AN ABSTRACT OF THE DISSERTATION OF
Jimmy Klick for the degree of Doctor of Philosophy in Horticulture presented on
November 14, 2014.
Title: Marking, Movement, and Management of Drosophila suzukii in Oregon Berry
Crops
Abstract approved: ______________________________________________________
Wei Q. Yang
Denny J. Bruck
Drosophila suzukii Matsumura (Diptera: Drosophilidae) are small invasive flies that in
the past five years (2009-2014) invaded berry and stone fruit production regions in
Europe and the Americas. Evolutionary adaptations, biological traits, and anthropogenic
factors have contributed to its current status as a global pest. Females oviposit eggs into
ripe fruit. Eggs develop into larvae that feed on fruit interiors, rendering fruit
unmarketable. Growers currently prevent infestation by targeting adult D. suzukii with
broad-spectrum insecticides multiple times during the harvest season. Aside from
environmental and non-target impacts of this intensive management strategy, growers are
faced with other challenges, such as fruit knockdown from sprayers, abiding by
insecticide restricted entry and preharvest intervals, disrupting current integrated pest
management (Southwood and Way 1970) programs, and increased input costs.
Pest activity levels and movement were tested in a field mark-capture study with
previously evaluated and inexpensive protein markers. Results confirmed high adult D.
suzukii activity and movement from surrounding non-FURSKRVWVVXFKDVµ+LPDOD\D¶
blackberry into nearby susceptible raspberry. Systemic markers are another method to
test pest ecology hypotheses that protein markers cannot help answer. Albeit more
expensive than protein marking, markers such as the trace element, rubidium, and stable
isotope, 15N, are readily absorbed by plants. In a greenhouse study, both markers were
detected in adults, from larvae that fed on enriched strawberry fruits; however, 15N was
highly persistent in adults after 14 days compared to the rapidly decaying rubidium.
Given D. suzukii¶Vhighly mobile nature and propensity to use non-crop areas
surrounding susceptible crop as overwintering sites or refugia, reduced insecticide
application strategies were tested from 2011±2013. Only the border of crop areas was
treated with insecticides while leaving the center untreated. Multiple border sprays during
two blueberry harvest VHDVRQVZHUHPDGHWRFUHDWHDµZDOORILQVHFWLFLGHV¶ and prevent
invasion of D. suzukii from surrounding non-crop areas. In addition, alternate row
(middle) sprays was tested, where one side of two rows was treated with each sprayer
pass. The untreated side of each row is thought to provide a refuge for natural enemies.
Subsequent sprays were applied on the previously untreated rows. Multiple raspberry
sites were treated with this method during three harvest seasons. These reduced
insecticide application methods managed D. suzukii adults and larvae as well as complete
field applications (border sprays in a low pressure situation), mitigated grower insecticide
application challenges (e.g., application time, fruit knockdown in border sprays
depending on grower practice), conserved post-harvest natural enemy populations, and
reduced input costs. These methods could be easily integrated into a pest management
program if associated risks (e.g., pest pressure) are accounted for.
©Copyright by Jimmy Klick
November 14, 2014
All Rights Reserved
Marking, Movement, and Management of Drosophila suzukii in Oregon Berry Crops
by
Jimmy Klick
A DISSERTATION
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Doctor of Philosophy
Presented November 14, 2014
Commencement June 2015
Doctor of Philosophy dissertation of Jimmy Klick presented on November 14, 2014.
APPROVED:
Co-Major Professor, representing Horticulture
Co-Major Professor, representing Horticulture
Head of the Department of Horticulture
Dean of the Graduate School
I understand that my dissertation will become part of the permanent collection of Oregon
State University libraries. My signature below authorizes release of my dissertation to
any reader upon request.
Jimmy Klick, Author
ACKNOWLEDGEMENTS
I must start by thanking my co-advisor, Denny Bruck, whose eloquent thinking, ceaseless
idioms, and serene personality inspired me to study insects. He is the creator and fearless
leader of the infamous J-Team (Joe Kleiber and myself), who battled the evil menace
Drosophila suzukii. The strong bond among the three of us and the entomology
laboratories at the USDA-ARS-HCRU (Molly Albrecht, Adam Cave, Austin Cuenca,
Hannah Curry, Evan Dishion, Kelly Donahue, Dave Edwards, Christina Fieland, Amanda
Lake, Jana Lee, Jesse Mindolovich, Danielle Selleck, Scott Shane, Bev Thomas, Amelia
Thornhill, Jeff Wong) created an aura of passion for research. At the inception of my
PhD, Wei Yang, Jana Lee, Amy Dreves, and Vaughn Walton graciously joined the force
as my committee members. I credit my co-advisor, Wei Yang, with financing much of
my work and salary and with expanding my skills in presentations and extension by
providing ample opportunities for me to share my research findings. I idolize Amy
'UHYHV¶SDVVLRQDQGHQWKXVLDVPLQH[WHQVLRQDQGVFLHQFHDQGWKDQNKHUIRUDOOKHU
patience and time in sculpting my thoughts towards an integrated pest management (IPM)
approach. Jana Lee was instrumental in instilling confidence in my statistics and writing
skills. 9DXJKQ:DOWRQ¶VFRQVWDQWZRUGVRIVXSSRUWDQGDGYLFHprovided much relief and
strength in my academic pursuit. I must also thank Jay Pscheidt, who facilitated my
preliminary and final exams as a graduate student representative. Many thanks to Scott
Machtley and James Hagler at the USDA-ARS-ALARC in Maricopa, AZ for training and
protein analysis; and James for exceptional writing and review contributions towards
manuscripts. I greatly appreciate 6XMD\D5DR¶VGLOLJHQWZRUNGHYHORSLQJWKH2UHJRQ State
University Entomology Program, with the following members contributing their thoughts
and expertise to my projects: Leonard Coop, Danny Dalton, Joe DeFrancesco, Chris
Hedstrom, George Hoffman, Louisa Hooven, Gail Langellotto-Rhodaback, Peter
McEvoy, Betsey Miller, Jeffrey Miller, Stephanie Parreira, Robin Rosetta, Peter Shearer,
Sam Tochen, Nik Wiman, and Megan Woltz. A special thank you to Paul Jepson, whose
incredible words and numerous publications shaped my perspective on IPM and whose
research advice stuck with me. I will never forget feeling inspired and enlightened after
our meetings.
Much of my research would not have been possible without the patience, support, and
humor from the raspberry growers (Jeff Kreder, Willard & Wendell Kreder, Jason Laube,
Gabriel, Charley & Nathan Goodman), blueberry growers (Doug Kramer, Mac Stewart,
Don Hatai), and Jacto Inc. I am grateful to berry consultant, Tom Peerbolt, and berry
professor, Bernadine Strik, for inviting me to give talks to growers and for helpful
discussions. I greatly benefited from the outgoing and kind people at the USDA-ARSHCRU, such as Andy Albrecht, Pauly Charron, Man-Yeon Choi, Chad Finn, Amanda
Howland, Karen Keller, Ted Mackey, Walt Mahaffee, Bob Martin, Jesse Mitchell, Tara
Neill, Suean Ott, Amy Peetz, Mary Peterson, Carolyn Scagel, Paul Schreiner, Lindsey
Thiessen, Inga Zasada, and the late and great Pete Moppin.
No acknowledgement is complete without thanking the current and former
administrative staff of the Department of Horticulture and USDA-ARS-HCRU (Lee Ann
Julson, Nancy Bremner, Caroline Charlton, Gina Hashagen, Ruth Hamlyn, Maryann
Resendes, Stefani Morgan) for making things easy in the spur of the moment. I
acknowledge the current and former Horticulture Department Heads, Bill Braunworth
and Anita Azarenko, respectively, and the Graduate Student Program Coordinator, John
Lambrinos, for their kindness and support.
Aside from being great friends, Danielle Lightle, Laura Sims, and Hannah Tavalire
are queens of the statistics world and helped me overcome obstacles in data analysis. Joe
Kleiber, the heart and soul of the J-Team, provided fruitful discussions, taught me about
HIILFLHQF\WUDQVODWHG'HQQ\¶VLGLRPV expanded my vocabulary, and made me enjoy life
to the fullest. Other friends that deserve mention and have given me much relief and joy
during the hours not devoted to rigorous research were Jan & Toni Egli, Rheadawn
Gomez, Matt Johnson, Kojun Kanda, Dabao Lu, Lorena Rangel, Jessie Reimer, Tim
Skalland, Emily Smith, Brandon Vig, Emily Weiss, Derek Wells, and Joy Yang.
Lastly and most importantly, I thank my mom, dad, brotherlove, and his amazing
wife, with pets Ruedi, Fritz, and Lola. They have fueled my thirst for a PhD with their
love and delicious treats from afar. Denny, you really hit the nail on the head when you
said these would be the best days of my life!
CONTRIBUTION OF AUTHORS
Drs. Denny Bruck, Amy Dreves, Jana Lee, and Wei Yang oversaw the planning, design,
and funding of projects. Dr. James Hagler analyzed all protein marking samples
(Chapters 2 and 3). Dr. Vaughn Walton and Danny Dalton assisted with spatial statistics
(Chapter 3). All co-authors provided invaluable reviews to manuscripts they were
associated with.

TABLE OF CONTENTS
Page
CHAPTER 1. Introduction..............................................................................................1
History.................................................................................................................2
Biology................................................................................................................2
Identification .......................................................................................................3
Monitoring ..........................................................................................................5
Hosts ...................................................................................................................5
Movement ...........................................................................................................6
Marking ...............................................................................................................7
Management ........................................................................................................8
CHAPTER 2. Evaluating Drosophila suzukii immunomarking for mark-capture
research .........................................................................................................................15
Abstract .............................................................................................................16
Introduction .......................................................................................................16
Materials and methods ......................................................................................19
Results ...............................................................................................................21
Discussion .........................................................................................................24
Acknowledgements ...........................................................................................27
CHAPTER 3. Distribution and activity of Drosophila suzukii in cultivated
raspberry and surrounding vegetation ...........................................................................39
Abstract .............................................................................................................40
Introduction .......................................................................................................40
Materials and methods ......................................................................................42
Results ...............................................................................................................45
Discussion .........................................................................................................46
Acknowledgements ...........................................................................................49
CHAPTER 4. Reduced spray programs for Drosophila suzukii management in
berry crops ....................................................................................................................56


TABLE OF CONTENTS (Continued)
Page
Abstract .............................................................................................................57
Introduction .......................................................................................................57
Materials and methods ......................................................................................59
Results ...............................................................................................................65
Discussion .........................................................................................................67
Acknowledgements ...........................................................................................71
CHAPTER 5. Marking Drosophila suzukii with rubidium or 15N................................81
Abstract .............................................................................................................82
Introduction .......................................................................................................82
Materials and methods ......................................................................................83
Results ...............................................................................................................86
Discussion .........................................................................................................86
Acknowledgements ...........................................................................................87
CHAPTER 6. Conclusion .............................................................................................91
Bibliography .................................................................................................................95

LIST OF FIGURES
Figure
Page
2.1 Effect of the number of days on mean (+ SE) ELISA optical density (OD) readings
and % laboratory-marked Drosophila suzukii adult males (M) and females (F) treated
topically with (A) egg albumin, (B) milk casein, and (C) soy trypsin proteins ......30
2.2 Effect of the number of days on mean (+ SE) ELISA optical density (OD) readings
and % marked cultivated blackberry leaves treated in field in (A±C) April, (D±F)
May, and (G±I) June with (A, D, G) egg albumin, (B, E, H) milk casein, and (C, F, I)
soy trypsin protein...................................................................................................31
2.3 Effect of the number of days on mean (+ SE) ELISA optical density (OD) readings
and % marked adult male (M) and female (F) Drosophila suzukii exposed to egg
albumin protein-treated cultivated blackberry leaves for (A, D, G) 1 min, (B, E, H) 10
min, and (C, F, I) 60 min in (A±C) April, (D±F) May, and (G±I) June..................33
2.4 Effect of the number of days on mean (+ SE) ELISA optical density (OD) readings
and % marked adult male (M) and female (F) Drosophila suzukii exposed to milk
casein protein-treated cultivated blackberry leaves for (A, D, G) 1 min, (B, E, H) 10
min, and (C, F, I) 60 min in (A±C) April, (D±F) May, and (G±I) June..................35
2.5 Effect of the number of days on mean (+ SE) ELISA optical density (OD) readings
and % marked adult male (M) and female (F) Drosophila suzukii exposed to soy
trypsin protein-treated cultivated blackberry leaves for (A±G) 1 min, (B±H) 10 min,
and (C±I) 60 min in (A±C) April, (D±F) May, and (G±I) June ..............................37
3.1 Monitoring traps for D. suzukii WUDSFDSWXUHVZHUHDPRGLILHGµFOHDU¶WUDS(Lee et al.,
2012) made of a bottomless 946 ml clear plastic deli container (DM32R, Solo Cup
Company, Lake Forest, IL) with ten 3.5-mm holes near the top, and nested over a
plastic cup (D32, Solo, Urbana, IL) containing ~100 ml apple cider vinegar (ACV)
(5% acidity, Fred Meyer Apple Cider Vinegar, Kroger Co., Cincinnati, OH) .......52
3.2 Mean D. suzukii (+SE) captured per plot (n=3) in Early Susceptible (ES) and Late
Susceptible (LS) 2011 and 2012 in (A) HB (Himalaya blackberry) and NH (non-host)
field margins and (B) crop by HB and NH .............................................................53
3.3 SADIE (Spatial Analysis with Distance IndicEs) contour maps created in Surfer®
overlaid with traps (small dots) of 3 plots near HB in the south and 3 plots near NH in
the north and the crop boundaries denoted in a dotted line in Early Susceptible (ES)
2011 (A), Late Susceptible (LS) 2011 (B), Early Susceptible 2012 (C), and Late
Susceptible 2012 (D)...............................................................................................54

LIST OF TABLES
Table
Page
2.1 Mean (± SE) precipitation, air temperature, relative humidity, and leaf wetness during
2-week experiments performed in April, May, and June collected from iMetos Ag
weather station within 4 km from the trial site .......................................................29
