The underestimated taxa: the role of non-bee pollinators in temperate vegetable crops, experimental research in strawberry (Fragaria spp.) crops

by

Ellen Richard

A Thesis presented to The University of Guelph

In partial fulfilment of requirements for the degree of Master of Science in School of Environmental Sciences

Guelph, Ontario, Canada

© Ellen Richard, September, 2019

ABSTRACT

THE UNDERESTIMATED TAXA: THE ROLE OF NON-BEE POLLINATORS IN TEMPERATE VEGETABLE CROPS, EXPERIMENTAL RESEARCH IN STRAWBERRY (Fragaria spp.) CROPS

Ellen Richard Advisor(s): University of Guelph, 2019 Dr. Nigel E. Raine Dr. Dirk Steinke

Pollination services are critical to agricultural systems, providing a third of global food production. Non-bee pollinators have received little recognition with regards to their role in commercial agricultural pollination. Diverse pollinator communities often provide better pollination services, and non-bee pollinators represent 95% of this diversity.

Additionally, research demonstrates that many non-bee pollinators are more resilient to land use intensification and climate change due to their nomadic life-history and tolerance to inclement weather. The aim of this thesis is two-fold. It demonstrates the diversity of non-bee insects that visit temperate vegetable crops in a comprehensive review. Secondly, it presents research on the non-bee floral visiting community of day- neutral strawberries in Southern-Ontario. Using barcoding methods as well as quantitative analysis it characterises flower visitor communities, their foraging preferences and levels of floral fidelity. Hoverflies were found to be important non-bee flower visitors, carrying comparable amounts of pollen to bees.

ACKNOWLEDGEMENTS

I would like to thank the members of the Raine lab that were present for the duration of my master’s degree, providing support and help when they could, in particular, Dr. Elizabeth Franklin, Leah Blechschmidt and Hayley Tompkins. Additional thank you to members of the Steinke lab for their training and patience, special thanks to Dr. Thomas Braukmann. Finally, thank you to Dr. Dirk Steinke for being available; for your help, support and guidance during the second half of my thesis and giving me the opportunity to attend the 8th iBOL conference in Norway. Thank you to the growers that allowed me access to their properties and allowed me to sample in their fields. I would also like thank the financial support I received to support my research. The Natural Sciences and Engineering Research Council (NSERC: Discovery grant 2015-06783 awarded to N.E.R.), the Food from Thought: Agricultural Systems for a Healthy Planet Initiative, by the Canada First Research Excellent Fund (grant 000054), and W.G. Matthewman Scholarship awarded to me in 2017.

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AUTHOR’S DECLARATION OF WORK COMPLETED

I declare that all work presented in this thesis is my own, with the following exceptions: Dr. Thomas Braukmann assisted with development of protocol for pollen metabarcoding.

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TABLE OF CONTENTS

Abstract ...... ii

Acknowledgements ...... iii

Author’s Declaration of Work Completed ...... iv

Table of Contents ...... v

List of Tables ...... vii

List of Figures ...... viii

List of Appendices ...... ix

1 Chapter 1: General Introduction ...... 1

1.1 Importance of non-bee pollinators ...... 3

2 Chapter 2: The underestimated taxa: the role of non-bee pollinators in temperate crops ...... 7

2.1 Introduction ...... 7

2.2 Methods ...... 9

2.3 Crop Assessments ...... 12

2.3.1 Fruits...... 12

2.3.2 Vegetables ...... 24

2.3.3 Nuts ...... 42

2.4 Discussion ...... 46

3 Chapter 3: Assessing non-bee flower visiting community of strawberries ...... 48

3.1 Introduction ...... 48

3.2 Methods ...... 51

3.2.1 Experimental Fields ...... 51

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3.2.2 Field Sampling ...... 52

3.2.3 Pollen Removal and Quantification ...... 53

3.2.4 Molecular Identification ...... 54

3.2.5 Data Analysis ...... 58

3.3 Results ...... 60

3.3.1 Diversity and Pollen Loads ...... 60

3.3.2 Pollen Metabarcoding and Pollinator Networks ...... 72

3.3.3 Environmental Variance on Community Structure ...... 77

3.4 Discussion ...... 81

3.5 General Conclusions ...... 85

References ...... 87

Appendices ...... 114

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LIST OF TABLES

Table 2.1: List of temperate crops assessed in this review, the degree of pollination dependence and assessment of whether non-bee pollination is likely, based on the literature reviewed...... 11

Table 3.1: Primers used for barcoding ...... 58

Table 3.2: Insect visitors collected from day-neutral strawberries ...... 63

Table 3.3: Insect visitors observed on day-neutral strawberries ...... 69

Table 3.4: A generalized linear model representing non-bee pollen count data at the genus level (n=53)...... 71

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LIST OF FIGURES

Figure 2.1: Pollinator papers assessed during literature review of non-bee pollinators, presenting trends across the years 1930 to present...... 9

Figure 3.1: Total pollen load on non-bee strawberry visitors ...... 66

Figure 3.2: Abundance of strawberry flower visiting species ...... 67

Figure 3.3: Average pollen carried by species visiting strawberry ...... 68

Figure 3.4: Plant-flower visitor network at the family level ...... 75

Figure 3.5: Plant-syrphid network at the plant family level ...... 76

Figure 3.6: Triplot of redundancy analysis with species scaling ...... 79

Figure 3.7: Boxplot representation of observed abundance ...... 80

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LIST OF APPENDICES

Appendix 1: List of species recorded visiting flowers of the focal crops assessed...... 114

Appendix 2: Species-level identification of specimens caught in strawberry fields, accompanied by the number of individuals caught and their average pollen load count...... 154

Appendix 3: Plant genera and families of pollen found on insect visitors of strawberry crops ...... 157

Appendix 4: Triplot of redundancy analysis coloured by site ...... 160

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1 Chapter 1: General Introduction

The importance of pollination for ecosystem function and services is well known.

Plant pollination results in the perpetuation of wildflowers and trees which provide food and shelter to animals. It is estimated that 78% of temperate flowering plant species rely on insect pollinators for reproduction (Ollerton et al. 2011). These plants are critical for maintaining ecosystem functions which provide services for humans (e.g., increased water and air quality, prevention of soil erosion, timber, fruit and nut production; Kearns et al. 1998, Ashman et al. 2004, Cardinale et al. 2012). In addition to the benefits provided by pollination in natural landscapes, insect pollinators are critically important to global food crops, contributing to 65% of the produced crop volume (Klein et al. 2007), valued at $293-720 billion CAD (Potts et al. 2016, but see Melathopoulos et al. 2015). In order to augment pollination services in crop fields, growers often use commercial honey bees

(Apis mellifera) (Free 1993, Walters 2005, Klein et al. 2007, Eaton and Nams 2012,

Shaheen et al. 2017). The reliance on honey bees has become problematic, however, with a mismatch in the increased acreage of pollinator-dependent crops and the number of hives available (Aizen and Harder 2009, Garibaldi et al. 2011, Schulp et al. 2014). The effects of the supply-and-demand mismatch is compounded by high rates of colony losses, resulting in local declines of available commercial hives and higher prices for renting hives (Ellis 2012, Pindar et al. 2017, vanEngelsdorp et al. 2017). Wild bee populations are also declining. Surveys from Europe and North America indicate declines in richness and abundance of wild bee populations (Biesmeijer et al. 2006, Grixti et al.

2009, Williams and Osborne 2009, Cameron et al. 2011, Carvalheiro et al. 2013). The

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leading causes for these declines include land-use intensification, habitat fragmentation, pesticide application, disease spillover, and climate change (Potts et al. 2010, Vanbergen et al. 2013, Ollerton et al. 2014, Pindar et al. 2017). The plight of the bees has been receiving growing consideration from the scientific community, policy makers, and the public (Kevan and Phillips 2001, Allsopp et al. 2008, Food and Agriculture Organization of the United Nations 2012, Senapathi et al. 2015). As such, there has been a surge in research to understand the contribution and importance of wild pollinators (Winfree et al.

2007, Klein et al. 2012, Garibaldi et al. 2013, Földesi et al. 2016, Mckechnie et al. 2017).

Bees are obligate floral-forgers, requiring pollen to provision food for their brood and nectar to fuel their flight (Müller et al. 2006). Their morphology and biology are specialized for floral manipulation, meaning they are frequently the most efficient pollinator group

(Kennedy et al. 2013, Scott et al. 2016). Additionally, bees are a relatively well-described taxon, with most species identifiable to the species level (Banaszak 2000, Michener

2000). Bees’ high pollination efficiency and well-resolved taxonomy has resulted in a severe bias towards bee taxa when considering wild pollinators in research, with many studies disregarding the contribution of non-bee pollinators (Klatt et al. 2013, Woodcock et al. 2013, Toledo and Papineau 2015). In particular, this skewed attention is exacerbated when considering policy makers and the public; this is well demonstrated in

Dicks et al. (2013). Hoverflies occasionally receive secondary recognition as pollinators due to their affinity with flowers and their abundantly hairy bodies (Skevington and Dang

2002). While several recent studies have jointly considered hoverflies and bees in their pollinator assessments (Baldock et al. 2015, Garratt et al. 2016, Joshi et al. 2016,

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Ahrenfeldt et al. 2017), these taxonomic biases limit the acknowledgment of other insect pollinators, such as wasps, non-syrphid flies, beetles, ants, bugs, butterflies, and thrips

(Kendall and Solomon 1973, Heithaus 1979, Larson and Kevan 2001, Blanche and

Cunningham 2005, Brodmann et al. 2008, Rader et al. 2016, Ollerton et al. 2017).

1.1 Importance of non-bee pollinators

Diversity provides stability and reliability of ecosystem services and functions, including pollination systems (Garibaldi et al. 2013, Rogers et al. 2014, Rader et al. 2016).

Diverse pollinator assemblages can result in an ensemble of species-specific foraging preferences (including specialists and generalists), which effectively exploit floral resources and deliver effective pollination services as a byproduct of foraging activity

(Fontaine et al. 2005, Garibaldi et al. 2013). However, pollinators have to cope with potentially substantial variation in their environment when making foraging decisions.

They must respond to variation in the cues provided by flowers (e.g. colour, odour and shape) about the rewards they might provide, the spatial distribution of resources (e.g. flower patches in the landscape or the location of flowers on an individual plant), and the variability in environmental conditions (such as, wind, precipitation and temperature).

Such environmental variation can result in partial niche partitioning, with distinct species or guilds (Blüthgen and Klein 2011). For example, honey bees preferentially forage from flowers at the tops of almond trees, while wild bees prefer to visit low flowers; thus, together the actions of these different groups of pollinators are complementary and result in the entire tree being pollinated (Klein 2011). Indeed, such functional complementarity has been demonstrated with experimental design in several instances (Fontaine et al.

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2005, Blüthgen and Klein 2011, Garibaldi et al. 2013, 2014, Rogers et al. 2014). An exception to this condition is highly specialized relationships between a single plant and a single animal species; however, these instances are rare (Waser et al. 1996, Pornon et al. 2017). In addition to functional complementarity, diversity provides functional redundancies, so that pollination success does not become the reliant on a single species. Despite the importance of diversity, most studies on functional complementarity and redundancy focus solely on bee diversity (Fontaine et al. 2005, Blüthgen and Klein

2011, Garibaldi et al. 2013, 2014, Rogers et al. 2014). The exclusion of non-bee pollinators is an oversimplification of reality, as bees represent a mere ~5.5% of the arthropod floral-visiting community, with over 330,000 species documented from other taxa that may also contribute significantly to pollination (Wardhaugh 2015, Ollerton 2017).

This substantial, yet largely overlooked, non-bee pollinator diversity is likely responsible for delivering a substantial amount of functional services by providing unique pollen transfer, due to their diversity of form, behaviour and physiological tolerances to a wide range of foraging conditions (Rader et al. 2016).

One of the leading justifications researchers give for the exclusion of non-bee pollinators is that bees are often the most efficient pollinator (Kennedy et al. 2013, Scott et al. 2016). Bees have a nectar and pollen-dependent diet; as such, their behaviour and foraging techniques often result in high pollen release and frequent flower visiting

(Sheffield 2014, Campbell et al. 2017b, Russo et al. 2017). When considering non-bee pollinators, their average pollination efficiency per flower visit may be low, but their ubiquity can lead to high visitation frequency, resulting in equal, or greater, pollen

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deposition than bees (Larson and Kevan 2001, Skevington and Dang 2002, Rader et al.

2009, 2016, Orford et al. 2015). This is especially true when considering Diptera, which are particularly speciose and abundant (Skevington and Dang 2002). The dietary reliance of bees on pollen also means they are expert groomers, removing pollen from their bodies and packing it into specialized pollen carrying structures (corbiculae or scopae), thus effectively removing this pollen from any active role in pollination (Jander 1976, Vaissaire et al. 2006, Lunau et al. 2015, Koch et al. 2017). While flies are also efficient groomers, the removed pollen does not become inactive (Barber and Starnes 1949, Lewis and

Hughes 1957, Kendall and Solomon 1973, Sutcliffe and McIver 1974, Holloway 1976,

Shaffer et al. 2007, Orford et al. 2015, Jacques et al. 2017). There is no information on the preferred location for flies to groom; however, it is likely that on occasions they are perched on flowers while grooming. As such, the free-groomed pollen could land on receptive conspecific stigmas and provide pollination services. Currently, very limited information exists in the literature about the grooming behaviours and pollination efficiency of other non-bee flower-visitors.

Unlike bees, most non-bee pollinators are not central-place foragers. As central- place foragers, female bees typically have a nest in a fixed location that they return to after each foraging excursion. Thus, bee foraging ranges are restricted, with most solitary species foraging only 150-600m from their nest (Osborne et al. 1999, Gathmann and

Tscharntke 2002, Greenleaf et al. 2007). Honey bees have a vastly larger foraging range of 3-5km, with a maximum range up to 15km (Beekman and Ratnieks 2000, Couvillon et al. 2014). As such, wild bees’ sensitivity to land-use practices are intensified by their

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inability to remove themselves from risk (Raine and Gill 2015, Klein et al. 2017). Flies and beetles are nomadic; they do not have established nest sites. Therefore, they are not restricted in their foraging ranges (Skevington and Dang 2002, Menz et al. 2019). As such, these taxa do not require nesting materials which may be contaminated with pesticides, and are less affected by land-use intensification compared to bees, which are impacted by loss of habitat and appropriate nesting areas (Jauker et al. 2009).

Additionally, the environmental conditions in which non-bees continue to forage on flowers is often less restricted than bees. Flies and beetles have been observed continuing to forage when it is cloudy, even raining, and when it is too cool or hot for bees

(Heinrich and Mcclain 1986, Inouye et al. 2015). As a specific example, when temperatures rise and there is low humidity, the sugars in nectar begin to crystalize, making it inaccessible for bees to ingest. Flies however, are able to regurgitate fluids onto the crystals, re-dissolving them for consumption (Inouye et al. 2015). As such, non-bee pollinators could be more resilient to climate change and land-use intensification and should be considered carefully for the pollination services they provide to both crops and wild plants (Biesmeijer et al. 2006, Meyer et al. 2009, Jauker et al. 2009, Grass et al.

2016, Rader et al. 2016).

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In order to examine the diversity and ubiquity of non-bee pollinators, while simultaneously highlighting the gaps in available literature regarding their role in crop pollination, this research project has the following objectives:

(1) To evaluate the literature on non-bee flower-visitors to a selection of temperate

crops (Chapter 2).

(2) To investigate the community of non-bee insects visiting flowers of strawberry

crops in Southern Ontario (Chapter 3).

2 Chapter 2: The underestimated taxa: the role of non-bee pollinators in temperate crops 2.1 Introduction

Given the apparent taxonomic biases of the last three centuries, which focused heavily on bees as the primary or only pollinators of crops (Figure 2.1), the aim of this chapter is to outline the important diversity of non-bee species that visit flowers and highlight knowledge gaps regarding their identity and the pollination services they provide. Provided that primary interest regarding pollination pertains to its ecosystem service, the scope of this review is confined to agricultural cropping systems. As there are hundreds of crops grown globally, my review is restricted to a subset of 23 temperate fruit and vegetable crops (Table 2.1). Information on non-bee flower-visiting insects was collected by close examination of the available literature. A summary table of the identity of crop-specific floral-visiting species is presented in Appendix 1, and corresponding details on their role in crop pollination in the main text. This information was placed in the context of the floral pollination systems, pollination requirements, and 7

the known roles of bees in each of the assessed cropping systems (Table 2.1). This document is meant to be a tool for agricultural applications, pollinator conservation and pollinator research. Readers can find their target crop and read a concise summary of the knowledge we have regarding non-bee pollinators. It highlights knowledge gaps and areas for future research.

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80 All diversity Bees and Syrphids Only Bees 70 60 50 40 30

20 Number of Papers ofNumber 10 0 1930-1944 1945-1959 1960-1974 1975-1989 1990-2004 2005-2019 Year

Figure 2.1: Pollinator papers assessed during literature review of non-bee pollinators, presenting trends across the years 1930 to present.

2.2 Methods

The crops chosen for this review were drawn from a previous review on global crop pollination (McGregor, 1976) and selected for fruit and vegetable crops which are grown primarily in temperate climates (Table 2.1). The review included 38 crops which met the criteria; 22 crops were selected. The selection was made to maximize variation in floral composition and degree of pollination requirement of crop types. I also added a single nut crop, almonds, which has a large economic impact, particularly with respect to pollination services provided; therefore, this crop has substantial research advocating for a diverse pollinating community. The pollination requirements, present knowledge of their

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pollination systems and non-bee visitors are presented in-text, in alphabetical order by family. A rigorous assessment of the available literature was conducted by using search term ‘pollination’ combined with each of the selected crops, using the University of

Guelph, Primo search engine. Any relevant references cited within the studies arising from the Primo search were also examined for additional information or records of non- bee pollinators. This search process yielded 364 studies that I reviewed in detail. Of these in paper references, those that could be found on in Primo, or through Google Scholar with an English translation were included. Research from temperate locations (North

America, North and Central Asia, Europe, United Kingdom, and New Zealand) were used preferentially. However, when no temperate examples were available, I referred to tropical research.

For an animal to be classified as a pollinator it must visit a flower, collect pollen on its body, visit another flower of the same species, and deposit viable pollen onto the stigma of the second receptive flower (Cox and Knox 1988). However, insects which have free active pollen on their bodies can be used as a proxy for a likely pollinator status.

Because should an insect visit a flower and have free pollen of that plant on its body, then it is likely to continue visiting, to some degree, that same floral species. Thus, despite the inevitable variability in pollination efficiencies, they are likely to participate in some degree of pollination. Inefficient pollinators can have significant influence on pollination services when abundance is considered (Rader et al. 2016). Most studies that provide information regarding non-bee insects simply report their presence on crop flowers and their relative abundance. This review aims to provide an in-depth synopsis of the information available

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on non-bee insects that may participate in crop pollination of the crops included in this review.

Table 2.1: List of temperate crops assessed in this review, the degree of pollination dependence and assessment of whether non-bee pollination is likely, based on the literature reviewed. Crop Requires crop Dependency Evidence of pollination category non-bee (Klein et al. 2007) pollination Fruits Apple Yes Great ✓ Apricot Yes Great NS Blackberry Enhances Great ✓ Blueberry Enhances Great ✓ Cantaloupe Yes Essential NS Raspberry Enhances Great ✓ Strawberry Enhances Modest ✓ Watermelon Yes Essential ✓ Vegetables Asparagus Yes ‡ n.a NS Beets No */‡ n.a ✓ Cabbage Yes ‡ n.a ✓ Cucumber Yes Great ✓ Eggplant Yes modest ✓ Onion Yes ‡ n.a ✓ Peas No Little ✓ Pumpkin Yes Essential ✓ Beans No Little ✓ Soybean No * Modest ✓ Squash Yes Essential  Sweet pepper Enhances Little ✓ Tomato No * Little  Zucchini Yes Essential NS Nuts Almond Yes Great ✓

Categorizations used for this review follow earlier schemes from McGregor and Todd 1952, Free 1993, Delaplane and Mayer 2000, with additionally information on the category of dependence on pollinators for crop production generated by Klein et al. (2007).

‡ indicates the crop only requires pollination to produce seed. * indicates hybrids require pollination § with the exception of runner beans (Phaseolus coccineus) n.a indicates no estimation was given for that crop NS indicates insufficient information

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2.3 Crop Assessments

2.3.1 Fruits

2.3.1.1 Amygdaloideae

2.3.1.1.1 Apricot (Prunus armeniaca)

Pollination system and requirements

Apricots are primarily self-incompatible; however, there are some European varieties which are self-compatible (Milatović et al. 2013). Additionally, some cultivars are male-sterile; thus, insect pollination is crucial for successful cross-pollination and fruit set

(Nakanishi 1982).

