Sean Higgins

ABSTRACT

Web spider diversity in the riparian forests of southwest Ohio

by Terrence Sean Higgins

Riparian forests are often the primary source of forest habitat in agricultural landscapes. I assessed the diversity of web spiders in riparian forests and hedgerows of SW Ohio. Samples were taken at the stream edge, in the center, and at the agricultural edge of riparian forests of three width classes (thin: 15-30m, medium: 45-60m, wide: >80m). Rarefaction and ANOVA compared diversity among forest types, and among the agriculture edge, center and stream edge. Detrended Correspondence Analysis compared the species assemblages among samples. Web spiders were significantly more diverse in riparian forests than in hedgerows. Thin riparian forests were most diverse of all forest types. While stream edges had the lowest diversity, their assemblages were distinct from other quadrats. My data suggest that the stream habitat plays a key role in structuring the adjacent terrestrial spider community, and that riparian forest corridors are important to regional spider diversity in agricultural landscapes. WEB SPIDER DIVERSITY IN RIPARIAN FORESTS

OF SOUTHWEST OHIO

A Thesis

Submitted to the

Faculty of Miami University

in partial fulfillment of

the requirements for the degree of

Master of Science

Terrence Sean Higgins

Miami University

Oxford, Ohio

2003

Advisor: Dr. Ann Rypstra

Reader: Dr. Tom Crist TABLE OF CONTENTS

TABLE OF CONTENTS…………………………………………………………… ii LIST OF TABLES………………………………………………………………….. iii LIST OF FIGURES………………………………………………………………… iv ACKNOWLEDGEMENTS………………………………………………………… vii CHAPTER 1………………………………………………………………………... 1 CHAPTER 2: INTRODUCTION………………………………………………….. 8 METHODS………………………………………………...... 10 RESULTS…………………………………………………………... 14 DISCUSSION………………………………………………………. 16 CHAPTER 3: INTRODUCTION………………………………………………….. 30 METHODS…………………………………………………………. 31 RESULTS………………………………………………………….. 35 DISCUSSION……………………………………………………… 37 LITERATURE CITED……………………………………………………………... 52

ii LIST OF TABLES

CHAPTER 2

Table 1 Spider families and species collected by quadrat type in riparian forests near Oxford, Ohio in August 2002…………………………… 26 Table 2 Results of ANOVA on web spider richness, abundance, Simpson diversity, and Shannon diversity in 5 x 10-m quadrats placed at the agriculture edge, forest center, and stream within replicated thin, medium and wide riparian forests…………………………………… 27 Table 3 Mean (± SE) abundance, species richness, Shannon diversity, and Simpson diversity of web spiders collected in riparian forests by landscape treatment (thin, medium, wide) and quadrat (agriculture edge, center, stream)………………………………………………… 28 Table 4 Mean (± SE) vegetation structure values as measured in riparian forests by landscape treatment (thin, medium, wide) and quadrat (agriculture edge, center, stream).……………………….……………. 29

CHAPTER 3 Table 1 Spider families, species, and relative abundance collected from riparian forests and hedgerows near Oxford, Ohio…………………… 47 Table 2 Mean (± SE) number of web spiders and species collected in riparian forests and hedgerow forests.…...... 48 Table 3 Repeated-measures ANOVAs for web spider abundance (ln) and richness………………………………………………………………. 49 Table 4 Summary of vegetation structure results from 2-factor ANOVAs……………………………………………………………... 50 Table 5 Mean (± SE) vegetation structure values as measured in riparian forests and hedgerows by quadrat type.………………………………. 51

iii LIST OF FIGURES

CHAPTER 2

Figure 1 The three major types of riparian forest habitat as designated by width, from the stream to the agricultural edge. Placements of the 5 x 10-m quadrats within each site are marked X…………………………………… 22 Figure 2 Species accumulation curves (±1 SD) for predicted spider species richness in riparian forests of three width treatments (thin, medium, and wide)…………………………………………………………… 23 Figure 3 Species accumulation curves (±1 SD) for predicted species richness at three quadrat locations (agriculture edge, center, stream) in riparian forests…………………………………………………………………. 24 Figure 4 DCA ordination of web spider species abundances collected from 18 quadrats.………………………………...... 25

CHAPTER 3 Figure 1 Riparian forest sites compared with hedgerow sites of similar width. Locations of the 5 x 10-m quadrats are marked X……………….. 42 Figure 2 Means (± 1 standard error) of web spider abundance and species richness from quadrats sampled within hedgerow forests and riparian forests………………………………………………………………. 43 Figure 3 Species accumulation curves (±1 SD) for predicted spider species richness in riparian forests and hedgerow…………………………. 44 Figure 4 Species accumulation curves (±1 SD) for predicted spider species richness in the edge and center quadrats of riparian forests and hedgerows………………………………………………………… 45 Figure 5 DCA ordination analysis of web spider species collected from 18 quadrats during the August sampling period.………………………. 46

iv ACKNOWLEDGEMENTS

This research was made possible by private land owners all over Butler County, Ohio who granted full access to their forests, spiders, and fields for the purpose of ecology research. I thank Dr. Rypstra, Dr. Crist, Dr. Schaefer, Dr. Claussen, Dr. Buddle, Dr. Walker, Dr. Veech, D. Mefford, K. Sigler, and The Spider Lab of Miami University for their contributions to this work. Special thanks to the staff of the Hefner Zoology Museum Staff, The Spider Lab, Miami ecology professors, and fellow graduate students for enlightening my outlook on science and nature throughout the course of this study. Finally, thanks to my friends, family, and Karen for their infinite support.

v WEB SPIDER DIVERSITY IN RIPARIAN FORESTS

OF SOUTHWEST OHIO

Chapter 1: Biological Conservation in Riparian Forests Biological Diversity Biological diversity, or biodiversity is variety in life. It can be measured at many scales of organization including the molecular level, the level of individual species, and the level of whole landscapes (Wilson 1992). Human alteration of the earth continues to cause an overall decrease in biodiversity, including loss of genetic diversity within populations, extinction of whole species, and homogenization of landscapes (Vitousek et al. 1997). Motives for biodiversity conservation include potential economic value derived from plants and animals, aesthetic and research value of species, and moral obligation to minimize species loss (Wilson 1992). Still, the majority of efforts to preserve biodiversity act at the level of conserving species (Folke et al. 1996). Loss of biodiversity includes more than just extinction of species; it includes changes in species composition, ecosystems, and landscapes that are caused by human development (Folke et al. 1996). For these reasons, further biodiversity conservation and research should focus at the level of species assemblages and communities.

Landscape Arrangement and Biological Diversity The types and arrangement of habitat within a landscape affect biodiversity (Forman 1995). A landscape is generally defined as a kilometers-wide area of land, which encompasses a number of reoccurring local ecosystems (Forman 1995). MacArthur and Wilson (1967) advanced community ecology when they suggested that populations of species would go extinct in isolated islands in the absence of recolonization. Their island biogeography theory was later used to show how species richness varies among habitat patches that differ in size and isolation in fragmented landscapes. As landscape ecology emerged, it brought about an increased awareness of the importance of the spatial arrangement of habitats. Ecologists recognize that patches in fragmented landscapes are heterogeneous. Physical factors, including amount of sunlight, moisture, and temperature, can cause

1 variation in species assemblages within habitat patches (Forman 1995). Edges of habitat patches tend to have high biodiversity, due in part to the mixing of species from two adjacent habitats (Cadenasso and Pickett 2001). Dispersing organisms may also be more likely to encounter edge habitat (Fahrig and Paloheimo 1987). These factors cause habitat heterogeneity which influences overall biodiversity. The size of a habitat patch can affect its heterogeneity. Smaller habitat fragments tend to have higher species density (number of species per unit area), because of a greater edge to total area ratio (Palmer 1994). However, larger habitat fragments are likely to include higher numbers of species than smaller fragments because they comprise more total area (Forman 1995). Interior species, those found in the center of habitat patches, are also more likely to occur in larger habitat patches (Bender et al. 1998). Studies of community composition suggest that there is often a minimum patch size for the presence of certain interior species (Forman 1995). In fragmented landscapes, a disproportionate percentage of interior species tend to be rare (Gaston 1994), and interior species may be clumped into isolated patches (With and Crist 1995). In such cases, fragmentation and smaller habitat patch sizes are likely to cause loss in biodiversity through the extinction of rare species (Kruess and Tscharntke 1994, Golden and Crist 1999, Tscharntke et al. 2001). Landscape arrangement and fragmentation may disproportionately affect rates of predation and parasitism and the spread of invasive species (Kruess and Tscharntke 1994, Sakai et al. 2001). These results can alter ecosystem functioning by increasing herbivory, decreasing rates of primary productivity, and altering the flux of nutrients. In agricultural areas, landscapes may be fragmented to the point of extinguishing whole landscape features, leading to widespread loss of biodiversity (Tscharntke et al. 2002).