3.1 Number of protein-marked (nm), assayed (na), the percentage (%) of marked D.
suzukii, and yearly marked ratio (i.e. the total marked flies between HB and NH in
ILHOGPDUJLQRUFURSLQDQGLQµ+LPDOD\D¶EODFNEHUU\+%DQGQRQ-host
(NH) field margins (area treated with egg marker) and in the crop near HB and NH
field margins during Early Susceptible (ES) and Late Susceptible (LS) in
2011/2012 ...............................................................................................................50
3.2 SADIE (Spatial Analysis with Distance IndicEs) summary statistics of Early
Susceptible (ES) and Late Susceptible (LS) in 2011/2012 .....................................51
4.1 Insecticide applications in the alternate row trials (Farms A±D) of raspberry and
border spray trials (Farm E) of blueberry during pre-harvest (p) and harvest (h)
seasons ....................................................................................................................73
4.2 Economic costs associated with alternate row and border spraying compared to the
complete spray method on 4.05 ha .........................................................................75
4.3 Comparison of mean (±SE) D. suzukii adults and larvae in alternate row and complete
spray plots throughout the harvest season and during the After Spray period (3±12 d
after treatment application) in 2011, 2012, and 2013 in raspberry .........................76
4.4 Comparison of mean (±SE) natural enemies in alternate row and complete spray plots
7 d post-harvest in 2011, 2012, and 2013 in raspberry ...........................................77
4.5 Comparison of mean (±SE) common pests found in alternate row and complete spray
plots 7 d post-harvest in 2011, 2012, and 2013 in raspberry ..................................78
4.6 Comparison of mean (±SE) D. suzukii adults throughout the harvest season and
natural enemies and common pests 7 d post-harvest in 2012 and 2013 in border and
FRPSOHWHVSUD\SORWVLQµ/LEHUW\¶EOXHEHUU\............................................................79
4.7 Comparison of mean (±SE) D. suzukii adults throughout the harvest season and
natural enemies 7 d post-harvest in 2012 and 2013 collected from border (~5 m into
the field) and interior (40 ± 60 m into the field) trap positions of border and complete
spray plots in µ/LEHUW\¶EOXHEHUU\ ...........................................................................80
LIST OF TABLES (Continued)
Table
Page
5.1 Mean ȝJ5EJD. suzukii (Rb marking) and 15N atom% D. suzukii (15N marking) (±
SD), ratio of marked: non-marked, and percent marked (%) in female and male D.
suzukii 1, 7, and 14 d after emergence from fruits of strawberry plants enriched with
Rb or 15N .................................................................................................................89
5.2 Output of statistical comparisons for Rb marker content and ratio of marked: nonmarked 1, 7, and 14 d after emergence from fruits of strawberry plants enriched with
Rb ............................................................................................................................90
Dedicated to mom and dad
CHAPTER 1
Introduction
Jimmy Klick
2
History
Drosophila suzukii Matsumura (Diptera: Drosophilidae) seem to inhabit coastal to high
elevations (up to 2,000 m) of subtropic, Mediterranean, and temperate mountainous areas
(Kaneshiro, 1983; Mitsui et al., 2010; Cini et al., 2012; Ometto et al., 2013; Deprá et al.,
2014). The native range of D. suzukii is thought to be Pakistan, northern India, Indochina,
North and South Korea, Taiwan, China, and Far East Russia (Lin et al., 1977; Sidorenko,
1992; Hauser et al., 2009; Ometto et al., 2013). Flies were first described and reported as
a pest of cherries in 1916 in a µhills region at the base of mountains¶ in Japan (Kanzawa,
1935). Drosophila taxonomists recognized its presence in Hawaii in 1980 at about 1,200
m elevation (Kaneshiro, 1983). In September 2008, a specimen suspected of causing
damage in healthy raspberry fruit in California was identified to Drosophila. No alarm
was raised because members of this genus are typically not considered pests and infest
overripe or damaged fruit. In spring 2009, larval specimens from healthy California
cherry fruit were initially falsely identified, but subsequently correctly identified to D.
suzukii (Hauser, 2011). Specimens collected in Spain and Italy in October 2008 were
confirmed as D. suzukii (Calabria et al., 2012; Cini et al., 2012). By 2009, D. suzukii was
also reported in Oregon, Washington, British Colombia, Florida, and France with first
reports of economic damage (Hauser, 2011; Cini et al., 2012). The fly continued to
spread across Europe, North America and most recently into South America, where it
was found for the first time in the coastal subtropical areas of Southern Brazil (Deprá et
al., 2014). Given the delay in recognizing this invasion, understanding its large host
range, and the effect of global trade on fresh fruits, D. suzukii was able to arrive,
establish, and spread across the globe at a rapid pace (Liebhold & Tobin, 2008).
Biology
Drosophilids, also known as vinegar or pomace flies, are typically associated with
infestation of damaged or overripe fruit or known as a laboratory workhorse (Borror &
'H/RQJ0DUNRZ2¶*UDG\. D. suzukii has evolved a unique trait to fit an
ecological niche and reduce competition with most other drosophilids: females have a
serrated and sclerotized ovipositor used to cut through the skin of undamaged and ripe
fruit for egg deposition (Lee et al., 2011a; Atallah et al., 2014). Eggs develop into larvae,
3
which molt three times (i.e., 3 instars) before turning into pupae that eclose into adults.
The entire life cycle can occur relatively rapidly (8±30 d) and can result in 3±15
generations per year (Kanzawa, 1935; Coop & Dreves, 2014), dependent on humidity and
temperature (Dalton et al., 2011; Tochen et al., 2014a,b). The optimal conditions for D.
suzukii development are 28 °C and 79% RH (Tochen et al., 2014b). In Corvallis, Oregon
three to seven generations per year were estimated based on a 20-year average of weather
data (Tochen et al., 2014b; Coop & Dreves, 2014). Adults mature after 1±2 d (Kanzawa,
1935) and use visual (i.e., wing spot), chemical (i.e., pheromones), and sound (i.e., wing
song) at close range for mating (Fuyama, 1978; Atallah et al., 2014). Adult females are
believed to primarily overwinter in a reproductive diapause state in litter, bark, and
buildings (Kanzawa, 1939; Dalton et al., 2011; Ometto et al., 2013). However, some have
found adults in the protection of tree bark, lichens and nooks of branches (A. J. Dreves,
unpublished). Adults and larvae can feed on yeasts and bacteria rich in carbohydrates
(Shorrocks, 1972; Hamby et al., 2012).
Identification
It is vital to correctly identify a pest for the purpose of monitoring, which is one of the
essential steps in any IPM program (Stern et al., 1959). Key identifying features of
drosophilids are: 2±4 mm body length; tan body color with red eyes; two small gaps in
the costal vein known as humeral and costal breaks; plumose arista; and convergent postvertical bristles. Furthermore, Drosophila can be distinguished by the following
characters: dense short hairs on the eyes; well developed post-vertical bristles crossing
over each other and three orbital bristles on the head; and two pairs of dorso-central
bristles on the thorax (Shorrocks, 1972). D. suzukii are polymorphic. Adult males have a
smaller body mass (~0.32 mg), a dark gray dot that appears 1±2 d after eclosion near the
apex of each wing and centered on the first major wing vein, and two sex combs that run
parallel on each foreleg. Females have a larger body mass (~0.46 mg), spotless wings,
and a dark and slightly curved serrated ovipositor tucked into the posterior end of the
abdomen (ovipositor typically exposed when in liquid) (Hauser et al., 2009). Both
genders have unbroken bands across the abdomen, no markings on the side of the thorax,
and clearly defined wing veins. Examples of Drosophila characteristics that might be
4
mistaken for D. suzukii in Oregon are: a smaller spot at the very apex of each wing, 1±2
µeyelash-like¶ sex combs that run perpendicular to male forelegs, broken bands on the
abdomen, µsmoky¶ wing veins, and a weak ovipositor with finer and lighter serrations
(A.J. Dreves, unpublished). Eggs are small and creamy white with two filamentous
breathing tubes, visible on fruit surface after egg deposition into fruit. There are three
instars: 1st instar is 1±2 mm, 2nd instar is 2±3.5 mm, and 3rd instar is 3.5±5 mm in size.
Larvae are slightly curved without legs or a visible head capsule, creamy white to pale
yellow with black visible mouth hooks anteriorly, and anterior and posterior spiracles
(Ashburner et al., 2011). Male larvae have gonads about three times the size of females,
making them relatively easy to distinguish (Hartenstein, 1993). The following examples
may appear similar to D. suzukii larvae collected from Oregon blueberry and caneberry
fields: seeds and floral parts, fruit pulp, thrips, aphids, aphid exoskeleton, and the larvae
of fruitworm, leafrollers, sap beetle, syrphid, lacewing and other drosophilids (Dreves et
al., 2014). The larvae of D. suzukii are difficult to distinguish from other drosophilids, but
are generally considered to be D. suzukii if fruit collected was intact and ripe.
Furthermore, larvae can be reared to adulthood to confirm identification using adult
morphological features. The D. suzukii genome was recently sequenced (Ometto et al.,
2013; Chiu et al., 2013), making the identification of adults and larvae using polymerase
chain reaction now possible (Dhami & Kumarasinghe, 2014; Kim et al., 2014).
At least two other drosophilids have similar capabilities of infesting undamaged and
ripe fruit: D. subpulchrella (Atallah et al., 2014) and Zaprionus indianus (Markow et al.,
2014). At this time, species overlap is not thought to occur in Oregon. D. subpulchrella is
a warm temperature species that is currently found only in Japan and China, where its
pest status is unknown (Takamori et al., 2006; Mitsui et al., 2010). Morphological
features are very similar to D. suzukii. Males have nearly identical spots and females have
a large serrated ovipositor, however, differences are evident in male sex combs and
female spermatheca and can further be distinguished using DNA barcoding (Hauser,
2011; Cini et al., 2012). Z. indianus, also known as the African fig fly, is a new pest
capable of developing on 70 species of fruit (Markow et al., 2014) and is morphologically
5
distinct from D. suzukii. To date, it has been reported in the Southwestern USA, Florida
and Virginia (Markow et al., 2014), and appears to be spreading rapidly.
Monitoring
Monitoring is essential to any IPM program because it infers pest densities and facilitates
decision-making (Southwood & Henderson, 2000; Pedigo, 2002; Kleiber et al., 2014). It
is also useful in developing model forecasts for pests, such as the validated degree-day
model for D. suzukii activity (Coop & Dreves, 2014). Initially, the most commonly used
monitoring tools for D. suzukii adults are wet lure attractants of fermented products, such
DVDSSOHFLGHUYLQHJDUDVXJDUEDNHU¶V\HDVWor wine, inside a clear cup trap with
ten 3±4 mm holes 2 cm below the lid (Lee et al., 2012). Attractants and trap designs are
still being improved with the goal of developing a dry lure and trap design for a more
specific (i.e., fewer non-targets), persistent, and attractive adult monitoring tool. Larval
counts in fruit can be estimated using a boil method (Van Timmeren & Isaacs, 2013),
salt, or sugar solutions (Dreves et al., 2014). In the boil method berries are boiled for 1
min in water, placed on a wire strainer with 0.64 cm mesh, lightly mashed, and rinsed
into a tray (Van Timmeren and Isaacs 2013). Larvae are washed through the strainer
while most of the fruit pulp remains. In the salt and brown sugar methods, solutions of
350 g (1 cup) salt or 650 g (2.5 cups) brown sugar, respectively, per 3.79 liter of water at
10 brix are added to lightly mashed fruit, poured into a tray, and larvae recorded up to 15
min (Dreves et al., 2014). The sugar solution is relatively messy, but has the advantage of
keeping larvae alive to confirm identification using morphological features.
Hosts
A variety of cultivated and non-cultivated plant species serve as D. suzukii hosts (Lee et
al., 2011b; Lee et al., 2014) ripening over an extended period of time (April-October),
facilitating persistence and increasing densities of D. suzukii throughout the growing
season. The host range of D. suzukii includes commercial berries (e.g., strawberry,
blueberry, caneberries) and stone fruits (e.g., cherry, apricots, peaches) as well as noncrop hosts (wild and ornamental) (Lee et al., 2014). D. suzukii are opportunistic and when
food is scarce may be found mainly feeding and sometimes ovipositing on overripe, split,
or damaged apples, persimmon, figs, and tomatoes (Hauser et al., 2009; Lee et al., 2014).
6
Early season non-crop hosts such as wild cherries, Lonicera sp. (MI), and ornamental
Sarcoccoca may substantially contribute to population influxes threatening nearby
susceptible commercial crops. µ+LPDOD\D¶EODFNEHUU\Rubus armeniacus, is a ubiquitous
late season non-crop host in Oregon suspected of supporting fall populations and
providing refugia (Lee et al., 2014; Klick et al., 2014a). Understanding non-crop host
presence, contribution, and quality (i.e., preference, fruit maturity, and suitability) in a
large and small spatial and temporal scale are important in assessing risk to cultivated
crops and determining their ecological role relative to D. suzukii ecology (i.e., refuge,
overwinter, sink-source relationship). The benefits of these non-crop areas must be
determined before management strategies can be recommended as they may also harbor
important resources for natural enemies, pollinators, and wildlife.
