Multi-Scale Patterns of Ground-Dwelling Spider (Araneae) Diversity in Northern Canada

Multi-scale patterns of ground-dwelling

spider (Araneae) diversity in northern

Canada

Department of Natural Resource Sciences

McGill University

Montréal, Québec, Canada

April 2013

A thesis submitted to the Faculty of Graduate Studies and Research in

partial fulfillment of the requirements for the degree of Master in Science

LIST OF TABLES ...... iii

LIST OF FIGURES ...... iv

LIST OF APPENDICES ...... vi

ACKNOWLEDGMENTS ...... vii

PREFACE AND CONTRIBUTION OF AUTHORS ...... ix

ABSTRACT / RÉSUMÉ ...... x

CHAPTER 1: GENERAL INTRODUCTION, LITERATURE REVIEW AND OBJECTIVES ...... 1

General introduction ...... 1

Patterns and spatial scale ...... 2

Diversity partitioning ...... 4

Patterns in arthropod diversity ...... 6

Arctic arthropods ...... 7

Spiders as model taxon ...... 9

Objectives ...... 11

Literature cited ...... 12

CHAPTER 2: MULTI-SCALE PATTERNS OF GROUND-DWELLING SPIDER (ARANEAE) DIVERSITY IN NORTHERN CANADA ...... 23

Abstract ...... 24

Introduction ...... 25

Methods ...... 27

Sampling design ...... 27

Environmental variables ...... 29

Vegetation ...... 29

Climate ...... 30

Statistical analyses ...... 30

Spatial variation in spider assemblage structure ...... 30

Comparison of composition ...... 31

Multi-scale patterns of α and β diversities ...... 31

Vegetation and climate ...... 32

Results ...... 33

Multi-scale patterns of spider diversity ...... 33

Multi-scale patterns of the dominant families ...... 35

Climate and vegetation ...... 36

Discussion ...... 37

Diversity patterns at the continental scale ...... 38

Diversity patterns at the regional scale ...... 39

Diversity patterns at the local scale ...... 40

Diversity patterns of the dominant families ...... 41

Vegetation and climate ...... 42

Conclusion ...... 43

Acknowledgments ...... 44

Literature cited ...... 45

CHAPTER 3: GENERAL CONCLUSIONS AND FUTURE WORK 81

Literature cited ...... 83

LIST OF TABLES

Table 1. Observed (SRobs) and estimated total species richness (Chao1 and Jack1 ± confidence interval) of ground-dwelling spiders (Araneae) per site of the three ecoclimatic regions. Completeness=SRobs/Jack1*100. Ecoclimatic regions: A=Arctic, S=Subarctic, NB=North-Boreal. Sites: HA=Hazen Lake, NU; IQ=Iqaluit, NU; CB=Cambridge Bay, NU; BA=Banks Island, NU; CH=Churchill, MB; SC=Schefferville, QC; TO=Tombstone mountains, YT; KU=Kugluktuk, NU; GB=Goose Bay, LB; MO=Moosonee, ON; YE=Yellowknife, NT and NW=Norman Wells, NT...... 55

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LIST OF FIGURES

Figure 1. Individual-based rarefaction curves of the species richness of ground- dwelling spiders in three ecoclimatic regions (Arctic, Subarctic and North- Boreal), in northern Canada...... 56

Figure 2. Abundance and diversity of ground dwelling spider families in twelve sites of northern Canada, sampled in 2010 and 2011. For each site, the abbreviation of the name, the number of species, a pie graph of the diversity by family and a bar graph with the relative abundance of the two most common families of spiders is given. Sites: HA=Hazen Lake, NU; IQ=Iqaluit, NU; CB=Cambridge Bay, NU; BA=Banks Island, NU; CH=Churchill, MB; SC=Schefferville, QC; TO=Tombstone mountains, YT; KU=Kugluktuk, NU; GB=Goose Bay, LB; MO=Moosonee, ON; YE=Yellowknife, NT and NW=Norman Wells, NT...... 57

Figure 3. Non-metric multidimensional scaling (NMDS) ordination of spider species composition of 72 replicates, described by the relative abundance of 306 spider species. Although all sites were included in the same ordination in a and b, in the upper right plot b, inverse triangle represent western sites and dark circles represent eastern sites. Western sites (c; 176 spider species) and eastern sites (d; 200 spider species) were then plotted separately with site names to ease interpretation. Ellipses depict ecoclimatic regions in plot...... 58

Figure 4. Percentage of continental diversity (γ=306 species) and Shannon diversity explained by α and β components. Observed species diversity was partitioned for the most diverse family of spiders, the Linyphiidae (169 species), and for the most abundant family of spiders, the Lycosidae (32 species). Gamma diversity was partitioned into mean diversity within trap (α1), between traps (β1), between replicates (β2), between sites (β3) and between ecoclimatic regions (β4). Asterisk indicates that the observed diversity at a level is significantly different than random expectations (***: significantly higher than expected (P<0.01), **:

iv significantly higher than expected (P<0.05) and *: significantly lower than expected (P>0.9))...... 59

Figure 5. Percentage of spider species richness (306 species) and Shannon diversity explained by α and β components within each ecoclimatic region: Arctic (γ=37 species), Subarctic (γ=170 species) and North-Boreal (γ=231 species).

Regional diversity was partitioned into mean diversity within trap (α1), between traps (β1), between replicates (β2) and between sites (β3). Asterisk indicates that the observed diversity at a level is significantly different than random expectations (***: significantly higher than expected (P<0.01), **: significantly higher than expected (P<0.05) and *: significantly lower than expected (P>0.9))...... 60

Figure 6. RDA biplot of the Hellinger-transformed spider data constrained by environmental variables, scaling 2, for the a) entire community, b) the Arctic ecoclimatic region, c ) the Subarctic ecoclimatic region and d) the North-Boreal ecoclimatic region. Environmental variables selected by the forward selection: gramcov=cover of graminoids, moscov=cover of mosses, lichcov=cover of lichens, forbcov=cover of forbs, maxveght=maximum vegetation height, long=longitude, sd.pd= standard deviation of active layer’ depth, mean.pd= average depth of active layer, maxT= maximum temperature of the warmest month of the site, DJA0= degree days above zero at the site, DJB0= degree day below zero at the site, AP= annual precipitation...... 61

LIST OF APPENDICES

Appendix 1. Location of the Northern Biodiversity Program study sites in northern Canada and relationship between hierarchical nested design and diversity partitioning components...... 62

Appendix 2. Table of sampling dates, spatial and environmental variables per site. Sites: HA=Hazen Lake, NU; IQ=Iqaluit, NU; CB=Cambridge Bay, NU; BA=Banks Island, NU; CH=Churchill, MB; SC=Schefferville, QC; TO=Tombstone mountains, YT; KU=Kugluktuk, NU; GB=Goose Bay, LB; MO=Moosonee, ON; YE=Yellowknife, NT and NW=Norman Wells, NT. Habitats: M=mesic, W=wet. The column ‘days’ refers to the number of sampling days. Environmental variables : mean.pd= average depth of active layer, sd.pd= standard deviation of active layer’ depth, maxveght=maximum vegetation height, gramcov=cover of graminoids, moscov=cover of mosses, lichcov=cover of lichens, forbcov=cover of forbsr, shrubcov=cover of shrubs, AMT= annual mean temperature of the site, maxT= maximum temperature of the warmest month of the site, minT= minimum temperature of the coldest month of the site, AP= annual precipitation, DJA0= degree days above zero at the site, DJB0= degree day below zero at the site. Values of environmental variables from the field are an average of values from 5 or 6 traps per replicate...... 63

Appendix 3. Pooled number of individuals and species collected in pitfall and yellow pan traps by the Northern Biodiversity Program during the summer 2010 and 2011 in 12 sites in Northern Canada. Sites: BA=Banks Island, NU; CB=Cambridge Bay, NU; HA=Hazen Lake, NU; IQ=Iqaluit, NU; CH=Churchill, MB; KU=Kugluktuk, NU; SC=Schefferville, QC; TO=Tombstone mountains, YT; GB=Goose Bay, LB; MO=Moosonee, ON; NW=Norman Wells, NT and YE=Yellowknife, NT. Provincial new records are based on the most recent checklist available for Canadians spiders (Paquin et al. 2010)...... 66

Acknowledgments:

The main funding for this project came from a Strategic Project Grant from The

Natural Sciences and Engineering Research Council of Canada (NSERC) awarded to C.M. Buddle and T. Wheeler (McGill University) and D.C. Currie (University of Toronto). This project is titled Ecological Structure of Northern Arthropods:

Adaptation to a Changing Environment.

First, I want to thank Chris Buddle, my supervisor, for giving me the chance to do a Master’s on Arctic spiders. I always felt lucky to be in your lab. You evaluate a human being on human qualities, such as motivation, passion and curiosity, and not only on grades. Your love for science, ecology and life is really inspiring.

Thank you for sharing your passion of the Arctic and spiders with me.

A special thought goes to Terry Wheeler. After the first field season, I lost my self-confidence to be a graduate student. You trusted me and because of you, I realised what I was good at. This was precious to me. I will always be grateful.

I want to thank every labmates “Buddlites”: Meggy Hervieux for every laugh together, Joey Bowden for all your time on google chat answering all my last minute and urgent questions, Raphaël Royauté for every geeky discussion,

Dorothy Maguire for all the entertainment, Kathrin Sim for your collection of geeky T-shirts, your amazing cupcakes and identification of spiders. I am thankful to Crystal Ernst for all the great advices you gave me, professionally and personally. You all are talented and inspiring. Like I told you so many times, you

vii are truly a second family for me. I could not imagine a better lab to evolve in as a grad student and as a parent. My last happy dance in the lab is for you all.

Thanks to the Northern Biodiversity Program (NBP) members for collecting and sorting specimens: Chris Buddle, Doug Currie, Terry Wheeler, Donna Giberson,

Laura Timms, Crystal Ernst, Meagan Blair, Anna Solecki, Kathrin Sim and

Christine Roussel. I want to thank Sarah Silverman for her help during sorting.

I want to thank Don Buckle for his help identifying some of the tiny Linyphiids.

At each email, I felt that I wasn’t the only one to be excited by spider identification. I really hope that we will meet soon to identify some Linyphiidae together! I want to thank Joseph Veech for his help and the time he gave to help me analyse data with the software Partition 3.0. I am grateful to everyone from the Lyman Museum who gave me advice and comments on early drafts of this thesis. Thank you for sharing your ideas and wine.

Finally, I want to thank my partner Mathieu for his unconditional support year after year. You are an incredible help. You believe in me like no one does. When I have a crazy project, you are the one who brings me down to earth to make sure that I do not just dream about it but I do everything I can in rational ways to make my dreams real. I am a super graduate student mom because of you. I love you !

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Preface and contributions of authors

This research is part of a collaborative research program called Northern

Biodiversity Program (NBP). Chris Buddle and other NBP co-applicants

T.Wheeler and D.C. Currie created the sampling design. Sarah Loboda was responsible for specimen preparation and identification, analysing data and writing the manuscript. Chris Buddle supervised the research and provided comments on methods of analysis and edited all chapters of this thesis.

This thesis is composed of three chapters, including an introduction and literature review, one manuscript that will be submitted for publication in a refereed journal, and a conclusion.

Chapter 1. This chapter provides an introduction and a review of relevant published literature. It introduces the main theme of the thesis and outlines the objectives of the thesis.

Chapter 2. This chapter is a manuscript in preparation for submission to

Ecography: Loboda, S. and Buddle, C.M. Multi-scale patterns of ground-dwelling spider (Araneae) diversity in northern Canada.

Chapter 3. This chapter compiles the main findings. Recommendations for future research are discussed.

Abstract

This thesis describes multi-scale patterns of ground-dwelling spiders (Araneae), a model arthropod taxon, in northern Canada. First, I examined how ground- dwelling spider diversity (i.e., composition, species richness, evenness and structure) varied at local, regional and continental scale, in three major ecoclimatic regions: the North-Boreal, Subarctic and Arctic. Second, I determined if diversity patterns varied at the family level. Third, I tested whether climate or vegetation explained spatial variation of diversity. Ground-dwelling spiders were collected in 12 sites across northern Canada using a hierarchical nested design.

Spider diversity was structured at continental scale across ecoclimatic regions but not by latitude. At regional scale, western sites differed from eastern sites indicating the importance of longitudinal diversity gradients in northern Canada, perhaps due to patterns of post-glacial dispersal. Vegetation and climate explained

Arctic diversity patterns of spiders, and thus predicted climate change may alter the distribution of spiders. Our results suggest that historical processes as well as vegetation and climate are important drivers of diversity patterns at continental scale in northern Canada while biotic factors may affect small scale variation in diversity. Due to the large extent and fine resolution, this research contributes to a better understanding of hierarchical patterns of diversity. It also provides baseline data on distribution and diversity of Arctic spiders that will be essential to monitor the effect of environmental changes on biodiversity in northern Canada.

