Corn Dust Research Consortium (CDRC) Final Report

FINAL - Page 1 of 136 CDRC – July 2017

Reviewed and approved by the CDRC.
For further Information contact:
Pollinator Partnership
423 Washington Street, 5th Floor
San Francisco, CA 94010
USA
info@pollinator.org
Val Dolcini
President and CEO
Pollinator Partnership
530.400.6100
Vdolcini@pollinator.org
Laurie Davies Adams
Executive Director Emeritus
Pollinator Partnership415.260.8092
LDA@pollinator.org
Kelly Rourke
Program Coordinator
Pollinator Partnership415.362.1137
KR@pollinator.org
Tom Van Arsdall
Public Affairs Director
703.507.4746
TVA@pollinator.org

FINAL - Page 2 of 136 CDRC – July 2017

Contents
Corn Dust Research Consortium (CDRC) Final Report .................................................................. 1
Executive Summary ......................................................................................................................... 4
Introduction and background ........................................................................................................... 5
The Corn Dust Research Consortium ............................................................................................. 6
Assessing strategies to reduce honey bee exposure to dust emitted during planting of treatedcorn seeds in Ohio ........................................................................................................................... 9
Reducing honey bee exposure to neonicotinoid dust emitted during planting of treated corn seeds....................................................................................................................................................... 62
The Long-Term Health Consequences of Exposure of Honey Bee Colonies to Dust Emitted
During Planting of Neonicotinoid-Treated Corn Seeds ................................................................. 92
Use by Honey Bees of Flowering Resources In and Around Corn Fields, Year 2 (Project 1) .... 121
Corn Dust Research Recommendations - 2017.......................................................................... 132
A.

Farmers ............................................................................................................................ 132

B.

Beekeepers ...................................................................................................................... 134

C.

Pesticide and lubricant manufacturers ............................................................................. 134

D.

Equipment manufacturers ................................................................................................ 135

E.

Seed dealers .................................................................................................................... 135

F.

Provincial, state and federal government agencies and regulators ................................. 135G.

Extension agents, agricultural and commodity organizations, and agricultural media .... 136

FINAL - Page 3 of 136 CDRC – July 2017

Executive Summary
From 2013-2017 the CDRC assessed the interactions that honey bees were having with
pollen and nectar sources during corn planting. In addition to pollen usage and foraging
preference, the neonicotinoid residues present in or around potential pollen sourceswere examined where possible. The effectiveness of an alternative planting lubricant
was also examined at one of the four study locations to determine if drift andconcentrations of residues were reduced compared to graphite and talc products.
Each of the study centers had different experimental designs and protocols, even wheninvestigating the same question. Because of these differences, which were encouragedby the CDRC, the executive summary illustrates highlights rather than combined
conclusions in some instances.
Investigations of pollen usage showed that the majority of pollen collected by honeybees came from woody tree and shrub species, during planting. Salix and Acer species
were most commonly used, as were members of the family Roseceae. Herbaceouspollen was less commonly collected. After planting there was a shift in pollen collection
to more herbaceous dominated species with clover (Trifolium hybridum) being mostcommon. Honey bees were noted to visit dandelion (Taraxacum spp.) very commonly
during this period, although this pollen only accounted for a small amount of pollen
returned to the hive, suggesting that they use these flowers as nectar sources.
The concentrations of neonicotinoids within bee-collected pollen during planting weresignificantly higher than after planting. The data from trees/shrubs and herbaceous
plants suggest that the availability of different species of flowering resources relative tothe time of corn planting can influence the exposure of honey bees to neonicotinoid
insecticides and will vary with the environmental conditions of the year.
Bee mortality results associated with planting activities varied between the replicates,with some showing increased mortality with planting activities (Iowa and Ohio) and someshowing no difference in mortality (Nebraska).
Neonicotinoid residues measured using vertical sticky traps and volumetric air samplers
downwind during tillage events were much lower than the residues collected during
planting (Guelph). The concentration of neonicotinoids captured at the field edge byeither method was similar to those at the neighboring field edge downwind. The CDRC
results are not consistent with other research regarding the extent to which
synthetic lubricants reduce net emission of dust-borne pesticide during plantingof treated seed; however, the CDRC research showed sufficiently significant
reductions to warrant use of these synthetic lubricants compared to talc orgraphite.
Efforts to reduce the amount of emitted dust with planter modifications and efforts toplace bees in locations that minimize their exposure during planting are recommended.

FINAL - Page 4 of 136 CDRC – July 2017

Introduction and background
Honey bees living near corn fields can have multiple routes of exposure to pesticides.
Exposure may be by contact (dust, soil), by ingestion (pollen/nectar/water), or a
combination of these exposure routes. The focus of this discussion is exposure via dust
from the planting of treated corn seeds.
Corn planting throughout the U.S. and Canada typically occurs from late April to early
May when the fields are sufficiently dry to enter with equipment. Corn seeds currently inuse by farmers are very frequently treated with pesticide(s). Under humid conditions,
treated seeds may become sticky and require a lubricant/fluency agent to moveeffectively through pneumatic planting equipment; talc and/or graphite are frequently
used as seed flow lubricants in the larger pneumatic planters to ensure uniform seeddrop. Abrasion of treated seed coatings can result in particles containing pesticide
residues mixing with the fluency agents to produce a contaminated “dust” (aka fugitivedust), which can be released by the air exhaust system during planting or subsequentcleaning of the equipment. This “dust” has the potential to be deposited on soil, water,
and flowers within and adjacent to corn fields where foraging honey bees, and otherpollinators, may be exposed to the pesticide(s).
In 2008, a large number of honey bee colonies in Germany were affected by the drift ofdust generated through the abrasion of treated seed during planting. Since that time
there has been concern regarding the extent to which one class of pesticides, i.e.,
neonicotinoid insecticides, can move off-site and represent a route of exposure for bees
foraging in the vicinity of fields where neonicotinoid-treated seeds have been planted.
Although the incident in Germany was attributed to a combination of factors (i.e., lack ofa suitable sticking agent for the pesticide on the seed, seeding equipment that vents
upward, dry windy conditions and an abundance of oilseed rape (canola) in full bloom
immediately adjacent to the fields being planted), subsequent research (Krupke et al.
2012; Tapparo et al. 2012) has indicated that fugitive dust may still represent a route of
exposure even where suitable sticking agents are used and seeding equipment vents
downward.

FINAL - Page 5 of 136 CDRC – July 2017

The Corn Dust Research Consortium
The Corn Dust Research Consortium (CDRC) was formed in early 2013 at the request of
the Pollinator Partnership, which provides administrative oversight to the CDRC, toexplore potential exposure routes of honey bees to seed treatment dust as well as
potential options to mitigate exposure. The CDRC secured the funding for andconducted the oversight of research into two specific corn dust/honey bee interactions in2013 and 2014.
Question 1) What are the flowering resources available to and used by honey bees inand around corn fields during planting?
Question 2) What is the efficacy of a newly proposed fluency agent relative to talc and/orgraphite in reducing the abrasion of treated seed coatings within planters during planting
and the subsequent levels of pesticide-contaminated dust released into theenvironment?
Research teams addressing question 1 conducted work in three states (Ohio, Iowa, andNebraska) and one province (Ontario). Question 2 was addressed by the research teamin Ohio. Findings and a summary report of the 2013 and 2014 study years can be foundat http://www.pollinator.org/PDFs/July2015CDRCFINAL.pdf. In 2015 the CDRC revisitedthese two research questions with an additional RFP solicitation and four project areas.
Project 1- Use by Honey Bees of flowering resources in and around cornfields during
spring planting, and how this behavior can be effectively managed to reduce exposure topesticide dust and residues;
Project 2 - The long-term health consequences of exposure of honey bee colonies todust emitted during planting of neonicotinoid treated corn seeds;
Project 3 – The efficacy of CDRC recommendations in preventing honey bee exposure
to corn dust; andProject 4 - Efficacy of seed lubricant products
In 2015, the research team from Montana addressed project area 2, the team from Ohio
addressed all four projects and the team from Ontario addressed project area one. The
research team from Iowa did not continue into 2015.
The goal of the consortium in addressing these project areas is to utilize data fromresearch conducted in during the 2013, 2014, and 2015 corn planting seasons acrossfour North American locations to develop best practice guidance for future corn planting
seasons, thereby reducing potential exposure of honey bees to fugitive dust during
planting.
It was clear from the beginning that the CDRC could not address all aspects of pollinatorexposure, and given limited resources and time, the decision was made to be focused inour efforts. The sampling was focused solely on the potential exposure to honey bees

FINAL DRAFT- Page 6 of 136 CDRC – March 2017

with respect to corn planting. No other species or other crops were considered by
CDRC-funded studies.
More than a dozen stakeholder groups that comprise the CDRC invested their time andresources to ensure that the research was conducted and presented in the most unbiased, open, and useful form. The participating stakeholders represent interests fromvarious aspects of this situation and include members from:
American Beekeeping Federation
American Seed Trade Association
American Honey Producers Association
Association of Equipment Manufacturers
Bayer CropScience
BASF
Canadian Honey Council
Farm Equipment Manufacturers Association
Industrial Minerals Association - North America
National Corn Growers Association
Pollinator Partnership
Syngenta
University of Maryland
In addition, reviews of protocols and study results have been provided by the U.S.
Department of Agriculture’s Agricultural Research Service (USDA ARS), Health
Canada’s Pest Management Regulatory Agency (PMRA), and the U.S. Environmental
Protection Agency’s Office of Pesticide Programs (EPA OPP).
The CDRC research was not formed with the intent to address all questions related topotential exposure to a specific class of insecticides, i.e. neonicotinoids and theirinteraction and/or potential effects on honey bees or all pollinators. In fact, the CDRC
research is NOT intended as:
•
•
•
•
•
•
•

An endorsement of seed treatment, neonicotinoids, or any practice
A program with a preconceived outcome
A study involving any pollinator other than honey bees
An examination of Colony Collapse Disorder (CCD)
Applicable to any other crop until tested
An examination of all potential routes of exposure
An examination of potential additive, synergistic or antagonistic
relationships between multiple pesticides (e.g., insecticides andfungicides)

What follows are the final reports for 2016-2017 for the teams from Montana, Ontario,
and Ohio, and the final report for 2015 from Iowa. It should be noted that researchers at
each of the four institutions took their own approach to the project areas. Their methods
and their observations are not identical, nor were they intended to be. The variety ofFINAL DRAFT- Page 7 of 136 CDRC – March 2017

landscape features and differences in grower practices, as well as the timing of theplanting, varied according to location.

FINAL DRAFT- Page 8 of 136 CDRC – March 2017

JUNE, 2016 FINAL REPORT

Assessing strategies to reduce honey bee exposure to dust emitted during
planting of treated corn seeds in Ohio
A research update addressing all four projects outlined in the Corn Dust ResearchConsortium 2015 request for proposals
PI:
Reed Johnson, Assistant Professor
Department of Entomology
Ohio State University – OARDC
1680 Madison Ave.
Wooster, OH 44691
Phone: Office – 330-202-3523, Cell – 330-439-8295
E-mail: Johnson.5005@osu.edu
Co-PI:
Harold Watters, Assistant Professor
Ohio State University Extension
Field Specialist Agronomic Systems
1100 S. Detroit St.
Bellefontaine, OH 43311
Phone: Office – 937-599-4227, Cell – 937-604-2415
E-mail: watters.35@osu.edu
Co-PI:
Chia-Hua Lin, Postdoctoral Research Associate
Department of Entomology
Ohio State University – OARDC
1680 Madison Ave.
Wooster, OH 44691
Phone: Cell – 614-596-5167
E-mail: lin.724@osu.edu

EXECUTIVE SUMMARYFINAL DRAFT- Page 9 of 136 CDRC – March 2017

●

●

●

●

●

●

●

In the process of planting of corn seed treated with neonicotinoid insecticides(clothianidin and thiamethoxam) particles of seed treatment are released into theenvironment. Particles are deposited both within and outside the planted field
and are detectable at least 100 m from the field edge in the downwind direction.
Aerial transport implies that suspended seed treatment particles are present in
the air above and around a field during planting. (Section 2)
Honey bees come into contact with seed treatment particles during corn planting.
Clothianidin and thiamethoxam residues are reliably detected at elevated levels(8 ppb above background, on average) in honey-bee-collected pollen harvested
during corn planting. (Section 3)
The corn planting period is associated with a 2.3-fold increase in adult honey bee
mortality. A significant positive correlation was observed between adult bee
mortality and the concentration of seed treatment insecticides detected in pollen
collected over the same period. (Section 4)
Increased adult mortality is observed even though the level of seed treatment
detected in pollen is not at a concentration predicted to cause acute mortality.
This suggests that insecticide concentrations measured in bulk pollen serve as a
useful indicator of bee exposure, but fail to capture the mechanism of exposure
leading to bee death. (Section 1)
Despite elevated adult mortality during corn planting, the magnitude of seedtreatment insecticide exposure through pollen is not predictive of colony strengthin subsequent months or overwintering success. (Section 5)
Landscape composition, apart from the area of corn fields being planted, is notcorrelated with contamination of pollen with seed treatment insecticides or adultmortality. The magnitude of seed treatment exposure during corn planting is
positively correlated with the total area of corn fields, but not with weed
prevalence in corn fields or with the intersection of seed treatment drift and offfield foraging habitat. Adult mortality is not correlated with any landscapevariable. This tentatively suggests that honey bee exposure during corn planting
occurs primarily by aerial contact with ubiquitously dispersed seed treatment
particles, not by the contamination of in-field or off-field flora or by aerialintersection with a localized dust plume. (Section 7)
Mitigation recommendations (Section 9).
○ Engineering and quality-control measures to ensure seed treatments are
well-adhered to corn seed.
○ Reduced aerial mobility of insecticide-laden seed treatment particles
through planter modification, changes to seed treatment formulation
and/or use of fluency agent.
○ Use of an insecticide in corn seed treatments demonstrating a lower
toxicity to honey bees.
○ Reduced use of insecticides in treated corn seeds in accordance with theprinciples of “Integrated Pest and Pollinator Management”.

FINAL DRAFT- Page 10 of 136 CDRC – March 2017

OUTLINE
I.
II.
III.

IV.
V.
VI.
VII.
VIII.
IX.
X.

Introduction: Objectives and study setup
Section 1: Routes of exposure and implications for mitigation
Section 2: The release of neonicotinoid-laden dust during the planting of treatedcorn
A. Dust drift during planting
B. Qualitative assessment of seed treatment integrity
Section 3: Neonicotinoid contamination of honey- bee-collected pollen duringcorn planting
Section 4: Elevated mortality of adult honey bees during corn planting
Section 5: Effects on colony strength
Section 6: Spatial and taxonomic foraging patterns revealed by dance analysis
and pollen identification
Section 7: Landscape as a predictor of exposure and effects
Section 8: Simulation modeling of exposure via floral contamination and its
sensitivity to weed suppression
Section 9: Conclusions Mitigation recommendations

INTRODUCTION:
Study sites and apiary setup
Apicultural work was conducted at 10 apiaries, at least 3.5 km apart, in Central Ohio
(Figure 1, Table 1). Apiaries were either managed by the Ohio State University
research team or were managed by experienced private beekeepers.
We selected up to 4 overwintered colonies to be monitored for bee mortality andwinter survival at each apiary. Additionally, we installed two new colonies started frompackages and one from a 4-frame nucleus colony at six apiaries. All of the new colonies
were installed in 8-frame Langstroth hives on solid bottom boards. Other colonies were
overwintered colonies, usually in 10-frame hives, made available by cooperating
beekeepers.

FINAL DRAFT- Page 11 of 136 CDRC – March 2017

Figure 1. Apiary locations plotted over satellite imagery (Google OpenLayers).
Observation hives were installed in four apiaries (asterisked) to record dance activities.

FINAL DRAFT- Page 12 of 136 CDRC – March 2017

site

% cornbeekeepe

(2015

r

data)

a

hive
equipmentb

no. hives

new

dance

monitorecoloniesc

mapping

d

FSR

49%

OSU

8-f standard

4

yes

yes

MO

41%

private10-f palletized

6

yes

yes

TV

36%

private10-f standard

2

HR

31%

private10-f standard

6

yes

yes

WB

31%

OSU

8-f standard

4

yes

IB

28%

private10-f standard

2

BR

27%

private10-f palletized

2

MB

21%

private10-f standard

4

yes

SD

14%

private10-f palletized

6

yes

DS

< 1%

OSU

8-f standard2

yes

a: Percent area of corn fields within 2 km radius from the apiary, calculated by visualgroundtruthing and GIS analysis
b: Hive equipment used for the overwintered colonies being monitored. All colonies werehoused in 8- or 10-frame Langstroth hives, on standard or palletized bottom boards.
c: Three new colonies, two started from packages and one nucleus colony, were
installed and monitored.
Table 1: Apiary information

FINAL DRAFT- Page 13 of 136 CDRC – March 2017

Corn planting
In 2015, consecutive days of sunny, warm and dry conditions in Central Ohio allowed
farmers to complete most of the corn planting quickly in early May. Planting of corn fields
near the study apiaries started as early as April 28, although the most intense corn
planting activity was observed May 2 - 8. Planting in most corn fields was completed by
May 9, but sporadic planting continued through the end of June. Planting in all of Ohio
was estimated at 15% complete on May 3 and 55% complete on May 10 (USDA-NASS2015).
Landscape composition
Based on preliminary dance analysis from 2014 and published data (Couvillon etal. 2014), we chose to define our landscapes using a 2 km radius. This decision was
supported by our 2015 dance analysis that showed the bulk of foraging activity (~75%)
occurred within two kilometers of the hive.
Landscape methods: Using a combination of visual ground-truthing and satellite imagery
analysis (Google OpenLayers), we determined the composition of the landscapes
surrounding each of our apiaries in terms the following categories: crop field, forest,
treeline, herbaceous patch (e.g. CRP), herbaceous strip (e.g. field margins), roadside,and residential lot. Crop fields were further subdivided according to crop type and preplanting weed abundance. Pre-planting weed abundance was assessed by visualground-truthing on April 30 and May 1, immediately prior to the start of corn planting.
Fields were assigned a “bloom level” of 0 (no blooming weeds), 1 (scarce blooming
weeds), or 2 ( abundant blooming weeds).
The crop types in fields were determined initially by ground-truthing in June, 2015
and later, in January 2016, with the updated USDA Cropland Data Layer(http://nassgeodata.gmu.edu/CropScape/). All landscape data were analyzed andvisualized using QGIS software (QGIS Development Team 2015).
Landscape results: Our sites represented a wide range of corn abundance, from 49%(FSR) to an urban site with less than 1% (DS) (Figure 2). Soybean was the other major
field crop at each of our sites. Non-crop land cover (tree canopy, herbaceous,residential) were of relatively low abundance (<25%) at most sites, but were moreprevalent at MB (~50%), IB (~40%), SD (~35%), and predominant at the urban DS site(>99%).
The prevalence of blooming weeds in cornfields prior to planting was highlyvariable (Figure 3), presumably due to differences among farmers in herbicide
application and tilling practices. At one extreme, FSR had zero cornfield area classified
at the highest bloom level. In contrast, the vast majority of cornfield area at HR and SD
was classified as bloom level 2. Our estimates of pre-planting bloom abundance might
be confounded by herbicide application that occurred in between our ground-truthing
trips and the start of planting.

FINAL DRAFT- Page 14 of 136 CDRC – March 2017

Figure 2: Landscape composition summary within a 2km radius of apiary sites.
Corn and soybean were major landscape features at all sites except for the one urban
site, DS. Other field crops consisted of wheat, alfalfa and vegetable crops. Some fields
visible in satellite imagery could not be surveyed on the ground due to inaccessibility, sothese were classified as “undetermined”. “Tree canopy” is a combination of all forest,
tree line, and orchard land cover, excluding trees on residential properties. “Herbaceous”
includes all non-crop herbaceous land cover, e.g. field margins, roadsides, CRP strips,
and old fields, excluding herbaceous cover in residential properties. Residential
properties were typically characterized by a combination of tree canopy(ornamental/landscaping trees), lawns, gardens, and built structures. “Paved” land coverrefers to roadways and industrial/commercial lots.

FINAL DRAFT- Page 15 of 136 CDRC – March 2017

Figure 3: Pre-planting bloom abundance in cornfields. Bloom level 0 fields had
virtually no flowering weeds in them, due either to spring herbicide application or falltillage. Bloom level 2 fields had abundant flowering weeds, with purple deadnettle(Lamium purpurea), dandelion (Taraxacum officinale), and various mustards(Brassicaceae spp.) being the most common constituents. Bloom level 1 fields had
scarce and/or patchy flowering weeds. Given the relative abundance of flowering plants
in off-field habitats and bloom level 2 fields, we deemed bloom level 1 fields to be
essentially unattractive to honey bees.

FINAL DRAFT- Page 16 of 136 CDRC – March 2017

SECTION 1:
Routes of exposure and implications for mitigation
Potential routes of exposure. One of the key objectives of our study was to evaluationand discrimination between of the multiple routes of exposure (ROE) that contribute tohoney bee mortality during corn planting. While there is evidence for indirect ROE likewater contamination and systemic uptake by non-crop flora (Long and Krupke 2015), it islikely that the two most important ROE for honey bees during corn planting are (1) floral
contamination by deposited seed treatment particles and (2) aerial contact withsuspended seed treatment particles (Table 2).
Floral contamination by deposited seed treatment particles has been the primary
focus of CDRC research thus far. Within this ROE, it is important to distinguish two
subroutes: (1) the contamination of in-field flora (“weeds”) by the immediate settling ofseed treatment particles and (2) the contamination of off-field flora by the drifting of seedtreatment particles. Seed treatment deposition data generated in our dust collection
studies (Section 2) show that the magnitude of active ingredient deposited within aplanted field is dramatically higher than that deposited even just one meter beyond thefield edge. Moreover, the particles that settle immediately within the field are likely larger
and less concentrated with active ingredient (Devarrewaere et al. 2016) than theparticles that are carried off-field by air currents, potentially causing qualitative
differences exposure patterns.
Aerial contact between foraging bees and suspended seed treatment particles
has thus far received little attention in CDRC research, but there is evidence suggestingthat this ROE may be equally or more important than floral contamination (Girolami et al.
2011, 2013, Tapparo et al. 2012). Again, it is useful to distinguish two sub-routes. First,
bees in flight may intersect with the spatially and temporally localized plume of dust
emitted from a running planter. The potential for this exposure route to deliver highdoses of active ingredient to flying bees has been convincingly demonstrated (Girolami
et al. 2011, 2013, Tapparo et al. 2012)⁠, but distinguishing this route from floral
contamination is difficult in a field study such as ours. Bees exposed to a localized plumeof dust may die in the field and fail to be detected, and dust adhering to the body of aforaging bee would be groomed into corbicular pollen pellets, which, based on pollen
residue data alone, could easily be misinterpreted as evidence of floral contamination. It
is also possible, though, that in addition to the threat of localized dust plumes, very finedust particles may become suspended and widely distributed in the atmosphere, forming
a diffuse and persistent route of exposure that extends well beyond the immediate
vicinity of a planted field. This route of exposure remains largely unexplored, but it isplausible given the extremely small seed treatment particle sizes (as small as < 1 µm in
diameter) we observed with scanning electron microscopy (Figure 4, Section 2). Aubiquitous distribution of fine seed treatment particles could explain the exposure we

FINAL DRAFT- Page 17 of 136 CDRC – March 2017

detected at our urban “control” site, where corn comprised less than 1% of thesurrounding landscape.
Implications for mitigation. It is crucial to discern which of these ROE is/are the principal
driver(s) of honey bee poisoning because each interacts differently with proposed
mitigation schemes (Figure 5). If, for example, the main ROE is the contamination of offfield flora by drifting seed treatment particles, then the use of a deflector or fluency agent
to decrease particle mobility might dramatically reduce honey bee exposure. If, however,
the main route of exposure is the contamination of in-field flora by settling of seedtreatment particles, the use of a deflector or fluency agent might exacerbate exposure byconcentrating emitted seed-treatment particles within the field. Similarly, the suppressionof in-field flora might reduce exposure from settling seed treatment particles, but it would
do nothing to mitigate aerial exposure, and might even exacerbate aerial exposure by
forcing bees to spend more time in flight searching for resources. It is also important tonote, however, that multiple mitigation schemes could be combined. For example, adeflector could be used in combination with in-field weed control to keep released seedtreatment particles within fields that are free of bee-attractive flora.
In Sections 6 and 7, we present data on the spatial and taxonomic patterns ofhoney bee foraging at our sites
during corn planting. We thenanalyze these data with respect toour data on pollen contamination(Section 3) and adult bee mortality(Section 4) in an effort todiscriminate between the routes
and sub-routes of exposure
outlined in Table 2.

Figure 4: SEM of seed treatment
coating illustrating the potential for
extremely small articles to be shed.
The smallest particles in this image are <1µm in diameter, suggesting a strong
potential for aerial transport.

FINAL DRAFT- Page 18 of 136 CDRC – March 2017

Table 2: Hypothesized routes of exposure and corresponding predictions of
exposure patterns.
Major RouteSub-route

Predicted patterns of exposure

Off-field drift

●
●
●
●

Moderate frequency
Low-moderate magnitude
High variability
Strong influence of proximity of foraging habitat tofield edge at foraging scale

In-field
settling●●●●

Moderate frequency
Moderate magnitude
Moderate-high variability
Strong influence of weed management in cornfields at foraging scale

Localized
plume

●
●
●
●

Low frequency
High magnitude
High variability
Strong influence of corn area at foraging scale

Ubiquitous
dispersal●●●●

High frequency
Low magnitude
Low variability
Strong influence of corn area, potentially beyond
foraging scale

Floral Contamination

Aerial Contact

FINAL DRAFT- Page 19 of 136 CDRC – March 2017

Figure 5: Interactions between hypothesized routes of exposure and proposed
mitigation schemes.