Movement
Agroecosystems are less diverse in insect and animal life than natural ecosystems. They
are composed of monocultures of typically 1±4 crops (Metcalf & Luckmann, 1994)
interconnected by natural corridors, such as hedgerows and riparian areas; and can
provide resources for insect pests and natural enemies, impact insect movement, and can
affect insect dispersal (Barrett, 2000). Pest dispersal occurs between and within these
crop and non-crop areas. According to Southwood & Way (1970) insect populations are
affected by on 1) surrounding and within-crop vegetation, 2) permanence of the crop in
space and time, 3) intensity of management (e.g., disruption by pesticides), and 4)
isolation from surrounding unmanaged vegetation. Most drosophilids distribute in
patches influenced by moisture and light and are found at the edge of forests with peak
activities at dusk and dawn (Shorrocks, 1972; Hamby et al., 2013). Vertical distribution
of drosophilids was favored at 10±15 m in oaks and conifers (Shorrocks, 1972). Although
there are no oviposition sites in oaks and conifers, flies seem to be attracted to
microorganisms in tree sap (Shorrocks, 1972). Drosophila spp. are avid fliers known to
disperse over long distances. D. suzukii were believed to migrate from unfavorable (i.e.,
resource poor) habitat at low elevation to more favorable (i.e., resource rich) habitat at
high elevation during the summer (Mitsui et al., 2010). D. pseudoobscura dispersed from
several meters in favorable habitats to several km per day in unfavorable habitats (Iliadi
7
et al., 2002). Other Drosophila have been shown to disperse 150±200 m per day
(McInnis et al., 1982; Taylor et al., 1984).
Marking
Insect marking can be used to track movement, determine trophic interactions, and
understand physiological mechanisms of insects. Movement and dispersal of insects in
the field can be studied using mark-release recapture and mark-capture. In mark-releaserecapture a known number of reared or wild-caught insects are marked in the laboratory,
released at a focal point, and recaptured in traps at a priori distances. In mark-capture,
resident insects are self-marked through direct or residual contact with a marked target
area (e.g., suspected refuge or overwintering habitat) and collected at a priori distances.
Successful movement studies require (an) effective marker(s) and highly attractive traps
for collecting marked individuals, as (re)capture rate is often relatively low (Hagler &
Jackson, 2001). An ideal marker should not affect insect behavior and biology; withstand
environmental degradation and persist in or on the insect; be nontoxic to humans and the
environment; be inexpensive and easy to apply over vast areas; and be easy to detect and
clearly identifiable (Southwood & Henderson, 2000; Hagler & Jackson, 2001). The most
appropriate marker may be species dependent.
Protein marking has been shown to be cost effective, easy to apply, and easy to detect
via enzyme-linked immunosorbent assays. Protein markers do not appear to have any
adverse side effects on insects (Hagler, 1997; Slosky et al., 2012). The first-generation
protein markers were based on vertebrate protein such as chicken or rabbit
immunoglobulin G, but are non-economical for large-scale marking studies (Hagler et al.,
1992). The second-generation markers of food proteins such as chicken egg white (egg
albumin protein), cow milk (milk casein protein), and soy milk (soy trypsin inhibitor
protein) are low-cost markers. These have been used successfully in the field to study
movement and dispersal of pests between managed and unmanaged areas of citrus (Boina
et al., 2009; Krugner et al., 2012), orchards (Jones et al., 2006; Horton et al., 2009;
Basoalto et al., 2010), and vineyards (Lessio et al., 2014). Fluorescent dust (Prasifka et
al., 1999; Hagler et al., 2011) and dye (Schellhorn et al., 2004) markers have been used
for mark-capture research but are difficult to apply over vast areas. Elemental markers
8
(e.g., trace elements, stable isotopes) (Prasifka et al., 2001; Qureshi et al., 2004) also
have been used in mark-capture type research; nonetheless, high costs in both marker
types and potential for negative behavioral and developmental effects in trace elements
(Hagler and Jackson 2001) limit the application of these markers at large scales.
However, these markers are systemic in plants and permit a unique application in markcapture research. The markers above are extrinsic markers, or markers that are added to
an organism. Conversely, intrinsic markers use information that is already in or on the
insect (Bayes et al., 2014). For example, isotope ratios vary in nature and can be used in
ecological studies of migration, trophic interactions, and feeding preferences. Large-scale
migration of monarch butterflies was determined with natural abundance of isotopic
signatures (Hobson et al., 1999). Smaller scale insect movement studies using natural
abundance of a unique 13C to 12C ratio between C3 and C4 plants are also possible (Gould
et al., 2002).
Management
Insecticides are easily applied at low costs for rapid pest control; however, several
environmental and ecological problems arise when insecticides are depended on
exclusively in pest management (Stern et al., 1959; Carson, 1962). Sub-lethal and lethal
effects of chemicals on non-target natural enemies can lead to secondary pest outbreaks
(Croft, 1990) because the µgeneral equilibrium position¶ (i.e., density in the absence of
change) of pest and its natural enemy is disrupted (Gray et al., 2009). Furthermore, overuse of an insecticide on a target pest may result in insecticide resistance. An IPM
program uses multiple tools to manage a pest and uses insecticides only when densities
reach the economic (action) threshold to prevent economic injury (Stern et al., 1959;
Gray et al., 2009). The economic injury level is driven by variation in management costs,
market values, pest activities, host response to injury, and efficient management tactics.
Currently, no threshold and injury level exist for D. suzukii partly because of limited pest
knowledge and a near zero pest tolerance.
The aforementioned factors make it challenging to develop a sound IPM program that
uses tools other than insecticides. Parasitoids in the Figitidae, Pteromalidae, Diapriidae,
and Braconidae families have successfully developed in or on D. suzukii larvae and pupae
9
(Cini et al., 2012; Chabert et al., 2012), however, their role in limiting D. suzukii
populations is largely unknown or thought to be minor. Recently, a previously
undescribed braconid parasitoid from Japan apparently specializes on D. suzukii and will
be further tested as a possible biological control agent (Nomano et al., 2014).
Explorations in South Korea in search of native and specialist D. suzukii parasitoids are
currently being undertaken (J.C. Miller et al., unpublished). Commercially available
predators, entomopathogenic fungi, and nematodes did not produce satisfactory control in
the laboratory (Woltz et al., 2014). Effectiveness of natural enemies in the field is
currently being explored (J.M. Woltz, unpublished).
Cultural control methods include sanitation, physical barriers (i.e., mesh netting), and
altering the host environment (e.g., canopy or floor management, irrigation method).
Other control methods currently being studied are mass trapping (Hampton et al., 2014),
area-wide management, and sterile-insect technique (Cini et al., 2012). A post-harvest
strategy, such as cold storage, has resulted in 70±90% early instar mortality in infested
fruit when placed in cold at 0.5° C or less for a period of 96 hours or more (A.J. Dreves,
unpublished).
To prevent D. suzukii infestations and meet near zero tolerance infestation levels set
by packing plants, growers currently apply broad-spectrum insecticides from the
pyrethroid, organophosphate, carbamate, neonicotinoid, and spinosyn chemical classes 1±
10 times during a typical 4±6 wk harvest season (Beers et al., 2011; Bruck et al., 2011;
Van Timmeren & Isaacs, 2013; Wise et al., 2014). Pyrethroids have been reported to
have the longest residual activity ranging from 7±14 d, followed by organophosphates
and carbamates at 7±10 d, and spinosyn at 3±5 d (Bruck et al., 2011). Neonicotinoids
were not effective on adults in direct or residual (i.e., exposure to treated leaves) trials,
but have shown efficacy against adult and immature stages in semi-field and field trials
(Beers et al., 2011; Van Timmeren & Isaacs, 2013) and curatively for infested fruit (Wise
et al., 2014). Organically certified biological insecticide formulations of pyrethroid and
spinosyn chemical classes known as pyrethrum and spinosad, respectively, are less
effective than synthetic insecticides and not as persistent (i.e., residual activity) (Cox,
2002). Pyrethrum and spinosad have zero to low (3±5 d) residual activity, respectively
10
(Bruck et al., 2011). Pyrethrum is derived from chrysanthemum flower extract (Cox,
2002) and spinosad is derived from fermentation of the actinomycete bacteria,
Saccharopolyspora spp. (Dripps et al., 2011). A semi-synthetic second-generation
derivative, spinetoram, is the form used in conventional pest management. Both forms
have short residence times in the environment, low impact on non-target organisms (i.e.,
natural enemies, pollinators, vertebrates), and greater effectiveness on pests than
beneficial organisms, thus providing an excellent tool for facilitating integration of
chemicals with biological control programs (Dripps et al., 2011).
Rotating chemical classes with different modes of action is an important strategy for
reducing insecticide resistance development. The mode of action of carbamates and
organophosphates is through inhibition of the acetylcholinestirase enzyme (Tomlin,
2003), however, in carbamates the enzyme is not blocked for as long as in
organophosphates (Thacker, 2002). Most organophosphates (e.g., malathion) and
carbamates (e.g., carbaryl) are non-systemic in plants; however, some, such as
diamethoate (organophosphate) and pirimicarb (carbamate) are systemic (Thacker 2002).
All pyrethroids are non-systemic and are contact or feeding poisons. They are also
neurotoxic and interfere with axonal transmission of nerve impulses and movement of the
sodium ions and characterized by quick pest knockdown (i.e., paralysis) (Thacker 2002).
Neonicotinoids are a relatively new insecticide class (1984) of contact and systemic
poisons. They bind to postsynaptic nicotinic acetylcholine receptors (Nauen & Jeschke,
2011). Spinosyns are an even newer class and have a similar mode of action as
neonicotinoids, but are highly specific of certain receptor subtypes, reducing the risk of
cross-resistance between chemical classes (Dripps et al., 2011). Most organophosphates,
carbamates, and pyrethroids have high vertebrate, mammalian, and non-target toxicities.
The neonicotinoids are less toxic to mammals, however, they are coming under increased
scrutiny for their non-target impact (Van der Sluijs et al., 2014). A recently registered
product in the US, from the anthranilic diamides (e.g., cyantraniliprole) chemical class, is
having acceptable levels of mortality on D. suzukii (Beers et al., 2011). This class has a
novel mode of action acting on ryanodine receptor modulators. The receptor is partially
propped open, causing uncontrolled release of calcium ions, which can lead to muscle
11
paralysis and rapid feeding cessation (Lahm et al., 2005). Despite the potential as an
additional chemical tool, several countries have not yet established maximum residue
levels (MRLs) for this class, limiting export of treated fruit. Acceptable pesticide MRLs
vary by country. Growers must use caution to avoid exceeding these MRLs or suffer
fines and possible industry-wide consequences.
These broad-spectrum insecticides applied to entire fields multiple times during the
harvest season have disrupted current IPM programs adopted by growers. In Washington
and Oregon cherries, for example, an organic attract-and-kill product (GF-120)
containing sugar, plant proteins, and extract as bait and spinosad as toxicant, was applied
at a low active ingredient per hectare rate to prevent infestations of Rhagoletis
indifferens, the western cherry fruit fly, with minimal impact to non-target organisms
(Beers et al., 2011). This program is now obsolete in cherries because insecticides used
against D. suzukii are also effective against R. indifferens. Until the arrival of D. suzukii,
blueberry and raspberry growers in the Willamette Valley of Oregon have had the fortune
of relatively few pest problems. In blueberry, aphids were occasionally treated for
contamination problems (D. Kramer, personal communication) because honeydew from
aphids is known to reduce fruit quality (Oatman & Platner, 1972; Blackman & Eastop,
1984); or as vectors of blueberry scorch virus (T. Peerbolt, personal communication).
Scales and winter moth (Operophtera brumata) are typically managed off-season (T.
Peerbolt, personal communication). In raspberries, 1±3 pre-harvest µFOHDQ-XS¶sprays
targeting orange tortix (Argyrotaenia franciscana) and oblique-banded leafroller
(Choristoneura rosaceana) as contamination problem are typically applied (Knight &
Croft, 1987). Soil drenches with insecticides are commonly used for raspberry crown
borer (Pennisetia marginata) management (T. Peerbolt, personal communication). Also,
late-season problems of spider mites can be common (Shanks Jr. et al., 1992). Since the
arrival of D. suzukii growers have significantly increased spray applications, which may
also control these pests or result in secondary pest outbreaks.
Pesticide sprays are highly inefficient at reaching the target pest. Only 0.03±6% of
insecticide active ingredient entering a system was estimated to reach the target organism
(Hull & Beers, 1985; Metcalf & Luckmann, 1994; Pimentel, 1995; Jepson, 2009). Proper
12
insecticide delivery to the target pest is critical to reduce costs, improve efficacy, and
mitigate non-target impacts. Insecticides have been delivered onto the fruiting crop plants
in various ways. A common application method in tree fruits and caneberries is by airblast sprayer, which uses air to propel the insecticide solution into dense canopies. In
caneberry and blueberry, a boom sprayer mounted to the rear of a tractor with a highcapacity pump is often used. Both methods use high-volume and pressure for adequate
penetration and coverage (Matthews, 2000). The electrostatic sprayer uses less volume
and pressure. Very fine droplets are charged as they emerge from nozzles, reducing drift
and improving coverage. However, deposition is affected by various factors and use is
limited by commercial development (Matthews, 2000). Aerial sprays are an expensive
but quick way to cover a fruiting crop, however, large droplet size, drift, and poor canopy
penetration limit the efficacy of this method.
Level of insecticide residual activity varies between production regions and may be
influenced by weather. For example, western Oregon likely has longer insecticide
residual activity (Bruck et al., 2011) than North Carolina because of lower humidity and
less rainfall in the summer (Burrack et al., 2013). Other factors possibly impacting
insecticide efficacy include the method of irrigation, ultraviolet light breakdown, and
inactive ingredients such as adjuvants, stickers, and spreaders (Van Timmeren & Isaacs,
2013). Overhead irrigation is suspected of reducing spray residuals and creating a more
favorable habitat of higher humidity and moisture for D. suzukii (Tochen et al., 2014a),
thus increasing crop risk.
