The underestimated taxa: the role of non-bee pollinators

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

University of Guelph, 2019

Advisor(s):

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.

iii

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.

iv

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.

v

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

vi

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

vii

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

viii

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

ix

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

1

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

2

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,

3

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.

4

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

5

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

6

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).

7

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

8

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.

9

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

0

10

20

30

40

50

60

70

80

1930-1944 1945-1959 1960-1974 1975-1989 1990-2004 2005-2019

Nu

mb

er o

f P

aper

s

Year

All diversity Bees and Syrphids Only Bees

10

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

11

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.

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

Crop Requires crop pollination

Dependency category (Klein et al. 2007)

Evidence of non-bee 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 ✓

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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).

13

2.3.1.2 Rosaceae

2.3.1.2.1 Strawberry (Fragaria spp.)


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

14

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,

15

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)


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).

16

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

17

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 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

18

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).

19

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).

20

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)


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

21

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,

22

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)


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

23

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).

24

2.3.2 Vegetables

2.3.2.1 Amaryllidaceae

2.3.2.1.1 Onion (Allium cepa)


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

25

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)


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

http://www.fao.org/pollination/db/downloadBook.do?file=FreeChapter17.pdf

26

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

27

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


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


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).

28

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

29

2.3.2.3.5 Cucumber (Cucumis sativus)


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)


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

30

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

31

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

32

(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)


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).

33

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)


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

34

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).

35

2.3.2.5 Leguminosae

2.3.2.5.1 Faba beans (Vicia faba)


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.

36

2.3.2.5.2 Runner beans (Phaseolus coccineus)


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,

37

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)


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).

38

2.3.2.6 Liliaceae

2.3.2.6.1 Asparagus (Asparagus officinalis)


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)


Bell pepper plants are self-fertile; however, fruit set is significantly enhanced when

supplemental insect pollination is provided (McGregor 1976).

Non-bee pollination

39

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)


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

40

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).

41

2.3.2.7.3 Tomato (Lycopersicon esculentum)


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

42

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)


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

https://www.google.com/search?rlz=1C1CHBF_enCA762CA762&q=Rosaceae&stick=H4sIAAAAAAAAAONgVuLQz9U3MEvJzVjEyhGUX5yYnJqYCgC4UxFAFwAAAA&sa=X&ved=2ahUKEwj__JPXueTiAhUkiOAKHe86CfwQmxMoATAiegQIDxAH

43

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

44

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

45

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

46

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

47

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.

48

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

49

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

50

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.

51

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

52

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

53

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’

54

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

55

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,

56

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

57

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

58

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).

59

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

https://github.com/VascoElbrecht/JAMP

60

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

61

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

62

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.

63

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.

Order Family Species Insect

Abundance Total

Pollen Average Pollen

StdDev (+/-)

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

Halictidae Lasioglossum anomalum

1 2233

Halictidae Lasioglossum pectorale

7 15906 7068

Halictidae Lasioglossum perpunctatum

2 7500 5400

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

Formicidae

Tetramorium caespitum

19 39150 2061 1893

Vespidae

Ancistrocerus adiabatus

1 1067 1067

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

64


Abundance Total


StdDev (+/-)

Chloropidae

Conioscinella triorbiculata

1 1267 1267

Chloropidae Liohippelates bishoppi 1 1300 1300

Chloropidae

Malloewia abdominalis

6 7183 1197 629

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

Sciaridae

Scatopsciara calamophila

1

1083

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

Syrphidae

Sphaerophoria contigua

3 2717 906 202

Syrphidae

Sphaerophoria philanthus

28 37333 1333 448

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

Syrphidae

Toxomerus marginatus

114 141783 1244 776

Tachinidae Dinera grisescens 6 12600 2100 1295

Tachinidae Ptilodexia mathesoni 1 1950 1950

Tachinidae

Strongygaster triangulifera

1 650 650

Tachinidae

tachJanzen01 Janzen3066

1 1617 1617

Tephritidae

Urophora quadrifasciata

2 1800 900 200

Hemiptera Lygaeidae Lygaeus kalmia 1 2167 2167

Lygaeidae Nysius niger 2 3433 1717 33

Miridae

Adelphocoris lineolatus

3 5217 1739 358

65


Abundance Total


StdDev (+/-)

Miridae Lygus lineolaris 19 35200 1853 1156

Miridae

Plagiognathus obscurus

2 2833 1417 0

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

Chrysomelidae

Diabrotica undecimpunctata

2 1883 942 325

Coccinellidae

Coleomegilla maculata

2 17033 8517 4333

Coccinellidae Hippodamia variegata 5 11383 2277 1994

Elateridae

Sylvanelater cylindriformis

1 3933 3933

Melyridae

Collops quadrimaculatus

1 883 883

Mordellidae Mordella marginata 8 20217 2527 1913

Nitidulidae

Carpophilus brachypterus

13 21933 1687 886

Nitidulidae Fabogethes nigrescens 2 6833 3417 550

Scarabaeidae Popillia japonica 4 15783 3946 2147

Scarabaeidae

Macrodactylus subspinosus

1 1950 1950

66

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.

