Varroa Mite Control in Honey Bee Colonies: the Use of a Fatty Acid Blend (C8910) for Varroa Mite Control and Exploring Management Practices Used by Beekeepers

Varroa mite control in honey bee colonies: The use of a fatty acid blend (C8910) for Varroa mite control and exploring management practices used by beekeepers

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

Natalia Solis Riusech

Graduate Program in Environmental Science

The Ohio State University

2017

Master's Examination Committee:

Dr. Reed Johnson, Advisor

Dr. Alia Dietsch

Dr. Thomas Janini

! ! ! ! ! ! ! ! ! ! !

Copyrighted by

Natalia Solis Riusech

2017

ABSTRACT

Varroa destructor mites are the greatest challenge facing modern beekeepers.

There are a variety of treatment and monitoring methods available, however, they are variable in efficacy, ease of application, and seasonality of application. In particular, many chemical options can only be used when honey intended for human consumption is not present. There is need for new treatments that can be used by beekeepers in late summer when harvestable honey is present. Known insecticidal properties of a C8910 fatty acid blend suggested that it may be a viable pesticide for controlling Varroa mites that can be used during the summer. Acute contact bioassays showed that the C8910 blend had a sufficient margin of safety to bees, however, the C8910 blend was not effective at controlling mites in full-sized colonies. Acute contact bioassays of shorter fatty acid chains showed that they are more toxic to mites and safer for bees and therefore may be more effective at controlling mites in full-sized colonies. Even though chemical options are essential for preventing colony loss, many beekeepers still choose not to treat with chemical products. It is essential to determine what drives beekeeping decisions in order to create new products that will be utilized by beekeepers. Survey results showed that there are distinctive differences between hobbyist and sideline beekeepers with regards to management methods used and factors used to make management decisions.

Hobbyists beekeepers in Ohio used more treatment and monitoring methods that are time-intensive, such as powdered sugar shakes and drone brood removal, than semi-

ii professional sideline beekeepers suggesting that factors pertaining to ease of application may be driving beekeeping decisions by beekeepers managing a larger number of colonies. Hobbyist beekeepers also used more methods that show little effectiveness

(screened bottom boards and drone brood removal), suggesting that treatment decisions may be influenced by years of beekeeping experience. “Is organic” was the least important factor to both beekeeper groups. Additionally, “effective at killing mites” was the most important factor to both groups. Contrary to popular belief this suggests that beekeepers value effectiveness over product origin and therefore new products do not need to be organic to be utilized by beekeepers.

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ACKNOWLEDGEMENTS

I would like to first extend my gratitude to my advisor, Reed Johnson, for his continued support in my studies and research, encouraging my interests in social science, and pushing me to become a better scientist. I would also like thank my committee member, Alia Dietsch for her advice on survey-based research, thoughtful edits, and patience as I learned new skills. Also, many thanks to my committee member, Thomas

Janini, for teaching me how to perform bioassays, his guidance in chemistry, and thoughtful advice. I would also like to thank Darlene Florence from Emery for providing materials for experiments and sharing her expertise. Thanks also to Andrei Khilkevich for his help with statistical analyses. Thanks to Bob Filburn, Andy Mondello, Luke Hearon,

Andrea Wade and Bridget Gross for their help collecting data. I would also like to thank my friends, Jon and Hannah, for their invaluable support and feedback. Lastly, I’d like to thank my family- Travis, Frank, Lucy and Isabel- for their unwavering support and encouragement in all my academic endeavors.

VITA

May 2010 ...... Westwood High School, Austin, Texas

2014...... B.A. Biology, The College of Wooster

2015 to present ...... M.S. Environmental Science, The Ohio

State University

Fields of Study

Major Field: Environmental Science

Minor Field: Entomology

TABLE OF CONTENTS

! ABSTRACT...... ii

ACKNOWLEDGEMENTS...... iv

VITA...... v

TABLE OF CONTENTS...... vi

LIST OF TABLES...... viii

LIST OF FIGURES...... ix

CHAPTER 1: Literature Review...... 1

1.1 Insect pollination as an Ecosystem Service...... 1

1.2 Honey bee colony loss...... 3

1.3 Varroa mites...... 7

1.4 Varroa management...... 9

CHAPTER 2: The use of a C8910 fatty acid blend for Varroa Control...... 14

2.1 INTRODUCTION...... 14

2.2 MATERIALS AND METHODS...... 16

2.3 RESULTS...... 20

2.3.1 Fatty acid toxicity...... 20

2.3.2 Polyol removal...... 22

2.3.3 C8910 in full-sized colonies...... 22

2.4 DISCUSSION...... 30

CHAPTER 3: Understanding management practices used by beekeeper for Varroa mite control...... 33

3.1 INTRODUCTION...... 33

3.2 MATERIALS AND METHODS...... 37

3.3 RESULTS...... 39

3.3.1 Beekeeper demographics...... 39

3.3.2 Monitoring methods...... 40

3.3.3 Treatment methods...... 44

3.4 DISCUSSION...... 48

LITERATURE CITED...... 53

APPENDIX : SURVEY INSTRUMENT...... 59!

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LIST OF TABLES

Table 1.1. Registered Varroa mite treatments……………………………….……..…....13

Table 2.1. Winter survival of colonies…………………………………………………...21

Table 2.2. Fatty acid margins of safety……………………………………………..……23

Table 2.3. LC50 values for Apis mellifera………………………………………………..24

Table 2.4. LC50 values for Varroa mites………………………………………………....25

Table 3.1. Beekeeper demographics……………………………………………………..39

Table 3.2. Monitoring factors……………………………………………………………44

Table 3.3. Treatment factors……………………………………………………………..47

viii

LIST OF FIGURES

Figure 2.1. Nonanoic acid………………………………………………………………..14

Figure 2.2. Honey bee bioassay……………………………………………………….....17

Figure 2.3. Polyol patty removal………………………………………………………....26

Figure 2.4. C8910 patty removal………………………………………………………...27

Figure 2.5. Mites on adult bees…………………………………………………………..28

Figure 2.6. Mites under 100 cappings...………………………………………………....29

Figure 2.7. Mean dead bees……………………………………………………………...30

Figure 3.1. Monitoring methods used in Summer 2016………………………………....41

Figure 3.2. Monitoring methods used the entire year…………………………………....42

Figure 3.3. Importance of monitoring factors…………………………………………....43

Figure 3.4. Treatments used the entire year……………………………………………...45

Figure 3.5. Importance of treatment factors……………………………………………...46

CHAPTER 1

Literature review

1.1 Insect pollination as an Ecosystem Service

Ecosystem services are defined as the benefits people receive from ecosystems. The ecosystem service with the most global economic value is crop production, worth 2000 trillion US dollars (estimated in 2005) (Millennium Ecosystem Assessment, 2005; Gallai et al., 2009). Crop productivity of many of the foods we consume depends on animal pollination: the process by which animal pollinators (mainly insects) exchange genetic material between plants that allows the plants to successfully reproduce (Klein et al.,

2007). In particular, insect pollination contributes approximately 9.5% to total global food production (Gallai et al., 2009; Delaplane and Mayer, 2000). Additionally, 60% of all leading crops, including crops used for animal feed, depend on pollinators to some extent (Klein et al., 2007).

The most economically valuable pollinator is the European honey bee (Apis mellifera), providing most of the managed pollination services required in large-scale agricultural production. Honey bee pollination is attributed to increased yield of many crops (Delaplane and Mayer, 2000). According to Klein et al. (2007) of the 115 major leading crops, pollinators (mostly honey bees) are essential for the production of 13 crops, highly important for the production of 30 crops, moderately important for 27, slightly important for 21, unimportant for 7 crops, and unknown dependence for 9 crops.

According to Southwick and Southwick (1992), without honey bees, crop yield for almonds, apples, alfalfa seed, cabbage seed, sunflowers, and cantaloupes would decrease by 70-90%. Likewise, plums, prunes, cucumbers, crimson clovers, cherries, carrot seeds, and cantaloupes would decrease by 50-60%. Although the complete loss of honey bees is unlikely, some pollinator loss could affect crop yield of many fruits and nuts. Even some crops that are primarily pollinated by native bees still depend on honey bees to some extent (strawberry, watermelon, sweet clover, white clover) (Southwick and Southwick,

1992)

Although the increased production from insect-pollinated crops may seem relatively small (9.5% of total global production), there are nutritional benefits that are not included in economic values. Human diets consist of macronutrients (carbohydrates, lipids and amino acids) and micronutrients (vitamins and minerals). Macronutrients are necessary for providing energy to the body and mainly come from wind-pollinated foods such as wheat, corn, rice, and cassava (Dellapenna, 1999). Micronutrients have many health benefits and are provided by a diversity of fruits, nuts, and vegetables (Eilers et al., 2011;

Dellapenna, 1999). More specifically insect pollinated foods provide 98% of available vitamin C, 55% of folate, 70% of vitamin A, 98% of carotenoid cryptoxanthin, 58% of calcium and 62% of fluoride (Eilers et al., 2011). Without these micronutrients from insect-pollinated foods people could experience severe health effects, especially in the majority world – a term used to describe countries that represent the majority of humankind, which excludes the United States and Western Europe. For example, Vitamin

A deficiency is a major health concern in the majority world characterized by blindness in children under 5 years old and increased mortality in children with preexisting diseases

(Imdad et al., 2010). Furthermore, calcium and fluoride are important for the development of healthy bones and teeth and can reduce bone loss associated with aging

(Heaney, 2000).

