Varroa Mite Management Among Small-Scale Beekeepers: Characterizing Factors That Affect IPM Adoption, and Exploring Drone Brood Removal As an IPM Tool

Varroa mite management among small-scale beekeepers: Characterizing factors that affect IPM adoption, and exploring drone brood removal as an IPM tool

THESIS

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

Hannah R. Whitehead

Graduate Program in Environmental Science

The Ohio State University

2017

Master’s Examination Committee:

Dr. Casey Hoy, Advisor

Dr. Reed Johnson

Dr. Anna Willow

Copyrighted by Hannah R. Whitehead 2017

ABSTRACT

Varroa mites (Varroa destructor) are the most damaging pest in modern beekeeping, and have been linked with elevated levels of colony loss. Experts increasingly recommend an integrated pest management (IPM) strategy to manage

Varroa, which incorporates both preventative and therapeutic controls. However,

Varroa IPM is complicated and knowledge-intensive. Small-scale beekeepers in particular seem to have difficulty adopting effective Varroa control strategies, and suffer especially high rates of colony loss. This study took an interdisciplinary approach to understanding the adoption of Varroa IPM among small-scale beekeepers. First, I used surveys and interviews to characterize mite management strategies among Ohio small-scale beekeepers, and to explore the effect of experience and risk perception on behavior. Second, as a case study, I took a closer look at the efficacy and adoption of one complex IPM tool – drone brood removal (DBR) – through interviews, surveys, and an on-farm trial. Overall, I found no relationship between beekeeping experience and mite management strategies, but sampling (risk perception) was associated with the use of “soft” miticides (organic acids/essential oils) and DBR. I also found that most beekeepers who used DBR combined it with drone sampling (adjusting DBR based on sampled mite levels), and that labor was the biggest barrier to DBR use. In the on-farm trial, DBR significantly reduced mites in year one but not year two. These results suggest that mite management failures

among small-scale beekeepers are not due to inexperience and may indicate a broader communication breakdown. They also suggest that risk perception – beekeepers’ understanding that they even have mites – may be a key factor driving adoption of mite management practices. Finally, they point to the fact that DBR is already being used in nuanced ways as a combined management and sampling strategy. They suggest that DBR is not a silver bullet, but can be an effective tool to reduce mites if used consistently, intensively, and in combination with other management tactics.

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Dedicated to my family

ACKNOWLEDGEMENTS

This project would not have been possible without help from so many people.

Thanks first to my advisor, Casey Hoy, who was open to advising a project outside his typical area of research, and who offered endless support, thoughtful edits and a systems perspective all along the way. Many thanks also to my committee members:

Reed Johnson, who introduced me the beekeeping scene in Ohio and allowed me to become an honorary member of the Bee Lab – borrowing equipment, attending bee events, and tagging along for beekeeping activities. And Anna Willow for providing thoughtful feedback and pushing me to consider the broader social implications of this research. Thanks also to fellow graduate students – Natalie, Julie, Fred, Matt, as well as the entomology crew – with whom I’ve had many passionate discussions about sustainable agriculture and beekeeping, and who made graduate school much more fun. Many thanks to the beekeepers who volunteered their bees, their knowledge and their time in order to make the field experiment a reality: Dave Noble,

Phil Young, Laura Urban, Al Blyth, Randall Westfall and Rod and Dru Pritchard.

Thanks to Chia Hua Lin for help with research design and set-up, to Alia Dietsch for help with survey analysis, and to Meghan Blackson, Sreelakshmi Suresh, Laura

Bond, Natalie Riusech and Andrea Wade for patiently helping me collect data.

Special thanks to Willi for invaluable support and insightful feedback throughout this

project and to my family, for their support and encouragement in all of my academic endeavors. Finally, this work would not have been possible without funding from an

Ohio State SEEDS grant.

VITA

2007……………………Hawken High School, Gates Mills, OH

2007-2011……………...B.A. History, The University of Chicago

2011-2012……………..Administrative Assistant, Common Threads

2012……………………Intern, Coonridge Organic Goat Cheese

2013-2014……………...Research Assistant, Agroecosystem Management Program, The Ohio State University

2014……………………Farm Manager, Muddy Fork Farm

2014-2016……………..Graduate Fellow, Environmental Science Graduate Program, The Ohio State University

2016……………………Graduate Teaching Associate, Environmental Science Graduate Program, The Ohio State University

Fields of Study:

Major Field: Environmental Science Specialization: Agroecosystem Science

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TABLE OF CONTENTS

ABSTRACT ...... ii ACKNOWLEDGEMENTS ...... v VITA ...... vii TABLE OF CONTENTS ...... viii LIST OF FIGURES ...... x LIST OF TABLES ...... xi CHAPTER 1 ...... 1 1.1 Introduction ...... 1 1.2 The big picture: why we should care about honey bees ...... 6 1.3 Ecology of honey bees and Varroa destructor ...... 8 1.4 Varroa mite IPM (integrated pest management) ...... 13 1.5 The beekeeping industry ...... 16 1.6 Varroa management among backyard beekeepers ...... 20 1.7 Varroa IPM and the Diffusion of Innovation Framework ...... 22 1.8 Drone brood removal ...... 25 1.9 Research Objectives ...... 31 CHAPTER 2 ...... 34 2.1 INTRODUCTION ...... 34 2.2 MATERIALS AND METHODS ...... 41 2.2.1 Study Region ...... 41 2.2.2 Interview Process ...... 42 2.2.3 Survey Administration ...... 43 2.2.4 Data Analysis ...... 44 2.3 RESULTS ...... 45 2.3.1 Survey Response ...... 45 2.3.2 Demographic Characteristics ...... 46 2.3.3 Characterize mite management strategies (Objective 1) ...... 48 2.3.4 Effect of years beekeeping on management and sampling (Objective 2) ...... 55 2.3.5 Effect of sampling on mite management (Objective 3) ...... 57 2.4 DISCUSSION ...... 59 CHAPTER 3 ...... 63 3.1 INTRODUCTION ...... 63 3.2 MATERIALS AND METHODS ...... 68 3.2.1 Study region ...... 68 3.2.2 Experimental design ...... 69 3.2.3 Interview process ...... 73 3.2.4 Survey administration ...... 73 3.2.5 Statistical analysis ...... 74 3.3 RESULTS ...... 76

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3.3.1 Experimental results ...... 76 3.3.2 Interview results ...... 81 3.3.3 Survey results ...... 83 3.4 DISCUSSION ...... 89 CHAPTER 4 ...... 102 LITERATURE CITED ...... 111 APPENDIX A: INTERVIEW GUIDE ...... 120 APPENDIX B: SURVEY INSTRUMENTS ...... 123

LIST OF FIGURES

Figure 1.1 Treatment concepts, (Eur. Group for Integrated Varroa Control 1999). ... 30

Figure 2.1 Number of respondents using the following management techniques...... 51

Figure 2.3 Reported combinations of chemical and mechanical tactics...... 53

Figure 2.4 Number of respondents using the following mite sampling methods...... 54

Figure 2.5 Sampling by beekeepers who reported using “soft” miticides and DBR. . 58

Figure 3.1 Mean number of cells removed during each month...... 79

Figure 3.2 Change in mite levels over the summer for 2015 and 2016...... 80

Figure 3.3 Box plots showing variation in mite levels in August ...... 81

Figure 3.4 Reasons why non-DBR users have not tried DBR (Survey B)...... 86

Figure 3.5 Importance of various factors to management decisions (Survey B)...... 87

Figure 3.6 DBR users who sample by uncapping drones...... 88

LIST OF TABLES

Table 2.1 Description of selected mite management techniques by type ...... 36

Table 2.2 Description of mite sampling techniques...... 37

Table 2.3 Survey and interview demographic characteristics...... 45

Table 2.4 Sampling practices of interviewed beekeepers (n=19)...... 50

Table 2.5 Early and current mite management strategies of interviewed beekeepers. 57

Table 3.1 Aspects of DBR that can be varied according to beekeeper preference. .... 67

Table3.2 Description of experimental sites in 2015 and 2016...... 71

Table 3.3 Number of drone frames and drone cells removed by location...... 78

Table 3.4 DBR downsides, according to interviewed beekeepers...... 83

Table 3.5 DBR variations, according to interviewed beekeepers...... 83

Table 3.6 Two alternative DBR strategies...... 99

CHAPTER 1

Literature Review

1.1 Introduction

The Varroa mite (Varroa destructor) is a highly virulent parasite of the

European honey bee (Apis mellifera). These mites have been linked with elevated levels of colony loss, meaning much higher costs for beekeepers (vanEngelsdorp and

Meixner 2010). They are currently found on every continent except Australia (they arrived in the United States in 1987), and are assumed to infest every colony within that range (Rosenkranz, Aumeier, and Ziegelmann 2010; vanEngelsdorp and Meixner

2010). They also make it very hard (some would argue, impossible), to keep bees successfully without using pesticides to reduce mite populations.

This is a radically new phenomenon in beekeeping: until the 1980s, the only pesticides that beekeepers encountered were the ones used on grain and vegetable crops, which occasionally killed their bees. Beekeepers today have become pesticide applicators themselves. And Varroa have thrust beekeepers and bee researchers into discussions that had long been taking place in other agricultural commodities: how do we control a pest in the short term as well as the long term while minimizing (and hopefully eliminating) reliance on pesticides?

Several of the synthetic miticides developed to control Varroa have lost efficacy due to mite resistance (Rosenkranz, Aumeier, and Ziegelmann 2010).

Experts today recommend an integrated pest management (IPM) approach to controlling mites (Honey Bee Health Coalition 2016). IPM involves combining control tactics based on time of year and observed pest levels: preventative tactics like stock selection, mechanical tactics like brood removal and colony fission, as well as rotating chemical miticides. It also means using chemical options carefully: when they work best, only at certain times of the year or in response to certain pest levels.

And it means using them along with non-chemical alternatives that can reduce the need for pesticides in the first place and, therefore, the chance of generating resistance.

However, IPM is complicated and knowledge-intensive. Chemical miticides can only be applied under certain conditions (Honey Bee Health Coalition 2016) and have very real downsides, including contamination of hive products and sub-lethal effects on bees (Rosenkranz, Aumeier, and Ziegelmann 2010). Cultural and mechanical tactics are especially difficult to execute. To make matters more confusing for beekeepers, there are a number of widely used non-chemical practices – such as powdered sugar dusting and screened bottom boards – that have been shown to be ineffective or minimally effective (Rosenkranz, Aumeier, and Ziegelmann 2010;

Honey Bee Health Coalition 2016) but are widely recommended (eg. Conrad 2013).

Most beekeepers have trouble controlling mites. Mites have been linked with elevated levels of colony loss (Guzmán-Novoa et al. 2010; vanEngelsdorp and

Meixner 2010), and large-scale beekeepers consistently name mites as one of the top causes of colony death (Kathleen V. Lee et al. 2015; Seitz et al. 2015). Small-scale beekeepers in particular are struggling. They suffer exceptionally high rates of winter

loss (almost 50% in recent years), are also less likely to apply miticides, and less likely to identify mites as a cause of colony loss – implying that they do not even know that mites are there (Kathleen V. Lee et al. 2015; Seitz et al. 2015). Beekeepers in regions like the Midwest also suffer from exceptionally high rates of winter loss

(The Bee Informed Partnership 2015e), perhaps because the region is dominated by backyard beekeepers (Daberkow, Korb, and Hoff 2009). Furthermore, media attention around bees observationally has led to an influx of new beekeepers – many of whom want to keep bees without applying chemicals – and the educational infrastructure appears to be struggling to keep pace. This is all complicated by the fact that mites are literally hard to see. Without proper sampling, it is nearly impossible to determine whether high mites caused the death of a colony

(Rosenkranz, Aumeier, and Ziegelmann 2010; vanEngelsdorp and Meixner 2010).

When backyard beekeepers mismanage (or don’t manage) Varroa mites it has severe local and landscape consequences: first, the colony will almost certainly die within two to three years (Rosenkranz, Aumeier, and Ziegelmann 2010). Second, mites are able to invade other hives within (Thomas D. Seeley and Smith 2015) and between (Frey, Schnell, and Rosenkranz 2011; Frey and Rosenkranz 2014) apiaries in a region, meaning that small-scale beekeepers who fail to adequately treat for mites can affect other beekeepers in the region. Finally, high rates of winter loss mean that small-scale hobbyists need to purchase more replacement bees – often from production facilities in southern climates. They thereby spread non-local genetics and probably import hitchhiking mites from Southern to Northern regions (Strange,

Cicciarelli, and Calderone 2008).

Generally, this project is concerned with understanding what Ohio small-scale beekeepers are doing to manage mites, and how beekeeping experience and risk perception (ie. understanding that mites are there) influences mite management practices. As a case study, it also explores in depth a mechanical mite trapping technique called drone brood removal (DBR) that can form a part of a Varroa IPM strategy. This technique is often mentioned in treatment recommendations (eg. Honey

Bee Health Coalition 2016), but remains surprisingly under-used and under-studied in the United States. DBR allows a beekeeper to cull particularly infested portions of their hives to reduce mite levels. Extensive research in Europe during the 1990s showed that DBR can reduce mite levels, and can form a crucial component of a larger pest management strategy involving strong genetics, colony splitting and a fall treatment with organic acids (when needed) (Calis et al. 1999; European Group for

Integrated Varroa Control 1999; Charriere et al. 2003; Imdorf et al. 2003). This particular suite of practices (DBR, brood-less period, organic acids) is still recommended for beekeepers in at least some parts of Europe (Hansen 2007), and

DBR is a common spring management practice among European beekeepers (Evans et al. 2016). Perhaps because studies show that DBR is not effective enough to be used in isolation, American beekeepers have been hesitant to promote it or use it.

However, there is a lot of evidence that DBR is a powerful tool as part of a larger

IPM strategy.

Given the overwhelming influx of new beekeepers who want to control mites

“naturally” without pesticides, it is surprising that this management tactic is not more widely adopted in the United States. The fact that it is relatively labor-intensive and

reduces pesticide use should make it appropriate for and appealing to hobbyists, and has the potential to reduce winter losses for this group. This project aims to re-visit the idea of drone brood removal as a mite management tactic for small-scale beekeepers – and specifically aims to explore whether it would be effective in this region and feasible for use by Midwestern small-scale beekeepers.

The long-term goal of this research project is to help improve Varroa mite control among small-scale beekeepers in the Midwest. The immediate goal is to understand factors that influence small-scale beekeeper mite management (explored in Chapter 2), as well as the practical potential, and application barriers, of a mechanical control method, drone brood removal (DBR), which could ultimately form a component of an IPM strategy (addressed in Chapter 3). The central hypotheses are that beekeeping experience and sampling methods affect mite management, and that DBR reduces mid-summer mite levels in the Midwest, but that labor requirements will be a significant barrier.

The following literature review presents the background and research that support this hypothesis. It will cover 1) The big picture: why we should care about honey bees, 2) Ecology of honey bees and Varroa mites, 3) Varroa mite IPM, 4) The beekeeping industry, 5) Varroa management among backyard beekeepers 6) Varroa management and the diffusion of innovation framework, 7) Drone brood removal and

8) Hypotheses and research objectives.

1.2 The big picture: why we should care about honey bees

Honey bees provide a critical function for agriculture: pollination. Of the 115 leading global commodities, 52 require pollination by bees for fruit or seed set, and another 53 require animal pollination to achieve a complete yield (Klein et al. 2007; vanEngelsdorp and Meixner 2010). And demand for these bee-pollinated crops – mostly high-value fruits, nuts and vegetables – is growing rapidly: in the past half- century, production devoted to pollinator dependent crops grew 4-fold, compared with non-bee dependent production that merely doubled (Aizen and Harder 2009).

Indeed, between 1961 and 2006, agriculture’s dependence on pollinators increased by

50% in the developed world. (Aizen and Harder 2009; vanEngelsdorp and Meixner

2010; Spivak et al. 2011). Without animal pollinators like honey bees, human beings would not starve (staple crops like wheat and corn are pollinated by the wind, not insects) – but it is estimated that 15-42% more land would need to be devoted to affected crops to make up for yield losses, with consequences for the long-term viability of agricultural production (Aizen and Harder 2009; vanEngelsdorp and

Meixner 2010).

Not only have pollinators in general come to play a larger role in our food supply – but honey bees in particular have become critical. Over the past century, agriculture has become increasingly concentrated and mechanized, with simpler crop rotations, greater reliance on chemical fertilizers and pesticides, and a greater concentration of agricultural production on fewer, larger farms (Liebman and Dyck

1993; Brown and Paxton 2009; Winfree et al. 2009; Spivak et al. 2011). Honey bee biology makes them particularly suited for use in large-scale monocultures. Since

they are kept in managed colonies, they can be moved easily from one crop to the next. They are able to pollinate many different crops, and are able to forage over long distances (vanEngelsdorp and Meixner 2010). And as native pollinator communities undergo a precipitous decline – largely a result of landscape changes wrought by chemical-intensive monocultures – honey bees are increasingly needed to fill pollination needs (Winfree et al. 2009; Potts et al. 2009; Spivak et al. 2011).

Although honey bees are well-suited to be an industrial pollinator, industrialized agriculture – particularly large-scale, high input, centralized monocultures – is not good for their health. The impacts on bee health can be grouped into three broad categories:

1. Poor forage. Many of the landscape changes that affect native pollinators

also negatively affect managed honey bees. Chemical fertilizers have replaced

flowering cover crops like clover and alfalfa, more powerful herbicides have

reduced the number of flowering weeds within fields and at field margins, and

many small-scale vegetable patches and pastures have been replaced with

grain monocultures (Winfree et al. 2009; Spivak et al. 2011). All of these

changes have reduced the nutritional landscape for bees.

2. Exposure to toxins. Insecticide used on crops has both lethal and sub-lethal

effects on honey bees (vanEngelsdorp and Meixner 2010; Spivak et al. 2011).

3. New pests and diseases. Globalization has led to the introduction of a

number of new honey bee pests and diseases, including – most importantly –

Varroa mites (Varroa destructor). These pests are often controlled with their

own set of pesticides, which contaminate hive products, create resistance, and

negatively impact the honey bees themselves (Rosenkranz, Aumeier, and

Ziegelmann 2010).

The combination of increasing demand for pollination services, and mounting threats to honey bee health has led some to claim that we are heading toward a

“pollination crisis” (Aizen and Harder 2009). It is critically important that we figure out both how to manage our crops in ways that support bee health – and to manage honey bee pests and diseases effectively and sustainably.

1.3 Ecology of honey bees and Varroa destructor

Varroa mites are widely considered the most damaging pest in modern beekeeping (Rosenkranz, Aumeier, and Ziegelmann 2010). They are so harmful, in part because they are a relatively new parasite of the European honey bee (Apis mellifera). Their native host is the Asian honey bee, Apis cerana, with whom they have a balanced host-parasite relationship: Apis cerana is able to live with Varroa infestations without negative effects (Rosenkranz, Aumeier, and Ziegelmann 2010).

In the mid-20th century, Varroa mites were first detected on European honey bees.

Despite efforts to stop the spread of the mites, they moved east to west across Europe

and arrived in the United States in 1987. They are now found on every continent except Australia, and it is assumed that every colony within that range is infested

(Rosenkranz, Aumeier, and Ziegelmann 2010).

The Varroa mite lifecycle is closely linked with the lifecycle of its honey bee host. Mature female mites latch onto the thorax of adult honey bees and consume their hemolymph. Mites reproduce in the brood cells of developing bee larvae. The female mite crawls into the cell with the larva when it is 10 days old, just before the cell is capped by nurse bees. Once the cell is capped, the female begins to feed on the hemolymph of the developing pupa, and lays a series of eggs. The first egg is male, and the subsequent eggs are female. Once the eggs hatch, the offspring also feed on the developing pupa, and the female mites mate with their brother. When the new bee emerges from the cell, the mated female mites (along with their mother), emerge from the cell (Rosenkranz, Aumeier, and Ziegelmann 2010).

Varroa mites profoundly affect bee health. These effects manifest and compound across three scales: the individual bee, the colony, and the beekeeping industry.

On the level of the individual bee, Varroa parasitism leads to a lower birth weight and shorter lifespan. The mites also vector a number of damaging viruses, including deformed wing virus (DWV) (Rosenkranz, Aumeier, and Ziegelmann

2010). As the name implies, this virus distorts a bee’s wings during development. A classic sign of a Varroa infestation is the presence of young bees with stunted, crinkled wings crawling around the hive. Recently, a group of researchers

demonstrated the importance of V. destructor in the global spread of DWV (Wilfert et al. 2016).

On the colony level, a high Varroa infestation causes colony death. Since the

Varroa reproductive cycle is coupled with that of their host, they tend to experience a similar – though slightly delayed – population peak. Typically, the population of a honey bee colony is lowest in the winter (when the colony does not forage, and remains clustered in the hive for warmth), then increases during the spring, reaches a peak mid-summer, and decreases again throughout late summer and fall. Varroa populations are similarly low in early spring, increase throughout the summer, and then rise sharply in late summer or early fall, just after the honey bee population has reached its mid-summer population peak. This means that the mite population is normally highest when the honey bee population is declining in preparation for winter. Honey bee colonies with high Varroa mite levels in autumn generally perish over the winter – a cumulative result of direct feeding, viruses and a subsequently reduced foraging force (Rosenkranz, Aumeier, and Ziegelmann 2010).

At the national level, Varroa mites have had a profound impact on the US beekeeping industry. Before the introduction of Varroa mites, overwintering losses of

10% (10 out of 100 colonies) were typical. Today, “normal” losses hover around 20-

30% and exceed 50% in some regions (vanEngelsdorp and Meixner 2010). Though these high losses certainly are related to a number of factors – including lack of forage and pesticide exposure – it is clear that Varroa mites play a large role

(Guzmán-Novoa et al. 2010; Rosenkranz, Aumeier, and Ziegelmann 2010;

vanEngelsdorp and Meixner 2010). In addition to higher losses, beekeepers now have to deal with the added expense and labor of treating for mites.

Finally, three aspects of bee-mite ecology particularly affect mite population dynamics in ways that are relevant to beekeepers. The first two point to the role that

DBR could play in an IPM strategy. The third indicates why it is so important to help small-scale beekeepers control mite populations and reduce winter loss.

First, mites strongly prefer male brood. Varroa are distributed over drone and worker cells unevenly: there are on average about 8 times more mites per drone cell than worker cell (Fuchs 1990), and hives with only drone brood have a mite invasion rate 11.6 times higher than hives with only worker brood (Boot et al. 1995; Beetsma,

Boot, and Calis 1999). Mites also reproduce more efficiently in drone brood, producing 5 mature mated female offspring, as opposed to 2 in worker brood

(Dietemann 2012). Models estimate that with 5% drone brood in the hive as many mites emerge from 50-60 drone cells as from 1000 worker cells (David Wilkinson and Smith 2002). The preference for drone brood may stem from a combination of the fact that mites are more likely to encounter available drone cells (since drone cells are 1.7 times larger than worker cells, and have an invasion period 2-3 times longer than worker cells) or the fact that drone larvae are larger than worker larvae and may therefore produce a stronger attractive chemical signal. Mites also may be displaying a preference for drone brood, since drones have a longer pupal stage, and the mite is able to produce more mature mated offspring in drone cells (Boot et al. 1995;

Beetsma, Boot, and Calis 1999). It is interesting to note that on their original host,

Apis cerana, Varroa mites reproduce exclusively in drone brood, and Apis cerana

will entomb highly infested drone pupae before they emerge, killing up to a quarter of reproducing mites (Rosenkranz, Aumeier, and Ziegelmann 2010).