67

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.

68

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.

69

Table 3.3: Insect visitors observed on day-neutral strawberries in Southern Ontario, CA, using observation and collection data.

Order Family Genera Percentage

of community Observed

Abundance Percent of

Total Pollen Total


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

Halictidae Agapostemon, Augochlora, 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

70

Order Family Genera Percentage

of community Observed

Abundance Percent of

Total Pollen Total


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

71

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.

Family Parameter Estimate Estimate SE

Lower 95% CI

Upper 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 *

72

Family Parameter Estimate Estimate SE

Lower 95% CI

Upper 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

73

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.

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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

82

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

83

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

84

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

85

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.

86

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.

87

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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)

Diptera Australia Langridge, Goodman 1981

Syrphidae Australia Langridge, Goodman 1981

Muscidae Australia Langridge, Goodman 1981

Musca sp. Australia Langridge, Goodman 1981

Lepidoptera Australia Langridge, Goodman 1981

Strawberry (Fragaria spp.)

Hymenoptera

Braconidae

Bracon sp. USA

Nye, Anderson 1974

Formicidae

Formica sp. USA

Nye, Anderson 1974

Formica subserices USA

Ashmann, King 2005

Prenolepis imparis USA

Ashmann, King 2005

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Tapinoma sessile USA

Ashmann, King 2005

Ichneumonidae USA

Nye, Anderson 1974

Proctotrupidae

Proctotrupes sp. USA

Nye, Anderson 1974

Sphecidae

Ammophila sp. USA

Nye, Anderson 1974

Ectemnius sp. USA

Nye, Anderson 1974

Podalonia luctuosa USA

Nye, Anderson 1974

Xylocelia sp. USA

Nye, Anderson 1974

Vespidae

Anistrocerus sp. USA

Nye, Anderson 1974

Odynerus dilectus USA

Nye, Anderson 1974

Polistes fuscatus USA

Nye, Anderson 1974

Diptera

Anthomyiidae

Hylemya platura USA

Nye, Anderson 1974

Bombyliidae

Bombylius major Canada

de Oliveira et al. 1991

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Bombylius pygmaeus Canada


Bombylius sp. USA

Nye, Anderson 1974

Villa utahensis USA

Nye, Anderson 1974

Villa sp. USA

Nye, Anderson 1974

Calliphoridae

Bufolucilia silvarum USA

Nye, Anderson 1974

Calliphora sp. USA

Nye, Anderson 1974

Phaenicia sericata USA

Nye, Anderson 1974

Phormia regina USA

Nye, Anderson 1974

Pollenia rudis USA

Nye, Anderson 1974

Conopidae

Thecophora luteipes USA

Nye, Anderson 1974

Muscidae

Coenosia tigrina USA

Nye, Anderson 1974

Otitidae

Tetanops myopaeformis USA

Nye, Anderson 1974

Sarcophagidae

117


Sarcophaga sp. USA

Nye, Anderson 1974

Wohlfahrtia vigil USA

Nye, Anderson 1974

Stratiomyidae

Odontomyia pubescens USA

Nye, Anderson 1974

Syrphidae Sweden

Stewart et al. 2017

Asemosyrphus polygrammus USA

Nye, Anderson 1974

Chrysogaster bellula USA

Nye, Anderson 1974

Chrysogaster parva USA

Nye, Anderson 1974

Dasysyrphus venustus Canada


Eristalis arbustorum Canada


Eristalis barda Canada


Eristalis bastardii Canada


Eristalis obscura Canada


Eristalis stipator Canada


Eristalis transversa Canada


118


Eristalis tenax Canada, USA

de Oliveira et al. 1991; Nye, Anderson 1974

Eristalis anthophorinus USA

Nye, Anderson 1974

Eristalis brousii USA

Nye, Anderson 1974

Eristalis latifrons USA

Nye, Anderson 1974

Eristalis sp. USA

Nye, Anderson 1974

Eristalis spp. USA Nye, Anderson 1974

Eumerus strigatus USA

Nye, Anderson 1974

Eupeodes volucris USA

Nye, Anderson 1974

Helophilus fasciatus Canada


Helophilus latifrons Canada, USA


Helophilus lunuatus USA

Nye, Anderson 1974

Helophilus stipatus USA

Nye, Anderson 1974

Helophilus sp. USA

Nye, Anderson 1974

Lejops hamatus Canada


119


Merodon equestris USA

Nye, Anderson 1974

Metasyrphus sp. Canada


Orthonevra pulchella Canada


Platycheirus clypeatus Canada


Sericomyia militaris Canada


Sphaerophoria sp. Canada, USA


Syritta pipiens Canada, USA


Syrphus ribesii Canada


Temnostoma alternans Canada


Xylota flavitibia USA

Nye, Anderson 1974

Tachinidae USA

Nye, Anderson 1974

Gonia spp. USA

Nye, Anderson 1974

Peleteria iterans USA

Nye, Anderson 1974

Coleoptera

Cerambycidea

120


Callidium antennatum USA

Nye, Anderson 1974

Curculionidae

Rhynchites bicolor USA

Nye, Anderson 1974

Melyridae

Collops sp. USA

Nye, Anderson 1974

Hemiptera

Cicadellidae USA

Nye, Anderson 1974

Pentatomidae

Cosmopepla conspicillaris USA

Nye, Anderson 1974

Miridae USA

Nye, Anderson 1974

Lepidoptera

Hesperiidae

Hesperia juba USA

Nye, Anderson 1974

Pholisora cattulus USA

Nye, Anderson 1974

Polites sabuleti USA

Nye, Anderson 1974

Lycaenidae

Lycaena helloides USA

Nye, Anderson 1974

Lycaena sp. USA

Nye, Anderson 1974

Noctuidae

121


Anagrapha falcifera USA

Nye, Anderson 1974

Nymphalidae

Phyciodes mylitta USA

Nye, Anderson 1974

Pieridae

Pieris protodice USA

Nye, Anderson 1974

Pieris rapae USA

Nye, Anderson 1974

Colias sp. USA

Nye, Anderson 1974

Satyridae

Coenonympha sp. USA

Nye, Anderson 1974

Neuroptera

Chrysomelidae

Chrysoperla cernea Mexico Zapata 1989

Trichoptera USA

Nye, Anderson 1974

Apple (Malus domestica)

