Impacts of Urban Greenspace Management on Beneficial Insect Communities Master's Thesis Presented in Partial Fulfillment of Th

Home , Agapostemon sericeus, Andrena alleghaniensis, Andrena asteris, Andrena brooksi, Andrena vicina, Anthidium bicolor

Impacts of Urban Greenspace Management on Beneficial Insect Communities

Master’s Thesis

Presented in partial fulfillment of the requirements for the Degree Masters of Science in Entomology in the Graduate School of The Ohio State University

MaLisa Rose Spring, B.S. Graduate Program in Entomology

The Ohio State University 2017

Thesis Committee:

Dr. Mary M. Gardiner, Advisor

Dr. Reed Johnson

Dr. Karen Goodell

MaLisa Rose Spring

2017

Abstract

Vacant land in cities potentially could offer important habitat for pollinators. As part of the economic downturn and ensuing foreclosures,

Cleveland, Ohio, USA maintains over 1,400 hectares of vacant land. The goal of this thesis is to determine management strategies that benefit the overall beneficial insect community. Thus, this thesis is broken into three chapters:

1) comparing the impact of rain garden installations on predatory and pollinating insects, 2) comparing the impact of prairie installations and alternative mowing schemes on native and exotic bee communities, and 3) documenting the bee species richness found in inner-city Cleveland.

The first chapter focuses on rain garden installations. Storm water runoff causes sewer overflows in areas with outdated combined sewer systems. To mitigate these issues, retrofit green infrastructure strategies are used as partial remedies, with anticipation of additional ecosystem services such as supporting beneficial arthropods. Infiltrative rain gardens were installed on formerly vacant land in the Slavic Village neighborhood of

Cleveland, OH. The abundance of pollinators and predatory insects within urban vacant lots and rain gardens were sampled June, July, and August

2014-2016 in six rain gardens and eight vacant lots using bee bowls and

sticky cards. A total of 3,005 bees were collected from bee bowls and 23,332 beneficial insects were collected from sticky cards across all years. Overall, there was no difference in beneficial arthropod abundances in rain gardens compared to resource rich vacant lots. Moreover, there was not a consistent local habitat factor driving differences in arthropod abundance by site across years. Each year had a different local habitat factors correlated with arthropod abundance.

The second chapter compares five habitat treatments: regular vacant lots, successional vacant lots, lots seeded with a flowering lawn plant mix, lots seeded with a low diversity prairie plant mix, and lots seeded with a high diversity prairie mix. Each of the eight inner-city neighborhoods had one site of each habitat type for a total of forty sites across Cleveland, Ohio. Floral visitors were collected with bee vacuums during timed floral surveys in 2015 and 2016. A total of 3,456 plant visitors were collected in 71 different arthropod families including 1,752 bees and 347 hoverflies. Floral resources were similar between habitat types, with most floral visits on “weedy” flora.

There was no difference in abundance of bees by habitat, but this could be partly due to slow establishment of perennial prairie plants or the pervasiveness of urban weedy flora across all sites. Moreover, several exotic

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species of plants were found to be important for several native species of bees in inner city Cleveland, with Cichorium intybus being visited by more than 30 species of native bees.

The third chapter documents the 96 species of bees and their relative abundance from combined sampling efforts. I also note the first reported case of Psuedoanthidium nanum and Hylaeus pictipes in Ohio, new exotic species to the United States. Overall, I documented a diverse community of native and non-native species of bees persisting in these urban areas.

Dedication

This thesis is dedicated to all of the underappreciated taxa yet to be discovered in Ohio.

Acknowledgements

I would like to thank the many people who helped me throughout this project including but not limited to:

Bryan Zake for programming consultation and unwavering support, Nicole Hoekstra and Chelsea Gordon for lab organization, technical assistance, and general enthusiasm and camaraderie, Sam Droege for verifying identifications of bees, Kyle Martins for null model code, Jeni Filbrum and Denise Ellsworth for organization of outreach events and opportunities, all entomology graduate students for collegial support and camaraderie, Dave Shetlar for entomological expertise and taxonomic training, and all entomology department faculty for additional training and support. I would also like to thank Luciana Musetti and the Museum of Biological Diversity in Columbus, Ohio for access to reference collections and for preservation of verified specimens sacrificed for this research. Moreover, I would like to thank members of the Gardiner Lab, the Goodell Lab, the Johnson Lab, the Columbus Bee Lab, and the Herms lab for access to lab space, resources, and advice. Thanks go to the City of Cleveland for access to urban land for this research. I would also like to thank my undergraduate institution, Marietta College, for properly preparing me for the many trials of graduate work with particular thanks to my undergraduate advisors: Dr. Katy Lustofin, Dr. Dave McShaffrey, and Dr. Dave Brown.

I want to thank the University and the College of Food, Agriculture, and Environmental Sciences for providing me with two fellowships to support me during my research and the following sources for funds to support my research: the United States Environmental Protection Agency (Contract EP-C- 12-048-C), The National Science Foundation CAREER grant (CAREER 1253197), and the graduate student SEEDS program through the Ohio Agricultural Research and Development Center. Thanks go to the Agricultural Technical Institute for allowing me to teach two semesters of General and Applied Entomology as the Instructor of Record in my final year of my graduate studies.

Vita

May 2010 ………………………………………..Maysville High School

May 2014…………………………………………B.S. Biology, Marietta College

Aug 2014 – present……………………...... Graduate Research Fellow, The Ohio State University

May – Aug 2014………………………………… Summer Undergraduate Assistant, OARDC

Jan 2012 – May 2014…………………………..Laboratory Technician, Marietta College

Aug 2012 – May 2014…………………………Library Night Supervisor, Marietta College

June 2012 – Aug 2012…………………...... Insect Diversity Laboratory Technician, University of Minnesota

Nov 2010 – Feb 2011………………………….Laboratory Assistant, Marietta College

Awards

2016. Delong Competition Graduate Student Presentation Award 2016. ESA PIE National Masters Student Achievement in Entomology Award 2016. NCB: Entomological Society of America: 2nd place Masters Presentation 2016. NCB: Entomological Society of America: 2nd place Linnaean Games team 2015. Entomological Society of America President’s Prize: 1st Place Graduate Presentation 2015. Ohio Valley Entomological Association: Masters Section: 2nd Place Presentation 2015. OSU Department of Entomology James E. Tew Extension Award for Excellence in Extension

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2015. NCB: Entomological Society of America: 3rd place Masters Presentation 2015. NCB: Entomological Society of America: 1st place Insect Pinning Competition 2014. Raymond C. Osburn Graduate Award 2014. Entomological Society of America President’s Prize: 1st Place Undergraduate Presentation 2014. ESA PIE National Undergraduate Achievement in Entomology Award 2014. Ohio Valley Entomological Association: Undergraduate Section: 3rd Place Presentation 2014. Eggleston-Ruby Prize: biology department award for most meritorious research 2014. Biology Capstone award: awarded for best capstone project 2014. Beta Beta Beta Award: biology honorary senior award 2012, 2013. David Young Award: based on devotion and enthusiasm for biology 2011. Marietta College Biology Department Freshman of the Year

Publications

1. Spring MR, Lustofin K, Hua-Lin C, Gardiner MM, McShaffrey D. 2017. Quantifying bee diversity and resource use in the Appalachian foothills near Marietta, Ohio. Ohio Biological Survey. 7:1-13.

2. Chaffin BC, Shuster WD, Garmestani AS, Furio B, Albro S, Gardiner MM, Spring MR, Green OO. 2016. A tale of two rain gardens: barriers and bridges to adaptive management of urban stormwater in Cleveland, Ohio. Journal of Environmental Management. 183(2): 431- 441.

3. Spring MR, Lustofin K, Gardiner M. 2015. Occurrence of a gynandromorphic Bombus bimaculatus (Hymenoptera: Apidae) in Southeastern Ohio. The Great Lakes Entomologist. 48(3&4): 155-163.

Fields of Study

Major field: Entomology

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Table of Contents

Abstract ...... ii Dedication ...... v Acknowledgements ...... vi Vita...... vii List of Tables ...... x List of Figures ...... xii Chapter 1: Impacts of rain garden implementation on beneficial insects ...... 1 Chapter 2: Urban floral visitor communities and the role of native/exotic bees for network function ...... 46 Chapter 3: Cleveland bee diversity and new invasive species ...... 81 References ...... 100

List of Tables Table 1. Table of number of sites samples were successfully obtained from per month per year by site type (Vacant lot, Rain Garden, or Bioswale). This indicates the number of sites where we were able to get at least one plot of one type of data, but not necessarily all data types (e.g. bee bowls, sticky cards, or plant data). *an additional rain garden was included here, but not utilized again due to intense mowing damage. **data was collected in bioswales in 2015, but not enough replicates (and plots within sites) were obtained to run proper statistical analyses...... 12 Table 2. Abundances of Coccinellidae taxa by year found in vacant lots, rain gardens, and bioswales collected on Yellow Sticky Card Traps...... 16 Table 3. Abundances of bees collected from Yellow Sticky Card Traps (YSCT) by year in vacant lots, rain gardens, and bioswales...... 16 Table 4. Bee species list from specimens collected via bee bowls in vacant lots, rain gardens, and bioswales in 2014, 2015, and 2016. An * denotes an exotic species to Cleveland. . 18 Table 5. Compliled results of PLS regression analysis comparing the influence of habitat factors on pollinators and predators. Bee bowl variables included overall bee abundance, Halictidae, Apidae, and Lasioglossum. Sticky card bee variables included overall bee abundance, Hylaues, and Lasioglossum. Sticky card predator variables included Anthocoridae, Coccinellidae, Dolichopodidae, Staphylinidae, and Syrphidae (2015 and 2016 only). Each model reports the Q2 (proportion of variance in response variable predicted by the model), R2Y (proportion of variance in response variable explained by the model), and R2X (proportion of variance in predictor variables used in the model) based on the model components of T1 and T2...... 30 Table 6. Plantings and management schedule for each of the five habitat treatments: Vacant lot, Successional lot, Flowering Lawn, Low Diversity Prairie, and High Diversity Prairie. All sites were either mown monthly or yearly depending on the treatment...... 53 Table 7. List of bee species collected by year with bee vacuums organized by family. Respective abundance per year (2015 or 2016) is noted in addition to overall abundance across year, and designation as native or exotic...... 59 Table 8. List of plant species that had at least one collected floral visitor across all sites. There were 40 sites in 2015 and 39 sites in 2016 with most plant species being only found at a few sites. Also includes a list of all floral visitors collected on the flower structure including wasps, butterflies, and any other arthropod. Abundances are listed as (bees/all arthropods) within each abundance column to give an idea of relative proportion of visits by bees versus all arthropod visits. Bee species richness is recorded by year...... 62 Table 9. Network matrix for 2015 summed across all sites in Cleveland. Only plants with representatives at more than 25% of sites were included. Plants with fewer than 20 arthropod observations were excluded from the analysis. Taxa are divided into native and exotic species keeping honey bees separate...... 72 Table 10. Network matrix for 2016 summed across all sites in Cleveland. Only plants with representatives at more than 25% of sites included. Plants with fewer than 20 arthropod observations were excluded from the analysis. Taxa are divided by native and exotic species keeping honey bees separate...... 72

Table 11. Common plant species level outputs for 2015 showing Paired Difference Index, and proportional generality. Values significantly different from null models are indicated with *...... 74 Table 12. Common plant species level outputs for 2016 showing Paired Difference Index, and proportional generality. Values significantly different from null models are indicated with *...... 75 Table 13. Compiled list of bee species collected from Cleveland with columns denoting sampling method and year (2014-2016). A separate column denotes the species status as native or exotic and their naming authority...... 84 Table 14. Species accumulation curve for combined Cleveland bee species data with Chao, Jacknife1, Jacknife2, and Bootrap estimates...... 91

List of Figures Figure 1. A) Vacant lot with Yellow Sticky Card Traps deployed. Note the abundant floral resources. B) Rain garden in the first year of establishment. Photo courtesy of Mary Gardiner. C) One of the Bioswale sites in 2015. These sites were actively managed for weeds and normally had abundant native floral resources...... 2 Figure 2. Ladybeetle (Coleoptera: Coccinellidae) abundance collected on Yellow Sticky Card Traps in Vacant lots, Rain Gardens, and Bioswales in 2014, 2015, and 2016. Letters indicate significant differences of habitat type within a year...... 25 Figure 3. Long-legged flies (Diptera: Dolichopodidae) abundance collected on Yellow Sticky Card Traps in Vacant lots, Rain Gardens, and Bioswales by month in 2016. Letters indicate significant differences of habitat type within a month...... 25 Figure 4. Pirate bugs (Hemiptera: Anthocoridae) abundance on Yellow Sticky Card Traps in Vacant lots and Rain Gardens by month in 2015. Letters indicate significant differences of habitat type within a month...... 26 Figure 5. Rove beetles (Staphylinidae) abundance collected on Yellow Sticky Card Traps in Vacant lots, Rain Gardens, and Bioswales in 2014, and 2015. Letters indicate significant differences of habitat type within a year...... 26 Figure 6. Hover flies (Syrphidae) abundance on Yellow Sticky Card Traps in Vacant lots, and Rain Gardens by month in 2015. Letters indicate significant differences of habitat type within a month...... 27 Figure 7. Bee (Apoidea) abundance per Yellow Sticky Card Traps in Vacant lots, Rain Gardens, and Bioswales by month in 2016. Letters indicate significant differences of habitat type within a month...... 28 Figure 8. Bee (Apoidea) abundance per bowl in Vacant lots, and Rain Gardens by month in 2014. Letters indicate significant differences of habitat type within a month...... 29 Figure 9. Correlation maps of the PLS regression of 2015 and 2016 predators on Yellow Sticky Card Traps. Only variables with VIP of > 0.8 are shown...... 33 Figure 10. Correlation maps of the PLS regression of 2014 and 2016 bees (Apiodea) on Yellow Sticky Card Traps. Only variables with VIP of > 0.8 are shown...... 35 Figure 11. Correlation maps of the PLS regression of 2014-2016 bees (Apioidea) collected from bee bowls. Only variables with VIP of > 0.8 are shown...... 38 Figure 12. Heavy Duty Hand Vacuums, also known as a Bee vacuums, are useful to quickly collect visitors from flowers without accidentally damaging large parts of the plant structure which is common with sweepnets. Handheld vacuums also allow greater certainty that specimens were collected from the intended floral resource. Photo by Nicole Hoekstra...... 54 Figure 13. Top 10 floral resources with the highest abundance of all floral visitors collected via bee vacuums in 2015 and 2016...... 66 Figure 14. Top 10 floral resources with the highest abundance of bee visitors (Apoidea) collected via bee vacuums in 2015 and 2016...... 66 Figure 15. Top 10 floral species in 2015 with highest abundance when accounting for the number of sites the plants were recorded (floral visitor abundance/total number of sites plant found)...... 67 Figure 16. Top 10 floral species in 2016 with highest abundance when accounting for the number of sites the plants were recorded (floral visitor abundance/total number of sites plant found)...... 67 xii

Figure 17. Top 10 floral resources for bees in 2015 illustrating bee abundance when accounting for the number of sites the plants were recorded (bee abundance/total number of sites plant found)...... 68 Figure 18. Top 10 floral resources for bees in 2016 illustrating bee abundance when accounting for the number of sites the plants were recorded (bee abundance/total number of sites plant found)...... 68 Figure 19. Floral resources that supported the highest richness of bees by year. Dark grey and light grey bars illustrate species richness in 2015 and 2016 respectively...... 69 Figure 20. Bee abundance per sampling effort per site by habitat type (Vacant lots, Successional Lots, Low Diversity Prairie mix, High Diversity Prairie mix, and Flowering Lawn Mix) in 2015. Significant differences noted by asterisk...... 70 Figure 21. Bee abundance per sampling effort per site by habitat type (Vacant lots, Successional Lots, Low Diversity Prairie mix, High Diversity Prairie mix, and Flowering Lawn Mix) in 2016. Significant differences noted by asterisk...... 71 Figure 22. Visual network web for 2015 (left) and 2016 (right) summed across all sites in Cleveland. Only plants with representatives at more than 25% of sites included. Plants with fewer than 20 arthropod observations were excluded from the analysis. Taxa are divided by native and exotic species keeping honey bees separate...... 71 Figure 23. Species accumulation curve for compiled bee species richness in Cleveland with Chao, Jacknife1, Jacknife2, and Boostrap estimates...... 92

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Chapter 1: Impacts of rain garden implementation on beneficial insects Beneficial insects, those that provide vital services such as pollination, predation, or decomposition, are important for a functioning ecosystem.

Wild, unmanaged arthropods provide an estimated $57 billion per year in the

United States for these services (Losey and Vaughan 2006) and thus warrant conservation concern. Urbanization is often considered a threat to biodiversity and conservation (McKinney 2006, Pauchard et al., 2006). Yet urban areas (especially shrinking cities) have been identified as a potentially important landscape to support beneficial arthropods, having been demonstrated to support high abundances and diversity of arthropod predators (Uno et al. 2010, Gardiner et al., 2013, Gardiner et al. 2014,

Baldock et al. 2015) and pollinators (Matteson and Ascher 2008, Frankie et al. 2009, Kearns and Oliveras 2009, Tonietto et al. 2011, Baldock et al. 2015).

Despite their ubiquity in shrinking cities, vacant lots (also known as brownfields) have been largely overlooked as a conservation resource. A vacant lot is an area where a structure once stood, but has since been demolished, the footprint of the structure filled with new soils, and then seeded with a turf mixture. Cleveland, Ohio has over 27,000 such vacant lots that are mown once a month during the growing season at an estimated cost of $3 million per year (James Greene pers. comm., Cleveland Land Lab 2008).

These lots are rarely managed to control weedy vegetation, and maintain a diverse mix of early successional low growing grasses and forbs that bloom throughout the season. There is mounting evidence that these vacant lots support unique arthropod biodiversity (Gardiner et al. 2014, Lowenstein et al. 2014, Hall et al. 2016). However, there may be other landscape management strategies that are more supportive to beneficial insects and have similar or lower maintenance costs to regular vacant lots while also mitigating other ecosystem disservices associated with urbanization such as air pollution, storm water runoff, and biodiversity loss.

Urban areas face a variety of management issues, with catchment and storage of storm water being a major challenge. Historically, combined sewer systems were designed to accommodate both sewage and storm water.

These systems have an inherent flaw of limited capacity that can be overwhelmed, and result in an overflow event in which the combined unprocessed storm water and sewage drains into nearby water bodies,

sometimes with as little as 3 cm of rainfall (Shuster et al. 2014, Herrmann et al. 2016). One solution is to update the existing grey infrastructure to separate sewage and storm water facilities at the cost of several billion dollars, which can be challenging to fund in cities with declining populations.

Another solution is to decrease the amount of storm water that goes into the sewer system to prevent the combined system from getting overwhelmed.

Urban greenspaces such as vacant lots have the potential to mitigate these combined sewer overflow events by catching and collecting rainwater.

