Abstract Boundary Dynamics Across Habitat Edges

ABSTRACT

BOUNDARY DYNAMICS ACROSS HABITAT EDGES: EFFECTS ON BENEFICIAL INSECT SPECIES ABUNDANCE AND RICHNESS

by Alyssa Whu

Conservation practices, such as retaining forest habitat or planting field margins with flowering perennials, may enhance the abundance and diversity of beneficial insects by providing essential supplementary and complementary resources. The availability of resources influences the movements and distributions of beneficial insects across boundaries between crops and natural areas. In this study, I studied how crop and field-margin resources change the diversity and abundance of beneficial insects. Using experimental arrays of forage crops and field-margin strips planted along forest edges, I manipulated the resource quality of both forage crops and field margins. Combinations of field and margin plantings supported predictions from one or more hypotheses, but insect richness and abundance were generally higher in forage crops with higher habitat quality. My findings suggest that a greater understanding of the mechanisms driving consumer-resource interactions across natural habitat–crop boundaries is needed to guide conservation practices and enhance ecosystem services.

BOUNDARY DYNAMICS ACROSS HABITAT EDGES: EFFECTS ON BENEFICIAL INSECT SPECIES ABUNDANCE AND RICHNESS

A Thesis

Submitted to the

Faculty of Miami University

in partial fulfillment of

the requirements for the degree of

Master of Science

Department of Zoology

Alyssa-Kristine Whu

Miami University

Oxford, Ohio

2012

Advisor______

Thomas O. Crist

Reader______

Ann Rypstra

TABLE OF CONTENTS

LIST OF TABLES ...... iii LIST OF FIGURES ...... iv ACKNOWLEDGEMENTS ...... vii CHAPTER 1 – BACKGROUND AND CONCEPTUAL FRAMEWORK ...... 1 INTRODUCTION ...... 1 A CONCEPTUAL FRAMEWORK ...... 3 CONCLUSION ...... 5 FIGURES ...... 6 CHAPTER 2 – “Boundary Dynamics across Forest and Field Habitats: Effects on Species Richness, Abundance, and Composition of Insect Parasitoids, Pollinators and Predators.” ...... 8 INTRODUCTION ...... 8 METHODS ...... 10 RESULTS ...... 15 DISCUSSION ...... 18 TABLES ...... 23 FIGURES ...... 29 LITERATURE CITED ...... 47 Appendix 1: List of Coleoptera: Predators by family and species...... 50 Appendix 2. List of Hymenoptera: Parasitoids by family and species...... 51 Appendix 3: List Hymenoptera: Pollinators by family and species...... 53 Appendix 4: List of Hymenoptera: Predators by family and species...... 54 Appendix 5: List of Vegetation Sampled...... 55

LIST OF TABLES

Table 1. The best-fitting (lowest AIC) generalized linear mixed model of abundance for: (a) Coleoptera (Predators): distance, distance squared, margin type; (b) Hymenoptera (Parasitoids): distance, distance squared; (c) Hymenoptera (Pollinators): distance, distance squared; and (d) Hymenoptera (Predators): distance………………………………………………………………22

Table 2. The best-fitting (lowest AIC) generalized linear mixed model of richness for: (a) Coleoptera (Predators): distance, distance squared, margin type; (b) Hymenoptera (Parasitoids): distance, distance squared; (c) Hymenoptera (Pollinators): distance, distance squared; and (d) Hymenoptera (Predators): distance. ……………………………………………………………. 23

Table 3. The best-fitting (lowest AIC) generalized linear mixed model of abundance for: (a) Coleoptera (Chauliognathus pennsylvanicus): distance, and margin type; (b) Coleoptera (Photinus pyralis): distance, and margin type; (c) Hymenoptera (Figitidae sp1): margin type……………………………………………………………………………………………….24

Table 4. Ordination Statistics: Permutational Manova for ordinations using site and margin type for Vegetation Species. ………………………………………………………………………….25

Table 5. Ordination Statistics: Permutational Manova for ordinations using site, margin type and habitat (forest,edge,field) for Insect Species. ……………………………………………………26

Table 6. Summary of Findings ………….... ……………………………………………………27

iii

LIST OF FIGURES

Figure 1. A continuous response of species distributions across forest-field edges (left) predicts a null pattern of similar total abundance and richness (right) in forest, edge, and field habitats. ……………………………………………………………………………………………………..6

Figure 2. Patterns of species distributions (left) and total abundance and richness (right) predicted by the habitat specialization hypothesis...... 6

Figure 3. The pattern of insect species distributions in forest and high quality field habitats (left) predicts a correspondingly greater abundance in field habitat (right)……………………………7

Figure 4. Species that use complementary resources in forest and field are expected to occur along forest-field edges (left). Complementary resources use is predicted to have higher species abundance and richness along habitat edges (right), especially in enhanced margin plantings. ……………………………………………………………………………………………………..7

Figure 5. Study sites (1) Fitton property; (2) Ag Plot; (3) Fryman South; (4) Fryman North. ……………………………………………………………………………………………………28

Figure 6. Resource Quality of study sites: (1) High Quality- Fitton property; (2) High Quality - Ag Plot; (3) Low Quality - Fryman South; (4) Low Quality - Fryman North...... 29

Figure 7. Resource Quality of study sites: (1) High Quality- Fitton property and Ag Plot ; (2) Low Quality - Fryman North and Fryman South. ……………………………………………….30

Figure 8. Flight intercept/ pan traps using Lexan™ panes inserted into the bucket, arranged perpendicularly to avoid directional wind influence. Flight intercept/pan traps were placed on a wooden stand slightly above the crop. …………………………………………………………..31

Figure 9. Insect sampling using flight-intercept/pan traps and flower visitation counts. ……………………………………………………………………………………………………32

Figure 10. Figure 9. Plot layout for sampling of forest vegetation for trees (20 x 20 m), shrubs (5 x 5 m) and herbs (1 x 1 m). species. ……………………………………………………………………………………………………33

Figure 11. Variation in percent cover of red clover with distance from forest edge at the four sites and plots with enhanced and unenhanced field margins. ……………………………………………………………………………………………………34

Figure 12. Variation in flower density in 1-m2 plots in plots within enhanced and unenhanced field margins at the Fitton and Ag field sites. …..………..………..………..…………………...35

Figure 13. Abundance of predatory Coleoptera by site and plots with enhanced and unenhanced field margins. Lines are predicted relationships from best-fitting general linear mixed models. ……………………………………………………………………………………………………36

Figure 14. Species richness of predatory Coleoptera by site. The effect of margin type was excluded from the best-fitting model. …………………………………….……………………..37

Figure 15. Abundance of hymenopteran parasitoids with respect to distance to forest edge at the four study sites and the two types of field margins. ……………………………………………………………………………………………………38

Figure 16. Species richness of hymenopteran parasitoids with respect to distance, plot, and margin type. The null model was the best-fitting model. distance by site. …..………………...39

Figure 17. Abundance of bees in relation to distance from forest edge and site. Abundances did not differ by field margin type. …………………………………………………..……………...40

Figure 18. Species richness of bees with respect to distance to forest-field edges across the four study sites. The null model was the best-fitting model for bee richness. ……..………………..41

Figure 19. The abundance of the soldier beetle, Chaluiognathus pennsylvanicus, in relation to distance from forest edges across four sites and plots with enhanced and unenhanced field margins. ………………………………………………………………………………………….42

Figure 20. Abundance of the lightning beetle , Photinus pyralis, with distance from the forest edge and site. Relationships did not differ between plots with enhanced and unenhanced field margin types. …………………………………………………………………………………….43