Without the ecosystem service provided by insect pollinators, particularly honey bees, we could expect to see diminished human health and well-being, reduction in global economic activity and employment, and a decrease in yield in certain crops (Eilers et al.,

2011; Gallai et al., 2009; Delaplane and Mayer, 2000). Additionally, the value of insect pollination as an ecosystem service is rapidly increasing. Aizen et al. (2008), found that from 1961-2006 the contribution of pollinator-dependent crops to total agricultural production almost doubled worldwide, whereas the contribution of nondependent crops decreased. In addition, the agricultural land cultivated for pollinator-dependent crops has increased by 70% in the developing world and 20% in the developed world (Aizen et al.,

2008). This increased dependency on pollinators will require increased pollination services. Recent declines in managed honey bee colonies have increased concern that current pollination services will not be able to meet increasing pollination demands. In order to support a rising global population it is imperative to sustain the ecosystem services that support us.

1.2 Honey bee colony loss

Pollinator loss is a growing concern affecting many wild and managed bee species.

Wild bees are important for the pollination of many specialty crops including tomatoes, watermelons, strawberries, and eggplants (Delaplane and Mayer, 2000). Unlike honey bees most wild bee species are solitary which makes them more difficult to manage.

Many farmers with crops highly dependent on native species still need to rent or buy

3 honey bee pollination services to meet pollination demands (Kremin et al., 2002). The contribution of honey bees to crop production can be explained by several charectaristics.

Honey bees live in large colonies that contain thousands of potential pollinators. The colonies are also easily managed and can be transported long distances. Honey bees are also generalist pollinators and can pollinate a variety of crops (Delaplane and Mayer,

2000). For these reasons, there has been increased focus on efforts to understand recent trends in honey bee colony loss (Lee et al., 2015; Seitz et al., 2015; Steinhaur et al.,

2016).

The number of managed honey bee colonies in the United States has been declining since the late 1940’s. In 1947, the number of honey-producing colonies was the highest with 5.1 million colonies in the United States (vanEnglesdorp and Meixner, 2010). The number of colonies in the United States was the lowest in 2006 with 2.39 million colonies. Since 2006 the number of colonies has recovered a little. In 2014, the number of colonies was approximately 2.7 million, a 12% increase since 2006 (Seitz et al., 2016). In most regions of the United States winter colony losses usually exceed summer losses.

This is probably because honey bee colonies are smaller in the winter and are more susceptible to cold temperatures and starvation (Seitz et al., 2016). However, recently beekeepers reported more colony loss in the summer months. From 2014-2015 average colony loss in summer was 26.2%, compared to 20.2% in winter (Seitz et al., 2016).

Overall honey bee populations have not yet suffered from increased annual summer losses. This is mostly because beekeepers can artificially build up population levels by splitting colonies or buying more bees. However, this method is expensive and labor intensive (Graham, 1992). Additionally, this management pattern is unsustainable and

4 eventually beekeepers may not be able to keep up with recent increases in pollination demands (Aizen et al, 2008).

There are several factors that contribute to honey bee colony loss in the United States.

These factors sometimes occur simultaneously and no single factor is responsible for honey bee colony loss. There are arguably four main reasons for colony loss. These reasons are:

1. Lack of nutrition. Agricultural practices and urbanization can

influence bees on an individual and colony level. A diverse floral diet is

important for colony longevity, development, and tolerance to diseases

(Di Pascuale et al., 2015). An increase in development of land for

agricultural purposes has increased concerns that monocultures (single

plant or crop in an area) cannot provide the necessary nutrients for bees

to maintain a healthy hive (Aizen et al., 2008; Donkersley et al., 2014;

Odoux et al., 2014). However, agricultural landscapes can also have a

higher prevalence of beneficial weeds which can positively influence

colony health (Sponsler and Johnson, 2015). As urban beekeeping

becomes more popular it will be important to ensure that the floral

resources available can support the colonies in the area (Beekman and

Ratnieks, 2001).

2. Pesticides. Many pesticides used to target harmful agricultural pests

can also have negative effects on beneficial pollinators, such as honey

bees. Bees are exposed to pesticides during foraging or from harmful

chemicals drifting into the colony. Pesticides can have lethal effects and

5 kill bees quickly or sub-lethal effects, which are more difficult to observe and usually require prolonged exposure to pesticides (Desneux et al., 2007). Some of the sub-lethal effects of pesticides include disrupted honey bee development (Chandel and Gupta, 1992; Deruijter et al., 1987), effects on learning and behavior (Armengaud et al., 2002;

Thompson, 2003), and reduced reproductive ability (Amdam et al.,

2002; Kairo et al., 2016).

3. Pests and diseases. Pests and diseases probably contribute the most to colony loss in the United States (Guzmán-novoa et al., 2009). In particular, the Varroa destructor mite, an ectoparasite, transfers lethal viral diseases to honey bees. These diseases can quickly spread throughout a colony or apiary and lead to colony loss (Martin et al.,

2010; Guzmán-novoa et al., 2009; Berthoud et al., 2010). Colonies not treated for Varroa mites will almost certainly die within a few years of initial infestation (Frey and Rosenkranz, 2014). There are several methods employed by beekeepers to treat for Varroa mites including chemical treatments, physical management, and genetics (“Tools for

Varroa management”).

4. Poor management. Poor management by beekeepers can also contribute to colony loss. For example, 54% of beekeepers did not treat for Varroa mites from 2014-2015. Beekeepers that did treat for Varroa mites lost 26.8% fewer colonies than beekeepers that did not treat (Seitz et al., 2015). Although evidence suggests that treatments can effectively

reduce colony loss, many beekeepers still choose not to treat for Varroa

mites (Seitz et al., 2015). Several factors may contribute to beekeepers’

opposition to treating for Varroa mites such as product origin (organic

vs. synthetic), product application requirements, pest resistance to

products, and cost of products.

1.3 Varroa mites

The Varroa destructor mite is believed to be the largest contributor to honey bee colony loss, associated with approximately 85% of colony loss in the United States

(Guzmán-novoa et al., 2009). Varroa mites were first discovered in Asia on its original host, the Eastern honey bee (Apis cerana) in 1904 (Oudemans, 1904). Around 1957 it is believed Varroa mites expanded their host range to include European honey bees, the most common managed species in the United States (Crane, 1984; de Guzman et al.

1997). Varroa mites were first described in the United States in 1987 (de Guzman et al.

1997; Oldroyd, 1999). Since the initial introduction of Varroa mites, evidence suggest they are present in 98% of colonies in the United States and can be found on every continent except Australia (Rennich et al., 2014; Rosenkranz et al., 2010).

Several factors help explain the pervasiveness of Varroa mites in the United States.

One factor is the recent introduction of Varroa mites to the United States in 1987 (de

Guzman et al. 1997; Oldroyd, 1999). Honey bees have had little time to evolve a balanced host-parasite relationship with Varroa mites and therefore are not adapted to the numerous diseases vectored by Varroa mites (Oldroyd, 1999). Another factor contributing to the success of Varroa mites is their biology and behavior. Varroa mites are obligate parasites and depend on honey bees to reproduce (Rosenkranz et al., 2010).

The closely linked lifecycle with honey bees allows Varroa mites to easily spread throughout a single colony or to neighboring colonies. Mite transmission occurs when foraging bees carrying a mite rob resources from weaker colonies and pick up a Varroa mite or accidentally drift into the wrong colony while carrying a mite (Rosenkranz et al.,

2010; Fries and Camazine, 2001). The factor contributing the most to the success of

Varroa mites is their ability to vector lethal diseases that lead to honey bee colony loss

(Martin et al., 2010; Guzmán-novoa et al., 2009; Berthoud et al., 2010).

The life cycle of the Varroa mite has two main phases: a reproductive phase and an adult (phoretic) phase. The reproductive phase begins when a female mite invades a larval cell just before it is capped. Once worker bees cap the cell, the larva will pupate.

The female mite will feed on the pupa and then shortly after lay her first egg, which is always a male. After the first egg is laid the female will lay another egg approximately every 60 hours up to five times. Only 1-2 of the eggs laid will reach maturity per reproductive cycle. The male mite will then mate with mature females in the cell. The phoretic phase begins when a mature female mite attaches to the emerging adult bee and feeds on its hemolymph. Phoretic mites can switch bee hosts facilitating the spread of diseases (Martin, 1994; Accorti and Nanneli, 1990; Fries and Rosenkranz, 1996; Martin and Kemp; Ruijter, 1987; Donzé and Guerin, 1994; Rosenkranz et al., 2010).

