The underestimated taxa: the role of non-bee pollinators ...
Transcript of 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.
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ACKNOWLEDGEMENTS
I would like to thank the members of the Raine lab that were present for the duration of my master’s degree, providing support and help when they could, in particular, Dr. Elizabeth Franklin, Leah Blechschmidt and Hayley Tompkins. Additional thank you to members of the Steinke lab for their training and patience, special thanks to Dr. Thomas Braukmann. Finally, thank you to Dr. Dirk Steinke for being available; for your help, support and guidance during the second half of my thesis and giving me the opportunity to attend the 8th iBOL conference in Norway. Thank you to the growers that allowed me access to their properties and allowed me to sample in their fields. I would also like thank the financial support I received to support my research. The Natural Sciences and Engineering Research Council (NSERC: Discovery grant 2015-06783 awarded to N.E.R.), the Food from Thought: Agricultural Systems for a Healthy Planet Initiative, by the Canada First Research Excellent Fund (grant 000054), and W.G. Matthewman Scholarship awarded to me in 2017.
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AUTHOR’S DECLARATION OF WORK COMPLETED
I declare that all work presented in this thesis is my own, with the following exceptions: Dr. Thomas Braukmann assisted with development of protocol for pollen metabarcoding.
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TABLE OF CONTENTS
Abstract ............................................................................................................................ii
Acknowledgements ......................................................................................................... iii
Author’s Declaration of Work Completed ........................................................................iv
Table of Contents ............................................................................................................ v
List of Tables .................................................................................................................. vii
List of Figures ................................................................................................................ viii
List of Appendices ...........................................................................................................ix
1 Chapter 1: General Introduction ............................................................................... 1
1.1 Importance of non-bee pollinators ...................................................................... 3
2 Chapter 2: The underestimated taxa: the role of non-bee pollinators in temperate crops ............................................................................................................................... 7
2.1 Introduction ........................................................................................................ 7
2.2 Methods ............................................................................................................. 9
2.3 Crop Assessments ........................................................................................... 12
2.3.1 Fruits.......................................................................................................... 12
2.3.2 Vegetables ................................................................................................. 24
2.3.3 Nuts ........................................................................................................... 42
2.4 Discussion ........................................................................................................ 46
3 Chapter 3: Assessing non-bee flower visiting community of strawberries .............. 48
3.1 Introduction ...................................................................................................... 48
3.2 Methods ........................................................................................................... 51
3.2.1 Experimental Fields ................................................................................... 51
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3.2.2 Field Sampling ........................................................................................... 52
3.2.3 Pollen Removal and Quantification ............................................................ 53
3.2.4 Molecular Identification .............................................................................. 54
3.2.5 Data Analysis ............................................................................................. 58
3.3 Results ............................................................................................................. 60
3.3.1 Diversity and Pollen Loads ........................................................................ 60
3.3.2 Pollen Metabarcoding and Pollinator Networks ......................................... 72
3.3.3 Environmental Variance on Community Structure ..................................... 77
3.4 Discussion ........................................................................................................ 81
3.5 General Conclusions ........................................................................................ 85
References .................................................................................................................... 87
Appendices ................................................................................................................. 114
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LIST OF TABLES
Table 2.1: List of temperate crops assessed in this review, the degree of pollination dependence and assessment of whether non-bee pollination is likely, based on the literature reviewed. ........................................................................................................ 11
Table 3.1: Primers used for barcoding .......................................................................... 58
Table 3.2: Insect visitors collected from day-neutral strawberries ................................. 63
Table 3.3: Insect visitors observed on day-neutral strawberries .................................... 69
Table 3.4: A generalized linear model representing non-bee pollen count data at the genus level (n=53). ........................................................................................................ 71
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LIST OF FIGURES
Figure 2.1: Pollinator papers assessed during literature review of non-bee pollinators, presenting trends across the years 1930 to present........................................................ 9
Figure 3.1: Total pollen load on non-bee strawberry visitors ......................................... 66
Figure 3.2: Abundance of strawberry flower visiting species ......................................... 67
Figure 3.3: Average pollen carried by species visiting strawberry ................................. 68
Figure 3.4: Plant-flower visitor network at the family level ............................................. 75
Figure 3.5: Plant-syrphid network at the plant family level ............................................ 76
Figure 3.6: Triplot of redundancy analysis with species scaling .................................... 79
Figure 3.7: Boxplot representation of observed abundance .......................................... 80
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LIST OF APPENDICES
Appendix 1: List of species recorded visiting flowers of the focal crops assessed. ..... 114
Appendix 2: Species-level identification of specimens caught in strawberry fields, accompanied by the number of individuals caught and their average pollen load count. .................................................................................................................................... 154
Appendix 3: Plant genera and families of pollen found on insect visitors of strawberry crops ........................................................................................................................... 157
Appendix 4: Triplot of redundancy analysis coloured by site ....................................... 160
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1 Chapter 1: General Introduction
The importance of pollination for ecosystem function and services is well known.