Vacant lots already serve as a form of green infrastructure that have been shown to have a high capacity to collect storm water (Herrmann et al.

2016). Transforming vacant lots into rain gardens and bioswales could further improve storm water mitigation. Rain garden creation can be as simple as selecting the lowest point within a vacant lot and digging an evenly-graded depression within it, allowing water to naturally flow into the garden area. Larger scale bioswales are high cost alternatives which involve major changes in soil type and grading and additional underground pipes for storm water catchment. However, impacts on the beneficial insect community should be considered when converting vacant lots to alternative green spaces. Rain gardens may provide the dual benefit of storm water mitigation and improved habitat for species conservation, following the idea of stacked ecosystem services (Fiedler et al. 2008, Wratten et al. 2012).

Alternatively, these installations may negatively impact the local beneficial

insect community by disrupting the soils and floral resources normally available in vacant lots.

I aimed to see if low and high cost rain garden installations, herein termed rain gardens and bioswales respectively, supported a similar beneficial insect community compared to vacant lots. Moreover, I wanted to see which habitat factors were most important for beneficial insect abundances. I monitored eight vacant lots, six rain gardens, and three bioswales in Cleveland, Ohio over a period of three years (2014-2016) using predatory insect abundances on yellow sticky card traps to sample the predatory insect community and abundances of bees per bee bowl to sample the pollinator community. This work was in partnership with the U.S.

Environmental Protection Agency, the U.S. Geological Survey, and the

Cleveland Botanical Gardens, which are agencies analyzing the effectiveness of rain gardens for storm water capture.

Methods:

This study took place in the Slavic Village neighborhood of Cleveland,

Ohio (41°27'07.0"N 81°38'18.3"W). All sites were located within a 1 km2 area between Broadway and Bessemer Avenues. The study sites included eight vacant lots, six rain gardens established on formerly vacant land in

2014; in 2015 three bioswale sites were added.

Vacant lots were managed by the City of Cleveland. This included mowing once a month and occasional trash pickup, but no maintenance for weedy vegetation (Figure 1A).

Rain garden construction began in winter of 2013, with final plant seeding occurring in early spring of 2014 (Figure 1B). Installation included removal of several inches of topsoil, grading of the site, and construction of a

0.75 m depression that ranged in length from 7-15 m and width of 3-10 m to catch rainwater. This depression was less than half of the available surface area within a lot. A layer of clean-fill topsoil was added to the entire site and

5-20 cm of mulch was added to the rain garden depression over the clean-fill.

One inch of leaf compost was added across entire site to aid vegetation establishment. Finally, the lots were seeded with a no-mow turf mix including forbs (Achillea millifolium, Fragaria virginiana, Geum triflorum,

Viola sororia, Allium cernuum, Anemone patens, Aster ptarmicoides, Geranium maculatum, Sisyrinchium campestre, Tradescantia bracteata, Vicia Americana,

Trifolium repens ‘Microclover®’), and grasses (Festuca spp., Lolium perenne,

Carex vulpinoidea,, Panicum virgatum). The center rain garden depression was planted with several water tolerant species of forbs (Asclepias incarnata,

Iris versicolor, Monarda didyma, Symphiotrichum leave, Helianthus strumosus,

Hibiscus moscheutos, Liatris spicata, and Ratibida pinnata). Modifications to the rain garden depression were made in 2015. Plantings, mulch, and top soil were removed and 15-20 cm of bioinfiltration soil mix (sandy/loamy soil) as 5

added to improve drainage. Each depression was planted with the same flowering resources originally established in 2014. In 2016, a single ornamental tree (Quercus bicolor, Acer rubrum, or Nyssa silvatica), ~2 meters tall, was added to each rain garden depression. Mulch was added at the base of the trees and stakes were also installed to ensure that the trees remained upright. The cost of initial installation of 9 rain garden sites was approximately $40,000 in 2014 and an additional $15,000 in 2015. The estimated replication cost is $5,000 per lot for grading the sites, soils amendments, and seeding.

Bioswales are a term used in this manuscript used to differentiate the low cost rain gardens from high cost installations which have had major hydrologic changes to increase soil water infiltration (Figure 1C). These features were designed in 2013 with construction completed in early 2014.

The three sites were graded to allow for better sheet flow of water and bioretention soils were added to improve infiltration. Each site included a large retention area (~50-105 m2) with a 30 cm minimum of bioretention soil on top, followed by a 5 cm minimum of clean washed concrete sand, a 10 cm minimum clean washed #8 aggregate (pea gravel), and finally a 30 cm minimum clean washed #57 aggregate. Beneath each of the main water collection areas, 15 cm diameter SDR 35 PVC perforated pipes were installed at a slope of 0.5%. These pipes connected to a 45 cm diameter overflow structure to accommodate large rain events. Two sites on 75th street had 6

curb cuts installed to allow additional storm water to flow into the site from the street. The curb cuts opened up into the bioretention area which had a concrete splash pad and a border of river stones (2.5-5 cm in diameter). Once the hydrology and structure of the lots were completed, erosion control blankets were installed across the main water drainage and sloped areas. All bioswale sites were planted with a plugs of perennial plants (Asclepias incarnata, Asclepias tuberosa, Aster laevis, Baptisia bracteata, Echinacea purpurea, Iris viginica, Liatris aspera, Liatris spicata, Lobelia cardinalis,

Lobelia siphilitica, Mondarda fistulosa, Penstamon digitalis, Rudbeckia hirta,

Verbena hastata, and Zizia aurea), shrubs (Aesculus parvifola, Cornus sericea

‘Baileyii’, Rhus aromatic ‘Gro-Low’, and Hydrangea quercifolia), grasses or sedges (Carex comosa, Carex lurida, Carex vulpinoidea, Koeleria cristata,

Scirpus atrovirens, Sporobolus heterolepis, and Panicum virgatum), and trees

(Cercis canadensis, Crataegus viridis ‘Winter King’, and Quercus alba). The

Northeast Ohio Regional Sewer District invested $14,126 to acquire land and

$314,956 to design and construct the three bioswales. This cost does not include the cost of maintaining the land and controlling for weeds. These sites capture storm water at a rate of 1.14 mega-liters per year in addition to

Combined Sewer Overflow reduction of 0.37 mega-liters per year.

A B 8

Figure 1. A) Vacant lot with Yellow Sticky Card Traps deployed. Note the abundant floral resources. B). Rain garden in the first year of establishment. Photo courtesy of Mary Gardiner. C) One of the Bioswale sites in 2015. These sites were actively managed for weeds and normally had abundant native floral resources.

Arthropod collection methods

Within each site, all samples were taken from within equally distributed 1 m2 quadrats in the center of the lots. These quadrats were consistent across years. The unconverted vacant lots had four quadrats per site whereas rain gardens had two additional quadrats within the garden/mulched area for a total of six quadrats per site. The number of quadrats per bioswale was variable with either four, five, or six quadrats within the site to account for overall larger lot size.

Trece Pherocon ® Unbaited AM Yellow Sticky Traps (23 cm W x 28 cm L with a 18 cm W x 23 cm L grid) were deployed for seven days on the following dates: 2014 (June 23, July 21), 2015 (June 10, July 6, Aug 3), and

2016 (June 9, July 14, Aug 2). One sticky trap was set per quadrat in each site with traps secured to step in fence posts above vegetation. These traps were used to collect insects in the following families: Staphylinidae, Syrphidae,

Dolichopodidae, Anthrocoridae, Coccinellidae, Apidae, Andrenidae,

Halictidae, Colletidae, and Megachilidae. Insects in following families were identified to genus and species where possible: Andrenidae, Apidae,

Colletidae, Coccinellidae, Halictidae, and Megachilidae. Due to the stickiness of the cards, bees were not removed or pinned. Moreover, identifying bees to

species on the cards is a major challenge as most species level diagnostic characters were obscured by the adhesive.

Bee bowls were set on the following dates: 2014 (July 10, July 31, Aug

20), 2015 (June 9, July 6, Aug 5), 2016 (June 9, July 26, Aug 8). Bee bowls consisted of 96 ml plastic soufflé bowls (Solo®) painted fluorescent blue, yellow, or left white. One bee bowl of each color was deployed per quadrat and half filled with soapy water (1% blue Dawn dish soap/water solution) for 24 hours. The average number of bees per bowl was calculated per site to account for the uneven distribution of trap loss at sampling locations. All bees from bee bowls were washed, blown dry, pinned, identified, and preserved with museum level archival labels.

Bees were identified using Discoverlife.org (Ascher and Pickering

2017), recent revisions by Jason Gibbs for Lasioglossum (Gibbs 2011, Gibbs et al. 2012), and Bumble Bees of North America (Williams et al. 2014). Voucher specimen identifications were verified by Sam Droege at the USGS Bee

Inventory and Monitoring Lab and then deposited to the Museum of

Biological Diversity in Columbus, Ohio.

Vegetation data were collected within each of the one meter quadrats on the following dates: 2014 (July 10-11, July 29), 2015 (June 10-11, July 7,

Aug 6-7), and 2016 (June 16-17, July 21, Aug 9). Within each one meter quadrat, the following were counted: total blooming floral species richness, 10

total bloom abundance. Each individual flower was counted for the bloom abundance with the exception of flowers with tiny bloom clusters (i.e.

Achillea millifolium and Daucus carota), which each cluster of flowers was counted as one. For each blooming species, three height measurements (cm) were taken of different individuals. Three flowers from separate individuals of each blooming species were also measured for length and width to estimate total bloom area per quadrat. If there were fewer than three plants blooming within a quadrat, then the number of available plants were measured. Within each quadrat, percent cover of vegetation was recorded.

Percent cover was broken down into the following categories: forb, grass, mulch, leaf litter/mown grass, bare, rocks/sticks, moss, garbage, and plant matting.

Sampling equipment and materials (sticky cards, stakes, and bee bowls) were lost due to theft or destruction by mowing equipment.

Occasionally, sampling equipment and materials would be returned to the lots after the sample period was over, but these cards were not included in the analyses. Similarly, stakes that had fallen over were not included in the sticky card analyses. Some sticky cards had obvious contamination of animal fur or feathers, but were still included in the analysis since a large portion of the sticky surface was available. Several sites were lost throughout the sample period (Table 1). However, at least one plot of data was obtained in enough sites to continue analyses (Table 1). 11

Vacant Lot Rain Bioswale Garden 2014 July 8 6 NA August 8 6 NA 2015 June 8 7* NA July 8 2 3** August 8 5 3** 2016 June 8 6 3 July 7 5 3 August 8 5 3 Table 1. Number of sites samples that samples were successfully obtained per month per year by site type (Vacant lot, Rain Garden, or Bioswale). These sites included at least one plot of one type of data, but not necessarily all data types (e.g. bee bowls, sticky cards, or plant data). *an additional rain garden was included here, but not utilized again due to intense mowing damage. **data was collected in bioswales in 2015, but too few replicates (and plots within sites) were obtained to run statistical analyses.

Statistical methods:

Generalized linear mixed models (Proc Mixed) were used to determine if arthropod natural enemies and pollinators varied among habitat types or across the sampling period. Models included the predictor variables

Treatment (vacant lot, rain garden, or 2016 bioswale), month (June (2015, and 2016 only), July, and August), and Treatment by Month interaction (SAS

Institute, Cary NC). Each model compared one measure of abundance as a fixed effect (Coccinellidae per Yellow Sticky Card Trap (YSCT),

Dolichopodidae per YSCT, Anthocoridae per YSCT, Staphylindae per YSCT,

Syrphidae per YSCT, Apoidea per YSCT, or Apoidea per bowl) to the predictor

variables. Month within a year by plots within a site were incorporated into the statistical model as a repeated factor. Bar charts were created in R 3.3.3

(R Core Team 2017) utilizing packages “ggplot2” version 2.2.1 (Wickham

2009) and “extrafont” version 0.17 (Chang 2014).

I examined how habitat variables correlate with the abundance of arthropods within each habitat using partial least squares regressions (PLS).

PLS models can incorporate multiple response and predictor variables while accounting for a small sample size relative to the number of predictor variables (Wold et al. 2001, Carrascal et al 2009). Moreover, PLS regression is similar to Principle Component Analysis combined with Multiple

Regression, but is more reliable in determining relevant variables and importance within a model (Carrascal et al 2009). The following predictor variables were initially included in all models: treatment type, month, plant height, bloom abundance, bloom area, bloom richness, forb, grass, leaf litter/mown, mulch, bare, and rocks/sticks. Three types of PLS-R models were created: predators on sticky cards, bees on sticky cards, and bees in bowls with separate models for each year. Sticky cards compared the abundance response of predatory insects in the following families:

Coccinellidae, Anthocoridae, Dolichopodidae, Syrphidae, and Staphylinidae.

Bees on sticky cards were analyzed separately and included: overall bees,

Lasioglossum species, and Hylaeus species to see if there was a taxa specific response to the site types. Additional PLS models for bee bowl specimens in 13

the following groups: all bees per bowl, Apidae per bowl, Halictidae per bowl, and Lasioglossum per bowl to see if there were differences in correlations of abundance within the different groups.

Predictor and response variables were centered to a mean of zero and a standard deviate of one for each model (Wold et al. 2001). Predictors with

Variable Importance in Projection (VIP) values less than 0.8 were not considered significant. Explanatory factors with VIP values less than 0.8 were removed, and the model rerun to create a second output. Only explanatory factors with a VIP greater than 0.8 were shown in the correlation loading plot. Interpretation of each model was based on the first two components of the PLS (t1 and t2), and only including Q2 scores that were above 0.097

(Johahnson and Nilsson 2002) PLS regressions were created in the PLS module of XLSTAT {2016.07}. PLS-R visual outputs were created in R 3.2.5 (R

Core Team 2017) utilizing packages “ggplot2” version 2.2.1 (Wickham 2009),

“ggrepel” version 0.6.5 (Slowikoski 2016), and “extrafont” version 0.17

(Chang 2014).

Results:

Rain gardens finished construction by the spring of 2014. There was a low rate of floral establishment in the first and second year of sampling; of the twenty forb species planted in the rain gardens, only seven species had successfully grown from seed and produced flowers by the fall of 2016: 14

Achillea millifolium, Asclepias incarnata, Iris versicolor, Monarda didyma,

Symphyotrichum leave, Liatris spicata, and Ratibida pinnata. Accidental mowing of the rain gardens by the city of Cleveland, both in the turf and in garden area was a persistent challenge, and hampered the plant establishment.

Arthropod abundances

A total of 23,332 arthropods were counted and identified from sticky cards over 3 years: 7,147 in 2014; 9,625 in 2015; and 6,560 in 2016. Of these,

5,438 were ladybeetles (Coleoptera: Coccinellidae) belonging to 12 genera

(Table 2). A total of 12,719 long-legged flies (Diptera: Dolichopodidae) were collected across all habitat types (3,387 in 2014; 6,810 in 2015; and 2,522 in

2016). A total of 2,397 pirate bugs (Hemiptera: Anthocoridae) were collected across all habitat types (779 in 2014; 848 in 2015; and 770 in 2016). A total of 542 rove beetles (Coleoptera: Staphylinidae) were collected across all habitat types (211 in 2014; 120 in 2015; and 211 in 2016). A total of 377 hoverflies (Diptera: Syrphidae) were collected across all habitat types (310 in 2015; 67 in 2016). Of specimens on sticky cards, 1,407 were of bees (368 in 2014; 432 in 2015; 607 in 2016) (Table 3).

Coccinellidae taxa 2014 2015 2016 Total Brachiacantha spp. 111 63 127 301 Coccinella septempunctata 0 0 6 6 Coleomegilla maculata 101 12 34 147 Cycloneda munda 18 44 26 88 Epilachna varivestis 0 2 1 3 Hippodamia convergens 1 0 0 1 Hippodamia parenthesis 1 8 5 14 Hippodamia variagata 5 4 55 64 Hyperaspis signata 0 0 1 1 Hyperaspis undulata 8 1 15 24 Harmonia axyridis 14 27 21 62 Propylea 323 266 156 745 quatuordecimpunctata Psyllobora vigintimaculata 7 0 11 18 Scymnus spp. 844 564 1649 3057 Other small black 661 25 221 907 Coccinellidae Total 2094 1016 2328 5438 Table 2. Abundances of Coccinellidae taxa by year found in vacant lots, rain gardens, and bioswales collected on Yellow Sticky Card Traps.

YSCT Bees 2014 2015 2016 Total Agapostemon spp. 0 2 4 6 Andrena spp. 2 1 3 6 Apis mellifera 1 0 1 2 Augochlora pura 1 1 2 4 Ceratina spp. 0 1 2 3 Holcopasites calliopsidis 1 0 0 1 Hylaeus spp. 115 187 395 697 Lasioglossum spp. 248 240 200 688 Total 368 432 607 1407 Table 3. Abundances of bees collected from Yellow Sticky Card Traps (YSCT) by year in vacant lots, rain gardens, and bioswales.

A total of 3,004 bees were collected from bee bowls over 3 years for this analysis: 1,018 in 2014; 946 in 2015; and 1,040 in 2016 (Table 4). A total of 27 bee genera were collected across all site types among 81 species (Table

4). A majority of specimens collected in bee bowls were in the family

Halictidae with bees in the genus Lasioglossum making up 37% of all collected specimens (477 in 2014; 316 in 2015; and 346 in 2016). Bees in the genus Agapostemon comprised of 17% of all bees collected via bowls and were common in all sites (118 in 2014; 136 in 2015; 259 in 2016).