There are several consequences of Varroa mite parasitism on honey bee colonies. On an individual level, parasitism by Varroa mites can result in decreased weight in worker and drone bees, deformation of bee legs or wings, altered flight ability in drones and reduced life span of parasitized bees (De Jong et al., 2015; De Jong et al., 1982;

Sammataro et al., 2000; Duay et al., 2002). On a colony level Varroa mites vector several

8 viruses that are associated with increased colony loss (Martin et al., 2010; Guzmán-novoa et al., 2009; Berthoud et al., 2010). There are 18 viruses vectored by Varroa mites that have been identified in the United States. The most prevalent diseases in U.S. colonies are deformed wing virus (80% prevalence) and black queen cell virus (> 90% prevalence)

(Chen and Siede, 2007; Rennich et al., 2014). Deformed wing virus can cause death at the pupal stage or the adult stage. Adult bees with deformed wing virus have shortened, stubby wings, discoloration, and reduced life span. Black queen cell virus causes mortality mostly in developing queens but can also affect worker bee larvae. There are currently no known drugs to treat these viruses, however, treatment with registered miticides and some cultural and physical control methods can significantly increase colony survival by controlling the Varroa mite vector (Chen and Siede, 2007;

Rosenkranz et al., 2009; Seitz et al., 2015).

1.4 Varroa management

There are three major categories of miticides: synthetic products, natural products, and cultural and physical control methods. These products can be variable in origin, mode of action, and effectiveness (Table 1). Synthetic or natural pesticides are the most reliable treatment options and show the most effectiveness at controlling Varroa mites in honey bee colonies (“Tools for Varroa Management”). The most effective cultural and physical methods are removing large areas of drone brood, which is more likely to be infested with Varroa mites (“Tools for Varroa management”; Charriere et al., 2015).

However, one downfall of this method is that it is labor intensive and requires vigilant monitoring of mite levels within the hive. Other cultural and physical methods include dusting bees with powdered sugar, applying essential oils, and using screened bottom

9 boards as the base of hives. Aside from drone brood removal, many cultural/physical methods show little effectiveness and should only be used as a supplement to more effective methods like chemical treatments (“Tools for Varroa Management”). Although miticides are the most effective treatment option there are some disadvantages to using chemical products.

The most obvious downfall to using chemicals is that mites can develop resistance to registered products over time. This is particularly true when the same products are used consecutively. Mite resistance is problematic because the product becomes ineffective and can no longer be used by beekeepers. This has already occurred for miticides containing the active ingredients coumaphos and Tau-fluvalinate (Milani, 1994; Elzen et al., 2000). Mite resistance can be reduced by rotating the miticides used and following the label application instructions exactly (Rosenkranz, 2010).

Other consequences of chemical use include lethal and sub lethal effects on honey bees, residue accumulation in hive products, and seasonality of treatment applications.

Research has revealed many lethal and sub lethal effects of chemicals on honey bees.

These include increased mortality of immature bees and adult bees, altered memory and learning, and delayed honey bee development (Berry et al., 2013; Desneux et al., 2007).

Pesticides can also leave residues in wax and honey. These residues can accumulate in the wax and affect bee fitness or change the taste of honey (Johnson et al., 2010). Timing of application can also be challenging for beekeepers. Many registered miticides can only be applied in early spring or when honey to be harvested for human consumption is not present. Consequently, mite populations are allowed to grow exponentially in the summer

(“Tools for Varroa management”). The above-mentioned reasons contribute to the

10 preference by many beekeepers to use natural methods that are acceptable to use while honey is being produced, or no treatment method at all (Seitz et al., 2015).

Another area of increasing concern is the use of the unregistered product Taktic

(active ingredient: amitraz) by many large-scale beekeepers (Flottum, “Inner cover”,

2016). This product is used by placing a towel, soaked in a mixture of Taktic and Crisco oil, near the brood area of a colony. The registered alternative Apivar, contains the same active ingredient but it is more expensive than the unregistered product and may be less effective at killing mites. It is unknown how many beekeepers use Taktic or how often it is used since many beekeepers use the product in secret to avoid getting penalized. Mite resistance to amitraz has already been observed in some mite populations in the United

States (Elzen et al., 1999). Mite resistance of amitraz could have serious impacts on many large-scale beekeepers that solely depend on Taktic. As large-scale beekeepers manage most the honey bee colonies in the United States, it is increasingly important to come up with new effective miticides to support our most economically important population of beekeepers.

Most insecticides used for controlling Varroa mites are incorporated into a formulation. Formulations are used to reduce the toxicity of a pure compound and maximize pest exposure to the pesticide. In order to choose the appropriate formulation, the physical properties of the pesticide should be considered. Kow is a partition coefficient which indicates whether a chemical is more likely to absorbed by organic material or solubilized in water. If the pesticide is lipophilic (high Kow), then the compound may end up in the beeswax, whereas compounds with low lipophilicity may end up in the honey (low Kow). Vapor pressure should also be considered. Products that

11 are highly volatile may quickly evaporate and leave the colony, whereas, products with low vapor pressure may persist longer in the colony (Spencer and Cliath, 1983; Suntio et al., 1988). Many registered miticides are impregnated into plastic or cardboard strips that are placed between the brood frames of a colony. A tablet is similar to the strips but is placed on top of the frames of boxes of brood. Miticides can also be mixed into a sugar solution and applied directly to the brood boxes using a syringe, a method called a drip formulation (Table 1.1) (“Tools for Varroa Management”).

Varroa mite exposure to the pesticide depends on removal of the formulation by bees. As the bees remove the formulation, mites attached to bees make direct contact with the miticide. Indirect exposure can occur when honey bees rub against other bees in the colony. Ideally, the formulated miticides persist in the colony for an entire brood cycle (21 days) so that all the mites in that colony can be exposed to the varroacide

(Sammataro et al., 2000).

Application duration/ Brood Honey Log Kow at 20°C, Vapor Pressure Product name Active ingredient Origin Formulation Frequency Y/N Y/N pH 7 (mm Hg)

42 to 56 days, 2 times per Apivar amitraz Synthetic Polymer strip Yes No 5.5 2.0 x 10-6 at 25°C year

Apistan tau-fluvalinate Synthetic Plastic strip 42 days, 1-2 times per year Yes No 7.02 8.42 x 10-9 at 25°C

CheckMite+ coumaphos Synthetic Plastic Strip 42 days, 2 times per year Yes No 4.13 1 x 10-7 at 20°C 13 Apiguard thymol Natural Gel 4 weeks, 1-2 times per year Yes No 3.30 0.016 at 25°C

ApiLife Var thymol Natural Tablet 7-10 days, 2 times per year Yes No N/A 0.04 at 25°C

(MAQS) formic acid Natural Gel strip 7-10 days, all season Yes Yes -0.54 42.59 at 25°C

21-30 days, up to 6 Formic Acid 65% formic acid Natural Slow release pads Yes No -0.54 42.59 at 25°C times/year

oxalic acid Oxalic acid Natural Sugar syrup drip 2 times per year No No -0.81 0.001 at 20°C dihydrate

Hopguard II Hops beta acids Natural Cardboard strip 4 weeks, 3 times per year No Yes N/A <0.1 at 20°C

(Table 1.1) This table shows the application information and chemical properties for all products currently registered for Varroa mite control. Included in this table is the name of each product, active ingredient, application duration and frequency, whether the product can be used in the presence of brood and honey, Log Kow, and vapor pressure (Honey bee health coalition. (2017) “Tools for Varroa Management”, National Center for Biotechnology Information. PubChem Bioassay Database.)

CHAPTER 2

The use of a C8910 fatty acid blend for Varroa mite control

2.1 INTRODUCTION

Insecticidal soaps are common contact pesticides that are used on a variety of pests such as aphids, cockroaches, mosquitos, and spider mites (Parry and Rose, 1983;

Baldwin et al., 2008; Samuel et al., 2015; Cloyd, 2013). Soaps owe their effectiveness to their fatty acid constituents (Siegler and Popanoe, 1925). Fatty acids are comprised of a hydrocarbon chain with a terminal hydroxyl group (Figure 2.1). The mechanism by which soaps and fatty acids kill arthropods is still unclear but is probably due to one of the following modes of action: the dissolution of the protective outer cuticle of the insect leading to dehydration, the blockage of tracheal openings needed for respiration, or the disruption of cell membranes leading to internal decay (Siegler and Popanoe, 1925;

Cloyd, 2013).

(Figure 2.1) Nonanoic acid (C9) fatty acid. Chemical structure is CH3(CH2)7COOH.

