Simulated Shrub Encroachment Impacts Function of Arctic Spider Communities

Simulated Shrub Encroachment Impacts Function Of Arctic Spider Communities

Geoffrey Boyd Legault

A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Ecology & Evolutionary Biology University of Toronto

Simulated Shrub Encroachment Impacts Function Of Arctic Spider Communities

Geoffrey Legault

Master of Science

Department of Ecology & Evolutionary Biology University of Toronto

2011 Abstract

The projected increase in shrub abundance across sub-Arctic zones is expected to alter patterns of snow cover during the winter. As the amount of snow cover in an area impacts both melt date and winter snow pack, these changes may affect the phenology and survival of overwintering arthropods, such as spiders (Araneae). In this field study, we used snow fences to simulate shrub encroachment on a series of large (375 m2) tundra plots and examined the effects on the local spider assemblages during the following growing season. Snow fences increased winter snow cover and delayed snow melt in the treatment plots, paralleling the conditions of nearby shrub sites. Although our simulated shrub treatment did not affect the abundance or composition of spider communities over the season, adults from the dominant genus Pardosa

(Lycosidae) had significantly higher body mass on treatment plots. This difference in mass was observed immediately following snow melt and persisted until halfway through the growing season. Given the importance of spiders as arthropod predators and as food sources for breeding birds, such a change in summer body mass could represent a significant shift in spiders’ functional contributions to Arctic ecosystems.

ii iii

Table of Contents

List of Figures ...... iv

List of Tables ...... iv

Introduction ...... 1

Methods ...... 5

Results ...... 11

Discussion ...... 13

References ...... 31

Appendix 1: Supplementary Figures and Tables ...... 39

iii iv

List of Figures

1 (a) Photographs of snow fences and (b) a typical sampling plot ...... 19

2 Aerial view (partial) of study site ...... 20

3 Relationship between (log) spiders body mass and (log) abdomen length ...... 21

4 Effectiveness of small-scare trenches at excluding spiders ...... 22

5 Daily abundances of spiders over the season by treatment ...... 23

6 ANOSIM comparison of spider communities over the season ...... 24

7 Penultimate and adult spider masses over the season by treatment ...... 25

8 Pardosa mass over the season by treatment ...... 26

9 Pardosa peak mass by site-specific winter snow depths ...... 27

Appendix

1 (a) Average air and (b) surface temperatures over the season by treatment ...... 39

2 Genera accumulation curves over the season ...... 40

3 Generic richness over the season by treatment ...... 41

4 May air temperatures for Churchill, Manitoba from 1945-2010 ...... 42

iv v

List of Tables

1 Season-wide catches of spider genera on heath tundra sites ...... 28

2 Repeated-measures ANOVA on Pardosa body mass ...... 29

3 ANOVA comparison of spider masses by genera over the season ...... 30

Appendix

1 Shapiro-Wilk normality scores for daily spider abundances by treatment ...... 43

2 Results of repeated-measures ANOVAs on seasonal spider abundances by genera ...... 44

3 Results of Wilcoxon rank-sum tests on season spider abundances by genera ...... 45

4 Similarity percentages analysis (SIMPER) of spider communities ...... 46

5 Results of Wilcoxon rank-sum tests on seasonal spider masses by genera ...... 47

v 1

Introduction

Recent environmental changes across the Arctic are well documented (Serreze et al.,

2000; Peterson et al., 2002; Hinzman et al., 2005) and have been associated with changes to the surface vegetation (Stow et al., 2004; Johansson et al., 2006; Olthof et al., 2009; Forbes et al.,

2010; Hill & Henry, 2011). The expansion of deciduous shrubs (in particular, Betula, Salix, and

Aldus species) has been especially significant on the tundra and boreal forest-tundra ecotone

(Sturm et al., 2001a; Tape et al., 2006; Hudson & Henry, 2009), with an average increase in landscape coverage of approximately 5-15% over the past half century. Experimental work suggests that such shrub encroachment is driven largely by increased fertilization (Press et al.,

1998; Dormann & Woodin, 2002; van Wijk et al., 2004) as a result of temperature-induced shifts in litter decomposition (Cornelissen et al., 2007), mineralization (Rustad et al., 2001; Rinnan et al., 2007), spring melt date (Stone et al., 2002) and other factors (Wookey et al., 1993; Wahren et al., 2005; Walker et al., 2006; Hudson et al., 2011). Moreover, the presence of shrubs may facilitate intraspecific recruitment and growth by increasing winter nutrient release (Sturm et al.,

2001b; Sturm et al., 2005), which would create a feedback mechanism where shrub coverage could continue to increase without an associated increase in air temperatures.

Among the consequences of increased shrub cover in the Arctic is higher winter snow pack due partly to a reduction in the wind-driven sublimation of snow directly upwind and downwind of the shrub stems. The tendency of tall shrubs to act as ‘wind breaks’ on the otherwise flat tundra region can also affect how wind distributes snow across the landscape, with areas of high shrub cover typically acquiring higher amounts of snow. Using simulations, Liston et al. (2002) found that increased shrub cover could decrease snow sublimation by 20% or more across a landscape and produce a roughly equivalent increase in winter snow cover. In the field,

Pomeroy et al. (2006) found that the influence of shrub coverage on snow cover was even more

pronounced, with snow depths in shrub dominated tundra sites on average twice that of nearby shrub-free sites receiving similar levels of snowfall.

Increased snow pack during the winter as a result of shrub encroachment would likely delay spring melt date, due to the larger amount of snow requiring melting (Liston et al., 2002).

There is some evidence that differences in the albedo and heat absorption of shrubs could accelerate melt rate (Strack et al., 2007), however, whether such differences could compensate for the higher initial snow pack would likely depend on other local factors, such as slope and total annual precipitation (Marsh et al., 2010). In any case, since shrubs alter the distribution of snow not only around their stems, but upwind and downwind of them, their presence on the landscape can have a substantial impact on how quickly a patch will melt out in the spring relative to neighboring shrub-free sites.