Figure 21. The abundance of the hymenopteran parasitoid, Figitidae morphospecies 1 with distance from the forest edge and across sites. Abundances also differed between plots with different field margin types. ……………………………………………………………………..44

Figure 22. MDS ordination for field herbaceous plants, forest trees, predatory beetles and parasitoids. Site abbreviations: AG=Ag Field, FT=Fitton, FRN=Fryman North, FRS=Fryman South. Field margin type abbreviations: U=unenhanced, E=enhanced……………….………...45

ACKNOWLEDGEMENTS

I would like to thank my advisor, Tom Crist, for his guidance and support on this project, even through all of the statistical difficulties. I would like to acknowledge my committee members, Dave Gorchov and Ann Rypstra, for their invaluable advice and feedback. In addition, I would like to thank past and present Crist lab members for their important help: Jason Nelson for answering my million and one questions, Kaitlin Uppstrom Campbell for her editorial suggestions, Alex Wright for the physical labor he endured out at the ERC during the summer of 2010 and Kelsey Seaman for her hours of pinning in the lab. I would like to thank the ERC staff; especially Rodney Kolb and Clayton Kantner, for helping me mow and maintain my research plots and helping me throughout the field season. Thank you to the Fitton family for allowing me to use their property for my research. I would like to thank my fellow graduate students, Mia Hall and Amber Rock, who provided me with the assurance that I was not alone in the madness. Also, I would like to thank my family and friends for their long distance support. Finally, I would like to thank Ryan Holdridge, for his love and support throughout this entire process, especially helping me through all of my thesis woes.

Funding for this project was provided by Sigma Xi and Miami University.

vii

CHAPTER 1 – BACKGROUND AND CONCEPTUAL FRAMEWORK INTRODUCTION

Habitat structure and composition in agricultural landscapes influence species diversity, abundance and interaction (Tscharntke et al. 2005). The mosaic structure of agricultural landscapes consists of large areas of cropped fields and smaller patches of adjacent natural and semi-natural habitats, often with large amounts of habitat edge between crop- and non-crop areas. Edges have an effect on direct and indirect species interaction across boundaries, serving as a filter or barrier to cross-edge dispersal (Cronin 2009). The resulting boundary dynamics are important determinants of species distribution, movement and processes (Fagan et al. 1998). Intensification of agricultural systems results in increased fragmentation and subsequent increases in habitat edge between production and natural areas. Habitat edges are defined as the boundary between habitats with distinct resource qualities (Ries & Sisk 2004). Edges define crop and non-crop habitats and create boundaries that differentiate the resource availability and distribution, or resource quality, within each habitat. Resource quality affects diversity, abundance and interaction of species, such as, insect pests, pollinators and predators (Rand and Louda 2006). Habitat qualities vary based on the availability and distribution of resources. High resource availability within a habitat, as compared to the adjacent habitat, indicates a high quality habitat that may support a higher species richness or abundance. Low resource availability within a habitat, as compared to the adjacent habitat, indicates a low quality habitat. Across adjacent habitats, resource distributions will complement or supplement each other. Landscape complementation occurs when different required resources occur in adjacent or nearby habitats (Dunning et al. 1992). Species require several resources, such as, foraging, nesting, and overwintering sites. Depending on species and habitat, these resources may be found within one habitat type or across several (Landis et al. 2006). Complementary resources improve the availability of alternative food sources, such as prey or hosts, to insect species within the crop area. Adjacent natural habitats also provide nesting, shelter and overwintering sites. Many bees that forage in crops also nest in adjacent natural areas (Chacoff and Aizen 2006). Resource proximity between the natural and crop areas enhances the quality of the boundary. Natural enemies that are specialists, such as parasitoids, often require non-host food sources. Access to both nectar and hosts enhances survival and fecundity of parasitoids, increasing their

effectiveness at controlling pests. Studies suggest that parasitoids have a positive edge response, in which species increase near the edge, to the crop-noncrop interface (Rand et al. 2006). Generalist natural enemies may or may not have a positive edge response with access to complementary resources, depending on the availability of suitable prey in noncrop habitats. In cases where generalists can exploit alternative prey from natural areas, they are predicted to have a positive edge response. If suitable prey are available in cropped areas, however, generalists may not need alternative prey, resulting in a neutral or negative edge response (Tscharntke et al 2005). Supplementation occurs when adjacent habitats contain the same or similar necessary resources for a species. Natural and crop areas contain supplementary resources. According to Ries and Sisk (2008), habitats of similar quality that only offer supplementary resources will result in a neutral edge response of insect species. However, natural and crop areas generally differ in habitat quality. Agricultural landscapes commonly planted as monocultures and are noted for low pollinator diversity. Chacoff and Aizen (2006) tested whether flora in natural remnants acted as a supplementary resource for pollinators of grapefruit. The authors found that as distance from the edge increased the diversity of pollinators decreased. Visitation and frequency was highest near the forest edge. Their study suggests that supplementary resources in habitats of unequal quality will result in a positive edge response. Thus, both theory and empirical studies suggest that resource availability along habitat boundaries may influence the distribution and abundance of beneficial insects in crops, and therefore have an important role in driving ecosystem services such as biological control and pollination. Cross-boundary resource subsidies are an important mechanism by which habitat edges influence the dynamics of ecological processes (Tscharntke et al. 2005). Species using multiple habitats, such as natural enemies requiring hosts and nectar or pollinators needing nesting sites and pollen, can take advantage of resource subsidies from adjacent habitats. Natural and semi- natural habitats within agricultural landscapes can provide these needed complementary and supplementary resources. The availability of resources in field margins and surrounding natural habitats interact with those found in crops to influence the movements and distributions of beneficial insects across boundaries between crops and natural areas (Holzschuh et al. 2010). Patterns of species abundance and shifts in species composition have been shown to vary within habitats, with respect to distance from the edge. Traditional focus of edge effects have

demonstrated changes in species diversity and abundance (e.g., Fagan et al. 1999; Ries and Sisk 2004; Ries et al. 2004). Edge responses have been classified as: (1) positive edge response - species abundance and richness increase near the edge; (2) negative edge response - species abundance and richness decrease near the edge; and (3) neutral edge response- species abundance and richness remain the same near the edge (Ries et al. 2004). However, the consumer-resource interactions underlying patterns of diversity and abundance are poorly known, and a conceptual framework has not been established to understand and predict these patterns. Resource availability and distribution can provide a mechanistic basis for understanding species edge responses.

A CONCEPTUAL FRAMEWORK

I propose a conceptual framework using a set of alternative hypotheses to explain patterns of beneficial insect species distributions across forest- field boundaries. These hypotheses lead to testable predictions of patterns of insect species distribution and abundance across habitat boundaries between forest and crop systems. These hypotheses are not mutually exclusive, and some combinations of resource distributions in forest, field, and edges may match predictions from one or more hypotheses.

Continuous Species Response Hypothesis (Null hypothesis): Insect species have a continuous response species distribution and abundances across forest-field boundaries with a mixture of habitat generalists and specialists in forest, edge, and field habitats.

Species differ in their resource needs and therefore in their habitat types. Some species are found in many habitat types, as they have general resource needs. Other species may only occur in a few specific habitat types that contain specific resources. The continuous response hypothesis of species distributions across habitat types leads to the prediction of a null pattern of similar species abundance and richness across forest-field boundaries (Figure 1).

Habitat Specialization Hypothesis: Insect species are specialists in either forest or field habitats, resulting in non-overlapping species distributions between habitats and lower abundance and richness along forest-field edges.