Traditionally, longer- chained fatty acids, containing eight to 18 carbon atoms, have been used for insecticidal purposes, possibly due to the phytoxicity of shorter fatty acid chains (Samuel et al., 2015; Baldwin et al., 2008; Siegler and Popanoe, 1925; Cloyd,

2013). In particular, the C8910 (1:1:1 mixture of octanoic, nonanoic, and decanoic fatty acids) blend has known toxic and repellant effect on mosquitos, house flies, horn flies and stable flies (Samuel et al., 2015; Dunford et al., 2014). The C8910 fatty acid blend is a good potential Varroacide for use in bee hives for many reasons. One reason is that the

C8910 blend may have a new mode of action that mites have not yet developed resistance to (Siegler and Popanoe, 1925; Cloyd, 2013). Additionally, the C8910 blend may be considered organic since it is naturally derived from palm kernel or coconut oil and beef tallow (Reifenrath patent, WO2010121142 A2). Another advantage of the C8910 blend is that it is non-toxic to mammals and can be safely applied by people (Siegler and

Popanoe, 1925; Reifenrath patent, WO2010121142 A2). Based on the known properties of the C8910 blend, the blend does not likely pass through beeswax, meaning it can be approved for use when honey for human consumption is present. If effective, the C8910 blend could be one of the three products available for use at this critical time in mite population growth (Table 1.1; Tools for Varroa Management).

The aim of this study is to: 1) Determine the differential toxicity of the C8910 blend to Varroa mites and honey bees 2) Test different polyester polyol formulations as a delivery method for the C8910 blend in full-sized colonies 3) Compare the effectiveness of the formulation alone, the C8910 incorporated into the formulation, and a registered product (Hopguard) in full-sized colonies.

2.2 MATERIALS AND METHODS

2.2.1 Fatty acid toxicity

Laboratory vial bioassays were performed to compare the acute contact toxicity of

C8910 to honey bees and Varroa mites. Vial testing was performed by dissolving the blend in acetone and coating the sides of a 1.5-quart jar (honey bees) or a 20-ml scintillation vial (Varroa mites)(Figure 2.2). The vials and jars were rotated on a hot dog roller to allow the solvent to evaporate and the fatty acid blend to form and even coat inside the container. Containers were prepared with varying concentrations of the C8910 blend, plus a negative solvent control. Each container received 10 mites collected from adult bees using a “sugar-shake” (Macedo and Ellis, 2002) or 20 three-day-old adult bees

(Johnson et al., 2013) taken from OSU apiaries. Mites were maintained in the dark at 27 degrees Celsius and fed on a pre-pupa bee supplied 1 h. after initiation of the test. Bees were maintained in a dark humid incubator (34 degrees Celsius) and supplied 1:1 (w/w) sucrose water ad libitum. Mortality was scored at 1, 4 and 24 h. At least three replicates were performed for each treatment. The LC50 was calculated using a log-probit analysis implemented in R (Johnson et al., 2013).

(Figure 2.2) Jar preparation for honey bee bioassays. Jars are rotated on a hot dog roller to create an even coat of the fatty acid blend on the inside of the jar.

Preliminary experiments in 2014 showed that the C8 and C9 components of the

C8910 blend were the most toxic to mites. For this reason, we decided to look at the toxicity of shorter and longer fatty acids to assess a difference in bee and mite toxicity with a change in fatty acid chain length. The acute contact toxicity was determined by performing contact bioassays on Varroa mites and bees with the following fatty acids: pentanoic acid (C5), hexanoic acid (C6), heptanoic acid (C7), octanoic acid (C8), nonanoic acid, decanoic acid (C10), undecanoic acid (C11), dodecanoic acid (C12). All fatty acids were provided by Emery Oleochemical (Cincinnati, Ohio).

The individual fatty acids were tested using the same contact vial bioassay methods used for C8910 blend. For the purposes of the field experiment we decided to only use the C8910 blend in full-sized colonies because it is already registered and could be utilized quickly by beekeepers, if proven effective. Dose response curves for mites and bees were fitted after correction for the different area in scintillation vials and jars and

LC50 values were calculated (Johnson et al., 2013). Statistical differences between LC50 values in Varroa mites and bees were determined using a ratio test (Robertson et al.,

2009). A margin of safety was calculated by dividing the LC10 for honey bees by the

LC90 for Varroa mites for each fatty acid.

2.2.2 C8910 blend in polyol

The polyol patties are made through an esterification reaction. Each polyol (#73,

#75, and #78) has a different ratio of a mono-acid (stearic acid or oleic acid) and a di-acid

(azelaic acid). The mixture reacts in the presence of glycerin at 220 degrees Celsius for

24 to 36 hours. Each polyol patty feels waxy and has a slightly different melting point:

Polyol 75 has the lowest melting point (10 to 40 °C) and was spreadable at room temperature, polyol 73 and 78 had higher melting points (25 to 45 °C and 15 to 45 °C) and had to be melted in order to apply them to the colonies (personal communication,

Darlene Florence, 4/4/17).

To determine which polyester polyol would be the most promising delivery vehicle for the C8910 fatty acid blend we tested different polyol formulations, provided by Emery Oleochemicals. Three different polyol formulations were tested- polyol #73,

#75, and #78. One 25g patty of each polyol was placed between two boxes in a strong full-sized colony. The patties were prepared by heating each polyol in a microwave and then pouring 25 grams into a weigh boat. The polyol was then scooped out of the weigh boat and spread evenly onto a sheet of paper towel and allowed to solidify. Three polyol patties and one control patty (vegetable shortening) were placed in the same colony to allow direct comparisons between formulations. This was repeated in five colonies from the same apiary in July 2016. Percent remaining of the patties was assessed visually and

18 through digital photos every 3 days for 10 days. A two-way ANOVA test in SPSS was used to compare percent removal of polyol in the treatment groups.

We also tested the C8910 blend incorporated into Polyol #73 to determine a colony-level dose and if there was a repellency effect of the formulated C8910, as noted in other insects (Reifenrath patent, WO2010121142 A2; Samuel et al., 2015; Dunford et al., 2014). Two 10g patties of each treatment were placed in 5 full-sized bee colonies in the same apiary in August 2016. The patties were prepared similarly to previous experiments by heating the polyol #73 and pouring out 10 grams into a weigh boat. Either

1% (100mg of C8910) or 4% (400mg C8910) was added to the 10g patty and mixed thoroughly. Two patties with 4% C8910, two patties with 1% C8910, and two control patties (Polyol #73 without C8910) were placed in the same colony. The patties were assessed visually through digital photos every 3-4 days for 7 days. A two-way ANOVA test was used to compare mean percent removal of the control, low dose, and high dose patties.

2.2.3 C8910 blend in full-sized colonies

The efficacy of the fatty acid blend was tested in 36 full-sized hives managed by

OSU in northeast and central Ohio from September - October 2016. Two colonies in each apiary received a 50g patty with 4% C8910, Hopguard (a registered varroacide), or no treatment. The patties were prepared by heating the Polyol 73 in a microwave and pouring 50g into a weigh boat. The patty was then removed and spread evenly across one sheet of paper towel and allowed to cool. Once the paper towel was hardened it was cut in half to make two 25g rectangular strips. Treatments were replicated across 6 apiaries

19 for a total of 12 colonies per treatment. To compare the effect of treatment on phoretic

Varroa mites on adult bees we used a two-way ANOVA.

All colonies were in standard 8-frame Langstroth hives with solid bottom boards. Colonies were a mix of overwintered colonies and new colonies started from packages in spring 2016. All colonies were maintained according to standard beekeeping practice, but had not been treated for Varroa mites previously in the 2016 season. Drop zone dead bee traps!were placed at the entrance of the colonies at three apiaries to determine the number of dead bees before and after treatment. Dead bee traps were made with 2’x4’x1/2’ wooden frames with ½” hardware cloth on top and window screen on the bottom. Colonies were visited on a weekly basis where the following measurements were taken: number of dead bees in the drop-zone trap, number of adult mites under 100 cappings, and number of phoretic mites on ~300 adults bees using an alcohol wash. The

50g C8910 patty was replaced each week and weighed to determine the rate of removal.

To compare the effect of treatment on dead bees we used a repeated measures ANOVA.

In addition, to determine if there was an effect of treatment on the number of colonies that survived the winter we used a chi-squared test.

2.3 RESULTS

2.3.1 Fatty acid toxicity

After correcting for the surface area differences between scintillation vials and the jars, the toxicity of pure C8910 (in a 1:1:1: ratio) was found to be significantly higher for

Varroa mites than for honey bees. The LC50 for honey bees is approximately 2-fold higher than for Varroa mites, which suggests that there is a sufficient margin of safety to

20 use the existing C8910 blend as a miticide.

The LC50 values for Varroa mites for pure C5, C6, C7, and C11 were approximately the same (2.08 mg/cm2; 1.61 mg/cm2; 1.87 mg/cm2; 1.94 mg/cm2).