FINAL DRAFT- Page 20 of 136 CDRC – March 2017

SECTION 2:
The release of neonicotinoid-laden dust during the planting of treated corn

Dust drift during planting
Methods. A wide selection of planting equipment was evaluated in 2015 for the releaseof seed treatment insecticides, with the goal of gaining an overall picture of the variability
in seed treatment release in different circumstances. Eight sites were located in central
to west central Ohio, with an additional two just across the western border into Indiana.
Planter type–including make, model and serial number–were recorded as well as thetype of seed and insecticide seed treatment at each site. A sample of the seed planted
was retained for qualitative assessment of seed treatment integrity. During the planting
operation, local wind conditions were measured at each field using a handheld windmeter. Wind direction was determined by compass. Relative humidity and temperature
were collected at the time of planting from the nearest fixed weather station via the
WeatherBug app.
Dust (potentially with insecticide) was collected with a target array arranged under theplanter and downwind from the planting activity. The concentration of clothianidin andthiamethoxam in ng/sq cm of the slide was used to determine the relative amount ofinsecticide-laden dust escaping from the planter. Seed treatment dust traveling
downwind was collected using Krupke-style dust collection stations (Krupke et al. 2012).
The collection stations were constructed from PVC pipe which held two sets of slide
trays: one in a horizontal orientation 30 cm above the ground to estimate dust deposition
on herbaceous flowers, and a second in a vertical orientation 2 m above the groundperpendicular to the wind to intercept blowing dust.
The slide tray targets were made up of five microscope glass slides held together byplastic grip strips glued to a piece of cardboard. Stations were held in place by a cleatedfence post so that the horizontal and vertical dust collectors would remain fixed at thecorrect orientation and height (30 cm and 2 m). Slides were attached once the PVC
frame was set up and before planting began, then were treated with aerosol Tangle-Trap
Sticky Trap Coating to hold dust particles.
Either a conventional farmer supplied seed lubricant (talc, graphite or blend) or theBayer fluency agent was used, each added according to directions from the
manufacturer. The Bayer fluency agent used consists of ethane, a homopolymer, at a
rate of 1/8 cup for every 80,000 seed. On one occasion the grower used Bayer fluency
agent treated seed (from the seed provider) but added their own lubricant to it as well. In
2015, a higher priority was given to planter variety than seed lubricant choice.
The stations were placed perpendicular to the orientation of the planting passes andplaced at 10-meter downwind of the planter starting point. Four detectors were set andspaced approximately 30 m apart. Planting began after station placement and continued
until approximately 100 m of field was planted beyond the starting point. Time of
exposure was recorded. Slide trays were also placed under the planter for one pass, tocollect dust ejected downward from the planter. The trays were then picked up andstored in a dust free area after that single pass.

FINAL DRAFT- Page 21 of 136 CDRC – March 2017

Slide trays from the field were removed immediately after planting. Slides wereorganized and stored in a dust proof cardboard box; taped and sealed. In 2015, whenfinished with a site slide trays were placed in a dry Coleman cooler, transported withinapproximately two hours to a secure chest freezer at the Western Agricultural Research
Station near South Charleston Ohio, and maintained at 0 degrees C for approximately
two weeks.
On June 10, 2015 the center 3 slides from each set of 5 were placed in a 50mL conicaltube separated by pipette tips so that their surfaces were not touching. Tubes werelabeled and set into a cooler of dry ice to transport to the lab freezer. Processed inbatches of 6 to 15 tubes, each tube was filled to the 50 mL mark with acetonitrile. Eachtube then received 10 microliters for 2 µg/ml d-4 imidacloprid in acetonitrile as an internal
standard. The tubes were resealed and sonicated at room temperature for 1 hour in thedark, then sat in the dark sonicator for an additional 23 hours.
After the 24 hour soaking period, liquid was transferred to another conical tube. New
tubes were placed under a nitrogen stream to dry to less than 1.5mL in volume. Drying
took between 6 and 15 hours, and remaining liquid was transferred to an Eppendorf
tube. Eppendorf tubes were then handed off to the university Mass Spec & Proteomics(http://www.ccic.ohio-state.edu/msp) lab staff to measure insecticide levels.

a.

b.

Instrumenti.

LC: Dionex UltiMate 3000

ii.

MS: Waters Xevo TQ-S

LC conditionsi.

Column: Waters XBridge BEC130 C18 (1*100 mm, 3.5 µm)

ii.

Column temp: 30 oC

iii.

Solvent A: aqueous NH4COOH (5 mM) with 0.1% formic acidiv.

Solvent B: ACNv.

Flow rate: 100 µL/minvi.
Gradient: 0 min, 5% B; 1 min, 5% B; 5 min, 90% B; 7 min, 90% B;
7.5 min, 5% B; 13 min, 5%B
c. MS channel -- The ion pairs of 256.0/209.0, 250.0/169.0, 292.0/211.0, and
260.0/213.0 are used to monitor the conc. of imidacloprid, clothianidin, thiamethoxam,and internal standard imidacloprid-d4; and the collision energy is 15, 12, 10, and 15 eV,
respectively. All other parameters are tuned to give the optimized MRM signal.

FINAL DRAFT- Page 22 of 136 CDRC – March 2017

Table 3. 2014 Ohio Corn Dust sites

Site

1b
& 1f

2b
& 2f

3b
& 3f

4f

Ohio
Location

Mechanics
burg

Planter

Type

Kinze
3660

Center fill,
nonvacuumrow

Insecticide

Clothianidin 500

Seed
Company

Lubricanttreatment

Beck'sBayer fluency
agent or Kinze
graphite

MonsantoBayer fluency
agent or John
Deere Premium
Talc

Beck'sBayer fluency
agent orPrecision Plant
E-flow

Clothianidin 250

Beck'sJohn Deere
Premium Talc

Insecticide

Seed
Company

Lubricanttreatment

Beck'sPrecision
Planting E Flow
Seed Lubricant
1/2 rategraphite-talc
blend

Dekalb/Delaware

John
Deere
1770NT

Row unit
vacuumLondonJohn
Deere
1770NT

Center fill &row unit
vacuumKentonJohn
Deere
1770NT

Center fill &row unit
vacuumClothianidin 500

thiamethoxam

Table 4. 2015 Ohio Corn Dust sites

Site

5f

Ohio
Location

LondonPlanter

Case IH Early
Riser 1255 AFS

Type

Center fill,
vacuumrow

Poncho1250/
clothianidin

Dekalb/6f

7f

Delaware

John Deere
1770NT

Row unit
vacuumNevadaJohn Deere
7200
Conservation

Row unit
vacuumClothianidin
500
Poncho1250/
clothianidin

MonsantoJohn Deere Talc

Beck's

1/2 rate John
Deere Talc, BFA
Pretreated seed

FINAL DRAFT- Page 23 of 136 CDRC – March 2017

Case IH Early
Riser 1255 AFS

Center fill,
vacuumrow

Poncho1250/
clothianidin

Beck's

Kinze graphite
on left, BFA on
right

9f

Gettysb
urg

Kinze 3600

Center fill,
vacuumrow

Cruiser 250

Master's
ChoiceKinze graphite

10b

Ridgeville, INWhite-MasseyFergusson/Agc
o 8800Air
pressure
row unit

Clothianidin
250

Stewarts

Bayer Fluency
Agent

MarionJohn Deere
7200
Conservation

No air,mechanica
l meterPoncho1250/
clothianidin

Beck'sJohn Deere
Graphite

Beck'sPrecision
Planting E Flow
Seed Lubricant
graphite- talc
blend

8b
& 8f

Ridgevill
e, IN

11f

12f

VersaillesJohn Deere
1770NT

Vacuumrow unit

Poncho1250/
clothianidin

Figure 6: Comparison of insecticide levels by seed lubricant from under plantertargets, 2014 and 2015.
Results and Discussion. Comparisons – Figures 6, 7, 8 and 9 shown indicate the levelof insecticide in dust collected on field placed slides. The whiskers represent the min andmax values, and the box encompasses the first quartile through the 3rd quartile. The
accompanying Appendix C includes site by site dust analysis values.
As seen in Figure 6 and discussed in the 2014 report, any reduction in the levelof insecticide differs between the two types of lubricant shown – the Bayer fluency agent
vs. the farmer choice – is not large. While a broader range of insecticide occurred withthe farmer chosen seed lubricant, much overlap between the two treatments is apparent.

FINAL DRAFT- Page 24 of 136 CDRC – March 2017

Figure 7: Comparison of insecticide levels by seed lubricant from ten-metertargets, from the high (2m) and low (0.3m) targets for 2014 and 2015.
Shown in Figure 7 are the comparisons between the Bayer fluency agent and the farmer
choice treatment. The 10-meter distance was chosen as the distance for comparison.
Detectors were set at a 10-meter distance from the planter on the first pass, thenallowed to collect dust as the planter made progress across the field until approximately
100 meters distance was achieved. H indicates the high (2m) target and L the low (0.3m)
target.
As seen in Figure 8 and discussed in the 2014 report there is little evidence that thelevel of insecticide leaving the planter differs between the two types of lubricant shown –the Bayer fluency agent vs. the farmer choice under the planter. Here at the 10-meter H
location the Bayer treatment has a broader range of values, but for the L height thefarmer treatment has a wider range – still at both heights at a 10-meter distance there isgreat overlap between the values.

FINAL DRAFT- Page 25 of 136 CDRC – March 2017

Figure 8. Comparison of insecticide levels by location and planter from underplanter targets, 2014 and 2015.
Planter design for seed delivery to the ground uses many methods; center fill hoppers orindividual row hoppers, and from pressurized systems to vacuum systems. The sites for2015 were chosen to broaden the range of planter types and manufacturers beyond the2014 sites and planters.
Range of planters for 2014 & 2015 –●●●Manufacturero John Deere 1770NT (5) and 7200 (2), Kinze (2), CaseIH (2), White/Agco(1). This range approximates the percentage type of planters in use
today.
Hopper typeo Center fill (CF) – requiring an air system to move seed to the row unit orindividual row unit seed box – with no air delivery
Air systemo No air at the row unit – meaning a mechanical finger pick up is used
(Mech), vacuum at the row unit (Rv), or air pressure at the row unit (Rair)

From 2014, it appeared there may be some planter differences that might lead toa reduction in released insecticide. As shown in Figure 8, and across the two years andtwelve planters it would appear that planter manufacturer or type does not have a
discernable impact on insecticide release. There is some indication that mechanical,
finger pickup type row units can reduce dust release but other types on occasion canalso meet these levels of release as well. One question from growers during wintermeeting discussions was whether the old stand-by finger pick up and row unit boxes withno air or vacuum could eliminate the insecticide loss – but that idea did not help as site
number eleven was that type and still had release of insecticide. Lack of gasketing orseals can lead to loss of the seed treatment insecticide through gaps in the assembly.

FINAL DRAFT- Page 26 of 136 CDRC – March 2017

Figure 9. Comparison of insecticide levels by site from ten-meter targets, from thehigh (2m) and low (0.3m) targets for 2014 and 2015.
Shown in Figure 9 are the 10-meter site values for insecticide. Generally, the 10-meter
incidence follows the under planter target levels for indications of loss from the planter.
Exceptions for sites 7 and 12 may be explained by the higher wind speed at the time of
the trial – in the range of 10 to 15 miles per hour. Site 3, with the highest level of
insecticide loss with the Bayer treatment, had low 10-meter insecticide levels.
A sample of the seed planted was retained for potential analysis in a Heubach
dustmeter. This seed was collected during the mid- to late-planting time period for eachsite. This was after the seed had ample opportunity to bounce and shake in the seedhopper across the field. It was noted and farmers discussed the amount of dyed seedcoat debris remaining in the hoppers during seed changes. On at least one occasion theappearance of seed treatment chips were evident on the target slide.
Qualitative assessment of seed treatment integrity
Methods. Color macrophotography and scanning electron microscopy (SEM) (Figure10) were used to perform a qualitative assessment of the integrity of seed treatment
material on treated corn seeds. Seed samples were taken directly from the seed units ofplanters being used by cooperating growers; seed was collected about halfway throughthe planting process, allowing time for normal seed agitation and abrasion to occur. After
collection, seed samples were stored in plastic freezer bags or conical vials at -20°C
until further analysis. Photography and SEM was performed in November 2015 (6months after planting). Seeds were selected at random by shaking a few seeds out ofeach sample container. An exception to this is the seed pictured in Figure 10 (B2),
which was intentionally selected due to its striking lack of seed treatment material. For
macrophotography, seeds were arranged on a white background and photographedusing a Canon SL1 (crop sensor) camera with a 65 mm MPE Macro lens, a Laowa Twinlight flash, and a custom diffuser. For SEM, seeds were mounted on stubs using carbon
FINAL DRAFT- Page 27 of 136 CDRC – March 2017

sticky pads, coated with platinum, and imaged on a Hitachi S-3500N scanning electron
microscope. All seed samples remain stored at room temperature for further analysis.
Results and Discussion. All examined corn seeds showed signs of seed treatment
degradation, varying in severity (Figure 10). We noticed no obvious differences between
conventional treated seeds and those from companies that advertise a special polymer
to enhance sticking, though our analysis was not systematic. Seed treatment material
also visibly accumulated on the gloved hands of the investigator who prepared the seeds
for photography and microscopy, and the readiness with which the seed treatment
material shed from the surface of the seed made it difficult to secure seeds to SEM stubs
using standard carbon sticky pads.

FINAL DRAFT- Page 28 of 136 CDRC – March 2017

Figure 10: Photographic and microscopic assessment of seed treatment integrity.
Seeds varied in the perceived integrity of the coating, but most showed signs particle
generation. In an extreme case, we found one seed that had almost no coating left on it(B2), though this was the only example we noticed of such extensive degradation. Seedtreatment appears to crumble away leaving patches of bare seed surface (smoothly
striated patch in middle) visible by SEM (bottom right). Shed particles vary widely in size.
The seeds pictured here came from the same batches of seed listed in Table 4, though
they are deliberately not presented in the same order. Photos by M. Spring, SEM by D.
Sponsler.

SECTION 3:
Neonicotinoid contamination of honey- bee-collected pollen during corn planting
Methods: A 3 g subsample of the bulk pollen collected from each site every 3-4 days
was submitted to the EPA Ecosystems Research lab in Athens, Georgia forquantification of neonicotinoid concentrations. Analysis results for samples collected on
May 2 -27 are presented in Figure 11 and Appendix A.
Results and Discussion: Clothianidin and thiamethoxam residues were detected in most
samples of pollen collected throughout May. Higher levels were observed May 2 - 8
when most corn was being planted, even at the urban “control” site (DS) . Pollen
collected during the peak corn planting window contained significantly more seedtreatment insecticide, 8.2 ppb more, than pollen collected at other times (Welch’s T-Test,
df=33.73, p=0.03). High levels of seed treatment insecticide in pollen observed after themain corn-planting period may be related to late-season planting near the study apiaries.
The concentrations observed in pollen (Appendix A) are well below the concentrations
predicted to cause mortality in nurse bees consuming pollen (predicted thiamethoxam
LD50 in pollen = 536 ppb; predicted clothianidin LD50 in pollen = 389 ppb). See
Appendix B.

FINAL DRAFT- Page 29 of 136 CDRC – March 2017

FINAL DRAFT- Page 30 of 136 CDRC – March 2017

Figure 11: Summary of pollen contamination with seed treatment insecticides (above)and dead bee trap catch (below) for 10 apiary sites. The peak corn planting window(May 2 - 8) is shaded with a gray box. Dead bee trap catches, calculated per day, forindividual colonies is indicated with thin lines while the apiary mean is presented in a
thick black line.

FINAL DRAFT- Page 31 of 136 CDRC – March 2017

SECTION 4:
Elevated mortality of adult honey bees during corn planting
Methods. Drop-zone dead-bee traps (40”x20”) were placed in front of each colony being
monitored. Dead bees were counted and traps were emptied every 3 - 4 days from April
26 to June 2. Trap catch for each sampling period was standardized to calculate thenumber of dead bees collected per day. For statistical analyses of the number of deadbees two related approaches were taken. To relate dead bees to insecticidecontamination in pollen the dead bees collected from traps at each colony wasstandardized by day, divided by the mean number of dead bees collected per day overthe entire month of sampling, then the natural log was taken of this ratio. The mean ofthese values was then taken for all colonies at each site for each sample collection
period. To relate dead bees to corn planting and landscape measures the mean dailydead bees ejected by each colony was taken for the peak corn planting period and thenon-planting period. Each of these values was divided by the average daily dead bees
for the whole month, then a natural log was taken of ratio.
Results. There was a 2.3-fold increase (95% CI=2.0 - 2.8) in the number of dead bees
collected in dead bee traps during the peak corn planting period relative to non-planting
periods (Welch’s Two-sample T-test, t=10.29, df=18, p-value < 0.0001) (Figure 11).
There was also a significant positive correlation between the concentration of seedtreatment insecticides in pollen and the number of dead bees captured in dead bee traps(Pearson’s correlation, df=86, r=0.34, p=0.001).

SECTION 5:
Delayed effects and long-term recovery
Post-planting colony growth. To evaluate colony-level effects of exposure to corn seedtreatment insecticides emitted during planting, we quantified hive parameters including
adult bee populations (“seams” of bees, the spaces between frames filled with bees
when viewed from above, as well as frame area covered by bees), brood (open andcapped), pollen, and honey on the frames of each hive with four complete inspections:
April 28 – 30 (before planting), May 20 – 22 (after planting), June 19 - 24, and August 14- 19. Quantitative changes of these hive parameters between inspections were recorded.
Despite a significant correlation between levels of seed treatment insecticides in pollen
and average mortality during the peak planting period (see Section 4), we did not detectsignificant correlation between insecticide levels in pollen and any of the hive
parameters in the first inspection interval (April - May, Pearson’s correlations, P > 0.15
for all comparisons). During the second interval (May - June), a positive correlation was
found between adult population (seams of bees) and the summed concentration of seedtreatment insecticides detected in pollen during peak planting (r = 0.66, P = 0.037). This

FINAL DRAFT- Page 32 of 136 CDRC – March 2017

increase in adult bees may reflect post-exposure population rebounds or other
responses to environmental variations independent of exposure.
Hive parameters in June - August showed no correlation with spring exposure to corn
seed treatment insecticides, but increases in pollen and nectar stores were observed at
apiaries surrounded by more corn fields (pollen: r = 0.79, P = 0.007; nectar: r = 0.67, P =0.038); this observation may be associated with food sources such as clover and othersummer wildflowers grown in grassy fields, roadsides and field margins and blooms ofsoybean cultivation, which is often planted as a rotating crop along with corn (Sponsler
and Johnson, 2015; Lin et al. 2016).
Overwinter survival. Of the 38 colonies being monitored, one colony at MO died in latesummer and three colonies at HR were relocated to another location by the beekeeper
and were excluded from overwinter monitoring. Therefore, a total of 34 colonies wereprepared for overwintering at the end of September. Colonies were checked 3 - 4 times
as weather permitted during October - February. Plain baker’s fondant and Dantant
AP23 winter patties were fed to the colonies as needed and vaporized oxalic acid wasapplied to all colonies in November to control varroa mites. Thirty one of the 34 colonies(91%) were alive at the end of March, 2016 although one of the surviving colonies wasqueenless and had developed laying-workers. No significant correlation was detected
between overwinter survival and the level of corn seed treatment insecticides in pollen or
percent corn area in the surrounding landscape across the 10 sites (Spearman’s rankcorrelation tests, P > 0.36 for all tests).

SECTION 6:
Spatial and taxonomic foraging patterns revealed by dance analysis and pollen
identification
Honey bees communicate to one another the location of valuable foraging patches bymeans of the “waggle dance” (von Frisch 1967). Because this dance language can be
decoded by human observers, it can provide a unique glimpse into the spatial foraging
patterns of a honey bee colony (Couvillon and Ratnieks 2015). These patterns can be
combined with the identification of honey- bee-collected pollen to yield both spatial andtaxonomic insight into the relationship between a colony and its surrounding landscape.
Such insight is central to the question of how honey bees are exposed to seed treatment
particles during corn planting, particularly via the floral contamination route of exposure(Section 1).
Dance analysis methods. A glass-walled observation hive (Bonterra Bees, Addison, ME;
SV-3TV), housed in a temporary shelter (Suncast Toter Trash Can Shed, Figure 12),
was installed at each of four apiaries: MB, HR, MO and FSR. These sites represented arange of corn abundance, consisting of 21%, 31%, 41%, and 49% corn within a 2 km
radius, respectively. These sites also varied in landscape complexity, from the mosaic ofFINAL DRAFT- Page 33 of 136 CDRC – March 2017

small crop fields, residential lots, and uncultivated areas at MB to the morehomogeneous crop-dominated landscape at FSR (Figures 16-19). Weedy fields wererelatively abundant prior to planting at MB, HR, and MO, but were extremely scarce at
FSR, reflecting local differences in tilling and herbicide practices (Figure 3). HR andespecially MC had notably more residential habitat than MO or FSR.
Each observation hive consisted of three standard deep frames populated withbees, brood, and a naturally mated queen. Using a wooden diverter at the hive entrance(Seeley 1995), all returning foragers were directed to one face of the bottom frame fromwhich video was recorded using an HD video camera (Canon Vixia HF G20). We
recorded dances only on days when weather conditions were favorable for foraging(sunny or partly cloudy with temperature above 65 F). Approximately one hour of bee
activity video was recorded at the observation hive on a recording day. We thensubsampled one 60-second segment for every 5 minutes of the video (12 segments perhour) and decoded all dances contained in these segments, following Couvillon et al.
(2012) adapted for use with FIJI biological image analysis software (Schindelin et al.
2012). Decoded dances were then mapped using the probabilistic method described by
Schürch et al. (2013) and in implemented in R software(R Core Team 2015).

FINAL DRAFT- Page 34 of 136 CDRC – March 2017

Figure 12: Shed housing a 3-frame observation hive.
Pollen identification methods. Pollen was collected every 3-4 days from two healthy
queen-right overwintered colonies at each site using bottom mounted pollen traps(Sundance I). Pollen traps remained in the “on” position throughout the study period.
Because of the effect that continual pollen trapping may have on colony health we did
not collect any other data from the colonies used for pollen collection. Pollen was pooled
from the two colonies to provide a single pollen sample for each site, which wasweighed, bagged and stored at -20°C. A total of 100 pollen samples (10 sampling dates
per site) were collected during April 26 - May 27.
Microscopic pollen identification. Pollen samples were identified by pellet color and by
microscopic palynology (Erdtman 1969). Ten grams of pollen from each site and foreach collection date were sorted into distinct color categories, and the relative proportionof each color category was estimated by weight. A 10% subsample from each color
category was blended in water and four drops of the pollen suspension were mounted
separately in basic fuchsin jelly on glass slides for microscopic examination. The pollentype(s) associated with each color category were determined by microscopic comparison
with reference pollen collected from fresh flowers.
Molecular pollen identification. The development of novel techniques for the molecular
identification of bee-collected pollen has been fruitful and we have published two papers
detailing our methods (Richardson et al. 2015; Richardson et al. 2015). While thesemethods papers have provided a strong foundation for the nascent field of molecularpollen analysis, we are currently working to further improve our method in order toFINAL DRAFT- Page 35 of 136 CDRC – March 2017

increase sample throughput capacity, decrease costs and improve our data analysis
approach.
Using our current protocol, DNA is first extracted from pollen samples using abead beater and the QIAGEN DNeasy Plant Mini Kit. Five plant barcoding loci, ITS2,
matK, rbcL, trnL and trnH, are then amplified in separate PCR reactions using primers
modified to include the Illumina MiSeq read priming oligo at the 5’ end of each primer. At
this point, 1 µL of PCR product from each reaction is used in a second PCR to append
sample-specific dual indices and the Illumina MiSeq lane hybridization oligo to each
amplicon library as in McFrederick et al. (2016)2015. Following this second PCR, 3 µL of
product are analyzed using gel electrophoresis to ensure amplification success and 20µL of the remaining PCR product are purified and normalized for sequencing using the
SequalPrep Normalization Plate Kit. Normalized libraries are then pooled in equimolar
amounts and the resulting pool is analyzed on a Qubit 2.0 fluorometer and an Agilent
2100 Bioanalyzer to ensure adequate quality and concentration before being sequenced
on an Illumina MiSeq platform.
To better analyze our pollen metabarcoding sequence data, we have beenworking closely with Johan Bengtsson-Palme, author of the Metaxa2 sequence classifier(Bengtsson-Palme et al. 2015), to improve the bioinformatics pipeline used to infer plant
species from sequence data. This new approach outperforms other classifiers in termsof both accuracy and sensitivity.
Results. Pollen samples collected at the four apiaries with observation hives have been
identified using microscopy and quantified during the corn-planting period (Figure 13,
Table 5). Pollen samples collected on April 29, before corn-planting, consisted of 29 –90% herbaceous plants, predominantly dandelion (Taraxacum officinale), mustards(family Brassicaceae) and purple deadnettle (Lamium purpureum). The majority (>95%)of the herbaceous pollen sources are weeds found in fields, field margins, roadsides,
lawns and uncultivated herbaceous vegetation.
Pollen from herbaceous plants gave way to pollen from trees and shrubs as
farmers began planting corn and soybean around May 2. Only 3 – 14% of the pollen
collected on May 8 originated from herbaceous plants. During this time, wild andcultivated trees in the Family Rosaceae, such as hawthorn (Crataegus spp.), apple(Malus spp.), cherry (Prunus spp.), and serviceberry (Amelanchier spp.) were the mostforaged pollen sources by honey bees. After the rosaceous trees, the second mostabundant pollen collected by bees was from ash trees (Fraxinus spp.). Pollen of othertrees including willow (Salix spp.), oak (Quercus spp.), mulberry (Morus spp.), and trees
in the family Fabaceae (e.g., redbud, Cercis canadensis) were also common in our
samples. Bees also collected pollen from honeysuckle (Lonicera spp.) and autumn olive(Elaeagnus umbellata), which commonly grow near forest edges and along roadways.
The phenological switch from field weeds to mass-flowering trees and shrubs occurringfrom late-April to mid-May is consistent with our 2013 – 2014 pollen collection data.

