Interactions of Wild Bees with Landscape, Farm Vegetation, and Flower Pollen

WILD BEE SPECIES RICHNESS ON NORTH CENTRAL FLORIDA PRODUCE FARMS: INTERACTIONS OF WILD BEES WITH LANDSCAPE, FARM VEGETATION, AND FLOWER POLLEN

ROSALYN DENISE JOHNSON

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2016

To my family and friends who have supported me through this process

ACKNOWLEDGMENTS

To Rose and Robert, Rhonda and Joe, and Katherine and Matthew without whose encouragement and support I could not have done this. I am grateful to my co- advisors, Kathryn E. Sieving and H. Glenn Hall, and my committee, Rosalie L. Koenig,

Emilio M. Bruna III, David M. Jarzen, and Mark E. Hostetler for the opportunity to contribute to the knowledge of wild bees with their expert guidance. I would also like to thank the farmers who allowed me to work on their land and my assistants Michael

Commander, Amber Pcolka, Megan Rasmussen, Teresa Burlingame, Julie Perreau,

Amanda Heh, Kristen McWilliams, Matthew Zwerling, Mandie Carr, Hope Woods, and

Mike King for their hard work

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 7

LIST OF FIGURES ...... 8

ABSTRACT ...... 13

CHAPTER

1 INTRODUCTION TO WILD BEE SPECIES RICHNESS AND POLLEN MOVEMENT IN NORTH CENTRAL FLORIDA ...... 15

2 FARM AND LANDSCAPE FACTORS INFLUENCING WILD BEE DIVERSITY ON NORTH FLORIDA PRODUCE FARMS ...... 18

Summary ...... 18 Introduction ...... 19 Background ...... 19 Research Objectives ...... 22 Methods ...... 24 Farming System and Species ...... 24 Study Design ...... 26 Bee Species Richness Assessment ...... 27 Vegetation and Landscape Assessment ...... 28 Data Analysis ...... 30 Results ...... 33 Bee Species Richness ...... 33 Vegetation and Landscape Assessment ...... 34 Discussion ...... 37 Plant And Bee Species Richness In Farm Fields ...... 37 A Signal From The Mesohabitat Scale ...... 38

3 POLLEN COLLECTION BY WILD BEES ON PRODUCE FARMS IN NORTH- CENTRAL FLORIDA...... 60

Summary ...... 60 Introduction ...... 61 Methods ...... 62 Study System and Strategy ...... 62 Bee Collection ...... 63 Pollen Preparation, Photography, and Counts ...... 64 Analytical Methods ...... 66 Results ...... 67

Vegetation ...... 67 Bees ...... 68 Pollen samples ...... 68 Discussion ...... 69 How Many Wild Bees Carried Pollen? ...... 69 Crop Pollen Carriers ...... 70 Non-Crop Pollen Carriers ...... 71 Management Perspectives and Future Directions ...... 73

4 ANNOTATED, ILLUSTRATED CHECKLIST OF POLLEN–CARRYING WILD BEES OF NORTH-CENTRAL FLORIDA PRODUCE FARMS ...... 87

Introduction ...... 87 Methods ...... 87 Results ...... 88

5 CONCLUSIONS AND RECOMMENDATIONS ...... 147

APPENDIX: FLORIDA NATURAL AREAS INVENTORY ...... 149

LIST OF REFERENCES ...... 151

BIOGRAPHICAL SKETCH ...... 160

LIST OF TABLES

Table page

2-1 Several characteristics describing management practices of the study farms. Numbers represent farms. Figure 2-1 for farm placement...... 43

2-2 Variables at micro- meso- and microhabitat scales. Data were collected from farms on 2011 and 2012 or from the Florida Natural Areas Inventory Cooperative Land Cover Map (2010)...... 44

2-3 Bee Individuals Collected By Species and Farm...... 46

2-4 Principal component loadings in relation to original landscape variables. Loadings indicate a principal component score above 0.5...... 50

2-5 General linear mixed model output showing factors tested for relationships with Chao2 bee species richness. Error was computed using the Satterthwaite method in Statistica (Academic v.12; 2015)...... 51

3-1 Management characteristics of the ten study farms (1-10) on which pollen- carrying bees were colected. Farms were all irrigated with low to no pesticide use...... 75

3-2 Family and species of wild bees caught carrying pollen on produce farms and the morphospecies of pollen (raw counts) they carried...... 76

4-1 Family, genus, and species of wild bees that were carrying pollen on produce farms...... 89

A-1 Defined land covers from the Florida Natural Areas Inventory and data categories...... 149

LIST OF FIGURES

Figure page

2-1 Bee study farm locations in North-central Florida, USA. Circles represent 500 m buffers (out to 3 km) around the farm fields that were sampled for wild bees...... 52

2-2 Layout for bee bowl and vegetation sampling on a produce farm. Nine bee bowls were primed for capture, three by each of the three quadrats (i.e., one meter sampling circles) in blooming crops...... 53

2-3 Mean species counts from four sampling periods with bars showing standard error. Sampling periods 1 and 3 were March/April 2011 and 2012 respectively...... 54

2-4 Species accumulation curves for cumulative raw bee counts on ten farms (farm ID in legend at right)...... 55

2-5 Wild bee species rarefaction curves estimated by farm with transects as sampling unit...... 56

2-6 The classification tree identified one principal component (Suburban vs. Pasture or DVvPST1) and another factor (Plant Species richness or Plant Types in fields) as important variables ...... 57

2-7 Scatterplot of Chao2 bee species richness against in-crop plant richness with curved lines representing confidence intervals. Bee richness rose significantly as plant richness increased in crop field quadrats...... 58

2-8 Scatterplot of Chao2 mean species richness showing seasonal sample variation in on 10 farms against the mesohabitat scale PC, Suburban vs. Pasture (within the first buffer)...... 59

3-1 Bee study farm locations (1-10) in North-central Florida, USA. Circles represent 500 m buffers (out to 3 km) around the farm fields that were sampled for wild bees...... 80

3-2 Pollen species (above) and wild bee species (below) accumulation curves ...... 81

3-3 Dominant blooming crops on produce farms from two sampling years (five sampling periods) according to walkabout observations...... 82

3-4 The pollen families by sample period (1=March/April 2011, 2=May/June 2011, 3= October 2011, 4= March/April 2012, 5= May/June 2012 ...... 83

3-5 Total number of pollen grains counted per bee by pollen family. Legend patterns indicate pollen class (Crop, Non-crop, or Either)...... 84

3-6 Pollen classes (Crop, Non-crop, or Either) carried by the bee families after weighting by size (i.e., pollen carried/size in mm) to emphasize small bee efforts...... 85

3-7 The wild bee crop pollen carriers and the amount of pollen (weighted) that they carried...... 86

4-1 Project location map. Circles indicate locations of wild bee collection farms...... 92

4-2 Images of Andrena banksi and pollen the species was carrying on small produce farms...... 93

4-3 Information on Andrena banksi and pollen the species was carrying on small produce farms...... 94

4-4 Images of Andrena barbara and pollen the species was carrying on small produce farms...... 95

4-5 Information on Andrena barbara and pollen the species was carrying on small produce farms...... 96

4-6 Images of Andrena cressoni and pollen the species was carrying on small produce farms...... 97

4-7 Information on Andrena cressoni and pollen the species was carrying on small produce farms...... 98

4-8 Images of Andrena miserabilis and pollen the species was carrying on small produce farms...... 99

4-9 Information on Andrena miserabilis and pollen the species was carrying on small produce farms...... 100

4-10 Images of Perdita bequaerti and pollen the species was carrying on small produce farms...... 101

4-11 Information on Perdita bequaerti and pollen the species was carrying on small produce farms...... 102

4-12 Images of Bombus bimaculatus and pollen the species was carrying on small produce farms...... 103

4-13 Information on Bombus bimaculatus and pollen the species was carrying on small produce farms...... 104

4-14 Images of Bombus griseocollis and pollen the species was carrying on small produce farms...... 105

4-15 Information on Bombus griseocollis and pollen the species was carrying on small produce farms...... 106

4-16 Images of Bombus impatiens and pollen the species was carrying on small produce farms...... 107

4-17 Information on Bombus impatiens and pollen the species was carrying on small produce farms...... 108

4-18 Images of Ceratina floridana and pollen the species was carrying on small produce farms...... 109

4-19 Information on Ceratina floridana and pollen the species was carrying on small produce farms...... 110

4-20 Images of Habropoda laboriosa and pollen the species was carrying on small produce farms...... 111

4-21 Information on Habropoda laboriosa and pollen the species was carrying on small produce farms...... 112

4-22 Images of Melissodes bimaculata and pollen the species was carrying on small produce farms...... 113

4-23 Information on Melissodes bimaculata and pollen the species was carrying on small produce farms...... 114

4-24 Images of Melissodes communis and pollen the species was carrying on small produce farms...... 115

4-25 Information on Melissodes communis and pollen the species was carrying on small produce farms...... 116

4-26 Images of Triepeolus remigatus and pollen the species was carrying on small produce farms...... 117

4-27 Information on Triepeolus remigatus and pollen the species was carrying on small produce farms...... 118

4-28 Images of Xylocopa micans and pollen the species was carrying on small produce farms...... 119

4-29 Information on Xylocopa micans and pollen the species was carrying on small produce farms...... 120

4-30 Images of Xylocopa virginica and pollen the species was carrying on small produce farms...... 121

4-31 Information on Xylocopa virginica and pollen the species was carrying on small produce farms...... 122

4-32 Images of Colletes latitarsis and pollen the species was carrying on small produce farms. Pollen photos are courtesy of the author...... 123

4-33 Information on Colletes latitarsus and pollen the species was carrying on small produce farms...... 124

4-34 Images of Agapostemon splendens and pollen the species was carrying on small produce farms...... 125

4-35 Information on Agapostemon splendens and pollen the species was carrying on small produce farms...... 126

4-36 Images of Augochlorella aurata and pollen the species was carrying on small produce farms...... 127

4-37 Information on Augochlorella aurata and pollen the species was carrying on small produce farms...... 128

4-38 Images of Halictus poeyi and pollen the species was carrying on small produce farms...... 129

4-39 Information on Halictus poeyi and pollen the species was carrying on small produce farms...... 130

4-40 Images of a Lasioglossum and pollen the species were carrying on small produce farms...... 131

4-41 Information on Lasioglossum spp. and pollen the species were carrying on small produce farms...... 132

4-42 Images of Hoplitis sp. and pollen the species was carrying on small produce farms...... 133

4-43 Information on Hoplitis sp. and pollen the species was carrying on small produce farms...... 134

4-44 Images of Megachile albitarsis and pollen the species was carrying on small produce farms...... 135

4-45 Information on Megachile albitarsis and pollen the species was carrying on small produce farms...... 136

4-46 Images of Megachile geogica and pollen the species was carrying on small produce farms...... 137

4-47 Information on Megachile georgica and pollen the species was carrying on small produce farms...... 138

4-48 Images of Megachile mendica and pollen the species was carrying on small produce farms...... 139

4-49 Information on Megachile mendica and pollen the species was carrying on small produce farms...... 140

4-50 Images of Megachile texana and pollen the species was carrying on small produce farms...... 141

4-51 Information on Megachile texana and pollen the species was carrying on small produce farms...... 142

4-52 Images of Osmia sandhouseae and pollen the species was carrying on small produce farms...... 143

4-53 Information on Osmia sandhouseae and pollen the species was carrying on small produce farms...... 144

4-54 Images of pollen carried by unidentified bees collected on small produce farms. Pollen photos courtesy of author...... 145

4-55 Information on pollen the unidentified species were carrying on small produce farms...... 146

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

WILD BEE SPECIES RICHNESS ON NORTH CENTRAL FLORIDA PRODUCE FARMS: INTERACTIONS OF WILD BEES WITH LANDSCAPE, FARM VEGETATION, AND FLOWER POLLEN

Rosalyn Denise Johnson

May 2016

Chair: Kathryn E. Sieving Major: Wildlife Ecology and Conservation

Wild bees are pollinators of crops and wild plants globally, and agriculturalists are interested in wild bees as insurance against the loss of introduced honey bees. The wild bees providing pollination services to farms are mostly undomesticated, and just like other wildlife, they require naturally occurring resources available at multiple scales relative to each species’ needs. Here I investigated bee species richness and pollen movement on working produce farms in North-central Florida. I addressed the hypotheses in Chapter 2 that both farm and landscape attributes correlate with bee richness. I conducted a comparative study on 10 farms that occurred across a gradient from mostly agricultural to mostly wooded landscapes. I quantified predictor variables for analysis at three scales relevant to bee movement and habitat use: macrohabitat

(land covers out to 3 km), mesohabitat (land covers on and immediately adjacent to farms), and microhabitat (vegetation structure and composition in farm fields). I collected approximately 1,500 bees of 65 species using bee bowls and insect nets then estimated true species richness for the farms with rarefaction. I modeled (with general linear models) bee richness with refined land cover and farm vegetation data, and

considered the composition of wild bee species on each farm (using analysis of similarities). I found that increased plant richness on the microhabitat scale, and more pasture than development on the mesohabitat scale, encouraged greater on-farm bee species richness (F=5.56, P=0.026 and F=7.82, P=0.009). I summarized my findings on wild bee pollen movement in Chapter 3, having collected, processed and photographed the pollen loads of about 150 wild bees caught in farm fields. I found that wild bees were moving pollen from sixteen families of plants, including Cucurbitaceae, Brassicaceae, and Ericaceae that all contain crop varieties. To raise awareness of the wild bees of local produce farms, Chapter 4 is an illustrated checklist that provides annotated images of bee-borne pollen grains and the bee species that carried them. These chapters document the capacity for several farm-caught species of wild bees to act as crop pollinators, and provide groundwork for future studies of bee ecology and pollination.

CHAPTER 1 INTRODUCTION TO WILD BEE SPECIES RICHNESS AND POLLEN MOVEMENT IN NORTH CENTRAL FLORIDA

Native, wild bees have increasingly drawn public attention coinciding with knowledge of European honey bee (Apis mellifera) declines in North America. Wild bees augment honey bee pollination on small produce farms in North Central Florida, and these largely-sustainable farms are part of important habitat for wild bees. These farms provide foraging and some nesting resources while the bees carry pollen away from parent flowers, perhaps to other flowers of the same species for pollination. The chapters of this dissertation describe the process I used to investigate wild bee species richness and pollen-carrying habits on largely-sustainable farms in one of North-central

Florida’s agricultural regions.