Résumé

Le but de cette thèse est de décrire les patrons de diversité des arthropodes sur plusieurs échelles spatiales dans le Grand Nord canadien en utilisant les Araignées

(Araneae) comme taxon modèle. Les questions de recherche sont les suivantes : 1)

Comment la diversité des araignées (c.-à-d. composition, richesse spécifique, uniformité de l’abondance et structure) varie à l’échelle locale, régionale et continentale dans trois grandes régions écoclimatiques : la région Nord-Boréale,

Subarctique et Arctique ? 2) Comment les patrons de diversité diffèrent au niveau des familles d’araignées ? et, finalement, 3) Est-ce que le climat et la végétation influencent les patrons de diversité observés? Les araignées vagabondes ont été capturées dans 12 emplacements dans le Grand Nord canadien selon un plan d’échantillonnage hiérarchique imbriqué. La diversité des araignées est structurée

à l’échelle continentale selon les régions écoclimatiques, et non selon la latitude.

À l’échelle régionale, un gradient de diversité entre l’ouest du Canada et l’est du

Canada est dû, non pas à la longitude, mais probablement aux évènements historiques tels que la dernière glaciation du Wisconsin. La végétation et le climat influencent également la variation de diversité des araignées. Grâce à la haute résolution des données à petite échelle sur une grande étendue spatiale, cette étude contribue à la compréhension des patrons de diversité et de l’effet de l’échelle spatiale sur les patrons. Les résultats pourront aussi être utilisés afin de mieux définir des stratégies de protection de la biodiversité arctique.

CHAPTER 1: GENERAL INTRODUCTION, LITERATURE REVIEW

AND OBJECTIVES

General Introduction

Biodiversity is not distributed uniformly on Earth (Wallace 1876). How and why spatial and temporal variations in biodiversity occur remains a persistent and challenging question in ecology (Brown and Lomolino 1998). Biodiversity patterns are used to develop and evaluate ecological theories, including the species-area relationships (Connor and McCoy 1979) and the equilibrium theory of island biogeography (MacArthur and Wilson 1967). Diversity patterns also have practical applications as they can be used to adopt conservation strategies

(e.g., Gering et al. 2003) or to predict the response of species to disturbances or environmental changes (e.g., Pearson and Dawson 2003, Guisan and Thuiller

2005).

Unfortunately, studies on diversity patterns are spatially biased toward temperate and tropical forests (Brown and Lomolino 1998, Whittaker et al. 2005, Beck et al.

2012). Ecological patterns and processes in temperate regions are known to differ from those in tropical regions (Algar et al. 2010) and thus it is reasonable to assume patterns and processes in Arctic regions will also differ from other major biomes on the planet. However, Arctic patterns have received relatively little attention in the literature (but see Danks 1993, Bowden and Buddle 2010a,

Virtanen et al. 2012, Yasuhara et al. 2012).

In addition to the spatial bias, ecological studies on large-scale patterns (e.g., at regional, continental and global spatial scale) are taxon biased toward plants and vertebrates (Platnick 1991, Diniz-Filho et al. 2010, Beck et al. 2012). Despite the growing body of research on diversity patterns, our comprehension of large-scale diversity patterns for hyper-diverse organisms, such as arthropods, remains sparse. It is unclear whether generalisations that emerge from studies on vertebrates or plants can be applied to arthropods, a taxon accounting for 85% of the known global species (Pearson and Carroll 1999, Lund and Rahbek 2002, Mac

Nally et al. 2002). Large moth richness was shown to be a good predictor of other animal richness in Denmark (Lund and Rahbek 2002). However, Wolters et al.

(2006) showed in a meta-analysis that no taxon is a good predictor of the species richness of another taxon (including arthropods).

In this thesis, I determined diversity patterns of ground-dwelling spiders, a model taxon for arthropods, at local, regional and continental spatial scale in northern

Canada. I also tested whether or not climate and vegetation explain diversity structure in order to find determinants of diversity patterns.

Patterns and spatial scale

Patterns and the mechanisms that govern these patterns vary with spatial scale, determined in ecology by the extent (i.e. geographic area investigated) and the grain (i.e size of sampling units or resolution of the study) (Shmida and Wilson

1985, Wiens 1989, Palmer and Dixon 1990, Levin 1992). Patterns observed at one scale are the result of complex interactions among processes operating at multiple

2 scales (Rahbek 2005). Therefore, diversity patterns and processes at one scale cannot be deduced from patterns at a single, different spatial scale (e.g., Larrivée and Buddle 2010). For example, the diversity of oribatid mites in a canopy system was random at a small spatial scale but structured at higher scales, suggesting that stochasticity may be important at a small spatial scale while dispersal, habitat availability and environmental factors will have an effect on diversity at higher spatial scales (Lindo and Winchester 2008). Consequently, assessment of biodiversity patterns requires study at multiple spatial scales including multiple grains and extents (Beck et al. 2012).

In practice, spatial extent and grain are dependent on each other (Beck et al.

2012). Biodiversity patterns are often explored on small spatial extent based on field data (fine-grained data). In this context, influence of large scale processes

(e.g., energy, productivity, water availability) is underestimated because only a small portion of the large environmental gradients is considered. In contrast, macroecology increases our understanding of diversity patterns over a large geographic extent based on comparison of atlas data (coarse-grained data)

(Gaston 2000, Beck et al. 2012). However, macroecology datas are often a list of species occurrences over a large area, and lack knowledge related to whether or not the species coexist at smaller, ecological scales. Therefore, species interactions (e.g. competition, parasitism) are often not formally considered in macroecological studies (Hortal 2008).

The combination of fine resolution data across a large geographic area provides an interesting view of how small and large scale processes respectively affect

3 patterns at different scales (Ricklefs and Jenkins 2011). With 20 beetles species collected in several sites across Great Britain, Gillingham et al. (2012) found that high-resolution temperature best explain species distributions at a local scale but habitat type best explain variation of species distributions at a regional scale.

Furthermore, a better comprehension of diversity patterns at a continental and global spatial scale can be obtained by examining not only richness, but other important aspects of diversity (composition or evenness) only acquired with smaller-scale ecological data from the field (Beck et al. 2012, Gillingham et al.

2012). For example, Andrew and Hughes (2005) collected herbivorous beetles on one host plan species along a latitudinal gradient in Australia and found that abundance and biomass of arthropods were consistent among latitudes.

Spatial scales are by definition nested which means biodiversity can be measured at multiple spatial scales using a standardized nested sampling design. Under such hierarchical designs, partition of diversity can be used to describe patterns at multiple spatial scales, without sacrificing grain or extent of investigation (Crist et al. 2003).

Diversity partitioning

Partition of diversity is based on a concept first described by Whittaker (1960) in which richness is partitioned in 3 components according to spatial scale: α diversity (within community), β diversity (among communities) and γ diversity

(total diversity at large scale). β diversity, or diversity turnover, is the proportion of the total species richness (γ diversity) found in one habitat (α diversity), as β

=γ/ α. The multiplicative partition measures the proportion by which a region is richer in species than the average locality within it. The multiplicative relation has been criticized since total diversity is overestimated when local communities share species (Lande 1996). Also, α, β and γ cannot be compared directly because they do not share the same unit (Lande 1996). Therefore, Lande (1996) proposed an additive relationship between diversity components where γ = α + β. Instead of a ratio, β is the average difference in number of species found between communities. The additive partitioning has also been critisized in part because, with this mathematical framework, α and β are not considered independent (Jost

2007, Baselga 2010). However, in a recent review of diversity partitioning, Chao et al. (2012) conclude that, when used properly, both approaches can be used to measure different aspects of diversity.

The additive partitioning has become popular in community ecology and conservation because results from this method are easier to interpret and compare than Whittaker’s model. Since the development of the Partition software (Veech and Crist 2009), additive partitioning can be calculated at multiple scales and compared to a random distribution. This framework has been used to evaluate biodiversity hotspots and highlight habitats of interest for conservation (Fournier and Loreau 2001). For example, Gering et al. (2003) found that the β diversity between ecoregions and β diversity between sites components contributed the most to overall γ diversity of arboreal beetles in deciduous forest, and thus, they suggested multiple sites in each ecoregion be protected to preserve beetle biodiversity.

Despite progress in ecology and macroecology, most broad-scale studies on biodiversity patterns are still taxon biased toward vertebrates and plants (Diniz-

Filho et al. 2010, Ricklefs and Jenkins 2011, Beck et al. 2012). Arthropods biodiversity remains largely understudied despite the fact that they represent about half of the global diversity described (Chapman 2009). The description of arthropod spatial patterns is far from complete making it difficult to determine whether or not generalisations, which emerge from studies on vertebrates or plants may hold, with arthropod taxa (Platnick 1991, Brown and Lomolino 1998,

MacNally et al. 2002, Whittaker et al. 2005, Diniz-Filho et al. 2010, Beck et al.

2012).

Patterns in arthropod diversity

The additive partitioning framework under a hierarchical sampling design has been particularly helpful when studying patterns of arthropod diversity. Research in tropical and temperate forests has focused on local and regional patterns of butterflies (Summerville et al. 2003, Ribeiro et al. 2008), flies (Stireman 2008,

Lévesque-Beaudin and Wheeler 2011), bees and wasps (Tylianakis et al. 2005), beetles (Fournier and Loreau 2001, Gering et al. 2003), desert ants (Paknia and

Pfeiffer 2011), spiders (Cabra-García et al. 2010, Larrivée and Buddle 2010) and mites (Lindo and Winchester 2008). In most of those studies, diversity patterns are non-random at every spatial scale. Larger scales of investigation accounted for much of the γ-diversity indicating that regional scale processes highly influence arthropod patterns in tropical and temperate forests.

Studies on multi-scale patterns of arthropod diversity generally consider local and regional diversity, while disregarding patterns at the continental scale. However, the study of incomplete environmental gradient by investigating a small spatial extent could give conflicting results as evidenced by Wiens (1989). The presence of the Least Flycatcher (Empidonax minimus) at the local scale was negatively correlated with the presence of another bird, the American Redstart (Setophaga ruticilla), but at the regional scale, there was a positive correlation between the presence of both species (Wiens 1989). It is critical, therefore, to describe patterns at several spatial scales over broad geographic extent. To study arthropod diversity patterns at the continental spatial scale, the Arctic, defined as the northern treeless expanse (Nuttal 2005), is an ideal ecosystem (Wisz et al. 2013).

Arctic arthropods

The Arctic is an ideal biome with which to study large-scale diversity patterns and determinants of biodiversity because of its relatively simple ecosystem (Strathdee and Bale 1998, Wisz et al. 2013). Even though diversity is reduced in the Arctic relatively to temperate and tropical regions (Strathdee and Bale 1998), over than

4000 described arthropods species are found above the latitudinal treeline

(Callaghan et al. 2004), with more than 2000 known from Arctic North America

(Danks 1981).

Some spatial patterns of arthropod species richness have been described, notably insects, based on atlas data. In general, richness of insect species (e.g. Orthoptera,

Coleoptera) follows the gradient of plant richness with a decrease from low to

7 high latitudes (Danks 1993). However, for some arthropod taxa, including

Diptera, an inverse gradient is observed (Danks 1993). Moreover, an increase of diversity has been observed from islands in the High-Arctic to islands in the Low-

Arctic to Arctic mainland (Danks 1993, Marusik and Koponen 2002).

Higher species richness and higher number of endemic species in the west of

Canada relative to the east have been observed in butterflies and other insect groups (Danks 1993, Chernov 1995, Callaghan et al. 2004). Evidence based on mammal, plant and reptile phylogeography suggests that western species likely originate from the Beringian refugium, the Haida Gwaii refugium or other cryptic western refugia while species currently in eastern Canada may originated from southern refugia after the Wisconsin glaciation (e.g. Janzen et al. 2002, Adams et al. 2003, Waltari et al. 2004). Danks (1993) also indicated that higher insect species richness in the western provinces of Canada was a result of the high diversity of habitats (e.g., coastal and cordilleran) in addition to the influence of historical events.

At northern latitudes, arthropod abundance shows interesting pattern with, for example, an increase in Collembola abundance towards the Arctic region

(Babenko 2000). The decline of species richness towards the Arctic region has consequences on species abundance (Chernov 1995, Callaghan et al. 2004) but abundance patterns in the Arctic varied with species (Bowden and Buddle 2010a).