In contrast to the continuous response hypothesis, the habitat specialization hypothesis predicts a greater total abundance of insects in each habitat as compared to the edge, but similar levels of richness in edge and non-edge habitats (Figure 2). This pattern is most likely to be observed in plots with forest-field boundaries with low- quality field margins, because differences in habitat quality between forest and margin habitats are likely to be less important than between forest and crop habitats.

Habitat Quality Hypothesis: Differences in habitat quality between field habitats will influence the distribution of beneficial insects across forest-field boundaries.

Habitat quality varies according to the resources it can provide, such as prey, nesting, foraging and overwintering sites. Habitat quality is measured by the availability and number of resources (plant diversity and flower density); high quality habitats will have more available resources than low quality habitats (Figure 3). Forage crops, such as clover or alfalfa, have high levels of flowering resources and alternative prey than grass or cereal fields (Diekötter et al. 2007). Species abundances should be greater in fields with higher levels of flowering resources. This effect should be altered in the presence of enhanced field margins, planted with additional flowering forbs.

Complementary Resources Hypothesis: Complementary resources in forest and field habitats increases access of resources to insects near the habitat boundary, resulting in higher species richness and abundance along edges than in adjacent habitats.

Complementarity leads to higher richness and abundance along edges. This effect should be greater when margins have greater or enhanced resources. Therefore, insects that use resources in two or more habitats should have higher abundances in close proximity to both habitats, this leads to higher species abundance and richness at habitat boundaries. In addition, enhanced and unenhanced field margins differ in the resources they provide. Enhanced field margins provide complementary floral resources to forest-dwelling insects and supplementary floral resources to insects in field habitats. The complementary resource hypothesis leads to the

prediction that species abundance and richness peaks across the forest-field boundary (Figure 4), and should be especially important in forage crops with flowering plants in field margins. These boundary dynamics or edge effects have been qualitatively described in many studies without any predictive framework (Ries & Sisk 2004).

CONCLUSION

Edge patterns have been extensively studied, showing various species edge responses. Patterns of species abundance and richness across boundaries are among the most described and the habitat quality, habitat specialization, complementary resources and continuous species distribution hypotheses provide a working framework to explain these trends. Understanding these patterns is of importance, as they serve as a functional link between habitat boundaries and ecosystem dynamics (Fagan et al. 1999). Edges mediate effects such as species interactions. Pollination and biological control are important ecological dynamics that may be affected by species edge responses across crop and non-crop boundaries. Changes in species distributions and the subsequent influence on species dynamics can be predicted by resource quality and use by the insect species. As agricultural intensification and resulting edges continues to increase, resource quality may provide a mechanism for understanding species distribution, movement and processes.

FIGURES Species Distributions 12

Continuous Response 10 15 8 Forest Margin Field 10 6 4 5 2 0 0

-10 -5 0 5 10 15 20 -10 -5 0 5 10 15 20

Figure 1. A continuous response of species distributions across forest-field edges (left) predicts a null pattern of similar total abundance and richness (right) in forest, edge, and field habitats.

Figure 2. Patterns of species distributions (left) and total abundance and richness (right) predicted by the habitat specialization hypothesis.

Species Distributions 12

Habitat Quality 10 15 8 Forest Margin Field 10 6 4 5 2 0 0

-10 -5 0 5 10 15 20 -10 -5 0 5 10 15 20

Figure 3. The pattern of insect species distributions in forest and high quality field habitats (left) predicts a correspondingly greater abundance in field habitats (right).

CHAPTER 2 – “Boundary Dynamics across Forest and Field Habitats: Effects on Species Richness, Abundance, and Composition of Insect Parasitoids, Pollinators and Predators.”

INTRODUCTION

Natural and semi-natural habitats surrounding crop systems are important determinants of ecosystem services provided by insects, such as pollination and biological control. Agricultural intensification results in the loss of natural and semi-natural habitat with corresponding reductions in ecosystem services. Pollinators and natural enemies require nesting or breeding habitat, and floral or host resources that are often absent from crops. Conservation practices, such as retaining forest habitat or planting field margins with flowering perennials, may enhance the abundance and diversity of beneficial insects by providing essential supplementary and complementary resources. The availability and distribution of resources influences the movements and composition of beneficial insects across boundaries between crops and natural areas. Habitat edges join resources of adjacent habitats, thereby increasing access to resources that are spatially separated. Edges provide access to resources that are absent from or similar to those in the adjacent habitat, complementary and supplementary resources, respectively. A concentration of complementary or supplementary resources at the edge is a strong determinant of a species’ abundance and richness response across a boundary. Species responses can be (1) positive edge response, species abundance and richness increases near the edge; (2) negative edge response, species abundance and richness decreases near the edge; (3) neutral edge response, species abundance and richness remains the same near the edge (Ries et al. 2004). A species response varies not only with resource distribution and availability but the demands of its survival and reproduction.

Biological control is an important ecosystem function that depends on the colonization of natural enemies. Crop areas are subject to high disturbance and rely on non-crop areas as a source of natural enemies. Natural habitats are important non-crop areas, which allow for establishment or as a refuge and source of colonization for natural enemies, due to the complementary and supplementary resources they can provide. Increased abundance along these edges allows for spillover or a mass movement, of natural enemies into the crop area, increasing

rates of parasitism (Tscharntke et al. 2007). Supplemental floral resources are expected to increase pollinator visits, influencing other trophic levels (Diekötter et al. 2007). Increased pollination affects seed set which, in turn, may influence the abundance of seed predators and their parasitoids (Diekötter et al. 2007). Cross-habitat spillover from the crop into the noncrop habitat is also likely, but is often ignored in studies of crop systems (Rand et al. 2006). Natural enemy and pollinator spillover into adjacent noncrop areas reduces their beneficial impacts in the crop. Crops that rely heavily on pollination may be negatively affected by pollinator spillover into the non-crop habitat. Natural enemies exploiting native herbivores in the noncrop areas release crop pests from predation. Spillover from crops into the surrounding landscape can increase abundances and modify species dynamics in the non-crop area. The effects of cross-habitat dispersal across the crop-noncrop interface are contrasting, as studies and reviews (e.g., Tscharntke et al. 2005; Tylianakis et al. 2006; Cronin 2009; Holzschuh et al. 2010) have shown natural habitats as both a source and a sink for beneficial insects. Resource quality is a possible underlying mechanism for these boundary dynamics. Conservation practices, such as retaining forest habitat or planting field margins with herbaceous plants, may enhance the abundance and diversity of beneficial insects by providing essential complementary and supplementary resources (Kleijn et al. 2006). Most existing studies are descriptive, however, and few manipulative experiments of field-margin habitats have been conducted, and even fewer have elucidated the mechanisms underlying patterns of insect diversity and abundance across crop and non-crop edges. Using an experimental model system, I manipulated resources at natural habitat–crop boundaries to provide a greater understanding of how they might guide conservation practices to enhance ecosystem services.

