix to 37 species, with 4 rare species excluded from analysis. The entire species matrices were used for analysis on species richness.

Ordinations performed using CCA yielded significant separation among sites (fig. 2, 3). All predictor variables show a high degree of correlation with ordination axes except elevational heterogeneity (TER). The first axis predominantly represents a latitudinal gradient and explains 43% and 57% of the variation in black flies and mosquitoes respectively. Axis 1 in both families separated Arctic and the northernmost Subarctic sites (Bks, Iql, CbB, Kgl) from remaining Subarctic and Boreal sites. The second axis in both families represented a longitudinal gradient, which explains 26% and 17% of the variation in black flies and mosquitoes respectively. Among black flies, the second axis shows a clear separation between eastern (Moo, Goo, Sch) and western (Chu, OgM, Ylk, NmW) sites in the Subarctic and Boreal Ecoclimatic regions. Mosquito assemblages follow a similar pattern; however, western sites are more dispersed, with Ylk and NmW further separated from Chu and OgM.

Scatterplots of pCCA results show the importance of environmental predictors, after accounting for the effects of geographic variables (suppl. fig. 2). In both families, temperature remains the greatest determinant of assemblage structure. Elevational heterogeneity becomes increasing important in structuring black fly assemblages after accounting for geographic variables (r2 increases from 0.29 in the CCA to 0.41 in the pCCA in black flies). Examination of this elevational vector suggests that after accounting for geographic differences, species assemblages are similar in areas of high- (i.e. OgM, Iql, Sch, Goo), and low- (i.e. Bks, Chu, CbB, Moo) elevational heterogeneity regardless of ecological factors . After accounting for geographic variation, only mean summer temperature (MST) remained highly correlated to mosquito assemblages and neither climatic nor elevational variables were highly correlated in black flies.

Partitioning variation into 3 categories (i.e., geography, climate and elevation) led to negative components of variation – a result of the large component of shared variation (28% and 31% in black flies and mosquitoes respectively). Therefore, climate and elevational variables were combined to describe local habitat characteristics. Variation partitioning by pCCA showed that a large portion of the explained variation is shared between environmental and geographic components (fig. 4). It also showed black fly and mosquito assemblages are roughly equally influenced by geographical variables, but habitat variables (i.e. climate + elevational heterogeneity) are more important for mosquitoes than black flies.

The cluster analysis of black fly assemblages (fig. 5) recovered three main groups: a northern cluster (Bks, CbB, Kgl and Iql), a western mainland cluster (OgM, NmW, Ylk, Chu) and an eastern mainland cluster (Moo, Sch, Goo). Among mosquito assemblages, the three Arctic sites also clustered with the northernmost subarctic site (Kgl) (fig. 6). However, unlike in black flies, the cluster analysis revealed no obvious ecological or geographical patterns among Boreal and Subarctic sites. Visual inspection of the ordered species by site matrix suggests that black flies exhibit distributional patterns consistent with high turnover or replacement, whereas mosquito distributions are more nested.

Species richness in mosquitoes was greatest in warmer southern sites, with a downward trend towards colder northern sites. This same overall trend was observed in black flies except that species richness was greatest at one of the Subarctic sites (OgM). However, this particular area had the greatest elevational heterogeneity of any site. Elevational heterogeneity is known to be important in determining regional species richness – c.f., discussion. Relative importance analysis reveals that mean summer temperature is the most important factor influencing species richness in each family; accounting for ~32% and ~42% of R2 in black flies and mosquitoes respectively (fig. 7). Among black flies, the next most important factor is longitude (~29%). Bootstrap confidence intervals were large in black flies, and the only significant difference was between MST and TER. Among mosquitoes, the second most important variable is latitude (~32%), and confidence intervals overlap to a lesser degree (i.e. only MST and LAT as well as LON and TER overlap). The LMG method of relative importance analysis does not penalize shared variation which is likely responsible for the larger error bars in black flies. The results of the AIC methods were very similar to LMG (Table 2). Regardless of which models and metrics were used LON consistently had the highest relative importance in black flies followed by LAT

15 and MST. Similarly, MST had the highest relative importance in mosquitoes, followed by LAT and LON.

2.5 Discussion

2.5.1 Assemblage Structure and the Importance of Predictor Variables

The results of this study demonstrate the importance of both historical and environmental factors for structuring continental-scale distributional patterns of mosquitoes and black flies. For both families the first CCA axis separated assemblages in the northernmost sites (i.e., the Arctic sites plus the northernmost subarctic sites) from those farther south. The second axis separated eastern from western sites, regardless of assignment to a particular Ecoclimatic region1. This second gradient had a greater influence on black flies than on mosquitoes.

The primary driver separating sites in the northernmost cluster from those farther south is climate – specifically MST. This agrees well with previous studies showing that water temperature is consistently among the most important predictors of mosquito and black fly distributions at local scales (Vinson & Hawkins, 1998; Schäfer & Lundström, 2001; McCreadie et al., 2005; Schäfer et al., 2006; Beketov et al., 2010; McCreadie & Adler, 2012). The present study was not designed to compare processes operating at different spatial scales but the effects of temperature appear to be important across a range of spatial scales. Temperature can influence species distributions by limiting two important life history processes. First, temperature is largely responsible for determining the rate of larval development (Becker, 1973; Colbo & Porter, 1981; Bernotiene & Bartkeviçiene, 2011). At northern latitudes, developmental rate is critical because species must complete their entire life history during the short summer months. Second, flight activity — which is also strongly influenced by temperature — is critical for host seeking, mating and dispersal (Shipp et al., 1988; Alto & Juliano, 2001).

The secondary gradient separated eastern and western sites at more southern latitudes, reflecting the influence of both ecological and geographical factors (figs. 2 & 3). Ecologically,

1 It should be noted that the Boreal, Subarctic and Arctic delineations in the NBP sampling design was based on the Ecoclimatic regions of Canada (Strong et al., 1989). The results of the present study are more consistent with newer Ecozone delineations (Marshall et al., 1999).

16 mainland Canada east of Hudson Bay receives considerably more precipitation and slightly lower temperatures than at equivalent latitudes west of Hudson Bay (Table 1). Precipitation can influence species distributions by: 1) determining whether suitable aquatic habitats are permanently available, 2) lowering water temperatures via snow melt (Finn & Poff, 2008), and 3) affecting nutrient content in aquatic habitats via runoff (Alto & Juliano, 2001). Geographical history can also play a role in shaping assemblage structure — especially in areas that were profoundly influenced by Pleistocene glaciations (Pielou, 2008). All but one of our sites were under thick layers of continental ice as recently as 18,000 years ago, meaning that the present- day biota was derived mainly from immigration from peripheral glacial refugia. This post-glacial dispersal from different source areas can confound inferences about the origin of species assemblages (Downes, 1965; Strathdee & Bale, 1998).

Disentangling the influence of geographical and environmental variables is difficult over the large spatial scales of the present study. Among black flies, the lower influence of habitat variables (fig. 4), greater spatial separation in CCA (fig. 2), and reduced correlation of variables in pCCA analysis all suggest geographical variables are more important in structuring black fly assemblages than are ecological ones; especially among southern mainland sites (fig. 2). Previous authors have also suggested that barriers to postglacial dispersal are an important factor structuring assemblages in northern Canada (e.g., Currie, 1997; Adler et al., 2004). In contrast, mosquito assemblage structure is more strongly determined by climatic factors, as shown by variation partitioning analysis (fig. 4), the reduced spatial separation in CCA (fig. 3) and higher correlation of mean summer temperature after accounting for geographic variables in pCCA. Comparisons with previous studies are not possible because none have explicitly investigated the effects of geography on continental-scale distributional patterns in these two families. We conclude that, at least among black flies, ecological differences alone cannot sufficiently explain assemblage patterns and recent glaciations had a discernable influence on contemporary species distributions.

The lack of explanatory power of elevational heterogeneity in determining species richness and assemblage structure among black flies was unexpected. On a regional scale, areas of high elevation (e.g. the Cordillera) can support significantly more species than in non- mountainous terrain (Corkum & Currie, 1987; Adler in Hershey et al., 1998; Kazanci, 2006). One possible explanation for the lack of explanatory power was the removal of rare species,

17 which strongly impacted the site with the greatest elevational heterogeneity — OgM. When such species were included in the ordination analysis, OgM separated from all other sites, with elevational heterogeneity being the most significant contributing factor (fig. 8). Another possibility is that -— despite the importance of elevation on a regional scale at larger (i.e., continental) scales — historical and environmental factors indeed explain more of the variation than elevational heterogeneity. This latter possibility is supported by the fact that accounting for historical factors using pCCA greatly increased the variation explained by elevational heterogeneity (TER; fig. 2), and the small contribution it makes to species richness (fig. 7).

2.5.2 Macrodistributional Patterns

At the continental scale, differences in regional species assemblages are the product of macrodistributional patterns. Typical methods for assessing the degree of nestedness or replacement may not be appropriate at this scale. Instead, the following observations are based on visual inspection of the ordered species matrices (fig. 5, 6). The present study shows that black flies appear to follow a pattern most similar to replacement (Muneepeerakul et al., 2008; Leprieur et al., 2009) (fig. 5) — where species typical of the Boreal Ecoclimatic region are gradually replaced at higher latitudes by those adapted to the Arctic Ecoclimatic region. This pattern is supported by the specialized life history among Arctic-adapted species (e.g., females do not require a blood meal to develop their eggs, reduced flight capability, parthenogenetic reproduction). Such species can thrive far beyond the northern limit of most other species, but cannot compete with southern-adapted species in warmer climates (Downes, 1965). While a similar suite of adaptions are expressed in certain Beringian or Cordilleran species (c.f.,Currie, 1997), such species were rarely encountered in the present study and were not included in the ordination analysis. Previous studies on black flies suggest a lack of nestedness on a regional scale is attributed to differences in breeding site preference (Malmqvist et al., 1999). On the continental scale of the present study regional climate differences, together with historical influences, might also favor particular regional assemblages as exemplified by the distribution of arctic-adapted species. Similarly, the presence of barriers to dispersal (such as Hudson Bay), suggests that dispersal limitation could also serve as a mechanism structuring black fly assemblages.

In contrast to the replacement pattern observed in black flies, mosquito distributions do

18 follow a pattern of nestedness, where compositional differences are based on loss of species towards northern latitudes (fig. 6). In a perfectly nested assemblage, species rich sites will include the same species as species poor sites, plus additional species. Accordingly, species that occur in Arctic sites also occur at Subarctic and Boreal sites. Also in contrast to black flies, none of the mosquito species exhibited marked adaptations to life in the Arctic, such as obligate autogeny, reduced flight capability or asexual reproduction. The pattern of nestedness observed in mosquitoes may be due to biological and habitat constraints. Mosquito assemblages were more strongly determined by environmental factors than black flies. Wright et al. (1998) suggest that nestedness is most prevalent in extinction and colonization dominated systems. The results of the present study show that geographic factors are less influential in determining mosquito assemblage structure (i.e., mosquitoes are good colonizers) and therefore assemblage differences are driven primarily by ecological conditions.

2.5.3 Patterns of Species Richness

In addition to assemblage structure, patterns of species richness have been used to understand broad-scale patterns in community ecology (e.g., Cornell & Lawton, 1992; White & Kerr, 2006; Belmaker & Jetz, 2011; Carvalho et al., 2012). Studies of terrestrial species richness show significantly more species in the tropics than in temperate regions (Simpson, 1964; Cook, 1969). However, for many organisms, especially aquatic invertebrates, these patterns remain largely unexplored (Vinson & Hawkins, 1998). Unlike assemblage structure, species richness does not consider species identity, and therefore provides a different perspective on large-scale biodiversity patterns.

The most important determinant of species richness in mosquitoes and black flies was temperature (MST-fig. 7). This suggests that continental scale patterns of species richness are predominantly driven by ecological limitations; more specifically, that the Arctic Ecoclimatic region is beyond the thermal physiological limits of most species. After temperature, the relative importance of predictor variables differs between black flies and mosquitoes. Geographic variables (LON and LAT) were the next most important contributors to species richness in black flies, again underscoring the importance of historical factors and impediments to post-glacial dispersal. The AIC methods (Table 2) produced similar results except MST was less important

19 than LON and LAT in describing patterns of species richness. These results again highlight the importance of geographic history in structuring black fly biodiversity patterns.

The relationship between species richness and predictor variables is more complex in mosquitoes. After temperature, the next most important contributors to r2 are LAT and TAP. The LMG method of relative importance analysis does not penalize for shared variation, and the large influence of LAT is likely related to its correlation with MST. The results of the AIC methods (Table 2) are similar to the LMG method with MST and LAT explaining the greatest amount of variation in species richness.