The impact of shrub encroachment on Arctic systems through increased winter snow cover and/or earlier spring snow melt, could be particularly significant for terrestrial arthropod communities, which account for the majority of all animal life in the Arctic (Danks, 1981) and for which overwintering conditions are perhaps the most significant abiotic component of survival (review in Strathdee & Bale, 1998; Danks, 2004). The Arctic beetle, Pytho americanus

Kirby, for instance, must overwinter under the bark of decaying spruce (Picea) trees, a habitat that enables gradual acclimation to low temperatures and allows them to supercool to temperatures well below zero (Ring & Tesar 1980). Similarly, Dendroctonus rufipenis

(Coleoptera) demonstrates little freeze tolerance in the lab and appears to require shelter in fallen timber in order to survive the winter (Miller, 1982). In a recent study on antifreeze proteins in

Arctic arthropods, Duman et al. (2004) found that many tundra insects and spiders exhibited little to no freeze tolerance, suggesting that the thermal character of overwintering sites may be especially important for Arctic species (Danks, 2004).

Snow can be a significant driver of the thermal character of a site due to its insulative properties, which will tend to produce warmer subnivean temperatures as snow accumulates

(Sturm et al., 2001b; Bartlett et al. 2004; Sturm et al. 2005). Moreover, as the snow layer increases in size, so too does protection from environmental disturbances such as wind, which might otherwise damage, relocate, or desiccate overwintering arthropods. We would expect, therefore, the increased snow pack brought on by enhanced shrub growth to improve local overwintering conditions for arthropods. However, if precipitation patterns remained stable, it would likely do so at the cost of reducing the quality of neighboring shrub-free sites; indeed, while snow would be distributed evenly across a comparatively flat shrub-free landscape, the invasion of tall shrubs would result in the ‘clumping’ of snow around shrubs and a deficit of snow around shrub-free areas, leading to increased heterogeneity in the quality of overwintering sites.

Delayed snow melt, the second major consequence of increased shrub cover on the tundra, could also affect arthropod communities in significant ways. Emergence time (i.e.: juveniles hatching from eggs or overwintering individuals resuming summer activity) is not strictly a product of melt date in the Arctic, but the two are often highly coupled in northern systems (Danks 1999). Further, data from one of the few long-term studies of Arctic arthropods suggests that seasonal abundance patterns are strongly correlated with the timing of snow melt

(Høye & Forchhammer, 2008). Similarly, in alpine environments, the timing and size of aerial insect peaks has been shown to depend partly on snow melt date (Finn & Poff 2008) as has the phenology and community structure of ground-dwelling arthropod communities (Dollery &

Hodkinson, 2006; Hågvar & Klanderud, 2009; see also Coulson et al., 1996 and Coulson et al.,

2000 for environmental manipulations on Arctic microarthropod communities). Importantly, if arthropod abundance and phenology patterns were to shift as a result of shrub-induced changes

to snow melt date, there could be cascading effects on northern ecosystems, given the importance of arthropods to general ecosystem functioning in the Arctic (Kevan, 1972; Klein et al., 2008;

Tulp & Schekkerman, 2008) and the significance of the timing of their abundance peaks for other species (Schekkerman et al., 2003; Hart et al., 2006; Meltofte et al. 2007).

In this study, we examined how changes to winter snow cover and spring melt date affected spider (Araneae) communities in a low Arctic landscape. We focused on spiders because they are a dominant group on the tundra (Danks, 1981), are top arthropod predators

(feeding on mites, springtails, and other microarthropods), and are a primary food source for birds and amphibians. Further, Arctic spiders live for multiple years, tend not to overwinter as eggs (Gertsch, 1979, Danks 1999) and may be highly active during the winter. A 10-year survey of alpine spiders, for example, found significant winter activity in members of the families

Linyphiidae and Lycosidae (especially those from the genus Pardosa) both on and under

(subnivean) the snow (Vanin & Turchetto 2007). Similarly, Fennoscandian spiders, such as

Bolephthyphantes index (Linyphiidae), are known to migrate to the snow surface during milder

(> -7 °C) parts of the winter, which implies they are also active in the subnivean environment for parts of the season (Hågvar 2010). Further, in a study on Arctic sheet-weaving spiders

(Linyphiidae), Gunnarsson (1988) found that spiders increased in body size over 1 of 3 winter seasons, suggesting that some Arctic spiders are able to forage during the winter, at least under certain environmental conditions. The notion that spiders may be active during the exceptionally long winters of the Arctic (usually lasting a minimum of 9 months) reinforces the importance of overwintering sites to arthropod survival and lends support to the idea that shrub encroachment could have lasting implications for northern arthropod communities.

To understand how shrub-induced changes to winter snow cover and spring snow melt might affect Arctic spider communities, we established a 1-year, large-scale (375 m2), replicated

(n=6) field experiment in which we simulated shrub encroachment using a series of snow fences.

The use of snow fences is common in shrub encroachment studies (see Buckeridge, 2008; Ayres et al., 2010; for a review of snow fence experiments on plants see Wipf & Rixen, 2010) and serves as a convenient method for simulating the snow-holding capacity of shrubs over the winter. We erected fences at the start of winter, allowing snow to accumulate naturally which we assumed would replicate how snow would settle around shrub stems. Following snow melt, we regularly sampled arthropods from the snow fence plots and paired controls using pitfall traps.

Unsurprisingly, the vast majority of specimens caught were spiders (Araneae), reflecting their significant contribution to terrestrial Arctic arthropod biomass. Since the snow fences led to an increase in winter snow cover and a delay in snow melt date, our experiment does not strictly separate between the two and instead tests how the two factors might operate together to alter seasonal patterns of abundances, diversity, and ecosystem functioning.