Additionally, the LC50 for Varroa mites of the C8910 blend was about 2-fold higher than the LC50 for C5, C6, C7, and C11, suggesting that the pure fatty acid chains (C5, C6, C7,

C11) are more toxic to Varroa mites than the C8910 blend. The LC50 for honey bees of pure C5 was the largest (>3000 mg/cm2), which suggests that C5 provides the largest margin of safety for honey bees (Tables 2.3 and 2.4).

To test if the mite and bee LC50 values were significantly different we performed a ratio test. The LC50 ratio for all the fatty acids except C5 and C6 were significantly different (confidence intervals not overlapping with 1) (Table 2.1) (Robertson, 2009).

Fatty acid Bee LC50/ Lower CI Upper CI Margin of Safety Varroa LC50 (LC10 bees/ LC90) mites) Ratio C5 1.4E+4 NA NA >692.84

C6 18.44 0.73 465.94 3.80

*C7 7.99 1.07 59.81 1.03

*C8 3.77 2.14 6.63 0.26

*C9 5.2 2.8 9.63 0.29

*C10 2.64 1.85 3.76 0.03

*C11 10.69 1.35 84.53 1.46

*C12 583.19 252.91 1344.79 0.05

C8910 1.78 1.01 3.16* 0.04

(Table 2.1) This table shows the bee/mite LC50 ratio, upper and lower confidence intervals, and margin of safety. * indicates that there is a significant difference between the bee and mite LC50 values using a ratio test.

2.3.2 Polyol removal

To compare the removal rate between different patties we used a two-way

ANOVA test in SPSS. There was a statistically significant difference in percent remaining between polyol types, F (9,64) = 2.072, P=0.045. Tukey post hoc analyses showed that patty 73 differed significantly from patty 75 (P<0.001) and patty 78

(P<0.001) but did not differ significantly from the control (P=0.526). Likewise, there was no significant difference between patty 75 and patty 78 (P=0.137). In other words, there was significantly more patty 73 removed by bees than the other two patty types (Figure

2.3). Based on these results patty 73 was used for subsequent tests.

A two-way ANOVA showed that there was a significant difference in percent remaining between patties with increasing concentrations of C8910, F (4,51) = 3.23, p=0.019. Tukey post hoc tests showed that percent remaining of the 4% C8910 patty differed significantly from the control (P=0.001) but did not differ significantly from the

1% C8910 patty. These results suggest that there is a repellant effect to the bees with an increasing concentration of C8910. Despite a possible repellency effect, the 4% C8910 patty was mostly removed after a week (mean= 17% remaining) (Figure 2.4).

2.3.3 C8910 in full-sized colonies

A two-way ANOVA was used to compare the effect of treatment on Varroa mites on adult bees and under cappings. Results showed that there was no significant difference in mites per 100 adult bees between the different treatment groups (P=0.845) (Figure

2.5). Likewise, there was no significant effect of treatment on mites under 100 cappings, p=0.554 (Figure 2.6). In addition, there were no differences in the mean number of dead

22 bees between treatment groups (p=0.957). Survival of colonies also did not differ significantly between treatment groups (X2=0.887) (Table 2.2).

Treatment # of colonies that Total # of colonies survived Control 4 12

4% C8910 5 12

Hopguard 5 12

36 total colonies

(Table 2.2) Number of colonies in each treatment group that survived through the winter.

Apis mellifera

Fatty n Slope±SE Intercept X2 df LC10 +CI LC50 +CI LC90 + CI acid C5 80 0.02 ± -7.01 ± 2.77E-10 3 7.4E+239 3.3E+293 N/A 16720.11 13406.22 C6 322 4.26 ± 0.95 -6.27 ± 1.41 32.83 7 14.82 (6.2 - 21.23) 29.65 (20.54 - 44.04) 59.31 (40.82 – 152.32)

C7 298 3.82 ± 0.89 -4.49 ± -0.63 24.32 5 6.91(1.81 - 10.48) 14.9 (9.52 - 22.24) 32.39 (21.90 – 107.42)

C8 964 3.51 ± 0.41 -4.49 ± 0.53 25.99 6 8.16(5.48 - 10.57) 18.90 (15.21 - 23.78) 43.76 (33.08 – 68.26) 24 C9 1008 2.36 ± 0.21 -3.17 ± 0.29 16.80 6 6.32(4.2 - 8.45) 22.12 (17.85 - 27.55) 77.37 (57.13 – 119.24)

C10 980 2.24 ± 0.23 -3.41 ± 0.34 18.73 6 8.96(5.69 - 12.18) 33.50 (26.42 - 43.9) 125.2 (85.51 – 226.9)

C11 332 5.62 ± 2.01 -7.39 ± 2.61 51.33 6 12.23(0.43 - 18.67) 20.68 (10.68 - 67.98) 34.97 (22.41- 2937.7)

C12 492 0.71 ± 0.23 -2.62 ± 0.34 5.19 6 238.39(68.91 - 1051560) 44869.68 (44869.68 - 8445258 (30141.58-9.1E+26) 2.88E+16) C8910 318 1.23 ± 0.59 -1.96 ± 0.18 51.89 6 2.24(0.03 - 5.21) 10.26 (3.87 - 33.61) 46.87 (19.21 – 5916.58)

(Table 2.3) This tables shows the honey bee LC10, LC50, and LC90 values for each fatty acid calculated using log probit analysis. 95% confidence intervals are based on the LC10, LC50, and LC90 values..

Varroa destructor

2 Fatty acid n Slope±SE Intercept ±E X df LC10 +CI LC50 +CI LC90 +CI

C5 191 4.03 ± 0.59 -1.28 ± 0.59 2.21 5 1(0.64 – 1.32) 2.08 (1.65-2.52) 4.33 (3.51 – 5.87)

C6 258 3.33 ± 0.68 -0.68 ± 0.32 15.56 5 0.66 (0.66 - .17) 1.61 (0.87 -2.54) 3.9 (2.47 – 10.31)

C7 275 2.32 ± 0.68 -0.63 ± 0.4 36.13 5 0.53 (0.004 – 1.3) 1.87 (0.37-4.75) 6.69 (12.54 – 60.97)

C8 397 1.6 ± 0.28 -1.12 ± -1.12 19.51 5 0.8 (0.14 – 1.69) 5.02 (2.63 -9.5) 31.67 (14.94 – 170.94)

C9 413 1.8 ± 0.25 -1.13 ± 0.24 12.7 5 0.82 (0.29 – 1.47) 4.25 (2.69-6.64) 21.96 (12.54 – 60.97)

C10 406 0.9 ± 0.13 -.1 ± 0.14 9.06 5 0.49 (0.09 - 1.17) 12.71 (6.7 -29.59) 333 (99.55 – 4159.12)

C11 205 2.01 ± 0.25 -.58 ± 0.16 4.23 5 0.45 (0.24 – 0.67) 1.94 (1.42 -2.55) 8.39 (5.93 – 13.83)

C12 237 0.71 ± 0.19 -1.35 ± 0.22 10.17 5 1.23 (0.01 – 4.2) 76.938 (20.68- 4821.97 (30141.58 – 9.1E+26) 17837.98)

(Table 2.4) This table shows the Varroa mite LC10, LC50, and LC90 for each fatty acid calculated using log probit analysis. 95% confidence intervals are based on the LC10, LC50, and LC90 values.

100% Patty # 73 75 78 Control 80%

60%

40% Percent Remaining

20%

1 4 7 10 Day

! Error bars: +/- 1 SE

(Figure 2.3) Mean percent remaining of different patty types over 7 days. The percent remaining of patty 73 was significantly different from the other two patty types (p<0.001) but not significantly different from the control (p=0.526). Error bars +/- 1 SE.

Page 2

100% Control 1% C8910 4% C8910

80%

60%

40% Percent remaining

20%

1 3 7 Day ! Error bars: +/- 1 SE (Figure 2.4) Mean percent remaining over 7 days of a 4% patty, a 1% patty and a control. The percent remaining of 4% C8910 patty was significantly different from the control (p=0.019) but not significantly different from the 1% C8910 patty. Error bars +/- 1 SE.

Page 2

25 Treatment Control 4% C8910 patty Hopguard 20

Phoretic mites on 100 bees 5

0 1 2 3 4 Week

Error bars: +/- 1 SE (Figure 2.5) Mean number of mites on adult bees in each treatment group. There was no significant difference in mite numbers (p=0.845). Error bars +/- 1 SE.

Page 2

Treatment Control 4%C8910 patty 12.5

10.0

7.5

5.0

Adult mites under 100 cappings 2.5

0 1 2 3 Week

Error bars: +/- 1 SE (Figure 2.6) Mean number of mites under 100 cappings in the control and 4% C8910 treatment groups. There were no significant differences between treatment groups (p=0.554). Error bars +/- 1 SE.

Page 2

350 Control Patty 300 Hopguard 250

200

150 Mean Dead Bees Mean

100

0 Week!1 Week!2

(Figure 2.7) Mean number of dead bees collected in drop zone dead bee traps for control, 4% C8910, and Hopguard groups before treatment application and one week after treatment application.