Previous studies have shown that patterns of species richness differ between lotic and lentic organisms (Ribera et al., 2003; Hof et al., 2008). A key difference between lotic and lentic assemblages is the reliance on ephemeral habitats. Previous studies have shown the proportion of species in lentic vs. lotic habitats increases with increasing latitude, and Hof et al. (2008) concluded that lentic organisms are less restricted by geographic factors due to a greater need for dispersal in order to find ephemeral habitats. In contrast, lotic organisms are less reliant on ephemeral habitats and therefore exhibit a lower propensity for dispersal. A similar pattern is observed in the present study, as mosquitoes appear to be less restricted by geographic factors than are black flies.

In summary, this is the first study to explicitly assess the influence of ecological and historical factors in structuring patterns of species assembly and richness in black flies and mosquitoes across northern Canada. Our data suggest that the marked differences observed in the Arctic Ecoclimatic region are driven primarily by ecological factors — especially temperature. The intrinsic link between insects and temperature (Strathdee & Bale, 1998; Bale, 2002) suggests that Arctic assemblages are particularly vulnerable to anthropogenic climate change (Rouse et al., 1997; Smol et al., 2005; Post et al., 2009). As temperatures warm, southern-adapted species will migrate to more northerly latitudes, significantly changing the ecological dynamics of the region. Our study also highlights the importance of history in structuring patterns of species assembly. In the Boreal- and Subarctic Ecoclimatic regions, differences between eastern- and western populations of mosquitoes and black flies appear to be influenced by a combination of historical and ecological factors; however, historical factors play a relatively more important role in black flies. Black fly assemblages exhibited a pattern of replacement, while mosquito

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2.7 Tables Table 1. Location of the 11 sampling localities, species richness (without removal of singletons), and predictor variables used in this study.

Locality (Province) Abbreviation Black Mosquito LAT LON TER MST TAP fly richness richness

Goose Bay (NL) Goo 21 23 5.89 20.67 654 13.95 940.40

Moosonee (ON) Moo 20 30 5.68 17.52 205 14.26 703.56

Schefferville (QC) Sch 18 14 6.07 19.64 530 10.57 790.78

Yellowknife (NT) Ylk 26 19 6.93 12.37 375 14.80 288.58

Norman Wells (NT) NmW 26 22 7.24 9.61 1867 15.25 294.37

Churchill (MB) Chu 27 23 6.51 15.45 79 10.63 452.47

Ogilve Mountains (YK) OgM 31 11 7.16 7.62 1918 10.11 485.61

Kugluktuk (NU) Kgl 19 4 7.51 11.57 639 8.42 247.22

Banks Island (NU) Bks 4 2 8.12 11.41 465 4.45 151.54

Cambridge Bay (NU) CbB 14 3 7.67 13.48 212 6.12 141.74

Iqaluit (NU) Iql 8 4 7.07 19.52 791 6.28 403.68

Table 2. Relative variable importance calculated across all (32) and top 5 models with Akaike Information Criterion (AIC) and small-sample-size corrected Akaike Information Criterion (AICc).

Taxa Models Criteria LAT LON TER MST TAP

Black flies All AIC 0.72 0.95 0.31 0.50 0.42

Black flies Top 5 AIC 0.77 1.0 0.17 0.23 0.34

Black flies All AICc 0.65 0.77 0.05 0.30 0.11

Black flies Top 5 AICc 0.66 0.81 0.03 0.27 0.06

Mosquitoes All AIC 0.74 0.43 0.41 0.95 0.47

Mosquitoes Top 5 AIC 1.0 0.03 0.04 1.0 0.05

Mosquitoes All AICc 0.42 0.12 0.13 0.96 0.10

Mosquitoes Top 5 AICc 0.37 0.08 0.12 1.0 0.07

Supplementary Table 1. Black fly species included in the present study.

Goo Moo Sch Ylk NmW Chu OgM Kug Bks CbB Iql Gymnopais dichopticoides 0 0 0 0 0 0 1 0 0 0 0 dichopticus 0 0 0 0 0 0 1 0 0 0 0 fimbriatus 0 0 0 0 0 0 1 0 0 0 0 holopticoides 1 0 0 0 1 0 1 1 1 1 1 holopticus 0 0 0 0 0 0 1 0 0 0 0 Twinnia tibblesi 1 0 1 0 0 0 0 0 0 0 0 Helodon onychodactylus 0 0 0 0 0 0 1 0 0 0 0 pleuralis 1 0 1 0 0 0 1 0 0 0 0 decemarticulatus 1 1 1 1 1 1 1 0 0 0 0 gibsoni 0 0 0 0 0 1 0 0 0 0 0 alpestris 0 0 0 0 1 0 1 0 0 0 0 irkutensis 0 0 0 0 0 0 0 0 1 1 0 Prosimulium fuscum 1 1 1 1 0 0 0 0 0 0 0 neomacropyga 0 0 0 0 0 0 1 0 0 0 0 travisi 0 0 0 0 0 0 1 0 0 0 0 esselbaughi 0 0 0 0 1 0 1 0 0 0 0 mixtum 1 1 1 0 0 0 0 0 0 0 0 ursinum 1 0 1 0 0 0 0 1 0 0 1 Stegopterna emergens 0 1 1 1 1 1 0 1 1 1 0 sp 0 0 0 0 0 0 0 1 0 0 1 mutata 1 0 1 0 0 1 0 0 0 0 0 decafilis 0 0 0 0 1 0 1 0 0 0 0 Tlalocomyia osbourni 0 0 0 0 0 1 0 0 0 0 0 Cnephia dacotensis 0 1 0 0 0 1 0 0 0 0 0 eremites 0 0 0 1 1 1 0 1 0 1 0 ornithophilia 1 1 0 0 0 0 0 0 0 0 0 Ectemnia taeniatifrons 0 0 0 0 0 1 0 0 0 0 0 Metacnephia borealis 0 0 0 0 0 0 0 1 1 1 1 bilineata 0 0 1 1 1 1 1 1 0 0 1 saskatchewana 0 0 0 0 0 1 1 0 0 0 0 sommermanae 0 0 0 0 0 0 1 0 0 0 0

Supplementary Table 1. Continued

Goo Moo Sch Ylk NmW Chu OgM Kug Bks CbB Iql Simulium (Hellichiella) spp. 0 1 0 1 1 1 1 0 0 0 0 excisum 0 0 0 1 0 1 0 0 0 0 0 annulus 1 1 0 1 1 1 0 1 0 0 0 baffinense 0 0 0 0 0 1 1 1 0 1 1 (Eusimulium) spp. 0 0 0 1 1 1 0 0 0 0 0 bicorne 0 0 0 0 0 0 1 0 0 0 0 craigi 0 0 0 1 1 1 1 0 0 1 0 croxtoni 1 1 0 1 0 0 0 0 0 0 0 fontinale 0 0 0 1 1 0 1 0 0 0 0 silvestre 1 1 1 1 1 1 1 1 0 1 0 furculatum 1 1 1 1 1 1 1 1 0 0 0 subpusillum 0 0 0 0 0 0 0 1 0 1 0 vittatum 1 1 1 1 1 1 1 1 0 0 1 pictipes 1 1 0 1 0 0 0 0 0 0 0 luggeri 0 1 0 1 1 1 0 0 0 0 0 arcticum complex 0 0 0 1 1 1 0 1 0 0 0 decimatum 0 0 0 0 0 0 1 1 0 0 0 malyschevi 0 0 0 1 1 1 1 1 0 0 0 murmanum 1 1 1 1 1 0 1 0 0 0 0 decorum 1 1 1 1 1 1 0 0 0 0 1 noelleri 0 0 0 0 0 1 0 0 0 0 0 rugglesi 1 1 1 1 1 0 0 0 0 0 0 tuberosum 1 1 1 1 1 1 1 1 0 1 0 vulgare 0 0 0 1 1 0 1 1 0 1 0 venustum complex 1 1 1 1 1 1 1 1 0 1 0 verecundum complex 1 1 1 1 1 1 1 0 0 1 0

Supplementary Table 2. Mosquito species included in the present study

Goo Moo Sch Ylk NmW Chu OgM Kug Bks CbB Iql Anopheles earlei 0 1 0 1 1 0 1 0 0 0 0 Aedes abserratus 1 1 0 0 0 0 0 0 0 0 0 atropalpus 1 1 0 0 0 0 0 0 0 0 0 campestris 0 1 0 0 0 1 0 0 0 0 0 canadensis 1 1 1 1 1 1 1 0 0 0 0 canator 1 1 0 0 0 0 0 0 0 0 0 cinereus 1 1 0 1 1 1 1 0 0 0 0 communis 1 1 1 1 1 1 1 0 0 0 0 decticus 1 1 1 0 0 1 0 0 0 0 0 diantaeus 1 1 1 1 1 1 0 0 0 0 0 euedes 0 0 0 1 0 1 1 0 0 0 0 excrucians 1 1 1 1 1 1 1 0 0 0 0 fitchii 1 1 1 1 1 1 0 0 0 0 0 flavescens 1 1 0 1 1 1 0 0 0 0 0 hexodontus 1 0 1 0 1 1 1 1 0 1 1 impiger 0 0 1 1 1 1 1 1 1 1 1 implicatus 1 1 1 1 1 1 0 0 0 0 0 intrudens 1 1 0 0 0 1 0 0 0 0 0 mercurator 0 1 0 1 1 0 0 0 0 0 0 nigripes 0 0 1 1 0 1 0 1 1 1 1 pionips 1 1 1 1 1 1 0 0 0 0 0 pullatus 1 0 1 0 0 0 1 0 0 0 1 punctor 1 1 1 1 1 1 0 0 0 0 0 riparius 0 1 0 0 1 1 0 0 0 0 0 strictus 1 1 0 0 0 1 0 0 0 0 0 vexans 0 1 0 0 0 1 0 0 0 0 0 Culex restuans 0 1 0 0 0 0 0 0 0 0 0 territans 1 1 0 0 1 0 0 0 0 0 0 Culesita alaskaensis 1 1 0 1 1 1 0 1 0 0 0 impatiens 1 1 1 1 1 1 1 0 0 0 0 incidens 0 0 0 0 1 0 1 0 0 0 0 inornata 0 0 0 0 1 1 0 0 0 0 0 morsitans 1 1 0 1 1 0 0 0 0 0 0 Mansonia pertubans 0 1 0 0 0 0 0 0 0 0 0 Wyomyea smithii 1 1 0 1 1 0 0 0 0 0 0

2.8 Figures

Figure 1. Location of 11 sampling localities in northern Canada. Colours represent the Boreal, Subarctic, and Arctic ecoclimatic regions, simplified from Strong et al., (1989).

Figure 2. Above: CCA ordination scatterplot showing assemblage structure of black flies in relation to predictor variables. Points represent locations, with colours and symbols denoting biogeographic groupings (Arctic, Boreal/Subarctic East and Boreal/Subarctic West). Vectors represent predictor variables in the direction of increasing values, with the length proportional to explained variation. Axes 1 and 2 explain 34.5% and 31.7% of variation respectively. Below: Correlation values (r2) of predictor variables with CCA (dark grey), and pCCA (light grey) axes.

Figure 3. Above: CCA ordination scatterplot showing assemblage structure of mosquitoes in relation to predictor variables. Points represent locations, with colours and symbols denoting biogeographic groupings (Arctic, Boreal/Subarctic East and Boreal/Subarctic West). Vectors represent predictor variables in the direction of increasing values, with the length proportional to explained variation. Axes 1 and 2 explain 56.9.1% and 17.4% of variation respectively. Below: Correlation values (r2) of predictor variables with CCA (dark grey), and pCCA (light grey) axes.

Figure 4. Variation partitioning of black fly and mosquito assemblage structure via pCCA. Local habitat variables include climatic and elevational predictors.

Figure 5. Community table of black fly species and distributions used in the analysis. Species ordered according to rank on CA axis 1. Hierarchical cluster dendrogram on top represents relationships between sites, based on Ward’s minimum variance method. None-bloodfeeding species are indicated with an *. Species complexes containing multiple cryptic species are indicated with a †. The ecoclimatic region of each site is labeled with an “A” for Arctic, “S” for Subarctic or “B” for Boreal.

Figure 6. Community table of mosquito species and distributions used in the analysis. Species ordered according to rank on CA axis 1. Hierarchical cluster dendrogram on top represents relationships between sites, based on Ward’s minimum variance method. The ecoclimatic region of each site is labeled with an “A” for Arctic, “S” for Subarctic or “B” for Boreal

Figure 7. Relative importance of predictor variables in determining regional species richness. Relative importance was measured as contribution to overall R2 of the regression based on the LMG unweighted, averaging-over-orders technique. Bars represent means, with confidence intervals calculated using 1,000 bootstrap replicates.

Supplemental Figure 1. Above: CCA ordination scatterplots showing assemblage structure in black flies (right) and mosquitoes (left) in relation to predictor variables with the inclusion of rare species. Points represent locations, with colours and symbols denoting biogeographic groupings (Arctic, Boreal/Subarctic East and Boreal/Subarctic West). Axis 1 and 2 explain 41.6% and 27.3% of variation among black flies, and 49.1% and 20.1% of variation in mosquitoes. Below: Correlation values (r2) of predictor variables with CCA (dark grey), and pCCA (light grey) axes.