Even with insecticides, growers are faced with challenges, such as knocking mature
fruit off of plants from machinery traveling down row alleys, managing insecticide preharvest and restricted entry intervals (PHI and REI), impacting natural enemies, risking
possible secondary pest outbreaks, and increasing production costs. Reduced insecticide
application strategies are tools that require fewer chemicals, conserve natural enemies,
and lower management costs, while providing adequate pest control. Examples of these
strategies include attract-and-kill, spatially targeted sprays, alternate row middle sprays,
and border sprays (Hull & Beers, 1985; Metcalf & Luckmann, 1994). Attract-and-kill
involves a semiochemical that draws the target pest towards a toxicant. Spatially targeted
13
sprays require knowledge of high-density and concentrated pest areas that are treated.
Alternate row middle sprays skip an alley so that only one side of two plant rows is
treated at the first application and the other sides treated at the next application. Border
sprays treat only the crop plants on the border of a plot, leaving the crop plants in the
center of the plot untreated. These strategies can be effective on pests that are mobile or
with a predictably favorable habitat (i.e., high-density areas), mitigating the impact on the
environment and natural enemies and reducing input costs such as fuel, labor, tractor
wear, and amount of insecticides.
The concept of alternate row and border sprays is not new. DeBach et al. (1955) and
Ripper (1956) reported in the early 1950s that spraying every third row of orange trees
and alternate 12 m strips of sugar beets, respectively, provided sufficient pest control and
conserved natural enemies that moved from untreated to treated areas. The term alternate
row middle first appeared in 1964 as a method to reduce application time when an apple
scab period was forecast in orchards (Lewis & Hickey, 1964). By the 1970s it was widely
used by Pennsylvania apple orchards to control an array of arthropod pests (Hull et al.,
1983). This method was also shown to be compatible with biological control agents of
pest mites (Asquith & Colburn, 1971) and scales (DeBach et al., 1955; Ripper, 1956).
The treatment of border areas was tested as early as 1949. Nishida and Bess (1950)
reported that treating the surrounding vegetation with DDT using a mist blower
successfully reduced melon fly infestation in tomato fruit from 65% in untreated to 3% in
treated sites. More recently, the crop is treated with a border spray application to prevent
pests from migrating into the field (Lafleur & Hill, 1987; Reardon & Spurgeon, 2003;
Ferguson et al., 2003), rather than treating the surrounding vegetation, which is a
biologically important area to the agroecosystem (Van Driesche & Bellows, 1996;
Barrett, 2000).
In summary, the minimal biological control, large monocultures, high production
standards, global trade of fruits, delayed identification, expansive host range, and unique
pest biology and ecology created the perfect storm for D. suzukii to establish as a global
pest. Insecticides are the primary management tool used today for protecting susceptible
fruit from infestation at a relatively low cost and high efficacy. However, environmental
14
and non-target concerns, insecticide resistance development, and lack of a sound IPM
program are driving research towards developing sustainable management tools.
15
CHAPTER 2
Evaluating Drosophila suzukii immunomarking for mark-capture research
Jimmy Klick, Jana C. Lee, James R. Hagler, Denny J. Bruck, Wei Q. Yang
Entomologia Experimentalis et Applicata
Wiley-Blackwell Publishing
101 George Street
Edinburgh, Scotland, EH2 3ES
United Kingdom
152(1): 31±41 (2014)
16
Abstract
Drosophila suzukii 0DWVXPXUD'LSWHUD'URVRSKLOLGDHXWLOL]HVµ+LPDOD\D¶EODFNEHUU\
Rubus armeniacus Focke (Rosaceae), as a host and may invade berry and stone fruit
crops from field margins containing this invasive weed. Laboratory and semi-field studies
were conducted to determine (1) the persistence of protein marks including 10% chicken
egg whites (egg albumin protein), 20% bovine milk (milk casein protein), and 20% soy
milk (soy trypsin inhibitor protein) on topically sprayed D. suzukii, (2) protein retention
on blackberry leaves, and (3) D. suzukii acquisition of protein after exposure to marked
blackberry leaves for up to 14 d after application. All flies and leaves were assayed for
the presence of the protein marks using protein-specific enzyme-linked immunosorbent
assays. Egg albumin, milk casein, and soy trypsin proteins persisted on 94, 49, and 25%
of the topically marked D. suzukii, respectively, throughout the 14-day study period. Egg
albumin was retained on 100% of treated leaves for 14 d, regardless of environmental
conditions. At least 50% of flies exposed residually to egg albumin-treated leaves were
marked for 3 d, regardless of exposure time and environmental conditions. However,
increasing fly exposure time to treated leaves in April and June appeared to improve
protein mark acquisition. Acquisition of protein by flies from treated leaves for milk
casein was inconsistent, and poor for soy trypsin, despite detectable levels on treated
leaves. Egg albumin had the longest and most consistent persistence on flies, leaves, and
flies exposed to leaves in laboratory and semi-field studies, under a variety of
environmental conditions and exposure times.
Keywords: Spotted wing drosophila, Rubus armeniacus, ELISA, insect dispersal, protein
marking, Diptera, Drosophilidae
Introduction
Spotted wing drosophila, Drosophila suzukii Matsumura (Diptera: Drosophilidae), is an
invasive pest that is capable of causing major economic loss in berry and stone fruit
crops. Drosophila suzukii is native to Southeast Asia and was first discovered in
mainland USA, in California, in 2008 (Hauser et al., 2009; Walsh et al., 2011).
Drosophila suzukii is now widely established across North America and Europe (Hauser,
2011; Calabria et al., 2012). In 2009, reports of yield losses in all susceptible crops
17
ranged from negligible to 80% in Pacific coast states (Bolda et al., 2010). Adult flies
oviposit in ripening fruit (Lee et al., 2011b). Fly larvae feed on the fruit interior, making
the fruit unmarketable. Growers heavily rely on protective insecticide applications to
manage this pest. A number of insecticides currently labeled for use in susceptible crops
are efficacious against D. suzukii (Beers et al., 2011; Bruck et al., 2011); however, their
increased use threatens existing integrated pest management programs and has high
potential for insecticide resistance. Increased pesticide use also elevates the cost of
production, but these expenditures are small in comparison to yield losses in the absence
of management (Goodhue et al., 2011). A variety of cultivated and non-cultivated plant
species serve as hosts ripening over an extended period of time (April ± October) and
may facilitate persistence and increased densities of D. suzukii throughout the Pacific
states (Lee et al., 2011b, 2014).
The most abundant invasive and noxious weed commonly found along field margins
and riparian areas of commercial fruits throughout the Pacific Northwest of the USA is
µ+LPDOD\D¶EODFNEHUU\+%Rubus armeniacus Focke (Rosaceae) (Ringold et al., 2008).
The effects of HB on D. suzukii population dynamics, presence, and movement between
field margins and cultivated crops are unknown. Unpublished field observations from
2010 through 2013 suggest that D. suzukii populations increase in field margins
containing HB and other non-cultivated hosts initially and subsequently colonize interiors
of cultivated crops when fruit begins to ripen. Landscape ecology and overwintering
studies from 2009 to 2013 also indicate that HB and diverse riparian habitat provide ideal
refuge for D. suzukii adults (A.J. Dreves, unpublished). These observations suggest that
the presence of HB in field margins is a key factor in annual D. suzukii infestations in
neighboring crops. An understanding of D. suzukii dispersal will aid in the timing of and
need for pest treatments and may allow for implementation of alternative management
VWUDWHJLHVVXFKDVFURSµERUGHU-VSUD\V¶PDVVWUDSSLQJDQGSRVVLEOHIXWXUHEDLWVSUD\VWR
mitigate D. suzukii invasion, significantly reducing insecticide usage, potential negative
environmental impacts, and grower expense. However, we currently lack definitive data
on the timing and extent of D. suzukii dispersal from non-cultivated hosts neighboring
cultivated plantings.
18
Insect mark-capture type dispersal research often requires (a) marker(s) to tag the
resident insect population of interest. Ideal markers should not affect insect behavior
(e.g., flight, growth, life span), withstand environmental degradation, be inexpensive and
easy to apply over vast areas, and be easy to detect (Hagler & Jackson, 2001).
Furthermore, the most appropriate marker may be species dependent. Therefore, studies
are necessary to determine the most suitable mark for the mobile D. suzukii prior to
conducting an extensive mark-capture study. Dust (Prasifka et al., 1999; Hagler et al.,
2011) and dye (Schellhorn et al., 2004) markers have been used for mark-capture
research, but they are difficult to apply over vast areas. Elemental markers (Prasifka et
al., 2001; Qureshi et al., 2004) also have been used in mark-capture type research;
however, high costs and potential for negative behavioral and developmental effects
(Hagler & Jackson, 2001) likely limit the application of these markers in large-scale
mark-capture studies for the small (2±3 mm) D. suzukii.
Protein marks have been shown to be cost effective, easy to apply, and easy to detect
via enzyme-linked immunosorbent assays (ELISA) (Jones et al., 2006). Additionally,
protein marks do not appear to have any adverse side effects on insects (Hagler, 1997;
Slosky et al., 2012). Proteins have been used successfully in the field to study movement
and dispersal of pests between managed and unmanaged areas of citrus (Boina et al.,
2009; Krugner et al., 2012) and orchards (Jones et al., 2006; Horton et al., 2009; Basoalto
et al., 2010). Currently, the efficacy of marking D. suzukii with proteins has not been
determined. Also, little is known on the effect of environmental conditions (e.g., rain,
temperature, humidity) on protein mark persistence.
The objective of this study was to identify the most compatible protein marker, which
included egg albumin in chicken egg whites, milk casein in bovine milk, and soy trypsin
inhibitor (hereafter referred to as soy trypsin) in soy milk, for future use in mark-capture
dispersal studies of D. suzukii. The attributes of each mark type were determined by
analyzing (1) protein persistence on topically-sprayed D. suzukii, (2) retention on
blackberry leaves under varying environmental conditions, and (3) residual acquisition of
protein by flies exposed to marked blackberry leaves up to 14 d after contact. Suitable
protein marks identified here will be used to study D. suzukii movement in
19
agroecosystems.
Materials and methods
Laboratory colony. Drosophila suzukii originated from adults collected from infested
fruit from grower fields in the Willamette Valley of Oregon in 2009. Male and female D.
suzukii adults were placed in 75-ml plastic culture vials filled with ca. 9.4 cm3
Drosophila cornmeal diet (San Diego Drosophila Stock Center, San Diego, CA, USA)
ZLWKDOLJKWVSULQNOLQJRI)OHLVFKPDQQ¶VDFWLYHGU\\HDVW$&+)RRG&RPSDQLHV
Memphis, TN, USA) and capped with foam plugs. Cultures were maintained in climate
chambers held at 22 ± 1 °C, 35 ± 5% RH, and L16:D8 photoperiod. Field-collected D.
suzukii were introduced into the colony on multiple occasions in 2010 and 2011 to ensure
that the genetic make-up was representative of the field population. Adult flies, ranging
from 3±15 d old, were used in the experiments.
Direct contact topical exposure. A laboratory study was conducted to evaluate the
persistence of three protein marks that were topically applied to adult flies. The
experiment was performed in a completely randomized block design with the date of
protein application used as the blocking factor. Each protein treatment was replicated 3×
on three application dates (4 May, 3 and 21 June 2011). An experimental unit of 50 D.
suzukii adults of each sex was randomly chosen from the colony and immobilized with a
portable CO2 dispenser (Genesee Scientific, San Diego, CA, USA) for 3±5 s, placed on a
100 × 15-mm Petri plate (VWR International, Randor, PA, USA), and treated with 2 ml
of 10% chicken egg whites (vol/vol) (All Whites; Papetti Foods, Elizabeth, NJ, USA),
20% bovine milk (vol/vol) (Hy-Top 2% reduced fat milk; Federated Group, Arlington
Heights, IL, USA), 20% soy milk (vol/vol) (WestSoy organic unsweetened soya milk;
The Hain Celestial Group, Melville, NY, USA), or water (untreated control) using a
Precision Potter Spray Tower (Burkard Scientific, Uxbridge, UK). Application treatments
were randomly assigned to flies. Within an hour after treatment, treated flies were moved
into respective transparent cages (22 × 22 × 27 cm) designated by treatment and replicate
to avoid cross contamination, and maintained in climate chambers as previously
described. The cages contained a Petri dish of the diet (as previously described) and a
watering system (water container with sponge wick). To determine marker durability,
20
five randomly selected D. suzukii of each sex were removed from each cage 1, 3, 7, 10,
and 14 d after treatment, killed by freezing, individually placed into 1.5-ml
microcentrifuge tubes, and stored at -80 oC until they were assayed for the presence of the
protein mark by ELISA, as described below.
Indirect contact residual exposure. 5HVLGXDOH[SRVXUHZDVGHILQHGDVDQXQPDUNHGIO\¶V
direct contact with a protein-PDUNHGOHDILHDIO\¶VDFTXLVLWLRQRIDJLYHQSURWHLQDIWHU
walking over a protein-treated leaf surface. Protein mark acquisition and subsequent
persistence was evaluated by exposing flies to treated blackberry leaf surfaces for 1, 10,
or 60 min. Mark acquisition was performed as a semi-field experiment in a completely
randomized block design with date of application (April, May, and June) as the blocking
factor. Four mature cultivated blackberry plants were systematically selected from a stand
of eight outdoor plants (buffer plant between each experimental treatment to avoid cross
contamination) located at the USDA-ARS Horticultural Crops Research Unit (Corvallis,
Oregon, USA). Plants were sprayed with fine droplets of chicken egg white, bovine milk,
and soy milk, or water (control) using a hand-held spray bottle on 17 April, 4 May, and
21 June 2011 at the same concentrations as used above. Each plant was sprayed with a
500-ml solution of each treatment to ensure full coverage of all leaf surfaces at a time
when no precipitation was forecasted for at least 24 h. Nine leaves were randomly
selected throughout each plant canopy 1, 3, 7, 10, and 14 d after treatment, with measures
to avoid contamination. Each leaf was trimmed to a 50-mm-diameter disc and placed into
a 50 × 11-mm Petri dish, randomly assigned to 1, 10, or 60 min of exposure, and
replicated 3×. Five D. suzukii adults of each sex were anesthetized with CO2 for 3±5 s
and placed into the Petri dish containing the treated leaf. After the exposure time elapsed,
flies were killed by freezing, leaf samples were taken by pressing the end of a plastic
drinking straw firmly into the surface and cutting a small section (fresh straws were used
between samples to avoid cross contamination), and fly and leaf samples individually
placed into 1.5 ml microcentrifuge tubes and stored at -80 °C until they were assayed for
the presence of protein by ELISA.