Family Species 2014 2015 2016 Total Authority

Andrenidae Andrena Smith 1879 0 2 9 11 commoda Andrena vicina Smith 1853 0 0 1 1 Andrena (Kirby 1802) 1 1 8 10 wilkella* Calliopsis Smith 1853 45 105 50 200 andreniformis Apidae Anthophora Cresson 1869 1 1 0 2 terminalis Apis mellifera* Linnaeus 1758 6 10 4 20 Bombus Cresson 1863 0 2 0 2 bimaculatus Bombus fervidus (Fabricius 1798) 2 16 2 20 Bombus (De Geer 1773) 5 2 0 7 griseocollis Bombus Cresson 1863 2 10 7 19 impatiens Bombus vagans Smith 1854 0 2 0 2 Ceratina Robertson 1900 31 11 41 83 calcarata Holcopasites (Linsley 1943) 6 7 0 13 calliopsidis Melissodes (Lepeletier 52 24 39 115 bimaculatus 1825) Melissodes Smith 1854 2 2 1 5 desponsus Melissodes LaBerge 1961 1 0 0 1 subillatus Melissodes Robertson 1901 0 2 0 2 trinodis Nomada Smith 1854 0 1 7 8 articulata Nomada 0 0 2 2 Bidentate Group Nomada Cresson 1863 0 0 1 1 pygmaea Peponapis Say 1837 8 6 5 19 pruinosa* Triepeolus (Say 1824) 2 0 0 2 lunatus Xylocopa (Linnaeus 1771) 0 0 1 1 virginica Colletidae Hylaeus 8 12 18 38 affinis/modestus Hylaeus Smith 1842 26 27 15 68 hyalinatus* Table 4. Bee species list from specimens collected via bee bowls in vacant lots, rain gardens, and bioswales in 2014, 2015, and 2016. An * denotes an exotic species to Cleveland. Continued

Table 4 continued Family Species 2014 2015 2016 Total Authority Colletidae Hylaeus (Morawitz 1871) 3 0 2 5 leptocephalus* Hylaeus mesillae (Cockerell 1896) 4 0 0 4 Hylaeus Say 1837 7 3 2 12 modestus Hylaeus pictipes* Nylander 1852 1 2 5 8 Hylaeus spp. 1 0 0 1 Halictidae Agapostemon (Forster 1771) 24 41 53 118 sericeus Agapostemon Cresson 1872 14 16 29 59 texanus Agapostemon (Fabricius 1775) 80 79 177 336 virescens Augochlora pura (Say 1837) 14 3 5 22 Augochlorella (Smith 1853) 1 12 14 27 aurata Halictus confusus Smith 1853 94 65 28 187 Halictus ligatus Say 1837 52 56 80 188 Halictus (Christ 1791) 15 6 0 21 rubicundus Halictus spp. 17 13 15 45 Lasioglossum (Mitchell 1960) (Dialictus) 0 1 1 2 apocyni Lasioglossum (Crawford 1902) (Dialictus) 11 1 2 14 bruneri Lasioglossum (Ellis 1913) (Dialictus) 4 1 4 9 cattellae Lasioglossum (Robertson (Dialictus) 3 0 2 5 1893) coeruleum Lasioglossum (Robertson (Dialictus) 6 5 15 26 1890) cressonii Lasioglossum Gibbs 2010 (Dialictus) 53 32 24 109 ephialtum Lasioglossum Gibbs 2011 (Dialictus) 0 0 1 1 gotham Lasioglossum Gibbs 2012 (Dialictus) 41 41 35 117 hitchensi Table 4. Continued

Table 4 continued Family Species 2014 2015 2016 Total Authority Halictidae Lasioglossum (Robertson (Dialictus) 0 9 15 24 1892) illinoense Lasioglossum (Smith 1853) (Dialictus) 156 89 80 325 imitatum Lasioglossum (Smith 1853) (Dialictus) 1 1 1 3 laevissimum Lasioglossum (Lovell 1908) (Dialictus) 0 1 0 1 leucocomum Lasioglossum (Crawford 1906) (Dialictus) 2 4 2 8 lineatulum Lasioglossum (Sandhouse (Dialictus) 2 4 2 8 1923) lionotum Lasioglossum (Knerer and (Dialictus) 0 1 1 2 Atwood 1966) paradmirandum Lasioglossum (Smith 1853) (Dialictus) 51 57 40 148 pilosum Lasioglossum Gibbs 2011 (Dialictus) 0 0 1 1 rozeni Lasioglossum (Robertson (Dialictus) 2 1 0 3 1897) smilacine Lasioglossum 34 34 36 104 (Dialictus) spp. Lasioglossum (Cockerell 1938) (Dialictus) 4 0 3 7 subviridatum Lasioglossum (Robertson (Dialictus) 24 10 13 47 1890) tegulare Lasioglossum Gibbs 2011 (Dialictus) 0 0 1 1 trigeminum Lasioglossum (Robertson (Dialictus) 1 2 3 6 1902) versatum Lasioglossum 1 (Mitchell 1960) (Dialictus) 0 1 0 weemsi Table 4. Continued

Table 4 continued Family Species 2014 2015 2016 Total Authority Halictidae Lasioglossum (Smith 1853) (Dialictus) 2 3 4 9 zephyrum Lasioglossum (Smith 1853) (Hemihalictus) 34 15 16 65 pectorale Lasioglossum (Hemihalictus) 0 0 3 3 spp. Lasioglossum (Provancher (Evylaeus) 2 0 0 2 1888) cinctipes Lasioglossum (Smith 1853) 3 4 21 28 coriaceum Lasioglossum (Schrank 1781) 3 0 3 6 leucozonium* Sphecodes spp. 4 4 2 10 Megachilidae Anthidium (Linnaeus 1758) 0 1 2 3 manicatum* Anthidium (Illiger 1806) 27 28 42 97 oblongatum* Chelostoma (Robertson 0 0 1 1 philidelphi 1891) Coelioxys sp. Cockerell 1912 0 0 1 1 Heriades Cresson 1864 0 0 1 1 carinata Hoplitis producta 0 3 1 4 (Cresson 1864) Megachile Spinola 1808 0 0 1 1 apicalis* Megachile (Linnaeus 1758) 1 3 4 8 centuncularis* Megachile frigida Smith 1853 0 0 2 2 Megachile Cresson 1878 0 6 1 7 mendica Megachile Say 1837 0 1 0 1 pugnata Megachile (Fabricius 1787) 16 35 24 75 rotundata* Megachile Cresson 1878 0 0 1 1 texana Osmia (Linnaeus 1758) 4 7 3 14 caerulescens* Osmia cordata Robertson 1902 0 1 0 1 Osmia pumila Cresson 1864 0 1 2 3 Pseudoanthidium (Mocsáry 1881) 0 0 2 2 nanum* Stelis lateralis 2 0 0 2 Cresson 1864 21

Generalized Linear Models

Predators on Yellow Sticky Card Traps

Ladybeetles (Coleoptera: Coccinellidae) were more abundant within rain gardens in 2014 (F1/110=4.08, p=0.0458), but no difference among habitat treatments was found in 2015 nor 2016 (2015: F1/142=1.28, p=0.2602; 2016: F2/204=0.68, p=0.5067; Figure 2). Coccinellidae abundance varied seasonally, with higher numbers of coccinellidae in August in 2014 and 2015 (2014: F1/110=34.09, p<0.001; 2015: F2/142=25.99, p<0.001), and in

July of 2016 (2016: F2/204=5.36, p=0.0054).

There were similar numbers of long-legged flies (Diptera:

Dolichopodidae) found on sticky card traps across all habitat types in 2014

(2014: F1/110=1.32, p=0.2532) and 2015 (2015: F1/142=0.02, p=0.8795). In

2015, there was a significant treatment by month interaction (F2/142=3.33, p=0.0387), however there were no significant differences among treatments, within a given month. In 2016, there was also a significant month by treatment interaction (F4/204=5.57, p=0.0003). Here, fly abundance was reduced in vacant lots relative to rain gardens in June; abundance was similar among treatments for the reminder of the growing season (Figure 3).

There was seasonal variation in abundance of long-legged flies (Diptera:

Dolichopodidae) on sticky cards in all years. In 2014, there was a lower abundance of long-legged flies in August (2014: F1/110=9.78, p=0.0023). In 22

2015, the lowest abundance of long-legged flies was midseason (July) and rebounded to have the highest abundance by August (2015: F2/142=27.94, p<0.0001). In 2016, there was seasonal variation within a treatment with more flies in June compared to July and August in rain gardens, bioswales, and vacant lots (Treatment*Month interaction: F4/204=5.57, p=0.0003).

For 2014, there was no difference in pirate bug (Hemiptera:

Anthocoridae) abundance by habitat type (F1/110=3.15, p=0.0785). In 2015, there were more pirate bugs collected in vacant lots compared to rain gardens in June, but no differences in abundance by habitat type in either

July or August (Figure 4). There was also a significant treatment and month interaction in 2016 (F4/204=3.61, p=0.0073), however there were no significant differences among treatments, within a given month. There was no seasonal variation of pirate bugs in 2014 (2014: F1/110=0.12, p=0.7316). In

2015, there were more pirate bugs in June compared to August in rain gardens and vacant lots (Treatment*Month interaction: F2/142=21.99, p<0.0001). In 2016, there were fewer pirate bugs in August compared to

June across all habitat types (Treatment*Month interaction: F4/204=3.61, p=0.0073).

There were higher abundances of rove beetles (Coleoptera:

Staphylinidae) found on sticky card traps in rain gardens compared to vacant lots in 2014 (2014: F1/110=9.56, p=0.0025; Figure 5). However, 2015 had

similar abundances of rove beetles in all habitat types (2015: F2/142=1.89, p=0.1716; Figure 5). For 2016, there was a significant treatment and month interaction (F4/204=2.42, p=0.0497), however, there were no significant

differences among treatments, within a given month. There was no seasonal variation of rove beetles found on sticky cards in any years of the study

(2014: F1/110=0.03, p=0.8598; 2015: F2/142=1.58, p=0.2097; 2016

Treatment*Month interaction: F4/204=2.42, p=0.0497).

Hoverflies (Diptera: Syrphidae) were more abundant in rain gardens in July, 2015, but no differences among habitat were found in June and

August (Treatment*Month interaction: F2/142=28.50, p<0.0001, Figure 6). In

2016, the highest abundance of Syrphidae was in June with lower abundances in July and August (2016: F2/204=18.16, p<0.0001), but no difference by habitats in 2016 (F2/204=0.90, p=0.4066).

Figure 2. Ladybeetle (Coleoptera: Coccinellidae) abundance collected on Yellow Sticky Card Traps in Vacant lots, Rain Gardens, and Bioswales in 2014, 2015, and 2016. Letters indicate significant differences of habitat type within a year.

Figure 3. Long-legged flies (Diptera: Dolichopodidae) abundance collected on Yellow Sticky Card Traps in Vacant lots, Rain Gardens, and Bioswales by month in 2016. Letters indicate significant differences of habitat type within a month.

Figure 4. Pirate bugs (Hemiptera: Anthocoridae) abundance on Yellow Sticky Card Traps in Vacant lots and Rain Gardens by month in 2015. Letters indicate significant differences of habitat type within a month.

Figure 5. Rove beetles (Staphylinidae) abundance collected on Yellow Sticky Card Traps in Vacant lots, Rain Gardens, and Bioswales in 2014, and 2015. Letters indicate significant differences of habitat type within a year.

Figure 6. Hover flies (Syrphidae) abundance on Yellow Sticky Card Traps in Vacant lots, and Rain Gardens by month in 2015. Letters indicate significant differences of habitat type within a month.

Bees on Yellow Sticky Card Traps

In 2014, there was a similar abundance of bees within rain gardens and vacant lots across the sampling period (Treatment*Month interaction:

F1/110=4.18, p=0.0432), but a difference in abundance by month within a treatment with more bees collected in August compared to July in vacant lots.

There was seasonal variation in bees on sticky cards in 2015 with higher bee abundance in early August (2015: F2/142=3.23, p=0.0423), but similar bee abundances across vacant lots, and rain gardens (2015: F1/142=0.00, p=0.9997). In 2016, there were more bees in rain gardens compared to 27

vacant lots in July, but no difference in abundance by habitat type in either

June or August (Treatment*Month interaction: F4/204=4.47, p=0.0017; Figure

7). Moreover, in 2016 there were more bees collected in July compared to

June and August in rain gardens, but no difference by month in bioswale or vacant lots (Treatment*Month interaction: F4/204=4.47, p=0.0017).

Figure 7. Bee (Apoidea) abundance per Yellow Sticky Card Traps in Vacant lots, Rain Gardens, and Bioswales by month in 2016. Letters indicate significant differences of habitat type within a month.

Bees from bee bowls

In 2014, more bees per bowl were collected at vacant lots than rain gardens in August, but no difference by habitat type in July

(Treatment*Month interaction: F1/119=12.29, p=0.0006; Figure 8). However, there was no difference in abundance by habitat in 2015 (F1/154=3.38, p=0.0678) or 2016 (F4/192=1.31, p=0.2723). In 2014, there were fewer bees per bowl collected in July compared to August in both rain garden and vacant lots (Treatment*Month interaction: F1/119=12.29, p=0.0006). Similarly, there was seasonal variation in 2015 and 2016 with a greater number of bees collected later in the season (2015: F2/154=45.08, p<0.0001; 2016:

F4/192=16.21, p<0.0001).

Figure 8. Bee (Apoidea) abundance per bowl in Vacant lots, and Rain Gardens by month in 2014. Letters indicate significant differences of habitat type within a month.

Partial Least Squares Regression PLS Model Year t1 t2 Q2 R2Y R2X Q2 R2Y R2X Sticky Trap: Predators 2014 0.076 0.156 0.481 0.036 0.238 0.740 2015 0.081 0.184 0.384 0.220 0.349 0.613 2016 0.208 0.259 0.301 0.212 0.331 0.450 Sticky Trap: Bees 2014 0.115 0.211 0.467 0.086 0.315 0.696 2015 -0.120 0.236 0.189 -0.169 0.296 0.428 2016 0.113 0.315 0.281 -0.092 0.343 0.547 Bee Bowls 2014 0.290 0.388 0.412 0.306 0.429 0.913 2015 0.301 0.385 0.359 0.283 0.456 0.523 2016 0.179 0.249 0.348 0.138 0.324 0.485

Table 5. Compliled results of PLS regression analysis comparing the influence of habitat factors on pollinators and predators. Bee bowl dependent variables included overall bee abundance, Halictidae, Apidae, and Lasioglossum. Sticky card bee variables included overall bee abundance, Hylaeus, and Lasioglossum. Sticky card predator variables included Anthocoridae, Coccinellidae, Dolichopodidae, Staphylinidae, and Syrphidae (2015 and 2016 only). Each model reports the Q2 (proportion of variance in response variable predicted by the model), R2Y (proportion of variance in response variable explained by the model), and R2X (proportion of variance in predictor variables used in the model) based on the model components of T1 and T2.

Predators on sticky cards and PLS-R models

Abundances of Dolichopodidae, Syrphidae, and Anthocoridae collected on sticky cards were influenced by local habitat management in

2015 and 2016. The PLS analysis for 2014 predators on sticky traps did not have significant Q2 values for either t1 or t2 (Table 5). However, the 2015 predatory model did have significant a Q2 score for t2 (Q2=0.220), but not for t1 (Q2=0.081) (Table 5). The predatory insect abundance was significantly related to the habitat factors on t2 with the data explaining 34.5% of the arthropod abundance within a given site (Table 5). For yellow sticky card

traps in 2015, five variables had a VIP score >0.8 for t1: month, plant height, bloom area, bloom richness, and percent forb cover.

For the year 2015, Dolichopodidae (R2 =0.367) and Syrphidae (R2

=0.233), had slightly stronger correlations with the t2 axis than Anthocoridae

(R2 =0.115), Coccinellidae (R2 =0.122), or Stapylinidae (R2 =0.000).

Dolichopodidae were more common in habitats with tall vegetation, and were positively associated with bloom area (Figure 9). Dolichopodidae were also more common in August than earlier in the growing season for 2015

(Figure 9). Interestingly, Syrphidae were more common in habitats with shorter vegetation which had fewer flowering resources present and were more common during the July sampling period (Figure 9).

Figure 9. Correlation maps of the PLS regression of 2015 and 2016 predators on Yellow Sticky Card Traps. Only variables with VIP of > 0.8 are shown.

The PLS-R model of predators on yellow sticky card traps in 2016 had significant Q2 scores for both t1 (Q2 = 0.208) and t2 (Q2 =0.212) (Table 5).

The predatory insect abundance was significantly related to the habitat factors on t1 with the data explaining 25.9% of the arthropod abundance within a given site (Table 5). An additional 7.2% of the variation in predator abundance is explained by t2 (Table 5). The 2016 predator model had seven factors with a VIP > 0.8: month, site type – Rain Garden, forb, leaf litter/mown, bloom area, and plant height.

In 2016, Coccinellidae were not strongly predicted by the model on either t1 (R2 = 0.019) or t2 (R2 =0.092). Similarly, Staphylinidae were not strongly predicted by the model on either either t1 (R2 = 0.044) or t2 (R2

=0.144). Dolichopodidae (R2 =0.449), Syrphidae (R2 =0.478), and

Anthocoridae (R2 =0.305) were strongly correlated with the t1 axis, but not t2

(R2 =0.008, R2 =0.110, and R2 =0.006 respectively), Dolicopodidae, Syrphidae, and Anthoridae are all positvely associated with percent of forb cover, higher bloom area, and taller plant vegetation in addition to the early sample season

(June) and Rain Gardens on the t1 axis (Figure 9). Dolicopodidae, Syrphidae, and Anthocoridae are negatively associated with sites with lots of leaf litter or mown grass and later season sample periods (July, August) (Figure 9).

Figure 10. Correlation maps of the PLS regression of 2014 and 2016 bees (Apiodea) on Yellow Sticky Card Traps. Only variables with VIP of > 0.8 are shown.

PLS-R of bees on sticky cards

Abundances of bees on sticky cards were influenced by habitat factors in 2014 and 2016. For bees on yellow sticky cards in 2014, there were significant Q2 scores for t1 (Q2 =0.115), but not t2 (Q2 = 0.086) (Table

5). The bee abundance was significantlly related to the habitat factors on t1 with the data explaining 21.1% of the bee abundance in a given site (Table 5).

An additional 10.4% of the variation in bee abundance on sticky cards is explained by t2 (Table 5). A total of seven variables a VIP > 0.8: Month, site type, bloom area, bloom richness, percent cover of mulch, rocks/sticks, and bare ground.

In 2014, the overall abundance of bees (R2=0.106) and bees in the genus Lasioglossum (R2=0.045) were not strongly predicted by the model on t1 or t2 (R2=0.141, R2=0.117 respectively). However, the abundance of bees in the genus Hylaeus were strongly predicted by t1 (R2=0.481), but not t2

(R2=0.054). Abundance of Hylaeus were postively assoicated with vacant lots, later season (August), higher bloom richness, higher abundances of rocks and sticks, and higher proportions of bare ground (Figure 10). Abundance of

Hylaeus were negatively associated with rain gardens, high proportions mulch cover, and mid season (July) (Figure 10).

The PLS-R analysis for 2015 bees on sticky cards did not have significant Q2 values on either t1 or t2 (t1= -0.120 and t2 = -0.169) (Table 5). 35

The PLS-R model for bees on yellow sticky cards in 2016 had a significant Q2 score for t1 (Q2 = 0.113), but not t2 (Q2 = -0.092) (Table 5). The bee abundance on sticky cards was significantly related to habitat factors on t1 with the data explaining 31.5% of the bee abundance within a given site

(Table 5). An additional 2.8% of variation of bee abundance is explained by t2

(Table 5). For t1, seven factors had a VIP of greater than 0.8: Site Type –

Vacant lot, Site Type – Rain Garden, Month – June, Month – July, plant height, grass coverage, forb coverage.

In 2016, the total number of bees on sticky cards (R2=0.354), bees in the genus Lasioglossum (R2=0.235), and bees in the genus Hylaues (R2=0.357) were more strongly correlated with the t1 than the t2 axis (R2=0.017;

R2=0.067; R2=0.001 respectively). Abundance of overall bees, bees in the genus Lasioglossum, and bees in the genus Hylaeus were postively associated with rain gardens, midseason sampling (July), taller plant vegetation, and higher dominance of forbs (Figure 10). Abundance of overall bees, bees in the genus Lasioglossum, and bees in the genus Hylaeus were negatively associated with vacant lots, early season sampling (June), and percent cover of grasses (Figure 10).