Riparian Forests Riparian forests are forests adjacent to waterways. They are vital ecotones, important in the functioning of both aquatic and terrestrial ecosystems. Deforestation of the riparian forest alters community and ecosystem functioning of aquatic systems by degrading water quality, altering physical and chemical features of streams, and affecting the biological diversity, abundance, and health of aquatic organisms (Lachavanne 1997,

2 Jones et al. 1999, Verry et al. 2000). Riparian forests prevent soil erosion and stream sedimentation, provide sources of nutrients in the form of organic matter to streams, and provide shade from sunlight which maintains water temperatures (Naiman et al. 1993). Because of these services to aquatic systems, many states prohibit land use in riparian forests within a specified width, referred to as the riparian buffer zone (Naiman and Decamps 1997, Verry 2000). In other cases, Federal and State governments encourage landowners to preserve and restore riparian buffers by offering monetary compensation (Verry 2000). In Ohio, the Conservation Reserve Enhancement Program of the U.S. Department of Agriculture awards land owners payments for riparian area preservation through annual land rental payments, land maintenance payments, and cost-share assistance payments for restoration (Farm Service Agency, 2000, http://www.fsa.usda.gov). Basynat et al.(1999) assigned economic value to riparian forest buffers, primarily on the basis of riparian ability to reduce nitrogen loads and other non-point-source pollution into waterways. Still, their study neglected to account for the value of riparian forests to terrestrial biological diversity. Riparian forests are among the most biologically diverse systems on earth (Lachavanne and Juge 1997). The majority of riparian forest biodiversity studies pertain to plants and birds. Knopf et al. (1988) stated that in western North America, less than 1 % of the total landscape is riparian habitat, yet it provides habitat for more species of birds than all other habitats combined. More than 70% of all vertebrates use riparian corridors at some point during their life cycles (Naiman et al.1993). A contributing factor to the high diversity of riparian forests may be the exchange of nutrients between the stream and the terrestrial environment (Nakano and Murakami 2001). Still, biodiversity of invertebrates in riparian forests is understudied compared to vertebrates (Naiman and Decamps 1997). Thin, continuous patches of habitat are typical of riparian corridors and hedgerows (Forman 1995). Corridors adjacent to agriculture fields potentially benefit crop productivity by providing refuge for predators of insect pests, including spiders (Price 1980). In many agricultural areas including southwest Ohio, riparian corridors are a primary source of forest habitat (Medley et a. 1995). Adding width to riparian forests increases the species richness of forest interior plants (Forman and Baudry 1984, Forman

3 1995), and increases bird species richness and breeding success (Spackman and Hughes 1994, Forman 1995, Maudsley 2000). Riparian forests in the northwest United States may act as corridors for the movement of many vertebrates (Harris 1984). In such instances, wide corridors should promote more movement than thin corridors (Forman 1995). Folke et al. (1996) called for biodiversity conservation in all regional land use practices, rather than simply protecting parks and preserves. Managing riparian forests is one such method of conserving regional biodiversity. More studies are needed to examine the effects of the riparian forest width on terrestrial arthropod biodiversity.

Hedgerows Hedgerows are uncultivated borders separating agriculture fields. Like riparian forests, hedgerows provide habitat for wildlife and may act as a ‘source’ of generalist arthropod predators important to agroecosystems (Forman and Baudry, 1984). However, the forested habitat of hedgerows is not adjacent to a stream which may contribute to have both physical and biological dissimilarity. Understanding differences between hedgerows and riparian forests and their contributions to biodiversity may be important to conservation planning in agricultural landscapes.

Importance of spiders Spiders are the most abundant arthropod predators in many terrestrial systems (Hurd and Fagan, 1992, Wise, 1993). Spider diversity and abundance is important to ecosystem functioning and overall community diversity for a number of reasons. They play an important role in primary productivity since they reduce plant damage from herbivory through limiting the populations of insect prey (Wise 1993, Carter and Rypstra 1995). Studies also indicate that multiple species assemblages of spiders are more effective at limiting prey than is a single spider species (Provencher and Riechert 1994). More predator species lead to the presence of more variation in body sizes and foraging strategies which may increase the probability of prey kill (Riechert and Lockley 1984). Therefore, maintaining species richness of spiders may be an economically important method of pest control.

4 Using particular taxa as a model for investigating community and ecosystem processes is a common practice in ecology. Wise (1993) offered spiders as a model predator because of their abundance, diversity and ubiquity. Predatory arthropods may be particularly likely to decline as a result of fragmentation and declining habitat patch size (Zabel 1998, Ozanne et al. 2000). Ozanne et al. (2000) found significantly greater densities of woodland spiders in 10 ha forest patches than in 1 ha patches. Due to their responses to landscape arrangement, their ecological importance, and their potential as a model, spiders are excellent taxa for investigating the effects of fragmentation in riparian forests on biological diversity.

Measuring Biological Diversity Indices of diversity are numerous and measure distinct patterns pertaining to natural communities. Indices of alpha diversity account for species within a particular site (Magurran 1988). The most common and simple alpha diversity measure is species richness, which simply measures the number of distinct species in a given area. Simpson and Shannon diversity indices, take into account both species richness and the abundance of individuals within each species (Magurran 1988). Rarefaction techniques allow for diversity comparisons among samples while accounting for the possibility of differing sampling efforts (Simberloff 1978). Rarefaction curves are produced through repeated sub-sampling of a species pool and are a useful tool for estimating both alpha diversity and how comprehensively a community may have been sampled (Gotelli and Colwell 2001). Beta-diversity measures changes in species composition between different habitats and/or the changes in species composition along habitat gradients. Beta-diversity distinguishes differences in the species assemblage between two habitats with similar measures of species richness (Magurran 1988). Other measurements of biodiversity center on rarity. Rare species, or species with limited abundance and/or range are often the focus of biodiversity conservation (Gaston 1994, Novotny and Basset 2000). This stems from the general assumption that rarity is a major determinant of a species’ likelihood of extinction (Gaston, 1994). All of the above diversity index categories are useful tools for observing effects of habitat fragmentation on species assemblages.

5 However they are exclusively measures of biodiversity at the level of species and community. Regional biological diversity (i.e. gamma diversity) combines diversity within specific habitats (alpha diversity) and diversity between these habitats (beta diversity) (Magurran 1988). In human dominated landscapes, variety of land uses creates heterogeneous habitat patches. These heterogeneous patches contribute more to regional species diversity than multiple homogenous patches because they consist of distinct biotic communities (Forman 1995). The environmental variables which drive differences in biotic community composition may be difficult to detect (ter Braak 1988). Still, conservation of biological diversity at the regional scale calls for preserving these heterogeneous patches. The ecological technique, ordination, separates biotic communities on the basis of their species composition (ter Braak 1988). When communities are separated by time and/or space, environmental factors among them may vary substantially. Ordination allows ecologists to reveal species specific patterns among communities without measuring these environmental factors (ter Braak 1994). Ordination arranges community level samples along a gradient based on their species occurrences, either by the combined species presence/absence or by their relative abundances. By discerning the types of land use that lead to distinct communities, ordination is a useful tool for determining how organisms are arranged in human dominated landscapes. Conservation of regional biological diversity requires knowledge of biological diversity within and between spatial scales. When assessing biodiversity, it is important to use a variety of indices, as all diversity values describe a small component of the actual community. Although the bulk of biological diversity conservation efforts focus on populations of individual species, there is a growing call to incorporate conservation of biodiversity at the level of functioning landscapes, regions, and functioning ecosystems (Franklin 1993).

Research Objectives In the following chapters, I present results of an investigation of the web spider community in riparian forests of southwest Ohio. In Chapter 2, I explore the effects of

6 riparian forest width on web spider abundance and diversity across transects that run from the stream edge to the agriculture edge. In this way, I can examine possible influence of the stream, the agriculture edge, and forest width on the spider community. In chapter 3, I compare the web spider community of riparian forests to the communities inhabiting hedgerows of similar width. In this way I can explore a differential contribution of hedgerows and riparian forests to web spider diversity in the agricultural landscape.

7 Chapter 2: Riparian forest web spider communities in an agricultural landscape: examining forest width and heterogeneity within the riparian forest

INTRODUCTION In agricultural landscapes, corridors of riparian forest are often the primary sources of forest habitat (Forman 1995). These forests are valuable in maintaining water quality, ecosystem functioning, and biodiversity (Naiman and Decamps 1997, Verry et al. 2000). Riparian forests contain more terrestrial biodiversity than any other habitat type for many taxa including birds and small mammals. (Lachavanne and Juge 1997, Knopf et al. 1998, Darveau et al. 2001). Riparian forest width may be important for conserving species regionally by adding to the amount of overall forest habitat and by influencing terrestrial communities within riparian forest fragments (Naiman et al. 1993, Spackman and Hughes 1995). Examining the communities both within and among riparian forests will help ecologists understand impacts of riparian forest conservation on regional biodiversity. Riparian areas contain the main remnants of forest habitats in much of the Midwestern United States (Naiman et al. 1993). Thus, they may be important habitat refuges for forest species and help to maintain regional diversity. These strips of habitat are heterogeneous because of the high ratio of edge habitat to total area. In addition, the edge consists of two distinct types of edges, one along the stream and one along the adjacent terrestrial habitat. The species assemblages within these habitats may be different from the agriculture edge to the stream (Forman 1995). For example, plant and animal communities within the riparian forest may be influenced by their proximity to the stream as they may be subject to unstable water levels and more humid environments (Naiman and Decamps, 1997), and energy supplements from stream derived sources (Henschel et al. 2001, Bastow et al. 2002, Sabo and Power 2002). The proximity of habitat to the agriculture edge is also a source of heterogeneity that may influence the abundance and diversity of the community (Cadenasso and Pickett 2001, Tscharntke et al. 2002). Organisms at an agriculture edge are exposed to greater degrees of disturbance, complexity in vegetation, and microhabitat variation (Naiman et al. 1993). However, it is unclear what the effects of the stream or agriculture edge are on the

8 diversity of riparian forest organisms or how far into the forest those effects may be evident. Understanding the effects of stream and agriculture edges on communities within riparian forests is important to conserving their biodiversity. Riparian forests vary greatly in width and thus may contain forest habitat with very different biotic communities. Wide riparian forests should contain more forest interior habitat and thus house organisms indigenous to the forest interior that could not survive in narrower strips, which will contribute to greater species diversity in wide sites (Gaston 1994, Bender et al. 1998). Alternatively, thin riparian forests could maintain higher species diversity because they have greater proportion of edge habitat and the influences of the agriculture and stream edge are more likely to extend throughout the forest, which may lead to greater species diversity (Davies et al. 2001). Knowledge of the effects of riparian forest width on terrestrial communities is important to conservation within agricultural landscapes.