I chose to study the area around Gainesville, FL, US, a mosaic landscape that can be roughly divided into wooded vs. agricultural land covers. With five study farms in each landscape type we assessed (in Chapter 2) bee species richness and vegetation characteristics on farms and summarized landscape level land cover data from the

Florida Natural Areas Inventory (FNAI) to find relationships between bee species richness and the habitats on and surrounding the farms. I captured bees, and evaluated the vegetation community in crops, on farm edges, and in the surrounding landscape

(i.e., through the FNAI land cover maps). I processed, labeled, and identified wild bees to species. Comparing species richness across the ten farms in the study, I determined how species richness differed in relation to vegetation metrics and landscape variables at three different scales (e.g., microhabitat, mesohabitat, and macrohabitat) out to a 3 km radius around the farms. Based on raw bee data, I used rarefaction to make accurate estimates of real bee species richness on each of the produce farms, and

used these bee estimates as response variables to be used with vegetation-based predictor variables. I found that predictors of species richness were fairly localized to the microhabitat (farm field) and mesohabitat (the farm center to 500 meters) scales. My work suggests that within the study region farmers can influence wild bee species richness utilizing vegetation management in their farm fields, but that the adjacent landscape around farms also has a significant effect on bee species richness. Over that area, the farmers may have little control.

After sampling the wild bees of produce farms, I focused in Chapter 3 on the pollen these bees were carrying. I recovered pollen from the bodies of hand-captured bees from farm fields to see what pollen they had collected up to the time of capture.

This chapter describes the methods I used to take pollen from identified bees and process that pollen so that it could be identified by palynologists and reported here. It answers the question of whether wild bees on Florida produce farms carry wildflower pollen or crop pollen, or some combination thereof. My work on pollen movement was intended to lay the foundation for future studies of pollination effectiveness of wild bees in Florida and other, similar systems.

Wild bees in this study demonstrated the capacity for several species to act as crop pollinators, by moving the right kinds of pollen on small produce farms. With the recovery of pollen from the roughly 150 bees from the pollen study, I also generated large numbers of photos of pollen grains which I used to create an annotated, illustrated checklist of wild bees and the pollen they carry on north-central Florida produce farms

(Chapter 4). The magnified images of pollen combined with composite photographs of wild bees are informative about the activities of each bee species caught on

Gainesville’s local farms, and give natural emphasis to the beauty and diversity of these small animals that provide pollination, an important ecosystem service.

CHAPTER 2 FARM AND LANDSCAPE FACTORS INFLUENCING WILD BEE DIVERSITY ON NORTH FLORIDA PRODUCE FARMS

Summary

Wild bees are important pollinators of plants around the world. I investigated wild bee species richness on small produce farms, and in order to understand the scale of influence on local bee species richness, I addressed the hypotheses that the land uses at larger landscape scales and habitat structure and composition on the largely- sustainable produce farms in this study are associated with bee species richness. I conducted a comparative study on 10 farms surrounding Gainesville, Florida, USA that were selected because they occurred across a gradient of surrounding land covers

(from mostly agricultural to mostly forested landscapes). I quantified predictor variables for analyses at three scales relevant to bee movement and habitat use: macrohabitat

(land use surrounding farms; out to 3 km), mesohabitat (land use on and immediately adjacent to the farm), and microhabitat (vegetation structure and flower availability in patches where bees were collected on farms). I collected approximately 1,500 bees of

65 species using bee bowls on transects and insect net samples from flower to flower walkabouts. I used species accumulation curves to determine sampling effort and rarefaction analysis to estimate true species richness on each farm. I used analysis of similarities to test for variation in species composition across the farms sampled, detecting no significant variation. Principal component analysis was utilized to refine predictor variables representing land covers, habitat and vegetation factors related to bee life history and habitat selection at three scales and tested for their relationships with estimated species richness using generalized linear models. I found that increased plant species richness on the microhabitat scale (within farm crops where bees forage)

and increased pastureland on the mesohabitat scale encourages greater on-farm bee species richness (F=5.56; P=0.026, and F= 7.82; P=0.009, respectively). My work suggests that within the study region, given that all farms had similar community composition of wild bee species and predictors of species richness were localized to the microhabitat and mesohabitat scales, farmers can influence wild bee species richness utilizing vegetation management in their fields. Land adjacent to the farm fields is not necessarily under the control of largely-sustainable farm operators, but more pasture in these areas also encourage bee species richness.

Introduction

Background

Wild bees augment the agricultural pollination services provided by declining

European honey bee populations (Rader et al. 2013, Winfree et al. 2007), and wild bees apparently act synergistically in agro-ecosystems in ways that enhance honey bee pollination services (Brittain et al. 2013). Hence, optimism has arisen in the agricultural industry for management practices that can support and magnify the positive effects of wild bees in providing key pollination services. However, unlike domesticated honey bees, the majority of wild bees are not actively conserved or managed on working farmlands and therefore their services are not under farmer control. Wild bees can travel over extensive areas in selecting foraging and nesting habitat; their mobility allows them to take advantage of off-farm resources even if they utilize on-farm resources (Carre et al. 2009, Stephen-dewenter et al. 2002, and Kremen et al. 2002).

Therefore, when inventorying the resources needed by any single wild bee species, or especially by a community of species in a given region, a variety of habitats, and

specific resources within those habitats, that are located on and off-farms must be considered as equally important in meeting wild bee resource requirements.

For example, wild bee nesting resources consist of wood cavities, stems, or soils in which to tunnel; about 30% of North American wild bees are cavity nesters (Black and

Vaughn 2007) and the rest are ground nesting bees. Pollen and nectar are collected by female bees that are commonly polylectic (i.e., collecting from multiple flower types) and rarely, depending on their species, specialists on particular flowers. Wild bee females store flower nectar and pollen mixtures in their nests where these resources sustain growing larvae (Bohardt and Nye 1956). The Insect Societies (Wilson 1971) describes the many levels of sociality among the wild bee species. Wild bees can be communal, involving a much more limited number of females than in honey bees, in building and stocking nests with food resources. Wild bee females can also be solitary; each female can build and provision a nest for her own larval offspring. In sum, wild bee management will look very different from honey bee management. Given the high diversity of resources, scales and habitat types needed to support healthy native bee communities, conservation and management of wild bees will demand nothing less than a paradigm shift in order to protect pollination services in a world with fewer honeybees.

Instead of bee keeping and husbandry practices that are appropriate for the European honey bee (Gegner 2003), traditional wildlife habitat assessment, protection, and population and community management practices will be required (Krausman and

Leopold 2013 for readings on practices that are traditional for wildlife, and Vaughan et al. 2015 for recommendations that are specific for on-farm wild bee management).

Wildlife science now assumes that species biodiversity in a location is influenced by resource availability across micro- (within home range), meso- (local resource patch), and macro- (population scale) habitat scales (Morrison et al. 2008; resource selection in Fryxell et al. 2014). Like other wildlife, bee species presence or absence in a local patch also depends on even larger scale factors such as availability of source habitats to enable colonization (Franzen and Nilsson 2013) and widespread landscape, land use, and climate modification by humans (Hadley and Betts 2011, Benton et al.

2003, Ferreira et al. 2013, Diaz et al. 2012, Hatfield and LeBuhn 2007). Because it is understood that wildlife populations vary in dynamics and resource use across spatial and temporal scales (Morrison et al. 2008), recent studies have encompassed appropriate scale variation in invertebrate communities (Clough et al. 2005, Benton et al. 2003), agricultural plant communities (Gabriel et al. 2006), and also with wild bee pollinators (Beil 2008, Kremen 2004, Steffan-Dewenter et al 2002). Thus, the paradigm of pollination service management is beginning to occur, but more work is needed in working farm environs to refine wild bee management practices that are under the control of growers and effective given the larger scale context of land uses and management practices that influence both bee richness and on-farm ecology (Dicks et al. 2015 for floral plantings).

Encouragements to take a cross-scalar view of agroecosystem management in the US have come from wildlife, soil and water conservationists (Feber et al. 2015, biodiversity in agricultural landscapes), and a variety of farm policies are in place that will aid in achieving wild bee management (e.g., the current Commodity Loan Programs and Conservation Reserve Programs of the U.S. Department of Agriculture). But in any

given region wild bee communities will be unique and efforts must be made to understand their specific needs and the services they can offer growers if they are to be managed effectively. I undertook such a study of the wild bee community in North- central Florida in order to test for cross-scalar effects of land use (macrohabitat, mesohabitat), on-farm management of field verges (mesohabitat), and within-field crop vegetation (microhabitat) on structuring the community of bees found foraging within crop fields on working produce farms. The farming system I selected is one that relies on production of a variety of bee-pollinated crops. Some of the bees in the region are known to be important pollinators of certain crops. For example, the squash bee genus

Xenoglossa (of which Florida’s X. kansensis is a part) pollinates squash plants in the family Cucurbitaceae (Hall 2010) and the southeastern blueberry bee, Habropoda laboriosa, provides pollination services for blueberry farms in the region (Rogers et al.

2014). Assuming that other wild bee species may be identified as crop pollinators in the future, due to the need to augment pollination services of declining European honey bees (Rader et al. 2013), I sought to evaluate wild bee species richness on largely- sustainable, working farms in an ecological context.

Research Objectives

The goal of this study was to characterize the community of wild bee species that forage in sustainably managed crop fields, and to identify factors that could be influencing species richness and, further, to determine whether these factors are amenable to management at the scale of individual growers. Moreover, I measured habitat-related factors at three scales on and around sampled farms in order to determine whether enhancement of wild bee communities through habitat management on and around farms is a possibility (Mader and Hopwood 2013, Mader et al. 2010).

Hypothesis 1 looks at large scale habitat dominance: Land use variation at the macro-scale will be correlated with bee richness and community measures. To test this hypothesis, I distinguished largely forested land uses from largely agricultural ones because these dominant land uses were easily told apart in aerial photographs and each broad category might contain habitats that could be used by a variety of wild bees in different ways. Once growers with farms located in this mosaic landscape had agreed to participate, I then could address habitat factors at smaller scales (Hypothesis 2) that could influence bee species richness in fields. Under Hypothesis 2 I tested whether vegetation structure and composition on the microhabitat and mesohabitat scales are correlated with bee community and richness. If so, then I predicted that species richness should be greater in fields with mixed crops in fields (micro-scale; Bonner et al.

2015, Borer et al. 2012) and with field verges comprised of habitats with potential for food, cover, and nesting sites preferred by wild bees (Batary et al. 2011).

Given that wild bee species richness across a number of studies in different geographic regions appears to be positively correlated with proximity to natural habitat

(Kennedy 2015 for multi-regional studies) I predicted that this pattern would emerge in this study as well. However, this prediction is tempered by the fact that vegetation type in the sampling site (where bees are captured) may heavily influence species richness of the sampled community (Billeter 2007). In this study, my focus on identifying potential pollinators led me to sample within cropped fields; habitats that specialist bees may not be able to use. Therefore, I also allowed for the possibility that the expected positive relationship with natural habitat would not hold, and that the reverse could be true; that richness may peak in farmed landscapes. Otherwise, I predicted that blooming density

and certain on-farm vegetative characteristics would be correlated with wild bee species richness.

Methods

Farming System and Species

North Central Florida is part of the Southeastern United States Coastal Plain, loose sediments that skirt the Atlantic and Gulf coasts from the Mid-Atlantic States through Texas. Alachua, Bradford, Gilchrist and Union Counties where study farms were located, are a mix of Florida’s highlands (clay and sandy river deposition soils) and flatwood-dominated lowlands (Whitney et al. 2004). The land covers surrounding study farms in this region are dominated by pine and hardwood woodlands (including pine plantations) or tilled and pastoral agricultural land. Two (of ten) study farms were located close to Gainesville (the population in 2011 and 2012 was 125-130 k, US

Census Bureau 2015) within the fringes of the suburban sector, and were adjacent to neighborhoods (Figure 2.1).

North-central Florida’s humid subtropical climate is warmer than average for the

United States with an average annual extreme minimum temperature of 20-25°

Fahrenheit (USDA 2015). This zone is shared with parts of California and Arizona, but those climates differ in rainfall with north-central Florida receiving an average of 30 to

40 additional inches of rain per year than California and Arizona, respectively (NOAA

2015). Florida farms that grow annual crops rest their fields from July to September when the heat is too intense for un-shaded field crops even on irrigated farms, leading to a spring/summer growing season and a fall/winter growing season. Climatically, this region is more similar to farming regions on other continents and in Central America than to others in North America. Vegetables and fruit farms that participated in the study

shared several common management characteristics as described in Table 2.1. Farm properties were primarily family owned and the largest farm comprised ~ 150 acres

(Jacobson et al. 2003 for overview of North-central FL farming systems).

The bee species in this region number more than 300, other than honey bees

(Apis mellifera), and are typically referred to as wild, native, or solitary bees. Here, all such non-honey bees are referred to as wild bees, and include both native and solitary bee species even if they are not native and are social (for taxonomy, Pascarella and

Hall 2006, Hall 2014, Mitchell 1960,1962, USGS 2015; for behavior Bohart and Nye

1956, Wilson 1971). Seventy percent of Florida’s wild bees are adapted to tunneling in soil or sand rather than building nests in dead wood, nest boxes, and hollows (e.g. plant stems) as do the other 30% of wild bees. All of the wild bee species observed on farms from this region (Hall 2011) forage on pollen and nectar, and the body lengths of these bees vary from three to 23 mm, influencing the distance they can travel for resources

(Greenleaf et al. 2007). The five bee families present in Northern Florida display varying degrees of sociality, which may affect the efficiency with which they move pollen. Roughly 25 per cent (Deyrup 2002) of wild bees in the study area are parasites on other wild bee species, appropriating pollen stores for their own offspring by stealing into host species’ nest undetected to lay hidden eggs. Although the managed honey bee is not a focus of this study, farmers on several study farms maintained hives and a small number of individuals were collected as by-catch.

The human-dominated landscape of North-central Florida is comprised of a mosaic of relatively small farming operations, urban, suburban, and rural settlements as well as a rich diversity of natural habitats from springs and wetlands to hardwood and

pine woodlands both natural and managed (Table 2.1 and Appendix). Therefore, a number of potential nesting, feeding and breeding habitats for wild bees are available in a variety of compositions across spatial and temporal scales. The landscape surrounding the study farms supports diversity of resources that wild bee communities rely on, and many farms are sustainably managed in the region with high native bird and plant species richness and vegetative structural diversity both on and around fields

(Jacobsen et al. 2003, Jones and Sieving 2006). Therefore, farming systems in this region hold great promise for application of wildlife management techniques to bee communities that, in turn, could potentially allow for management of pollination services by this native bee community.