ELISA analysis. Flies and leaves were analyzed using protein-specific ELISAs (Jones et
al., 2006). In brief, each sample was soaked in 750 Pl Tris buffered saline (pH 7.4) at 27
21
°C for 1 h at 100 r.p.m. on an orbital shaker and then assayed for the presence of
protein using the anti-chicken egg albumin, anti-milk casein, or anti-soy trypsin inhibitor
ELISA. Fly and leaf samples were scored positive for the presence of the protein mark if
the ELISA optical density (OD) reading was three standard deviations greater than the
mean negative control result (Hagler & Jones, 2010).
Weather station. Weather data were collected from iMETOS Ag weather stations (Pessl
Instruments, Styria, Austria) with temperature/RH and leaf wetness sensors at a location
within 4 km from the trial site (Table 2.1).
Statistical analysis. Proteins on leaves and topically- and residually-treated flies were
statistically analyzed using Proc GLIMMIX (SAS Ver. 9.3; SAS Institute, Cary, NC,
USA), with ELISA OD as the continuous response variable and assuming Gaussian,
exponential, or lognormal data distribution, where appropriate. Separate analyses were
done for each protein (egg albumin, milk casein, or soy trypsin) from each study (leaf,
WRSLFDORUUHVLGXDOFRQWDFW7KHSUHGLFWRUYDULDEOHVIRUµOHDI¶ZHUHGD\VDQGPRQWKVIRU
µGLUHFWFRQWDFW¶H[SRVXUHWLPHVH[DQGGD\VDQGIRUµUHVLGXDOFRQWDFW¶H[SRVXUHWLPH
sex, days, and month. Interaction terms were included as predictor variables, but only the
highest-order interaction terms were analyzed as non-significant interactions were
sequentially removed from the model. The model included month of application (April,
May, and June) as a random factor in analysis of topically treated flies, but as a fixed
effect in residual experiments because we were interested in the effect of month (i.e.,
environmental conditions). To detect ELISA OD differences across days, LSMeans
comparison tests were applied. To simplify, the LSMeans only compared means from
each sex when the effect of sex was significant. Due to the variation by month, separate
LSMeans tests were done for each month for the leaf and residual studies. To investigate
the interaction between exposure time and day, the 15 combinations of exposure time and
day (i.e., 1 min and 1 day) were compared altogether by LSMeans for each month of the
residual study.
Results
Direct contact topical exposure. The egg albumin persisted on all D. suzukii for 7 d after
the application and declined only slightly (<15%) after 10 and 14 d. The ELISA OD
22
readings significantly declined over time and were higher for females than males (day
effect: F4,438 = 36.59, P-value<0.0001; sex effect: F1,438 = 7.40, P-value = 0.0068; Figure
2.1A). Milk casein was detected on only 65% of the flies the day after the application and
then decreased to 50% after 3 d, after which it remained relatively constant. The mean
ELISA OD readings yielded by the milk casein-marked flies was almost 3× less than that
of the egg albumin-marked flies (sex*day interaction: F4,438 = 4.46, P-value = 0.0015;
Figure 2.1B). The persistence of soy trypsin on the flies sharply declined after the 1st day
to less than 10% by day 14. ELISA OD readings for soy trypsin-marked D. suzukii were
similar to the milk casein-marked individuals and gradually decreased over time. The
females had significantly higher ELISA OD readings than males (day effect: F4,435 =
36.46, P-value <0.0001; sex effect: F1,435 = 5.65, P-value = 0.018).
Indirect contact residual exposure. Egg albumin was detected on 100% of the field-aged
cultivated blackberry leaves over the course (14 d) of the study (Figure 2.2A,D,G) despite
exposure to a variety of environmental conditions (e.g., precipitation, temperature,
relative humidity, and leaf wetness) during the three trial periods (Table 2.1: April, May,
and June). Mean ELISA OD readings for leaves treated with chicken egg white in April,
May, and June were high and showed very little variation over time (day effect, April:
F4,30 = 8.41, P-value <0.0001; May: F4,30 = 1.64, P-value = 0.19; June: F4,24 = 1.48, Pvalue = 0.24; Figure 2.2A,D,G). Milk casein ZDVGHWHFWHGRQ•RIDOOOHDYHVRYHUWKH
2-wk study in April and May. However, in June the protein was not retained well on leaf
surfaces. The percentage of leaves marked with bovine milk fluctuated for 10 d between
80 and 100% and then sharply declined to 30% by day 14. The milk casein ELISA OD
readings were consistently lower than egg albumin and gradually declined over time (day
effect, April: F4,30 = 2.92, P-value = 0.038; May: F4,30 = 3.25, P-value = 0.025; June: F4,30
= 5.11, P-value = 0.0029; Figure 2.2B,E,H). Milk casein retention on leaves was lowest
in June. The leaves treated with soy milk yielded similar ELISA OD values as the milk
casein mark; that is, they were lower than egg albumin and lowest in June. In addition,
ELISA OD readings for soy milk-treated leaves decreased over time (day effect, April:
F4,30 = 14.34, P-value<0.0001; May: F4,30 = 6.27, P-value = 0.0009; June: F4,30 = 7.65, Pvalue = 0.0002; Figure 2.2C,F,I). The total percentage of leaf samples containing soy
23
trypsin was 100% in April; however, the retention of the mark on the leaves decreased
to 60% after 2 wk in May and June.
Exposure time*day interaction was significant for those flies exposed to the egg
albumin treated leaves in all three trial periods (April: F8,420 = 4.64, P-value<0.0001,
Figure 2.3A±C; May: F8,420 = 15.14, P-value<0.0001, Figure 2.3D±F; June: F8,420 = 2.95,
P-value = 0.0032, Figure 2.3G±I). In June, female flies yielded significantly higher
readings than males (F1,420 = 5.60, P-value = 0.018; Figure 2.3G,H,I). Overall, at least
50% of the flies acquired and retained the egg albumin mark for 3 d after a 1, 10, or 60
min exposure period to the treated leaves (Figure 2.3). In April, the percentage of marked
flies subjected to the 1 and 10 min exposure treatments sharply declined to less than 40%
after 3 d (Figure 2.3A,B). However, 60% of the female flies subjected to the 60-min
treatment acquired and retained the egg albumin for up to 10 d (Figure 2.3C). In May,
•RIWKHIOLHVwas marked over the duratLRQRIWKHVWXG\DQG•IRUXSWRd
after residual exposure to the leaves (Figure 2.3D±),Q-XQH•RIWKHIOLHVZHUH
marked 7 d after exposure (Figure 2.3G±I). Increasing exposure time from 1 to 10 or 60
min resulted in more marked flies 10 and 14 d after contact exposure of the flies to the
protein treated leaves.
7KHUHZHUHQRVLJQLILFDQWGLIIHUHQFHVLQWKHIO\¶VDFTXLVLWLRQIURPPLONFDVHLQ-treated
leaves with regard to exposure time and day in the April and May experiments. However,
in June, there was a significant exposure time*day interaction (F8,420 = 11.58, Pvalue<0.0001; Figure 2.4G±I) with males having significantly higher ELISA OD
readings than females (F1,420 = 11.74, P-value = 0.0007). In April and May, less than 50%
of the flies were marked throughout the 2-wk study. In June, no flies were marked on day
1, regardless of exposure time (Figure 2.4G±I). Surprisingly, as the milk casein residue
RQWKHOHDIDJHGWKHSHUFHQWDJHRIPDUNHGIOLHVLQFUHDVHGWR•DIWHUd. High
concentrations on the milk casein-treated leaves (e.g., high ELISA OD values) resulted in
low ELISA OD readings and percentages of marked flies exposed to those leaves.
Conversely, low ELISA OD readings on milk casein-treated leaves resulted in higher
readings and percentages of marked flies. This discrepancy is discussed below.
No differences were found in flies exposed to soy trypsin-treated leaves. However, in
24
May and June, there were significant exposure time*day interactions (May: F8,417 =
3.63, P-value = 0.0004, Figure 2.5D±F; June: F8,419 = 2.47, P-value = 0.013, Figure
2.5G±I) and females had higher ELISA OD readings than males (May: F1,417 = 6.24, Pvalue = 0.013; June: F1,419 = 11.12, P-value = 0.0009). The percentage of flies marked
containing soy trypsin was never greater than 20% in all trials.
Discussion
Throughout the 14-day laboratory trials, the vast majority (94%) of flies topically marked
with egg albumin retained the mark, whereas only 49 and 25% of the milk casein and soy
trypsin marked flies were positive for the mark, respectively. Female flies retained more
egg albumin and soy trypsin than males. An interaction effect in milk casein did not
permit analysis of sex alone. Females may have acquired more protein because of
physiological (e.g., larger body size) (Hauser, 2011) or behavioral (e.g., feeding,
grooming) differences. Regardless, quantifying female movement in the field is more
important than male movement because females cause the direct damage to the fruit. Soy
trypsin was readily detectable on the leaves, but not on flies exposed to those leaves.
Specifically, the retention of soy trypsin on flies sharply declined after only 1 day.
Similar findings have been reported by Jones et al. (2006). They suggested that the soy
trypsin on leaves might flake off or dry, thus making the protein less available to the
target insect.
Despite thorough coverage of egg albumin on leaf surfaces in April, May, and June, it
appears that flies did not acquire the egg albumin mark as well in the wettest (April) and
driest (June) months of the study. Specifically, mark acquisition declined after 3 d in
short exposure (1 and 10 min) and 7 d in longer exposure (60 min) treatments (except for
a spike on day 10 in April); whereas in May, egg albumin mark acquisition only slightly
declined after 10 d, regardless of the exposure time treatment. ELISA OD readings
yielded by the flies exposed to egg albumin marked leaf tissue were similar for each
exposure time treatment. Further research is needed to determine whether continuous
light rain that occurred in May improved the acquisition of egg albumin from the plant
tissue to the flies and to determine the effect of other weather conditions (i.e., heavy rain,
dry periods) on fly marking.
25
Overall, the leaves treated with milk casein in June yielded poor ELISA results, but
those flies exposed to the leaves yielded strong positive results (except flies exposed to
day 1 leaves). This seems counterintuitive, as one might expect day 1 to have the highest
percent flies marked. Instead, none of the flies were marked, suggesting that a protein
PDUNLQWHUIHUHQFHZLWKWKH(/,6$LHWKHVDPSOHVPD\KDYHKDGµWRRPXFK¶PLONFDVHLQ
on them) might have occurred (Hagler et al., 2011). If so, this phenomenon, known as
µVWHULFLQKLELWLRQ¶&URZWKHUGRHVQRWDOORZWKHWDUJHW-specific antibody to bind to
the antigen (protein), because the overcrowding of marker molecules interferes with
DQWLERG\DWWDFKPHQW7KHUHIRUHLWLVSRVVLEOHWKDWDPRUHµRSWLPDO¶DPRXQWRIPLONFDVHLQ
was present on the leaves in June (compared to April and May) and improved as the
protein degraded over time. This increasing trend in milk casein acquisition over time has
been shown in previous research (Hagler & Jones, 2010; Irvin et al., 2012). For instance,
milk casein-marked Gonatocerus ashmeadi Girault increased 12% from day 1 to day 11
(Irvin et al., 2012). None of these papers specifically address this increasing trend in
percent marked, perhaps this was due to the fact that it was a more subtle trend than that
REVHUYHGLQRXUVWXG\)XUWKHUUHVHDUFKLVQHHGHGWRGHWHUPLQHWKHµRSWLPDO¶DPRXQWRI
milk casein needed for effective acquisition. Milk casein may still be appropriate for
large-scale field studies because applications will likely result in variable coverage (with
VRPHµRSWLPDO¶SURWHLQDPRXQWRQOHDYHVIRUVXFcessful acquisition by flies (J.R. Hagler,
unpublished).
Many factors potentially influence the retention of proteins in field settings. For
instance, abiotic factors such as rain, temperature, relative humidity, and dew point might
influence protein retention on surfaces and protein acquisition by insects in the field.
Jones et al. (2006) simulated rain events by washing treated leaf surfaces for various
amounts of time. They found that milk casein had a greater rain-fastness than egg
albumin or soy trypsin. However, a 1.5-mm rainfall event 12 d after application, in that
same study, caused an increased immunoresponse to egg albumin and a decreased
response to milk casein and soy trypsin to protein-treated leaf samples. Boina et al.