Methods

Study Site

The experiment was conducted between November 2009 and August 2010, approximately 23 km east of the town of Churchill, Manitoba (N58.73527, W93.80790) in a low

Arctic zone on the northwest rim of the Hudson Bay Lowlands. The area is characterized by a mosaic of three vegetation types: wet sedge meadow (primarily Carex sp. and some grasses), dwarf shrub tundra (grasses, sedges, mosses, and shrubs > 40 cm tall, particularly Betula and

Salix sp.), and heath tundra (lichens, grasses, and ericaceous shrubs < 20 cm tall, such as

Rhododendron and Vaccinium sp.). We focused on heath tundra systems, which make up

between 10-20% of the vegetated area in the low Arctic (Walker et al., 2005), because sampling efforts in previous years indicated that they contained a higher prevalence of terrestrial arthropods and that they were frequent foraging sites for breeding birds (G Legault & RL

Jefferies, unpublished data). Further, the dominant tall, deciduous shrub in the area (Betula glandulosa) is likely to expand onto heath sites under projected temperature and nutrient regimes

(See Betula nana in Gough et al, 2002; Biasi et al., 2008; Jägerbrand et al., 2009).

The heath sites chosen for the experiment were on slightly elevated ridges (< 1 m higher than the surrounding vegetation) adjacent to areas of high deciduous shrub coverage. Winter snow cover is typically low on the sites (between 0 and 30 cm of snow in late March) and they are usually the first vegetated areas to melt out in the spring. Following melt, there is no standing water, though the acidic soil remains moist until mid-summer, when water becomes limiting.

Permafrost depth is highly variable, but is rarely less than 10 cm or more than 35 cm (x =20.03 cm, σx=10.37). Above the soil layer is a loose mat of vegetation, 10-20 cm thick, consisting chiefly of lichen interspersed with ericaceous shrubs and a small number of low-growing deciduous shrubs.

Experimental Treatment

A series of 6 snow fences were erected in early winter (November 2009) to increase the depth and duration of snow cover on the focal heath sites (Figure 1). The snow fences (15 m long and 1.5 m tall – consistent with the height of deciduous shrubs in the area) were constructed of a single layer of 50/50 circular mesh (Quest Plastics Model #SF4850X, Home Hardware,

Churchill, Manitoba) secured to the ground by steel T-posts, spaced 5 m apart. To maximize snow accumulation around the fences, they were positioned perpendicular to the prevailing wind

direction (NW). Prior snow accumulation experiments in the area indicated that fences could retain snow both upwind and downwind over an area equal to 10 x fence height by the total length of the fence (GP Kershaw, personal correspondence), so we therefore expected each fence to increase snow depth across an area of 450 m2. Due to strong winds, however, the fences sagged somewhat and the actual area of increased snow depth was approximately 375 m2 (25 m x 15 m) for each plot. Measurements of snow depths over the winter indicated that the fences increased snow depth differently in each plot (x =55.75 cm, σx=19.92), however all treatment plots melted out at the same time (+/- 12 hours), 14 days after nearby control plots (Figure 2), which had been left untouched over the winter and had also melted out within 12 hours of each other.

The size of the experimental plots, along with logistical constraints and concerns about minimizing environmental variability between plots, meant that 3 of the 6 treatment plots were separated by less than 10 m at their shortest edge. To reduce the effect of pseudo-replication and to prevent the contamination of experimental plots by terrestrial arthropods from the surrounding environment, we dug trenches (30 cm deep and 20 cm across) around the areas of increased snow depth (375 m2) for all treatment plots (and over an equivalent sized area for control plots) immediately following snow melt in the spring. In most cases, the bottoms of the trenches were filled with water from melted permafrost for much of the season, which we took to be an effective barrier to migration between plots.

To test the efficacy of the trenches at excluding terrestrial arthropods, we performed a small-scale trench experiment on two nearby heath tundra sites. Pitfall traps were placed in the ground and square trenches (20 cm deep and 20 cm across) were dug at varying distances from the trap. ‘Open’ traps were not surrounded by trenches, ‘tight’ traps were surrounded by trenches

with no space between the trench and the trap, and ‘wide’ traps were surrounded by trenches with 50 cm of vegetation between the trap and each side of the trench (n=10 for each). The average number of spiders caught in each set of traps over a 1-day and 5-day period was recorded.

Arthropod Sampling

For each experimental plot, a line of 10 pitfall traps was placed along a centre transect such that all traps were spaced 2 m apart and the first and last traps were 2.5 m from a shorter edge (all traps were 7.5 m from the longer edges). Traps consisted of yellow plastic bowls (10 cm diameter, 5 cm deep), dug flush with the ground and half filled with water and a drop of soap

(Palmolive, Original Scent, OECD No. 301 B/D) to break the surface tension. They were left uncovered as prior sampling efforts indicated that trap robbery by birds and other animals was negligible (G Legault and VG Rohwer, unpublished data).

Pitfall trap capture numbers are a function of both abundance and activity during the sampling period (Luff 1975). Arthropod activity on a given day can be influenced by short-term weather fluctuations, such as rain, and other environmental factors, particularly temperature. To account for this, on each sampling day we measured air and surface temperatures at a stable reference point for each plot using a digital thermocouple. We then performed a repeated- measures ANOVA on the data, with temperature as a response variable, treatment as the between-site factor, and date as the within-site factor. Based on our results (Appendix, Figure 1), air and surface temperatures did not differ between treatments or sites over the season and they could therefore be eliminated as confounding factors.

During sampling, which began following snow melt and continued every 5-14 days thereafter until the end of the growing season, traps were ‘activated’ in all plots (control and treatment) and left for 24 hours, at which point arthropods were collected and traps were removed. We elected not to pursue a more frequent sampling regime over concerns that it would deplete the local spider community to the extent that it might mask late-season patterns of interest.