From an applied perspective, understanding patterns and determinants of diversity in the Arctic is critical as it is one of the most threatened ecosystems on Earth

(IPCC 2007). The Arctic has warmed two times more than the global average over the last half century (IPCC 2007). Arthropods, because of their small size and ectothermy, are particularly sensitive to changes in temperature (e.g.,

Strathdee et al. 1995), vegetation (e.g., Bowden and Bowden 2010b) and precipitation changes (e.g., Hodkinson et al. 1998). As arthropods respond rapidly to environmental changes (e.g., Quinlan et al. 2005), they can be used as ecological bioindicators of climate change (Danks 1992, Churchill 1997,

McGeoch 1998). Temporal comparisons of arthropod diversity showed that the effect of environmental change on species may be idiosyncratic. For example, over a decade, the increase of sexual dimorphism in an Arctic spider in Greenland was due to an increase of temperature (Hoye et al. 2009) while no obvious change was observed in body size or community richness and composition in parasitoid wasps on Ellesmere Island over five decades (Timms et al. 2013). Hence, more comparative studies using multiple arthropod taxa are necessary to understand the effect of environmental change on biodiversity in the Arctic. To accomplish this, more baseline data on arthropod species richness, abundance and distribution are required.

Spiders as model taxon

Ground-dwelling spiders (Araneae) are an ideal arthropod taxon with which to gain insights about Arctic biodiversity patterns. Arctic spiders are abundant

(Pickavance 2009, Bowden and Buddle 2010a), easy to collect (Bowden and

Buddle 2010a), and have micro-habitat preferences (Leech 1966), which allow effective comparisons of biodiversity within and between habitats (Leech 1966,

Koponen 1992, Bowden and Buddle 2010a). Arctic spiders are also diverse

(Danks 1981, Bowden and Buddle 2010b, Platnick 2013) and ecologically important prey items at northern latitudes (Elmhagen et al. 2000, Meltofte et al.

2007, Tulp and Schekkerman 2008, Bolduc et al. 2013).

Spiders are also a good model taxon to study factors that might govern diversity.

At large spatial scale, spider species richness has been related with water limitation (Kumschick et al. 2009), latitude (Finch et al. 2008), vegetation (Beals

2006, Bowden and Buddle 2010b), temperature (Jimenez-Valverde and Lobo

2007) and habitat complexity (Rystra et al. 1999, Halaj et al. 2000, Larrivée et al.

2005, Jimenez-Valverde and Lobo 2007). At small spatial scales, spider diversity is correlated with abiotic factors such as moisture (DeVito et al. 2004, Entling et al. 2007), and biotic factors including dispersal (Jimènez-Valverde et al. 2010), and competition (Birkhofer et al. 2006), even though relative importance of intra- and inter-specific competition of spiders is controversial (Marshall and Rypstra

1999, Persons et al. 2001).

Arctic spider communities are dominated numerically by wolf-spiders

(Lycosidae) whereas sheetweb spiders (Linyphiidae) have high species richness at more northern latitudes (Koponen 1991, Koponen 1992, Høye and Forchhammer

2008, Bowden and Buddle 2010a, Rich et al. 2013). The Linyphiidae show a surprisingly high representation in Arctic environment with 18% of total linyphiid species in the world found north of 60° (Marusik and Koponen 2002).

Thesis objectives

The objective of this thesis is to document multi-scale patterns of Arctic spiders, focusing on their abundance, species richness, composition and patterns of dominant spider families. More specifically, the following topic will be addressed: 1) How does species richness, abundance and composition of ground- dwelling spiders vary at local, regional and continental scale, in three major ecoclimatic regions: the North-Boreal, Subarctic and Arctic; 2) The spatial patterns of the dominant ground-dwelling spider families; and 3) The relationship between environmental data, specifically climate and vegetation, and spider assemblages.

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CHAPTER 2: MULTI-SCALE PATTERNS OF GROUND-DWELLING

SPIDER (ARANEAE) DIVERSITY IN NORTHERN CANADA

Manuscript formatted for submission to the journal Ecography

Authors:

Sarah Loboda (email: [email protected])

Natural Resource Sciences, Macdonald campus, McGill University

21 111 Lakeshore Road, Ste-Anne-de-Bellevue, QC

Canada, H9X 3V9

Christopher M. Buddle (email:[email protected])

Natural Resource Sciences, Macdonald campus, McGill University

21 111 Lakeshore Road, Ste-Anne-de-Bellevue, QC

Canada, H9X 3V9

Abstract: Elucidating general patterns of diversity at multiple spatial scales requires fine resolution data collected over a large geographic extent. We examined how patterns of ground-dwelling spiders (Araneae) diversity (i.e. richness, evenness, composition and structure) vary at local, regional and continental spatial scales in northern Canada, using a hierarchical sampling design that covered 30 degrees of latitude and 80 degrees of longitude. Over 23, 000 spiders, representing 306 species in 14 families, were collected in 12 sites located in Arctic, Subarctic and North-Boreal regions. Spider diversity was structured at continental scale across ecoclimatic regions but not with latitude. At regional scale, western sites differed from eastern sites indicating the importance of longitudinal diversity gradients in northern North-America, perhaps due to post- glacial dispersal patterns. Vegetation and climate also influence Arctic diversity patterns, and thus predicted climate change may alter the distribution of spiders, an important ecological group in the Arctic food webs. Due to the large extent and fine resolution, this research contributes to a better understanding of hierarchical patterns of diversity and will help to define conservation strategies for the Arctic biodiversity.

Keywords: biodiversity, Arctic, spatial scale, additive partitioning, spiders

Nomenclature: Platnick, 2013

Introduction

Investigating spatial distribution of species around the planet is essential to develop and test theories in ecology (e.g., Connor and McCoy 1979), develop conservation strategies (e.g. Gering et al. 2003) or model how biodiversity responds to disturbances (e.g. Guisan and Thuiller 2005). Understanding spatial patterns of diversity is thus central in ecology (Ricklefs 2004) but challenging because patterns and their underlying processes vary with spatial scale, defined in ecology by the extent (i.e. area of investigation), and the grain (i.e. the unit of observation or resolution) (Wiens 1989, Shmida and Wilson 1985, Levin 1992,

Willig et al. 2003, Rahbek 2005).

Diversity pattern observed at one scale is the result of complex interactions among processes operating at multiple spatial scales (Rahbek 2005). Although in practice, spatial extent and grain are often dependent on each other (Ricklefs and

Jenkins 2011, Beck et al. 2012), the combination of fine resolution data over a large geographic extent provides a deeper understanding about how small and large-scale processes respectively, relate to multi-scale patterns of richness, abundance and composition (e.g., Andrew and Hughes 2005, Sinclair and Hughes

2008, Whitehouse et al. 2009, Kozlov et al. 2013).

Despite the fact that arthropods represent half of the global diversity described

(Chapman 2009), macroecological research is generally biased towards plants and vertebrates (Ricklefs and Jenkins 2011, Beck et al. 2012). Moreover, studies on arthropod diversity patterns commonly consider local and regional diversity (e.g.,

Fournier and Loreau 2001, Gotelli and Ellison 2002, Summerville et al. 2003,

Tylianakis et al. 2005, Lindo and Manchester 2008, Ribeiro et al. 2008, Cabra-

Garcìa et al. 2010, Larrivée and Buddle 2010, Lévesque-Beaudin and Wheeler

2011, Paknia and Pfeiffer 2011), while disregarding patterns at broader spatial scale, over large environmental gradient (e.g., the climatic gradient).

The Arctic, defined as the northern treeless expanse (Nuttall 2005), is an ideal biome with which to study large-scale diversity patterns of arthropods because of the large latitudinal and longitudinal gradients of the relatively simple habitat

(Hodkinson and Coulson 2004, Gauthier et al. 2011, Wisz et al. 2013). The Arctic is also one of the most threatened ecosystems on Earth (IPCC 2007), it is thus critical to understand diversity patterns and determinants of arthropods, which can be used as ecological indicators of environmental change (Danks 1992).

In our research, ground-dwelling spiders (Araneae) were selected as a model taxon because they are abundant, easy to collect, and have micro-habitat preferences (Leech 1966, Pickavance 2009, Bowden and Buddle 2010a), which allow effective comparisons of biodiversity within and between habitats (Leech

1966, Koponen 1992, Bowden and Buddle 2010a). Arctic spiders are also diverse

(Danks 1981, Bowden and Buddle 2010b, Platnick 2013), ecologically important prey items at northern latitudes (Elmhagen et al. 2000, Meltofte et al. 2007, Tulp and Schekkerman 2008, Bolduc et al. 2013) and taxonomically well known (e.g.,

Dondale et al. 1997). Arctic spider assemblages are dominated numerically by wolf-spiders (Lycosidae), yet another family, sheetweb spiders (Linyphiidae),

26 exhibit high species richness at northern latitudes (Koponen 1991, Høye and

Forchhammer 2008, Bowden and Buddle 2010a, Rich et al. 2013).

The objective of this research is to document patterns of Arctic ground-dwelling spider assemblages from local to continental scale. We addressed the following questions: 1) How do ground-dwelling spider species richness, abundance, composition and structure vary at local, regional and continental scale, in three major ecoclimatic regions: the North-Boreal, Subarctic and Arctic? 2) Are patterns identical among the most dominant families? and 3) Does climate or vegetation best explain variation of spider assemblages?

Methods

Sampling design

This study is part of the Northern Biodiversity Program, a collaborative research initiative that aims to document spatial and temporal arthropod diversity patterns in northern Canada. The hierarchical nested sampling design consisted of four spatial scales of diversity: (1) trap, (2) replicate, (3) site and (4) ecoclimatic region scale. This study was carried out in northern Canada at 12 sites from three broad ecoclimatic regions: North-Boreal, Subarctic and Arctic. Ecoclimatic regions are characterized by unique climate, soil type and vegetation composition (Strong and

Zoltai 1989). The ecoclimatic region is the largest spatial scale of the hierarchical design used in this study (Appendix 1). In each ecoclimatic regions, four sites were selected for sampling (Appendix 1).

At each site, we sampled ground-dwelling arthropods in mesic and wet natural open habitat (i.e., no canopy cover by trees). Mesic open sites were characterized by elevated topography and well-drained soils. The vegetation on mesic sites was a discontinuous cover of dwarf shrubs (e.g. willows (Salix spp.) and Labrador tea

(Rhododendrum spp.) and perennial forbs like dryas, saxifrages (Saxifraga spp.) or wood rush (Luzula spp.) with a layer of fructose lichen (Cladonia and Cladina spp.). Open wet habitats were water-saturated, with continuous cover of moss, sphagnum, saxifrages and sedges like cotton grass (Eriophorum spp.).

Each habitat was sampled in three independent locations (replicates) separated by at least 500 m. The design of each replicate consisted of three rows of six traps; three pitfall traps and three pan traps were placed randomly in each row, 15 m apart, for a total of eighteen traps per replicate. Pitfall traps are used because they collect ground-dwelling arthropods in a reliable and repeatable manner even at large spatial scale (Gotelli and Ellison 2002, Bowden and Buddle 2010b).

Although yellow pan traps are usually used to collect flying insects, when sunk into the ground with the rim at the surface level, pan traps are as efficient to catch spiders as pitfall traps (Buddle and Hammond 2003).

The pitfall trap was a plastic circular container 10 cm in diameter, with a permanent outer cup (15 cm depth) and an inner sampling cup (7 cm depth), covered by a square plastic corrugate (approx. 12 x 12 cm), and positioned 3 cm above each trap in order to provide protection from rain (see Ernst and Buddle

2012). Each pan trap was bright yellow, 20 cm wide and 3cm deep (see Timms et al. 2013). Propylene glycol diluted with water (2:1) was used as preservative with

28 a small amount of surfactant to break surface tension. Traps were emptied approximately every four days. The propylene solution was drained and arthropods were kept in 95% ethanol, returned to the laboratory, and sorted. A total of 108 traps per site and 1296 traps for the complete design were used, spanning 30 degrees of latitude and 80 degrees of longitude across northern

Canada. Each site was sampled for two weeks in 2010 or in 2011 (Appendix 2).

All mature spiders were identified to species. Nomenclature followed the world spider catalog (Platnick 2013). Voucher specimens are deposited at the Lyman

Entomological Museum (Sainte-Anne-De-Bellevue, Québec).

Environmental Variables

Vegetation

In each replicate, maximum vegetation height (maxveght) and depth of active layer (sd.pd and mean.pd) were measured using a graduated metal rod in five quadrats of 1x1m area around randomly selected traps. Variables related to vegetation and soil type, known to influence local diversity of Arctic spiders, were measured (Bowden and Buddle 2010a, Rich et al. 2013). Vegetation composition was visually assessed and, using the Braun-Blanket scale (Elzinga

2001), a cover class was assigned to each category of vegetation: mosses

(moscov), lichens (lichcov), graminoids (gramcov), forbs (forbcov) and shrubs

(shrcov).

Climate

Four climatic variables were extracted from the Canadian national climate data and information archive (http://climate.weatheroffice.gc.ca) for the weather station closest to each site. The average distance between the site and the weather station is less than 15 km, with the exception of the northern site, Hazen Lake, which is about 300 km away from the weather station chosen. The variables selected were: annual mean temperature (AMT), maximum temperature of the warmest month (maxT), minimum temperature of the coldest month (mint), annual precipitation (AP), degree days above zero (DJA0) and degree days below zero (DJB0). Those variables were chosen because they are known to affect

Arctic spider diversity (Bowden and Buddle 2010b). Latitude (lat) and longitude

(long) were used as surrogates for large-scale environmental gradients.