Hymenoptera

Chalicidoidea

Anacharis spp. Canada Boyle-Moleski, 1983

Pholetesor ornigis Canada Boyle-Moleski, 1983

Sympiesis marylandensis Canada Boyle-Moleski, 1983

122


Eumenidae Spain

Vicens et al. 2000

Formicidae

Camponotus spp. Canada Boyle-Moleski, 1983

Formica fusca Canada Boyle-Moleski, 1983

Formica glacialis Canada Boyle-Moleski, 1983

Lasius neoniger Canada Boyle-Moleski, 1983

Linepithema spp. Columbia Botero, 2000

Prenolepis imparis Canada Boyle-Moleski, 1983

Ichneumonidae

Diplazon laetatorius Canada Boyle-Moleski, 1983

Pycnocryptus director Canada Boyle-Moleski, 1983

Syrphoctonus flavolineatus Canada Boyle-Moleski, 1983

Tryphon seminiger Canada Boyle-Moleski, 1983

Tymmophorus rufiventris Canada Boyle-Moleski, 1983

Tentredinidae

Eutomostethus ephippium Canada Boyle-Moleski, 1983

Vespidae Spain

Vicens et al. 2000

123


Agelaia spp. Columbia Botero, 2000

Epipona spp. Columbia Botero, 2000

Vespula maculata Canada Boyle-Moleski, 1983

Vespula germanica New Zealand

Palmer-Jones, Clinch 1967

Diptera

Agromyzidae

Japanagromyza viridula Canada Boyle-Moleski, 1983

Anthomyiidae

Spain

Vicens et al. 2000

Hylemya brassicae Canada Boyle-Moleski, 1983

Hylemya florilega Canada Boyle-Moleski, 1983

Hylemya fugax Canada Boyle-Moleski, 1983

Hylemya platura Canada Boyle-Moleski, 1983

Hylemya spp. Canada Boyle-Moleski, 1983

Nupedia dissecta Canada Boyle-Moleski, 1983

Bibionidae

Bibio

albipennis Canada Boyle-Moleski, 1983

Bibio spp. Columbia, Canada

Botero, 2000; Boyle-Moleski, 1983

124


Bombyliidae

Bombylius pygmatus Canada Williams, 1932

Bombylius major Canada Williams, 1932

Calliphoridae

New Zealand, Spain

Palmer-Jones, Clinch 1967; Vicens et al. 2000

Bufolucilia silvarum Canada Boyle-Moleski, 1983

Lucilia illustris Canada Boyle-Moleski, 1983

Phaenicia eximia Columbia Botero, 2000

Phormia regina Canada Boyle-Moleski, 1983

Pollenia rudis Canada, Canada

Williams, 1932; Boyle-Moleski, 1983

Chironomidae

Canada Boyle-Moleski, 1983

Chironomus spp. Canada Boyle-Moleski, 1983

Chironomus maturus Canada Boyle-Moleski, 1983

Cricotopus spp. Canada Boyle-Moleski, 1983

Endochironomus spp. Canada Boyle-Moleski, 1983

Limnophyes spp. Canada Boyle-Moleski, 1983

125


Micropsectra spp. Canada Boyle-Moleski, 1983

Orthocladius spp. Canada Boyle-Moleski, 1983

Procladius spp. Canada Boyle-Moleski, 1983

Conopidae

Myopa vesiculosa Canada Boyle-Moleski, 1983

Dolichopodiae Columbia Botero, 2000

Dolichopus

spp. Canada Boyle-Moleski, 1983

Ephydridae

Hydrellia spp. Canada Boyle-Moleski, 1983

Muscidae

Columbia, Spain

Botero, 2000; Vicens et al. 2000

Fannia spp. Canada Boyle-Moleski, 1983

Fannia coracina Canada Boyle-Moleski, 1983

Sarcophagidae

Boettcheria spp. Canada Boyle-Moleski, 1983

Ravinia latisetosa Canada Boyle-Moleski, 1983

Scathophagidae

Scathophaga furcata Canada Boyle-Moleski, 1983

126


Scathophagidae

Scathophaga stercorarium Canada Boyle-Moleski, 1983

Sciaridae Columbia Botero, 2000

Stratiomyidae

Odontomyia interrupta Canada Williams, 1932

Syrphidae

Allograpta spp. Columbia Botero, 2000

Allograpta obliqua Canada Boyle-Moleski, 1983

Brachyopa perplexa Canada Williams, 1932

Cartosyrphus slossonae Canada Williams, 1932

Criorhina badia Canada Williams, 1932

Epistrophe

eligans Hungary Foldesi et al. 2016

Epistrophe

euchroma Hungary Foldesi et al. 2016

Episyrphus balteatus

Spain, Hungary

Vicens et al. 2000; Foldesi et al. 2016

Eristalinus aeneus Hungary Foldesi et al. 2016

Eristalis

arbustorum

Canada, Canada, Hungary

Williams, 1932; Boyle-Moleski, 1983; Foldesi et al. 2016

Eristalis bastardi Canada Williams, 1932

Eristalis compactus Canada Williams, 1932

Eristalis dimidiata Canada Boyle-Moleski, 1983

127


Eristalis spp. Canada Boyle-Moleski, 1983

Eristalis peristallis Kendall 1973

Eristalis

tenax Canada, Spain

Boyle-Moleski, 1983; Kendall 1973; Vicens et al. 2000

Eupeodes corollae Hungary Foldesi et al. 2016

Helophilus fasciatus Canada Boyle-Moleski, 1983

Helophilus latifrons Canada Boyle-Moleski, 1983

Hylemya spp. Canada Williams, 1932

Melanostoma spp. Canada Boyle-Moleski, 1983

Melanostoma pictipes Canada Williams, 1932

Metasyrphus spp. Canada Boyle-Moleski, 1983

Metasyrphus latifasciatus Canada Boyle-Moleski, 1983

Neoascia

podagrica Hungary Foldesi et al. 2016

Pipiza viduata Hungary Foldesi et al. 2016

Platycheirus

scutatus Hungary Foldesi et al. 2016

Platycheirus quadratus Canada Boyle-Moleski, 1983

128


Platycheirus scutatus Canada Boyle-Moleski, 1983

Rhingia nasica Canada Williams, 1932

Sericomyia militaris Canada Williams, 1932

Sphaerophoria scripta Hungary Foldesi et al. 2016

Sphaerophoria spp. Canada Boyle-Moleski, 1983

Sphaerophoria pilanthus Canada Boyle-Moleski, 1983

Sphecomyia vittata Canada Williams, 1932

Syritta

pipiens Hungary Foldesi et al. 2016

Syrphus ribesii Hungary Foldesi et al. 2016

Syrphus vitripennis Hungary Foldesi et al. 2016

Syrphus rectus Canada Boyle-Moleski, 1983

Syrphus torvus Canada, Canada

Williams, 1932; Boyle-Moleski, 1983

Syrphus wiedemanni Canada Williams, 1932

Syrphus rectus Canada Williams, 1932

Syrphus amalopis Canada Williams, 1932

Syrphus ribesii Spain

Vicens et al. 2000

Toxomerus germinatus Canada Boyle-Moleski, 1983

129


Toxomerus marginatus Canada Boyle-Moleski, 1983

Tachinidae

Spain Vicens et al. 2000

Paralipse spp. Columbia Botero, 2000

Periscepsia helymus Canada Boyle-Moleski, 1983

Tachinomya nigricans Canada Boyle-Moleski, 1983

Mericia ampelus Canada Williams, 1932

Tipulidae

New Zealand

Palmer-Jones, Clinch 1967

Coleoptera Spain

Vicens et al. 2000

Cantharidae

Cantharis bilineatus Canada Boyle-Moleski, 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