Study Design

I conducted a comparative study at the landscape scale by selecting farms that were located across a gradient of largely wooded to largely agricultural land covers within a 3 km radius sample circle; Fig 2-1. A 3 km buffer around these farms would conservatively encompass most normal bee movement given that the largest bees detected during preliminary surveys were, Xylocopa virginica, at 23 mm (Mitchell 1962).

Similarly sized bees in Zurbuchen et al. (2010) and Gathmann (2007) had ranges of approximately 3 km, and travel distances for wild bees are positively correlated with body length (Greenleaf 2007). Buffers around each farm were separated by at least 3 km.

The land cover gradient around farms was determined through use of 2010 aerial images (Figure 2.1; Google Earth 2015) prior to fieldwork in order to insure a range of land use intensity would be sampled at the landscape scale by farm location. Five farms were located in woody and five farms in agricultural habitats. As such, a moderate

degree of causal inference about the importance of wooded versus farmed land use composition at the largest scale was obtained by this design (James and McCulloch

1990). At smaller scales, no effort was made to select contrasting habitat characteristics; I simply measured what was on participating farms. Therefore, at the mesohabitat and microhabitat scales, the design of this study was descriptive. However, because bee species richness has already been established to be causally linked to small scale variation in local vegetation structure and composition (Billeter et al. 2007), any significant correlations I obtained between on-farm and in-field factors with bee species richness could be assumed to be potentially causally linked.

Bee Species Richness Assessment

Passive collection in bee bowls. Bees were attracted to the colors of translucent plastic 3.25 oz. soufflé cups (Solo®, Highland Park, IL), flew into the soapy water contained therein and remained there until bowls were collected 24 hours later. I used approximately two teaspoons of Dawn® dishwashing liquid in solution with a gallon of water to fill the bowls. The cups were placed in sets (i.e. fluorescent blue, yellow, and white) every five meters along ten meter transects in blooming row crops alongside the quadrats (i.e., meter-wide plant sampling circles) where I collected vegetation data (Figure 2-2). The method of using bee bowls and preparation of wet specimens is described in Droege (2012, revised April 2015), but our bowls were modified by protecting the bottom interior of the cups with a layer of latex paint prior to using spray paint (Hall 2010). I used Ace® Brand, made by Krylon, I17052A00 (yellow), and I19716A00 (blue), and Krylon® Fusion 2320 (white) consistent with Hall (2010).

Bees collected in bee bowls were deposited in labeled vials and processed as described in the Very Handy Bee Manual (Droege 2012).

Insect net captures and “Walkabout” sampling. I collected foraging bees from flowers using insect nets during a 30-40 minute walk around blooming crops and weeds on the farms. If more than one experienced netter was working, walking time was reduced proportionally (e.g. two experienced netters would spend 15-20 minutes capturing bees). I observed two bee species, honey bees (Apis mellifera) and common carpenter bees (Xylocopa virginica) on every farm during each visit. Since these bees were easily identifiable on the wing I recorded but did not typically capture either species when I encountered them during surveys. These “walkabout” species are both represented in the community analysis at the rate of one individual per farm visit.

Vegetation and Landscape Assessment

Microhabitat. Table 2-1 describes common characteristics of our ten study farms. I selected farms that fell within a range of landscape compositions from mostly natural vegetation (pine or hardwood forest cover) to mostly agricultural (including pastoral) and more developed land covers, and that were similar in insect-attractive crops grown and largely-sustainable crop field management. In particular, all farms were dedicated to low or no pesticide use, and all were irrigated. I visited local farmer’s markets and used farm websites in 2010 and 2011 to survey farmers on their crops and level of interest in participating in the study. Farmers were asked about general crop types but not varieties, pesticide use, their awareness of wild bees, and their willingness to allow farm visits over the course of the study. I sampled the study farms within thirty- day cycles, two days per month from March 1st until approximately July 1st between 9:00 am and 3:00 pm. Rain delayed or cancelled sampling. I placed three vegetation quadrats randomly to the left or right of ten m transects (Figure 2-2) located alongside however many crops were blooming on that visit. I also collected vegetation data along

forty meter transects at the edge of cleared farmland to characterize the transition zone between crops and surrounding habitat. Coverage of vegetation types (non-crop vs. crop, blooming and non-blooming), coverage of bare soil or horticultural plastic, and non-crop and crop heights were recorded. Table 2-2 describes study variables and definitions.

Mesohabitat and Macrohabitat. Mesohabitat included the area adjacent to the farm inside the first 500 m buffer while macrohabitat included the outer five buffers from

500 m to three kilometers. I assessed both scales using the Florida Natural Areas

Inventory (FNAI) Cooperative Land Cover Map (2010; Appendix). The layered FNAI map was developed in a partnership between the Florida Fish and Wildlife Conservation

Commission (FWC) and FNAI “to develop ecologically-based statewide land cover from existing sources and expert review of aerial photography” (FNAI 2010). The FNAI inventory is vegetation based, but includes a variety of potentially bee-appropriate landscapes that combine both land uses (e.g. cattle pasture) and land covers (e.g. wet prairie). On the meso- and macrohabitat scales I was able to consider land covers that ranged from natural to developed, open area vs. shrubby, wooded cover, as well as wet and drier habitats aggregated by their likelihood to contribute bee habitat value within the three km effective landscapes (Zurbuchen et al 2010, Greenleaf 2007) around the farms. Although bee nesting habitat values are not well studied across the approximately 300 cavity and ground-nesting species in Northern Florida, Norden

(2008) described a Florida bee specie’s semi-aquatic nesting behavior, so I included seasonally inundated wetlands (e.g. wet prairie) among potentially bee-valued habitats.

I aggregated the seventy-two land cover types (e.g., commercial services, wet prairie, orchards, coniferous plantations, etc.) into the five categories in (Table 2-2 and

Appendix). “Untilled open lands” could be more successful at producing ground-nesting bees than frequently disturbed “tilled agricultural lands” so I divided open, terrestrial land covers into these two categories. Open water (permanent and unsuitable habitat), woody/shrubby areas and developed lands (both possibly suitable for ground or cavity nesting) made up the final three categories. I used ArcMap to aggregate land covers within the six 500 m buffers around each farm’s center and return type counts in meters squared. These counts, subdivided by category and farm, were the variables I used for the principal component analysis. Later, preliminary analyses showed that there was no significant signal from the individual, outer buffers (beyond 500 meters to three km), so I clumped those buffers into one macrohabitat area for the final analyses.

Data Analysis

Species richness estimation. I used rarefaction, effort-based species richness estimation, to assess whether sampling effort was balanced across the ten farms, to balance the samples through systematic resampling, and to derive species richness estimators (Gotelli and Ellison 2004). Because some species accumulation curves

(Figure 2-5) did not level off, signifying that raw species counts could not be compared quantitatively, I conducted a rarefaction analysis (or, effort balanced re-sampling) to estimate unbiased maximum species numbers for each farm (EstimateS, version 9.1.0, http://purl.oclc.org/estimates; Gotelli and Colwell, 2001). I considered bee bowl data only for this analysis because the nine bowls present on each transect represented a more replicable and standardized effort than was achieved with hand netting or walkabout methods (an important assumption in rarefaction analysis; Gotelli and Ellison

2004). The rarefaction analysis was run two ways using species incidence/farm (n=10) and also species incidence/sampling period/farm (n=33). I used season (i.e., sampling period) to subdivide sample transects from each farm to obtain a sampling unit for rarefaction. I estimated rarefaction curves, resampling without replacement, and extrapolated from real data to three times the number of each farm’s original samples using the classic formula for Chao2 bias correction. An upper abundance limit for rare species was set at two (lowest) since there were several individuals and pairs that were the only representatives of their species in the sample.

I chose the Chao2 richness indicator for a descriptor of the comparative levels of bee species richness that I detected per sampling period because Chao2 considers the incidence of rare species. Overall, 32% of the wild bees (18 of 65 species) collected by all three methods were collected only one or two times across all samples, and by bowl collection only 13 species out of 35. Chao2 (derived using EstimateS, version 9.1.0, http://purl.oclc.org/estimates; Gotelli and Colwell, 2001 from Chao 2005) was also the most relevant and informative bee richness estimator with the greatest range of variation related to the set of predictor variables. I also considered ICE, incidence-based coverage that emphasizes the species overlap between sampling sites, but no important predictor variables were identified for ICE, so only Chao2 was used in general linear modeling (below). I did this to ascertain whether different farmers in North-central

Florida might be seeing quantitatively different sets of species (Brosi et al. 2007).

Data reduction and hypothesis testing. I used principal component analysis to reduce the number of variables and the covariance between buffers, then I used decision trees to explore the relationship between Chao2 (Chao 2005) and potential

predictor variables represented by the principal components and a few non-correlated vegetation metrics (e.g. in-field plant species richness). I used the CART method

(Breiman et al. 1984) to screen all of my predictor variables for their potential correlations with Chao2. This analysis requires few assumptions about variable distributions and employs a simple algorithm for identifying homogenous subsets of data based on successive iterations of the predictor variables. The analysis produces relative importance of all the variables in explaining the variation in Chao2 across the farms. I used Chao2 estimates for each seasonal sample on each farm because certain variables like plant species richness, blooming cover, and vegetation height in fields varied with season. Importance values greater than 0.5 from the CART were used to identify variables to include in a generalized linear model testing for significant relationships with Chao2 richness. I used a general linear model (GLM) in Statistica

(Academic v.12, 2015) to test for relationships between Chao2 and the important variables identified by the CART. Using a normal probability plot I found that a log base

10 transformation of Chao2 normalized the distribution, therefore we utilized the normal distribution in the analysis. GLM assumes a normal distribution in diversity measures.

Community ordination. I used nonmetric multidimensional scaling in R (RStudio

Version 0.98.994) to collapse bee specimen information from all collection methods on multiple sampling sites into two dimensions for visualization and analysis. Using analysis of similarities (ANOSIM in the Vegan package in RStudio, Version 0.98.994,

2009-2013 RStudio, Inc.) I tested whether there was a significant difference in species composition between three groups I predetermined on the basis of which farms 1) were

located in agricultural or natural landscapes, 2) had high or low bee species richness, or

3) had high or low in-crop plant species richness.

Results

Bee Species Richness

I collected 1,461 wild bees of sixty-five species on the ten farms (Table 2-3) during four two-month sampling periods (Figure 2-3): March/April and May/June in 2011 and 2012. There were twenty-four genera and five families from “walkabouts” and hand netting of bees on each visit, and 234 bee bowl transects set in farm fields. A total of 189 transects caught bees with a mean of 47 transects per season, SD = 13.5. Of the individuals collected by hand and bee bowl, 18 species were detected only once or twice. Forty-five percent of individuals collected were of two common species,

Melissodes communis (n=336) and Lasioglossum puteulanum (n=316) that were recorded on every farm surveyed during their emergence seasons (e.g. sampling period two and four for M. communis; and for L. puteulanum sampling periods one, two, three, and four in Figure 2-3). Other bee species to appear commonly on farms in lower numbers were Lasioglossum pectorale, Lasioglossum nymphale, Halictus poeyi, and

Agapostemon splendens. Xylocopa virginica and Apis mellifera were also common and were found on all farms during walkabouts. I did not collect honey bees or the fast flying X. virginica (except as needed for Chapter 3), but recorded the first individual of these two species I could identify in flight or on a flower during a farm visit. The average number of species collected by sampling period ranged from 5-8 by all collection methods and 1-3 in bee bowls alone (Figure 2-3).

Species accumulation curves (Figure 2-4) for the ten farms indicated that our sampling was not perfect, but, based on collected samples, an accurate estimate of

bowl-based species richness would have been achieved within three two-year sampling bouts. Had we continued to sample beyond two years we would have detected more species, but I was successful at sampling sufficiently to estimate true species richness on nine of the ten farms (those for which the rarefaction curve leveled off).

Rarefaction and Richness Indices. Species extrapolation curves (Figure 2-5) for all ten farms were based on rarified reference samples. The average raw number of bees collected in bowls per farm was 15.6 and the per farm species incidence (Chao2 estimate) was approximately 18. With only bee bowls represented and with farm samples subdivided into seasons (reducing the species richness per sample and making the estimates more conservative) estimates were based on mu=9, n=33.

Vegetation and Landscape Assessment

Data Reduction. I reduced seven microhabitat and fifty macrohabitat variables representing vegetation habitat (Table 2-2) to six independent principal components

(PCs) that are shown with their loadings in Table 2-4. The first PC expresses the contrast between vegetation height and cover characteristics in crop fields and on-farm edges with the presence of horticultural plastic (i.e., black plastic for weed prevention and moisture retention), bare soil, and blooming cover. This first PC is positively related to percent vegetation and negatively related to percent horticultural plastic, bare soil, and blooming cover. I called this component “Vegetation vs. Plastic, Microhabitat.” The second PC expresses the contrast between low crop height, low coverage of agricultural plastic, and high blooming cover on farms and farm edges. “Blooming Cover vs. Plastic, Microhabitat” is positively related to percent blooming cover and negatively related to percent plastic and low crop height. The third PC expresses the contrast between woody shrub and open water in the first buffer and tilled agricultural land within

500 m of a farm center. This PC, “Natural vs. Tilled Agriculture, Mesohabitat,” is positively related to woody shrub and open water (natural habitats) and negatively related to tilled agriculture. The fourth PC expresses the contrast between development and untilled open land (pasture and parks) within the first buffer only. This PC is positively related to development and negatively related to untilled pasture and open lands and is called “Suburban vs. Pasture, Mesohabitat”. The fifth and sixth components are in the macrohabitat scale area and are called “Natural vs. Tilled Agriculture,

Macrohabitat” and “All Agriculture vs. Suburban.” Natural vs. Tilled Agriculture,

Macrohabitat, expresses the contrast between woody shrub and open water (natural habitat) and tilled agriculture and has the same positive relationship with habitat as the earlier component for buffer one. All Agriculture vs. Suburban, Macrohabitat expresses the contrast between development and open lands or tilled agriculture with a strong negative relationship to development and a positive relationship with agriculture.

Principal components were Verimax-rotated in SPSS (Version 21 and 23) and used as the predictor variables representing landscape factors in later analyses.

Microhabitat Scale- the farm fields. The mean temperature on farm visits was

75° F (min 58° F, max 90° F, SD= 9) with a light breeze, and sunshine. Farms varied in size from 0.20 to 35 hectares (mean=5.21, SD=11.24), however the area of the largest farm, number five, was much larger than that of the other farm areas and without it the potentially cultivated areas of these farms fell precipitously to mean=1.49 hectares, SD=

1.37. The mean in-crop plant species richness across all farms was 1.77 types of crop and non-crop plants (SD=0.38) per quadrat.