Plant pollination results in the perpetuation of wildflowers and trees which provide food
and shelter to animals. It is estimated that 78% of temperate flowering plant species rely
on insect pollinators for reproduction (Ollerton et al. 2011). These plants are critical for
maintaining ecosystem functions which provide services for humans (e.g., increased
water and air quality, prevention of soil erosion, timber, fruit and nut production; Kearns
et al. 1998, Ashman et al. 2004, Cardinale et al. 2012). In addition to the benefits provided
by pollination in natural landscapes, insect pollinators are critically important to global
food crops, contributing to 65% of the produced crop volume (Klein et al. 2007), valued
at $293-720 billion CAD (Potts et al. 2016, but see Melathopoulos et al. 2015). In order
to augment pollination services in crop fields, growers often use commercial honey bees
(Apis mellifera) (Free 1993, Walters 2005, Klein et al. 2007, Eaton and Nams 2012,
Shaheen et al. 2017). The reliance on honey bees has become problematic, however,
with a mismatch in the increased acreage of pollinator-dependent crops and the number
of hives available (Aizen and Harder 2009, Garibaldi et al. 2011, Schulp et al. 2014). The
effects of the supply-and-demand mismatch is compounded by high rates of colony
losses, resulting in local declines of available commercial hives and higher prices for
renting hives (Ellis 2012, Pindar et al. 2017, vanEngelsdorp et al. 2017). Wild bee
populations are also declining. Surveys from Europe and North America indicate declines
in richness and abundance of wild bee populations (Biesmeijer et al. 2006, Grixti et al.
2009, Williams and Osborne 2009, Cameron et al. 2011, Carvalheiro et al. 2013). The
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leading causes for these declines include land-use intensification, habitat fragmentation,
pesticide application, disease spillover, and climate change (Potts et al. 2010, Vanbergen
et al. 2013, Ollerton et al. 2014, Pindar et al. 2017). The plight of the bees has been
receiving growing consideration from the scientific community, policy makers, and the
public (Kevan and Phillips 2001, Allsopp et al. 2008, Food and Agriculture Organization
of the United Nations 2012, Senapathi et al. 2015). As such, there has been a surge in
research to understand the contribution and importance of wild pollinators (Winfree et al.
2007, Klein et al. 2012, Garibaldi et al. 2013, Földesi et al. 2016, Mckechnie et al. 2017).
Bees are obligate floral-forgers, requiring pollen to provision food for their brood and
nectar to fuel their flight (Müller et al. 2006). Their morphology and biology are specialized
for floral manipulation, meaning they are frequently the most efficient pollinator group
(Kennedy et al. 2013, Scott et al. 2016). Additionally, bees are a relatively well-described
taxon, with most species identifiable to the species level (Banaszak 2000, Michener
2000). Bees’ high pollination efficiency and well-resolved taxonomy has resulted in a
severe bias towards bee taxa when considering wild pollinators in research, with many
studies disregarding the contribution of non-bee pollinators (Klatt et al. 2013, Woodcock
et al. 2013, Toledo and Papineau 2015). In particular, this skewed attention is
exacerbated when considering policy makers and the public; this is well demonstrated in
Dicks et al. (2013). Hoverflies occasionally receive secondary recognition as pollinators
due to their affinity with flowers and their abundantly hairy bodies (Skevington and Dang
2002). While several recent studies have jointly considered hoverflies and bees in their
pollinator assessments (Baldock et al. 2015, Garratt et al. 2016, Joshi et al. 2016,
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Ahrenfeldt et al. 2017), these taxonomic biases limit the acknowledgment of other insect
pollinators, such as wasps, non-syrphid flies, beetles, ants, bugs, butterflies, and thrips
(Kendall and Solomon 1973, Heithaus 1979, Larson and Kevan 2001, Blanche and
Cunningham 2005, Brodmann et al. 2008, Rader et al. 2016, Ollerton et al. 2017).
1.1 Importance of non-bee pollinators
Diversity provides stability and reliability of ecosystem services and functions,
including pollination systems (Garibaldi et al. 2013, Rogers et al. 2014, Rader et al. 2016).
Diverse pollinator assemblages can result in an ensemble of species-specific foraging
preferences (including specialists and generalists), which effectively exploit floral
resources and deliver effective pollination services as a byproduct of foraging activity
(Fontaine et al. 2005, Garibaldi et al. 2013). However, pollinators have to cope with
potentially substantial variation in their environment when making foraging decisions.
They must respond to variation in the cues provided by flowers (e.g. colour, odour and
shape) about the rewards they might provide, the spatial distribution of resources (e.g.
flower patches in the landscape or the location of flowers on an individual plant), and the
variability in environmental conditions (such as, wind, precipitation and temperature).
Such environmental variation can result in partial niche partitioning, with distinct species
or guilds (Blüthgen and Klein 2011). For example, honey bees preferentially forage from
flowers at the tops of almond trees, while wild bees prefer to visit low flowers; thus,
together the actions of these different groups of pollinators are complementary and result
in the entire tree being pollinated (Klein 2011). Indeed, such functional complementarity
has been demonstrated with experimental design in several instances (Fontaine et al.
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2005, Blüthgen and Klein 2011, Garibaldi et al. 2013, 2014, Rogers et al. 2014). An
exception to this condition is highly specialized relationships between a single plant and
a single animal species; however, these instances are rare (Waser et al. 1996, Pornon et
al. 2017). In addition to functional complementarity, diversity provides functional
redundancies, so that pollination success does not become the reliant on a single
species. Despite the importance of diversity, most studies on functional complementarity
and redundancy focus solely on bee diversity (Fontaine et al. 2005, Blüthgen and Klein
2011, Garibaldi et al. 2013, 2014, Rogers et al. 2014). The exclusion of non-bee
pollinators is an oversimplification of reality, as bees represent a mere ~5.5% of the
arthropod floral-visiting community, with over 330,000 species documented from other
taxa that may also contribute significantly to pollination (Wardhaugh 2015, Ollerton 2017).
This substantial, yet largely overlooked, non-bee pollinator diversity is likely responsible
for delivering a substantial amount of functional services by providing unique pollen
transfer, due to their diversity of form, behaviour and physiological tolerances to a wide
range of foraging conditions (Rader et al. 2016).