Coccinella transversoguttata richardsoni Canada

Boyle-Moleski, 1983

Curculionidae

Pandeleteius spp. Columbia Botero, 2000

130


Nicentrus testaceipes Columbia Botero, 2000

Elateridae

Pomachilus suturalis Columbia Botero, 2000

Ctenicera lobata tarsalis Canada Boyle-Moleski, 1983

Melolonthidae

Isonychus spp. Columbia Botero, 2000

Macrodactyus spp. Columbia Botero, 2000

Anomala spp. Columbia Botero, 2000

Nitidulidae

Meligethes canadensis Canada Boyle-Moleski, 1983

Meligethes nigrescens Canada Boyle-Moleski, 1983

Scarabaeidae

Phyllophaga spp. Canada Boyle-Moleski, 1983

Phyllophaga rugosa Canada Boyle-Moleski, 1983

Phyllophaga luteola Canada Boyle-Moleski, 1983

Hemiptera

Anthocoridae

Orius insidosus Canada Boyle-Moleski, 1983

Coreidae

Kleidocerys resedae Canada Boyle-Moleski, 1983

Miridae

131


Lygus spp. Canada Boyle-Moleski, 1983

Lygus lineolarius Canada Boyle-Moleski, 1983

Monalonion velezangeli Columbia Botero, 2000

Taylorilygus spp. Columbia Botero, 2000

Lepidoptera Spain

Vicens et al. 2000

Ctenuchidae Columbia Botero, 2000

Gelechiidae Canada Boyle-Moleski, 1983

Geometridae

Haematopis Grataria Canada Boyle-Moleski, 1983

Gracilariidae

Lithocolletis spp. Canada Boyle-Moleski, 1983

Hesperiidae

Urbanus proteus Columbia Botero, 2000

Panoquina spp. Columbia Botero, 2000

Pythonides thespieus Columbia Botero, 2000

Mysoria spp. Columbia Botero, 2000

Erynnis juvenalis Canada Boyle-Moleski, 1983

Noctuidae

Anagrapha falcifera Canada Boyle-Moleski, 1983

Apamea finitima Canada Boyle-Moleski, 1983

132


Pseudaletia unipuncta Canada Boyle-Moleski, 1983

Nymphalidae

Actinote spp. Columbia Botero, 2000

Vanessa atalanta rubria Canada Boyle-Moleski, 1983

Olethreutidae

Pseudeexentera spp. Canada Boyle-Moleski, 1983

Pieridae

Leptophobia aripa Columbia Botero, 2000 Blackberry (Rubus fruticosus, R. resticanus inermis, R. argutus, R. allegheniensis, R. spp.)