Second: winter loss is all about thresholds. Honey bee colonies can sustain low Varroa mite populations without experiencing negative effects (Rosenkranz,

Aumeier, and Ziegelmann 2010). Indeed, populations of bees that are considered resistant to Varroa mites (Apis cerana, Africanized honey bees and some isolated populations of Apis mellifera) often have Varroa infestations – but those infestations remain at relatively low levels (Thomas D. Seeley 2007). The goal should not be to eliminate Varroa mites, but to keep the fall mite population below a target level. This point is consistent with the central philosophy of IPM – the goal is not to eliminate pests, but to keep their populations below critical economic and ecological thresholds

(Gray, Ratcliffe, and Rice 2008).

Third: mites travel between hives in an apiary, and they travel between apiaries in a region. Studies have shown that honey bees drift significantly between hives in an apiary, causing hives with high Varroa mite populations to infest hives with low Varroa mite populations (Thomas D. Seeley and Smith 2015). Furthermore, studies have shown that Varroa mites are frequently transmitted between apiaries in a region (Frey, Schnell, and Rosenkranz 2011; Frey and Rosenkranz 2014), and suggest that mites can be exchanged when bees steal honey from other colonies (called robbing) (Greatti, Milani, and Nazzi 1992). Even if small-scale beekeepers don’t contribute significantly to pollination or honey production, their pest-management choices can have landscape-level implications.

1.4 Varroa mite IPM (integrated pest management)

Varroa mites have had such a profound impact on US beekeeping in part because they are very hard to control: they have a short generation time, quickly evolve resistance to pesticides, spread between hives rapidly, and are ubiquitous throughout their range. Since they are relatively closely related to honey bees (both arthropods), it is difficult to develop a pesticide that does not also adversely affect bees.

Today, experts recommend a multi-pronged integrated pest management

(IPM) approach to managing mites (Honey Bee Health Coalition 2016). The IPM framework was developed in the 1960s and 1970s in response to concerns over excessive pesticide use (sparked by Rachel Carson’s 1962 Silent Spring), as well as widespread reports of resistance among agricultural pests starting in the 1950s (Dent

2000). Previously, most farmers applied pesticides based on a fixed calendar schedule, whether or not pests were present in their fields. IPM was designed to reduce pesticide use by using observed pest levels to determine whether or not a pesticide needs to be applied – and then only applying the pesticide when pest populations reach economically damaging thresholds. IPM also emphasizes the use of non-chemical alternative techniques (insect pheromones, host-plant resistance, good site design, mechanical controls), in addition to rotating therapeutic controls (applied pesticides) when pests exceed thresholds. It generally involves integrating multiple tactics (preventative and therapeutic) based on the time of year, the conditions, and observed pest levels, in order to keep pest populations below levels that would be

economically damaging while controlling for resistance, reducing the use of chemicals and minimizing environmental impacts.

The move toward IPM in Varroa mite management is also a response to widespread pesticide resistance. When Varroa first arrived in the US in the late

1980s, beekeepers began applying tau-fluvalinate (tradename: Apistan) and amitraz

(tradename: Apivar) in their hives to kill mites. These were followed by other products, including coumaphos (Checkmite+) and fenproximate (Hivastan). However, by the mid-1990s, mites became resistant to tau-fluvalinate (Milani 1994), and today there are reports of resistance to coumaphos and amitraz (Rosenkranz, Aumeier, and

Ziegelmann 2010). These products have also been shown to contaminate hive products, bio-accumulate in wax, and affect bees (Rosenkranz, Aumeier, and

Ziegelmann 2010).

Varroa IPM involves integrating multiple management techniques based on time of year and observed pest levels. It is impossible to gauge the severity (or often even the presence) of a mite infestation by visually inspecting adult bees. Instead, beekeepers can determine pest levels using a number of sampling techniques. These include uncapping drone brood to look for mites (David Wilkinson and Smith 2002), shaking 100ml of bees with powdered sugar to dislodge mites (“powdered sugar roll”) (K.V. Lee et al. 2010), washing a sample of bees in ether or alcohol, or counting the mites that drop through a screened hive base onto a sampling tray

(Dietemann 2012). None of these methods are extremely complicated, but they require extra time and knowledge on the part of the beekeeper.

Once mite levels have been assessed, a number of non-chemical and chemical mite control tools could form a part of a comprehensive IPM strategy. These include

(1) stock selection (beekeepers who use local queens have lower losses, and many beekeepers are working to breed mite resistant traits) (The Bee Informed Partnership

2015f; Rosenkranz, Aumeier, and Ziegelmann 2010) as well as (2) mechanical techniques like colony fission (also called “splitting”, “creating nucs”, or generating

“artificial swarms”), brood interruption, and various forms of brood trapping

(European Group for Integrated Varroa Control 1999). Additionally, (3) a number of natural compounds (sometimes referred to as “soft” miticides (Rosenkranz, Aumeier, and Ziegelmann 2010)) have been shown to reduce mite levels, and could be applied when mite levels exceed thresholds; these include organic acids (oxalic acid, formic acid) and essential oils (thymol, hop oil) (Rosenkranz, Aumeier, and Ziegelmann

2010; Honey Bee Health Coalition 2016). Finally, (4), there are several synthetic chemicals that can be applied to kill mites. See the recent guide by the Honey Bee

Health Coalition for more information on these practices, and when they are most effective (Honey Bee Health Coalition 2016).

Varroa IPM is complicated. It requires a lot of background information and knowledge to understand not only how and when to manage mites, but even how and when (and whether) to sample. Making matters more confusing for beekeepers, there are a number of mite management tactics that were proposed, tested, and shown to be ineffective or minimally effective – but are still widely disseminated in books and on the Internet. These include dusting with powdered sugar (Ellis, Hayes, and Ellis 2009;

Rosenkranz, Aumeier, and Ziegelmann 2010), small-cell foundation (Berry, Owens,

and Delaplane 2010; Thomas D. Seeley and Griffin 2011) and screened bottom boards (Rosenkranz, Aumeier, and Ziegelmann 2010; Honey Bee Health Coalition

2016).

1.5 The beekeeping industry

Before exploring mite management practices and IPM adoption among beekeepers, it is important to step back and take a look at the structure of the broader beekeeping industry in the United States, and a few of the dramatic changes that it has undergone in recent decades.

Honey bee hive management as an agricultural practice is only about 150 years old. Humans have enjoyed taking honey from beehives for millennia, but before the late 19th century, beekeepers had no ability to manipulate colonies, monitor for disease or collect honey without destroying a hive. They either hunted wild colonies, or kept bees in woven “skeps” or hollow log “gums” with minimal intervention. The native range of Apis mellifera stretches from Northern Europe to

Southern Africa and across to Central Asia (Ruttner 1988). European settlers brought honey bees to North America as early as 1620 (Crane 1999). Wild swarms spread across Eastern forests faster than the settlers – as fast as 70km/year – and there are reports that Native Americans could detect the advance of European settlers when they started seeing the “white man’s fly” (Crane 1999). Importing honey bees (as well as cows) was culturally important to settlers in order to fulfill the biblical promise of

a land flowing with “milk and honey”, and also provided essential food, sweetener and candles (Horn 2006).

Almost all of the equipment and techniques that are used by modern beekeepers were invented during the second half of the 19th century (known as the

“golden age of beekeeping”) and have hardly changed since: the moveable frame hive, wax foundation, the smoker, the honey extractor, the shipment of live

“packages” of bees, queen rearing and even queen shipment via mail (Pellett 1938).

All of these changes coincided with increased cultivation of clover and alfalfa on

American farms, which spurred the rapid creation of a honey industry. As soon as true hive management became possible, people began raising bees and selling honey on a large scale: by the 1880s, there were honey producers maintaining over 1,000 hives (Pellett 1938). This story is important as context for understanding present-day honey bee management: in the United States, there is no indigenous honey culture, and there are essentially no relevant pre-industrial hive management practices. Bees went from being a largely unmanaged species – imported by colonists and foraged occasionally by people – directly into our industrializing food system.

However, the structure of the US beekeeping industry has changed dramatically in recent decades, in ways that are highly relevant for understanding

Ohio beekeepers and their management choices. These changes in part reflect broader agricultural trends of consolidation and mechanization, and in part are a response to increasing demand for pollination. They can be summarized into two broad trends:

First, the beekeeping industry has become increasingly consolidated into a handful of very large operations. Between 1982 and 2002, the number of farms

claiming apicultural activity fell by 70%, while the number of honey bee colonies declined by only 20%. According to a review by Daberkow et al. (2009), this discrepancy implies that a large number of beekeepers with very small colony inventories (<25), exited apiculture during this time period (Daberkow, Korb, and

Hoff 2009). By 2002, about 73% of farms claiming apicultural activity kept fewer than 25 colonies – and accounted for roughly 2% of all US colonies. In contrast, fewer than 2% of farms claiming apicultural activity kept more than 2000 colonies but those large farms account for 50% of all colonies in the United States (Daberkow,

Korb, and Hoff 2009). This consolidation reflects a broader trend toward fewer, larger farming operations within US agriculture generally.

Second, beekeeping has become consolidated in geographic regions. As demand for pollination grows, large-scale beekeepers increasingly make a living from pollination fees – most significantly from almond pollination in California. The majority of large-scale beekeepers (and therefore the majority of honey bee colonies) are located in the Northern Plains, Pacific and Mountain regions, closer to regions with large-scale fruit, nut, and vegetable production. In contrast, the majority of small-scale beekeepers (and therefore the majority of all farms claiming apicultural activity) are located in Appalachia, the Northeast and the Corn Belt (Daberkow,

Korb, and Hoff 2009). Again, this trend is part of a broader change in US agriculture, marked by a push toward larger operations consolidated into optimal growing regions. It is also a response to the geographic consolidation of other agricultural industries (such as fruit and nut production in California) – which create a clustered need for large-scale pollination services.

Ohio has a particularly interesting history with the beekeeping industry, which reflects both of these national trends. In the early part of the 20th century, Western

Ohio was home to a large clover-seed industry, and the northern portion of the state was dominated by small-scale pasture-based dairy farms. The blooming clover and flowering legumes that dotted pastures and hay fields provided enough forage to support a robust honey bee population, and Ohio was a large honey-producing state.

In 1940, there were roughly 330,000 colonies registered in Ohio (B. Bloetscher

[ODA, Div. Plant health, Apiary], personal communication, November 29, 2016).

After changes to national agricultural policy under secretary of Agriculture Earl Butz in the early 1970s, the agricultural land in Ohio was gradually converted away from specialized crops and pasture-based dairy, into fencerow-to-fencerow corn and soybeans. The clover-seed industry and small-scale dairy farms disappeared, and the region could no longer support a large-scale honey industry. By the 1980s, the number of registered colonies had dropped to 55,000. By 2014, there were just over

39,000 colonies (B. Bloetscher, personal communication, November 29, 2016).

Today, Ohio – like most regions in the eastern part of the country – is dominated by small-scale beekeepers. In 2015, the Ohio Department of Agriculture registered

4,838 beekeepers and 36,235 hives in the state of Ohio – suggesting an average of 7.5 hives per beekeeper (Ohio Department of Agriculture, Apiary 2015).

Finally, it is important to point out that there are many ways to refer to demographic groups in beekeeping. Throughout the rest of this paper I will generally use categories defined by the Bee informed Partnership (Kathleen V. Lee et al. 2015): backyard beekeepers (50 or fewer hives), side-liners (51-500 hives), and commercial

beekeepers (>500 hives). For the survey and experiment, I included both small-scale beekeepers (<50 hives) and small sideliners (<100 hives). For the interviews, I spoke with both small-scale beekeepers and sideliners (<500 hives).

1.6 Varroa management among backyard beekeepers

While some beekeepers are able to manage mites and sustain low losses, most beekeepers – commercial, sideliners and hobbyists – struggle to control mites. Large- scale beekeepers consistently report Varroa mites as one of the top two causes of colony death (Kathleen V. Lee et al. 2015; Seitz et al. 2015). Research suggests that

Varroa mites are a key driver of colony loss (Guzmán-Novoa et al. 2010;

Rosenkranz, Aumeier, and Ziegelmann 2010; vanEngelsdorp and Meixner 2010).

Backyard beekeepers especially struggle with mites. According to the Bee Informed

Partnership (BIP) national survey, over the winter of 2013-2014, backyard beekeepers lost on average 45.3% of their colonies, compared with commercial beekeepers who lost on average 22.7% (Kathleen V. Lee et al. 2015). In 2014-2015, losses were

44.3% and 22.9% respectively (Seitz et al. 2015). Regions like the Midwest and

North East that are dominated by backyard beekeepers also consistently have much higher rates of winter loss than other regions. In 2014-2015, the Midwest had an average overwintering loss of 50% (the North East, 49%), compared with 25% in the

Southwest, and 39% in the West (The Bee Informed Partnership 2015e). The National

Agricultural Statistical Service reported that in Jan-March 2015, Ohio beekeepers with five or more hives lost 48% of their colonies (“Honey Bee Colonies Report”

2016). While those losses may be due to a number of factors – including pesticide exposure, poor forage and weather – researchers hypothesize that mite management may play a big role (Kathleen V. Lee et al. 2015).

Most of the information on beekeeper management practices comes from the

Bee Informed Partnership (BIP) national management survey, which has been conducted annually since 2010. This project correlates management practices and demographic characteristics with colony loss, and their data is available on their website (https://beeinformed.org/) in addition to publications (most recently Kathleen

V. Lee et al. 2015; Seitz et al. 2015). However, they do not offer data summarizing management practices, showing combination of practices, or relating practices to demographic characteristics. The National Agricultural Statistical Service (NASS) also conducts an annual beekeeper survey, but this survey only documents colony loss, disease loads and honey production – it does not report hive management

(“Honey Bee Colonies Report” 2016).

Overall, among beekeepers surveyed by the BIP, just under half (46%) reported applying a chemical miticide in 2014-2015 (The Bee Informed Partnership

2015g). Only 16% of beekeepers surveyed reported using drone brood removal (The

Bee Informed Partnership 2015c). No information was founding regarding mite sampling.

Small-scale beekeepers have unique mite management pressures and concerns. First, it is important to point out that there has observationally been a huge influx of new beekeepers (perhaps due to media attention around honey bee losses), and the educational infrastructure around beekeeping seems to have struggled to keep

pace. Second, surveyed small-scale beekeepers rarely cite Varroa mites as a cause of colony death (unlike large-scale beekeepers, who name it as a key driver of loss), implying that they may not know that they have a problem (Kathleen V. Lee et al.

2015; Seitz et al. 2015). Third, small-scale beekeepers tend to keep bees with minimal use of chemicals. Over half of surveyed backyard beekeepers reported that they use

“no non-bee derived products”, “only natural products” or “prefer natural products”

(The Bee Informed Partnership 2015a). Furthermore, surveyed beekeepers who reported using chemical miticides owned 162 (+/- se 35) hives on average, compared to 7.6 (+/- se 0.7) on average among those who reported using no miticide product

(The Bee Informed Partnership 2015g). This is promising, since it means that a chemical-reducing IPM strategy should be especially appealing to this population.

However, organic pest management generally requires greater background knowledge than conventional pest management (DeDecker et al. 2014). Indeed, effective non- chemical Varroa management is even more complicated and requires even more background knowledge than general Varroa management.

1.7 Varroa IPM and the Diffusion of Innovation Framework

In order to understand how small-scale beekeepers might adopt more effective mite control strategies, it is useful consider Varroa management through the lens of the diffusion of innovation framework. This model was developed in the middle of the 20th century by rural sociologists working alongside green revolution scientists who studied the spread of agricultural innovations (including idea, practices and

objects). The researchers broke down innovations into two components – the

‘hardware’, or physical components, and the ‘software’, or the background information (Padel 2001). They predicted that innovations spread easily when they are primarily ‘hardware’ based, have clear benefits and minimal costs (Padel 2001).

Innovations that are knowledge-based, with more diffuse or long-term benefits, tend to spread more slowly. A classic example of this type of slow-moving innovation that is heavy on ‘software’ and light on ‘hardware’ is organic agriculture (Padel 2001;

Stofferahn 2009).

Varroa IPM similarly does not fit the mold of a rapidly spreading innovation.

This is because (1) it is complex and information-based, (2) the costs (time and money) are clear, but (3) the benefits are less apparent. This is because mites are literally hard to see, so beekeepers often are often unaware that mites are the cause of colony death. They can easily blame the loss on starvation, harsh weather, or other diseases. It is also impossible to see mites spread to neighboring beekeepers, so the social benefits of mite control are largely invisible. Indeed, as mentioned above, surveyed small-scale beekeepers rarely cite Varroa as a cause of colony death, implying that they may not be aware of the damage mites are doing to their colonies

(or, conversely, the benefits of mite control). Finally, the influx of new beekeepers who have read about honey bee declines and want to keep bees without using chemicals, and the fact that the education infrastructure around beekeeping has struggled to keep pace, may further slow the spread of Varroa IPM.

Past research on the adoption of other complex farming practices (eg. integrated weed management, climate-adapted agriculture, organic practices) can help

us to understand factors that may help farmers to adopt information-intensive innovations. Research has shown that years farming, information-seeking behavior, education level (DeDecker et al. 2014) and risk perception (Tautges, Goldberger, and

Burke 2016) can influence adoption of integrated weed management and that access to information, social networks (Wood et al. 2014), risk perception, risk aversion

(Jain et al. 2015) and efficacy beliefs (believing that behavior can affect outcomes)

(Truelove, Carrico, and Thabrew 2015) impact climate change adaptation among farmers. These factors are consistent with broader theories of behavior, which have moved away from the idea that actions are based in a logical analysis of expected outcomes, and instead have come to acknowledge the impact of peers, emotions, values and heuristics, as well as external opportunities and constraints on behavior

(McLeod et al. 2015). They suggest that in the case of Varroa IPM factors that influence beekeepers’ behaviors may include beekeeping experience (or lack thereof), risk perception (ie. knowing that mites are there), efficacy beliefs (ie. believing that they can reduce losses, and it’s not due to the fact that “the bees are dying”), and access to information.

Of these, the first two – beekeeping experience and risk perception – are particularly interesting. (a) Is the fact that small-scale beekeepers have such trouble controlling mites driven by the fact that there are so many new beekeepers (and mite management is complicated)? In other words, is it simply an artifact of inexperience?

Are beekeepers with more beekeeping experience more likely to manage mites and less likely to use non-validated de-bunked techniques? And/or – on the other hand –

(b) are small-scale beekeepers failing to adequately address the mite problem because

they simply don’t know that they have a mite problem (as past surveys suggest)? In other words, do they have a distorted perception of risk (personal and social) due to mites? Would mite sampling (which would reveal a mite infestation) change behavior? Are beekeepers who sample more likely to use certain mite management tactics?

Chapter two will explore these questions across the following research objectives:

• Objective 1. Explore factors affecting IPM adoption among small-scale beekeepers o Objective 1.1. Characterize mite management practices (including combinations of practices) of small-scale Ohio beekeepers. o Objective 1.2. Test whether there is a relationship between beekeeping experience (years beekeeping) and management practices. o Objective 1.3. Test whether there is a relationship between risk perception (sampling) and management practices

1.8 Drone brood removal

Chapter three will focus on drone brood removal as a case study of a complex non-chemical management tool that could form a component of an IPM strategy (and is recommended as part of Varroa IPM strategies in Europe, as will be discussed below). This technique is interesting because it is one of only a handful of non- chemical mechanical mite control options that have been shown to be effective in the literature. This short list includes other forms of brood trapping (trapping using worker brood, or a trap frame) and colony fission (splitting, or creating an artificial swarm) (Rosenkranz, Aumeier, and Ziegelmann 2010; European Group for Integrated

Varroa Control 1999; Honey Bee Health Coalition 2016). These validated techniques are often listed beside a number of non-chemical techniques that have been shown to

be ineffective or minimally effective, namely dusting with powdered sugar, screened bottom boards, and small-cell foundation, adding to the confusion of beekeepers looking for non-chemical mite control tools. DBR is popular in Europe, but is less common in the United States. This is surprising, given the influx of new beekeepers who want to keep bees without using chemicals. It is therefore an interesting case study of a non-chemical tool that has been well studied in Europe, and has the potential for widespread adoption among small-scale beekeepers in the US.

The mechanism behind DBR is straightforward. It is essentially a trapping method. Because mites show a preference for drone brood, a beekeeper can add a frame or two to the hive that encourages the bees to build drone comb in one area

(large-cell foundation, foundationless frame, shallow frame in a deep box). The beekeeper then waits until the frame is capped, and removes it from the hive. The frame can be scraped clean or frozen to kill the mites, and then put back into the hive.

This process is repeated throughout the summer. It can be thought of as a process of baiting, trapping and removing mites – or a process of concentrating and culling diseased portions of the colony.

Most of the research on drone brood removal was conducted in Europe in the

1990s. Most significantly, in the mid 1990s, Dutch researchers Boot, Beetsma and

Calis conducted a series of experiments testing and calibrating the effects of removing drone brood. They drew on work out of Russia from the 1960s and 1970s, showing that mites invade drone brood more frequently than worker brood, and that removing drone brood can reduce mite levels (Grobov 1977) as well as experiments in Switzerland showing that removing drone brood could significantly reduce mite

populations, and could be integrated with a formic acid treatment (Charriere et al.

2003). They conducted controlled experiments to determine the exact invasion rates of mites into drone and worker brood, and used those rates to generate models. Using their model, they predicted that inserting and removing a drone frame (1500 cells) can reduce mite populations 26.7% (Calis, Boot, and Beetsma 1999). They showed that efficacy dramatically increases when a second drone frame is added one week after the first (50.5 % population reduction), when three drone frames are used (inserted at weekly intervals) (64.1% reduction) or when one or two frames are used during a brood-less period (96.6% and 99.7% reductions respectively) (Calis, Boot, and

Beetsma 1999). They estimated that 462 drone cells would be needed to trap 95% of mites in a 1kg colony that is otherwise brood-less (Boot et al. 1995). That’s equivalent to 2,750 drone cells in a full-size 12kg colony (for comparison, a deep frame contains about 3,400 drone cells (Free and Williams 1975)).

This group of researchers conducted a field trial verifying their model and further testing the idea of combining drone brood removal with a brood break. They inserted drone frames into the hive at weekly intervals to trap mites nearly continuously and, similar to earlier DBR experiments (Charriere et al. 2003), cut out the drone brood to remove it. They found that removing drone brood combined with a brood-less period (by splitting the hive, as part of routine swarm prevention) reduced mite populations by 67-96% depending on how many drone cells were filled (Calis et al. 1999). They recommended combining DBR with spring swarm management, and even designed a DBR method that would combine drone brood removal with a brood break (Calis et al. 1997).

In 1998 and 1999, in response to the first accounts of fluvalinate resistance among mites (Milani 1994), a group of European beekeepers (predominantly from

Sweden, Denmark, the Netherlands, Germany, Switzerland and Italy) had a series of conferences to coordinate efforts on mite control, and come up with approaches that would minimize the use of synthetic chemicals and manage for resistance. Their results are summarized in a comprehensive report (European Group for Integrated

Varroa Control 1999). They concluded that brood trapping is the most effective mechanical form of mite control, and defined three types: “drone brood removal”

(removing drones), “trapping comb method” (removing workers), and “drone brood method” (DBR + a brood break). They concluded that drone brood removal was significantly effective at reducing mites – and most effective when combined with a brood-less period – but that it is not effective enough to forgo a fall miticide treatment. They recommended a general mite management strategy involving spring drone brood removal, summer monitoring, a formic acid treatment in late summer, and a lactic acid treatment in the fall (depending on mite levels) (European Group for

Integrated Varroa Control 1999). See Figure 1.1.