Statistical analyses

Immature spiders were excluded from the analyses because they cannot accurately be identified to species. Mature specimens were pooled by trap for the two week sampling period for each site.

Spatial variation in spider assemblage structure

To calculate completeness of the inventories, the absolute species richness in each ecoclimatic region was estimated using the nonparametric estimators Chao1 and

Jackknife 1 (Magurran 2004). Completeness values are derived from the ratio between observed and Chao1 estimated richness (Sѳrensen et al. 2002).

Individual based rarefaction curves were used to compare the observed and estimated richness of each ecoclimatic region (Gotelli and Ellison 2002).

Rarefaction allows proper comparison of diversity at similar sample size (Buddle et al. 2005).

Comparison of composition

Assemblage composition was analysed using ordination methods. Prior to ordination analysis, singletons were removed in order to better detect composition similarities (Legendre and Legendre 1998). Species abundance was standardized as the number of individual caught per day and then transformed in Bray-Curtis distance dissimilarities. A non-metric multidimensional scaling ordination

(NMDS) with 2 dimensions based on Bray-Curtis distance was performed to determine species composition similarities at the region and the site spatial scale

(Legendre and Legendre 1998). NMDS was conducted using the metaMDS

(Oksanen et al. 2013) function in R, which uses several random starting configurations to select a solution with low stress.

Multi-scale patterns of α and β diversities

We choose to use the additive partitioning mathematical framework to test the relative contributions of components of diversity at different scales to the overall diversity. The Partition 3.0 software (Veech and Crist 2009) was used to additively decompose the total diversity of spiders into local diversity (the average diversity within (α1) and among trap (β1) and the diversity among replicate (β2)), regional diversity (average diversity among site (β3)) and

31 continental diversity (average diversity among ecoclimatic region (β4)).

Partitioning diversity can be summarized as:

γ (total) = α1 (trap) + β1 (trap) + β2 (replicate) + β3 (site) + β4 (ecoclimatic region)

Additive partitioning divides species richness and the Shannon diversity index into several components. For each level, α and β diversities (richness and Shannon index) observed were compared with predicted α and β diversities obtained with random distribution generated with 10, 000 randomizations (Crist et al. 2003).

The individual-based randomization model, with weighting of samples, generates random distribution of spider species among samples at each spatial scale, creating null distributions for α and β richness estimates of each spatial scale.

Statistical significance of the difference between the estimated and observed richness, given as P-value, is determined by the proportion of null values that are greater (or less) than the observed estimate. For example, if 50 out of 10, 000 null values are greater than or equal to the observed estimate, the probability of obtaining by chance an estimate as great or greater than the observed value is

0.005. In this case, the observed richness is significantly higher than the estimated one. We evaluated differences of diversity partitioning between regions by doing the analyses separately in each region. Finally, to estimate the relative influence of the two most abundant families of Arctic spiders, additive partitioning analyses were then performed on Linyphiidae and Lycosidae diversity.

Vegetation and climate

Variance partitioning was used to determine the relative influence of multiple complementary sets of environmental factors on spider composition (Borcard et al. 1992; Peres-Neto et al. 2006). Three explanatory matrices were tested: matrix with vegetation, climate and spatial variables. The effect of one matrix independent of the influence of others (marginal effect) and the conditional variation explained by the combined effect of several matrices are calculated.

Because the high environmental heterogeneity between sites is reflected in the species matrix by a high proportion of zeros, the species matrix was then transformed to the Hellinger distance, the most suitable transformation in this case

(Legendre and Gallagher 2001). A direct gradient analysis -such as a redundancy analysis- was performed on all data and then separately for each region to determine which variables best explain variation of spider composition. The permutation forward selection procedure was used to reduce the number of explanatory variables for the spider species matrix. We retained significant variables with a cumulative R2 adjusted below the R2 adjusted obtained with all variables. Monte Carlo tests with 10 000 permutations were used to determine the significance of axes of the RDA.

Statistical analyses, other than additive partitioning, were done using the R software (R Development Core Team 2009).

Results

A total of 28, 427 spider specimens representing 14 families was collected (Table

1); 23, 015 were mature specimens and were identified to species. Total species

33 richness (γ diversity) was 306 species, with 131 spider species new Provincial or

Territorial records (Appendix 3). Rarefaction curves revealed that collection time and effort was probably sufficient in Arctic and Subarctic regions (i.e., the curves reach an asymptote) while an spider species in North-Boreal region were likely undersampled (Figure 1). The completeness of the collection varied between 69% and 100% within site, with lower values in the North-Boreal region (Table 1).

Multi-scale patterns of spider diversity

The Arctic spider assemblage was less species-rich than the Subarctic and North-

Boreal assemblages. A total of 200 species was found in Canada’s east compared to 176 in the west. Richness is higher is the west in the North-Boreal region and higher in the east in the Subarctic region (Figure 2). At similar latitudes, species richness was generally higher in western than eastern Canada. For example,

Norman Wells (NW) in west Canada had a species richness of 132 at 65° latitude and Iqaluit (IQ) at 62° latitude in Canada’s east had a richness of only 22 species

(Figure 2).

The NMDS ordination resulted in low stress values, indicating that the main structure of the data was depicted effectively in 2-dimentional ordination space

(Figure 3). First, ecoclimatic regions showed clear differences of species composition. Variation of composition between sites was higher in the Arctic region (Figure 3a). Variation of composition within region was likely due to differences between eastern and western sites (Figure 3b) with the exception of

Churchill, a Subarctic eastern site which composition was similar to Kugluktuk, a

Subarctic western site (circles and triangles are overlapping in the upper right corner, Figure 3b). Assemblage composition in Kugluktuk was therefore more similar to Churchill, almost 1500 km away, than to Tombstone Mountains, 1000 km away. NMDS with only western sites (Figure 3c) and only eastern sites

(Figure 3d) showed that variation between sites in each ecoclimatic region is lower in west Canada.

Diversity partitioning results showed that spider diversity was structured (i.e., non-random) at continental, regional and local scale (Figure 4). The observed values of β4 and β3 were significantly higher than expected with a random distribution (Figure 4). The ecoclimatic region is the most important spatial scale in structuring diversity; β4 contributes to 50% of the total diversity of γ diversity meaning that half of the species are restricted to one ecoclimatic region. The regional scale was the second most important spatial scale with β3 contributing to

30% of the total richness. Components at local scale (α1, β1 and β2) were significantly lower than expected by chance. Shannon’s diversity index was significantly lower than expected by random distribution at local scale (α1 and β1) but still contributed to half of the total diversity index (Figure 4).

Additive partitioning of diversity within each ecoclimatic region did not show differences between regions. β3 contributed to almost half of the diversity within each region (Figure 5). Shannon’s diversity index was significantly lower at local scale (α1 and β1) and higher at regional scale (β3) than expected by chance (Figure

5). However, Shannon’s index at local scale represented 80% of the total diversity

35 in the North-Boreal region, 75% in the Subarctic region and 70% in the Arctic region.

Multi-scale patterns of the dominant families

With 169 species and 55% of the total richness, the Linyphiidae family was the most diverse family of spiders collected (Figure 2). The most abundant family was the Lycosidae, with 15, 778 individuals and 32 species, representing 67% of the total abundance (Figure 2). The proportion of the total diversity represented by

Linyphiidae species increased from North-Boreal sites to Arctic sites (Figure 2), while the proportion of the total abundance represented by Lycosidae individuals decreased from North-Boreal sites to Arctic sites in eastern Canada (Figure 2) .

Partitioning of Linyphiidae and Lycosidae richnesses were similar to the partitioning with all spider species with continental (β4) and regional scale (β3) as the most important spatial scales structuring diversity. At local scale (α1 and β1),

Shannon’s diversity index was significantly lower than expected by random distribution for both families but still represented 50% of the total diversity index for Linyphiidae and less than 35% for Lycosidae. At the continental scale (β4),

Shannon’s index for Linyphiidae represented only 30 % of the total diversity index compared to 50% for Lycosidae.

Climate and vegetation

The three explanatory matrices (vegetation, climate and spatial variables) explained 59.6% of the variation of spider composition in the response matrix.

Variance partitioning revealed that vegetation was the most important determinant

36 of ground-dwelling spider assemblages in northern Canada, explaining 38.1% of the diversity structure while climate explained 35.2%. Latitude was not an important driver and spatial variables explained only 17.1% of the diversity variation. Variation partitioning within each region showed similar results in different proportions. Effect of vegetation explained respectively 61% and 46% in

Arctic and North-Boreal ecoclimatic region.

The constrained ordination was made using all variables because no variable was discarded by the permutation selection (Figure 6a). The first two canonical axes explained together 26.7% of the total variance of spider composition, the first axis alone explained 16%.

Within each region, significant variables selected to find parsimonious models were different (Figure 6 b,c,d). Variables selected in each region were a mix of several local variables and one or two climatic variables with the exception of the

Arctic region where longitude was also significant. For the Arctic and the North-

Boreal ecoclimatic regions, maximum temperature of the warmest month seems to influence differences between east and west sites (maxT in Figure 6b and d). The first two canonical axes explained 62% in Arctic (Figure 6b), 52% in Subarctic

(Figure 6c) and 50% in North-Boreal region (Figure 6d).

Discussion

We used Arctic spiders as model taxa to describe multi-scale patterns of diversity

(i.e. species richness, composition, abundance and structure) across three northern ecoclimatic regions, and test the influence of climate and vegetation on patterns.

Species richness, composition and abundance of the ground-dwelling spider assemblages were structured at the continental, regional and local spatial scale.

Dominant families tend to have small differences of patterns compared to the all spider assemblages. Vegetation composition and climate explain the majority of the variation of spider diversity overall and the percentage of variation explained increased with latitude.

To our knowledge, our collection of over 300 species of spiders across 80 degrees of longitude and 30 degrees of latitude is unparalleled in the literature in terms of spatial extent, with fine-resolution data collection methods. We have contributed significantly to knowledge about northern Arachnids, and provided an important benchmark for future studies. Given that 131 species were new provincial and territorial records (Appendix 3), it is clear that much work is still required to begin to unravel the patterns of arthropod biodiversity in the North.

Diversity patterns at the continental scale

Species richness and evenness of spiders were mainly generated by the turnover of species between the three ecoclimatic regions and it was constant across the dominant families. Species richness of ground-dwelling spiders decreased from the North-Boreal to the Arctic region. High beta diversity richness values at broad spatial levels are consistent with other studies on forest beetles (Gering et al.

2003), oribatid mites (Lindo and Winchester 2008) and forest spiders (Larrivée and Buddle 2010). This result suggests that large-scale processes influence spider richness in northern Canada.

Spider composition was structured at continental scale across ecoclimatic regions, categorized by vegetation, climate and soil type (Strong and Zoltai 1989). Unlike past work on spiders from Europe and Australia (Finch et al. 2008, Kumschick et al. 2009, Whitehouse et al. 2009), we found that latitude was not a strong predictor of spider diversity. This may be because of the longitudinal extent of our study area or perhaps because of the types of habitats we sampled. Gotelli and

Ellison (2002), for example, found that correlation between ant species richness and latitude was less strong in open habitat (i.e. without canopy) than in forests.

Similarly, latitude was not correlated with species richness of desert grasshoppers

(Otte 1976) and various herbivorous insects in different open-canopy habitats in

Australia (Andrew and Hughes 2005, Sinclair and Hughes 2008). Taken together, this body of knowledge suggests when studying arthropods in open habitats, the factors influencing diversity patterns may be similar among sites regardless of latitude.

Diversity patterns at the regional scale

Within each ecoclimatic region, assemblage compositions in eastern and western

Canada were different. This pattern has been observed by others for birds, plants, butterflies and other insect groups in Canada (Chernov 1995, Callaghan et al.

2004, Danks 1993, Qian 1998). It is argued that post glacial migration from different refugia in northern Canada created differences in species regional pools.

Western species probably originated from Beringian refugium, the Haida Gwaii refugium or other cryptic western refugia whereas species in eastern Canada may have orginated from southern refugia after the Wisconsin glaciation (e.g., Janzen

39 et al. 2002, Adams et al. 2003, Waltari et al. 2004). The presence of natural biogeographic barriers like the Mackenzie River (e.g., Waltari et al. 2004) or the sea of Hudson Bay (Danks 1993) might also explain why, for example, the

Kugluktuk spider assemblage is more similar to the Churchill assemblage than to the Tombstone one within the Subarctic region.

In the Arctic region, spider richness on Ellesmere Island, part of the Queen

Elizabeth Islands, was lower than richness on islands in the low- Arctic, which is consistent with patterns of insect richness as reported by Danks (1993).