FINAL DRAFT- Page 36 of 136 CDRC – March 2017

Figure 13. Pollen types collected from four sites (FSR, MO, HR, and MB) from April
29 – May 8. The percent abundance shown for each pollen type is the average of its
percent abundance across all four sites.
Trees and shrubs

Herbaceous plants

Site

Rosacea
e
Ash

FSR

42.2%

22.6%

1.2%

7.6%

73.6%

22.6%

1.3%

2.4%

26.3%

MO

25.6%

15.6%

10.6%

4.4%

56.1%

9.7%

27.7%

6.4%

43.8%

HR

23.2%

23.0%

4.2%

18.7%

69.1%

13.1%

6.5% 10.6%

30.2%

MB

53.8%

14.0%

6.4%

16.1%

90.3%

9.6%

0.01%

0.2%

9.7%

Overall

35.4%

19.0%

5.6%

11.6%

71.4%

13.9%

9.3%

5.1%

28.4%

Willow

Other

Sum

Dandelion Mustards Other

Table 5. Summary of major pollen sources collected from April 29 - May 8.

FINAL DRAFT- Page 37 of 136 CDRC – March 2017Sum

Dance analysis revealed that foraging activity tended to occur within a 3 km
radius (Figure 14), but foraging distances varied between sites (Figure 15). Foraging“hotspots” generally agreed with the phenological changes observed in the assemblagesof bee-collected pollen. At MB, HR, and MO, where weedy fields were abundant, dancesindicated frequent foraging activity in fields close to the hive on May 4 - 5. This patterncorresponded with the higher proportion of weed pollen collected before May 5 at thesesites. As field weeds were removed and fields were prepared for planting, bees
increasingly foraged on resources outside crop fields and, consequently, collected lesspollen from weeds. Bees returned to forage in fields toward the end of May after mostplanting had been done and other wildflowers were beginning to emerge. At FSR, wherevery few floral resources were present in the surrounding fields, bees were forced totravel farther to find floral resources. As a result, bees at this site on average foraged for
longer distance and the hotspots were relatively diffuse (Figure 15).

Figure 14: Visitation probability by distance, pooled across all sites and dates.
Dashed lines indicate the distances at which 50% (blue) and 95% (green) of total
visitation probability were accounted for. Visitation probability can be understood as aproxy of total foraging activity. When data were pooled across all sites, the 50% ofFINAL DRAFT- Page 38 of 136 CDRC – March 2017

foraging activity occurred within about 1100 m of the hive, and 95% of foraging activity
occurred within about 3000 m from the hive. The red curve represents a nonlinear leastsquares regression of visitation probability on distance.

Figure 15: Visitation probability by distance at each site. Dashed lines indicate thedistances at which 50% (blue) and 95% (green) of total visitation probability were
accounted for. Visitation probability can be understood as a proxy of total foraging
activity. The red curve represents a nonlinear least squares regression of visitation
probability on distance.

FINAL DRAFT- Page 39 of 136 CDRC – March 2017

Figure 16. Pollen collected by bees at MB on April 29 - May 8 (top), landscape withfield bloom level before planting (bottom left), and two dance maps recorded during thisperiod (bottom center and right). Bees foraged over all land classes, with higher foraging
probability over wooded and residential areas. On May 5 (35 dances recorded), foraging
was concentrated near residential areas and tree lines close to the apiary. On May 6 (26dances), activities occurred throughout the 2 km radius area with high concentrations in
the residential area where the apiary was located. Some bees were also foraging
beyond the 2 km range.

FINAL DRAFT- Page 40 of 136 CDRC – March 2017

Figure 17. Pollen collected by bees at HR on April 29 - May 8 (top), landscape withfield bloom level before planting (bottom left), and two dance maps recorded during thisperiod (bottom center and right). On May 5 (26 dances), bees foraged predominantly inweedy areas and adjacent tree lines; very concentrated activities were observed in theweedy field adjacent to the apiary. On May 7 (33 dances), foraging activity was reduced
in weedy fields and became more concentrated along tree lines; bees also foraged
beyond the 2 km range to the SW of the apiary. We also noticed farmers applying
herbicides to many of the fields here during this time. Removal of field weeds may have
driven the bees from fields to forage on trees and travel longer distances for suitable
resources.

FINAL DRAFT- Page 41 of 136 CDRC – March 2017

Figure 18. Pollen collected by bees at MO on April 29 - May 8 (top), landscape withfield bloom level before planting (bottom left), and two dance maps recorded during thisperiod (bottom center and right). On May 4 (35 dances), dense foraging occurred about
1.5km from the hive in fields, forests and uncultivated herbaceous habitats. On May 7(27 dances), foraging became less intense in fields and more concentrated inuncultivated areas and at longer distances from the hive.

FINAL DRAFT- Page 42 of 136 CDRC – March 2017

Figure 19. Pollen collected by bees at FSR on April 29 - May 8 (top), landscape withfield bloom level before planting (bottom left), and two dance maps recorded during thisperiod (bottom center and left). On May 5 (26 dances recorded), bees foraged heavily on
the field margins, forest edges, and the residential lot to the west and NW of the hive.
Some bees were also foraging approximately 2.2 km on the SW near an interstate
highway. Similar resources were being used on May 6 (35 dances), with moreconcentrated activities near the forested area. Additional activities were observed on theeast side along field margins and approximately 3 km outside the mapped landscape.

SECTION 7:
Landscape as a predictor of exposure and effects
Testing predictions of hypothesized routes of exposure. Each of the four routes of
exposure (ROE) proposed in Section 1 implies a distinct prediction about the role thatlandscape plays in modulating the exposure of honey bees to seed treatment particles(e.g. pollen residues) and the effects thereof (e.g. adult mortality) (Table 6). Thus, theFINAL DRAFT- Page 43 of 136 CDRC – March 2017

relationship between landscape and exposure/effects can be used to test the plausibilityof each ROE.

Route of exposure

Predicted relationship to landscapeFloral contamination: infield settling

Exposure and effects are a function of the amount of corn fieldarea containing blooming weeds at the time of planting.

Floral contamination:
off-field drift

Exposure and effects are a function the amount of intersection
between the off-field drift of dust and honey bee foraging habitat

Aerial contact:

Exposure and effects are a function of total corn area surrounding
the colony

localized plume
Aerial contact:
ubiquitous dispersal

Exposure and effects are a function of total corn area surrounding
the colony and possibly regional corn prevalence

Table 6: Predictions of each hypothesized route of exposure.
Methods. The landscape surrounding each of our apiaries was first digitized andcharacterized according to the methods described in the Introduction. Further
processing was necessary, though, for the statistical testing of hypothesized ROE.
First, the concept of “foraging habitat” had to be formalized in relationship to ourlandscape classification. Based on the floral surveys we conducted in the field, we choseto classify the following landscape elements as foraging habitat: bloom level 2 crop
fields, residential areas, forests/tree-lines, and non-crop herbaceous vegetation(roadsides, field margins, fallow fields).
Next, we rasterized the vector layers of our digitized landscapes and performed aseries of functions using the R packages “raster”, “rgdal”, and “rgeos”.
1. Using the rasterized crop layer from each of our landscape, we calculated a newraster layer in which the value of each cell was equal to its distance to thenearest corn field (corn distance raster).
2. We fit our 2014 dust drift data with a non-linear function modeling the relationshipbetween dust deposition and distance from corn field edge. We then applied thisfunction to the corn distance raster described above to create a new raster ofpredicted neonicotinoid concentrations (contamination raster).
3. Because honey bee foraging is strongly constrained by distance, a contaminatedpatch located close to a colony poses greater risk than an equally contaminatedpatch far from the colony. We formalized the distance-bias of honey bee foraging

FINAL DRAFT- Page 44 of 136 CDRC – March 2017

by fitting a non-linear function to our pooled dance data (Section 6) that models
visitation probability as a function of distance from the hive. We then applied thisfunction to a raster whose cell values were equal to the distance of each cell fromthe hives at the center of the landscape. This resulted in a new raster predicting
the probability of each patch being visited based solely on its distance from thehive (visitation probability raster).
4. We then multiplied the contamination raster by the visitation probability raster toyield a raster in which contamination values (i.e. hazard) are weighted bydistance (i.e. probability of exposure) to yield a risk raster (risk = hazard x
exposure).
5. This risk raster was then constrained in various ways to isolate the componentsof risk needed to test each hypothesized ROE.
a. In-field settling hypothesis => risk raster constrained to bloom level 2 cornfieldsb. Off-field drift hypothesis => risk raster constrained to foraging habitat
outside corn fields
c. Localized plume hypothesis => risk raster unconstrained by habitat typed. Ubiquitous dispersal hypothesis => risk raster replaced with non-distanceweighted corn area

The cumulative risk (sum of all cells in the raster) of each constrainment of therisk raster was then used as the explanatory variable in a statistical test of eachhypothesized route of exposure (Table 7). In each test, cumulative pollen seedtreatment residues during the peak corn planting window (Section 3) and the adultmortality ratio (Section 4) were used separately as response variables. Because of
skew in our data, we used the nonparametric Spearman’s rank-order correlation
coefficient for all tests. Also, one study site (SD) was omitted from the test of the in-field
floral contamination hypothesis because 40% of its corn fields were inaccessible for preplanting bloom assessment.
Results and Discussion. Pollen seed treatment residues were significantly predicted byunweighted corn area (rho = 0.77, p = 0.01) (Figure 20). All other tests indicate no
significant relationship (p > 0.05) between landscape and either pollen seed treatment
residues or adult mortality (Table 7). The in-field floral contamination route is refuted by
our finding that FSR, which had zero bloom 2 corn field area, also had the highest
neonicotinoid residues in pollen samples (Section 3). These findings provide support for
the ubiquitous dispersal hypothesis, though this support is weakened by the failure ofunweighted corn area to predict adult mortality. It is likely that the influence of landscapeis obscured by other drivers of exposure and effects, such as variation in seed treatment
quality (Section 2) and local climatic conditions.

FINAL DRAFT- Page 45 of 136 CDRC – March 2017

Figure 20: The sum of clothianidin and thiamethoxam residues found in pollen
during corn planting was positively correlated with corn area.

ROE

Model

Spearman’s rho

p-valuepollen residues ~ risk weedy corn

0.286

0.501

adult mortality ~ risk weedy corn

0.214

0.620

pollen residues ~ risk non-corn foraging habitat

0.479

0.166

adult mortality ~ risk non-corn foraging habitat-0.2480.492

pollen residues ~ risk total

0.636

0.054

adult mortality ~ risk total

0.006

1

pollen residues ~ corn area

0.770

0.014*

adult mortality ~ corn area

0.430

0.218

In-field settling

Off-field drift

Localized plume

Ubiquitous dispersal

Table 7: Statistical models testing hypothesized routes of exposure by relatinglandscape variables to exposure and effects. Pollen insecticide residues werepositively correlated with corn area, but all other models were non-significant.

FINAL DRAFT- Page 46 of 136 CDRC – March 2017

SECTION 8:
Simulation modeling of exposure via floral contamination and its sensitivity to infield weed prevalence
In addition to the statistical modeling described above (Section 7), we also approached
the problem of honey bee exposure to seed treatment particles from the perspective of
simulation modeling. Honey bees, like other motile organisms, experience pesticide
exposure as the spatiotemporal intersection of contamination and foraging activity.
Conventional models of honey bee exposure assume that honey bee foraging occurs ona single uniformly contaminated crop (Wisk et al. 2014). While such models may be
useful for screening-level risk assessment, they provide no mechanistic insight into how
exposure occurs under natural foraging conditions where individual bees are exposed arange of doses arising from differentially contaminated habitats. Thus, there is a need formodels of honey bee pesticide exposure that capture the key mechanisms ofcontamination and honey bee foraging activity to generate stochastic and distributional
predictions of exposure
Accordingly, we developed a distributional and stochastic model of honey bee
exposure to seed treatment particles via the floral contamination route. The goals of ourmodel are to (1) characterize the distribution of exposure levels experienced by colony
members on an individual basis and (2) evaluate the sensitivity of exposure to theprevalence of in-field flora.
Methods
Landscape submodel. Simulation environment consists of a 4000 x 4000 array of 1 x 1
meter patches representing an idealized corn/soybean rotation system composed ofthree habitat types: corn fields, soybean fields, and interstitial strips (roadsides and fieldmargins) (Figure 21).
●

Field geometries generated by voronoi tessellation => 25 fields with an average
size of 64 ha● 10 fields (40%) randomly assigned to corn, 15 to soybean (60%), consistent with
Ohio crop data
● Linear field borders laterally expanded 5 m into adjacent fields, resulting in 10 m
wide interstitial strips representing field margins● 7/15 soybean fields and a variable number of corn fields set to “weedy”, i.e.
containing flowering plants attractive to honey bee foragers; weedy fields andfield margins together comprise the “foragable” subset of the simulated
landscapePesticide drift submodel. Drift of neonicotinoid-laden dust modeled by fitting the fielddata of Lin et al. (in prep) with a function relating active ingredient deposition to distancefrom field edge (Figure 21).

FINAL DRAFT- Page 47 of 136 CDRC – March 2017Foraging submodel
●

●
●
●

Simulated colony draws 10 foraging focal points from the foragable subset of thelandscape using a random but distance-biased algorithm. Distance-bias iscalibrated to honey bee dance language data generated in the Ohiocorn/soybean landscape (Lin et al., in prep) (Figure 21)
100 simulated “foragers” allocated to each of the 10 foraging focal points, starting
randomly within a 250 m radius.
Foragers proceed in a 10-step random walk; in each step, the forager “picks up”
a concentration of pesticide; net exposure = mean concentration over 10 steps
Colony-level exposure represented as histogram of net exposure experienced byeach of 1000 foragers.

Weed control experiment. The presence of flowering weeds in corn fields at the time ofplanting varies according to tilling and herbicide practices, and may be an important
modulator of exposure. We evaluate the influence of weed prevalence in corn fields
using the following design:●●●●

Presence of flowering weeds in fields modeled as a binary variable, i.e.
presence/absence.
Soybean fields set to constant 7/15 fields weedy, consistent with typicalconditions in Ohio
Weed prevalence in corn fields set to 0/10, 1/10, 2/10, 5/10, 8/10, and 10/10,
respectively.
Model iterated 3 times at each level of weed prevalence

Figure 21: Model simulates a honey bee colony (star) surrounded by corn (yellow) andsoybean (green) fields separated by narrow interstices of non-crop habitat. Dust drift

FINAL DRAFT- Page 48 of 136 CDRC – March 2017

simulated by distributing a contamination gradient according to distance from corn fieldedge. Weedy (foragable) fields are represented by dotted fill. To simulate foraging, 10
foraging foci are drawn from foragable patches (weedy field or interstitial strip) using arandom, distanced biased algorithm. Then, the foraging of individual bees is represented
by 100 ten-step random walks distributed within each focal area.

Results and Discussion
Exposure profiles are strongly bimodal, with a mode at zero representing
foraging in uncontaminated habitat and a higher mode representing the contamination inand near corn fields (Figure 22). In-field weed prevalence changes not only themagnitude of exposure but also the shape of the exposure distribution. When in-fieldblooms are absent, foraging is restricted to interstitial strips, resulting in a dispersed
distribution of exposure levels. As in-field weed prevalence increases, weedy fields
dominate the foraging environment, yielding a tighter distribution around the high mode.
The model also exhibits strong stochasticity arising from randomization of landscapegeometry, crop and weed assignment, and foraging simulation.
The strong sensitivity of this model to in-field weed prevalence might beinterpreted to recommend in-field weed control as an effective means of mitigatinghoney bee exposure. Our statistical models (Section 7), however, strongly refuted infield floral contamination as a route of exposure. Interpreted in that light, our simulation
model strengthens the conclusions of our statistical models. If in-field floral
contamination were an important route of exposure, then our simulation model says that
exposure should be highly sensitive to in-field weed prevalence in corn fields. Since
exposure was not found to be correlated with weedy corn field area, there is strong
evidence in favor of dismissing in-field floral contamination as a major route of exposurefor honey bees during corn planting.

FINAL DRAFT- Page 49 of 136 CDRC – March 2017

Figure 22. Exposure
profiles arising from six
levels of flowering weed
prevalence in corn fields.
Data visualized above
represent the output of
three iterations (rows) of
the model run at each of
six levels (columns) ofweed prevalence in cornfields: 0/10 fields, 1/10
fields, 2/10 fields, 5/10
fields, 8/10 fields, and10/10 fields. Eachhistogram depicts thefrequency (y axis) withwhich 1000 simulated
bees received varying
levels of net exposure (xaxis).

FINAL DRAFT- Page 50 of 136 CDRC – March 2017

SECTION 9:
CONCLUSIONS and MITIGATION RECOMMENDATIONS
Release, exposure, and effects
Seed treatment insecticides are consistently released during the planting oftreated corn. This release appears to be due to the failure of seed treatment material toadhere securely to the seed surface under the stresses of the planting process. Seedtreatment active ingredients can be detected both in- and off-field.
During corn planting, seed treatment insecticides are consistently detected inhoney- bee-collected pollen. Concurrently, honey bee colonies exhibit a 2.3-foldincrease in the number of dead adult hive bees collected in dead bee traps (forager
mortality would not be detected by our methods). This increase in mortality had noapparent effect on colony strength in subsequent months, or on The increase in adultmortality, however, would not be expected based on the concentrations of seedtreatment insecticide measured in bulk pollen samples.
Route of exposure
While the concentration of seed treatment insecticides in bulk pollen appears to
be a reliable indicator of overall exposure, it does not appear to fully represent the
exposure that bees receive. The primary route of exposure that drives the mortality ofhoney bees during corn planting remains uncertain, but landscape analysis and thesignificant correlation between corn area and insecticide residues in pollen supports theidea that honey bees are exposed via aerial contact with seed treatment particles. We
found no support for the hypothesis that honey bee exposure is driven by thecontamination of floral resources, either by in-field settling or off-field drift of seedtreatment particles.
Mitigating exposure
Because we found no support for the hypothesis that honey bee exposure isdriven by the contamination of either in-field or off-field flora, mitigation schemes
involving in-field weed suppression or off-field floral enhancement are unlikely to beeffective and may be counterproductive. Instead, mitigation efforts should be aimed atpreventing the initial release of seed treatment particles through engineering and quality
control solutions that ensure seed treatment formulations are well-adhered to the seed.
To the extent that initial release cannot be prevented, the aerial mobility of seedtreatment particles could be minimized through planter modification, seed treatment
reformulation or use of a fluency agent. An alternative to these approaches would be to

FINAL DRAFT- Page 51 of 136 CDRC – March 2017

plant either untreated seeds or seeds treated with an insecticide exhibiting lower toxicity
to honey bees.

REFERENCES
Bengtsson-Palme, J., Hartmann, M., Eriksson, K. M., Pal, C., Thorell, K., Larsson, D. G.
J., & Nilsson, R. H. (2015). metaxa2: improved identification and taxonomic classificationof small and large subunit rRNA in metagenomic data. Molecular Ecology Resources,
15(6), 1403–1414. http://doi.org/10.1111/1755-0998.12399

Couvillon, M. J., Riddell Pearce, F. C., Harris-Jones, E. L., Kuepfer, A. M., MackenzieSmith, S. J., Rozario, L. A., Schurch R., Ratnieks, F. L. W. (2012). Intra-dance variation
among waggle runs and the design of efficient protocols for honey bee dance decoding.
Biology Open, 1(5), 467–472. http://doi.org/10.1242/bio.20121099

Couvillon, M. J., Schürch, R., & Ratnieks, F. L. W. (2014). Waggle Dance Distances as
Integrative Indicators of Seasonal Foraging Challenges. PLoS ONE, 9(4), e93495.
http://doi.org/10.1371/journal.pone.0093495.g004

Couvillon, M. J., & Ratnieks, F. L. W. (2015). Environmental consultancy: dancing bee
bioindicators to evaluate landscape “health.” Frontiers in Ecology and Evolution, 3.
http://doi.org/10.3389/fevo.2015.00044

Cresswell, J. (2011) A meta-analysis of experiments testing the effects of aneonicotinoid insecticide (imidacloprid) on honey bees. Ecotoxicology. 20: 149–157.
http://doi.org/10.1007/s10646-010-0566-0

Devarrewaere, W., Janssen, S., & Foqué, D. (2016). CFD modelling to simulate dust
emissions from pneumatic seed drills. Aspects of Applied Biology 132:227-234.

FINAL DRAFT- Page 52 of 136 CDRC – March 2017

Girolami, V., Marzaro, M., Vivan, L., Mazzon, L., Greatti, M., Giorio, C., et al. (2011).
Fatal powdering of bees in flight with particulates of neonicotinoids seed coating andhumidity implication. Journal of Applied Entomology, 136(1-2), 17–26.
http://doi.org/10.1111/j.1439-0418.2011.01648.x

Girolami, V., Marzaro, M., Vivan, L., Mazzon, L., Giorio, C., Marton, D., & Tapparo, A.
(2013). Aerial powdering of bees inside mobile cages and the extent of neonicotinoid
cloud surrounding corn drillers. Journal of Applied Entomology, 137(1-2), 35–44.
http://doi.org/10.1111/j.1439-0418.2012.01718.x

Henry, M., M. Béguin, F. Requier, O. Rollin, J.-F. Odoux, P. Aupinel, J. Aptel, S.
Tchamitchian, and A. Decourtye. (2012) A common pesticide decreases foraging
success and survival in honey bees. Science. 336: 348–350.
http://doi.org/10.1126/science.1215039

Krupke CH, Hunt GJ, Eitzer BD, Andino G, Given K (2012) Multiple routes of pesticide
exposure for honey bees living near agricultural fields. PLoS ONE 7(1): e29268. doi
10.1371/ journal.pone.0029268

Lin, C.-H., P. Monagan and R. Johnson. 2016. Soybeans as a potential nectar source forhoney bees. 2016 American Bee Research Conference, Ponte Vedra Beach, FL.

McFrederick, Q. S., & Rehan, S. M. (2016). Characterization of pollen and bacterial
community composition in brood provisions of a small carpenter bee. Molecular Ecology,25(10), 2302–2311. http://doi.org/10.1111/mec.13608

QGIS Development Team (2015). QGIS Geographic Information System. Open Source
Geospatial Foundation Project. Available at http://qgis.osgeo.org

R Core Team. 2013. R: a language and environment for statistical computing. Vienna: R
Foundation for Statistical Computing. Available at http://www.R-project.org/.

FINAL DRAFT- Page 53 of 136 CDRC – March 2017

Richardson, R. T., Lin, C.-H., Sponsler, D. B., Quijia, J. O., Goodell, K., & Johnson, R.
M. (2015). Application of ITS2 Metabarcoding to Determine the Provenance of Pollen
Collected by Honey Bees in an Agroecosystem. Applications in Plant Sciences, 3(1),1400066. http://doi.org/10.3732/apps.1400066

Richardson, R. T., Lin, C.-H., Quijia, J. O., Riusech, N. S., Goodell, K., & Johnson, R. M.
(2015). Rank-Based Characterization of Pollen Assemblages Collected by Honey Bees
Using a Multi-Locus Metabarcoding Approach. Applications in Plant Sciences, 3(11),1500043. http://doi.org/10.3732/apps.1500043

Schindelin, J.; Arganda-Carreras, I. & Frise, E. et al. (2012), "Fiji: an open-source
platform for biological-image analysis", Nature methods 9(7): 676-682.

Schneider, C. W., J. Tautz, B. Grünewald, & S. Fuchs. (2012) RFID Tracking ofSublethal Effects of Two Neonicotinoid Insecticides on the Foraging Behavior of Apis
mellifera. PLoS One. 7: e30023. http://dx.doi.org/10.1371/journal.pone.0030023

Schürch R, Couvillon M. J., Burns D. D. R., Tasman K.,Waxman D., Ratnieks F. L. W.
(2013) Incorporating variability in honey bee waggle dance decoding improves the
mapping of communicated resource locations. J Comp Physiol A 199:1143–1152

Sponsler, D. B., & Johnson, R. M. (2015). Honey bee success predicted by landscapecomposition in Ohio, USA. PeerJ, 3, e838. http://doi.org/10.7717/peerj.838/supp-5

Tapparo, A., Marton, D., Giorio, C., Zanella, A., Soldà, L., Marzaro, M., et al. (2012).
Assessment of the Environmental Exposure of Honeybees to Particulate Matter
Containing Neonicotinoid Insecticides Coming from Corn Coated Seeds. Environmental
Science & Technology, 46(5), 2592–2599. http://doi.org/10.1021/es2035152

von Frisch, K. (1967). The Dance Language And Orientation Of Bees. Cambridge, MA,
USA: Belknap Press of Harvard University Press.