Collected spiders were pooled by plot, sorted into morphs based on visual similarities and stored in 70% ethanol. Following transport from the field site, adult and penultimate (one moult from adulthood) specimens were mounted for imaging and then sorted to genus using Ubik et al.

(2007).

Length-mass Regression

We also wanted to test the effect of simulated shrub encroachment on spider (dry) body mass. To do so, we used a length-mass regression to infer the mass of spiders based on the length of their abdomen. This was necessary due to the large number of spiders collected (n=2811) and the extreme fragility of spider carcasses when they have been dried. Length-mass regression is common in ecological studies involving large numbers of arthropods (Dial & Roughgarden,

1995; Tulp & Schekkerman, 2008; Chaves-Campos et al., 2009) and produces very accurate estimates of body mass (Sample et al., 1993; Edwards, 1996; Brady & Noske, 2006; Höfer &

Ott, 2009)

We used 106 spider specimens collected in 2009 from a natural population located near our focal site to create a length-mass model relevant to our system. Spiders were photographed and measured digitally, using the program ImageJ (http://rsbweb.nih.gov/ij/). They were

subsequently dried in an oven at 60 C for 5 days and then weighed to the nearest 0.001 mg. We fitted linear (y=ax+b), exponential (y=aebx), and power (y=axb) models to the data, where y equals dry body mass, x is abdomen length, and a,b are the model coefficients. The power model had the best fit (y = 2.587132 x-1.67867; r2=0.935, Figure 3), which is consistent with previous findings (Rogers et al., 1976; Caruso & Migliorini, 2009). We fitted the power model to all collected spiders that had not been dissected for identification purposes and that had intact abdomens (n=2344, 83% of the specimens collected).

Statistical Analysis

To examine the effects of simulated shrub encroachment on spider abundances over the season, we analyzed the data using a repeated-measures ANOVA with abundance as the response variable, treatment as the between-site factor and date as the within-site factor.

Although abundance data appeared to meet the assumptions of ANOVA (Appendix, Table 1), sample sizes (n=6/day) were too small to adequately test for normality. As a result, we also analyzed abundance data using the nonparametric Wilcoxon rank-sum test to measure between- treatment differences in abundances on each sampling day. Total community abundances and generic abundances were examined in this way. All analyses were done in R, version 2.12.1

(http://cran.r-project.org/)

The impact of increased winter snow cover on spider community structure was assessed by creating Bray-Curtis dissimilarity matrices for each sampling day and using the ANOSIM

(Analysis of Similarity; Clarke, 1993) procedure to calculate the standardized mean rank difference of between-treatment and within-treatment compositional variation:

where rb is the mean rank of between-treatment dissimilarities, rw is the mean rank of within- treatment dissimilarities, and n is the number plots. When R is close to 0, mean between- treatment dissimilarity is equal to mean within-treatment dissimilarity, suggesting that treatment level does not explain compositional variation between plots; an R approaching 1 suggests that treatment groups differ substantially in terms of species structure (R values of -1 are not readily interpretable). The statistical significance of the observed R was determined by its position in the distribution of a set of R values obtained after randomly permuting group membership (n=999).

Further, we calculated the Similarity Percentages (SIMPER; Clark 1993) of each genera to determine their relative contribution to the overall dissimilarity scores. To complement this analysis, we also performed two separate repeated-measures ANOVAs, testing for an effect of treatment on generic richness and Simpson diversity score over the season.

Finally, the effect of simulated winter shrub cover on spider mass was analyzed using a repeated-measures ANOVA (omitting the first and last day of sampling due to zero catches in some plots on those days) as well as separate one-way ANOVAs on the square-root transformed mass data for each sampling day (using all data). In some cases normality was still violated despite the transformation, so we repeated the one-way analysis with Wilcoxon rank-sum tests.

Analyses were performed on both pooled mass data and generic mass data.

Results

Our catches from the small-scale trench experiment (Figure 4) largely validated our use of trenches to isolate plots, with spider catch numbers in the ‘tight’ traps significantly lower than those of ‘open’ traps (p<0.01) for both the 3-day and 5-day trapping period. Nevertheless, since

trenches did not perfectly exclude spiders from the sampling plots, late-season findings should be treated with caution.

We captured a total of 2811 adult and penultimate spiders over the season from approximately 10 genera (Table 1). Spiders from the genus Pardosa (Lycosidae) were by far the most common, accounting for 73.6% of all individuals caught, followed by Xysticus

(Thomisidae) at 7.2%. Pooled spider abundance did not vary considerably between plots on sampling days, but did vary over the season (Figure 5), with the highest abundance achieved in both late-melt and control plots on July 5th (Day 186), around the same time tundra bird hatchlings were first observed in the area. At the genus level, abundance also varied with time for most groups (Appendix, Table 2), except for Pardosa (Lycosidae), Allomenga (Linyphiidae), and Erigone (Linyphiidae), which maintained consistent abundance levels throughout the season

(high, low, and low, respectively). Further, except for Allomenga (Linyphiidae), which showed a weakly significant response to increased winter snow cover (p=0.09), treatment did not affect generic abundance patterns (Appendix, Table 2). These patterns were supported by separate

Wilcoxon rank-sum tests (Appendix, Table 3).

Generic richness was highest early in the season and declined by more than half within a month of sampling (Appendix, Figure 2 & 3). This was likely a result of our intensive sampling effort, which would have quickly removed rare species from the plots. While community composition changed over time, it largely did not vary by treatment, as only a single day (June

19th) had an R value statistically different from zero (Figure 6). Similarity percentages analysis

(SIMPER) indicated that what differences there were in community composition were driven largely by the relative abundance of members of Pardosa (Appendix, Table 4). The lack of compositional differences between treatment groups found by the ANOSIM was supported by our repeated-measures ANOVAs on generic richness and Simpson diversity.