Composition was also more variable between sites in the Arctic than in the North-

Boreal region. According to Chernov (1995), sharp thermal gradients in the tundra biome reflect on biodiversity with great differences of composition within the same region. The unique geography of the Canadian Arctic archipelago combined with harsh climatic conditions affects biodiversity patterns of plants (Chernov

1995) and probably explains the high variation of composition between sites that were on different islands of the archipelago. However, in a harsh environment, community composition is expected to be more homogeneous (Chase 2007). The study of diversity patterns within and between islands of the archipelago is necessary to complete our understanding of the respective effect of insularity, climate and geography on biodiversity patterns in the Canadian Arctic.

Diversity patterns at the local scale

Species richness and evenness at local scale were lower than expected by chance indicating a reduce richness and abundance of spider species at local scale.

However, the high values of local evenness suggest that local factors influence more abundance and dominance of species than the large-scale determinants

(Summerville et al. 2003), especially in the North-Boreal region. This suggests that local factors in this region, such as shrub cover and vegetation height

(variables selected for the North-Boreal RDA), might be more influential on spider abundances there than in the Arctic region.

Assemblage composition was more similar between different habitats of the same site than between similar habitats of different regions like observed in other systems (e.g., Gering et al. 2003). The decrease in similarity with geographic distance is called ‘distance decay’ (Soininen et al. 2007). This suggests dispersal is an important factor structuring diversity, especially at local scale (e.g., Moritz

2013). A low local turnover can also be explained by the presence of other biotic interactions (Wisz et al. 2013). For example, burrowing spiders in sand dunes showed reduced species density and diversity at local scale due to competition and this effect was scale dependant (Birkhofer et al. 2006). Given that the parasitism rate of Lycosidae’ egg sacs was surprisingly high in Subarctic populations (Bowden and Buddle 2012), biotic interactions might play an important role in structuring Arctic diversity at local scales, but this area of study requires much attention.

Patterns of the dominant families

The relative number of Linyphiidae species increased toward the Arctic. This trend has previously been found in Europe (Koponen 1991) but our results are the

41 first evidence of such pattern in North-America, and at this large spatial scale.

Linyphiidae are relatively well known taxonomically in the Arctic with 18% of total linyphiid described species in the world found north of 60° (Marusik and

Koponen 2002). However, their ecological roles at northern latitudes are not resolute yet (but see Hodkinson et al. 2001).

Although continental scale was not the most important scale structuring evenness of the entire assemblage, it was the most important scale structuring evenness of

Lycosidae, which represented more than 60% of the total assemblage abundance.

However, the relative abundance of Lycosidae spiders decreased from low to high latitudes in eastern Canada, suggesting their abundance is related to large-scale processes such as climate. Global warming is expected to affect the abundance and range of dominant species (Callaghan et al. 2004). Determining functional roles of Lycosidae species, already affected by climate change (Hѳye et al. 2009), is essential as they can influence Arctic ecosystem stability (König et al 2011).

Inconsistency of richness and abundance patterns can indicate that different processes regulate different attributes of diversity. For example, abundance and richness of butterflies in North America had different patterns and were structured, respectively, by productivity and topography (Kocher and Williams

2000). Given the abundance of Lycosidae in our study, more work on understanding the relationship between their abundance and their richness across their range would be valuable.

Vegetation and climate

Vegetation composition, but not climate variables, best explained variation in the diversity of spiders at a broad scale, as has been observed in other northern systems (e.g., Bowden and Buddle 2010b, Rich et al. 2013), and in other more temperate habitats at regional or local scales (e.g., Carvalho et al. 2010, Jimenez

Valverde and Lobo 2007, Jimenez Valverde et al. 2010). However, because terrestrial arthropods have micro-habitat preferences (Leech 1966), the strength of correlation between ground-dwelling spider diversity and climate variables would have been clearer if micro-climate data were used (Suggitt et al. 2011). Solar radiation is an important factor influencing diversity of Arctic ground-dwelling arthropods (Hѳye and Forchhammer 2008) and probably more in habitats with low shrub cover (Rich et al. 2013). This may explain why Bolduc et al. (2013) reported a high abundance of Arctic spiders throughout the summer season in open habitat with signs of spider activity as early as the beginning of the snow melt. We found that maximum temperature of the warmest month (maxT) was an important variable influencing regional diversity patterns of Arctic and North-

Boreal spiders. Similarly, at northern latitudes, species richness of birds and ground-beetles were strongly correlated with temperature of the warmest month or daily temperatures (Chernov 1995, Ernst and Buddle 2012). Experimental studies with manipulated solar radiation and modified vegetation composition would be a good way to quantify the respective importance of those factors on

Arctic arthropod biodiversity.

Conclusion

Spider richness, abundance and composition were structured at the continental, regional and local spatial scale. While biotic interactions may influence structure of diversity at small spatial scale, vegetation composition and climate influenced spatial patterns of spiders at multiple spatial scales in addition to the historical influence of post-glacial dispersal. However, the effect of those factors needs to be quantified at multiple spatial scales and for multiple taxa in order to understand and predict geographic variation of Arctic biodiversity. The Arctic is under immense stress as it has warmed two times more than the global average (IPCC

2007). To monitor the effect of expected changes in temperature and vegetation cover (Callaghan et al. 2004), spiders are promising candidates to be ecological bioindicators in the Arctic.

Acknowledgements – We thank Doug Currie and Terry Wheeler, principal investigators of the Northern Biodiversity Program. Funding was provided by a

Natural Sciences and Engineering Research Council of Canada Strategic Project

Grant, with logistical support provided by the Polar Continental Shelf Program.

The NBP team collected specimens. We thank also S. Sylverman for assistance with specimen processing. We thank K. Sim, J. Bowden and D. Buckle who helped with identification of spiders. We thank Parks Canada and provincial

Governments who provide permits to collect.

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Table 1: Observed (SRobs) and estimated total species richness (Chao1 and Jack1 ± confidence interval) of ground-dwelling spiders (Araneae) per site of the three ecoclimatic regions. Completeness=SRobs/Jack1*100. Ecoclimatic regions: A=Arctic, S=Subarctic, NB=North-Boreal. Sites: HA=Hazen Lake, NU; IQ=Iqaluit, NU; CB=Cambridge Bay, NU; BA=Banks Island, NU; CH=Churchill, MB; SC=Schefferville, QC; TO=Tombstone mountains, YT; KU=Kugluktuk, NU; GB=Goose Bay, LB; MO=Moosonee, ON; YE=Yellowknife, NT and NW=Norman Wells, NT

Regions Sites N SRobs Singleton Jack1 Chao1 Completeness HA 1088 8 0 8 ± 0 8 ± 0 100 IQ 384 22 5 31 ± 3 34 ± 10 74 A CB 3509 21 5 27 ± 2 28 ± 8 82 BA 1383 16 3 20 ± 2 19 ± 3 85 CH 2478 74 25 105 ± 6 127 ± 27 71 SC 2123 109 29 146 ± 7 152 ± 19 74 S TO 1354 52 20 75 ± 6 119 ± 44 70 KU 2326 35 6 41 ± 3 41 ± 7 85 GB 1557 81 34 117 ± 7 174 ± 48 69 MO 2228 99 38 139 ± 9 191 ± 44 71 NB YE 2311 104 23 132 ± 6 129 ± 12 80 NW 2274 132 39 173 ± 7 181 ± 21 76 Total 23015 306 68

Figure 1. Individual-based rarefaction curves of the species richness of ground- dwelling spiders in three ecoclimatic regions (Arctic, Subarctic and North- Boreal), in northern Canada.

306 169 32 100%

80% *** *** ***

diversity 60%

40% *** *** ***

Species richnessSpecies * Contribution to γ Contributionto 20% * * * * * * 0% * * 100%

*** *** *** 80% *** *** 60% γ diversity γ *** *** *** β4 (between regions) *** 40% β (between sites)

* * 3 Shannondiversity * β2 (between replicates) Contributionto 20% * * β1 (between traps) * 0% α1 (within trap) Entire Linyphiidae Lycosidae community

37 170 231 100%

80% *** *** ***

60%

40% * *

Species richnessSpecies *

Contribution to γ diversity Contribution γ to 20% * * * * 0% * *

100% *** *** *** 80% *** *** 60% *** * * 40%

* β3 (between sites) Shannondiversity * β2 (between replicates) Contribution to γ diversity γ Contributionto 20% * * β1 (between traps)

0% α1 (within trap) Arctic Subarctic N-Boreal

Figure 5.Percentage of spider species richness (306 species) and Shannon diversity explained by α and β components within each ecoclimatic region: Arctic (γ=37 species), Subarctic (γ=170 species) and North-Boreal (γ=231 species).

Appendix 1. Location of the Northern Biodiversity Program study sites in northern Canada and relationship between hierarchical nested design and diversity partitioning components

Map of ecoclimatic regions Sampling design Partitioning diversity components

Ecoclimatic region α4 β4 (between regions) Site α3 β3 (between sites) Replicate α2 β2 (between replicates) = Trap α β (between traps) 1 + 1

15m

15m 2010 -east Yellow pan trap 2011 - west Pitfall trap

site Hab. rep. dates days latitude longitude mean.pd sd.pd maxveght gramcov moscov lichcov forbcov shrubcov AMT maxT minT AP DJA0 DJB0

BA M 1 7-19 july 2011 12 73.22181 -119.56059 41.66 6.68 9.16 3.5 0.83 0.33 1.5 0 -13.3 24.9 -48.9 149.4 456.2 5322.9

BA M 2 7-19 july 2011 12 73.22656 -119.57728 44.44 6.96 9.02 3.25 0.8 0.38 1.41 0 -13.3 24.9 -48.9 149.4 456.2 5322.9

BA M 3 7-19 july 2011 12 73.22855 -119.58662 48.18 7.67 8.86 2.95 0.6 0.45 1.48 0 -13.3 24.9 -48.9 149.4 456.2 5322.9

BA W 1 7-19 july 2011 12 73.22412 -119.55255 48.38 6.21 9.51 3.45 0.7 0.52 1.23 0 -13.3 24.9 -48.9 149.4 456.2 5322.9

BA W 2 7-19 july 2011 12 73.23284 -119.54719 45.27 6.79 10.26 3.35 0.82 0.28 1.27 0 -13.3 24.9 -48.9 149.4 456.2 5322.9

BA W 3 7-19 july 2011 12 73.23193 -119.58330 45.49 6.55 10.3 3.58 0.79 0.33 1.31 0 -13.3 24.9 -48.9 149.4 456.2 5322.9

CB M 1 7-19 july 2011 12 69.11993 -105.42065 31.46 6.36 15.33 3 1.33 0.5 3 0.66 -14.4 19.9 -44.6 138.8 599.6 5836.8

CB M 2 7-19 july 2011 12 69.12070 -105.42582 30.04 5.79 15.55 3 1.05 0.58 3.16 0.61 -14.4 19.9 -44.6 138.8 599.6 5836.8

CB M 3 7-19 july 2011 12 69.12157 -105.43124 29.88 5.98 15.81 3.16 1.06 0.51 3.02 0.54 -14.4 19.9 -44.6 138.8 599.6 5836.8

CB W 1 7-19 july 2011 12 69.12177 -105.41688 30.66 5.09 16.78 3.36 1.07 0.43 2.86 0.63 -14.4 19.9 -44.6 138.8 599.6 5836.8

CB W 2 7-19 july 2011 12 69.12225 -105.42191 34.01 5.14 17.91 3.58 1.25 0.33 2.67 0.74 -14.4 19.9 -44.6 138.8 599.6 5836.8

CB W 3 7-19 july 2011 12 69.12366 -105.42531 34.21 5.26 17.06 3.51 1.29 0.39 2.95 0.86 -14.4 19.9 -44.6 138.8 599.6 5836.8

HA M 1 19-28 july 2010 9 81.83216 -71.45594 23.24 3.39 18.4 4.2 3.4 0 1.4 1.2 -19.7 18.5 -45.4 75.5 359.2 7516.2

64 site Hab. rep. dates days latitude longitude mean.pd sd.pd maxveght gramcov moscov lichcov forbcov shrubcov AMT maxT minT AP DJA0 DJB0

HA M 2 19-28 july 2010 9 81.82941 -71.48788 22.88 3.36 17.08 4.04 3.08 0 1.68 1.24 -19.7 18.5 -45.4 75.5 359.2 7516.2

HA M 3 19-28 july 2010 9 81.83171 -71.45110 27.33 3.37 18.12 4.31 4.12 0 1.27 1.11 -19.7 18.5 -45.4 75.5 359.2 7516.2

HA W 1 19-28 july 2010 9 81.82975 -71.32244 27.33 3.37 18.12 4.31 4.12 0 1.27 1.11 -19.7 18.5 -45.4 75.5 359.2 7516.2

HA W 2 19-28 july 2010 9 81.82911 -71.49242 23.71 3.13 18.34 4.37 3.94 0 1.12 1.13 -19.7 18.5 -45.4 75.5 359.2 7516.2