Supplemental Figure 2. pCCA ordination scatterplots showing assemblage structure of black flies (right) and mosquitoes (left) in relation to habitat variables, after accounting for geographic factors. Points represent locations, with colours and symbols denoting biogeographic groupings (Arctic, Boreal/Subarctic East and Boreal/Subarctic West). Vectors represent predictor variables in the direction of increasing values, with the length proportional to explained variation. Axis 1 and 2 explain 54.6% and 28.2% of variation among black flies, and 46.1% and 35.6% of variation in mosquitoes.

Chapter 3 Climate-induced changes in Arctic black fly communities 3.1 Abstract

Black flies are worldwide bloodsucking pests of birds and mammals, and rank among the most important vectors of disease agents to their hosts. The prospect of a northward migration of pest species onto the Canadian Arctic Archipelago (CAA) is of concern because the islands are home to populations of rare and threatened birds and mammals, such as the Red Knot and Peary Caribou. In this study we use baseline data from the 1947-1962 Northern Insect Survey (NIS) to evaluate how black fly species richness and community composition have changed over a half- century. Contemporary collections of black flies from Banks-, Victoria- and Baffin Island doubled (9 to 18) the number of black fly species known from the CAA. Unlike historically collected black flies — which are mainly non-bloodsucking arctic-adapted species — all but one of the newly recorded species are bloodsucking pests of birds or mammals. We conducted a more comprehensive survey of breeding sites on Victoria Island to determine how extensively the newly recorded (and hence, presumably immigrant) species were distributed. We found that populations of biting species are currently restricted to the south-central portion of Victoria Island. The distribution of bloodsucking species was significantly related with temperature (p<0.0001), and we calculated that a minimum average summer temperature of 5.8°C is required to sustain such populations. This figure corresponds well with the minimum temperature needed to sustain flight in northern black flies — a prerequisite for host finding. Temperatures during the time period when baseline collections were made reveals that the 5.8°C minimum threshold was largely absent from the CAA, supporting the hypothesis that newly-recorded species are indeed recent immigrants (as opposed to being overlooked by previous collectors). Temperatures predicted by future climate scenarios suggest that most of the southern CAA will be habitable by bloodsucking species by the 2080s. This is the first study to document rapid (i.e., on a half- century time scale) and profound changes in species richness and structure in a High Arctic insect community. The ongoing colonization and proliferation of bloodsucking species on the CAA could have a profound and negative impact on local birds and mammals, and the indigenous peoples that depend upon them, in part, for their sustenance. Further research is

46 needed to better understand the consequences of haematophagy and disease transmission on resident and migratory birds and mammals.

3.2 Introduction

Warming climates are predicted to have an accelerated and pronounced effect on arctic ecosystem (Post et al., 2009). Insects and arachnids are by far the most numerous inhabitants of northern landscapes, and they respond rapidly to environmental change. They are particularly sensitive to climate due to their physiology (ectothermy and short life cycles) and marked variation in population size over time and space (Strathdee & Bale, 1998; Bale, 2002). To date, virtually all studies documenting a northward shift in insect distribution have been conducted in temperate regions (Chen et al., 2011; Andrew et al., 2013). In contrast, the Arctic — where the effects of climate change are most pronounced (Holland & Bitz, 2003) — has received relatively little attention. This deficiency stems largely from the remoteness of the Arctic and the logistical problems associated with fieldwork in the far north. Furthermore, baseline data for the great majority of northern insects are lacking, which precludes the analysis of distributional change. One exception is biting flies — the focus of intensive study during the 1947-1962 Northern Insect Survey (NIS) (Riegert, 1999).This unprecedented initiative sampled 72 sites throughout northern Canada and Alaska at a time when climate change was not yet of global concern.

Few groups of insects are as strongly associated with the north as are black flies. Members of this worldwide family of bloodsucking fly occur in astronomical numbers in the boreal ecoclimatic zone, where they attack a wide variety of mammalian and avian hosts. In addition to their status as bloodsucking pests, female black flies are vectors of various disease agents to their hosts including protozoa, filarial nematodes, arboviruses and bacteria (Pinkovsky et al., 1981; Cupp & Cupp, 1997; Mead et al., 1997). Consequently, changes in the distribution of black flies have potential to significantly affect the health and wellbeing of northern host species, including humans. While black flies reach their zenith in terms of abundance and diversity in the boreal ecoclimatic zone (McCreadie et al., 2005), relatively few species are adapted for life in the arctic. In fact, only 9 species of black flies are known from the vast territory of the Canadian Arctic Archipelago (CAA), compared to 87 species from the northern (i.e., north of 60°) mainland of Canada and Alaska. Equally significant is the fact that 7 of the 9 archipelagic black flies are arctic-adapted species whose females are incapable of taking a blood

47 meal, a stark contrast to southern latitudes where roughly 90% of species are capable of taking a blood meal. The distance between the mainland and the southernmost islands of the CAA is mostly within the flight range of strong flying insects such as black flies, and suitable hosts and breeding sites (i.e., variously-sized streams and rivers) are in abundance on the islands. But as temperature is known to be among the most important determinants of flight activity in biting flies (Edmund, 1952), the marked dominance of arctic-adapted species on the CAA suggests that climate has played a key role in limiting colonization by more southern-adapted bloodsucking species.

In this study we compare historical collections of black flies on the CAA with those made from 2010 to 2012. Our goals were to (a) determine whether the southernmost islands of the CAA have been colonized by southern-adapted black fly species during the last half century, (b) determine the relationship between species richness and temperature, (c) investigate the relationship between local and regional species richness, (d) estimate future changes in black fly distribution, and (e) to discuss the implications for resident and migratory birds and mammals.

3.3 Materials and Methods

Material was collected under Wildlife Research Permits from Nunavut (2010-006, 2011- 023 and 2012-039), a Scientific Research Licence from Northwest Territories (No. 14914), and a Parks Canada Research and Collection Permit for Aulavik National Park (AUL-2011-8735).

3.3.1 Study Sites

The Canadian Arctic Archipelago (CAA) consists of 94 major islands distributed across 1.4 million km2. Personnel from the 1947-1962 Northern Insect Survey (NIS) sampled 8 sites on 5 different islands, and two of these sites (Iqaluit, Baffin Island, 63°44′55″N 68°31′11″W; Cambridge Bay, Victoria Island, 69°07′02″N 105°03′11″W) were chosen for re-sampling of black flies in 2010 and 2011 (fig. 1). Both sites are situated in the southernmost CAA and are in relatively close proximity to mainland populations of bloodsucking species. We sampled one additional southern island site (Aulavik National Park, Banks Island, Northwest Territories, 73°13'50.58"N, 119°32'26.76"W) in 2011 for comparative purposes. Although not included among the sites visited during the NIS, material from Banks Island was sampled by personnel from the Canadian National Collection of Insects and Arachnids (CNCI) during the late 1960s

(c.f., Peterson 1970). Data from Banks Island were included as a contemporary point-of- reference because the climate is cooler than on Baffin and Victoria Islands. Travel to Iqaluit and Cambridge Bay was by commercial airlines, with collecting sites accessed mainly by truck and all-terrain vehicles (ATVs). Access to Aulavik National Park on Banks Island was via a chartered aircraft, with collecting sites accessed by foot or kayak from a base camp “Green Cabin” (73°13.843'N, 119°32.446'W). All sites were visited during the peak of black fly development in mid-July to maximize sampling of species richness. Immature stages were collected from variously-sized streams and rivers at each site over a two week period. An effort was made to collect a minimum of 30 specimens from each stream, with representation from all available microhabitats. Although sampling was only semi-quantitative, species lists derived using this method are comparable to quantitative repeatable sampling units (McCreadie & Adler, 1998). Adults were collected using sweep nets and malaise traps. Victoria Island was visited for an additional two-week period in 2012 to determine how widely newly recorded (and, hence, presumably recently immigrating) species were distributed. Sites near Cambridge Bay and environs were once again visited by ATV, whereas more distant localities were accessed by chartered float plane and boat. In total, 21,092 specimens of black flies were collected from 81 streams on Banks, Victoria, and Baffin Islands. Detailed locality information is provided in Supplemental Table S1. Most material was identified morphologically using the keys in Adler et al. (2004); however, selected individuals of taxonomically difficult species were examined cytologically or by DNA barcoded following the methods of Rivera & Currie (2009). All material collected is held in the Entomology Collection of the Royal Ontario Museum, Toronto.

3.3.2 Climate and Species Assemblages

The great majority of black fly development occurs during the summer. Larval development occurs mainly during this period, with pupation and emergence of adults occurring before freeze-up in the fall. As northern black flies typically overwinter in the egg stage, they are largely insulated from temperature stress during the coldest months of the year. Consequently, climatic conditions experienced during that particular life stage are unlikely to limit the distribution of species. Therefore, mean summer temperature (June-August) was the only environmental variable assessed in this study.

Historically, collecting events on the CAA have been haphazard and concentrated largely near the few communities serviced by regularly scheduled flights. Our more comprehensive collection efforts on Victoria Island during 2012 spanned a latitudinal distance of more than 300km, covering a wide temperature gradient. Although collections tended to be spatially aggregated, sufficient coverage was achieved to estimate the thermal limits of biting species. Mean summer temperature data from 2001-2010 was estimated at each collection site using ClimateWNA ver 4.72 (Wang et al., 2012). A Generalized Linear Model (GLM) with a logit link was used to determine the relationship between temperature and the presence of biting species from collections in 2012 across Victoria Island. This model estimates the probability of biting species being present relative to mean summer temperatures. A conservative thermal limit for the presence of biting species was estimated as the 0.5 probability from the GLM. For this analysis, species were classified as either autogenous (non-blood feeder) or anautogenous (blood feeder) based on development of the female mouthparts.

To evaluate whether our estimated thermal threshold (0.5 probability from the GLM) for biting species adequately describes the northern distributional limit of biting species, we compared average summer temperature with the distribution of biting species from Iqaluit, Cambridge Bay and Sachs Harbour (Banks Island) at two different time periods: 1951-1970 and 1992-2011. This roughly corresponds with historical (i.e., NIS) and contemporary collecting events from those locations. Although contemporary collections from Banks Island (Green Cabin) were further north than Sachs Harbour, it is the nearest climate station with data available during the historical time period. Temperature data were gathered from Environment Canada’s Homogenized Surface Air Temperature datasets (Vincent et al., 2002).

Regression analyses were used to assess the relationship between local and regional species richness as well as between temperature and regional species richness. The distinction between local and regional scales for lotic species richness is unclear (Angermeier & Winston, 1998); however, we follow previous work in considering each stream as the local scale, and the regional species pool as the sum of all species from the local scale in that region (McCreadie et al., 2005). The dispersal abilities of black flies are largely unknown. While some species have been recorded dispersing over long distances (e.g., up to 500km by members of the Simulium damnosum complex), ranges of ~15km are more typical (Bennett, 1963; Moore & Noblet, 1974; Baldwin et al., 1975). Therefore, species richness values for streams within 50km of each other

50 were pooled to ensure that local assemblages were accurately accounted for. Collections from Iqaluit and Green Cabin were also pooled and included in the analysis. Temperatures for these localities were gathered from Environment Canada (Vincent et al., 2002) and Parks Canada, respectively. For comparative purposes, local mean species richness (± Standard Error) was calculated above and below the thermal threshold for bloodsucking species on Victoria Island, as well as on Baffin and Banks Islands. These values were compared against published records (McCreadie et al., 2005) using a one-way ANOVA and pairwise t-tests assuming unequal variances. Finally, a regression analysis was applied to determine whether arctic assemblages are saturated (local species assemblages regulated by local level processes) or unsaturated (local species assemblages regulated by regional level processes). We applied a linear and power regression model to the data (Cornell & Lawton, 1992; McCreadie et al., 2005). A significant linear relationship between local and regional richness was taken as evidence of non-saturation, whereas a significant power regression is interpreted as a saturated assemblage.

All statistical tests were performed in R 3.02 (R Core Development Team, 2013). Maps were prepared using ArcGIS 10.2 (ESRI, 2006). Graphs and tables were created in Microsoft Excel 2010.

3.4 Results

3.4.1 Historical and Contemporary Species Records

Collections from Iqaluit and Cambridge Bay in 2010-2012 increased species richness on the CAA from 9 to 18 species (Table 1). The largest increase was on Victoria Island, which now supports 14 species of black flies (compared to just 5 species historically). Only one additional species was recorded on each of Baffin and Banks Islands. In terms of species composition, nearly all new species records are members of the genus Simulium s.l. Latreille. Previously, this genus was represented by just 2 of 9 known species from the CAA. The 9 previously recorded species on the CAA were distributed among 7 other genera as follows: Gymopais Stone (1), Helodon Enderlein (1), Prosimulium Roubaud (1), Stegopterna Enderlein (1), Cnephia Enderlein (1) and Metacnephia Crosskey (2), Simulium Latreille (2). In terms of feeding habits, females of 8 of the 11 new species records (72%) are equipped with biting mouthparts, of which 6 are predominantly blood-feeders on mammals; the other two species are blood-feeders on birds. The

51 incidence of bloodsucking among members of the newly recorded species is markedly higher than that of previously known species, in which only 2 of 9 species (22%) are capable of bloodsucking. The only two historical records of bloodsucking species from the CAA — Metacnephia bilineata (Stone) and Simulium vittatum (Zetterstedt) —were known from just a single collecting event each on southern Baffin Island (fig. 1).