Model Taxa This study examined the diversity of web spiders in riparian forests of differing widths. Using particular taxa as a model for investigating community and ecosystem processes is a common practice in ecology (Wise 1993). Web spiders are a good model for this study since they are important in agriculture landscapes as predators of insect pests (Provencher and Riechert 1994, Carter and Rypstra 1995, Halaj et al. 2000), are abundant and diverse (Coddington and Levi 1991, Hurd and Fagan 1992, Wise 1993), and are sensitive to habitat variation and fragmentation (Zabel 1998, Kendi et al. 2000). Recent studies have revealed that streams influence terrestrial communities, including web spiders, in adjacent riparian areas (Henschel et al. 2001, Batow et al.2002, Sanzone et al. 2003). For instance, Sanzone et al. (2003) found that web spiders in riparian habitats derived a large portion of their total energy from stream sources, and that spider abundance and richness decreased with distance away from the stream. While some studies have investigated the relationship between riparian forest width and bird communities (Spackman and Hughes 1995, Verry et al. 2000), few have investigated the relationship between riparian forest width and terrestrial arthropod communities.

9 Objectives The objectives of this study were to: 1) quantify the diversity of web spiders in riparian forests in the agricultural landscape of southwest Ohio, 2) determine how the width of the riparian forest buffer along a stream influences the abundance, species composition, and diversity of web spiders in the forest, 3) determine if the web spider community inhabiting the stream edge, the agriculture edge and the interior differed from one another, and 4) describe the contribution to regional biodiversity of web spider community variation within and among riparian forests.

METHODS Study Area This study was conducted in riparian forests of class 3 streams within a 15- kilometer radius of Oxford, Butler Co., Ohio. Corn and soybean agriculture fields dominate this landscape, with a 10-24 % beech-maple deciduous forest cover (Griffith et al. 1993). The region exhibits a continental humid climate with mean annual precipitation of 930 mm and a summer mean annual precipitation of 275 mm (Griffith et al. 1993). In addition to sampling the web spider fauna, vegetation complexity was measured as it may be correlated with web spider abundance and diversity (Greenstone 1984, Rypstra 1986, Wise 1993). Sampling occurred near Oxford, OH (39°30' N, 84° 45' W) along Seven-mile creek and Four-mile creek in nine riparian forest sites: three replicate riparian forest sites from each of three width treatments (thin, medium, and wide). Riparian forest width was measured by a transect line that connected the shortest distance between annual high water mark of the stream with the forest-agriculture edge. Sites were chosen such that the wide, medium, and thin sites had measured forest cross-sections of > 80 m, 45-60 m, and 15-30 m respectively (Fig. 1.). I selected these width classifications because they reflect three common degrees of riparian fragmentation observed in southwest Ohio, and previous studies suggest minimum riparian corridor width for maintaining desirable species conservation is taxon specific and may range from 10-30 meters for streamside plants to 75-175 for birds (Spackman and Hughes, 1995). Although I only sampled riparian forests on one side of the stream, the width of the forest on both sides of the

10 stream was similar. Additionally, the selected forests remained within the same width classification for 250 m along the stream (i.e., forest width of wide sites was greater than 80 m for a length greater than 250 m). To control for the degree of forest isolation, agricultural fields separated forest sites from adjacent large forest patches by at least 250 m. I initially selected sites using 3-7 year-old aerial photographs provided by Microsoft terra-server (http://terraserver.homeadvisor.msn.com). I visited all sites to gain permission to access the land, and to make certain that aerial photos were still representative of the site.

Sampling and Identification Sampling of web spiders was performed between the hours of 0800 and 1200, from 8-31, August 2001. This seasonal sampling period was chosen because it exhibits considerably high abundances of mature spiders in this sample region (personal field notes) and previous studies have documented high diversity of spiders in the Midwestern U.S. during August (Brown et al. 2003, Rypstra and Carter 1995). I classified web spiders as any spider species that uses a web to catch prey and resides in the foliage. Morning temperatures during the sampling period ranged from approximately 21-31°C and the average morning relative humidity was 83 % (Ohio Automated Weather Network Station, http://www.units.muohio.edu/erc). Sampling was conducted in three 5 x 10-m quadrats at each site. The quadrats were oriented so that the 10-m side of the quadrat ran parallel to the stream. The three quadrat locations were at the stream edge (stream quadrat), at the agriculture edge (edge quadrat), and at the interior (center quadrat), midway between the stream and the agriculture edge (Fig. 1). Two collectors hand-collected web spiders using 15-min visual searches in each quadrat. This collecting technique was a modified version of the Coddington protocol for collecting arachnids (Coddington et al. 1996). All observed web spiders from just above the forest floor up to a height of 2 m were collected, stored in marked containers filled with 70 % ethanol, and identified to species in the laboratory. Spiders were identified to species in the laboratory and vouchers were placed in the Hefner Zoology Museum of Miami University (Oxford, OH). I was unable to

11 identify some sub-adult individuals to species, but these individuals were included in the relative abundance analyses. When I could ascertain that sub-adults were unique from all other species in the sample, these unidentified individuals were recognized as morphospecies and included in the diversity and species richness analyses. Spiderlings, or individuals that would need to survive the winter in order to become adults, were excluded from all analyses. Some web spider species have clutch sizes over 2,500 (Foelix 1996), so including spiderlings would add disproportionate variation to the results. Hereafter, I refer to species where only one individual was collected as singletons. I refer to common species as those that comprised >10 % of the total collection. Three types of vegetation structure were measured, as vegetation structure has been shown to be a correlated with spider abundance (Greenstone 1984, Rypstra 1986). To quantify the vegetation structure, I held a 2-m stick upright with its end touching the ground at 15 evenly spaced locations within each quadrat. I summed the number of times vegetation hit the stick from 0-1 m high at each of the 15 locations and recorded this as the value of low horizontal vegetation for each quadrat. I also summed the total number of vegetation hits from 1-2 m high at each of the 15 locations and recorded this as the value of high horizontal vegetation for each quadrat. I quantified the low and high horizontal vegetation values separately to compare vegetation differences in the herbaceous vegetation layer (0-1 m) as well as the rest of the forest understory (1-2 m). I also quantified a value of vertical vegetation structure to account for the vertical structure of tree trunks and under-story plants. I measured vertical vegetation structure through three evenly spaced 1 x 5-m planes running parallel to the 5-m width of each quadrat. I held a meter stick horizontally at a height of 1 m and walked along the three 1 x 5-m planes, and I summed the total vegetation hits as the vertical vegetation value for each quadrat.

Data Analyses Individual-based rarefaction analyses were used as diversity comparisons among landscape treatments and among quadrat locations using Internet software provided by Brzustowski (2002). This analysis allowed me to describe species richness in relation to

12 relative abundance by estimating the number of expected species in equally sized sub- samples (Simberloff 1978). I pooled the total species abundances from all sites for each width treatment and for each quadrat location for rarefaction analyses. In addition, species richness, the natural log abundance of the total collected, Simpson diversity, and Shannon diversity of web spiders were calculated for each quadrat. I used the proportional abundance (Pi) of each species to calculate Simpson diversity (1- Σ Pi²) and Shannon diversity (1 / Σ Pi(lnPi). I used these diversity measures because they are commonly used indices that indicate the collective effects of abundance and species richness. A split-plot analysis of variance (ANOVA) design tested the effects of width treatment (thin, medium, and wide) and quadrat location (edge, center, and stream) on web spider abundance (ln), species richness, Simpson diversity and Shannon diversity, using the program PC-SAS (SAS Institute 199). In the program JMP 4.0, I used Tukey’s post-hoc test to compare means for all ANOVA with an alpha of 0.05. Detrended Correspondence Analysis (DCA) (ter Braak, 1988) was used to analyze variation among samples and to show community level responses to width treatment and quadrat location. I used the computer program PC-Ord for this ordination analysis (McCune and Mefford, 1999). Additive partitioning compared the total contribution to web spider diversity of each of the three spatial levels of organization (i.e., quadrat location within a site, replicate site, and forest width treatment). Here I assumed that the total forest web spider diversity in the region, (gamma diversity) is the sum of the within-habitat diversity (alpha diversity) and the (beta diversity) diversity among sampling units at each spatial scale. I used the program PARTITION (Gering et. al. 2003), which calculated alpha and beta diversity values at each spatial level using species richness as the diversity index. PARTITION pooled the overall species abundances from the study, then randomly assigned individuals to quadrats based on the total web spider abundance in each quadrat. PARTITION performed 1000 randomizations to generate a null distribution of diversity values and tested if the beta values at each spatial level were significantly different than from those expected by chance. Diversity at each spatial level was considered significant if the probability of achieving its diversity value was p < 0.05.

13 Regression analyses were used to examine the responses of web spiders to vegetation structure using the program StatView 4.0. I investigated the dependence of web spider abundance and species richness on high horizontal vegetation, low horizontal vegetation, and vertical vegetation as independent variables. I also compared vegetation structure among width treatments and quadrat locations using the same type of split-plot ANOVA design as used for the web spider data.