HA W 3 19-28 july 2010 9 81.83179 -71.44115 24.9 3.32 18.01 4.24 3.73 0 1.34 1.15 -19.7 18.5 -45.4 75.5 359.2 7516.2

IQ M 1 17-29 july 2010 12 63.79113 -68.57375 13.32 8.38 20.6 1.6 4.4 4.2 2.6 0 -9.8 219 -34.3 412 653.8 4196.5

IQ M 2 17-29 july 2010 12 63.77830 -68.54961 10.96 4.7 18.4 1.2 2.8 4 3 0 -9.8 219 -34.3 412 653.8 4196.5

IQ M 3 17-29 july 2010 12 63.75117 -68.45898 11 6.21 21.6 2 2.8 2.6 3.8 0 -9.8 219 -34.3 412 653.8 4196.5

IQ W 1 17-29 july 2010 12 63.76144 -68.57352 25.76 13.81 24.6 5 1.6 0 1.4 0.8 -9.8 219 -34.3 412 653.8 4196.5

IQ W 2 17-29 july 2010 12 63.75672 -68.56770 29.48 10.86 24.8 4 4.4 1.8 2.2 0 -9.8 219 -34.3 412 653.8 4196.5

IQ W 3 17-29 july 2010 12 63.75122 -68.45927 40.72 20.11 24.2 4.4 3.4 1 3.2 0 -9.8 219 -34.3 412 653.8 4196.5

CH M 1 1-13 july 2010 12 58.73351 -93.79792 24.3 5.53 17.5 2.2 2.2 3.6 3.8 0.6 -6.9 23.9 -35.8 431.6 1204.9 3681.3

CH M 2 1-13 july 2010 12 58.73235 -93.79028 21.86 3.86 16 2.04 1.84 3.92 3.96 0.72 -6.9 23.9 -35.8 431.6 1204.9 3681.3

CH M 3 1-13 july 2010 12 58.72235 -93.83991 22.43 3.88 16.2 2.24 2 3.9 3.95 0.86 -6.9 23.9 -35.8 431.6 1204.9 3681.3

CH W 1 1-13 july 2010 12 58.73573 -93.79789 24.41 4.15 16.44 2.09 2 3.88 3.94 0.43 -6.9 23.9 -35.8 431.6 1204.9 3681.3

CH W 2 1-13 july 2010 12 58.73034 -93.79509 24.2 3.9 16.22 1.91 1.81 3.86 3.73 0.52 -6.9 23.9 -35.8 431.6 1204.9 3681.3

CH W 3 1-13 july 2010 12 58.65735 -93.83104 23.44 4.27 16.47 2.1 1.97 3.83 3.87 0.62 -6.9 23.9 -35.8 431.6 1204.9 3681.3

KU M 1 22 june - 2 july 2011 11 67.78182 -115.27699 17.5 7.57 59.5 0.33 2.66 1.33 1.66 3.33 -10.6 28.9 -41.4 249.3 887.5 4728.1

KU M 2 22 june - 2 july 2011 11 67.83565 -115.20968 23.3 5.85 35.33 0.5 1.83 2.5 0.16 4.66 -10.6 28.9 -41.4 249.3 887.5 4728.1

KU M 3 22 june - 2 july 2011 11 67.83427 -115.21136 18.53 4.75 27.33 1.5 2.16 3.33 0.33 4.66 -10.6 28.9 -41.4 249.3 887.5 4728.1

KU W 1 22 june - 2 july 2011 11 67.78157 -115.27824 15.16 6.04 30.33 4.16 3.16 1.83 0.5 2.33 -10.6 28.9 -41.4 249.3 887.5 4728.1

KU W 2 22 june - 2 july 2011 11 67.83396 -115.21370 18.46 3.47 25.33 3.66 3.83 3.33 0.83 1.83 -10.6 28.9 -41.4 249.3 887.5 4728.1

KU W 3 22 june - 2 july 2011 11 67.83617 -115.20895 22.63 7.04 32.33 4.33 3.66 2.33 1 1.83 -10.6 28.9 -41.4 249.3 887.5 4728.1

SC M 1 30 june-9 july 2010 9 54.90526 -67.15049 57.64 9.81 47.6 0.6 2 2 1 2.6 -5.3 25.7 -35.7 822.9 1270.1 3163.6

SC M 2 30 june-9 july 2010 9 54.90414 -67.14888 50.36 9.1 50.12 0.72 1.8 2.4 1 2.52 -5.3 25.7 -35.7 822.9 1270.1 3163.6

SC M 3 30 june-9 july 2010 9 54.90310 -67.14765 59.68 9.65 50.54 0.86 2.16 1.88 1 2.62 -5.3 25.7 -35.7 822.9 1270.1 3163.6

SC W 1 30 june-9 july 2010 9 54.75970 -66.71120 71.13 11.08 50.65 1.03 2.59 1.25 1 2.54 -5.3 25.7 -35.7 822.9 1270.1 3163.6

SC W 2 30 june-9 july 2010 9 54.85262 -66.66897 65.36 13.29 52.78 1.24 2.11 1.5 0.8 2.65 -5.3 25.7 -35.7 822.9 1270.1 3163.6

SC W 3 30 june-9 july 2010 9 54.85350 -66.67043 60.83 10.59 50.34 0.89 2.13 1.8 0.96 2.59 -5.3 25.7 -35.7 822.9 1270.1 3163.6

TO M 1 21 june-1 july 2011 10 64.60560 -138.36143 22.83 5.42 30.83 3 2.83 2.33 1.5 1.5 -4.4 27 -50 324.3 1817.9 3395.1

TO M 2 21 june-1 july 2011 10 64.59915 -138.30611 22.8 5.2 30.13 3.16 2.8 2.05 1.58 1.41 -4.4 27 -50 324.3 1817.9 3395.1

65 site Hab. rep. dates days latitude longitude mean.pd sd.pd maxveght gramcov moscov lichcov forbcov shrubcov AMT maxT minT AP DJA0 DJB0

TO M 3 21 june-1 july 2011 10 64.58353 -138.26843 22.43 4.75 28.49 2.86 2.93 2.39 1.68 1.31 -4.4 27 -50 324.3 1817.9 3395.1

TO W 1 21 june-1 july 2011 10 64.60629 -138.35637 22.34 4.59 28.24 2.67 3.09 2.63 1.62 1.2 -4.4 27 -50 324.3 1817.9 3395.1

TO W 2 21 june-1 july 2011 10 64.59736 -138.31009 22.23 4.62 28.78 2.78 2.94 2.56 1.73 1.4 -4.4 27 -50 324.3 1817.9 3395.1

TO W 3 21 june-1 july 2011 10 64.57942 -138.28212 22.94 4.93 28.58 2.91 2.77 2.66 1.68 1.3 -4.4 27 -50 324.3 1817.9 3395.1

GB M 1 15-24 june 2010 9 53.31890 -60.29594 58.2 10.06 36 0.4 2.4 2 0 2.6 -0.5 31.4 -26 949 1856.7 2025.4

GB M 2 15-24 june 2010 9 53.32036 -60.29691 49.84 12.07 38.2 0.28 1.88 2.4 0 2.72 -0.5 31.4 -26 949 1856.7 2025.4

GB M 3 15-24 june 2010 9 53.32035 -60.29268 53.2 13.59 39.84 0.33 2.25 1.88 0 3.06 -0.5 31.4 -26 949 1856.7 2025.4

GB W 1 15-24 june 2010 9 53.21199 -60.45062 58.64 15.74 37.8 0.4 2.7 1.25 0 3.27 -0.5 31.4 -26 949 1856.7 2025.4

GB W 2 15-24 june 2010 9 53.21408 -60.45044 57.57 14.33 40.36 0.28 2.24 1.5 0 3.33 -0.5 31.4 -26 949 1856.7 2025.4

GB W 3 15-24 june 2010 9 53.21620 -60.45001 55.49 13.16 38.44 0.34 2.29 1.8 0 2.99 -0.5 31.4 -26 949 1856.7 2025.4

MO M 1 17-26 june 2010 9 51.24622 -80.67281 100 0 65 5 2.4 0 1.2 0.4 -1.1 30.6 -33 681.6 1959.1 2339.3

MO M 2 17-26 june 2010 9 51.24466 -80.67767 100 0 65 5 2.28 0 1.04 0.48 -1.1 30.6 -33 681.6 1959.1 2339.3

MO M 3 17-26 june 2010 9 51.24690 -80.68102 100 0 65 5 2.13 0 0.84 0.57 -1.1 30.6 -33 681.6 1959.1 2339.3

MO W 1 15-25 june 2010 10 51.28034 -80.64252 100 0 58 5 2.56 0 0.81 0.29 -1.1 30.6 -33 681.6 1959.1 2339.3

MO W 2 16-25 june 2010 9 51.28288 -80.63926 100 0 57.6 5 2.27 0 0.98 0.34 -1.1 30.6 -33 681.6 1959.1 2339.3

MO W 3 16-25 june 2010 9 51.27717 -80.64778 100 0 62.12 5 2.33 0 0.97 0.41 -1.1 30.6 -33 681.6 1959.1 2339.3

NW M 1 7-17 june 2010 10 65.29204 -126.63725 38.1 4.2 46.66 1.66 2.5 0.66 1.16 1.5 -5.5 28.7 -44.2 290.7 1860.2 3844

NW M 2 7-17 june 2010 10 65.26694 -126.72827 39.25 4.63 44.44 1.44 2.41 0.77 1.19 1.41 -5.5 28.7 -44.2 290.7 1860.2 3844

NW M 3 7-17 june 2010 10 65.30494 -126.70873 36.42 4.44 46.01 0.85 2.81 0.9 1.22 1.48 -5.5 28.7 -44.2 290.7 1860.2 3844

NW W 1 7-17 june 2010 10 65.29112 -126.62262 39.66 4.87 46.52 0.99 2.45 1.05 1.26 1.56 -5.5 28.7 -44.2 290.7 1860.2 3844

NW W 2 7-17 june 2010 10 65.25226 -126.66128 31.8 5.16 48.44 0.99 2.86 1.23 1.3 1.49 -5.5 28.7 -44.2 290.7 1860.2 3844

NW W 3 7-17 june 2010 10 65.28901 -126.84077 33.94 4.63 50.51 1.15 2.84 0.94 1.36 1.57 -5.5 28.7 -44.2 290.7 1860.2 3844

YE M 1 7-18 june 2011 11 62.51070 -113.39479 13.66 3.76 45.83 2.5 1.33 1.83 0.16 2 -4.6 27.3 -41.7 280.7 1835.5 3475.4

YE M 2 7-18 june 2011 11 62.50293 -113.40479 9.57 3.65 44.8 2.08 1.05 2.13 0.19 2 -4.6 27.3 -41.7 280.7 1835.5 3475.4

YE M 3 7-18 june 2011 11 62.50714 -113.39443 9.1 3.09 40.6 1.59 1.23 2.49 0.22 1.83 -4.6 27.3 -41.7 280.7 1835.5 3475.4

YE W 1 7-18 june 2011 11 62.52110 -113.38174 10.25 3.47 47.04 1.86 1.27 2.24 0.26 2.13 -4.6 27.3 -41.7 280.7 1835.5 3475.4

YE W 2 7-18 june 2011 11 62.51923 -113.38494 11.16 3.66 53.21 2.17 0.98 2.11 0.14 2.32 -4.6 27.3 -41.7 280.7 1835.5 3475.4

YE W 3 7-18 june 2011 11 62.51591 -113.39146 12.16 3.66 58.58 2.53 1.14 1.8 0.16 2.05 -4.6 27.3 -41.7 280.7 1835.5 3475.4

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Amaurobiidae Cybaeopsis euopla (Bishop & Crosby) 8 9 12 1

Araneidae Aculepeira packardi (Thorell) 1

Araneidae Araneus groenlandicola (Strand) 1

Araneidae Hypsosinga groenlandica (Docherty and Leather) 1 17 2 MB

Araneidae Hypsosinga pygmaea (Sundevall) 7 1 1 1

Araneidae Hypsosinga rubens (Hentz) 1 9 4 LB

Araneidae Larinioides cornutus (Clerck) 1 1

Clubionidae Clubiona bryantae (Gertsch) 1 4 1 11 1 26 LB

Clubionidae Clubiona furcata (Emerton) 1 1

Clubionidae Clubiona kulczynskii (Lessert) 2

Clubionidae Clubiona norvegica (Strand) 1 1

Clubionidae Clubiona opeongo (Wagner and Edwards) 1 LB

Clubionidae Clubiona praematura (Emerton) 2

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Clubionidae Clubiona riparia (L.Koch) 1