3.4.2 Temperature Thresholds for Bloodsucking Species

Comparison of historic (1951-1970) and contemporary (1992-2011) mean summer temperatures reveal marked summer warming at the three sampling sites (fig. 3). During this interval, temperatures increased by 0.3°C, 0.95°C and 1.04°C at Iqaluit, Cambridge Bay and Sachs Harbour, respectively. Contemporary mean summer temperatures (2001-2010) at sites on Victoria Island ranged from 4.3°C to 7.2°C. A significant relationship was found between temperature and the distribution of blood sucking species from the GLM (p<0.0001, figs. 2, 3). The estimated thermal threshold (0.5 probability of the GLM) for bloodsucking species based on 2012 collections was 5.8°C. This temperature threshold corresponds exactly with historic and contemporary distributions of bloodsucking black flies across the Canadian Arctic (fig. 3): sites that historically supported populations of bloodsucking species had average summer temperatures above this minimum threshold, whereas sites with temperatures below that threshold supported only non-bloodsucking species. Projecting the thermal threshold onto the A1B future climate scenario suggests that most terrain in the southern CAA will be habitable for bloodsucking black flies by the year 2080.

3.4.3 Patterns of Species Richness

The one-way ANOVA revealed species richness differed significantly between regions

(F6,127 = 9.25, p<0.0001). Comparison of mean summer temperatures and species richness also yielded a significantly positive relationship (fig. 4). Most regions included a minimum of 4 streams of varying sizes; only 2 streams were sampled in group c because of logistical constraints. Mean distance between streams within each region is 37.1km, whereas mean distance between streams of different regions was 195.4km. Mean local species richness (±SE) in south-central Victoria Island (fig. 2 d-f) is 5.13±0.41 (n=22) — significantly greater than the mean richness from Nearctic streams overall 3.53±0.08 (n=447) (McCreadie et al., 2005)

(t22=3.81, p<0.001). In contrast, streams in northern and eastern Victoria Island (fig. 2 a-c) have a significantly lower mean richness 2.61±0.27 (n=14) than the average for Nearctic streams

(t14=3.51, P=0.003). Mean per stream species richness on Banks Island and Baffin Island are both lower than the Nearctic mean although significantly so only on the former (1.36±0.20

(t11=4.24, p<0.0001) and 2.67±0.23 (t15=1.96, p=0.051), respectively).

Black fly assemblages from 7 different regions were used for the purposes of comparing local vs. regional species richness (Table 2). Regression analysis revealed a significant linear relationship between local and regional species richness at arctic sites (i.e., a type 1 or unsaturated assemblage – fig. 5) (Cornell & Lawton, 1992). Inclusion of species-richness data from Alaska and Alberta (McCreadie et al., 2005) returned a significant curvilinear relationship — the pattern of species richness exhibited by the Nearctic black fly fauna as a whole.

3.5 Discussion

3.5.1 Distinguishing Inadequate Baseline Data from Bona Fide Examples of Range Expansion.

The Arctic ecoclimatic zone is among the least known areas of Canada in terms of its insect fauna. The vastness and inaccessibility of the region — in combination with the difficulties of conducting a comprehensive biotic inventory over a large geographical area — means that reliable baseline data are lacking for most arctic-adapted species. For example, many arctic species are little known taxonomically and, because of their compressed life cycle , are likely to be missed during the course of a short survey (Danks, 1981). Fortunately, black flies were a major focus of the 1948-1962 Northern Insect Survey, and are arguably among the most completely known groups of insects in northern Canada. Although detailed distributional information remains lacking for many species, it is nonetheless possible to reasonably infer which species are long-time residents of the Canadian Arctic Archipelago (CAA) versus those that have colonized the islands during the last half century. Black flies can be considered “residents” of the CCA if they are (a) arctic-adapted autogenous (i.e., a non-bloodsucking) species, and (b) if populations of such species are known to be widely distributed on the CAA. Examples of these are Stegopterna emergens (Stone) and Simulium baffinense (Twinn) — recorded in this study for the first time from Banks and Victoria Islands, respectively. Both

53 species can reasonably be inferred to be long-time residents of those islands based on the fact they are both arctic-adapted and occur widely on other islands. In other words, lack of historical records for those species on Banks and Victoria Islands is likely the result of inadequate sampling. In contrast, black flies can be considered “immigrants” of the CAA if (a) they are southern-adapted anautogenous (i.e., bloodsucking) species, and (b) if populations of such species were unrepresented in historical collecting records. Only two bloodsucking species (Metacnephia bilineata and Simulium vittatum) have ever been recorded from the CAA, based on a single collecting event each on southern Baffin Island. The majority of species in this category are members of the southern-adapted genus Simulium s.l. Two species that could not be assigned confidently to either the “resident” or “immigrant” categories are Simulium subpusillum (Rubtsov) and Simulium giganteum (Rubtsov). The former species is widely distributed north of 60° from Alaska to the western shores of Hudson Bay (Adler et al. 2004). While this markedly northern distribution is typical of an arctic-adapted species, S. subpusillum is bloodsucking species that has not previously been recorded from the CAA. We tentatively assign it to the immigrant category pending further study. Simulim giganteum is among the most enigmatic and little known species of northern black flies. This Holarctic species was previous known in North America from a single male specimen collected from the vicinity of Arviat, Nunavut. Surprisingly, we found it to be among the most abundant and commonly collected black fly species in south-central Victoria Island — a region that was surveyed intensively by the NIS and by visits by subsequent specialists during the 1980s (Peterson, 1970; Wood, 1978; Procunier, 1982; Riegert, 1999; D.M. Wood, pers. comm.; W.S. Procunier, pers. comm.). While we cannot rule out the possibility that S. giganteum has been a long-time (albeit sparsely represented) resident of Victoria Island, it seems clear that conditions on the south-central part of the island now strongly favour development of that species. Although S. giganteum is a non-bloodsucking (and hence is presumably an arctic-adapted) species, we tentatively assign it to the immigrant category pending further study. To summarize, of the 18 species of black fly collected from Banks, Victoria and Baffin Islands, 9 are considered long-term residents whereas the other 9 are presumed to have colonized the islands during the last half century. A full list of species from those islands, including a summary of their distributional status, feeding habit, and vector status, is presented in Table 1.

3.5.2 Factors Limiting the Distribution of Bloodsucking Black Flies

Temperature is among the most important determinants of black fly larval development (Ross & Merritt, 1978) and adult flight activity (Edmund, 1952). Our results indicated that an average summer temperature of 5.8°C is needed to maintain bloodsucking species (fig. 3). This figure, based on present-day distributional patterns of bloodsucking species, corresponds closely with empirical studies of flight- and bloodsucking activity in subarctic black flies. More specifically, a minimum temperature of 7.8°C is needed to sustain intermittent flight (Edmund, 1952) and a minimum temperature of 6.0°C is needed to sustain bloodsucking activity (Berzina, 1953). The close correspondence among these temperature thresholds provides a baseline from which to predict the presence or absence of bloodsucking black flies.

Insects are expected to expand their range northward as the climate warms (Parmesan et al., 1999; Thomas, 2010); however, little evidence for this phenomenon has been adduced for the Arctic ecoclimatic zone. While paleolimnological studies reveal marked community changes over long time scales (i.e., 10s to 100s of thousands of years) (Smol et al., 2005), studies of the contemporary biota yield mixed results. Some studies reveal marked changes in community composition and species richness during historical times, whereas others do not (Lougheed et al., 2011; Timms et al., 2013). In fact, we observed striking differences even among sites in our own study; for example, the black fly fauna of Banks Island remained unchanged during the last half century whereas that of neighbouring Victoria Island experienced a threefold increase in species richness over the same period.

Warming temperature may have little impact unless a critical threshold is attained, at which point a dramatic biotic shift may occur (Scheffer & Carpenter, 2003). A half century ago, temperatures on Banks and Victoria Islands were too cold to support biting species of black flies (fig. 3), although many such species were present on the adjacent mainland (Adler et al., 2004). Because the temperature in south-central Victoria Island has now surpassed the critical threshold needed to support bloodsucking species, a dramatic shift in community composition was observed. In contrast, while the temperature on Banks Island has also warmed significantly over the last half century, it remains below the critical mean summer temperature (i.e., 5.8°C) needed to support bloodsucking species

It is well known that species distributional boundaries are influenced by both climatic (through physiological- and life history responses) and physical (geography, barriers) constrains (Thomas, 2010). Based on present-day temperature regimes, southern Baffin Island could theoretically support the same species richness as south-central Victoria Island (fig. 4); however, species composition on Baffin Island has remained little changed over the last half century (except for the evident recent immigration of Simulium decorum). The lower richness on southern Baffin Island is perhaps related to is relatively greater distance to the nearest source area for immigrant black flies on the mainland — a distance of more than 120 km over Hudson Strait. In contrast, Dease Strait between Victoria Island and Kent Peninsula is less than 23 km. While black flies are strong fliers, open water distances of more than 100km represent a significant barrier (Adler et al., 2005) — especially in the arctic where cold and windy conditions could negatively affect flight performance.

In summary, the relative paucity of bloodsucking black flies on the Canadian Arctic Archipelago is probably most strongly influenced by temperature and distance from the mainland, although other abiotic and biotic factors could play a role (for example, the availability suitable breeding sites or host species). Given the current lack of basic ecological information for most northern species, considerably more work is needed to assess the relative importance of potential limiting factors.

3.5.3 Species Richness and Community Saturation

Many groups of organisms have the greatest number of species in tropical regions, with a trend towards decreased richness towards the poles (Willig & Lyons, 1998; Willig et al., 2003; Hillebrand, 2004). Lotic (i.e., stream dwelling) insects are unusual in that many taxa are no more diverse in the tropics than they are in temperate regions (Vinson & Hawkins, 1998; Hillebrand, 2004). Black flies exhibit the typical lotic-insect pattern in that richness in the tropics is equivalent to or lower than in temperate regions, at both local and regional scales (McCreadie et al., 2005). In an analysis of richness patterns among black flies from the Nearctic Region, McCreadie et al. (2005) found no relationship between regional and local species richness, the latter exhibiting an average of 2.25-4.74 species per stream despite marked differences in regional species richness (7-40). Those authors concluded that black flies exhibit a saturated community structure (i.e., there is an upper limit to local species richness).

Our results show a positive relationship between local and regional richness within the arctic regions of this study (fig. 5), and lower regional richness at cooler temperatures indicating that assemblages are regulated by factors operating on a regional (i.e., climate, dispersal limitation), as opposed to a local scale (e.g., stream reach characteristics). Several authors have suggested strong local regulation of lotic insects (Palmer et al., 1995; Downes et al., 2000); however, dominance of regional regulators is perhaps not surprising in the Arctic where species persistence is more dependent on their physiological ability to withstand the harsh environment than stream reach characteristics (Strathdee & Bale, 1998). Regulation by regional factors also suggests the presence of vacant niches in arctic streams that allow colonization by southern species once climates become suitable.

The higher than average species-richness value for south-central Victoria Island was unexpected. It could be a product of the small sample size in our study (22 streams vs. 40 streams in Alaska); alternatively, perhaps it is a reflection of the smaller geographical scale of southcentral Victoria Island relative to the larger-scale political units considered by McCreadie et al (2005). If the higher than average species-richness in south-central Victoria Island is not an artifact of sample size or study design, it may suggest that these streams are in a transitional stage where arctic- and south-adapted species can coexist. As temperatures continue to warm, we expect to see a gradual replacement of arctic-adapted species with southern-adapted ones, with local species richness values declining towards the Nearctic mean.

3.5.4 Implications of a Northward Migration of Bloodsucking Black Flies.

The northward migration of bloodsucking black flies into previously uninhabited terrain has implications for arctic-dwelling birds and mammals — some of which are already under threat. Larvae of arctic-adapted (i.e., non-bloodsucking) species currently outnumber those of bloodsucking ones in most of the streams and rivers sampled on Victoria Island (fig. 2). However, the reverse was encountered in three streams in the south-central part of the island (fig. 2 d, e). As the climate continues to warm, conditions will begin to favour development of the southern-adapted species, which in turn will breed in ever increasing numbers (ultimately supplanting the arctic adapted species). In time, it seems likely that pest species will eventually attain population sizes where host-seeking females will impose a serious impact on their hosts.

The most notorious mammalian pests discovered on Victoria Island is Simulium tormentor Adler, Currie & Wood. This species is among the most significant pests of humans and other large mammals in subarctic Canada (Adler et al., 2004). Currently, S. tormentor is among the rarest species encountered on Victoria Island, and there have so far been no reports of attacks on humans or any other host. It would be instructive to regularly resample previous collecting sites to determine whether S. tormentor is increasing in prevalence and population size. Given the rate of climate change in northern Canada, resampling on a 5 or 10-year time scale seems warranted.