In this study, I determined the effects of margin type and distance from the crop (red clover or grass fields) and non-crop (forest) edge on the species richness, abundance, and composition of predatory beetles and wasps, and hymenopteran pollinators and parasitoids. For these insect functional groups, higher prey abundance and flower availability in fields were assumed to provide higher quality habitat, whereas forest habitat may provide lower quality but potentially complementary resources. Differences in floral abundance in the margins between habitats were expected to modify differences in quality and complementarity of forest and field habitats. I tested three alternative hypotheses on the roles of habitat quality, specialization, and complementarity in determining species distributions and diversity across forest-field boundaries

(Chapter 1). The habitat quality hypothesis is based on differences in resource availability between clover-grass field habitats than in forests, which lead to greater abundance and richness of beneficial insects in clover and greater spillover from field-dwelling insects into forest habitats. The habitat specialization hypothesis suggests that insects use primarily field or forest habitat, but not both, leading to a prediction of greater total abundance of insects in each habitat as compared to the edge but similar levels of richness in edge and non-edge habitats. The complementary resource hypothesis applies if species use both habitats, leading to the prediction that species abundance and richness peaks across the forest-field boundary. This should be especially important in clover-grass plots with enhanced margins if complementary resources drive species response. Finally, the null hypothesis of continuous species distributions across habitat edges would apply if species distributions and abundances across forest-field boundaries are unrelated to differences in resource quality in the two habitats.

METHODS

Study Site & Experimental Design

To test these alternative hypotheses, replicated pairs experimental plots, 20 x 20 m in size, were planted with red clover and orchard grass adjacent to forest edges, which created habitat boundaries between a forage crop and forest. A 5-m margin between the plots and the forest edge were planted with orchard grass (unenhanced controls) or a native mix of annual and perennial wildflowers and orchard grass (enhanced) to change the resource quality of the field margins. Pairs of plots with enhanced or control field margins were replicated in four blocks (Fryman North, Fryman South, Fitton and the Ag plot), located 1 km apart at the Miami University Ecology Research Center near Oxford, OH (Figure 5). Field plots were planted with pure medium red clover (Trifolium pratenese). Plantings of enhanced or control margins were randomly assigned to plot pairs within each block. Plot pairs were separated by 20 m of bare ground, which were maintained by mechanical cultivation throughout the study. There were unexpected differences in planned and actual patterns of vegetation establishment at the four different sites and their margins. Red clover failed to establish within the Fryman North and Fryman South fields. These plots consisted of only a mixed grass vegetation cover. The red clover in the Fitton property and Ag plot established as red clover- grass mixtures. Annual and perennial forbs also did not establish in the enhanced-margin

treatments at the Fryman North and Fryman South sites. At these locations, both margins established only as orchard grass. A diverse array of flowering forbs was present in the enhanced margins at both the Fitton property and Ag plot. The actual pattern of plant establishment therefore created two blocks with fields and margins of relatively low resource quality (Fryman N and S), and two blocks with fields of higher resource quality (Fitton and Ag plot) and experimental manipulations of margins with high or low resource quality (Figure 6) and (Figure 7).

Study Organisms: Crop & Insect Species

Red clover (Trifolium pratenese) was chosen as the focal crop because it supports a diverse assemblage of flower-visiting and predatory insects, and relies heavily on insect pollination for seed production (Free 1965, Plowright and Hartling 1981). The effects of landscape structure on its pollinators and parasitoids have been examined at my study site (e.g. Diekötter et al. 2007). Results indicated wild bees, honeybees, bumblebees, and butterflies as the primary visitors, obtaining both food and nectar resources from red clover. Natural enemies, both generalist predators and parasitoids, also use diverse assemblage of herbivores associated with clover (Haynes and Crist 2009). Therefore, beneficial insects that function as pollinators and natural enemies - predators and parasitoids - were the focus of this study.

Insect Sampling

Combined flight-intercept/yellow pan traps were used to quantify insect diversity and abundance along transects spanning the forest habitat, field margin, and crop at 5-m intervals. Flight intercept traps sample species in the immediate area and those that pass by on their dispersal flights. Yellow pan traps attract flower-visiting insects and parasitoid wasps. Flight intercept/pan traps used were a modification of the design from Duelli et al. (1999). Yellow buckets (7.6 L; 29 cm diameter x 21 cm deep) were used for pan traps; yellow is known to attract flower visitors. To intercept flying insects, Lexan™ panes (41 cm) were inserted into the bucket; panes were arranged perpendicularly so as to avoid directional wind influence. Flight intercept/pan traps were placed on a wooden stand slightly above the crop, as described by Duelli (1999) (Figure 7). Water, with soap to reduce surface tension, was added to the bucket. Each plot contained a single transect of 8 traps that was set through the center of the crop, margin and

forest edge. Traps were 5 m apart, starting at the center of the field margin (2.5 m from the forest edge) and spanning 22.5 m out into the field and 12.5 m into the forest (Figure 8). Traps were left out for 1 week, for three sampling periods in July, August and September. When collected, samples were screened through noseum netting (Nicamaka™) and then washed and stored with 70% ethanol into Nalgene™ bottles for storage and later sorting and identification.

In the laboratory, samples were sorted to separate Coleoptera and Hymenoptera from other orders of insects. Only beneficial predators, pollinators and parasitoids of both groups were pinned or pointed and then later identified. Focal predatory coleopteran families were identified to species. The most abundant families were Carabidae, Coccillinidae, Elateridae, Meloidae and Staphylinidae. Additional families are noted in Appendix 1. Hymenopterans were sorted into parasitoids, pollinators and predators and identified to family and species or morphospecies. Brachonidae, Ichneumonidae and Pteromalidae were the most abundant parasitoid groups with five additional groups noted in Appendix 2. Pollinators identified belonged to the superfamily Apoidea, with families noted in Appendix 3. Pompilidae and Vespidae were the most important predator families with three additional families noted in Appendix 4.

All species were classified into one of the following groups, according to their recorded life histories: predator, parasitoid or pollinator. Predators were classified as any hymenopteran or coleopteran insect that consumed another living organism at any life stage. While many insect species may passively pollinate, species were only included as pollinators if they actively collected and transferred pollen. Parasitoids were families of Hymenoptera whose larvae are parasites that kill its host. Species were excluded if their functional history noted that they did not meet the criteria of pollinator or predator e.g. species of Anthicidae. All species of parasitoids were included due to sparse natural histories on these families.

Vegetative Cover: Field

Cover of red clover, other forbs, and grasses, was recorded by species in fields and field margins in all plots. Sampling occurred once during the last flight-intercept/ pan trap measures. Cover was recorded by species in one of eight categories of percent cover (0, 1, 5, 10, 25, 50, 75 or 100%) in two 1- m2 quadrats placed at 5-m intervals starting in the center of the field margin (2.5 m) to the outer edge (22.5 m) of the plot (Figure 8.).

Vegetative Cover: Forest

Trees ≥10 cm diameters at breast height (DBH) were recorded within a 20 x 20 m block that bordered the forest edge and was centered on the insect sampling transect. The estimated percent cover of each species of shrub was sampled in 5 x 5 m quadrats that were regularly spaced within four quadrants of each 20 x 20 m block. Herbaceous percent cover was measured in two 1 x 1 m quadrats nested diagonally within the 5 x 5 m quadrats (Figure 9). Percent cover was recorded for shrubs and herbaceous plants in one of eight categories of percent cover (0, 1, 5, 10 25, 50, 75 or 100%).

Flower Counts in the Forest, Margin & Field

Flowers and inflorescences of each species were counted in the forest, margin and field, once during each insect sampling period (July, August, and September). Flowers and inflorescences were surveyed in 2 x 2 m quadrats parallel to the flight-intercept/pan traps through the clover plot, margin and forest of each block. Woodland flowering species in the adjacent forest habitats were surveyed, while red clover and various forb species were surveyed in the margin and field (Figure 8). Red clover and other flowering species were not flowering during all three sampling periods; therefore, data was pooled for analysis.