RESULTS A total of 1285 spiders were collected representing 31 species in five families (Table 1). Of this total, 845 were identified to species, 188 sub-adult spiders were identified as morphospecies, and 121 sub-adult spiders were indistinguishable and included only in the total spider abundance analyses. The remaining 131 individuals were spiderlings that were excluded from the analyses. Species accumulation curves from the rarefaction analysis show that web spider diversity differed significantly among the three width treatments (Fig. 2). Rarefaction curves indicate that species richness was greatest in thin riparian forests and least in medium width riparian forests. Although the split-plot ANOVA did not show significant differences in web spider abundance or species richness among width treatments (Table 2, Table 3), they revealed a similar trend to the rarefaction curves. Thin riparian forests had significantly greater Shannon diversity than the medium and wide width treatments, and thin treatments had significantly greater Simpson diversity than medium width treatments (Table 2, Table 3). Rarefaction curves showed no differences among agriculture edge, center, and stream quadrats (Fig. 3). However, ANOVA revealed that web spiders were significantly more abundant in quadrats located at the agriculture edge than they were near the stream (Table 2, Table 3). There was a general trend in that agriculture edge quadrats had more species richness than stream quadrats; however there were no significant differences in species richness, Shannon diversity or Simpson diversity among quadrats (Table 3). Additive partitioning revealed significantly more web spider beta-diversity than expected by chance at each spatial level (i.e. quadrat location, forest site, and width treatment). Beta diversity was higher among width treatments (beta = 9.3) than it was

14 among sites (beta = 5.8) or quadrats (beta = 5.4). Width treatment was the spatial level that provided the greatest contribution to regional diversity, accounting for 33.2 %. Forest site, quadrat placement, and alpha diversity accounted for 20.7 %, 19.3 %, and 26.8 % of regional diversity respectively. DCA ordination results showed that web spider assemblages from the stream quadrats were relatively similar to each other and distinctive from other quadrat types (Fig. 4). Axes 1 and 2 accounted for 26.7 % and 18.9 % of the variation of species data respectively. Proximity to the stream (stream edge, center, agriculture edge) appeared to be the main factor driving the grouping of quadrats along Axis 1. Stream quadrats from wide riparian forest sites were particularly similar in their species assemblages. Center quadrats from all width treatments also appeared to have similar species assemblages, as detected in ordination space. Agriculture edge quadrats displayed the most variation among the three quadrat locations, but a pattern separating them from other quadrat types was still evident. Agriculture edges of thin sites showed considerable variation in species assemblages, with Thin Riparian Site #1 (T1E) particularly isolated from all other assemblages. No clear species assemblage patterns were detectable due to width treatment alone. Nine singleton species were collected, of which the majority were collected from one site (i.e., Thin Riparian Site #1). Five singletons were collected in this particular site; four in the agriculture edge quadrat and one in the center quadrat. In total, five singletons were collected in the thin sites, three in the wide sites, and one in the medium sites. The majority of these rare species were also collected in edge quadrats. Six singletons were collected in the edge quadrats, two in the center quadrats, and only one in the stream quadrats. Mangora maculata, Neriene radiata, and Micrathena gracilis were the three most common species collected (Table 1). Mangora maculata accounted for more than 20 % of all identified spiders and was by far the most common species collected. This species was particularly common in the medium width sites, such that > 57 % of all Mangora maculata individuals were collected from medium width sites. Web spider abundance and species richness were not correlated with any of the vegetation structure measurements. Agriculture edge quadrats had more vegetation

15 structure than center quadrats or stream edge quadrats, with significantly greater low horizontal (F = 9.92, df = 2, 24, P = 0.002) and vertical vegetation (F = 8.29, df = 2, 24, P = 0.005). There were no significant effects of width treatment on vegetation structure.

DISCUSSION Riparian Forest Width Thin riparian forests exhibited the greatest web spider diversity of all width treatments in all analyses (Table 2, Fig. 2). One explanation for this result is that thin riparian forests were characterized by a greater edge to area ratio. A higher proportion of edge habitat often increases habitat heterogeneity, which may lead to greater species diversity (Davies et al. 2001). A higher proportion of edge habitat could also influence the rate of web spider colonization in thin riparian forests. Many web spiders colonize habitat through wind driven dispersal (ballooning) as spiderlings (Wise 1993, Suter 1999). Trees at the agriculture edge could act as a wind block and cause spiderlings to settle from their aerial dispersal (Suter 1999). Through this process, one might expect forest habitat near agriculture edges to have relatively high species richness. Web spider diversity in thin riparian forests would therefore be high, as all habitat within thin riparian forests is relatively close to an agriculture edge. Wide riparian forests exhibited the second most web spider diversity (Table 2, Fig. 2). Web spider diversity was greater in wide sites than in medium sites for all analyses. Wide riparian forests contain the greatest amount of forest habitat and the least edge to area ratio. Ecological theory concerning habitat fragmentation predicts that wide sites would exhibit lower population extinction rates (MacArthur and Wilson 1967, Forman 1995, Bender et al. 1998). Wide forests may sustain forest interior species, which are typically rare and clumped into isolated patches (Gaston 1994, With and Crist 1995). Thus, biodiversity in wide forests would be supplemented by these rare species which may be lost in thinner riparian forests through extinction (Kruess and Tscharntke 1994, Golden and Crist 1999). In fact, I found that wide riparian forest sites included 7 species that were not found in the thin width treatment, of which 3 were singletons and all were relatively rare (i.e. < 0.5 % of the total collection).

16 Medium width sites clearly exhibited the lowest web spider diversity of the three forest types investigated (Table 2, Fig. 2). There may be separate reasons why medium width sites were less diverse than both thin sites and wide sites. Perhaps medium sites did not include a sufficient edge/area ratio to support the colonization potential of thin sites and were not wide enough to include the species indigenous to forest interiors that may be characteristic of wide sites. Interestingly, the low web spider diversity of medium width sites corresponded with them exhibiting a particularly high relative abundance of one species, Mangora maculata (Table 1). Mangora maculata was by far the most abundant species collected overall, and it was disproportionately abundant in the medium width riparian forests. While little is known about the specific competitive abilities or habitat requirements of Mangora maculata, the low diversity found in medium width sites could be attributed to the abundance of this common species. In this study, the species richness value (total number of species collected), Simpson diversity, and Shannon diversity were recorded for each 5 x 10-m quadrat and were measures that are sensitive to sample abundance. On the other hand, rarefaction removes the effect of sample abundance on species richness. Species density (the number of species per unit area) and other density dependent diversity measures may be less suitable than rarefaction methods for comparing diversity among different regions or habitat types (Gotelli and Colwell 2001). In this study, the species accumulation curves reached an asymptote for all width treatments suggesting that the species pools were sampled rather comprehensively. This also suggests that there is not a major discrepancy between the web spider species density and the web spider species richness as sampled. Therefore, the finding that rarefaction curves were significantly greatest for thin riparian forests reinforces the trend that thin riparian forests exhibited the greatest values for all diversity measures. The differences detected in web spider diversity among width treatments are reinforced by additive partitioning results. There was significantly greater beta-diversity among width treatments than would be expected by chance, showing that species assemblages varied in response to width treatments. Beta-diversity values were higher among width treatments than among sites or quadrat locations. Therefore, width treatment was the spatial scale that contributed the most to regional diversity. This

17 finding demonstrates that riparian forest width has an effect on web spider diversity in that riparian sites of different widths support different subsets of the regional species pool.

Proximity to Stream The habitat directly adjacent to streams exhibited significantly lower web spider abundance than all other quadrats (Table 2, Table 3). There was also a trend for lower species richness in stream quadrats. However, this trend was not evident in the rarefaction analysis (Fig.3). Therefore, the low species richness trend in stream quadrats may be the effect of low web spider abundance along the stream. The finding of lower web spider abundance adjacent to streams seems counter- intuitive, as studies have shown that streams supplement available prey for riparian predators (Bastow et al.2002, Sanzone et al. 2003) and Gillespie (1987) described web spiders along streams consuming large amounts of emerging aquatic insects. Additionally, Henschel et al. (2001) found greater spider abundance along a river shore than in similar habitat 30-60 m away. The lower web spider abundance I observed in stream quadrats deserves further explanation. One possibility is that web spiders in stream quadrats are subject to increased predation. Aquatic insect emergences have been shown to increase the occurrence of visiting birds, bats and other opportunistic predators that may also be preying on spiders (Nakano and Murakami 2002). However, studies linking riparian habitat to increased bird abundance have largely been conducted in grasslands, dry woodlands, and desert habitat (Knopf and Samson 1994, Nakano and Murakami 2002). Conversely, studies in wetter woodlands have not exhibited this relationship (McGarigal and McComb 1992, Meiklejohn and Hughes 1999). For instance, McGarigal and McComb (1992) showed that avian species richness and abundance in upland forest plots between 100 and 400 m from the stream exceed those of plots directly adjacent to streams. While increased depredation along streams cannot be ruled out, I do not attribute all of the depressed web spider abundance in streamside quadrats to increased numbers of vertebrate predators. More study is necessary to determine the impacts of visiting vertebrate predators on web spiders and more generally food webs in riparian areas of eastern deciduous forests.

18 The streamside habitats I investigated were dominated by a single large bodied species that was found only in the stream edge quadrats. In some cases, large dominant spiders have been shown to out-compete smaller, more abundant species (Spiller 1984, Marshall and Rypstra 1999). Tetragnatha elongata, was unique to stream quadrats where it was relatively common (i.e. > 3 % of the total collection). Tetragnatha elongata may be so successful as a streamside specialist that it reduces the number of other species that could occupy this habitat, thus contributing to lower diversity at stream edge quadrats. There are many possible explanations for the greater web spider abundance in agriculture edge quadrats. Edge habitats exhibited the greatest vegetation structure. Although our study did not find an overall correlation between vegetation structure and increased web spider abundance and richness, such relationships have been revealed in previous studies (Greenstone 1984, Rypstra 1986). In addition, the immigration behavior of web spider may also lead to greater abundance in agriculture edge quadrats, as they often disperse through launching into the wind as aerial plankton (Richter 1970, Bowman et al. 2002). Agriculture edges could act as a wind block and cause dispersing spiderlings to settle from the air. Some web spiders may also be more likely to colonize edges since they disperse through random movement after descending from the aerial plankton (Gillespie 1987). This process could facilitate web spider colonization in agriculture edges and the dispersing spiderlings could serve as additional prey for established web spiders. There are several sources of variation that could affect web spider results based on the quadrat location. For instance, the compass orientation of the riparian forest could influence the community of web spiders along the agriculture edge. Also, the nature of the crop adjacent to the riparian forest could influence the web spider assemblages. I noted the type of crop adjacent to each riparian forest site and there were no discernable differences between sites adjacent to corn fields and sites adjacent to soybean fields in examining the DCA. However this study did not account for differences in compass orientation of riparian forest sites.