While most of the presumed immigrant species on the CAA are mammalophilic, the discovery for the first time of ornithophilic species is especially noteworthy. Evidence is accumulating that such species are gaining in prevalence throughout the arctic. A recent study in northern Norway and Finland, for example, documented a 7 per cent failure of Snowy Owl (Bubo scandiacus) nests due to black fly attacks (fig. 7) (Solheim et al., 2013). This particular owl population had been the subject of study for many years, yet this was the first time black flies were ever observed at nesting sites. A similar phenomenon was observed at Peregrine Falcon (Falco peregrinus) nesting sites near Rankin Inlet, Nunavut, in 2013 (Alasdair Franke, pers. comm.). A comprehensive survey of black flies from Rankin Inlet and environs in 2003 (D.C. Currie, unpublished data) yielded no species of ornithophilic black flies. Therefore, such species evidently migrated into the area at some point during the last decade, now occurring in sufficient numbers to induce mortality in Peregrine Falcon nestlings.

In addition to the physical and psychological stress caused by attacks from bloodsucking females, the possible introduction of parasitic diseases imposes an even greater threat to hosts. Perhaps the most serious of these at northern latitudes is the avian malaria-like disease, Leucocytozoonosis, which caused 80-100% mortality in a domestic geese near Kuujjuaq (as Fort Chimo), Quebec (Laird & Bennett, 1970). Rising temperatures are known to increase blood parasite prevalence in birds (Zamora-Vilchis et al., 2012) and, in the Arctic, migrant birds could carry Leucocytozoon spp. from the south (Laird, 1961). The presence of known vectors of Leucocytozoonosis on the CAA (i.e., Simulium silvestre and S. craigi) opens the potential for transmission to nestling birds, which are particularly susceptible to mortality from infection (Hunter et al., 1997; Smith et al., 1998; Currie and Hunter, 2008). Other potential diseases whose vectors are now known from the CAA include the nematodes Onchocerca cervipedis

(Wehr & Dikmans) and Dirofilaria ursi (Yamaguti). The former species — transmitted by the immigrant species Simulium decorum and S. tormentor — affects large ungulates. Massive infection of roundworms causes swelling on the legs and hooves of hosts, increasing the risk of predation. A recent study on Grant’s Caribou (Rangifer tarandus granti) found O. cervipedis as far north as 66° in Alaska and the Yukon Territory (Verocai et al., 2012). In our study, populations of S. tormentor are nearing the range of the endangered Peary Caribou (Rangifer tarandus pearyi), a species whose population on Victoria Island was estimated to be just 150 individuals (Species at Risk Committee, 2012). Diroflilaria ursi is so far only known to infect the American Black Bear (Ursus americana). It is unclear whether the absence of published records from Grizzly Bears (Ursus arctos) and Polar Bears (Ursus maritimus) indicates true absence or lack of study. But given that known vectors of D. ursi are now known to be in the range of the northernmost bear species, vigilance is warranted.

Our study reveals that Victoria Island has experienced the greatest change in its black fly fauna over the last half century. As temperatures continue to warm, biting species are expected to become increasingly prevalent (figs. 2, 4). The island includes 8 areas identified by Environment Canada as important wildlife habitats, including breeding grounds for the Red Knot (Calidris canutus - assessed as a ‘species at risk’ by Committee On the Status of Endangered Wildlife In Canada - COSEWIC) and the rare Buff-breasted Sandpiper (Tryngites subruficollis). The potential impacts of bloodsucking flies could be significant for insular wildlife and the indigenous peoples that depend on them, in part, for their sustenance. Assuming the current rate of warming in northern Canada, our projection indicates that most of the southern CAA will be colonized by biting black flies by 2080 (fig. 6). Of particular concern are Southampton Island and northern Baffin Island, which include 21 sites identified as important to local and migrating wildlife, including 100% of the Canadian populations of Dovekie (Alle alle Linnaeus).

The vagaries of long-term climate projections notwithstanding, the thermal threshold established for bloodsucking species provides researchers with a means to predict the present and future distributions of bloodsucking species on the CAA. Such information provides much needed focus for monitoring efforts in areas of ecological, cultural, and economic importance (e.g., human settlements, wildlife sanctuaries, migratory bird nesting sites). Of immediate concern to wildlife managers are ongoing changes in black fly community composition. While nearly half the species on the CAA are now known to be bloodsuckers they are currently

59 dominated numerically by their non-bloodsucking relatives. Future studies should monitor the inevitable replacement of arctic-adapted species by bloodsucking, southern-adapted ones. Further study is also needed about host-preferences among northern black flies and the potential impact of parasitic diseases.

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3.7 Tables

Table 1. Summary of black fly occurrence on Banks, Victoria and Baffin Islands, with indication of distributional category, feeding habits and vector status. Symbols: • = historical records for islands; X = new records for islands. Acronyms and symbols for distributional categories: R = resident, I = Immigrant, “*” = tentative assignment to a particular category. Acronyms for feeding habits: A = autogenous, O = ornithophilic, M = mammalophilic.

Distributional Feeding Taxon Vector Status

Status Habit

Banks Banks Is. BaffinIs.

Victoria Is.

Gymnopais holopticoides R A N/A • • • Helodon irkutensis • • R A N/A

Prosimulium ursinum • R A N/A Stegopterna emergens x • • R A N/A Cnephia eremites • • R A N/A

Metacnephia borealis • • • R A N/A bilineata • R O Unknown Simulium (Boreosimulium) baffinense x • R A N/A baffinense (Nevermannia ) craigi x I O Leucocytozoon spp. silvestre x I O Leucocytozoon spp. craigi (Schoenbaueria ) silvestre sub pusillum x I* M Unknown subpusillum gigantium x I* A N/A (Psilozia) gigantium vittatum • R M Vesicular stomatitis virus (Simulium s.s.) Vittatu decorum m x I M Onchocerca cervipedis tuberosum x I M Unknown decorum vulgare x I M Unknown tuberosum tormentor x I M Onchocerca cervipedis, vulgare rostratum x I M UnknownDinofilaria ursi tormentor rostratum

Table 2. Estimates of local and regional species richness.

Number of Regional Mean Local

Region Streams Richness Richness (±SE)

Cambridge Bay (2011) 15 12 3.33 (± 0.278)

Iqaluit (2010) 15 8 2.67 (± 0.334)

Green Cabin (2011) 11 3 1.36 (± 0.453)

Victoria Island –south of thermal threshold (2012) 13 14 5.13 (± 0.366)

Victoria Island– north of thermal threshold

(2012) 22 5 2.61 (± 0.522)

Alaska (McCreadie et al., 2005) 40 40 4.1 (± 0.102)

Alberta (McCreadie et al., 2005) 18 29 3.72 (± 0.128)

Supplementary Table 1. Black fly collection sites.

Site Number Location Collection year Latitude Longitude 1 Victoria Island 2012 69° 7.529’N 104° 59.924’W 2 Victoria Island 2012 69° 12.317’N 104° 46.668’W 3 Victoria Island 2012 69° 11.083’N 104° 45.728’W 4 Victoria Island 2012 69° 10.722’N 104° 49.395’W 5 Victoria Island 2012 69° 07.922’N 105° 28.504’W 6 Victoria Island 2012 69° 09.251’N 105° 32.305’W 7 Victoria Island 2012 69° 09.274’N 105° 32.389’W 8 Victoria Island 2012 69° 06.676’N 105° 05.284’W 9 Victoria Island 2012 69° 07.170’N 105° 07.668’W 10 Victoria Island 2012 69°09.490’N 105°11.499’W 11 Victoria Island 2012 69°11.695’N 105°12.451’W

12 Victoria Island 2012 69°13.169’N 105°12.980’W 13 Victoria Island 2012 69°50.025’N 107°58.164’W 14 Victoria Island 2012 69°21.834’N 108°45.027’W

15 Victoria Island 2012 69°21.588’N 108°45.474’W 16 Victoria Island 2012 68°56.863’N 108°30.067’W 17 Victoria Island 2012 68°56.692’N 108°32.113’W 18 Victoria Island 2012 69°46.218’N 108°09.501’W 19 Victoria Island 2012 69°48.480’N 108°33.520’W 20 Victoria Island 2012 69°46.021’N 108°32.953’W 21 Victoria Island 2012 69°46.741’N 108°05.847’W 22 Victoria Island 2012 69°49.943’N 105°44.823’W 23 Victoria Island 2012 69°49.854’N 105°45.613’W 24 Victoria Island 2012 69°43.293’N 103°43.263’W 25 Victoria Island 2012 69°36.427’N 103°32.605’W 26 Victoria Island 2012 71°18.862’N 107°12.126’W 27 Victoria Island 2012 71°26.569’N 107°41.253’W 28 Victoria Island 2012 71°44.156’N 108°13. 414’W 29 Victoria Island 2012 71°44.110’N 108°13. 649’W 30 Victoria Island 2012 69°48.929’N 108°00.749’W 31 Victoria Island 2012 69°43.473’N 107°30.990’W 32 Victoria Island 2012 69°42.672’N 103°37.951’W 33 Victoria Island 2012 69°42.660’N 103°37.635’W 34 Victoria Island 2012 69°33.229’N 103°21.017’W 35 Victoria Island 2012 69°32.538’N 103°17.929’W 36 Victoria Island 2012 69°32.561’N 103°17.653’W

Supplementary Table 1. Continued

Site Number Location Collection year Latitude Longitude

1 Green Cabin, Banks Island 2011 73°13.602'N 119°33.307'W 2 Green Cabin, Banks Island 2011 73°14.731'N 119°34.271'W 3 Green Cabin, Banks Island 2011 73°13.55'N 119°32.526'W 4 Green Cabin, Banks Island 2011 73°13.204'N 119°32.336'W 5 Green Cabin, Banks Island 2011 73°12.758'N 119°31.111'W 6 Green Cabin, Banks Island 2011 73°12.487'N 119°33.92'W 7 Green Cabin, Banks Island 2011 73°12.261'N 119°33.975'W 8 Green Cabin, Banks Island 2011 73°11.807'N 119°34.181'W 9 Green Cabin, Banks Island 2011 73°16.569'N 119°34.749'W 10 Green Cabin, Banks Island 2011 73°13.605'N 119°32.303'W 11 Green Cabin, Banks Island 2011 73°10.544'N 119°36.584'W 12 Green Cabin, Banks Island 2011 73°13.843'N 119°32.446'W 1 Cambridge Bay, Victoria Island 2011 69°9.481'N 105°11.47'W 2 Cambridge Bay, Victoria Island 2011 69°8.141'N 104°58.47'W 3 Cambridge Bay, Victoria Island 2011 69°7.912'N 105°28.516'W 4 Cambridge Bay, Victoria Island 2011 69°5.959'N 105°13.361'W 5 Cambridge Bay, Victoria Island 2011 69°5.959'N 105°13.361'W 6 Cambridge Bay, Victoria Island 2011 69°5.241'N 104°56.335'W 7 Cambridge Bay, Victoria Island 2011 69°8.692'N 105°29.276'W 8 Cambridge Bay, Victoria Island 2011 69°9.263'N 105°32.392'W 9 Cambridge Bay, Victoria Island 2011 69°9.161'N 105°31.722'W 10 Cambridge Bay, Victoria Island 2011 69°9.481'N 105°11.47'W 11 Cambridge Bay, Victoria Island 2011 69°6.695'N 105°5.294'W 12 Cambridge Bay, Victoria Island 2011 69°11.704'N 105°12.456'W 13 Cambridge Bay, Victoria Island 2011 69°7.163'N 105°7.666'W 14 Cambridge Bay, Victoria Island 2011 69°8.141'N 104°58.47'W 15 Cambridge Bay, Victoria Island 2011 69°7.912'N 105°28.516'W 16 Cambridge Bay, Victoria Island 2011 69°7.518'N 104°59.963'W 17 Cambridge Bay, Victoria Island 2011 69°7.895'N 104°59.457'W 18 Cambridge Bay, Victoria Island 2011 69°6.455'N 105°13.733'W 19 Cambridge Bay, Victoria Island 2011 69°7.163'N 105°28.394'W 1 Iqaluit, Baffin Island 2010 63°45.073'N 68°27.556'W 2 Iqaluit, Baffin Island 2010 63°45.905'N 68°34.85'W 3 Iqaluit, Baffin Island 2010 63°47.432'N 68°34.042'W 4 Iqaluit, Baffin Island 2010 63°45.392'N 68°34.547'W 5 Iqaluit, Baffin Island 2010 63°45.26'N 68°27.689'W 6 Iqaluit, Baffin Island 2010 63°47.609'N 68°33.975'W 7 Iqaluit, Baffin Island 2010 63°47.609'N 68°33.975'W 8 Iqaluit, Baffin Island 2010 63°47.429'N 68°33.929'W 9 Iqaluit, Baffin Island 2010 63°46.867'N 68°33.052'W 10 Iqaluit, Baffin Island 2010 63°45.551'N 68°27.461'W 11 Iqaluit, Baffin Island 2010 63°45.551'N 68°27.461'W 12 Iqaluit, Baffin Island 2010 63°45.061'N 68°28.337'W 13 Iqaluit, Baffin Island 2010 63°45.38'N 68°34.621'W 14 Iqaluit, Baffin Island 2010 63°45.42'N 68°28.429'W 15 Iqaluit, Baffin Island 2010 63°44.597'N 68°34.183'W

3.8 Figures

Figure 1. Historical collections of black flies in northern Canada. Dots represent focal areas for previous collections of black flies (Shewell, 1957, Adler et al., 2004). Named locations are mentioned in the text. Red square indicates the area in Figure 2 that was sampled intensively in 2012. Ecozone classification is from Marshall et al., (1999).