Non-bee pollination

In Australia, honey bees comprised 97.6% of insect flower visitors, hoverflies

(Syrphidae) represented 1.5% of visitation and bush flies (Muscidae) 0.6%. Collectively, flies and honey bees increased fruit set nearly two-fold. The low frequency of native bee visitors is speculated to be a result of the surrounding land-use practices – agricultural land with high insecticide use (Langridge and Goodman 1981). In Utah’s Fruita orchards, surrounded by Capitol Reef National Park in Utah, apricots are primarily visited by honey bees, which are commercially supplied. Flies were infrequent visitors to these apricot flowers (1-2% of visits), and fifteen native bee species were also recorded on these crop flowers (Tepedino et al. 2007).

Bee pollination

Despite high-volume nectaries (up to 9.1 mg), bee visitation was quite low, averaging one to three bee visits per flower per six-hour-day. Those bees observed visiting apricot flowers appeared to be foraging only for pollen (Benedek et al. 1995). 12

2.3.1.2 Rosaceae

2.3.1.2.1 Strawberry (Fragaria spp.)

Pollination system and requirements

Strawberry flowers are classified as self-fertile hermaphroditic plants. However, self-pollination is estimated to result in only 8% of the commercial value of flowers that received supplemented pollination (hand or insect pollinated) (Wietzke et al. 2018). Insect pollination also reduces the number of misshapen fruit (Lopez-Medina et al. 2006).

Non-bee pollination

Syrphid flies are often reported to be the most abundant non-Apis insect found on strawberry flowers. In Quebec, syrphids represented (25%) of flower visitors, second only to honey bees (52%), which were stocked in the field and so their dominance is explained by artificially augmented populations (de Oliveira et al. 1991). Similarly, in Utah, syrphids were second only to honey bees (Nye and Anderson 1974). In Sweden, syrphids were

(82%) of visitors, their abundance significantly increasing when there was a pond in the nearby vicinity. This increased abundance of syrphids was correlated with an increase in pollination, fruit set, and a decrease in malformation of strawberry fruits (Stewart et al.

2017). Syrphid species Eristalis tenax and E. brousii were classified as two of the four most important pollinators to strawberry fields in Utah. This classification was devised with a combination of pollination efficiency and abundance (Nye and Anderson 1974).

Additionally, some syrphid species are mass reared for greenhouse pollination services, such as Eristalis cerealis in Japan (Delaplane and Mayer 2000). The flower-visiting community for strawberries can be quite diverse. Sixty-six (61%) of 108 flower visitor species reported from Utah were non-bees (Nye and Anderson 1974), and 28 (62%) of 13

45 flower visitors species from Quebec were also non-bee species (de Oliveira et al.

1991) Additionally, ant (Formicidae) visitation results in 90% of the fruit set of flowers visited by flies and bees, thus classifying them as effective strawberry pollinators. The following three ant species are pollinators: Prenolepis imparis, Formica subsericea, and

Tapinoma sessile. However, ants often damage pistils and reduce the visitation rate of flying pollinators, limiting further pollination (Ashman and King 2005). The pest control lacewing species Chrysoperla carnea was tested for its ability to pollinate strawberry flowers, as both larvae and adults will visit flowers for pollen and nectar. However, due to flight activity, form, and few pollen-collecting hairs, C. carnea is not an efficient pollinator.

Percent of flowers pollinated by C. carnea was 48%, compared to 42% in insect excluded plots (Zapata et al. 2008).

Hooper (1932) estimated that when temperatures are cool, the majority of pollinators will not be bees, but rather, likely flies. Calliphorids are occasionally used to stock greenhouses for strawberry pollination (Free 1993). Calliphora vomitorid was found to have equivalent pollination efficiency to honey bees while being more cost efficient and lower maintenance (Carden and Emmett 1973, Clements 1982).

Bee pollination

Honey bees often provide suitable pollination to strawberries 84-100% fruit set

(Svensson 1991, Chagnon et al. 1993, Kakutani et al. 1993, Zapata et al. 2008). However bumblebees represent a better option when considering greenhouse pollination, or early bloom strawberries when temperatures are often below 12˚C, when honey bees will not forage (Paydas et al. 1998, Dimou et al. 2008). A stingless bee, Trigona minangkabau,

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was found to be an efficient greenhouse strawberry pollinator; however, stocking densities would need to be almost double that of honey bees (Kakutani et al. 1993).

2.3.1.2.2 Apple (Malus domestica)

Pollination system and requirements

Apples require pollination to set fruit, and most cultivars are self-incompatible

(Ramírez and Davenport 2013). Apple pollen does not adhere readily to the stigma; therefore, wind pollination is not considered an important avenue for pollination. Thus, insect pollination is crucial for fruit set in these crops (Garratt et al. 2014).

Non-bee pollination

Syrphid flies are reported to be potential apple pollinators, representing 7.4% of visitation abundance to apple flowers in a UK cider orchard (Campbell et al. 2017a). In

Hungary, Földesi et al. (2016) found that thirteen species of syrphids comprised 33% of non-Apis observations on apple blossoms. Exclusion experiments indicate that flower visits from only the syrphid Eristalis tenax resulted in yield equivalent to that of open pollination by all wild pollinators (Solomon and Kendall 1970). Flies in a UK orchard were found to have comparatively few pollen grains (2-806 grains/individual), of which a low percentage were apple pollen (13-61%), compared to bees (388-38610 grains/individual,

75-94% apple pollen). Of the flies, syrphids carried the highest amount of pollen on average, 61% of which was from apple (Boyle and Philogène 1983). Specifically, syrphid species, Eristalis pertinex, E. tenax, E. argustorum, and the conopid species Myopa buccata were found to fertilize 29%, 18%, 51%, and 32% of ovules in a single visit, respectively. In comparison, the average fertilization for bees was 26% (Kendall 1973).

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Syrphid visitation frequencies can be low in UK orchards (Garratt et al. 2016).

When testing the efficiency of a subset of the flower visitor community, the syrphid

Eristalis balteatus had significantly lower pollination efficiency than bee species. Overall, syrphids only contribute about 3% to UK apple pollination (Garratt et al. 2016). Syrphid abundance has also been reported to be very low in Pennsylvania orchards (Joshi et al.

2016). Eristalis syrphids have been considered for commercial pollination; however, their abundance in the crop reduces remarkably in just 24 hours after their introduction

(Kendall and Solomon 1973).

Other prominent fly visitors to apple flowers include species from the family

Anthomyiidae, representing the most abundant non-Apis visitor, carrying an average of

32 pollen grains, of which 68% are apple pollen (Boyle and Philogène 1983, Boyle-

Makowski and Philogene 1985). In Columbia, fly visitors (Calliphoridae, Tachinidae,

Syrphidae, Muscidae) were the most abundant visitors (8.7%), second only to honey bees

(76%). The remaining proportions of flower visitors were: 4.5% native bees, 3.7% Diptera

(Bibionidae, Sciaridae, Tipulidae), 3.1% Coeloptera, 2.2% Lepidoptera (Botero and

Gilberto 2000). In Nova Scotia, Mycetophilidae flies were found to be the most abundant flower visitor by far, whilst carrying substantial pollen loads. Beetles were the most frequent visitors, but did not provide significant pollination services (Brittain 1932). Vicens,

Bosch and Vicens (2000) found, on average, flies were the most abundant visitor, second to honey bees (~30% and ~50% respectively). Of the fly diversity, 77% belonged to muscoids (Calliphoridae, Tachinidae, Muscidae, Anthomyiidae). Other than a single mason bee species (Osmia cornuta), muscoids were the only insects found visiting

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flowers at low solar radiation levels (100-200 w/m2) and in light rain. Although relatively inactive, most non-bee pollinators and O. cornuta were seen on flowers at low temperatures (10-13 °C). However, it is noted that the muscoid flies did not frequently move between flowers, or make contact with the stigma (Vicens et al. 2000).

Bee pollination

The visitation frequency and effectiveness of honey bees to pollinate apple is summarized in Free (1953). Honey bees are able to rob nectar from apple blossoms by side-feeding, suggesting they may be an inefficient pollinator, although they are also often the most abundant (Delaplane and Mayer 2000, Botero and Gilberto 2000, Földesi et al.

2016). Diversity is often found to be more important factor to increasing fruit set in apple orchards than increasing honey bee abundance alone (Mallinger and Gratton 2015,

Földesi et al. 2016). High bee species richness (up to 53 species) has been found in apple orchards. The dominant genus, Andrena, represented 62% of the wild bees collected.

Halictidae were the most specious and rare. However, honey bees represented half of the total bee abundance (Russo et al. 2015, Blitzer et al. 2016). Commercially, mason bees (Osmia sp.) have been considered for pollination of apple orchards (Gruber et al.

2011).

2.3.1.2.3 Blackberry (Rubus fruticosus, R. resticanus inermis, R. argutus, R. allegheniensis, R. spp)

Pollination system and requirements

Pollination requirements of blackberries vary substantially across species. While wild diploid plants are self-incompatible (require insect pollination), most cultivated species are self-compatible (Haskell 1960, Nybom 1987, Cane 2005). Although cultivated 17

species do not require insect pollination, self-pollination often does not successfully pollinate the most central stigmas, thus resulting in incomplete terminal fruitlets

(McGregor 1976, Free 1993, Cane 2005). Additionally, self-pollinating plants produce only about a quarter of the fruits produced by plants pollinated by insects (Mello et al.

2011).

Bee pollinators

Data from Brazil suggests that blackberry flowers are heavily visited by bees, with only around 30 of 1400 insects collected from blackberry flowers being non-bees

(although their taxonomic identity was not provided; Mello et al. 2011). Among the bees on blackberry flowers, honey bees were the predominant visitors comprised 92% of the bee visits (Mello et al. 2011). Cross-pollination in a commercial field, stocked with two commercial honey bee hives, ranges from 5 to 32%, with greater cross pollination nearer the field edge (Haskell 1960).

Osmia aglaia, a native Utah mason bee, provides comparable pollination services to honey bees in blackberry fields, making it suitable for commercial pollination (Cane

2005). Similarly, Osmia cornuta (European orchard bee), a native bee to Italy, is a viable commercial option as it performs well in confined environments, such as greenhouses and tunnels (Pinzauti et al. 1997). For Canada, Osmia lignaria (blue orchard bee) is an equivalent commercialized native mason bee (Cane 2005).

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2.3.1.2.4 Raspberry (Rubus idaeus, R. pubescens, R. strigosus)

Pollinator system and requirements

The majority of raspberry cultivars are self-fertile; however, wild raspberry (R. idaeus) is self-incompatible (Keep 1968, Schmidt et al. 2015a). Raspberry flowers provide substantial nectar rewards for visiting insects, providing an average of 17.5 µl per flower per day with a sugar concentration of 22.4% (Whitney 1984).

Non-bee pollinators

Within the spruce-forest of Maine, the insect community visiting raspberry flowers consists of 38 species of Syrphidae and 47 bee species (full list of syrphids in Appendix

1). In addition to the bees and syrphids visiting these raspberry flowers, beetles

(Scarabaeidae Trichiotinus affinis, and Cerambycidae) were also considered as potential pollinators of this crop (Hansen & Osgood 1983). Raspberry crops in Scotland were visited by non-bee insects less than 10% of the time, comprising 15 species of hover flies, most commonly Syrphus and Episyrphus, and beetles. The two beetle species observed,

Byturus toentosus (raspberry pest) and Coccinela 7-punctata, were feeding on pollen and mating on the flowers (Willmer et al. 1994). In the mountains of Italy, syrphids (Volucella spp., Blera fallax, Brachymia berberina) comprised about 10% of insect visitation

(Prodorutti and Frilli 2008). Ants (Formicidae) and horse flies (Chryosops spp.) were observed visiting raspberry flowers in Hungary (Schmidt et al. 2008). Additionally, butterflies, such as the Karner blue butterfly (Lycaeides melissa samuelis), have been observed collecting raspberry nectar (Grundel et al. 2000).

19

Bee pollination

Honey bees and bumblebees are frequently the most abundant pollinators of raspberries (Schmidt et al. 2015a). In Scotland, bumblebees represented about 60% of the bee visitors; the other 40% was primarily honey bee visits. Bumblebees are surmised to be more efficient raspberry pollinators than honey bees, as they foraged on flowers at a higher rate, collected and deposited more pollen on crop flowers, foraged more frequently between rows, and foraged over a wider range of environmental conditions.

The most common and efficient bumblebee pollinators are Bombus lapidarius and B. terrestris (Willmer et al. 1994). In New Hampshire, wild diploid species, Rubus idaeus and

R. pubescens, were largely visited by bumblebees and solitary (Andrena) bees. Although flies were observed on surrounding flowers, they were not observed visiting Rubus flowers (Whitney 1984). Osmia aglaia, a Utah native bee, is suitable for commercial raspberry pollination. This mason bee species exhibits equivalent pollination service delivery as honey bees and has the potential for commercialization (Cane 2005).

2.3.1.3 Cucurbitaceae

2.3.1.3.1 Watermelon (Citrullus lanatus)

Pollination system and requirements

Watermelons are self-compatible, but require insect pollination, as the grains are too large to be carried by wind (Delaplane and Mayer 2000). On average, 95% of pollination is due to insects (Klein et al. 2007). Seedless watermelons (triploid) plants have male flowers that produce mostly nonviable pollen and thus require diploid plants and insect pollination to provide pollen (Walters 2005). The use of growth regulators are 20

being assessed for the replacement of honey bees for fruit development in greenhouses

(Ferre et al. 2003).

Non-bee pollination

Records of non-bee pollinators were given in a study conducted in Kenya, four butterflies (Lepidoptera Pieridae: Eurema brigitta, Nymphalidae: Danaus chrysippus,

Neocoenyra gregorii and Junonia hierta), two beetle species (Coleoptera Chrysomelidae:

Aphthona marshalii and Leptaulaca fissicollis) and three fly genera (Diptera Calliphoridae:

Chrysomya, Cosmina and Syrphidae: Phytomia; Njoroge et al. 2004). These non-bee visitors were documented carrying pollen and thus could contribute to watermelon pollination in Kenya. No studies have included non-bee visitors in pollination assessments in temperate locations.

Bee pollination

Managed honey bees are the most common managed pollinator used in watermelon fields (Campbell et al. 2018). Bumblebees (Bombus impatiens) are also used, and are most effective in greenhouses as they prefer to forage on other flowers available in the landscape (Campbell et al. 2018). However, when bumblebees do visit watermelon flowers they are more efficient pollinators than honey bees on a per visit basis

(Stanghellini et al. 1991, Dasgan et al. 1999, Campbell et al. 2018). There are reports of diverse bee communities visiting watermelon flowers. In Pennsylvania and New Jersey,

59 bee species were recorded, 51 species in Israel and 43 species in Mexico (Meléndez-

Ramirez et al. 2002, Pisanty et al. 2016, Genung et al. 2017). The dominant species visiting watermelon flowers in Mexico were Partamona bilineata, Trigona fulviventris,

21

Nannotrigona perilampoides, Ceratina aff. capitosa, Trigona nigra (Meléndez-Ramirez et al. 2002). The efficiency of pollen deposition varies across bee functional groups: in descending order, squash bees (Peponapis), long-horned bees (Melissodes), bumblebees (Bombus) deposited the most pollen on a single visit basis (Rader et al.

2013).

2.3.1.3.2 Cantaloupe, Melon, Muskmelon (Cucumis melo)

Pollination system and requirements

Melons require pollination to set fruit; however, growth regulators can also be used to induce fruit set (Mann and Robinson 1950, McGregor and Todd 1952, Mann 1953,

Shin et al. 2007). Some studies have concluded that insect pollination is more economical than artificial pollination (Sakamori et al. 1977). While fruit pollinated by growth regulator developed faster, there was a higher percentage of fermented fruit as the hardness and soluble solids (sugars) of fruits was lower than bee pollinated fruits. Fruit set was also higher in crops visited by bees than for those using growth regulators. Sugar content was roughly the same from both pollination methods when the fruit was fully ripe (Shin et al.

2007). Although hand pollination typically results in less fruit set than open insect pollinated plants, hand pollination is occasionally used instead of insect pollination (Mann and Robinson 1950, McGregor and Todd 1952, Mann 1953).

Bee pollination

There are no records of non-bee pollinators in this crop. Generally, honey bees and bumblebees are the most prominent visitors to melon flowers (Handel 1983, Shin et al. 2007). Honey bees have been found to increase fruit yield in tropical and temperate

22

climates (Mann 1953, Taylor 1955, de la Hoz 2007, Siqueira et al. 2011) and are particularly helpful in enclosed row covers and greenhouse settings (Gaye et al. 1991).

Bumblebees (Bombus terrestris) and honey bees (Apis mellifera) are equivalently efficient pollinators in a greenhouse setting (Dasgan et al. 1999). While visitation by carpenter bees (Xylocopa pubescens) results in three times as many fruits per plant compared to honey bees in a greenhouse setting (Sadeh et al. 2007).

Other bee species reported as melon pollinators include small halictid bees, particularly in the Mediterranean. The sweat bee, Lasioglossum malachurum, was ranked as a major pollinator in the Mediterranean, due to consistently high abundance and visitation rate. Lasioglossum marginatum was also highly abundant in pan traps in 2011, but none were found in 2012 (Rodrigo Gómez et al. 2016). Additionally, there were a few other sweat bees, L. discum, Halictus vestitus, H. fulvipes, Nomioides minutissimus and honey bees, which appeared to have a minor role in pollination. 31 bee species were recorded in melon fields; however, only 16 of those species were observed foraging on melon flowers (Rodrigo Gómez et al. 2016). In France, 37 sub-genera were found in melon fields, the majority belonging to the genera Dasypoda and Evylaeus (Carré et al.

2009). In Mexico, there were relatively low bee visitation rates to melon flowers. The flower visitor community contained at least 22 bee species, of which more than half (13 of 22) of these species were singletons. Ceratina was the dominant genus (65% of individuals caught) found in these sites (Meléndez-Ramirez et al. 2002). Five bee species visited melon flowers within the Cerrado biome in Brazil, honey bees, Halictus spp.,

Plebeia spp., Trigona pallens and T. spinipes (Tschoeke et al. 2015).

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2.3.2 Vegetables

2.3.2.1 Amaryllidaceae

2.3.2.1.1 Onion (Allium cepa)

Pollination system and requirements

Pollination is solely required for seed production of onion crops. Flowers are self- infertile and the majority of pollination is insect-mediated (Delaplane and Mayer 2000).

When flowers are open to all visiting pollinators, the average seed set per umbel is 50%, which is significantly higher than either hand pollination (14.2%) or wind pollination alone

(pollination exclusion: 0.8%; Walker et al. 2011).

Non-bee pollination

Bees and flies are often considered the most abundant and important pollinators for onion. In Utah, flies were the most abundant and efficient pollinator, with syrphids

Eristalis tenax and E. brousii contributing nearly half of the pollination services (Bohart and Nye 1970). Individual E. tenax flies carried equivalent amounts of pollen to individual honey bees, and thus are considered effective onion pollinators (Kumar et al. 1985a).

Numerous fly families, including Syrphidae, Calliphoridae, Anthomyiidae, Stratiomyidae,

Sarcophagidae, Bibionidae, Tachinidae and Muscidae, were abundant flower visitors in

New Zealand (Howlett et al. 2009). Several syrphid species have been recorded visiting onion flowers in Poland (Wojtowski et al. 1980). In Pakistan, 87% of insect visits to flowers were by flies, 72% of which were syrphid species (Table 2; Sajjad et al. 2008). Blowflies

(Calliphoridae: Calliphora and Lucilia) have been shown to be effective pollinators of onion in greenhouses (Currah and Ockendon 1983, Schittenhelm et al. 1997). In addition, some wasps have made appreciable contributions to pollination. For example, the sand 24

wasp, Bembix amoena, contributed about 5% to pollination in Utah (Bohart and Nye

1970). Although onion flowers are visited by many minute (< 3mm) insects (including

Diptera, Coleoptera, Thysanoptera, Hemiptera and Collembola), these insects do not appear to provide significant pollination (0.8% seed set) compared to other visitors

(Walker et al. 2011).

2.3.2.2 Chenopodiaceae

2.3.2.2.1 Sugar beets (Beta vulgaris)

Pollination system and requirements

The commercial value of beets is the sale of the taproot, as such the plant does not require pollination to produce the marketable parts of the plant. Pollination is only required when producing seed for future crop plantings. Beets are self-infertile; thus, they require cross-pollination, via wind or insects (Stewart 1946, Archimowitsch 1949). The dispersal range of beet pollen by wind has been determined to be approximately 1200 metres (Darmency et al. 2009). While not necessary for pollination, insects can increase seed yield, particularly in tetraploid hybrid plants, which produce fewer and larger pollen grains (Mikitenko 1959, Free et al. 1975).