Statistical Analysis: Insect Abundance and Richness

Data were analyzed to assess insect species abundance and richness in relation to distance from the edge and margin type (enhanced vs. unenhanced). Catch was dependent upon other factors in addition to abundance, such as activity and trapability. Abundance is therefore not an absolute measure of density but instead is a relative measure of insect population size in that immediate area and those that are dispersing through a habitat. Samples were first pooled across sampling periods and then compared by trap, margin type, and site. Although pooling removes the seasonal variation in insect abundance across boundaries, separate analyses by season were not possible because of sparse data. There were a total of 8 traps, 4 traps in the clover/grass field, 1 trap in the margin, and 3 traps in the non-crop (forest). Separate models were developed for the species abundance and richness of coleopteran predators, hymenopteran predators, pollinators and parasitoids. Models were also developed for single species of each functional

group that had a sample size of 50 or more individuals. General linear mixed models, with Poisson response variables were tested using the lmer function in lme4 package of R software (R Development Core Team, 2009) with site as a random effect. Fixed effects included distance, distance squared (to allow for non-linear relationships), margin type, and the interaction of margin type and distance. Distance was used to indicate both habitat type (field or forest) and the proximity to adjacent habitat types. The null model was statistically represented as varying only by site and did not include any of the predictors.

The lowest Akaike Information Criteria (AIC value) was used to choose the best fitting statistical models. During model selection, quadratic effects of distance were always removed before linear effects. AIC values of competing models that differed by only a few points or had the same values than the model with the least number of predictors was selected based on the principle of parsimony (Burnham & Anderson, 2002).

Statistical Analysis: Vegetative Cover and Flower Densities A similar modeling approach to analyzing insect abundance and richness was used to analyze red clover cover at the sites and flower densities in the margins. Due to low counts of flower densities during each survey data was pooled across all three sampling periods. To assess overall differences in plant species in the field, a Gaussian response was used and clover or grass cover was analyzed as a continuous variable, using the lmer function in lme4 package of R software (R Development Core Team, 2009) with site as a random effect. To analyze flower density samples in the margin, general linear mixed models, with Poisson response variables were also tested. The lowest Akaike Information Criteria (AIC value) was used to choose the best fitting statistical models.

Statistical Analysis: Species Composition

Variation in insect and plant species composition among habitats (field, edge or forest), margin type (enhanced or unenhanced), and site was analyzed using metric multidimensional scaling (MDS) ordination with Bray-Curtis dissimilarity (Anderson and Willis 2003). MDS ordinations were used to assess composition of herbaceous plants in the field, trees in the forest, and predatory beetles and parasitoids in the field-edge-forest habitats. The capscale function in the vegan package of R was used to conduct MDS. To partition the total variation in species

composition, permutational multivariate analysis of variance (PERMANOVA) was also conducted for each ordination, using site, margin type, and habitat type as hierarchical factors. Ordinations were not completed on hymenopteran pollinators or predators due to sparse data matrices.

RESULTS

Red Clover Percent Cover Red clover percent cover varied among the four sites (Ag plot, Fitton, Fryman North, and Fryman South). Fryman North and Fryman South had little or no clover established in the field, whereas the Fitton and Ag plot sites had red clover present at similar levels (Figure 10). Percent cover of red clover in the Fitton and Ag plot varied across the field as distance from the forest edge increased (Figure 10). However, the degree to which percent cover increased and decreased was different between sites.

Flower Counts in Field Margins

The enhanced and unenhanced margin treatments differed in their flower abundance at two of the four sites. The results showed that annual and perennial forbs did not establish at the Fryman North and Fryman South sites. At these locations, both margins established as only orchard grass. A diverse array of flowering forbs was present in the enhanced margins at both the Fitton property and Ag plot (Figure 11).

Insect Abundance and Richness

A total of 231 insect species of 1755 individuals was recorded across the three sample periods. Total predatory beetle species sampled was 62 with 766 individuals. A total of 169 hymenopteran species was sampled and separated into parasitoids, pollinators and predators. There were 989 individuals, comprising of 104 parasitoid species with 671 individuals, 35 pollinator species with 224 individuals, and 30 predator species with 94 individuals.

Predatory Coleoptera: Insect Abundance and Richness The best fitting model, which included distance, distance squared and margin type, was significant as compared to the null model (X² = 277.3, df = 12, p < 0.0001). Across all sites there

was an initial increase in beetle abundance as distance from the forest edge increased. At one of the sites (Fitton), abundance increased continuously across the field but at three of the sites (Ag plot, Fryman North and Fryman South) there was a peak in abundance and then a decrease across the field (Figure 12).

The best fitting model to explain beetle richness in all sites included the effects of distance and distance squared and was significant when compared to the null model (X² = 60, 52, df = 7, p < 0.0001). At each site, beetle richness increased as distance from the forest edge increased. Beetle richness peaked in the field for all sites but to varying degrees in slope (Figure 13).

Parasitoids: Insect Abundance and Richness The best fitting model included distance, distance squared, margin type and the interaction of margin type and distance, as the most important variables. In a likelihood ratio test against the null, this model was significant (X² = 30.06, df = 9, p < 0.0004). Patterns of parasitoid abundance varied per site. At the Ag and Fryman sites, abundance was a continuous response as distance from the forest edge increased. The Fitton site showed an increase at the edge with abundance peaking in the field. Parasitoids in the Fryman North site showed a decrease in abundance across the site as distance from the forest edge increased (Figure 14).

Parasitoid richness was best explained by distance from the forest edge. The model was not significant when compared to the null (X² = 2.701, df = 3, p = 0.440). Patterns of richness varied per site. The Fitton and Fryman South sites showed an increase in richness away from the forest, peaking at the edge and then decreasing across the field. Richness at the Ag plot decreased with distance away from the forest edge. The Fryman North site showed higher richness in each habitat with a decrease at the edge of both sites (Figure 15).

Pollinators: Insect Abundance and Richness The general linear mixed model showed that the best fitting model with the lowest AIC contained the effects of distance and distance squared and was significant as compared to the null model (X² = 52.58, df = 7, p < 0.0001). Pollinator abundance, across sites, was significantly influenced by distance from the forest edge and distance squared. Abundance for all sites

increased as distance from the forest edge increased and peaked in the field, around 10m. The slope of each peak varied but showed a similar trend (Figure 16).

The best fit model to explain pollinator richness at all sites also included the effects of distance and distance squared. At each site, pollinator richness increased as distance from the forest edge increased. Pollinator richness peaked in the field for all sites but to varying degrees in slope (Figure 17) (X² = 38.06, df = 7, p < 0.0001).

Predatory Hymenoptera: Insect Abundance and Richness

Abundance and richness patterns for predators were similar among all sites. The best fitting model to explain both of these patterns included only the effects of distance. Abundance and richness were continuous across all sites for predatory hymenoptera (Figure 19). The null model was accepted as the best for abundance and richness (X² = 1.612, df = 3, p = 0.228).

Single Species

Abundance patterns were analyzed for two predatory species of Coleoptera, Chauliognathus pennsylvanicus and Photinus pyralis, as well as that for one parasitoid species, Figitidae_sp1. The best fitting model for Chauliognathus pennsylvanicus contained both distance, distance squared and margin type and was significant when compared to the null model (X² = 134.78, df = 18, p < 0.0001). At all sites, abundance patterns increased across habitats, peaking in the field. Photinus pyralis abundance patterns were best explained by the mixed model that had only distance as a predictor value. The Fitton and Ag plot showed abundance increasing as distance from the forest edge increased. The field had higher abundances than the forest at these sites. Both the Fryman North and South sites had similar patterns. Abundance was a continuous response across habitats (X2=47.67, df=3, p < 0.001). The best fitting model that explained patterns of Figitidae _ sp1 across habitat boundaries was distance, distance squared and margin type. Patterns of abundance were similar across the Ag plot, Fryman North and Fryman South sites. Abundance at these sites was continuous across the habitats. Abundance in the Fitton property increased at the margin and then decreased in the field (X² = 26.317, df = 5, p < 0.0001).