Figure 2. Distribution of black flies on Victoria Island relative to mean summer temperature (°C). 2A Surface map of mean summer temperatures based on climatic data from 2001 to 2010. Symbols represent collection sites in 2012 (n=33). Dashed line represents the approximate northern limit for bloodsucking species based on the 0.5 probability cutoff of the GLM—5.8°C (see figure 3). Red boxes indicate main collection areas, shown in greater detail in 2B. 2B Pie charts show the proportion of bloodsucking (red) to non-bloodsucking (blue) species in each stream. Species richness is represented by size of pie chart.

Figure 3. Relationship between temperature and presence of biting black fly species. Red line represents probability (0-1) of sites supporting biting species relative to temperature generated by the Generalized Linear Model (GLM). Dashed line represents the 0.5 probability from the GLM. Diamonds represent individual collection sites Victoria Island (n=33), where biting species were present (1) or absent (0). Results of the GLM are highly significant (p<0.0001). Bars represent average summer temperature (+/- standard error) time periods 1951-1970 and 1992-2011 for each location.

14 Cambridge Bay, Victoria Island 12

Victoria Island "e" Iqaluit, 10 Baffin Island

8 Victoria Island "d"

6 Victoria Island "b" Victoria Island "c" Green Cabin,

Regional Regional Species Richness 4 Banks Island

Victoria Island "a" 2

0 4 4.5 5 5.5 6 6.5 7 Mean Summer Temperature (°C)

Figure 4. Relationship between temperature and species richness. Letters correspond to groupings of sites as shown in figure 2. Solid diamonds represent areas with bloodsucking black flies, whereas open diamonds represent areas without bloodsucking 2 black flies. The relationship is significant p<0.01, r Adj.=0.702.

Figure 5. Relationship between local and regional species richness. Grey dots represent arctic sites from the present study (c.f., Table 2), whereas black are the northern sites (i.e., Alberta and Alaska) from McCreadie et al., (2005). The linear model is significant (p<0.05) only when arctic sites are included in the regression; the power relationship is significant (p<0.05) when all sites are included.

Figure 6. Predicted future distribution of bloodsucking black flies on the Canadian Arctic Archipelago based on GLM results.

Figure 7. Nesting female snowy owl (Bubo scandiacus) after attacks by black flies in Karasjok, Norway. Note clotted blood and closed eyelids. Reproduced, with permission, from Solheim et al., (2013). Photo credit: Thomas Aarvak.

Chapter 4 Cryptic diversity in northern Nearctic Stegopterna Enderlein (Diptera: Simuliidae). 4.1 Abstract

Black flies are model organisms for studying the earliest stages of the speciation process. Examination of banding patterns on the larval polytene chromosomes provides insight into reproductive isolation and the speciation process. One lineage of black flies that is particularly notable for cryptic speciation are members of the genus Stegopterna, as half of all North American species were originally recognized based on cytological grounds. Knowledge of the northernmost members of the genus is hindered because of logistical problems associated with sampling in the far north. In this study we used mitochondrial DNA (mtDNA) markers to test species boundaries in two little known northern Stegopterna species: Stegopterna emergens and St. trigonium. Using COI and COII genes we found evidence for 3 lineages of northern Nearctic Stegopterna. One lineage representing a hitherto unknown species was separated from its northern congeners by 7.1% COI genetic distance. This species, currently known only from Baffin Island and a single western mainland site, was found to be morphologically distinct from other northern species. Two other lineages — possibly representing Stegopterna emergens and St. trigonium — were separated from each other by a genetic distance of just 2.7%. Monophyly varied with phylogenetic reconstruction method. One lineage has a predominantly northern (i.e., north of 60° latitude) distribution whereas the other lineages is more widely distributed, its range extended southward to Montana and Michigan. Molecular evidence is equivocal whether these two lineage represent intraspecific variation or recently diverged species. In summary, mtDNA is a useful tool for exploring species boundaries in a taxonomically difficult lineage of black flies, but an integrated approach combining molecular, morphological and cytological data sets is need to confidently address species status and nomenclatural issues.

4.2 Introduction

The speciation process is a continuum, ranging from interpopulation variation to reproductive isolation, and ultimately to morphological differentiation. Black flies are excellent models for tracking changes along the speciation continuum because their larvae possess giant

76 polytene chromosomes (Rothfels, 1989; Shields et al., 2009; Conflitti et al., 2010, 2012). Analyses of chromosomal banding patterns can provide valuable insights into the degree of reproductive isolation among lineages and, consequently, black flies are among among the most completely known groups of insects in North America in terms of their cryptic diversity. Nonetheless, cytogenetics remains a highly specialized subdiscipline with relatively few practitioners, and chromosomal analysis is possible only if larvae of a particular stage are available for study. This presents a challenge for studies at northern latitudes where lack of access and shortness of season are impediments to progress.

DNA barcoding has become an increasingly commonly method for species identification (Hebert et al., 2003; Hajibabaei et al., 2007; Ratnasingham & Hebert, 2013). The DNA barcoding gene and other mitochondrial markers also have utility for revealing cryptic diversity and identifying specimens regardless of life history stage (e.g. Rivera & Currie, 2009). Accordingly, a DNA barcoding approach has potential to greatly accelerate the exploration of species boundaries in circumstances where few specimens are available for cytogenetic study.

The genus Stegopterna Enderlein is well known for its cryptic diversity as revealed through cytological studies (Basrur, 1957; Basrur & Rothfels, 1959; Madahar, 1969; Adler & Kim, 1986; Currie & Hunter, 2003). Fourteen nominal species are distributed throughout the Holarctic Region, with 8 known from North America (Adler & Crosskey, 2014). Among the latter species, the presence (or validity) of half was initially established on the basis of cytological studies.

To date, only three nominal species of Stegopterna are known from the vast territory of northern North America north of 60°: St. decafilis (restricted to Alaska and the Yukon Territory, St. emergens (transcontinental including the southernmost Canadian Arctic Archipelago) and St. trigonium (continental Alaska, Northwest Territories and Nunavut). One issue that remains incompletely resolved is the relationship between the latter two species. Historically, St. emergens was the only widely distributed species of Stegopterna known to occur north of 60°. More recently, (Adler et al., 2004) provisionally applied the name St. trigonium (an existing Palearctic name) to an exclusively northern population whose larvae exhibited slight morphological and chromosomal differences from those of St. emergens. More work is needed to determine whether these entities represent separate species and, if so, whether the name St.

77 trigonium applies validly to North American populations (c.f., Adler et al., 2004). Given the general sparseness of sampling effort in northern Canada, what are the prospects that other species have been overlooked? In this study we use mtDNA markers to (a) screen for additional cryptic species of northern Stegopterna and (b) test species boundaries between Nearctic populations of St. emergens and St. trigonium.

4.3 Materials and Methods

4.3.1 Samples and laboratory procedures

Collections of Stegopterna were made at 6 widely distributed localities in northern Canada (fig. 1). Sampling locations broadly encompassed the known range of both St. emergens and St. trigonium according to cytologically verified distribution maps in Adler et. al. (2004). Given the dearth of cytologically confirmed records of St. trigonium, it is likely that the range of that species is considerably larger than illustrated in Figure 1. Larvae of Stegopterna were collected opportunistically from streams at each site and fixed in 95% ethanol. Samples were maintained at ca. 4°C until processing in the laboratory. As the larvae collected were unsuitable for cytological verification, a special effort was made to select exemplars for analysis that expressed the full range of morphological variation present at each site. A total of 66 specimens were selected for molecular analyses. Abdominal segments I-V were used for DNA extraction, with the anterior- and posterior-most ends of the larva retained as vouchers. These are held in the Entomology collection of the Royal Ontario Museum, Toronto. Genomic DNA was extracted using the Qiagen® DNeasy blood and tissue kit. All extracts were stored at -20°C. Two protein coding mitochondrial genes (COI and COII) were targeted for amplification. Each 25µL polymerase chain reaction (PCR) was conducted in a DNA Engine PT200 Thermocycler™ (MJ Research Inc.) using the following cycling parameters: 2 min at 94°C for initial denaturation; 45 s at annealing temperature; 45 s at 72°C; 36 cycles of 30 s at 94°C (denature), 45 s at annealing temperature, 45 s at 72°C (extension); and 4 min at 72°C for final extension. Amplification products were visualized on 1% agarose gels stained with SYBR®Safe. COI sequences were amplified using primers LCO1490 (GGTCAACAAATCATAAAGATATTGG) and HCO 2198 (TAAACTTCAGGGTGACCAAAAAATCA) and an annealing temperature of 57.4°C (Folmer et al., 1994). COII sequences were amplified using primers TL2-J-3034

(ATTATGGCAGATTAGTGCA) and TK-N-3785 (GTTTAAGAGACCAGTACTTG), with an annealing temperature of 49°C (Simons et al., 1994).

4.3.2 Data Analysis

A COI only data set was constructed using sequences from 66 specimens of northern Stegopterna collected in this study, plus 28 additional sequences downloaded from BOLD (Table 1, Ratnasingham & Hebert, 2007, 2013). Included among these latter are St. decafilis, a species of uncertain identity from Finnish Lapland (the type locality of St. trigonium) and specimens identified as St. emergens from Manitoba CAN and Montana USA. These data were subjected to DNA barcoding analysis using tools on the BOLD website. More specifically, we used Barcode Index Number (BIN) system (Ratnasingham & Hebert, 2013) to detect the presence of molecular operational taxonomic units (MOTUs). This analysis groups sequences based on iterative clustering algorithms, and have been shown to closely match morphologically defined species in various taxa (Ratnasingham & Hebert, 2013). COI pairwise sequence divergence was calculated in MEGA using K2P distances. Intra- and interspecific statistics were calculated in Microsoft Excel 2010. The Akaike- and Baysian Information-Criteria within jModelTest 2.1.2 (Guindon & Gascuel, 2003; Darriba et al., 2012) was used to determine the best fitting evolutionary model for the analysis on the COI+COII data set.

Trees were constructed using neighbour-joining (NJ), maximum-parsimony (MP) and Bayesian methods. COI trees were rooted using Cnephia dacotensis as the outgroup, whereas COI+COII trees were rooted at their midpoint. jModelTest 2.1.2 (Guindon & Gascuel, 2003; Darriba et al., 2012) was used to select the model of DNA substitution for the COI+COII dataset. NJ trees were constructed in MEGA with K2P distances for COI dataset. Significance of each node was assessed with 10,000 bootstrap replicates. MP trees were also constructed in MEGA. The Subtree-Pruning-Regrafting (SBR) heuristic search method was applied from 10 random starting trees across 3 search levels with 300 retained trees. Clade support was estimated from 10,000 bootstrap replicates.

Bayesian analysis was performed using MrBayes v3.2.2 (Huelsenbeck & Ronquist, 2001; Ronquist et al., 2012) by Markov Chain Monte Carlo sampling for 5.0x106 generations. For the COI+COII dataset, estimates of tree parameters were linked between COI and COII genes, but substitution parameters were allowed to vary independently. The analysis consisted of two

79 simultaneous runs with random starting trees and six Markov chains sampled every 100 generations. The first 25% of parameter estimates was discarded as burnin. Stationarity was confirmed by plotting –ln likelihood (-lnL) scores against generation time. A 50% majority-rule consensus tree was constructed from 37,500 post burn-in trees.

4.4 Results

4.4.1 mtDNA Sequence Diversity and Barcoding Analysis

The COI dataset consisted of 609 unambiguously aligned base pairs. As is typical of insect mtDNA (Nardi et al., 2001), the dataset exhibited an A-T bias of 0.648. The COII dataset consisted of 562 unambiguously aligned base pairs with an A-T bias of 0.722.