Wilkinson et al (2001), in England, separately modeled drone brood removal, and came to similar conclusions: they showed that reducing drone brood should reduce mite populations, and that drone brood removal would be most effective during a brood-less period (D. Wilkinson, Thompson, and Smith 2001).

Overall, the European researchers used models and experiments to understand how and when DBR is most effective. They showed that DBR reduces mite levels, but not enough to be used in isolation. They also showed that the efficacy of DBR is

increased by: 1) increasing the number of cells removed and 2) combining with a brood-less period. Finally, they recommended a complete IPM management regime integrating drone removal, creating nuclei (splitting), monitoring, and organic acids.

In 2003, the Swiss Bee Research Centre put out a document recommending a very similar mite management regime (Imdorf et al. 2003). And a present-day Danish beekeeping club recommended the same mite management strategy to their members

(Hansen 2007). Today, DBR is commonly used by European beekeepers in the spring

(Evans et al. 2016).

In the early 2000s, a handful of American researchers also explored drone brood removal for mite control. Zachary Huang out of Michigan State designed a system for flash-heating drone brood in the hive to kill mites, which would allow beekeepers to kill drone brood without opening the hive (Huang 2001). Nicholas

Calderone at Cornell showed that a simple application of drone brood removal with two drone frames per hive (freezing the frames) could reduce mite levels (Calderone

2005). Holly Wantuch at North Carolina State tried combining drone brood removal with a “drone receiving” hive to retain genetic diversity (Wantuch and Tarpy 2009), and Dennis vanEngelsdorp at the University of Maryland designed a two-queen tower hive that would allow the beekeeper to access the brood nest (and the drone frame) without removing honey supers (Vanengelsdorp, Gebauer, and Underwood 2009).

Overall, these American researchers seemed more focused on ease of use than efficacy.

Figure 1.1 Two treatment concepts from the “Coordination in Europe of integrated control of Varroa mites in honey bee colonies", final technical report, APPENDIX VI, pgs. 57 (above) and 53 (below). Note: “nucs” refers to “creating nuclei”, another phrase meaning “making splits”, and implying a brood break.

For the present study, we were interested in the practical potential of DBR as a mite control tool for small-scale beekeepers in the United States. I was also interested in testing its efficacy in the American Midwest, where it has never been tested. In order to understand the practical potential of this method – and barriers to use – I conducted an interdisciplinary study involving an on-farm trial in

collaboration with local beekeepers, as well as series of interviews and surveys with

Ohio beekeepers. Chapter 3 describes the results of this research, which aimed to address the following research questions:

• Objective 2. Determine whether drone brood removal could reduce mid- season mite populations in working apiaries in Ohio. o Objective 2.1 Determine the effect of DBR on August mite levels o Objective 2.2 Identify barriers to adoption o Objective 2.3 Characterize how Ohio DBR users implement the method as part of an IPM strategy

1.9 Research Objectives

The long-term goal of this research project is to improve Varroa mite control among small-scale beekeepers. The immediate goal is to characterize mite management practices among small-scale beekeepers, and to understand the practical potential, as well as application barriers of a nonchemical control method, drone brood removal (DBR), as a component of an IPM strategy.

My thesis is that beekeeping experience and risk perception impact small- scale beekeepers’ Varroa management and that DBR could be an effective non- chemical way to reduce mite populations for this group. Specifically, I predict that more experienced beekeepers are more likely to use effective management tools (and to use more management tools), as are beekeepers who sample for mites. I also predict that DBR can reduce mid-summer mite levels, and that labor is a significant barrier to use. The research to support this thesis consisted of a series of interviews and surveys with small-scale beekeepers in Ohio, and an on-farm DBR trial conducted over two summers, in collaboration with six local beekeepers. This

research is uniquely interdisciplinary in that it combines a biological experiment, with quantitative and qualitative social data collection.

It will be organized according to the following objectives. The surveys and interviews will be used to answer Objective 1. The surveys, interviews and experiment will be used to answer Objective 2:

Objective 1. Characterize adoption of Varroa IPM, and test whether it is correlated with experience and/or risk perception. Hypothesis 1. Both beekeeping experience and risk perception influence mite management practices.

1.1 Describe current mite management and sampling practices (including combinations of practices) used by Ohio small-scale beekeepers.

1.2 Test the relationship between beekeeping experience (years beekeeping) and management choices.

1.3 Test the relationship between risk perception (mite sampling) and management choices.

Objective 2. Determine whether drone brood removal could reduce mid- season mite populations in working apiaries in Ohio. Hypothesis 2. Drone Brood Removal can reduce mid-summer mite levels. Labor will be the biggest barrier to adoption.

2.1 Test the effect of DBR on mite levels and hive size in Ohio.

2.2 Identify barriers to DBR adoption.

2.3 Determine how Ohio DBR users implement DBR (what variations do they use? How do they incorporate it into a larger IPM strategy?)

Objective 1 will be addressed in Chapter 2, “Understanding Beekeepers’ use of Integrated Pest Management for Varroa Mites”, and Objective 2 will be addressed

in Chapter 3, “Revisiting drone brood removal for small-scale mite management: an on-farm trial in the Midwest.”

CHAPTER 2

Understanding Beekeepers’ use of Integrated Pest Management for Varroa Mites

2.1 INTRODUCTION

Chapter 2 aims to characterize Varroa management strategies of small and mid-scale Ohio beekeepers, and to test whether there is a relationship between management behavior and (a) beekeeping experience and/or (b) risk perception. My hypothesis is that both beekeeping experience (years beekeeping) and risk perception

(use of accurate sampling methods) correlate with management choices. Before describing the experiment, it is important to re-emphasize several points from the literature review:

First, Varroa IPM is complicated. It involves combining tactics based on pest levels, time of year, bee population dynamics and temperature. Management tools include stock selection (buying bees bred for mite resistant traits), mechanical techniques like brood trapping and splitting, as well as rotating chemical miticides when mite levels exceed thresholds. Integrating tactics is especially important for controlling Varroa mites because they are resistant to several miticides, and no one technique offers complete, long-term protection. See Table 2.1 for descriptions of available management tools. Because Varroa mites are small and spend much of their lifecycle underneath capped bee brood, it is impossible to accurately evaluate the

severity (or even the presence) of an infestation by visually examining adult bees.

Instead, there are a number of sampling methods that can be performed with varying degrees of ease and accuracy to assess mite levels. See Table 2.2 for descriptions of sampling tools. There are many ways to combine Varroa management tools based on sampling results. Some of the most comprehensive IPM plans were developed in the late 1990s by European researchers responding to early reports of miticide resistance.

These “treatment concepts” generally recommended non-chemical mechanical techniques in the spring (drone brood removal and splitting) with organic acid treatments in late summer and fall based on infestation levels (Figure 1.1) (European

Group for Integrated Varroa Control 1999; Imdorf et al. 2003). More recently, the

Honey Bee Health Coalition’s 2016 “Tools for Varroa Mite Management” summarized the efficacy of various management options at different times during the season – making it easier for beekeepers to construct an integrated yearly management plan (Honey Bee Health Coalition 2016).

Table 2.1 Description of selected mite management techniques by type. See Rosenkranz, Aumeier, and Ziegelmann 2010 for a complete review of Varroa mite biology and control. Also see the Honey Bee Health Coalition’s 2016 guide to Varroa management for updated user-friendly information about efficacy and use of management tools.

MITE MANAGEMENT TOOLS Technique Type Description stock selection preventative Several honey bee lines have been selected for Varroa tolerance (eg. "Russian bees") or specific Varroa-tolerant traits like the removal of dead or diseased brood (eg. HYG and SMR queens). These strains display at least partial tolerance to Varroa; however, they do not confer complete or long-term protection against mites, and require supplementary mite management.1 In addition, surveyed beekeepers who kept locally selected queens reported significantly lower overwintering losses than other beekeepers during all four years that the question was asked (2012-2015).2 brood mechanical, Mites reproduce in honey bee brood (larvae + pupae) comb. Withdrawing capped brood trapping preventative cells therefore manually removes mites from the colony. There are two main forms: the trapping comb technique, in which worker cells are removed and the queen is confined to target frames, and drone brood removal (DBR), where only capped drone (male) cells are removed (and the queen is not confined).1 The advantage of DBR is that >8x more mites are found in drone vs. worker cells, and mites reproduce more efficiently in drone cells.3 Studies show that removing two drone frames at weekly intervals can reduce mites populations >50%.4 brood break mechanical, Studies find that swarming reduces mite populations (as long as hives are sufficiently /splitting preventative isolated from each other to prevent additional mite invasions). 5,6 Swarming affects mite levels for two reasons: first, it exports a large portion of the colony's mites, and second, it entails a broodless period where the mites cannot reproduce.5 These results suggest that beekeeping practices like splitting (a practice that mimics swarming, also called "creating nuclei" (singular: nuc) in Europe), or caging the queen (to pause brood production) could disrupt mite population growth. Studies show that combining drone brood removal with a brood break can dramatically increase efficacy (from 50% to >95% MODERATE-HIGH EFFECACY MODERATE-HIGH mite reduction).4,7 organic acids chemical, Several natural compounds (organic acids and essential oils) have been shown to reduce and essential therapeutic/ mite levels, including formic acid (eg. Checkmite+), oxalic acid, thymol (eg. ApiGuard), oils ("soft" applied and hop oil (eg. HopGuard). These compounds have a lower risk of contaminating hive miticides) products or harming bees than synthetic pesticide. However, there are limitations to their use: for instance, high temperatures increase formic acid's toxicity to bees, and oxalic acid is most effective when the colony is broodless (eg. early spring or late fall).1 Lactic acid is used in Europe, but not the United States. synthetic chemical, Four compounds are commonly used in the United States: Coumaphos, an chemicals therapeutic/ organophosphate (eg. Checkmite+), tau-fluvalinate, a pyrethroid (eg. Apistan ), amitraz, a ("hard" applied formamidine (Apivar) and fenpyroximate (eg. Hivastan). Varroa mites became resistant to miticides) fluvalinate over a decade ago. There are reports of resistance to coumaphose and amitraz. There is also evidence that these compounds harm bees and contaminate hive products. 1

screened preventative The wooden hive bottom is replaced with a wire netting bottom board. The idea is that any bottom board mites that fall off of the bees will drop through the screen and not be able to crawl back up into the hive. Screened bottom boards have been shown to have no or little effect on mites, but can be a valuable tool for diagnosing mite population levels (also called "natural mite drop/fall") (see Table 2).1 powdered therapeutic, Dusting a fine powder into the hive was thought to dislodge mites (causing them to fall) or sugar dusting applied induce grooming behavior in the bees (leading them to remove mites).8 Often combined with a screened bottom board, so that fallen mites cannot crawl back into the hive. Has been shown to be ineffective or minimally effective.1 Can be confused with the sugar shake sampling method (also called a "powdered sugar roll") (see Table 2).

LOW-NO EFFICACY EFFICACY LOW-NO small-cell preventative Some honey bee subspecies that are resistant to Varroa (eg. Africanized bees) build comb foundation with smaller cells. It has been proposed that smaller cells may restrict mite reproduction or affect mite invasion of cells. Unfortunately, studies have found no impact on mite levels in 1,9 other subspecies. 1. (Rosenkranz, Aumeier, and Ziegelmann 2010), 2. (The Bee Informed Partnership 2012; The Bee Informed Partnership 2013; The Bee Informed Partnership 2014; The Bee Informed Partnership 2015), 3. (Beetsma, Boot, and Calis 1999), 4. (Calis et al. 1999), 5. (Seeley and Smith 2015), 6. (Loftus, Smith, and Seeley 2016), 7. (Wilkinson and Smith 2002), 8. (Berry et al. 2012), 9. (Seeley and Griffin 2011)

Table 2.2 Description of mite sampling techniques. See Dietemann 2012, chapter 4.2 for a detailed review of sampling methods. Also see the Honey Bee Health Coalition’s 2016 guide to Varroa management for user- friendly information about sampling methods

MITE SAMPLING TOOLS Technique Measures… Description sugar shake adult bee The beekeeper gathers 100ml of bees in a container with a screen lid, and adds two tsbp of infestation powdered sugar. The jar is shaken over a white surface so that any dislodged mites fall through the screen. This gives an accurate estimate of the mite-to-bee ratio in the colony.1,2,3 Also called "powdered sugar roll", can be confused with "powdered sugar dusting" (see Table 1). alcohol wash " Similar to the sugar shake, except ethanol is used instead of powdered sugar. Very accurate. Can also use soapy water instead of alcohol.1,2 ether roll " Similar to the sugar shake and alcohol wash, except ether is used. No longer recommended because highly flammable.1 uncap drone brood Varroa mites reproduce in the brood (larvae, pupae) cells of developing honey bees, and brood infestation are more likely to parasitize drone than worker brood. In order to get a rough estimate of an infestation, a beekeeper can uncap a section of drone brood and count the number of mites. Not extremely accurate, but has been shown to give a rough estimate of infestation level.4 screened natural mite A screened bottom board is installed in the hive, and a sticky board is inserted below the bottom board fall/drop screen. After 48 hrs the screen is removed, and the number of mites that have dropped onto the screen are counted. Also called "natural mite drop". Not extremely accurate but easy and allows a rough estimation of mite levels.1 Ineffective as a treatment method (see Table 1). 1. (Vincent Dietemann 2012), 2. (Honey Bee Health Coalition 2016), 3. (Lee et al. 2010), 4. (Wilkinson and Smith 2002)

Second, hive management among small-scale beekeepers is particularly interesting and important for two reasons: First, small-scale beekeepers comprise the majority of beekeepers in the United States, and are clustered in regions like the

Midwest and Northeast (Daberkow, Korb, and Hoff 2009). Second, small-scale beekeepers suffer from strikingly high rates of colony loss. Over the winter of 2014-

2015, small-scale beekeepers on average lost nearly half (44.3%) of their colonies

(commercial beekeepers lost less than a quarter on average during the same period)

(Seitz et al. 2015). This trend has held true for several years (just over 45% average winter loss in both 2013-2014 and 2012-2013) (Steinhauer et al. 2014; Kathleen V.

Lee et al. 2015), and may explain the exceptionally high loss rates reported in the

Midwest and Northeast (50% and 49% respectively in 2014-2015) (The Bee Informed

Partnership 2015e). While small-scale beekeeper losses are certainly driven by

multiple factors (including pesticides, poor forage and harsh winters), some have suggested that inadequate mite management is a critical element (Kathleen V. Lee et al. 2015). Even though small-scale beekeepers are not essential for crop pollination or honey production in the US, mite management among this population is critical because mites are able to invade other hives within (Thomas D. Seeley and Smith

2015) and between apiaries (Frey, Schnell, and Rosenkranz 2011; Frey and

Rosenkranz 2014), meaning that small-scale beekeepers who fail to adequately treat for mites can dramatically affect other beekeepers on a regional scale.

Not only is mite management important among small-scale beekeepers, but they are unique agricultural decision-makers in several ways. (1) Many of them are inexperienced. There has observationally been a surge of interest in beekeeping

(perhaps due to media attention around bees) and a wave of people buying bees for the first time. (2) Small-scale beekeepers want to keep bees without chemicals. Over half of backyard beekeepers surveyed by the BIP indicated they use “no non-bee derived products”, “only natural products” or “prefer natural products” (The Bee

Informed Partnership 2015a), and surveyed beekeepers who reported using chemical miticides had on average much larger operations (162 hives) than those who reported using no miticides (7.6 hives) (The Bee Informed Partnership 2015g). (3) Small-scale beekeepers are less likely to report Varroa mites as a cause of colony death (Kathleen

V. Lee et al. 2015; Seitz et al. 2015). On the surface this suggests that they don’t have mite problems, but most likely implies that they do not know they have mites. Indeed,

“Do not know” was one of the top reported causes of colony death among backyard

beekeepers (for comparison, commercial beekeepers consistently point to Varroa as one of the top causes of death) (Kathleen V. Lee et al. 2015; Seitz et al. 2015).

Finally, research on the diffusion of agricultural technologies and the adoption of complex farming practices like integrated weed management and climate adapted agriculture shed light on factors that can influence farmer behavior. The diffusion of innovation model – developed by rural sociologists working alongside agricultural scientists during the green revolution – predicted that innovations that spread quickly are easy-to-use physical technologies with clear benefits and minimal costs (Padel

2001). Varroa IPM does not fit this mold because (1) it is information-based, complex and context-dependent, (2) the costs (time and money invested) are clear, and (3) the benefits not always apparent, since mites are hard to see and it is often impossible to tell if a colony has been killed by mites. The literature on adoption of other complex farming practices (eg. organic agriculture, integrated weed management, climate-adapted agriculture) shows a range of factors that affect adoption, including years farming, risk perceptions, efficacy beliefs, farm size, social networks, access to information, and education level (DeDecker et al. 2014; Jain et al.

2015; Truelove, Carrico, and Thabrew 2015; Wood et al. 2014; Tautges, Goldberger, and Burke 2016). This suggests that Varroa IPM adoption among beekeepers may be influenced by factors, including beekeeping experience, mite risk perception

(knowing that mites are there), efficacy beliefs (believing that bee losses can be reduced), apiary size, bee club involvement, access to information about mite management and education level.

There are two important overlaps between the literature on farmer behavior and small-scale beekeeper characteristics: experience and risk perception have been shown to influence management behavior – and small-scale beekeepers may be especially inexperienced and unaware of risk due to mites. This opens up several interesting questions: do more experienced beekeepers use better mite management tools? (And, conversely, do new beekeepers fail to manage mites properly?) Are beekeepers who don’t sample (and therefore don’t know that they have mites), less likely to mange mites? This chapter explored factors influencing IPM adoption by testing the effect of experience and risk perception on management choices.

Research questions. Chapter 2 aims to characterize Varroa IPM adoption among small and mid-scale Ohio beekeepers and understand how management is affected by experience and risk perception. This research sought to (1) characterize mite management strategies and mite sampling techniques used by small and mid- scale beekeepers, including combinations of practices (2) test whether there is a correlation between beekeeping experience and mite management or sampling practices (including the number of practices used, and combinations of practices), and whether (3) there is a correlation between sampling (as a measure of risk perception) and management choices, also including combinations of practices. Specifically, I was interested to see whether there would be a negative correlation between years beekeeping and the use of minimally effective tools or no tools at all (and, conversely, a positive relationship between years beekeeping and the use of effective tools). I also predicted that beekeepers with more experience would combine more mite management tools than those with less experience. Similarly, I was interested to see

whether beekeepers who didn’t use a valid sampling technique were more likely to use minimally effective tools or no tools at all, and whether beekeepers who sampled were more likely to use effective tools (see Table 2.1 and 2.2 for descriptions of sampling and mite management methods). This study is unique in bee research in that it combines quantitative and qualitative data through surveys and interviews. Overall, the aim is to gain a better understanding of how small and mid-scale Midwest beekeepers manage mites. This information can help improve education and support for these beekeepers in order to reduce yearly losses.

2.2 MATERIALS AND METHODS

2.2.1 Study Region

The study took place in central and northeast Ohio, which is dominated by small-scale beekeepers, and suffers from particularly high rates of colony loss. The average number of hives per beekeeper in Ohio surveyed by the BIP in 2014-2015 was 11.2 (+/- SE 2.2) (The Bee Informed Partnership 2015d). This number is only slightly higher than the one reported by the Ohio Department of Agriculture, who registered 36,235 hives in 2015, to 4,838 registrations – implying an average of 7.5 hives per beekeeper (Ohio Department of Agriculture, Apiary 2015).

Ohio has particularly high rates of winter loss – 49.2% average colony loss over the winter of 2014-2015 (The Bee Informed Partnership 2015d). These loss rates are consistent with other states in the Midwest and with loss rates over the past few years – the region as a whole had an average loss of 50% over 2014-2015 (The Bee

Informed Partnership 2015e). The National Agricultural Statistical Service reported

48% colony loss in Ohio from January-March 2015. Nationally, only about 18% of colonies died during that time. However, the 48% loss rate is consistent with other states in the region, such as Kentucky (39%) and Illinois (40%) (“Honey Bee

Colonies Report” 2016). Again, these numbers point to exceptionally high rates of colony loss in Ohio and the Midwest.

2.2.2 Interview Process

Semi-structured interviews were conducted with nineteen local beekeepers.

The interviews covered current and past mite management, sampling practices, and general beekeeping experience. Initial interview subjects were identified by approaching beekeepers at farmer’s markets, personal connections through Ohio

State, and by cold-calling beekeepers listed on bee club websites. Further interview subjects were identified through snowball sampling.

Interviews lasted approximately 30-45 minutes, and were conducted in-person if possible, at a convenient location – subject’s home, restaurant or public space. If an in-person interview was not possible, the interview was conducted over the phone.

The interview consisted of a 9 basic multiple-choice questions (Part A), followed by 7 open-ended questions (Part B). The interview guide is available in Appendix A. Part

B was recorded. These interviews were used to inform survey design and add nuance to survey results.

2.2.3 Survey Administration

Using information from the semi-structured interviews, a 22-question survey was designed (Survey A). The survey had two main sections: the first asked for demographic information and basic information about the beekeeping operation, and the other asked for information on mite management and mite sampling practices.

The survey was reviewed by several honey bee researchers, an anthropologist and a beekeeper. It was distributed at the Ohio State Beekeeping Association (OSBA) meeting in Plain City Ohio on October 31, 2015.

The survey was subsequently modified to add questions about beekeeping philosophy and constraints and was reviewed by honey bee experts and a sociologist.

This second 23-question survey was distributed the Tri-County Beekeeping

Association (TCBA) meeting in Wooster Ohio on March 4, 2016 (Survey B). See

Appendix B for both surveys.

Even though Survey A and Survey B differed on several questions, only questions that were identical or nearly identical between surveys were analyzed as a combined data set (specifically, questions on demographics, sampling and mite management). The advantage of combining the surveys was that I was able to get a larger and more diverse sample of Ohio beekeepers. The questions that remained constant between surveys were located toward the beginning of both surveys, so it is unlikely that differences in survey design would influence results.

2.2.4 Data Analysis

Immediate impressions from the interviews were used to guide survey construction. Interview recordings were also partially transcribed, and organized according to specific subject-areas/”codes” for further analysis.

Objective 1. In order to detect significant differences between survey types/locations, demographic statistics (beekeeping experience and apiary size) were compared between Survey A and Survey B using t-tests. Mite management responses were also compared between surveys using a chi-square test.

Objective 2. The effect of experience on management and sampling was determined using a probit regression. The binary dependent variable corresponded to a management practice or sampling practice (1 indicating use, 0 indicating no use), and was regressed on the independent variable “years beekeeping”. Survey type (A or

B) was used as a covariate. Mite management practices and combinations with over

15 users were tested. Sampling practices with over 15 users were also tested. Finally, linear regression was used to compare years beekeeping against the number of management tactics used.

Objective 3. In order to test the effect of sampling on management, a new variable was created to distinguish beekeepers who used any accurate sampling method (“1”) from those who used no sampling method, or reported only

“observation of adult bees” (“0”) (see Table 2.2 for a list of sampling methods considered accurate). The responses of beekeepers who did or did not sample were compared across all mite management practices with over 15 respondents. When all cells in the contingency table had a value >5, a chi-square test was used to assess

significance. When any cell had a value <=5, Fisher’s exact test was applied. In order to take into account the effect of survey/location (A vs. B) on reported sampling, a chi-square was also performed to test the relationship between sampling and survey type.