(2009) showed that simulated rainfall to field-marked leaves decreased egg albumin, milk
casein, and soy trypsin detection. Similarly, all proteins on field-aged leaves decreased in
26
activity due to three rainfall events. Contrary to these previous studies, our data
suggest that a 2-wk mean of 4 (0±21.5) and 2 (0±8.2) mm rainfall per day in April and
May, respectively, did not reduce protein detection on leaves. Furthermore, milk casein
detection on leaves was poorest during the driest month, June (mean rainfall of 0.2 mm
per day, ranging from 0 to 2 mm). The effect of temperature on proteins has also been
investigated. Boina et al. (2009) showed that there was no significant difference in
protein acquisition to insects exposed to treated leaves (residual acquisition) when held in
25 or 35 °C growth chambers. They concluded that temperature did not have an effect on
protein retention. Our study shows that perhaps a combination of factors (e.g., rainfall,
temperature) may influence protein detection. For example, the highest number of flies
retained their mark with egg albumin after exposure to field-aged leaves during May (i.e.,
light steady rain and a mean temperature of 11 °C) compared to April (i.e., occasional
heavy rain and cool weather) and June (i.e., dry and warm weather). Biotic factors related
to insects and plants may also influence protein acquisition and retention. These factors
include insect body size, body type (e.g., hairy, smooth, scaly), and behavior (e.g.,
feeding, grooming). Hagler & Jones (2010) showed that Hippodamia convergens GuérinMéneville and Lygus hesperus Knight obtained an egg albumin mark after only 5 min of
contact exposure to protein-treated cotton leaf tissue; however, acquisition of the protein
by Trichoplusia ni (Hübner) took between 20 and 240 min. Various additives
incorporated into protein solutions may also influence protein detection; however, their
effects remain uncertain (Jones et al., 2006; Williams et al., 2013). The water softener,
EDTA, when added to protein solutions resulted in a positive effect (Jones et al., 2006) or
no effect (Boina et al., 2009). These differences may have been influenced by abiotic
(e.g., UV light, RH) and/or biotic (e.g., phenotypic traits of plants and insects) factors
that contribute to the dissipation of protein-marked leaf surfaces and residually marked
flies. For example, protein persistence on pubescent (apple leaves used in Jones et al.,
2006) vs. glossy (citrus leaves used in Boina et al., 2009) leaf surfaces has not been
tested. The biological solvent, dimethyl sulfoxide, when added to the protein solutions
enhanced rabbit and chicken IgG protein retention for marking a beetle and its predator,
but may have had a deterrent effect on beetles (Williams et al., 2013). Future studies are
27
needed to test the effect of these factors on protein mark persistence and insect
behavior in the environment.
We hypothesized that longer exposure time would improve protein mark acquisition
by flies exposed to protein marked leaves. Increasing the exposure time of D. suzukii to
treated leaf surfaces appeared to improve protein mark acquisition. We tested 1, 10, and
60-min exposure periods of insects to marked leaf tissue to mimic short, medium, and
long field exposure situations. However, at present, it is unknown how much time D.
suzukii VSHQGVLQILHOGPDUJLQVFRQWDLQLQJµ+LPDOD\D¶EODFNEHUU\$QRWKHUGLIIHUHQFH
between these laboratory/semi-field studies and field-scale studies is the application
method. Herein we used a hand-held sprayer, whereas conventional spray equipment
(e.g., airblast, boom, backpack, aerial spray) has been used to apply these proteins in the
field (Krugner et al., 2012; Sivakoff et al., 2012; Swezey et al., 2013). Coverage will
likely depend on the method of application.
In conclusion, the egg albumin protein appears to be the most effective mark for
tagging D. suzukii. It was well retained on flies and leaves and is rapidly and readily
acquired by flies exposed to protein-marked plant tissue. Rainfall did not appear to
adversely affect egg albumin retention on the leaves; however, a steady amount of rain
throughout the trial appeared to improve the acquisition of the protein by residual contact
with protein-treated plants. Based on the results from this study, we have selected the egg
albumin mark to tag the resident D. suzukii population for future mark-capture field
studies.
Acknowledgments
We are grateful for the technical support of Amelia Thornhill, Scott Shane, Bev Thomas,
Kelly Donahue, Adam Cave, Amanda Lake, and Scott Machtley. Thanks to Dr. Walter
Mahaffee for sharing weather data. We also would like to acknowledge Bruce Mackey
and Danielle Lightle for assistance with statistical analysis. We appreciate manuscript
reviews by Vaughn Walton and Amy Dreves. Thanks to Vaughn Walton for travel funds
to Arizona and California for laboratory procedure training and a visual design workshop,
respectively. Funding was provided by Oregon State University Agricultural Research
Foundation, USDA SCRI Grant 2010-51181-21167, and USDA CRIS 5358-22000-032-
28
00D. Mention of proprietary or brand names are necessary to report factually on
available data; however, the USDA neither guarantees nor warrants the standard of the
product, and the use of the name by USDA implies no approval to the exclusion of others
that also may be suitable. This article is in the public domain and not copyrightable. It
may be freely reprinted with customary crediting of source.
29
Table 2.1 Mean (± SE) precipitation, air temperature, relative humidity, and leaf
wetness during 2-wk experiments performed in April, May, and June collected from
iMetos Ag weather station within 4 km from the trial site.
Month
April
May
June
Precipitation
(mm)
4 ± 1.5
2 ± 0.7
0 ± 0.1
Temperature (°C)
Mean
Min
8 ± 0.3
2 ± 0.7
11 ± 0.3 6 ± 0.7
17 ± 0.4 10 ± 0.6
RH (%)
Max
13 ± 0.6
16 ± 0.7
24 ± 0.8
76 ± 2.1
76 ± 1.6
71 ± 1.4
Leaf wetness
(min)
212 ± 68.1
121 ± 37.8
114 ± 45.1
Leaf wetness is the mean period when top and bottom leaf surfaces were wet
30
0.3
OD F
% egg F
b
c
OD M
% egg M
d
0.2
e
0.1
3
0.4
Mean optical density (OD)
40
0
1
7
Days after mark applied
10
14
100
OD F
% milk F
0.3
OD M
% milk M
80
60
0.2
40
0.1
bc ab
dc dc
1
3
a
de
de
e
de de
0
C!
20
0
0.4
Mean optical density (OD)
60
20
0
B!
80
7
Days after mark applied
10
14
100
OD F
% soy F
0.3
OD M
% soy M
80
60
0.2
% D. suzukii marked
100
a
% D. suzukii marked
0.4
a
40
b
0.1
c
d
7
Days after mark applied
10
c
20
0
% D. suzukii marked
Mean optical density (OD)
A!
0
1
3
14
Figure 2.1 Effect of the number of days on mean (+ SE) ELISA optical density (OD)
readings and % laboratory-marked Drosophila suzukii adult males (M) and females (F)
treated topically with (A) egg albumin, (B) milk casein, and (C) soy trypsin proteins. Fly
samples were scored positive for the presence of the protein mark if the OD reading was
three standard deviations greater than the mean negative control result. Mean ODs within
a panel (and in panel B within sex) capped with different letters are significantly different
(LSMeans comparisons of transformed data: P-value<0.05). LSMeans estimates of soy
trypsin-treated D. suzukii (C) were 2.50, 2.69, 2.78, 2.92, 2.82 for 1, 3, 7, 10, 14 d after
treatment, respectively.
31
Figure 2.2 Effect of the number of days on mean (+ SE) ELISA optical density (OD)
readings and % marked cultivated blackberry leaves treated in field in (A±C) April, (D±
F) May, and (G±I) June with (A, D, G) egg albumin, (B, E, H) milk casein, and (C, F, I)
soy trypsin protein. Leaf samples were scored positive for the presence of the protein
mark if the OD reading was three standard deviations greater than the mean negative
control result. Mean ODs within a panel capped with different letters are significantly
different (LSMeans comparisons of transformed data: P-value<0.05).
32
b
1
60
40
0.5
20
0
0
1
3
7
10 14
Days OD
after application
% egg
ab
a
b
1
ab
ab
80
60
40
0.5
20
0
0
1
G
3
7
10 14
% egg
Days OD
after application
1.5
1
80
a
a
a
ab
b
0.5
1.5
a
b
ab
ab
1
80
60
40
0.5
20
0
0
1
3
7
10 14
Days after application
60
40
0
20
1
E
3
7
10 14
OD
% milk
Days after application
%%
soy
marked with soy
100
1.5
1
80
a
60
a
b
b
0.5
b
1.5
1
80
a
ab
bc
0.5
60
ab
c
0
40
20
1
H
3
7
10 14
% milk
Days OD
after application
0
0
1
F
3
7
10 14
OD
% soy
Days after application
100
1.5
1
80
a
ab
60
ab
c
0.5
bc
0
0
1
I
80
1
0.5
60
a
0
1
ab
b
bc
40
c
3
7
10 14
Days after application
20
40
20
3
7
10 14
OD application
% soy
Days after
100
100
1.5
40
20
100
100
ab
OD
100
100
1.5
C
% leaves marked with soy
a
%%
milk
marked with milk
1.5
80
1
60
a
0.5
40
b
b
bc
c
0
20
0
1
3
7
10 14
Days after application
% leaves marked with soy
a
OD
Mean leaf optical density (OD)
% leaves marked with milk
a
B
Mean leaf optical density (OD) Mean leaf optical density (OD)
% leaves marked with milk
% leaves marked with milk
80
a
Mean
optical
density
%leaf
leaves
marked
with(OD)
egg
1.5
D
JUNE
MAY
Mean leaf optical density (OD) Mean leaf optical density (OD)
marked with egg
%%
egg
100
OD
Mean
optical
density
leaf optical
density
% leaf
leaves
marked
with(OD)
egg Mean
% leaves
marked
with (OD)
egg
APRIL
Mean leaf optical density (OD)
A
% leaves marked with soy
Figure 2.2
33
Figure 2.3 Effect of the number of days on mean (+ SE) ELISA optical density (OD)
readings and % marked adult male (M) and female (F) Drosophila suzukii exposed to egg
albumin protein-treated cultivated blackberry leaves for (A, D, G) 1 min, (B, E, H) 10
min, and (C, F, I) 60 min in (A±C) April, (D±F) May, and (G±I) June. Fly samples were
scored positive for the presence of the protein mark if the ELISA OD reading was three
standard deviations greater than the mean negative control result. Mean ODs within a
month (i.e., group of three panels) capped with different letters are significantly different
(LSMeans comparisons of transformed data: P-value<0.05).
34
Figure 2.3
0.4
Mean OD
% marked
MAY
Mean optical density (OD)
% marked
Mean OD
D
hi
i
1 Days
3 after7application
10
14
OD F
% egg F
0
0
E
0.4
600.3
bc
bc
0.2
de
de
de
0.1
0
OD F
% egg F
a
0.4
d
0.2
e
0.1
fg
g
10
14
0
OD F
% egg F
3
7
H
Days after application
0.2
0
d
cd
ef
0
OD M
% egg M
F
100
0.6
80 0.5
a
ab
20 0.1
1
40
ghi
Days
3 after
7 application
10
14
OD F
% egg F
b
40
de
e
e
a
0
1 Days3 after 7application
10
14
80
OD F
% egg F
OD M
% egg M
80 0.5
0.4
60
0.3
40
0.2
20 0.1
bc
ef
efg
0
0
1
3
7
10
Days after application
14
cd
40
de
de
0
80 0.5
0.4
60
0.3
40
0.2
20 0.1
cd
b
0.1
1000.6
cd
60
0.3
I
0
100
0.2
20
20
OD M
% egg M
60 0.4
1000.6
0
1
hi
0
OD M
% egg M
0.6
0.3
ghi
1 Days
3 after7application
10
14
400.2
1 Days3 after 7application
10
14
0.5
fgh
200.1
0
G
40
bc
0.6
100
0.5
800.4
0.5
60
0.3
200.1
OD M
% egg M
0.6
0.3
60
cd
% marked
Mean OD
0.1
0
JUNE
Mean optical density (OD)
de
Mean OD
% marked
0.2
efg
100
80
0.4
20
0
1 Days3 after 7application
10
14
OD F
% egg F
OD M
% egg M
100
80
ab
% marked
Mean OD
a
0.3
OD M
% egg M
% D. suzukii marked
80 0.5
OD F
% egg F
% D. suzukii marked
800.5
0.4
60
0.3
40
0.2
60 min
C
OD M
% egg M
1000.6
OD F
% egg F
0.5
Mean OD
% marked
APRIL
Mean optical density (OD)
0.6
10 min
B
OD M
% egg100
M0.6
OD F
% egg F
cd
60
d
40
ef
ef
0
20
0
1
3
7
10
Days after application
14
% D. suzukii marked
1 min
A
35
Figure 2.4 Effect of the number of days on mean (+ SE) ELISA optical density (OD)
readings and % marked adult male (M) and female (F) Drosophila suzukii exposed to
milk casein protein-treated cultivated blackberry leaves for (A, D, G) 1 min, (B, E, H) 10
min, and (C, F, I) 60 min in (A±C) April, (D±F) May, and (G±I) June. Fly samples were
scored positive for the presence of the protein mark if the ELISA OD reading was three
standard deviations greater than the mean negative control result. Mean ODs within a
month (i.e., group of three panels) capped with different letters are significantly different
(LSMeans comparisons of transformed data: P-value<0.05).