One of the leading justifications researchers give for the exclusion of non-bee
pollinators is that bees are often the most efficient pollinator (Kennedy et al. 2013, Scott
et al. 2016). Bees have a nectar and pollen-dependent diet; as such, their behaviour and
foraging techniques often result in high pollen release and frequent flower visiting
(Sheffield 2014, Campbell et al. 2017b, Russo et al. 2017). When considering non-bee
pollinators, their average pollination efficiency per flower visit may be low, but their
ubiquity can lead to high visitation frequency, resulting in equal, or greater, pollen
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deposition than bees (Larson and Kevan 2001, Skevington and Dang 2002, Rader et al.
2009, 2016, Orford et al. 2015). This is especially true when considering Diptera, which
are particularly speciose and abundant (Skevington and Dang 2002). The dietary reliance
of bees on pollen also means they are expert groomers, removing pollen from their bodies
and packing it into specialized pollen carrying structures (corbiculae or scopae), thus
effectively removing this pollen from any active role in pollination (Jander 1976, Vaissaire
et al. 2006, Lunau et al. 2015, Koch et al. 2017). While flies are also efficient groomers,
the removed pollen does not become inactive (Barber and Starnes 1949, Lewis and
Hughes 1957, Kendall and Solomon 1973, Sutcliffe and McIver 1974, Holloway 1976,
Shaffer et al. 2007, Orford et al. 2015, Jacques et al. 2017). There is no information on
the preferred location for flies to groom; however, it is likely that on occasions they are
perched on flowers while grooming. As such, the free-groomed pollen could land on
receptive conspecific stigmas and provide pollination services. Currently, very limited
information exists in the literature about the grooming behaviours and pollination
efficiency of other non-bee flower-visitors.
Unlike bees, most non-bee pollinators are not central-place foragers. As central-
place foragers, female bees typically have a nest in a fixed location that they return to
after each foraging excursion. Thus, bee foraging ranges are restricted, with most solitary
species foraging only 150-600m from their nest (Osborne et al. 1999, Gathmann and
Tscharntke 2002, Greenleaf et al. 2007). Honey bees have a vastly larger foraging range
of 3-5km, with a maximum range up to 15km (Beekman and Ratnieks 2000, Couvillon et
al. 2014). As such, wild bees’ sensitivity to land-use practices are intensified by their
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inability to remove themselves from risk (Raine and Gill 2015, Klein et al. 2017). Flies and
beetles are nomadic; they do not have established nest sites. Therefore, they are not
restricted in their foraging ranges (Skevington and Dang 2002, Menz et al. 2019). As
such, these taxa do not require nesting materials which may be contaminated with
pesticides, and are less affected by land-use intensification compared to bees, which are
impacted by loss of habitat and appropriate nesting areas (Jauker et al. 2009).
Additionally, the environmental conditions in which non-bees continue to forage on
flowers is often less restricted than bees. Flies and beetles have been observed
continuing to forage when it is cloudy, even raining, and when it is too cool or hot for bees
(Heinrich and Mcclain 1986, Inouye et al. 2015). As a specific example, when
temperatures rise and there is low humidity, the sugars in nectar begin to crystalize,
making it inaccessible for bees to ingest. Flies however, are able to regurgitate fluids onto
the crystals, re-dissolving them for consumption (Inouye et al. 2015). As such, non-bee
pollinators could be more resilient to climate change and land-use intensification and
should be considered carefully for the pollination services they provide to both crops and
wild plants (Biesmeijer et al. 2006, Meyer et al. 2009, Jauker et al. 2009, Grass et al.
2016, Rader et al. 2016).
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In order to examine the diversity and ubiquity of non-bee pollinators, while simultaneously
highlighting the gaps in available literature regarding their role in crop pollination, this
research project has the following objectives:
(1) To evaluate the literature on non-bee flower-visitors to a selection of temperate
crops (Chapter 2).
(2) To investigate the community of non-bee insects visiting flowers of strawberry
crops in Southern Ontario (Chapter 3).
2 Chapter 2: The underestimated taxa: the role of non-bee pollinators in temperate crops
2.1 Introduction
Given the apparent taxonomic biases of the last three centuries, which focused
heavily on bees as the primary or only pollinators of crops (Figure 2.1), the aim of this
chapter is to outline the important diversity of non-bee species that visit flowers and
highlight knowledge gaps regarding their identity and the pollination services they
provide. Provided that primary interest regarding pollination pertains to its ecosystem
service, the scope of this review is confined to agricultural cropping systems. As there
are hundreds of crops grown globally, my review is restricted to a subset of 23
temperate fruit and vegetable crops (Table 2.1). Information on non-bee flower-visiting
insects was collected by close examination of the available literature. A summary table
of the identity of crop-specific floral-visiting species is presented in Appendix 1, and
corresponding details on their role in crop pollination in the main text. This information
was placed in the context of the floral pollination systems, pollination requirements, and
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the known roles of bees in each of the assessed cropping systems (Table 2.1). This
document is meant to be a tool for agricultural applications, pollinator conservation and
pollinator research. Readers can find their target crop and read a concise summary of
the knowledge we have regarding non-bee pollinators. It highlights knowledge gaps and
areas for future research.
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Figure 2.1: Pollinator papers assessed during literature review of non-bee pollinators, presenting trends across the years 1930 to present.