Mesohabitat Scale- between the farm and the first buffer. The non-farm areas within 500 m of each farm center varied with the size of the tilled area of the farm it enclosed. Even the largest farm was not large enough at the time of the study to reach the 500 m mark, which left a broad area that could influence bee species richness close to farms. Characteristics of these areas varied by farm, but were still dominated by

“Wood and Shrub” category variables, with the exception of the tenth farm in which the

“Untilled Open Land” category dominated.

Macrohabitat Scale. The macrohabitat portion of the landscape began at 500 m from the farm center and extended to three km. These areas were large and variable, with half centered on farms with similar macrohabitat profiles given that the areas are each in excess of 2000 hectares (4942 acres) and all the outermost macrohabitat boundaries were at least five km apart.

Classification and Regression Tree (CART). The CART method, used to screen all of my predictor variables (Table 2-2) for their potential correlations with

Chao2 bee species richness, showed the importance of two variables: a principal component (PC) representing the suburban vs. pasture contrast within buffer one and the in-crop plant species richness variable. The Figure 2-6 tree for the Chao2 species richness index shows that greater plant species richness is the main microhabitat factor that splits the node into one branch farms with higher bee richness and one branch with the lower richness farms. On the next node the ratio of suburbia to untilled open spaces on the mesohabitat scale divides the high species richness farms from those with less bee species richness. The importance plot from the CART indicated that only these two

variables were influential enough to be considered in the linear model (importance value

> 0.5).

Hypothesis Testing. The crop field plant species richness (Figure 2-7) and the mesohabitat principal component called suburban vs. pasture (Figure 2-8) were identified by the CART as important, so I fit a general linear mixed model using a normal log distribution (for Chao2) and the plant richness and suburban vs. pasture PC (4) and sampling season (1-4) as fixed effects, and farm as a random effect. Both plant richness in fields and the proportion of pasture to suburban development at the mesohabitat scale were significant predictors of Chao2, but season of sampling was not (Table 2-5;

Figures 2-7, 2-8).

Community Ordination. My results indicated that the three predetermined groupings (i.e., high and low bee richness, high and low plant richness, and more natural vs. more agricultural landscape) were random, so there was no difference in bee community across sampling sites based on any of those groupings. For bee richness the ANOSIM results were R=0.03, P=0.37; for plant richness R=0.01, P=0.47; and, R=-

0.02, P=0.45 for the landscape groupings.

Discussion

Plant And Bee Species Richness In Farm Fields

Bee species richness increased significantly with plant species richness in crop fields (Figure 2-7), confirming hypothesis two. I note that the number of plant species in quadrats only went up to 3; cropped areas only had single crop species and additional plant species were due to the growth of weeds. Therefore, an incremental change in plant species richness in the fields was correlated with a substantial increase in bee species richness (Figure 2-7). A strong positive correlation between invertebrate and

plant species richness is well known (e.g., McIntyre and Hostetler 2001: bees with native plant diversity; Wiebull et al. 2003; butterflies and carabid beetles with plant diversity), and between birds and plant species richness in cropped areas of the same

Florida study system as this study (Jones and Sieving 2006). Plants provide food directly to insects, and insects attracted to plants comprise food for birds and other predators, and the link between animal and plant-provided resources is deeply rooted in the ecological literature and holds across ecosystems (Ambrect et al. 2004, ants;

Kissling et al. 2007, avian frugivores; Lees et al. 2015, forest birds). Results presented here emphasize the high sensitivity of this pervasive plant-animal species richness link: increasing plant species from one to three plant species (e.g. one crop plus two weeds) more than doubled the number of bees species (from five to > 10; Figure 2-7).

A Signal From The Mesohabitat Scale

I found a significant relationship between bee richness and the proportion of pasture vs. suburban land covers in areas adjacent to fields on or near farms. Positive associations between the presence of more complex, natural semi-natural habitats with higher bee diversity and abundance was found in German farmlands (Stephan- dewenter et al., 2002, measured at 250m and 500 m) and with pollination services from wild bees in California (Kremen et al. 2004). Both of these studies had more intensive vegetation sampling and characterization at the mesohabitat scale (as defined here); so our detection of a similar trend was not unexpected. My findings support the idea that like wildlife communities, bee communitiess need complex habitats to support their survival and reproductive needs.

No Macro-Scale Effects

Land use variation at the macrohabitat scale (> 500m from center of the farm) was not correlated with bee richness and community measures (Hypothesis 1). There are several possible explanations. One factor relates to bee sizes and travel distance.

Half of my bee community was comprised of relatively small (n ~ 35 species < 1 cm) and half of larger (n ~ 30 > 1 cm) bees, and only 4 or 5 species (Xylocopa micans, X. virginica, and Bombus impatiens, B. griseocollis, and B. pensylvanicus) were large enough to forage disproportionately greater distances than smaller bees (Greenleaf et al. 2007), and at least far enough to reach the edges of the study area. I relied heavily on bee bowls for my collections, and bowls were more effective at capturing smaller bee species (than hand netting) that are less likely to utilize, or respond to variation in, large- scale land use patterns.

Additionally, the categories I used to describe the habitat types may have been too broadly defined to pick up indices of bee habitat quality. For example, Kennedy et al. (2013) and (Lonsdorf et al. 2009) predicted bee abundance based on habitat composition and resource abundance by also evaluating the relative importance of landscape composition, landscape configuration, local farm management and their potential interactions for 39 farms and 675 bee taxa. Assessing data from over 600 field sites, the most important predictors of wild bee abundance and richness were two local/microhabitat scale variables (i.e., organic field type and plant species richness on the field level) and one landscape scale index variable for landscape composition. This latter index expressed habitat values for bees across the off-farm lands within three km of sampling locations. I used the same three km scale to define my macro-scale, but my

land use categories were not tied to indices of bee habitat quality. My overall approach was similar to these two studies, and my results align well with theirs at the scale of fields (my study fields were organic or low input and I had more bees with higher plant species richness) and their adjacent surroundings (macrohabitat). However, the dissimilarity in sampling effort (samples and farms), and possibly small-bee biased reliance on bee bowls, likely compromised my ability to detect macrohabitat scale influences on local scale bee communities if they exist.

Lastly, results of the community similarity test (ANOSIM in Results) suggest that all of my study farms hosted bee communities with the same set of species. This is in contrast to Hall and Ascher (2014) who detected variable bee community compositions across North-central Florida at the same scale of comparison as my study, but their sampling sites included natural communities as well as farm environs. Their unique bee community in a natural area included rare endemics that I did not detect. Therefore, the bee community I sampled was likely to be comprised of common, generalist species that do not rely heavily on undisturbed natural habitats, many of which dominated the outer buffers of several of my study farms.

Applications to Wild Bee Conservation

The obvious sensitivity of wild bees to on- and near-farm land management is encouraging news for native bee conservation in general, because it suggests that enhancement of local bee species richness in North-central Florida is under land owner control as it is elsewhere (Newbold et al. 2015; Williams et al. 2015). Growers can control field management and can readily increase plant species richness for bees and other beneficial insects by intercropping (Brooker et al. 2015), which is often practiced

on several of the study farms (Jones and Gillett 2005). They can add other plantings around fields (thoroughly described by Vaughan et al. 2015) and this study suggests that some leniency in weed control can also attract bees (Fig 2-7). Additionally, since most of the bees I detected on North-central Florida farms are ground-nesters, open grassy and sandy strips can be maintained to support reproduction of this bee community (Vaughan et al. 2015). Thus on farm and in-field factors that are readily under grower control can be deployed to enhance local bee species richness, foraging activities and presumably pollination activities in cropped fields. Given that the largely sustainable farms of North-central Florida grow a diversity of bee-pollinated crops, it is likely that farmers will be able to rely on local management practices to foster important crop pollinating species. Little work has been accomplished, however, on identifying wild species of bees that provide significant pollination services, but once that is accomplished then it will be important to determine what management practices best support the dominant crop pollinators. For example, Habropoda laboriosa, the

Southeastern blueberry bee, functions in pollination of commercial blueberry crops and is a ground nester that is abundant in the community of bees I detected (Chapter 3).

Management for ground-nesting bees is emerging as nesting habits are described (e.g.,

Graham et al. 2015).

My work showed that the study farms were all exposed to the same community pool of bee species (i.e., no compositional differences were detected) despite occurring across a range of landscape contexts from largely agricultural to largely naturally forested. Therefore, in this region farm location does not constrain native bee management as it might in regions where landscape context has a strong impact on

local bee species richness (Kennedy et al. 2013). Many of the species we detected carry pollen and some seem to specialize on crop pollen at least part of the time

(Chapter 3). So diverse plantings can support more bees and pollen transport on North- central Florida farms. Of course, more research is needed into the habits and resource requirements influencing wild bee population dynamics and pollination activities and effectiveness (Dicks et al. 2013). It is important to note that though I did not detect an important effect of off-farm habitat availability for bees, this could be because the landscape of North-central Florida remains largely natural with a diverse mosaic of native flora in abundant open woodland, grassland and wetland habitats (FNAI 2010).

Along with the smaller scale and largely sustainable management regime of the farming operations (Jacobson et al. 2003), this region experiences an overall agricultural intensity on the lower end of the global scale (Tscharntke et al. 2012). Protecting off- farm areas that wild bees use for alternate foraging and nesting, especially on the mesohabitat scale as indicated by my results, is as important as it is to other beneficial species’ conservation (e.g., Jones and Sieving 2006). Some of the larger-bodied and common bee species will likely tie local and regional ecological management schemes to one another (Cranmer et al. 2011). Finally, just as modern wildlife conservation is a blend of single species and community conservation along with protection of regenerative processes across scales (Allen et al. 2011), I argue that wild bee conservation is no different. As such, a strong focus on discovering the natural history and ecological roles of individual bee species will be fundamental to modernizing agroecosystem management to insure healthy wild pollinator communities.

Table 2-1. Several characteristics describing management practices of the study farms. Numbers represent farms. Figure 2-1 for farm placement. Characteristic Description 1 2 3 4 5 6 7 8 9 10 Use of horticultural Plastic at plant bases for plastic weed and moisture control. X X X X X X

Low pesticide use Pesticide use limited to localized fire ant treatment X X X X X X X X X X

Use of composted Soil nutrient and water manure retention improvement X X X X X X X

Structures and bluebird and/or purple martin plantings for houses beneficial insects X X X X X and/or birds

Cultivated area of > 0.50 ha 0.50 hectares or X X X X X X X X more

Irrigation water Drip lines with black plastic conservation for irrigation present in X X X X X X X X X X most crops

Table 2-2. Variables at micro- meso- and microhabitat scales. Data were collected from farms on 2011 and 2012 or from the Florida Natural Areas Inventory Cooperative Land Cover Map (2010). Response variables are indicated by **, all others are predictor variables. Marked (+) variables were used in the data analysis. Scale Variable Definition Micro Bee Species Richness**+ The rarefied number of bee species collected per farm by walkabout, bee bowls and hand netting. Bee Assemblage**+ The assemblage of species present on each farm. Farm Size Farm size in hectares.

Temperature Temperature recorded on arrival for each farm visit.

Plant Species Richness+ The raw number of plants recorded in quadrat samples in farm fields. Crop Type+ Agricultural crop types that were blooming during each farm visit. Crop Height+ The mean height of crop vegetation averaged across the three quadrats measured per transect within crop fields. Crop % Cover+ Percent cover of crop vegetation averaged across three quadrats per transect within crop fields. Non-crop Height+ Mean height of non-crop vegetation from crop transects. Non-crop % Cover+ Percent cover of non-crop vegetation averaged across transects. Litter Depth Mean depth of litter from quadrats in crop fields. Bare Soil/Litter Or Plastic Per cent cover not composed of live vegetation from % Cover+ quadrats in crop fields.

Meso Non-crop Mean Height+ Mean height of non-crop vegetation from farm edges. Non-crop % Cover+ Percent cover of non-crop vegetation averaged across transects on farm edges. Litter Mean Depth+ Mean depth of litter from quadrats on farm edges. Bare Soil/Litter Or Plastic Percent cover not composed of live vegetation from % Cover+ quadrats along farm edges.

Canopy Mean Height Overstory canopy mean height on farm edges. Canopy % Cover Percent cover of tree canopy on farm edges. Open Water 1+ Standing water habitats inside the first 500M buffer. Untilled Open Land 1+ Pastures and park-like lands within the first buffer. Wood and Shrub Lands Wooded lands within the first buffer. 1+ Developed Lands 1+ Residential, road, and other built up areas within 500 m.

Table 2-2. Continued. Scale Variable Definition Tilled Agricultural Land 1+ Plowed and planted croplands within the first buffer (including the study farm) Macro Open Water + Standing water habitats in five outermost 500M buffers around each farm. Untilled Open Land + Pastures and park-like lands in the five outer buffers. Wood and Shrub Lands+ Wooded lands in the five outer buffers. Developed Lands+ Residential, road, and other built up areas within 500 m. Tilled Agricultural Land 2 + Plowed croplands in the five outer buffers.