Non-bee pollination

Shaw (1914) suggested that flower visits by thrips are potentially valuable for pollination of beets, despite their pest status. Thrips, when present, are usually highly abundant, typically occurring at 80-190 individuals on a single flower spike. Each individual thrips found on a blooming beet plant had pollen grains on its body, with an average load of 140 grains/adult. In addition, thrips maintain pollen on their bodies while

25

flying between plants (Shaw 1914). A UK study determined that beetles and flies likely represent important beet pollinators. The most abundant flower-visitors (with highest respective pollen grain counts in parentheses) were Coleoptera: Cantharidae (9,350),

Coccinellidae (12,943), Diptera: Syrphidae (69,875), Larvaevoridae (1,458) and

Muscidae (11,083; Free et al. 1975). The lowest proportion of sugar beet pollen was found on dipteran families, Syrphidae, Tabanidae, Larvaevoridae, Calliphoridae, representative of their nomadic life-history (Free et al. 1975). Additional reports indicated that the percentage of insects visiting beet flowers were 32% Coccinellidae, 21% Syrphidae, 20% honey bees, 14% solitary bees and 13% Hemiptera, making these groups candidate pollinators for this crop (Treherne 1923). Many beet flower visitors foraged on select floral resources; for example, the syrphid Melithreptus scriptus foraged for nectar, Coleoptera

(Zonabris, Leptura and Cerocoma species) consumed pollen. However, several bee species (Apis meliffera, Andrena and Halictus) fed on both nectar and pollen from beet flowers. Additionally, pest status insects, such as thrips, aphids like Aphis fabae and other insects (e.g. Mesocerus and Palomena), visited flowers to suck sap from floral tissues.

Finally floral visitors included predators of the aforementioned visitors, e.g. coccinellid beetles (Coccinella septempunctata, Coccinella spp.) and ant foragers of aphid honeydew (Archimowitsch 1949). Despite the range of motivations for floral visitation, all these insects have the potential to be classified as pollinators, as they could incidentally acquire pollen on their bodies and visit another conspecific flower.

Bee pollination

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Though honey bees have been reported as “reluctant” to visit beet flowers, and will more readily forage on other floral resources, they have been known to pollinate beets

(Archimowitsch 1949). When assessing bee visitors to beet flowers, wild bee families

Halictidae, Megachilidae, Andrenidae and Anthophoridae are the most abundant visitors

(Popov 1952).

2.3.2.3 Cruciferae

2.3.2.3.1 Brassica oleracea

Pollination system and requirements

Cole (Brassica) requires insect-mediated pollination for seed production, but not to produce the marketable portion of the plant, the immature florets or leaf bunches

(Nieuwhof 1963). Cole crops are mostly self-incompatible, although this may vary slightly with the variety or age of the plant (Nieuwhof 1963).

Generally, Hymenoptera (Apis spp. and Bombus spp.) and Diptera (Calliphoridae and Syrphidae) are the most important pollinators of seed cole crops (Pearson, 1932;

Stanley et al., 2017).

2.3.2.3.2 Cauliflower

Pollination system and requirements

Cauliflower is attractive to insect visitors, with high nectar volume and sugar content (Selvakumar et al. 2006). Of the cole crops, it has the highest degree of self- compatibility (Nieuwhof 1963, Watts 1963). However, common hybrid varieties are self- incompatible (Selvakumar et al. 2006).

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Insect pollination

In India, honey bees (Apis dorsata, A. cerana and A. florea) are reported to be the most abundant and important pollinator for cauliflower (Selvakumar et al. 2006). However, it estimated that six visits from A. cerana is equivalent to eight visits from syrphid, Eristalis tenax; either is sufficient to achieve the highest pollination rate of 59% (Dhaliwal and

Bhalla 1981).

2.3.2.3.3 Cabbage

Non-bee pollination

Cabbage is highly self-infertile, requiring insect-mediated pollen transfer for successful pollination (Fang et al. 2005). Flies are regarded as moderately important pollinators for cabbage. Syrphids, including Episyrphus balteatus, Ischiodon spp., and

Eristalis tenax, were recorded as 26-32% of the flower visitors in the North Western Indian

Himalayas. Additionally, Diptera (Calliphoridae: Lucilia sericata) and Lepidoptera

(Pieridae: Papilio machaon, Pieris rapae, and Celastrina argiolus) were reported visiting cabbage flowers (Stanley et al. 2017). In California, Diptera (Syrphidae, Calliphoridae,

Muscidae) and some beetles were found visiting cabbage flowers; no pollen counts were provided (Pearson 1932).

2.3.2.3.4 Other Brassica crops

There insufficient information in the existing literature to determine the role of non- bee flower visitor in the pollination of Brussels sprouts, radish, kale and other Brassica crops.Cucurbitaceae

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2.3.2.3.5 Cucumber (Cucumis sativus)

Pollination system and requirements

Most varieties require insect pollination, increasing yield by up to three times

(Gingras et al. 1999). Barber and Starnes (1949) reports that 75% of yield is due to insect pollination alone. Varieties of seedless cucumbers grown in greenhouses do not require pollination as they are parthenocarpic (Free 1993).

Non-bee pollination

Barber and Starnes (1949) reported few visits from hoverflies (Diptera: Syrphidae), butterflies (Lepidoptera: Pieridae) and skippers (Lepidoptera: Hesperiidae) to cucumber flowers, but they do not report their relative abundance or comment on their efficiency as pollinators. Similarly, Motzke et al. (2015) reported fewer than 4% of flower visits from three butterfly species, three wasp species and eight fly species (Syrphidae, Tachinidae,

Miridae, Fannidae) in Indonesian cucumber crops.

Bee pollination

Bees often are reported to be the most abundant visitors to cucumber flowers making up 78% (Barber and Starnes 1949) to 96% (Motzke et al. 2015) of visits.

2.3.2.3.6 Pumpkin, Squash, Zucchini (Cucurbita pepo)

Pollination system and requirements

Flowers of Cucurbita pepo are distinctly male or female. Insects are required for pollination, as the pollen grains are too heavy and sticky to be carried by wind.

Bee pollination

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There are four main bee groups responsible for the pollination of C. pepo, honey bees (Apis mellifera), bumblebees (Bombus spp.), squash bees (Peponapis pruinosa) and gourd bees (Xenoglossa spp.; Petersen & Nault 2014). Most pollination assessments find more than 95% of the flower visitors belong to these four groups of bees (Matsumoto and Yamazaki 2013, Petersen and Nault 2014, Phillips and Gardiner 2015). Squash and gourd bees have specialized relationship with Cucurbita species, foraging exclusively on cucurbit pollen (Hurd et al. 1971, Willis and Kevan 1995). Thus, when natural populations of these bee species are abundant, their visits are usually sufficient for C. pepo pollination

(Tepedino 1981, but see Walters & Taylor 2006; Artz & Nault 2011). There are reports of non-bee pollinators landing on C. pepo flowers, however their relative abundances are sufficiently low they are not likely contributing any meaningful pollination services to the crop.

2.3.2.3.7 Pumpkin (Cucurbita pepo, C. moschata, C. maxima)

Non-bee pollination

Reports of non-bee visitors to pumpkin flowers include four fly species and two butterfly species from Pakistan, syrphid flies from Ohio, and syrphids, beetles, sawflies and ants from Japan (Matsumoto and Yamazaki 2013, Ali et al. 2014, Phillips and Gardiner 2015).

Bee pollination

There appears to be regional and temporal variation in which bee taxa are the dominant pollinator of pumpkin. A study in Ohio found variable results between years, with honey bees being the most abundant flower visitor (47%), followed by squash bees

(30%) in 2011, and bumblebees with 76% of visitation in 2012 (Phillips and Gardiner

30

2015). In Japan, 94% of flower visits were made by honey bees (Matsumoto and

Yamazaki 2013). In New York, the most abundant visitors were squash bees (52%;

Petersen, Huseth & Nault 2014). A study indicated that bumblebees deposited three times the amount of viable pollen to pumpkin stigmas, and came in contact with stigmas more frequently than squash bees or honey bees (Artz and Nault 2011). However, fields stocked with bumblebees (Bombus impatiens) did not increase fruit size or seed set

(Petersen, Huseth and Nault 2014). In Pakistan, different bee species were reported to be the best pumpkin pollinators, Nomia spp., Apis dorsata, and Halictus spp. (Phillips and

Gardiner 2015). Some researchers dispute whether wild pollination is sufficient at all (Artz and Nault, 2011; Petersen et al., 2014; Walters and Taylor, 2006). A study from Illinois reported that visitation rates by wild pollinators were not sufficient to reach maximum pollination (highest seed count and fruit weight). They found that the addition of honey bee colonies for supplemental pollination increased fruit weights by 26% for C. pepo, 70% for C. moschata and 78% for C. maxima (Walters and Taylor 2006). However, no pollination deficits were found in New York pumpkin fields (Petersen et al. 2014).

2.3.2.3.8 Summer Squash (Cucurbita pepo)

Non-bee pollination

Interestingly, a common pest of cucurbit species, the cucumber beetle (Acalymma vittata), was considered a summer squash pollinator (Durham 1928). Beetles

(Coleoptera: Chrysomelidae, Nitidulidae, Meloidae, Latridiidae) made up 63% of the insects collected in Kansas summer squash flowers (Fronk and Slater, 1956).

Additionally, ten species of flies (Diptera), four species of bugs (Hemiptera) and thrips

31

(Thysanoptera) were documented in flowers (Table 2; Fronk and Slater, 1956).

Furthermore, ants, beetles (Coleoptera: Scarabidae, Meloidae), flies (Diptera), and moths

(Lepidoptera) have been reported visiting squash flowers (McGregor, 1976).

Bee pollination

Honey bees and squash bees (P. pruinosa) can provide equal pollination services to summer squash. When squash bees are present, they will pollinate squash in the early morning, prior to honey bee activity (Tepedino 1981), and even male squash bees can deliver appropriate amounts of pollination (Cane et al. 2011). Thus, flowers are predominantly pollinated by squash bees; therefore, honey bees are not required in fields with healthy squash bee populations. In fact, if squash bees are sufficiently abundant, they deplete all the pollen from anthers prior to honey bee activity each morning, thereby preventing any role of pollination by honey bees. However, in the absence of squash bees, honey bees can provide an reasonable pollination service (Tepedino 1981).

2.3.2.3.9 Zucchini (Cucurbita pepo)

Pollination system and requirements

In greenhouses it is popular to use phytohormones or biostimulants to induce parthenocarpy, rather than rely on insects for pollination. However, there has been research into the effectiveness of pollination by insects, particularly bumblebees, for greenhouse zucchini pollination rather than chemical inputs (Roldán-Serrano and Guerra-

Sanz 2005).

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Bee pollination

In Spain, reports suggest that bumblebees (Bombus terrestris) are sufficient greenhouse pollinators for zucchini in the winter and fall, and honey bees (Apis mellifera) are sufficient in the spring (Gázquez et al. 2012). However, the highest yields were found when bumblebee pollination was augmented with biostimulants. There is insufficient research on the potential role of non-bee pollinators in zucchini.

2.3.2.4 Fabaceae

2.3.2.4.1 Soybeans (Glycine max)

Pollination system and requirements

Self-pollination is prominent in this species; however, a range of 0.6% to 6.2% outcrossing occurs in fields (Ray et al. 2003). Outcrossing by wind is minimal, with only

0.18 grains/cm2 of airborne pollen collected between rows (Yoshimura et al. 2006). Soy flowers are entomophilous, and as such, insects are suspected to be the vector of this observed outcrossing (Erickson and Garment 1979). Insect pollination is shown to increase soybean yield by 15%-18% in greenhouses and a 21% increase in field systems and 3-5% heavier seeds (Erickson et al. 1978, Blettler et al. 2018). Some studies report drastically higher yields with insect-mediated pollination, with up to 65% increase in pod number (Chiari et al. 2005).

Non-bee pollination

Thrips have repeatedly been considered for their role in soybean pollination (Free

1993, Yoshimura et al. 2006, de O Milfont et al. 2013, Santos et al. 2013). In Japan, thrips species, Frankliniella intonsa, was consistently the most abundant insect visitor to

33

soybean flowers, followed by predatory Hemiptera (Table 2). Records of beetles

(Monolepta dichoroa) and cabbage white butterflies (Pieris rapae) were also reported visiting soybean flowers (Yoshimura et al. 2006). A study conducted in Mississippi collected wasps, beetles and flies, and no bees (Table 2; Ray et al. 2003). Brazilian non- bee flower visitors included, flies (Diptera, mostly syrphids), thrips (Thysanoptera), bugs

(Hemiptera), beetles (Coleoptera) and butterflies (Lepidoptera; de O Milfont et al. 2013).

In Uruguay, flies (Drosophilidae: Drosophila), beetles (Chrysomelidae: Diabrotica speciosa) and thrips (Thripidae: Thrips) were recorded visiting soybean flowers, however bees were the most abundant visitors (Santos et al. 2013). A study from India reported muscid flies as abundant visitors to soybean flowers (Free 1993).

Bee pollination

There is a diverse community of wild bees (26 species) that visit soybeans in the

United States; however, only 6 of these species were found to have soybean pollen on their bodies. Bees with notable pollen were Megachile rotundata, Megachile mendica, and Dialictus testaceus (Rust et al. 1980). Supplemental provision of commercial honey bees has been shown to increase soybean yield (Erickson et al. 1978, de O Milfont et al.

2013, Blettler et al. 2018).

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2.3.2.5 Leguminosae

2.3.2.5.1 Faba beans (Vicia faba)

Pollination system and requirements

Insect-mediated pollination is required for sterile inbred plants, but not for hybrids.

About a third of faba bean crops are hybrids, which can self-fertilise and produce pods, the remaining two-thirds require insect mediated pollination (Kendall and Smith 1975).

The degree of self-pollination in faba beans varies greatly, from 1-79%, depending on environmental conditions and variety (McVetty and Nugent-Rigby 1984). However, insect pollination is still beneficial in self-fertile varieties and provides resilience to heat stress, preventing the usual 15% yield reduction noted at 30 °C (Suso et al. 1996, Bishop et al.

2016).

Bee pollination

Flower visitation by honey bees has been found to increase yield by 17% in a field setting (Cunningham and Le Feuvre 2013). All bumblebee species and honey bees are equally efficient pollinators when entering the flower from the front. However, short- tongue bumblebees tend to bite holes in the sides of flowers for access to nectar from the side, termed (primary) nectar robbing. These holes are subsequently used by honey bees engaging in secondary nectar robbery. Although, robbers were not as effective at pollination, fruit set was higher than seen in unvisited flowers (Kendall and Smith 1975).

No literature was found regarding the potential role of non-bee pollinators.

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2.3.2.5.2 Runner beans (Phaseolus coccineus)

Pollination system and requirements

While the majority of research indicates runner beans require insect pollination

(Darwin 1876, Mackie and Smith 1935, Free 1966, Łabuda 2010), contradictory evidence also exists (Tedoradze 1959).

Non-bee insects that potentially contribute to pollination of runner beans are pollen beetles (Meligethes spp.) and thrips (Blackwall 1971). Free (1993) found blowflies

(Diptera: Calliphoridae) were ineffective pollinators compared to honey and bumblebees, resulting in pollination rates similar to plants from which insects had been excluded. Their inefficiency is likely a result of the inaccessibility of the floral nectaries due to the length of their proboscis (Free 1993). While information regarding temperate non-bee insect visitors is limited, (see Free 1993), there is some recent work describing insect visitors in tropical regions, including Lepidoptera (Pieridae Eurema spp., Lycaenidae), Coleoptera

(Meloidae, Lagriidae Lagria villosa), Hymenoptera (Vespidae: Belonogaster juncea,

Polistes spp.) from Cameroon (Fohouo et al. 2014). In Costa Rica, several non-bee hymenopterans were recorded visiting runner beans, including: wasps (Vespidae

Synagris cornuta, Sphecidae Philanthus triangulum), and ants (Formicidae Camponotus flavomarginatus; Pando et al. 2011).

Bee pollination

The evidence for bee pollination is similar to that for faba beans. Bumblebees and honey bees have similar pollination efficiency when flowers are visited from the front,

36

while robbers did not significantly increase pollination from that of non-visited flowers

(Kendall and Smith 1976).

2.3.2.5.3 Green beans (Phaseolus vulgaris)

Pollination system and requirements

Cross pollination is not sought after in green beans. Cultivar purity is critical, so that selected traits remain undiluted. Additionally, insect pollination is not required, and does not increase yield, as the flowers are self-pollinated (Free 1993).

Non-bee pollination

Typically about 1% cross pollination is found in green bean fields, the vector is suspected to be the western grass thrips (Frankliniella occidentalis; Mackie and Smith,

1935). This species is found in significant numbers with considerable amounts of pollen on each individual. This thrips is not to be confused with the common bean thrips

(Hercothrips fasciatus) that causes leaf feeding damage (Mackie and Smith 1935).

Frankliniella occidentalis is the only plausible vector route for cross-pollination in field beans, as foraging honey bees and bumblebees could not result in cross pollination due to the timing of floral maturation.

Bee pollination

Carpenter bees are common pollinators of green beans in tropical areas. For example, Xylocopa olivacea was found to be an efficient pollinator in Cameroon and X. calens in Costa Rica (Pando et al. 2011, Fohouo et al. 2014).

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2.3.2.6 Liliaceae

2.3.2.6.1 Asparagus (Asparagus officinalis)

Pollination system and requirements

Asparagus requires insect pollination to set seed, producing an average of 776g of seed per female plant, compared to the 6g produced when no insect-mediated pollination is provided (Eckert 1956).

Bee pollination

Wild bee visitation rates are fairly low, with a single bee visit reported every few hours. Insect flower visitors include Bombus pratorum, B. pascuorum, and B. terrestris.

On average, each of these bumblebees had 83 grains of asparagus pollen on their ventral side, representing about 35% of their total pollen load. Megachile leachella bees averaged 195 asparagus pollen grains, representing 58% of total pollen load (de Jong et al. 2005). Honey bees are often used to supplement insect pollination to acquire fertile seeds for asparagus propagation (Walker et al. 1999). Research on asparagus pollination is slim and requires further investigation to determine if any non-bee insects visit and pollinate these flowers (Free 1993).

2.3.2.7 Solanaceae

2.3.2.7.1 Bell Pepper (Capsicum annuum)

Pollination system and requirements

Bell pepper plants are self-fertile; however, fruit set is significantly enhanced when supplemental insect pollination is provided (McGregor 1976).

Non-bee pollination

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Bell pepper crops might be pollination limited in some settings, as hand pollination can produce significantly more fruit set compared to either honey bee pollination alone

(produced 30% of fruit set by hand pollination) or flies (Calliphora and Lucilia spp.), which resulted in 10-20% of fruit set compared to hand-supplemented pollination (Burnie and

Pochard 2000). In contrast, commercial use of the syrphid fly Eristalis tenax has been shown to increase fruit quality and size of greenhouse peppers (Jarlan et al. 1997).

Additionally, ants have been reported to enhance pollination in peppers (McGregor 1976).

Bee pollination

Honey bees, bumblebees, leafcutter bee (Megachile rotundata) and mason bees

(Osmia cornifrons) are successfully used in greenhouse pollination of bell peppers

(Kristjansson and Rasmussen 1991, de Ruijter et al. 1991, Shipp et al. 1994, Serrano and Guerra-Sanz 2006). Most (90%) visitors to bell pepper flowers in Brazil belonged to four bee species: Apis mellifera, Paratrigona lineata, Trigona spinipes, and Tetragonisca angustula (Pereira et al. 2015). Hot pepper (Capsicum annuum) flowers were reported to be solely visited by bees in Brazil (Raw 2000).

2.3.2.7.2 Eggplant (Solanum melongena)

Pollination system and requirements

Like most Soleanaceious plants, eggplant (Aubergine) flowers require sonication or buzz-pollination (McGregor 1976). There is some divergent evidence regarding the degree to which eggplants are pollinator dependent. While results in Jamaica found no evidence that eggplants require insect pollination (Free 1993), another study estimated

60% of eggplant pollination comes from insect pollination, the remaining 40% being a

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combination of wind and gravity (Sambandam 1964). However, hybrid eggplants are

100% reliant on insects for pollination (Free 1993).

Non-bee pollination

Hoverflies (Syrphus spp. and Toxomerus spp.) have been observed to visit eggplant flowers in urban studies in Chicago, and their visitation rates are significantly correlated with seed (Lowenstein et al. 2015). Further investigation is required to determine whether any other non-bee insects visit eggplant flowers, and whether they are effective pollinators. However, given that the flower does not provide nectar, visits are likely to be rare. Furthermore, the inability of non-bee insects to sonicate (buzz-pollinate) the anther means they are not likely to contribute significantly to eggplant pollination.

Bee pollination

Honey bees do not readily forage on eggplant due to its lack of nectar production and low pollen yield (McGregor 1976, Free 1993). Despite their inability to sonicate flowers, honey bees foraging in a greenhouse setting produced eggplants weighing approximately one-and-a-half times that of those that did not have honey bees; however, there was no significant increase in the number of fruit (Levin 1989). Bumblebees, which can sonicate very effectively, are found to be efficient pollinators of eggplant, increasing yields in greenhouses by 22% (Abak et al. 1998). The native bumblebees to Brazil are not commercialized; therefore, an alternative native species is valuable to prevent introduction of European species. The native stingless bee Melipona fasciculata can also sonicate and has been shown to be an effective pollinator in eggplant greenhouses in

Brazil (Nunes-Silva et al. 2013).