Species Composition

In Figure 21, MDS ordinations for field herbaceous plants, forest trees, predatory beetles and parasitoids were shown in a four plot graph. Permutational MANOVAs of the metric multidimensional scaling (MDS) ordinations using site, and margin type showed that 76% of the variation for trees species was explained by site (df = 3,7, p = 0.004). The variance of herbaceous plant species at each site and margin type was 95% explained by site (df = 3,7, p = 0.008). MANOVAs of predatory beetles and parasitoids for each of the ordinations used sites, margin type and habitat (forest, edge, and field) to explain the variance in species composition. Site and habitat type were shown to significantly explain species composition of predatory beetles. Site explained 17% of the variance (df =3, 23, p = 0.011) and habitat explained 28% of the variance (df = 2,23, p = 0.001). For parasitoid composition, MDS showed that site significantly explained 19% of species variance ( df = 3,23, p = 0.001). Habitat also significantly explained composition, 13% (df = 2, 23, p = 0.004).

DISCUSSION

My study supports the role of resource availability and distribution on insect species patterns of richness, abundance and composition across varying habitats. Previous research (e.g., Fagan et al. 1999; Chacoff and Aizen 2006; Cronin 2009) has shown how habitat edges influence patterns of species abundance and richness. However, only a few studies have elucidated the possible underlying mechanisms of the patterns observed (Ries and Sisk 2004; Ries et al. 2004; Tscharntke et al. 2006). In my study, I proposed a conceptual framework for understanding patterns of insect species abundance and richness across habitat boundaries. Specifically, my main objective was to determine how the effects of margin type, habitat type (forest, edge, field) and distance from the crop (red clover field) and non-crop (forest) edge would influence the abundance and diversity of predatory beetles and wasps, and hymenopteran pollinators and parasitoids.

General linear mixed model analysis showed that resource quality among sites and margin types was different. Results demonstrated that patterns of abundance and richness varied

among insect species and across sites. More specifically, abundance and richness variation was dependant on these resource quality differences that were predicted by margin type, habitat type and distance. Therefore, the habitat quality and continuous species response hypotheses were the most supported in this study. There was little or no support for the habitat specialization and complementary resources hypotheses. The habitat quality hypothesis was strongly supported by predatory Coleoptera and hymenopteran predators, as abundance and richness was greater in the field for all sites. Parasitoids showed little support for this hypothesis as abundance and richness were not greater in the field for all sites. Predatory coleopteran richness and abundance were greater in the field than in the forest. Species composition was distinct, non overlapping species between the forest and field habitats, showing support for the habitat specialization hypothesis. In both individual species of Chauliognathus pennsylvanicus and Photinus pyralis, abundance was greater in the field than in the forest. Hymenopteran pollinator richness and abundance were greater in the field than in the forest for all four sites, supporting the habitat quality hypothesis. Parasitoid abundance at the Fitton field was greater than in the forest, supporting the habitat quality hypothesis but at the Fryman North, Fryman South and Ag field, the continuous response hypothesis was supported. The site-level differences in support of these two hypotheses suggest that greater habitat quality in fields depended on red clover as a high-quality resource. Species composition of parasitoids did not support any of the proposed hypotheses as composition in the field was shown to be a subset of that in the forests. Abundance of Figitidae sp1 was greater in the field at the Fitton site, supporting the habitat quality hypothesis but supported the continuous response hypothesis at the other three sites. Predatory hymenoptera strongly supported the continuous response or null hypothesis. The richness and abundance of predatory hymenoptera was similar in both habitats and between all sites (Table 6). Generalist predatory beetles, such as Carabids or Coccillinids, are strong dispersers (Rand and Louda 2006). Their study showed how prey and natural habitat adjacent to crops influenced beetle movement. According to the habitat quality hypothesis, in my study, greater species abundance and richness will occur in habitats of higher resource quality. General predatory beetle abundance patterns were highest in the field. Due to stronger dispersal abilities, abundances may have been greater due to abundant prey species in plots with red clover.

Species composition analysis showed that vegetative cover of the field when compared to the forest was significantly different. Two adjacent habitats that differ in cover provide complementary or supplementary resources. Pollinators, like parasitoids, can utilize alternative resources. Chacoff and Aizen (2006) found greater and more diverse pollinator densities in grapefruit flowers that were near forest remnants. They also noted that pollinators declined as distance from the forest edge increased because of the reduced accessibility to both habitats. Nesting bees, such as bumble bees, were more likely to be found near the forest edge than other pollinators. In my study, nine species of bumble bees were recorded. Bumblebees, according to Free (1965) are the most common pollinators of red clover, which is important as red clover is self sterile. In my study, bumble bees and other general pollinator patterns across sites illustrated higher peaks of abundance and richness near or at the edge of both habitats, as predicted by the complementary resource hypothesis. Abundance and richness data for predatory Coleoptera increased at the edge and was greatest in the field. These patterns are expected if the field offered a more diverse and abundant prey resource, therefore suggesting the resource quality hypothesis. Single species analysis of Chauliognathus pennsylvanicus and Photinus pyralis also showed similar trends of greater abundance and richness near the edge and in the field. Photinus pyralis correlated with clover cover among sites. Abundance and richness were greater at the sites with highest red clover cover. Patterns such as these may suggest an important resource for Photinus pyralis. However, ordinations of species composition revealed that species of predatory Coleoptera in the field and forest were different and not overlapping. This suggests that predatory beetles readily dispersed among habitats with strong species-sorting patterns of species within their preferred habitat types. . There was also greater heterogeneity in beetle composition among sites in forest compared to field habitat. Consequently, beetle abundance and richness patterns are supported by the habitat specialization hypothesis. Patterns were driven by the different resources that each vegetation cover available to individual species and not by limited access to both types of resources. Parasitoid resource needs include the availability of suitable hosts, high-energy food sources such as nectar or pollen, overwintering sites, or temporary shelter from extreme weather. As Louda and Rand (2004) described, the needs of parasitoids are many and diverse, it might therefore be expected that there is no great overall abundance in one habitat over the other

because their various needs require them to use many habitats and not just one. At three sites (Ag plot, Fryman North and Fryman South), abundance patterns were a continuous gradient across boundaries. This is as predicted by the null hypothesis which stated that due to a mixture of specialist and generalist species there is a continuous response in the forest, edge and field habitats. In addition, ordinations of the species composition suggest that species in the field are subsets of those in the forest. Cronin (2009) found that parasitoid oviposition behavior increased near the edge; however, this conflicted with Esch et al. (2005). In their 2005 study, a host specialist parasitoid was used as the study model; they investigated the effects of patch distances on parasitoid dispersal. Their results showed that parasitoids did not vary with distance from ovipositioning sites. These two alternative conclusions suggest that parasitoid patterns of richness and abundance may depend on their degree of host or habitat specialization. Parasitoid richness was best predicted by the null model. Richness patterns were also a continuous response across habitats. These patterns may have been determined by their diverse needs but ordination data also suggests that the needs of different species are driving continuous response patterns. Predator abundance and richness was a continuous response as distance from the forest edge increased within all four sites. This is as predicted by the null hypothesis which stated that due to a mixture of specialist and generalist species there is a continuous species response across the forest, edge and field habitats. It might be expected that there is no great overall abundance in one habitat over the other because of the distribution of their nesting and prey resources. These diverse needs require them to use many habitats and not just one. The findings of this study emphasize the possible underlying framework that could explain some of the described patterns of species abundance and richness. Parasitoids, pollinators and predators supported predictions from one or more hypotheses, suggesting complex determinants of abundance and richness across boundaries. As agricultural intensification continues to increase and reduce natural and semi-natural habitat it is important to understand how beneficial insects respond to conservation practices, such as retaining forest habitat or planting field margins. Natural habitat remnants, such as forests, are important for parasitoids but also for field beetles that may depend on forest for overwintering. Field flowering resources were more important than floral resources in the margin as my study found few cases where enhanced margins substantially altered relationships and patterns. My study provides an increased understanding and potential mechanism of how

conservation practices (natural habitat, margins and extra floral resources) may influence beneficial insect relationships and patterns.