2.2 Methods
The crops chosen for this review were drawn from a previous review on global crop
pollination (McGregor, 1976) and selected for fruit and vegetable crops which are grown
primarily in temperate climates (Table 2.1). The review included 38 crops which met the
criteria; 22 crops were selected. The selection was made to maximize variation in floral
composition and degree of pollination requirement of crop types. I also added a single nut
crop, almonds, which has a large economic impact, particularly with respect to pollination
services provided; therefore, this crop has substantial research advocating for a diverse
pollinating community. The pollination requirements, present knowledge of their
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1930-1944 1945-1959 1960-1974 1975-1989 1990-2004 2005-2019
Nu
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aper
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All diversity Bees and Syrphids Only Bees
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pollination systems and non-bee visitors are presented in-text, in alphabetical order by
family. A rigorous assessment of the available literature was conducted by using search
term ‘pollination’ combined with each of the selected crops, using the University of
Guelph, Primo search engine. Any relevant references cited within the studies arising
from the Primo search were also examined for additional information or records of non-
bee pollinators. This search process yielded 364 studies that I reviewed in detail. Of these
in paper references, those that could be found on in Primo, or through Google Scholar
with an English translation were included. Research from temperate locations (North
America, North and Central Asia, Europe, United Kingdom, and New Zealand) were used
preferentially. However, when no temperate examples were available, I referred to
tropical research.
For an animal to be classified as a pollinator it must visit a flower, collect pollen on
its body, visit another flower of the same species, and deposit viable pollen onto the
stigma of the second receptive flower (Cox and Knox 1988). However, insects which have
free active pollen on their bodies can be used as a proxy for a likely pollinator status.
Because should an insect visit a flower and have free pollen of that plant on its body, then
it is likely to continue visiting, to some degree, that same floral species. Thus, despite the
inevitable variability in pollination efficiencies, they are likely to participate in some degree
of pollination. Inefficient pollinators can have significant influence on pollination services
when abundance is considered (Rader et al. 2016). Most studies that provide information
regarding non-bee insects simply report their presence on crop flowers and their relative
abundance. This review aims to provide an in-depth synopsis of the information available
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on non-bee insects that may participate in crop pollination of the crops included in this
review.
Table 2.1: List of temperate crops assessed in this review, the degree of pollination dependence and assessment of whether non-bee pollination is likely, based on the literature reviewed.
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).
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2.3.1.2 Rosaceae
2.3.1.2.1 Strawberry (Fragaria spp.)
Pollination system and requirements
Strawberry flowers are classified as self-fertile hermaphroditic plants. However,
self-pollination is estimated to result in only 8% of the commercial value of flowers that
received supplemented pollination (hand or insect pollinated) (Wietzke et al. 2018). Insect
pollination also reduces the number of misshapen fruit (Lopez-Medina et al. 2006).
Non-bee pollination
Syrphid flies are often reported to be the most abundant non-Apis insect found on
strawberry flowers. In Quebec, syrphids represented (25%) of flower visitors, second only
to honey bees (52%), which were stocked in the field and so their dominance is explained
by artificially augmented populations (de Oliveira et al. 1991). Similarly, in Utah, syrphids
were second only to honey bees (Nye and Anderson 1974). In Sweden, syrphids were
(82%) of visitors, their abundance significantly increasing when there was a pond in the
nearby vicinity. This increased abundance of syrphids was correlated with an increase in
pollination, fruit set, and a decrease in malformation of strawberry fruits (Stewart et al.
2017). Syrphid species Eristalis tenax and E. brousii were classified as two of the four
most important pollinators to strawberry fields in Utah. This classification was devised
with a combination of pollination efficiency and abundance (Nye and Anderson 1974).
Additionally, some syrphid species are mass reared for greenhouse pollination services,
such as Eristalis cerealis in Japan (Delaplane and Mayer 2000). The flower-visiting
community for strawberries can be quite diverse. Sixty-six (61%) of 108 flower visitor
species reported from Utah were non-bees (Nye and Anderson 1974), and 28 (62%) of
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45 flower visitors species from Quebec were also non-bee species (de Oliveira et al.
1991) Additionally, ant (Formicidae) visitation results in 90% of the fruit set of flowers
visited by flies and bees, thus classifying them as effective strawberry pollinators. The
following three ant species are pollinators: Prenolepis imparis, Formica subsericea, and
Tapinoma sessile. However, ants often damage pistils and reduce the visitation rate of
flying pollinators, limiting further pollination (Ashman and King 2005). The pest control
lacewing species Chrysoperla carnea was tested for its ability to pollinate strawberry
flowers, as both larvae and adults will visit flowers for pollen and nectar. However, due to
flight activity, form, and few pollen-collecting hairs, C. carnea is not an efficient pollinator.
Percent of flowers pollinated by C. carnea was 48%, compared to 42% in insect excluded
plots (Zapata et al. 2008).
Hooper (1932) estimated that when temperatures are cool, the majority of
pollinators will not be bees, but rather, likely flies. Calliphorids are occasionally used to
stock greenhouses for strawberry pollination (Free 1993). Calliphora vomitorid was found
to have equivalent pollination efficiency to honey bees while being more cost efficient and
lower maintenance (Carden and Emmett 1973, Clements 1982).
Bee pollination
Honey bees often provide suitable pollination to strawberries 84-100% fruit set
(Svensson 1991, Chagnon et al. 1993, Kakutani et al. 1993, Zapata et al. 2008). However
bumblebees represent a better option when considering greenhouse pollination, or early
bloom strawberries when temperatures are often below 12˚C, when honey bees will not
forage (Paydas et al. 1998, Dimou et al. 2008). A stingless bee, Trigona minangkabau,
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was found to be an efficient greenhouse strawberry pollinator; however, stocking
densities would need to be almost double that of honey bees (Kakutani et al. 1993).