2.4 DISCUSSION

2.4.1 Fatty acid toxicity

In general, the shorter chain fatty acids seem to be more toxic to mites than the longer chain fatty acids. Additionally, the shorter chains had larger margins of safety for honey bees. This suggests that the shorter chains are more toxic to mites and safer for bees than the C8910 blend. A shorter chain fatty acid blend may be more promising as a colony treatment than the long-chain C8910 blend that was tested because more material can be applied without harming the bees. Although the C8910 blend was less toxic to mites than the shorter chains, laboratory tests showed that the C8910 blend had a 2-fold margin of safety for bees. For this experiment, we used the C8910 blend because it was

30 already registered for use on other arthropods and could be quickly registered for this additional use.

Patty 73 was removed the fastest from the colonies, suggesting that there is no repellency to the patty alone. We also looked at removal of the C8910 blend incorporated into the patty 73 to see if there was a repellency effect of the blend. There did seem to be decreasing removal with increasing concentration suggesting a repellency effect of the

C8910 blend. Even though there was some repellency of the C8910 blend in the patty, the highest dose (4% C8910 blend) was removed within a week. The removal rate was ideal for this experiment because it coincided with other weekly measurements and required us to only inspect each colony once a week.

2.4.2 Field experiments

Although the C8910 blend looked promising as a varroacide in laboratory tests, there was no significant effect of the C8910 treatment on either phoretic mite levels or mites under cappings in full-sized colonies. Likewise, there was no significant effect of the Hopguard treatment on phoretic mite levels, even though this treatment is registered for controlling Varroa mites and it is recommended as an “effective” treatment (“Tools for Varroa Management”). One explanation for why the Hopguard treatment was not effective is that mite levels were too high for the treatment to be effective. Our results showed that mite levels at the beginning of the experiment were above the 3% threshold that is used to indicate high mite levels (Tools for Varroa Management). One possible reason that the C8910 treatment was not effective is that the bees did not disperse the material throughout the entire hive. Doubling the amount of patty in the colonies may provide more coverage. Additionally, the dose may not have been high enough to treat an

31 entire colony. However, increasing the dose may cause more adult bee death. Future work should try a more selective blend, perhaps a short-chain blend, and increase the amount of patty in the colonies to provide more thorough coverage.

With regards to the phoretic mite levels, there seems to be a non-significant decrease in mites in the Hopguard treatment group in week 3. This is possibly because the Hopguard treatment was mildly effective until week 3 and then stopped being effective, which explains why there is a sharp increase in mites by week 4 (Figure 2.5).

Similarly, there was a decrease in mites in the C8910 treatment group in week 3. As the

C8910 was reapplied each week, a decrease in mites is not likely due to the treatment losing effectiveness over time. One explanation for this trend is that mite levels exceeded the threshold level that is treatable with these products.

Results also showed that there was no significant effect of the C8910 treatment on mites under cappings, which suggests that the C8910 blend cannot pass through the wax cappings. Although a shorter-chain blend may be more effective, the shorter-length structure may also more easily pass through wax cappings, contaminating the honey.

Overall, the C8910 was not effective as a treatment for Varroa but showed comparable effectiveness to the registered product, Hopguard.

CHAPTER 3

Understanding management practices used by beekeepers for Varroa mite control

3.1 INTRODUCTION

3.1.1 Mite monitoring practices

Monitoring methods are primarily used by beekeepers to detect increases in mite levels in a colony. Accurately assessing mite levels within a colony is important because it can help determine which treatment to use for Varroa control. The most reliable monitoring methods are powdered sugar shakes and alcohol washes. This is because both methods provide an accurate mite level per unit of bee (standardized to the number of mites per 100 bees). Powdered sugar shakes are used by shaking bees in a jar with powdered sugar. The powdered sugar coupled with the shaking releases the mites’ grasp on the bees causing them to fall through the screened lid of the jar. One downfall to this method is that it requires time to get bees from each colony for the sugar shake. Alcohol washes are similar to powdered sugar shakes but use alcohol in place of powdered sugar.

Some disadvantages of this method is that it requires more time to execute and the bees in the jar are killed by the alcohol (“Tools for Varroa Management”)

The least accurate methods include screened bottom boards and observing mites on adult bees. Screened bottom boards are placed underneath the colonies and collect mites that drop naturally or that have been knocked off through the application of

33 powdered sugar. One problem with this method is that it only catches the mites that fall off adult bees and may not accurately represent the severity of the mite infestation. Many beekeepers may also monitor mites by simply observing them on adult bees. This method can also be misleading because Varroa mites are usually attached to the abdomen of the bee and can be difficult see (“Tools for Varroa Management”; Rosenkranz et al., 2010).

No studies have looked at which monitoring methods are used most often by beekeepers, however, some evidence suggests that beekeepers are using monitoring methods in place of treatment methods, particularly screened bottom boards (Seitz et al., 2015). As monitoring is the basis for treatment choices it is important to understand which monitoring methods are used and more importantly if they are being used correctly.

3.1.2 Treatment methods

Treatment options for controlling Varroa mites include chemical treatments or cultural treatments. Chemical products with known effectiveness for controlling Varroa mites are Apiguard, Apilife Var, Checkmite +, Apistan, Mite Away Quick Strips

(MAQs), Hopguard, and Oxalic acid (Table 1; “Tools for Varroa Management”). Cultural or physical treatments include drone brood removal, screened bottom boards, dusting bees with powdered sugar, and manipulating brood. The only cultural treatment that shows effectiveness against Varroa is drone brood removal. However, drone brood removal requires a lot of manipulation in the hive and may not be practical for beekeepers that manage many hives. Additionally, this method can only be used when drone brood are present in the beginning of the beekeeping season (Charrière et al., 2003;

Whitehead et al., 2016, “Tools for Varroa Management”). According to the Bee Informed

Partnership (BIP) National survey, beekeepers that treated with a known Varroa control

34 method lost 30% fewer colonies than beekeepers that chose to use no treatment or used only natural treatments (Seitz et al., 2015). Although Varroa mite treatments seem to effectively reduce colony losses, over half of all beekeepers chose not to treat with a

Varroa control product from 2014-2015 (Seitz et al., 2015). It is still unclear why beekeepers choose not to treat for Varroa mites. However, the BIP national survey from

2014- 2015 found that 35% of beekeepers said they prefer natural products (Seitz et al.,

2015). This may suggest that product origin could be an important factor used by beekeepers in making treatment choices.

The best approach for controlling Varroa mites is a combination of monitoring and treatment techniques. Recommended Integrative Pest Management (IPM) suggests that beekeepers should use monitoring methods early in the season to assess mite levels.

Monitoring methods should also be used after treatments are applied to see if they were effective. If monitoring methods indicate a mite level above 3% (3 mites per 100 bees) the colony should be treated with an effective product to avoid colony death. Cultural methods, particularly less effective methods (screened bottom boards and powdered sugar), can be used to deter mite population growth but should be followed with more effective treatments. Chemical treatments should be rotated to minimize the development of mite resistance (“Tools for Varroa Management”; Rosenkranz et al., 2010).

Treatment practices can vary by operation size. Hobbyist beekeepers on average manage 6.1 ± 0.1 colonies, sideline beekeepers manage 136 ± 7.8 colonies, and commercial beekeepers manage 4572.7 ± 867.1 (Seitz et al., 2015). According to the BIP

National Survey, about 35% of hobbyist beekeepers used a known Varroa mite product in 2015, compared to 90% of commercial beekeepers (Steinhaur et al., 2015). In addition,

35 small-scale beekeepers were more likely to cite starvation, cold winters, and weak bees as causes of colony death, whereas, commercial beekeepers identified Varroa mites, queen failure, and colony collapse disorder as the main causes of colony death. Commercial beekeepers may perceive Varroa mites as riskier since a greater amount of their income depends on colony survival (Seitz et al., 2015).

Collectively hobbyist beekeepers make-up about 96% of the beekeeping population but manage less than 5% of all the colonies in the United States (Steinhaur et al., 2016). Even though hobbyist beekeepers only manage a small fraction of the total colonies in the United Sates, their management styles can have a big impact on commercial beekeepers. Mite infested colonies can easily spread mites to neighboring colonies within 1 mile of each other. Even though a commercial beekeeper may be properly treating for mites, their apiary may quickly become reinfested with mites from untreated neighboring colonies (Frey et al., 2011). The large proportion of hobbyist beekeepers in the beekeeping community along with evidence that shows that hobbyist beekeepers are more likely to use no treatment or only natural treatments, suggests that hobbyist beekeepers have the most potential to reduce total colony loss by treating for

Varroa mites (Steinhaur et al., 2016; Seitz et al., 2015).