FUTURE DIRECTIONS

Identify prey responses to the availability and distributions of resources across habitats Examine spillover of species across habitats Study parasitoid fecundity in red clover Use empirical evidence to investigate the link between ecosystem services and resources

TABLES Table 1. The best-fitting (lowest AIC) generalized linear mixed model of abundance for: (a) Coleoptera (Predators): distance, distance squared, margin type; (b) Hymenoptera (Parasitoids): distance, distance squared; (c) Hymenoptera (Pollinators): distance, distance squared; and (d) Hymenoptera (Predators): distance. Variances reflect the degree of variability in the estimated coefficients for distance and margin type among sites.

Abundance (a)Coleoptera (b)Hymenoptera (c)Hymenoptera (d)Hymenoptera Models (Predators): (Parasitoids): (Pollinators): (Predators): distance, distance, distance distance, distance (intercept) distance squared, margin squared squared, type and interaction margin type Coefficients of fixed effects Distance 0.0887 0.0246 0.0775 0.250 Distance ^2 -0.0024 -0.0007 -0.0033 - Margin Type -0.0498 0.1693 - -

Variances for random effects of data sets Distance 9.591 x 10^-4 5.198 x 10^-4 1.002 x 10^-3 0.033 Distance^2 3.980 x 10^-6 6.937 x 10^-7 8.631 x 10^-7 - Margin Type 0.0913 - - -

Table 2. The best-fitting (lowest AIC) generalized linear mixed model of richness for: (a) Coleoptera (Predators): distance, distance squared, margin type; (b) Hymenoptera (Parasitoids): distance, distance squared; (c) Hymenoptera (Pollinators): distance, distance squared; and (d) Hymenoptera (Predators): distance. Variances reflect the degree of variability in the estimated coefficients for distance and margin type among sites.

Richness (a)Coleoptera (b)Hymenoptera (c)Hymenoptera (d)Hymenoptera Models (Predators): (Parasitoids): (Pollinators): (Predators): distance, distance (null) distance, distance (intercept) squared squared Coefficients of fixed effects Distance 0.0239 Null 0.0764 0.111 Distance^2 -0.0009 Null -0.0030 - Margin Type - Null - -

Variances for random effects of data sets Distance 3.503 x 10^-6 Null 6.845 x 10^-4 0.185 Distance^2 6.578 x 10^-8 Null 6.462 x 10^-8 - Margin Type - Null - -

Abundance Models (a)Coleoptera (b)Coleoptera (c)Hymenoptera ( ( ): ( ): ): distance distance, distance distance, distance squared and margin squared, margin type type and interaction Coefficients of fixed effects Distance 0.0876 0.0385 0.0388 Distance ^2 -0.0038 - -0.0020 Margin Type -0.2341 - -0.3727

Variances for random effects of data sets Distance 7.918 x 10^-5 0.0005 - Distance^2 9.435 x 10^-7 - - Margin Type 0.241 - 0.1535

Table 4. Ordination Statistics: Permutational Manova for ordinations using site and margin type for Vegetation Species.

DF R² P-value

Tree Data

Site 3 0.755 0.004

Margin Type 1 0.060 0.507

Residuals 3 0.185 -

Herbaceous Plant Data Site 3 0.959 0.008

Margin Type 1 0.013 0.354

Residuals 3 0.027 -

Table 5. Ordination Statistics: Permutational Manova for ordinations using site, margin type and habitat (forest,edge,field) for Insect Species.

DF R² P-value

Predatory Beetles Site 3 0.175 0.011

Margin Type 1 0.019 0.823

Habitat 2 0.276 0.001

Residuals 17 0.529 -

Parasitoids

Site 3 0.192 0.001

Margin Type 1 0.036 0.484

Habitat 2 0.134 0.004

Residuals 17 0.639 -

Table 6. Summary of Findings

Response Pattern Hypothesis (Field)

Predatory Coleoptera Richness Greater Habitat Quality Abundance Greater Habitat Quality Species Similar Habitat Composition Specialization Chauliognathus Abundance Greater Habitat Quality pennsylvanicus Photinus pyralis Abundance Greater Habitat Quality Parasitoids Richness Null Continuous Response Abundance Greater, Null Habitat Quality, Continuous Response Species Subset of Forest ------Composition Figitidae sp1 Abundance Greater, Null Habitat Quality, Continuous Response Hymenoptera Pollinators Richness Greater Habitat Quality Abundance Greater Habitat Quality Predatory Hymenoptera Richness Null Continuous Response Abundance Null Continuous Response

FIGURES

Figure 5. Study sites at Miami University, Oxford, Ohio (1) Fitton property; (2) Ag Plot; (3) Fryman South; (4) Fryman North. (Photo Credit: Google)

Figure 6. Resource Quality of study sites: (1) High Quality- Fitton property; (2) High Quality - Ag Plot; (3) Low Quality - Fryman South; (4) Low Quality - Fryman North. (Photo Credit: Google)

Figure 7. Resource Quality of study sites: (1) High Quality- Fitton property and Ag Plot ; (2) Low Quality - Fryman North and Fryman South.

(Photo Credit: Jason Nelson) Figure 8. Flight intercept/ pan traps using Lexan™ panes inserted into the bucket, arranged perpendicularly to avoid directional wind influence. Flight intercept/pan traps were placed on a wooden stand slightly above the crop.

Figure 9. Insect sampling using flight-intercept/pan traps and flower visitation counts.

Figure 10. Plot layout for sampling of forest vegetation for trees (20 x 20 m), shrubs (5 x 5 m) and herbs (1 x 1 m).

80 60 40 20 0

0 5 10 15 20 25

Figure 11. Variation in percent cover of red clover with distance from forest edge at the four sites and plots with enhanced and unenhanced field margins

Figure 12. Variation in flower density in 1-m2 plots in plots within enhanced and unenhanced field margins at the Fitton and Ag field sites.

60 50 40 30 20 10 0

-10 0 10 20

Figure 13. Abundance of predatory Coleoptera by site and plots with enhanced and unenhanced field margins. Lines are predicted relationships from best-fitting general linear mixed models.

Figure 14. Species richness of predatory Coleoptera by site. The effect of margin type was excluded from the best-fitting model. .

Figure 15. Abundance of hymenopteran parasitoids with respect to distance to forest edge at the four study sites and the two types of field margins.

Figure 16. Species richness of hymenopteran parasitoids with respect to distance, plot, and margin type. The null model was the best-fitting model.

Figure 17. Abundance of bees in relation to distance from forest edge and site. Abundances did not differ by field margin type.

Figure 18. Species richness of bees with respect to distance to forest-field edges across the four study sites. The null model was the best-fitting model for bee richness.

Figure 19. The abundance of the soldier beetle, Chauliognathus pennsylvanicus, in relation to distance from forest edges across four sites and plots with enhanced and unenhanced field margins.