2.3 RESULTS

2.3.1 Survey Response

53 surveys were received for Survey A, and 60 for Survey B. Beekeepers with over 100 hives (n=1, Survey A) were removed. For most questions, surveys were combined and analyzed together. For this combined data set, participants from Survey

B who indicated that they also took Survey A (n=12) were removed. This meant that, combined, there were n=100 survey responses (113 total responses – 12 who took both surveys – 1 with over 100 hives) (Table 2.3).

Table 2.3 Survey and interview demographic characteristics compared to statewide statistics from the Ohio Department of Agriculture (ODA), and the Bee Informed Partnership (BIP).

2.3.2 Demographic Characteristics

The average number of hives per beekeeper was significantly greater for

Survey A (12.8) than Survey B (6.3) (t=1.76, df = 147.83, p=0.081). This may be because Survey A was distributed in Central Ohio, a region that is flatter and dominated by large-scale grain agriculture, while Survey B was distributed in

Northeast Ohio, a region that is hillier, with smaller-scale agriculture. It may also reflect urban beekeepers around Cleveland, Akron and Youngstown. The average years of beekeeping experience was not statistically different (t=0.94, df=150.82, p=0.346) between Survey A (mean 11.2 years) and Survey B (mean 7.5 years).

Overall, these numbers are consistent with statewide apiary registration statistics and the results from the 2015 BIP survey (see Table 2.3). By combining surveys from study populations in two different regions of Ohio, I felt that I was able to get a more robust picture of mite management practices in the state.

Interviewed beekeepers tended to have even larger apiaries and more experience than beekeepers in either survey – with 22.8 average years of beekeeping experience, and 111.3 average number of hives (Table 2.3). This is not unexpected, since many interview participants were identified via connections with the university, and it is more likely that beekeepers involved with the university would be more experienced. For interview responses, all beekeeping operation sizes were retained, because the large-scale beekeepers were able to describe management practices that they used when they had fewer hives. The increased experience of interview participants was also valuable because interviewees were able to describe how their

beekeeping practices changed over time, and many had experience interacting with and teaching newer beekeepers.

Other background information: reasons for keeping bees, mite management constraints and information sources. Among respondents to Survey A, just over

61.5% reported making some money from beekeeping, mostly from selling honey

(97% of sellers). They reported an average of 3.6 information sources (+/- 1.9 standard deviation). The vast majority (84.6%) reported getting information on mite management from a bee club, followed by the Internet (55.8%), friends/mentors

(53.8%), magazines (53.8%), books (44.2%), classes (42.3%) and university extension (26.9%). 71.2 % claimed that they had sufficient info on mite management, but only about half (55.8%) said that they were satisfied with their mite management strategy.

In Survey B, these descriptive questions were slightly different. Most respondents (93.3%) reported that their motivation for keeping bees was as a hobby or due to personal interest. This is not inconsistent with the results from Survey A, since many beekeepers who keep bees as a hobby sell a small amount of honey on the side.

Among interviewed beekeepers, most (sixteen out of nineteen) sold honey, about a third (seven) sold nucs and about a quarter (five) sold queens. However, only four out of 19 said that beekeeping was a primary source of income. For information on mite management, most (fourteen) learned from a mentor, almost half (eight) learned through “reading” and just over a quarter (five) cited bee clubs and classes respectively as sources of information.

2.3.3 Characterize mite management strategies (Objective 1)

Overall, “soft” miticides (organic acids and essential oils) were by far the most popular type of mite control – 60% of respondents reported using a soft miticide, followed by 53% who reported using screened bottom boards, 32% who reported using a mechanical technique, and 12% who reported using a synthetic miticide or stock selection. 12% reported using no form of mite management. Among soft miticides, formic acid (33%) and oxalic acid (25%) were the most popular. 20% reported using DBR (Figure 2.1).

Mite management strategies with over 20 responses were compared between

Survey A and Survey B. There was no statistically significant difference in terms of the use of mechanical methods, minimally effective methods, screened bottom boards, formic acid, oxalic acid, some form of mite management, and some legitimate form of mite management (x2 < 2.7, df=1, p > 0.122). There was a statistically significant difference in terms of the use of any miticide and soft miticides (x2 > 6.5, df=1, p < 0.015). Miticide use in general and soft miticide use in particular were higher in Survey A (79% and 73%, respectively, in Survey A; 50% and 46% in

Survey B).

In order to take a closer look at how beekeepers combined practices, I looked at how beekeepers combined miticides, mechanical techniques and stock selection.

The average number of management practices used by beekeepers was 2.14 (+/- 1.46 standard deviation), with a range of 0-6 (Figure 2.2). 25% of beekeepers reported using chemical miticides alone. 18% reported combining miticides with mechanical techniques, and only 10% reported combining mechanical techniques with stock

selection. Few beekeepers combined all three (chemical, mechanical with stock selection) (5%) (Figure 2.3). None of the beekeepers surveyed relied on stock selection alone for mite management – every beekeeper that indicated that they used

“genetics” to control mites also used some form of moderately effective mechanical or chemical mite control. Even though 57% of beekeepers used some form on mite control that has minimal-to-no efficacy, only 9% used one of these methods without also using some type of effective mite control. Overall, 88% of surveyed beekeepers used some form of mite control. Only 21% used either nothing, or only minimally effective methods. Among those who used powdered sugar and screened bottom boards, 19% of beekeepers combined the two (comprising 36% of screened bottom board users, and 83% of powdered sugar users).

The most popular sampling methods were screened bottom boards (51%),

“observation of mite on adult bees” (44%), uncapping drones (29%) and sugar shakes

(21%). Only 8% and 2% of respondents reported using either alcohol washes or ether rolls respectively. 10% of respondents reported using no sampling method at all

(2.6). 21% of beekeepers reported using either no sampling method, or only

“observation of mites on adult bees” (Figure 2.4).

Interview participants were more likely to use brood breaks and stock selection. Over half (11) used a brood break, and about half (10) selected specific genetic stock. Eight beekeepers reported using formic acid, and just over a fifth (Four out of 19) used drone brood removal. Oxalic acid, hop guard, thymol, powdered sugar, screened bottom boards and amitraz were used by three or fewer interview participants (Table 2.5). In terms of sampling, about a third (six) used screen bottom

boards, just over a fourth (five) uncapped drones, about a fifth (four) used sugar rolls and two used an alcohol wash, ether roll and observation each (see Table 2.4). Two interview participants did not understand the difference between using a “sugar shake” as a sampling technique, and using “powdered sugar dusting” as a treatment.

Table 2.4 Sampling practices of interviewed beekeepers (n=19). Sampling methods Users Sugar shake 4 Alcohol wash 2 Ether roll 2 Screened bottom board 6 Uncap drones 6 Observe bees 2

100

Number of respondents of respondents Number 30

0 [Apivar] [Apivar] [Apistan] [Apistan] [Thymol] [Thymol] [Nothing] [Nothing] [Hivistan] [Hivistan] [HopGuard] [Checkmite] [Checkmite] [Oxalic Acid] Acid] [Oxalic 51 [Formic Acid] Acid] [Formic [Brood-break] [Brood-break] "SOFT", ANY ANY "SOFT", "HARD", ANY ANY "HARD", [Stock selection] selection] [Stock [Powdered Sugar]

CHEMICAL, ANY ANY CHEMICAL, [Drone brood removal] [Drone brood removal] MECHANICAL, ANY ANY MECHANICAL, [Small-cell-foundation] [Small-cell-foundation] [Screened bottom board] board] bottom [Screened TOTAL # RESPONDENTS TOTAL MINIMALLY EFFECTIVE, ANY ANY EFFECTIVE, MINIMALLY SOME FORM OF MITE MANAGEMENT SOME FORM OF MANAGEMENT MITE SOME VALIDATED FORM OF MITE MANAGEMENT FORM OF MANAGEMENT MITE VALIDATED SOME [Synthetic] [Organic acids/Essential oils] OVERALL CHEMICAL MITICIDE MECHANICAL GENETIC MINIMAL-NO EFFICACY Figure 2.1 Number of respondents who reported using the following mite management techniques.

Number of mite management tactics used

None One Two Three Four More than four

0 10 20 30 40 50 60 70 80 90 100 Number of respondents

Figure 2.2 Number of mite management tactics used, as reported by survey respondents.

100

40 Number of Respondents of Respondents Number 30

0 One Two Two 53 None Three Three [alone] [alone] [alone] [alone]

[+ chemical] [+ chemical] [+ chemical] [+ mechanical] [+ mechanical] [+ mechanical] More than three three More than [+ stock selection] selection] [+ stock selection] [+ stock CHEMICAL, ANY ANY CHEMICAL, MECHANICAL, ANY ANY MECHANICAL, [+ chemical + mechanical] + mechanical] [+ chemical TOTAL # RESPONDENTS TOTAL [+ chemical + stock selection] selection] + stock [+ chemical [+ mechanical + stock selection] selection] + stock [+ mechanical MINIMALLY EFFECTIVE, ANY ANY EFFECTIVE, MINIMALLY SOME FORM OF MITE MANAGEMENT SOME FORM OF MANAGEMENT MITE OVERALL NUMBER OF TACTICS CHEMICAL MECHANICAL MINIMALLY EFFECTIVE

Figure 2.2 Reported combinations of chemical and mechanical tactics.

100

40 Number of Respondents Number

30 54

0 TOTAL # SOME FORM OF [Sugar Shake] [Ether Roll] [Alcohol Wash] [Mite drop through [Uncap drones] [Observation of mites on JUST observation of [None] RESPONDENTS VALID SAMPLING screened bottom board] adult bees] mites on adult bees (no other sampling method) OVERALL SHAKE METHOD OTHER INACCURATE

Figure 2.3 Number of respondents who reported using the following mite sampling methods.

2.3.4 Effect of years beekeeping on management and sampling (Objective 2)

Effects of years beekeeping were explored across management categories, combinations, and sampling methods with 15 or more users (Figures 2.1, 2.3 and 2.4), using survey type (A or B) as a covariate. In terms of mite management, no significant effect of years beekeeping was detected on any variables. This included the use of a mite management strategy (any), miticides, “soft” miticides, mechanical techniques or non- validated methods, as well as formic acid, oxalic acid, powdered sugar, a brood break,

DBR, powdered sugar or screened bottom boards (-1.5 < z < 0.9, df=95, p>0.14). There was no significant effect of years beekeeping on the number of management techniques used (z=0.15, df=95, p=0.88). Combinations of moderately effective mite management practices (“chemical, alone”, “chemical + mechanical”) were tested against years beekeeping, as were combinations of minimally effective tactics with chemical, mechanical and chemical + mechanical tools. There were no significant relationships (-

1.41.5, df=95, p>0.16).

In terms of sampling methods, no significant effect of years beekeeping was detected for uncapping drones, screened bottom boards, sugar shakes, or use of any accurate method (-1.10.3). There was a significant negative correlation between years beekeeping and “observation of mites on adult bees” as a sampling technique (z=-1.95, df=95, p=0.051).

Interviews. Interview participants were asked to describe how their mite management strategies changed over time. This allowed me to gather nuanced information about how beekeepers make decisions earlier and later in their beekeeping

career (when they have less vs. more experience). Four interviewees started out applying synthetic miticides, and then switched to organic acids or essential oils because they felt that the synthetic chemicals were too harsh, and they wanted to avoid residues. Four started out using some type of miticide (“hard” or “soft”), and switched to only using mechanical techniques and genetics, citing similar concerns over chemical residues and the effect on the bees. On the other hand, three beekeepers started out using only powdered sugar and then switched to miticides, or mechanical techniques because the powdered sugar didn’t seem to work. Others started out using nothing at all, and switched to using mechanical tactics, genetics, soft miticides, or a combination of the three. Overall, seven out of 19 interviewed beekeepers moved away from synthetic chemicals, and only one started using them (Table 2.5). Common reasons cited for changing mite management tactics were harsh chemicals (including effect on bees and residues in hive) (8), and lack of efficacy (mostly associated with powdered sugar use)

(4). Only one beekeeper each cited labor or mite resistance as reasons for adopting a new technique.

Table 2.5 Early and current mite management strategies of interviewed beekeepers (n=19).

Mite management Past Current Change Genetics 1 9 +8 Mechanical 1 12 +11 DBR 1 5 +4 Brood break 1 11 +10 Miticide, any 11 13 +2 "Soft" miticide 6 13 +7 Formic acid 4 9 +5 Oxalic acid 0 3 +3 Thymol 1 2 +1 HopGuard 1 2 +1 "Hard" miticide 6 1 -5 Amitraz 1 1 0 Fluvalinate 5 0 -5 Coumaphos 4 0 -4 Non-validated 5 4 -1 Powdered sugar 4 2 -2 Screened bottom board 2 3 +1 Nothing 7 0 -7

2.3.5 Effect of sampling on mite management (Objective 3)

There was no significant relationship between survey type and whether or not beekeepers sampled (x2=0.081, df=1, p=0.776). For each management category and combination with at least 15 users (see Figures 2.3 and 2.5), the responses of beekeepers who did or did not sample were compared. Statistically significant differences between beekeepers who did and did not sample were found for the use of a “soft” miticide (any)

(x2=4.22, df=1, p=0.04) and drone brood removal (x2=2.75, df=1, p=0.07) (Figure 2.5).

There was no statistically significant difference between beekeepers who sampled and those who did not for the use of a mite management technique (any), a mechanical technique, a non-validated technique, a miticide overall (“chemical, any”), or formic

acid, oxalic acid, a brood break, a screened bottom board or powdered sugar (x2<1.9, df=1, p>0.1). There was also no relationship between sampling and particular management combinations: just chemical tools, chemical and mechanical tools, as well as minimally effective methods combined with chemical tools, mechanical tools, and both (x2<1.4, df=1, p>0.2).

40 Don't sample 30 Sample Number of responses Number 20

0 Use a "soft" miticide (n=60) Use DBR (n=20)

Figure 2.4 Sampling by beekeepers who reported using “soft” miticides and DBR.

2.4 DISCUSSION

These data suggest four key findings:

First, small-scale beekeepers already sample and combine management tactics, indicating that they may be primed to adopt a relatively complex IPM management strategy. Almost 80% of beekeepers reported sampling for mites, and of those, methods that were less accurate but easier to execute were more popular (screened bottom boards and uncapping drones). The majority of surveyed beekeepers used more than one management tactic. However, the most popular combinations involved at least one method that has been shown to be minimally effective (or not effective at all). Only about a fifth of respondents combined mechanical and chemical tools, as has been recommended in IPM plans (European Group for Integrated Varroa Control 1999). This suggests that small-scale beekeepers understand that they need to use multiple management tools, but may not know which tools or combinations are most effective.

Surprisingly, I found that 65% of survey respondents reported using some kind of miticide product, which is much higher than the number reported by the 2014-2015 BIP survey (which found that 46% of respondents applied a miticide product). Looking closer, Survey B responses (50% miticide use) were relatively consistent with BIP results, but Survey A responses (79% miticide use) were much higher. Why were Survey

A respondents so much more likely to apply a miticide? It is possible that the design and context of the survey encouraged different results. Perhaps these results actually indicate a relationship between apiary size and miticide use, since respondents to Survey A reported larger apiaries on average than respondents to Survey B. Or maybe other local factors are at play, including social networks and information sources.

Second, I found no significant relationship between beekeeping experience and mite management. This is consistent with results from the BIP survey, which found no impact of years beekeeping on colony loss during 2013-2014 and 2011-2012

(beekeepers with <1-2 years of experience had slightly higher losses in 2014-2015) (The

Bee Informed Partnership 2012b; The Bee Informed Partnership 2014c; The Bee

Informed Partnership 2015h). It is particularly important to point out that I found no relationship between the use of minimally effective methods (powdered sugar, screened bottom boards, etc.) and years beekeeping. This implies that the use of these methods is not due to inexperience. Interviews revealed that there may be confusion surrounding some of these methods: for instance, two beekeepers (with 8 and 10 years of experience each) were unsure of the difference between a “sugar shake” (an accurate sampling method), and “powdered sugar dusting” (an ineffective management tool) (see Tables

2.1 and 2.2 for descriptions). Overall, these results are important because they suggest that high losses among small-scale beekeepers may not be driven by inexperience, and may indicate broader communication gaps or implementation barriers surrounding mite management.

I did find that there was a significant relationship between years beekeeping and using only “observation” to diagnose mite levels. Perhaps experience does play a factor in beekeepers’ understanding that sampling is necessary to detect an infestation.

Third, I found a relationship between risk perception and management.

There was a significant relationship between mite sampling and the use of “soft” miticides (organic acids/essential oils) as well as drone brood removal. This is encouraging, because it indicates that beekeepers who don’t use intensive management

approaches may not know that they have mites. It also suggests that encouraging beekeepers to sample may lead to more proactive mite management. However, it is important to remember that correlation does not imply causation. It is possible that one group of beekeepers is generally more knowledgeable about mites, and is more likely to both sample and treat. It is also possible that there is some confounding relationship between sampling, management, and apiary size. Nevertheless, it is promising that I detected a relationship between sampling and management behavior.

It is important to point out that the way I grouped beekeepers according to whether they used “accurate” vs. “inaccurate” sampling methods was extremely broad.

They were put into the former group if they reported use of any scientifically supported sampling method (see Table 2.2 for a list), and into the latter if they reported using no sampling method, or only “observation of mites on adult bees”. I did not take into account how often beekeepers sampled, when during the year they sampled, or whether they used the sampling methods properly. I also did not distinguish between sampling methods that are more accurate (sugar shake, alcohol wash, ether roll), and those that are less accurate (uncapping drones, screened bottom boards). I was not able to incorporate these nuances because of survey limitations, but I believe that grouping beekeepers broadly into whether they did or did not report a scientifically validated sampling method is still meaningful as a first step toward understanding the relationship between sampling and management. In future research, however, it would be worthwhile to investigate how sampling type, frequency or timing (all of which contribute to sampling accuracy) affect management behavior.

Overall, a potential weakness of this study is that it collectively analyzed data from two separate surveys. This decision was made because combining the two surveys generated a larger and more diverse sample of beekeepers in Ohio. In order to take into account variation due to survey type/location, this was included as a factor in the analysis. In the future, it would be valuable to explore how other factors like apiary size, social networks, beekeeper preferences and information-seeking behavior affect mite management decisions. For instance, is there a relationship between apiary size and miticide use (as these results suggest)? Do beekeepers who prefer non-chemical methods use more management tools on average? What is the effect of social networks and bee clubs on sampling and management?

In sum, this study found that there is a relationship between risk perception and management behavior – but not between experience and management behavior. Future research is needed to determine whether improved risk perception (via sampling) affects management choices. If this is the case, it suggests that teaching or encouraging sampling would be an effective way to improve management.

CHAPTER 3

Revisiting drone brood removal for small-scale mite management: an on-farm trial in the Midwest.

3.1 INTRODUCTION

In Chapter 2, I broadly explored mite management strategies among small-scale beekeepers, and factors that might be related to management choices. I found that sampling (as a measure of risk perception) correlated with the use of “soft” miticides and

DBR, but that there was no relationship between years beekeeping and the use of any management tactic. In Chapter 3, I take a deep dive into one mite management tool that can form a part of an IPM strategy: drone brood removal (DBR). As mentioned in the literature review, DBR is interesting because it has been shown to reduce mite levels, is often incorporated into IPM schedules and is commonly used in Europe, but has relatively low adoption in the United States. Only 16% of surveyed beekeepers used

DBR in 2014-2015 (The Bee Informed Partnership 2015c). This is surprising, given the interest among American small-scale beekeepers in non-chemical mite control tools.

This chapter can be thought of a case study exploring more nuanced factors affecting the adoption and use of a complex mite control tool among small-scale beekeepers in the

Midwest. In this chapter, I use a biological field experiment, along with interview and survey data, to explore efficacy, perception and use of DBR as a mite management tool.

First, it is important to review how DBR works, when it is most effective and how it has been incorporated into IPM strategies. Here I will also touch on DBR variations described in the literature, and mention some research on using drone brood to sample for mites. All of this information is essential for understanding perceptions and use of DBR by beekeepers.

Drone brood removal (DBR) is a trapping method: the beekeeper baits and removes mites in sacrificial frames of brood. The method leverages the fact that, while mites reproduce in both worker (female) and drone (male) brood cells, they preferentially invade drone brood and have greater reproductive success in drone cells.

There are on average about 8 times more mites per drone cell than worker cell (Fuchs

1990; Beetsma, Boot, and Calis 1999), and mites produce 3 more mature female offspring per cell in drone versus worker brood (Dietemann 2012). Indeed, models estimate that when 5% of the hive consists of drone brood, as many mites emerge from

50-60 drone cells as from 1000 worker cells (David Wilkinson and Smith 2002). In order to take advantage of this preference, a beekeeper using DBR inserts a special frame designed to encourage drone production (eg. large-cell foundation, foundationless frame) near the brood nest. The beekeeper then waits 2-3 weeks until the frame is filled with capped pupae and destroys the contents of the frame (pupae and mites) by scraping the brood cells onto the ground or freezing the entire frame. A new frame is inserted and the process is repeated – thereby attracting, trapping and removing mites throughout the season. It requires that the beekeeper open the brood nest at least once every 2-3 weeks, and so is considered relatively labor intensive. DBR has been shown to reduce mite

levels in field trials (Calis et al. 1999; Charriere et al. 2003; Calderone 2005; Wantuch and Tarpy 2009), and is a popular spring management tool in Europe (Evans et al. 2016).

Models and studies have explored how and when DBR is most effective, giving us clues to how it might be combined with other techniques as part of a larger IPM strategy. For instance, studies show that DBR is most effective when it is combined with a brood break (a period where the queen is not laying eggs, which pauses mite reproduction and is another non-chemical strategy for reducing mite levels). A brood break often naturally occurs when a beekeeper splits colonies (in order to simulate swarming, usually in the spring), or can be artificially created by caging the queen. Calis et al. used a model to predict that inserting and removing a drone frame (1500 cells) can reduce mite populations 26.7%, and showed that efficacy dramatically increases when a second drone frame is added one week after the first (50.5% population reduction), when three drone frames are added at weekly intervals (64.1% reduction) or when one or two frames are used during a brood-less period (96.6% and 99.7% reductions respectively)

(Calis, Boot, and Beetsma 1999). They conducted a field trial verifying their model and found that removing drone brood combined with a brood-less period reduced mite populations by 67-96% depending on how many drone cells were filled (Calis et al.

1999). Wilkinson et al. similarly found that the efficacy of DBR increases during a brood-less period (David Wilkinson and Smith 2002). The fact that DBR is most effective during a brood-less period is not surprising, given that all reproducing mites would be forced to invade the “trap” frame. Studies have also looked at combining DBR with a fall organic acid treatment; Charriere et al. showed that it can significantly reduce mites when combined with a fall formic acid treatment (Charriere et al. 2003).

DBR has been incorporated into several proposed IPM strategies. Perhaps the most robust set of IPM regimes was developed by European researchers in the late

1990s, reacting to early reports of miticide resistance (European Group for Integrated

Varroa Control 1999). In general, they recommended using DBR in the spring, followed by treatment with an organic acid in the fall if mite levels exceed thresholds. Many recommend making splits (also called “creating nuclei”) in the spring in order to create a brood break concurrent with DBR use (Figure 1.1).

In practice, there are several ways that DBR can be implemented. It is important to point out these variations because they can impact labor, inputs and beekeepers’ overall experiences with the method. Specifically, the beekeeper can vary the type of frame used (large-cell foundation, foundationless frame, medium frame in deep box), how the mites are killed (freezing, cutting), and the time of year DBR is applied (Table

3.1). For instance, using large-cell foundation to encourage drone production requires an additional input (specialized foundation). In contrast, putting a medium frame in a deep box or inserting a foundationless frame to encourage drone production, allows the beekeeper to repurpose existing equipment. And killing mites by freezing frames requires ample freezer space; while killing mites by cutting out the drone comb does not.