FINAL DRAFT- Page 54 of 136 CDRC – March 2017

Wisk JD et al. (2014). Assessing exposure of pesticides to bees. In Fischer D, Moriarty
T, eds, Pesticide Risk Assessment for Pollinators. John Wiley & Sons, Inc., Hoboken,
NJ, USA, pp. 45–74.

Appendix A. Levels of thiamethoxam and clothianidin detected in unsorted pollen
samples. Highlighted dates indicate the period when corn planting activity was at its
peak in Central Ohio.

Thiamethoxa
Clothianidinm

CLO + THI

Site

Date

(ng/g)(ng/g)(ng/g)

FSR

4/29

1.1

0.3

1.4

5/2

73.0

32.2

105.2

5/5

33.0

0

33.0

5/8

0.5

0.6

1.1

5/11

13.0

8.8

21.8

5/14

1.3

1.4

2.7

FINAL DRAFT- Page 55 of 136 CDRC – March 2017

MO

TV

5/19

2.0

0

2.0

5/23

4.1

0

4.1

5/27

8.0

0

8.0

4/29

0.0

0.4

0.4

5/2

6.0

0.9

6.9

5/5

17.7

1.2

18.9

5/8

9.3

0.5

9.8

5/11

0.5

0

0.5

5/14

2.5

0

2.5

5/19

5.5

3.9

9.4

5/23

18.0

7.3

25.3

5/27

3.3

1

4.3

4/29

0.8

0

0.8

5/2

7.4

0

7.4

5/5

16.6

9

25.6

5/8

4.8

0.6

5.4

5/11

13.0

0.8

13.8

5/14

0.4

0

0.4

5/19

2.3

1.2

3.5

5/23

0.0

1.5

1.5

FINAL DRAFT- Page 56 of 136 CDRC – March 2017

HR

WB

5/27

0.0

1.2

1.2

4/29

6.8

0

6.8

5/2

10.1

1.2

11.3

5/5

9.8

1.7

11.5

5/8

16.4

10.3

26.7

5/11

1.7

0

1.7

5/14

1.8

0

1.8

5/19

6.4

4

10.4

5/23

0.0

2.6

2.6

5/27

0.0

9

9

4/29

0.0

0

0

5/2

10.7

0

10.7

5/5

4.0

0

4.0

5/8

2.1

11

13.1

5/11

6.7

0

6.7

5/14

1.9

0.5

2.4

5/19

0.0

0

0

5/23

0.0

4.7

4.7

5/27

3.5

0

3.5

4/29

8.5

0

8.5

FINAL DRAFT- Page 57 of 136 CDRC – March 2017

BR

IB

MB

5/2

0

0

0

5/5

0

3.2

3.2

5/8

8.3

2.1

10.4

5/11

3

2.8

5.8

5/14

0.1

0.2

0.3

5/19

0

0

0

5/23

0

0

0

5/27

5.7

0

5.7

4/29

3.7

0

3.7

5/2

0.9

0

0.9

5/5

10.2

0.6

10.8

5/8

5.9

2.9

8.8

5/11

6.2

0.5

6.7

5/14

1.4

4.9

6.3

5/19

6.8

0

6.8

5/23

0.0

0.4

0.4

5/27

3.9

2

5.9

4/30

2.0

2.2

4.2

5/2

17.6

0

17.6

5/5

8.1

0

8.1

FINAL DRAFT- Page 58 of 136 CDRC – March 2017

SD

DS

5/8

1.3

3.7

5.0

5/11

0.6

0.5

1.1

5/14

0.0

0.9

0.9

5/19

1.4

0

1.4

5/23

2.0

0.6

2.6

5/27

2.3

0

2.3

4/29

0.0

1.5

1.5

5/2

17.1

3.3

20.4

5/5

4.0

0.6

4.6

5/8

2.7

0.3

3.0

5/11

2.0

2.7

4.7

5/14

0.3

0

0.3

5/19

2.0

0

2.0

5/23

37.0

12

49

5/27

0.0

0

0

5/1

4.1

1.6

5.7

5/2

0.2

0.5

0.7

5/5

1.6

0.6

2.2

5/8

6.4

0.5

6.9

5/11

1.5

0

1.5

FINAL DRAFT- Page 59 of 136 CDRC – March 2017

5/14

0.7

0.3

1

5/19

2

0

2

5/23

1.4

0

1.4

5/27

0.8

6

6.8

FINAL DRAFT- Page 60 of 136 CDRC – March 2017

Appendix B. Visual tool tointerpret insecticide
residues detected in bees,
pollen and surfaces inreference to toxicity of theneonicotinoids
clothianidin, thiamethoxam
to adult worker honeybees.

FINAL DRAFT- Page 61 of 136 CDRC – March 2017

Corn Dust Research Consortium 2015
University of Guelph Final Report
December 2015

Reducing honey bee exposure to neonicotinoid dust emitted during planting of treated corn
seeds
Addresses Project 1: Use by honey bees of flowering resources in and around cornfields
during spring planting, and how this behavior can be effectively managed to reduce exposure topesticide dust and residues

Principal Investigator:
Dr. Art Schaafsma, Professor
Field Crop Pest Management
Department of Plant Agriculture
University of Guelph - Ridgetown Campus
Ridgetown, ON N0P 2C0
CANADA
Tel: Phone: 519-674-1500 ext. 63624
Fax: 519-674-1515
Email:aschaafs@uoguelph.ca

Contributing authors:
Dr. Yingen Xue – University of Guelph - Ridgetown Campus
Gabriel Forero- University of Guelph - Ridgetown Campus
Jocelyn Smith – University of Guelph - Ridgetown Campus
Dr. Victor Limay-Rios - University of Guelph - Ridgetown Campus
Tracey Baute – Ontario Ministry of Agriculture, Food and Rural Affairs

FINAL DRAFT- Page 62 of 136 CDRC – March 2017

Acknowledgments
We would like to thank our grower and beekeeper co-operators for their time and effort put
towards this study. We especially acknowledge Todd Phibbs without whose technical support inequipment design, manufacturing, and operations in the field and in the laboratory, this work
could not have begun. We could not have carried out this research without the dedication ofsummer and undergraduate staff including Darrell Galbraith, Carissa Zandstra, Corina Bierling,
Michael Brouwer, Christina MacTavish, Allison Brouwer, Emily Marchand, Rachel England, KarliBarton, Prabhjot Kumar, Samuel Salamun, Wesley Luu, and Junjun Luo.
Support for this study was provided by the Corn Dust Research Consortium, OMAFRA, theOntario Soil and Crop Improvement Association, Syngenta and Bayer CropScience Inc. This
project was funded in part through Growing Forward 2 (GF2), a federal-provincial-territorial
initiative. The Agricultural Adaptation Council assists in the delivery of GF2 in Ontario.

FINAL DRAFT- Page 63 of 136 CDRC – March 2017

Objectives
This project was configured based on the results of 2013 and 2014, with the main purpose to
identify the key sites of honey bee exposure to neonicotinoids resulting from the movement offugitive planter dust. The objectives of this project were: (1) survey of flowering resources in andaround corn fields during spring planting; (2) identify species of bee-collected pollen, anddetermine neonicotinoid residues in bee-collected pollen and dead bees at apiaries associatedwith corn fields; (3) quantify and characterize neonicotinoid contaminated fugitive dust escaping
corn fields; and (4) quantify neonicotinoid residues on/in flowers that are main pollen sources, inhoney bees foraging on these flowers, and in the soil these plants are growing in.
Summary of methods
Nine locations were studied, 8 of which were used previously in 2014, and one was newly
recruited in 2015. Each location included an apiary and two fields; one corn and one soybean,canola, or corn. Field selection was based on the most suitable orientation to tree lines andbush in proximity (best downwind) of the field with the presence of trees/shrubs of Salix spp.
(willow), Crataegus spp. (hawthorn), Malus spp, (apple, wild apple) and/or Acer spp.(maple).
Activities from April to June 2015 focused on field surveys and sample collection of
flowering resources, foraging honey bees and dust during three sampling periods - the week
before, the week during and 2 wk after planting. During each sampling period, blooming
vegetation was surveyed in and around the 18 study fields and bee-collected pollen and deadbees were collected from the 9 apiaries. Samples of fugitive dust leaving the study fields werecollected using sticky dust collection towers during tillage, planting or wind events. The 18 study
fields were also surveyed for plant species that honey bees were actively foraging on during thethree sampling periods. The two most abundant flowering plant species were identified fromeach field and collections of flowers, foraging honey bees, and soil to the 10 cm depth from thebase of each plant were made. Representative pollen samples were sent to Johanne Parent(Laboratoire BSL, Rimouski, QC) for species identification. Neonicotinoid residues in dust traps,
flowers, soil, dead bees and bee-collected pollen were determined by LC/MS/MS. The α level todetermine statistical significance was set at 0.05 for all analyses.
Note: The experiments were designed as separate objectives. The testing of dust drift, whilenear apiaries, was not designed to allow testing of any direct impacts on honey bees in these
apiaries.
Summary of results
Abundance of blossoms in and around cornfields: Before corn planting, the most abundant
blossoms available in trees and shrubs were of Acer spp. and Salix spp. The most abundant
herbaceous blossoms were of Anemone, Taraxacum, and Viola spp.. During the same period,
bee-collected pollen in associated pollen traps was comprised mainly of Salix, Liliaceae, Acer
and Ulmus spp. During the planting period between 29 April and 22 May, the most abundant
blooming trees and shrubs were of Rosaceae, Prunus, Salix and Acer spp. The most abundant
herbaceous blooms were of Taraxacum, and Barbarea, and Alliaria spp. During the same
period, bee-collected pollen in associated pollen traps was comprised mainly of Acer, Salix, andRosaceae spp. After planting, beyond 23 May, the most abundant blooming trees and shrubs
were of Rosaceae and Prunus spp. The most abundant herbaceous blooms were Brassicaceae,

FINAL DRAFT- Page 64 of 136 CDRC – March 2017

Lotus, Barbarea, Asteraceae and Viola spp.. During the same period, bee-collected pollen inassociated pollen traps was comprised mainly of Rosaceae, Salix, Rhamnus, Brassicaceae andTrifolium ssp.
Neonicotinoid residue in bee-collected pollen and dead bees: The concentrations ofneonicotinoids within bee-collected pollen during planting (9.0 ng/g) were significantly higher
than before planting (2.2 ng/g) and after planting (2.9 ng/g). Neonicotinoid concentrations in
bee-collected pollen during planting in 2015 were similar to that found in 2013 (9.3 ng/g), and2014 (7.87 ng/g). Neonicotinoid concentration within dead bees increased significantly frombefore and during planting to after planting. No significant differences in neonicotinoid
concentration were found on the surface of dead honey bees among the three sampling periods
in 2015. The mean total neonicotinoid residues (those within and on the surface of dead honeybees combined) in 2015 was 1.32 ng/bee, which was similar to that measured in 2014 (1.42
ng/bee) and in the 2013 study (13.9 ng/g, assuming that 10 dead bees = 1 g).
Fugitive dust escaping fields: During corn planting, the mean neonicotinoid concentration
captured on sticky traps was 2.16 (0.84 in 2014) and 0.12 (0.42 in 2014) ng/cm2, for the
downwind and neighbouring field edges, respectively. The variation between years may havebeen a result of the large seed treatment particle size captured by the traps. Using volumetric
air samplers, the mean neonicotinoid concentration captured during corn planting at the
downwind and neighbouring field edges was 32.58 (21.7 in 2014) and 14.30 (12.2 ng/m3 in2014), respectively.
During soybean planting, the mean neonicotinoid concentration captured on sticky traps were0.11 and 0.10 ng/cm2, for the downwind and neighbouring field edges, respectively. Using
volumetric air samplers, the mean neonicotinoid concentration captured during soybean planting
at the downwind and neighbouring field edges were 8.64 and 5.31 ng/m3, respectively whichwere much lower than that measured during corn planting.
During tillage events, the mean neonicotinoid concentration captured on sticky traps were 0.01
and 0.04 ng/cm2, for the downwind and neighbouring field edges, respectively. Using volumetric
air samplers, the mean neonicotinoid concentration captured during tillage at the downwind andneighbouring field edges were 3.13 and 2.47 ng/m3, respectively which were much lower thanduring corn or soybean planting.
During wind events the mean neonicotinoid concentration captured on sticky traps andvolumetric air samplers in the downwind field edge were 0.02 ng/cm2 and 1.82 ng/m3,
respectively which were much lower than during corn/soybean planting or tillage events.
Neonicotinoid residue on/in flowers, foraging honey bees on the flowers, and soil on thebase of the blossoming plants:
Due to difficulty collecting from tall trees, there were not many blossoms of trees and shrubswith foraging bees collected. The trees/bushes included Salix (willow), Acer spp. (maple),
Rosaceae, and Robinia (black locust). The anthers and pollen of the blossoms usually had
lower neonicotinoid residue than on/in flowers (Table 9). However, the flower surface had

FINAL DRAFT- Page 65 of 136 CDRC – March 2017

similar neonicotinoid residue as inside the flowers. Salix was the most important foraging
resource of bees before corn planting (81.7%) (Table 10). During corn planting, Acer (35.2%),
Salix (27.4%) and Rosaceae (27.4%) were the most important foraging resources for bees. The
foraging bees collected from Acer spp. on May 1 had elevated neonicotinoid residues relative toother sources, which may have been related to fugitive dust at planting.
Similar to our 2014 results, lower levels of neonicotinoid residues were found on the surface of
herbaceous flowers compared to inside blossom tissues (Figs. 15 -19). These data suggest thatperhaps uptake of neonicotinoids from the soil or from leaf deposition during or after corn
planting may result in greater residue levels in the plant. This effect may be less certain for trees
which may be generally more distant from the source of neonicotinoid application in space andtime, and have different morphology and physiology. Neonicotinoid residue levels found on thesurface of foraging honey bees were higher than that inside of bees, which suggest that
neonicotinoid exposure is from contact with the residue.
No significant correlation was found between the neonicotinoid concentrations in soil collectedfrom the base of plants with that found in foraging bees or in the anthers/pollen of the plant
blossoms (R2 = 0.006, p = 0.472). Further there was no correlation between concentrations inanthers/pollen of blossoms and in the bees foraging on these blossoms (R2 = 0.001, p = 0.792).

FINAL DRAFT- Page 66 of 136 CDRC – March 2017

Site information
Experimental fields and apiaries: We worked again at 9 locations; each one with two fields
and one apiary. One of the two fields was a corn field, and one soybean, corn, or canola. Sites 4
and 5 used in 2014 were combined into one site due to beehive accessibility; therefore one site(10) at Ridgetown, ON was added to the study. Field selection was based on the most suitableorientation to tree lines and bush in proximity (best downwind) to the field and presence oftrees/shrubs of Salix spp. (willow), Crataegus spp. (hawthorn), Malus spp. (apple, wild apple)
and/or Acer spp. (maple) (Table 1).
Table 1. Experimental fields and associated apiaries studied in southwestern Ontario in 2015.

Site #CountyField/Apiary

GPS coordinates

Crop in 2014

1C

42.075947,-82.788867

Soybean

1D

42.101325,-82.790456

Corn

Apiary 1

42.101325,-82.790456

Treeline

2A

42.190045,-82.596593

Corn

2C

42.177147,-82.595489

SoybeanApiary 242.198964,-82.569236

Bush

3A

42.434817,-81.998893

Corn

Chatham- Kent 3B

42.438886,-81.994086

Corn

Apiary 342.443377,-82.025256

Back yard

4B

42.906519,-82386902

SoybeanComments

Essex
1

Essex
2

3

4/5

6

7

LambtonLambtonMiddlesex

5A

42.927426,-82.342670

Corn

Apiary 4/5

42.921387,-82.347268

Bush

6A

42.827311,-81.727359

Corn

6D

42.830091,-81.911898

SoybeanApiary 642.830101,-81.887554

Bush

7C

42.812989,-81.731458

Soybean

7D

42.821947,-81.765375

Corn

Apiary 742.821894,-81.758160

Bush

FINAL DRAFT- Page 67 of 136 CDRC – March 2017

Mergedfrom Site 4&5
Fungicide
only

8

9

10

8A

43.101433,-81.501658

Corn

8C

43.099319,-81.488125

SoybeanApiary 8

43.099451,-81.482637

Bush

9C

42.740948,-81.108048

Corn

9D

42.739912,-81.098815

SoybeanApiary 942.724245,-81.089501

Bush

10A

42.427791,-81.873907

Corn

Chatham- Kent 10B

42.423072,-81.869027

Canola42.423072,-81.869027

Farm yard

Middlesex

Elgin

Apiary 10

New recruit

Table 2. Hybrid, planting date, neonicotinoid seed treatment, and rate of Bayer
Fluency Agent used by growers in 2015 corn planting studies.

Field

Crop

HybridPlanting
date

Neonicotinoid insecticide
used
Activeingredient

Rate of Bayer
Fluency Agent
used
Rate (mg(% ofa.i./kernel) recommended1)

1D

Corn

DKC 57-75RIB

201505-22

clothianidin

0.25

100

2A

Corn

DKC 50-78RIB

201505-04

clothianidin

0.25

100

3A &
3B

Corn

P0506AM //DKC 57-75RIB

201505-01

clothianidin

0.75

100

5A

Corn

A7270G8 //DKC 53-56

201505-01

clothianidin

0.25

100

6A

Corn

DKC 53-56

201504-29

clothianidin

0.25

100

6D

Corn

DKC 50-78

201505-03

None

0

100

7C

Soybeans N/A

201505-25

None

0

0

FINAL DRAFT- Page 68 of 136 CDRC – March 2017

7D

Corn

DKC 50-78RIB

201505-09

clothianidin

0.125

100

8A

Corn

DKC 50-78

201505-02

clothianidin

0.25

100

8C

Soybeans Chikala

201505-19

Thiamethoxam

0.122

0

9C

Corn

DKC 50-90

201505-13

Clothianidin

0.25

100

9D

Soybeans

P22T69RKA26

201505-20

Thiamethoxam

0.33

N/A

10A

Corn

P0496AMXKM67

201505-04

clothianidin

1.25

100

1

Recommended application rate for corn: 1/8 cup per 80,000 seeds.

Modifications to original protocol and deliverables
To maximize the samples of fugitive dust escaping corn fields, we combined the 3 sticky traps
samples from the 3 replicates for each of the proximal or distal locations in corn fields into one
LC/MS/MS injection to allow for additional air sampler samples (original sticky trap deliverables
108; final sticky trap + air sampler deliverables: 80+41 = 121) (Table 3).

FINAL DRAFT- Page 69 of 136 CDRC – March 2017

Table 3. Number of samples from sticky dust traps and volumetric air samplers collected in
2015.

Crop

Planting dateNo.
samplesduringtillageevents

1C

Soybeanafter May 31

-

-

-

1D

Corn

2015-05-22

-

6

-

2 planting

2A

Corn

2015-05-04

-

6

-

2 planting

2C

Soybeanafter May 31

-

-

-

1 tillage

3A

Corn

6

6

-

2 tillage, 2planting

3B

Corn

6

6

-

2 tillage, 2planting

4B

Soybeanmissed

-

-

-

5A

Corn

2015-05-01

-

6

-

2 planting

6A

Corn

6

6

-

2 tillage, 2planting

6D

Soybean

2015-05-03

-

6

-

2 planting

7C

Soybean

2015-05-25

-

6

-

2 planting

7D

Corn

2015-05-09

-

6

-

2 planting

8A

Corn

6

6

-

2 tillage, 2planting

8C

Soybean

2015-05-19

-

6

-

2 planting

9C

Corn

2015-05-13

-

6

-

2 planting

9D

Soybean

2015-05-20

-

6

-

2 planting

10A

Corn

2015-05-04

-

6

-

2 planting

Field

2015-05-01

2015-05-01

2015-04-29

2015-05-02

No.
No.
samplessamplesduring during wind
eventsplanting

FINAL DRAFT- Page 70 of 136 CDRC – March 2017

No. samples fromvolumetric air
sampler

10B

CanolaWinter canola

-

-

-

Extra 1Corn

2015-05-22*

-

-

3

1 wind event

Extra 2

Corn

2015-05-22*

-

-

3

1 wind event

Extra 3Corn

2015-05-22*

-

-

3

1 wind event

Extra 4

Soybean

2015-05-22*

-

-

3

1 wind event

FINAL DRAFT- Page 71 of 136 CDRC – March 2017

Methods and results
1. Survey of flowering resources in and around corn fields during spring planting andspecies identification of bee-collected pollen
1.1. Method
Vegetation in bloom was surveyed in and around the 18 study fields weekly from 28 April to 3
June 2015. For each field and bush, one side of the perimeter with the most abundant blooming
species was selected for the survey. Photos of blooming plants, trees and shrubs in the different
zones were captured using iPhone and iPad devices and geo-referenced using Photo GPS
Extractor free software (http://pge.bvsoft.be/). The plant species and their spatial densities wereidentified and categorized using an abundance index (AI) of 0-4 where 0 = not observed, 1 = 0-5
individuals observed/m2 for herbaceous weeds or 0-1 observed/100 m2 for trees and shrubs, 2 =6-10/m2 for weeds, 2-5/100 m2 for trees and shrubs, 3 = 11-20/m2 for weeds, 6-10/100 m2 fortrees and shrubs, and 4 = >20/m2 for weeds, >10/100 m2 for trees and shrubs. The percentageof occurrences of patches of a blooming plant species was considered its frequency; this was
multiplied by the AI value to determine the relative abundance index (RAI) for each plant
species which was converted to a percentage of the total vegetation of either trees and shrubs
or herbaceous plants. We divided the field survey data into three sampling periods based on thecorn planting dates: (1) before planting (before 28 April); (2) during corn planting (29 April – 22May); and (3) after planting (23 May – 3 June).
In order to determine the taxonomic composition and proportion of pollen collected from tree,
shrub, and herbaceous plants near corn and soybean fields by honey bees during the spring
corn planting season bee-collected pollen was sampled at the 9 apiaries using pollen traps
attached to the bee hives (39 cm x 15 cm x 10.5 cm; Anel Standard, Athens, Greece.
www.anel.gr.) (Fig. 1). Pollen traps were engaged at ca.16:00 h on the day previous to thespecified pollen collection date and pollen samples were removed from the sites no later than
24 hours after trap engagement. When weather conditions were not ideal for bee foraging (i.e.
cooler temps or significant rain), pollen traps were left engaged for an additional 24 h. Species
identification and proportion of pollen species was determined by Johanne Parent (Laboratoire
BSL, Rimouski, QB).

Figure 1. Anel standard pollen trap

1.2. Results

FINAL DRAFT- Page 72 of 136 CDRC – March 2017

Before corn planting, the most abundant blooming trees and shrubs available were of Acer.
(relative AI 173.3) and Salix spp. (relative AI 66.7) (Fig.2). The most abundant herbaceous
blooms were of Anemone (relative AI 173.3), Dandelion (Taraxacum officinale) (relative AI
66.7), and Viola spp. (relative AI 66.7) (Fig. 3). During the same period, bee-collected pollen inassociated pollen traps was comprised mainly of Salix (81.7%), Liliaceae (7.6), Acer (4.2%) andUlmus spp. (3.5%) (Fig.4).
200
173.3

180
160
140
120

Freq %

100

AI

80

66.7

66.7

Relative AI

60
40

33.3

20

2.0

2.6

Salix spp

Acer spp

0

Figure 2. The most abundant blooming tree/shrubs before corn planting in 2015.
Legend Notes: Freg. - the percentage of occurrences of the patches of a blooming plant
species; AI - Abundance Index, 0-4 where 0 is not observed, 1 is 0-5 individuals observed /m2
for herbaceous weeds, 0-1 observed/100m2 for trees and shrubs 2 is 6-10/m2 for weeds, 25/100m2 for trees and shrubs, 3 is 11-20/m2 for weeds, 6-10/100m2 for trees and shrubs), and 4
is >20/m2 for weeds, >10/100m2 for trees and shrubs. Relative AI is the product of freq (%) and
AI.

100.0

100
90
75.0

80

75.0

70
60

50.0

50

Freq %
AI

40
30

25.0

Relative AI

25.0

20
10

3.0

3.0

2.0

Taraxacum
officinale

Viola spp

Anemone spp

0

Figure 3. The most abundant herbaceous blooming plants before corn planting in 2015. See
Fig. 2 for explanation of legend.

FINAL DRAFT- Page 73 of 136 CDRC – March 2017

100
90
81.7
80

Percentage (%)

70
60
50
40
30
20
7.6

10

4.2

3.5

Acer

Ulmus

0.4

2.6

0
Salix

Liliaceae

Taraxacum

OthersFigure 4. Proportion of bee-collected pollen species before corn planting in 2015.
During the planting period between 29 April and 22 May, the most abundant blooming trees andshrubs were of Rosaceae (relative AI 170.4), Prunus (relative AI 28.9), Salix .(relative AI 18.5),
Acer (relative 11.1) and Crateagus spp. (relative 11.1). The most abundant herbaceous blooms
were Dandelion (Taraxacum officinale) (relative AI 180.0), Barbarea vulgaris (relative AI 90.0),
and Alliaria officinalis (relative AI 90.0) (Fig. 6). During the same period, bee-collected pollen
sampled from associated pollen traps was comprised mainly of Acer (35.2%), Salix (27.4%) andRosaceae spp. (22.0%) (Fig. 7).