36
Figure 2.4
20
0.1
0.6
0 0
E
14
OD M
100
% milk M0.6
0.5
0.2
0.4
60
0.3
40
0.2
0.1
20
0.1
0.3
1
3
7
10
OD F
% milk F
0.6
0.5
14
H
OD M
% milk 100
M
0.6
80
0.5
0.4
0
0
F
3 after7application
10
14
Days
OD F
OD M
% milk F
% milk M1000.6
80
h
h
cd
bc
de
0
3
7
10
Days after application
14
3 after7application
10
14
Days
OD F
OD M
% milk F
% milk M
0.5
100
80
60
20 0.1
20
60
0.3
40
0
1
3 after7application
10
Days
OD F
% milk F
14
OD M
% milk M
40
0.2
0
I
0
1
3 after7application
10
Days
OD F
% milk F
1000.6
14
OD M
% milk M
80 0.5
0.4
60
0.3
40
0.2
h
g
a
ab
f
0 0
1
0
1
20 0.1
0
1
3
7
10
Days after application
14
100
80
Mean OD
0.2
0.3
40
0.2
20
0.1
20
0.4
0.4
60
0.3
0.1
1
0 0
0
40
0.2
20 0.1
0.5
80
0.4
G
JUNE
Mean optical density (OD)
3 after7application
10
Days
OD F
% milk F
40
% marked
MAY
Mean optical density (OD)
1
Mean OD
0
D
60
0.3
% D. suzukii marked
0.1
0.4
% D. suzukii marked
0.2
0.3
60
80
60
40
h
ef
f
cd
ef
0
20
0
1
3
7
10
Days after application
14
% D. suzukii marked
0.4
60
0.3
40
0.2
OD M
% milk M 100
Mean
OD
%
marked
0.4
OD F
% milk F
80 0.5
Mean OD
0.5
80
Mean OD
% marked
0.5
60 min
C
OD M
% milk M 1000.6
OD F
% milk F
Mean OD
% marked
APRIL
Mean optical density (OD)
0.6
10 min
B
OD M
% milk 100
M0.6
OD F
% milk F
% marked
1 min
A
37
Figure 2.5 Effect of the number of days on mean (+ SE) ELISA optical density (OD)
readings and % marked adult male (M) and female (F) Drosophila suzukii exposed to soy
trypsin protein-treated cultivated blackberry leaves for (A±G) 1 min, (B±H) 10 min, and
(C±I) 60 min in (A±C) April, (D±F) May, and (G±I) June. Fly samples were scored
positive for the presence of the protein mark if the ELISA OD reading was three standard
deviations greater than the mean negative control result. Mean ODs within a month (i.e.,
group of three panels) capped with different letters are significantly different (LSMeans
comparisons of transformed data: P-value<0.05).
38
Figure 2.5
OD M
% soy
M
100
0.6
0.4
0.4
60
0.3
40
0.2
20
0.1
0.3
0.2
0.1
gh
0.6
defg
defg
0.5
80
0.4
60
0.3
40
0.2
Mean OD
JUNE
80
0.4
0.3
0.2
abc
cd
cde
cde
bcd
0
20
0.1
60
3
7
10
Days after application
14
100
80
0.4
60
0.3
40
ab
fgh
de
efg
efg
40
0.2
20 0.1
bc
def
cd
h
defg
60
20
0
1 Days
3 after 7application
10
14
OD F
OD M
% soy F
% soy M
80 0.5
100
80
0.4
60
0.3
40
abc
cd
bc
cd
de
0 0
1
0
1 Days
3 after 7application
10
14
OD F
OD M
% soy F
% soy M
0.5
0
0 0
0
3 after 7application
10
14
1 Days
3 after 7application
10
14
I
H 1 Days
OD F
OD M
OD F
OD M
0.6
100
% soy F
% soy
M0.6
% soy F
% soy100
M
0.5
0.1
20
0.1
20
20 0.1
Mean OD
% marked
0
fg
40
0.2
Mean OD
% marked
Mean OD
a
0.1
G
40
0.4
60
0.3
40
0.2
0.3
60
0.3
0.5
80
0.4
100
80
0.4
0 0
0
0
1 Days
3 after 7application
10
14
3 after 7application
10
14
F
E 1 Days
OD F
OD M
OD F
OD M
% soy F
% soy100
M
% soy F
% soy
M0.6
0.6
100
0.5
0.2
60
% marked
MAY
Mean optical density (OD)
0.6
OD M
% soy M
80 0.5
% marked
0
D
OD F
% soy F
OD M
% soy
M0.6
100
Mean OD
% marked
0.5
80
OD F
% soy F
60 min
C
% marked
0.5
Mean OD
APRIL
0.6
10 min
B
OD F
% soy F
20 0.1
0
1
3
7
10
Days after application
14
40
0.2
a
cde
ab
e
e
20
0
0
1
3
7
10
Days after application
14
% D. suzukii marked
1 min
A
39
CHAPTER 3
Distribution and activity of Drosophila suzukii in cultivated raspberry and
surrounding vegetation
Jimmy Klick, Wei Q. Yang, Vaughn M. Walton, Daniel T. Dalton, James R. Hagler,
Amy J. Dreves, Jana C. Lee, Denny J. Bruck
Journal of Applied Entomology
John Wiley & Sons Inc.
350 Main Street
Malden, MA 02148
USA
Manuscript accepted and currently in revision
40
Abstract
Spotted wing drosophila, Drosophila suzukii Matsumura (Diptera: Drosophilidae),
UHDGLO\XWLOL]HVZLOGµ+LPDOD\D¶EODFNEHUU\+%Rubus armeniacus Focke, as a refuge,
among other non-crop plants, and possibly exploits adjacent field margins before
colonizing cultivated fruiting crops. Studies were conducted to determine the role of field
margins containing HB and their effect on D. suzukii activity, density, and distribution in
an adjacent commercial red raspberry crop. One-ha plots adjacent to field margins
containing HB or non-hosts (NH) (winter wheat in 2011; tall fescue in 2012) were
established and replicated three times. Each plot contained two transects with monitoring
traps for D. suzukii in the field margin (0 m) and spaced approximately 10 (crop
boundary), 40, 70 and 100 m into the adjacent crop (n=10 traps/plot). Field margin
vegetation was treated weekly from pre-harvest until the end of harvest with a 10%
chicken egg white mark solution using a cannon sprayer. Adult D. suzukii were collected
from traps weekly and analyzed for the presence of the egg white mark using an egg
white-specific enzyme-linked immunosorbent assay (ELISA). During both years,
significantly more marked flies were collected in HB field margins and virtually no
marked flies were found where adjacent vegetation contained no known alternate host.
Spatial Analysis by Distance IndicEs (SADIE) and mean D. suzukii trap captures
additionally displayed elevated fly densities in the raspberry field near HB. These results
indicate that HB may contribute to elevated D. suzukii populations and pest pressure in
comparison to field margins containing no known alternate D. suzukii host vegetation.
Other non-crop plants may also contribute towards a favorable field margin for D. suzukii
and this work indicates the importance of surrounding vegetation when considering pest
management options.
Keywords: Spotted wing drosophila, Rubus armeniacus, immunomarking, insect
dispersal, non-crop host, spatial statistics, Drosophilidae
Introduction
Drosophila suzukii Matsumura (Diptera: Drosophilidae) is a pest of small and stone fruits
in all major production regions throughout North America and Europe (Walsh et al.,
2011; Cini et al., 2012). Biological attributes that favored its population growth and
41
widespread establishment include: mobility (Mitsui et al., 2010), high reproductive
capacity (Tochen et al., 2014b), a lack of natural enemies (Cini et al., 2012; Chabert et
al., 2012), and an ability to utilize a wide range of ripe and intact fruit (Walsh et al.,
2011; Burrack et al., 2013), including non-crop hosts (Atallah et al., 2014; Lee et al.,
2014). The globalization of fruit markets and recent expansion of susceptible fruit
production likely resulted in the rapid spread and contributed to the rise in economic
importance of D. suzukii (Bolda et al., 2010; Goodhue et al., 2011; Cini et al., 2012). In
2009, up to 80% annual crop loss ($421.5 million) of cherry, blueberry, caneberry, and
strawberry was estimated in the absence of control as worst-case scenario in western US
production regions (Bolda et al., 2010).
Host plants adjacent to cultivated commercial crops may exacerbate the economic
impact of pests (Lafleur & Hill, 1987; Boina et al., 2009; Basoalto et al., 2010). Nearby
µ+LPDOD\D¶EODFNEHUU\+%Rubus armeniacus Focke (formerly R. discolor and R.
procerus) and seedling cherry, Prunus spp., habitats (Poyet et al., 2014), may be a
possible refuge and source of D. suzukii invasion when residual toxicity of field applied
insecticides decreases (Schneider, 1989; Longley et al., 1997; Bruck et al., 2011).
Movement of D. suzukii from field margins to commercial crops is, however, largely
unknown. Major cultivated D. suzukii host crops tested in a laboratory include, in order
of host potential rating: raspberry, strawberry, blackberry, cherry, peach, blueberry, and
grape (Bellamy et al., 2013). Wild hosts in the same genera include R. armeniacus, HB
(Caplan & Yeakley, 2006; Fierke & Kauffman, 2006), Prunus avium Linnaeus (sweet
cherry) and P. cerasus Linnaeus (sour cherry) (Thilenius 1968; Poyet et al., 2014), all of
which can be found in unmanaged field margins of the Pacific Northwest and could serve
as refuge and overwintering site.
Drosophila species are highly mobile and opportunistic in order to optimize seasonal
survival (Taylor et al., 1984; Coyne & Milstead, 1987; Bell, 1990; Iliadi et al., 2002).
Provided unfavorable conditions, D. pseudoobscura (Frolova and Astaurov) can disperse
from a few meters to several kilometers per day to exploit more favorable conditions
(Iliadi et al., 2002). Drosophila suzukii is known to have high dispersal capabilities,
which may have contributed to its rapid spread to virtually all suitable production regions
42
in North America and Europe within a relatively short period (Hauser, 2011). When
resources decline or population densities exceed optimal levels, D. suzukii are believed to
migrate to more favorable habitats (Mitsui et al., 2010). Given these potential dispersal
capabilities and the close proximity of wild hosts preferentially utilized by D. suzukii to
commercially cultivated hosts suggest that the impact of adjacent crop surroundings on
D. suzukii crop invasion needs to be determined (Becher et al., 2010).
A better understanding of seasonal activity and distribution of D. suzukii between
non-crop areas and proximate crops will aid to formulate future integrated pest
management strategies (Lee et al., 2011a; Cini et al., 2012). Various protein mark-capture
methods have been used to study insect movement (Jones et al., 2006; Boina et al., 2009;
Horton et al., 2009; Basoalto et al., 2010; Krugner et al., 2012; Swezey et al., 2013, 2014;
Lessio et al., 2014). In mark-capture studies, as opposed to mark-release-recapture
studies, resident populations self-mark. This technique provides several advantages for D.
suzukii within a crop. Protein mark-capture techniques are inexpensive, easily applied,
environmentally benign, persistent, and clearly identifiable (Jones et al., 2006; Hagler &
Jones, 2010; Hagler et al., 2011; Sivakoff et al., 2012; Klick et al., 2014b).
The overall goal of this work was to conduct mark-capture studies to determine the
activity levels of D. suzukii within non-crop host field margins and cultivated raspberry
crop fields. Our specific objectives were to determine: 1) if D. suzukii utilize HBcontaining field margins as a refuge, 2) if crops adjacent to HB-containing field margins
have higher population densities compared to crops near non-host (NH) field margins, 3)
the role of the field margins on D. suzukii activity in comparison with cultivated
raspberries, and 4) the distribution pattern of D. suzukii in cultivated raspberries adjacent
to field margins containing HB in comparison to NH field margins.
Materials and methods
Study site and design. A 33.4-ha cultivated red raspberry (R. idaeus Linnaeus) study site
with field margins containing either HB or NH was located near Jefferson, Oregon
ƒ¶´1ƒ¶´:7KH1+DUHDLQZDVSODQWHGZLWKDVRIW-white winter
wheat (Triticum aestivum /LQQDHXVµ0DGVHQ¶PRQRFXOWXUHDQGWKHVDPH1+DUHDLQ
2012 was planted with tall fescue (Lolium arundinaceum Darbyshire ex. Schreb.) for turf
43
seed production. The commercial raspberry crop was grown using conventional
management practices. One-ha plots were systematically selected near the two field
margin classifications and replicated three times. Each plot contained two transects with
D. suzukii traps in the field margin (0 m) and spaced approximately 10 (crop boundary),
40, 70 and 100 m into the adjacent crop (n=10 traps/plot). The plots with HB in the field
margin were spaced 70±180 m from each other. The plots with NH in the field margin
were spaced approximately 50 m from each other. The two plot types (HB vs. NH in field
margin) were spaced 350±500 m from each other. Monitoring traps for D. suzukii were a
modified clear 10-hole trap (Lee et al., 2012) made of a bottomless 946-ml clear plastic
deli container (DM32R, Solo Cup Company, Lake Forest, IL) with ten 3.5-mm holes near
the top, and nested over a plastic cup (D32, Solo, Urbana, IL) containing ~150 ml apple
cider vinegar (ACV) (5% acidity, Fred Meyer Apple Cider Vinegar, Kroger Co.,
Cincinnati, OH) (Figure 3.1). A 6.5 × 9 cm double-sided yellow sticky card (ASTO103,
Alpha Scents Inc., West Linn, Oregon) was placed on top of the mesh that was positioned
between the two cups. This trapping method attracted flies into the cup with bait and onto
yellow sticky cards, while preventing flies from drowning and potentially washing off the
protein mark. The trap in Figure 3.1, mounted on a trestle pole and shielded from
machine harvesters by two pieces of plywood, is located at the edge of the red raspberry
field approximately 10 m from the field margin containing HB (seen in the background).
Insect marking. The field margins were treated weekly with 10% liquid chicken egg
white (All Whites; Papetti Foods, Elizabeth, NJ) (Klick et al., 2014b) using a cannon
sprayer (AJ-401, Jacto Inc., Pompea, Brazil) at 282 L ha-1 from pre-harvest (27 June 2011
and 14 June 2012) through harvest (12 August 2011 and 15 August 2012). The cannon
sprayer treated a field margin width of approximately 15 m. The monitoring traps were
removed from the field margins prior to protein application and returned to their
designated locations within 0.5 h after application in order to limit contamination. On
each insect collection date, sticky cards containing adult D. suzukii were removed from
the traps, covered with wax paper, and placed in a cooler. Traps were refreshed weekly at
each location by adding ACV and a clean sticky card. Collected sticky cards were
returned to the laboratory and frozen at -80 °C. Sticky cards were removed from the
44
freezer and each D. suzukii adult was carefully removed with a disposable toothpick
and individually placed into a 1.5-ml microcentrifuge tube along with the tip of the
toothpick to prevent cross-contamination. Trap location and number of D. suzukii
captured per trap were recorded. All fly samples were returned to -80 °C freezer until
adults were removed and analyzed for the presence of egg albumin by enzyme-linked
immunosorbent assay (ELISA).