DNA barcoding analysis of the total COI dataset revealed the presence of 5 operational taxonomic units (OTUs) of Stegopterna based on the Barcode Index Number (BIN) system (Ratnasingham & Hebert, 2013) (fig. 3 and 7). Stegopterna decafilis, a morphologically distinctive species whose North American distribution is restricted to Alaska and the Yukon Territory, was recovered as a single BIN (AAB6274). This species, in turn, was resolved as sister to a BIN consisting of populations from Iqaluit and Kugluktuk, Nunavut (ACE4392). These two BINs together are separated from the other three populations by a distance of 7.1% K2P in both the COI and COI+COII datasets, providing strong evidence of their specific distinctiveness. The monophyletic sister group of these two OTUs consisted of a Finnish Lapland bin of uncertain identity (ACE9571) plus two North American BINs— one that included populations across a wide latitudinal gradient from Montana and southern Manitoba north to northern Ontario and Northwest Territories (AAD8484), and another of exclusively northern populations in Northwest Territories and Nunavut, including the Canadian Arctic Archipelago (ACJ5631). For convenience, the latter two lineages will hereafter be referred to as the “southern” BIN and “northern” BIN, respectively. The Lapland BIN is separated from its North American counterparts by a K2P distance of 3.1%. The southern and northern bins were separated from each other by a genetic distance of 2.3% in COI dataset and 2.7% in COI+COII dataset.

Mean pairwise intra-BIN genetic distances based on the K2P model ranged from 0.00% to 2.35% with a mean of 0.37% (fig. 2.). The greatest divergence was found among members of

80 the southern BIN. Inter-BIN genetic distance ranged from 1.02% to 8.27% with a mean of 5.05%.

4.4.2 Phylogenetic Structure

The NJ tree of COI sequences based on K2P distances (fig. 3) shows high support for the monophyly of all OTUs except members of the widely distributed southern BIN. NJ analysis also suggests population differentiation within the southern BIN, although with weak bootstrap support. The Tamura 3-parameter model (Tamura, 1992) was chosen for NJ analysis of the COI+COII dataset. Tree topology did not change with the addition of the COII gene (fig. 5) and support for the monophyly of the southern BIN increases from 41%-55%.

MP trees were constructed from 105 and 190 informative molecular characters for the COI and COI+COII datasets, respectively. A total of 300 equally parsimonious trees were constructed of 283 steps for the COI dataset, and of 170 steps for the combined COI and COII datasets. The consistency, retention, and composite indices were 0.706, 0.977 and 0.690 respectively for the COI dataset,and 0.794, 0.971 and 0.771 for the COI+COII dataset. The MP strict consensus tree showed considerably less resolution than the NJ tree, although supporting monophyly of the same clades. Given the lack of resolution, bootstrap support values for MP analysis are presented on the NJ tree (fig. 3 and 5).

The GTR+G+I model was chosen for Bayesian analysis of both COI and COI+COII data sets. Relationships among Stegopterna species based on Bayesian inference are shown in figures 4 and 6. These analyses supported the same clades as the NJ and MP analyses, except that the southern BIN was not recovered as monophyletic.

4.5 Discussion

Molecular genetic evidence reveals that the diversity of northern Nearctic Stegopterna is greater than previously recognized. Only three nominal species are currently recognized north of 60° — the morphologically distinct St. decafilis plus two weakly differentiated species (St. emergens and St. trigonium) (fig. 1- Adler et al., 2004). In the present study, there is evidence for at least one additional species (fig. 3 and 7). Re-examination of voucher specimens revealed that populations from Iqaluit and Kugluktuk represent a previously unrecognized species with

81 close affinity to St. decafilis. The presence of 12 gill filaments borne on markedly elongate gill base readily distinguishes the pupa of this species from those of St. decafilis (which have only 10 gill filaments) and St. emergens and St. trigonium (which possess a short gill base) (fig. 8). Furthermore, the presence of biting mouthparts in the female distinguishes this species from those of St. decafilis and St. emergens.

The sister-group of St. decafilis+BIN ACE4392 exhibits considerable genetic diversity. Palearctic population identified as “St. trigonium” in BOLD is well differentiated from related populations in the Nearctic Region — perhaps not surprising given the magnitude of the geographic distance between them (Bergsten et al., 2012; Conflitti et al., 2013). If the identification of St. trigonium is sound (see below for further comment), then that species evidently does not occur in the Nearctic Region. In fact, Nearctic populations tentatively assigned to St. trigonium, differ chromosomally from those of Palearctic populations (Adler et al., 2004).

The sister group of “St. trigonium” is two Nearctic populations that may represent unique species. However, only members of the ‘northern clade’ have high bootstrap- and posterior- probability support. The ‘southern clade’ is not strongly supported in NJ analysis despite being assigned a unique BIN, and is paraphyletic in Bayesian analysis. Of the causes of nonmonophyly outlined by (Funk & Omland, 2003) only inadequate genetic information and incomplete lineage sorting are likely causes for the pattern observed here. Evidence for inadequate genetic information includes lack of support for clades that exhibit paraphyly depending on method of phylogenic inference used. With addition of data from the COII gene, support for monophyly of the southern clade increased from 41% to 55% in NJ analysis, and 56% to 57% in MP analysis. Addition of more rapidly evolving genes may eventually provide stronger support for monophyly of these two clades. Incomplete lineage sorting is another potential explanation. Coalescent- based species delimitation using multilocus data may be necessary to rule this out (Fujita et al., 2012).

An alternative explanation is that the northern and southern clades represent intraspecific variation — perhaps the result of a relatively recent vicariance event. During the Wisconsinan glacial maximum (ca. 18,000 ybp), thick layers of continental ice covered much of northern Canada (Dyke, 2004). It is conceivable that a single northern population survived the glacial

82 maximum in two different refugia (e.g., Beringia versus a southern- or eastern refugium), wherein the isolated populations experienced genetic differentiation. The geographic distributions of the northern and southern clades conform well with previous studies that investigated the genetic consequences of glacial vicariance and post-glacial recolonization from multiple refugia (e.g., Brunhoff et al., 2003; Weider & Hobaek, 2003; Galbreath & Cook, 2004; Klütsch et al., 2012).

Assuming that the BINs identified in Figure 3 represent valid species, we must now consider which of the available specific names applies to the northern and southern populations. The answer is not straightforward as we lack sequences of definitively identified material from the type localities of St. emergens (Fairbanks, Alaska) and St. trigonium (Kittila, Finland). If we follow the species concepts of Adler et al., (2004), then the name St. emergens would apply to members of the southern BIN because that species’ range is extended much farther south (i.e., into Montana, Manitoba and Michigan) than are members of the northern BIN. While the name emergens may very well prove to apply validly to the southern BIN, results from our study reveal that members of the northern BIN are both common and widely distributed at northern latitudes. Accordingly, we cannot rule out the possibility that the name emergens actually applies to the northern BIN. Indeed, members of the northern and southern BINs are broadly sympatric at northern latitudes, and their immature stages were found living together in the same streams in Norman Wells, NT — an ecological setting not unlike that of the type locality of St. emergens in Fairbanks, AK. Clearly, more work is needed to establish true identity of typical St. emergens.

The applicability of the name St. trigonium to one of the northern North American populations is equally problematic. Stegopterna trigonium is an unresolved complex of several nominal species and a number of cytological forms (Adler & Crosskey, 2014). Sequence data from a species of uncertain identity (though collected near the type locality of St. trigonium in Finnish Lapland) proved to be specifically distinct from all North American species included in our study. Unfortunately, the Palearctic Stegopterna have not received the same level of cytological scrutiny as their Nearctic counterparts, and sequence data from that region is sparsely represented in GenBank. While it is clear that the one Palearctic species included in this study is not conspecific with any North American species, we cannot rule out the possibility that the

83 name St. trigonium (or one or more of the other nominal species included in that complex) applies to a population in North America.

To summarize, molecular genetic evidence suggests that at least 4 species of Stegopterna inhabit northern North America. While the identity of St. decafilis — a morphologically distinctive species — is clear, there remains considerable doubt about what names apply to the other 3 species. It seems likely that the name St. emergens will apply validly to members of either the northern or southern BIN, though cytogenetic and molecular scrutiny is needed for populations in the vicinity of the type locality. The name St. trigonium (or any one of the other nominal species assigned to that complex) may apply to one (or both) of the other two species. But, as in the case with St. emergens, further cytological- and molecular screening is needed to account for prospective names from the Palearctic region. In the absence of such efforts, it is risky to propose new names for the North American Stegopterna.

Nomenclatural issues notwithstanding, the discovery of a hitherto unknown species of bloodsucking black fly in northern Canada raises questions. Historical records suggest that St. emergens was the only species of Stegopterna present on Baffin Island, Nunavut (Shewell, 1957); however, contemporary collections yielded only this previously unrecognized one. It is unclear whether historically collected specimens were simply misidentified, or whether St. emergens was supplanted on Baffin Island by members of BIN ACE4392. Reexamination of historically collected material is needed to select from these alternative hypotheses. Another issue pertains to how widely distributed the newly discovered species is. It was commonly collected in Iqaluit and environs, but was absent from all other sampled localities except for a single individual collected at Kugluktuk. This individual could not be identified morphologically because it was an early instar larva — lacking histoblasts that would have allowed examination of the pupal gill. However, is seems unlikely this newly discovered species is restricted to Baffin Island because previous studies of black flies have found no evidence for endemism on continental islands within 100km of the mainland (Adler et al., 2005). This suggests that BIN ACE4392 is likely more widely distributed than previously supposed, albeit in small enough numbers to escape detection by previous collecting efforts.

In summary, DNA analyses of Stegopterna populations from across northern Canada revealed the presence of 4 species — one more than previously recognized. Given the logistical

84 problems associated with fieldwork in the far north, combined with the necessity of obtaining the “correct” life stage(s) for morphological and cytogenetic studies, a molecular genetic approach offers the prospect of accelerating discovery of little known and cryptic species. However, DNA data alone is not sufficient to resolve the nomenclatural problems associated with such species. It is clear that an integrated approach using morphological, cytogenetic and molecular tools is required to sort out the taxonomy of this enigmatic and little studied group of flies.

4.6 References

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4.7 Tables

Table 1. List of samples used in this study with corresponding collection information BOLD Process ID number and Barcode Identification Number (BIN). Sequences obtained from BOLD are denoted with an *.

Taxon Code Locality BOLD Process ID BOLD BIN Cnephia dacotensis* MB Manitoba NBPSI025-11 AAB7512 Stegopterna decafilis* N/A Alaska ACBB729-09 AAB6274 St. decafilis* N/A Alaska ACBB727-09 AAB6274 St. decafilis* N/A Alaska ACBB728-09 AAB6274 St. decafilis* N/A Alaska ACBB736-09 AAB6274 St. decafilis* N/A Yukon Territory ACB1067-06 AAB6274 St. decafilis* N/A Yukon Territory ACB1060-06 AAB6274 St. decafilis* N/A Yukon Territory ACB1064-06 AAB6274 St. decafilis* N/A Yukon Territory ACB1066-06 AAB6274 St. decafilis* N/A Yukon Territory ACB1054-06 AAB6274 St. decafilis* N/A Yukon Territory ACB1065-06 AAB6274 St. decafilis* N/A Yukon Territory ACB1063-06 AAB6274 St. decafilis* N/A Yukon Territory ACB1057-06 AAB6274 St. sp1 NU-IQ01 Iqaluit, Nunavut NBPSI318-13 ACE4392 St. sp1 NU-IQ02 Iqaluit, Nunavut NBPSI351-14 ACE4392 St. sp1 NU-IQ03 Iqaluit, Nunavut NBPSI319-13 ACE4392 St. sp1 NU-IQ04 Iqaluit, Nunavut NBPSI320-13 ACE4392 St. sp1 NU-IQ05 Iqaluit, Nunavut NBPSI321-13 ACE4392 St. sp1 NU-IQ06 Iqaluit, Nunavut NBPSI322-13 ACE4392 St. sp1 NU-IQ07 Iqaluit, Nunavut NBPSI323-13 ACE4392 St. sp1 NU-IQ08 Iqaluit, Nunavut NBPSI324-13 ACE4392 St. sp1 NU-IQ09 Iqaluit, Nunavut NBPSI325-13 ACE4392 St. sp1 NU-IQ10 Iqaluit, Nunavut NBPSI176-11 ACE4392 St. sp1 NU-IQ11 Iqaluit, Nunavut NBPSI177-11 ACE4392 St. sp1 NU-IQ12 Iqaluit, Nunavut NBPSI178-11 ACE4392 St. sp1 NU-KG05 Kugluktuk, Nunavut NBPSI331-13 ACE4392 St. trigonium* LAP01 Lapland, Finland ACB435-06 ACE9571 St. trigonium* LAP02 Lapland, Finland ACB434-06 ACE9571 St. trigonium* LAP03 Lapland, Finland ACB433-06 ACE9571 St. trigonium* LAP04 Lapland, Finland ACB436-06 ACE9571 St. emergens/trigonium ON-MO01 Moosonee, Ontario NBPSI337-13 ACJ5631 St. emergens/trigonium ON-MO02 Moosonee, Ontario NBPSI338-13 ACJ5631 St. emergens/trigonium ON-MO03 Moosonee, Ontario NBPSI339-13 ACJ5631 St. emergens/trigonium ON-MO04 Moosonee, Ontario NBPSI340-13 ACJ5631 St. emergens/trigonium ON-MO05 Moosonee, Ontario NBPSI341-13 ACJ5631 St. emergens/trigonium NT-NW02 Norman Wells, Northwest Territories NBPSI343-13 ACJ5631 St. emergens/trigonium NT-NW04 Norman Wells, Northwest Territories NBPSI345-13 ACJ5631 St. emergens/trigonium NT-NW08 Norman Wells, Northwest Territories NBPSI349-13 ACJ5631 St. emergens/trigonium NT-NW10 Norman Wells, Northwest Territories NBPSI357-14 ACJ5631 St. emergens/trigonium NT-NW13 Norman Wells, Northwest Territories NBPSI360-14 ACJ5631 St. emergens/trigonium* MB01 Manitoba JRB138-08 ACJ5631 St. emergens/trigonium* MB02 Manitoba JRB022-08 ACJ5631 St. emergens/trigonium* MB03 Manitoba JRB190-08 ACJ5631 St. emergens/trigonium* MB04 Manitoba JRB004-08 ACJ5631 St. emergens/trigonium* MB05 Manitoba JRB144-08 ACJ5631 St. emergens/trigonium* MB06 Manitoba JRB114-08 ACJ5631 St. emergens/trigonium* MT01 Montana JRB010-08 ACJ5631 St. emergens/trigonium NU-BK01 Banks Island, Nunavut NBPSI287-13 ACJ5631 St. emergens/trigonium NU-BK02 Banks Island, Nunavut NBPSI288-13 ACJ5631