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2.3.2.7.3 Tomato (Lycopersicon esculentum)

Pollination system and requirements

Tomato is self-fertile and self-pollinating, so does not require insects to produce fruit (Free 1993). However, despite an efficient self-pollinating mechanism, tomatoes grown in greenhouses often do not produce marketable fruit without hand or insect- mediated pollination (McGregor 1976). Greenhouse tomatoes set only ~60% fruit without supplemental pollination (Banda and Paxton 1991). Moreover, F1 hybrids, which require cross-pollination, are sought after and also require hand or insect-mediated pollination.

Non-bee pollination

There are limited records of tomato flower visits by Diptera: Brewer & Denna

(2009) report ‘a few flies’ on the flowers, but state they are not likely contributing to pollination.

Bee pollination

Tomatoes yield the best fruit when sonicating insects visit the flowers. Fruit set was 75% when visited by honey bees, 90% with mechanical vibration (by hand) and 98% by bumblebee pollination in a greenhouse setting (Banda and Paxton 1991). Thus, commercial bumblebees are now typically used in greenhouses for pollination in most parts of the world. The most common commercial bumblebee species in North America is Bombus impatiens. However, use of native bumblebees is being assessed for greenhouse pollination in order to reduce the importation of non-native bees and decrease introduction of pathogens (Strange 2015). For example, Bombus vosnesenskii and B. huntii are equally effective pollinators of tomatoes compared to B. impatiens, while

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B. occidentalis was less efficient, requiring higher stocking densities in order to compensate (Dogterom et al. 1998, Whittington and Winston 2004, Strange 2015).

Bombus terrestris, B. hypnorum, and B. pascuorum were also found to be effective for producing F1 hybrids in a greenhouse setting, while B. hortorum was comparatively less efficient (Pinchinat et al. 1979). Commercial tomato plants (Lycopersicon esculentum) grown in the field are not found to be attractive to any insects, while L. peruvianum (a

Peruvian tomato species) attracted honey bees and multiple species of bumblebees, the most common visitor being B. griseocollis (Brewer and Denna 2009).

2.3.3 Nuts

2.3.3.1 Rosaceae

2.3.3.1.1 Almond (Prunus dulcis)

Pollination system and requirements

Almond trees are self-incompatible, requiring insect-mediated cross-pollination

(Tufts and Philp 1922, Connell 2000). Movement of pollen between different varieties in adjacent or nearby rows in almond orchards is important for fruit set. Pollinators of this crop must be resistant to poor weather conditions as the bloom period in February is often accompanied by inclement weather (Connell 2000, Dag et al. 2006). Pollen viability degrades quickly within the flower; as such, pollen that is distributed in the morning, closer to the time of dehiscence, will contribute more to pollination (Dag et al. 2006).

Non-bee pollination

The insect diversity caught in pan traps in Australian almond orchards demonstrates that the overwhelmingly dominant order is Diptera (93% of trapped

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abundance), followed by wasps (4%) and native bees (3%). Tachinidae and Calliphoridae were the most abundant dipteran families, and Diapriidae and Braconidae were the most abundant wasp families from these samples (Saunders et al. 2013). The abundance and richness of hymenopteran groups are influenced by the amount of ground cover and plant richness of orchards, while dipteran diversity remained consistent regardless of ground cover. Orchards with no ground cover supported no wild bees (Saunders et al. 2013).

These findings are supported by another Australian study in which pan traps caught 82%

Diptera (Dolichopodidae, Tachinidae, Chloropidae, Phoridae, Drosophilidae,

Heleomyzidae, Calliphoridae, Muscidae, Platypezidae), 12% wasps (Diapriidae,

Scelionidae, Pteromalidae, Braconidae, Eulophidae, Ceraphronidae, Ichneumondiae,

Mymaridae), and 6% wild bees (Lasioglossum; (Saunders and Luck 2014). While these studies did not sample insects on almond flowers, these results suggest that monoculture almond orchards, without any surrounding natural habitat, support a less diverse potential wild pollinator community (Saunders and Luck 2014). California almond orchards are heavily stocked during bloom with managed honeybees. Ignoring these managed honey bees, the proportion of wild insect visitations are around 37% wild bees, 33% hoverflies, and 30% other insects (i.e., primarily other flies: Bombyliidae, Muscidae, and ants

Formicidae; Klein et al. 2012). The abundance and diversity of wild insect visitors was positively correlated with quantity of surrounding natural habitat, which in turn was positively correlated with almond fruit set (Klein et al. 2012). The abundance of these wild pollinators was higher in organic orchards, while species richness remained constant

(Klein et al. 2012). Hoverfly visitation frequency was increased in organic orchards

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independent of available surrounding natural habitat, while wild bees required 10% natural habitat surrounding in order to increase visitation frequency (Klein et al. 2012). All orchards had substantial edge effects for wild insect pollinators, with a greater abundance and diversity at orchard margins than in the interior. Hoverfly visitation frequency was the most closely positively correlated to almond fruit set (Klein et al. 2012).

Bee pollination

Honey bees hives are often placed in almond orchards to increase pollination services (Traynor 1993, Connell 2000, Dag et al. 2006). A study conducted in California almond orchards showed a strong positive correlation of honey bee visitation and hive stocking densities. However, the visitation frequency of honey bees did not correlate to almond fruit set. Inversely, wild insect visitation frequency was positively correlated with fruit set (Klein et al. 2012). Despite the habit of honey bees choosing to forage on flowers along the same row, thus mainly collecting incompatible pollen, their services are often complemented by wild pollinators (Thorp 1979, Yong et al. 2012, Broly et al. 2013). Wild pollinators (bees, hoverflies, and other visitors – mostly flies) have demonstrated a preference to forage from the bottoms of trees, while honey bees prefer to forage at the tops of almond trees (Brittain et al. 2013). As such, this is an example of spatial complementarity, where the preferences of one group are different than the other, and thus the pollinator community as a whole provides a full pollination service. Additionally, pollinator communities which are predominately honey bees will likely provide little or no pollination services in high winds, as honey bees do not forage under these conditions

(Brittain et al. 2013). A diverse pollinator community will deliver crop pollination services

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despite high winds, as wild bees and flies will continue to forage in these conditions. This demonstrates functional redundancy, that more than one taxa can perform a function and their unique preferences allow for a better service provisions in spite of changes in the system (Brittain et al. 2013). Interestingly, the majority of honey bees within an orchard have compatible pollen on their bodies, likely due to the change in behaviour they exhibit due to interactions with other insects diverting their linear course (Greenleaf and Kremen

2006, Yong et al. 2012). The interspecific interactions of all foraging insects result in a more dispersed distribution of pollination services resulting in homogenous fruit set

(Morse 1981).

Commercial augmentation of bumblebee hives has also been used to enhance pollination in almond orchards. While honey bees and bumblebees deposit an equivalent amount of pollen per visit, bumblebees are more effective pollinators (Thomson and

Goodell 2002), likely because of their lower temperature tolerance for foraging and their more sporadic flight patterns resulting in more frequent cross-pollination events between rows (Dag et al. 2006). The mason bee Osmia cornuta is a more efficient pollinator than honey bees. These mason bees contact the stigma with nearly every flower visit, whilst honey bees only contacted the stigma 40-63% of the time. Osmia cornuta also visit more flowers and support higher rates of cross-pollination than honey bees (Bosch and Blas

1994). Additionally, O. lignaria, a native bee to California, has been shown to be an effective almond pollinator, allowing honey bee stalking densities to be halved. This mason bee species is available commercially, and the numbers of wild bees can be

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naturally augmented via enhancing nesting environment (Artz et al. 2013). Furthermore, the use of O. lignaria has been shown to be economically beneficial (Koh et al. 2018).

2.4 Discussion

My extensive survey of the literature reveals that there is a general dearth of information relating to the role of non-bee flower visitors in the pollination of temperate fruit and vegetable crops. However, sufficient evidence exists to demonstrate there is a diverse assemblage of non-bee insects visiting crop flowers and likely contributing to pollination (Appendix 1). There are a few selected crops, predominately from the

Solanaceae family, for which non-bee pollinators do not enhance pollination services; however, this represents a small proportion of the crops assessed (Table 2.1). There was insufficient evidence of non-bee insects fulfilling roles as pollinators for zucchini, asparagus, and some cole crops. The role of non-bee pollinators is particularly important in communities where non-bees are more abundant than bee populations. In these scenarios, regardless of their pollination efficiency, non-bee insects are likely to have an large role in pollination (Rader et al. 2016). In accordance with previous literature, hoverflies are ubiquitous among crop flowers (Solomon and Kendall 1970, Holloway

1976, Bańkowska 1980, Grass et al. 2016). Hoverflies are increasingly acknowledged for their role in crop pollination and are used commercially for greenhouse pollination for a number of crops, including onion, bell pepper, and beans (Currah and Ockendon 1983,

Jarlan et al. 1997, Haenke et al. 2014). While non-syrphid Diptera are likely important pollinators, we don’t yet know how important due to a general lack of studies trying to investigate this question (Orford et al. 2015). Furthermore, the remaining diverse taxa of

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beetles, butterflies, thrips, ants, bugs, and lacewings, which have been observed frequently visiting select crop flowers, have not been thoroughly assessed for their significance in pollination.

Determining the identity and the pollination efficiencies of these non-bee visitors is the first step to incorporating them into future pollination assessments. Furthermore, determining how their foraging preferences and tolerances might differ from well-known bee taxa across the extent of spatial, temporal and environmental variance that they encounter in the field will reveal the importance of their role. Previous evidence demonstrates that non-bee pollinators have an increased resilience to dealing with the impacts of land-use change and climatic stress factors (Biesmeijer et al. 2006, Meyer et al. 2009, Jauker et al. 2009, Grass et al. 2016, Rader et al. 2016). With inclement shifts in climate with increasing land-use, there is an increasing urgency to determine complementary species which will augment pollination services. This review provides the most rigorous collection of literature outlining the most up to date list of potential non-bee pollinators of temperate vegetable crops. This is particularly important as it demonstrates the diversity of insect taxa that visit crop flowers, and likely engage in pollination, and highlights that these taxa should be considered in future pollination assessments.

Furthermore, the wider importance of non-bee pollinators for resilient and sustainable crop pollination should be acknowledged and conveyed in public engagement, conservation efforts, agricultural management practices and government policy.

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3 Chapter 3: Assessing non-bee flower visiting community of day-neutral strawberries

3.1 Introduction

Pollination services are critical for most agricultural production (Klein et al. 2007) and these services are often solely credited to bees (Woodcock 2002, Dicks et al. 2013).

While bees are obligate nectar and pollen foragers, and are often the most efficient pollinator per visit, they are not the sole providers of this important ecosystem service

(Müller et al. 2006; Chapter 1, 2). There is a wealth of other insect flower visitors from other large orders, such as flies, beetles, wasps, moths and butterflies. This means there are more than 330,000 species which may provide pollination services that are often unaccounted for in public and political views; this trend is reflected in scientific research of pollinators (Wardhaugh 2015, Ollerton 2017). This is despite evidence showing that diverse pollinator assemblages leads to better pollination services; resulting in higher fruit set and fruit weight with fewer blemishes due to insufficient pollination (Nye and Anderson

1974, Lopez-Medina et al. 2006, Hodgkiss et al. 2018).

The importance of diversity in agricultural pollination is derived from the evenness of the service. Each species has its own foraging preferences and tolerances, which result in more thorough visitation of flowers and transfer of conspecific pollen (Fontaine et al.

2005, Blüthgen and Klein 2011, Garibaldi et al. 2013, 2014, Rogers et al. 2014). Some insect communities are abundant early in the growing season, maintaining large populations for pollination services for only a week or two, while others have peaks later in the season, while others still have a lower population density that is sustained

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throughout the season (Bartomeus et al. 2013). Thus, there is always a large pollinating community with potentially complementary and overlapping population peaks (Garratt et al. 2018). Additionally, each species may prefer different areas to forage; honey bees for instance tend to prefer to forage along the tops of trees, and travel in a linear fashion, following crop row, while solitary bees and flies tend to forage on lower branches in a more sporadic pattern (Klein 2011). This is beneficial so that not just lower or just upper branches are pollinated, and thus the whole tree receives pollination and therefore sets fruit. Finally, different environmental conditions can affect which insects are foraging. High winds and cloudy days tend to keep honey bees inside their hives, while flies, bumblebees and some solitary bees will continue to forage in the rain and the cold (Morgan and

Heinrich 1987, Klein 2011).

Species-level identification of non-bee pollinators is critical for their inclusion in passive sampling methods. Given the taxonomic breadth of flower visitor communities

(Appendix 1), the number of taxonomic experts required for accurate species-level identification is substantial and typically unobtainable. For these reasons I decided to employ genetic methods for flower visitor specimen identifications. The cytochrome c oxidase I (COX1) gene is an established protein-coding region in animal DNA that is relatively conserved within a species and divergent among species; thus, this gene is able to distinguish species from just a small sample (Hebert et al. 2003a). The identification of plant pollen has traditionally been achieved using light microscopy, comparing samples to an extensive and palynological collection; however this method often restricts taxonomic resolution to the genus or family level and requires expertise in these

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comparative methods (Rahl 2008, Keller et al. 2015). Emerging metabarcoding methods have been explored for their accuracy in the qualification and quantification of pollen samples (Bell et al. 2019). Metabarcoding uses high-throughput sequencing to concurrently barcode multi-species samples, allowing identification of all the plants within a pollen sample (Cristescu 2014). The resulting sequences are queried against a reference database, attaching a taxonomic name to the sequence; therefore, it is important to use standardized gene regions with robust reference libraries. The CO1 gene has been found insufficient for identification of plants; rather, the Consortium for the

Barcode of Life has chosen the plastid gene regions of rbcL and matK as standard DNA barcode identifiers (CBOL Plant Working Group 2009). A robust rbcL reference library is available for the plants of Canada, with the highest coverage of species, with 168 families comprising 4,790 species (compared to matK with 118 families and 2,000 species;

Braukmann et al. 2017). The rbcL gene provides good assignment of taxa at the genus level, but performs comparatively poorly at the species level (Braukmann et al. 2017).

This study focused on defining non- bee flower visitors (i.e. putative pollinators) in strawberry crops. Day-neutral strawberries have been engineered to provide fruit for the whole summer growing season (late April to late September in Ontario). Thus, flowers were available for prolonged sampling, providing a valuable temporal scale, and simultaneously increased chance of a wide spectrum of environmental conditions.

Strawberries are capable of wind pollination; however, insect-mediated pollination increases the evenness of pollen deposition, resulting in more symmetrical and larger fruits that are marketable produce (Section 2.3.1.2.1. Strawberry (Fragaria); Klatt et al.

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2014). The primary goal of this study was to determine which non-bee visitors are probable pollinators of strawberry crops. We used barcoding methods to provide species- level identifications of the non-bee flower visiting community. The pollen loads collected from the bodies of non-bee flower visitors were quantified and metabarcoded for identification. Metabarcoding provided genus-level identification of the floral community that each insect species visited, allowing me to generate a plant-pollinator network and assess floral fidelity. The taxonomic resolution for plants remained at the genus-level because of the resolution of the markers chosen in this study (Section 3.2.4). Species with a high floral fidelity (flower constancy) for visiting strawberries were likely to be more effective pollinators (vectors of conspecific pollen between reproductively receptive strawberry plants). Additionally, small amounts of pollen from other plant genera suggested that the insect was active and mobile, rather than staying stationary on a single flower. Secondly, this study assessed how the non-bee floral visiting communities changed across the season and in response to variation in local environmental conditions, including temperature, humidity, solar radiation, and wind speed.

3.2 Methods

3.2.1 Field Sites

Three strawberry fields from Southern Ontario were selected for their large-scale crop production, allowing consideration of potential edge-effects. Since size of crop was the presiding selection criteria, fields had differing crop varieties, surrounding habitat and pollinator-friendly additions, or lack thereof. Fields were within 120 km of each other and within a latitudinal gradient of 0.15 degrees. The narrow latitudinal gradient was to

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increase the similarity in flowering time and temperature fluctuations. All fields had a seven-day spraying rotation; however, the pesticides used are largely unknown and therefore are not considered. Each field was sampled weekly between May 1st and August

31st of 2018 when the crop reached at least 20% bloom. Bloom percentage was assessed by walking up a row from the field edge and counting the number of flowers on each side, to a depth of 50 flowers (100 flowers total); this was repeated in the field centre, and numbers were averaged.

3.2.2 Field Sampling

Sampling took place from 09:30 to 16:00 and consisted of five, hour-long periods followed by a 30-minute break. Each 60-minute period was divided into a 30-minute active sampling period and a 30-minute observation sampling period. During active sampling periods non-bee flower-visitors (excluding Lepidoptera and Drosophila spp.) were collected directly into sterile vials. Lepidoptera were excluded from these collection samples, because the scales from Lepidoptera wings would disrupt the quantification of pollen found on individuals. Drosophila spp. were excluded because they were far too numerous to capture without affecting the capture rate of other specimens. These were placed in a small cooler containing freezer packs at the end of each 30-minute sampling to minimize grooming behaviour and regurgitation. The remaining 30 minutes of each sampling hour were for observation sampling, where all flower-visiting insects were identified to the lowest confident taxonomic unit (aiming for species level identifications when possible). This approach provided a non-lethal sampling method to determine the insect community (including bees) and eliminating collector bias. A small number of bees

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were sporadically collected, to provide comparative pollen quantification and qualification.

Because this sampling was not standardized, the abundance of these collections cannot be considered representative of true populations; only observational data are representative of bee abundance at each site. The order of active and passive sampling portions of each hour periods were randomly selected. Sampling periods rotated between edge habitat (the edge of the crop, to 50 m into the interior) and interior habitat (at least

60 m into the crop), while randomizing whether the first period was interior or exterior.

Measurements were collected for wind speed, rainfall, humidity, and temperature using

AcuRite weather station and solar radiation using TES 1333R Solar Power Meter, every half-hour. These environmental measurements were averaged for each 90-minute period

(including 1 hour sampling and 30-minute break period), for the analysis.

3.2.3 Pollen Removal and Quantification

Pollen from the exterior of insects’ bodies was removed following the protocol by

Lucas et al., (2018). Each specimen was washed in 500 µL of wash solution containing

2% PVP and 1% SDS (buffer solution) using a 1.5 mL Eppendorf tube. For larger specimens (>8 mm) additional wash solution was added until they were submerged.

Blanks, tubes filled with wash solution, were placed under a sterile hood to detect contamination from pollen dispersal during specimen handling. They were processed identically to other samples. The specimens were agitated by hand for 1 minute and then centrifuged at 158,000 rcf for 20 seconds, to ensure the specimen was submerged in the washing solution. The specimens were allowed to sit for 5 minutes and were shaken for an additional 20 seconds in order to resuspend any pollen accumulated on the insects’

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body during the centrifuge spin. The insects were then removed from the Eppendorf tube and stored in 95% ethanol. The remaining washing solution and suspended pollen were centrifuged at 158,000 rcf for 5 minutes, in order to form a pollen pellet at the base of the tube. Supernatant was removed and discarded; samples were stored at -20°C.

The pollen pellet was then resuspended in 250 µL of 95% ethanol by vortexing for

4 minutes. Samples that were difficult to homogenize were heated at 56°C for 5 minutes and vortexed for an additional 4 minutes. An aliquot of 50 µL was taken and dried in a sterile incubation oven for quantification; the remainder was used for metabarcoding.

Pollen counts were determined for each sample using a Multisizer 3 Coulter Counter

(Beckman Instruments, Fullerton, CA, USA). A blank of 10 mL of Isoton II diluent was measured in a 30 mL cuvette and used to calibrate the machine to background particles for each sample. The pollen sample was suspended in 300 µL of diluent by vortexing for

10-20 seconds. This pollen suspended diluent was added to the background blank cuvette. Additional diluent was added to reach 11 mL of liquid. The cuvette was gently vortexed for 3-5 seconds to homogenize the sample. The coulter counter was then used to take three 1 mL samples to quantify the number of particles in the size range 10-120

µm; the sample was agitated by swirling between each of the replicates.