2.3.1.2.2 Apple (Malus domestica)
Pollination system and requirements
Apples require pollination to set fruit, and most cultivars are self-incompatible
(Ramírez and Davenport 2013). Apple pollen does not adhere readily to the stigma;
therefore, wind pollination is not considered an important avenue for pollination. Thus,
insect pollination is crucial for fruit set in these crops (Garratt et al. 2014).
Non-bee pollination
Syrphid flies are reported to be potential apple pollinators, representing 7.4% of
visitation abundance to apple flowers in a UK cider orchard (Campbell et al. 2017a). In
Hungary, Földesi et al. (2016) found that thirteen species of syrphids comprised 33% of
non-Apis observations on apple blossoms. Exclusion experiments indicate that flower
visits from only the syrphid Eristalis tenax resulted in yield equivalent to that of open
pollination by all wild pollinators (Solomon and Kendall 1970). Flies in a UK orchard were
found to have comparatively few pollen grains (2-806 grains/individual), of which a low
percentage were apple pollen (13-61%), compared to bees (388-38610 grains/individual,
75-94% apple pollen). Of the flies, syrphids carried the highest amount of pollen on
average, 61% of which was from apple (Boyle and Philogène 1983). Specifically, syrphid
species, Eristalis pertinex, E. tenax, E. argustorum, and the conopid species Myopa
buccata were found to fertilize 29%, 18%, 51%, and 32% of ovules in a single visit,
respectively. In comparison, the average fertilization for bees was 26% (Kendall 1973).
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Syrphid visitation frequencies can be low in UK orchards (Garratt et al. 2016).
When testing the efficiency of a subset of the flower visitor community, the syrphid
Eristalis balteatus had significantly lower pollination efficiency than bee species. Overall,
syrphids only contribute about 3% to UK apple pollination (Garratt et al. 2016). Syrphid
abundance has also been reported to be very low in Pennsylvania orchards (Joshi et al.
2016). Eristalis syrphids have been considered for commercial pollination; however, their
abundance in the crop reduces remarkably in just 24 hours after their introduction
(Kendall and Solomon 1973).
Other prominent fly visitors to apple flowers include species from the family
Anthomyiidae, representing the most abundant non-Apis visitor, carrying an average of
32 pollen grains, of which 68% are apple pollen (Boyle and Philogène 1983, Boyle-
Makowski and Philogene 1985). In Columbia, fly visitors (Calliphoridae, Tachinidae,
Syrphidae, Muscidae) were the most abundant visitors (8.7%), second only to honey bees
(76%). The remaining proportions of flower visitors were: 4.5% native bees, 3.7% Diptera
(Bibionidae, Sciaridae, Tipulidae), 3.1% Coeloptera, 2.2% Lepidoptera (Botero and
Gilberto 2000). In Nova Scotia, Mycetophilidae flies were found to be the most abundant
flower visitor by far, whilst carrying substantial pollen loads. Beetles were the most
frequent visitors, but did not provide significant pollination services (Brittain 1932). Vicens,
Bosch and Vicens (2000) found, on average, flies were the most abundant visitor, second
to honey bees (~30% and ~50% respectively). Of the fly diversity, 77% belonged to
muscoids (Calliphoridae, Tachinidae, Muscidae, Anthomyiidae). Other than a single
mason bee species (Osmia cornuta), muscoids were the only insects found visiting
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 system and requirements
Pollination requirements of blackberries vary substantially across species. While
wild diploid plants are self-incompatible (require insect pollination), most cultivated
species are self-compatible (Haskell 1960, Nybom 1987, Cane 2005). Although cultivated
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)
Pollination system and requirements
Watermelons are self-compatible, but require insect pollination, as the grains are
too large to be carried by wind (Delaplane and Mayer 2000). On average, 95% of
pollination is due to insects (Klein et al. 2007). Seedless watermelons (triploid) plants
have male flowers that produce mostly nonviable pollen and thus require diploid plants
and insect pollination to provide pollen (Walters 2005). The use of growth regulators are
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)
Pollination system and requirements
Melons require pollination to set fruit; however, growth regulators can also be used
to induce fruit set (Mann and Robinson 1950, McGregor and Todd 1952, Mann 1953,
Shin et al. 2007). Some studies have concluded that insect pollination is more economical
than artificial pollination (Sakamori et al. 1977). While fruit pollinated by growth regulator
developed faster, there was a higher percentage of fermented fruit as the hardness and
soluble solids (sugars) of fruits was lower than bee pollinated fruits. Fruit set was also
higher in crops visited by bees than for those using growth regulators. Sugar content was
roughly the same from both pollination methods when the fruit was fully ripe (Shin et al.
2007). Although hand pollination typically results in less fruit set than open insect
pollinated plants, hand pollination is occasionally used instead of insect pollination (Mann
and Robinson 1950, McGregor and Todd 1952, Mann 1953).
Bee pollination
There are no records of non-bee pollinators in this crop. Generally, honey bees
and bumblebees are the most prominent visitors to melon flowers (Handel 1983, Shin et
al. 2007). Honey bees have been found to increase fruit yield in tropical and temperate
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 system and requirements
Pollination is solely required for seed production of onion crops. Flowers are self-
infertile and the majority of pollination is insect-mediated (Delaplane and Mayer 2000).
When flowers are open to all visiting pollinators, the average seed set per umbel is 50%,
which is significantly higher than either hand pollination (14.2%) or wind pollination alone
(pollination exclusion: 0.8%; Walker et al. 2011).