Table 2-3. Bee Individuals Collected By Species and Farm. ** Indicates species observed on ‘walkabout.’ Captured males are indicated by parentheses. Rows that total 1 or 2 specimens are considered the rare species for this study (those with low occurrence in our samples). Bee Species* Farms Total

1 2 3 4 5 6 7 8 9 10

Family Colletidae Colletes latitarsus Robertson (1) 1 2 Family Halictidae Augochlorella aurata (Smith) 4 1 1 2 1 4 12 8 2 35 Augochloropisis (Paraugochloropsis) 1 2 3 metallica (Fabricius) Agapostemon (Agapostemon) splendens (Lepeletier) 3(1) 13(3) 7(8) 4(3) 1(3) 4(3) 2(2) 8 3 1(1) 70 Sphecodes atlantis Mitchell (2) 2 Sphecodes mandibularis Cresson 1 1 2 Halictus (Odontalictus) poeyi Lepeletier 1 21(7) 6(2) 19 1 11(1) 6 14 3 26(2) 120 Lasioglossum (Dialictus) apopkense (Robertson) 1 3 1 5 Lasioglossum (Dialictus) callidum (Sandhouse) 1 10 11 Lasioglossum (Dialictus) creberrimum (Smith) (1) 1 Lasioglossum (Dialictus) floridanum (Robertson) 15 1 1 3 2 3 25 Lasioglossum (Dialictus) longifrons (Baker) 7 1 2 3 13

Lasioglossum (Hemihalictus) lustrans (Cockerell) (1) 1

Lasioglossum (Evylaeus) nelumbonis (Robertson) 3 2 3 1 2 11 Lasioglossum (Dialictus) nymphale (Smith) 2 34 27(1) 73(1) 9 4 16 6(1) 4(1) 179 Lasioglossum (Dialictus) pectorale (Smith) 1 4 9 20 3 18(1) 6 18 1 6 87 Lasioglossum (Dialictus) puteulanem Gibbs 14 38 27 7 48 57 21(1) 43 27 33 316

Table 2-3. Continued. Bee Species* Farms Total 1 2 3 4 5 6 7 8 9 10 Lasioglossum (Dialictus) tamiamense (Mitchell) 3 1 4 Lasioglossum (Dialictus) tarponense (Mitchell) 1 1 Family Andrenidae Andrena (Trachandrena) atlantica (Mitchell) 4 4

Andrena (Archiandrena) banksi (Malloch) 3 2 1 6

Andrena (Melandrena) barbara (Bouseman and LaBerge) 1 5 2 8 Andrena (Holandrena) cressonii cressonii Robertson 1 1 Andrena (Larandrena) miserabilis Cresson 1 1 2 4

Andrena (Tylandrena) perplexa (Smith) (1) 1 Perdita (Cockerellia) bequaerti (Viereck) 3(1) 1 5 Family Megachildae Anthidiellum (Loyolanthidium) perplexum (Smith) (1) 1 Osmia (Melanosmia) sandhouseae Mitchell 1 2(3) 6 Megachile (Acentron) albitarsis Cresson 1 1 Megachile (Litomegachile) pseudobrevis Say (1) 1(1) (1) 1(1) 6 Megachile (Chelostomoides) campanule (Robertson) (1) 1 Megachile (Chelostomoides) exilis parexilis (3) 3 (Cresson)

Megachile (Chelostomoides) georgica (Cresson) (1) 1 1 3 Megachile (Xeromegachile) integrella (Mitchell) 1 1 Megachile (Litomegachile) mendica mendica Cresson (3) 1 (4) 8

Table 2-3. Continued. Bee Species* Farms Total 1 2 3 4 5 6 7 8 9 10 Megachile (Megachiloides) rubi Mitchell 1 1 Megachile (Eumegachile) sculptularis Smith 1 1 Megachile (Litomegachile) texana Cresson (1) 1(2) 1 (2) (1) 1 9 Megachile xylocopoides Smith (1) 1 Coelioxys (Haplocoelioxys) mexicana Cresson 1 1 Family Apidae Xylocopa (Schonnherria) micans Lepeletier 1 2 3(1) 1 1 1 10 Xylocopa (Xylocopoides) virginica virginica L. ** 1 ** ** ** ** ** ** 3(1) 1 6 Ceratina (Ceratinula) cockerelli Smith 2 2

Ceratina (Zadontomerus) floridana Mitchell 2 6 1 1 2 12 Nomada australis Mitchell 5 1 6 Nomada illinoensis Robertson (3) 3 Nomada imbricata Smith (1) 1 Nomada rubicunda Olivier 1(1) 2 Nomada sayi Robertson 1(1) 2 Triepiolus remigatus (Fabricius) 1 3 4 Triepiolus lunatus lunatus Say 1 2 3 Epeolus bifasciatus Cresson 1 1 Epeolus glabratus Cresson (1) 1 2 Melissodes (Melissodes) bimaculata bimaculata 2(3) (1) 2 1 2(3) (1) 2(1) 18 (Lepeletier)

Table 2-3. Continued. Bee Species* Farms Total 1 2 3 4 5 6 7 8 9 10 Xenoglossa (Eoxenoglossa) kansensis Cockerell (3) 3(3) (1) 1(13) 24 Habropoda laboriosa (Fabricius) 1 2 1 4 8 Bombus (Pyrobombus) bimaculatus Cresson 1 2 1 4 Bombus (Cullumanobombus) griseocollis (DeGeer) 1 3 1 5 Bombus (Pyrobombus) impatiens Cresson 4 2 6 Bombus (Thoracobombus) pensylvanicus (DeGeer) 2 2 Apis (Apis) mellifera L. ** ** ** ** ** ** ** ** ** ** 0 Total species per farm 13 25 16 21 20 23 29 19 14 34 Total individuals per farm 40 356 129 78 160 178 89 153 96 182 1461

Table 2-4. Principal component loadings in relation to original landscape variables. Loadings indicate a principal component score above 0.5. Micro PCs explained 51% and 79% of variance. Meso PCs explained 54% and 79% of variance. Macro PCs explained 53% and 82% of variance. *** Indicates a loading below 0.3. Principal Components Habitat Scales for Vegetation Variables Vegetation vs. Blooming Microhabitat, Crop Fields and Edge Plastic Cover vs. Plastic Understory Height .963 *** Canopy Height .821 .309 Canopy Cover (%) .805 .351 Crop Height .755 -.529 Understory Cover at Farm Edge .751 *** Bare Soil, Litter or Horticultural Plastic Cover (%) *** -.910 Blooming Cover *** .878 Natural vs. Suburban vs. Mesohabitat, Farm Center to 500m Tilled Ag Pasture Tilled Agricultural Land -.853 *** Woody Shrub .800 .495 Open Water .772 *** Suburban *** .848 Untilled open land -.435 -.819 Natural vs. Ag vs. Macrohabitat, 500m - 3km Tilled Ag Suburban Tilled Agricultural Land .935 *** Woody Shrub .850 *** Open Water -.683 .621 Suburban *** -.885 Untilled open land -.432 .761

Table 2-5. General linear mixed model output showing factors tested for relationships with Chao2 bee species richness. Error was computed using the Satterthwaite method in Statistica (Academic v.12; 2015).

Predictor Effect (fixed DF DF Error MS Error MS Effect F p Variables vs. random) (Type 1) Agriculture vs. Fixed 1 27.00 29.06 161.35 5.56 0.026 Suburban PC

Plant Species Fixed 1 27.00 29.06 227.46 7.82 0.009 Richness

Season Fixed 3 27.00 29.06 25.16 0.86 0.471

Farm (Subject) Random 27 29.06

Figure 2-1. Bee study farm locations in North-central Florida, USA. Circles represent 500 m buffers (out to 3 km) around the farm fields that were sampled for wild bees. Darker circles are located in a more natural/wooded landscape context and the lighter circles are located within a more agricultural mix.

Figure 2-2. Layout for bee bowl and vegetation sampling on a produce farm. Nine bee bowls were primed for capture, three by each of the three quadrats (i.e., one meter sampling circles) in blooming crops. Bolted lettuce and Brassicaceae are shown here on a standard10m transect.

Figure 2-3. Mean species counts from four sampling periods with bars showing standard error. Sampling periods 1 and 3 were March/April 2011 and 2012 respectively. Sampling periods 2 and 4 were May/June 2011 and 2012 (with July), respectively.

Sampling Month

Figure 2-4. Species accumulation curves for cumulative raw bee counts on ten farms (farm ID in legend at right). Total bee species detected per farm (at right of each line) include all sampling methods combined (bowls, hand-netting and walkabouts).

Figure 2-5. Wild bee species rarefaction curves estimated by farm with transects as sampling unit. Solid lines represent field samples collected in bee bowls while dotted lines are bee species estimates (Chao2; Chao 2005) and shaded areas represent confidence intervals. Each panel is listed (i.e., from top left to bottom right) in descending order of plant species richness as measured in vegetation quadrats during sampling.

Figure 2-6. The classification tree identified one principal component (Suburban vs. Pasture or DVvPST1) and another factor (Plant Species richness or Plant Types in fields) as important variables (>50% importance values) in determining wild bee species richness (Chao2 estimates). DVvPST1 expresses a gradient from suburban development with heavy tree cover to open pasture lands within 500m of the sample point (mesohabitat scale) and Plant Types is a count of the number of plant species growing in the immediate vicinity of bee bowls (micro-scale). Using this analysis, we selected DVvPST1 and Plant Types for inclusion in the final GLM (Table 2-5). N=33 represents 10 farms sampled 3 or 4 times by season (bowls relocated to random sites each time).

Mean Bee Species Richness (Chao2) Richness Species Bee Mean 0

1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 Mean Plant Species Richness in Cropped Areas

Figure 2-7. Scatterplot of Chao2 bee species richness against in-crop plant richness with curved lines representing confidence intervals. Bee richness rose significantly as plant richness increased in crop field quadrats.

Mean Bee Species Richness (Chao2) SpeciesBee Richness Mean 0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 Suburban vs. Pasture in Buffer 1 (PC 4)

Figure 2-8. Scatterplot of Chao2 mean species richness showing seasonal sample variation in on 10 farms against the mesohabitat scale PC, Suburban vs. Pasture (within the first buffer). Without the outlying variables on the left (representing Farm #10) the slope of the regression line is lost.

CHAPTER 3 POLLEN COLLECTION BY WILD BEES ON PRODUCE FARMS IN NORTH-CENTRAL FLORIDA

Summary

Increasing reliance on native, wild bee faunas for crop pollination may be necessary depending on the future of the honey bee industry, but little is known about pollination services provided by wild bee communities. I took a first step toward understanding the crop pollination potential of the wild bee community in North-central

Florida by describing the pollen community being moved around largely-sustainable farms by these bees. Produce farms in the region grow a variety of crops requiring pollination. I collected and identified wild bees active on a selected set of ten farms in

Alachua, Gilchrist, Bradford, and Union counties over two years and extracted pollen from each bee’s exterior and scopae. 158 wild bees were captured by hand and identified to 23 taxonomic species. About 31,000 pollen grains from bees were prepared by acetolysis, slide mounted, identified by morphospecies, and identified down to taxonomic family by palynology experts. I determined that three wild bee families carried six out of seven families of available crop pollen and a variety of non-crop plant families.

Halictus poeyi was the main carrier for this study, even given its small-medium size of

11 mm, it is a common, socially nesting wild bee that moves a lot of crop and non-crop pollen. Included among the chief carriers of crop pollen were Melissodes communis,

Habropoda laboriosa, and Bombus griseocollis. Wild plant pollen carriers were mostly

Andrenidae, a family on which I detected no crop-only pollen families. Wild bees pollen- carrying activities in this region are likely to be important to pollination of crops as well as to diverse non-crop plant species on farms. This study lays a foundation of

information on pollen carrying, a necessary precursor to pollination, for future studies of wild bee crop pollination services.

Introduction

Wild bee species are known to be important pollinators for agricultural fruits and vegetables (e.g. Habropoda laboriosa on blueberry, Rogers et al. 2014; Osmia aglaia on red raspberry and blackberries, Cane 1988; Bombus spp. on cranberry, Broussard et al. 2011; and Xenoglossa spp. on squash, Hall 2010). This suggests that wild bees may compensate for the pollination services lost to farmers in areas where European honey bees have declined (Rader et al. 2013, Winfree et al. 2008). For example, Rader et al.

(2013) found that pollination services from managed honey bees were predicted to decline under climate change, but these decreases would be offset by increases in the pollination provided by wild taxa. While wild bee taxa may also decline due to climate change, the diversity of responses by multiple taxa would likely buffer aggregate pollination services. The first step in determining whether there are significant wild pollinators in an area is to assess the target pollen collected by the local bee community in farmland areas (as did Alves et al. 2014 and Beil et al. 2008).

Pollen-carrying by wild bees does not equate to pollination of the plant species whose pollen the bees carry. Pollen collection’s purpose, from the bee’s perspective, is to gather food stores for larval bees (Eckhardt et al. 2014, Thorp 2000); pollination is a by-product. Few wild bees are pollen specialists, i.e., they do not visit only a single plant (crop or non-crop); foraging wild bees visit a diversity of non-crop plant types (e.g.,

Beil et al. 2008). Pollination is also dependent on the morphology of both flower and bee, and the bee’s behavior in and around the flower. For example, according to Thorp

(2000), some bees exhibit special behavioral movements to enhance the uptake of

pollen, including vibration of the flower. And, bees have specialized appendages and hair to help with the recovery and transport of pollen (Thorp, 2000).“With so many local species on local, sustainable farms (Chapter 2; Hall and Ascher 2011), sizes (Table 3-

2), and flower-visiting behaviors (Thorp 2000) represented among wild bees, the bees may perform well as pollinators (Winfree et al. 2008, Lowenstein et al. 2015, Mallinger and Gratton 2015). If a wild bee can serve as a pollinator for a given plant, however, it must carry that species’ pollen.

In this study, I focused on illuminating wild bee-facilitated pollen movement in cultivated fields and field edges of small sustainably managed produce farms.

Identification of which wild bees might be contributing to crop pollination in these fields was my primary goal. Previous studies (Biel 2008) and (my) preliminary work on pollen from wild bees indicates that some bees carry multiple pollen types at the same time, including non-crop pollen. Therefore, in conjunction with an assessment of the native bee fauna of North-central Florida farms, I collected the pollen from wild bees. In this study I characterized the taxonomic families of pollen that wild bees carried as they foraged on small, low-pesticide produce farms in the region.

Methods

Study System and Strategy

The North Central Florida terrain is part of the Southeastern United States

Coastal Plain, which comprises primarily loose sediments that skirt the Atlantic and Gulf coasts from the Mid-Atlantic States through Texas. The ten study farms, selected in

Alachua, Bradford, Gilchrist and Union Counties, are part of a mix of Florida’s highlands and flatwood-dominated lowlands (Whitney et al. 2004). The landscape surrounding the study farms is dominated by pine and hardwood woodlands (including pine plantations)

and tilled and pastoral agricultural land, but also included housing subdivisions and suburban land uses (Florida Natural Areas Inventory 2010). Selected farms fell within a range of landscape compositions from mostly natural vegetation (pine or hardwood forest cover) to mostly agricultural (croplands and pastoral) (Figure 3-1), and were similar in insect-attractive crops grown and crop field management. In particular, all farms were dedicated to low or no pesticide use and all were irrigated as described in

Table 3-1.

The bee species in this region (N= ~300) other than European honey bees (Apis mellifera) are typically referred to as wild, native, or solitary bees. Here, all such non- honey bees will be referred to as wild bees, and include both native and solitary bee species even if they are not native and are social (for the taxonomy of Florida bees see

Pascarella 2006, Hall 2014, Mitchell 1960,1962, and USGS 2015; for behavior as it relates to sociality see Bohart and Nye 1956, Wilson 1971).

I conducted a descriptive study of bees and pollen on small produce farms.

Farms were selected based on low or no pesticide use, and having multiple bee- attractive crops growing during the field season (e.g., squash, blueberries, peppers, etc.). Assistants and I hand-collected (by insect net) wild bees by checking all flowering plants in the immediate vicinity of agricultural fields for bees rather than sweeping up the ones that were most commonly available on blooming crops during each visit. We conducted these “walkabouts” from April to early July in 2011, October 2011, and again from April to early July in 2012.