3.2.4 Molecular Identification

Each insect specimen had a leg or tarsus (depending on the specimen size) removed for Sanger sequencing of the Folmer region (Folmer et al. 1994) of the

Cytochrome c oxidase I (COI) gene (Table 3.1), samples were processed at the Canadian

Centre for DNA Barcoding (CCDB; www.ccdb.ca). DNA extraction was an automated 54

process following a modified protocol described by Ivanova et al. (2006) using a silica membrane-based extraction performed in 96-well microplate layout using a 3 μm glass fibre over 0.2 μm Bio-Inert membrane filter plate (Pall Corporation). To maximize DNA yield, tissue lysis was performed overnight at 56°C before DNA extraction. PCR amplification of the COI barcode region was performed with a total PCR reaction volume of 6 μL: 3 μL of 10% D-(+)-trehalose dihydrate for microbiology (≥99.0%; Fluka

Analytical), 0.92 μL of ultra-pure water (Hyclone, Thermo Scientific), 0.60 μL of 10×

PlatinumTaq buffer (Invitrogen), 0.30 μL of 50 mM MgCl2 (Invitrogen), 0.06 μL (0.1 μM) of each primer (C_LepFolF/C_FepFolR; Hernández-Triana et al. 2014), 0.03 μL of 10 mM dNTP (KAPA Biosystems), 0.03 μL of 5 U/μL PlatinumTaq DNA Polymerase (Invitrogen), and 1 μL of DNA template. All PCR reactions employed the same thermocycling parameters: 94°C for 1 min; 5 cycles at 94°C for 40 s, 45°C for 40 s, and 72°C for 1 min; followed by 35 cycles at 94°C for 40 s, 51°C for 40 s, and 72°C for 1 min; and a final extension at 72°C for 5 min.

PCR products were diluted 1:4 with molecular grade water and then sequenced with a total sequencing reaction volume of 5.5 μL: 0.14 μL of BigDye terminator v3.1

(Applied Biosystems), 1.04 μL of 5X sequencing buffer (400 mM Tris-HCl pH 9.0 + 10 mM MgCl2 (Invitrogen)), 2.78 μL of 10% D-(+)-trehalose dihydrate from Saccharomyces cerevisiae(≥99%; Sigma-Aldrich), 0.48 μL of ultra-pure water (Hyclone, Thermo

Scientific), 0.56 μL (0.1 μM) of primer. All sequencing reactions employed the same thermocycling protocol: 96°C for 1 min; followed by 15 cycles at 96°C for 10 s, 55°C for 5 s, and 60°C for 85 s; followed by 5 cycles at 96°C for 10 s, 55°C for 5 s, 60°C for 105 s,

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and then 60°C for 15 s; followed by 15 cycles at 96°C for 10 s, 55°C for 5 s, and 60°C for

2 min; and a final extension at 60°C for 1 min. An automated, magnetic bead-based sequencing cleanup method was employed using PureSEQ (ALINE Biosciences) before sequencing on an ABI 3730xl DNA Analyzer (Applied Biosystems).

Pollen DNA was extracted using a modified CCDB glass fibre protocol (Ivanova et al. 2006). The remaining 200 µL of ethanol suspended pollen samples were dried via evaporation under a sterile hood and resuspended in 300 µL of insect lysis buffer and then transferred into 8 plates with microbeads (MP Biomed, lysis matrix E, OH, USA).

Samples were randomly assigned a location in the plate matrices. In order to detect contamination, 116 negative controls were added into the matrices, randomly assigned with at least one negative control per column in the 96 well plate matrix. Pollen grains were pulverized by shaking samples at 28 Hz for two minutes. Samples were incubated at 56°C for 2 hours, followed by 1 hour at 65°C. Samples were not agitated during the incubation process in order to reduce contamination. 6M GuSCN buffer was added to lysate in a (2:1 to lysate, 400 µL to 200 µL), mixed briefly by vortexing, centrifuged at

1000 x g for 20 seconds. The lysate was transferred to a glass fibre plate and centrifuged at 5000 x g for 5 minutes, followed by the addition of 300 µL of binding mix and centrifuged at 5000 x g for 2 minutes. The glass fibre plate was then washed twice with 600 µL of wash buffer and spun down at 5000 x g for 5 minutes. The plate was spun for an additional

5 minutes at 5000 x g to dry the plate. The plate was incubated at 56°C for 30 minutes.

DNA was eluted into a PCR plate with 25 µL of elution buffer and incubated at 56°C for 1 minute and then centrifuged at 5000 x g for 5 minutes. To assess plant diversity, we

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amplified a 184 bp fragment of rbcL (large subunit of RuBisCo) using rbcL1 and rbcLB

(Palmieri et al., 2009). The rbcL fragment was chosen over other genes because of the completeness of the rbcL reference library for plants in Canada, while other genes may have provided better taxonomic resolution but also more primer bias (Braukmann et al.

2017). The rbcL gene fragment was amplified using PCR with Qiagen multiplex plus

(QIAGEN, Hilden, Germany), which was selected for its performance with mixed templates, and the primers for mini-barcodes F (rbcL1/rbcLB; Palmieri et al., 2009), previously tested for efficiency of amplification of degraded DNA (Table 3.1; Little, 2014).

Amplification was performed under the following thermal conditions: 5 minutes at 95°C;

35 cycles of 30 s at 95°C, 30 s at 50°C, and 1 min at 72°C; 5 min at 72°C; then held at

4°C. The 25 µL PCR reaction mix included 12.5 µL of Master Mix, 1.25 µL of each 10X

PCR forward and reverse rbcL primer (F mini-barcode) and 10 µl of DNA template

(Palmieri et al. 2009, Little 2014). PCR amplicons were visualized on a 1.0% agarose gel using GelRed® Nucleic Acid Gel Stain (Biotium, Hayward, CA, USA). A total of 284 samples were selected for the libraries. Samples were indexed with a secondary PCR, and run under the same thermal conditions. PCR reaction mix included 12.5 µL of Master

Mix, 9 µL of molecular grade water, 1.25 µL of each 10X PCR forward and reverse primer with custom tags (Elbrecht and Steinke 2018) and 1 µL of DNA template. The samples were combined and cleaned using SequalPrep™ Normalization Plate Kit (Invitrogen,

Thermo Fisher Scientific Inc., MA, USA) according to manufacturer’s instructions, to remove primer dimers. Three libraries were created and pooled. The product was quantified using a Qubit Fluorometer with the Qubit dsDNA HS Assay Kit according to

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manufacturer's instructions. The three libraries were sequenced using Illumina MiSeq at

the Genomics Facility, Advanced Analysis Centre at the University of Guelph.

Table 3.1: Primers used for barcoding Cocktail Primer Sequence (5'-3') Orientation Reference rbcL1 TTGGCAGCATTYCGAGTAACTCC Forward Palmieri et al. 2009 rbcLB AACCYTCTTCAAAAAGGTC Reverse Palmieri et al. 2009 C_LepFolF LepF1 ATTCAACCAATCATAAAGATATTGG Forward Hebert et al. 2003a, 2003b LCO1490 GGTCAACAAATCATAAAGATATTGG Folmer et al. 1994 C_LepFolR LepR1 TAAACTTCTGGATGTCCAAAAAATCA Reverse Hebert et al. 2003a, 2003b HCO2198 TAAACTTCAGGGTGACCAAAAAATCA Folmer et al. 1994

3.2.5 Data Analysis

3.2.5.1 Pollen Quantification Analysis

Pollen loads were assessed by comparing non-bee insect visitors to the genus of

bee with the largest pollen loads, Halictus, using a generalized linear model (GLM) using

quasi-poisson distribution. A GLM was used in place of a linear model to account for the

non-normal distribution of the data. The data were overdispersed, so a quasi-poisson

distribution was used (Ver Hoef and Boveng 2007). The pollen counts for each respective

genus was the response variable. Each non-bee genus was treated as a factor and input

as explanatory variables. Visualizations of pollen loads and insect abundance were

presented using TreeMaps generated in R (version 2.5-5). In order to assess total

available pollen contribution, data from observations were combined with pollen counts

from collected specimens, total pollen = observed abundance x average pollen count

(Tables 3.2, 3.3). The percentage of total pollen was calculated by taking the average

pollen load for each insect taxon and dividing by the absolute sum of total pollen counts

(Table 3.3). 58

3.2.5.2 Barcoding Analysis

Trace files were manually uploaded to the Barcode of Life Data system (BOLD) and were automatically assessed for quality based on predefined parameters

(Ratnasingham and Hebert 2007). Trace files that received medium- and high-quality assessments were automatically trimmed and edited by the BOLD platform. Those deemed low quality, or classified as failed reads, were ignored. Trimming was performed using a sliding window approach, discarding leading and trailing segments of the sequence that had more than 4 bp with a quality value (QV) score lower than 20 in a window of 20 bp. All sequences with less than 500 bp in the barcode region (the threshold for BIN assignment; see below) were manually edited with CodonCode v. 3.0.1

(CodonCode Corporation) to see if additional sequence information could be recovered.

Barcode Index Number (BIN, proxies for species distinguished sequences without an assigned taxonomic name) associations, or species-level identifications, were assigned using the RESL algorithm in BOLD (Ratnasingham and Hebert 2013).

Pollen metabarcoded libraries were analyzed using JAMP

(https://github.com/VascoElbrecht/JAMP). In summary, the pipeline demultiplexed the sequences by the assigned custom tags, trimmed the primers using cutadapt (v. 2.4;

Martin 2011), filtered by length (184 +/- 10 bp) and expected error (1), and denoised using

Usearch (Edgar 2010). The results exact sequence variants (ESV) were queried using

MegaBlast (Tan et al. 2006) against a custom rbcL library (Kuzmina et al. 2017) in

Geneious (ver 9.1.1; Kearse et al. 2012). The extracted Blast hits were then queried against the ESV using the classify sequences command in Geneious with a minimum

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98% identity match and 0.5% to the next best hit. A 98% threshold was chosen to allow more sequences to be included, as rbcL markers are distinct at the family-level.

Singletons and ESVs below 0.01% were excluded as these are likely not true diversity but rather sequencing or PCR errors.

3.2.5.3 Analysis of Environmental Variables

The following analyses were completed using vegan package (Oksanen et al.

2019) in R (version 2.5-5). Redundancy analysis (RDA) was used to assess how the non- bee community changed due to environmental variance, such as the parameters measured in the experimental methods: wind speed (km/h), solar radiation (W/m2), humidity (%), temperature (°C) and edge effect (binary: interior or exterior). These variables only explained 8% of the variance; therefore, time and date were also added to the model as explanatory variables. To visualize the potential effects of site, communities were colour coded by collection location (Appendix 4). A Hellinger transformation was applied to remove the arch effect by normalizing the data by reducing the effect of zeros

(Legendre and Gallagher 2001). The significance of the model and the axes generated were tested using ‘anova.cca’ (vegan ver. 2.5-5; Oksanen et al. 2019).

3.3 Results

3.3.1 Diversity and Pollen Loads

Within the observation period 3732 insects were observed; 972 were honey bees

(26%), 644 were other bees (17%), and 2116 were non-bee visitors (57%). When considering only the data from collected specimens, the families which contributed the

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most amount of active pollen (average pollen count x abundance), of the non-bee visitors, were flies of the families Syrphidae, Calliphoridae and Anthomyiidae (Figure 3.1). These observations are a better representation of the abundance for the groups found in the fields, as the counts are less affected by collector bias, have a more robust sample size and provides standardized abundance counts for bees; however, they lack consistent species-level identifications.

A total of 608 non-bee insects were collected, 541 species-level identifications of non-bee visitors belonging to 4 orders, 27 families, 53 genera, 62 species (Figure 3.2;

Table 3.2; Appendix 2). Sequence read lengths ranged from 359 base pairs (bp) to 658 bp, with an average of 644 bp. For pollen load comparison purposes 32 bee specimens were caught, 26 were assigned species level identification from 3 families containing 14 species (Table 3.2). The species which carried the most pollen on average per individual in the order of magnitude 10,000-20,000 were Eristalis tenax > E. arbustorum > Halictus confusus > Lasioglossum pectoral > Heringia coxalis > Callirhytis tumifica > Bombus impatiens > Ceratina dupla (Figure 3.3; Table 3.2). Of the captured non-bee pollinators,

30 of the 53 genera caught, had pollen loads that were not significantly different from the genus of bee with the highest pollen count (Table 3.4). Eristalis was the only genus that carried more pollen than Halictus (Figure 3.3; Table 3.4). The variance in pollen loads was very large, even within a species group; Eristalis tenax individuals’ pollen loads ranged from 1,617- 316,300 pollen grains (Table 3.2). Table 2.3 demonstrates how we can extrapolate pollen count data from collected specimens to observed data. Total pollen

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count is the average pollen count for the respective group (Table 3.2) multiplied by the observed abundance, which is a more accurate abundance measure.

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Table 3.2: Insect visitors collected from day-neutral strawberries in Southern Ontario, CA. * Yellow box indicates that abundance values cannot be considered representative and therefore total pollen cannot be calculated. Insect Total Average StdDev Order Family Species Abundance Pollen Pollen (+/-) Hymenoptera Andrenidae Perdita halictoides 1 1867 Apidae Bombus impatiens 3 12539 25644 Apidae Ceratina dupla 1 11500 Apidae Ceratina mikmaqi 1 4200 Apidae Melissodes druriella 1 4250 Halictidae Agapostemon sericeus 1 6883 Halictidae Augochlora pura 1 2300 Halictidae Halictus confusus 3 21289 17435 Halictidae Halictus rubicundus 1 1367 Lasioglossum Halictidae 1 2233 anomalum Lasioglossum Halictidae 7 15906 7068 pectorale Lasioglossum Halictidae 2 7500 5400 perpunctatum Halictidae Lasioglossum pilosum 2 3517 1767 Halictidae Lasioglossum sagax 1 1833 Halictidae Sphecodes sp. 1 3767

Hymenoptera Braconidae Peristenus digoneutis 1 567 567 Cynipidae Callirhytis tumifica 1 13000 13000 Formicidae Formica subsericea 2 1883 942 42 Formicidae Prenolepis imparis 6 15300 2550 861 Tetramorium Formicidae 19 39150 2061 1893 caespitum Ancistrocerus Vespidae 1 1067 1067 adiabatus

Diptera Agromyzidae Ophiomyia nasuta 1 950 950 Anthomyiidae Delia florilega 31 44200 1426 1061 Anthomyiidae Delia platura 44 73750 1676 1770 Calliphoridae Lucilia sericata 2 5317 2658 375 Calliphoridae Pollenia pediculata 22 47858 2175 2848 Calliphoridae Pollenia rudis 47 109900 2442 1348 Chironomidae Orthocladius dorenus 4 4617 1154 313 Chironomidae Orthocladius mallochi 3 3133 1044 213 Chloropidae Apallates particeps 5 5900 1180 357

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Insect Total Average StdDev Order Family Species Abundance Pollen Pollen (+/-) Conioscinella Chloropidae 1 1267 1267 triorbiculata Chloropidae Liohippelates bishoppi 1 1300 1300 Malloewia Chloropidae 6 7183 1197 629 abdominalis Chloropidae Olcella parva 2 2667 1333 17 Conopidae Myopa virginica 1 3467 3467 Ephydridae Discomyza incurva 1 1717 1717 Sarcophagidae Sarcophaga subvicina 4 13150 3288 858 Sarcophagidae Senotainia trilineata 2 2050 1025 342 Scatopsciara Sciaridae 1 1083 calamophila Syrphidae Eristalinus aeneus 2 2650 1325 575 Syrphidae Eristalis arbustorum 10 216117 21612 43511 Syrphidae Eristalis dimidiata 1 1317 1317 Syrphidae Eristalis tenax 5 350017 70003 123314 Syrphidae Eristalis transversa 1 9150 9150 Syrphidae Eumerus funeralis 1 1783 1783 Syrphidae Heringia coxalis 2 26417 13208 11875 Sphaerophoria Syrphidae 3 2717 906 202 contigua Sphaerophoria Syrphidae 28 37333 1333 448 philanthus Syrphidae Syritta pipiens 5 6883 1377 592 Syrphidae Syrphus ribesii 1 3333 3333 Syrphidae Temnostoma barberi 1 8733 8733 Syrphidae Toxomerus geminatus 5 7417 1483 204 Toxomerus Syrphidae 114 141783 1244 776 marginatus Tachinidae Dinera grisescens 6 12600 2100 1295 Tachinidae Ptilodexia mathesoni 1 1950 1950 Strongygaster Tachinidae 1 650 650 triangulifera tachJanzen01 Tachinidae 1 1617 1617 Janzen3066 Urophora Tephritidae 2 1800 900 200 quadrifasciata

Hemiptera Lygaeidae Lygaeus kalmia 1 2167 2167 Lygaeidae Nysius niger 2 3433 1717 33 Adelphocoris Miridae 3 5217 1739 358 lineolatus 64

Insect Total Average StdDev Order Family Species Abundance Pollen Pollen (+/-) Miridae Lygus lineolaris 19 35200 1853 1156 Plagiognathus Miridae 2 2833 1417 0 obscurus Miridae Plagiognathus politus 2 3483 1742 642 Nabidae Nabis americoferus 4 6850 2283 1044 Nabidae Nabis rufusculus 2 3133 1567 33

Coleoptera Carabidae Lebia viridis 4 4567 1142 549 Diabrotica Chrysomelidae 2 1883 942 325 undecimpunctata Coleomegilla Coccinellidae 2 17033 8517 4333 maculata Coccinellidae Hippodamia variegata 5 11383 2277 1994 Sylvanelater Elateridae 1 3933 3933 cylindriformis Collops Melyridae 1 883 883 quadrimaculatus Mordellidae Mordella marginata 8 20217 2527 1913 Carpophilus Nitidulidae 13 21933 1687 886 brachypterus Nitidulidae Fabogethes nigrescens 2 6833 3417 550 Scarabaeidae Popillia japonica 4 15783 3946 2147 Macrodactylus Scarabaeidae 1 1950 1950 subspinosus

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Figure 3.1: Total pollen load on non-bee strawberry visitors. Size of the rectangle represents total pollen carried by each species (Collected abundance multiplied by average pollen). White labels give species identification, while orange labels indicate family-level groupings.

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Figure 3.2: Abundance of strawberry flower visiting species (white text), grouped by family (orange text). Size of the rectangle and numbers in each rectangle represents species abundance from collected specimens.

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Figure 3.3: Average pollen carried by species visiting strawberry. Size of the rectangle represents average amount (corresponds to the number present in each box) of pollen carried per individual for that species.

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Table 3.3: Insect visitors observed on day-neutral strawberries in Southern Ontario, CA, using observation and collection data. Percentage Observed Percent of Total Average Order Family Genera of community Abundance Total Pollen Pollen Pollen Hymenoptera 5.42 129 4.81 602,501 4671 Apidae Bombus 0.92 22 2.20 275,858 12539 Apidae Ceratina 4.87 116 7.27 910,600 7850 Apidae Melissodes 0.42 10 0.34 42,500 4250 Agapostemon, Augochlora, Halictidae Augochorella, Augochloropsis 2.60 62 2.27 284,704 4592 Halictidae Halictus 3.12 74 0.81 101,133 1367 Halictidae Lassioglossum 8.70 207 10.24 1,282,986 6198 Halictidae Sphecodes 0.21 5 0.15 18,833 3767

Hymenoptera Formicidae 3.87 92 1.36 170,292 1851

Diptera 14.62 348 13.10 1,640,124 4713 Calliphoridae 0.42 10 0.19 24,250 2425 Chironomidae 2.73 65 0.57 71,435 1099 Syrphidae 22.73 541 42.21 5,286,652 9772 Tephritidae 0.04 1 0.01 900 900

Hemiptera 4.50 107 1.57 197,308 1844 Miridae Lygus lineolaris 13.32 317 4.69 587,401 1853 Miridae 1.93 46 0.62 77,648 1688 Nabidae 1.09 26 0.40 50,050 1925

Coleoptera 1.60 38 0.92 115,634 3043 Carabidae Lebia viridis 0.13 3 0.03 3,426 1142 Chrysomelidae Diabrotica undecimpunctata 0.21 5 0.04 4,710 942 Coccinellidae Coleomegilla maculata 1.76 42 2.86 357,714 8517 69

Percentage Observed Percent of Total Average Order Family Genera of community Abundance Total Pollen Pollen Pollen Coccinellidae 0.29 7 0.13 15,939 2277 Mordellidae 0.50 12 0.24 30,324 2527 Scarabaeidae Popillia japonica 3.91 93 2.93 366,978 3946 Scarabaeidae 0.08 2 0.03 3,900 1950