Community Analyses

19 While there was much similarity in species assemblages across all samples, DCA ordination distinguished the web spider community in stream edge quadrats as different from all other quadrats. This finding reinforces the call for preserving riparian forests, as they contain natural communities that are distinct from other habitat types. The three component quadrats from each riparian forest site did not appear to aggregate in the DCA ordination. Rather, the type of quadrat (stream edge, center, agriculture edge) appeared to be the main factor driving the grouping. One might expect a stream edge quadrat and center quadrat from the same riparian forest site to aggregate since they are in close proximity to each other, especially in the case of thin riparian forests where quadrats were separated only by 0-5 m. The fact that such a grouping by site trend was not apparent emphasizes the influence of the stream edge and agriculture edge on web spider assemblages. DCA ordination revealed that the greatest variation among the same quadrat type was among agriculture edges. These quadrats are most likely subject to human disturbance. Thin Riparian Site #1 (T1E) exhibited the greatest variation of all quadrat samples. Field notes recorded that some of the herbaceous vegetation along this agriculture edge appeared desiccated, as if sprayed by herbicide. Interestingly, this was also the site that contained the majority of the singletons collected in the study. Perhaps this high disturbance cleared the quadrat of more common agriculture edge species and/or created a dissimilar habitat type which encouraged the colonization of rare web spider species.

Conclusions These findings show that riparian forest width impacts web spider diversity and is an important landscape feature contributing to regional diversity. Both thin and wide sites were more diverse than sites of medium width, which could be caused by numerous factors including differences in habitat heterogeneity due to proportion of edge habitat, availability of forest interior habitat, and different rates of colonization. Spiders are often rapid colonizers, thus it is possible that some riparian forest habitats serve as population sources for spider colonization. Future studies investigating temporal changes (i.e., seasonal and annual) in web spider assemblages could determine if wide riparian sites

20 sustain a more stable community across time and if greater diversity in thin riparian sites is a result of higher colonization rates. Within riparian forests, the proximity of habitat to the stream and to the agriculture edge impacts the web spider community. While more study is necessary to investigate the lower web spider abundance found in stream edge quadrats, streamside habitat makes up a distinct community of web spiders. Therefore, conserving riparian forests is important both to preserve the riparian web spider community and to preserve a source of web spiders for regional forest biodiversity.

21 Agriculture Forest Stream

THIN 15—30 m

30 m

MEDIUM 45-60 m

WIDE > 80 m

Figure 1. The three major types of riparian forest habitat as designated by width, from the stream to the agricultural edge. Placements of the 5 x 10-m quadrats within each site are marked X.

20 ies ec

Sp 15 f # o d e t 10 Thin a Series1 m i SMeediries2um Est 5 SWieridees3

0 0 100 200 300 Number of individuals

Figure 2. Species accumulation curves (±1 SD) for predicted spider species richness in riparian forests of three width treatments (thin, medium, and wide).

23 25

20 s e i c e

Sp 15 f o # d e t 10 Edge

a Series1 m i t SeCreients2er Es 5 SeStrireesa3m

0 0 50 100 150 200 250 300 Number of individuals

Figure 3. Species accumulation curves (±1 SD) for predicted species richness at three quadrat locations (agriculture edge, center,stream) in riparian forests.

T1E =0.25 λ 200

T1C

W1C W1E T1S W1S M2E W2C W2E W2S T2S M1EM3C M2S Axis 2 100 M3E W3S M3S T3C M2C T2E T3S T2C M1C M1S W3E W3C

λ=0.44 T3E 0 0 100 200 300 Axis 1

Figure 4. DCA ordination of web spider species abundances collected from 18 quadrats. Samples are labeled by width treatment and quadrat location: thin (T), medium (M), wide (W), edge (E), center (C), and stream (S). Replicated sites of each riparian forest width treatment are numbered 1-3. Polygons have been added to illustrate the agriculture edge, center and stream quadrats.

25 Table 1. Spider families and species collected by quadrat type in riparian forests near Oxford, Ohio in August 2002.

Thin Thin Thin Medium Medium Medium Wide Wide Wide Family Species Ag. Center Stream Ag. Center Stream Ag. Center Stream Total Edge Edge Edge Agelenidae Agelenopsis naevia (Walckenaer) 1 ------1 - 2 Agelenopsis pennsylvanica (C.L. Koch) - 2 1 ------3 Araneidae Araneus thaddeus (Hentz) ------1 - - 1 Argiope aurantia Lucas 1 ------1 Argiope trifasciata (Forskal) - - - 1 - - - - - 1 Cyclosa conica (Pallas) 5 2 - 10 11 - 9 5 1 43 Cyclosa turbinate (Walckenaer) ------* Eustala anastera (Walckenaer) - - - - 1 - 1 1 - 3 Larinioides cornuta Clerck 1 ------1 Mangora maculate (Keyserling) 24 20 18 25 65 34 4 11 16 217 Mangora placida (Hentz) 2 1 - 3 - - 3 1 3 13 Metepeira labyrinthea (Hentz) - - - - - 1 1 1 - 3 Micrathena gracilis (Walckenaer) 13 37 21 11 13 5 5 21 6 132 Micrathena mitrata (Hentz) - 5 2 - - - - 3 - 10 Micrathena sagittata (Walckenaer) 10 1 - 5 2 - 12 4 - 34 Neoscona arabesca (Walckenaer) 7 3 2 - 2 1 - - - 15 Neoscona crucifica (Hentz) 4 2 1 1 2 - 4 - 2 16 Verrucosa arenata (Walckenaer) 4 5 11 1 4 1 2 1 11 40 Ceratinella brunnea Emerton 1 ------1 Linyphiidae Ceratinopsis purpurescens Keyserling 1 ------1 Frontinella pyramitela (Walckenaer) 5 2 - 1 - - 3 2 1 14 Neriene radiata (Walckenaer) 6 14 2 30 14 - 51 23 4 144 Neriene virabilis (Banks) ------1 - 1 Leucauge venusta (Walckenaer) 7 3 2 10 4 1 3 1 1 32 Tetragnathidae Tetragnatha elongate Walckenaer - - 14 - - 17 - - 14 45 Tetragnatha laboriosa Hentz 14 9 5 2 - - 15 15 2 62 Argyrodes fictillium (Hentz) ------1 1 Theridiidae Argyrodes trigonum (Hentz) ------2 2 Theridion antonii Banks - 1 ------1 Theridion frondeum Hentz - - - - - 1 1 - - 2 Theridion lyricum Walckenaer - 1 2 - - - - - 1 4 Total 106 108 80 100 117 61 113 91 65 845 * C. turbinata and C. conica were considered one morphospecies as they were often indistinguishable

Table 2. Mean (± SE) abundance, species richness, Shannon diversity, and Simpson diversity of web spiders collected in riparian forests by landscape treatment (thin, medium, wide) and quadrat (agriculture edge, center, stream).

Treatment Count Abundance Richness Shannon Simpson Diversity Diversity Thin 9 30.0±1.1 10.22±.90 1.45±.10 4.78±.56 Medium 9 28.2±1.2 7.88±.93 0.90±.08 2.99±.42 Wide 9 28.2±1.1 10.00±.64 0.91±.10 4.20±.38

Edge 9 33.4±1.1 10.44±.85 1.12±.14 4.34±.50 Center 9 33.8±1.2 10.00±.68 1.14±.11 4.00±.59 Stream 9 21.3±1.1 7.66±.88 1.00±.08 3.62±.45

27 Table 3. Results of ANOVA (split-plot design with two error terms) on web spider richness, abundance (ln), Simpson diversity, and Shannon diversity in 5 x 10-m quadrats placed at the agriculture edge, forest center, and stream within replicated thin (N=3), medium (N=3), or wide (N=3) width riparian forests.

Type III Source DF SS F P Significant Effect Abundance Treatment 2 0.0261 0.10 0.90 none (ln) Site 6 0.8064 0.99 0.47 none Quadrat location 2 1.2400 4.56 0.03 Edge > Stream; Center > Stream (Treatment x 4 0.2168 0.40 0.80 none Quadrat)

Richness Treatment 2 29.851 3.22 0.11 none Site 6 27.777 0.81 0.57 none Quadrat location 2 40.074 3.52 0.06 none (Treatment x 4 16.370 0.72 0.59 none Quadrat)

Simpson Treatment 2 15.0061 5.1 0.05 Thin > Medium Site 6 8.8348 0.63 0.70 none Quadrat location 2 2.3353 0.50 0.61 none (Treatment x 4 7.0137 0.75 0.57 none Quadrat)

Shannon Treatment 2 1.7590 10.21 0.01 Thin > Medium; Thin > Wide Site 6 0.5170 1.65 0.21 None Quadrat location 2 0.0982 0.94 0.41 None (Treatment x 4 0.0785 0.38 0.82 None Quadrat)

Table 4. Mean (± SE) vegetation structure values as measured in riparian forests by landscape treatment (thin, medium, wide) and quadrat (agriculture edge, center, stream). Unitless values represent the number of vegetation contact points along a meter stick.