Furthermore, these factors can impact each other. If a beekeeper chooses to cut out drone brood (rather than freeze), that means that the bees need to draw new wax comb each time the drone frame is replaced. Bees only draw wax in the spring and early summer, so this method could only be implemented in the early part of the season. If the beekeeper freezes the drone frames, in contrast, the wax comb is not destroyed and the method can

be implemented all summer. There are other variations (eg. electrocuting frames to kill mites) (Huang 2001), but they require more specialized equipment, and are less popular.

Table 3.1 Aspects of DBR that can be varied according to beekeeper preference. Large-cell foundation DRONE Foundationless frame FRAME Medium frame in deep box HOW MITES Freeze drone frame ARE KILLED Cut drone cells out of frame Spring-early summer SEASON Mid-late summer All season

Finally, it is important to mention that uncapping a section of drone brood and counting the number of mites underneath has been shown to give a rough indication of infestation level (David Wilkinson and Smith 2002). Accurately estimating pest levels is a critical component of IPM. But because mites are very small and spend much of their lifecycle under capped brood, it is impossible to accurately diagnose a mite infestation by visual examination. Wilkinson and Smith (2002) showed that uncapping drones, while not extremely precise, is accurate enough to inform management decisions. Based on model evaluations, they recommend sampling at least 100, and preferably 200-300 drone pupae every two weeks, and treating when the drone infestation level exceeds

15% (David Wilkinson and Smith 2002).

Research questions. Chapter 3 explores the practical potential of DBR as a mite control tool for small-scale beekeepers in the Midwest United States. I collaborated with six Ohio small-scale beekeepers across eight apiaries to test the efficacy of DBR on-farm

in this region. I also conducted interviews and surveys with Ohio beekeepers to understand how they perceive DBR (potential barriers to use) and how they use it (which variations, what they combine it with). The goals of the chapter were to (1) test the effect of DBR on mite levels and hive strength in Ohio (2) identify potential barriers to use, and (3) understand how beekeepers use DBR (eg. what time of year do they use it? What do they combine it with?). This uniquely interdisciplinary study (combining a biological experiment with qualitative and quantitative social data) is a first step toward understanding the potential benefits and possible drawbacks of DBR for backyard beekeepers in the Midwest

3.2 MATERIALS AND METHODS

3.2.1 Study region

The study took place in central and northeast Ohio. Most beekeepers in this region are small-scale. In 2015, the Ohio Department of Agriculture registered 36,235 hives in the state, managed by 4,838 beekeepers. This implies an average of 7.5 hives per beekeeper (Ohio Department of Agriculture, Apiary 2015). The average number of hives per beekeeper in Ohio surveyed by the Bee Informed Partnership in 2014-2015 was only slightly higher (11.2) (The Bee Informed Partnership 2015d).

Over 2014-2015, Ohio had 49.2% average winter loss (The Bee Informed

Partnership 2015d). This rate is consistent with past years (55% in 2013-2014 and 48% in 2012-2013), as well as other states in the Midwest, which as a region suffered 50%

average loss in 2014-2015 (The Bee Informed Partnership 2015e; The Bee Informed

Partnership 2013b; The Bee Informed Partnership 2014b)

3.2.2 Experimental design

The experiment was conducted on three apiaries in 2015, located in central or central-west Ohio (Delaware, Galloway, and Mechanicsburg). Six, ten and eight hives were kept at each location, respectively. All colonies were overwintered, and received no mite treatment during spring 2015. Total, there were n=12 control hives, and n=12 treatment hives. More information about each site can be found in Table 3.2.

In 2016, the experiment was conducted on five apiaries located in central and northeast Ohio (Delaware, Akron, Sunbury, West Salem and Wooster). Each site contained six experimental colonies (three control, three treatment). The site in Delaware was managed by a beekeeper who participated in 2015, but comprised different hives, at a different location. Again, all colonies were overwintered, and received no mite treatment during spring 2016. Total there were n=15 control and n=15 treatment hives.

See Table 3.2 for more information about sites.

Set-up. On the first visit (mid-May in 2015, late April in 2016), colonies were assessed for size and mite levels (see “mite levels” below), and were divided into two roughly equal treatment groups. One drone frame was placed near the brood nest of each of the treatment colonies. Drone frames were inserted May 13-16 in 2015, and April 24-

May 2 in 2016. Drone frames were inserted earlier the second year so that the bees would draw out the frames more consistently. The frames consisted of large-cell wax foundation (Mechanicsburg), foundationless frames (Delaware, both years), or large-cell

plastic foundation (all other sites). Colony configuration (deep or medium boxes) differed among apiaries, and deep or medium-sized drone frames were used accordingly

(see Table 3.2). The control colonies received no drone frame, except at the Delaware sties, where drone frames were inserted at the start of the study, but never removed

(Table 3.2). The practice of maintaining a drone frame in each hive is consistent with the normal beekeeping practices of the managing beekeeper at those sites.

DBR management. One drone frame was maintained in each hive. Drone frames were removed by the beekeepers when capped, and placed in a freezer for at least 48 hours. Capped frames were replaced with an empty drone frame, or a previously frozen frame. Except for the Wooster site (which was managed by the researcher), all DBR management was conducted by the beekeepers, with regular updates and reminders from the researcher. All colonies were managed normally by the beekeeper, including feeding, adding supers, harvesting honey, and swarm-prevention practices. When any study hives were split, the original queen was left with the study hive. Colonies received no additional mite treatment during the study period (May-Aug. 2015, April-Aug. 2016).

Table3.2 Description of experimental sites in 2015 and 2016. Previous Beekeeper characteristics Num. Drone frame… Site Year Location Surroundings year mite Beekeeper total # # yrs Past DBR study in description type size mngmt. hives beekeeping use? hives control? Organic diversified Delaware Ecological Foundation- 2015 farm, nature DBR A >50 >20 yes 6 Medium yes (site 1) Center less preserve Conventional Beekeeper Large cell 2015 Galloway corn/soy/pasture, Thymol B ~23 7 no 8 Medium no home foundation some wooded areas Conventional Beekeeper Large cell Med. and 2015 Mechanicsburg corn/soy/pasture, Formic acid C ~20 ~20 no 10 no home foundation deep some wooded areas Organic diversified Delaware Theological Foundation- 2016 farm surrounded by DBR A >50 >20 yes 6 Medium yes

71 (site 2) seminary less woods Urban setting, Abandoned Large cell 2016 Akron unmanaged Formic acid D ~30 ~10 no 6 Medium no factory site foundation field/brush Woods and Shallow, Beekeeper Large cell 2016 Sunbury agricultural fields, None E 8 >40 no 6 med. and no home foundation small orchard deep Wooded area next Agricultural Large cell Med. and 2016 West Salem to conventional None F ~25 ~30 no 6 no field foundation deep pumpkin farm University Agricultural Large cell 2016 Wooster research research station, Oxalic acid Researcher / / no 6 Deep no foundation station fields/pasture

Measurements. Once a month, the researcher visited the site to assess hives for mite levels and colony size. In 2015, these assessments occurred May 13-16, June

5-10, July 16-22, and August 13-15. In 2016, they were conducted April 24-May 2,

May 23-30, June 24-July 2, July 27-August 1 and August 15-20. During assessments, colonies were also evaluated for queen status (presence of eggs).

-Mite levels. Mite levels were assessed using the sugar-shake method (K.V.

Lee et al. 2010). Three sugar shakes were performed for each hive in the field, using

100ml of bees (~300 individuals) gathered from three different frames of brood (from the upper brood box, whenever possible). Bees were measured by volume (using a measuring cup) and then placed in a quart-sized jar with a mesh lid. Two tablespoons of powdered sugar were added to each jar, the jar was turned three times, sat for two minutes, and was shaken vigorously for one minute over a white surface. The mites that fell through the mesh lid were counted, and the bees were returned to the hive.

-Hive size. At each assessment, the configuration of each hive was recorded (# boxes, size of boxes). Population size was estimated by counting the number of spaces in between frames that were filled with bees (called “seams”). This allowed for a rapid assessment of hive size. A version of this method is used by the Bee

Informed Partnership Tech Transfer Teams to assess hive size (Andree 2011).

Estimations were made by the same person to reduce variation. As much as possible, hive size assessments were conducted mid-day during good weather.

-Number of capped cells removed. Capped drone frames were photographed by the beekeeper when removed, and sent to the researcher. The number of capped

cells in each photograph was counted (similar to Calderone 2005). This data is reported for descriptive purposes. One photograph of a removed frame from Akron,

July 2016 was lost. In order to get a rough estimate of the number of cells removed, the average was taken of the cells removed from that hive on the previous and following removal dates.

3.2.3 Interview process

Semi-structured interviews were conducted with 19 Ohio beekeepers during

Autumn 2015. Four of the 19 were also beekeepers who participated in the DBR study. Interview participants were identified via cold-calling beekeepers listed on bee club websites, approaching beekeepers at farmer’s markets, and personal connections.

Additional participants were identified by snowball sampling. Interviews lasted 30-45 minutes, and included two sections – 9 basic multiple-choice questions (part A), followed by 7 open-ended questions (part B) addressing past and current mite control practices, as well as attitudes and experiences with DBR. Part B was recorded. The interview guide can be found in Appendix A.

3.2.4 Survey administration

A 22-question survey was designed, based on information gathered in interviews (Survey A). The survey asked about mite management and sampling practices, as well as demographic characteristics (years beekeeping, apiary size, etc.).

The survey was reviewed by several honey bee researchers, an anthropologist and a beekeeper, and was distributed October 31, 2015 to beekeepers at a regional

beekeeping meeting in Central Ohio. The survey was distributed in hard copy in the welcome packet of the meeting.

The survey was subsequently modified to include questions about mite management constraints and drone brood removal use. This 23-question survey

(Survey B) was distributed to beekeepers in Northeast Ohio at a regional beekeeper meeting on March 4, 2016. The survey consisted of two parts – one section concerning general beekeeping and demographic information and one addressing mite sampling and management, including a short section specifically about DBR use. The survey was also distributed in the welcome packet of the meeting.

For both surveys, beekeepers were asked to indicate the mite management tools that they use out of a list of management options (Appendix B, Survey A

Question 10, and Survey B Question B4). For survey B, beekeepers additionally filled out a short section on DBR use, where they were explicitly asked whether they used

DBR, and, if so, which other management tools they combined it with (Appendix B,

Survey B, Questions C1-C4). Both full surveys can be found in Appendix B.

3.2.5 Statistical analysis

All experimental data were tested for equality of variance and normality of residuals. The number of mites in each sugar shake (mites/300 bees) was divided by three to give the number of mites per 100 bees. The 2015 mite data was log- transformed (log10(x+1)) because they were count-data and had heterogeneous variances (Bartlett: p=0.00098, Transformed Bartlett: p=0.2721). Mite data from

2016 were similarly transformed (log10(x+1)). The mean number of mites/100 bees

was then calculated for each hive on each treatment date. One-way and two-way

ANOVAs were conducted to test the effect of treatment (DBR or control) on mite levels. Location was used as a blocking factor if it reduced MSE, otherwise it was left out of the model. Tests were conducted on mite data from the first and last sampling dates for 2015 (May, August) and 2016 (April, August). A repeated-measures

MANOVA was also conducted for all dates in 2015 to test the effect of DBR on mite levels.

Seam data from 2015 and 2016 were not transformed (Bartlett: p=0.4101 and

Bartlett: p= 0.1246, respectively). Two-way and one-way ANOVAs were conducted to compare the effect of DBR on hive size. Location was again used as a blocking factor. Tests were performed for seam data on the first and last sampling dates

Interview recordings were partially transcribed, and then organized according to specific subject-areas/”codes” for analysis.

Combined survey data (using results from Survey A and Survey B) was used to assess how beekeepers combine DBR with other methods, and whether DBR use is correlated with beekeeping experience or apiary size. Results from only Survey B were used to answer questions about barriers to DBR use, as well as how DBR users combine it with other practices. Reported data from Survey B is purely descriptive.

For the combined survey data, the following statistical tests were performed: the relationship between DBR use and survey type was tested using a chi-square test.

Apiary size and years beekeeping were compared between surveys using a t-test. A probit regression was used to test the relationships between DBR use (binary dependent variable), and beekeeping experience (years beekeeping) as well as the size

of the apiary (number of hives) (continuous independent variables). Survey type (A or

B) was used as a covariate. Chi-square tests were used to test for correlations between

DBR use and mite management tactics (a brood break, “soft” miticide, “hard” miticide, genetics, powdered sugar, screened bottom board), as well as mite sampling techniques (use of any sampling method (incl. screened bottom board, sugar shake, ether roll, alcohol wash, uncapping drones), and the use of uncapping drones in particular).

3.3 RESULTS

3.3.1 Experimental results

Year 1. 2015 was an extremely wet summer in Central Ohio, with heavy thunderstorms throughout June and July. Four treatment hives were removed from the study. Two hives in Mechanicsburg were unexpectedly manipulated by the beekeeper in ways that were inconsistent with other hives and sites. In Galloway, frames of drone brood from two hives completely emerged before the beekeeper was able to remove the frame, and so could not be considered to have received a true treatment.

The following analysis for 2015 were conducted on n = 12 control hives and n = 8 treatment hives.

Year 2. 2016, unlike 2015, was an extremely dry summer in Northeast Ohio, with only a few days of rain in June and July. Two treatment hives (in Wooster and

Sunbury) were removed from the study because they did not draw out a sufficient number of drone cells for removal. Coordination was generally more difficult with

five sites: in five hives, over 75% of the drones emerged before a frame was removed

(all hives in Delaware, one hive in Sunbury and one hive in West Salem). Ultimately, two sites were removed from the study because hives did not receive a true treatment

– Delaware, (where all frames emerged) and Sunbury (where only one hive received a true treatment). Two additional treatment hives were removed because the treatment was incomplete – one hive in Wooster that was weak and did not draw any drone cells, and one hive in West Salem that experienced 100% emergence. The following analysis for 2016 was conducted on n = 9 control hives, and n=7 treatment hives, across three sites (Wooster, Akron, West Salem).

Cells Removed. In 2015, an average of 2.75 frames were removed from treatment hives (range: 2-3), with an average of 970.1 cells/frame (range: 109-1661) and an average of 2,697.5 cells total removed per treatment hive (range: 1806-3394).

In 2016, an average of 4.4 frames was removed from treatment hives (range: 3-6), with an average of 981.2 cells per frame (range: 121-2517), and an average of 4296.0 cells total removed per treatment hive (range: 2367-9557) (Table 3.3, Figure 3.1).

Mites. For the treatment hives (n=8), the average increase in mites/100 bees between mid-May and mid-August was 0.94 (SEM=0.55), whereas for the control hives (n=12), it was 2.87 (SEM=0.51) (Figure 3.2). The average number of mites/100 bees mid-August was 1.68 (SEM=0.32) for treatment hives, and 3.3 (SEM=0.53) for control hives (Figure 3.3). Treatment group (DBR vs. control) had a statistically significant effect on mite levels in August (F=5.083, df= 1, 18, p=0.037), but not in

May (F=0.609, df=1, 18, p=0.445). The pattern of change in mites/100 bees over the

four months of the study (treatment by time interaction) was not significantly different between treatment and control (Pillai: F=1.244, df=4,15, P=0.334).

In 2016, the average increase in mites/100 bees between late April and late

August was 1.95 (SEM=0.81) for the treatment hives and 3.19 (SEM=0.71) for the control hives (Figure 3.2). The average number of mites per 100 bees in mid-August was 2.29 (SEM=0.74) for treatment hives and 3.32 (SEM=0.73) for control hives

(Figure 3.3). DBR did not have a significant effect on mite levels in August

(F=1.611, df = 1, 2, 12, p=0.228). In April (at the start of the experiment) the number of mites per 100 bees was higher among treatment colonies (0.33 +/- SEM 0.16) than control colonies (0.14 +/- SEM 0.06) (F=3.674, df= 1,2,12, p=0.079) (Figure 4).

Seams. DBR did not have a statistically significant effect on hive size (number of “seams”) in May or August for 2015 (August: F=0.883, df=1,2,16 p=0.361; May:

F=0.00, df=1,2,16, p=0.985) or 2016 (August: F=0.032, df=1,2,13, p=0.861; April:

F=0.022, df=1,2,12, p=0.884).

Table 3.3 Number of drone frames and drone cells removed by location.

Year Site n Frames removed Cells/frame Total cells removed mean mean +/- SEM mean +/- SEM 2015 Delaware 3 3 941.9 +/- 170.6 2825.7 +/- 288.5 Galloway 2 2.5 846.8 +/- 222.5 2117.0 +/- 191.1 Mechancisburg 3 2.7 1090.6 +/- 150.7 2908.3 +/- 311.0 2016 Akron 2 4 1011.5 +/- 148.3 3948.0 +/- 538.2 WS 3 4.5 712.3 +/- 76.7 3090.5 +/- 723.5 Wooster 2 5 1204.7 +/- 706.7 6023.5 +/- 3533.5

1800.00

1600.00

1400.00

1200.00

1000.00 2016 2015 800.00

mean number of cells removed removed of cells number mean 600.00

400.00

200.00

0.00 May June July August Figure 3.1 Mean number of cells removed for all treatment hives during each month. Error bars indicate SEM.

2015

4.50

4.00

3.50

3.00

2.50

2015 Treatment (n=8) 2.00 2015 Control (n=12)

1.50 Mites per 100 bees 100 bees per Mites

1.00

0.50

0.00 April May June July August -0.50

2016

4.50

4.00

3.50

3.00

2.50 2016 Treatment (n=7)

2.00 2016 Control (n=9) Mites per 100 bees 100 bees per Mites 1.50

1.00

0.50

0.00 April May June July August

Figure 3.2 Change in mite levels over the summer (mean and SEM) for 2015 and 2016.

August 8 6 4 mites per 100 bees 2 0 Control.2015 Treatment.2015 Control.2016 Treatment.2016

Figure 3.3 Box plots showing variation in mite levels in August, for treatment and control hives, 2015 and 2016.

3.3.2 Interview results

19 beekeepers were interviewed. They managed an average of 111.3 hives

(SEM=38.4) with an average of 22.8 (SEM=4.4) years of beekeeping experience. 13 out of 19 managed fewer than 100 hives, and 11 out of 19 managed fewer than 50.

Five indicated that they currently used DBR, and two indicated past (but not present)

DBR use.

Barriers to use. Among all interview subjects, labor was the most common concern about using DBR. Five interview subjects mentioned that they either did not practice DBR because it is too labor intensive (3), no longer use it because of labor

requirements (1) or currently use it, but are concerned about labor (1). One interview subject who used DBR in the past, specifically indicated that he thought it was only appropriate for beekeepers with fewer than 50 hives. Several beekeepers also worried about consistently removing the drone frame before the pupae emerged (which would release all of the “trapped” mites back into the hive). The other beekeeper who used

DBR in the past (but not presently) stopped using the method after he forgot to remove the frames a few times, and realized that nothing bad happened. Now he leaves drone frames in his hives but does not remove them (Table 3.4).

How it is used. Of the five current DBR users, about half (3) used drone cell foundation, and half (2) used foundationless frames. Similarly, about half froze DBR frames (3), while about half cut the drone cells onto the ground (2) Two beekeepers indicated that when they started using DBR, they inserted a shallow or medium frame into a deep, but that they eventually switched to using drone cell foundation or a foundationless frame. One out of the five DBR users described using DBR only in the early part of the season (spring and early summer), while two beekeepers described using it only in mid-late summer. All DBR users combined it with at least one other technique. Most (four) combined it with a brood break, four combined it with stock selection, and three combined it with a “soft” miticide (organic acid or essential oil).

Three out of the five DBR users mentioned that they also use the drone frame to sample for mites (ie. they check for mites by uncapping the drones), and four out of the five DBR users mentioned that they adjust their DBR practice based on sampling results (removing frames with high mite levels, and leaving frames with no detected mites) (Table 3.5).

Table 3.4 Number of interviewed beekeepers who mentioned the following DBR downsides.

Current DBR users Past DBR users Never used DBR Total n 5 2 12 19 Mentioned that DBR is "labor intensive" 1 1 3 5 Worried about consistency removing drones 1 0 1 2

Table 3.5 Number of interviewed DBR users who described using the following DBR variations.

DBR variations Responses n 5 Frame type Drone cell foundation 3 Shallow/med in deep 0 Foundationless frame 2 Mite disposal Freezing 3 Cutting/scraping 2 Schedule Early season use 1 Late season use 2 No season specified 2 Sampling Some sampling method 5 Sampling using drones 4 Adjust DBR based on sampling 4 Combine with… Another technique 5 A brood break 4 Genetics 4 A "soft" miticide 3

3.3.3 Survey results

53 beekeepers responded to Survey A, and 60 to Survey B. Beekeepers with over 100 hives (n=1, Survey A) were removed. 12 respondents to Survey B indicated that they had previously taken Survey A, and so were discarded from the combined data set. The combined data set therefore contained n=100 responses (113 total responses – 12 who took both surveys – 1 with over 100 hives). The average number of hives per beekeeper was greater for Survey A (12.8) than Survey B (6.3) (t=1.76,

df = 147.83, p<0.1), while the average number of years of beekeeping experience between Survey A (average 11.2 years) and Survey B (average 7.5 years) was not statistically different (t=0.94, df=150.82, p>0.3).

For the combined surveys, 20% of beekeepers indicated that they currently use DBR. There was no significant relationship between survey location and DBR use (x2 < 0.01, df = 1, p > .99). There was also no relationship between DBR use and years beekeeping or apiary size (-0.180.53). For Survey B, when beekeepers were asked explicitly “Have you ever used drone brood removal?” and

“Do you still use drone brood removal?” (Appendix B, Survey B, Questions C1 and

C3), 22 respondents indicated that they have used DBR before, and 16 of those 22 indicated that they still use the method. It is interesting to note that only 12 Survey B respondents checked the box for “DBR” when asked to indicate how they manage mites by choosing management options from a list (Appendix B, Survey B, Question

B4).

Barriers to use. Survey B asked non-DBR users to indicate why they do not use DBR, and asked all beekeepers what factors influence their mite management choices (Appendix B, Survey B, Questions C2 and B5). Among beekeepers who had never tried DBR (n=38) the most popular reason indicated for not using DBR was

“no need (happy with current method)” (n=11), “too much labor” (n=9), “don’t want to kill drones” (n=6), and “never heard of it (n=6) (Figure 3.4). Of these barriers, only two – “too much labor” and “don’t want to kill drones” – specifically concern the mechanics of performing DBR. In general, about a fifth of respondents reported that labor (23.3%) or cost (20%) is an “important” or “extremely important” to their

mite management choices. This is compared with two thirds who claimed that reducing chemical use was “important” or “extremely important” and just under half

(46.7%) who reported that using no chemicals at all was “important” or “extremely important” (Figure 3.5).

How it is used. Among the combined surveys, every respondent who reported using DBR indicated using at least one other mite management tool. DBR use was significantly correlated with the use of a brood break (x2 = 2.96, df = 1, p < 0.1) and genetics (x2=9.95, df = 1, p < 0.01), but not the use of “soft” or “hard” miticides (x2 <

0.6, df = 1, p > 0.4). It was also significantly correlated with the use of both powdered sugar and screened bottom boards (x2 > 2.9, df = 1, p < 0.1). There was a significant relationship between DBR use and the use of any mite sampling technique (x2=2.75, df =1, p<0.1). There was also a significant relationship between DBR use and the use of uncapping drones as a sampling method (x2 >13.5, df = 1, p< 0.001). 19 out of 20

DBR users reported using some sampling method and over two thirds (13) of DBR users reported sampling by uncapping drones (Figure 3.6).