170.4

180
160
140
120

Freq %

100
74.1

80

Relative AI

60
40
20

AI

18.5

11.1
3.7 3.0

11.1
3.7 3.0

7.4

Crataegus spp.

Acer spp

Salix spp

2.5

28.9
11.1
2.6

0
Prunus spp

2.3
Rosaceae spp

Figure 5. The most abundant blooming trees and shrubs during the period of corn planting in
2015. See Fig. 2 for explanation of legend.

FINAL DRAFT- Page 74 of 136 CDRC – March 2017

200

180.0

180
160
140
120
90.0

100

Freq %

90.0

AI

80
60
40
20
0

Relative AI

46.2
10.3
2.6 4.0

10.3
2.6 4.0

10.3
2.6 4.0

Lotus
Corniculatus

Trifolium spp

Anemone spp

23.1

23.1

3.9

3.9

3.9

Barbareavulgaris

Alliaria
officinalis

Taraxacum
officinale

Figure 6. The most abundant herbaceous blooming plants during the period of corn planting in
2015. See Fig 2 for explanation of legend.
100.0
90.0
80.0
Percentage (%)

70.0
60.0
50.0
40.0
30.0

35.2
27.4
22.0

20.0
10.0

3.1

2.9

1.8

1.7

5.9

0.0

Figure 7. Proportion of bee-collected pollen species during the corn planting period in 2015.
After planting, beyond 23 May, the most abundant blooming trees and shrubs were of Rosaceae(relative AI 176.0) and Prunus spp. (relative AI 40.0). The most abundant herbaceous blooms
were of Brassicaceae spp (relative AL 123.0), Lotus corniculatus (relative AI 92.3), Barbarea
vulgaris (relative AI 92.3), Asteraceae spp (relative AI 61.5) and Viola spp (relative AI 23.1).
During the same period, bee-collected pollen in associated pollen traps was comprised mainlyof Rosaceae (32.0%), Salix (14.0), Rhamnus (11.5%), Brassicaceae (10.8%) and Trifolium(9.3%) spp.

FINAL DRAFT- Page 75 of 136 CDRC – March 2017

200

176.0

180
160
140
120

Freq %

100
80

Relative AI

60
40
20

AI

80.0
40.0
20.0
2.0

2.2

Prunus spp

Rosaceae spp

0

Figure 8. The most abundant blooming trees and shrubs after corn planting in 2015. See Fig. 2
for explanation of legend.

140

123.1

120
92.3

100

92.3

80
60

AI
Relative AI

40
20

Freq %

61.5

23.1
7.7

23.1

15.4

3.0

4.0

Viola spp

Asteraceae spp

30.8

23.1
4.0

4.0

4.0

0
Barbarea vulgaris Lotus corniculatus Brassicaceae spp

Figure 9. The most abundant herbaceous blooming plants after corn planting in 2015. See Fig.
2 for explanation of legend.

FINAL DRAFT- Page 76 of 136 CDRC – March 2017

100.090.0

Percentage (%)

80.0
70.0
60.0
50.0
40.0

32.0

30.0
20.0
10.0

14.0

11.5

10.8

9.3

5.7

3.2

3.2

2.7

1.7

5.9

0.0

Figure 10. Proportion of bee-collected pollen species after corn planting in 2015.
2. Determine neonicotinoid residue in bee-collected pollen and dead bees
2.1. Method
At each of the 9 apiaries, dead bees were collected from Drop-Zone Dead Bee traps (100 x 50 x14cm) installed in front of four bee hives during 24 h intervals (Figure 11). Bee-collected pollen
was collected at the same time for proportional species identification (see Method 1.1). There
were three sampling periods: (1) before planting (28 April); (2) during corn planting (29 April –22 May); and (3) after planting (23 May– 3 June). Neonicotinoid residues in dead bees and beecollected pollen were determined by LC/MS/MS.
Because clothianidin and thiamethoxam are the most commonly used neonicotinoids insouthwestern Ontario and clothianidin is a metabolite of thiamethoxam, we used the total
quantity of clothianidin and thiamethoxam to represent the neonicotinoid residues,
hereinafter.

Figure 11. Drop-Zone dead bee trap

FINAL DRAFT- Page 77 of 136 CDRC – March 2017

PROC MIXED was used to compare the concentration of neonicotinoids across sampling
periods with sampling period as the fixed effect and apiary as a random effect. Data were
subjected to log10(x+1) transformation to satisfy the assumptions of normality. The α level forstatistical significance was set at 0.05 for all analyses.
2.2. Results
The concentrations of neonicotinoids within bee-collected pollen during planting weresignificantly higher than those before and after planting (Figure 12). Neonicotinoid
concentrations in bee-collected pollen in 2015 were similar to those found in 2013 (9.3 ng/g)
and 2014 (7.87 ng/g).

Total1 neonicotinoid concentration(ng/g)

12.0

B

10.0
8.0
6.0
4.0

9.0
A

2.0
2.2
0.0

Before planting(April 28)

A

2.9
During planting After planting (May(April 29 - May 22)
23 - June 3)

Figure 12. Mean concentrations (±SE) of neonicotinoid residues in bee-collected pollen
collected before, during, and after corn planting in 2015. Columns with the same letter are notsignificantly different (P > 0.05) as determined by PROC MIXED.
1

Total of clothianidin and thiamethoxam (LOD and LOQ were 0.2378 and 0.5878 ng/g for
clothianidin, and 0.0681 and 0.1805 ng/g for thiamethoxam).

The neonicotinoid concentration within dead bees increased significantly from before planting toduring and after planting (Table 4). No significant differences in neonicotinoid concentration
were found on the surface of dead honey bees among the three sampling periods in 2015
(Table 4). The mean combined total neonicotinoid residue within and on the surface of deadFINAL DRAFT- Page 78 of 136 CDRC – March 2017

honey bees in 2015 was 1.32 ng/bee, which was similar to that measured in 2014 (1.42 ng/bee)and 2013 (13.9 ng/g, assuming that 10 dead bees = 1 g).

Table 4. Neonicotinoid residues within and on the surface of dead honey bees collected fromdead bee traps at apiaries in 2015. (Data within columns with different letters are significantly
different (P < 0.05) as determined by PROC MIXED).

Neonicotinoid 1 (ng/bee) (mean ± SE)
Sampling periodnWithinOn surface

Total

Before planting

2

0.16 ± 0.03 a

0.38 ± 0.11

0.54 ± 0.14

During planting

18

0.33 ± 0.03 b

0.36 ± 0.08

0.69 ± 0.09

After planting

7

0.46 ± 0.03 c

2.28 ± 1.34

2.74 ± 1.35

1Total of clothianidin and thiamethoxam (For residue within bee, LOD and LOQ were 0.0235
and 0.0667ng/bee for clothianidin, and 0.0078 and 0.0230 ng/bee for thiamethoxam; For
residue on bee surface LOD and LOQ were 0.0576 and 0.1631 ng/bee for clothianidin, and0.0323 and 0.0921 ng/bee for thiamethoxam).

3. Determine the fugitive dust escaping fields
3.1. Methods
Dust leaving the field was collected using sticky dust collection towers (Figure 13) at threesampling times. Dust events such as from tillage, planting, and wind erosion events weretargeted as they presented themselves. Each collection tower consisted of one 2-m metal stakewith one vertically-oriented panel of microscope slides on a wood frame at a height of 2 m fromthe ground. The microscope slide panels were coated with Tangle Trap® adhesive (The
Tanglefoot Company, Grand Rapids, MI). Three dust collection towers were placed at the
downwind edge of the field being planted (proximal) and three at the far downwind edge of theneighbouring field (distal). For the safety reason the dust traps at the downwind edge of the field
being planted were located around 2 feet from the planter. Towers were orientated so that thevertical panels faced directly towards the wind. A single volumetric air sampler (Figure 14) was
set at 2 m height on the same field edge and far edge of the neighbouring fields as the sticky
traps.

FINAL DRAFT- Page 79 of 136 CDRC – March 2017

Figure 13. Vertical sticky dust trap

Figure 14. Volumetric air sampler

The distance between the proximal and distal traps was recorded. Planting time collections
were not made at 2 soybean fields because of extreme delayed planting and at the wintercanola field which was already planted in the fall. We also selected 3 extra corn fields (around 1
month after planting) and 1 extra soybean field (1 week after planting) to collect wind event dust
samples. All fields for wind event collection were planted with treated seed. Samples collected
at each location were all standardized to the time it took to plant or till a 150-m width of eachfield so data collected in 2015 can eventually be related to those collected in 2013 and 2014.
Extraction and LC/MS/MS analysis were conducted at the University of Guelph Ridgetown
Campus. To maximize the sampling of fugitive dust escaping corn fields, we combined the 3
sticky trap samples from the 3 replicates of proximal or distal in corn fields into one LC/MS/MS
injection, and compensated the deliverables by adding the volumetric air sampler samples (seemodification section).
3.2. Results
3.2.1. During corn planting

FINAL DRAFT- Page 80 of 136 CDRC – March 2017

The mean neonicotinoid concentration captured on sticky traps during corn planting was 2.16
(0.84 in 2014) and 0.12 (0.42 in 2014) ng/cm2, for the downwind and neighbouring field edges,
respectively (Table 5). The variation between the years for field edge may be caused by thelarge seed treatment particles captured by the traps. Using volumetric air samplers, the mean
neonicotinoid concentrations captured during corn planting at the downwind and neighbouring
field edges were 32.58 (21.7 in 2014) and 14.30 (12.2 ng/m3 in 2014), respectively (Table 5).
We expected that neonicotinoid residue concentrations decreased as the distance away fromthe field being planted increased; however, there were some anomalies at individual locations
that showed the opposite.
At some locations when samples were taken, other producers
were planting corn in the region, which could not have been avoided, and these may haveconfounded some of our results.
Table 5. Neonicotinoid residues collected at downwind locations during corn planting in 2015
using vertical sticky traps and volumetric air samplers.

Field edge (Proximal)
Location

Neighbouring field edge (Distal)

Vertical sticky
trap (ng/cm2)*

Air sampler(ng/m3)Distance(m)

Vertical sticky
trap (ng/cm2)*

Air sampler(ng/m3)

1D

0.54

7.15

694

0.05

1.61

2A

0.43

6.82

330

0.15

2.42

3A

16.41

95.89

300

0.58

54.76

3B

3.53

175.52

152

0.16

75.95

5A

0.05

8.52

345

0.01

0.19

6A

0.59

6.17

167

0.01

1.84

6D

0.97

4.70

200

0.03

3.65

7D

0.17

13.08

681

0.01

5.70

8A

0.47

11.73

140

0.03

5.60

9C

0.01

0.95

70

0.01

1.20

10A

0.60

27.85

300

0.24

4.42

Min

0.01

0.95

0.01

0.19

Max

16.41

175.52

0.58

75.95

FINAL DRAFT- Page 81 of 136 CDRC – March 2017

Mean

2.16

32.58

0.12

14.30

SE

1.45

16.42

0.05

7.76

* Data standardized to the area required to plant 150 m of field width. For sticky traps, LOD and
LOQ were 0.2712 and 0.9032 ng/cm2 for clothianidin, and 0.0809 and 0.2694 ng/cm2 forthiamethoxam; For air sampler, LOD and LOQ were 0.7070 and 2.3544 ng/m3 for clothianidin,
and 0.1061 and 0.3533 ng/m3 for thiamethoxam).

3.2.2. During soybean planting
The mean neonicotinoid concentration captured on sticky traps during soybean planting was
0.11 and 0.10 ng/cm2, for the downwind and neighbouring field edges, respectively (Table 6).
Using volumetric air samplers, the mean neonicotinoid concentration captured during soybean
planting at the downwind and neighbouring field edges was 8.64 and 5.31 ng/m3, respectively(Table 6) which were lower than during corn planting.

Table 6. Neonicotinoid residues collected at downwind locations during soybean planting in2015 using vertical sticky traps and volumetric air samplers.

Field edge (Proximal)
Location

Neighbouring field edge (Distal)

Vertical sticky
trap (ng/cm2)*

Air sampler(ng/m3)Distance(m)

Vertical sticky
trap (ng/cm2)*

Air sampler(ng/m3)

7C

0.10

12.89

370

0.03

1.25

8C

0.16

11.14

150

0.21

11.01

9D

0.06

1.88

266

0.06

3.68

Min

0.06

1.88

0.03

1.25

Max

0.16

12.89

0.21

11.01

Mean

0.11

8.64

0.10

5.31

SE

0.03

3.42

0.06

2.93

* Data standardized to the area required to plant 150 m of field width.LOD and LOQ were thesame as in Table 5.

FINAL DRAFT- Page 82 of 136 CDRC – March 2017

3.2.3. During tillage
The mean neonicotinoid concentration captured on sticky traps during tillage was 0.01 and 0.04
ng/cm2, for the downwind and neighbouring field edges, respectively (Table 7). Using volumetric
air samplers, the mean neonicotinoid concentration captured during tillage events at the
downwind and neighbouring field edges was 3.13 and 2.47 ng/m3, respectively (Table 7) which
was much lower than during corn or soybean planting.
Table 7. Neonicotinoid residues collected at downwind locations during tillage events in 2015
using vertical sticky traps and volumetric air samplers.
Field edge (Proximal)
Location

Neighbouring field edge (Distal)

Vertical sticky
trap (ng/cm2)*

Air sampler(ng/m3)Distance(m)

Vertical sticky
trap (ng/cm2)*

Air sampler(ng/m3)

2C

n/a

2.65

n/a

n/a

n/a

3A

0.02

4.48

358

0.01

4.47

3B

0.01

1.5

214

0.05

1.04

6A

0.01

3.99

167

0.04

1.15

8A

0.01

3.02

140

0.04

3.22

Min

0.01

1.50

0.01

1.04

Max

0.02

4.48

0.05

4.47

Mean

0.01

3.13

0.04

2.47

SE

0.00

0.52

0.01

0.75

* Data standardized to the area required to plant 150 m of field width.LOD and LOQ were thesame as in Table 5.

3.2.4. During wind events
The mean neonicotinoid concentration captured on sticky traps and volumetric air samplers
during wind events in the downwind field edge was 0.02 ng/cm2 and 1.82 ng/m3, respectively(Table 8). The neonicotinoid residue concentrations were much lower than during corn orsoybean planting or during tillage events.
Table 8. Neonicotinoid residues collected at downwind locations during wind events in 2015
using vertical sticky traps and volumetric air samplers.
FINAL DRAFT- Page 83 of 136 CDRC – March 2017

Field edge (Proximal)
Location
Vertical sticky trap
(ng/cm2)*

Air sampler (ng/m3)

Thamesville 1

0.02

0.65

Thamesville 2

0.04

0.68

Thamesville 3

0.01

4.39

Thamesville 4

0.01

1.55

Min

0.01

0.65

Max

0.04

4.39

Mean

0.02

1.82

SE

0.01

0.88

* Data standardized to the area required to plant 150 m of field width.
the same as in Table 5.

LOD and LOQ were

4. Determine neonicotinoid residues on/in flowers, foraging honey bees on flowers, andsoil at the base of blossoming plants
4.1. Methods
To detect neonicotinoid residues on and in blossoms foraged by honey bees during the corn
planting period, the 18 study fields above were surveyed for plant species that honey bees wereactively foraging on during the three sampling periods. The blossoms of the two most abundant
flowering plant species along with honey bees foraging on them were collected in each field.
Soil to the 10-cm depth was collected from the base of each plant sampled for flowers andbees. All plant blossoms, foraging bees and soil samples were stored in complete darkness at 20ºC until processed and tested. There were no foraging bees collected in April, and few
foraging bees were found in early May due to unusually low temperatures; therefore, we
extended the collection period until 25 June. The trees/bushes with foraging bees included Salix
spp. (willow), Acer spp. (maple), Rosaceae, and Robinia pseudoacacia (black locust). The
herbaceous plants with foraging bees included Trifolium repens (white clover) Melilotus spp.
(yellow sweet clover), Barbarea vulgaria (yellow rocket), Taraxacum spp. (dandelion), Cirsium
spp. (thistle), and Lotus corniculatus (birdsfoot trefoil). Neonicotinoid residues in flowers (inside,outside and anthers), foraging bees (inside and outside), and in soil samples at the base of theplants were determined by LC-MS/MS.

FINAL DRAFT- Page 84 of 136 CDRC – March 2017

4.2. Results
4.2.1 Trees and shrubs
Due to difficulties collecting from tall trees, very few blossoms with foraging bees were collectedfrom trees and shrubs in 2015. The trees/bushes sampled included Salix spp. (willow), Acer
spp. (maple), Rosaceae, and Robinia spp.(black locust). The anthers and pollen of theblossoms usually had lower neonicotinoid residues than on/in the flowers (Table 9); however,the flower surface had similar neonicotinoid residue concentrations to those measured inside
the flowers. Salix spp. were the most important foraging resources of bees before corn planting(81.7%) (Table 10). During corn planting, Acer spp. (35.2%), Salix spp. (27.4%) and Rosaceae(22.0%) were the most important foraging resources. Foraging bees collected from Acer spp. on
1 May had higher neonicotinoid residue concentrations, which may have been related to corn
planting nearby.
Table 9. Total1 neonicotinoid concentration on/in flowers, foraging honey bees, and soil from thebase of blossoming trees and shrubs in 2015.
Flower (ng/flowers)
Tree/bushnSoil(ng/g)

Surface Inside

Anther +pollenForaging bee (ng/bee)InsideSurfaceAcer spp. (maple)

1

missing

0.54

0.14

0.06

4.77

18.02

Salix spp. (willow)

1

missing

0.53

0.59

0.17

missing

missing

Rosaceae

5

1.21

0.11

0.05

0.04

0.29

1.22

Robinia spp. (Blacklocust)

3

13.91

0.06

0.06

0.03

0.44

0.32

1

.Total of clothianidin and thiamethoxam. For soil, LOD and LOQ were 0.1033 and 0.2390 ng/g
for clothianidin, and 0.0215 and 0.0448 ng/g for thiamethoxam; For flower surface, inside andanther + pollen, LOD and LOQ were 0.0366 and 0.0977 ng/flower for clothianidin, and 0.0096
and 0.0263 ng/flower for thiamethoxam; For inside of foraging bee, LOD and LOQ were 0.0243
and 0.0808 ng/bee for clothianidin, and 0.0295 and 0.0981 ng/bee for thiamethoxam; For
surface of foraging bee, LOD and LOQ were 0.0663 and 0.2208 ng/bee for clothianidin, and0.0652 and 0. 2171 ng/bee for thiamethoxam).

Table 10. The proportion of pollen from blooming plants observed with foraging bees found inbee-collected pollen before, during, and after corn planting in 2015.

FINAL DRAFT- Page 85 of 136 CDRC – March 2017

Proportion of bee-collected pollen (%)
Category

Trees andshrubsHerbaceous

Plant

Beforeplanting

Duringplanting

After
planting

Acer spp. (maple)

4.2

35.2

0.0

Salix spp. (willow)

81.7

27.4

14.0

Rosaceae

0.0

22.0

32.0

Robinia spp. (Black locust)

0.0

0.0

0.0

Taraxacum (dandelion)

0.4

1.8

0.4

Melilotus (sweet clover)

0.0

0.0

0.2

Lotus (birdsfoot trefoil)

0.0

0.0

0.0

Barbarea (yellow rocket)

0.0

0.9

1.9

Trifolum (clover)

0.0

0.0

9.3

Cirsium (thistle)

0.0

0.1

0.0

Vicia (cow vetch)

0.0

0.0

0.0

4.2.2. Herbaceous Plants
Similarly to our results in 2014, generally lower levels of neonicotinoid residues were
found on the surface of herbaceous flowers relative to what was measured inside
blossom tissues (Figs. 15 -19). These data suggest that perhaps uptake ofneonicotinoids from the soil or from leaf deposition during or after corn planting may
result in greater residue levels in the plant. This effect may be less certain for trees
which may be generally more distant from the source of neonicotinoid application in
space and time, and have different morphology and physiology. Neonicotinoid residue
levels found on the surface of foraging honey bees were higher than that measured
inside bees. To be clear we observed in several cases for herbaceous plants the residue
levels were greater inside the flower tissue compared with what was found on the flower
surface. In many cases the plant leaves would have been unfurled at the time ofplanting, if flowering coincided with planting and sampling. So in these cases theresidues found inside the flower tissue could have come from the soil or from the leavesurface after deposition.
Taraxacum spp. (dandelion)

FINAL DRAFT- Page 86 of 136 CDRC – March 2017

Figure 15. Total1 neonicotinoid concentration on/in flowers of Taraxacum spp. (ng/flower),
foraging honey bees (ng/bee) on these flowers, and in soil (ng/g) collected from the base of thesame plants. (1Total of clothianidin and thiamethoxam) in ON 2015. LOD and LOQ were thesame as in Table 9.

Melilotus spp. (yellow sweet clover)Figure 16. Total1 neonicotinoid concentration on/in flowers of Melilotus spp. (ng/flower), foraging
honey bees (ng/bee) on these flowers, and in soil (ng/g) collected from the base of the same

FINAL DRAFT- Page 87 of 136 CDRC – March 2017

plants. (1Total of clothianidin and thiamethoxam) in ON 2015. LOD and LOQ were the same asin Table 9.

Lotus corniculatus (birdsfoot trefoil).

Figure 17. Total1 neonicotinoid concentration on/in flowers of Lotus corniculatus (ng/flower),
foraging honey bees (ng/bee) on these flowers, and in soil (ng/g) collected from the base of thesame plants. (1Total of clothianidin and thiamethoxam) in ON 2015. LOD and LOQ were thesame as in Table 9.

FINAL DRAFT- Page 88 of 136 CDRC – March 2017

Barbarea vulgaria (yellow rocket)

Figure 18. Total1 neonicotinoid concentration on/in flowers of Barbarea vulgaria (ng/flower),
foraging honey bees (ng/bee) on these flowers, and in soil (ng/g) collected from the base of thesame plants. (1Total of clothianidin and thiamethoxam) in ON, 2015. LOD and LOQ were thesame as in Table 9.
Trifolium spp. (clover)Figure 19. Total1 neonicotinoid concentration on/in flowers of Trifolium spp. (ng/flower), foraging
honey bees (ng/bee) on these flowers, and in soil (ng/g) collected from the base of the sameplants. (1Total of clothianidin and thiamethoxam) in ON, 2015. LOD and LOQ were the same asin Table 9.

FINAL DRAFT- Page 89 of 136 CDRC – March 2017

Other herbaceous species:
Table 11. Total1 neonicotinoid concentration on/in other herbaceous flowers (ng/flower),
foraging honey bees (ng/bee) on the flowers, and soil (ng/g) on the base of the plants.
Flower (ng/flowers)
HerbaceousnSoil(ng/g)

Anther +pollenSurface Inside

Foraging bee (ng/bee)InsideSurface

Vicia (cow vetch)

1

2.06

0.37

0.63

0.47

0.22

0.26

Cirsium (thistle)

4

10.05

0.16

0.22

0.17

0.16

0.27

1

Total of clothianidin and thiamethoxam. LOD and LOQ were the same as in Table 9.

4.2.3 Relationship between the neonicotinoid concentration in soil, on the surface,inside, anthers and pollen of flowers, and on the surface and inside of foraging honeybees.
No significant correlation was found between the neonicotinoid concentrations measured in soil
collected from the base of blooming plants and that measured in/on foraging bees or theanthers/pollen of the plant blossoms (R2 = 0.006, p = 0.472). Nor was there a correlation
between the concentrations measured in anther/pollen tissue of blossoms and that measured
in/on bees foraging on the blossoms (R2 = 0.001, p = 0.792).
5. Summary of the level of detection (LOD) and the level of quantification (LOQ)
Table 12. Summary of the level of detection (LOD) and the level of quantification (LOQ)
Clothianidin

Thiamethoxam

Matrix
LOD

LOQ

LOD

LOQ

Bee collected pollen (ng/g)

0.23780.58780.06810.1805

Dead bee (inside) (ng/bee)

0.02350.06670.00780.0230Dead bee (surface) (ng/bee)

0.0576

0.16310.03230.0921

Sticky trap (ng/cm2)

0.27120.90320.08090.2694Air sampler (ng/m3)

0.70702.35440.10610.3533

Soil (ng/g)

0.10330.23900.02150.0448Flower (surface) (ng/flower)

0.0366

0.09770.0096

0.0263

Flower (inside) (ng/flower)

0.0366

0.09770.0096

0.0263

FINAL DRAFT- Page 90 of 136 CDRC – March 2017

Flower (anther +pollen) (ng/flower)

0.0366

0.09770.0096

0.0263Foraging bee (inside) (ng/bee)

0.02430.08080.02950.0981Foraging bee (outside) (ng/bee)

0.06630.22080.06520.2171

FINAL DRAFT- Page 91 of 136 CDRC – March 2017

The Long-Term Health Consequences of Exposure of Honey Bee Colonies to Dust
Emitted During Planting of Neonicotinoid-Treated Corn Seeds
A Research Project Addressing Project 2 of the Corn Dust Research Consortium, 2015
RFP Final Report, June 30, 2016
By
Jerry J. Bromenshenk, Ph.D.
Research Professor – The University of Montana-Missoula CEO/President, Bee Alert
Technology, Inc.
PMB 2604
91 Campus Drive
Missoula, Montana 59801
E-mail: beeresearch@aol.com
Tel: 406-544-9007
Colin B. Henderson, Ph.D.
Professor – Missoula College, University of Montana, Vice President, Bee Alert Technology, Inc.
.
E-mail: cbhend2504@msn.com
Tel: 406-544-8991
Robert A. Seccomb, M.S.
Computer Specialist, Bee Alert Technology, Inc.
E-mail: bob.seccomb@gmail.com
Tel: 406-554-4947
with
Lucas Whitcher – Missoula College, UM
Kins Loree – Missoula College, UM
Lori Mitchell – Missoula College, UM
Scott Debnam – Division of Biological Sciences and Bee Alert Technology, UM
Phillip Welch – Bee Alert Technology, Inc.