Bee Collection

We caught a total of 158 pollen-carrying wild bees in insect nets, and placed them in killing jars. I wiped loose pollen from the killing jar with dry paper towels when it

was visible in order to limit the potential for cross-contamination of bee specimens and associated pollen. Wiping the tubes removed excess pollen shed by heavily-pollen laden bees, while the pollen we would later sample in the lab was packed into pollen scopae. According to Thorp (2000), most pollen removal (from flowers) by bees is passive, especially when their foraging focus is nectar rather than pollen. Pollen is collected for feeding bee offspring, and the majority of bees have specialized structures for collection and transport of pollen. In this study we focused on pollen that had already been transferred to each bee’s transport structures and remained there until pollen recovery in the lab.

We spent a cumulative total of about thirty-seven hours capturing bees by hand over two field seasons. Experienced wild bee collectors conducted walkabouts during each farm visit. If more than one experienced netter was working, we set off in different directions and spent about 20 minutes looking for bees (e.g. two experienced netters would spend a total of about 40 minutes). We targeted bees that looked like they were carrying pollen, but also caught many small bees on which pollen in the scopae was only visible with microscopic examination. European honey bees (Apis mellifera) were not collected, and only a fraction of common carpenter bees (Xylocopa virginica) were collected when encountered because they tended to foul the collection tubes with regurgitated nectar. Crop types and wild plants that commonly hosted foraging bees on the ten farms were also recorded on walkabouts.

Pollen Preparation, Photography, and Counts

I based methods to prepare pollen on those described by Jarzen (2008). I placed pinned bees separately in standard 15cc centrifuge tubes, immersed in 5% potassium hydroxide (KOH), and warmed to 90° C for two to three minutes to clear the

pollen of surface oils. Bees were processed in sets of six, i.e., one per tube. After agitating for 10-15 seconds, bees were rinsed, re-labeled, and stored. The warm KOH removed the surface pollen from the bees, notably, that stored in the pollen scopae, and also pollen dusted on and not groomed off by the bee, but not internal pollen from the bees’ crops. I centrifuged the solution (without bees) at 1500 rpm for two-three minutes, decanted the KOH, and washed the pollen with distilled water, centrifuged it, and decanted it twice more. The pollen was rinsed with glacial acetic acid, centrifuged for two to three minutes and decanted in preparation to be acetolyzed, a process that strips protoplasm from within the pollen grain and an oily coat from the outside the wall of a pollen grain, leaving a darkened wall for easier identification (Jarzen 2008).

The acetolysis mixture consists of one part concentrated sulfuric acid and nine parts acetic anhydride. Approximately 50 ccs of this mixture was added to each pollen sample, and samples were heated to 90°C for three to five minutes to fully remove the internal contents of each pollen grain. Checking the pollen under the microscope during acetolysis improved the quality of the pollen preparations. After rinsing, centrifuging, and decanting, I prepared samples by additional rinsing of glacial acetic acid, distilled water (2x), then stabilized the solution with a 50% solution of glycerin and distilled water. After the final decanting, I left the centrifuge tubes to rest upside-down overnight to drain off any remaining water from the sample.

The following morning, I added three to six drops of heated glycerin jelly to the sample-bearing centrifuge tubes depending on the amount of pollen residue in each tube (e.g. more jelly for more pollen). I heated the residue and warm glycerin and placed two drops on the center of a pre-cleaned, heated, and marked microscope slide.

I covered the sample with a cover slip, removed bubbles, and left it to settle and dry for

24 hours before sealing with Sally Hansen “Hard-As-Nails,” clear butyl acetate-based fingernail polish. Slides were labeled with farm identity, bee database identification number, and date of collection. I made two slides per sample, unless the pollen amount was limited, as it often was on small bees.

I trained two assistants to photograph and count pollen in shifts using an

Axiocam microscope and camera by Zeiss with Axiovision software (AxioVs 40 V

4.5.0.0, copyright 2002-2005) to determine scale. We counted up to 300 pollen grains per slide (i.e., producing a right-censored data set), and we used 40x magnification to photograph pollen types encountered. Counts were conducted as miniature, unmarked transects, comprising no more than three horizontal passes in non-overlapping visual fields on each slide. Pollen morphotypes, i.e., differently appearing pollen types, were submitted to two pollen experts, Dr. David Jarzen, formerly of the Palynology

Department at UF, and Dr. Vaughn Bryant, Jr. of Texas A&M, Department of

Anthropology, for identification to taxonomic family. The pollen families were divided into data analysis categories related to the different kinds of plant families represented on farms: “crop pollen,” “non-crop pollen,” or “either” (i.e., plant families with both cultivated and weedy plants included).

Analytical Methods

Because big bees have a larger surface area and pollen scopae than small bees, pollen abundance from big bees was over-represented in the raw samples. Also, capping the pollen counts at 300 grains per bee created a uniform distribution of sample amounts that did not tell us much about variation between bees, so I used a simple weighting method (i.e., total pollen carried/ average size of bee carrying species) to

emphasize pollen carried by small bees over that carried by large bees (the average size of the wild bee species came from Mitchell, 1960). Weighting did not affect the species richness of pollen in the samples; just their relative proportions.

Differentiation beyond the family level was sometimes possible for pollen, but was generally beyond the scope of this study, so several types of pollen were classed as “either.” Pollen in “Either” families could be crops or non-crop plants. The brassicaceae family, for example, is represented both by wild varieties of Brassica oleracea that can be pest plants on farms, and their crop relatives: collard greens, kale, broccoli and cabbage.

I used SPSS v. 23 to produce descriptive graphics of pollen and bee results.

I present graphical representations of pollen collected by wild bees, and the bee species

(and families) that carried them, augmented by a table with pollen families identified for each bee species collected. I also present common farm characteristics, the blooming crops observed during walkabouts, and species accumulation curves for pollen morphospecies and pollen-carrying bee species sampled for pollen.

Results

Vegetation

The dominant blooming crops across all farms and sampling periods were squashes and melons (Cucurbitaceae), eggplants, tomatoes and peppers

(Solanaceae), followed by other plant families, including a number of Asteraceae intercrops, sunflowers and other largely commercial ornamental flowers, flowering broccoli, mustard greens, chard and arugula from the Brassicaceae family (Figure 3-4).

Bees

Of 338 bees collected by hand during the bee study (Chapter 2),158 bees were carrying pollen in farm fields. These 158 represent 35 species from five bee families

(Table 3-2). The largest numbers of detected bees were Halictus poeyi (n=54),

Lasioglossum pectorale (n=10), and Lasioglossum puteulanum (n=8). Pollen was detected on one male among these bees. An anomalous Melissodes communis male was dusted with pollen from Solanaceae and three other pollen families. The diversity study (Chapter 2) found only 12.5% males among 1239 bees (Chapter 2) where sex was recorded, and female bees are the active collectors of pollen, so low numbers of pollen-carrying male bees were expected. Table 3-2 is a listing of sampled wild bees, the pollen families they carried, and proportions of crop or non-crop pollen found on the species as a group.

Pollen samples

I detected 41 morphotypes and 15 pollen families that were viewed microscopically and 31,573 pollen grains were counted. The most commonly found pollen across all bee species and samples were Brassicaceae (mustard family) followed by Malvaceae (mallow family), Plantaginaceae (plantain family), and eleven other pollen families (Figure 3-5). Crop pollen was carried by three families of bees (Figure 3-5), and non-crop pollen was carried by four out of five bee families sampled. “Either” pollen was carried by all five bee families. After weighting, crop pollen displayed similar proportions to the two other pollen classes carried by the five bee families (Figure 3-8) because smaller bees were also crop pollen carriers. The four species that carried the most pollen were, in descending order, Bombus griseocollis (60% Cucurbitaceae of 900 grains), Habropoda laboriosa (50% Ericaceae of 900 grains), Melissodes communis

(25% Cucurbitaceae of 856 grains), and Xylocopa virginica (13% Ericaceae of 900 grains); (Table 3-2). Figure 3-6 indicates which plant families fell into the pollen classes that wild bees carried. There are only two pollen families in the crop class, nine families in the non-crop class, and four in the “either” class, i.e., families that have both crop plants and non-crop plants in central Florida. Species accumulation curves for both bees and pollen types did not level out, suggesting that more intensive sampling would have been needed to capture all pollen and bee species from the sites. Bee species that were carrying the three crop pollen classes (Figure 3-9) were all outnumbered by

Halictus poeyi, a common bee on produce farms. An unusual find was a Triepeolus remigatus with pollen. A parasite on other species of wild bee and lacking pollen scopae, this Triepeolus female was not expected to have carried the 196 grains of mixed Asteraceae (morphospecies one and three) and Brassicaceae that I detected.

These common pollens could have contaminated the specimen from other wild bees collected that day (6/22/12) or T. remigatus may have been foraging for nectar in the same blooming plants as the other species captured that day (i.e., Halictus poeyi, and

Lasioglossum puteulanum). With the exception of Fabaceae, all of the families of crop plants available to bees (Figure 3-3) were present in pollen samples taken (Figure 3-6).

Discussion

How Many Wild Bees Carried Pollen?

The pollen-carrying wild bees in Table 3-2 represent one third of the raw bee species richness found in our study of bee species richness (Chapter 2). For example, pollen carrying Halictus poeyi were 54 of 120 H. poeyi specimens (45%), and 16% of the 338 specimens collected by hand among the 1,461 wild bees collected by all methods for species richness totals, and 1/65th of total species caught by all methods.

Wild bees captured in bee bowls were sometimes observed with residual pollen, but the previously-immersed, possibly mixed samples from multiple bees caught in the bowls were not analyzed. So, while I recorded that 47% of hand captured bees were carrying pollen, more bees may have entered the bee bowls laden with pollen, but we cannot know that number because bee bowls made pollen recovery impractical and differentiation among pollen samples impossible. Bees visit flowers for both pollen and nectar (Bohart and Nye 1956), and it is reasonable that about half the bees collected by hand were foraging for nectar, or were captured while returning from dropping off pollen at the nest, or were males.

Crop Pollen Carriers

The bee that dominated crop pollen movement after the weighting adjustment

(Figure 3-9) was Halictus poeyi carrying 4% (i.e., 516 grains 12,891 detected on individuals of the species) of all five morphospecies of Cucurbitaceae), followed by

Bombus griseocollis, and Habropoda laboriosa. Considering H. poeyi’s small size and relative abundance of 34% in pollen-carrying bee collections (n= 158 pollen carrying bees total), this species moves a lot of pollen overall. H. poeyi, was responsible for carrying almost half of the observed pollen from each of the three pollen classes: crop, non-crop, and either (Table 3-2). This species was well represented in the overall study because it was common from spring through summer and found foraging on multiple flower types. H. poeyi. is eusocial like Apis mellifera, with a caste system governing tasks in a communal nest (Dunn 1998, Wilson 1971). 96% of the pollen we recorded from the bodies of H. poeyi specimens was either non-crop pollen or from one of the

“Either” families like Solanaceae which encompasses both non-crop species and important crops (e.g. tomato, peppers, and eggplant were grown on several of the study

farms), so the pollen count for crops could potentially be higher from all of these wild bee species. We consider these numbers to be conservative, since we did not identify pollen down to species or varietal levels in this study, and some crop pollen are encompassed in the “either” category. Three species of wild bee, Halictus poeyi,

Bombus griseocollis, and Habropoda laboriosa all carried proportionally more crop pollen than the other nine crop pollen-carrying species (Figure 3-7).

I collected anecdotal information by finding burrows occupied by H.poeyi and H. laboriosa on and off farms. There was an H. poeyi nest on farm four (Figure 3-1) that I found during walkabout sampling for bees (Chapter 2). Several bees of the species came and went from a small hole in a grassy, periodically-mowed pathway between cropped areas near the edge of the farm. The one H. laboriosa individual I encountered at a nest was nesting in sandy soil under a few inches of oak leaf litter on the sun- dappled edge of a mixed pine and oak woodland in a power line right-of-way through a natural area. I could find little information published on how to encourage nesting by wild bees like these two species and Bombus griseocollis. More work is needed on topics like nest depth, soil types and temperatures, and the nesting parameters that these bee species find acceptable. Detailed nesting information (e.g. nest depth, soils, configuration, and number of individuals for eusocial species) is available for another eusocial Halictus sp. from Utah (Albert and Packer 2013) a Colletes sp. (López-Uribe et al. 2015), a Hoplitis sp. (Muller 2015), and others, but general studies from other locales may not be relevant to wild bee nesting choices here.

Non-Crop Pollen Carriers

Wild bees by weighted and non-weighted measures carry mostly non-crop and

“either” pollen. In terms of sheer quantity, the generally large-bodied Apidae family

species carried the most pollen, but Andrenidae and Halictidae species, especially H. poeyi, carried the most weighted pollen. 96% of what H.poeyi carried was classified as non-crop or “either.” Brassicaceae was the family of plants that wild bees appeared to rely on most. Bolted Brassicaceae plants from the previous season were some of the first and most abundant flowers on farms at the beginning of sampling in March 2011 and 2012, and were a major source of pollen on bees, as evidenced by Figure 3-5 which also indicates that the pollen was carried disproportionately by small bees. Non- crop “specialists” were the Andrenidae (0% crop pollen), and Megachilidae (0.063% crop pollen). Pollen families carried by these non-crop carriers included Lythraceae

(from crepe myrtle shrubs and relatives), Passifloraceae which is a crop in some places

(Junqueira 2012) but was a weedy species on farms that hosted it here in north-central

Florida, and Malvaceae (Mallow family). Where passion fruit is grown commercially (as it is in Florida), carpenter bees (Xylocopa sp.) can be managed on farms with habitat enhancement like lots of supplemental, dead wood (Junquiera et al. 2013) and captive rearing techniques may be developed in the future (Kesear 2010).

Little information is available in the literature on nesting preferences for most of the ground-nesting species, instead management recommendations tend to focus on techniques that supply diverse flowers along field margins and as intercrops and cover crops (SARE 2015). By increasing the local species richness of plants, researchers have found that bee species richness can be increased as well (Benton 2003,

Holzschuh 2007), as we found also in Chapter 2. Intercropping of marketable cut flowers is a strategy that farmers use to increase bee species richness since they can also profit from selling cut flowers. Both of the highest bee species richness farms

(Farm #7 and Farm #10) in my earlier study (Chapter 2) grew flower cultivars for sale.