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Table 3.4: A generalized linear model representing non-bee pollen count data at the genus level (n=53), with Halictus (the bee genus with the highest pollen count) as the baseline. Parameter Lower Upper Family Estimate Estimate SE 95% CI 95% CI t value Pr(>|t|) Intercept 9.97 0.36 9.04 10.89 28.06 < 2e-16 *** Agromyzidae Ophiomyia -3.11 2.93 -4.04 -2.18 -1.06 0.29 Anthomyiidae Delia -2.61 0.44 -3.56 -1.65 -5.91 0.00 *** Braconidae Peristenus -3.63 3.79 -4.55 -2.70 -0.96 0.34 Calliphoridae Lucilia -2.08 1.28 -3.03 -1.13 -1.62 0.11 Pollenia -2.20 0.42 -3.15 -1.25 -5.23 2.57E-07 *** Carabidae Lebia -2.93 1.37 -3.97 -1.89 -2.13 0.03 * Chironomidae Orthocladius -2.96 1.08 -3.90 -2.01 -2.74 0.01 ** Chloropidae Apallates -2.89 1.22 -3.86 -1.93 -2.37 0.02 * Conioscinella -2.82 2.55 -3.75 -1.89 -1.11 0.27 Liohippelates -2.80 2.51 -3.72 -1.87 -1.11 0.27 Malloewia -2.88 1.12 -3.90 -1.86 -2.58 0.01 * Olcella -2.77 1.77 -3.70 -1.84 -1.56 0.12 Chrysomelidae Diabrotica -3.12 2.10 -4.16 -2.08 -1.49 0.14 Coccinellidae Coleomegilla -2.06 0.46 -3.07 -1.04 -4.51 8.37E-06 *** Hippodamia -2.24 0.91 -3.44 -1.03 -2.45 0.01 * Conopidae Myopa -1.81 1.57 -2.74 -0.89 -1.16 0.25 Cynipidae Callirhytis -0.49 0.86 -1.42 0.43 -0.57 0.57 Dictynidae Emblyna -2.82 2.55 -3.75 -1.89 -1.11 0.27 Elateridae Sylvanelater -1.69 1.47 -2.62 -0.76 -1.15 0.25 Ephydridae Discomyza -2.52 2.20 -3.44 -1.59 -1.15 0.25 Formicidae Formica -3.12 2.10 -4.05 -2.19 -1.49 0.14 Prenolepis -2.12 0.81 -3.09 -1.16 -2.63 0.01 ** Tetramorium -2.34 0.58 -3.35 -1.32 -4.05 0.00 *** Lygaeidae Lygaeus -2.28 1.96 -3.21 -1.36 -1.17 0.24 Nysius -2.52 1.57 -3.45 -1.59 -1.60 0.11 Melyridae Collops -3.18 3.04 -4.11 -2.26 -1.05 0.30 Miridae Adelphocoris -2.50 1.29 -3.46 -1.55 -1.94 0.05 . Lygus -2.44 0.60 -3.41 -1.47 -4.10 4.93E-05 *** Plagiognathus -2.60 1.18 -3.58 -1.63 -2.20 0.03 * Mordellidae Mordella -2.13 0.72 -3.20 -1.07 -2.94 0.00 ** Nabidae Nabis -2.37 0.97 -3.43 -1.30 -2.45 0.01 * Nitidulidae Carpophilus -2.54 0.70 -3.50 -1.57 -3.61 0.00 *** Fabogethes -1.83 1.14 -2.78 -0.88 -1.60 0.11 Sarcophagidae Sarcophaga -1.87 0.86 -2.83 -0.91 -2.17 0.03 * Senotainia -3.03 2.01 -4.07 -2.00 -1.51 0.13 Scarabaeidae Macrodactylus -2.39 2.06 -3.32 -1.46 -1.16 0.25 Popillia -1.42 0.62 -2.51 -0.32 -2.28 0.02 * 71

Parameter Lower Upper Family Estimate Estimate SE 95% CI 95% CI t value Pr(>|t|) Sciaridae Scatopsciara -2.98 2.75 -3.91 -2.05 -1.08 0.28 Syrphidae Eristalinus -2.78 1.78 -3.88 -1.67 -1.56 0.12 Eristalis 0.47 0.37 -0.97 1.90 1.24 0.21 Eumerus -2.48 2.16 -3.41 -1.55 -1.15 0.25 Heringia -0.48 0.66 -2.03 1.08 -0.73 0.47 Sphaerophoria -2.80 0.57 -3.74 -1.87 -4.90 1.34E-06 *** Syritta -2.74 1.14 -3.74 -1.74 -2.41 0.02 * Syrphus -1.85 1.59 -2.78 -0.93 -1.16 0.25 Temnostoma -0.89 1.02 -1.82 0.04 -0.87 0.38 Toxomerus -2.83 0.42 -3.77 -1.90 -6.67 7.25E-11 *** Tachinidae Dinera -2.32 0.88 -3.37 -1.27 -2.65 0.01 ** Ptilodexia -2.39 2.06 -3.32 -1.46 -1.16 0.25 Strongygaster -3.49 3.54 -4.42 -2.56 -0.99 0.32 tachJanzen01 -2.58 2.26 -3.50 -1.65 -1.14 0.25 Tephritidae Urophora -3.16 2.15 -4.14 -2.19 -1.48 0.14 Vespidae Ancistrocerus -2.99 2.77 -3.92 -2.07 -1.08 0.28 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

3.3.2 Pollen Metabarcoding and Pollinator Networks

The pollen loads of 284 insects were investigated for plant family or genus composition. Qubit readings of the finished libraries were quite low: 1.58, 1.30 and 1.29 ng/µL of double stranded DNA. Following read processing, two libraries had approximately 11 million reads, and the other had approximately 6 million reads.

Specimens with counts as low as 565 pollen grains received sequence reads; however, read counts for specimens with under 1,000 pollen grains were highly variable and resulted in some of the lowest read counts (Appendix 2). Contamination was found in many of the negative controls. Therefore, low reads from the low pollen count samples could be a result of contamination rather than true representation of the pollen recovered from those samples. However, there was a high diversity of pollen from

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different plants found on the insect visitors; 110 genera of plants were discovered with at least 98% hit match to reference library (Appendix 3). As a more conservative estimate, 48 families of plant were found on insects; 2 families had to be removed from the network analysis because the specimens they were collected from did not have a family-level taxonomic assignment (Appendix 2, Figure 3.4). The relative abundance of sequence reads are used as a proxy of relative abundance of pollen load composition for the remaining analysis (Richardson et al. 2015, Kraaijeveld et al. 2015, Pornon et al.

2017).

All species, apart from three (Liohippelates bishoppi, Callirhytis tumifica, and

Lygaeus kalmia), had some strawberry pollen on their bodies, the former did not have a successful PCR, so no pollen sequences were available (Appendix 2). Species which had 100% strawberry pollen on their bodies were dipterans: Ophiomyia nasuta,

Conioscinella triorbiculata, Strongygaster triangulifera, Toxomerus germinatus, ant:

Prenolepis imparis, beetle: Collops quadrimaculatus, and the bug: Plagiognathus politus. The most generalist families were Syrphidae (from which pollen data from 21 plant families, and 56 genera were recorded), Calliphoridae (22 plant families, 53 genera), and Anthomyiidae (20 plant families, 35 genera). Syrphidae as a family are quite generalist; however, this classification changes when analyzing them at a species level, with some species being quite selective in their floral visitations, while others are generalist (Figure 3.5). Even within closely related species there is representation of both generalist and specialist. For example, Toxomerus marginatus had pollen from 36 genera (18 families) of plant, while T. germinatus carried only strawberry pollen

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(Appendix 2). The same can be seen regarding Sphaerophoria, S. contigua contained pollen from only 2 genera, while S. philanthus carried pollen from 10 genera.

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Figure 3.4: Plant-flower visitor network at the family level. Fragaria is included at the genus level for distinction of strawberry pollen.

The relative number of sequence reads for each plant family (or genus) per insect family is represented by a gradient from black (1) to nearly white (0.0001), yellow squares represent zero values. n is the number of specimens with successful metabarcoded pollen loads.

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Figure 3.5: Plant-syrphid network at the plant family level. Fragaria is included at the genus level for distinction of strawberry pollen.

The relative number of sequence reads for each plant family (or genus) per syrphid species is represented by a gradient from black (1) to nearly white (0.0001), yellow squares represent zero values. n is the number of specimens with successful metabarcoded pollen loads.

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3.3.3 Environmental Variance on Community Structure

A Redundancy analysis (RDA) modelling was applied to Hellinger transformed observation data with respect to five environmental explanitory variables (wind speed, solar radiation, temperature, humidity, edge). The model was statistically significant (F =

3.94, p< 0.001); however, it only explained 14% of the variance. The model generated by the inclusion of temporal variables explained 65% of the variance. The new model was significant (F = 5.79, p< 0.001); the first 7 axes were significant (ANOVA, p<

0.001). The RDA demonstrates that 65.2% (R2 adj = 53.9%) of the taxa variance can be explained by the variables included in the model (Figure 3.6). The eigenvalues demonstrate that the first four axes represent 42% (Axis 1: 16%, Axis 2: 11%, Axis 3:

9%, Axis 4: 7%; Figure 3.6) of the taxa variance. The majority of the variance is explained by date (ANOVA, p< 0.001) models that include date improve the explained variance by more than 45%. Time was also significant (ANOVA, p< 0.03), with ellipses which showed a small gradient across the communities. All environmental variables are well represented by the axes, but do not match the spead of communities in the model.

The effect of sites on the community compoistion appears to be low as there is no distinct clustering with this variable (Appendix 4). General trends in insect community composition across the season shows consistant presence of native bees and

Hemiptera, while the abundance of Diptera, Syrphidae and Apis mellifera were quite variable (Figure 3.7). Formicidae (ants) were rare or absent most of the season; however, in one week (May 18th) there was a large surge in their abundance on flowers.

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Coleoptera and Lepidoptera consistently have low levels of occurance on strawberry flowers.

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Figure 3.6: Triplot of redundancy analysis with species scaling. Includes explanatory environmental variables, time was also included as a continuous variable (blue arrows), temperature, humidity, solar radiation and wind, and temporal variables (blue x’s), date and time (ellipses), and the response variables (black circles) is the insect floral visiting community and their composition (red crosses). Both axes are significant (p< 0.001), Axis 1 explains 16% of the variance and axis 2 explains 11% variance. Data are Hellinger transformed. 79

Figure 3.7: Boxplot representation of observed abundance for 8 taxa across 25 dates

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3.4 Discussion

A high diversity of non-bee visitors was observed on strawberry flowers. More than half of the non-bee genera collected carried similar amounts of pollen as the native bee genus Halictus, with the highest pollen loads (Table 3.4). When assessing pollen loads at a coarse level, Syrphidae had the most available pollen, contributing more than four- times as much pollen as Halictidae (Figures 3.1, 3.3 ;Table 3.2), this was primarily due to the high pollen loads found on Eristalis tenax and E. arbustorum (Figure 3.3; Table

3.2). However, the abundance of syrphids is largely driven by Toxomerus marginatus (n

= 114), which often carried less pollen, but when analyzing total pollen available in the field, these three species all contributed meaningfully (Figure 3.2; Table 3.2). During sampling, syrphids were not stationary on flowers, they took flight at the slightest disturbance and alighted on neighboring flowers. These findings are consistent with previous findings regarding effective syrphid pollination, with large pollen loads and appropriate flower-flower movement (Section 2.3.1.2.1; Bohart and Nye 1970, Solomon and Kendall 1970, Kendall and Solomon 1973, Nye and Anderson 1974, Kumar et al.

1985, Hodgkiss et al. 2018). Syrphid abundance has been correlated with an increase in pollination, fruit set and a decrease in malformation of strawberry fruits (Section

2.3.1.2.1; Stewart et al. 2017). The fly families Anthomyiidae and Calliphoridae also contributed large amounts of pollen (Figure 3.1). Calliphoridae are already known to be efficient pollinators of strawberry, imparting services equivalent to honey bees and have been used for stocking greenhouses (Section 2.3.1.2.1; Free 1966, Carden and Emmett

1973, Clements 1982). Anthomyiidae, also known as root-maggot flies are a crop pest

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to strawberries, and thus their role as pollinators needs to be weighed against the consequence of their pest status. Interestingly, two of the three ant species that were recorded as confirmed pollinators (Ashman and King 2005), Prenolepis imparis and

Formica subsericea, were also collected in this study (Section 2.3.1.2.1); however, the proportion of strawberry pollen on them varied substantially (30% to 100% respectively)

(Appendix 2). This study also found Tetramorium caespitum with 92% strawberry pollen

(Appendix 2). The exclusion of the collection of Lepidoptera is not likely affect the assessment of non-bee flower visitors as their abundances were so low (Figure 3.7).

The exclusion of Drosophila was necessary given the resources and collection methods, however due to their high abundance it is possible that even if they carried only a small amount of pollen that they could collectively carry a lot of pollen. However, while observing them in the field they often did not move from flower to flower, but rather stayed clustered together and stationary on a single flower.

The majority of the pollen that was found on non-bee pollinators was indeed strawberry pollen, with an average of 69% of all non-bee visitors’ pollen loads consisting of strawberry pollen (Figure 3.5). The species with the highest pollen loads had over 70% strawberry pollen: Eristalis tenax (npollen = 350017, 85% strawberry), E. arbustorum (npollen

= 216117, 70% strawberry), Toxomerus marginatus (npollen = 141783, 76% strawberry), and Pollenia rudis (npollen = 109900, 87% strawberry; Figure 3.5; Appendix 2). Thus, these species are likely contributing to pollination and should be investigated further to verify their role in strawberry pollination. However, species which had only strawberry pollen could be suspect of never leaving the strawberry flowers, thus cannot be classified a

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pollinator. Species which carried no pollen can be excluded from consideration as pollinators. Interestingly, the most generalist families coincided with those that were covered in the largest amount of pollen, Syrphidae (56 plant genera), Calliphoridae (53 plant genera), and Anthomyiidae (35 plant genera; Figure 3.5). Anthomyiidae have been recorded as a largely generalist family of flower visitors (Larson and Kevan 2001). Within

Syrphidae, there are pairs of generalist and specialist species within a genus. This could be the result of speciation due to differing food exploitation strategies (Schluter et al.

1985). It should be noted that the larger sample sizes also seem to be the more generalist species; further research should investigate if this trend is a true representation of these species. These plant (pollen) diversity counts should be taken with care when considering which plants these insects visit, as many of the genera that were identified with metabarcoding were grasses (Poaceae) with 15 genera identified, and other wind- pollinated plants (Rabinowitz et al. 1981). The presence of wind-pollinated plants in the samples could be incidental, found on these insect bodies via contact with windborne pollen when flying, rather than a confirmed visit to the plant itself (although this also cannot be excluded as a possibility). The high resolution and diversity of metabarcoding is far more accurate and representative of the pollen that is present than previous light microscopy techniques (Keller et al. 2015).

The RDA analysis demonstrates that environmental variables are a poor predictor of insect community visitation (Figure 3.6). A strong explanatory variable in the model is date and to a lesser degree time. This suggests that the flower visitor community was quite different on each day of sampling. As such, this model could be

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detecting phenological patterns of the non-bee visitors; insects that emerge and are abundant for a short time and not recorded outside of their biological timeline. This is supported by observations (see Figure 3.77), where large concentrated peaks of activity can be found in the taxa groupings, particularly prominent in Syrphidae and Formicidae.

Many insects are restricted to narrow ranges of temperature for flight, as endothermy is a rare trait in insects, requiring a rise in ambient temperature or basking in sunlight to warm their flight muscles (Inouye et al. 2015). Most syrphid species, however, do have endothermic capabilities and will forage in cloudy and cool weather (Morgan and

Heinrich 1987). Other dipteran families also forage when bees and butterflies do not

(Section 1.3.1.2.1; Hooper 1932, Inouye et al. 2015). Indeed, during field sampling, syrphids and other flies were foraging on cool, overcast days and even in light rain. Low abundance of solitary bees, particularly Dialictus, were out on flowers during these less than ideal weather conditions; however, they were stationary, and not actively pollinating during this time. This range in degree of specialization(s) could reduce the effect of the environmental variables in the model.

There was a high diversity of non-bee visitors, and the primary non-bee pollinators were flies. Syrphids carried more pollen on average than native bees, contextualizing their role as pollinators. The collective contribution of three fly families,

Syrphidae, Calliphoridae and Anthomyiidae, represented most of the active pollen in the fields. Although these families also tended to be the most generalist foragers, their pollen loads contained large proportions of strawberry pollen. Generalist pollinators are highly valuable in agriculture; they contribute to the diversity of pollinators visiting crop

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flowers and therefore increase the pollination success, and they are more robust against landscape intensification (Ghazoul 2005, Blüthgen and Klein 2011, Garibaldi et al. 2014). Furthermore, generalists may be more resilient to adverse weather conditions

(Heinrich and Mcclain 1986, Inouye et al. 2015). Further research into the quality of pollen deposition by the species described in this paper is required.

3.5 General Conclusions

The role of non-bee pollinators in agriculture has been neglected in scientific studies in the last 3 decades (Figure 2.1). Species-level identification and the extent of pollination provided by this insect diversity remains largely unknown. The current knowledge available in the literature is summarized in thorough review provided in

Chapter 2. Most of the crops analyzed had records of non-bee insects visiting their flowers; however, many of them could not be confirmed as pollinators because of a lack of data on their average pollen load, mobility, and floral fidelity. The few scenarios where there was evidence on the role of non-bee pollinators, their efficiency was often matched, if not superior, to the pollination services provided by bees (Solomon and

Kendall 1970, Boyle and Philogène 1983, Currah and Ockendon 1983, Kumar et al.

1985). These are consistent with the findings reported in Chapter 2. Non-bee pollinators were more ubiquitous on strawberry flowers than bees. They had higher pollen loads on average, with a high percent of strawberry pollen. Flies were the most abundant order found on the flowers and were found to forage in a larger range of environmental conditions.

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Details on the species-level identification and determination of the capacity of non- bees as pollinators remains largely unexplored. The research presented here is highly novel, because research regarding non-bee flower-visitors is still uncommon in current literature (Chapter 2). Furthermore, the use of DNA metabarcoding to determine the flowers that these insects are visiting has been explored only once prior to this experiment (Lucas et al. 2018). I implore future research to include established non-bee pollinators in future pollinator assessments and research, and to conduct new research to unveil the role and identity of other non-bee pollinators in each respective crop.

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APPENDICES Appendix 1: List of species recorded visiting flowers of the focal crops assessed. In the order they are presented in-text. Only records from temperate climates were included. In addition, the location of the recorded observation was made is available for reference. Notice that watermelon and other melons are not included in this table, as there is no records in the literature that reveal non-bee visitors in temperate locations to these crops. * indicates the species is confirmed to participate in pollination. Crop Order Family Genus Species Location Reference Apricot (Prunus armeniaca) Langridge, Diptera Australia Goodman 1981 Langridge, Syrphidae Australia Goodman 1981 Langridge, Muscidae Australia Goodman 1981 Langridge, Musca sp. Australia Goodman 1981 Langridge, Lepidoptera Australia Goodman 1981 Strawberry (Fragaria spp.) Hymenoptera Braconidae Nye, Anderson USA Bracon sp. 1974

Formicidae Nye, Anderson USA Formica sp. 1974 Ashmann, King USA Formica subserices 2005 Ashmann, King USA Prenolepis imparis 2005 114

Crop Order Family Genus Species Location Reference Ashmann, King USA Tapinoma sessile 2005 Nye, Anderson USA Ichneumonidae 1974 Proctotrupidae Nye, Anderson USA Proctotrupes sp. 1974 Sphecidae Nye, Anderson USA Ammophila sp. 1974 Nye, Anderson USA Ectemnius sp. 1974 Nye, Anderson USA Podalonia luctuosa 1974 Nye, Anderson USA Xylocelia sp. 1974 Vespidae Nye, Anderson USA Anistrocerus sp. 1974 Nye, Anderson USA Odynerus dilectus 1974 Nye, Anderson USA Polistes fuscatus 1974 Diptera Anthomyiidae Nye, Anderson Hylemya platura USA 1974 Bombyliidae de Oliveira et al. Bombylius major Canada 1991 115

Crop Order Family Genus Species Location Reference de Oliveira et al. Bombylius pygmaeus Canada 1991 Nye, Anderson Bombylius sp. USA 1974 Nye, Anderson Villa utahensis USA 1974 Nye, Anderson Villa sp. USA 1974

Calliphoridae Nye, Anderson Bufolucilia silvarum USA 1974 Nye, Anderson Calliphora sp. USA 1974 Nye, Anderson Phaenicia sericata USA 1974 Nye, Anderson Phormia regina USA 1974 Nye, Anderson Pollenia rudis USA 1974

Conopidae Nye, Anderson Thecophora luteipes USA 1974

Muscidae Nye, Anderson Coenosia tigrina USA 1974

Otitidae Nye, Anderson Tetanops myopaeformis USA 1974

Sarcophagidae

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Crop Order Family Genus Species Location Reference Nye, Anderson Sarcophaga sp. USA 1974 Nye, Anderson Wohlfahrtia vigil USA 1974

Stratiomyidae Nye, Anderson Odontomyia pubescens USA 1974 Stewart et al. Sweden Syrphidae 2017 Nye, Anderson Asemosyrphus polygrammus USA 1974 Nye, Anderson Chrysogaster bellula USA 1974 Nye, Anderson Chrysogaster parva USA 1974 de Oliveira et al. Dasysyrphus venustus Canada 1991 de Oliveira et al. Eristalis arbustorum Canada 1991 de Oliveira et al. Eristalis barda Canada 1991 de Oliveira et al. Eristalis bastardii Canada 1991 de Oliveira et al. Eristalis obscura Canada 1991 de Oliveira et al. Eristalis stipator Canada 1991 de Oliveira et al. Eristalis transversa Canada 1991