FINAL DRAFT- Page 92 of 136 CDRC – March 2017

The Long-Term Health Consequences of Exposure of Honey Bee
Colonies to Dust Emitted During Planting of Neonicotinoid-Treated Corn Seeds
Project Summary
Our project objective was to assess the effect of experimental exposure of whole honey beecolonies to Clothianidin-contaminated dusts and the potential mitigating influence of postexposure supplemental feeding. Notwithstanding a late date of project approval and restrictedavailability of colonies, in May of 2015 we successfully secured 44 colonies that we dispersed
among three bee yards spaced at a minimum of two-miles separation in the Missoula valley:
Fort Missoula (W Missoula, n = 12), Missoula Cemetery (N Missoula, n = 16), and Mount
Sentinel (E Missoula, n = 16).
Consistent with our objective; we conducted a balanced, two x two, complete random
experiment for pesticide exposure and supplemental feeding. Two frames of bees from half thecolonies in each yard (n = 22) were dusted with Clothianidin in chalk dust to produce anestimated contact dose of 0.2 μg Clothianidin per bee. In our laboratory dusting test trials with
caged bees, this dose killed half of the exposed bees within the first 24 hours.
Following dusting, half of the exposed colonies and half of the controls received post-exposure
supplemental feeding. Colony metrics were collected at pre-dose (July), at two-three weeks
post-dose (August), and at a longer-term post-dose period (third week of September), with afinal assessment (June, 2016) of all colonies that survived the winter.
We obtained a full set of measurements for colony size and condition metrics: (1) before dosingwith Clothianidin, (2) after pesticide exposure, (3) again in September at the end of the 2015
field season with summary metrics for surviving colonies at the beginning of the 2016 fieldseason.
It is noteworthy that during the course of our project, Missoula experienced the second worst
drought on record, so nutritional stress in non-supplemented colonies was assured. Then during
the last two weeks of August and the first week of September 2015, we experienced persistent
heavy atmospheric smoke and ash from extensive forest fires throughout the western U.S. andCanada. Our anecdotal observations suggested that this had some effect on out-of-the-hive
foraging activity as well as colony growth.
At the start of the experiment (pre-dosing), frame coverage by adult bees varied from a low offour to a high of 19 frames, with an overall average of 10 frames of bees per colony. Frames ofbrood varied from a low of 1.63 to a high of 8.75. At the time of Clothianidin dusting, colonies
averaged approximately 11 frames of bees and 5 frames of brood. Equalization and proportional
assignment to treatment groups kept the within-group range in mean bees and brood within one
frame of bees.
As indicated from trapping of dead bees, we successfully induced adult bee kills at levels similar
to those we observed at field sites in our previous study in Nebraska in 2014. Clothianidin
exposure produced immediate kills in the dusted treatment groups of more than 1,100 bees on
average in exposed colonies. After one week, bee mortality dropped to normal levels in the
exposed colonies which received supplemental feeding. After two weeks, mortality in the nonsupplemented colonies also dropped to normal levels. We observed much variation in colony
growth within treatment groups but still measured a trend in colonies exposed to Clothianidin
dust to have fewer frames of bees at the end of the season than controls. In August, all colonies
were still queen-right, had brood, and had survived the Clothianidin dosing. Frame counts ofFINAL DRAFT- Page 93 of 136 CDRC – March 2017

bees ranged from 4 to18, frames of brood from 1.5 to 8.75, averaging 11 frames of adult bees.
By late September, except for one colony, all colonies were still alive with an average of 10.6
frames of bees for colonies which had both adult bees and brood. One colony had absconded.
Another colony had 11 frames of bees but no brood. Curiously, one of these two marked
queens (either from the absconded colony or the broodless colony) ended up in another colony,co-existing with that colony’s original queen. In sum, 42 of the 44 colonies still had bees andbrood. September adult frame counts by colony ranged from 5 to19, brood from 4.25 to 9.
Two-thirds of the colonies were transferred to our fenced apiary at Fort Missoula at the end of
September; the third group was moved later. By the end of October, all colonies had beentransferred to our fenced apiary at Fort Missoula and placed on elevated stands. Queenexcluders were removed and a quick frame count was conducted to assess the population sizeof surviving colonies. At that time, 40 of the original 44 colonies were still alive; although broodrearing had ceased for the season. Colonies then went onto a winter schedule of inspection andfeeding (when required). In November, just prior to wrapping, two more colonies had died,bringing the number of surviving colonies down to 40 from 44.
Overall, overwintering colony survival was 50 percent. This is not substantially worse that what
is commonly being reported by commercial and hobby bee keepers, with the Bee Informed
Partnership reporting 28.1 percent average winter loss and a 44.1percent annual loss
nationwide for April 2015 through March, 2016. Given the late start to our project, beginning withpackage bees near the end of June 2015, and managing them through an unusually dry
summer; our 12 month, fifty percent survival rate, especially when half of the colonies were
subjected to high dust and dietary doses of pesticides and record-tying drought conditions, wasa reasonable outcome.
The importance of extending our project through the winter was illustrated in the final numbers
on colony mortality which we recorded in June 2016. Clothianidin-exposed colonies had a onethird greater risk of death than unexposed colonies, the same as the increased risk associatedwith the absence of post-exposure food supplementation.
Although these increases in risk of mortality were not statistically significant, they are in line with
our findings from our previous CDRC project. Specifically, we experienced two significant bee
kills from pesticide exposure in our previous Nebraska study. Yet, at the end of that study,
during in which we provided supplemental syrup and pollen substitute, the final condition of the
exposed colonies was nearly equal to unaffected colonies.
Increased post-exposure feeding to pesticide-affected colonies may prove to be an effective
way to mitigate colony losses. Relative to other colony attributes, in the 2015 Montana study,colony weights showed only minor differences. Among surviving colonies, queen survival andoverall brood success were not greatly affected. However, we did observe a significant
reduction by roughly two-thirds in brood area in pesticide exposed colonies which did notreceive post-exposure supplemental feeding. That effect was not evident during the 2015
summer and fall months following exposure; it only became apparent in the 2016 spring
resumption of colony activity. This suggests that an important potential long-term effect ofClothianidin-bearing dusts occurs the second season following the exposure. Differences incolony vigor reinforce our findings from Nebraska field studies that supplemental feeding of
exposed colonies is an important action that can mitigate long-term effects.

FINAL DRAFT- Page 94 of 136 CDRC – March 2017

Introduction
Rationale/Background. Colonies exposed to Clothianidin-contaminated pollen and dusts in
Nebraska during the 2014 planting season were supplemented with nectar (syrup) and pollen(substitute) ad lib. While overall exposure to neonicotinoids was low, two of three sites exposed
to high (75.1ppb to 137ppb) levels of Clothianidin in pollen sustained severe losses. Yet by endof trial, all colonies were queen-right. The seriously impacted colonies had recovered to nearly
equal population and overall condition of the other colonies. The third site sustained exposure
with no obvious acute mortality.
Goals and Objectives. In 2015-2016, we investigated long-term effects of neonicotinoidcontaminated dust exposures (by direct deposition and through contaminated pollen) on honeybees to assess whether the impact can be mitigated by better nutrition and bee management.
The persistence of neonicotinoids and other agro-chemicals in corn-growing regions made itnecessary not only to document long-term effects of contaminated dust exposure, but also toseek possible interventions which beekeepers can use to sustain bee health.
Project Overview
Measurement Endpoints. The experimental design we employed was a balanced, two x two,complete random design that included two factors: Clothianidin dusting and Supplemental
feeding. With this design we had controls for each factor and an absolute control that was not
exposed to Clothianidin and did not receive supplemental feeding. Measurement endpoints
included estimated mortality induced by Clothianidin exposure and changes in population size
during the exposure season and the following spring: colony weight (bees plus stores), andreproduction (brood area).
Clothianidin Exposure. We exposed bees to Clothianidin by two routes: ingestion ofcontaminated pollen, and contact with contaminated dust. Dust and contaminated pollen
exposures were calculated to approximate those experienced during planting and simulated
those measured in our 2014 experiments. Experimental bee colonies were monitored over a full,
four-season year; including over-wintering and spring build up. All experiments were conductedin Montana which provides the advantage of a pristine environment, relatively free from agrochemicals, where we can focus on the effect of Clothianidin with low risk of uncontrolled
pesticide exposure.
Colony Maintenance. Each hive received normal honey bee colony maintenance. Bee colony
maintenance included normal bee medications to control common honey bee ailments andpests throughout the course of the experiments, and monthly inspections monitoring frame
counts, honey stores, counts of dead bees in traps, and periodic inspection to ensure that all
hives were queen-right. Between exposure events, colonies were treated as ‘working’commercial colonies for pollination and honey production; moved and fed as needed.
Over-Wintering. In late November/early December 2015, the research bee colonies wereprepared for overwintering using the same techniques used by bee keeping operations in similar
climates. Over-wintered bees were monitored using thermal imaging, acoustic inspection, andweighing systems. In spring 2016, these colonies were taken out of winter storage, inspected,
and all measured endpoints recorded.
Contaminated Pollen and Dust Makeup. We used a simulated dust for exposure treatments.
We prepared the dust using powdered calcium carbonate chalk and technical grade Clothianidin

FINAL DRAFT- Page 95 of 136 CDRC – March 2017

(95%) received from Bayer Crop Science. This chalk/Clothianidin mixture was chemicallyanalyzed at the end of the project to verify the final concentration of Clothianidin per gram ofchalk used in our pollen and dust treatments. For the contaminated pollen, we mixed
Clothianidin directly with Ultra-Bee Pollen Substitute purchased from Mann Lake.
We have previously found that bee colonies readily consume this product and perform well. The
objective was for the bees to consume the entire dose over a period of a few days. In Nebraska,
we experienced a bee kill associated with pre-planting contaminated pollen that ran its course in
about a week.
Application of Contaminated Pollen and Dust Simulants. Contaminated pollen simulant was
fed in a single dose, 0.5-pound dry powder, placed on the top bars of the brood nest, insideeach beehive. Contaminated crop dust simulant was applied to forager bees using the Atkin’s
Dust Tower Implosion System.
Target Concentrations. Our objective was to use exposure levels observed in Crop Planting
Dust studies. In Nebraska, we observed severe bee mortality in colonies at two sites during the
pre-planting period. The measured pesticide residues in the dead and dying bees were 8.5 and16.3 ppb Clothianidin. Bee-collected pollen displayed the greatest amounts of Clothianidin
during the pre-planting period (75-137 ppb at four sites), lower concentrations during planting
period (12-44 ppb), and no detectable ppb at three sites pre-planting, three sites during planting,and all sites post-planting. Consequently, we calculated chalk/Clothianidin concentrations so as
to achieve concentrations greater than 20 ppb in exposed bees.
Methods
Experimental Design. We employed 44 colonies in a two x two experimental design employing
two treatments at two levels with 12 colonies per treatment. Treatments were Control with no e xpos ure or s upple m e nta l fe e ding.
 No e xpos ure with s upple m e nta l fe e ding.
 Expos ure , no supplemental feeding.
 Expos ure with s upple m e nta l fe e ding.
We exposed bees from randomly assigned hives to chalk (calcium carbonate) dust mixed withtechnical Clothianidin at a prescribed concentration.
After exposing bees, we monitored colony progress by measuring classical honey bee
population metrics:
 Ea rly m orning counts of fra m e s cove re d by be e s .
 P e riodic m a nua l a s s e s s m e nt of colony we ights .
 P a s s ive tra ps in front of the hive s to colle ct de a d a nd dying be e s .
 Q ua ntifica tion of brood for reproduction assessments by visual estimates of capped anduncapped brood areas, with photographs taken of a subset of brood frames for calibration of thevisual estimates and archival records of brood responses.
o Brood areas were estimated to within ¼ of each brood comb surface.
o Technicians underwent pre-experimental training and periodic calibration against test broodcombs to assess, improve, and document observer accuracy.

FINAL DRAFT- Page 96 of 136 CDRC – March 2017

Chamber Testing and Determination of Dusting Levels. Analytically certified Clothianidin

Figure 1. Calibration curve for dusting chamber; surface deposition of ash results fromdifferent application rates. Ash application in mg/cm2.
technical (99.7%, lot # 2013-003931, ID # 647438) was provided by Bayer Crop Science. We
made up the crop planter dust simulant by mixing appropriate amounts of the Clothianidin with
chalk dust. We retained subsamples for chemical analysis to verify the final concentration of
Clothianidin per gm of dry chalk used in our dust treatments.
Given the concerns of CDRC reviewers about the method of application of the simulated crop
dust using a powder coating sprayer, and our own concerns about variable particle size of thesimulant, we chose to use a proven dust exposure protocol, equipment, and technique for
evaluation of pesticide dusts in toxicological studies of honey bees (Atkins et al. 1954):
 Atkins ’dus t towe r, is ba s e d on a be ll-jar vacuum duster originally described by Farrar (1948),
Richards and Murphy (1949), and McCallan (1950). It has been a standard method for
determining the toxicity to honey bees of dust-formulated pesticides for US EPA pesticide
registration.
 We de ve lope d a nd s till ha ve a m ode rn, s ole noid-controlled, larger version of the Atkins belltower dusting system that we constructed for a USDA Forest Service study of the effects ofMount Saint Helen’s Ash on spruce budworm larvae. Similar to our proposed study herein, we
exposed one set of budworm to treatments of ash in diet and another to a coating with ash dust.
The budworm study yielded very different budworm results by route of exposure (Bromenshenk
et al., 1987).
 Based on targets placed in our dusting chamber, our implosion device produced a very
consistent coating, as evidenced by the calibration curve below generated for a previous study(Figure 1). As can be seen in the figure, deposition was proportional to loading with reasonablevariation among repeated samples at a given loading.

FINAL DRAFT- Page 97 of 136 CDRC – March 2017

Table 1. Chalk deposition as a function of initial quantity in vacuum dosing chamber tests.
Chalk (g)

s.d.

CV %

0.5
0.75
1
2

Quantity
Deposited(g/cm2)0.00010.00040.00020.00020.00006
0.001420.00004
0.00017

57
339
23
85

5
10

0.00080.00130.00035
0.00202

43
157

We improved deposition consistency by using a solenoid-controlled valve which opens instantly
and more consistently than a manually-operated valve described by Atkins. When theelectronically-controlled solenoid is opened to admit air entry, inrushing air aerosolizes anddisperses the dust in a uniform cloud, dusting the bees. Our system is also portable, facilitating
exposure in the field at the bee collection site. The dusting chamber is large enough to holdseveral frames of bees.
We first tested the vacuum dusting chamber in our laboratory to ensure that it worked reliably.
Using filter paper deposition targets, we performed a series of tests to establish the type andquantity of dusting powder to be used in the dosing experiment. We explored the use of two
inert easily obtainable powders: chalk and talc. Talc proved to be too fine a particle size which
affected repeatability and gave us some concern about its tendency to be transported into thetracheal system of bees, causing health effects unrelated to pesticide exposure. Commerciallyprepared chalk dust of the type used for construction marking purposes was readily and cheaply
available. Tests with it proved that it could be satisfactorily dispersed in the vacuum chamber.
Chalk dust is commonly used for marking bees for behavioral testing, as well as for studying
dust removal
by grooming (Land and Seeley, 2005).
We determined that a 5-gram quantity of powder proved to be easily weighed with precision to
0.001 grams and also produced relatively consistent deposition in the vacuum chamber (Table
1).
Using 5 grams of powder as our dosing quantity we next performed several laboratory trials todetermine the dose of Clothianidin in the powder that produced the desired mortality in caged
bees. Our emphasis was on producing a bee kill equivalent to the observed severe poisoning
incident in Nebraska, not on testing the predicted toxicity of Clothianidin dust.
We collected cages of approximately 200 bees and dosed each at a different concentration of
Clothianidin (Table 2). We settled on the lowest concentration that produced significant mortality
within 24 hours of exposure for our field dosing. The selected Clothianidin concentration(0.00025 g/g or 250 ppm) weighted by deposition (0.8 mg dust/cm2) yielded an estimatedcontact dose of 0.2 μg Clothianidin per bee. This dose killed half of the exposed bees within thefirst 24 hours. Complete kill was observed after 48 hours. That concentration and duration are

FINAL DRAFT- Page 98 of 136 CDRC – March 2017

also on the same order of magnitude as that which we observed in the bee kill just prior to the2014 planting season in Nebraska.

Table 2. Summary of Laboratory dosing experiments to establish field dosing levels of
Clothianidin in chalk powder.
Clothianidin in
Grams Powder
Dose
Observed Effect on
Powder (g/g)(ng/cm2)
Bees
1.0 x 10-3
5812.0
rapid kill < one hour
5.0 x 10-45406.0
~75% kill 24 hour
2.5 x 10-4
1.0 x 10-4
1.0 x 10-5
1.0 x 10-6
Project Chronology

5
5
5
5

203.0
81.2
8.1
0.8

~ 50% kill 24 hour
no kill 24 hour
no kill 24 hour
no kill 24 hour

Colony acquisition. We had extreme difficulty obtaining 48 packages of honey bees given the
drought in California. This was confounded by similar drought conditions which developed inwestern Montana. Weather conditions in Montana slowed colony growth, even with feeding ofsyrup and pollen substitute. From the first week of May 2015 until the start of the experiment,
we periodically monitored the colonies for population size and visually inspected them for any
evidences of pests or diseases. We also medicated all of the colonies with antibiotics.
Our target criteria for colonies to be used in this experiment included absence of disease andpests such as mites, sufficient bee population size (with an overall average size of 8 frames ofbees), a laying queen, several frames of brood, and bees in two stories (two deep hive bodies).
We started with 52 colonies in early May 2015. Supercedure of a few of the package queens
and removal of two colonies that showed evidence of health problems soon reduced the numberof viable colonies to 49. As the drought intensified, by the time most of the colonies reached thetarget population size, one colony had absconded and a couple of others fell below ourminimum target size of at least five frames of bees and three frames of brood, reducing thenumber of viable colonies to 47.
In order to keep a balanced number of colonies in each of the four treatments; we reduced thenumber of colonies per treatment from 12 to 11, giving us a total of 44 colonies that met ourstart-of–the-experiment criteria. We did not want to risk compromising the experiment by
including weak, slow-growing colonies that were likely to be marginal in terms of reaching
sufficient population size and stores for successful overwintering.
Colony Pesticide Exposure. As we described above, we selected 44 colonies that were
sufficiently strong to be used in the Clothianidin-contaminated dust exposure experiment. The
colonies were dispersed among three sites in the Missoula valley to reduce the risk of floral
resource depletion at any one site. We used three registered apiary sites; placing16 colonies on
a mountain slope on the east margin of Missoula (MS site), 16 colonies on the north side ofMissoula near rolling hills (MC Site), and 12 colonies at our fenced research yard at Fort
Missoula (FM Site) on the southeast side of Missoula. This site has access to riparianvegetation along the banks of the adjacent Clark Fork River.

FINAL DRAFT- Page 99 of 136 CDRC – March 2017

Prior to exposure all colonies were inspected and equalized as needed. Even though we
redistributed bees among colonies to equalize them as much as possible prior to exposure,some difference among colonies remained. Consequently, colonies were ranked by relative
strength then arbitrarily assigned to different locations and to treatment groups to ensure asbalanced a set of colonies at each site as possible.
Within each set, colonies were then randomly assigned to one of four treatment groups as
described in our experimental plan.
The dust exposures were all completed between July 23 and July 27, 2015. The vacuum
chamber was transported to each site on the day of exposure. All work was coordinated so thatbee collection and exposure was completed by approximately 9:00 a.m. to minimize the numberof foragers that were away from the hive when bees were collected.
Our target was to expose a sample of bees that approximated the adult forager population orapproximately 25% of each colony. As nearly all colonies were 8 frames or greater strong, we
settled on two full frames of bees to be exposed per colony. For the weaker colonies some ad
hoc adjustments were made to keep the fraction exposed roughly equal. We collected bees
from honey/nectar-rich frames to avoid disturbing the queen or developing brood, and also toensure we collected foragers. Both frames were shaken into a wire mesh cage and dusted with
5 grams of the Clothianidin/chalk mixture. Cages with bees were placed inside a dome-shaped
chamber, which had a weighed amount of dry dust on a tray, placed at the central point of thedome. When the prescribed vacuum was reached, the evacuation line was closed, and arelease valve opened. After 15 seconds, the bees were removed from the chamber.
After dusting, the cage of bees was returned to the hive. We ensured that bees reentered thehive by placing an empty frame box on top of the colony. The cage was opened and inverted on
top of the exposed frames then covered to allow the exposed bees to re-enter the colony. After
15-20 minutes we gently shook any bees remaining in the cage into the colony and removed thebox from the top. The photos below (Figure 2) illustrate the field exposure process:FINAL DRAFT- Page 100 of 136 CDRC – March 2017

Figure 2. Dusting of bees using vacuum chamber in the field. Bees were shaken fromframes into a screen cage. The cage was placed inside one of the chamber domes. A
vacuum was drawn and released, filling the dome and cage with suspended dust. The cagewith dusted bees was then returned to the source colony.

We obtained full colony measurements prior to dusting of the colonies. We then photographedand collected the 24-48-hour bee kills. After 48 hours, we began weekly collection of dead bees
from the traps into plastic storage bags which were kept frozen until they were weighed,counted, and subsampled for chemical analysis. Samples were submitted to the USDA AMSNational Science Laboratory for analysis for Clothianidin residues.
Photographs of the three apiary sites are shown in Figure 3. Only a portion of the Fort Missoulasite is shown. A perimeter fence and adjacent buildings made it difficult to show all 12 colonies
in a single photograph. Figure 4 shows 24-hour bee mortality.

FINAL DRAFT- Page 101 of 136 CDRC – March 2017

Figure 4. Photographs of dead/dying bee capture by traps 24 hours after dosing. For
each site,(FM, MC, andMS)
the top MC
row(16
depicts
the beeof control andcolonies,
theFigure3. Registeredapiarylocations,colonies),
MSloss(16 colonies),
FM (12colonies). Notebottom
row
the
loss
of
bees
from
colonies
dustedwith
Clothianidin
inchalk.
FMandMCdosed withdead bee traps in front of hives and feeder jars on 50% of the colonies, both dosed and notsustained more
Clothianidin
dust severe, early loss. MS losses were more evident at 48 hours.