Success of these biodiversity increasing techniques may depend on the diversity of flowers planted (Wood et al. 2015)

Management Perspectives and Future Directions

More investigation is needed into the ecology of wild bees (Chapter 2), especially within the context of their beneficial interactions with small farms. My work here suggests that crop pollen alone does not support the needs of our pollen-carrying wild bee species, as even bees carrying large amounts of known crop pollen were also carrying non-crop pollen. Research on what makes up good larval diets for wild bee species (as in Eckhardt 2014 for Osmia cornuta) would help to determine what kinds of border plantings and intercrops can best support crop pollen carriers.

Based on my results, we should also investigate the pollen preferences and foraging strategies of Halictus poeyi which, though small, proved to be a workhorse for pollen movement in this study. As a eusocial bee, it may have some potential for management, although its ground-nesting habit likely means it has to be managed in- situ. Habropoda laboriosa, a solitary ground nester, and a pollinator for the important blueberry crop in north-central Florida (Williamson et al. 2015) may have habitat preferences that can be enhanced in the vicinity of blueberry farms. I know from

Chapter 2 that mesohabitat scale pastureland encourages bee richness, and investigating H. laboriosa’s nesting preferences may give us an idea one mechanism, i.e., nesting, that may support that relationship. Bombus griseocollis is a social or family nester with solitary queens that start nests each year for their offspring above and below ground in dead tree cavities, old rodent nests, old bird nests, and similar locales

(Hatfield et al. 2015). Management with artificial nests may be possible for this species

as with other Bombus species (Hatfield et al. 2012). Melissodes communis, the common long-horned bee, though it has been included in numerous pollination studies, does not have well documented nesting habits.

My study results concern pollen movement by wild bees on farms. Future pollination studies will focus on flowers and the bees that visit them (e.g. excluding some pollinators, admitting others, and monitoring fruit production from pollinated flowers as in Kearns and Inouye, 1993). Understanding the pollination effectiveness of different species of wild bees is the next step in investigating the pollination services provided by wild bee communities.

Table 3-1. Management characteristics of the ten study farms (1-10) on which pollen-carrying bees were colected. Farms were all irrigated with low to no pesticide use. Criterion Description 1 2 3 4 5 6 7 8 9 10 Use of horticultural Plastic at plant bases for weed and plastic moisture control. X X X X X X

Low pesticide use Pesticide use limited to localized fire ant treatment X X X X X X X X X X

Use of composted Soil nutrient and water retention manure improvement X X X X X X X

Structures and Bluebird and/or purple martin plantings for houses beneficial insects X X X X X and/or birds

Cultivated area of 0.50 > 0.50 ha hectares or more X X X X X X X X

Irrigation water Drip lines with black plastic for conservation irrigation present in most crops X X X X X X X X X X

Honey bee hives At least one active hive on the present farm X X X X X X X X

Table 3-2. Family and species of wild bees caught carrying pollen on produce farms and the morphospecies of pollen (raw counts) they carried. Pollen morphospecies are identified by these abbreviations in the table: Asteraceae (Ast), Convolvulaceae (Con), Brassicaceae (Bra), Ericaceae (Eri), Fabaceae (Fab), Geraniaceae (Ger), Lythraceae (Lyt), Oleacaeae (Ola), Onagraceae (Ona), Passifloraceae (Pas), Plantaginaceae (Pla), Rosaceae (Ros), Rubiaceae (Rub), Solanaceae (Sol), and UnIdentified (Unk). The first three letters of the morphospecies abbreviations represent the plant family to which it was assigned by palynologists, and the numbers that follow indicate it was the Nth member of the plant families. If wild bees were foraging on a known plant when captured that plant family is listed in the last column of the table. Mean Pollen Proportion Bee Pollen Proportion Proportion Bee Collection Bee Family Bee Genus Bee Species Bee Size Count Non-crop Count Morphospecies Crop Pollen Either Plant Family (mm) Total pollen

Andrena banksi 11 3 540 Bra, Lyt, Pas 0 0.22 0.78 Unk Andrenidae Andrena barbara 12.5 1 151.5 Ast1, Lyt 0 0.01 0.99 Cuc Andrena cressonii 9.5 1 300 Bra 0 0 1 Unk Andrena miserabilis 8.2 2 600 Bra, Lyt 0 0 1 Unk Perdita bequaerti 8 1 37 Ast1, Bra, Pla 0 0.96 0.04 Unk Eri Bombus bimaculatus 19 2 600 Unk5, Eri 0.02 0.98 0

Ast1, Bra, Lyt, Pas, Rub1, Sol, Ros Bombus griseocollis 22 3 900 Unk1, Ast2, 0.60 0.06 0.33 Cuc Cuc2, Lyt2, Apidae Unk2, Rub1 Bombus impatiens 19 1 300 Ast1, Sol 0 1 0 Unk Ceratina floridana 7 1 300 Ast1, Ast3, Bra 0 0.15 0.85 Unk Eri, Bra, Lyt, Habropoda laboriosa 12.5 3 900 0.50 0.002 0.49 Eri Ast2, Rub1 Ast1, Ast2, Ast3, Melissodes Unk 13.5 1 223 Cuc Cuc, Eri, Lyt, Sol

Table 3-2. Continued. Mean Pollen Proportion Bee Family Bee Pollen Proportion Proportion Bee Collection Bee Genus Bee Species Bee Size Count Non-crop Count Morphospecies Crop Pollen Either Plant Family (mm) Total pollen Melissodes bimaculata 14 1 300 Rub1, Unk2 0 1 0 Cuc Sol, Ast1, Eri, Bra, Ast2, Ast3, Rub Melissodes communis 13.5 5 856 0.25 0.38 0.37 Cuc, Lyt, Ona, Cuc Pas Apidae Triepiolus remigatus 13 1 196 Ast1, Ast3, Bra 0 0.98 0.02 Unk Xylacopa micans 17 1 300 Ast1, Bra 0 0.01 0.99 Unk Bra, Pas, Sol, Ast1, Eri, Bra, Xylocopa virginica 21 3 900 Ona, Rub1, 0 0.06 0.94 Pas Unk1, Ast1, Ast2, Lyt Colletidae Ast1, Bra, Lyt, Colletes latitarsus 11 1 219.5 0 0.70 0.30 Unk Sol, Unk3, Unk5 Ast, Bra, Ona, Cuc Halictidae Agapostemon splendens 10 5 1246 Pas, Lyt, Unk, 0 0.40 0.60 Bra Ole, Ona Bra, Ast1, Cuc5, Augochlorella aurata 5.5 2 652 0.0008 0.005 0.99 Unk Poly, Lyt, Lyt3

Table 3-2. Continued. Mean Pollen Proportion Bee Pollen Proportion Proportion Bee Collection Bee Family Bee Genus Bee Species Bee Size Count Non-crop Count Morphospecies Crop Pollen Either Plant Family (mm) Total pollen Ast3, Ast4, Bra, Pol, Unk1, Unk5, Pla, Ast2, Cuc2, Eri, Ger, Lyt, Ast1, Unk6, Mal, Ros Halictus poeyi 11 54 12891 Ole, Rub1, Unk7, 0.04 0.69 0.27 Ast Cuc, Unk8, Cuc3, Unk Cuc4, Ole2, Cuc5, Sol, Ros2, Ros1, Lyt2, Pas, Rub1, Ona

Lasioglossum Unk 8 1 300 Bra, Pla Bra Bra, Lyt, Pla, Lasioglossum apopkense 4 1 34 0 0.03 0.97 Unk Unk9 Halictidae Lasioglossum callidum 6 1 25 Bra, Pla, Unk9 0 0.04 0.96 Unk Ast1, Bra, Con1, Lasioglossum floridanum 5.7 4 382 0 0.01 0.99 Unk Lyt, Unk7 Lasioglossum nymphale 4 1 179 Cuc, Bra, Lyt, Pla 0.01 0.04 0.99 Unk Ast1, Unk9, Bra, Pla, Ast2, Eri, Bra Lasioglossum pectorale 6 13 2573 0.003 0.15 0.85 Ger, Lyt, Ast3, Unk Pas, Unk5 Ast1, Con1, Bra, Lasioglossum puteulanum 8 7 1509 Lyt, Pla, Eri, 0.02 0.015 0.97 Unk Ast2, Con1, Unk1 Ast1, Ast3, Bra, Lasioglossum reticulatum 8 4 1025 Lyt, Pla, Ast1, 0 0.08 0.92 Unk Pol, Unk10 Lasioglossum tamiamense 4 1 57 Unk11 0 1 0 Unk

Lasioglossum Unk 1 0

Table 3-2. Continued. Proportion Proportion Mean Pollen Proportion Bee Pollen Crop Non-crop Bee Collection Bee Family Bee Genus Bee Species Bee Size Count Either Count Morphospecies Pollen pollen Plant Family (mm) Total

Hoplitis Unk 11 1 300 Ast2, Bra Bra Megachile albitarsis 12.5 1 222 Ast1, Lyt, Pla 0 0.47 0.53 Unk Megachile georgica 12.5 1 112 Ast2, Bra, Lyt 0 0.06 0.94 Unk Ast1, Ast3, Bra, Megachilidae Megachile mendica 12 2 359 Lyt, Ast2, Cuc, 0.003 0.94 0.064 Fab Unk2,Unk3,Unk4 Ast1, Ast2, Bra, Megachile texana 12.5 1 300 0 0.14 0.87 Unk Mal, Pas, Unk5 Ast3, Ast4, Bra, Lyt, Ole, Unk2, Osmia sandhouseae 9.5 2 602 0.06 0.78 0.16 Unk Unk5, Ast1, Eri, Rub1 Pla, Lyt, Ast1, Unidentifiable Unk Unk Unk 2 1846 Bra, Ast1, Bra, 0.11 0.09 0.80 Bra

Ros2

4 2

10 6

1 3 8

7 9 ×

Figure 3-1. Bee study farm locations (1-10) in North-central Florida, USA. Circles represent 500 m buffers (out to 3 km) around the farm fields that were sampled for wild bees.

Figure 3-2. Pollen species (above) and wild bee species (below) accumulation curves that show that species richness in both novel pollen and previously unseen wild bees continued to increase strongly as we collected samples. They indicate that we did not approach a point where the curves would level off, which they would if we were not finding any more novel species with each sample.

Figure 3-3. Dominant blooming crops on produce farms from two sampling years (five sampling periods) according to walkabout observations. The majority of crops were Cucurbitaceae (squash family) and Solanaceae (nightshade family, e.g., eggplant, tomatoes, and peppers). The “Other” category (third largest) included okra, onions, and flowers grown primarily for sale.

Figure 3-4. The pollen families by sample period (1=March/April 2011, 2=May/June 2011, 3= October 2011, 4= March/April 2012, 5= May/June 2012 represented by total pollen grain counts that were capped at 300 grains per sample slide (600 per bee) . The most pollen recovered from bees was in sample periods 1 and 4 (Early Spring, light grey in figure). Low pollen numbers in the fall (sample period 3, white in figure) were partially the result of limited sampling at that time. In the second year, especially, (sample period 5, dark grey) relatively fewer pollen families were detected in June and July 2012.

Figure 3-5. Total number of pollen grains counted per bee by pollen family. Legend patterns indicate pollen class (Crop, Non-crop, or Either). The boxplots represent raw counts that were capped at 300 grains, but were typically from two sample slides.

Figure 3-6. Pollen classes (Crop, Non-crop, or Either) carried by the bee families after weighting by size (i.e., pollen carried/size in mm) to emphasize small bee efforts. The counts from two slides were summed for the total. The five bee families are ANDR=Andrenidae, APID=Apidae, COLLET=Colletidae, HALIC=Halictidae, and MEGA=Megachildae). The “Either” pollen class describes plant families that contain both crops and non-crops. Subcategories in bars represent the contributions of each species to the bar.

3 1 3 5

2 8 2 6 2 4 2 3

Figure 3-7. The wild bee crop pollen carriers and the amount of pollen (weighted) that they carried. Numbers above the bars indicate the number of wild bees collected of that species. AUAU= Augochlorella aurata, BOBI=Bombus bimaculatus, BOGR= Bombus grisescens, HALA= Habropoda laboriosa, HAPO= Halictus poeyi, LANY= Lasioglossum nymphale, LAPE= Lasioglossum pectorale, LAPU= Lasioglossum puteulanum, ME1= Unidentified Melissodes sp., MECO= Melissodes communis, OSSA= Osmia sandhouseae, XYVI= Xylocopa virginica.

CHAPTER 4 ANNOTATED, ILLUSTRATED CHECKLIST OF POLLEN–CARRYING WILD BEES OF NORTH-CENTRAL FLORIDA PRODUCE FARMS

Introduction

Wild bee species are known crop pollinators, and others have been observed to pollinate wild plants. But, there is still much to learn about the ecology of wild bees, their habitats, and their contribution to pollination on small farms in Florida and across North

America. I undertook a study of wild bee species richness and the influences of potential bee habitat at multiple scales, and had the opportunity to gain additional insight into what the bees were actually doing on working produce farms by looking closely at the pollen that a fraction of wild bees were carrying.

Methods

My assistants and I caught wild bees by hand, using insect nets, on 10 small produce farms in North-central Florida in 2011 and 2012 (Figure 4-1), walking the farms checking flowering plants for bees for about 30 minutes per visit. After identifying all the bees that were carrying pollen in farm fields I took the pollen off of their bodies, chemically processed it, and identified it with the help of two pollen experts, Dr. David

Jarzen, formerly of UF’s Department of Palynology and Dr. Vaughn Bryant of the

Anthropology Department at Texas A&M (Methods for Chapter 3). Assistants and I counted more than 31,000 recovered pollen grains for relative abundance, using a cap of 300 pollen grains per slide to better distribute our limited time over samples from 158 bees. Large bees carried the most pollen, so their counts were always capped, while samples from smaller bees did not always reach the cap.

Results

Table 4-1 and Figures 4-2 through 4-55 display pollen counts and pollen proportions found on each species of wild bee, and photos of the bees plus the pollen grains from each family of plants that the bees were carrying. Numbers of bees and pollen grains per sample are noted in the explanatory pages after each photo group.

Photo credits are attributed in each bee species-based composition of photos and in figure legends.

Table 4-1. Family, genus, and species of wild bees that were carrying pollen on produce farms. Pollen morphospecies are identified by these abbreviations in the table: Asteraceae (Ast), Convolvulaceae (Con), Brassicaceae (Bra), Ericaceae (Eri), Fabaceae (Fab), Geraniaceae (Ger), Lythraceae (Lyt), Oleacaeae (Ola), Onagraceae (Ona), Passifloraceae (Pas), Plantaginaceae (Pla), Rosaceae (Ros), Rubiaceae (Rub), Solanaceae (Sol), and UnIdentified (Unk). The first three letters of the morphospecies abbreviations represent the plant family.