Figure 11. Correlation maps of the PLS regression of 2014-2016 bees (Apioidea) collected from bee bowls. Only variables with VIP of > 0.8 are shown.

PLS-R models of bees from bee bowls

Abundances of bees collected from bee bowls were associated with several habitat management or seasonal factors in 2014-2016. The PLS-R model for bees collected from bee bowls in 2014 had a significant Q2 score on both t1 (Q2 =0.290) and t2 (Q2 =0.306) (Table 5). The bee abundance collected by bowls was significantly related to the habitat factors on t1 with the data explaining 38.8% of the bee abundance within a given site (Table 5). An additional 4.1% of the variation in predator abundance is explained by t2

(Table 5). Only two factors had a VIP of greater than 0.8: Month-July, Month-

August.

In 2014, the overall abundance of bees (R2=0.501), bees in the family

Apidae (R2=0.315), bees in the family Halictidae (R2=0.381), and bees in the genus Lasioglossum (R2=0.354) were all strongly correlated with the t1 axis, but not the t2 axis (R2=0.026; R2=0.031; R2=0.050; R2=0.056 respectively).

The overall abundance of bees, bees in the family Apidae, bees in the family

Halictidae, and bees in the genus Lasioglossum were all positively associated with the sampling period of August and negatively associated with the sampling period of July in 2014 (Figure 11).

The PLS-R model for bees collected from bee bowls in 2015 had significant Q2 scores on both t1 (Q2 =0.301) and t2 (Q2 =0.283) (Table 5). The

bee abundance collected by bowls was significantly related to the habitat factors on t1 with the data explaining 38.5% of the bee abundance within a given site and an additional 7.1% of the variation in predator abundance is explained by t2 (Table 5). A total of five factors had a VIP of greater than 0.8:

Month-June, Month-August, bloom richness, forb cover, and leaf litter/mown grass.

In 2015, the overall abundance of bees (R2=0.345), bees in the family

Apidae (R2=0.321), bees in the family Halictidae (R2=0.408), and bees in the genus Lasioglossum (R2=0.467) were all strongly correlated with the t1 axis, but not the t2 axis (R2=0.119; R2=0.054; R2=053; R2=0.056 respectively). The overall abundance of bees, bees in the family Apidae, bees in the family

Halictidae, and bees in the genus Lasioglossum were all positively associated with the sampling period of August and higher abundances of leaf litter/mown grass (Figure 11). The overall abundance of bees, bees in the family Apidae, bees in the family Halictidae, and bees in the genus

Lasioglossum were negatively associated with bloom richness, percent cover of forbs and early season sampling (June) in 2015 (Figure 11).

The PLS-R model for bees collected from bee bowls in 2016 had significant Q2 values on both t1 (Q2 =0.179) and t2 (Q2 = 0.138) (Table 5). The bee abundance collected by bowls was significantly related to the habitat factors on t1 with the data explaining 24.9% of the bee abundance within a

given site and an additional 7.5% of the variation in abundance is explained by t2 (Table 5). A total of six factors had a VIP of greater than 0.8: Month-June,

Month-July, Month-August, bloom area, rocks/sticks, forb, and leaf litter/mown grass.

In 2016, the overall abundance of bees (R2=0.364), bees in the family

Halictidae (R2=0.299), and bees in the genus Lasioglossum (R2=0.269) were all strongly correlated with the t1 axis, but not the t2 axis (R2=0.082;

R2=0.162; R2=0.022 respectively). The abundance of bees in the family

Apidae was not strongly correlated on t1 (R2=0.064) or t2 (R2=0.033). The overall abundance of bees, bees in the family Halictidae, and bees in the genus Lasioglossum were all positively associated with the later sample period (August) and higher abundanecs of leaf litter/mown grass (Figure

11). The overall abundance of bees, bees in the family Halictidae, and bees in the genus Lasioglossum were all negatively associated with the early sample season (June), higher bloom area, and high amounts of forb cover (Figure

11).

Discussion

The overarching goal of this collaborative partnership is to determine if rain garden installations have the dual benefit (stacked ecosystem services) of both mitigating stormwater overflow events while also supporting beneficial arthropods. The US EPA, USGS, and Cleveland Botanical 40

Gardens are continuing to analyze the potential stormwater capture of the low cost rain gardens. The goal for this chapter was to determine whether establishing low or high cost green infrastructure (here termed rain gardens and bioswales respectively) altered the value of urban vacant land for beneficial arthropods.

I found a wide diversity of beneficial insects during this study. Across all habitat types, a total of 81 species of bee and 12 genera of ladybeetles were able to persist inner-city habitats. In both ladybeetles and bees, there were several non-native species present. With Coccinellidae, Scymnus was the most abundant genus, but I was unable to determine to a lower taxonomic level due to diagnostic features being obscured by the adhesive.

The second most abundant group of ladybeetles was a complex of small black ladybeetles which could not be determined to a lower level due to obscured diagnostic features. However, the third most abundant group of ladybeetles was Propylea quatuordecimpunctata (n=745), a non-native species. Several other non-native species were found including Hippodamia variagata (n=64),

Harmonia axyridis (n=62), and Coccinella septempunctata (n=6). However, several native species of ladybeetles were also collected in these urban habitats including Coleomegilla maculata (n=147), Cycloneda munda (n=88),

Hyperaspis undulata (n=24), and Psyllobora vigintimaculata (n=18) among others. This distribution of native species is in stark contrast to ladybeetle populations found in agricultural crops, with exotic species sometimes

dominating by up to 90% of the total Coccinellidae abundance (Gardiner et al., 2009). Excluding groups that could not be identified to species (and thus their native/exotic status), I found that exotic ladybeetles make up ¾ of the total abundance, largely driven by the high abundances of Propylea quatuordecimpunctata.

Looking at bee species composition, there is a very different pattern, with exotic species of bees making up only 11% of the total abundance of bees collected via bee bowls. Here, the most abundant species are

Agapostemon virescens (n=336), Lasioglossum (Dialictus) imitatum (n=325), and Calliopsis andreniformis (n=200), all native species. The exotic species with the highest abundance is Anthidium oblongatum (n=97), which is the

12th most abundant species of bee collected.

Differences in abundance by habitat type were inconsistent across years by taxa. Of all the taxa compared with generalized linear models, 80% of the time abundance did not vary by habitat type. However, 15% of the time there was an increase in beneficial arthropod abundance at rain gardens and 4% of the time there was a decrease in abundance of beneficial insects at rain gardens. When looking at predatory taxa, 19% of the time there is an increase in abundance at rain gardens versus 78% no difference and 2% with a decrease in abundance. Looking at bee abundances with both collection methods, there are higher abundances in rain gardens 5% of the time, no difference 86% of the time, and a decrease in abundance 8% of the time.

Overall, when looking across an entire year, these rain garden installations do little to either positively or negatively impact beneficial insect populations most of the time, which can imply that installing rain gardens or bioswales for rain water collection and stormwater overflow reductions does not necessarily have the stacked ecosystem service of benefiting pollinators and predatory insects. However, this still raises the question as to the drivers of differences in beneficial insect abundance. These differences could be partly due to the readily abundant floral and nesting resources already in vacant lots. As they are not maintained to a similar rigor of suburban lawns with weed control services, these vacant lots have high abundances of floral resources year round.

Thus, I attempted to determine which habitat resources were the most important drivers of variation in arthropod abundances. Similar to the generalized linear model results, few local habitat factors were consistent drivers of predatory arthropod abundances across years. Several predatory taxa were more commonly associated with taller plant vegetation and higher bloom area (but not bloom abundance, or bloom richness).

Moreover, it is important to take into consideration potential prey population levels within these sites and how changes in prey abundance could impact predator abundance. Prey populations were not measured, so I can only conjecture potential prey population levels. To measure prey populations, I would have needed to visually search plants within the

quadrats for aphids and mites, which are common prey of Coccinellidae,

Syrphidae, and Staphylinidae. Ideally, predator populations will be high and maintain prey populations at low levels so that they do minimal damage (top down effects). However, prey populations can also swell to be much larger and in turn support a larger predator population (bottom up effects). More research and collection efforts is needed to elucidate how the prey populations change within vacant lots and rain gardens and to which local habitat factors they more closely associate.

The bees collected with the two collection methods seemed to have different local habitat drivers. Bees collected via sticky cards did not have consistent local habitat factors driving their abundances between years.

Abundances of bees collected with bee bowls were not explained by local habitat factors in 2014, but some variation was explained in 2015 and 2016.

The challenge with the bees collected via bee bowls is that in addition to not responding consistently to local habitat factors, they also do not appear to respond to the same habitat factors as bees collected via sticky cards.

Paradoxically, bee abundance was negatively associated with bloom richness and abundances of forbs in 2015, which is contrary to most literature (Potts et al. 2009, Crone and Williams 2016). Moreover, bees were negatively associated with bloom area and abundances of forbs in 2016, which is also contrary to most literature (Potts et al. 2009, Crone and Williams 2016). The negative relationship to bloom area in 2016 can partly be explained as an

artifact of the floral resources driving floral area in 2016. This was the year where rain gardens finally had high abundances of Achillea millefolium blooming. This is a species of flower that has a rather large bloom area (thus conflating the bloom area measurement), but is not traditionally attractive to most species of bees. Moreover, its growth pattern in the turf section of rain gardens causes it to grow much taller and outcompete most other floral resources, potentially reducing bees foraging preference in that local area.

Conclusion

Although rain garden installations can potentially have benefits for storm water management and reducing sewage overflow events, the newly constructed habitats might not immediately support (nor detract) beneficial arthropods present in the local community. Overall, there does not seem to be a consistent positive or negative impact of rain garden installations compared to vacant lots. Although these converted vacant lots do not seem to consistently support one taxa of beneficial insects, they also do not appear to have long lasting negative impacts on beneficial insects. Moreover, there do not appear to be consistent habitat factors that directly impact the beneficial insect abundances at such local scale habitat management.

Chapter 2: Urban floral visitor communities and the role of native/exotic bees for network function

Introduction

Importance of pollinators Worldwide, bee pollinators are required for 35% of crops (Klein et al.

2007), though a larger percent of crops also benefit by increased yield and fruit set with additional pollen deposition (Burd 1994, Porcher and Lande

2005). Pollination services are worth an estimated $15 billion in the United

States per year (Calderone 2012). These services are provided by both managed and unmanaged bees. Moreover, there is a vast body of literature explaining the importance of native, unmanaged bees to pollination services

(Losey and Vaughan 2006, Garibaldi et al. 2013). Providing refuge habitat for these pollinators is important in light of recent declines in pollinators

(Brown and Paxton 2009).

Economic valuation and pollinator decline

Native pollinators provide pollination services valued at over $3 billion annually in the United States (Losey and Vaughan 2006). However, bees have been in decline throughout the world, with particular attention focused on the European honey bee, Apis mellifera (Winfree et al. 2007, Aizen and Harder 2009). Apis mellifera is only a single species of the estimated 46

20,000 bee species worldwide (Ascher and Pickering 2017). Yet, many of these species are understudied and their current conservation status remains unclear (Potts et al. 2010). However, thanks to historical datasets available in Europe, many authors have been able to document native bee decline in their region (Fitzpatrick et al. 2007, Kosior et al. 2007, Potts et al.

2010).

In the United States, a dearth of historical records make determining species loss difficult. In the few areas with historical records, researchers have found small levels of species decline, but drastic changes to the overall community composition with fewer species of once abundant pollinators and an increase in non-native species (Bartomeus et al. 2013, Burkle et al. 2013).

Bumblebees are of particular conservation concern, with some taxa declining by 96% in abundance in the United States (Cameron et al. 2011). Overall, pollinators are going through drastic changes which warrants efforts into mitigating these pollinator losses.

Pollinator community change

Several factors contribute to pollinator abundance and diversity declines including habitat loss and degradation (Brown and Paxton 2009,

Winfree et al. 2009, Goulson et al. 2015). Bee richness and abundance is directly correlated with habitat area (Steffan‐Dewenter 2003), thus increasing suitable habitat is imperative for supporting pollinator communities. Moreover, land use change may negatively impact pollinators,

but having a diversity of habitat types can positively impact these communities (Senapathi et al. 2015). Therefore, a key factor to support bee populations is habitat conservation and restoration.

Habitat quality is also important to a functioning ecosystem. Providing adequate floral and nesting resources is required for both pollinator abundance and richness. Both floral abundance and diversity can influence pollinator communities. Many studies show that increasing floral abundance, diversity, and density yields greater pollinator abundance (Ghazoul 2006) or pollinator richness (Potts et al. 2003, Hegland and Boeke 2006).

Urban Ecology and Biodiversity

Our understanding of urban ecology and drivers of urban biodiversity is still being developed as more ecologists direct their focus to understanding urban areas. Moreover, biodiversity studies in urban areas serve as an important baseline for future research to compare biodiversity after expected changes in disease prevalence, altered climate, and increased human population and density.

There is a perception that urban vacant land is wasted space waiting to be developed. However, urban vacant land and other urban greenspaces may serve as important habitat refuges in an otherwise barren landscape of concrete and metal. Various studies have already found that urban vacant land can support a variety of beneficial arthropods (Uno et al. 2010, Gardiner and Burkman 2013, Gardiner et al. 2014). New species are still waiting to be 48

discovered in these urban landscape, with recent examples including the

Gotham Sweat Bee (Gibbs 2011) or the many new species of flies found in

Los Angeles as part of a biodiversity survey (Hartop et al. 2015).

Of the body of urban ecology literature, a majority of it focuses on remnant habitats and managed gardens, with less emphasis on personal gardens, parks, or minimally/unmanaged sites (Hernandez et al. 2009).

Diversity studies in urban areas do show that several bee species readily colonize and live in a variety of urban areas (Tommasi et al. 2004, Matteson et al. 2008, Baldock et al. 2015, Sirohi et al. 2015). A different study found that compared to agricultural land, the nearby cities lost proportionally fewer pollinator species over a period of 80 years (Senapathi and Carvalheiro

2015). Moreover, even endangered bee species have been found in urban settings (Sirohi et al. 2015), thus illustrating the potential for conservation in urban areas. However, increased levels of development and less greenspace strongly correlated with lower bee species richness (Hernandez et al. 2009,

Lowenstein et al. 2014), thus care must be taken to encourage and protect the remaining greenspace in urban areas.

There also remains the question of which available floral resources best support pollinators and other beneficial insects. One way to determine this is to look at individual floral resources to see which species of plants attract the highest abundance of floral visitors, highest abundance of bees, or

highest richness of pollinators. Common “weedy” plants have few published papers on what types of pollinators readily forage on them and at what abundance. As an example, Cichorium intybus is a common roadside weed also found in vacant lots in the Midwestern United States, yet most of the literature focuses on its potential as livestock feed (Barry 1998) or for medicinal purposes (Bischoff et al. 2004, Pushparaj et al. 2007).

Moreover, different combinations of floral communities can potentially attract higher abundances of pollinators. Specifically, adding floral resources that have generally higher amounts of pollen and nectar resources should attract more floral visitors, and in turn support overall higher populations within a local habitat.

Finally, there is the question of the impact of these native and exotic plant species and whether they are preferred by native or exotic species of pollinators. Williams et al (2011) found that it was not whether the plant species were native or exotic, but their abundance within a particular habitat that drove the resource use by bees, with bees more often utilizing alien plant resources in highly disturbed habitats. However, their study did not look at whether the bees being native or exotic potentially played a role in this outcome.

The overarching goal of this chapter is to determine the importance of inner city habitat for bee conservation and ways to alter this habitat to 50

increase its conservation potential. Thus, this chapter has the following objectives: a) document arthropod biodiversity in inner-city Cleveland, Ohio; b) determine important floral resources for this biodiversity; c) determine influence of planting mixes on bee abundance; and d) determine which common plant species are preferred by native and exotic bee species. I expect native plant species to be more important for native bee species, and thus the native plant mixes to have higher abundances of bees.

Methods:

Research plots were located within eight neighborhoods in Cleveland,

Ohio, USA: Glenville, Hough, Detroit Shoreway, Slavic Village, Tremont/Clark

Fulton, Fairfax, Central, and Buckeye. Within each neighborhood, five vacant lots were assigned to habitat treatments as follows: 1) vacant lot with regular mowing, 2) successional vacant lot only mown once a year, 3) vacant lot with a low growing flowering lawn mix, 4) vacant lot with the low diversity prairie mix, and 5) vacant lot with the high diversity prairie mix (Table 6). Each neighborhood had one lot of each habitat treatment, with the exception of

Detroit Shoreway in 2016, which did not have a successional habitat, to make a total of 40 sites in 2015 and 39 in 2016. Lots were leased through the City of Cleveland Land bank for the duration of the study.

In the prairie and flowering lawn treatments sites, a glyphosate based, non-selective herbicide was applied twice (1st treatment: May 28-30, 2014;

2nd treatment: June 23-25, 2014). Sites then had the soil lightly broken up for the broadcast seed application and seeded with their respective floral mixes.

The flowering lawn seed mix contained a fescue grass blend and six forb species (Table 6). The low and high diversity prairie treatments contained three native grass species (Elymus canadensis, Sorghastrum nutans,

Schizachyrium scoparium) and either 4 or 16 forbs (Table 6). On January 28 and 29 2016, the low and high diversity prairie sites were overseeded with two and six additional forb species for a total planted richness of six and twenty-two species respectively. All seeded treatments were mown monthly during 2015. In 2016, the flowering lawn sites mown monthly and prairie sites mown once in October.

Habitat name Vegetation structure Mowing schedule Vacant lot Existing volunteer forbs and grasses Once a month Successional Existing volunteer forbs and grasses Once a year plus monthly border/edge trimmings Flowering Herbicide applied in fall of 2014 and the following Once a month lawn seed mix added: Nemophila menziesi, Bellis perennis, Trifolium repens, Trifolium fragiferum, Achillea millefolium, Lobularia maritima Low Diversity Herbicide applied in fall of 2014 and the following Once a year plus Prairie seed mix added: Elymus canadensis, Sorghastrum monthly border/edge 3 grasses + 6 nutans, Schizachyrium scoparium, Lobelia trimmings forbs siphilitica, Ratibida pinnata, Zizia aurea, Eupatorium purpureum Overseed mix: Monarda citriodora, Rudbeckia hirta High Diversity Herbicide applied in fall of 2014 and the low Once a year plus Prairie diversity prairie seed mix added plus the monthly border/edge 3 grasses + 22 following: Liatris spicata, Verbena hastata, trimmings forbs Silphium perfoliatum, Penstemon digitalis, Vernonia fasciculata, Coreopisis lanceolata, Aster novae-angliae, Tradescantia ohiensis, Silphium terebinthinaceum, Eryngium yuccifolium, Solidago riddellii, Monarda fistulosa Overseed mix: low diversity overseed + Chamaecrista fasciculata, Gaillardia pulchella, Bidens aristosa, Coreopsis tinctoria Table 6. Plantings and management schedule for each of the five habitat treatments: Vacant lot, Successional lot, Flowering Lawn, Low Diversity Prairie, and High Diversity Prairie. All sites were either mown monthly or yearly depending on the treatment.