In Survey B, past and present DBR users were asked explicitly, “Do/did you combine drone brood removal with any of the following mite control methods?”

(Question C4). Most DBR users reported combining it with some other mite management tactic (17 out of 22 DBR users). Almost half indicated that they combine it with a “soft” miticide (n=10) and almost a third with a brood break (n=8). Only a handful indicated combining it with resistant genetic stock or a synthetic chemical

(n=5 and n=6, respectively).

6 86

Number of respondents of respondents Number 4

0 No need (happy Too much labor Don't want to kill Never heard of it Afraid it won't be Don't know how to with current drones effective enough use it method)

Figure 3.4 Reasons why non-DBR users have not tried DBR (Survey B).

Reducing chemicals

No chemicals 1 Not Important 2

Labor 3 Somewhat Important 4 5 Extremely Important Cost 87

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage of respondents

Figure 3.5 Importance of various factors to mite management decisions (Survey B).

Sampling practices of DBR users (combined survey, n=20)

Sample by uncapping drones Sample using another method Don't sample 88

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Figure 3.6 DBR users who sample by uncapping drones.

3.4 DISCUSSION

Effect of DBR on mite levels and hive size. Consistent with past studies, I found no significant difference in hive size – using “seams” as a proxy – between treatment and control colonies (Charriere et al. 2003; Calderone 2005; Wantuch and

Tarpy 2009). There was a significant difference in August mite levels between treatment and control colonies in 2015, but not in 2016. This result is not inconsistent with past literature, which also shows that DBR results in significant effects but only in some years. The BIP survey found that DBR users in northern states lost significantly fewer colonies than non-DBR users in 2011-2012, 2012-2013 and 2013-

2014 but not in 2010-2011 or 2014-2015 (The Bee Informed Partnership 2011; The

Bee Informed Partnership 2012a; The Bee Informed Partnership 2013a; The Bee

Informed Partnership 2014a; The Bee Informed Partnership 2015b). In a 2005 study,

Calderone found that DBR significantly lowered mite to bee ratios in two study apiaries, but not in a third (Calderone 2005).

However, the question remains: what was different between the two years, and why would DBR have a significant effect in one year but not the other? The pattern of change was similar between years, but the differences were not statistically significant in the second year because the variation was greater overall. Why would there be more variation in mite levels in 2016 than in 2015? First, it is important to point out several limitations of the present study that may explain these differences:

(1) The final sample size was extremely small, due to unexpected execution errors

during the season. This was especially the case in the second summer. (2) Sampling dates were slightly different between the two years – hives were sampled for mites during the second week of each month during 2015, and during the last week of each month (and sometimes the first few days of the following month) in 2016. (3) Sites were different between years. This was deliberate, since it would not have been possible to use the same control and treatment hives a second year, and the cleanest option was to use entirely different sites. However, this does introduce a new source of variation between years. (4) The three final sites in 2016 were located significantly north of the three sites in 2015 (in Northeast vs. Central Ohio), and were also further from each other in a north-south direction. And, (5), The length of the entire experiment differed between years. In 2015, it lasted between mid-May and mid-

August. In 2016, it was an entire month longer, beginning in late April and ending in late August. The final sampling dates are especially critical, because mite levels can change dramatically during later summer/early fall (discussed below). All of these factors may have contributed to the difference in results between years, and to the greater variation in mite levels in 2016.

One additional factor that may explain why DBR was effective in one year but not in the other, is the number of drone cells removed per hive. The total numbers of cells removed from hives in the study was, in general, quite low (average of 2,697.5 cells removed in 2015, and 4,296.0 in 2016). This is consistent with the number removed by Charriere et al. 2003 (just over 3,000 per hive), but is much lower than the average number of cells removed per hive by Calderone 2005 (7,000). Similar to the present study, Charriere et al. used only one drone frame per hive. However, other

studies, including Calderone 2005, used two drone frames per hive (Calderone 2005;

Wantuch and Tarpy 2009; Calis et al. 1999). In general, models have found that the efficacy of DBR increases with the number of cells removed (Calis, Boot, and

Beetsma 1999; D. Wilkinson, Thompson, and Smith 2001). It is possible that inserting and removing only one drone frame withdraws enough mites to make an impact in some conditions but not in others. Indeed, when Wilkinson and Smith

(2001) modeled DBR, they found that removing 1,500 drone cells only delayed high mite levels one month, but removing 3,000 drone cells once a month for four months delayed mites from reaching high levels for 3-4 months and removing 6,000 cells a month delayed the mite population spike for a whole year (David Wilkinson and

Smith 2002). Based on these results, it would make sense to recommend that beekeepers try to insert two drone frames rather than one, and to remove them as soon as they are capped in order to maximize the number of cells removed. These models

(along with experiments) also show that the efficacy of DBR is greatly increased if combined with a brood-less period (Calis, Boot, and Beetsma 1999; David Wilkinson and Smith 2002). Therefore, the inconsistent effect of the present study may be due to the fact that a minimal form of DBR was applied (only about 2,500-4,500 cells removed total, with other brood in the hive), which has been shown to have a smaller effects on mite populations than a more complete implementation of the strategy.

It is also important to understand the significance of August mite levels within the context of yearly honey bee and mite population dynamics, as well as the yearly beekeeping calendar. (1) In general, mite populations grow dramatically between late summer and mid-fall (during and after August). Because mites reproduce in brood,

they experience a population peak slightly after the bee population peak, just as the bee population is beginning to decline in preparation for winter (Rosenkranz,

Aumeier, and Ziegelmann 2010). The ratio of mites to bees in the hive increases as the mites population grows and the number of honey bees declines. (2) There is also high rate of mite transmission during the fall, meaning that colonies can unexpectedly develop quite high mite populations (Frey and Rosenkranz 2014). Between peak nectar flow and the beginning of winter, honey bees frequently invade un-related colonies to steal nectar, a behavior known as “robbing”. Robbing spreads mite infestations, often moving mites from weak or collapsing hives (the ones that get robbed) to stronger hives (the ones that do the robbing) (Greatti, Milani, and Nazzi

1992; Rosenkranz, Aumeier, and Ziegelmann 2010). It can also lead to unexpected spikes in mite populations during the late summer and fall. (3) Late summer and fall – after honey has been harvested – is also typically when beekeepers apply miticide treatments. (4) Finally, in the fall, colonies produce less drone brood, and eventually none, making DBR less feasible and eventually impossible (Free and Williams 1975;

Rowland and McLellan 1987).

In a study on DBR in North Carolina, researchers found that mite levels increased roughly 10-fold between August and September in DBR colonies, and nearly 5-fold in control colonies. They found that DBR colonies had significantly lower mite levels than control colonies earlier in the season, but detected no significant difference in late summer and fall (Wantuch and Tarpy 2009). In contrast, researchers in upstate NY measured the effect of DBR through early October, and found that DBR colonies had significantly lower mite levels on their final sampling

date (Calderone 2005). A study in Switzerland similarly found a significant difference between mite levels in DBR and control colonies in October (Calderone 2005).

Model evaluations by Wilkinson and Smith (2001) found that removing drone brood delayed mite population peaks by one month to one year depending on the number of cells removed. It is therefore probable that we would have seen a dramatic increase in mite levels in September and October – though it is unclear whether the observed difference between treatment and control colonies in 2015 would have persisted (or, conversely, whether mite levels between treatment and control colonies in both years would have diverged). In either case, lower mite levels in August are significant because August typically coincides with the end of the honey harvest and the beginning of the miticide treatment window. Reduced mite levels during this period might increase the efficacy of the miticide treatment or allow a beekeeper to delay treatment. In general, it is important to remember that drone brood removal is recommended as a spring method, and is recommended in combination with a late summer or fall miticide application (Imdorf et al. 2003).

Barriers to use. This simple, on-farm design was chosen because I was interested in the effect of a basic application of DBR in the messy setting of a real- world apiary. The fact that I still found a significant difference between treatment and control hives in one year is quite promising. Overall, this on-farm study was limited because of low control and consistency between study colonies. However, because it was conducted on-farm with beekeepers, it provides valuable information about the barriers and pitfalls to DBR use:

1) The difficulty of drawing out frames. In both years, several hives simply did

not touch the drone trapping frames. Usually, these were relatively small or

weak hives. This is consistent with research showing that hives only allocate

resources toward reproduction (drones) once they reach a critical population

size (Free and Williams 1975; Smith et al. 2014), or amass sufficient

resources (T. D. Seeley and Mikheyev 2003). The time of year can also

influence drone production (Free and Williams 1975; Smith, Ostwald, and

Seeley 2015), since colonies tend to produce the most drones in the early

spring and summer during swarming season, when virgin queens are most

available and reproductive success is highest. This suggests that beekeepers

may have the most success getting the bees to draw out the drone comb during

swarm season, and that they may have difficulty using DBR in small or weak

colonies. Studies also show that hives are more likely to draw out a drone

frame when there is less drone comb elsewhere in the hive (Free and Williams

1975), suggesting that beekeepers may want to destroy extra drone comb

before inserting the trap frame.

2) The importance of not letting drones emerge. One of the hardest parts about

DBR is simply good record-keeping. If a beekeeper allows the drones to

emerge, all of the trapped mites (and their offspring) are released into the

hive. DBR requires that a beekeeper either check the brood box frequently (at

least every 3 weeks), or keep diligent records indicating when the frame needs

to be swapped. It is unclear how drone emergence affects mite levels, though

it is likely that adding extra drone frames (that are left to emerge) without

removing existing drone comb in the hive would lead to elevated mite levels.

In model evaluations, the amount of drone brood in the hive is positively

correlated with mite population levels (D. Wilkinson, Thompson, and Smith

2001). Furthermore, studies have shown that colonies given plentiful drone

frames (at least 20% drone area in the hive) produce more drone comb (Allen

1965) and more drones (Thomas D. Seeley 2002) than colonies where drone

rearing is restricted. However, studies also show that colonies given drone

foundation or foundationless frames build fewer drone cells on worker

foundation elsewhere in the hive (Allen 1965; Thomas D. Seeley 2002). It is

possible that if a beekeeper adds only one drone frame and destroys all other

drone comb in the hive, the total amount of drone comb in the hive will not be

augmented. Future research is needed to quantify the effect of emerged drone

traps on mite populations.

Interview participants identified labor (ie. checking the brood box every 2-3 weeks) as a key factor keeping them from adopting DBR. Several explained that, specifically, they were worried about being able to swap frames at the right time

(before they emerged). This fear seems well-justified, given that seven out of 27 treatment hives were taken out of the experiment because pupae emerged.

Survey participants similarly indicated labor as a key barrier to DBR use.

However, fewer than 25% indicated that labor is important or very important to their mite control choices (compared with, for instance, more than 65% who indicated that

“reducing chemicals” is important or very important). This discrepancy may be due to the fact that beekeepers are not be motivated by labor concerns in theory, but, in practice, labor does limit their management options. Alternatively, these conflicting attitudes toward labor may have to do with the fact that “labor” is a general term, open to interpretation. Perhaps when beekeepers indicate that “labor” is a key barrier to DBR use, they are referring specifically to the logistics of removing frames on time, and the fear of not being able to remove frames consistently. But when they answer a question about “labor” related to beekeeping more generally, they may be thinking about the total time devoted to beekeeping, or the work of lifting and moving hive boxes. Logistics, time and physical work are three very different interpretations of the term “labor”, and should be teased out in future research.

How DBR is used. The results from the interviews and surveys indicate that beekeepers are not using DBR as a single all-in-one mite control, but rather in combination with other mite management techniques, and tailored to the season and the infestation level. All interviewed and surveyed DBR users combined it with some other mite control tool. Across both surveys, DBR use was correlated with the use of other non-chemical management tools, such as a brood break, genetics, screened bottom boards and powdered sugar dusting but not the use of miticides. This suggests that beekeepers who prefer not to use any miticides may be eager to combine multiple non-chemical management tools. When beekeepers from Survey B were explicitly asked what tools they combined with DBR, a third still indicated that they combined it with a brood break, but almost half indicated combining with “soft” miticides. It is unclear whether the conflicting results about combining DBR and miticides are due to

the format of the questions (generally asking beekeepers to indicate the management tools they use – versus explicitly asking what tools they combine with DBR), or whether the discrepancy is due to factors related to survey location. In either case it is promising that there was a correlation between DBR use and a brood break, since performing DBR during a brood-less period dramatically increases its efficacy (Calis,

Boot, and Beetsma 1999; Calis et al. 1999; D. Wilkinson, Thompson, and Smith

2001).

In both the interviews and surveys, there was a strong correlation between

DBR use and sampling, especially sampling by uncapping drones. Most interviewed

DBR users said that they adjusted whether or not to remove a drone frame based on mite levels, and that they use the drone frame itself to sample for mites. Similarly, across both surveys, there was a significant correlation between DBR use and sampling by uncapping drones. In some ways this should not be surprising, since

DBR involves controlling the location of drone brood in the hive, making it easier to find drones for uncapping. However, it is important because it means that beekeepers are using the drone frame as a multifunctional tool: to manage mites (by removing it), and also use to sample for mites (by uncapping it). It also indicates that beekeepers who use DBR employ it in a context-dependent way, calibrating use based on sampling results.

Finally, most interviewed DBR users reported using DBR primarily during only one half of the season (early or late), and letting the drones emerge during the other part of the season. This is especially interesting given that “don’t want to kill drones” was one of the top reasons for not wanting to use DBR cited by survey

respondents: it implies that beekeepers using DBR don’t have to sacrifice all of their drones all of the time. They can selectively sacrifice drones based on the time of year and observed mite levels. It is also interesting given that it may be less labor intensive and less logistically complicated for beekeepers to remove drones during only part of the beekeeping season, rather than needing to maintain an aggressive schedule for the entire season. In other words: DBR users watch the hive closely, and tailor DBR to maximize mite removal while still retaining some drones and keeping labor and logistics at a minimum. This nuanced approach is promising because it incorporates core principles if integrated pest management (tailoring pest management based on time of year and observed pest levels), and because it points toward avenues around adoption barriers (labor, logistics and fear of killing drones).

A closer look at the DBR literature, in light of these interviews, reveals two main DBR “styles” that may be suited to beekeepers with different labor concerns.

They are built around the two different methods for killing mites: cutting out the capped drone cells and discarding them on the ground, or freezing the entire frame:

European researchers (Calis et al. 1999; Charriere et al. 2003), and beekeepers

(Evans et al. 2016) typically cut out the drone brood. The advantage of cutting is that the beekeeper does not need freezer space, and does not need to carry frozen frames back and forth between the freezer and the field. The disadvantage is that the bees need to draw new wax comb for every drone frame, which is energy-intensive, and which is only possible in spring and early summer. The cutting method can therefore only be used in the early part of the season. However, beekeepers are in their hives frequently in the spring is, so using DBR would not add much additional labor during

that time. Indeed, beekeepers who participated in the on-farm study said that using

DBR did not add any extra labor in the spring, because they had to check their hives anyway. It only added labor in the late summer, when they normally would not open the hive as often. This option might be ideal for beekeepers who worry that DBR is too labor intensive, and might be especially appropriate a larger-scale beekeepers, since it doesn’t involve as much logistical planning or carrying around equipment.

European beekeepers typically use DBR only as a spring management tool (Evans et al. 2016).

Table 3.6 Two alternative DBR strategies.

TYPE A B Early season Early season, late season SEASON (spring/early summer) (late summer), or both Foundationless frame OR Foundationless frame OR TYPE OF FRAME medium frame in deep box large cell foundation

MITES ARE KILLED Scraping capped drone cells Freezing capped drone frames BY... onto the ground

Because wax comb is removed, Drone comb isn't destroyed; …which means bees need to draw new comb for bees don't need to draw new that… every drone frame wax comb with each frame.

No equipment to carry, doesn't Can be used in late summer, require freezer space, spring is when bees don't draw wax; bees ADVANTAGES a natural season to use DBR don't use resources to draw new because the beekeeper is wax with each frame already in the hives often Need freezer space, more Can only use when bees will equipment to carry and more draw wax (spring, early DISADVANTAGES complicated logistics (bringing summer), uses resources to frames back and forth between draw wax hives and freezer)

The other approach – centered around freezing – is described in some

American papers (Calderone 2005), and was used by several interview participants.

Freezing the frame does not destroy the wax, so frames can be inserted and removed throughout the summer. Drawing out new wax comb also uses significant hive resources, and freezing the frame (thereby retaining and reusing the wax comb) allows the bees to conserve those resources. However, this method requires significant freezer space, and is more logistically complicated, since the beekeeper has to carry frames back and forth between the freezer and the field. Beekeepers also inspect their hives less often during mid and late summer. Going into the hive to swap a drone frame would constitute extra work during this season, especially if it involves a trip to the freezer. Beekeepers who participated in the DBR experiment found that it became harder to remember to remove drone frames in mid to late summer, since they weren’t in their hives as often. This type of DBR might be appropriate for a beekeeper who wants to apply DBR as intensively as possible, has freezer space, and doesn’t mind a little extra labor (see Table 3.6 for a summary of DBR “styles”).

In short, this study supports previous work showing that DBR can be an effective non-chemical tool to reduce mites – but that it may be less effective when fewer drone cells are removed, and should be combined with other practices to increase efficacy. It shows that current DBR users already use IPM principles, combining DBR with other management techniques and integrating frame removal with sampling. And it points toward two DBR styles that may be appropriate for beekeepers with different labor concerns. Overall, it suggests the importance of

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taking a nuanced view toward mite management, one that addresses not just whether a technique is used, but how – how many frames are inserted, when they are removed, how the mites are killed, etc. It points toward the need for future research on DBR best management practices.

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CHAPTER 4

Conclusions

Through this project, I aimed to identify factors affecting adoption of Varroa

IPM, and to determine whether DBR could reduce mite levels for small-scale Ohio beekeepers. Specifically, I predicted that beekeeping experience and risk perception

(sampling for mites) would affect mite management choices, that DBR could reduce mid-summer mite levels in Ohio, and that labor would be a barrier to DBR adoption.

I found no relationship between beekeeping experience and management choices, but significant relationships between sampling and the use of “soft” miticides (organic acids/essential oils) and DBR. DBR reduced mite levels in one year but not the other and labor was indeed a significant barrier to its use (specifically, the logistics of swapping out frames on time). I also found that DBR users tended to implement the method in a nuanced way; using drone brood to sample for mites, calibrating use based on sampling, and combining DBR with other management tools.

Specifically, in Chapter 2, I found that (1) beekeepers are already using multiple tactics, and prefer “soft” miticides (organic acids and essential oils) and mechanical tactics over synthetic miticides. However, use of non-validated methods is quite common. (2) There was no correlation between years beekeeping and any mite management tactics. This is surprising, because I expected newer beekeepers to

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use less effective management options. However, this is consistent with results from interviews, in which experienced beekeepers still expressed confusion and misinformation about methods. (3) There was a correlation between sampling and the use of soft miticides and DBR. It is unclear whether this means that sampling encourages mite management (and that a limitation to mite management is perception of risk due to mites) – or whether one group of beekeepers is both more likely to sample and more likely to treat. However, it does suggest that there is a link between sampling and treatment, and that perception of risk may impact mite management choices.

In Chapter 3, I found that DBR significantly reduced mites in one year, but not the other. Studies show that efficacy can be increased by boosting the number of drone cells removed, and by combining DBR with a brood-less period (Calis, Boot, and Beetsma 1999; Calis et al. 1999; David Wilkinson and Smith 2002). Labor was identified as a key barrier to use. Specifically, beekeepers worried about removing drone frames before the pupae emerged. During the on-farm experiment, I also encountered difficulties removing frames before emergence so this fear is not misplaced. I found that DBR users tended to combine DBR with other management tools, especially other non-chemical tools like a brood break. They also calibrated use based on sampling results, particularly sampling by uncapping drones.

Together, these results suggest a couple of interesting directions for drone brood removal specifically, and for mite management more generally among small- scale beekeepers. They also have broader implications for science literacy and landscape-level approaches to mite management:

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First, drone brood removal should not be thought of as a simple, applied treatment. Rather, it changes the structure of the hive (adding a drone frame, which consolidates drone brood), giving beekeepers an additional tool for monitoring and manipulating colony dynamics. This drone frame is multi-functional – beekeepers can use it to sample (uncap the pupae to estimate mite levels), and to treat (based on mite levels, they can decide to replace the frame and thereby remove a batch of mites).

This dual function is consistent with how surveyed and interviewed beekeepers used

DBR. DBR is similar to other forms of non-chemical pest control more generally in that it is (1) not a silver bullet, but its efficacy depends on how it is used and how it is combined with other treatments, (2) it is a preventative rather than a therapeutic control and (3) it is multi-functional, with multiple benefits (sampling, mite removal) for the beekeeper.

Furthermore, DBR is important because it might be an appealing option and a gateway to integrated mite management for small-scale beekeepers who might otherwise use no mite control. An approach known as the “live and let die” or “Bond” method (Fries and Bommarco 2007) has anecdotally become quite popular among small-scale beekeepers in recent years. This method essentially involves leaving the hives alone (with no mite control), in order to “breed mite resistant bees”. If a hive dies, it is because it is “weak”, not resistant to mites, and should die anyway. If a hive lives, it is presumed to be resistant to mites. In theory, and in an isolated environment, this method might lead to mite resistance, because it creates selective pressure on hives (Fries and Bommarco 2007). But in practice, and applied piece-meal, what it does is amplify and spread mite infestations. In addition, many beekeepers buy

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replacement bees from Southern states – meaning that not only are they spreading non-local genetics, but they are cycling mites (which inevitably hitch a ride with the new bees) from Southern to Northern regions (Strange, Cicciarelli, and Calderone

2008).

Organic crop farmers don’t simply withhold chemical applications –they use a suite of management practices that manipulate the farm system to reduce the chance of pest outbreaks. These include selecting resistant cultivars, using cover crops and green manures, adjusting planting dates, rotating crops, planting buffers, using trap crops, tilling etc. (see Kremen and Miles 2012 for some examples). There is similarly a suite of beekeeping practices that can manipulate the system to reduce mite outbreaks. These might include selecting resistant stock, planting good forage (for good honey bee nutrition), isolating hives from neighbors (to reduce incoming mites), frequent splitting (which breaks mite reproductive cycles), brood trapping (including

DBR) and selective breeding for mite resistance based on measured mite levels or mite resistant traits (European Group for Integrated Varroa Control 1999;

Rosenkranz, Aumeier, and Ziegelmann 2010). In short, non-chemical mite management may be possible, but will take active management on the part of the beekeeper (just like organic crop management requires more labor by farmers).

The nuanced view of DBR described by interviewed beekeepers (integrating drone sampling and removal) suggests how DBR may be appealing to “live and let die” beekeepers – and might become a gateway to more active might management. If beekeepers sample drone brood and only remove highly infested drones, they are also removing mite-susceptible drones from the local gene pool. If the drones have low (or

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no) mites, they are allowed to emerge, and the beekeeper releases what may be more resistant genetic stock. And if using a drone frame makes sampling easier, it will help beekeepers understand which hives have low versus high mites, and allow them to be more selective about retaining or removing colonies – or might spur them to adopt more active mite management practices.