Non-bee pollination
Bees and flies are often considered the most abundant and important pollinators
for onion. In Utah, flies were the most abundant and efficient pollinator, with syrphids
Eristalis tenax and E. brousii contributing nearly half of the pollination services (Bohart
and Nye 1970). Individual E. tenax flies carried equivalent amounts of pollen to individual
honey bees, and thus are considered effective onion pollinators (Kumar et al. 1985a).
Numerous fly families, including Syrphidae, Calliphoridae, Anthomyiidae, Stratiomyidae,
Sarcophagidae, Bibionidae, Tachinidae and Muscidae, were abundant flower visitors in
New Zealand (Howlett et al. 2009). Several syrphid species have been recorded visiting
onion flowers in Poland (Wojtowski et al. 1980). In Pakistan, 87% of insect visits to flowers
were by flies, 72% of which were syrphid species (Table 2; Sajjad et al. 2008). Blowflies
(Calliphoridae: Calliphora and Lucilia) have been shown to be effective pollinators of
onion in greenhouses (Currah and Ockendon 1983, Schittenhelm et al. 1997). In addition,
some wasps have made appreciable contributions to pollination. For example, the sand
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)
Pollination system and requirements
The commercial value of beets is the sale of the taproot, as such the plant does
not require pollination to produce the marketable parts of the plant. Pollination is only
required when producing seed for future crop plantings. Beets are self-infertile; thus, they
require cross-pollination, via wind or insects (Stewart 1946, Archimowitsch 1949). The
dispersal range of beet pollen by wind has been determined to be approximately 1200
metres (Darmency et al. 2009). While not necessary for pollination, insects can increase
seed yield, particularly in tetraploid hybrid plants, which produce fewer and larger pollen
grains (Mikitenko 1959, Free et al. 1975).
Non-bee pollination
Shaw (1914) suggested that flower visits by thrips are potentially valuable for
pollination of beets, despite their pest status. Thrips, when present, are usually highly
abundant, typically occurring at 80-190 individuals on a single flower spike. Each
individual thrips found on a blooming beet plant had pollen grains on its body, with an
average load of 140 grains/adult. In addition, thrips maintain pollen on their bodies while
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
Pollination system and requirements
Cole (Brassica) requires insect-mediated pollination for seed production, but not
to produce the marketable portion of the plant, the immature florets or leaf bunches
(Nieuwhof 1963). Cole crops are mostly self-incompatible, although this may vary slightly
with the variety or age of the plant (Nieuwhof 1963).
Generally, Hymenoptera (Apis spp. and Bombus spp.) and Diptera (Calliphoridae
and Syrphidae) are the most important pollinators of seed cole crops (Pearson, 1932;
Stanley et al., 2017).
2.3.2.3.2 Cauliflower
Pollination system and requirements
Cauliflower is attractive to insect visitors, with high nectar volume and sugar
content (Selvakumar et al. 2006). Of the cole crops, it has the highest degree of self-
compatibility (Nieuwhof 1963, Watts 1963). However, common hybrid varieties are self-
incompatible (Selvakumar et al. 2006).
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)
Pollination system and requirements
Most varieties require insect pollination, increasing yield by up to three times
(Gingras et al. 1999). Barber and Starnes (1949) reports that 75% of yield is due to insect
pollination alone. Varieties of seedless cucumbers grown in greenhouses do not require
pollination as they are parthenocarpic (Free 1993).
Non-bee pollination
Barber and Starnes (1949) reported few visits from hoverflies (Diptera: Syrphidae),
butterflies (Lepidoptera: Pieridae) and skippers (Lepidoptera: Hesperiidae) to cucumber
flowers, but they do not report their relative abundance or comment on their efficiency as
pollinators. Similarly, Motzke et al. (2015) reported fewer than 4% of flower visits from
three butterfly species, three wasp species and eight fly species (Syrphidae, Tachinidae,
Miridae, Fannidae) in Indonesian cucumber crops.
Bee pollination
Bees often are reported to be the most abundant visitors to cucumber flowers
making up 78% (Barber and Starnes 1949) to 96% (Motzke et al. 2015) of visits.
2.3.2.3.6 Pumpkin, Squash, Zucchini (Cucurbita pepo)
Pollination system and requirements
Flowers of Cucurbita pepo are distinctly male or female. Insects are required for
pollination, as the pollen grains are too heavy and sticky to be carried by wind.
Bee pollination
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)
Pollination system and requirements
In greenhouses it is popular to use phytohormones or biostimulants to induce
parthenocarpy, rather than rely on insects for pollination. However, there has been
research into the effectiveness of pollination by insects, particularly bumblebees, for
greenhouse zucchini pollination rather than chemical inputs (Roldán-Serrano and Guerra-
Sanz 2005).
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)
Pollination system and requirements
Self-pollination is prominent in this species; however, a range of 0.6% to 6.2%
outcrossing occurs in fields (Ray et al. 2003). Outcrossing by wind is minimal, with only
0.18 grains/cm2 of airborne pollen collected between rows (Yoshimura et al. 2006). Soy
flowers are entomophilous, and as such, insects are suspected to be the vector of this
observed outcrossing (Erickson and Garment 1979). Insect pollination is shown to
increase soybean yield by 15%-18% in greenhouses and a 21% increase in field systems
and 3-5% heavier seeds (Erickson et al. 1978, Blettler et al. 2018). Some studies report
drastically higher yields with insect-mediated pollination, with up to 65% increase in pod
number (Chiari et al. 2005).