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Crop Order Family Genus Species Location Reference de Oliveira et al. Canada, Eristalis tenax 1991; Nye, USA Anderson 1974 Nye, Anderson Eristalis anthophorinus USA 1974 Nye, Anderson Eristalis brousii USA 1974 Nye, Anderson Eristalis latifrons USA 1974 Nye, Anderson Eristalis sp. USA 1974 Nye, Anderson Eristalis spp. USA 1974 Nye, Anderson Eumerus strigatus USA 1974 Nye, Anderson Eupeodes volucris USA 1974 de Oliveira et al. Helophilus fasciatus Canada 1991 de Oliveira et al. Canada, Helophilus latifrons 1991; Nye, USA Anderson 1974 Nye, Anderson Helophilus lunuatus USA 1974 Nye, Anderson Helophilus stipatus USA 1974 Nye, Anderson Helophilus sp. USA 1974 de Oliveira et al. Lejops hamatus Canada 1991 118

Crop Order Family Genus Species Location Reference Nye, Anderson Merodon equestris USA 1974 de Oliveira et al. Metasyrphus sp. Canada 1991 de Oliveira et al. Orthonevra pulchella Canada 1991 de Oliveira et al. Platycheirus clypeatus Canada 1991 de Oliveira et al. Sericomyia militaris Canada 1991 de Oliveira et al. Canada, Sphaerophoria sp. 1991; Nye, USA Anderson 1974 de Oliveira et al. Canada, Syritta pipiens 1991; Nye, USA Anderson 1974 de Oliveira et al. Syrphus ribesii Canada 1991 de Oliveira et al. Temnostoma alternans Canada 1991 Nye, Anderson Xylota flavitibia USA 1974 Nye, Anderson Tachinidae USA 1974 Nye, Anderson Gonia spp. USA 1974 Nye, Anderson Peleteria iterans USA 1974

Coleoptera

Cerambycidea 119

Crop Order Family Genus Species Location Reference Nye, Anderson USA Callidium antennatum 1974

Curculionidae Nye, Anderson USA Rhynchites bicolor 1974

Melyridae Nye, Anderson USA Collops sp. 1974 Hemiptera Nye, Anderson USA Cicadellidae 1974

Pentatomidae Nye, Anderson USA Cosmopepla conspicillaris 1974 Nye, Anderson USA Miridae 1974 Lepidoptera Hesperiidae Nye, Anderson USA Hesperia juba 1974 Nye, Anderson USA Pholisora cattulus 1974 Nye, Anderson USA Polites sabuleti 1974 Lycaenidae Nye, Anderson USA Lycaena helloides 1974 Nye, Anderson USA Lycaena sp. 1974 Noctuidae 120

Crop Order Family Genus Species Location Reference Nye, Anderson USA Anagrapha falcifera 1974

Nymphalidae Nye, Anderson USA Phyciodes mylitta 1974

Pieridae Nye, Anderson USA Pieris protodice 1974 Nye, Anderson USA Pieris rapae 1974 Nye, Anderson USA Colias sp. 1974 Satyridae Nye, Anderson USA Coenonympha sp. 1974 Neuroptera Chrysomelidae Chrysoperla cernea Mexico Zapata 1989 Nye, Anderson USA Trichoptera 1974 Apple (Malus domestica) Hymenoptera Chalicidoidea Boyle-Moleski, Anacharis spp. Canada 1983 Boyle-Moleski, Pholetesor ornigis Canada 1983 Boyle-Moleski, Sympiesis marylandensis Canada 1983

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Crop Order Family Genus Species Location Reference Vicens et al. Spain Eumenidae 2000

Formicidae Boyle-Moleski, Camponotus spp. Canada 1983 Boyle-Moleski, Formica fusca Canada 1983 Boyle-Moleski, Formica glacialis Canada 1983 Boyle-Moleski, Lasius neoniger Canada 1983 Linepithema spp. Columbia Botero, 2000 Boyle-Moleski, Prenolepis imparis Canada 1983 Ichneumonidae Boyle-Moleski, Diplazon laetatorius Canada 1983 Boyle-Moleski, Pycnocryptus director Canada 1983 Boyle-Moleski, Syrphoctonus flavolineatus Canada 1983 Boyle-Moleski, Tryphon seminiger Canada 1983 Boyle-Moleski, Tymmophorus rufiventris Canada 1983 Tentredinidae Boyle-Moleski, Eutomostethus ephippium Canada 1983 Vicens et al. Spain Vespidae 2000 122

Crop Order Family Genus Species Location Reference Agelaia spp. Columbia Botero, 2000 Epipona spp. Columbia Botero, 2000 Boyle-Moleski, Vespula maculata Canada 1983 New Palmer-Jones, Vespula germanica Zealand Clinch 1967 Diptera Agromyzidae Boyle-Moleski, Japanagromyza viridula Canada 1983 Vicens et al. Anthomyiidae Spain 2000 Boyle-Moleski, Hylemya brassicae Canada 1983 Boyle-Moleski, Hylemya florilega Canada 1983 Boyle-Moleski, Hylemya fugax Canada 1983 Boyle-Moleski, Hylemya platura Canada 1983 Boyle-Moleski, Hylemya spp. Canada 1983 Boyle-Moleski, Nupedia dissecta Canada 1983

Bibionidae Boyle-Moleski, Bibio albipennis Canada 1983 Botero, 2000; Columbia, Boyle-Moleski, Bibio spp. Canada 1983 123

Crop Order Family Genus Species Location Reference Bombyliidae Bombylius pygmatus Canada Williams, 1932

Bombylius major Canada Williams, 1932 Palmer-Jones, New Clinch 1967; Calliphoridae Zealand, Vicens et al. Spain 2000 Boyle-Moleski, Bufolucilia silvarum Canada 1983 Boyle-Moleski, Lucilia illustris Canada 1983

Phaenicia eximia Columbia Botero, 2000 Boyle-Moleski, Phormia regina Canada 1983 Williams, 1932; Canada, Boyle-Moleski, Pollenia rudis Canada 1983 Boyle-Moleski, Chironomidae Canada 1983 Boyle-Moleski, Chironomus spp. Canada 1983 Boyle-Moleski, Chironomus maturus Canada 1983 Boyle-Moleski, Cricotopus spp. Canada 1983 Boyle-Moleski, Endochironomus spp. Canada 1983 Boyle-Moleski, Limnophyes spp. Canada 1983

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Crop Order Family Genus Species Location Reference Boyle-Moleski, Micropsectra spp. Canada 1983 Boyle-Moleski, Orthocladius spp. Canada 1983 Boyle-Moleski, Procladius spp. Canada 1983 Conopidae Boyle-Moleski, Myopa vesiculosa Canada 1983 Dolichopodiae Columbia Botero, 2000 Boyle-Moleski, Dolichopus spp. Canada 1983 Ephydridae Boyle-Moleski, Hydrellia spp. Canada 1983 Botero, 2000; Muscidae Columbia, Vicens et al. Spain 2000 Boyle-Moleski, Fannia spp. Canada 1983 Boyle-Moleski, Fannia coracina Canada 1983

Sarcophagidae Boyle-Moleski, Boettcheria spp. Canada 1983 Boyle-Moleski, Ravinia latisetosa Canada 1983 Scathophagidae Boyle-Moleski, Scathophaga furcata Canada 1983 125

Crop Order Family Genus Species Location Reference Boyle-Moleski, Scathophagidae Scathophaga stercorarium Canada 1983 Sciaridae Columbia Botero, 2000 Stratiomyidae Odontomyia interrupta Canada Williams, 1932 Syrphidae Allograpta spp. Columbia Botero, 2000 Boyle-Moleski, Allograpta obliqua Canada 1983

Brachyopa perplexa Canada Williams, 1932

Cartosyrphus slossonae Canada Williams, 1932

Criorhina badia Canada Williams, 1932 Foldesi et al. Epistrophe eligans Hungary 2016 Foldesi et al. Epistrophe euchroma Hungary 2016 Vicens et al. Episyrphus Spain, 2000; Foldesi et balteatus Hungary al. 2016 Foldesi et al. Eristalinus aeneus Hungary 2016 Williams, 1932; Canada, Boyle-Moleski, Eristalis Canada, 1983; Foldesi et arbustorum Hungary al. 2016

Eristalis bastardi Canada Williams, 1932

Eristalis compactus Canada Williams, 1932 Boyle-Moleski, Eristalis dimidiata Canada 1983

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Crop Order Family Genus Species Location Reference Boyle-Moleski, Eristalis spp. Canada 1983

Eristalis peristallis Kendall 1973 Boyle-Moleski, 1983; Kendall Eristalis Canada, 1973; Vicens et tenax Spain al. 2000 Foldesi et al. Eupeodes corollae Hungary 2016 Boyle-Moleski, Helophilus fasciatus Canada 1983 Boyle-Moleski, Helophilus latifrons Canada 1983

Hylemya spp. Canada Williams, 1932 Boyle-Moleski, Melanostoma spp. Canada 1983

Melanostoma pictipes Canada Williams, 1932 Boyle-Moleski, Metasyrphus spp. Canada 1983 Boyle-Moleski, Metasyrphus latifasciatus Canada 1983 Foldesi et al. Neoascia podagrica Hungary 2016 Foldesi et al. Pipiza viduata Hungary 2016 Foldesi et al. Platycheirus scutatus Hungary 2016 Boyle-Moleski, Platycheirus quadratus Canada 1983

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Crop Order Family Genus Species Location Reference Boyle-Moleski, Platycheirus scutatus Canada 1983

Rhingia nasica Canada Williams, 1932

Sericomyia militaris Canada Williams, 1932 Foldesi et al. Sphaerophoria scripta Hungary 2016 Boyle-Moleski, Sphaerophoria spp. Canada 1983 Boyle-Moleski, Sphaerophoria pilanthus Canada 1983

Sphecomyia vittata Canada Williams, 1932 Foldesi et al. Syritta pipiens Hungary 2016 Foldesi et al. Syrphus ribesii Hungary 2016 Foldesi et al. Syrphus vitripennis Hungary 2016 Boyle-Moleski, Syrphus rectus Canada 1983 Williams, 1932; Canada, Boyle-Moleski, Syrphus torvus Canada 1983

Syrphus wiedemanni Canada Williams, 1932

Syrphus rectus Canada Williams, 1932

Syrphus amalopis Canada Williams, 1932 Vicens et al. Syrphus ribesii Spain 2000 Boyle-Moleski, Toxomerus germinatus Canada 1983

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Crop Order Family Genus Species Location Reference Boyle-Moleski, Toxomerus marginatus Canada 1983 Vicens et al. Tachinidae Spain 2000

Paralipse spp. Columbia Botero, 2000 Boyle-Moleski, Periscepsia helymus Canada 1983 Boyle-Moleski, Tachinomya nigricans Canada 1983

Mericia ampelus Canada Williams, 1932 New Palmer-Jones, Tipulidae Zealand Clinch 1967 Vicens et al. Spain Coleoptera 2000 Cantharidae Boyle-Moleski, Cantharis bilineatus Canada 1983 Chrysomelidae

Diabrotica spp. Columbia Botero, 2000

Systena spp. Columbia Botero, 2000

Nodonota spp. Columbia Botero, 2000

Pachyonicus spp. Columbia Botero, 2000

Diabrotica balteata Columbia Botero, 2000 Galeruca spp. Columbia Botero, 2000 Coccinelidae transversoguttata Boyle-Moleski, Coccinella richardsoni Canada 1983 Curculionidae Pandeleteius spp. Columbia Botero, 2000

129

Crop Order Family Genus Species Location Reference Nicentrus testaceipes Columbia Botero, 2000 Elateridae Pomachilus suturalis Columbia Botero, 2000 Boyle-Moleski, Ctenicera lobata tarsalis Canada 1983 Melolonthidae Isonychus spp. Columbia Botero, 2000

Macrodactyus spp. Columbia Botero, 2000

Anomala spp. Columbia Botero, 2000 Nitidulidae Boyle-Moleski, Meligethes canadensis Canada 1983 Boyle-Moleski, Meligethes nigrescens Canada 1983 Scarabaeidae Boyle-Moleski, Phyllophaga spp. Canada 1983 Boyle-Moleski, Phyllophaga rugosa Canada 1983 Boyle-Moleski, Phyllophaga luteola Canada 1983 Hemiptera Anthocoridae Boyle-Moleski, Orius insidosus Canada 1983 Coreidae Boyle-Moleski, Kleidocerys resedae Canada 1983 Miridae

130

Crop Order Family Genus Species Location Reference Boyle-Moleski, Lygus spp. Canada 1983 Boyle-Moleski, Lygus lineolarius Canada 1983 Monalonion velezangeli Columbia Botero, 2000 Taylorilygus spp. Columbia Botero, 2000 Vicens et al. Spain Lepidoptera 2000 Ctenuchidae Columbia Botero, 2000 Boyle-Moleski, Gelechiidae Canada 1983 Geometridae Boyle-Moleski, Haematopis Grataria Canada 1983 Gracilariidae Boyle-Moleski, Lithocolletis spp. Canada 1983 Hesperiidae Urbanus proteus Columbia Botero, 2000 Panoquina spp. Columbia Botero, 2000 Pythonides thespieus Columbia Botero, 2000 Mysoria spp. Columbia Botero, 2000 Boyle-Moleski, Erynnis juvenalis Canada 1983 Noctuidae Boyle-Moleski, Anagrapha falcifera Canada 1983 Boyle-Moleski, Apamea finitima Canada 1983

131

Crop Order Family Genus Species Location Reference Boyle-Moleski, Pseudaletia unipuncta Canada 1983 Nymphalidae Actinote spp. Columbia Botero, 2000 Boyle-Moleski, Vanessa atalanta rubria Canada 1983 Olethreutidae Boyle-Moleski, Pseudeexentera spp. Canada 1983 Pieridae Leptophobia aripa Columbia Botero, 2000 Blackberry (Rubus fruticosus, R. resticanus inermis, R. argutus, R. allegheniensis, R. spp.) Diptera Syrphidae Gyan, Woodell Eristalis spp. England 1987 Raspberry (Rubus idaeus, R. pubescens, R. strigosus) Hymenoptera Hansen, Osgood USA Braconidae 1983 Hansen, Osgood USA Chalcididae 1983 Hansen, Osgood USA Chrysididae 1983

Eumenidae Hansen, Osgood Ancistrocerus sp USA 1983 Hansen, Osgood Eumenes crucifer USA 1983 132

Crop Order Family Genus Species Location Reference Hansen, Osgood Euodynerus sp USA 1983 Hansen, Osgood Stenodynerus sp USA 1983 Hansen, Osgood Symmorphus sp USA 1983 Hansen, Osgood USA Formicidae 1983

Gasterupiidae Hansen, Osgood Gasteruption kirbii USA 1983 Hansen, Osgood USA Ichneumonidae 1983 Hansen, Osgood USA Pompilidae 1983 Hansen, Osgood USA Pteromalidae 1983

Sphecidae Hansen, Osgood Ammophila azteca USA 1983 Hansen, Osgood Ammophila evansi USA 1983 Hansen, Osgood Ammophila mediata USA 1983 Hansen, Osgood Crossocerus sp. USA 1983 Hansen, Osgood Ectemnius arcuatus USA 1983 Hansen, Osgood Ectemnius atriceps USA 1983 133

Crop Order Family Genus Species Location Reference Hansen, Osgood Ectemnius borealis USA 1983 Hansen, Osgood Ectemnius continuus USA 1983 Hansen, Osgood Ectemnius dives USA 1983 Hansen, Osgood Ectemnius USA lapidarisus 1983 Hansen, Osgood Ectemnius ruficornis USA 1983 Hansen, Osgood Ectemnius stirpicola USA 1983 Hansen, Osgood Lestica sp. USA 1983 Hansen, Osgood USA Tenthredinidae 1983

Vespidae Hansen, Osgood Dolichovespula arenaria USA 1983 Diptera Hansen, Osgood Anthomyiidae USA 1983 Hansen, Osgood Asilidae USA 1983

Bombyliidae Hansen, Osgood Hemipenthes sp. USA 1983 Hansen, Osgood Lepidophora sp. USA 1983

134

Crop Order Family Genus Species Location Reference Hansen, Osgood Calliphoridae USA 1983 Hansen, Osgood Chironomidae USA 1983 Hansen, Osgood Conopidae USA 1983 Hansen, Osgood Dolichopodiae USA 1983 Hansen, Osgood Empididae USA 1983 Hansen, Osgood Lauxaniidae USA 1983 Hansen, Osgood Muscidae USA 1983 Hansen, Osgood Sarcophagidae USA 1983 Hansen, Osgood Simuliidae USA 1983

Syrphidae Hansen, Osgood Blera confusa USA 1983 Hansen, Osgood Carposcalis obsurum USA 1983 Hansen, Osgood Cartosyrphus pallipes USA 1983 Hansen, Osgood Cartosyrphus sp. USA 1983 Hansen, Osgood Chalcosyrphus libo USA 1983

135

Crop Order Family Genus Species Location Reference Hansen, Osgood Chrysotoxum fasciolatum USA 1983 Hansen, Osgood Eristalis obsurus USA 1983 Hansen, Osgood Epistrophe emarginata USA 1983 Hansen, Osgood Epistrophe xanthostoma USA 1983 Hansen, Osgood Heringia coxalis USA 1983 Hansen, Osgood Heringia sp. USA 1983 Hansen, Osgood Leucozna lucorum USA 1983 Hansen, Osgood Mallota posticata USA 1983 Hansen, Osgood Melangyna lasiophthalma USA 1983 Hansen, Osgood Metasyrphus perplexus USA 1983 Hansen, Osgood Microdon tristis USA 1983 Hansen, Osgood Orthonevra pulchella USA 1983 Hansen, Osgood Parasyrphus genualis USA 1983 Hansen, Osgood Parasyrphus semiinterruptus USA 1983 Hansen, Osgood Parasyrphus sp. USA 1983 136

Crop Order Family Genus Species Location Reference Hansen, Osgood Sericomyia chrysotoxoides USA 1983 Hansen, Osgood Sericomyia lata USA 1983 Hansen, Osgood Sericomyia militaris USA 1983 Hansen, Osgood Sphaerophoria contingua USA 1983 Hansen, Osgood Sphaerophoria longipilosa USA 1983 Hansen, Osgood Sphaerophoria novaengliae USA 1983 Hansen, Osgood Sphegina rufiventris USA 1983 Hansen, Osgood Syritta pipiens USA 1983 Hansen, Osgood Syrphus rectus USA 1983 Hansen, Osgood Syrphus ribesii USA 1983 Hansen, Osgood Syrphus torvus USA 1983 Hansen, Osgood Temnostoma alternans USA 1983 Hansen, Osgood Temnostoma barberi USA 1983 Hansen, Osgood Temnostoma vespiforme USA 1983 Hansen, Osgood Taxomerus geminatus USA 1983 137

Crop Order Family Genus Species Location Reference Hansen, Osgood Taxomerus marginatus USA 1983 Hansen, Osgood Volucella bombylans USA 1983 Hansen, Osgood Xylota annulifera USA 1983 Hansen, Osgood Xylota quadrimaculata USA 1983 Hansen, Osgood Tachinidae USA 1983 Hansen, Osgood Tipulidae USA 1983 Coleoptera Hansen, Osgood USA Anobiidae 1983 Hansen, Osgood USA Byrrhidae 1983

Byturidae Hansen, Osgood Byturus rubi USA 1983 Hansen, Osgood USA Cantharidae 1983

Cerambycidea Hansen, Osgood Anastranglia sanguinea USA 1983 Hansen, Osgood Clytus ruricola USA 1983 Hansen, Osgood Cosmosalia chrysocoma USA 1983

138

Crop Order Family Genus Species Location Reference Hansen, Osgood Evodinus monticola USA 1983 Hansen, Osgood Judolia montivagens USA 1983 Hansen, Osgood capitata USA Neoalosterna 1983 Hansen, Osgood Pidonia ruficollis USA 1983 Hansen, Osgood Strangalepta abbreviata USA 1983 Hansen, Osgood USA Curculionidae 1983 Hansen, Osgood USA Elateridae 1983 Hansen, Osgood USA Lagriidae 1983

Lampyridae Hansen, Osgood Photuris pennsylvanica USA 1983 Hansen, Osgood USA Mordellidae 1983 Hansen, Osgood USA Ptilodactylidae 1983

Scarabaeidae Hansen, Osgood Trichiotinus affinis USA 1983 Hemiptera Hansen, Osgood USA Miridae 1983

139

Crop Order Family Genus Species Location Reference Hansen, Osgood USA Pentatomidae 1983

Lepidoptera Hansen, Osgood USA Lycaenidae 1983 Hansen, Osgood USA Macrolepidoptera 1983 Hansen, Osgood USA Microlepidoptera 1983

Nymphalidae Hansen, Osgood Nyphalis antiopa USA 1983 Hansen, Osgood Vanessa atalanta USA 1983

Papilionidae Hansen, Osgood Papilio glaucus USA 1983 Onion (Allium cepa) Hymenoptera Ichneumonidae New Howlett et al. Echthromorpha intricatoria Zealand 2009 New Howlett et al. Netelia producta Zealand 2009