Clubionidae Clubiona trivialis (C.L.Koch) 1 NU

Dictynidae Arctella lapponica (Holm) 5 2 NU

Dictynidae Argenna obesa (Emerton) 5 85 14 NT

Dictynidae Cicurina brevis (Emerton) 1

Dictynidae Dictyna arundinacea (Linnaeus) 3

Dictynidae Dictyna brevitarsa (Emerton) 1 1 LB

Dictynidae Dictyna major (Menge) 1

Dictynidae Emblyna annulipes (Blackwall) 1 3 8 NU

Dictynidae Emblyna borealis (O.P.-Cambridge) 29 3 2

Dictynidae Emblyna phylax (Gertsch & Ivie) 1 LB

Dictynidae Lathys pallida (Marx) 1 NT

Gnaphosidae Callilepis pluto (Banks) 25

Gnaphosidae Drassodes mirus (Platnick & Shadab) 1 2 NT, MB

Gnaphosidae Drassodes neglectus (Keyserling) 6 6

Gnaphosidae Gnaphosa borea (Kulczynski) 15 80 32 5 26 17 NU

Gnaphosidae Gnaphosa brumalis (Thorell) 5 26 2 4 1

Gnaphosidae Gnaphosa microps (Holm) 6 4 39 1 10 5

Gnaphosidae Gnaphosa muscorum (L.Koch) 2 7 13 12

Gnaphosidae Gnaphosa orites (Chamberlin) 38 5 1 MB

Gnaphosidae Gnaphosa parvula (Banks) 1 1 2 11 6 LB

Gnaphosidae Haplodrassus eunis (Chamberlin) 13 8 3 LB, NT

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Gnaphosidae Haplodrassus hiemalis (Emerton) 6 9 57 3 14 23 LB

Gnaphosidae Haplodrassus signifer (C.L.Koch) 22 1 9 6 LB, NT

Gnaphosidae Micaria aenea (Thorell) 11 15 6 LB

Gnaphosidae Micaria alpina (L.Koch) 17 15 1

Gnaphosidae Micaria constricta (Emerton) 5

Gnaphosidae Micaria pulicaria (Sundevall) 6 1 2 5 19 LB

Gnaphosidae Micaria rossica (Thorell) 20 10

Gnaphosidae Sergiolus montanus (Emerton) 1

Gnaphosidae Zelotes fratris (Chamberlin) 2 11 13 12

Gnaphosidae Zelotes puritanus (Chamberlin) 8 7

Gnaphosidae Zelotes sula (Lowrie & Gertsch) 5 1

Hahniidae Antistea brunnea (Emerton) 12

Hahniidae Hahnia cinerea (Emerton) 1 1 LB, NT

Hahniidae Hahnia glacialis (Sorensen) 20 6 NT

Hahniidae Hahnia ononidum (Docherty and Leather) 8 1

Hahniidae Neoantistea agilis (Keyserling) 13 LB

Hahniidae Neoantistea magna (Keyserling) 17

Linyphiidae Agyneta allosubtilis (Loksa) 6 3 3 NT

Linyphiidae Meioneta nigripes (Docherty and Leather) 1 1

Linyphiidae Agyneta olivacea (Docherty and Leather) 2 43 1 1 2 22 74 LB, NU

Linyphiidae Agyneta sp.1 23 58 33 1

Linyphiidae Aphileta misera (O.P.-Cambridge) 1 21 LB

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Linyphiidae Arcterigone pilifrons (L.Koch) 17 7

Linyphiidae Praestigia groenlandicum (Holm) 28 62 141

Linyphiidae Praestigia kulczynskii (Eskov) 1 11 1 11 5 13 NU

Linyphiidae Baryphyma trifrons affine (Schenkel) 2

Linyphiidae Bathyphantes brevipes (Emerton) 1 ON

Linyphiidae Bathyphantes brevis (Emerton) 3

Linyphiidae Bathyphantes canadensis (Emerton) 3

Linyphiidae Bathyphantes gracilis (Blackwall) 1 NT

Linyphiidae Bathyphantes pallidus (Banks) 2 3 15

Linyphiidae Bathyphantes eumenis (L.Koch) 1 19 4 NU

Linyphiidae Carorita limnaea (Crosby & Bishop) 8 3 4 1 LB, NT

Linyphiidae Centromerus longibulbus (Emerton) 23 19 1 LB

Linyphiidae Ceraticelus bulbosus (Emerton) 2 36 5 6 6

Linyphiidae Ceraticelus crassiceps (Chamberlin & Ivie) 3 8 2 NT

Linyphiidae Ceraticelus emertoni (O.P.-Cambridge) 1

Linyphiidae Ceraticelus laetabilis (O.P.-Cambridge) 1

Linyphiidae Ceraticelus laetus (O.P.-Cambridge) 1

Linyphiidae Ceraticelus rowensis (Levi & Levi) 1 NT

Linyphiidae Ceraticelus silus (Dondale) 3

Linyphiidae Ceraticelus similis (Banks) 24

Linyphiidae Ceraticelus sp.1 2

Linyphiidae Ceratinella brunnea (Emerton) 1 9 1 3 12 1 NT, YT

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Linyphiidae Ceratinella buna (Chamberlin) 3

Linyphiidae Ceratinella ornatula (Crosby & Bishop) 5 2

Linyphiidae Ceratinella parvula (Fox) 3 3 1 NT

Linyphiidae Ceratinops latus (Emerton) 1 1 LB, NT

Linyphiidae Ceratinopsis labradorensis (Emerton) 39 2 6 NT

Linyphiidae Cheniseo sphagnicultor (Bishop & Crosby) 1 LB

Linyphiidae Cnephalocotes obscurus (Blackwall) 1 5 9 7 LB

Linyphiidae Collinsia plumosa (Emerton) 21

Linyphiidae Dicymbium elongatum (Emerton) 1 NT

Linyphiidae Diplocentria bidentata (Emerton) 3 8 75 1 15 30 31 LB, NU

Linyphiidae Diplocentria perplexa (Chamberlin & Ivie) 1

Linyphiidae Diplocentria rectangulata (Emerton) 31 1 LB

Linyphiidae Diplocephalus barbiger (Roewer) 7 1 2 5

Linyphiidae Diplocephalus cristatus (Blackwall) 1

Linyphiidae Dismodicus decemoculatus (Emerton) 1

Linyphiidae Entelecara sombra (Chamberlin & Ivie) 1 NT

Linyphiidae Erigone arctica (White) 40 43

Linyphiidae Erigone arctophylacis (Crosby & Bishop) 13 ON

Linyphiidae Erigone atra (Blackwall) 77 1

Linyphiidae Erigone dentigera (O.P.-Cambridge) 1 44 2

Linyphiidae Erigone psychrophila (Thorell) 128 20 149 3 1

Linyphiidae Erigone sp.1 4

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Linyphiidae Erigone tirolensis (L.Koch) 5

Linyphiidae Estrandia grandaeva (Keyserlling) 1 1

Linyphiidae Floricomus rostratus (Emerton) 6 48

Linyphiidae Glyphesis idahoanus (Chamberlin) 1

Linyphiidae Glyphesis scopulifer (Emerton) 2 2

Linyphiidae Gonatium crassipalpum (Bryant) 1 11 1 4

Linyphiidae Grammonota angusta (Dondale) 1 1

Linyphiidae Grammonota gigas (Banks) 186 1 52 LB

Linyphiidae Grammonota maritima (Emerton) 7 2 NT

Linyphiidae Grammonota sp.1 2

Linyphiidae Hilaira canaliculata (Emerton) 1 2 NT

Linyphiidae Hilaira herniosa (Thorell) 4 3 1

Linyphiidae Hilaira proletaria (L.Koch) 1 9

Linyphiidae Hilaira vexatrix (O.P.-Cambridge) 117 1 301 19

Linyphiidae Horcotes quadricristatus (Emerton) 4 41 76 5 NU

Linyphiidae Hybauchenidium aquilonare (L.Koch) 38 14 1

Linyphiidae Hybauchenidium gibbosum (Sorensen) 57

Linyphiidae Hypomma subarcticum (Chamberlin & Ivie) 1

Linyphiidae Hypselistes florens (O.P.-Cambridge) 1

Linyphiidae Hypselistes semiflavus (L.Koch) 1 NT

Linyphiidae Improphantes complicatus (Emerton) 2 16 8 1 NT

Linyphiidae Incestophantes washingtoni (Zorsch) 4 1 1

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Linyphiidae Islandiana falsifica (Keyserling) 2 1 2 MB

Linyphiidae Islandiana longisetosa (Emerton) 17

Linyphiidae Islandiana princeps (Braendegaard) 1

Linyphiidae Ivielum sibiricum (Eskov) 8

Linyphiidae Kaestneria pullata (O.P.-Cambridge) 8 1

Linyphiidae Kaestneria rufula (Hackman) 2 1 1 NT

Linyphiidae Lepthyphantes alpinus (Emerton) 2 2 3

Linyphiidae Tenuiphantes zebra (Emerton) 1

Linyphiidae Masikia indistincta (Kulczynski) 39 6 2 NU

Linyphiidae Mecynargus borealis (Jackson) 5 7 MB

Linyphiidae Mecynargus monticola (Holm) 5 NU

Linyphiidae Mecynargus paetulus (O.P.-Cambridge) 3 3 1 5 NU

Linyphiidae Mecynargus sphagnicola (Holm) 4 3 2 NU

Linyphiidae Mecynargus tungusicus (Eskov) 1

Linyphiidae Meioneta amersaxatilis (Saaristo & Koponen) 2 2 1 8 1 2 NU, NT

Linyphiidae Meioneta fabra (Keyserling) 21

Linyphiidae Meioneta jacksoni (Braendegaard) 11 79 17 1 3 8 MB, LB, ON , NT

Linyphiidae Meioneta maritima (Emerton) 10 5 3 1

Linyphiidae Meioneta simplex (Emerton) 1 1 96 1 89 40 25 NU, LB

Linyphiidae Mermessus entomologicus (Emerton) 2 15 LB

Linyphiidae Mermessus tridentatus (Emerton) 3 1 LB

Linyphiidae Mermessus undulatus (Emerton) 6 2 39 2 1

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Linyphiidae Metopobactrus prominulus (O.P.-Cambridge) 12 23 1 3 MB, NU, YT

Linyphiidae Microlinyphia dana (Chamberlin & Ivie) 6 NT

Linyphiidae Microlinyphia mandibulata (Emerton) 1

Linyphiidae Microlinyphia pusilla (Sundevall) 1

Linyphiidae Microneta viaria (Blackwall) 1 1 LB, NT

Linyphiidae Neriene clathrata (Sundevall) 1 NT

Linyphiidae Oedothorax trilobatus (Banks) 2 7 19 1 NT

Linyphiidae Oreoneta beringiana (Saaristo & Marusik) 5 NU

Linyphiidae Oreoneta brunnea (Emerton) 1 5 1 MB

Linyphiidae Oreoneta sp.1 1

Linyphiidae Oreonetides flavescens (Crosby) 3 LB

Linyphiidae Oreonetides rectangulatus (Emerton) 4 1 NT

Linyphiidae Oreonetides vaginatus (Thorell) 4 3 3

Linyphiidae Oreophantes recurvatus (Emerton) 1

Linyphiidae Pelecopsis mengei (Pickard-Cambridge and Howes) 2 3

Linyphiidae Perregrinus deformis (Tanasevitch) 1 7

Linyphiidae Phlattothrata parva (Kulczynski) 1

Linyphiidae Pityohyphantes subarcticus (Chamberlin & Ivie) 2

Linyphiidae Pocadicnemis americana (Millidge) 22 27 1 22 8

Linyphiidae Poeciloneta vakkhanka (Tanasevitch) 1 YT

Linyphiidae Poeciloneta variegata (Blackwall) 1 MB

Linyphiidae Satilatlas carens (Millidge) 6 NU

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Linyphiidae Satilatlas gertschi (Millidge) 1

Linyphiidae Satilatlas marxi (Keyserling) 2

Linyphiidae Sciastes dubius (Hackman) 1

Linyphiidae Sciastes mentasta (Chamberlin & Ivie) 2 NT

Linyphiidae Sciastes truncatus (Emerton) 1 16 2

Linyphiidae Scironis tarsalis (Emerton) 10 NT

Linyphiidae Scotinotylus pallidus (Emerton) 2 LB

Linyphiidae Scotinotylus sacer (Crosby) 3 3 4

Linyphiidae Scyletria inflata (Bishop & Crosby) 75

Linyphiidae Semljicola beringianus (Eskov) 243 3 16 2 YT

Linyphiidae Semljicola obtusus (Emerton) 1 6 MB

Linyphiidae Silometopoides pampia (Chamberlin) 6 160 2 2 1

Linyphiidae Sisicottus montanus (Emerton) 15

Linyphiidae Sisicottus quoylei (Miller) 1

Linyphiidae Sisicus penifusifer (Bishop & Crosby) 1 LB

Linyphiidae Sisis rotundus (Emerton) 19 9 NT

Linyphiidae Stemonyphantes blauveltae (Gertsch) 4

Linyphiidae Styloctetor stativus (Docherty and Leather) 18 17 9 LB

Linyphiidae Tapinocyba bicarinata (Emerton) 1 24 7 1 3 19 LB

Linyphiidae Tapinocyba minuta (Emerton) 29 14 1 8 6 LB

Linyphiidae Tapinocyba simplex (Emerton) 2 3 1 LB, NT

Linyphiidae Tapinocyba sp.1 1

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Linyphiidae Tarsiphantes latithorax (Strand) 13 1 16 4