Pollinator Collection:

Sampling took place once per month on non-rainy days at each site on the following dates: 2015: July 8-15, August 12-19, September 13-25; 2016:

June 9-21, July 5-8, Aug 2-8. Sampling occurred between 10 am and 4 pm on those dates. Arthropods on floral structures were collected during timed collections of 4.5 minutes per floral species per site and the floral species they were collected on was recorded. Arthropods smaller than 3 mm were not collected as specimens under that size range rarely carry enough or any pollen to warrant documentation for the network (Rader et al. 2011).

Arthropods were collected from floral structures with Heavy Duty Hand

Vacuums from Bioquip (Figure 12) which have greater precision and were less likely to damage vegetation than sweep nets. Within each vacuum, the canisters were lined with a disposable sock so arthropods could be easily transferred in the field and avoid pollen contamination.

Figure 12. Heavy Duty Hand Vacuums, also known as a Bee vacuums, are useful to quickly collect visitors from flowers without accidentally damaging large parts of the plant structure which is common with sweepnets. Handheld vacuums also allow greater certainty that specimens were collected from the intended floral resource. Photo by Nicole Hoekstra.

All arthropods were identified to family level. Arthropods in the following families were identified to genus and species where possible:

Andrenidae, Apidae, Colletidae, Halictidae, Megachilidae, and Syrphidae.

These groups were identified with a variety of resources including the key to the Genera of Nearctic Syrphidae (Miranda et al. 2013), Discoverlife.org for bee genera (Ascher and Pickering 2017), recent revisions by Jason Gibbs for

Lasioglossum (Gibbs 2011, Gibbs et al. 2012), and Bumble Bees of North

America (Williams et al. 2014). Bee species were verified by Sam Droege at the USGS Bee Inventory and Monitoring Lab. Voucher specimens of bees and other arthropods were deposited to the Museum of Biological Diversity in

Columbus, Ohio.

Habitat abundance comparisons:

Total abundances of bees were summed per site across a sampling year. To account for variation in sampling effort, each abundance was divided by the number of sampling units (sum of floral species sampled per month) per site across the year.

In order to compare weighted abundances of bees per sampling effort across habitat types, Generalized linear models were created in R (v3.3.3; R

Core Team 2017) and then histograms were created with package “ggplot2”

(Wickham 2009). The model was bee abundance per sampling effort as the response variable and habitat type as the fixed effect. Type 3 fixed effects

were calculated with the Anova function in package “car” (Fox and Weisberg

2011) to determine significant differences in abundance between habitat types.

Community Modelling:

I examined floral visitation of native exotic bees and created visitation networks to compare the community level differences of their floral preferences. Native is classified as indigenous to Ohio whereas exotic is defined as any species not thought to be historically present in Ohio. All bee species were categorized as native or exotic based on Discoverlife.org

(Ascher and Pickering 2017) and a recent paper by Russo (2016). Networks were created in the bipartite package (Dormann 2011) in R 3.2.2 (R Core

Team 2017). All networks were summed across all of the sites in Cleveland and across a year, but not between years. The Native/Exotic bee network included three categories for bees: Native, Exotic, and Apis mellifera. Network models assume that all plant/visitor combinations are possible, when in reality, these visitations are constrained by spatial and temporal factors

(forbidden links; see Olesen et al., 2010). An attempt to control for spatial factors was to subset the plant visitation networks to only plant species found in at least a quarter of the sites. These networks were compared by creating species level metrics of Paired Difference Index (PDI), and

proportional generality. Then 1,000 null models were created to see which values differed from the expected null distributions.

Results:

Objective a) document arthropod biodiversity In 2015, a total of 2,041 arthropods in 71 families were collected off flowers across all sites. Hymenoptera were the most common Order with

1,137 individuals. Diptera (n=584) and Coleoptera (n=173) were also abundant in 2015 collections. Furthermore, a total of 254 flies in the family

Syrphidae were collected among 12 genera. The second most abundant

Dipteran family in 2015 was Calliphoridae with 159 specimens.

In 2016, a total of 1,415 arthropods in 63 families were collected from flowers. Similarly, Hymenoptera was the most abundant Order (n=881) followed by Coleoptera (n=243) and Diptera (n=195). In 2016, the most abundant Coleopteran family was Nitidulidae (n=80). Syrphidae was the

Dipteran family with highest abundance with a total of 96 flies among 11 genera in 2016.

For 2015, 961 specimens were in the five bee families (Andrenidae,

Apidae, Colletidae, Halictidae, and Megachilidae) across 51 species (Table 7).

For 2016, 791 specimens were bees in 59 species (Table 7). Of all bees collected and identified to species level, 560 individuals in 13 species (n=220 in 2015; n=340 in 2016) were representatives of exotic bee taxa (Table 7). Of these, 246 were honey bees, Apis mellifera (Table 7). A total of 1,032

individuals (n=633 in 2015; n=399 in 2016) represented native bee species

(Table 7).

Family Species 2015 2016 Total Andrenidae Andrena alleghaniensis 0 1 1 Andrena asteris 1 0 1 Andrena vicina 0 1 1 Andrena wilkella* 8 43 51 Calliopsis andreniformis 0 3 3 Apidae Anthophora terminalis 3 0 3 Apis mellifera* 99 147 246 Bombus bimaculatus 7 16 23 Bombus fervidus 86 13 99 Bombus griseocollis 40 53 93 Bombus impatiens 130 18 148 Bombus vagans 19 1 20 Ceratina calcarata 74 97 171 Ceratina strenua 1 0 1 Melissodes agilis 1 1 2 Melissodes bimaculatus 7 16 23 Melissodes subillatus 0 6 6 Nomada pygmaea 0 1 1 Peponapis pruinosa* 2 0 2 Triepeolus lunatus 0 6 6 Xylocopa virginica 8 10 18 Colletidae Colletes compactus 5 0 5 Hylaeus affinis 0 1 1 Hylaeus affinis/modestus 53 27 80 Hylaeus fedorica 4 3 7 Hylaeus hyalinatus* 24 29 53 Hylaeus leptocephalus* 6 4 10 Hylaeus mesillae 4 15 19 Hylaeus modestus 11 14 25 Hylaeus pictipes* 13 20 33 Hylaeus spp. 0 2 2 Halictidae Agapostemon sericeus 9 4 13 Agapostemon spp. 1 0 1 Agapostemon texanus 11 7 18 Agapostemon virescens 76 25 101 Table 7. List of bee species collected by year with bee vacuums organized by family. Respective abundance per year (2015 or 2016) is noted in addition to overall abundance across year. Exotic species are denoted with an * .

continued

Table 7 continued Family Species 2015 2016 Total Halictidae Augochlora pura 17 5 22 Augochlorella aurata 3 0 3 Halictus confusus 25 2 27 Halictus ligatus 12 17 29 Halictus rubicundus 4 1 5 Halictus spp. 0 6 6 Lasioglossum (Dialictus) bruneri 1 0 1 Lasioglossum (Dialictus) cattellae 2 0 2 Lasioglossum (Dialictus) ephialtum 12 3 15 Lasioglossum (Dialictus) hitchensi 1 0 1 Lasioglossum (Dialictus) illinoense 0 1 1 Lasioglossum (Dialictus) imitatum 22 9 31 Lasioglossum (Dialictus) laevissimum 3 0 3 Lasioglossum (Dialictus) lineatulum 1 1 2 Lasioglossum (Dialictus) lionotum 0 1 1 Lasioglossum (Dialictus) pilosum 10 5 15 Lasioglossum (Dialictus) smilacine 4 0 4 Lasioglossum (Dialictus) spp. 50 17 67 Lasioglossum (Dialictus) tegulare 1 0 1 Lasioglossum (Dialictus) versatum 1 0 1 Lasioglossum (Hemihalictus) pectorale 4 5 9 Lasioglossum (Hemihalictus) spp. 2 0 2 Lasioglossum coriaceum 3 0 3 Sphecodes spp. 2 0 2 Megachilidae Anthidium manicatum* 2 4 6 Anthidium oblongatum* 32 32 64 Coelioxys alternata 0 1 1 continued 60

Table 7 continued. Family Species 2015 2016 Total Megachilidae Heriades carinata 1 6 7 Megachile addenda 0 1 1 Megachile brevis 0 1 1 Megachile campanulae 1 5 6 Megachile centuncularis* 9 17 26 Megachile frigida 3 9 12 Megachile mendica 5 6 11 Megachile mucida 0 1 1 Megachile rotundata* 25 33 58 Megachile sculpturalis* 0 1 1 Megachile texana 0 2 2 Osmia caerulescens* 0 8 8 Osmia georgica 0 1 1 Osmia pumila 0 3 3 Pseudoanthidium nanum* 0 2 2 Stelis louisae 0 1 1

Objective b) determine important floral resources

Floral resource use: Total Total Floral Floral Bee Floral Bee sites sites visitors Plant species visitors Richness visitors Richness in in all in 2015 in 2015 in 2016 in 2016 2015 2016 years Achillea 5 8/64 5 6 4/53 3 12/117 millefolium* Ageratina 1 10/18 6 0 0/0 0 10/18 altissima Alcea sp.* 0 0/0 0 1 10/22 2 10/22 Apocynum 1 6/6 5 1 0/4 0 6/10 cannabinum Arctium lappa* 0 0/0 0 1 5/6 2 5/6 Asclepias syriaca 3 12/55 4 6 20/54 6 32/109 Bidens frondosa 1 0/1 0 0 0/0 0 0/1 Blephilia ciliata 0 9/13 5 1 4/4 4 13/17 Calystegia 0 0/0 0 2 1/1 1 1/1 sepium(*?) Caprifoliaceae 0 0/0 0 1 2/3 1 2/3 Catalpa speciosa 0 0/0 0 1 0/0 0 0/0 Chamaecrista 0 0/0 0 1 0/0 0 0/0 fasciculata Cichorium 28 213/327 31 36 124/144 22 337/471 intybus* Cirsium arvense* 0 0/0 0 6 33/66 11 33/66 Cirsium spp. 2 26/100 13 0 0/0 0 26/100 Cirsium vulgare* 0 0/0 0 1 4/5 3 4/5 Convolvulus 4 18/60 10 5 11/70 8 29/130 arvensis* Conyza 8 16/35 8 1 0/0 0 16/35 Canadensis* Coreopsis 0 0/0 0 4 9/17 5 9/17 lanceolata Daucus carota* 20 120/409 17 24 115/278 16 235/687 Erigeron annuus 5 7/20 1 18 17/68 9 24/88 Galinsoga 1 0/0 0 0 0/0 0 0/0 quadriradiata* Glechoma 0 0/0 0 1 2/2 1 2/2 hederacea* Table 8. List of plant species that had at least one collected floral visitor across all sites. There were 40 sites in 2015 and 39 sites in 2016 with most plant species being only found at a few sites. Also includes a list of all floral visitors collected on the flower structure including wasps, butterflies, and any other arthropod. Abundances are listed as (bees/all arthropods) within each abundance column to give an idea of relative proportion of visits by bees versus all arthropod visits. Bee species richness is recorded by year. * denotes an exotic species Continued 62

Table 8 continued Total Total Floral Floral Bee Floral Bee sites sites visitors Plant species visitors Richness visitors Richness in in all in 2015 in 2015 in 2016 in 2016 2015 2016 years Hibiscus 2 4/5 3 1 1/1 1 5/6 moscheutos Hypochaeris 0 0/0 0 2 3/5 2 3/5 radicata* Ipomoea sp. 1 1/1 1 0 0/0 0 1/1 Lactuca serriola* 3 8/9 4 0 0/0 0 8/9 Lathyrus 2 5/23 3 4 14/20 7 19/43 latifolius* Leucanthemum 0 0/0 0 1 2/3 2 2/3 vulgare* Lilium 0 0/0 0 1 0/0 0 0/0 lancifolium* Lobularia 2 0/3 0 0 0/0 0 0/3 maritima* Lotus 11 50/67 6 17 47/55 9 97/122 corniculatus* Malva neglecta 1 16/21 5 0 0/0 0 16/21 Medicago 15 6/40 3 14 0/8 0 6/48 lupulina* Melilotus albus* 1 5/7 3 7 53/61 12 58/68 Melilotus 0 0/0 0 8 26/33 11 26/33 officinalis* Monarda 0 0/0 0 1 0/0 0 0/0 fistulosa Monarda 0 0/0 0 1 0/0 0 0/0 punctata Oenothera 1 1/1 1 0 0/0 0 1/1 biennis Oxalis stricta 3 5/7 2 0 0/0 0 5/7 Penstemon 0 0/0 0 1 0/2 0 0/2 digitalis Phlox paniculata 0 0/0 0 1 0/1 0 0/1 Phytolacca 1 6/9 1 0 0/0 0 6/9 americana Plantago 34 47/120 13 35 32/91 10 79/211 lanceolata* Plantago major* 2 0/3 0 0 0/0 0 0/3 Polygonum 3 2/8 1 0 0/0 0 2/8 cespitosum* Polygonum 1 2/7 1 0 0/0 0 2/7 virginianum Prunella vulgaris 2 4/5 2 2 0/0 0 4/5 Ratibida pinnata 0 0/0 0 10 25/35 9 25/35

63 Continued

Table 8 continued. Total Total Floral Floral Bee Floral Bee sites sites visitors Plant species visitors Richness visitors Richness in in all in 2015 in 2015 in 2016 in 2016 2015 2016 years Rudbeckia hirta 1 0/0 0 7 11/34 4 11/34 Rudbeckia 0 0/0 0 2 3/3 2 3/3 triloba Securigera 1 2/5 2 6 10/17 5 12/22 varia* Solanum 1 1/1 1 1 3/5 1 4/6 carolinense Solanum 0 0/0 0 1 0/0 0 0/0 dulcamara* Solidago spp. 3 5/29 2 0 0/0 0 5/29 Sonchus spp. 6 6/18 4 3 0/1 0 6/19 Symphyotrichum 1 0/2 0 0 0/0 0 0/2 novae-angliae Symphyotrichum 0 25/48 7 0 0/0 0 25/48 pilosum Symphyotrichum 19 39/56 6 10 5/10 3 44/66 spp. Thlaspi arvense* 3 3/26 3 0 0/0 0 3/26 Tradescantia 0 0/0 0 1 0/0 0 0/0 ohiensis Tragopogon 0 0/0 0 1 0/0 0 0/0 dubius* Trifolium 1 4/5 3 2 8/10 4 12/15 hybridum* Trifolium 37 254/459 15 37 131/191 15 385/650 pratense* Trifolium 19 15/33 9 32 51/78 15 66/111 repens* Verbena hastata 0 0/0 0 1 4/4 3 4/4

Table 8 illustrates that several plant species are only found at a few sites, but there are a few plant species that are able to grow in at least a quarter of sites (i.e. Cichorium intybus, Daucus carota, Erigeron annuus, Lotus

corniculatus, Medicago lupulina, Plantago lanceolata, Trifolium pratense, and

Trifolium repens). Moreover, some plant species are visited by predominantly other arthropod floral visitors (Achillea millefolium, Asclepias syriaca,

Convolvulus arvensis, Medicago lupulina)(Table 8 and Figure 13) versus plant species being utilized predominantly by bees (Cichorium intybus, Lotus corniculatus, and Melilotus albus) (Table 8 and Figure 14). A few “weedy” species were arthropod hotspots with several hundred floral visitors collected across the two years (Cichorium intybus, Daucus carota, Plantago lanceolata, and Trifolium pretense) which might be partly explained by their abundance at so many sites (Figure 13). If accounting for the number of sites the plant species were found (but not abundance within sites), the following plant species were particularly attractive to arthropod visitors: Achillea millefolium, Ageratina altissima, Alcea sp., Asclepias syriaca, Blephilia ciliata,

Cichorium intybus, Cirsium spp., Convolvulus arvensis, Daucus carota, Lathyrus latifolius, Malva neglecta, and Trifolium pratense (Table 8, Figure 15, Figure

16). Of these plant species, the following attracted more than 10 bees per site in at least one year: Ageratina altissima, Alcea sp., Cirsium spp., and Malva neglecta (Figure 17 and Figure 18). Several plant species were important for supporting more than 10 species of bees in at least one of the years:

Cichorium intybus, Cirsium arvense, Convolvulus arvensis, Daucus carota,

Melilotus albus, Melilotus officinalis, Plantago lanceolata, Trifolium pretense, and Trifolium repens (Figure 19).

Cirsium spp. Asclepias syriaca Trifolium repens Achillea millefolium Lotus corniculatus Convolvulus arvensis Plantago lanceolata Cichorium intybus Trifolium pratense Daucus carota

0 100 200 300 400 500 600 700 800

Floral visitors in 2015 Floral visitors in 2016

Figure 13. Top 10 floral resources with the highest abundance of all floral visitors collected via bee vacuums in 2015 and 2016.

Asclepias syriaca Cirsium arvense Symphyotrichum spp. Melilotus albus Trifolium repens Plantago lanceolata Lotus corniculatus Daucus carota Cichorium intybus Trifolium pratense

0 50 100 150 200 250 300 350 400 450

Bee vistors in 2015 Bee Visitors in 2016

Figure 14. Top 10 floral resources with the highest abundance of bee visitors (Apoidea) collected via bee vacuums in 2015 and 2016.

Floral Visitation: 2015

Lathyrus latifolius Cichorium intybus Trifolium pratense Achillea millefolium Convolvulus arvensis Ageratina altissima Asclepias syriaca Daucus carota Malva neglecta Cirsium spp.

0 10 20 30 40 50 60 Abundance

Figure 15. Top 10 floral species in 2015 with highest abundance when accounting for the number of sites the plants were recorded (floral visitor abundance/total number of sites plant found).

Floral visitation: 2016

Cirsium vulgare Trifolium pratense Arctium lappa Melilotus albus Achillea millefolium Asclepias syriaca Cirsium arvense Daucus carota Convolvulus arvensis Alcea sp.

0 5 10 15 20 25 Abundance

Figure 16. Top 10 floral species in 2016 with highest abundance when accounting for the number of sites the plants were recorded (floral visitor abundance/total number of sites plant found).

Bee Visitation: 2015

Lotus corniculatus Melilotus albus Apocynum cannabinum Daucus carota Phytolacca americana Trifolium pratense Cichorium intybus Ageratina altissima Cirsium spp. Malva neglecta

0 2 4 6 8 10 12 14 16 18 Bee Abundance

Figure 17. Top 10 floral resources for bees in 2015 illustrating bee abundance when accounting for the number of sites the plants were recorded (bee abundance/total number of sites plant found).