Individual spider body mass showed a bimodal distribution, peaking between June 19th and July 5th and then rising again between August 7th and August 21st (Figure 7). Repeated- measures ANOVA on the full spider community data suggested a significant effect of date on body mass (p<<0.01), but showed no significant effect of treatment (p=0.45). A similar pattern was found when spider mass was analyzed by genus, the only exception being Pardosa, which displayed a weak effect of treatment between sites and a weakly significant interaction between date and treatment within sites (Table 2). Subsequent one-way ANOVAs found a significant effect of treatment for Pardosa beginning after snow-melt and lasting until mid-summer (Figure

8, Table 3). These findings are further supported by a set of Wilcoxon rank-sum tests (Appendix,

Table 5).

Discussion

A delay in spring snow melt and an increase in winter snow cover did not affect short- term patterns of abundance in the heath tundra spider communities we examined. The only exception was prior to formal collections, during the approximately 14 day interval between control versus treatment melt dates, in which low numbers of spiders and other arthropods were observed (but not collected) on control sites whereas no specimens were found on the snow- covered fenced sites. From the perspective of spiders as a food source, this suggests that shrub encroachment could reduce resource availability to migrant bird species, which may arrive on breeding or spring staging grounds prior to complete snow melt in shrub dominated sites (Baker,

1977; Klaassen et al., 2006; Vagvari et al., 2009). Since many Arctic bird species are not capital breeders (Klaassen et al., 2001), the lack of tundra arthropod activity on late-melt plots could

lead to lower reproductive success in species which do not shift their phenologies (Møller et al.,

2008). Further, the delay in melt dates of patches on a landscape undergoing shrub expansion could focus bird foraging efforts onto early melting patches, potentially resulting in increased competition for resources as well as asymmetric predation pressures on arthropod communities in invaded versus non-invaded sites.

It is possible that our catch numbers were influenced by environmental conditions from the previous year’s growing season. The year 2009 was an unusually late year in terms of snow melt (mid-June near our focal plots) and thus spiders alive in that year (i.e.: the majority of our specimens) may have been ‘pre-programmed’ to emerge later in all sites. This would partly explain the consistent catch numbers in the middle to late parts of the summer, but it is difficult to see how it would account for the aforementioned ‘early’ emergence of spiders on the control plots. Further, the high inter-annual climatic variability of the Arctic implies that the conditions of one year do not necessarily predict those of the following year, so a simple pre-programmed emergence strategy would not be optimal for arthropod survival (Danks 1999). Moreover, since spider emergence timing appears to be at least somewhat flexible to local environmental conditions (Gertsch, 1979), it is doubtful that the lack of abundance differences between treatments was merely an artefact of last year`s season.

Generic richness and community structure were also unaffected by our simulated shrub treatment, consistent with the notion that landscape factors, such as summer vegetation cover, are the primary drivers of spider diversity in northern ecosystems (Hatley & MacMahon, 1980;

Bowden & Buddle, 2010). Because our collections were intermittent, rather than continuous, it is possible that we missed short-term differences in community structure brought on by genera- specific responses of emergence times to snow conditions. Given that diversity and sampling effort were highest at the start of the season, however, such differences would have had to have

been quite subtle and likely of little ecological significance both for the spider communities and the systems with which they interact. A second concern is that the low taxonomic resolution in our study may have masked compositional differences between plots. We suggest that the extremely low diversity of Arctic spider assemblages (Danks, 1981; Marusik & Koponen, 2005) and our singular habitat focus meant that generic richness was a close approximation to true species richness; nevertheless, in light of the potential for cryptic diversity in spider clades

(Barrett & Hebert, 2005), our community-level findings should be treated carefully and be considered chiefly as a comparison similar to functional diversity. It is also worth noting that early snow melt treatments in temperate and alpine systems, which have considered systems at coarser taxonomic and temporal scales, have found quantifiable differences in arthropod community structure (Dollery & Hodkinson, 2006; Hågvar & Klanderud, 2009; for spiders see

Schmidt et al., 2008), which suggests that our genera-level approach may have some merit.

The dominance of Pardosa in the heath tundra communities is consistent with prior collections around Hudson`s Bay (Koponen, 1992; Pickavance, 2009) and around other low

Arctic sites (MacLean & Pitelka, 1971; Danks 1981; Bowden & Buddle, 2010). In our case, the exceptionally high relative abundance numbers of the genus may have been a product of its active foraging strategy combined with our passive (pitfall) trapping methods. Pardosa members are polyphagous predators, feeding on the collembolans, mites, and other spiders they encounter as they wander along the tundra. Other spider taxa, such as Sitticus (Salticidae) are less locomotory, relying on ambush strategies or line-trapping, and thus may be biased against in terms of capture numbers. From an ecosystem functioning perspective, however, such a bias may not be especially problematic, since it is likely that foraging birds feed more often on mobile – and thus highly visible – arthropods. Consequently, while our data might not reflect the precise

composition of Arctic spider communities, they are probably representative of the Araneae contributions to the Arctic food web.

Of all the factors considered in our analysis, Pardosa body mass was the only one that appeared to differ consistently between treatment groups. We assert that this difference was probably not a result of the 14 day interval between snow melt dates since recent work on the species Pardosa glacialis suggests that differences in snow melt date alone tend to affect biomass in the opposite direction of our results (Høye et al., 2009). Nevertheless, we must point out that air temperatures were quite low (x =-0.23 C) across the study site during the 14 day period between control and treatment plot melt dates, and since temperature and moisture strongly influence both activity and development in spiders (Gunnarsson & Johnsson, 1990;

DeVito et al., 2004), it is conceivable that these conditions may have hindered early-emerging individuals. Such a period of non-optimal growing conditions following snow melt has been found in Arctic and alpine plants communities (Steltzer et al., 2009; Wipf, 2009) and indirectly in high Arctic arthropods (Meltofte et al., 2007; Høye & Forchhammer, 2008). Our mass findings could be evidence that this kind of post-melt latency period may also exist for low

Arctic spiders. Given that 2010 was an average year in terms of snow fall and spring air temperatures in Churchill (Appendix, Figure 4), it may also be relatively common for sites like ours.