FINAL DRAFT- Page 102 of 136 CDRC – March 2017

In general, bee mortality was readily discernible within 24 hours of dusting, and the bee kill wasmost severe over the first 48 hours after exposure to the contaminated dust. At MC and FM, the24-hour dead bee drop was heavier than at MS, where the 24-hour loss of bees wasn’t as
severe, but after 48 hours all sites exhibited similar total losses.
Post-exposure monitoring. Daily visual observations at all three apiary locations continued
through mid-September 2015. After Clothianidin exposure dead and dying bees were collected
every 48 hours from all hives for one week. Hive mortality clearly peaked about 48 hours after
dosing. One week after exposure, dead bee counts at dosed hives visually appeared to diminish
to levels similar to control hives.
After the first week, weekly collections of dead bees were made for two weeks. After three
weeks, end-of season feeding protocols were put into effect on all hives to help maintain brooddevelopment and foraging in preparation for winter. Collection of dead bees from traps
continued on an as-needed basis and tracked in field logs. Hives were surveyed every two days
for signs of disease, swarming, or absconding. Consumption of pollen substitute and syrup wasrecorded. Full colony measurements were taken again the third week of August and in midSeptember 2015.
End of season. In Montana, queens typically curtail brood rearing as early as September. Yet
in mid-September, except for one colony, all the rest of the colonies were still viable andcontained brood. In September we also experienced attempted mammalian predation on
several colonies. Two skunks were trapped and removed from the Fort Missoula yard. At Mount
Sentinel, a black bear tipped over several hives. As all hives were safety-strapped theyremained intact. The affected colonies were righted and the entire apiary moved to Fort
Missoula inside the chain-link fenced yard for protection.
Due to the second-worst draught on record for Missoula and extensive forest fires, all of theexperimental colonies were exposed to wild fire smoke for a period of approximately three
weeks. On some days, when the smoke was heaviest, the colonies exhibited greatly reduced
bee flight and foraging. Many also became aggressive and prone to stinging. Despite thepredator and smoke stressors, by mid-September at all three apiaries, many of the Clothianidinexposed colonies had brood areas and frame counts similar to those observed during the predosing inspection.
Smoke and weather conditions cleared significantly by end of September. Colonies appeared toresume foraging on late season bloom, including spotted knapweed bloom, as evidenced byassorted pollens being brought back to the hives by foraging bees.
Weak hives were given entrance reducers, while queen excluders remained in place in between
the brood box and honey super in all hives.
Winter preparation. Colonies were wrapped for winter on November 14, 2015 and moved into
the fenced yard at Fort Missoula. The fenced bee yard provided a measure of security against
vandalism and bears. The elevated stands placed the hives above the reach of skunks.
Prior to wrapping, at end of season, another frame count was conducted to assess population
size in each surviving colony. Hives placed on stands included all of the trial colonies, whether
alive and strong, alive and weak, or weak and expected to die.
Colonies were placed side by side on the stands and pushed tightly together. Styrofoam
insulation was place across the top of the hive covers, and the hives then wrapped in 6 ml,
black plastic, leaving a small entrance opening. Initial infrared (IR) imaging indicated that theFINAL DRAFT- Page 103 of 136 CDRC – March 2017

plastic had to be tightly affixed to the colony front and back in order to detect heat fromclustered colonies. Loose plastic interfered with heat transfer from the hive surface to thesurface of the plastic wrap.
End-of-season frame counts indicated that some colony populations had decreased in size
since the post-dosing collection of data for all measurement endpoints conducted in midSeptember 2015. A few colonies had either died or were failing. None of the colony losses
appeared to be due to shortage of food. Surviving colonies generally had 100 or more pounds ofstores, which appeared to be sufficient for wintering. Nevertheless, we monitored and provided
supplemental food if needed to prevent starvation.
IR camera imaging was used from that point forward to periodically monitor colony survival
throughout the winter. This provided us with the ability to monitor the population status of eachcolony without opening the hives and adding cold stress to the bee colonies.
During warm periods beginning in late January 2016 when the bees were taking cleansing
flights, colonies were opened and visually examined to verify survival status and to add
supplemental food, if needed.
A final colony inspection was made in the spring to collect the full complement of metrics: queen
status, brood areas, population size, colony weight, presence of mites, and any evidence ofdisease.
Results:
Pre-exposure colony condition. All colonies were inspected and final adjustments made toensure all colonies were as consistent as possible at the outset of the experiment. Adult bees
(frames), brood (frames) and total colony weight were assessed. Colonies were then randomly
assigned to treatments with the constraint that weaker and stronger colonies were proportionally
represented in each treatment category. Overall, the number of frames of adult bees ranged
from 4 to 19 (x̅ = 10.7, s.d. = 3.4, n = 44); number of brood frames ranged from 1.5 to 8.75 (x̅ =5.4, s.d. = 1.7), and weight ranged from 28 to 52 kg (x̅ = 39.1, s.d. = 6.1).
After assignment to experimental groups the mean values remained relatively consistent amonggroups. Mean frames per colony ranged from 10.7 to 11.1 and mean brood frames ranged from
4.9 to 5.6 with groups. (Figure 5). Mean weight ranged from 38.1 to 41.2 within groups (Figure
6).

FINAL DRAFT- Page 104 of 136 CDRC – March 2017

Figure 5. Pre-exposure colony strength in frames of adult bees and brood among
treatment groups. N=44 or 11 colonies per group.

Figure 6. Pre-exposure colony weights among treatment groups.

FINAL DRAFT- Page 105 of 136 CDRC – March 2017

Post-exposure colony responses. Prior to exposure we observed minimal bee losses in alltreatment groups. The mean number of dead bees in traps across treatments was 43 (s.d. = 28,
n = 14). Within groups, the mean losses ranged from 24 to 61 bees with no statisticaldifferences among treatment groups. Within the first few days’ post-exposure, however,substantial mortality occurred in the treated colonies (Figure 7). A mean of 1,108 and 1,528
dead bees were collected in traps from Clothianidin exposed colonies compared to 113 and 32
from controls. One week after exposure mortality dropped to slightly less than pre-exposurelevels in all treatment groups except the treated group which received no supplemental feeding.
After two weeks, observed mortality in all groups was near normal and approximately equal.

Figure 7. Numbers of dead bees collected in traps from the four treatment groups beginningjust prior to and up until two weeks following exposure to Clothianidin-contaminated chalk dust.
Clothianidin residues. The number of bees that died and accumulated in traps following
exposure to Clothianidin contaminated dust was dramatic (Figure 7). All dead bees wereperiodically collected from traps and sorted by treatment and date. Twenty-five bees from eachsample were taken from each sample collected during the two weeks following the experimental
dusting (July 15-31, 2015). The samples were then pooled into twelve composite samples
representing each treatment group and each bee yard used in the study. Analysis of thecomposite samples was performed by the USDA AMS Laboratory and Testing Division,
Gastonia, North Carolina. Samples were tested only for neonicotinoid pesticides and their
metabolites.
The returned analyses indicated only Clothianidin in every sample with no other neonicotinoid or
metabolites present. Clothianidin residues were present in every composite sample (Table 3).
Concentrations ranged from 7.9 to 155 PPB with an overall mean of 58 PPB Clothianidin.
Assuming a typical honey bee weight of 0.1 grams, observed concentrations translate to an
average Clothianidin residue per bee of 5.8 ng with a range from 0.8 to 15.5 ng per bee.

FINAL DRAFT- Page 106 of 136 CDRC – March 2017

The only obvious pattern was that Clothianidin residues were higher in samples collected fromcolonies in the exposed, unfed treatment group. Residue concentrations in those colonies weremore than two times higher than those in the exposed colonies that received supplemental
feeding (98.7 vs. 40.4 PPB) or the unexposed colonies (Figure 8).

Although the difference was large, there was sufficient variation among samples that no
statistically significant differences were present. Analysis of variance of square-root transformed
Clothianidin concentrations indicated no significant difference in either main effect or theinteraction between treatment and supplemental feeding (Table 4).

Table 3. Clothianidin concentrations in dead bee samples (PPB). Analysis of pooled
samples performed by USDA AMS Lab, Gastonia, NC. Limit of detection for Clothianidin
was 1.0 PPB.
Unexposed
Exposed byby Bee Yard
Bee Yard
FM
MC
MS
SubFM
MC
MS
SubGrand
Total
Total
Total
Fed
79.6
72.6
7.9
53.4
43.1
66.0
12.1
40.4
46.9
Not
80.7
21.0
17.3
39.7
155.0
88.6
52.6
98.7
69.2
Fed
All
80.2
46.8
12.6
46.5
99.1
77.3
32.4
69.6
58.0

Table 4. Summary of analysis of variance for differences in Clothianidin concentration indead bee samples.

Exposure
Supplemental FeedingExposure*Su
pplemental
Feeding
Error

Type III SS

d.f.

F-Ratiop-Value

1
1

Mean
Squares
7.016
5.739

7.016
5.739

0.925
0.757

0.364
0.410

14.8841

14.884

1.963

0.199

60.6588

7.582

Post-exposure bee populations. The end-of-season inspection indicated that with the
exception of the Clothianidin exposed colonies that received supplemental feeding, all colonies
increased in numbers of adult bees and population size.
Of the original 44 colonies, 42 survived the dosing. One colony was broodless. Either the queen
stopped laying or had been lost. Another colony had absconded. Curiously, we found a marked
queen in another colony, which had two queens. Obviously, either the queen from theabsconding colony or from the broodless colony had moved into another, queen-right, colony.

FINAL DRAFT- Page 107 of 136 CDRC – March 2017

The controls grew more than the pesticide dosed colonies, as expected, but substantial
variation within experimental groups suggests that the differences are not significant (Figure 9).
The change in population size is more evident when the change in frame count from pre- topost-exposure is charted. It is clear that the supplemented, exposed colonies had no increase inpopulation and that the unfed controls increased the most.

Figure 8. Clothianidin concentrations in dead bees collected from traps at colony entrances.
Samples were pooled by treatment within separate bee yards before analysis.

FINAL DRAFT- Page 108 of 136 CDRC – March 2017

Figure 9. Frames of adult bees in control and colonies exposed to Clothianidin contaminatedchalk dust.
It is somewhat surprising that the exposed and control groups that did not receive supplemental
feeding following exposure increased more in terms of number of frames of bees more thantheir comparable unfed groups (Figure 10).
Infrared imaging. The IR imaging was done at no equipment cost to CDRC. We had in hand,

Figure 10. Change in frames of adult bees among control and Clothianidin-exposedcolonies.

FINAL DRAFT- Page 109 of 136 CDRC – March 2017

from our own work and a study funded by Project Apis m (PAms) several IR cameras, ranging
from simple point-and-shoot IR cameras that affix to a cell phone to fully featured, calibrated,
professional IR cameras.
For winter checking of the CDRC colonies, we used a FLIR E60 camera to periodically assesscolony survival. This handheld camera has 76,800 calibrated temperature measurement points
in each image. To avoid any air gap between the hive bodies and the wrapping material, we
stretched the plastic wrap tight and secured with staples.
The following discussion and pictures are intended to be illustrative of the setup of the colonies
of winter at the FM yard, of the camera, and of the IR images captured.

Figure 11. Handheld E60 FLIR
IR/visible light camera.

Figure 11 is our best, E60 FLIR camera, priced atabout $7,000. It can capture both still and video IR
images, and has two cameras – a combined
thermal camera and a visible color digital camera.
Thus, we get both an IR and digital picture fordocumentation. Pictures are stored on an SD
flash card as radiometric jpegs. A radiometric jpeg
saves the actual temperature measurement ofeach and every pixel. In this case, each picture
yields 78,600 calibrated temperature data points.
These images can be post-processed using
proprietary software from FLIR. We have both theStandard FLIR Tools and the advanced FLIR
Research analysis tools software. The first isbundled with the camera; the 2nd is a limited
distribution, relatively expensive program forthermographers and researchers. Again, none of
the costs for the camera or software were charged
to CDRC.

Immediately after wrapping, the hives on one of the stands were imaged (Figure 12) to test theefficacy of the camera. The left picture is a visible color image of one of the sets of colonies on astand. The end of another set of colonies on a stand appears in the background. The IR image
in the picture to the right readily detects the heat from strong colonies, but the image is a bitvague due to taking the picture in daylight and the initial loose fit of the plastic wrap. Colored
plastic banners along the bottom edge of the stands indicate overall colony status at time ofwrapping.

FINAL DRAFT- Page 110 of 136 CDRC – March 2017

Figure 12. Test photos of wrapped colonies. The somewhat loose wrapping
obscures imaging, especially for smaller clusters.
Figure 13 pictures were taken at night after the plastic wrap had been secured more tightly tothe hives. The left picture is of four of the hives on a stand, the middle is of a dead colony at theend of a stand, and the right is of a viable, strong (populous) colony.
The cross hairs are spots where the temperatures shown in the upper left corner of each image
were taken. The ambient temperature averaged < 28o F. That is why the hive with temperatures
ranging from 25.7 to 28o in the center picture is nearly invisible. By comparison, the surface
temperatures of the hive with a strong colony range from 29.7 to 36.3o. Securing the black
plastic wrap to the hive surface effectively makes the wrap transparent to the thermal image.

Figure 13. IR images of wrapped colonies with the plastic tightly wrapped and stapled tohive bodies. The center image is of a dead colony.
With all colonies stored for winter at the FM apiary for security from bears, vandalism, and theft,
periodic checks of colony viability were conducted throughout the winter. Because each month
had a few days of above freezing weather, we were able to lift the lid and quickly confirm the IR
images of colony viability. A final full-colony inspection and collection of colony metrics was
conducted in the early summer of 2016.
Survival of colonies post-treatment. In late September 2015, colonies from the three yards
were moved to a common yard and prepared for winter. Colonies were individually wrapped inplastic and placed on stands in a fenced yard. Periodic checks of colonies through theremaining fall and winter were done to check food status and to identify dead colonies.
Supplemental food in the form of sugar fondant was added as needed through the winter toFINAL DRAFT- Page 111 of 136 CDRC – March 2017

prevent colony death due to starvation. Fifty percent of colonies survived through to spring(Table 5). The general trend was for greater mortality within the exposed colonies where justforty percent survived the winter (Figure 14). Within exposure groups, supplemental feeding
had little effect on survival (55% not fed versus 45% fed). Interestingly, more fed colonies
survived in the exposed group, while more unfed colonies survived in the unexposed group.
Contingency analysis showed that none of the frequency differences were significant (Pearson
Χ2 = 1.73, d.f. = 3, P = 0.63).

We calculated the risk that Clothianidin-exposed colonies and unfed colonies would die over the
winter period as the relative risk coefficient. Relative risk is a ratio of the risk of two eventsoccurring, in our case the risk of overwinter death in Clothianidin-exposed and unexposedcolonies, or the risk of death in fed and unfed colonies. Relative risk for Clothianidin exposure
was 1.33, indicating a 33 percent greater risk of winter colony failure after exposure to
Clothianidin but that the increased risk was not significant (z = 0.903, P = 0.37). The same wastrue for relative risk of failure in colonies that received no supplemental feeding after exposure.
Relative risk was identical, 1.33, meaning failure risk was again 33 percent greater in unfedcolonies, but not significant.

Table 5. Mortality of honey bee colonies by treatment from
September 2015 to June 2016.
Dead
Survived
Percent
Mortality
Exposed
13
9
59.1
Fed
7
4
63.6
Not Fed6554.5
Not Exposed
9
13
40.9
Fed
5
6
45.5
Not Fed4
7
36.4
Column Totals 22
22

Figure 14. Comparison of honey bee mortality between exposure and feeding
treatments.

FINAL DRAFT- Page 112 of 136 CDRC – March 2017

Viability of surviving colonies. Colonies that survived through the winter were generally ingood condition. Average weight for all was 39.7 kg (Table 6). Subtracting the average empty
box and frame weights of 22.6 kg, bees and stores in the surviving colonies averaged
approximately 17 kg (37 pounds).

Table 6. Weights of surviving colonies taken in June
2016.
Surviving
Mean Weights.d.
Colonies(kg)
Exposed
38.9
5.1
Fed
34.9
3.5
Not Fed
42.2
3.7
Not Exposed
40.3
5.3
Fed
39.4
2.9
Not Fed
41.0
6.7
All colonies
39.7
5.1

Figure 15. Colony weights in spring (June) 2016 for survivingcolonies.

FINAL DRAFT- Page 113 of 136 CDRC – March 2017

Colonies that received no supplemental feeding after exposure were slightly heavier, but noneof the differences were significant (Figure 15). Analysis of variance indicated that the only
difference approaching significance was the higher weights in unfed colonies (Table 7; F = 4.36;

Table 7. Summary of analysis of variance for differences in colony weights of survivingcolonies.
Type III SS
d.f.
Mean
F-Ratiop-Value
Squares
Exposure
14.23
1
14.23
0.618
0.443
Supplement 100.34
1
100.344.357
0.052
al Feeding
Exposure*S
40.85
1
40.85
1.774
0.201
upplemental
Feeding
Error
391.4817
23.03
d.f. =1, 17; P = 0.052).
We inspected the surviving hives and measured the brood area, including a survey for presenceof eggs, larvae and pupae. We also searched for presence of a queen in each colony. Only fiveof the surviving colonies were queenless. Three were in the unexposed colonies; two in
Clothianidin-exposed colonies. Four of the five queenless bee populations, however, were incolonies that had no supplemental feeding post exposure. Only one of the queenless colonies
had a viable queen cell present.
Only one of the queenless colonies had any brood or pupae present. Total brood area wasmeasured for the remaining 17 colonies (Table 8). The overall mean was approximately 14
frames of brood per colony, and included eggs, larvae and pupae in every case except for one
colony that apparently had a newly mated queen. The most important difference that is apparent
in the brood data is the three-fold difference in brood between fed and unfed Clothianidin
exposed colonies.

Table 8. Frames of brood counted in 17 queen right colonies remaining among the
22 colonies that survived to June 2016.
Supplemental
Clothianidin
Not Exposed
Row Total
Feeding
Exposed
Mean
s.d.
Mean
s.d.
Mean
s.d.
Fed
15.69
1.95
14.90
0.91
15.25
1.42
Not Fed
5.00
7.81
16.65
5.93
12.28
8.59
Column
11.11
7.41
15.78
4.10
13.85
5.97
Total

FINAL DRAFT- Page 114 of 136 CDRC – March 2017

The analysis of variance indicated that although there were no differences in brood area that
could be attributed to Clothianidin exposure or to supplemental feeding by themselves, theinteraction between exposure and feeding was significant (Table 9; F = 2.9; d.f. = 1,13; P =0.039). Specifically, as pointed out above, Clothianidin-exposed colonies and unexposedcolonies that received supplemental feeding post exposure had nearly equal brood areas in ourJune 2016 inspection. On the other hand, colonies that received no supplemental feeding post
exposure had greatly different mean brood areas—five frames in unfed compared to 15 frames
in fed colonies (Figure 16).

Figure 16. Interaction plot illustrating the effect of supplemental feeding on spring brood area in
Clothianidin-exposed colonies.

Table 9. Summary of analysis of variance for differences in brood area.
SourceType III SS
d.f.
Mean
F-Ratio
Squares
Exposure
1.276
1
1.276
2.326
Supplementa 1.036
1
1.036
1.888
l FeedExposure*Su 2.892
1
2.892
5.271
pplemental
Feed
Error
7.132
13
0.549

FINAL DRAFT- Page 115 of 136 CDRC – March 2017

p-Value
0.151
0.193
0.039

General Discussion
Our overall objective was to determine whether supplemental feeding could mitigate some of
the adverse impacts of high-dose exposure to dust and food borne Clothianidin.
Our methods and approach included simulating common practices of commercial beekeepers in
the USA in terms of colony layout within an apiary as well as typical management practices. We
also focused on duplicating the severity of a bee kill that we observed just prior to planting oftreated corn seed in Nebraska in 2014.
These are the conditions under which pesticide exposure incidents actually occur. Colonies areplaced in yards in numbers ranging from 10 to 200, with 20-30 typical of honey production sites,
larger numbers of colonies arranged in groups around fields for pollination, and at times tens of
thousands of colonies placed in holding yards prior to shipping. In all cases, hives are set close
together to conserve space and to facilitate inspection. Unlike many research designs wherecolonies are spaced far apart to reduce drift, real, working colonies are packed together, either
in rows on single stands, or in groups of four- or six-colonies per pallet.
Whereas it is well known that if colonies are set out in rows where the prevailing wind is parallelto the row, downwind drift to the last colonies in the row may occur, what is not commonly
known is that drift is as much, if not more, an innate property of any colony, regardless of its
placement or location.
In the 1990’s for several years, we had 27 colonies, all equipped with highly accurate bidirectional bee egress and ingress counters, located at several sites on and near the US Army’s
Aberdeen Proving Ground – Edgewood.
What we found (Bromenshenk et al., 1996) was that drift was a property of each colony.
Whereas for any given apiary, in the absence of exposure to toxins, the daily forager bee return
rates were in the mid- to high-90 percent, there were always a few outlier colonies that either
consistency lost bees or that consistently gained bees. The colonies that gained bees (i.e.,
greater than 100% return on a daily basis) were not necessarily at ends of rows or in corners of
the apiary, but could occur anywhere, even in the center of a group of colonies. The colony
itself, not its position, was the critical factor. We concluded that either these colonies that gained
bees were more attractive, possibly emitting higher concentrations of queen pheromone to theatmosphere, or showing less tendency by guard bees to rebuff interlopers. Similarly, we suspectthat the colonies that consistently lose bees may have lower titers of queen pheromone which
affect ability to recognize their own colony or queen. Thus, we arrayed colonies in rows using
commonly found spacing, but we also closely monitored the bee drop into traps for collecting
dead bees, kept photographic records, as well as collected, weighed, and counted the numberof bees in these traps. These are typical of the conditions that occur within commercial
beekeeping operations. Our post-exposure results with respect to numbers of dead bees ineach entrance trap and concentrations of Clothianidin in the bees in those traps have relevanceto field-sampling of dead and dying bees to determine whether a pesticide exposure has
occurred.
Also, when investigating a possible pesticide exposure incident, we remind the investigator thatchemical analysis instrumentation has improved to the point that limits of detection are often as
low as 1-2 parts per billion, which is a vast improvement over the ppm detection levels of the
1960s and 1970s when bee kills by pesticides first came to the foreground of beekeeper andenvironmental concerns. The downside of increasingly lower limits of detection (as well as

FINAL DRAFT- Page 116 of 136 CDRC – March 2017broad spectrum, simultaneous pesticide determination e.g., 200+ pesticides at one time) is that
it is hard to determine what trace levels of one or more pesticides actually mean.
Understandably, there is now a focus on associating small numbers of dead and dying bees infront of beehives which show residues of pesticides with a supposedly confirmed bee kill. As
such, it is important to address the question of what constitutes a bee kill. Johansen and Mayer
and Atkins spent their entire careers studying, testing, and ranking pesticides and in theirseminal book Pollinator Protection: A Bee and Pesticide Handbook, 1990 (available as a recent
reprint from Wicca’s Press). They point out that in a colony where a queen can lay 1-3,000 eggs
per day; one would expect to see some dead and dying bees in front of each hive.
It is excessive numbers of dead bees piling up in front of the hive that is a likely sign of chemical
poisoning. For Todd dead bee traps the following criteria are set: > 100 be e s pe r da y is a norm a l die-off, 200-400 is a low kill, 500 to 900 is a m ode ra te kill, a nd
 1000 or m ore is a high kill.

In other words, a few bees on the ground in front of a hive are not necessarily an indication of abee kill.
Conclusions
Our objective for this project was to induce an acute honey bee kill, then measure short term
and long term effects on colony health. We were particularly interested in the mitigating effects,
if any, of post-kill supplemental feeding on colony recovery. We did so in consideration of theoutcome of our previous year’s research on field exposure to Clothianidin in airborne dusts(Bromenshenk et al., 2014). In that study we generally observed low levels of the pesticide, bothin dust and in honey bee gathered pollen.
However, prior to crop planting activity, significant bee kills occurred at two sites, andClothianidin concentrations in pollen and dust were significantly elevated at three locations.
Surprisingly, colonies at one of three high-exposure sites, as evidenced by increased
Clothianidin in dust and pollen, did not exhibit a bee kill incident. Colonies at both sites
displaying a readily apparent bee pesticide kill event recovered from losses of nearly onequarter of the colony populations. By the end of the approximately eight-week study period,
these colonies were nearly equal in strength to unaffected colonies. Inasmuch as we
supplemented all colonies in the 2014 study with pollen substitute and sucrose syrup, wehypothesized that supplemental nutrition may have been the reason the impacted colonies
recovered so quickly and so well.
For this current study, our experimental Clothianidin dust exposure mirrored our fieldobservations. Exposing two frames of bees per colony to Clothianidin-contaminated chalk (a surrogate for soil dust) induced heavy kills within a few days of
exposure. We observed mean kills of approximately 1,300 bees in exposed colonies which,with an estimated seventy percent recovery efficiency in the dead bee traps we used (Porrini etal., 2002), indicated upwards of 1900 bees per colony were lost in the first few days following
exposure. This would be characterized as a high severity kill by Johansen and Mayer (1990).
For the eight frame average population size colonies that we used, this represented an acute

FINAL DRAFT- Page 117 of 136 CDRC – March 2017

loss of between twenty and twenty-five percent of the bee population and was ten-fold higher
than losses we observed in control colonies over the same period.
The dust concentration of Clothianidin needed to induce our observed kill, 203 ng / bee, may
seem high, but actual contact dose experienced by exposed bees was much lower. Analysis ofdead bees indicated only 5.8 ng / bee Clothianidin residue which was well within published
LC50 which varies between 2 and 44 ng / bee (Iwasa et al. 2001, EPA 2003, Bailey et al. 2005).
It was initially disconcerting that dead bees collected from traps in control and exposed colonies
had similar pesticide concentrations, suggesting that perhaps cross contamination had occurredamong treated and control hives. However, dead bee count data do not indicate that any crosscontamination occurred and closer examination of the data shows that only three sets ofuntreated colonies had high Clothianidin levels. It seems more likely that the presence ofClothianidin in dead bees in the traps in front of control colonies is evidence of drift in sick ordying bees.
Several recent studies have suggested that neonicotinoid exposure can effect orientation andmemory in bees (Blacquière et al. 2012) which would increase errors in hive fidelity. Sick bees
would most likely then be forced out of the hive by guard and housekeeping bees ending up in
the traps of otherwise uncontaminated colonies. Regardless, the absence of increased mortality
and observable differences in other colony variables make it unlikely that the results of our study
are compromised by cross- contamination.
Post-exposure, all colonies increased in number of frames of bees through the season; all werein better condition than pre-exposure counts. Supplement-fed colonies did not increase as muchas their unfed counterparts. This observation confused us at first. It may suggest that absenceof readily accessible food stimulated increased production of brood in unfed colonies to try tocompensate for the difficulty in provisioning the colonies. Through the winter, total colony
weights were all skewed in favor of untreated and of fed colonies but by spring, all of thesurviving colonies emerged within one kilogram mean weight of each other.
The most important long term effects we observe were that over-winter risk of colony death was
33 percent greater in unfed, exposed colonies. Most importantly, spring 2016 brood counts
suggest that the subtle brood effects we observed through the post-exposure flight season in2015 compounded over the winter to have significant effect when brood rearing resumed thefollowing spring in 2016.
In the spring of 2016, significantly smaller brood area, nearly four frames less, was observed in
exposed colonies that did not receive supplemental feeding post-exposure. Depressed broodrearing during the critical early spring period of resumption of foraging would put affectedcolonies at much greater risk for failure in the second year following pesticide exposure. In thespring, colonies need to replace older, over-wintered forager bees with young, vigorous forager
bees as quickly as possible; especially in temperate climates where floral resources become
available rapidly and last for a relatively short growing season.
Supplemental feeding effectively negated the second year brood depression; mitigating the firstyear Clothianidin exposure. So, although hard hit colonies may show apparent rapid recovery
from Clothianidin-induced bee kill during the remainder of the foraging season of the year of the
exposure incident; it appears that in the absence of supplemental feeding, population growth(reproductive) vigor becomes significantly reduced the following spring. Thus, as we observed inFINAL DRAFT- Page 118 of 136 CDRC – March 2017

Nebraska in 2014, post-kill supplemental feeding can negate long-term negative effects, eveninto the second year.