Comparison Treatment Count Horizontal Horizontal Vertical (High) (Low) Vegetation Treatment Thin 9 13.556 ± 44.889 ± 37.778 ± 3.452 3.268 6.576 Medium 9 22.556 ± 42.333 ± 44.778 ± 4.507 10.822 5.535 Wide 9 13.667 ± 30.778 ± 21.889 ± 3.516 4.219 4.135

Quadrat Edge 9 20.333 ± 56.556 ± 47.556 ± 5.036 8.710 5.979 Center 9 10.778 ± 33.111 ± 25.111 ± 2.460 3.683 4.803 Stream 9 18.667 ± 28.333 ± 31.778 ± 3.651 3.640 5.773

29 Chapter 3: A comparison between the web spider communities of riparian forests and hedgerow forests in an agriculture landscape

INTRODUCTION Agricultural practices have destroyed and fragmented forest habitat globally. In agricultural landscapes, the remaining forest habitat is often limited to thin corridors of riparian forests (forests adjacent to waterways) and hedgerows (uncultivated field borders) (Forman 1995). Both landscape features are important for maintaining regional biodiversity and ecosystem functioning (Forman and Baudry 1994, Naiman and Decamps 1997, Varcholoa and Dunn 2001). There are fundamental differences between riparian forest and hedgerow corridors, however, which may determine their relative contribution to the biodiversity terrestrial communities. Understanding the differential contribution of riparian forests and hedgerows to regional biological diversity in agricultural systems is important to conservation planning. Riparian forests are universally recognized as areas of high conservation concern because of their role in protecting water quality and maintaining high levels of aquatic and terrestrial biodiversity (Verry et al. 2000). Species richness in riparian forests often exceeds that of adjacent upland areas for plants, birds, and mammals (Naiman et al. 1993). A mutual exchange of nutrients between aquatic systems and riparian habitats may subsidize riparian plants, herbivores, and insectivores (Naiman and Decamps 1997, Nakano and Murakami 2001, Sanzone et al. 2003), potentially leading to this greater diversity. In the Midwestern United States, riparian forests are often limited to thin (<30 m) corridors alongside steams (Naiman 1993). Hedgerows have been shown to be important habitat for preserving biodiversity and promoting animal movements in agricultural landscapes (Forman and Baudry 1984). Hedgerow corridors in the Midwestern United States are often thin forested field borders between 15 and 30 m wide. They are similar to many riparian forest corridors in their dimensions and that they add vegetative complexity at field edges. However, hedgerows lack streamside habitat and the nutrient exchange from the stream that are common features of riparian forests. Still, both hedgerows and riparian forests contain biological communities that are distinct from surrounding agriculture fields and serve as important

30 sources for species to colonize fallow fields and agriculture fields that are disturbed on an annual basis (Naiman et al. 1993, Bedford and Usher 1994, Nicholls et al. 2001). Riparian forests and hedgerows may also be economically important, by providing refuge for spiders and other generalist predators that can reduce crop damage by insect pests (Price 1980, Varcholoa and Dunn 2001). Spiders have been used to study effects of agriculture conservation practices on biodiversity (Reichert and Bishop 1990, Rypstra and Carter 1995, Rypstra et al. 1999). Spiders are a good model for such studies because they are diverse, abundant, and important to agricultural landscapes as predators of insect pests (Wise 1993). The amount of vegetation structure in a given area has been shown to be correlated with spider abundance (Greenstone 1984, Rypstra 1986). Web spiders, spiders that use a web to catch prey, were used as model taxa for this study. Web spiders may be particularly sensitive to loss of forest habitat in agricultural landscapes because they require complex vegetation for web scaffolding. Here, the web spider community in riparian forests was compared with hedgerow forests in a southwest Ohio agriculture landscape. The objectives of this study were to: 1) quantify the diversity of web spiders in riparian forests and hedgerows in the agricultural landscape of southwest Ohio, 2) compare the abundance, diversity and species composition of web spiders between hedgerows and riparian forests of similar width, and 3) quantify vegetation structure as it may relate to web spiders in an attempt to determine if it is important to the similarities and differences in the web spider community.

METHODS Study Area This study was conducted in riparian forests and hedgerow forests in the Four- mile Creek watershed within a 15-kilometer radius of the town of Oxford, Butler Co., Ohio (39°30' N, 84° 45' W). Corn and soybean agriculture fields dominate this landscape, with a 10-24% beech-maple deciduous forest cover (Griffith 1993). The region exhibits a continental humid climate with mean annual precipitation of 930 mm and a summer mean annual precipitation of 275 mm (Griffith 1993). All of the riparian

31 forests and hedgerow forests studied included trees of at least 0.5 meters diameter at breast height and were bordered by an agriculture matrix of corn or soybean. The soil gradient at all sites was between 0-4 % and the stream at all riparian forest sites was a class 3 stream. The web spider fauna was sampled in three riparian forest and three hedgerow forest sites. I initially selected sites using 3-7 year-old aerial photographs provided by Microsoft terra-server (http://terraserver.homeadvisor.msn.com). I visited sites to gain permission to access the land and to make certain that aerial photos were still representative of the site. The riparian forest sites all measured between 15-30 m from the annual high water mark to the agriculture edge for at least 250 m along the stream. Although I sampled one side of the stream, the width of the forest on both sides of the stream was similar. The hedgerow forests were also between 15-30 m wide as measured from agriculture edge to agriculture edge for at least 250 m. To control for the degree of forest isolation, agricultural fields separated forest sites from adjacent large forest patches by at least 250 m.

Sampling and Identification Web spiders were collected at all six sites during three separate sampling periods in June, August, and late September/early October 2001, and collecting occurred between 0800 and 1200 hours. I classified web spiders as any spider species that uses a web to catch prey and resides in the foliage. The annual average morning relative humidity during the sampling months is 83 % (Ohio Automated Weather Network Station, http://www.units.muohio.edu/erc). Each sampling period was completed within three weeks. Sampling of web spiders was conducted in three 5 x 10-m block quadrats at each site. The longer 10-m side of the block quadrat ran parallel to the length of the riparian forest or hedgerow forest. In riparian forest sites, I sampled one quadrat at the stream edge (stream quadrat), one at the agriculture edge (edge quadrat), and one at the interior (center quadrat), midway between the stream and the agriculture edge (Fig. 1). In the hedgerow forest sites, quadrats were sampled at each of the two agriculture edges and at the center.

32 Two collectors hand collected web spiders using 15-min visual searches in each quadrat. These time and space sampling limits provided thorough web spider sampling. This hand collecting technique was a modified version of the Coddington protocol for assessing spider diversity (Coddington et al. 1996). All web spiders found in the area above the forest floor up to a height of 2 m were collected and stored in marked containers with 70 % ethanol for later identification. All adult spiders were identified to species and vouchers were placed in the Hefner Zoology Museum of Miami University. Even though I was unable to identify some sub-adult individuals to the level of species, I included these individuals in the abundance analyses. When I could ascertain that these sub-adults were unique from other species in the sample, these unidentified individuals were recognized as morpho-species and included in the diversity and species richness analyses. Spiderlings, or individuals that would need to survive over winter in order to become adults, were disregarded from all analyses. Some web spider species have clutch sizes over 2,500 (Foelix 1996), so including spiderlings would add disproportionate variation to the results. Vegetation structure was quantified in each quadrat during the August sampling period. Three types of vegetation structure were measured, as vegetation structure has been shown to be a correlated with spider abundance (Greenstone 1984, Rypstra 1986). To quantify the vegetation structure, I held a 2-m stick upright with its end touching the ground at 15 evenly spaced locations within each quadrat. I summed the number of times vegetation hit the stick from 0-1 m high at each of the 15 locations and recorded this as the value of low horizontal vegetation for each quadrat. I also summed the total number of vegetation hits from 1-2 m high at each of the 15 locations and recorded this as the value of high horizontal vegetation for each quadrat. I quantified the low and high horizontal vegetation values separately to compare vegetation differences in the herbaceous vegetation layer (0-1 m) as well as the rest of the forest understory (1-2 m). I also quantified a value of vertical vegetation structure to account for the vertical structure of tree trunks and under-story plants. I measured vertical vegetation structure through three evenly spaced 1 x 5-m planes running parallel to the 5-m width of each quadrat. I held a meter stick horizontally at a height of 1 m and walked along the three 1 x 5-m

33 planes, and I summed the total vegetation hits as the vertical vegetation value for each quadrat.

Data Analyses Species richness and natural log of the total number of web spiders were calculated for each quadrat in order to compare the habitats within each forest site. I also pooled the three quadrat samples from each riparian forest site (edge, center, and stream) and each hedgerow forest site (edge, center, and edge) to calculate the total spider abundance (ln) and the species richness for each site. This allowed me to study the possible treatment effects on the web spider community within the entire forested site. Repeated-measures analysis of variance was used to test the main effect of landscape treatment (riparian forest and hedgerow forest) on web spider abundance (ln) and species richness using the pooled data from the three quadrats in each site. Seasonal sampling period (June, August, Sept/Oct) was the repeated measure and site was the blocked factor. I also compared web spider abundance and species richness between the of hedgerow and riparian forest landscape treatments while excluding the effect of the stream quadrats, as the streamside quadrats directly contain habitat not found in hedgerow forests. I did so by performing two sets of repeated-measures ANOVAs, one using solely the agricultural edge quadrats and one using solely the center quadrats, with landscape treatment as the main factor. I used Tukey’s post-hoc test to compare means for all ANOVAs. I also tested the effect of quadrat location on web spider abundance and richness in the riparian forest sites exclusively using repeated-measures ANOVAs with quadrat location (edge, center, and stream) as the main factor. The program Statview 4.0 was used for all ANOVA comparisons. Individual-based rarefaction analysis was used as a diversity comparison between the riparian forest and hedgerow forest treatments using the Internet software (Brzustowski 2002). Rarefaction analysis allowed me to describe species richness in relation to relative abundance by estimating the number of expected species in equally sized sub-samples (Simberloff 1978). I pooled the total species abundances from all sampling dates and quadrats for both landscape treatments. In order to control for habitat

34 differences I implemented a second rarefaction analysis, excluding stream quadrats from the riparian forest sites. Detrended Correspondence Analysis (DCA) (ter Braak, 1988) was used to show community level responses to landscape treatment and quadrat location using the program PC-Ord (McCune and Mefford 1999). I used exclusively the August sampling date because it contained considerably more abundance and species richness than the other sampling dates. I plotted the DCA of each individual quadrat sample from the August sampling date. Stepwise multiple regression analysis was employed to examine the response of web spiders to vegetation structure using the program Statview 4.0. I used web spider abundance (ln) and species richness as the dependent variables, and high horizontal vegetation, low horizontal vegetation, and vertical vegetation as the independent variables. Vegetation structure was compared between riparian forests and hedgerow sites while excluding the stream quadrats. I excluded the stream quadrats since hedgerows did not have this quadrat type and so I could compare vegetation structure in centers and agriculture edges between treatments. Using high horizontal vegetation, low horizontal vegetation, and vertical vegetation as independent variables, I performed three separate two-factor ANOVAs with the factors of landscape treatment and quadrat location (center and edge).