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Appendix 1: List of Coleoptera: Predators by family and . Coleoptera: Predators

Anthicidae Lampyridae Notoxus_desertus Photinus_pyralis Notoxus_murinipennis Photuris_marginellus Cantharidae Photuris_pennsylvanicus Chauliognathus_marginatus Pyropyga_decipiens Chauliognathus_pensylvanicus Lycidae Ditemnus_bidentatus Calopteran_terminale Carabidae Meloidae Amara_rubrica Epicuata_atrata Amphasia_sericeus Epicuata_funebris Anisodactylus_sanctaecrucis Epicuata_pennsylvanica Bembidion_rapidum Epicuata_vittata Bemidion_affine Zonitis_bilineata Chlaenius_aestivus Pyrochoridae Clivina_bipustulata Neopyrochroa_femoralis Colliuris_pennsylvanica Ripiphoridae Lebia_atreventris Macrosiagon_limbata Lebia_grandis Rhipiphorous_diadasiae Lebia_pumila Rhipiphorus_luteipennis Lebia_viridis Staphylinidae Leptotrachelus_dorsalis Astenus_discopunctatus Notiobia_sayi Atheta_sp. Selenophorus_hylacis Bryoporus_rufescens Stenolophus_comma Coproporus_ventriculus Stenolophus_ochropezus Cordalia_obscure Coccillinidae Lobrathium_collare Brachiacantha_ursina Meronera_venustula Coleomegilla_maculata Ontholestes_cingulatus Cycloneda_munda Paederus_littorarius Diomus_terminatus Philonthus_caeruleipennis Harmonia_axyridis Philonthus_caucasicus Dystiscidae Philonthus_rufulus Uvarus_granarius Platydracus_maculosus Elateridae Platydracus_sp. Hemicrepidius_bilobatus Photinus_pyralis Hemicrepidius_hemipodus Photuris_marginellus Melanotus_castanipes Photuris_pennsylvanicus Melanotus_communis Pyropyga_decipiens Melanotus_sagittarius Histeridae Phelister_subrotundus

Appendix 2. List of Hymenoptera: Parasitoids by family and . Hymenoptera:Parasitoids

Braconidae Diapriidae Braconidae_1 Diapriidae_1 Braconidae_2 Diapriidae_2 Braconidae_3 Diapriidae_3 Braconidae_4 Diapriidae_4 Braconidae_5 Diapriidae_5 Braconidae_6 Diapriidae_6 Braconidae_7 Diapriidae_7 Braconidae_8 Pteromalidae Braconidae_9 Pteromalidae_1 Braconidae_10 Pteromalidae_2 Braconidae_11 Pteromalidae_3 Braconidae_12 Pteromalidae_4 Braconidae_13 Pteromalidae_5 Braconidae_14 Pteromalidae_6 Braconidae_15 Pteromalidae_7 Braconidae_16 Pteromalidae_8 Braconidae_17 Pteromalidae_9 Ichneumonidae Pteromalidae_10 Ichneumonidae_1 Pteromalidae_11 Ichneumonidae_2 Pteromalidae_12 Ichneumonidae_3 Pteromalidae_13 Ichneumonidae_4 Pteromalidae_14 Ichneumonidae_5 Pteromalidae_15 Ichneumonidae_6 Pteromalidae_16 Ichneumonidae_7 Pteromalidae__17 Ichneumonidae_8 Pteromalidae_18 Ichneumonidae_9 Pteromalidae_19 Ichneumonidae_10 Pteromalidae_20 Ichneumonidae_11 Pteromalidae_21 Ichneumonidae_12 Pteromalidae_22 Ichneumonidae_13 Pteromalidae_23 Mymaridae Pteromalidae_24 Mymaridae_1 Platygastridae Mymaridae_2 Platygastridae_1 Mymaridae_3 Platygastridae_2 Eupelmidae Platygastridae_3 Eupelmidae_1 Platygastridae_4 Eupelmidae_2 Platygastridae_5 Eupelmidae_3

Platygastridae (Cont.)

Platygastridae_6 Platygastridae_7 Platygastridae_8 Platygastridae_9 Platygastridae_10 Platygastridae_11 Platygastridae_12 Platygastridae_13 Platygastridae_14 Platygastridae_15 Platygastridae_16 Platygastridae_17 Platygastridae_18 Platygastridae_19 Platygastridae_20 Platygastridae_21 Platygastridae_22 Platygastridae_23 Platygastridae_24 Platygastridae_25 Platygastridae_26 Platygastridae_27 Figitidae Figitidae_1 Figitidae_2 Figitidae_3 Figitidae_4 Figitidae_5 Figitidae_6 Figitidae_7 Figitidae_8 Figitidae_9

Figitidae_10

Appendix 3: List Hymenoptera: Pollinators by family and . Hymenoptera: Pollinators

Apidae Apis_mellifera Bombus_sp1 Bombus_sp2 Bombus_sp3 Bombus_sp4 Bombus_sp5 Bombus_sp6 Bombus_sp7 Bombus_sp8 Bombus_sp9 Eucera_sp1 Xylocopa_sp1 Halictidae Agapostemon_sp1 Agapostemon_sp2 Augochlora_sp1 Augochlora_sp2 Augochlora_sp3 Augochlora_sp4 Augochlorapsis_sp1 Augochlorella_sp1 Halictidae_sp1 Halictidae_sp2 Halictidae_sp3 Halictidae_sp4 Halictidae_sp5 Halictidae_sp6 Halictidae_sp7 Halictus_sp1 Halictus_sp2 Halictus_sp3 Halictus_sp4 Lasioglassum_sp1 Lasioglassum_sp2 Lasioglassum_sp3 Lasioglassum_sp4

Appendix 4: List of Hymenoptera: Predators by family and . Hymenoptera:Predators

Bethylidae Anisepyris_sp1 Laelius_sp1 Chrysididae Chrysis_angolensis Holopyga_sp1 Pseudomalus_auratus Pompilidae Ageniella_sp1 Ageniella_sp2 Ageniodeus_sp1 Anoplius_sp1 Anoplius_sp2 Aporus_sp1 Arachnospila_sp1 Auplopus_sp1 Caliadurgus_sp1 Entypus_ sp2 Entypus_sp1 Sericopompilus_sp Sphecidae Ammophila_1 Eremnophila_1 Isodenttia_1 Tiphiidae Tiphia_vernalis Vespidae Ancistrocerus_adiabatus Ancistrocerus_antilope Dolichovespula_maculata Euodynerus_forminatus Polistes_fuscatus Polistes_metricus Polistes_sp1 Stenodynerus_pulvinatus Vespula_maculifrons

Appendix 5: List of Vegetation Sampled.

Trees

Acer_negundo Acer_saccharum Aesculus_glabra Carya_cordiformis Celtis_occidentalis Fagus_grandifolia Fraxinus_americana Gleditsia_triacanthos

Juglans_nigra Maclura _pomifera Morus_sp. Platanus _occidentalis Prunus_serotina Quercus_macrocarpa Quercus_prinus Tilia_americana Ulmus _rubra

Shrubs

Asimina_triloba Lonicera_maackii Ribes_sp. Rubus_allegheniensis Vitis_sp.

Herbaceous Plants

Artemesia_vulgaris Bidens_frondosa Eupatorium_maculatum Eupatorium_rugosum Fragaria_virginiana Galium_sp. Geum_canadense Impatiens_capensis Oxalis_europaea Parthenocissus_quinquefolia Smilax_rotundifolia Viola_papilionacea