Bee Visitation: 2016

Trifolium pratense Trifolium hybridum Verbena hastata Blephilia ciliata Cirsium vulgare Daucus carota Arctium lappa Cirsium arvense Melilotus albus Alcea sp.

0 2 4 6 8 10 12 Bee Abundance

Figure 18. Top 10 floral resources for bees in 2016 illustrating bee abundance when accounting for the number of sites the plants were recorded (bee abundance/total number of sites plant found).

Melilotus officinalis

Cirsium arvense

Melilotus albus

Trifolium repens

Convolvulus arvensis

Plantago lanceolata

Cirsium spp.

Trifolium pratense

Daucus carota

Cichorium intybus

0 5 10 15 20 25 30 35

Bee Richness in 2016 Bee Richness in 2015

Figure 19. Floral resources that supported the highest richness of bees by year. Dark grey and light grey bars illustrate species richness in 2015 and 2016 respectively.

Objective c) determine influence of floral plantings and habitat management on bee abundance

Figure 20. Bee abundance per sampling effort per site by habitat type (Vacant lots, Successional Lots, Low Diversity Prairie mix, High Diversity Prairie mix, and Flowering Lawn Mix) in 2015. Significant differences noted by asterisk.

Figure 21. Bee abundance per sampling effort per site by habitat type (Vacant lots, Successional Lots, Low Diversity Prairie mix, High Diversity Prairie mix, and Flowering Lawn Mix) in 2016. Significant differences noted by asterisk.

A total of 961 bees were collected in 2015 and 791 bees in 2016 across all sites. There is no significant difference in bee observations per habitat type when accounting for sampling effort per site in 2015 (F4/35=1.55, p=0.2086; Figure 20) or 2016 (F4/34=1.65, p=0.185; Figure 21).

Objective d) Native bee versus Exotic bee Networks

2015 Native Exotic Apis mellifera Cichorium intybus 199 9 5 Trifolium pratense 201 7 46 Plantago lanceolata 37 0 10 Daucus carota 81 35 4 Lotus corniculatus 3 47 0 Total 521 98 65 Table 9. Network matrix for 2015 summed across all sites in Cleveland. Only plants with representatives at more than 25% of sites were included. Plants with fewer than 20 arthropod observations were excluded from the analysis. Taxa are divided into native and exotic species keeping honey bees separate.

2016 Native Exotic Apis mellifera Trifolium repens 23 11 17 Lotus corniculatus 4 43 0 Trifolium pratense 52 26 53 Plantago lanceolata 13 2 17 Cichorium intybus 103 11 10 Daucus carota 72 33 10 Ratibida pinnata 25 0 0 Total 292 126 107 Table 10. Network matrix for 2016 summed across all sites in Cleveland. Only plants with representatives at more than 25% of sites included. Plants with fewer than 20 arthropod observations were excluded from the analysis. Taxa are divided by native and exotic species keeping honey bees separate.

Figure 22. Visual network web for 2015 (left) and 2016 (right) summed across all sites in Cleveland. Only plants with representatives at more than 25% of sites included. Plants with fewer than 20 arthropod observations were excluded from the analysis. Taxa are divided by native and exotic species keeping honey bees separate.

In 2015, there were only five common plant species found at least a quarter of all sites: Cichorium intybus, Trifolium pratense, Plantago lanceolata,

Daucus carota, and Lotus corniculatus (Table 9). In 2016, there were two additional species compared to 2015: Trifolium repens and Ratabida pinnata

(Table 10).

The pollinator network illustrates common floral resource by native and exotic bees (Figure 2232). Cichorium intybus (2015 and 2016) and

Ratibida pinnata (2016 only) are both visited predominantly by native bee species (Figure 22). Lotus corniculatus is consistently visited by predominantly exotic species in both 2015 and 2016 (Figure 22). The remaining plant species are visited by a mix of native and exotic species of bees (T. repens, T. pratense, Daucus carota, and P. lanceolata) (Figure 22).

Plant species level analyses: (the analyses comparing plants and their interactions)

Proportional 2015 PDI generality Cichorium 0.96* 0.65* intybus Trifolium 0.87 0.89 pratense Plantago 0.86 0.83 lanceolata Daucus 0.76 1.03 carota Lotus 0.97 0.62 corniculatus Table 11. Common plant species level outputs for 2015 showing Paired Difference Index, and proportional generality. Values significantly different from null models are indicated with *. 74

Proportional 2016 PDI generality Trifolium 0.39 1.07 repens Lotus 0.95* 0.50* corniculatus Trifolium 0.26* 1.06 pratense Plantago 0.56 0.89 lanceolata Cichorium 0.90* 0.66 intybus Daucus 0.70 0.88 carota Ratibida 1.00 0.37 pinnata Table 12. Common plant species level outputs for 2016 showing Paired Difference Index, and proportional generality. Values significantly different from null models are indicated with *.

Paired Difference Index (PDI): This index implies species generalism or specialization on 0-1 scale respectively. For 2015, only Cichorium intybus had a value significantly different from the null models at a score of 0.96

(Table 11). This implies specialization by one group, in this case predominantly natives. For 2016, Cichorium intybus scored 0.90, again implying specialization by native bee species (Table 12). For 2016, Lotus corniculatus scored 0.95 (Table 12) implying that one bee group is specialized on it, which is non-Apis exotic species. For 2016, T. pretense scored 0.26 implying generalism and that all three groups of bees visited it

(Table 12).

Proportional generality: This index quantitatively measures proportional resource use (utilized resources versus total potential resources). For 2015, only Cichorium intybus had a score significantly

different from the null models at 0.65 (Table 11). For 2016, only L. corniculatus is significant with a score of 0.496 (Table 12).

Discussion

I have documented the family level richness of floral visitors in inner city Cleveland. Although some public officials view these inner-city areas as dead zones with few resources, I was able to collect and identify 71 families,

27+ genera, and 71+ species of taxa across vacant land in Cleveland. These vacant parcels can serve as important biodiversity hotspots in an otherwise concrete cityscape. Urban areas as biological refuges have become increasingly reported in the literature as more focus returns to ecology of city land management (Tommasi et al. 2004, Matteson et al. 2008,

Lowenstein et al. 2014, Baldock et al. 2015, Senapathi and Carvalheiro 2015,

Sirohi et al. 2015). For example, a biodiversity study in Los Angeles found 12 new species of flies (Hartop et al. 2015), whereas bee diversity surveys throughout Chicago (Lowenstein et al. 2014), New York City (Matteson et al.

2008), and elsewhere are reporting species able to persist in what was traditionally considered unfavorable environments.

This survey documented several key floral resources for urban arthropods. These plant species supported high arthropod abundances, bee abundances, or bee richness. Many homeowners focus their efforts on floral resources with certain aesthetics, however, I found that several plant species

readily establish and proliferate in urban areas and are being used by a variety of arthropods. A prime example is Plantago lanceolata, an inconspicuous plant without colorful petals to attract visitors, yet several bee and fly species were collected from it. P. lanceolata is traditionally thought to be wind pollinated, yet has been noted in other literature to have bees and hoverflies foraging on it (Clifford 1962, Cavers and Bassett 1980). Similarly,

Cichorium intybus is disliked by homeowners for the tall and scraggly vegetation structure, yet it supports the highest richness of bee species and is readily found in inner city habitats.

Although I sampled at habitats seeded with a variety of native plants, few of those flowered during the study period. This is partly due to the plants growth habits; prairie plants are perennials that take several years to fully establish before they start blooming in higher abundances. Thus, I cannot say the potential visitors to these floral resources as they have yet to fully establish. The flowering lawn sites initially flowered well in June of 2015, but later died off due to a combination of weather (both extreme wet and dry periods) and out competition by other plant species. Ratibida pinnata was the hardiest of the planted resources and established well in comparison of most of the other plant species, but did not rank higher than the available exotic plant species.

At least for the first two years of the study, the treatment type was not an important factor in bee abundance when accounting for effort per site.

This could partly be due to slow habitat establishment as perennial plants take several years to flower in high abundances.

In both 2015 and 2016, Cichorium intybus was mainly utilized by native species of bees, whereas the other common floral species were visited by a mix of native and exotic species of bees. Trifolum pratense, Daucus carota, and Plantago lanceolata were visited by a variety of bees, though there did not seem to be a preference based on native or exotic categorization. Ratabida pinnata flowered in enough abundance during the second year of the study to compare the preference of natives versus exotics; it was preferred by native species. Only Lotus corniculatus seemed to be preferred by exotic species such as Anthidium oblongatum, Megachile centuncularis, Megachile rotundata, and Osmia caerulescens.

Recommendations to the City of Cleveland and growers

Ideally, if someone is trying to support pollinators, they will also choose to cultivate native plants as an additional conservation tool of preserving native flora. However, this research shows that several “weedy” species of plants are regularly utilized by a variety of bee species in inner-city

Cleveland. Determining whether the management goal is to support honey bees (Apis mellifera), other exotic bee species, or native bees will help 78

growers and land managers decide whether to manage their readily available floral resources. Exotic species seem to prefer Lotus corniculatus whereas several native bees appear to prefer Cichorium intybus, both of which are abundant in urban vacant lots but considered nuisance plants to homeowners. However, no single species of plant supports all available species of bees. Instead, a diversity of floral resources are needed to support more pollinators.

Future research:

Ideally, one would try to compare the impact of habitat management on the foraging preferences and structure of the pollinator community.

However, the above data simply does not have enough pollinator observations per site to do a thorough analysis of community wide network metrics by site. Baldock and colleagues (2015) collected 7,500 specimens from 36 sites. They made networks for each site to compare 3 habitat types:

Agricultural, woodland, and urban. This averaged around 210 specimens per site. They were able to make networks by site and then statistically compare each of the network outputs to see how the community changed within each of the three habitat groupings. I have ~200 bee specimens per habitat type and many sites with fewer than 20 specimens total, so I cannot make site level networks and I therefore cannot statistically compare habitat level networks. However, if someone is to repeat this study and spend more time

collecting specimens in the field, they might be able to properly address this concern.

Moreover, another additional part of this research could be pollen analysis of the specimens collected on flowers. Pollen networks could be incorporated to the other networks to get a better understanding of the overall community. All of the specimens with visible pollen loads in 2015 and

2016 had half of their pollen provisions removed and stored in a freezer for identification. With the advent of better molecular techniques this can be completed somewhat quickly, though molecular methods for pollen meta- barcoding are still being modified and perfected. Alternatively, the pollen can be identified visually by staining with basic fuchsin jelly and slide mounted. A pollen library of all floral resources at each of the sites is available, though this would be a laborious process.

Chapter 3: Cleveland bee diversity and new invasive species

Pollinators are key for global food security by supporting the pollination of ¾ of the worlds food crops (Klein et al. 2007). The plight of pollinators is a popular topic for the media. However, the issue is often misrepresented in an attempt to simplify the issue for public audiences. Bees in particular have been shown to be undergoing major community changes worldwide with many studies from Europe (Grixti et al. 2009, Bommarco et al. 2012, Scheper et al. 2014) , and an increasing body of literature from

North America (Grixti et al. 2009, Cameron et al. 2011, Burkle et al. 2013).

Pollinators are imperiled due to land use change and habitat loss

(Hendrickx et al. 2007, Goulson et al. 2008, Brown and Paxton 2009), pesticides (Gill et al. 2012, Goulson et al. 2015), emerging pathogens and disease (Otterstatter and Thomson 2008), interspecies competition

(Lindström et al. 2016), and a combination of all these factors (Potts et al.

2010). However, a major part of understanding the challenges faced by pollinators is to first understand the current population distribution.

Pollinators can include anything that transfers pollen from one flower to another. This can include bees, flies, beetles, birds, and even bats.

However, bees are often considered the most important or most effective pollinators (with several notable exceptions: see Cacao (Hernández 1965,

Winder and Silva 1972), the flowering vine Mucuna macrocarpa pollinated mainly by squirrels (Kobayashi et al. 2016), and this review on fly pollination

(Larson and Kevan 2001)).

Bees are grouped broadly in the Superfamily Apoidea (Anthophila).

There are six families of bees in the United States: Andrendiae, Apidae,

Colletidae, Halictidae, Megachilidae, and Melittidae. Together, these six families consist of approximately 4,000 species across the United States

(Michener 2007). However, new species are still being identified in addition to newly invasive species increasing their range.

Bee biodiversity studies are scattered across the United States. There have been small, local bee biodiversity surveys in various habitats or ecological preserves in the US (Giles and Ascher 2006, Matteson and Ascher

2008, Ascher et al. 2014). Pennsylvania has had a concerted effort to understand their bee biodiversity, with a total of 371 species identified in

2010, but more species likely identified in recent years (Donovall and vanEngelsdorp 2010). Moreover, a recent thesis by Matthew McKinney in

West Virginia compiled a list of 301 species of bees in West Virginia while also noting that the state is still largely understudied due to lack of collecting effort (McKinney 2016).

Ohio has been relatively understudied, with few yearlong bee diversity surveys. There have been disparate projects across Ohio looking at various ecological (Goodell and McKinney 2010, McKinney and Goodell 2011,

Cusser and Goodell 2013) or agricultural questions (Phillips and Gardiner

2015), but few with the explicit focus of bee biodiversity surveys. To date, there have only been two formally published papers focusing solely on bee diversity in Ohio (Arduser 2010, Spring et al. 2017). The first formally published paper focusing on bee diversity in the Oak Openings – Kitty Todd

Nature Preserve in Northwestern Ohio (Arduser 2010). This study found 124 species of bees on the preserve, sampling whenever the author happened to be in the region (Arduser 2010). The second formally published paper on bee diversity was part of an undergraduate research project of the current author. A total of 2,756 bees were collected in Southeastern Ohio over the entire flight period (last frost to first frost) of native bees (Spring et al. 2017).

This study found a total of 130 species of bees at three sites in Washington

County, Ohio. Seven of these species were state records which were previously unreported for the state of Ohio. Moreover, this study yielded several stylopized bees and a single gynandromorphic Bombus bimaculatus, the first reported case in this species (Spring et al. 2015).

There are other collaborations through university researchers and natural areas also attempting to get a sense of the bee diversity at their particular preserves. The US Fish and Wildlife Survey completed a bee 83

diversity survey at Huffman Prairie on Wright Patterson Air Force Base in

2015, but to the author’s knowledge have not identified the specimens yet.

There is another collaboration between the Edge of Appalachia and Dr. Karen

Goodell, who is currently identifying the specimens from their unique preserve in southwestern Ohio.

The goal of this chapter is to compile a list of confirmed bee species records from Cleveland, Ohio to get a better understanding of the bee diversity in Northeastern Ohio. Any rare or unique specimens will also be noted.

Methods:

Two separate projects analyzing bee community response to habitat factors are compiled here. Rain Garden bees were collected with bee bowls in the Slavic Village Neighborhood of Cleveland, Ohio. Bee bowls were set once a month in June, July, and August of 2014-2016. Bee bowls specimens were stored in 70% ethanol, separated from bycatch, washed, blown dry, and pinned. Network bees were collected with bee vacuums lined with disposable socks. The network bees were collected from 40 sites of 5 habitat treatments across 8 neighborhoods in Cleveland, Ohio. Within each site, all abundant floral resources were monitored to collect any organism from the floral structure. Sampling took place once a month at each of the sites. In

2015, sampling occurred in July, August, and September. In 2016, vacuum 84

sampling occurred in June, July, and August. Specimens were stored in the disposable socks in a freezer and then pinned without washing. Specimens with visible pollen loads had half of their pollen removed for later analysis.

Bees were identified with Discoverlife.org for bee genera (Ascher and

Pickering 2017), recent revisions by Jason Gibbs for Lasioglossum (Gibbs

2011, Gibbs et al. 2012), and Bumble Bees of North America (Williams et al.

2014). Specimen identifications were initially compared to the verified reference collection from the Spring et al. (2017) publication which were preserved at the Museum of Biological Diversity in Columbus, Ohio.

Identifications were further verified by Sam Droege at the USGS Bee

Monitoring and Inventory Lab and voucher specimens deposited that the

Museum of Biological Diversity.

Species accumulation curves for the combined methods of bee bowls and bee vacuums were created with package vegan (v2.3-1, Oksanen et al.,

2017) in R (v3.2.2; R Core Team 2017). Samples were summed over the entire year and species complexes were removed from the analysis.