Linyphiidae Tennesseellum formica (Emerton) 3 NT

Linyphiidae Tiso aestivus (L.Koch) 3 NT

Linyphiidae Tmeticus ornatus (Emerton) 1

Linyphiidae Tunagyna debilis (Banks) 1 2 2 LB

Linyphiidae Vermontia thoracica (Emerton) 3 1 1 4 2 YT, LB

Linyphiidae Wabasso cacuminatus (Millidge) 63 78 1 LB

Linyphiidae Wabasso quaestio (Chamberlin) 12 2 8 3 NT

Linyphiidae Walckenaeria arctica (Millidge) 4 2 4 2 1 LB

Linyphiidae Walckenaeria atrotibialis (O.P.-Cambridge) 1

Linyphiidae Walckenaeria auranticeps (Emerton) 5

Linyphiidae Walckenaeria castanea (Emerton) 2 1 1

Linyphiidae Walckenaeria clavicornis (Emerton) 1 1 1 MB

Linyphiidae Walckenaeria clavipalpis (Millidge) 7

Linyphiidae Walckenaeria communis (Emerton) 2 1 3

Linyphiidae Walckenaeria cuspidata brevicula (Crosby & Bishop) 3 1 NT

Linyphiidae Walckenaeria directa (O.P.-Cambridge) 2 3 1

Linyphiidae Walckenaeria exigua (Millidge) 178 39 4 LB

Linyphiidae Walckenaeria fallax (Millidge) 2

Linyphiidae Walckenaeria fraudatrix (Millidge) 1

Linyphiidae Walckenaeria karpinskii (O.P.-Cambridge) 8 1 8 54 1

Linyphiidae Walckenaeria kochi (O.P.-Cambridge) 1 NT

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Linyphiidae Walckenaeria minuta (Emerton) 5

Linyphiidae Walckenaeria pallida (Emerton) 1 3 LB

Linyphiidae Walckenaeria palustris (Millidge) 12

Linyphiidae Walckenaeria redneri (Millidge) 3

Linyphiidae Walckenaeria spiralis (Emerton) 1 1 4 2 2 NT

Linyphiidae Walckenaeria tibialis (Emerton) 1

Linyphiidae Walckenaeria tricornis (Emerton) 17 4 25 10

Linyphiidae Walckenaeria tumida (Crosby & Bishop) 1 1 LB

Linyphiidae Walckenaeria vigilax (Blackwall) 1 1 YT, NT

Linyphiidae Walckenaerianus aimakensis (Wunderlich) 15 25 NT, ON

Lycosidae Alopecosa aculeata (Clerck) 6 25 20 404 1 447 154

Lycosidae Alopecosa exasperans (O.P.-Cambridge) 304 99

Lycosidae Alopecosa hirtipes (Kulczynski) 431 1 1

Lycosidae Alopecosa pictilis (Emerton) 13 168 24

Lycosidae Arctosa alpigena (Doleschall) 1 27 2 1 15 10

Lycosidae Arctosa emertoni (Gertsch) 2

Lycosidae Arctosa insignita (Thorell) 6 46 2 25 1 2

Lycosidae Arctosa raptor (Kulczynski) 66 90 60 33 11

Lycosidae Arctosa rubicunda (Keyserling) 8 10 4 NT, LB

Lycosidae Hogna frondicola (Emerton) 1 8 LB

Lycosidae Pardosa albomaculata (Emerton) 1

Lycosidae Pardosa algens (Kulczynski) 413 2773 95 14 1 2

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Lycosidae Pardosa concinna (Thorell) 1564 290 2 757 1 1 18 24

Lycosidae Pardosa furcifera (Thorell) 322 215 73 10

Lycosidae Pardosa fuscula (Thorell) 70 90 1 8 357 154 74

Lycosidae Pardosa glacialis (Thorell) 41 11 7 98

Lycosidae Pardosa groenlandica (Thorell) 1

Lycosidae Pardosa hyperborea (Thorell) 60 156 3 425 12 256 18

Lycosidae Pardosa labradorensis (Thorell) 8 1 YT

Lycosidae Pardosa mackenziana (Keyserling) 2 59 23

Lycosidae Pardosa modica (Blackwall) 4 NT

Lycosidae Pardosa moesta (Banks) 59 1 775 199 1282

Lycosidae Pardosa podhorskii (Kulczynski) 95 2

Lycosidae Pardosa sodalis (Holm) 273 5 NU

Lycosidae Pardosa uintana (Gertsch) 1 20 3 17 3

Lycosidae Pardosa xerampelina (Keyserling) 1 3 71 117 7

Lycosidae Pirata bryantae (Kurata) 4 2 5

Lycosidae Piratula canadensis (Dondale & Redner) 14

Lycosidae Piratula cantralli (Wallace & Exline) 81 7 58 6 LB

Lycosidae Pirata piraticus (Clerck) 12 22 194 15 2

Lycosidae Trebacosa marxi (Stone) 1

Lycosidae Trochosa terricola (Thorell) 13 9

Philodromidae Philodromus alascensis (Keyserling) 1

Philodromidae Philodromus cespitum (Walckenaer) 1

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Philodromidae Thanatus arcticus (Thorell) 57 12 1 26 4 7 QC

Philodromidae Thanatus formicinus (Clerck) 1

Philodromidae Tibellus maritimus (Menge) 6 3 2 6

Philodromidae Thanatus striatus (C.L.Koch) 4 15

Philodromidae Tibellus oblongus (Walckenaer) 1

Pisauridae Dolomedes striatus (Giebel) 9 2

Pisauridae Dolomedes triton (Walckenaer) 1

Salticidae Chalcoscirtus alpicola (L.Koch) 1 NT

Salticidae Evarcha proszynskii (Marusik & Logunov) 6 8

Salticidae Habronattus borealis (Banks) 1 NT

Salticidae Pelegrina montana (Emerton) 3

Salticidae Pellenes lapponicus (Sundevall) 11 NT

Salticidae Phidippus whitmani (Peckham & Peckham) 1 2 NT

Salticidae Sitticus cutleri (Pròszynski) 1

Salticidae Sitticus floricola palustris (Peckham & Peckham) 1

Salticidae Sitticus ranieri (Peckham & Peckham) 3 1 1 1 12 10

Salticidae Sitticus striatus (Emerton) 2 1 1 NT

Salticidae Talavera minuta (Banks) 1 1 12 6 LB

Tetragnathidae Pachygnatha clercki (Sundevall) 8 2 3 NU

Tetragnathidae Tetragnatha caudata (Emerton) 7

Tetragnathidae Tetragnatha versicolor (Walckenaer) 1

Tetragnathidae Tetragnatha extensa (Linnaeus) 1

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Theridiidae Arctachaea sp.1 1 undescribed

Theridiidae Dipoena nigra (Emerton) 1 LB

Theridiidae Enoplognatha caricis (Fickert) 1 3 NT

Theridiidae Euryopis argentea (Emerton) 42 20 NT

Theridiidae Robertus borealis (Kaston) 2 3 LB

Theridiidae Robertus fuscus (Emerton) 1 12

Theridiidae Rugathodes aurantius (Emerton) 1

Theridiidae Steatoda albomaculata (De Geer) 2

Theridiidae Theonoe stridula (Crosby) 1 2 LB, NT

Theridiidae Theridion differens (Emerton) 1

Theridiidae Thymoites minnesota (Levin) 2

Thomisidae Bassaniana utahensis (Gertsch) 1

Thomisidae Misumena vatia (Clerck.) 1 1

Thomisidae Ozyptila arctica (Kulczynski) 5 18 12 MB

Thomisidae Ozyptila curvata (Dondale & Redner) 1 ON

Thomisidae Ozyptila gertschi (Kurata) 15 2 4

Thomisidae Ozyptila praticola (C.L.Koch) 2

Thomisidae Ozyptila sincera canadensis (Dondale & Redner) 1 20 1 50 38 LB

Thomisidae Xysticus banksi (Bryant) 1 NT

Thomisidae Xysticus britcheri (Gertsch) 23 1 14 68 36 5 3

Thomisidae Xysticus deichmanni (Sorensen) 26 47 17 4

Thomisidae Xysticus durus (Sorensen) 4 3 6 7 MB

Arctic Subarctic North-boreal New provincial

and territorial

Family Species BA CB HA IQ CH KU SC TO GB MO NW YE record

Thomisidae Xysticus ellipticus (Turnbull, Dondale & Redner) 2 24 2 12 LB

Thomisidae Xysticus emertoni (Keyserling) 16 5 5 30 23 LB

Thomisidae Xysticus ferox (Hentz) 1 28

Thomisidae Xysticus luctuosus (Blackwall) 1 15 1 3 3 NT

Thomisidae Xysticus montanensis (Keyserling) 7 NT

Thomisidae Xysticus obscurus (Collett) 1 6 NU

CHAPTER 3: GENERAL CONCLUSION AND FUTURE WORK

The main objective of this thesis was to describe diversity patterns of ground- dwelling spiders at multiple spatial scales in northern Canada. I found that richness, composition and abundance of ground-dwelling spiders were structured at continental, regional and local spatial scale. The main structure was a difference of species richness and composition between the North-Boreal, Subarctic and

Arctic ecoclimatic region. At regional scale, western sites differed from eastern sites indicating the importance of longitudinal diversity gradients in northern

North-America, perhaps due to post-glacial dispersal patterns. Abundance of spiders was more structured at small spatial scales indicating that biotic interactions may play an important role in determining dominance of spider species in the North. Vegetation and climate explained well variation of spider diversity but no single factor was found to best explain diversity patterns.

Because this study is the first quantitative study on spiders in Canada’s North at continental scale, the contribution to Canadian spider species distribution is vast.

On the 306 species identified, 131 have at least one new province record

(Appendix III). The two provinces with higher numbers of new records are

Northwest Territories and Labrador. New records in western Canada were expected as Paquin et al. (2010), authors of the most recent checklist of Canadian spiders, highlighted the potential high level of novelty in western provinces.

However, spiders from some eastern provinces like Labrador or Newfoundland are also understudied.

This study is the first to describe multi-scale patterns of terrestrial arthropod diversity from local to continental scale (20°latitude, 30°longitude) in Arctic ecosystems. The need to understand biodiversity changes at northern latitudes increases given the support that species are already affected by rapid climate change (e.g., Fernandez-Triana et al. 2011, Hѳye et al. 2009). To better quantify biodiversity changes, the International Arctic Vegetation Database was created to provide information on plant species cover from small plots (e.g., 5m x 5m) distributed across the whole Arctic biome (Walker and Raynolds 2011). Such initiative for arthropod taxa would be of great interest. Only two weeks of passive sampling was enough to collect more than 70% of the diversity in the Subarctic and Arctic regions indicating that mapping arthropod biodiversity across the

Canadian North is realistic. Moreover, the use of higher taxonomic level is possible in arctic like in tropical ecosystems (Balmford et al. 1996), as gradient of species richness also reflected on genera for insects (Danks 1993) and spiders (my thesis). I think that spiders can be useful ecological bioindicators on environmental changes in the Arctic. This study has provided baseline data on

Arctic ground-dwelling spider diversity, structure and distribution. However, much work on arthropod diversity patterns is still required to obtain a more accurate description of spatial patterns in northern Canada. Research on Arctic diversity patterns should also test for congruency of general patterns by examining other taxa.

Literature cited

Balmford, A. et al. 1996. Using higher-taxon richness as a surrogate for species

richness: I. Regional tests. — P. Roy. Soc. Lond. B. Bio. 263(1375):

1267-1274.

Danks, H.V. 1993. Patterns of diversity in the Canadian insect fauna. —

Mem.Entomol. Soc. Can. 125(S165): 51-74.

Fernandez-Triana, J. et al. 2011. A poorly known high-latitude parasitoid wasp

community : unexpected diversity and dramatic changes through time. —

PLoS ONE 6(8): e23719.

Hѳye, T.T. et al. 2009. Climate change and sexual size dimorphism in an Arctic

spider. — Biol. Lett. 5(4): 542-544.

Paquin, P. et al. 2010. Checklist of the spiders (Araneae) of Canada and Alaska.

— Zootaxa 2461: 1-170.

Walter, D.A. and Raynolds, M.K. 2011. An International Arctic Vegetation

Database: a foundation for panarctic biodiversity studies. — Concept

Paper. CAFF International Secretariat, CAFF Strategy Series Report.

p29.