Although extensive survey work has been done on beekeepers by the Bee Informed

Partnership, these surveys focus on specific treatments or practices used and fail to consider the motives behind treatment decisions. Identifying the factors that influence beekeeping decisions may help focus the development of products that are effective and consider beekeeper needs. The aim of this survey-based study is to: 1) Determine which monitoring and treatment techniques are currently being used by beekeepers; 2) Identify!

36 factors!that!are!important!to!beekeepers!when!choosing!a!management!or!treatment! method.!

3.2 MATERIALS AND METHODS

The research design of this study was a one-time, 15-minute survey, which was administered via multiple response options (online and on paper) aimed at maximizing response (Dillman et al., 2014). The participants of this survey were the attendees of the

Ohio State Beekeeper’s Association (approximately 500 people attended the conference in November 2016). Participants that registered prior to the conference received an email with the survey link and directions. The email was sent 4 days prior to the conference date and a reminder email was sent the day before the conference. Additionally, all participants received a survey reminder in their welcome packet, containing the survey link, instructions, and a personalized code. Since some participants may have registered the day of the conference and therefore missed the email, paper copies of the survey were also available upon request at The Ohio State University booth at the conference.

Additionally, laptops were available at the OSU booth for people who did not have access to computers or preferred to take the online survey at the conference.

In order to minimize the number of participants taking the survey multiple times, participants received a unique 4-digit code to access the survey through the internet or in- person at the conference. It is possible that people took the online version and then requested a paper copy at the conference. We tried to discourage this by having the paper surveys distributed only at the OSU booth instead of in the welcome packets. This allowed the opportunity to remind people that they only need to take one.

Additionally, several people from the same beekeeping operation may have registered for the meeting and therefore would have access to the survey. To discourage this, the instructions of the survey asked that only the main beekeeper at each apiary complete the survey. The use of a code also allowed us to keep the surveys confidential and encourage participants to answer truthfully. Participants at the conference were asked to return their survey to a slotted box located near the exit to avoid accidentally associating the participant with the surveys.

The survey instrument consisted of three different parts (Appendix 1). The first part of the survey asked questions on beekeeper characteristics, such as hives managed, years beekeeping, and operation type. The second part of the survey focused on monitoring methods (familiarity with methods, how often they were used, and which season they were used in). The last part of the survey asked about treatment methods used by beekeepers (familiarity with the treatments, how often they were used, and what season they were used in). We also asked about the importance of certain factors in choosing a monitoring or treatment method. To measure importance, we used a 4-point unipolar scale that ranged from 1 being “not at all important” to 4 “most important”.

3.2.1 Data analysis

Operation-type questions were used to determine different beekeeper types from which analysis could be run. T-tests were used to determine if there was a significant difference in the number of hives kept in 2016 by hobbyist and sideline beekeepers.

Similarly, a t-test was used to determine if the maximum number of hives kept and years beekeeping were significantly different between hobbyists and sideline beekeepers

(Question 2-6). To determine if there were seasonal differences in monitoring or

38 treatment methods, a Fisher’s Exact test was used. Additionally, a Fisher’s Exact test was used to see if there were differences in monitoring and treatment methods used over the entire year (Question 10 and 13). To determine the importance of different factors to hobbyists and sideline beekeepers in choosing monitoring or treatment methods, we used a t-test. A reliability test was used to determine how well each individual factor fit with the rest of the scale (Question 11 and 14). If the Cronbach’s alpha for the entire group was higher than the Cronbach’s alpha for each individual factor then there is justification for leaving the factors as a group instead of splitting them into multiple groups.

3.3 RESULTS

3.3.1 Beekeeper demographics

A total of 45 beekeepers took the survey; 34 (75.5% of participants) self- identified as hobbyist beekeepers and 11 (24.4% of participants) identified as sideline beekeepers. Sideline beekeepers kept significantly more hives and had significantly more experience than hobbyist beekeepers (p<0.001). In addition, the maximum number of hives kept by sideline beekeepers was significantly higher (p<0.001) (Table 3.1).

n Mean Std. Error t-statistic Average # of Hobbyist 33 6.76 1.65 P<0.001 hives in Sideline 10 34.40 7.39 Summer 2016 Maximum # Hobbyist 32 9.33 2.09 P<0.001 of hives ever Sideline 10 77.18 25.5 managed Years Hobbyist 33 5.83 1.09 P<0.001 beekeeping Sideline 11 21.3 5.92

(Table 3.1) Mean number of hives kept in 2016, maximum number of hive ever managed, and years beekeeping for hobbyist and sideline beekeepers.

3.3.2 Monitoring methods

Question 10: “…if you have used the monitoring method within the last year, please tell us during what seasons you have used each method.”

In looking at mite monitoring methods, the proportion of hobbyists (29%) that used powdered sugar to monitor mite levels in summer 2016 was significantly higher than the number of sideliners (0%) using this approach (p=0.04, df=1). Likewise, significantly more hobbyists (53%) used screened bottom boards for monitoring than sideline beekeepers (18%) in summer 2016 (p=0.045, df=1,) (Figure 3.1). There were no significant differences in the monitoring methods used across all seasons between hobbyist and sideline beekeepers (p>0.05) (Figure 3.2). The most popular monitoring methods used for all participants were screened bottom boards, observing mites on adult bees, and uncapping drone brood- 63% used screened bottom boards, 46% observed mites on adult bees, and 44% uncapped drone brood.

! ! ! ! !

8 Hobbyist

6 Sideline! Number!of!beekeepers! 4

Figure (3.1) Number of hobbyist and sideline beekeepers that used each montitoring method in Summer 2016. ! ! ! ! ! ! ! ! ! ! !

10 Hobby

5 Sideline

Number!of!beekeepers!that!responded 0

(Figure 3.2) Number of hobbyist and sideline beekeepers that used each montitoring method across all seasons in 2016.

Question 11: “Please rate the importance of the following factors, to you personally, when choosing a method to monitor for Varroa mites”

The overall Cronbach’s alpha for all the factors together was higher than value for each individual factor, which suggests the factors should not be combined (Cronbach’s alpha=0.755). T-tests showed that were no significant differences in perceived importance of certain factors related to mite monitoring (p>0.05)(Table 3.2).

4 Very important 3.5

2.5

1.5 Hobbyist

1 Sideline

0.5 Least important 0

(Figure 3.3) The mean importance of factors related to choosing monitoring methods for hobbyist and sideline beekeepers (p>.05). Error bars +/- 1 SE. !

! n! Mean!! Std.! t-statistic!! Error!

…is!quick!to!use! Hobbyist! 34! 3.15! 0.153! 0.160!

Sideline! 11! 3.55! 0.157! !

…takes!few!trips! Hobbyist! 33! 2.82! 0.177! 0.269! to!the!bee!yard! Sideline! 10! 3.2! 0.200! !

…is!easy!to!apply! Hobbyist! 33! 3.24! 0.151! 0.916!

Sideline! 11! 3.27! 0.195! !

…is!safer!for!bees! Hobbyist! 32! 3.44! 0.142! 0.551!

Sideline! 10! 3.6! 0.163! !

…makes!clear! Hobbyist! 33! 3.42! 0.123! 0.805! reccomendations! for!furture! Sideline! 11! 3.36! 0.203! ! management! …minimizes! Hobbyist! 32! 2.16! 0.186! 0.206! stinging! Sideline! 11! 2.64! 0.338! !

…is!reccomended! Hobbyist! 33! 3.24! 0.151! 0.626! by!sources!I!trust! Sideline! 10! 3.4! 0.306! !

..is!inexpensive! Hobbyist! 33! 2.55! 0.163! 0.061!

Sideline! 11! 3.18! 0.296! ! !

(Table 3.2) Number of hobbyists and sideline beekeepers that responded, mean imporatnace, std.error, and t-statistic for each monitoring factor. * indicates a significant difference.

3.3.3 Treatment methods

Question 13: “…if you have used the treatment method within the last year, please tell us during what seasons you have used them”!

In looking at individual seasons, there were no significant differences in treatments used by hobbyists and sideline beekeepers (Fisher’s Exact test, p>0.05).

However, there was a significant difference in the use of drone brood removal across all seasons. Hobbyists beekeepers (32%) used drone brood removal significantly more than sideline beekeepers (0%) over the entire year (p=0.042, df=1). The most popular treatment methods used by all participants were screened bottom boards, MAQs (formic acid), and oxalic acid- 58% of beekeepers used screened bottom boards, 42% used MAQs

(formic acid), and 39% used oxalic acid.

8 Hobby 6

Number!of!beekeepers Sideline 4

(Figure 3.4) Number of hobbyist and sideline beekeepers that used each treatment method in at least one of the seasons throughout the year (n=36).

Question 14: “Please rate the importance of the following factors, to you personally, when choosing a method to treat for Varroa mites.”