Bee Bee Collection Bee Family Bee Genus Bee Spp Bee Size Pollen Count Pollen Morphospecies Count Plant Family (mm) (total) Andrena banksi 11 3 540 Bra, Lyt, Pas Unknown

Andrena barbara 12.5 1 151.5 Ast1, Lyt Cucurbitaceae

Andrenidae Andrena cressoni 9.5 1 300 Bra Unknown

Andrena miserabilis 8.2 2 600 Bra, Lyt Unknown

Perdita bequaerti 8 1 37 Ast1, Bra, Pla Unknown

Bombus bimaculatus 19 2 600 Eri, Unk5 Ericaceae Ast1, Ast2, Bra, Cuc2, Lyt, Lyt2, Pas, Cucurbitaceae Bombus griseocollis 22 3 900 Rub1, Sol, Unk1, Unk2 Rosaceae Bombus impatiens 19 1 300 Ast1, Sol Unknown

Ceratina floridana 7 1 300 Ast1, Ast3, Bra Unknown

Habropoda laboriosa 12.5 3 900 Ast2, Bra, Eri, Lyt, Rub1 Ericaceae Apidae Melissodes bimaculata 14 1 300 Rub1, Unk2 Cucurbitaceae Ast1, Ast2, Ast3, Bra, Cuc, Eri, Lyt, Ona, Cucurbitaceae Melissodes communis 13.5 5 856 Pas, Sol Rubiaceae Triepeolus remigatus 13 1 196 Ast1, Ast3, Bra Unknown

Xylocopa micans 17 1 300 Ast1, Bra Unknown Ast1, Ast2, Bra, Eri, Lyt, Ona, Pas, Sol, Xylocopa virginica 21 3 900 Passifloraceae Unk1

Table 4-1. Continued. Bee Size Pollen Count Bee Collection Bee Family Bee Genus Bee Species Bee Count Pollen Morphospecies (mm) (total) Plant Family

Colletidae Colletes latitarsus 11 1 219.5 Ast1, Bra, Lyt, Sol, Unk3, Unk5 Unknown

Cucurbitaceae Agapostemon splendens 10 5 1246 Ast, Bra, Lyt, Ole, Ona, Pas, Unk Brassicaceae

Augochlorella aurata 5.5 2 652 Ast1, Bra, Cuc5, Lyt, Lyt3, Poly Unknown

Ast1, Ast2, Ast3, Ast4, Bra, Cuc, Cuc2, Rosaceae Cuc3, Cuc4, Cuc5, Eri, Ger, Lyt, Lyt2, Mal, Halictus poeyi 11 54 12891 Asteraceae Ona, Ole, Ole2, Pol, Pla, Pas, Ros1, Ros2, Unknown Rub1, Sol, Unk1, Unk5, Unk6, Unk7, Unk8

Lasioglossum apopkense 4 1 34 Bra, Lyt, Pla, Unk9 Unknown

Lasioglossum callidum 6 1 25 Bra, Pla, Unk9 Unknown Halictidae Lasioglossum floridanum 5.7 4 382 Ast1, Bra, Con1, Lyt, Unk7 Unknown

Lasioglossum nymphale 4 1 179 Bra, Cuc, Lyt, Pla Unknown

Ast1, Ast2 Ast3, Bra, Eri, Ger, Lyt, Pas, Pla, Brassicaceae Lasioglossum pectorale 6 13 2573 Unk5, Unk9 Unknown

Lasioglossum puteulanum 8 7 1509 Ast1, Ast2, Bra,Con1, Lyt, Pla, Eri, Unk1 Unknown

Lasioglossum reticulatum 8 4 1025 Ast1, Ast3, Bra, Lyt, Pla, Pol, Unk10 Unknown

Lasioglossum tamiamense 4 1 57 Unk11 Unknown

Lasioglossum unknown 8 1 300 Bra, Pla Brassicaceae

Table 4-1. Continued. Bee Size Pollen Count Bee Collection Bee Family Bee Genus Bee Species Bee Count Pollen Morphospecies (mm) (total) Plant Family

Hoplitis Unk 11 1 300 Ast2, Bra Brassicaceae

Megachile albitarsis 12.5 1 222 Ast1, Lyt, Pla Unknown

Megachile georgica 12.5 1 112 Ast2, Bra, Lyt Unknown Ast1, Ast3, Bra, Lyt, Ast2, Cuc, Megachile mendica 12 2 359 Fabaceae Megachilidae Unk2,Unk3,Unk4 Ast1, Ast2, Bra, Megachile texana 12.5 1 300 Unknown Mal, Pas, Unk5

Ast3, Ast4, Bra, Lyt, Ole, Unk2, Unk5, Ast1, Osmia sandhouseae 9.5 2 602 Eri, Unknown Rub1 Unidentifiable Unknown unknown Unk 2 1846 Pla, Lyt, Ast1, Bra, Ros2 Brassicaceae

Figure 4-1. Project location map. Circles indicate locations of wild bee collection farms.

Figure 4-2. Images of Andrena banksi and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

Figure 4-3. Information on Andrena banksi and pollen the species was carrying on small produce farms.

Figure 4-4. Images of Andrena barbara and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

Figure 4-5. Information on Andrena barbara and pollen the species was carrying on small produce farms.

Figure 4-6. Images of Andrena cressoni and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

Figure 4-7. Information on Andrena cressoni and pollen the species was carrying on small produce farms.

Figure 4-8. Images of Andrena miserabilis and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

Figure 4-9. Information on Andrena miserabilis and pollen the species was carrying on small produce farms.

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Figure 4-10. Images of Perdita bequaerti and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-11. Information on Perdita bequaerti and pollen the species was carrying on small produce farms.

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Figure 4-12. Images of Bombus bimaculatus and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-13. Information on Bombus bimaculatus and pollen the species was carrying on small produce farms.

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Figure 4-14. Images of Bombus griseocollis and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-15. Information on Bombus griseocollis and pollen the species was carrying on small produce farms.

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Figure 4-16. Images of Bombus impatiens and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-17. Information on Bombus impatiens and pollen the species was carrying on small produce farms.

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Figure 4-18. Images of Ceratina floridana and pollen the species was carrying on small produce farms. Bee photo by Tim Lethbridge, 2009. Reprinted with permission from Bugguide.net, http://creativecommons.org/licenses/by-nd- nc/1.0/. Source: http://bugguide.net/node/view/263482/bgimage. Pollen photos are courtesy of the author.

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Figure 4-19. Information on Ceratina floridana and pollen the species was carrying on small produce farms.

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Figure 4-20. Images of Habropoda laboriosa and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-21. Information on Habropoda laboriosa and pollen the species was carrying on small produce farms.

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Figure 4-22. Images of Melissodes bimaculata and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-23. Information on Melissodes bimaculata and pollen the species was carrying on small produce farms.

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Figure 4-24. Images of Melissodes communis and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-25. Information on Melissodes communis and pollen the species was carrying on small produce farms.

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Figure 4-26. Images of Triepeolus remigatus and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Richard Orr via Discoverlife.org. Source: http://w.ww.discoverlife.org/mp/20q?guide=Triepeolus_female. Pollen photos courtesy of author.

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Figure 4-27. Information on Triepeolus remigatus and pollen the species was carrying on small produce farms.

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Figure 4-28. Images of Xylocopa micans and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-29. Information on Xylocopa micans and pollen the species was carrying on small produce farms.

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Figure 4-30. Images of Xylocopa virginica and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-31. Information on Xylocopa virginica and pollen the species was carrying on small produce farms.

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Figure 4-32. Images of Colletes latitarsis and pollen the species was carrying on small produce farms. Pollen photos are courtesy of the author.

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Figure 4-33. Information on Colletes latitarsus and pollen the species was carrying on small produce farms.

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Figure 4-34. Images of Agapostemon splendens and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-35. Information on Agapostemon splendens and pollen the species was carrying on small produce farms.

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Figure 4-36. Images of Augochlorella aurata and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-37. Information on Augochlorella aurata and pollen the species was carrying on small produce farms.

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Figure 4-38. Images of Halictus poeyi and pollen the species was carrying on small produce farms. Bee photo by Tim Lethbridge, [email protected], July 2009. Reprinted with permission from Bugguide.net, http://creativecommons.org/licenses/by-nd-nc/1.0/. Source: http://bugguide.net/node/view/353466. Pollen photos are courtesy of the author.

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Figure 4-39. Information on Halictus poeyi and pollen the species was carrying on small produce farms.

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Figure 4-40. Images of a Lasioglossum and pollen the species were carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-41. Information on Lasioglossum spp. and pollen the species were carrying on small produce farms.

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Figure 4-42. Images of Hoplitis sp. and pollen the species was carrying on small produce farms. Bee photo by Lawrence Packer, 2014. Reprinted with permission from Discoverlife.org, Source: http://www.discoverlife.org/mp/20q?guide=Hoplitis. Pollen photos courtesy of the author.

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Figure 4-43. Information on Hoplitis sp. and pollen the species was carrying on small produce farms.

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Figure 4-44. Images of Megachile albitarsis and pollen the species was carrying on small produce farms. Bee photo by Tim Lethbridge, 2011, with permission from Bugguide.net, http://creativecommons.org/licenses/by-sa/3.0/. Source: http://bugguide.net/node/view/486289

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Figure 4-45. Information on Megachile albitarsis and pollen the species was carrying on small produce farms.

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Figure 4-46. Images of Megachile geogica and pollen the species was carrying on small produce farms. Bee photo by Lawrence Packer, 2014. Reprinted with permission from Discoverlife.org. Source: http://www.discoverlife.org/mp/20q?guide=Hoplitis. Pollen photos courtesy of the author.

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Figure 4-47. Information on Megachile georgica and pollen the species was carrying on small produce farms.

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Figure 4-48. Images of Megachile mendica and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-49. Information on Megachile mendica and pollen the species was carrying on small produce farms.

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Figure 4-50. Images of Megachile texana and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-51. Information on Megachile texana and pollen the species was carrying on small produce farms.

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Figure 4-52. Images of Osmia sandhouseae and pollen the species was carrying on small produce farms. Bee photo reprinted with permission from Sam Droege, US Geological Survey via Flickr. Source: https://www.flickr.com/photos/usgsbiml/ (December 2015). Pollen photos are courtesy of the author.

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Figure 4-53. Information on Osmia sandhouseae and pollen the species was carrying on small produce farms.

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Figure 4-54. Images of pollen carried by unidentified bees collected on small produce farms. Pollen photos courtesy of author.

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Figure 4-55. Information on pollen the unidentified species were carrying on small produce farms.

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CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS

Animal pollinators are essential reproductive facilitators for a number of global crops and the majority of wild plants (Klein 2007), and appreciation of the pollination services that wild bees provide in agriculture (Kremen and Chapin-Taylor 2007) is increasing as research studies illuminate their behavior (Alarcon 2010, Biel 2008, Cane

2005, Bushman and Drummond 2015, and Chapter 3 of this document). While honey bee populations seem uniquely suited to human needs with characteristics like hive living, general plant pollination, production of honey, and even tolerance of long- distance shipping, are demonstrating that multiple, concurrent environmental stresses like non-target pesticide effects, treatment-resistant and parasitic virus-carrying mites, malnutrition, and disease (Becher et al. 2013 for a review article) are too much for them to continue to thrive while providing the pollination services for agriculture.

Wild bees, native to North America and augmenters of declining honey bee crop pollination services, are not as well adapted to traditional bee management practices being 70% ground nesting and therefore not mobile, and being largely solitary foragers who may work and nest in aggregations but are not cooperative foragers like their honey bee cousins. But, wild bees have strengths lacked by honey bees. They are a diverse group of families and species that can be found across the human-dominated mosaic landscape of North-central Florida (n=300) and across North America (n= 3,700) on city rooftops (ref), in town gardens (ref), in the suburbs, and in rural areas. They are adapted to conditions here and have adapted to human landscapes. If we assume that wild bees are best at fulfilling pollination services in-situ, then we need to investigate ways to work with ecological needs of the species that perform crop pollination on

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farms. Also, since they are susceptible to some of the same maladies (Furst et al.

2014) and pesticides (Brittain and Potts, 2010) that effect honey bees, better understanding wild bee ecology may help us protect these pollination service providers.

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APPENDIX FLORIDA NATURAL AREAS INVENTORY

Table A-1. Defined land covers from the Florida Natural Areas Inventory and data categories.

Analysis Categories FNAI Land Cover Types Tilled Agricultural land Fallow Cropland Field Crops Row crops Untilled open lands Wet prairie Golf Courses Orchards and Groves Vineyard/Nurseries Rural Open Improved Pasture Parks Unimproved Woodland Developed CommercialPasture services Communication Community Rec Facilities Feeding operations High Intensity Urban Industrial Institutional Low structure density Rails Residential medium Roadsdensity Sand/Gravel pits Specialty farm Spoil area Transportation Utilities Wood and Shrubs Citrus Bay swamp Other wetland forested Livemixed oak Mesic flatwoods Mixed hardwoods- Sandhillconiferous Scrubby flatwoods Successional hardwood forest

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Table A-1. Continued. Analysis Categories FNAI Land Cover Types Upland coniferous Upland hardwood forest Upland pine Xeric hammock Ornamentals Shrub and brushland Tree nurseries Coniferous plantations

Wood and Shrubs Hydric pine flatwoods Wet coniferous Bayplantations swamp Hydric Hammock Mixed scrub shrub Mixedwetland wetland Otherhardwoods wetland forested Basinmix Marsh

Open Water Alluvial streams Aquacultural ponds Artificial Imp/Reservoir Basin swamp Bay gall Cypress Depression marsh Flatwoods prairie marsh Floatinglake emergent Freshwatervegetation marshes Gum pond Natural lakes and ponds Non-vegetated wetland Sewage treatment pond Sinkhole lake Storm water treatment pond

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BIOGRAPHICAL SKETCH

Rosalyn D. Johnson is a scientist and conservationist with 28 years experience in wildlife fieldwork, environmental planning, and conservation of non-game invertebrate and vertebrate species. She began studying wild bees while working for the US

Environmental Protection Agency, where she was encouraged to explore her invertebrate interest in the name of professional growth at the 2002 Calumet City

BioBlitz. She has been studying the native bee communities of local farms and the relationship to vegetation structure and surrounding landscape cover in Florida since

2009, and will be continuing her career in conservation with a new doctorate and renewed energy. She received her Ph.D. from the University of Florida in May 2016.

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