Diptera

Syrphidae

Eristalis spp. England Gyan, Woodell 1987

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

Hymenoptera

Braconidae USA

Hansen, Osgood 1983

Chalcididae USA

Hansen, Osgood 1983

Chrysididae USA

Hansen, Osgood 1983

Eumenidae

Ancistrocerus sp USA

Hansen, Osgood 1983

Eumenes crucifer USA

Hansen, Osgood 1983

133


Euodynerus sp USA

Hansen, Osgood 1983

Stenodynerus sp USA

Hansen, Osgood 1983

Symmorphus sp USA

Hansen, Osgood 1983

Formicidae USA

Hansen, Osgood 1983

Gasterupiidae

Gasteruption kirbii USA

Hansen, Osgood 1983

Ichneumonidae USA

Hansen, Osgood 1983

Pompilidae USA

Hansen, Osgood 1983

Pteromalidae USA

Hansen, Osgood 1983

Sphecidae

Ammophila azteca USA

Hansen, Osgood 1983

Ammophila evansi USA

Hansen, Osgood 1983

Ammophila mediata USA

Hansen, Osgood 1983

Crossocerus sp. USA

Hansen, Osgood 1983

Ectemnius arcuatus USA

Hansen, Osgood 1983

Ectemnius atriceps USA

Hansen, Osgood 1983

134


Ectemnius borealis USA

Hansen, Osgood 1983

Ectemnius continuus USA

Hansen, Osgood 1983

Ectemnius dives USA

Hansen, Osgood 1983

Ectemnius

lapidarisus USA

Hansen, Osgood 1983

Ectemnius ruficornis USA

Hansen, Osgood 1983

Ectemnius stirpicola USA

Hansen, Osgood 1983

Lestica sp. USA

Hansen, Osgood 1983

Tenthredinidae USA

Hansen, Osgood 1983

Vespidae

Dolichovespula arenaria USA

Hansen, Osgood 1983

Diptera

Anthomyiidae USA

Hansen, Osgood 1983

Asilidae USA

Hansen, Osgood 1983

Bombyliidae

Hemipenthes sp. USA

Hansen, Osgood 1983

Lepidophora sp. USA

Hansen, Osgood 1983

135


Calliphoridae USA

Hansen, Osgood 1983

Chironomidae USA

Hansen, Osgood 1983

Conopidae USA

Hansen, Osgood 1983

Dolichopodiae USA

Hansen, Osgood 1983

Empididae USA

Hansen, Osgood 1983

Lauxaniidae USA

Hansen, Osgood 1983

Muscidae USA

Hansen, Osgood 1983

Sarcophagidae USA

Hansen, Osgood 1983

Simuliidae USA

Hansen, Osgood 1983

Syrphidae

Blera confusa USA

Hansen, Osgood 1983

Carposcalis obsurum USA

Hansen, Osgood 1983

Cartosyrphus pallipes USA

Hansen, Osgood 1983

Cartosyrphus sp. USA

Hansen, Osgood 1983

Chalcosyrphus libo USA

Hansen, Osgood 1983

136


Chrysotoxum fasciolatum USA

Hansen, Osgood 1983

Eristalis obsurus USA

Hansen, Osgood 1983

Epistrophe emarginata USA

Hansen, Osgood 1983

Epistrophe xanthostoma USA

Hansen, Osgood 1983

Heringia coxalis USA

Hansen, Osgood 1983

Heringia sp. USA

Hansen, Osgood 1983

Leucozna lucorum USA

Hansen, Osgood 1983

Mallota posticata USA

Hansen, Osgood 1983

Melangyna lasiophthalma USA

Hansen, Osgood 1983

Metasyrphus perplexus USA

Hansen, Osgood 1983

Microdon tristis USA

Hansen, Osgood 1983

Orthonevra pulchella USA

Hansen, Osgood 1983

Parasyrphus genualis USA

Hansen, Osgood 1983

Parasyrphus semiinterruptus USA

Hansen, Osgood 1983

Parasyrphus sp. USA

Hansen, Osgood 1983

137


Sericomyia chrysotoxoides USA

Hansen, Osgood 1983

Sericomyia lata USA

Hansen, Osgood 1983

Sericomyia militaris USA

Hansen, Osgood 1983

Sphaerophoria contingua USA

Hansen, Osgood 1983

Sphaerophoria longipilosa USA

Hansen, Osgood 1983

Sphaerophoria novaengliae USA

Hansen, Osgood 1983