Sphecidae Bohart, Nye, USA Bembix amoena 1970

Vespidae New Howlett et al. Vespula germanica Zealand 2009 140

Crop Order Family Genus Species Location Reference

Diptera

Anthomyiidae New Howlett et al. Delia platura Zealand 2009 New Howlett et al. Anthomyia punctipennis Zealand 2009

Bibionidae New Howlett et al. Dilophus nigrostigma Zealand 2009

Calliphoridae Pakistan Sajjad et al. 2008 New Howlett et al. Calliphora stygia Zealand 2009 New Howlett et al. Calliphora vicina Zealand 2009 New Howlett et al. Calliphora hortona Zealand 2009 New Howlett et al. Calliphora quadrimaculata Zealand 2009 New Howlett et al. Lucilia sericata Zealand 2009 New Howlett et al. Pollenia pseudorudis Zealand 2009

Chloropidae Bohart, Nye, Thaumatomyia glabra USA 1970

Muscidae New Howlett et al. Hydrotaea rostrata Zealand 2009

141

Crop Order Family Genus Species Location Reference Pakistan, Sajjad et al. New 2008; Howlett et Musca domestica Zealand al. 2009 New Howlett et al. Spilagona melas Zealand 2009

Sarcophagidae Sarcophaga sp. Pakistan Sajjad et al. 2008 Stratiomyidae New Howlett et al. Odontomyia sp. Zealand 2009

Syrphidae Episyrphus balteatus Pakistan Sajjad et al. 2008 Eristalinus aeneus Pakistan Sajjad et al. 2008 Bohart, Nye, USA, New Eristalis tenax 1970; Howlett et Zealand al. 2009 New Howlett et al. Eumerus funeralis Zealand 2009

Eupeodes corollae Pakistan Sajjad et al. 2008 New Howlett et al. Helophilus hochstetteri Zealand 2009 New Howlett et al. Helophilus seelandicus Zealand 2009 New Howlett et al. Melangyna novae-zelandia Zealand 2009 New Howlett et al. Melanostoma fasciatum Zealand 2009

Mesembrius bengalensis Pakistan Sajjad et al. 2008

Sphaerophoria scripta Pakistan Sajjad et al. 2008

142

Crop Order Family Genus Species Location Reference Bohart, Nye, Syritta pipiens USA 1970

Tabanidae New Howlett et al. Scaptia sp. Zealand 2009

Tachinidae New Howlett et al. Campbellia lancifer Zealand 2009 New Howlett et al. Gracilicera sp. Zealand 2009 New Howlett et al. Pales usitata Zealand 2009 New Howlett et al. Procissio sp. Zealand 2009 New Howlett et al. Protohystricia alcis Zealand 2009 New Howlett et al. Voriini sp. Zealand 2009

Tipulidae New Howlett et al. Tipula sp. Zealand 2009

Coleoptera

Coccinelidae New Howlett et al. Adalia bipunctata Zealand 2009 New Howlett et al. Coccinella leonina Zealand 2009 New Howlett et al. Coccinella undecimpunctata Zealand 2009

Elateridae 143

Crop Order Family Genus Species Location Reference New Howlett et al. Conoderus exsul Zealand 2009

Hemiptera

Pentatomidae New Howlett et al. Nezara viridula Zealand 2009

Lepidoptera Crambidae New Howlett et al. Orocambus flexuosellus Zealand 2009

Lycaenidae New Howlett et al. Zizina labradus Zealand 2009

Nymphalidae New Howlett et al. Danaus plexippus Zealand 2009

Pieridae New Howlett et al. Pieris rapae Zealand 2009 Beets (Beta vulgaris) Hymenoptera Free, Williams, Aphidiidae England 1975 Free, Williams, Tenthredinidae England 1975 Free, Williams, Braconidae England 1975 Ichneumonidae Free, Williams, Amblyteles fossorius* England 1975 144

Crop Order Family Genus Species Location Reference Free, Williams, Lissonata sulphurifera* England 1975 Free, Williams, Pteromalus puparum* England 1975 Diptera Free, Williams, Anthomyiidae England 1975 Free, Williams, Asilidae England 1975 Calliphoridae Free, Williams, Phormia sp. England 1975 Free, Williams, Lucilia richardsi* England 1975 Free, Williams, Pollenia rudis England 1975 Free, Williams, Chloropidae England 1975 Cordiluridae Free, Williams, Scopeuma stercorarium* England 1975 Free, Williams, Empididae England 1975 Larvaevoridae Free, Williams, Phytomyptera nitidiventris* England 1975 Free, Williams, Eriothrix rufomaculatus* England 1975 Free, Williams, Arrhinomyia innoxia* England 1975 145

Crop Order Family Genus Species Location Reference Muscidae Free, Williams, Muscina assimilis* England 1975 Free, Williams, Thricops sp. England 1975 Free, Williams, Fannia sp. England 1975 Free, Williams, Phoridae England 1975 Free, Williams, Platypezidae England 1975 Sepsidae Free, Williams, Sepsidomorpha pilipes* England 1975 Syrphidae Free, Williams, Eristalis pertinax* England 1975 Free, Williams, Eristalis tenax* England 1975 Free, Williams, Eristalis arbustorum* England 1975 Free, Williams, Eristalis horticola* England 1975 Free, Williams, Melanostoma scalare* England 1975 Free, Williams, Melanostoma mellinum* England 1975 Archimowitsch, Melithreptus scriptus Ukraine 1949

146

Crop Order Family Genus Species Location Reference Free, Williams, Platychirus manicatus* England 1975 Free, Williams, Scaeva pyrastri* England 1975 Free, Williams, Sphaerophoria scripta* England 1975 Free, Williams, Syritta pipens* England 1975 Free, Williams, Syrphus glaucius* England 1975 Free, Williams, Syrphus vitripennis* England 1975 Free, Williams, Syrphus ribesii* England 1975 Free, Williams, Syrphus corollae* England 1975 Free, Williams, Syrphus luniger* England 1975 Free, Williams, Syrphus balteatus* England 1975 Tabanidae Free, Williams, Chrysops caecutiens* England 1975 Tipulidae Free, Williams, Nephrotoma sp. England 1975 Free, Williams, Nephrotoma flavescens* England 1975 Coleoptera Cantharidae 147

Crop Order Family Genus Species Location Reference Free, Williams, Cantharis paludosa* England 1975 Free, Williams, Cantharis lateralis* England 1975 Free, Williams, Rhagonycha fulva* England 1975 Free, Williams, Malthodes sp. England 1975 Chrysomelidae Archimowitsch, Leptura sp. Ukraine 1949 Coccinelidae Archimowitsch, Coccinella septempunctata Ukraine 1949 Free, Williams, Adalia bipunctata* England 1975 Free, Williams, Adalia 10-punctata* England 1975 Free, Williams, Cocinella 7-punctata* England 1975 Free, Williams, Propylea 14-punctata* England 1975 Curculionidae Free, Williams, Phyllobius pomaceus* England 1976 Elateridae Free, Williams, Corymbites sp. England 1975 Meloidae

148

Crop Order Family Genus Species Location Reference Archimowitsch, Zonabris sp. Ukraine 1949 Archimowitsch, Cerocoma sp. Ukraine 1949 Serropalpidae Free, Williams, Melandrya caraboides* England 1975 Hemiptera Cimicidae Free, Williams, Calocoris sp. England 1975 Free, Williams, Calocoris sexguttatus* England 1975 Free, Williams, Calocoris norvegicus* England 1975 Lepidoptera Tortricidae Free, Williams, Tortrix rusticana* England 1975 Thysanoptera Thripidae Heliothrips fasciatus USA Shaw, 1914 Frankliniella fusca USA Shaw, 1914 Frankliniella tritici USA Shaw, 1914 Thrips tabaci USA Shaw, 1914 Dermaptera Forficulidae Free, Williams, Forficula auricularia England 1975

149

Crop Order Family Genus Species Location Reference

Cabbage (Brassica sp.) Diptera Syrphidae USA Pearson 1932 Calliphoridae USA Pearson 1932 Muscidae USA Pearson 1932 Cucumber (Cucumis sativus) Diptera Syrphidae Lowenstein et al. Syrphus spp USA 2015 Lowenstein et al. Toxomerus spp. USA 2015 Pumpkin (Cucurbita pepo) Hymenoptera Matsumoto, Formicidae Japan Yamazaki, 2013 Tenthredinidae Matsumoto, Allantus luctifer Japan Yamazaki, 2013 Diptera Syrphidae Matsumoto, Syritta pipiens Japan Yamazaki, 2013 Matsumoto, Sphaerophoria indiana Japan Yamazaki, 2013 Coleoptera Chrysomelidae

150

Crop Order Family Genus Species Location Reference Matsumoto, Atrachya menetriesi Japan Yamazaki, 2013 Scarabaeidae Matsumoto, Popillia japonica Japan Yamazaki, 2013 Soybean (Glycine max) Hymenoptera Braconidae Ray 2003 Ichneumonidae Ray 2003 Scoliidae Yoshimura et al. Campsomeriella annulata Japan 2006 Diptera Chloropidae Ray 2003 Syrphidae Ray 2003 Coleoptera Chrysomelidae Yoshimura et al. Monolepta dichoroa Japan 2006 Coccinelidae Ray 2003 Hemiptera Anthocoridae Yoshimura et al. Orius sauteri Japan 2006 Yoshimura et al. Orius minutus Japan 2006 Geocoridae Yoshimura et al. Geocoris proteus Japan 2006 151

Crop Order Family Genus Species Location Reference Yoshimura et al. Geocoris varius Japan 2006 Miridae Yoshimura et al. Creontiades colripes Japan 2006 Lepidoptera Pieridae Yoshimura et al. Pieris rapae crucivara Japan 2006 Thysanoptera Thripidae Yoshimura et al. Frankliniella intonsa Japan 2006 Yoshimura et al. Thrips hawaiiensis Japan 2006 Yoshimura et al. Thrips sp. Japan 2006 Phlaeothripidae Yoshimura et al. Haplothrips chinensis Japan 2006 Neuroptera Chrysopidae Ray 2003 Butter bean (Phaseolus lunatus) Hymenoptera Sphecidae Free 1993 Vespidae Polistes sp. Free 1993 Green bean (Phaseolus vulgaris) Thysanoptera 152

Crop Order Family Genus Species Location Reference Thripidae Mackie, Smith Frankliniella occidentali* USA 1935 Bell Pepper (Capsicum annuum) Diptera Calliphoridae Breuils and Calliphora spp. Pochard 1975 Breuils and Lucilia spp. Pochard 1975 Syrphidae Eristalis tenax Canada Jarlan et al. 1997 Eggplant (Solanum melongena) Diptera Syrphidae Lowenstein et al. Syrphus spp. USA 2015 Lowenstein et al. Toxomerus spp. USA 2015

153

Appendix 2: Species-level identification of specimens caught in strawberry fields, accompanied by the number of individuals caught and their average pollen load count. # Average Family Species n (seq) insects # of % Fragaria # of plant # of plant pollen count caught reads pollen families genera Agromyzidae Ophiomyia nasuta 1 1 950 16 100 1 1 Anthomyiidae Delia platura 28 44 3352 1244528 67 14 20 Anthomyiidae Delia florilega 18 31 1426 798896 73 9 13 Braconidae Peristenus digoneutis 1 1 567 762 1.8 3 3 Calliphoridae Pollenia rudis 28 47 8792 1935025 87 19 44 Calliphoridae Lucilia sericata 1 2 2658 71296 16 5 8 Calliphoridae Pollenia pediculata 13 22 2175 747261 83 11 20 Carabidae Lebia viridis 3 4 1142 81767 96 2 2 Chironomidae Orthocladius mallochi 3 3 1044 285889 87 8 11 Chironomidae Orthocladius dorenus 1 4 1154 14618 82 2 2 Chloropidae Apallates particeps 2 5 1180 144911 63 4 5 Chloropidae Malloewia abdominalis 4 6 1197 239580 87 3 3 Chloropidae Conioscinella triorbiculata 1 1 1267 45235 100 1 1 Chloropidae Olcella parva 1 2 2667 5530 1.9 2 2 Chloropidae Liohippelates bishoppi 1 1 1300 0 0 0 0 Diabrotica Chrysomelidae 1 2 924 undecimpunctata 69912 89 2 2 Coccinellidae Hippodamia variegata 2 5 2277 179882 90 2 2 Coccinellidae Coleomegilla maculata 18 2 8517 1077366 86 10 19 Conopidae Myopa virginica 1 1 3467 81174 32 5 12 Crambidae Loxostege sticticalis 0 2 30900 n.a n.a n.a n.a Cynipidae Callirhytis tumifica 1 1 13000 26049 0 2 2 Dictynidae Emblyna hentzi 0 1 1267 n.a n.a n.a n.a Elateridae Sylvanelater cylindriformis 1 1 3933 36932 0.9 2 2 154

# Average Family Species n (seq) insects # of % Fragaria # of plant # of plant pollen count caught reads pollen families genera Ephydridae Discomyza incurva 1 1 1717 9396 1 3 3 Formicidae Tetramorium caespitum 10 19 2061 397115 92 6 7 Formicidae Formica subsericea 2 2 942 236794 30 3 3 Formicidae Prenolepis imparis 1 6 2550 77733 100 1 1 Lygaeidae Nysius niger 0 2 1717 n.a n.a n.a n.a Lygaeidae Lygaeus kalmii 1 1 2167 19673 0 2 2 Melyridae Collops quadrimaculatus 1 1 883 27075 100 1 1 Miridae Adelphocoris lineolatus 1 3 1739 23766 0.8 2 2 Miridae Lygus lineolaris 7 19 1863 445233 77 5 6 Miridae Plagiognathus obscurus 2 2 1417 192790 94 2 2 Miridae Plagiognathus politus 1 2 1742 15 100 1 1 Mordellidae Mordella marginata 3 8 2527 201445 80 4 5 Nabidae Nabis rufusculus 1 2 1567 61081 99 2 3 Nabidae Nabis americoferus 1 4 2284 15507 81 3 3 Nitidulidae Carpophilus brachypterus 8 13 3405 945496 96 4 6 Nitidulidae Fabogethes nigrescens 2 2 3417 82477 79 3 3 Sarcophagidae Sarcophaga subvicina 2 4 3288 154575 47 9 14 Sarcophagidae Senotainia trilineata 2 2 1367 312979 79 5 5 Scarabaeidae Popillia japonica 3 4 3945 226547 99 3 3 Scarabaeidae Macrodactylus subspinosus 1 1 1950 65968 66 5 5 Sciaridae Scatopsciara calamophila 1 1 1083 13529 64 3 3 Syrphidae Eristalis tenax 3 5 70000 197991 85 7 12 Syrphidae Sphaerophoria philanthus 15 28 2667 537697 80 7 10 Syrphidae Sphaerophoria contigua 3 3 906 145177 91 2 2 Syrphidae Toxomerus marginatus 60 114 1244 2788625 76 18 36

155

# Average Family Species n (seq) insects # of % Fragaria # of plant # of plant pollen count caught reads pollen families genera Syrphidae Syrphus ribesii 1 1 3333 112056 77 9 12 Syrphidae Toxomerus geminatus 2 5 1483 165863 100 1 1 Syrphidae Eristalis arbustorum 5 10 21611 250556 70 8 14 Syrphidae Syritta pipiens 3 5 1377 113762 89 4 7 Syrphidae Eristalinus aeneus 2 2 1700 173155 96 5 6 Syrphidae Heringia coxalis 1 2 13208 72497 80 2 2 Syrphidae Eristalis transversa 0 1 9150 n.a n.a n.a n.a Syrphidae Eumerus funeralis 1 1 1783 39660 95 4 5 Syrphidae Eristalis dimidiata 0 1 1317 n.a n.a n.a n.a Syrphidae Temnostoma barberi 0 1 8733 n.a n.a n.a n.a Tachinidae Dinera grisescens 4 6 2100 337669 90 12 22 Tachinidae Strongygaster triangulifera 1 1 650 26870 100 1 1 Tachinidae Ptilodexia mathesoni 1 1 1950 86136 75 5 8 Tephritidae Urophora quadrifasciata 0 2 900 n.a n.a n.a n.a Vespidae Ancistrocerus adiabatus 1 1 1067 77314 59 3 4

156

Appendix 3: Plant genera and families of pollen found on insect visitors of strawberry crops Order Family Genus Alismatales Alismataceae Sagittaria Apiales Apiaceae Aegopodium Apiales Apiaceae Daucus Apiales Apiaceae Pteryxia Asparagales Alliaceae Allium Asparagales Asparagaceae Asparagus Asparagales Orchidaceae Epipactis Asparagales Orchidaceae Cypripedium Asterales Asteraceae Agoseris Asterales Asteraceae Ambrosia Asterales Asteraceae Chondrilla Asterales Asteraceae Chrysanthemum Asterales Asteraceae Cichorium Asterales Asteraceae Crepis Asterales Asteraceae Eurybia Asterales Asteraceae Nabalus Asterales Asteraceae Psilocarphus Asterales Asteraceae Solidago Asterales Asteraceae Symphyotrichum Asterales Menyanthaceae Menyanthes Brassicales Brassicaceae Borodinia Brassicales Brassicaceae Brassica Brassicales Brassicaceae Bunias Brassicales Brassicaceae Cardamine Brassicales Brassicaceae Cochlearia Brassicales Brassicaceae Lepidium Caryophyllales Amaranthaceae Amaranthus Caryophyllales Caryophyllaceae Silene Caryophyllales Caryophyllaceae Stellaria Caryophyllales Chenopodiaceae Chenopodium Caryophyllales Polygonaceae Fagopyrum Caryophyllales Polygonaceae Persicaria Caryophyllales Polygonaceae Polygonum Cornales Cornaceae Cornus Cucurbitales Cucurbitaceae Citrullus Cucurbitales Cucurbitaceae Cucurbita Cucurbitales Cucurbitaceae Echinocystis

157

Order Family Genus Cucurbitales Cucurbitaceae Marah Dipsacales Adoxaceae Sambucus Fabales Fabaceae Coronilla Fabales Fabaceae Glycine Fabales Fabaceae Gymnocladus Fabales Fabaceae Lotus Fabales Fabaceae Medicago Fabales Fabaceae Pisum Fabales Fabaceae Trifolium Fagales Betulaceae Betula Fagales Fagaceae Quercus Fagales Juglandaceae Carya Gentianales Apocynaceae Cynanchum Gentianales Rubiaceae Galium Lamiales Lamiaceae Lamium Lamiales Oleaceae Fraxinus Lamiales Plantaginaceae Gratiola Lamiales Plantaginaceae Plantago Lamiales Plantaginaceae Veronica Lamiales Verbenaceae Verbena Laurales Lauraceae Sassafras Laurales Lauraceae Lindera Liliales Melanthiaceae Trillium Malpighiales Hypericaceae Hypericum Malpighiales Salicaceae Populus Malpighiales Salicaceae Salix Malvales Malvaceae Alcea Malvales Malvaceae Hibiscus Malvales Malvaceae Tilia Oxalidales Oxalidaceae Oxalis Pinales Pinaceae Picea Pinales Pinaceae Pinus Pinales Cupressaceae Juniperus Poales Juncaceae Juncus Poales Poaceae Agrostis Poales Poaceae Arrhenatherum Poales Poaceae Bromus Poales Poaceae Calamagrostis Poales Poaceae Deschampsia Poales Poaceae Digitaria Poales Poaceae Echinochloa 158

Order Family Genus Poales Poaceae Festuca Poales Poaceae Hordeum Poales Poaceae Lolium Poales Poaceae Phalaris Poales Poaceae Poa Poales Poaceae Schizachyrium Poales Poaceae Sclerochloa Poales Poaceae Sorghastrum Proteales Platanaceae Platanus Ranunculales Ranunculaceae Anemone Ranunculales Ranunculaceae Thalictrum Rosales Cannabaceae Celtis Rosales Moraceae Morus Rosales Rhamnaceae Frangula Rosales Rhamnaceae Rhamnus Rosales Rosaceae Dasiphora Rosales Rosaceae Fragaria Rosales Rosaceae Malus Rosales Rosaceae Physocarpus Rosales Rosaceae Potentilla Rosales Rosaceae Prunus Rosales Rosaceae Spiraea Rosales Ulmaceae Ulmus Santalales Santalaceae Comandra Sapindales Anacardiaceae Rhus Sapindales Anacardiaceae Toxicodendron Sapindales Rutaceae Zanthoxylum Sapindales Sapindaceae Acer Saxifragales Crassulaceae Hylotelephium Solanales Solanaceae Solanum Vitales Vitaceae Parthenocissus Vitales Vitaceae Vitis

159

Appendix 4: Triplot of redundancy analysis coloured by site. Includes explanatory environmental variables, time was also included as a continuous variable (blue arrows), temperature, humidity, solar radiation and wind, and temporal variables (blue x’s), date, and the response variables (coloured circles) coloured by the site they were collected from; the insect floral visiting community and their composition (red crosses). Both axes are significant (p< 0.001). Axis 1 explains 16% of the variance and axis 2 explains 11% variance. Data are Hellinger transformed.

160