Results Vac Vac Bowl Bowl Bowl Native/ Family Genus Species 2015 2016 2014 2015 2016 Total Exotic? Authority Andrenidae Andrena alleghaniensis 0 1 0 0 0 1 N Viereck 1907 asteris 1 0 0 0 0 1 N Robertson 1891 commoda 0 0 0 2 9 11 N Smith 1879 vicina 0 1 0 0 1 2 N Smith 1853 wilkella 8 43 1 1 8 61 E (Kirby 1802) Calliopsis andreniformis 0 3 45 105 50 203 N Smith 1853 Apidae Anthophora terminalis 3 0 1 1 0 5 N Cresson 1869 Apis mellifera 99 147 6 10 4 266 E Linnaeus 1758 Bombus bimaculatus 7 16 0 2 0 25 N Cresson 1863 86 fervidus 86 13 2 16 2 119 N (Fabricius 1798) griseocollis 40 53 5 2 0 100 N (De Geer 1773) impatiens 130 18 2 10 7 167 N Cresson 1863 vagans 19 1 0 2 0 22 N Smith 1854 Ceratina calcarata 74 97 31 11 41 254 N Robertson 1900 strenua 1 0 0 0 0 1 N Smith 1879 Hoclopasites calliopsidis 0 0 6 7 0 13 N (Linsley 1943) Melissodes agilis 1 1 0 0 0 2 N Cresson 1878 bimaculatus 7 16 52 24 39 138 N (Lepeletier 1825) desponsus 0 0 2 2 1 5 N Smith 1854 subillatus 0 6 1 0 0 7 N LaBerge 1961 trinodis 0 0 0 2 0 2 N Robertson 1901 Table 13. Compiled list of bee species collected from Cleveland with columns denoting sampling method and year (2014-2016). A separate column denotes the species status as native or exotic and their naming authority. Continued

Table 13 continued. Vac Vac Bowl Bowl Bowl Native/ Family Genus Species 2015 2016 2014 2015 2016 Total Exotic? Authority Apidae Nomada articulata 0 0 0 1 7 8 N Smith 1854 Bidentate Group 0 0 0 0 2 2 pygmaea 0 1 0 0 1 2 N Cresson 1863 Peponapis pruinosa 2 0 8 6 5 21 E* Say 1837 Triepeolus lunatus 0 6 2 0 0 8 N (Say 1824) Xylocopa virginica 8 10 0 0 1 19 N (Linnaeus 1771) Colletidae Colletes compactus 5 0 0 0 0 5 N Cresson 1868 Hylaeus affinis 0 1 0 0 0 1 N (Smith 1853) affinis/modestus 53 27 8 12 18 118 fedorica 4 3 0 0 0 7 N (Cockerell 1909) hyalinatus 24 29 26 27 15 121 E Smith 1842

leptocephalus 6 4 3 0 2 15 E (Morawitz 1871)

87 mesillae 4 15 4 0 0 23 N (Cockerell 1896) modestus 11 14 7 3 2 37 N Say 1837 pictipes 13 20 1 2 5 41 E Nylander 1852 spp. 0 2 1 0 0 3 Halictidae Agapostemon sericeus 9 4 24 41 53 131 N (Forster 1771) spp. 1 0 0 0 0 1 texanus 11 7 14 16 29 77 N Cresson 1872 virescens 76 25 80 79 177 437 N (Fabricius 1775) Augochlora pura 17 5 14 3 5 44 N (Say 1837) Augochlorella aurata 3 0 1 12 14 30 N (Smith 1853) Smith 1853 Halictus confusus 25 2 94 65 28 214 N Continued 85

Table 13 continued. Vac Vac Bowl Bowl Bowl Native/ Family Genus Species 2015 2016 2014 2015 2016 Total Exotic? Authority Halictidae Halictus ligatus 12 17 52 56 80 217 N Say 1837 rubicundus 4 1 15 6 0 26 N (Christ 1791) spp. 0 6 17 13 15 51 Lasioglossum (Dialictus) apocyni 0 0 0 1 1 2 N (Mitchell 1960) bruneri 1 0 11 1 2 15 N (Crawford 1902) cattellae 2 0 4 1 4 11 N (Ellis 1913) coeruleum 0 0 3 0 2 5 N (Robertson 1893) cressonii 0 0 6 5 15 26 N (Robertson 1890) ephialtum 12 3 53 32 24 124 N Gibbs 2010 gotham 0 0 0 0 1 1 N Gibbs 2011 hitchensi 1 0 41 41 35 118 N Gibbs 2012 illinoense 0 1 0 9 15 25 N (Robertson 1892)

imitatum 22 9 156 89 80 356 N (Smith 1853) 88 laevissimum 3 0 1 1 1 6 N (Smith 1853) leucocomum 0 0 0 1 0 1 N (Lovell 1908)

lineatulum 1 1 2 4 2 10 N (Crawford 1906) lionotum 0 1 2 4 2 9 N (Sandhouse 1923) (Knerer and paradmirandum 0 0 0 1 1 2 N Atwood 1966) pilosum 10 5 51 57 40 163 N (Smith 1853) rozeni 0 0 0 0 1 1 N Gibbs 2011 smilacine 4 0 2 1 0 7 N (Robertson 1897) spp. 50 17 34 34 36 171 86 Continued

Table 13 continued Vac Vac Bowl Bowl Bowl Native/ Family Genus Species 2015 2016 2014 2015 2016 Total Exotic? Authority Lasioglossum Halictidae (Dialictus) subviridatum 0 0 4 0 3 7 N (Cockerell 1938) tegulare 1 0 24 10 13 48 N (Robertson 1890) trigeminum 0 0 0 0 1 1 N Gibbs 2011 versatum 1 0 1 2 3 7 N (Robertson 1902) weemsi 0 0 0 1 0 1 N (Mitchell 1960) zephyrum 0 0 2 3 4 9 N (Smith 1853) Lasioglossum (Hemihalictus) pectorale 4 5 34 15 16 74 N (Smith 1853) spp. 2 0 0 0 3 5 Lasioglossum (Evylaeus) cinctipes 0 0 2 0 0 2 N (Provancher 1888) Lasioglossum coriaceum 3 0 3 4 21 31 N (Smith 1853) leucozonium 0 0 3 0 3 6 E (Schrank 1781) Sphecodes spp. 2 0 4 4 2 12 Megachilidae Anthidium manicatum 2 4 0 1 2 9 E (Linnaeus 1758)

89 oblongatum 32 32 27 28 42 161 E (Illiger 1806) Chelostoma philidelphi 0 0 0 0 1 1 N (Robertson 1891) Coelioxys alternata 0 1 0 0 0 1 N Say 1837 spp. 0 0 0 0 1 1 Heriades carinata 1 6 0 0 1 8 N Cresson 1864 Hoplitis producta 0 0 0 3 1 4 N (Cresson 1864) Megachile addenda 0 1 0 0 0 1 N Cresson 1878 Spinola 1808 apicalis 0 0 0 0 1 1 E Continued 87

Table 13 continued Vac Vac Bowl Bowl Bowl Native/ Family Genus Species 2015 2016 2014 2015 2016 Total Exotic? Authority Megachilidae Megachile brevis 0 1 0 0 0 1 N Say 1837 campanulae 1 5 0 0 0 6 N (Robertson 1903) centuncularis 9 17 1 3 4 34 ? (Linnaeus 1758) frigida 3 9 0 0 2 14 N Smith 1853 mendica 5 6 0 6 1 18 N Cresson 1878 mucida 0 1 0 0 0 1 N Cresson 1878 pugnata 0 0 0 1 0 1 N Say 1837 rotundata 25 33 16 35 24 133 E (Fabricius 1787) sculpturalis 0 1 0 0 0 1 E Smith 1853 texana 0 2 0 0 1 3 N Cresson 1878 Osmia caerulescens 0 8 4 7 3 22 E (Linnaeus 1758) cordata 0 0 0 1 0 1 N Robertson 1902 georgica 0 1 0 0 0 1 N Cresson 1878 pumila 0 3 0 1 2 6 N Cresson 1864 Pseudoanthidium nanum 0 2 0 0 2 4 E (Mocsáry 1881) 90 Stelis lateralis 0 0 2 0 0 2 N Cresson 1864 louisae 0 1 0 0 0 1 N Cockerell 1911 Total Specimens 961 791 1018 946 1040 4756 Total Species 51 59 52 60 64 96

A total of 29 bee genera in 96 species were collected from 4,756 specimens across Cleveland, Ohio (Table 13). Of these, 71 species were collected from bee vacuums and 81 were collected from bee bowls (Table

13). A total of 40 species had fewer than 5 representatives. Of these species,

33 had fewer than 3 representatives and 22 species only had a single representative (Table 13). Of all bees, 14 species were exotic (n=896, 20% of abundance) and 82 were native (n=3,497, 80%). Notably, these are the first reports of both Psuedoanthidium nanum and Hylaeus pictipes in Ohio.

Species accumulation curves

Species Chao Chao Jack1 Jack1 Jack2 Boot Boot n SE SE SE Overall 96 109.89 7.45 116 10.95 122.9 105.73 6.55 5 Table 14. Species accumulation curve for combined Cleveland bee species data with Chao, Jacknife1, Jacknife2, and Bootstrap estimates.

Figure 23. Species accumulation curve for compiled bee species richness in Cleveland with Chao, Jacknife1, Jacknife2, and Boostrap estimates.

After removing species complexes, 4,393 bees were used to create the species accumulation curves. Species accumulation curves were created using chao, jackknife, and bootstrap (Table 14). The estimated species richness that could be collected via the combined methods of bee bowls and bee vacuums if sampling period is restricted from June to September is 108

(Chao), 116 (Jackknife1), 122 (Jackknife2), and 105 (Bootstrap) (Figure 23).

Discussion

These 96 bee species are not a full representation of the species present in Cleveland, Ohio. Instead, it is a starting point to understand the populations during a truncated portion of the year in inner city habitats.

There are still many more species to be documented by sampling earlier and later in the flying season and by sampling in a wider variety of habitats.

Despite the public perception that honey bees (Apis mellifera) dominate the landscape, I found that they do not make up a majority of bees collected in urban Cleveland. There has been a recent push by the public to increase the number of beekeepers, but the areas in inner city Cleveland have not been overwhelmed with hundreds of hives of honey bees. This could be due to the cost of owning a hive with many start up kits averaging over $200, which is cost prohibitive for most inner city residents. However, this lack of honey bee hives might have actually benefitted the other species of bees in inner city Cleveland. The negative impacts of honey bees on other bee species have long been argued (Paini 2004, Moritz et al. 2005), but are challenging to design conclusive studies since honey bees are ubiquitous in most landscapes and there are many confounding factors (Paini 2004, Paini and

Roberts 2005, Artz et al. 2011). However, recently a controlled study that involved honey bee density manipulation in Sweden has shown that high levels of honey bees depress the densities of wild insects (Lindström et al.

2016). Thus, the lack of honey bee hives managed by beekeepers in inner- city Cleveland might actually be benefiting the surprising diversity of native bees present. However, it is important to note the importance of honey bee colonies for agricultural food production, especially in monoculture systems.

Non-native species

Russo (2016) recently compiled a list of non-native bees and their impacts around the world. These non-native species can have several negative implications: 1) increased competition among bee species, 2) increased dispersal due to competition for food or nesting resources, 3) increased disease spread or introduction of novel parasites, 4) increased pollination rates of non-native and invasive plant species. However, these new invasive species can still benefit the natural community by potentially supporting higher pollination rates for native plant species and agricultural crops.

It is hypothesized that most non-native species were actually accidentally introduced into the United States (Russo 2016), though there are a few exceptions including the European honey bee, Apis mellifera. Accidental introduction via plant materials would be one potential route of transfer.

Interestingly, the distribution of invasive species that are stem or cavity nesters (69%) as opposed to ground nesters or exposed nests (26% and 5% respectively) (Russo 2016) would seem to support the idea that the 94

invasions started via infested plant material. The normal distribution of nesting types in bees is 70% ground nesters and 30% cavity nesters

(Michener 2007). Moreover, soils have strict regulations for importation, with most plant materials entering the country without soils, thus invasion of new cavity nesters is much more plausible.

Andrena wilkella Kirby is the only invasive species in the family

Andrenidae (Russo 2016). This species is thought to have been accidentally introduced in the early 20th century though it was a challenge to properly identify and verify at the time (Malloch 1918). Now the species can be found in various parts of Northeastern United States and Southern Canada and is the main species of Andrena identified on Bugguide.net.

Anthidium manicatum (L.) is a species of wool carder bee originally from the Eastern Hemisphere (Jaycox 1967). It first reported in New York in the 1960s (Jaycox 1967), but was not identified in Ohio until a specimen was reported in 1996 from Akron, Ohio (Miller et al. 2002). It has since spread across most of the United States (Gibbs and Sheffield 2009, Strange et al.

2011).

Anthidium oblongatum (Illiger) is a different species of wool carder bee that was accidentally introduced in the mid-1990s (Hoebeke et al. 1999).

Its native range includes Europe and the Near East, but can now be found in

Northeastern United States and parts of Southern Canada (Miller et al. 2002, 95

Romankova 2003, O’Brien et al. 2012). A. oblongatum was first reported in

Ohio in 1999/2000 during a survey looking for A. manicatum (Miller et al.

2002). Both A. manicatum and A. oblongatum are rather territorial species

(Wirtz et al. 1988) and have the potential to change pollinator interaction networks by guarding floral resources and chasing other species away.

Apis mellifera was intentionally introduced back in the early settlement of the United States. Although it is native to Europe, Apis mellifera can be found in most regions of the world, with a number of managed varieties adapted to local regions.

Hylaeus hyalinatus is a species native to Europe that was thought to have been accidentally introduced to the US in the early 1990s (Ascher

2001). It was first found in New York in 1997 (Ascher 2001) and has since been found in Chicago and westward (Tonietto and Ascher 2008).

Hylaeus leptocephalus is another species native to Europe that has an earlier introduction around the start of the 20th century (Snelling 1970). It is thought to potentially specialize on Meliotus (Snelling 1970), but I collected it from Meliotus spp., and Daucus carota, and Symphyotrichum pilosum.

Hylaeus pictipes is a new report for Ohio, with this study having the earliest confirmed species report in the United States in 2014, though there

are probable misidentified specimens collected by other researchers in

Cleveland (Jason Gibbs, pers. comm).

Lasioglossum leucozonium is a species of Lasioglossum that originates from Europe, but has been in the United States for so long that it was thought to be a native species (Giles and Ascher 2006).. Recent geographical and phylogenetic analyses have revealed that is actually a naturalized solitary species (Giles and Ascher 2006).

Megachile apicalis is a European species first reported in North

America in the 1930s, but it was not until 1982 when a sustainable population was reported from California (Cooper 1984).

Megachile centuncularis is currently a Holarctic species with little information about its original distribution or if has always had such a large geographic range (Ascher and Pickering 2017).

Megachile rotundata is a managed species of cavity nesting bee used for alfalfa seed production where it has tripled production (Pitts-Singer and

Cane 2011). Originally from the Eastern Hemisphere, this species is part of an ongoing research program at the United States Department of Agriculture to increase crop seed yields and returns of bees (Pitts-Singer and Cane

2011).

Megachile sculpturalis Smith, also known as the giant resin bee, is thought to have been accidentally introduced in the 1990s from Asia

(Mangum and Brooks 1997), first reported in Ohio in 1998 (Hinojosa-Díaz et al. 2005), and is now found across the United States (Parys et al. 2015). This species is a nest thief of our large carpenter bee, Xylocopa virginica (L.), as M. sculpturalis is unable to make its own cavities out of the hardwood that it prefers to nest (Mangum and Brooks 1997).

Osmia caerulescens is thought to be the first invasive species of Osmia in the United States, establishing sometime in the 1800s (Sheffield et al.

2011), but is native to Europe and parts of Africa (Rust 1974). Interestingly, this was the most abundant species of Osmia collected, but that could be due to an artifact of the sampling period; most Osmia are more active during the early flight season with all sampling for this research occurring from June onwards.

Peponapis pruinosa, also known as the squash bee, could be argued as non-native to Ohio. Indeed, this species is native to the southern United

States, and Mexico, but has undergone a major range expansion with the spread of agricultural practices across the United States (López-Uribe and

Cane 2016). It is now found regularly in regions where cucurbits are grown.

Pseudoanthidium nanum is a newly invasive species to the

Northeastern United States, first discovered in New Jersey and then 98

Maryland, with origins in Europe (Droege and Shapiro 2011). This species is also a State Record for Ohio and currently the farthest west the species has been reported (Sam Droege, Pers. Comm).

State records

The following are the first confirmed representatives by Sam Droege for the state of Ohio: Hylaeus pictipes (Exotic), H. fedorica, Pseudoanthidium nanum (Exotic), Megachile mucida, M. frigida, Coelioxys alternata, and

Lasioglossum lionotum (Sam Droege, Pers. Comm).

Conclusion:

Overall, this study adds to the understanding of current bee species richness in Ohio. Although the research took place in only a small portion of the active flight time, I was able to document several new and exotic species in Ohio. More sampling across a larger diversity of habitats and during the early spring and fall is likely to find several more species. Much more work is needed to have a robust understanding of the bee species richness in Ohio and to document bee species invasions.

References

Aizen, MA, and LD Harder. 2009. The global stock of domesticated honey bees is growing slower than agricultural demand for pollination. Current biology. 19(11): 915-918. Arduser, M. 2010. Bees (Hymenoptera: Apoidea) of the Kitty Todd Preserve, Lucas County, Ohio. The Great Lakes Entomologist. 43(1/4) 45-68. Artz, DR, CL Hsu, and BA Nault. 2011. Influence of honey bee, Apis mellifera, hives and field size on foraging activity of native bee species in pumpkin fields. Environmental entomology. 45(5): 1144-1158. Ascher, JS, S Kornbluth, and RG Goelet. 2014. Bees (Hymenoptera: Apoidea: Anthophila) of Gardiners Island, Suffolk County, New York. Northeastern Naturalist. 21(1): 47-71. Ascher, J. 2001. Hylaeus hyalinatus Smith, a European bee new to North America with notes of other adventive species (Hymenoptera: Apoidea). Proceedings of the Entomological Society of Washington. 103(1): 184–190. Ascher, J., and J. Pickering. 2017. Bee species guide (Hymenoptera: Apoidea: Anthophila). http://www.discoverlife.org/mp/20q?search=Apoidea Baldock, K., MA Goddard, DM Hicks, WE Kunin, N Mitschunas, LM OSgathorpe, SG Potts, KM Robertson, AV Scott, GN Stone, IP Vaughan, and J Memmot. 2015. Where is the UK’s pollinator biodiversity? The importance of urban areas for flower-visiting insects. Proceedings of the Royal Society B. 282(1803): 20142849. Barry, TN. 1998. The feeding value of chicory (Cichorium intybus) for ruminant livestock. The Journal of Agricultural Science. 131(3): 251- 257. Bartomeus, I, JS Ascher, J Gibbs, BN Danforth, SM Hedtke, R Winfree. 2013. Historical changes in northeastern US bee pollinators related to shared ecological traits. Proceedings of the National Academy of Sciences. 110(12): 4656-4660. Bischoff, TA, CJ Kelley, Y Karchesy, M Laurantos, P Nguyen-Dinh, and AG Arefi. 2004. Antimalarial activity of Lactucin and Lactucopicrin: sesquiterpene lactones isolated from Cichorium intybus L. Journal of Ethnopharmacology. 95(2): 455-457.