Sphegina rufiventris USA

Hansen, Osgood 1983

Syritta pipiens USA

Hansen, Osgood 1983

Syrphus rectus USA

Hansen, Osgood 1983

Syrphus ribesii USA

Hansen, Osgood 1983

Syrphus torvus USA

Hansen, Osgood 1983

Temnostoma alternans USA

Hansen, Osgood 1983

Temnostoma barberi USA

Hansen, Osgood 1983

Temnostoma vespiforme USA

Hansen, Osgood 1983

Taxomerus geminatus USA

Hansen, Osgood 1983

138


Taxomerus marginatus USA

Hansen, Osgood 1983

Volucella bombylans USA

Hansen, Osgood 1983

Xylota annulifera USA

Hansen, Osgood 1983

Xylota quadrimaculata USA

Hansen, Osgood 1983

Tachinidae USA

Hansen, Osgood 1983

Tipulidae USA

Hansen, Osgood 1983

Coleoptera

Anobiidae USA

Hansen, Osgood 1983

Byrrhidae USA

Hansen, Osgood 1983

Byturidae

Byturus rubi USA

Hansen, Osgood 1983

Cantharidae USA

Hansen, Osgood 1983

Cerambycidea

Anastranglia sanguinea USA

Hansen, Osgood 1983

Clytus ruricola USA

Hansen, Osgood 1983

Cosmosalia chrysocoma USA

Hansen, Osgood 1983

139


Evodinus monticola USA

Hansen, Osgood 1983

Judolia montivagens USA

Hansen, Osgood 1983

Neoalosterna capitata USA

Hansen, Osgood 1983

Pidonia ruficollis USA

Hansen, Osgood 1983

Strangalepta abbreviata USA

Hansen, Osgood 1983

Curculionidae USA

Hansen, Osgood 1983

Elateridae USA

Hansen, Osgood 1983

Lagriidae USA

Hansen, Osgood 1983

Lampyridae

Photuris pennsylvanica USA

Hansen, Osgood 1983

Mordellidae USA

Hansen, Osgood 1983

Ptilodactylidae USA

Hansen, Osgood 1983

Scarabaeidae

Trichiotinus affinis USA

Hansen, Osgood 1983

Hemiptera

Miridae USA

Hansen, Osgood 1983

140


Pentatomidae USA

Hansen, Osgood 1983

Lepidoptera

Lycaenidae USA

Hansen, Osgood 1983

Macrolepidoptera USA

Hansen, Osgood 1983

Microlepidoptera USA

Hansen, Osgood 1983

Nymphalidae

Nyphalis antiopa USA

Hansen, Osgood 1983

Vanessa atalanta USA

Hansen, Osgood 1983

Papilionidae

Papilio glaucus USA

Hansen, Osgood 1983

Onion (Allium cepa)

Hymenoptera

Ichneumonidae

Echthromorpha intricatoria New Zealand

Howlett et al. 2009

Netelia producta New Zealand

Howlett et al. 2009

Sphecidae

Bembix amoena USA

Bohart, Nye, 1970

Vespidae

Vespula germanica New Zealand

Howlett et al. 2009

141


Diptera

Anthomyiidae

Delia platura

New Zealand

Howlett et al. 2009

Anthomyia punctipennis

New Zealand

Howlett et al. 2009

Bibionidae

Dilophus nigrostigma

New Zealand

Howlett et al. 2009

Calliphoridae Pakistan Sajjad et al. 2008

Calliphora stygia

New Zealand

Howlett et al. 2009

Calliphora vicina

New Zealand

Howlett et al. 2009

Calliphora hortona

New Zealand

Howlett et al. 2009

Calliphora quadrimaculata

New Zealand

Howlett et al. 2009

Lucilia sericata

New Zealand

Howlett et al. 2009

Pollenia pseudorudis

New Zealand

Howlett et al. 2009

Chloropidae

Thaumatomyia glabra USA

Bohart, Nye, 1970

Muscidae

Hydrotaea rostrata

New Zealand

Howlett et al. 2009

142


Musca domestica

Pakistan, New Zealand

Sajjad et al. 2008; Howlett et al. 2009

Spilagona melas

New Zealand

Howlett et al. 2009

Sarcophagidae

Sarcophaga sp. Pakistan Sajjad et al. 2008

Stratiomyidae

Odontomyia sp.