Non-bee pollination
Thrips have repeatedly been considered for their role in soybean pollination (Free
1993, Yoshimura et al. 2006, de O Milfont et al. 2013, Santos et al. 2013). In Japan, thrips
species, Frankliniella intonsa, was consistently the most abundant insect visitor to
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)
Pollination system and requirements
Insect-mediated pollination is required for sterile inbred plants, but not for hybrids.
About a third of faba bean crops are hybrids, which can self-fertilise and produce pods,
the remaining two-thirds require insect mediated pollination (Kendall and Smith 1975).
The degree of self-pollination in faba beans varies greatly, from 1-79%, depending on
environmental conditions and variety (McVetty and Nugent-Rigby 1984). However, insect
pollination is still beneficial in self-fertile varieties and provides resilience to heat stress,
preventing the usual 15% yield reduction noted at 30 °C (Suso et al. 1996, Bishop et al.
2016).
Bee pollination
Flower visitation by honey bees has been found to increase yield by 17% in a field
setting (Cunningham and Le Feuvre 2013). All bumblebee species and honey bees are
equally efficient pollinators when entering the flower from the front. However, short-
tongue bumblebees tend to bite holes in the sides of flowers for access to nectar from the
side, termed (primary) nectar robbing. These holes are subsequently used by honey bees
engaging in secondary nectar robbery. Although, robbers were not as effective at
pollination, fruit set was higher than seen in unvisited flowers (Kendall and Smith 1975).
No literature was found regarding the potential role of non-bee pollinators.
36
2.3.2.5.2 Runner beans (Phaseolus coccineus)
Pollination system and requirements
While the majority of research indicates runner beans require insect pollination
(Darwin 1876, Mackie and Smith 1935, Free 1966, Łabuda 2010), contradictory evidence
also exists (Tedoradze 1959).
Non-bee insects that potentially contribute to pollination of runner beans are pollen
beetles (Meligethes spp.) and thrips (Blackwall 1971). Free (1993) found blowflies
(Diptera: Calliphoridae) were ineffective pollinators compared to honey and bumblebees,
resulting in pollination rates similar to plants from which insects had been excluded. Their
inefficiency is likely a result of the inaccessibility of the floral nectaries due to the length
of their proboscis (Free 1993). While information regarding temperate non-bee insect
visitors is limited, (see Free 1993), there is some recent work describing insect visitors in
tropical regions, including Lepidoptera (Pieridae Eurema spp., Lycaenidae), Coleoptera
(Meloidae, Lagriidae Lagria villosa), Hymenoptera (Vespidae: Belonogaster juncea,
Polistes spp.) from Cameroon (Fohouo et al. 2014). In Costa Rica, several non-bee
hymenopterans were recorded visiting runner beans, including: wasps (Vespidae
Synagris cornuta, Sphecidae Philanthus triangulum), and ants (Formicidae Camponotus
flavomarginatus; Pando et al. 2011).
Bee pollination
The evidence for bee pollination is similar to that for faba beans. Bumblebees and
honey bees have similar pollination efficiency when flowers are visited from the front,
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)
Pollination system and requirements
Cross pollination is not sought after in green beans. Cultivar purity is critical, so
that selected traits remain undiluted. Additionally, insect pollination is not required, and
does not increase yield, as the flowers are self-pollinated (Free 1993).
Non-bee pollination
Typically about 1% cross pollination is found in green bean fields, the vector is
suspected to be the western grass thrips (Frankliniella occidentalis; Mackie and Smith,
1935). This species is found in significant numbers with considerable amounts of pollen
on each individual. This thrips is not to be confused with the common bean thrips
(Hercothrips fasciatus) that causes leaf feeding damage (Mackie and Smith 1935).
Frankliniella occidentalis is the only plausible vector route for cross-pollination in field
beans, as foraging honey bees and bumblebees could not result in cross pollination due
to the timing of floral maturation.
Bee pollination
Carpenter bees are common pollinators of green beans in tropical areas. For
example, Xylocopa olivacea was found to be an efficient pollinator in Cameroon and X.
calens in Costa Rica (Pando et al. 2011, Fohouo et al. 2014).
38
2.3.2.6 Liliaceae
2.3.2.6.1 Asparagus (Asparagus officinalis)
Pollination system and requirements
Asparagus requires insect pollination to set seed, producing an average of 776g
of seed per female plant, compared to the 6g produced when no insect-mediated
pollination is provided (Eckert 1956).
Bee pollination
Wild bee visitation rates are fairly low, with a single bee visit reported every few
hours. Insect flower visitors include Bombus pratorum, B. pascuorum, and B. terrestris.
On average, each of these bumblebees had 83 grains of asparagus pollen on their ventral
side, representing about 35% of their total pollen load. Megachile leachella bees
averaged 195 asparagus pollen grains, representing 58% of total pollen load (de Jong et
al. 2005). Honey bees are often used to supplement insect pollination to acquire fertile
seeds for asparagus propagation (Walker et al. 1999). Research on asparagus pollination
is slim and requires further investigation to determine if any non-bee insects visit and
pollinate these flowers (Free 1993).
2.3.2.7 Solanaceae
2.3.2.7.1 Bell Pepper (Capsicum annuum)
Pollination system and requirements
Bell pepper plants are self-fertile; however, fruit set is significantly enhanced when
supplemental insect pollination is provided (McGregor 1976).