Although we did not control for melt date in this experiment, we were lucky to achieve near synchronous melt dates for both our control and treatment plots, despite differences in winter snow cover. This afforded us the opportunity to examine how body mass scaled with winter snow depths, irrespective of melt date. The relatively strong relationship between Pardosa mass and winter snow depth (r2=0.73, Figure 9) lends further support to our contention that the

14-day latency period was not the primary driver of mass differences between individuals.

We suggest, rather, that the increased winter snow cover of simulated shrub sites combined with the overwintering behaviour of Pardosa juveniles/adults is the most likely explanation for the observed mass differences between plot types. Indeed, although activity is certainly reduced in spiders during the winter months, there is evidence that some spiders actively hunt during this period and can feed at temperatures as low as -2 C (Norberg, 1978;

Aitchison, 1984; Gunnarsson, 1988). It is not known whether the Pardosa in our study are winter-active, but as a group they are highly cold-tolerant (Duman et al. 2004; Murphy 2008) and will hunt during the winter in more temperate zones (Edgar & Loenen, 1974; Norberg, 1978).

Given the insulating effect of snow, it is therefore possible that the increased snowpack brought on by the fences improved subnivean conditions during the winter and enabled the spiders to feed more often than their counterparts in the control plots. If this is true, than Pardosa must not have been feeding on other spiders, since abundance levels in all other spider genera were similar between treatment groups in the spring. They would likely have been feeding on other arthropods, such as mites (Acari) and springtails (Collembola), which have also been found to be active beneath the snow (Merriam et al., 1983) and would probably respond to warmer subnivean temperatures (Sturm et al. 2005) with increased activity. A parallel explanation for the observed differences in body mass is that the improved winter conditions simply reduced energy loss in spiders, with little to no effect on winter activity, but given that metabolism scales with temperature in ectotherms, it is questionable whether warmer temperatures alone would have been advantageous for retaining energy reserves.

It remains an open question why the differences in Pardosa biomass disappeared in the middle of the season, but it could reflect the leakiness of our trenches or be a by-product of declining environmental conditions as the growing season progressed. Since the drop in body mass occurred following the average hatch dates of many Arctic tundra birds, it also possible that

size-selective grazing by hatchlings may have severely reduced the abundances of the most massive spiders. Lastly, it could reflect a synchronous egg-laying period, which would have effectively ‘reset’ the mass of the females in our plots. Our limited observations of egg numbers during the summer supports this notion, insofar as eggs were found only in July and primarily following the peak in spider biomass on July 5th (unfortunately, eggs were not collected in sufficient numbers to include them in the analysis). It would be have been interesting to examine whether spiders from the late-melt plots had higher reproductive success, as one might predict based on body size differences (Gunnarsson, 1988; Simpson, 1993) particularly since if reproductive success differed between plots, we might expect to see more long-term changes in abundance and diversity as a result of increased shrub growth.

This study, which to our knowledge is the first macro-scale experimental test of the impact of increased winter snow cover on arthropod activity, demonstrated that the abundance and diversity of Arctic spider communities was largely unaffected by the type of landscape-level changes one would expect under increased shrub growth. Interestingly, simulated winter shrub cover did produce a significant difference in the body mass of the dominant spider genus,

Pardosa, likely as a result of facilitating winter feeding activities. Insofar as spiders are significant arthropod predators in tundra systems and also serve as a significant food source for birds and amphibians, the effect of shrub-induced changes to snow cover on spider biomass could have cascading effects on other aspects of low Arctic ecosystems.

(a)

(b)

Figure 1. (a) Picture of a snow fence and the accumulated snow cover (January 2010); (b) Representative heath plot with trenches dug for excluding surface arthropods. 20

Figure 2. Aerial view (partial) of the study site. The perimeter of plots are marked with rectangles (black=treatment, white=control). 21

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5 Ln Body Mass (mg) BodyMass Ln -1.0

-1.5

-2.0

-2.5

-3.0

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Ln Abdomen Length (mm)

Figure 3. Relationship between (log) spider body mass and (log) abdomen length from a season- wide sampling effort in 2009 (n=106, r2=0.935). Based on the strength of the relationship, we used the following equation to estimate body mass, y, in our 2010 specimens using abdomen length, x: y = 2.587132 x-1.67867 . 22

3.5 (a) A

3.0

2.5

AB 2.0

1.5 SpiderCatch

1.0 B

0.5

0.0

Control Tight Wide

Trench Treatment

9 (b) A 8 A

SpiderCatch B 3

Control Tight Wide

Trench Treatment Figure 4. Effectiveness of small-scale trenches at excluding spiders. (a) Mean spider catches from the 1-day small-scale trench experiment (May 31st 2010), +/- standard error. Control-Tight catch differences were strongly significant (ANOVA, p<0.01) and Control-Wide catch differences were weakly significant (ANOVA, p=0.16). (b) Mean spider catches from the 5-day small-scale trench experiment (August 11th 2010), +/- standard error. Control-Tight and Tight- Wide catch differences were significant (ANOVA, p=0.08 for both). 23

70 Control Late-melt 60

40 SpiderCatch 30

158 168 178 188 198 208 218 228

Day of Year

Figure 5. Daily abundances of spiders over the season by treatment. Points represent the mean, +/- standard error, beginning on June 7th (Day 158) and ending on August 21st (Day 233) 2010. 24