New Zealand

Howlett et al. 2009

Syrphidae

Episyrphus balteatus Pakistan Sajjad et al. 2008

Eristalinus aeneus Pakistan Sajjad et al. 2008

Eristalis tenax USA, New Zealand

Bohart, Nye, 1970; Howlett et al. 2009

Eumerus funeralis

New Zealand

Howlett et al. 2009

Eupeodes corollae Pakistan Sajjad et al. 2008

Helophilus hochstetteri

New Zealand

Howlett et al. 2009

Helophilus seelandicus

New Zealand

Howlett et al. 2009

Melangyna novae-zelandia

New Zealand

Howlett et al. 2009

Melanostoma fasciatum

New Zealand

Howlett et al. 2009

Mesembrius bengalensis Pakistan Sajjad et al. 2008

Sphaerophoria scripta Pakistan Sajjad et al. 2008

143


Syritta pipiens USA

Bohart, Nye, 1970

Tabanidae

Scaptia sp.

New Zealand

Howlett et al. 2009

Tachinidae

Campbellia lancifer

New Zealand

Howlett et al. 2009

Gracilicera sp.

New Zealand

Howlett et al. 2009

Pales usitata

New Zealand

Howlett et al. 2009

Procissio sp.

New Zealand

Howlett et al. 2009

Protohystricia alcis

New Zealand

Howlett et al. 2009

Voriini sp.

New Zealand

Howlett et al. 2009

Tipulidae

Tipula sp.

New Zealand

Howlett et al. 2009

Coleoptera

Coccinelidae

Adalia bipunctata New Zealand

Howlett et al. 2009

Coccinella leonina New Zealand

Howlett et al. 2009

Coccinella undecimpunctata New Zealand

Howlett et al. 2009

Elateridae

144


Conoderus exsul New Zealand

Howlett et al. 2009

Hemiptera

Pentatomidae

Nezara viridula New Zealand

Howlett et al. 2009

Lepidoptera

Crambidae

Orocambus flexuosellus New Zealand

Howlett et al. 2009

Lycaenidae

Zizina labradus New Zealand

Howlett et al. 2009

Nymphalidae

Danaus plexippus New Zealand

Howlett et al. 2009

Pieridae

Pieris rapae New Zealand

Howlett et al. 2009

Beets (Beta vulgaris)