100

Bommarco, R., O. Lundin, H. G. Smith, and M. Rundlöf. 2012. Drastic historic shifts in bumble-bee community composition in Sweden. Proceedings of the Royal Society B. rspb20110647. Brown, M., and RJ Paxton. 2009. The conservation of bees: a global perspective. Apidologie. 40(3): 410-416. Burd, M. 1994. Bateman’s principle and plant reproduction: the role of pollen limitation in fruit and seed set. The Botanical Review. 60(1):83- 139. Burkle, LA, JC Marlin, and TM Knight. 2013. Plant-pollinator interactions over 120 years: loss of species, co-occurrence, and function. Science. 339(6127): 1611-1615. Calderone, NW. 2012. Insect pollinated crops, insect pollinators and US agriculture: trend analysis of aggregate data for the period 1992– 2009. PloS one. 7(5): e37235. Cameron, SA, JD Lozier, JP Strange, JB Koch, N Cordes, LF Solder, and TL Griswold. 2011. Patterns of widespread decline in North American bumble bees. Proceedings of the National Academy of Sciences. 108(2): 662-667. Cavers, PB, IJ Bassett, and CW Crompton. 1980. The Biology of Canadian Weeds. 47. Plantago lanceolata L. Canadian Journal of Plant Science 60(4): 1269-1282. Chang, W. 2014. extrafont: Tools for using fonts. R package version 0.17. https://CRAN.R-project.org/package=extrafont Cleveland Land lab. 2008. The Cleveland Land Lab: Experiments for a city in transition. In Cities Growing Smaller, eds. Steve Rugare and Terry Schwarz. pp 72-83. Clifford, HT. 1962. Insect pollination of Plantago lanceolata L. Nature. 193: 196. Cusser, S, and K Goodell. 2013. Diversity and distribution of floral resources influence the restoration of plant–pollinator networks on a reclaimed strip mine. Restoration Ecology. 21(6): 713-721. Donovall III, LR, and D vanEngelsdorp. 2010. A checklist of the bees (Hymenoptera: Apoidea) of Pennsylvania. Journal of the Kansas Entomological Society. 83(1):7-24. Dormann, C.F. 2011. How to be a specialist? Quantifying specialisation in pollination networks. Network Biology 1, 1 - 20. Droege, S. USGS Bee Monitoring and Inventory Lab. Personal Communication. February 8, 2017. Fiedler, AK, DA Landis, and SD Wratten. 2008. Maximizing ecosystem services from conservation biological control: the role of habitat management. Biological control. 45(2): 254-271. Fitzpatrick, Ú., TE Murray, RJ Paxton, J Breen, D Cotton, V Santorum, and MJ Brown. 2007. Rarity and decline in bumblebees–a test of

101

causes and correlates in the Irish fauna. Biological Conservation. 136(2): 185-194. Fox, J, and S. Weisberg. 2011. An {R} Companion to Applied Regression, Second Edition. Thousand Oaks CA: Sage. URL: http://socserv.socsci.mcmaster.ca/jfox/Books/Companion Frankie, G, R Thorp, J Hernandez, M Rizzardi, B Ertter, J Pawelek, S Witt, M Schindler, R Coville, and V Wojcik. 2009. Native bees are a rich natural resource in urban California gardens. California Agriculture. 63(3): 113-120. Gardiner, MM, CE Burkman, and SP Prajzner. 2013. The value of urban vacant land to support arthropod biodiversity and ecosystem services. Environmental entomology. 42(6): 1123-1136. Gardiner, MM, SP Prajzner, CE Burkman, S Albro, and PS Grewel. 2014. Vacant land conversion to community gardens: influences on generalist arthropod predators and biocontrol services in urban greenspaces. Urban Ecosystems. 17(1): 101-122. Gardiner, MM, DA Landis, C Gratton, N Schmidt, M O’Neal, E Mueller, J Chacon, GE Heimpel, and CD DiFonzo. 2009. Landscape composition influences patterns of native and exotic lady beetle abundance. Diversity and Distributions. 15(4):554-564. Garibaldi, LA, I Steffan-Dewenter, R Winfree MA Aizen, R Bommarco, SA Cunningham, C Kremen, LG Caravalheiro, LD Harder, O Afik, I Bartomeus, F Benjamin, V Boreux, D Cariveau, NP Chacoff, JH Dudenhoffer, BM Freitas, J Ghazoul, S Greenleaf, J Hipolito, A Holzchuh, B Howlett, R Isaacs, SK Javorek, CM Kennedy, KM Mrewenka, S Krishnan, Y Mandelik, MM Mayfield, R Motzke, T Munyuli, BA Nault, M Otieno, J Petersen, G Pisanty, SG Potts, R Rader, TH Ricketts, M Rundlof, CL Seymour, C Schuepp, H Szentgyorgyi, H Taki, T Tscharntke, CH Vergara, BF Viana, TH Wanger, C Westphal, N Williams, AM Klein. 2013. Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science. 339(6127): 1608-1611. Ghazoul, J. 2006. Floral diversity and the facilitation of pollination. Journal of ecology. 94(2): 295-304. Gibbs, J. 2011. Revision of the metallic Lasioglossum (Dialictus) of eastern North America (Hymenoptera: Halictidae: Halictini). Zootaxa. 3073:1- 216. Gibbs, J, L Packer, S Dumesh, and BN Danforth. 2012. Revision and reclassification of Lasioglossum (Evylaeus), L.(Hemihalictus) and L.(Sphecodogastra) in eastern North America (Hymenoptera: Apoidea: Halictidae). Zootaxa. 3672: 1-117. Gibbs, J, and CS Sheffield. 2009. Rapid range expansion of the Wool-Carder Bee, Anthidium manicatum (Linnaeus)(Hymenoptera: Megachilidae),

102

in north america. Journal of the Kansas Entomological Society. 82(1): 21-29. Giles, V, and JS Ascher. 2006. A survey of the bees of the Black Rock Forest preserve, New York (Hymenoptera: Apoidea). Journal of Hymenoptera Research. 15(2): 208-231. Gill, RJ, O Ramos-Rodriguez, and NE Raine. 2012. Combined pesticide exposure severely affects individual-and colony-level traits in bees. Nature. 491(7422): 105-108. Goodell, K, AM McKinney, and CH Lin. 2010. Pollen limitation and local habitat-dependent pollinator interactions in the invasive shrub Lonicera maackii. International journal of plant sciences. 171(1): 63- 72. Goulson, D, GC Lye, and B Darvill. 2008. Decline and conservation of bumble bees. Annual Review of Entomolology. 53: 191-208. Goulson, D, E Nicholls, C Botías, and EL Rotheray. 2015. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science. 347(6229): 1255957. Green, J. Department of Community Development. Personal Communication. July 7, 2016. Grixti, JC, LT Wong, SA Cameron, and C Favret. 2009. Decline of bumble bees (Bombus) in the North American Midwest. Biological conservation. 142(1): 75-84. Hall, DM, GR Camilo, RK Tonietto, J Ollerton, K Ahrne, M Arduser, JS Ascher, KC Baldock, JI Jackson, G Langellotto, D Lowenstein, ES Minor, SM Philpott, SG Potts, MH Spevak, GN Stone, and CG Threlfall. 2016. The city as a refuge for insect pollinators. Conservation Biology. 31(1): 24-29. Hartop, EA, BV Brown, and R. Disney. 2015. Opportunity in our ignorance: urban biodiversity study reveals 30 new species and one new Nearctic record for Megaselia (Diptera: Phoridae) in Los Angeles (California, USA). Zootaxa. 3941(4): 451-484. Hegland, SJ, and L Boeke. 2006. Relationships between the density and diversity of floral resources and flower visitor activity in a temperate grassland community. Ecological Entomology. 31(5): 532-538. Hendrickx, F., J. Maelfait, W. V. Wingerden, O. Schweiger, M. Speelamns, S. Aviron, I. Augenstein, R. Billeter, D. Bailey, R. Bukacek, F. Burel, T. Diekotter, J. Dirksen, F. Herzog, J. Liira, M. Roubalova, V. Vandomme, and R. Bugter. 2007. How landscape structure, land‐use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes. Journal of Applied Ecology. 44(2): 340–351 Hernández, B. 1965. Insect pollination of cacao (Theobroma cacao L.) in Costa Rica. University of Wisconsin-Madison Press. 334 p.

103

Hernandez, J. L., G. W. Frankie, and R. W. Thorp. 2009. Ecology of urban bees: a review of current knowledge and directions for future study. Cities and the Environment (CATE). 2(1): 3. Herrmann, DL, WD Shuster, and AS Garmestani. 2016. Vacant urban lot soils and their potential to support ecosystem services. Plant and Soil. 1-13. Hoebeke, ER, W. A. Jr, and GW Byers. 1999. Anthidium oblongatum (Illiger): an Old World bee (Hymenoptera: Megachilidae) new to North America, and new North American records for another adventive species, A. manicatum (L.). University of Kansas Natural Huistory Museum Special Publication 24: 21-24. Jaycox, ER. 1967. An adventive Anthidium in New York State (Hymenoptera: Megachilidae). Journal of the Kansas Entomological Society. 124-126. Johansson, M.E., C. Nilsson. 2002. Responses of riparian plants to flooding in free-flowing and regulated boreal rivers: an experimental study. Journal of Applied Ecology. 39(6): 971-986. Kearns, CA, and DM Oliveras. 2009. Environmental factors affecting bee diversity in urban and remote grassland plots in Boulder, Colorado. Journal of Insect Conservation. 13(6): 655-665. Klein, AM, BE Vaissiere, JH Cane, I Steffan-Dewenter, SA Cunningham, C Kremen, and T Tscharntke. 2007. Importance of pollinators in changing landscapes for world crops. Proceedings of the Royal Society B. 274(1608): 303-313. Kobayashi, S, T Denda, and CC Liao. 2016. Squirrel pollination of Mucuna macrocarpa (Fabaceae) in Taiwan. Journal of Mammology. 98(2): gyw189. Kosior, A, W Celary, P Olejniczak, J Fijal, W Król, W Solarz, and P Plonka. 2007. The decline of the bumble bees and cuckoo bees (Hymenoptera: Apidae: Bombini) of Western and Central Europe. Oryx. 41(1): 79-88. Larson, B., PG Kevan, and DW Inouye. 2001. Flies and flowers: taxonomic diversity of anthophiles and pollinators. The Canadian Entomolgist. 133(4): 439-465. Lindström, S., L. Herbertsson, M. Rundlöf, R. Bommarco, and H. Smith. 2016. Experimental evidence that honeybees depress wild insect densities in a flowering crop. Proc Biological Sci. 283(1843): 20161641. Losey, JE, and M Vaughan. 2006. The economic value of ecological services provided by insects. Bioscience. 56(4): 311-323. López-Uribe, MM, and JH Cane. 2016. Crop domestication facilitated rapid geographical expansion of a specialist pollinator, the squash bee Peponapis pruinosa. Proceedings of the Royal Society B. 283(1833): 20160443

104

Lowenstein, DM, KC Matteson, I Xiao, and AM Silva. 2014. Humans, bees, and pollination services in the city: the case of Chicago, IL (USA). Biodiversity and conservation. 23(11): 2857-2874. Malloch, J. 1918. Occurrence of a European Solitary Bee (Andrena wilkella Kirby) in the Eastern United States. Proc. Proceedings of the Biological Society of Washington. 31: 61–64. Mangum, WA, and RW Brooks. 1997. First records of Megachile (Callomegachile) sculpturalis Smith (Hymenoptera: Megachilidae) in the continental United States. Journal of the Kansas Entomological Society. 70(2):140-142. Matteson, KC, JS Ascher, and GA Langellotto. 2008. Bee richness and abundance in New York City urban gardens. Annals of the Entomological Society of America. 101(1): 140-150. McKinney, AM, and K Goodell. 2011. Plant–pollinator interactions between an invasive and native plant vary between sites with different flowering phenology. Plant Ecology. 212(6): 1025-1035. McKinney, M. 2016. Bee Natural History, Diversity, and Management in West Virginia. (Doctoral Dissertation) West Virginia University. McKinney, M.L. 2006. Urbanization as a major cause of biotic homogenization. Biological Conservation. 127(3): 247-260. Michener, C. D. 2007. Bees of the World, Second. ed. The Johns Hopkins University Press. Miller, SR, R Gaebel, and RJ Mitchell. 2002. Occurrence of two species of Old World bees, Anthidium manicatum and A. oblongatum (Apoidea: Megachilidae), in northern Ohio and southern Michigan. Great Lakes Entomologist. 35(1): 65-70. Miranda, G. F. G., A. D. Young, M. M. Locke, S. A. Marshall, J. H. Skevington, and F. C. Thompson. 2013. Key to the Genera of Nearctic Syrphidae. Canadian Journal of Arthropod Identification. 23: 1-351. Moritz, R., S. Härtel, and P. Neumann. 2005. Global invasions of the western honeybee (Apis mellifera) and the consequences for biodiversity. Ecoscience. 20: 289–301. Oksanen, J., F. Guillaume Blanchet, Michael Friendly, Roeland Kindt, Pierre Legendre, Dan McGlinn, Peter R. Minchin, R. B. O'Hara, Gavin L. Simpson, Peter Solymos, M. Henry H. Stevens, Eduard Szoecs and Helene Wagner. 2017. vegan: Community Ecology Package. R package version 2.4-2. https://CRAN.R- project.org/package=vegan Olesen, J.M., J. Bascopmpte, Y.L. Dupont, H. Elberling, C. Rasmussen, and P. Jordano. 2010. Missing and forbidden links in mutualistic networks. Proceedings of the Royal Society B. doi:10.1098/rspb.2010.1371

105

Otterstatter, MC, and JD Thomson. 2008. Does pathogen spillover from commercially reared bumble bees threaten wild pollinators? PLoS One. 3(7): e2771. Paini, DR. 2004. Impact of the introduced honey bee (Apis mellifera) (Hymenoptera: Apidae) on native bees: a review. Austral ecology. 29(4): 399-407. Paini, DR, and JD Roberts. 2005. Commercial honey bees (Apis mellifera) reduce the fecundity of an Australian native bee (Hylaeus alcyoneus). Biological conservation. 123(1): 103-112. Parys, KA, AD Tripodi, and BJ Sampson. 2015. The Giant Resin Bee, Megachile sculpturalis Smith: New Distributional Records for the Mid- and Gulf-south USA. Biodiversity data journal. 3: e6733. Pauchard, A., M. Aguayo, E. Pena, R. Urritia. 2006. Multiple effects of urbanization on the biodiversity of developing countries: the case of a fast growing metropolitan area (Concepcion, Chile). Biological Conservation. 127(3): 272-281. Phillips, BW, and MM Gardiner. 2015. Use of video surveillance to measure the influences of habitat management and landscape composition on pollinator visitation and pollen deposition in pumpkin (Curcurbita pepo) acroecosystems. PeerJ. 3. e1342. Porcher, E, and R Lande. 2005. The evolution of self‐fertilization and inbreeding depression under pollen discounting and pollen limitation. Journal of evolutionary biology. 18(3): 497-508. Potts, SG, JC Biesmeijer, C Kremen, and P Neumann. 2010. Global pollinator declines: trends, impacts and drivers. Trends in ecology & evolution. 25(6): 345-353. Potts, SG, B Vulliamy, A Dafni, G Ne’eman, and P Willmer. 2003. Linking bees and flowers: how do floral communities structure pollinator communities? Ecology. 84(10): 2628-2642. Pushparaj, PN, HK Low, J Manikandan, B. Tan, and CH Tan. 2007. Anti- diabetic effects of Cichorium intybus in streptozotocin-induced diabetic rats. Journal of Ethnopharmacology. 111(2): 430-434. R Core Team. 2017. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Rader, R., W. Edwards, D. A. Westcott, S. A. Cunningham, and B. G. Howlett. 2011. Pollen transport differs among bees and flies in a human modified landscape. Diversity and Distributions. 17(3): 519– 529 Russo, L. 2016. Positive and negative impacts of non-native bee species around the world. Insects. 7(4): 69. Scheper, J, M Reemer, R van Kats, WA Ozinga, GT van der Linden, JH Schaminee, H Siepel, and D Kleijn. 2014. Museum specimens reveal loss of pollen host plants as key factor driving wild bee decline in The 106

Netherlands. Proceedings of the National Academy of Sciences. 111(49): 17552-17557. Senapathi, D., L. Carvalheiro, J. Biesmeijer, C.-A. Dodson, R. Evans, M. McKerchar, R. D. Morton, E. Moss, S. P. M. Roberts, W. Kunin, and S. Potts. 2015. The impact of over 80 years of land cover changes on bee and wasp pollinator communities in England. Proceedings of the Royal Society of London B: Biological Sciences. 282(1806): 20150294. Shuster, WD, S Dadio, P Drohan, R Losco, and J Shaffer. 2014. Residential demolition and its impact on vacant lot hydrology: Implications for the management of stormwater and sewer system overflows. Landscape and Urban Planning. 125: 48-56. Sirohi, MH, J Jackson, M Edwards, and J Ollerton. 2015. Diversity and abundance of solitary and primitively eusocial bees in an urban centre: a case study from Northampton (England). Journal of insect conservation. 19(3): 487-500. Slowikowski, K. 2016. ggrepel: Repulsive Text and Label Geoms for 'ggplot2'. R package version 0.6.5. https://CRAN.R- project.org/package=ggrepel Spring, M., K. Lustofin, and M. M. Gardiner. 2015. Occurrence of a Gynandromorphic Bombus bimaculatus (Hymenoptera: Apidae) in Southeastern Ohio. The Great Lakes Entomologist. 48(3-4): 150-158. Spring, M. R., K. S. Lustofin, C.-H. Lin, M. M. Gardiner, and D. McShaffrey. 2017. Quantifying bee diversity and resource use in the Appalachian foothills near Marietta, Ohio. Ohio Biological Notes Series. 7: 1–13. Steffan-Dewenter, I, AM Klein, and V Gaebele. 2006. Bee diversity and plant-pollinator interactions in fragmented landscapes. Specialization and Generalization in Plant-Pollinator Interactions. pp 387-410. Steffan‐Dewenter, I. 2003. Importance of habitat area and landscape context for species richness of bees and wasps in fragmented orchard meadows. Conservation biology. 17(4): 1036-1044. Strange, JP, JB Koch, VH Gonzalez, and L Nemelka. 2011. Global invasion by Anthidium manicatum (Linnaeus)(Hymenoptera: Megachilidae): assessing potential distribution in North America and beyond. Biological Invasions. 13(9): 2115. Tommasi, D, A Miro, HA Higo, and ML Winston. 2004. Bee diversity and abundance in an urban setting. Canadian Entomologist. 136(6): 851- 869. Tonietto, R, J Fant, J Ascher, K Ellis, and D Larkin. 2011. A comparison of bee communities of Chicago green roofs, parks and prairies. Landscape and Urban Planning. 103(1): 102-108. Tonietto, RK, and JS Ascher. 2008. Occurrence of the Old World Bee Species Hylaeus hyalinatus, Anthidium manicatum, A. oblongatum, and Megachile sculpturalis, and the Native Species Coelioxys banksi, Lasioglossum michiganense, and L. zophops in Illinois (Hymenoptera: 107

Apoidea: Colletidae, Halictidae, Megachilidae). The Great Lakes Entomologist. 41(1-2): 200-203. Uno, S, J Cotton, and SM Philpott. 2010. Diversity, abundance, and species composition of ants in urban green spaces. Urban Ecosystems. 13(4): 425-441. Wickham, H. 2009. ggplot2: Elegant Graphics for Data Analysis. Springer- Verlag New York. Williams, NM, D Cariveau, and R Winfree. 2011. Bees in disturbed habitats use, but do not prefer, alien plants. Basic and Applied Ecology. 12(4): 332-341. Williams, P. H., R. W. Thorp, L. L. Richardson, and S. R. Colla. 2014. Bumble Bees of North America: an Identification Guide. Princeton University Press. Winder, JA, and P Silva. 1972. Cacao pollination: Microdiptera of cacao plantations and some of their breeding places. Bulletin of Entomological Research. 61(4): 651-655. Winfree, R, R Aguilar, DP Vázquez, G LeBuhn, MA Aizen. 2009. A meta‐ analysis of bees’ responses to anthropogenic disturbance. Ecology. 90(8): 2068-76. Winfree, R, NM Williams, J Dushoff, and C Kremen. 2007. Native bees provide insurance against ongoing honey bee losses. Ecology letters. 10(11):1105-1113. Wirtz, P, M Szabados, H Pethig, and J Plant. 1988. An extreme case of interspecific territoriality: male Anthidium manicatum (Hymenoptera, Megachilidae) wound and kill intruders. Ethology. 78(6): 159-167. Wold, S., M. Sjöström, and L. Eriksson. 2001. PLS-regression: a basic tool of chemometrics. Chemometrics and intelligent laboratory systems. 58(2): 109–130. Wratten, SD, M Gillespie, A Decourtye, and E Mader. 2012. Pollinator habitat enhancement: benefits to other ecosystem services. Agriculture, Ecosystems, and Environment. 159: 112-122.

108