Table 1. Continued

Taxon Code Locality BOLD Process ID BOLD BIN St. emergens/trigonium NU-BK03 Banks Island, Nunavut NBPSI290-13 ACJ5631 St. emergens/trigonium NU-BK04 Banks Island, Nunavut NBPSI294-13 ACJ5631 St. emergens/trigonium NU-BK05 Banks Island, Nunavut NBPSI296-13 ACJ5631 St. emergens/trigonium NU-BK06 Banks Island, Nunavut NBPSI298-13 ACJ5631 St. emergens/trigonium NU-BK07 Banks Island, Nunavut NBPSI299-13 ACJ5631 St. emergens/trigonium NU-BK08 Banks Island, Nunavut NBPSI300-13 ACJ5631 St. emergens/trigonium NU-CB01 Cambridge Bay, Nunavut NBPSI301-13 ACJ5631 St. emergens/trigonium NU-CB02 Cambridge Bay, Nunavut NBPSI302-13 ACJ5631 St. emergens/trigonium NU-CB03 Cambridge Bay, Nunavut NBPSI303-13 ACJ5631 St. emergens/trigonium NU-CB04 Cambridge Bay, Nunavut NBPSI304-13 ACJ5631 St. emergens/trigonium NU-CB05 Cambridge Bay, Nunavut NBPSI305-13 ACJ5631 St. emergens /trigonium NU-CB06 Cambridge Bay, Nunavut NBPSI306-13 ACJ5631 St. emergens/trigonium NU-CB07 Cambridge Bay, Nunavut NBPSI307-13 ACJ5631 St. emergens/trigonium NU-CB08 Cambridge Bay, Nunavut NBPSI308-13 ACJ5631 St. emergens/trigonium NU-CB09 Cambridge Bay, Nunavut NBPSI310-13 ACJ5631 St. emergens/trigonium NU-CB10 Cambridge Bay, Nunavut NBPSI311-13 ACJ5631 St. emergens/trigonium NU-CB11 Cambridge Bay, Nunavut NBPSI312-13 ACJ5631 St. emergens/trigonium NU-CB12 Cambridge Bay, Nunavut NBPSI313-13 ACJ5631 St. emergens/trigonium NU-CB13 Cambridge Bay, Nunavut NBPSI314-13 ACJ5631 St. emergens/trigonium NU-CB14 Cambridge Bay, Nunavut NBPSI315-13 ACJ5631 St. emergens/trigonium NU-CB15 Cambridge Bay, Nunavut NBPSI317-13 ACJ5631 St. emergens/trigonium NU-KG01 Kugluktuk, Nunavut NBPSI327-13 ACJ5631 St. emergens/trigonium NU-KG02 Kugluktuk, Nunavut NBPSI328-13 ACJ5631 St. emergens/trigonium NU-KG03 Kugluktuk, Nunavut NBPSI329-13 ACJ5631 St. emergens/trigonium NU-KG04 Kugluktuk, Nunavut NBPSI330-13 ACJ5631 St. emergens/trigonium NU-KG06 Kugluktuk, Nunavut NBPSI332-13 ACJ5631 St. emergens/trigonium NU-KG07 Kugluktuk, Nunavut NBPSI333-13 ACJ5631 St. emergens/trigonium NU-KG08 Kugluktuk, Nunavut NBPSI334-13 ACJ5631 St. emergens/trigonium NU-KG09 Kugluktuk, Nunavut NBPSI335-13 ACJ5631 St. emergens/trigonium NU-KG10 Kugluktuk, Nunavut NBPSI336-13 ACJ5631 St. emergens/trigonium NU-KG11 Kugluktuk, Nunavut NBPSI352-14 ACJ5631 St. emergens/trigonium NU-KG12 Kugluktuk, Nunavut NBPSI353-14 ACJ5631 St. emergens/trigonium NU-KG13 Kugluktuk, Nunavut NBPSI354-14 ACJ5631 St. emergens/trigonium NU-KG14 Kugluktuk, Nunavut NBPSI355-14 ACJ5631 St. emergens/trigonium NU-KG15 Kugluktuk, Nunavut NBPSI356-14 ACJ5631 St. emergens/trigonium NT-NW01 Norman Wells, Northwest Territories NBPSI342-13 ACJ5631 St. emergens/trigonium NT-NW03 Norman Wells, Northwest Territories NBPSI344-13 ACJ5631 St. emergens/trigonium NT-NW05 Norman Wells, Northwest Territories NBPSI346-13 ACJ5631 St. emergens/trigonium NT-NW06 Norman Wells, Northwest Territories NBPSI347-13 ACJ5631 St. emergens/trigonium NT-NW07 Norman Wells, Northwest Territories NBPSI348-13 ACJ5631 St. emergens/trigonium NT-NW09 Norman Wells, Northwest Territories NBPSI350-13 ACJ5631 St. emergens/trigonium NT-NW11 Norman Wells, Northwest Territories NBPSI358-14 ACJ5631 St. emergens/trigonium NT-NW12 Norman Wells, Northwest Territories NBPSI359-14 ACJ5631 St. emergens/trigonium NT-NW14 Norman Wells, Northwest Territories NBPSI361-14 ACJ5631 St. emergens/trigonium NT-NW15 Norman Wells, Northwest Territories NBPSI362-14 ACJ5631

4.8 Figures

Figure 1. Map of study area showing sampling sites and known distributions of three currently recognized species of northern Stegopertna, as inferred from Adler et al., (2004).

Figure 2. Frequency distribution of intraspecific (light gray) and interspecific (dark gray) K2P distances for five Stegopterna BINs.

Figure 3. NJ tree generated using K2P distances. Analysis is based on 94 Stegopterna barcode sequences, 609bp in length. Branch numbers indicate bootstrap support for NJ and MP analyses respectively (i.e. NJ/MP).

Figure 4. Phylogenetic relationships Stegopterna species using Bayesian methods. Analysis is based on 94 Stegopterna barcode sequences, 609bp in length. The 50% majority-rule consensus tree sampled from the posterior distribution is presented (-lnL: - 2856.83). Branch numbers indicate Bayesian posterior probabilities.

Figure 5. NJ tree generated using T92 distances. Analysis is based on 66 Stegopterna COI and COII sequences, 1171bp in length. Branch numbers indicate bootstrap support for NJ and MP analyses respectively (i.e. NJ/MP).

Figure 6. Phylogenetic relationships Stegopterna species using Bayesian methods. Partitioned analysis is based on 66 Stegopterna COI and COII sequences, 1171bp in length. The 50% majority-rule consensus tree sampled from the posterior distribution is presented (-lnL: -2603.44). Branch numbers indicate Bayesian posterior probabilities.

Figure 7. Map showing approximate distribution of three northern Stegopterna BINs based on samples analyzed in this study.

Figure 8. A Pupa of previously unrecognized Stegopterna BIN from Iqaluit. Black lines highlight the markedly elongate pupal gill base. B Pupal gill of Stegopterna emergens. Black lines highlight the short pupal gill base, typical of St. emergens, St. trigonium and St. decafilis.

Chapter 5 General conclusion

Contemporary climate change disproportionately impacts northern latitudes. A better understanding of the ecological structure of northern species is needed to evaluate the potential impacts of a warming climate. Unfortunately, the insect fauna at northern latitudes remain among the least known, due largely to the vastness of the territory, lack of access, and the high costs of conducting fieldwork in the far north. The Northern Biodiversity Program was established to redress this deficiency by sampling arthropods at 12 widely distributed sites in northern Canada using standardized quantitative and qualitative techniques. My role in this collaborative project was to study the biting fly fauna. More specifically, the key goal of my thesis is to determine how climate and geographical history have affected the historical- and contemporary diversity and distribution of biting flies.

Chapter 2 investigated how, and to what degree, the richness and structure of mosquito (Culicidae) and black fly (Simuliidae) assemblages change in the transition from the Boreal ecoclimatic zone to the Arctic ecoclimatic zone. Results showed that biting fly assemblages in the Arctic differ markedly from those of the Boreal and Subarctic ecoclimatic zones, with temperature being the primary driver. In the Boreal and Subarctic zones, black fly assemblages exhibit significant differences between eastern and western sites, whereas mosquito assemblages are shaped more by ecological factors, with little geographical structure. This chapter highlights the importance of both ecological and historical factors in determining macrodistributional patterns. Sampling in this study was too broad to adequately address ecological changes that may have resulted from contemporary climate change.

To determine how climate change is impacting community structure in northern biting flies, Chapter 3 used finer-scale sampling on Victoria Island with sites covering a marked temperature gradient. Historically, the Canadian Arctic Archipelago (CAA) was dominated numerically by arctic-adapted (i.e., non-bloodsucking) species of black flies, with a total of just 9 species known throughout the archipelago. Contemporary collections from 3 islands in this study revealed the presence of 9 additional species — most of which are southern-adapted bloodsucking species. By mapping the present-day distribution of species on a climate map, I showed that there is a strong correlation between temperature and the presence of bloodsucking

100 black flies. The thermal threshold for presence of biting species was an average summer temperature of 5.8°C. Except for southern margins of some of the southernmost islands, this minimum temperature was absent from the CAA a half century ago — a time when the CAA was most intensively collected for black flies. This supports the hypothesis that newly-recorded species are indeed recent immigrants (as opposed to being overlooked by previous collectors). This is among the first studies to definitively document rapid and profound changes in species richness and ecological structure attributable to climate change in the Arctic. As temperatures continue to warm, additional species of southern-adapted biting flies are likely to colonize the CAA. Monitoring ongoing changes in community composition and structure is fundamental to projecting potential impacts on host species.

Many arthopods can only be identified to species level if a particular life history stage or gender is available for study. Furthermore, identification is possible in some instances only if material is fixed in a particular fashion, as is the case for cryptic black flies that require examination of the giant polytene chromosomes of larvae. This presents a particular challenge at northern latitudes, where the “correct” life stage or gender might not be available during the short collecting season. In Chapter 4 I used two mitochondrial genes to assess genetic diversity among northern members of the black fly genus Steopterna. This genus is well known for cryptic diversity, with half the North American species originally being recognized by cytogenetic studies. Because the great majority of Stegopterna collected in this study were unsuitable for chromosomal examination, the use of molecular markers opened the possibility that all material could be identified. Results showed that the Stegopterna fauna of northern Canada is richer than previously supposed, with discovery of hitherto unrecognized species on southern Baffin Island. Molecular data confirmed the presence of two other (more widely distributed) species in northern Canada, though our results cast doubts about which of the available specific names apply to each. An integrated approach combining chromosomal, molecular and morphological data, along with resampling type localities for available names, is needed to settle the nomenclature of this taxonomically difficult genus.

In summary, my thesis uses data from a broad-scale survey of northern Canadian biting flies conduced over a short (3 year) period of time. As such I was able to address a range of otherwise intractable ecological and evolutionary questions. Combining historical and contemporary collection records provided confidence when assessing broad-scale ecological

101 structure. Technological advances in the interpretation of GIS spatial data allowed me to evaluate how environmental variables can influence finer-scale black fly distributions for the first time. Using a molecular genetic approach, I was able to extract the maximum amount of information from material collected at 11 widely distributed sites in northern Canada, including the identification of cryptic species.

In order to more fully understand how the ecological structure of northern biting flies is changing, a long-term monitoring program should be established wherein particular sites are sampled repeatedly over a 5-10 years time scale (as opposed to the half century one used in this study). Such programs should also include finer-scaled sampling of taxa of special concern, such as vectors of parasitic diseases of rare- and threatened birds and mammals.