Hymenoptera

Aphidiidae England Free, Williams, 1975

Tenthredinidae England Free, Williams, 1975

Braconidae England Free, Williams, 1975

Ichneumonidae

Amblyteles fossorius* England Free, Williams, 1975

145


Lissonata sulphurifera* England Free, Williams, 1975

Pteromalus puparum* England Free, Williams, 1975

Diptera

Anthomyiidae England Free, Williams, 1975

Asilidae England Free, Williams, 1975

Calliphoridae

Phormia sp. England Free, Williams, 1975

Lucilia richardsi* England Free, Williams, 1975

Pollenia rudis England Free, Williams, 1975

Chloropidae England Free, Williams, 1975

Cordiluridae

Scopeuma stercorarium* England Free, Williams, 1975

Empididae England Free, Williams, 1975

Larvaevoridae

Phytomyptera nitidiventris* England Free, Williams, 1975

Eriothrix rufomaculatus* England Free, Williams, 1975

Arrhinomyia innoxia* England Free, Williams, 1975

146


Muscidae

Muscina assimilis* England Free, Williams, 1975

Thricops sp. England Free, Williams, 1975

Fannia sp. England Free, Williams, 1975

Phoridae England Free, Williams, 1975

Platypezidae England Free, Williams, 1975

Sepsidae

Sepsidomorpha pilipes* England Free, Williams, 1975

Syrphidae

Eristalis pertinax* England Free, Williams, 1975

Eristalis tenax* England Free, Williams, 1975

Eristalis arbustorum* England Free, Williams, 1975

Eristalis horticola* England Free, Williams, 1975

Melanostoma scalare* England Free, Williams, 1975

Melanostoma mellinum* England Free, Williams, 1975

Melithreptus scriptus Ukraine Archimowitsch, 1949

147


Platychirus manicatus* England Free, Williams, 1975

Scaeva pyrastri* England Free, Williams, 1975

Sphaerophoria scripta* England Free, Williams, 1975

Syritta pipens* England Free, Williams, 1975

Syrphus glaucius* England Free, Williams, 1975

Syrphus vitripennis* England Free, Williams, 1975

Syrphus ribesii* England Free, Williams, 1975

Syrphus corollae* England Free, Williams, 1975

Syrphus luniger* England Free, Williams, 1975

Syrphus balteatus* England Free, Williams, 1975

Tabanidae

Chrysops caecutiens* England Free, Williams, 1975

Tipulidae

Nephrotoma sp. England Free, Williams, 1975

Nephrotoma flavescens* England Free, Williams, 1975

Coleoptera

Cantharidae

148


Cantharis paludosa* England Free, Williams, 1975

Cantharis lateralis* England Free, Williams, 1975

Rhagonycha fulva* England Free, Williams, 1975

Malthodes sp. England Free, Williams, 1975

Chrysomelidae

Leptura sp. Ukraine Archimowitsch, 1949

Coccinelidae

Coccinella septempunctata Ukraine Archimowitsch, 1949

Adalia bipunctata* England Free, Williams, 1975

Adalia 10-punctata* England Free, Williams, 1975

Cocinella 7-punctata* England Free, Williams, 1975

Propylea 14-punctata* England Free, Williams, 1975

Curculionidae

Phyllobius pomaceus* England Free, Williams, 1976

Elateridae

Corymbites sp. England Free, Williams, 1975

Meloidae

149


Zonabris sp. Ukraine Archimowitsch, 1949

Cerocoma sp. Ukraine Archimowitsch, 1949

Serropalpidae

Melandrya caraboides* England Free, Williams, 1975

Hemiptera

Cimicidae

Calocoris sp. England Free, Williams, 1975

Calocoris sexguttatus* England Free, Williams, 1975

Calocoris norvegicus* England Free, Williams, 1975

Lepidoptera

Tortricidae

Tortrix rusticana* England Free, Williams, 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

Forficula auricularia England Free, Williams, 1975

150


Cabbage (Brassica sp.)

Diptera

Syrphidae USA Pearson 1932

Calliphoridae USA Pearson 1932

Muscidae USA Pearson 1932

Cucumber (Cucumis sativus)

Diptera

Syrphidae

Syrphus spp USA

Lowenstein et al. 2015

Toxomerus spp. USA

Lowenstein et al. 2015

Pumpkin (Cucurbita pepo)

Hymenoptera

Formicidae Japan Matsumoto, Yamazaki, 2013

Tenthredinidae

Allantus luctifer Japan Matsumoto, Yamazaki, 2013

Diptera

Syrphidae

Syritta

pipiens Japan Matsumoto, Yamazaki, 2013

Sphaerophoria

indiana Japan Matsumoto, Yamazaki, 2013

Coleoptera

Chrysomelidae

151


Atrachya menetriesi Japan Matsumoto, Yamazaki, 2013

Scarabaeidae

Popillia japonica Japan Matsumoto, Yamazaki, 2013

Soybean (Glycine max)

Hymenoptera

Braconidae Ray 2003

Ichneumonidae Ray 2003

Scoliidae

Campsomeriella annulata Japan Yoshimura et al. 2006

Diptera

Chloropidae Ray 2003

Syrphidae Ray 2003

Coleoptera

Chrysomelidae

Monolepta dichoroa Japan Yoshimura et al. 2006

Coccinelidae Ray 2003

Hemiptera

Anthocoridae

Orius sauteri Japan Yoshimura et al. 2006

Orius minutus Japan Yoshimura et al. 2006

Geocoridae

Geocoris proteus Japan Yoshimura et al. 2006

152


Geocoris varius Japan Yoshimura et al. 2006

Miridae

Creontiades colripes Japan Yoshimura et al. 2006

Lepidoptera

Pieridae

Pieris rapae crucivara Japan Yoshimura et al. 2006

Thysanoptera

Thripidae

Frankliniella intonsa Japan Yoshimura et al. 2006

Thrips hawaiiensis Japan Yoshimura et al. 2006

Thrips sp. Japan Yoshimura et al. 2006

Phlaeothripidae

Haplothrips chinensis Japan Yoshimura et al. 2006

Neuroptera

Chrysopidae Ray 2003

Butter bean (Phaseolus lunatus)

Hymenoptera

Sphecidae Free 1993

Vespidae

Polistes sp. Free 1993

Green bean (Phaseolus vulgaris)

Thysanoptera

153


Thripidae

Frankliniella occidentali* USA Mackie, Smith 1935

Bell Pepper (Capsicum annuum)

Diptera

Calliphoridae

Calliphora spp.

Breuils and Pochard 1975

Lucilia spp.

Breuils and Pochard 1975

Syrphidae

Eristalis tenax Canada Jarlan et al. 1997

Eggplant (Solanum melongena)

Diptera

Syrphidae

Syrphus spp. USA Lowenstein et al. 2015

Toxomerus spp. USA Lowenstein et al. 2015

154

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

Family Species n (seq) #

insects caught

Average pollen count

# of reads

% Fragaria pollen

# of plant families

# of plant 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

Chrysomelidae Diabrotica undecimpunctata

1 2 924 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

155


insects caught


# of reads

% Fragaria pollen

# of plant families

# of plant 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

156


insects caught


# of reads

% Fragaria pollen

# of plant families

# of plant 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

157

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

158

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

159

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

160

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.

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The underestimated taxa: the role of non-bee pollinators