RESULTS Web Spider Diversity and Abundance A total of 1310 spiders, representing 32 species were collected from the three combined sampling dates (Table 1). Of this total, 824 were identified to species, 168 sub-adult spiders were identified as morphospecies, and 86 sub-adult spiders were indistinguishable and included only in the total spider abundance analyses. A total of 232 spiderlings were collected but excluded from the analyses. Overall, August samples had the highest abundance and species richness, and the June sampling date had the lowest species richness (Table 2, Table 3).

35 Riparian forests had significantly higher web spider richness and abundance than hedgerow forests for all comparisons (Fig. 2, Table 3). Even with stream edge excluded, there was significantly greater abundance and species richness in the agriculture edge quadrats and the center quadrats of riparian forest sites than in those of hedgerow sites (Table 3). Rarefaction curves confirm that web spider diversity was significantly higher in riparian forests than in hedgerows (Fig. 3). Even with the stream quadrats excluded, rarefaction curves show that web spider diversity was significantly higher in riparian forests than hedgerow forests (Fig. 4). This rarefaction analysis reinforces the species richness results from the repeated-measures ANOVA while accounting for differences in sample abundances. There were 14 species found in riparian forests that were not found in hedgerow forests, while only 3 species were collected exclusively in hedgerow forests. All three of the species unique to hedgerow forests were relatively rare (i.e. <0. 05 % of the total collection). Of the 14 species unique to riparian forest sites, only one (Tetragnatha elongata) was also unique to the quadrats directly adjacent to the stream. Four of the 14 species unique to riparian forests were fairly common in my samples (i.e., >2% of the total collection) (Table 1). DCA ordination results show that web spider assemblages from stream quadrats of riparian forests were similar to one another but distinct from those of all other quadrats (Fig. 5). Axes 1 and 2 accounted for 21.7% and 13.2% of the variation of species data respectively. The center quadrats of riparian forests had similar species assemblages to one another and were also distinct from other quadrats in ordination space. There was high variation in web spider assemblages among the edge quadrats of riparian forests. The greatest separation of all quadrats sampled was that of an agriculture edge of one the riparian forest sites, R3E (Fig. 5). Field notes recorded in August stated that some of the herbaceous vegetation along this agriculture edge appeared desiccated, as if sprayed by herbicide. The hedgerow center, hedgerow agriculture edge, and riparian forest agriculture edge quadrats were all indistinguishable from each other in ordination space. Comparing separate quadrat locations exclusively within riparian forest sites using repeated-measures ANOVAs, there was significantly greater web spider species

36 richness and abundance in agricultural edge quadrats than stream quadrats (Table 3). Mean web spider abundance and species richness were generally lower in steam quadrats than center or agricultural edge quadrats of riparian forests.

Vegetation Structure The best stepwise regression model for the response of web spider abundance to vegetation structure was with vertical vegetation and low horizontal vegetation (r² = 0.614, p = 0.0008, df 2, 17). Web spider abundance was inversely related to vertical vegetation and positively related to low horizontal vegetation. Web spider abundance was unrelated to high horizontal vegetation. Web spider species richness was unrelated to all measures of vegetation structure. Center and edge quadrats of hedgerow forest sites had significantly greater high horizontal vegetation structure (1-2 m) then did those of riparian forest sites (Table 4). However, the center and edge quadrats of riparian forest sites had significantly greater low vegetation structure (0-1 m) than did those of hedgerows sites (Table 4). Edge quadrats also had significantly greater horizontal vegetation structure in the 0-1 m height range than did center quadrats (Table 4). Hedgerow forest sites had greater mean vertical vegetation structure, including a significant interaction effect in which riparian center quadrats had less vertical vegetation structure than did all other quadrats (Table 4).

DISCUSSION Riparian forests supported a more diverse web spider community than hedgerow forests of similar width. The forest interiors and agriculture edges of riparian forests exhibited greater diversity than those of hedgerows. The greater species richness in riparian forests was due largely to relatively common species. Four species that were relatively abundant (i.e., common species) were completely absent from hedgerow samples, while the three species unique to hedgerows were rare species. These findings suggest that riparian forests contributed more than hedgerows to the regional biodiversity of web spiders. Ordination analyses indicate that riparian forests are likely to preserve a unique web spider community. Stream edge quadrats and riparian forest center quadrats

37 supported web spider assemblages distinct from those of other quadrats. There were no discernable differences in the ordination of riparian forest agriculture edges, hedgerow agriculture edges, or hedgerow interiors. These results suggest that the web spider habitat of riparian forests contributes more to diversity than do hedgerows. The riparian forest habitat directly adjacent to steams generally exhibited lower web spider species richness and abundance than the riparian forest interior and agriculture edge. These findings do not reflect recent studies that suggest streams have a positive influence on the numbers of spiders and other invertebrate predators (Bastow et al. 2002, Henshchel et al. 2003). While there are no known explanations for the low abundance and species richness of web spiders in stream quadrats compared to elsewhere in riparian forests, there are many possible reasons for this result. For example, the low diversity in found in stream quadrats could be the result of increased spider depredation along the stream by birds and bats. Additionally, the sampling design of this study promoted the collection of diurnal web spiders. If the web spider community directly adjacent to the stream contains a higher proportion of nocturnal web spiders, competition among web spiders could result in fewer diurnal web spiders. Another possibility for the low diversity of stream quadrats concerns the wind driven dispersal behavior of spiders, known as ballooning (Suter 1999). If trees at the edge of agriculture fields act as a wind block and facilitate the colonization of ballooning web spiders, one might expect high diversity of web spiders near agriculture edges. More study is needed of the riparian web spider community and the factors that affect its diversity. It is notable that hedgerow forests had relatively low web spider diversity, even though diversity in riparian forests was highest at the agriculture edge and lowest at the stream edge. The experimental design sampled two agriculture edges for each hedgerow forests while only sampling one for each riparian forest. Still, greater web spider species richness and abundance was found in riparian forests for all comparisons. Thus, there are clear and detectable differences between the agriculture edge of a riparian forest and that of a hedgerow. Similarly, the forest interior of a riparian forest is not comparable to that of a hedgerow. It appears that even at a distance of 15 to 30 m, the presence of the

38 stream has a positive influence on web spider diversity. This positive influence could be the result of the nutrient exchange between the terrestrial and aquatic habitat. Microclimatic differences between hedgerow forests and riparian forests may have influenced the web spider diversity results of this study. Studies comparing riparian and upland areas have cited soil moisture and temperature as correlates for terrestrial invertebrate abundance (Wenninger and Fagan 2000). However, the fairly consistent weather conditions throughout this study, with average morning relative humidity of 83%, should have reduced the extent of microclimatic variation. Still, small differences in microclimate may have contributed to differences in the web spider communities. The total forested area in the riparian forests was often greater than that of the hedgerows, due to the fact the riparian forest was only sampled on one side of the stream. It is possible that this increased amount of forested area in riparian forests contributed to them having greater web spider diversity. However, a concurrent study with a similar experimental design found that riparian forests 15-30 m wide actually had greater species richness than riparian forests 45-60 m wide (Chapter 2). Additionally, streamside quadrats appeared unique from other quadrats in ordination space. This may indicate that the stream acted as a habitat barrier, further justifying the comparison of hedgerow forests with riparian forests on one side of the stream. There are several sources of variation that could affect web spider results based on the quadrat location. For instance, the compass orientation of the riparian forest or hedgerow could influence the community of web spiders along the agriculture edge. Also, the nature of the adjacent crop could influence the web spider assemblages. I noted the type of crop adjacent to each site; there were no discernable differences between sites adjacent to corn fields and sites adjacent to soybean fields in examining the DCA. However this study did not account for differences in compass orientation of riparian forest and hedgerow sites. Significant differences in vegetation structure may have contributed to the differences between riparian forest and hedgerow web spider diversity. Hedgerow forests had significantly greater high horizontal structure (1-2 meter) and significantly less low horizontal structure (0-1 meters) than riparian forests. After analyzing these vegetation structure data, I revisited the field sites to help explain the results. In doing so,

39 I noted that the invasive shrub, Lonicera maackii (Amur honeysuckle) was present in all six study sites. Lonicera maackii is a common invasive in secondary forests in southwest Ohio, where it has been shown to cause diminished abundance and richness of understory plants (Collier et al. 2001, Gould and Gorchov 1999). Its abundance has been correlated with the extent of anthropogenic disturbance (Hutchinson and Vankat 1997). I noted that Lonicera maackii accounted for approximately 25-50 % of the forest understory in riparian forests and 75 –100 % of the forest understory in hedgerow forests. This invasive shrub typically has a sprawling crown 2-4 m above the ground. Thus, Lonicera maackii contributed to the greater high vegetation found in hedgerows and indirectly to less low vegetation structure by suppressing other understory plants. Web spider abundance was inversely related to vertical vegetation and positively related to low horizontal vegetation. Plant architecture that correlates to low web spider abundance is consistent with that of Lonicera maackii. The invasive plant may have directly affected web spiders through changing the type and availability of scaffolding necessary for web construction, and indirectly affected web spiders by suppressing annual herbs that may promote spiders (Buddle et al. 2000). Thus, Lonicera maackii may have contributed to the lower abundance and species richness of web spiders in hedgerow forests. No studies have attributed a negative impact of Lonicera maackii on animal communities. My study clearly shows that riparian forests in this region harbor greater web spider diversity than similarly sized hedgerow forests. Future studies may help clarify mechanisms driving these results. On a global scale, two of the greatest threats to biological diversity may be habitat loss and the spread of invasive species (Vitousek et al. 1997). It is possible that the diminished web spider diversity observed in hedgerow forests is a mutual effect between habitat fragmentation and the spread of an invasive plant. Regionally, future research should explore the direct effects of Lonicera maackii on animal populations. The emerging trend in ecology to investigate the role of terrestrial-aquatic exchange in food webs may help describe the apparent stream effect on the web spider community (Nakano and Murakami 2002, Power 2002). The heightened web spider abundance and diversity in riparian forests suggests they are better sources of generalist predators than hedgerow forests, which may be

40 important for limiting pest outbreaks in this agricultural landscape. Web spiders adjacent to streams appeared to constitute a unique community, whereas the web spiders present in hedgerow forests appeared to be a subset of those found in riparian forests. Thus, land management plans in the region should emphasize the conservation of riparian forests for maintaining natural predator populations and preserving biodiversity.