The overall Cronbach’s alpha for all the factors together was higher than value for each individual factor, which suggests the factors should not be combined (Cronbach’s alpha=0.827) (Table 3.3). Results showed that inexpensive treatments were significantly more important to sideline beekeepers than hobbyists (p<0.001, df=43). Furthermore, hobbyist beekeepers perceived organic certification as significantly more important than sideline beekeepers (p=0.037, df=40) (Figure 3.3 and Figure 3.4). Overall “certified organic” was the least important factor to both beekeeper groups (Mean=1.82 ± .854), whereas “is effective at killing mites on adult bees” was the most important (Mean=3.59

±.715).

Very important 4.5 4 3.5 3 2.5 2 1.5 1 0.5 Least important 0

Hobbyist Sideline !

(Figure 3.5) The mean importance of treatment factors to hobbyists and sideline beekeepers. Error bars +/- 1 SE.

! n! Mean!! Std.!Error! t-statistic!!

…can!be!used!when! Hobbyist! 33! 2.76! 0.169! 0.349! honey!supers!are! Sideline! 11! 3.09! 0.343! ! on! …does!not! Hobbyist! 33! 3.27! 0.125! 0.445! contaminate!wax! Sideline! 11! 3.45! 0.157! ! …ia!safe!for!the! Hobbyist! 33! 3.03! 0.141! 0.914! beekeeper! Sideline! 11! 3.00! 0.234! ! …can!be!used!ina! Hobbyist! 32! 2.63! 0.140! 0.929! any!weather! Sideline! 10! 2.6! 0.221! ! conditions! …is!“natural”! Hobbyist! 33! 2.7! 0.166! 0.785! Sideline! 10! 2.6! 0.340! ! …is!quick!to!use! Hobbyist! 33! 2.79! 0.155! 0.105! Sideline! 11! 3.27! 0.195! ! …takes!few!trips!to! Hobbyist! 34! 2.5! 0.175! 0.100! the!bee!yard! Sideline! 10! 3.1! 0.277! !

…is!easy!to!apply! Hobbyist! 34! 2.79! 0.162! 0.072! Sideline! 11! 3.36! 0.203! !

…is!safe!for!bees! Hobbyist! 32! 3.66! 0.106! 0.184! Sideline! 11! 3.36! 0.203! ! ..is!certified! Hobbyist! 31! 1.97! 0.157! 0.037*! Organic! Sideline! 11! 1.36! 0.152! ! …is!effective!at! Hobbyist! 33! 3.55! 0.131! 0.261! killing!mites!on! Sideline! 11! 3.82! 0.122! ! adult!bees! ...is!effective!at! Hobbyist! 33! 3.18! 0.165! 0.782! killing!mites!under! Sideline! 11! 3.27! 0.273! ! cappings! …is!reccommended! Hobbyist! 34! 3.06! 0.152! 0.923! by!sources!I!trust!! Sideline! 11! 3.09! 0.343! !

…is!inexpensive! Hobbyist! 34! 2.21! 0.139! 0.000*! Sideline! 11! 3.36! 0.244! ! ! (Table 3.3) Number of hobbyists and sideline beekeepers that responded, mean importance, std.error, and t-statistic for each treatment factor. * indicates a significant difference.

3.4 DISCUSSION

This survey focused on determining which monitoring and treatment methods are used by different types of beekeepers and identifying factors used in making monitoring and treatment decisions. Overall our results on common monitoring and treatment methods used by beekeepers were consistent with similar survey studies (Whitehead et al., 2016; Seitz et al., 2015). Results pertaining to beekeeper demographics were consistent with our expectations that sideline beekeepers manage more hives and have more experience beekeeping. This is further supported by Steinhaur et al. (2014) which found that hobbyists manage fewer than 10 hives and sideliners manage between 50-100 hives. This suggests that beekeepers consistently self-identify themselves and supports our decision to treat them as distinctive groups.

3.4.1 Monitoring methods

With regards to monitoring methods used, our study showed key differences in screened bottom boards and powdered sugar shakes used by different beekeeping groups.

Since sideliners care for more hives, it is not surprising that they were less likely to perform behaviors that take more time such as using powdered sugar shakes to monitor for mites. On the other hand, hobbyists manage fewer colonies and have the time to use techniques that are more time-intensive. In addition to time constraints, sideline beekeepers are more likely to use treatment products on their colonies and therefore may not bother with monitoring for mites because treatment seems inevitable. However, it is important that products are only applied when mite levels are high to avoid mite resistance to products.

Hobbyists have less experience beekeeping than sideline beekeepers which may explain why they use more screened bottom boards as a monitoring method. Sideline beekeepers may have learned through their experience that screened bottom boards are less effective and therefore avoid using them. The most commonly used monitoring methods by both groups were screened bottom boards (63%), observed mites on adult bees (46.34%), and uncapped drone brood (43.9%). This pattern is consistent with

Whithead et al., (2016) which found that the most common monitoring methods were screened bottom boards (51%), observation of mites on adult bees (44%), uncapping drones (29%), and sugar shakes (21%). Our results are likely higher because our sample size was much smaller.

Our results pertaining to the importance of monitoring factors were different from our expectiations. Considering, sideline beekeepers manage more colonies, we might expect factors dealing with time to be more important to sideline beekeepers. Likewise, for the same reason, we might expect cost to be more important to sideline beekeepers.

The lack of differences between hobbyists and sideline beekeepers demonstrates that both groups respond similarly to monitoring factors. Both groups rated “minimizes stinging” as the least important factor and “is safe for bees” as the most important factors. This suggests that research should consider safety to bees in looking at new monitoring methods.

3.4.3 Treatment methods!

Results pertaining to treatment methods used did meet our expectations. Drone brood removal requires more time and therefore may not be accessible to sideline beekeepers who manage many hives. This suggests that sideline beekeeepers are mostly

49 relying on chemical products to treat for Varroa mites. Contrary to our expectations, the most common treatments used by both groups were screened bottom boards, which is not an effective treatment method. This may be explained by the high proportion of hobbyists participating in the study and may not be representative of the beekeeping community.

Whitehead, et al., (2016), which had a larger sample size, found that the most common treatments were MAQs (32%) and oxalic acid (25%).

Not surprisingly, cost of treatments was more important to sideline beekeepers than hobbyists. This is likely because sideline beekeepers manage more colonies than hobbyists and therefore need treatments that are cost effective. On the contrary, hobbyists perceived “certified organic” as significantly more important than sideline beekeepers.

This is supported by the Bee Informed National Beekeeper’s Survey 2015-2016, which found that more hobbyist beekeepers use all natural treatments or only bee-derived products (Seitz et al., 2015). However, in looking at beekeepers as single group,

“certified organic” was the least important factor, suggesting that it is not a very important factor in making treatment decisions. Both beekeeping groups rated “is effective at killing mites” as the most important factor in choosing a treatment method.

This is somewhat surprising considering that hobbyists seem to use more methods with less effectiveness such as powdered sugar and screened bottom boards. This may suggest a disconnect between what hobbyists perceive as effective and what is actually effective.

Overall, hobbyist beekeepers used more methods that require time such as, powdered sugar shakes for monitoring, and drone brood removal for mite control.

However, this is contrary to our results which found that the importance of application timing was approximately equal in hobbyist and sideline beekeepers. This suggests that

50 there may be another factor driving monitoring and treatment decisions by beekeepers that is unrelated to timing, such as beekeeping experience.

One limitation of this study is the small sample size of beekeepers. In addition, no commercial beekeepers participated in the study. This is likely because commercial beekeepers make-up 2% of the beekeeping population and are therefore less likely to attend the conference. Another limitation is that the survey was only distributed at the

Ohio State Beekeeper’s Association Meeting in 2016. Beekeepers that attend the conference may not be representative of beekeeping population and therefore results should not be considered causative or conclusive. !

Based on our results, future research should focus on making accurate monitoring methods more available to sideline beekeepers such as powdered sugar shakes and alcohol washes. Developing monitoring methods that are accurate and less time- consuming may encourage sideline beekeepers to use more monitoring methods and follow recommended IPM strategy. This may also reduce mite resistance due to over application of products. In addition, research should focus on making more monitoring methods that are “safe for bees” as that was the most important factors to both beekeeping groups.

Furthermore, research should focus on making drone brood removal more reliable as a treatment method to encourage use by sideline beekeepers. Although some chemical products are highly effective, drone brood removal is a good option in early in the season when most chemical products are the least effective (Whitehead et al., 2016). Making drone brood removal more accessible to sideline beekeepers could provide another treatment method that can be rotated with chemical options. Likewise, all beekeepers in

51 the study indicated that “is effective at killing mites” was the most important factor and should be considered in the development of new products. Research should not focus on developing organic products as that was the least important factor to both beekeeping groups.

With regards to C8190 blend our study showed that beekeepers are likely to use the product if it “is effective at killing mites”. Additionally, beekeepers are not likely to be discouraged from using the C8910 blend if is not certified organic. Although the

C8910 blend was not an effective treatment in full-sized colonies, shorter fatty acid chains with more toxicity to mites may be a promising new treatment that is in line with beekeeper values

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APPENDIX : Survey instrument