0.4 Within < Between

* 0.3

0.2

0.1 R valueR

0.0 No difference

-0.1

Within > Between -0.2

158 168 178 188 198 208 218 228

Day of Year

Figure 6. ANOSIM comparison of spider communities from control versus treatment plots over the season. R values close to zero indicate small differences in the mean rank of Bray-Curtis dissimilarity scores. Except for June 19th (Day 170 – denoted by *), community composition did not differ significantly between treatment groups (ANOSIM, p>0.05). 25

4.5

4.0 *

3.5

3.0

* Individualbiomass(mg) spider

2.5 Control Late-melt

2.0

158 168 178 188 198 208 218 228

Day of Year

Figure 7. Penultimate and adult spider masses over the season by treatment. Points represent the mean individual mass of spiders from a given treatment collected during the sampling day, +/- standard error. Asterisks (*) indicate significant difference between treatments (ANOVA, p<0.05). 26

4.75

* 4.25

* *

3.75

3.25 *

2.75 Individualbiomass(mg) spider

Control 2.25 Late-melt

1.75

158 168 178 188 198 208 218 228

Day of Year

Figure 8. Pardosa mass over the season by treatment. Points represent the (square-root) mean individual masses, +/- standard error. Asterisks (*) indicate significant differences between treatments (ANOVA, p<0.05). 27

6.0

5.5

5.0

4.5

4.0

3.5 Pardosa mass (mg) Pardosamass

3.0 Control Late-melt 2.5

2.0

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Winter snow depth (cm)

Figure 9. Pardosa peak mass by late winter snow depths. Points represent site means of individual spider masses obtained on July 5th according to site-specific snow depths, measured on April 23rd, close to the end of winter (r2=0.73), +/- standard error. 28

Table 1. Season-wide catches of spider genera on tundra heath sites. Genera with fewer than 2 individuals and specimens that could not be identified (n=52, 0.02%) were not included in the analysis.

Family Genus Ambient Late-melt (control) (treatment)

Clubionidae Clubiona 17 18

Gnaphosidae Zelotes 47 58

Linyphiidae Allomenga 5 17 Erigone 23 31

Lycosidae Alopecosa 22 16 Arctosa 21 32 Pardosa 1059 1010

Philodromidae Thanatus 61 53

Salticidae Sitticus 75 43

Thomisidae Xysticus 97 106

TOTAL 1427 1384 29

Table 2. Repeated-measures ANOVA table for comparison of Pardosa body mass (site means). Due to unbalanced data, it was necessary to remove a replicate from each of the treatment groups and restrict our analysis to Days 158-219. P values near 0.05 (bolded) indicate a significant effect of the associated factor on mean body mass.

Factor Df SS Mean SS F statistic P value Between Sites Treatment 1 0.16471 0.164711 2.8134 0.132 Residuals 8 0.46837 0.058546

Within Sites Date 8 1.89050 0.236313 9.1637 <<0.001 Date*Treatment 8 0.37224 0.046530 1.8043 0.0925 Residuals 64 1.65042 0.025788 30

Table 3. Analysis of variance (ANOVA) comparison of spider masses by genera over the season. Numbers (p-values) near 0.05 (bolded) indicate significant differences in mass between treatments for the genus on a particular day.

Day of Year Family Genus 158 164 170 175 186 196 201 210 219 233 Clubionidae Clubiona 0.79 0.06 0.48 0.21 0.13 0.30 0.80 0.64 - 0.86 Gnaphosidae Zelotes 0.16 0.36 0.10 0.76 0.13 - 0.04 0.91 0.43 0.20 Linyphiidae Erigone - 0.88 - - - - 0.77 - - - Alopecos Lycosidae a - - 0.89 ------Arctosa - 0.20 0.73 0.82 0.31 0.71 0.07 0.79 0.39 - Pardosa <0.01 0.37 <0.01 0.06 <0.01 0.50 0.61 0.33 0.74 0.83 Philodromidae Thanatus - 0.70 0.57 0.85 0.88 - 0.71 0.05 0.35 0.67 Salticidae Sitticus - 0.22 - - - - 0.96 0.71 0.88 - Thomisidae Xysticus 0.26 0.10 - 0.73 0.15 0.28 0.51 0.69 0.46 0.24 All genera 0.05 0.88 0.23 0.36 0.01 0.11 0.96 0.86 0.82 0.75 31

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Appendix 1: Supplementary Figures and Tables

10 AirTemperature (C)

Control Late-melt 5

158 168 178 188 198 208 218 228

Day of Year

Control

SurfaceTemperature (C) Late-melt 5

158 168 178 188 198 208 218 228

Day of Year

Appendix Figure 1. (a) Average air temperatures over the season by treatment (b) Average surface temperatures over the season by treatment. 40

4 Generic Richness Generic

2 Jun 7 Jun 13 Jun 24 Aug 7 0

1 2 3 4 5 6 7 8 9 10

Number of traps

Appendix Figure 2. Genera accumulation curves for a single plot on 4 of the 10 sampling days. Except for the points lacking error bars (which reflect actual richness achieved during sampling), each point represents the generic richness that would have been achieved at a particular sampling effort, based on randomized permutations, +/- standard deviation. 41

8 Control Late-melt

4 Generic Richness Generic

158 168 178 188 198 208 218 228

Day of Year

Appendix Figure 3. Generic richness over the season by treatment group. Although diversity did change over the season, there was no significant effect of treatment group on either richness or Simpson diversity score (p=0.84, p=0.49). 42

-2

-4 Air Temperature (C) Temperature Air

-6

-8

1945 1955 1965 1975 1985 1995 2005

Year

Appendix Figure 4. May air temperatures for Churchill, Manitoba from 1945-2010. Points represent the average for the month and the dashed line is the 65 year average. Data from National Climate Data and Information Archive (Environment Canada). 43

Appendix Table 1. Shapiro-Wilk normality scores for daily spider abundances by treatment. Numbers (p-values) near 0.05 (bolded) are indicative of violations of normality; however, due to the small sample sizes (n=6), positive results are not necessarily a sufficient condition for meeting the assumptions of ANOVA.