More generally, the results of this study suggest two important findings about mite management and Varroa IPM: (A) it is not a lack of experience problem, but potentially a larger communication problem. Part of this communication problem might rest on clarifying which methods work and don’t work – especially which non- chemical methods are most and least effective. (B) There is a correlation between sampling and management, suggesting that there is a relationship between risk perception due to mites and management behavior among small-scale beekeepers.

Further research is needed to determine whether sampling practices influence management choices, or whether the observed relationship is due to other factors

(some beekeepers may be more likely to both sample and treat, or there may be confounding factors like apiary size or social networks). Understanding whether there is any causation underlying the observed correlation is important, because if risk perception spurs more active management behavior, it would suggest that teaching and encouraging mite sampling could help beekeepers to understand risks, and adopt pro-active mite management strategies.

This study also points to the need for more research on the role of social networks (specifically, bee clubs) in the adoption and spread of Varroa management tools. During interviews, it became clear that beekeepers from different bee clubs

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shared views on mite management (both correct and incorrect), and survey respondents at the Central Ohio meeting were far more likely to use miticides than those at the Northeast Ohio meeting, suggesting that there may be local factors at play. It would be valuable to explore how beekeeping information is communicated through bee clubs, and to understand what makes bee clubs purveyors of sound – or unsound – beekeeping advice. More broadly, this line of research could explore the effects of social pressure and culture on how beekeepers understand beekeeping and their bees. Furthermore, while much of the rationale for this study drew on the observation that there is currently a major influx of new beekeepers (derived from countless conversations with beekeepers and bee researchers), there is a need to quantify and describe this apparent trend in order to better understand its size and scope.

Even more broadly, this study allows us to explore themes of science literacy.

The “Bond” approach to beekeeping may be a result of the influx of new beekeepers who seek a sustainable lifestyle and want to keep honey bees as “naturally” as possible by leaving them alone. However, this attitude belies a deep misunderstanding of how sustainable agriculture is practiced, and the relationship between honey bees and humans. Honey bees are far from “natural” in the United

States. They were imported to North America by European settlers in the 1600s along with cattle and other livestock (Horn 2006). The rectangular boxes in which most beekeepers keep bees are far larger than nests found in the wild (Simpson and Riedel

1963; T. D. Seeley and Morse 1976 cited in Loftus, Smith, and Seeley 2016). And to produce excess honey, beekeepers must maintain artificially large hives. Furthermore,

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as described above, sustainable agriculture is not about leaving the farm system alone.

Rather, it is about using ecological knowledge to manipulate the system in order reduce pest outbreaks, increase nutritional quality and maximize yield using minimal external inputs – benefiting the farmer and the community in the long run. (This is in contrast to conventional or “green revolution” approaches which rely on external inputs to increase fertility and reduce pests). The possible proliferation of the “Bond” approach suggests that more work needs to be done to effectively communicate what sustainable or organic agriculture involves (that it does not simply mean withholding chemicals). And it points to the need for future research to explore not only how common the “Bond” approach actually is, but also how backyard beekeepers’ understanding of nature and sustainability influences their views on honey bees. It would also be important to take into account the way the Internet is a source of information – and misinformation – about beekeeping, sustainable agriculture and other environmental concerns. This type of research might help us to understand why people decide to start beekeeping, how environmental ethics might affect their mite management choices, and – more broadly – how people are understanding and engaging with ideas of sustainability.

Finally, it is important to zoom out biologically and reconnect mite management to landscape change. It has been documented that mites spread easily among hives within (Thomas D. Seeley and Smith 2015) and between apiaries (Frey,

Schnell, and Rosenkranz 2011; Frey and Rosenkranz 2014). I mentioned this at the outset of the thesis as an argument for why mite management is important for small- scale beekeepers who are not otherwise critical to the honey or pollination industries,

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but it is worth considering in more depth here. Studies show that mites can spread when bees drift into the wrong hive (Thomas D. Seeley and Smith 2015), when bees rob nectar out of unrelated hives (Rosenkranz, Aumeier, and Ziegelmann 2010), and potentially when foragers encounter one another on flowers. It is therefore possible that the decrease in floral resources over the past few decades (due to agricultural intensification, increased herbicide and fertilizer use as well as urbanization), has not only reduced the diversity and quantity of nutrition available for honey bees, but has also led to greater crowding on the remaining floral resources, potentially increasing the chances for mite transmission between un-related foragers. Not only that, but nectar scarcity causes greater robbing activity (Greatti, Milani, and Nazzi 1992;

Downs and Ratnieks 2000), further increasing chances for mite transmission. Future research is needed to determine the most significant routes of mite transmission

(drifting, robbing and/or foraging), and potential avenues for reducing transmission.

These might include tactics to reduce drifting between hives (painting hives different colors, facing them in different directions), reduce robbing (potentially planting floral resources that bloom during periods of low nectar flow, or feeding intensively), or reduce the chance of transmission on flowers (also by increasing floral resources).

These questions are clearly outside the scope of this thesis project, but it is important to consider mite management among individual beekeepers within the context of landscape-level dynamics and the potential effects of land-use change on disease transmission.

In short, this study points to the fact that small-scale beekeepers are eager to control mites effectively while reducing chemicals, but struggle to implement

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effective strategies. These results suggest that DBR could be an effective management tool for small-scale beekeepers, but that it should be applied in an intensive way and combined with other management tools for maximum efficacy.

They imply that a strategy to help small-scale beekeepers become better pest managers should include: effective communication for all beekeepers (not just new beekeepers), emphasizing effective vs. ineffective mite management tools, and possibly stressing sampling for mites. Future research is needed to determine IPM and DBR best management practices, and the most effective outreach and education tactics for small-scale beekeepers.

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LITERATURE CITED

Aizen, Marcelo A., and Lawrence D. Harder. 2009. “The Global Stock of Domesticated Honey Bees Is Growing Slower Than Agricultural Demand for Pollination.” Current Biology 19 (11): 915–18.

Allen, M. Delia. 1965. “The Effect of a Plentiful Supply of Drone Comb on Colonies of Honeybees.” Journal of Apicultural Research 4 (2): 109–19.

Andree, Michael. 2011. “Frames of Bees | Bee Informed Partnership.” September 15. https://beeinformed.org/2011/09/15/frames-of-bees/.

Beetsma, J., W. J. Boot, and J. Calis. 1999. “Invasion Behaviour of Varroa Jacobsoni Oud.: From Bees into Brood Cells.” Apidologie 30 (2).

Berry, Jennifer A., William B. Owens, and Keith S. Delaplane. 2010. “Small-Cell Comb Foundation Does Not Impede Varroa Mite Population Growth in Honey Bee Colonies.” Apidologie 41 (1): 40–44.

Boot, W. J., J Schoenmaker, JNM Calis, and J Beetsma. 1995. “Invasion of Varroa Jacobsoni into Drone Brood Cells of the Honey Bee, Apis Mellifera.” Apidologie, Springer Verlag (Germany), 26 (2): 109–18.

Brown, Mark J. F., and Robert J. Paxton. 2009. “The Conservation of Bees: A Global Perspective.” Apidologie 40 (3): 410–16.

Calderone, N. W. 2005. “Evaluation of Drone Brood Removal for Management of Varroa Destructor (Acari: Varroidae) in Colonies of Apis Mellifera (Hymenoptera: Apidae) in the Northeastern United States.” Journal of Economic Entomology 98 (3): 645–50.

Calis, J. N. M., W. J. Boot, and J. Beetsma. 1999. “Model Evaluation of Methods for Varroa Jacobsoni Mite Control Based on Trapping in Honey Bee Brood.” Apidologie (1999) 30 30 (2–3).

Calis, J. N. M., W. J. Boot, J. Beetsma, J. H. P. M. van den Eijnde, A. de Ruijter, and J. J. M. van der Steen. 1999. “Effective Biotechnical Control of Varroa: Applying Knowledge on Brood Cell Invasion to Trap Honey Bee Parasites in Drone Brood.” Journal of Apicultural Research 38 (1–2): 49–61.

111

Calis, J. N. M., J. Schmidt-Bailey, J. Beetsma, W. J. Boot, J. H. P. M. van den Eijnde, S. Fuchs, A. de Ruijter, and J. J. M. van der Steen. 1997. “Successful Trapping of Varroa Jacobsoni with Drone Brood in Broodless Apis Mellifera Colonies.” Apiacta.

Charriere, J. D., A. Imdorf, B. Bachofen, and A. Tschan. 2003. “The Removal of Capped Drone Brood: An Effective Means of Reducing the Infestation of Varroa in Honey Bee Colonies.” Bee World 84 (3): 117–24.

Conrad, Ross. 2013. Natural Beekeeping: Organic Approaches to Modern Apiculture, 2nd Edition. Chelsea Green Publishing.

Crane, Ethel Eva. 1999. The World History of Beekeeping and Honey Hunting. Routledge.

Daberkow, Stan, Penni Korb, and Fred Hoff. 2009. “Structure of the US Beekeeping Industry: 1982-2002.” Journal of Economic Entomology 102 (3): 868–86.

DeDecker, James J., John B. Masiunas, Adam S. Davis, and Courtney G. Flint. 2014. “Weed Management Practice Selection Among Midwest U.S. Organic Growers.” Weed Science 62 (3): 520–31.

Dent, David. 2000. Insect Pest Management. CABI.

Dietemann, Vincent. 2012. “Standard Methods for Varroa Research.” Journal of Apicultural Research 52 (1): 1–54.

Downs, Stephen G., and Francis L. W. Ratnieks. 2000. “Adaptive Shifts in Honey Bee (Apis Mellifera L.) Guarding Behavior Support Predictions of the Acceptance Threshold Model.” Behavioral Ecology 11 (3): 326–33.

Ellis, Amanda M., Gerry W. Hayes, and James D. Ellis. 2009. “The Efficacy of Dusting Honey Bee Colonies with Powdered Sugar to Reduce Varroa Mite Populations.” Journal of Apicultural Research 48 (1): 72–76.

European Group for Integrated Varroa Control. 1999. “Coordination in Europe of Research on Integrated Control of Varroa Mites in Honey Bee Colonies, Appendix VI to the Final Technical Report.” Merelbeke, Belgium.

Evans, J., A. Müller, A.b. Jensen, B. Dahle, R. Flore, J. Eilenberg, and M.b. Frøst. 2016. “A Descriptive Sensory Analysis of Honeybee Drone Brood from Denmark and Norway.” Journal of Insects as Food and Feed, June, 1–8.

112

Free, J. B., and Ingrid H. Williams. 1975. “Factors Determining the Rearing and Rejection of Drones by the Honeybee Colony.” Animal Behaviour 23, Part 3 (August): 650–75.

Frey, Eva, and Peter Rosenkranz. 2014. “Autumn Invasion Rates of Varroa Destructor (Mesostigmata: Varroidae) Into Honey Bee (Hymenoptera: Apidae) Colonies and the Resulting Increase in Mite Populations.” Journal of Economic Entomology 107 (2): 508–15.

Frey, Eva, Hanna Schnell, and Peter Rosenkranz. 2011. “Invasion of Varroa Destructor Mites into Mite-Free Honey Bee Colonies under the Controlled Conditions of a Military Training Area.” Journal of Apicultural Research 50 (2): 138–44.

Fries, Ingemar, and Riccardo Bommarco. 2007. “Possible Host-Parasite Adaptations in Honey Bees Infested by Varroa Destructor Mites.” Apidologie 38 (6): 525–33.

Fuchs, S. 1990. “Preference for Drone Brood Cells by Varroa Jacobsoni Oud in Colonies of Apis Mellifera Carnica.” Apidologie 21 (3).

Gray, Michael E., Susan T. Ratcliffe, and Marlin E. Rice. 2008. “The IPM Paradigm: Concepts, Strategies and Tactics.” In Integrated Pest Management. Cambridge University Press.

Greatti, M., N. Milani, and F. Nazzi. 1992. “Reinfestation of an Acaricide-Treated Apiary byVarroa Jacobsoni Oud.” Experimental & Applied Acarology 16 (4): 279–86.

Grobov, O.F. 1977. “Varroasis in Bees.” In Varroasis a Honeybee Disease, 46–90. Bucharest: Apimondia Publishing House.

Guzmán-Novoa, Ernesto, Leslie Eccles, Yireli Calvete, Janine Mcgowan, Paul G. Kelly, and Adriana Correa-Benítez. 2010. “Varroa Destructor Is the Main Culprit for the Death and Reduced Populations of Overwintered Honey Bee (Apis Mellifera) Colonies in Ontario, Canada.” Apidologie 41 (4): 443–50.

Hansen, Carsten Wolff. 2007. “The Safe Strategy.” The Danish Beekeepers’ Assocation. http://www.biavl.dk/english/varroa-eng/331-the-safe- startegy.html.

“Honey Bee Colonies Report.” 2016. National Agricultural Statistical Service (NASS), Agricultural Statistics Board, USDA.

113

Honey Bee Health Coalition. 2016. “Tools for Varroa Management: A Guide to Effective Varroa Sampling and Control.” The Keystone Policy Center.

Horn, Tammy. 2006. Bees in America: How the Honey Bee Shaped a Nation. University Press of Kentucky.

Huang, Z. 2001. “Mite Zapper - A New and Effective Method for Varroa Mite Control.” American Bee Journal 141 (10): 730–32.

Imdorf, Anton, Jean-Daniel Charriere, Verena Kilchenmann, Stefan Bogdanov, and Peter Fluri. 2003. “Alternative Strategy in Central Europe for the Control of Varroa Destructor in Honey Bee Colonies.” Swiss Bee Research Centre.

Jain, Meha, Shahid Naeem, Ben Orlove, Vijay Modi, and Ruth S. DeFries. 2015. “Understanding the Causes and Consequences of Differential Decision- Making in Adaptation Research: Adapting to a Delayed Monsoon Onset in Gujarat, India.” Global Environmental Change 31 (March): 98–109.

Klein, A.-M., B. E Vaissiere, J. H Cane, I. Steffan-Dewenter, S. A Cunningham, C. Kremen, and T. Tscharntke. 2007. “Importance of Pollinators in Changing Landscapes for World Crops.” Proceedings of the Royal Society B: Biological Sciences 274 (1608): 303–13.

Kremen, Claire, and Albie Miles. 2012. “Ecosystem Services in Biologically Diversified versus Conventional Farming Systems: Benefits, Externalities, and Trade-Offs.” Ecology and Society 17 (4): 40.

Lee, Kathleen V., Nathalie Steinhauer, Karen Rennich, Michael E. Wilson, David R. Tarpy, Dewey M. Caron, Robyn Rose, et al. 2015. “A National Survey of Managed Honey Bee 2013–2014 Annual Colony Losses in the USA.” Apidologie, April, 1–14.

Lee, K.V., R.D. Moon, E.C. Burkness, W.D. Hutchison, and M. Spivak. 2010. “Practical Sampling Plans for Varroa Destructor (Acari: Varroidae) in Apis Mellifera (Hymenoptera: Apidae) Colonies and Apiaries.” Journal of Economic Entomology 103 (4): 1039–50.

Liebman, M., and E. Dyck. 1993. “Crop-Rotation and Intercropping Strategies for Weed Management.” Ecological Applications 3 (1): 92–122.

Loftus, J. Carter, Michael L. Smith, and Thomas D. Seeley. 2016. “How Honey Bee Colonies Survive in the Wild: Testing the Importance of Small Nests and Frequent Swarming.” PLOS ONE 11 (3): e0150362.

114

McLeod, Lynette J., Donald W. Hine, Patricia M. Please, and Aaron B. Driver. 2015. “Applying Behavioral Theories to Invasive Animal Management: Towards an Integrated Framework.” Journal of Environmental Management 161 (September): 63–71.

Milani, N. 1994. “Possible Presence of Fluvalinate-Resistant Strains of Varroa Jacobsoni in Northern Italy.” In A. Matheson [Ed.] New Perspectives, 87. Cardiff, UK: IBRA.

Ohio Department of Agriculture, Apiary. 2015. “2015 Inspection Report.” Plant Health Division - Apiary Program. http://www.agri.ohio.gov/divs/plant/apiary/apiary.aspx.

Padel, Susanne. 2001. “Conversion to Organic Farming: A Typical Example of the Diffusion of an Innovation?” Sociologia Ruralis 41 (1): 40–61.

Pellett, Frank C. 1938. History of American Beekeeping. Ames, Iowa: Collegiate Press, Inc.

Potts, S. G., B. A. Woodcock, S. P. M. Roberts, T. Tscheulin, E. S. Pilgrim, V. K. Brown, and J. R. Tallowin. 2009. “Enhancing Pollinator Biodiversity in Intensive Grasslands.” Journal of Applied Ecology 46 (2): 369–79.

Rosenkranz, Peter, Pia Aumeier, and Bettina Ziegelmann. 2010. “Biology and Control of Varroa Destructor.” Journal of Invertebrate Pathology 103 (January): S96–119.

Rowland, C. M., and A. R. McLellan. 1987. “Seasonal Changes of Drone Numbers in a Colony of the Honeybee, Apis Mellifera.” Ecological Modelling 37 (3–4): 155–66.

Ruttner, Friedrich. 1988. Biogeography and Taxonomy of Honeybees. Springer- Verlag.

Seeley, T. D., and A. S. Mikheyev. 2003. “Reproductive Decisions by Honey Bee Colonies: Tuning Investment in Male Production in Relation to Success in Energy Acquisition.” Insectes Sociaux 50 (2): 134–38.

Seeley, T. D., and R. A. Morse. 1976. “The Nest of the Honey Bee (Apis Mellifera L.).” Insectes Sociaux 23 (4): 495–512.

Seeley, Thomas D. 2002. “The Effect of Drone Comb on a Honey Bee Colony’s Production of Honey.” Apidologie 33 (1): 75–86.

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———. 2007. “Honey Bees of the Arnot Forest: A Population of Feral Colonies Persisting with Varroa Destructor in the Northeastern United States.” Apidologie 38 (1): 19–29.

Seeley, Thomas D., and Sean R. Griffin. 2011. “Small-Cell Comb Does Not Control Varroa Mites in Colonies of Honeybees of European Origin.” Apidologie 42 (4): 526–32.

Seeley, Thomas D., and Michael L. Smith. 2015. “Crowding Honeybee Colonies in Apiaries Can Increase Their Vulnerability to the Deadly Ectoparasite Varroa Destructor.” Apidologie 46 (6): 716–27.

Seitz, Nicola, Kirsten S. Traynor, Nathalie Steinhauer, Karen Rennich, Michael E. Wilson, James D. Ellis, Robyn Rose, et al. 2015. “A National Survey of Managed Honey Bee 2014–2015 Annual Colony Losses in the USA.” Journal of Apicultural Research 54 (4): 292–304.

Simpson, J., and Inge B. M. Riedel. 1963. “The Factor That Causes Swarming by Honeybee Colonies in Small Hives.” Journal of Apicultural Research 2 (1): 50–54.

Smith, Michael L., Madeleine M. Ostwald, J. Carter Loftus, and Thomas D. Seeley. 2014. “A Critical Number of Workers in a Honeybee Colony Triggers Investment in Reproduction.” Naturwissenschaften 101 (10): 783–90.

Smith, Michael L., Madeleine M. Ostwald, and Thomas D. Seeley. 2015. “Adaptive Tuning of an Extended Phenotype: Honeybees Seasonally Shift Their Honey Storage to Optimize Male Production.” Animal Behaviour 103 (May): 29–33.

Spivak, Marla, Eric Mader, Mace Vaughan, and Ned H. Euliss. 2011. “The Plight of the Bees.” Environmental Science & Technology 45 (1): 34–38.

Steinhauer, Nathalie A., Karen Rennich, Michael E. Wilson, Dewey M. Caron, Eugene J. Lengerich, Jeff S. Pettis, Robyn Rose, et al. 2014. “A National Survey of Managed Honey Bee 2012-2013 Annual Colony Losses in the USA: Results from the Bee Informed Partnership.” Journal of Apicultural Research 53 (1): 1–18.

Stofferahn, Curtis W. 2009. “Personal, Farm and Value Orientations in Conversion to Organic Farming.” Journal of Sustainable Agriculture 33 (8): 862–84.

Strange, James P., Richard P. Cicciarelli, and Nicholas W. Calderone. 2008. “What’s in That Package? An Evaluation of Quality of Package Honey Bee

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(Hymenoptera : Apidae) Shipments in the United States.” Journal of Economic Entomology 101 (3): 668–73.

Tautges, Nicole E, Jessica R Goldberger, and Ian C Burke. 2016. “A Survey of Weed Management in Organic Small Grains and Forage Systems in the Northwest United States.” Weed Science 64 (3): 513–22.

The Bee Informed Partnership. 2011. “Drone Brood Removal By Region.” National Management Survey 2010-2011. https://beeinformed.org/wp- content/uploads/2012/03/Drone-brood-removal-by-region.pdf.

———. 2012a. “Drone Brood Removal By Region.” National Management Survey 2011-2012. https://beeinformed.org/wp-content/uploads/2013/08/drone- brood-removal-by-region.pdf. ———. 2012b. “Years as Beekeeper.” National Management Survey 2011-2012. https://beeinformed.org/wp-content/uploads/2014/11/Years-as-Beekeeper.pdf.

———. 2013a. “Drone Brood Removal By Region.” National Management Survey 2012-2013. https://beeinformed.org/wp-content/uploads/2014/11/Drone- Brood-Removal-By-Region.pdf.

———. 2013b. “Losses By State.” National Management Survey 2012-2013. https://beeinformed.org/wp-content/uploads/2014/11/Losses-By-State.pdf.

———. 2014a. “Drone Brood Removal By Region.” National Management Survey 2013-2014. https://beeinformed.org/wp-content/uploads/2014/09/Drone- Brood-Removal-by-Region.pdf.

———. 2014b. “Losses By State.” National Management Survey 2013-2014. https://beeinformed.org/wp-content/uploads/2014/09/Losses-by-State.pdf.

———. 2014c. “Years as a Beekeeper.” National Management Survey 2013-2014. https://beeinformed.org/wp-content/uploads/2014/09/Years-as-Beekeeper.pdf.

———. 2015a. “Average Loss in Operations with Different Beekeeping Management Philosophies.” National Management Survey 2014-2015. https://beeinformed.org/wp-content/uploads/2015/09/ManagementPhilosphy- RF.pdf.

———. 2015b. “Drone Brood Removal By Region.” National Managment Survey, 2014-2015. https://beeinformed.org/wp- content/uploads/2015/09/DroneBroodRemovalByRegion-RF.pdf.

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———. 2015c. “Drone Brood Removal Use.” National Management Survey 2014- 2015. https://beeinformed.org/wp- content/uploads/2015/09/DroneBroodRemovalUse-RF.pdf.

———. 2015d. “Losses By State.” National Management Survey 2014-2015. https://beeinformed.org/wp-content/uploads/2015/09/LossesByState-RF.pdf.

———. 2015e. “Losses in Geographic Sub-Regions Excluding Multiregional Operations.” National Management Survey 2014-2015. https://beeinformed.org/wp- content/uploads/2015/09/ByGeographicSubRegion-RF.pdf.

———. 2015f. “Single Stock.” National Management Survey 2014-2015. https://beeinformed.org/wp-content/uploads/2015/09/SingleStock-RF.pdf.

———. 2015g. “Varroa Mite Control Product Use.” National Management Survey 2014-2015. https://beeinformed.org/wp- content/uploads/2015/09/VarroaControlProductUse-RF-TW.pdf.

———. 2015h. “Years as a Beekeeper.” National Management Survey 2014-2015. https://beeinformed.org/wp-content/uploads/2015/09/YearsAsBeekeeper- RF.pdf.