FINAL DRAFT- Page 119 of 136 CDRC – March 2017

Literature Cited
Atkins, E.L., L.D. Anderson, and J. Tuft. 1954. Equipment and technique used in laboratory
evaluation of pesticide dusts in toxicological studies with honey bees. Econ. Entomol. 47(6):965969. Chapter 13:302-317.
Bromenshenk, J.J. and C.B. Henderson. 2014. Nebraska crop dust study, April-May, 2014.
Final Technical Report to Crop Dust Research Consortium, December 1, 2014. 46 pp.
Bromenshenk, J.J.; Smith, G.C.; King, B.E.; Seccomb, R.A.; Alnasser, A.; Henderson, C.B.;
Loeser, M.R. and Wrobel, C.L. New and improved methods for monitoring air quality and theterrestrial environment. 1996. Technical Report ADA 326262, National Technical Information
Service, Springfield, VA.
Bromenshenk, J.J., R.C. Postle, G.M. Yamasaki, D.G. Fellin, and H.E. Reinhart. 1987. The
effect of Mount St. Helens and on the development and mortality of the western sprucebudworm and other insects. In: Mount St. Helens 1980. Botanical Consequences of the
Explosive Eruptions, D.E. Bilderback, Ed., Pacific Division American Association for the
Advancement of Science, University of California Press, Berkeley
Blacquière, T., Smagghe, G., van Gestel, C.A.M. et al. 2012. Neonicotinoids in bees: A review
on concentrations, side-effects, and risk assessment. Ecotoxicology 21 (4): 973-992.
doi:10.1007/s10646-012-0863-x
EPA. 2003. Fact Sheet: fs_PC-044309_30-May-03.pdf.
https://www3.epa.gov/pesticides/chem_search/reg_actions/registration/fs_PC-044309_30-May03.pdf.
Farrar, M.D., W.C. Kane, and H.W. Smith. 1948. Vacuum dusting on insects and plants. J.
Econ. Entolomol. 59(4):714-715.
Gary, N E (1960) A trap to quantitatively recover dead and abnormal honey bees from the hive.
Journal of Economic Entomology 53(5): 782-785.
Johansen, C.A. and D.F. Mayer. 1990. Pollinator Protection: A Bee and Pesticide Handbook.
Wicwas Press, Chesire, Connecticut, 212 pp.
Johansen, C.A. 1966. Digest on bee poisoning, its effect and prevention. Bee World 47:9-25.
McCallan, S.E.A. 1950. Factors influencing deposition in the vacuum bell jar duster. Boyce
Thompson Institut. Contrib. 16*1):27-37.
Porrini, C; Medrzycki, P; Bentivogli, L; Celli, G (2002) Studies to improve the performance ofdead honey bee collection traps for monitoring bee mortality. In VIII Simposio Internazionale
ICPBR on hazards of pesticides to bees, Bologna, Italy, 4-6 September 2002. pp 29.
Richards, M.C. and D. Murphy. 1949. The vacuum duster for applying fungicides and inoculum
to plants. Phytopath. 30:30.
Steinhauer, N. et al. 2016. Colony Loss 2015-2016: Preliminary Results.

FINAL DRAFT- Page 120 of 136 CDRC – March 2017

Use by Honey Bees of Flowering Resources In and Around Corn Fields, Year 2 (Project 1)

Dr. Mary Harris
maharris@iastate.edu
339 Science II
Iowa State University
Ames, IA 50011-3221
phone: (515) 294-2171

Dr. Joel Coatsjcoats@iastate.edu
116 Insectary
Iowa State University
Ames, IA 50011-3140
phone: (515) 294-4776

Dr. Reid Palmer
rpalmer@iastate.edu
G301 Agronomy
Iowa State University
Ames, IA 50011-1010
phone: (515) 294-7378

FINAL DRAFT- Page 121 of 136 CDRC – March 2017

Summary of Results and Recommendations
The basis of this study was to examine the early season weeds and other flowering plants inand around corn fields from which bees could collect pollen. The objective of this study was todetermine best practices for corn production weed management in order to mitigate exposure ofbees to insecticide contamination from planting dust. Detectible levels of clothianidin andthiamethoxam were found in samples of all 12 species analyzed and from pollen collected at all
study sites. Detection of neonicotinoids was most frequent on May 7 and May 19 corresponding
to peak corn planting activities among and adjacent to the study areas. A significant increase in
numbers of dead bees was observed as neonicotinoid contamination levels increased. The
extended period of localized planting and potential contamination from fields adjacent to eachstudy site may possibly preclude a distinct spike in number of dead bees. Results of this study
identify the majority of bee-collected pollen at the time of corn planting in NW Iowa to be fromwoody plants. Woody vegetation in Iowa does not occur within corn fields or along field margins,
but typically is found in farm yards, small woodlots or along water-ways. Therefore weed
management changes would do little to reduce the exposure of honeybees to neonicotinoid
contaminated forage. Recommendations for mitigating the exposure of bees to neonicotinoid
contaminated forage is to discontinue the use of these seed treatments or to improvemethodology to reduce discharge of contaminated dust.
Methods, Cooperators and Study Sites Cooperating farmers who participated in 2014 arelocated in 3 NW Iowa counties and together provided eight corn production sites. Among thesesites both pneumatic (4) and finger type (4) planters were employed and no-till (5), strip-till (1)and conventional (2) cultivation used (table 1). The landscape cover was characterized over a 3
km radius centered on the location of study hive pairs for each site (figures 1 and 2). Covertypes at all sites were heavily predominated by corn and soybean ranging between 75 and 90%.
Hive pairs were positioned at each site along the field margin. Each hive consisted of two 10frame brood boxes containing a queen, brood, approximately 20,000 workers, honey stores,
and a feeding reservoir. All hives were fitted with an external Betterbee® Anatomic Pollen Trap
collect corbicular pollen pellets from returning forager bees prior to and following corn planting.
The traps were deployed for 48 hours with the sampling date representing the second 24 hours.
Bee-collected pollen sampling commenced in 2014 the day of the earliest planting date among
our cooperators (April 21 at site 1). Pollen sampling continued for 5 weeks concluding in lateMay. Drop-zone dead-bee traps measuring 102 by 51 cm were placed in front of each hive anddead bees collected for the same 48-hour periods the pollen traps were deployed.
Pollen was collected from plant species in flower at each site on each date corbicular pollenpellets were trapped. We used these samples to build a pollen library to utilize in species
identification of bee-collected pollen. Bee-collected pollen pellets were sorted by color andrepresentatives selected randomly for imaging. Pollen images were compared to images fromour reference pollen library, allowing identifications for most pollen types. Use of collection date,available plant phenology data, location of plants in bloom and comparison to published pollen
micrographs allowed identification of samples not represented in our pollen library. Using thesemethods we were able to identify the species or genus of 98% of 462 samples in 2014.
Selection of pollen samples for chemical analysis was based on sufficient quantity of
proportionately important species at the maximum number of sites for each collection date.

FINAL DRAFT- Page 122 of 136 CDRC – March 2017

Samples were sent to the USDA, AMS, National Science Laboratory, Gastonia, NC for thedetection of neonicotinoid contamination. Analyses utilized GC/MS with a limit of detection(LOD) of 1.0 ppb for each of the following neonicotinoids; clothianidin, thiamethoxam andimidachloprid).

Results
Neonicotinoid analyses Important forage species in 2014 included maple (Acer sp.) which wasparticularly important as an early season forage source representing large proportions of total
pollen collected over several dates; 72% April 21, 95% April 25, ≥46% May 4 and 7 (figure 3).
Furthermore, maple pollen was collected at the majority of the sites among these dates. Anotherimportant early season forage species was ash (Fraxinus sp.), which represented 34% by
weight of total pollen collected May 4. Apple (Malus domestica) was of similar importance as aforage source accounting for nearly 60% of all pollen by weight collected on May 19. A pollen
species tentatively identified as Artemisia sp. was collected at 5 sites on May 16 in representing
48% by weight of all pollen collected that date.
These results identify the majority of bee-collected pollen at the time of corn planting to be fromwoody plants. Woody vegetation in Iowa does not occur within corn fields or along the margins,
but typically is found in farm yards, small woodlots or along water-ways. The landscape analysis
of each study site (figure 3) can be used to inform availability and proximity of these importantpollen sources (figures 1 and 2). The cover types that could potentially provide woody plant bee
forage include developed land, deciduous and mixed forest, and woody wetlands (table 2).
Together these landscape cover types account for an average of only 9.71% of the landscapesurrounding the hives due to the preponderance of corn and soybean.
Detectible levels of clothianidin and thiamethoxam were found in samples of all 12 species
analyzed (appendix A) and from pollen collected at all study sites. Detection of neonicotinoids
was most frequent on May 7 and May 19 likely corresponding to peak corn planting activities
among and adjacent to the study areas. Planting corresponded to precipitation levels andfollowed periods of low rainfall. It is possible as well that periods of intense rainfall such as that
occurring in the interval between sampling dates of May 7 and 16 can explain some of ourobservations. None of the analyzed pollen species (4) or samples (11) collected on May 16
contained detectable levels of neonicotinoids. During the preceding interval 5.05 cm (>2 inches)of precipitation was recorded. The effects on pollen contamination may be twofold. First, the rain
may rinse any carryover contamination from the exposed flowers and second, newly generated
dust contamination was unlikely due to the saturated soils in the fields precluding the use of
dust generating planting machinery.
Dead bee counts The extended period of localized planting and potential contamination fromfields adjacent to each study site may possibly preclude a distinct spike in number of dead bees.
We recorded planting dates for neighboring fields surrounding site 7 that demonstrate thelikelihood of a planting period effect instead of a specific planting date effect (figure 4). A
significant increase in numbers of dead bees was observed as neonicotinoid contamination

FINAL DRAFT- Page 123 of 136 CDRC – March 2017

levels increased. Average site ppb clothianidin and thiamethoxam levels and site effects were
each highly significant (p<0.0001 and p=0.0006, respectively) (ANOVA; Rsquare=0.65, F Ratio
6.74, Prob>F <0.0001). Furthermore, when days pre/post plant by site was added to the model
along with it's square (based on the data distribution) planting date by site was not a significant
predictor of number of dead bees (p=0.2751).

Table 1. Cooperator planter make, model and serial numbers, type of cultivation, planting dates
and applied seed treatments.
Planting
Site Planter make/model (serial no.)Cultivation
date (s)Seed treatment
1

Case 1250, 24 row (Y8S007175)

no-till

23-Aprclothianidin2Case 1250, 24 row (Y8S007175)

no-till

26-Aprclothianidin,

3

Case 1250, 24 row (Y8S007175)

no-till

21-22 Aprclothianidin,

4

John Deere 1770NT, 24 row(1A01770ZLBM745110)

no-till

21-AprCruiserMaxx250

5White 6122, 12 row 30" airpressure/disc (607742)

conventional

18- Maynone

6John Deere 7000, 6 row narrow
finger (082747A)

conventional

17-19 Maynone

7

John Deere 7000 Max-Emerge, 8
row finger (010025A)

no-till

7-May

CruiserMaxx250

strip till

6/16 May

CruiserMaxx250

8John Deere 7000, 8 row finger(028220) Kinze
3500, 8 row finger (902925)

FINAL DRAFT- Page 124 of 136 CDRC – March 2017

Figure 1. Land cover types surrounding hives to a 3 km radius at each study site with percent landscape in corn andgiven for each site.

03,000 Meters

Site 1-82%

Site 2-83%

Site 3-84%

Site 4-90%

Site 5-75%

Site 6-84%

Site 7-76%

Site 8-83%

FINAL DRAFT- Page 125 of 136 CDRC – March 2017

soybean combined

FINAL DRAFT- Page 126 of 136 CDRC – March 2017

Figure 2. Landscape composition at each study site within a 3 km radius centered on thehive pair. Corn and soybean predominated across all sites ranging between 76 and 90%.

100%

Corn

90%
80%

Soybeans

70%

Developed

60%

Grass/Pasture/Hay

50%
40%

Herbaceous & Woody
Wetlands
Deciduous & Mixed Forest

30%
20%

Alfalfa

10%
0%
1

2

3

4

5

6

7

8

Open Water

Study site

1

2

3

4

5

6

7

8

Alfalfa
Deciduous & Mixed
ForestDeveloped

0.22

0.30

0.21

0.38

0.98

0.16

0.69

0.05

0.37

0.23

1.22

0.34

0.62

0.48

0.06

1.47

8.43

9.16

6.90

5.77

4.68

8.61

11.79

8.79

Herbaceous Wetlands

1.36

1.13

0.42

0.07

0.75

0.47

4.16

0.37

Herbaceous & Woody
Wetlands

1.36

1.14

0.43

0.07

0.76

0.47

4.17

0.37

Total potential forage

12

12

9

6

8

11

21

11

Site

Table 2. Percent landscape cover types potentially providing honeybee forage at each study
site. Totals of potential forage cover types ranged between 6 and 12% at all sites except site
7 where these types covered 21% of the landscape.

FINAL DRAFT- Page 127 of 136 CDRC – March 2017

FINAL DRAFT- Page 128 of 136 CDRC – March 2017

Figure 3 (Previous page). A comparison of pollen species proportions at each site across allpollen collection dates

Figure 4: Field configurations and planting dates adjacent to and within foraging distances ofstudy site 7 hives. Planting occurred over a 4-week period between April 28 and June 4 with the
majority of fields planted between May 11 and 24.

FINAL DRAFT- Page 129 of 136 CDRC – March 2017

Appendix A. clothianidin (clo) thiamethoxam (thi)Clothianidin +Thiamethoxam (ppb)
Dat
e

4/2
1

4/2
5

5/4

5/7

5/1
6

Date
ave.

Precipitation
(cm)

No.

No.

% siteswithclo + thisinceprevious(ppb)

sample date

22.40

-

9.60

1.25

18.53

2.37

61.85

0.00

0.00

5.05

Pollen species

Max.

Min.

Ave.

site
s

sampl
es

clo/thiAcer rubrum

48.6

5.9

23.3

3

3

100.0

Acer sp.

15.2

15.2

15.2

6

6

17.0

Populus sp.

26.9

26.9

26.9

3

3

33.0

Acer sp.

10.3

8.8

9.6

6

6

33.0

Acer sp.

9.1

9.1

9.1

7

7

14.0

Fraxinus sp.

18.7

8.3

13.5

4

4

50.0

Salix sp.

38.0

38.0

38.0

1

1

100.0

Taraxacum
officinales

0.0

0.0

0.0

2

2

0.0

Acer s.

177.1

22.8

60.3

7

13

54.0

Fraxinus sp.

178.1

30.1

77.2

4

4

100.0

Malus domestica

215.0

63.8

121.1

4

4

100.0

Taraxacum
officinales

35.6

5.5

15.4

5

6

100.0

Acer spp.

0.0

0.0

0.0

1

1

0.0

Artemisia sp.

0.0

0.0

0.0

5

5

0.0

Malus domestica

0.0

0.0

0.0

2

2

0.0

Taraxacum
officinales

0.0

0.0

0.0

3

3

0.0

FINAL REPORT- Page 130 of 136 CDRC –October 2017

5/1
9

5/2
3

Lilac

13.1

4.9

9.3

3

3

100.0

Malus domestica

17.0

5.0

11.0

7

7

43.0

Taraxacum
officinales

268.0

5.5

63.4

8

8

63.0

Artemisia spp.

10.5

8.7

9.1

6

6

50.0

Cornus spp.

21.9

6.7

13.0

4

4

75.0

Forsythia spp.

9.1

9.1

9.1

7

7

14.0

Lilac

9.3

7.6

8.5

5

5

60.0

Salix spp.

6.0

6.0

6.0

1

1

100.0

Taraxacum
officinales

4.0

4.0

4.0

4

4

75.0

FINAL REPORT- Page 131 of 136 CDRC –October 2017

43.80

0.00

9.34

0.02

Corn Dust Research Recommendations - 2017
Pollinators provide an important ecosystem service, facilitating the production of foods
and thus helping to provide food security. Concerns have been raised about the
declining populations of some pollinators, and attempts have been made to identify thefactors underlying these declines. Pesticides are among the potential contributors tosuch declines, and much is known about their toxicity and how they are being used, butthere is a need for a better understanding of potential mechanisms of exposure and theirconsequences.
The CDRC was established to study one potential route of insecticide exposure forhoney bees that is associated with the planting of neonicotinoid-treated coated corn
seeds. Some of the planters used to plant these treated seeds may result in someabrasion of the coatings, and generation of dust (referred to as fugitive dust or dust-off)containing insecticide residues that can then be dispersed into the environment in andaround the planted fields. Research funded by the CDRC has investigated thetransmission of fugitive dust, how it can result in exposure to honey bees in the local
environment, and what the consequences may be for honey bee colonies. The CDRC
recommendations are based on data from three years’ work at four separate institutions.
The original CDRC goal was to be as helpful as possible in influencing the behaviors of
all stakeholders with respect to the corn growing season.
Several steps will need to be taken to reduce exposure of honey bees to neonicotinoids
in dust from abraded treated seed coatings that can be released during planting.
Contributions are needed from every sector involved – from farmers, beekeepers,
pesticide and lubricant manufacturers, equipment manufacturers, seed dealers, seedtreatment application operations, government agencies and regulators, extension
agents, agricultural and commodity organizations, and agricultural media. The CDRC
recommendations in bold are identified as having come directly from the resultsof the CDRC research. Other recommendations are supported by work outside the
CDRC research program. All recommendations have been vetted with the members of
the CDRC; and, within the group there is general agreement that the recommendations
though based on three years’ data will benefit from further research. Recommendations
are presented as a part of an incremental approach that will need to be tried and tested,monitored and adaptively managed.
RECOMENDATIONS
A. Farmers•

Use abrasion-reducing lubricants in pneumatic planters during planting to
reduce dust. The CDRC results are not consistent with other research
regarding the extent to which synthetic lubricants reduce net emission of
dust-borne pesticide during planting of treated seed; however, the CDRC
research showed sufficiently significant reductions to warrant use of thesesynthetic lubricants compared to talc or graphite.

FINAL REPORT- Page 132 of 136 CDRC –October 2017

•All research sites showed that during the corn planting window(approximately two weeks) honey bees foraged primarily on the pollen of
woody shrubs and trees including apples, crab apples, hawthorns, maples
and/or willow in areas outside of treated fields. These are important
foraging sources to honey bees, particularly when sufficiently distant fromthe planting area to be unaffected by dust but within the foraging range ofthe honey bee. Bee-attractive woody pollen sources can be vulnerable todrift of pesticides in exhausted dust when corn is planted within 50 metersof such forage.

•

Remove flowering vegetation within fields through tillage, mowing or useof herbicides where appropriate prior to planting.

•

Follow the principles of Integrated Pest Management (IPM). Get information at
http://www.northeastipm.org/ and https://www.epa.gov/managing-pestsschools/introduction-integrated-pest-management.

•

Follow all directions on treated seed container labeling and take precautions to
reduce dust and drift, especially with respect to wind speed and weather
conditions during corn planting. As stewards of the land, farmers play asignificant role in the health of pollinators by reducing drift during corn
planting. See the Guide to Seed Treatment Stewardship http://seed-treatmentguide.com/.

•

Minimize unnecessary use of seed treatment insecticides. Use them only whenneeded, such as where historic pest infestations are above threshold or high risk
factors for pest pressure have been anticipated or determined. While untreatedseeds are available, they may need to be ordered in the fall prior to spring
planting•

Seeding equipment foils and baffles are available that can help deflect dust
downward thereby reducing drift. Please see
https://www.iso.org/standard/61136.html for further information, though thesestandards refer to equipment design, not necessarily foils or baffles.

•

Clean and maintain planting equipment regularly and carefully. Keep in mind that
dust left in the hopper can still cause harm. In cleaning and maintaining planting
equipment avoid generating additional dust and avoid contaminating areas withwash water. The dust needs to be scrubbed or filtered out of the exhaust andplaced below ground or properly disposed of.

•Communicate with beekeepers to ensure that they are aware of planting timing
and can take appropriate precautions to protect colonies (see below).

•

If planting cover crops, choose varieties that are not in bloom during corn
planting.

FINAL REPORT- Page 133 of 136 CDRC –October 2017•Properly store and handle seeds by adhering to recommendations on the seedtreatment tag. Treated seed should be protected from direct sunlight, extreme
heat and moisture and kept in a well-ventilated area.

B. Beekeepers•

Position hives away from areas where drift of corn dust can settle on
herbaceous or woody plants during planting. Prevailing wind direction andwind speed may be helpful indicators for placement.

•

Supplement the hive with internal feeding during and right after corn
planting, and provide clean water to reduce the need for bees to seek waterfrom sources in and adjacent to corn fields that may have been
contaminated by fugitive dust.

•

Protect supplemental food and water from dust drift.

•

Bees that are exposed to fugitive dust can have greatly improved recovery
through post-exposure supplemental feeding and access to clean water. Thisaction has the potential to mitigate long-term effects of exposure.

•

If possible, reduce foraging of bees on the days of planting by confining bees tocolony and/or by providing supplemental feeding source protected from dust drift.

•

Communicate with growers/producers when you have hives in the area to beseeded.

•Clearly label hives with your contact information.

•

Check hives regularly and report incidents to state/tribal lead agencies and/or
EPA. https://www.epa.gov/pollinator-protection/report-bee-kills

C. Pesticide and lubricant manufacturers•

Continue work to improve seed treatments and fluency agents to reduce dust
and dust movement at planting to further reduce risk to bees. This includes
reduction in the generation and movement of contaminated dust off-field (e.g.,
improved sticking agents and coatings, and improved fluency agents).

•

Ensure the lowest effective labeled rate of neonicotinoid treatment is applied tothe seed.

•

Offer fungicide-only seed treatment options.

•

Avoid/limit post-processing of treated seeds.

•

Reach out to farmers, and help make them aware of the potential for pollinators
to be exposed to contaminated dust and of the importance of farmers
implementing recommended actions to reduce bee exposure.

FINAL REPORT- Page 134 of 136 CDRC –October 2017

D. Equipment manufacturers•

Ensure that equipment users understand the importance of bee protections
and the value of using lower-drift lubricants.

•

Reduce aerial mobility of insecticide-laden particles by directing dust
downward through planter design including foils and deflectors inequipment.

•

Provide mechanical means to reduce the movement of dust from fan exhaust
during planting using equipment design principles and verification methods
established in internationally recognized standards (ref. ISO 17962:2015,
Agricultural machinery – Equipment for sowing – Minimization of theenvironmental effects of fan exhaust from pneumatic systems https://www.iso.org/standard/61136.html).

E. Seed dealers•

Adhere to quality control measures outlined in http://seed-treatmentguide.com/wp-content/uploads/2014/12/ASTA-Seed-Guide-Application.pdf•

Support bee health by providing outreach to producers to make wise seed
choices and to follow best seed planting practices.

•

Offer untreated seeds as an option for farmers, and make it clear that this option
is available.

•

Take care in all production, movement, and storage of treated seed before andafter it is used in planting. All abrasion of seed or residue from production has
the potential to contribute to fugitive dust.

F. Provincial, state and federal government agencies and regulators•

Provide financial and instructional support for maintaining trees and shrubs
outside drift areas for bee forage during planting season.

•

Provide guidance for the reduction of attractive herbaceous forage in and aroundcorn fields.

•

Fully fund governmental provisions to ensure that pollinator forage area
enhancement can increase and be sustained.

•

Encourage application of the lowest effective labeled rate of neonicotinoid
treatment on the seed.

•

Ensure that both insecticide-treated and fungicide-only seeds are available, andeducate farmers about this option.

•

Ensure that IPM practice information is available to the producer.

FINAL REPORT- Page 135 of 136 CDRC –October 2017

•Provide a responsive structure for bee-incident reporting and be sure that it isunderstood and used by beekeepers. Ensure that incident report procedures areadequately funded and operate in a timely fashion commensurate with theurgency of this situation for honey bees and beekeepers.

•

Ensure that seed bag labeling is clear and that growers are aware of the potential
risk posed by planter dust.

•

Dedicate transportation corridor and rights-of-way plantings to support theestablishment of pollinator habitat.

•

Reach out to farmers, and help make them aware of the situation and of theimportance of farmers implementing recommended actions to reduce bee
exposure from dust-off.

G. Extension agents, agricultural and commodity organizations, and agricultural
media•

Ensure that IPM practice information is available to the grower/producer.

•

Educate the beekeeper in practices that will safeguard bees.

•

Educate beekeepers on bee-incident reporting.

•

Educate growers/beekeepers so that label directions are clearly understood.

•

Help agricultural producers, seed dealers and other stakeholders become awareof the situation and encourage them to adopt recommendations from this report
to reduce bee exposure.

FINAL REPORT- Page 136 of 136 CDRC –October 2017