Day Treatment Shapiro-Wilk (p-value) 158 Control 0.28 Late-melt 0.15 164 Control 0.86 Late-melt 0.59 170 Control 0.07 Late-melt 0.30 175 Control 0.54 Late-melt 0.26 186 Control 0.32 Late-melt 0.66 196 Control 0.06 Late-melt 0.25 201 Late-melt 0.60 Control 0.50 210 Late-melt 0.19 Control 0.64 219 Late-melt 0.87 Control 0.16 233 Late-melt 0.46 Control 0.51 44

Appendix Table 2. Results of repeated-measures ANOVAs on seasonal spider abundances by genera. Numbers (p-values) near 0.05 (bolded) indicate a significant effect of the column sub- heading on abundance.

Family Genus ANOVA (p-values) Treatmen Between-site t Clubionidae Clubiona 0.79 Gnaphosidae Zelotes 0.52 Allomeng Linyphiidae a 0.09 Erigone 0.41 Lycosidae Alopecosa 0.59 Arctosa 0.30 Pardosa 0.74 Philodromidae Thanatus 0.58 Salticidae Sitticus 0.31 Thomisidae Xysticus 0.72 All genera (pooled) 0.79

Treatment:Date Within-site Date * Clubionidae Clubiona <0.01 0.88 Gnaphosidae Zelotes 0.01 0.22 Allomeng Linyphiidae a 0.59 0.76 Erigone 0.94 0.35 Lycosidae Alopecosa 0.01 0.52 Arctosa <0.01 0.68 Pardosa 0.13 0.77 Philodromidae Thanatus <0.01 0.60 Salticidae Sitticus 0.08 0.40 Thomisidae Xysticus <0.01 0.51 All genera (pooled) <0.01 0.83 *Interaction term 45

Appendix Table 3. Results of Wilcoxon rank-sum tests on seasonal spider abundances by genera. Numbers (p-values) near 0.05 (bolded) indicate significant differences in abundance between treatment groups.

Family Genus Day of Year 158 164 170 175 186 196 201 210 219 233 Clubionidae Clubiona 1.00 1.00 0.59 0.92 0.40 0.40 0.40 1.00 0.40 0.40 Gnaphosidae Zelotes 0.26 0.86 0.61 0.25 0.32 - 0.79 0.01 0.92 0.64 Linyphiidae Erigone 0.40 0.10 1.00 0.40 0.80 0.40 0.66 0.34 0.86 - Allomeng a 0.67 1.00 - 0.40 0.40 0.18 0.40 0.07 - 0.17 Lycosidae Pardosa 0.13 0.69 0.37 0.87 0.34 0.69 0.13 0.81 0.11 1.00 Arctosa 0.52 1.00 0.17 0.20 - 0.40 0.66 0.53 - 0.40 Alopecosa 1.00 0.46 0.21 0.40 - - - - 0.11 0.40 Philodromidae Thanatus 0.42 0.51 0.43 0.93 0.22 - 1.00 0.34 0.52 0.40 Salticidae Sitticus 0.40 0.30 0.09 - 0.07 0.40 0.44 0.87 0.65 0.40 Thomisidae Xysticus 1.00 0.74 1.00 0.68 0.25 0.72 0.87 1.00 0.50 0.72 All genera (pooled) 0.94 0.70 0.94 1.00 0.70 1.00 0.70 0.70 1.00 1.00 46

Appendix Table 4. Similarity percentages analysis (SIMPER) of the sampled spider communities. Numbers represent the average relative contribution (%) of each genus to the between-treatment Bray-Curtis dissimilarity scores on each day. Pardosa had the highest relative contribution to the dissimilarity scores over the entire season, meaning it was the principle driver of compositional differences between treatment groups.

Day of Year Family Genus 158 164 170 175 186 196 201 210 219 233 Clubonidae Clubiona 7 3 3 5 - 2 1 2 1 2 Gnaphosidae Zelotes 11 6 13 5 7 - 9 9 5 8 Allomeng Linyphiidae a 4 2 - 1 1 6 1 4 - 5 Erigone 1 5 3 1 5 3 6 4 6 - Lycosidae Alopecosa 2 9 8 1 - - - - 5 5 Arctosa 5 6 3 7 - 3 6 3 - 2 Pardosa 47 32 49 59 67 71 52 50 58 59 Philodromidae Thanatus 9 8 7 11 7 - 6 5 6 2 Salticidae Sitticus 1 19 9 - 6 3 8 14 10 3 Thomisidae Xysticus 13 10 5 10 7 12 12 9 9 14 47

Appendix Table 5. Results of Wilcoxon rank-sum tests on seasonal spider masses by genera. Numbers (p-values) near 0.05 (bolded) indicate significant differences in mass between treatments.

Day of Year Family Genus 158 164 170 175 186 196 201 210 219 233 Clubionidae Clubiona 0.63 0.33 0.61 0.47 0.57 0.71 0.61 1.00 - 1.00 Gnaphosidae Zelotes 0.46 0.46 0.51 1.00 0.35 - 0.14 0.95 0.54 0.81 Linyphiidae Arctosa - 0.52 1.00 0.97 0.60 1.00 0.47 1.00 0.64 - Lycosidae Erigone - 1.00 - - - - 1.00 - - - Pardosa 0.03 0.88 0.19 0.11 0.01 0.76 0.66 0.60 1.00 0.78 Alopecosa - - 1.00 ------Philodromidae Thanatus - 0.75 0.79 0.82 0.70 - 0.88 0.30 0.55 1.00 Salticidae Sitticus - 0.50 - - - - 0.86 0.83 1.00 - Thomisidae Xysticus 0.95 0.61 - 0.87 0.72 0.85 1.00 0.67 0.61 0.47 All genera 0.02 0.68 0.27 0.04 <0.01 0.15 0.92 0.98 0.85 0.48