Truelove, Heather Barnes, Amanda R. Carrico, and Lanka Thabrew. 2015. “A Socio-Psychological Model for Analyzing Climate Change Adaptation: A Case Study of Sri Lankan Paddy Farmers.” Global Environmental Change 31 (March): 85–97.

Vanengelsdorp, Dennis, Shane Gebauer, and Robyn Underwood. 2009. “A Modified Two-Queen System: ‘Tower’ Colonies Allowing For Easy Drone Brood Removal for Varroa Mite Control.” Bee Culture 1 (1). vanEngelsdorp, Dennis, and Marina Doris Meixner. 2010. “A Historical Review of Managed Honey Bee Populations in Europe and the United States and the Factors That May Affect Them.” Journal of Invertebrate Pathology 103 (January): S80–95.

Wantuch, Holly A., and David R. Tarpy. 2009. “Removal of Drone Brood from Apis Mellifera (Hymenoptera: Apidae) Colonies to Control Varroa Destructor (Acari: Varroidae) and Retain Adult Drones.” Journal of Economic Entomology 102 (6): 2033–40.

Wilfert, L., G. Long, H. C. Leggett, P. Schmid-Hempel, R. Butlin, S. J. M. Martin, and M. Boots. 2016. “Deformed Wing Virus Is a Recent Global

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Epidemic in Honeybees Driven by Varroa Mites.” Science 351 (6273): 594– 97.

Wilkinson, D., H. M. Thompson, and G. C. Smith. 2001. “Modelling Biological Approaches to Controlling Varroa Populations.” American Bee Journal 141 (7): 511–16.

Wilkinson, David, and Graham C. Smith. 2002. “Modeling the Efficiency of Sampling and Trapping Varroa Destructor in the Drone Brood of Honey Bees (Apis Mellifera).” American Bee Journal 142 (3): 209–12.

Winfree, Rachael, Ramiro Aguilar, Diego P. Vazquez, Gretchen LeBuhn, and Marcelo A. Aizen. 2009. “A Meta-Analysis of Bees’ Responses to Anthropogenic Disturbance.” Ecology 90 (8): 2068–76.

Wood, Stephen A., Amir S. Jina, Meha Jain, Patti Kristjanson, and Ruth S. DeFries. 2014. “Smallholder Farmer Cropping Decisions Related to Climate Variability across Multiple Regions.” Global Environmental Change 25 (March): 163–72.

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APPENDIX A: INTERVIEW GUIDE

THE OHIO STATE UNIVERSITY

Varroa Mite Management Interview Guide

Participant ID #: ______Interviewer: ______Date: ______Time Started: ______Time Ended: ______Location: ______

I’d like to start off by asking some basic questions about your background and your beekeeping practices:

1. How long have you been keeping bees? ______2. How many hives do you have currently? ______3. Is beekeeping your primary source of income? Yes/No 4. Do you participate in any of the following niche markets? a. ____Organic, certified (for other farm products) b. ____Organic, uncertified c. ____All natural d. ____Chemical-free e. ____Local f. ____Other: 5. Do you sell any of the following? a. ____Honey b. ____Queens c. ____Other hive products: 6. What percent of your operation successfully overwintered last year? ______7. What percent of your operation typically overwinters? ______8. How would you describe your current experience with varroa mites? a. ____Severe problem (I frequently lose colonies because of mites) b. ____Moderate problem (I sometimes lose colonies because of mites) c. ____Might be a problem (I often lose colonies and don’t know why) d. ____Not a problem (I have mites but they don’t impact my operation) e. ____Don’t have any f. ____Don’t know 9. Are you happy with your mite management strategy? Circle all that apply: a. ____Yes b. ____No, my strategy is not effective enough c. ____No, my strategy is effective but I don’t like it for other reasons (labor intensive, chemical, expensive etc.) d. ____No, I don’t know what to do e. ____I don’t have varroa mites

Thank you. That completes the survey portion of the interview, now I would like to transition to the open-ended conversation part of the interview.

Varroa Management Interview Guide 1

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THE OHIO STATE UNIVERSITY

READ: Today is [DATE] at [time AM/PM], the participant ID is [###] and the interviewer’s name is [###]. Thank you very much for meeting with me. Today, I am interested in learning more about your experiences keeping bees and managing varroa mites. Please remember that all of your information is confidential, and you do not have to talk about any topics that you do not want to. Do you have any questions before we begin?

1. Please tell me about your mite management strategy a. Products, drone brood trapping, brood break, etc. i. When do you treat? ii. How often (and how) do you check for mites? b. What is the single most important tool that you use? c. How has your mite management (and your issues with varroa mites) evolved over time? d. Are there major constraining factors in your management decisions? i. Time/labor, money, chemical-free e. What are your views on the use of chemical miticides? i. (How do they feel about the “live and let live” philosophy?) f. Are you happy with your current management practices?

2. Can you tell me about how the arrival of varroa mites changed beekeeping practices? a. What year did you start beekeeping? b. Did you experience the arrival of varroa mites? c. What is your impression of what happened, and how it changed beekeeping? d. How did your management practices change as a result of mites?

3. Can you describe any other beekeeping practices that you think influence your varroa mite population? a. Are there any other practices that you think are critically important for mite management or hive health? b. Views on genetics/queens i. How do you get new bees? ii. Do you breed your own queens? (how?) iii. Where do you get your queens? (VSH?) iv. Do you allow the bees to raise their own queen? (how do you deal with splits/swarms?) v. Views on packages c. What are your views on feeding? i. How would you describe your surroundings/forage? d. Hive volume/equipment e. What has been the biggest pest in your apiary? i. What do you do about other diseases, like EFB?

Varroa Management Interview Guide 2

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THE OHIO STATE UNIVERSITY

1. Do you currently or have you ever used drone brood trapping? a. Have you heard of it? b. How were your experiences? i. Details: frames, how destroy, timing, etc. ii. Would you recommend it? iii. What do you think is the maximum appropriate apiary size? iv. Caveats? c. Do other people you know use it? d. What have you heard about it? e. If you’ve heard of it and don’t use it, why not?

2. Can you tell me about your beekeeping education/experience? a. How did you first learn about beekeeping? i. Classes, books, bee club, mentor, peers, internet, On-farm experiments b. Why did you get into beekeeping in the first place? c. Where do you turn when you have new questions? d. What is your favorite part about being a beekeeper? e. Do you make money from their bees? i. What do you sell?

3. Can you talk to me a little about your views on the experiences of new beekeepers today, with respect to mite management? a. What do you see new beekeepers doing for mite control? i. What philosophies do you think many subscribe to? ii. Do they want non-chemical options? b. Any mistakes that you see lots of beginners making? i. Are they doing anything? ii. Checking for mites? c. What resources do you think beginners are using? d. Do you feel like there are adequate resources available to beekeepers? i. Is the information confusing? e. Is there any misinformation that you think a lot of new beekeepers are getting? f. What resources do you think would help beginners?

4. Follow-up, contacts (can specify if they don’t want me to contact, or don’t want me to use their name): a. Is there anyone else who you think would be interested in participating? b. (Do you know anyone who uses DBR?)

5. Is there anything else you’d like to add?

Varroa Management Interview Guide 3

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APPENDIX B: SURVEY INSTRUMENTS

Survey A

Varroa%Mite%Management%Survey% % Thank&you&for&your&help&with&varroa&mite&research!&The&following&survey&is&part&of&an&Ohio&State&University&research&project&exploring& varroa&mite&management.&Your&answers&will&help&us&understand&how&Ohio&beekeepers&are&managing&mites,&and&will&advance&research& on&varroa&control&here&in&the&Midwest.&Some&questions&may&be&hard&to&answer&exactly&–&just&give&your&best&estimate.&The&survey&is& anonymous&and&confidential.&It&should&take&no&more&than&10H15&minutes&to&complete,&and&participation&is&voluntary.&By&filling&out&this& survey,&you&consent&to&participate&in&the&study.&If&you&have&any&questions,&please&contact:&&& Hannah&Whitehead&([email protected],&216H849H5260)&or&Dr.&Casey&Hoy&([email protected],&330H263H3611).&& & For&questions&about&your&rights&as&a&participant&in&this&study&or&to&discuss&other&studyHrelated&concerns&or&complaints&with&someone&who&is¬& part&of&the&research&team,&you&may&contact:&Ms.&Sandra&Meadows&in&the&Office&of&Responsible&Research&Practices&at&1H800H678H6251.& ! Background! 1) What%year%did%you%begin%beekeeping?%______% 2) Roughly%how%many%hives%did%you%manage%this%past%summer?%______% 3) What%is%the%largest%number%of%hives%that%you%have%ever%managed%at%one%time?%______% % Overwintering!Loss! 4) What%percent%of%your%colonies%did%you%lose%last%winter%(2014D2015)?%______% 5) Please%estimate%the%range%of%your%typical%winter%loss%(over%the%past%5%winters)%%_____%(low)%to%_____(high)% % General!Practices! 6) Do%you%sell%any%of%the%following?%Check%all%that%apply:% Honey%%%Queens%%%Nucs%%%%Packages%%%Equipment%%%Pollination&Services%%%Other&(wax,&pollen,&etc.)& & 7) When%you%expand%or%replace%losses,%how%do%you%obtain%new%hives?%Check%all%that%apply:% Packages&(Southern&States)%%Packages&(California)%%%Packages&(Unknown&Origin)%%%%Nucs%%%%Splits&&&Swarms/CutHouts & & & 8) When%you%purchase%packages,%under%what%circumstances%do%you%replace%the%queen?%Check%all%that%apply:! Never/rarely& ReHqueen&if&the&original&queen&disappears/dies Always&and&as&soon&as&possible&replace&the&original&package&queen& % 9) In%general,%when%you%make%a%split%or%reDqueen,%where%do%you%get%your%new%queen?%Check%all%that%apply:% Purchase&a&queen&from&a&bee&supply&store&or&queen&vendor' ' Purchase&a&queen&from&a®ional&queen&producer/breeder' Purchase&a&queen&(Unknown&Origin/Type)&' Purchase&a&specialty&queen&(VSH,&legHchewers,&Russian,&New&World&Carniolan)&& Use&a&queen&produced&onHsite&(grafting)& & Encourage&the&colony&to&raise&a&queen&by&manipulating&swarm&cells&or&brood&frames Leave&the&colony&alone&–&let&them&raise&their&own&queen&& Don’t&know/Not&applicable& Varroa!Management! 10) This'past'season'(2015),%did%you%use%any%of%the%following%varroa%control%methods?%Check%all%that%apply:%% Checkmite+&(Coumaphos)& Powdered&Sugar& Apivar&(Amitraz)& SmallHcell&Foundation& Apistan&(Fluvalinate)& Break&in&the&Brood&Cycle&&& Hivastan& Drone&Brood&Removal& ApiGuard&or&ApiLife&Var&(Thymol)& Screened&Bottom&Boards& MiteAway&Quick&Strips&(Formic&Acid)& Special&Queens/Genetics& Oxalic&Acid& Other:& HopGuard&& NONE % 11) If%you%used%drone%brood%removal,%what%type%of%frame%did%you%use%to%encourage%drone%production?& Drone&cell&foundation& &&&&Shallow/medium&frame&in&deep&box&&&&&Foundationless&frame&&&&&Other:& & &

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12) Throughout'your'beekeeping'career,%have%you%used%any%of%the%following%methods?%Check%all%that%apply:% Checkmite+&(Coumaphos)& Powdered&Sugar& Apivar&(Amitraz)& SmallHcell&Foundation& Apistan&(Fluvalinate)& Break&in&the&Brood&Cycle& Hivastan& Drone&Brood&Removal& ApiGuard&or&ApiLife&Var&(Thymol)& Screened&Bottom&Boards& MiteAway&Quick&Strips&(Formic&Acid)& Special&Queens/Genetics& Oxalic&Acid& Other:& HopGuard&& NONE % 13) If%you%changed%varroa%control%tactics%over%time,%why%did%you%abandon%your%old%method?%Check%all%that%apply:% Not&effective&enough&&&Mites&became&resistant&&&Chemicals&too&harsh&&&Too&much&labor&&&Other:&& % 14) If%you%have%never%tried%“drone%brood%removal”,%why%not?%Check%all%that%apply:% Never&heard&of&it& No&need&(happy&with¤t&method)& Don’t&know&how&to&use&it& & Too&much&labor&&&&& Afraid&it&won’t&be&effective&enough& Haven’t&gotten&around&to&it& Other:&& % 15) This%past%season%(2015),&roughly%how%often%did%you%monitor%for%mites?%% Never&&&&&&&Once&&&&&&&Twice&&&&&&Once&a&month&&&&&&Twice&a&month&&&&&&Once&a&week&& % 16) What'method%did%you%use%to%monitor?%Check%all%that%apply:% Observation&of&mites&on&adult&bees& & SugarHroll&&& & AlcoholHwash& & EtherHroll&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& MiteHdrop&through&screened&bottom&board& Uncap&drone&brood& Other&& & NONE& % 17) On%the%whole,%would%you%say%you%are%satisfied%with%your%mite%management%strategy?%% Yes& No,&I&don’t&know&what&to&do& No,&my&strategy&is¬&effective&enough& No,&my&strategy&is&effective&but&I&don’t&like&it&for&other&reasons&(labor,&chemicals,&expense,&etc.)& % 18) If%you%are%not%satisfied%with%your%strategy,%what%would%you%like%to%change?%Check%all%that%apply:% More&effective&mite&control&& & & Fewer&chemicals&& & & Less&labor& & & & & Better&genetics&(local&or&resistant&queens,&breeding&own&queens)& & Less&expense& & & & & Other:& & 19) If%you%are%not%satisfied%with%your%strategy,!what%is%standing%in%the%way%of%changing%to%another%method?% Don’t&know&what&other&technique&to&choose&&&& Don’t&know&HOW&to&use&other&technique& & Don’t&want&to&risk&trying&something&new&&&& Labor Expense& & & & & Other:& % 20) How%do%you%get%information%about%mite%management?%Check%all%that%apply:% Bee&club&&&&&Friends/Mentors&&&Classes&&&&Books&&&&Internet&&&Magazines&&&Extension/University&& & 21) Do%you%feel%like%you%have%sufficient%information%about%mite%management?% Yes&&&&&&&&&&&&&&No& % 22) In%a%few%words:%what%do%you%consider%to%be%the%MOST!IMPORTANT%part%of%your%mite%control%strategy?%Feel%free%to%list%a% topic%or%practice%that%is%not%a%direct%varroa%treatment%(eg.&location,&genetics,&feeding,&equipment,&splitting,&etc.):! & ! ! THANK!YOU!!This!concludes!the!survey.! Please!return!your!completed!survey!to!the!Ohio!State!Nosema!Testing!Booth.!! % If&you&wish&to&learn&more&about&this&project&or&receive&future&updates,&email&Hannah&Whitehead&at&& [email protected]&or&visit&the&Ohio&State&Booth& %

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Survey B

!Varroa!Mite!Management!Survey! ! Thank!you!for!your!help!with!varroa!mite!research!!The!following!survey!is!part!of!an!Ohio!State!University!research!project! exploring!varroa!mite!management.!Your!answers!will!help!us!understand!how!Ohio!beekeepers!are!managing!mites,!and!will! advance!research!on!varroa!control!here!in!the!Midwest.!Some!questions!may!be!hard!to!answer!exactly!–!just!give!your!best! estimate.!The!survey!is!anonymous!and!confidential.!It!should!take!no!more!than!10I15!minutes!to!complete,!and!participation! is!voluntary.!By!filling!out!this!survey,!you!consent!to!participate!in!the!study.!If!you!have!any!questions,!please!contact:! Hannah!Whitehead!([email protected],!216I849I5260)!or!Dr.!Casey!Hoy!([email protected],!330I263I3611).! ! For!questions!about!your!rights!as!a!participant!in!this!study!or!to!discuss!other!studyIrelated!concerns!or!complaints!with!someone!who!is! not!part!of!the!research!team,!you!may!contact:!Ms.!Sandra!Meadows!in!the!Office!of!Responsible!Research!Practices!at!1I800I678I6251.! ! This'survey'is'part'of'the'same'project'as'the'OSU'mite'survey'distributed'at'the'Ohio'State'Beekeepers'Association'meeting'last'October.' This'survey'is'different'from'that'one.!However,'it'is'important'for'statistical'purposes'to'know'whether'or'not'you'took'the'other'survey.! ! ! A1.!Did!you!take!the!Ohio!State!mite!survey!at!the!OSBA!meeting!(10.31.15),!or!in!the!OSBA!winter!newsletter?'! ! ! !'YES! !!!! !NO! ! ! ! "All'answers'(YES'and'NO)'please'proceed'to'the'rest'of'this'survey!! ! ! ! YOUR!MITE!MANAGEMENT!STRATEGY! The'following'set'of'questions'will'help'us'learn'about'your'mite'management'strategy,'this'year'and'in'previous'years.''

! ! B1.!This!past!season!(summer!2015),!roughly!how!often!did!you!MONITOR!for!mites?!!(Please'choose'ONE)' !Never!!!!!!!!Once!!!!!!!!Twice!!!!!!!Once!a!month!!!!!!!Twice!a!month!!!!!!!Once!a!week!! ! B2.!What!METHODS!did!you!use!to!monitor?!(Check'ALL'that'apply)! Observation!of!mites!on!adult!bees! ! SugarIroll!!! ! AlcoholIwash! ! EtherIroll!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! MiteIdrop!through!screened!bottom!board! Uncap!drone!brood! NONE ' B3.!When!you!consider!mite!treatment!options,!do!you:'(Please'choose'ONE)! !Only!use!beeKderived!materials!in!the!hive!(eg.'wax,'honey,'etc.)! ! !Prefer!beeKderived!materials!in!the!hive,!but!will!use!organic!products!if!necessary!(eg.'formic'acid,'oxalic'acid,'thymol)! !Only!use!organic!products!in!the!hive!(eg.'formic'acid,'oxalic'acid,'thymol)! ! !Prefer!beeKderived/organic!products,!but!will!use!synthetic!products!if!necessary'(eg.'Checkmite+,'Apivar,'Apistan)! ! !Use!synthetic!products!if!necessary!(eg.'Checkmite+,'Apivar,'Apistan)! !No!preference! ! B4.!What!form!of!mite!control!do!you!use?!Please!indicate!what!(if!any)!you!used!LAST!YEAR!(2015)!and!in!PREVIOUS! YEARS.!If!2015!was!your!first!year,!simply!leave!the!second!column!blank.!(Check'ALL'that'apply)' ! ! Mite'Control'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''LAST!Year!(2015)! ! Previous!Years! ! a.!Checkmite+!(Coumaphos)! ! ! ! b.!Apivar!(Amitraz)!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! c.!Apistan!(Fluvalinate)!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! d.!Hivastan!(Fenpyroximate)!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! !! ! e.!ApiGuard!or!ApiLife!Var!(Thymol)!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! f.!MiteAway!Quick!Strips!(Formic!Acid)!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! g.!Oxalic!Acid!! ! ! h.!HopGuard!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! i.!Powdered!Sugar!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! ! j.!SmallIcell!Foundation! ! ! ! k.!Break!in!the!Brood!Cycle!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! ! l.!Drone!Brood!Removal!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! ! m.!Screened!Bottom!Boards! ! ! ! n.!Special!Queens/Genetics!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! !

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B5. There are a number of downsides to treating for mites, including expense, chemical use, and increased labor. These factors can influence your mite management choices. How important are the following factors when making decisions about your mite management? Please rank from 1 to 5. (1 = Not Important to 5 = Extremely Important)

Not Important Somewhat Important Extremely Important a. Labor requirements 1 2 3 4 5 b. Cost 1 2 3 4 5 c. NO chemicals at all (incl. organic) 1 2 3 4 5 d. Reducing chemical use 1 2 3 4 5

DRONE BROOD REMOVAL We are particularly interested in learning about your exposure to drone brood removal as a mite control method

C1. Have you ever used drone brood removal? ¡YES à skip to C3 ¡NO à please answer C2 and then skip to YOUR MANAGEMENT SCHEDULE

C2. If you NEVER tried drone brood removal, WHY NOT? (Check ALL that apply) Never heard of it No need (happy with current method) Don’t know how to use it Don’t want to kill drones Too much labor Afraid it won’t be effective enough

FOR DRONE BROOD REMOVAL USERS (past and current)

C3. Do you still use drone brood removal? ¡YES ¡NO

C4. Do/did you combine drone brood removal with any of the following mite control methods? (Check ALL that apply) Break in the Brood Cycle Synthetic product (eg. Checkmite+, Apivar, Apistan) Local/Resistant Queen Natural product (eg. Formic Aid, Thymol, Oxalic Acid) Other (please explain):

C5. Do you agree with this statement? Drone brood removal requires more labor than other mite control methods.

1 2 3 4 5 Strongly Disagree Neutral Strongly Agree

YOUR MANAGEMENT SCHEDULE Many beekeepers have to fit their beekeeping around other obligations, and this influences the time they can devote to their bees. The following questions ask about your beekeeping schedule and scheduling challenges.

D1. During the summer, roughly how often do you inspect the brood box in your hives (for instance, checking for eggs and larvae)? (Please choose ONE) ¡Never ¡Once a year ¡A few times a year ¡Once a month ¡Twice a month ¡Once a week

D2. Despite other demands on your time, do you feel like you are able to get beekeeping TASKS done APPROXIMATELY when they need to be done? Please rank from 1 (rarely) to 5 (always). (RARELY = I almost never get things done on time, ALWAYS = I am always able to get things done on time)

1 2 3 4 5

Rarely Sometimes Often Usually Always

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YOU AND YOUR BEES The following set of questions asks about your beekeeping background.

E1. How many years have you been keeping bees? ______years

E2. Roughly how many hives did you manage this past summer? ______hives

E3. What is the largest number of hives that you have ever managed at one time? ______hives

E4. What is your beekeeping experience level?

1 2 3 4 5

Beginner Expert

E5. What is your motivation for keeping bees? (Check ALL that apply) Sale of hive products (honey, pollination, etc.) Hive products for personal use Hobby/personal interest Education/teaching

E6. Over the past FEW YEARS, how have you typically purchased or obtained new bees? (This includes your first bees if you are a new beekeeper). Please rank from 1 (never get bees in this way) to 5 (frequently get bees in this way).

Never Rarely Sometimes Often Always a. Packages (southern states) 1 2 3 4 5 b. Packages (California) 1 2 3 4 5 c. Packages (unknown origin) 1 2 3 4 5 d. Nucs (local) 1 2 3 4 5 e. Nucs (non-local origin) 1 2 3 4 5 f. Swarms/cut-outs 1 2 3 4 5

E7. In general, do you re-queen packages immediately? ¡No ¡Yes: Always and as soon as possible ¡Only if the queen disappears/dies ¡N/A

E8. Are LOCAL and/or SPECIALTY (New World Carniolan, Russian, VSH, leg- chewer) nucs or queens an important part of your current beekeeping strategy? (1 = Not Important to 5 = Extremely Important).

1 2 3 4 5

Not Important Somewhat important Very Important

OVERWINTERING LOSS The following questions are about your experiences with winter loss. We understand that these questions might be particularly difficult to answer exactly – just give us your best estimate. Please answer as a percent (75%) or a proportion (3 of 4) hives):

F1. What percent of your colonies did you lose THIS WINTER (2015-2016)? ______%

F2. What percent of your colonies did you lose LAST WINTER (2014-2015)? ______%

F3. What is a TYPICAL RANGE of winter loss for you? ______% (low) - ______% (high)

THANK YOU! This concludes the survey. Please return your completed survey at the exit.

If you wish to learn more about this project or receive future updates, email Hannah Whitehead at [email protected]

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