Non-bee pollination
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)
Pollination system and requirements
Like most Soleanaceious plants, eggplant (Aubergine) flowers require sonication
or buzz-pollination (McGregor 1976). There is some divergent evidence regarding the
degree to which eggplants are pollinator dependent. While results in Jamaica found no
evidence that eggplants require insect pollination (Free 1993), another study estimated
60% of eggplant pollination comes from insect pollination, the remaining 40% being a
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)
Pollination system and requirements
Tomato is self-fertile and self-pollinating, so does not require insects to produce
fruit (Free 1993). However, despite an efficient self-pollinating mechanism, tomatoes
grown in greenhouses often do not produce marketable fruit without hand or insect-
mediated pollination (McGregor 1976). Greenhouse tomatoes set only ~60% fruit without
supplemental pollination (Banda and Paxton 1991). Moreover, F1 hybrids, which require
cross-pollination, are sought after and also require hand or insect-mediated pollination.
Non-bee pollination
There are limited records of tomato flower visits by Diptera: Brewer & Denna
(2009) report ‘a few flies’ on the flowers, but state they are not likely contributing to
pollination.
Bee pollination
Tomatoes yield the best fruit when sonicating insects visit the flowers. Fruit set
was 75% when visited by honey bees, 90% with mechanical vibration (by hand) and 98%
by bumblebee pollination in a greenhouse setting (Banda and Paxton 1991). Thus,
commercial bumblebees are now typically used in greenhouses for pollination in most
parts of the world. The most common commercial bumblebee species in North America
is Bombus impatiens. However, use of native bumblebees is being assessed for
greenhouse pollination in order to reduce the importation of non-native bees and
decrease introduction of pathogens (Strange 2015). For example, Bombus vosnesenskii
and B. huntii are equally effective pollinators of tomatoes compared to B. impatiens, while
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)
Pollination system and requirements
Almond trees are self-incompatible, requiring insect-mediated cross-pollination
(Tufts and Philp 1922, Connell 2000). Movement of pollen between different varieties in
adjacent or nearby rows in almond orchards is important for fruit set. Pollinators of this
crop must be resistant to poor weather conditions as the bloom period in February is often
accompanied by inclement weather (Connell 2000, Dag et al. 2006). Pollen viability
degrades quickly within the flower; as such, pollen that is distributed in the morning, closer
to the time of dehiscence, will contribute more to pollination (Dag et al. 2006).
Non-bee pollination
The insect diversity caught in pan traps in Australian almond orchards
demonstrates that the overwhelmingly dominant order is Diptera (93% of trapped
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
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
Order Family Species Insect
Abundance Total
Pollen Average Pollen
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
Order Family Species Insect
Abundance Total
Pollen Average Pollen
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
Pollen Average Pollen
Hymenoptera 5.42 129 4.81 602,501 4671
Apidae Bombus 0.92 22 2.20 275,858 12539
Apidae Ceratina 4.87 116 7.27 910,600 7850
Apidae Melissodes 0.42 10 0.34 42,500 4250
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
Pollen Average Pollen
Coccinellidae 0.29 7 0.13 15,939 2277
Mordellidae 0.50 12 0.24 30,324 2527
Scarabaeidae Popillia japonica 3.91 93 2.93 366,978 3946
Scarabaeidae 0.08 2 0.03 3,900 1950
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
74
(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.
75
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.
76
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.
77
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.
78
Coleoptera and Lepidoptera consistently have low levels of occurance on strawberry
flowers.
79
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.
80
Figure 3.7: Boxplot representation of observed abundance for 8 taxa across 25 dates
81
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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Crop Order Family Genus Species Location Reference
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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Crop Order Family Genus Species Location Reference
Bombylius pygmaeus Canada
de Oliveira et al. 1991
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
Crop Order Family Genus Species Location Reference
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
de Oliveira et al. 1991
Eristalis arbustorum Canada
de Oliveira et al. 1991
Eristalis barda Canada
de Oliveira et al. 1991
Eristalis bastardii Canada
de Oliveira et al. 1991
Eristalis obscura Canada
de Oliveira et al. 1991
Eristalis stipator Canada
de Oliveira et al. 1991
Eristalis transversa Canada
de Oliveira et al. 1991
118
Crop Order Family Genus Species Location Reference
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
de Oliveira et al. 1991
Helophilus latifrons Canada, USA
de Oliveira et al. 1991; Nye, Anderson 1974
Helophilus lunuatus USA
Nye, Anderson 1974
Helophilus stipatus USA
Nye, Anderson 1974
Helophilus sp. USA
Nye, Anderson 1974
Lejops hamatus Canada
de Oliveira et al. 1991
119
Crop Order Family Genus Species Location Reference
Merodon equestris USA
Nye, Anderson 1974
Metasyrphus sp. Canada
de Oliveira et al. 1991
Orthonevra pulchella Canada
de Oliveira et al. 1991
Platycheirus clypeatus Canada
de Oliveira et al. 1991
Sericomyia militaris Canada
de Oliveira et al. 1991
Sphaerophoria sp. Canada, USA
de Oliveira et al. 1991; Nye, Anderson 1974
Syritta pipiens Canada, USA
de Oliveira et al. 1991; Nye, Anderson 1974
Syrphus ribesii Canada
de Oliveira et al. 1991
Temnostoma alternans Canada
de Oliveira et al. 1991
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
Cabbage (Brassica sp.)
Diptera
Syrphidae USA Pearson 1932
Calliphoridae USA Pearson 1932
Muscidae USA Pearson 1932
Cucumber (Cucumis sativus)
Diptera
Syrphidae
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Crop Order Family Genus Species Location Reference
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
Family Species n (seq) #
insects caught
Average pollen count
# 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
Family Species n (seq) #
insects caught
Average pollen count
# 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.