41 Agriculture Forest Stream

Riparian Forest

30 m

Hedgerow

Figure 1. Riparian forest sites compared with hedgerow sites of similar width. Locations of the 5 x 10-m quadrats are marked X.

s l 30 a u

d 25 vi i

d 20 n I

f 15

# o 10

ean 5

M 0

EDGE CENTER EDGE CENTER STREAM Hedgerow forest Riparian forest

12 s

e 10

eci 8 p S f 6

# o 4 an

e 2 M 0 EDGE CENTER EDGE CENTER STREAM Hedgerow forest Riparian forest

Figure 2. Means (± 1 standard error) of web spider abundance and species richness from quadrats sampled within hedgerow forests and riparian forests.

ecies 20

15 # of sp ted a 10

tim riparian

s Series1

E forests 5 Se hedgerriesow2 s 0 0 100 200 300 400 500 600 Number of individuals

Figure 3. Species accumulation curves (±1 SD) for predicted spider species richness in riparian forests and hedgerow.

30 25 ecies 20 sp f

# o 15 riparian edges

ted hedgerows

a 10 Seandri ecents1ers Series2 tim s

E 5 0 0 100 200 300 400 500 Number of individuals

Figure 4. Species accumulation curves (±1 SD) for predicted spider species richness in the edge and center quadrats of riparian forests and hedgerows.

200 R3E =0.228 λ

150

R2E R3S R3C 100 H1E H3C H3E R1S Axis 2 H3E R1C

50 H1E H2E R2S H1C R2C H2C H2E R1E λ=0.374 0 0 100 200 Axis 1

Figure 5. DCA ordination analysis of web spider species collected from 18 quadrats during the August sampling period. Samples are labeled (R) riparian, (H) hedgerow, (E) edge, (C) center, and (S) stream. Polygons have been added to illustrate the different quadrat types. Replicated sites of each riparian forest or hedgerow are numbered 1-3.

46 Table 1. Spider families, species, and relative abundance collected from riparian forests and hedgerows near Oxford, Ohio.

Family Species Riparian Hedgerows Total forests Araneidae Argiope aurantia Lucas 1 0 1 Cyclosa conica (Pallas) 52 56 108 Cyclosa turbinata (Walckenaer) * * * Eustala anastera (Walckenaer) 0 6 6 Larinioides cornuta Clerck 1 0 1 Mangora gibberosa (Hentz) 3 3 6 Mangora maculata (Keyserling) 66 21 87 Mangora placida (Hentz) 30 13 43 Metepeira labyrinthea (Hentz) 4 27 31 Micrathena gracilis (Walckenaer) 108 13 121 Micrathena mitrata (Hentz) 15 0 15 Micrathena sagittata (Walckenaer) 27 0 27 Neoscona arabesca (Walckenaer) 13 0 13 Neoscona crucifica (Hentz) 8 0 8 Verrucosa arenata (Walckenaer) 33 0 33

Tetragnathidae Leucauge venusta (Walckenaer) 25 13 38 Tetragnatha pallescens (Cambridge) 1 0 1 Tetragnatha elongata Walckenaer 36 0 36 Tetragnatha laboriosa Hentz 50 21 71

Linyphiidae Ceratinella brunnea Emerton 2 0 2 Ceratinopsis purpurescens Keyserling 1 0 1 Frontinella pyramitela (Walckenaer) 12 5 17 Neriene radiata (Walckenaer) 60 74 134

Theridiidae Argyrodes fictillium (Hentz) 1 5 6 Argyrodes trigonum (Hentz) 1 1 2 Coleosoma blandum O.P. Cambridge 0 1 1 Theridion albidum Banks 0 1 1 Theridion antonii Banks 1 0 1 Theridion frondeum Hentz 4 0 4 Theridion lyricum Walckenaer 3 2 5

Agelenidae Agelenopsis naevia (Walckenaer) 1 0 1 Agelenopsis pennsylvanica (C.L. Koch) 3 0 3 Total 562 262 824 * C. turbinata and C. conica where considered one morphospecies

Table 2. Mean (± SE) number of web spiders and web spider species collected in riparian forests and hedgerow forests. Pooled samples comprise all three quadrats from a site.

Comparison Treatment Count Mean Species Mean Richness Abundance Sampling June 6 6.8 ± 1.1 32.1 ± 1.2 Date August 6 11.3 ± 1.4 82.2 ± 1.2 (Pooled Sept/Oct 6 7.0 ± 1.0 46.0 ± 1.1 Sites)

(Pooled Hedgerow 3 6.2 ± 0.7 34.4 ± 1.1 Quadrats) Riparian 3 10.5 ± 1.0 71.5 ± 1.1

(Edge Hedgerow 6 5.5 ± 0.4 12.3 ± 1.1 Quadrats) Riparian 3 9.0 ± 0.8 28.5 ± 1.1

(Center Hedgerow 3 3.7 ± 0.5 7.2 ± 1.1 Quadrats) Riparian 3 8.0 ± 1.0 21.1 ± 2.0

Riparian Edge 3 9.0 ± 0.8 28.5 ± 1.1 Quadrat Center 3 8.0 ± 1.0 21.1 ± 1.2 Location Stream 3 6.2 ± 0.7 18.3 ± 1.2

Table 3. Repeated-measures ANOVAs for web spider abundance (ln) and richness. ANOVAs assessed the web spider community by pooling the three quadrats from each site, and in edge and center quadrats only. The fourth set of ANOVAs evaluated the web spider community exclusively in riparian forest sites using quadrat location (edge, center, and stream) as the main factor. All interaction effects were non-significant.

Comparison Measurement DF SS F P Significant Effect Pooled Quadrats Landscape Abundance 1, 8 2.419 37.734 .0036 riparian > hedgerow Treatment Richness 1, 8 84.500 27.161 .0065 riparian > hedgerow

Sampling Abundance 2, 18 2.684 18.34 .0010 August > Sept/Oct; Date August > June Richness 2, 8 78.111 13.650 .0026 August > Sept/Oct; August > June Edge Quadrats Landscape Abundance 1, 14 4.274 24.875 .0016 riparian > hedgerow Treatment Richness 1, 14 71.185 47.709 .0002 riparian > hedgerow

Sampling Abundance 2, 14 2.187 9.054 .0030 August > June; Sept/Oct > Date June Richness 2, 14 43.815 6.067 .0002 August > June; August > Sept/Oct Center Quadrats Landscape Abundance 1, 8 5.157 86.048 .0008 riparian > hedgerow Treatment Richness 1, 8 80.222 36.100 .0039 riparian > hedgerow

Sampling Abundance 2, 8 4.640 28.369 .0002 August > June; August > Date Sept/Oct Richness 2, 8 50.778 6.392 .0220 August > June; August > Sept/Oct Riparian Forest Sites Quadrat Abundance 2, 12 .904 5.633 .0420 edge > stream Placement Richness 2, 12 36.222 6.887 .0279 edge > stream

Sampling Abundance 2, 12 2.739 9.671 .0032 August > June; August > Date Sept/Oct Richness 2, 12 84.222 11.093 .0019 August > June; August > Sept/Oct

Table 4. Summary of vegetation structure results from three 2-factor ANOVAs. The ANOVAs evaluated web spider results using landscape treatment (hedgerow or riparian) and quadrat location (edge or center) as factors. Interaction effects were removed from the high and low horizontal vegetation analyses, as they were all non-significant. There was a significant interaction effect with the vertical vegetation lowest in riparian forest centers.

Measurement DF SS F P Significant Effect Treatment Horiz (High) 1, 12 1366.865 10.367 .0074 hedge > riparian Horiz. (Low) 1, 12 591.500 6.056 .0300 riparian > hedge Vertical Veg - - - - interaction effect, see below*

Quadrat Horiz (High) 1, 12 144.643 1.097 .3156 None (Center vs. Horiz. (Low) 1, 12 1219.556 12.487 .0041 agricultural edge > center Edge) Vertical Veg 1, 11 624.857 5.441 .0397 * riparian centers quadrats less than other quadrats

50 Table 5. Mean (± SE) vegetation structure values as measured in riparian forests and hedgerows by quadrat type. Unitless values represent the number of vegetation contact points along a meter stick.

Quadrat Count Horizontal Horizontal Vertical (High) (Low) Vegetation Hedgerow Agricultural Edge 6 36.2 ± 4 45.6 ± 4.5 71 ± 3.1

Center 3 28.6 ± 8.9 21 ± 4.3 65.7 ± 5.4

Riparian Agricultural Edge 3 15.3 ± 9.2 52.6 ± 4.3 57 ± 5.2

Center 3 10.3 ± 4.2 42 ± 5 24.7 ± 10.2

Stream 3 15 ± 5.6 40 ± 6.1 18.3 ± 12.8

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