Egg albumin ELISA. Fly samples were thawed and 1.0 ml of tris buffered saline (pH
7.4) was added to each sample. The samples were placed on an orbital shaker at 100 rpm
for ca. 1 h. After an hour, a 100 µl aliquot from each sample was added to an individual
well of a 96-well ELISA plate. All samples were then assayed by the egg albumin ELISA
described in detail by Hagler & Jones (2010). Drosophila suzukii samples were scored
positive for the presence of the mark using the positive ELISA reaction threshold criteria
defined by Sivakoff et al. (2011).
Data analysis. Data collected from the field margins and crop areas were divided into
two distinct time periods to address the changes in fly abundance and host plant
SKHQRORJ\µ(DUO\6XVFHSWLEOH¶DQGµ/DWH6XVFHSWLEOH¶6HDVRQDOSKHQRORJ\RIWKHFURS
and D. suzukii counts were considered when determining the two selected time periods.
7KHµ(DUO\6XVFHSWLEOH¶SHULRGZDVIURPWKHDSSHDUDQFHRIWKHILUVWULSHEHUU\WRMXVW
before the first substantial D. suzukii SRSXODWLRQLQFUHDVHZKLFKFRLQFLGHGZLWKWKHµILUVW
generation peak egg-OD\LQJ¶DVGHILQHGDQGYDOLGDWHGE\DGHJUHH-day model for D.
suzukii activity (Coop, 2014)7KHµ/DWH6XVFHSWLEOH¶SHULRGZDVGHILQHGIURPILUVW
generation peak egg-OD\LQJWRWKHHQGRIKDUYHVW,QWKHµ(DUO\6XVFHSWLEOH¶SHULRG
ZDV-XQHWR-XO\DQGµ/DWH6XVFHSWLEOH¶SHULRGZDV-XO\WR$XJXVW,Q
WKHµ(DUO\6XVFHSWLEOH¶SHULRGZDV-XQHWR-XO\DQGµ/DWH6XVFHSWLEOH¶SHULRGZDV
July to 15 August.
All statistical analyses were made in R v3.0.3 (R Core Team 2013) using RStudio
v0.97.306 (RStudio, 2012) with D = 0.05. All D. suzukii captured in the HB or NH field
margin and adjacent crop regardless of marked/unmarked status were averaged across
collecting dates and traps within each time period, log10 (x + 1)-transformed in the
instance that model assumptions were not met, and statistically compared using linear
45
mixed-effects model with field margin type as fixed effect and plot as random effect
(Crawley, 2013). Averages, instead of totals or repeated measures, were used to account
for variability in harvest period and differences in field management between plots.
0DUNHGIOLHVDUHSUHVHQWHGDVPDUNHGWRWDODVVD\HGDQGSHUFHQWDJHPDUNHGIOLHV7KHȤ2
goodness-of-fit test was used to determine the significant level of marked ratio, i.e. the
total marked flies between HB and NH in field margin or crop in 2011 and 2012.
Non-parametric spatial analysis was conducted in order to describe general spatial
trends. SADIE (Spatial Analysis with Distance IndicEs; Perry, 1995) was used to
determine the overall index of aggregation of D. suzukii total trap captures for each time
period. The index of aggregation, Ia, quantified aggregation patterns found in plots during
the Early Susceptible and Late Susceptible periods of each year. The observed counts
have spatially random arrangement when Ia is near to unity (i.e. between -1.5 and 1.5),
aggregated arrangement when values are larger than unity, and regular arrangement when
values are smaller than unity (Perry, 1996; Maestre & Cortina, 2002; De Villiers 2006).
Another index, v, is a dimensionless index of clustering. This index was used to measure
the degree of clustering in areas with above-average density i.e., patches (high counts
near each other) or areas with below-average density i.e., gaps (low counts near each
other) (Winder et al., 2001, 2012; Maestre & Cortina, 2002; De Villiers 2006). Values of
vi between -1.5 and 1.5 indicate randomness (Winder et al., 2001; Perry & Dixon, 2002;
De Villiers 2006). To test for non-randomness, the mean values of the clustering indices,
‫ݒ‬i and ‫ݒ‬j were used. Significant clustering in patches, random association, and gaps were
illustrated using Surfer® v12 (Golden Software, Inc., Golden, CO). Interpolation between
data points created by SADIE cluster analysis was calculated using the inverse distance
weighted method in order to illustrate spatial distribution patterns.
Results
Mean captured flies in the HB field margin were numerically higher than NH during
Early Susceptible 2011 (t = -1.00, d.f. = 2, P-value = 0.42), Late Susceptible 2011 (t = 1.39, d.f. = 2, P-value = 0.30), Early Susceptible 2012 (t = -1.00, d.f. = 2, P-value =
0.42), and Late Susceptible 2012 (t = -1.99, d.f. = 2, P-value = 0.19) (Figure 3.2A). Mean
captured flies in the crop near HB were numerically higher than near NH during Late
46
Susceptible 2011 (t = -1.31, d.f. = 2, P-value = 0.32) and Late Susceptible 2012 (t = 0.58, d.f. = 2, P-value = 0.62) and statistically higher in Early Susceptible 2012 (t = 22.52, d.f. = 2, P-value = 0.002), but not in Early Susceptible 2011 (t = 0.68, d.f. = 2, Pvalue = 0.68) (Figure 3.2B).
In 2011, field margins treated with egg protein resulted in 22 marked flies in HB and
zero in NH (Table 3.1). In the adjacent crop, five flies were marked near HB and four
near NH (Table 3.1). In 2012, field margins treated with egg resulted in 66 marked flies
in HB and one in NH. In the adjacent crop, 21 flies were marked near HB and 16 near
NH. Although there were numerically more marked flies in HB and the adjacent crop, the
PDUNHGUDWLRZDVRQO\VLJQLILFDQWLQWKHILHOGPDUJLQȤ2 = 22.00, d.f. = 1, PvalueȤ2 = 63.06, d.f. = 1, P-value<0.0001) but not in the adjacent crop
Ȥ2 = 0.11, d.f. = 1, P-value Ȥ2 = 0.68, d.f. = 1, P-value = 0.41).
Spatial analysis (Table 3.2, Figure 3.3) indicated significant D. suzukii aggregation
(Ia) and clustering in all time periods except Early Susceptible 2011. Contour maps
overlaid with locations of monitoring traps show patches in three HB regions in the south
and gaps near three NH regions in the north (Figure 3.3). In Late Susceptible 2012, a
small patch is visible near NH in the north.
Discussion
Understanding landscape complexity and pest activity are key elements of developing a
pest management strategy (Schneider, 1989; Holland & Fahrig, 2000; Carriere et al.,
2006; Blackshaw & Vernon, 2006). This study is the first to demonstrate that D. suzukii
utilize nearby habitat containing HB as a refuge and from there may migrate and colonize
within the crop. Several arthropods are known to seasonally colonize nearby non-crop
areas and cultivated crops (Duelli, 1990; Pedigo 2002) including Cydia pomonella
Linnaeus (Lepidoptera: Torticidae) (Basoalto et al., 2010), Sitobion avenae Fabricius
(Hemiptera: Aphididae) (Longley et al., 1997), Scaphoideus titanus Ball (Hemiptera:
Cicadellidae) (Lessio et al., 2014), and Diaphorina citri Kuwayama (Hemiptera:
Psyllidae) (Boina et al., 2009). Focusing on field margins, management tools proven for
other pests such as bait sprays (Vargas et al., 2001; Prokopy et al., 2003), mass trapping
(Cohen & Yuval, 2000), and non-crop host removal (i.e., ecological management) may
47
significantly reduce D. suzukii populations, especially if implemented in area-wide
programs. However, field margins may play an important ecological role by providing
food and habitat for pollinators and natural enemies (Holland & Fahrig, 2000; Marshall &
Moonen, 2002). Furthermore, field margins could provide a refuge to reduce D. suzukii
insecticide resistance development as it may house pesticide resistant alleles (Tabashnik
& Croft, 1985).
We demonstrated that elevated D. suzukii populations within the cultivated crops are
often associated with high activity levels in the field margin, which may contain HB and
possible other host plants. We propose three hypotheses as to why a similar number of
marked flies were caught in the crop near both field margin types: 1) the greater influx of
flies from HB field margins made it more difficult to detect marked flies, essentially
diluting the proportion of marked flies near HB, whereas marked flies near NH were not
so strongly affected by these influxes due to presence of fewer flies overall; 2) the total
adult fly population is most likely underestimated and marked flies from HB in the
southern plots moved toward NH in the northern plots. Drosophila obscura Pomini
(Diptera: Drosophiliade) and D. subobscura Collin dispersed up to 100 and 200 m per
day, respectively (Taylor et al., 1984). A preliminary mark-release-recapture study using
fluorescent dusts found that D. suzukii moved approximately 67±87 m in 36 h (J.C. Lee,
unpublished), and; 3) inefficient trap design, bait attraction, or placement inaccurately
assessed population density (Knight & Croft, 1987; Cha et al., 2014; Kleiber et al., 2014).
All NH plots and one HB plot had field margin traps exposed to full sun which seems to
be less preferred habitat for D. suzukii (Tochen et al., 2014a). These traps had low counts
throughout the two-year study, which may have been a reason for not detecting a
statistical difference between captures in HB and NH field margins.
Evaluating the impact of vegetation containing early ripening hosts of D. suzukii
populations adjacent to a commercial fruit crop needs further investigation. Prunus avium
(Thilenius 1968), which provides important resources to D. suzukii (Poyet et al., 2014),
was present in an HB field margin that had consistently high trap counts. The fruitripening period of P. avium around the end of June to early July can provide an early
ovipositional habitat for D. suzukii. Peak egg-laying by first generation females predicted
48
by degree-day model in mid July (Coop, 2014) coincided with the presence of
susceptible cherry fruit and designates a key shift from low to high populations. By the
time HB ripens in the Pacific Northwest of the USA, the raspberry crop is near the end of
harvest (typically early August). In 2012, the crop adjacent to the field margin containing
P. avium and HB had substantial dieback, which reduced fruit and canopy load (i.e.,
unfavorable canopy architecture) and likely reduced humidity. Early Susceptible 2012
flies may have traveled further in search of the ideal crop area (Coyne & Milstead, 1987;
Iliadi et al., 2002). This could explain why a similar number of marked flies were found
near HB and NH field margins (i.e., flies from HB flew further to the crop near NH).
Spraying the NH field margin with a different protein marker, such as milk, may have
explained the importance of this factor more clearly; however, the logistics of the project
and uncertainties of the milk marker made this an unfeasible option (Klick et al., 2014b).
In summary, mark-capture using egg white protein has documented the movement of
self-marked resident D. suzukii from field margins into the adjacent cultivated crop. Field
margins containing possible host plants as highlighted may have contributed to D. suzukii
population buildup and resultant emigration to the cultivated crop. These conclusions
were reached based on statistically and numerically higher marked D. suzukii trap counts
in field margins containing HB. Higher levels of D. suzukii activity were found in crop
areas, illustrated by significant patching in close proximity to HB. Finally, our marking
data indicated movement of D. suzukii into the crop.
These findings illustrate the potential risks associated with surrounding vegetation on
pest pressure exerted by D. suzukii to crops. Limited information is available on the
relative importance of differing landscape types adjacent to cultivated crops, host plant
usage, and the impact of distance of non-crop hosts on pest pressure from D. suzukii into
the crop. Overall, the activity of D. suzukii in non-crop host areas may be dependent on
plant architecture, age, competition, multiple hosts, water source, and seasonal fruit
selection. A landscape with a combination of diverse and abundant overstory and
understory plants that provide D. suzukii with a spring-fall food source, overwintering
refuge, and satisfactory environmental conditions could increase potential risks by D.
suzukii. The benefits of surrounding vegetation, such as D. suzukii resistance
49
management, potential as D. suzukii trap crop, alternate resources for pollinators, and
possible enhancement of biological control need to be determined before management
strategies can be recommended.
Acknowledgements
We acknowledge Adam Cave, Kelly Donahue, Joe Kleiber, Amanda Lake, Scott
Machtley, Scott Shane, Bev Thomas, and Amelia Thornhill for their diligent technical
support and the cooperating raspberry grower for his collaboration and patience during
the busy field season. Thanks to Oregon State University Statistics Student Consulting
Service and Laura Sims for statistical assistance. Funding was provided by Oregon State
University Agricultural Research Foundation, USDA SCRI Grant 2010-51181-21167 and
USDA CRIS 5358-22000-032-00D. Mention of proprietary or brand names are necessary
to report factually on available data; however, the USDA neither guarantees nor warrants
the standard of the product, and the use of the name by USDA implies no approval to the
exclusion of others that also may be suitable. This article is in the public domain and not
copyrightable. It may be freely reprinted with customary crediting of source.
50
Table 3.1 Number of protein-marked (nm), assayed (na), the percentage (%) of marked
D. suzukii, and yearly marked ratio (i.e. the total marked flies between HB and NH in
ILHOGPDUJLQRUFURSLQDQGLQµ+LPDOD\D¶EODFNEHUU\+%DQGQRQ-host
(NH) field margins (area treated with egg marker) and in the crop near HB and NH field
margins during Early Susceptible (ES) and Late Susceptible (LS) in 2011/2012.
ES 2011
Location
nm/na
%
Field margin: HB
2/16
12.5
Field margin: NH
0
0
Marked ratiob by year
nm/na
%
20/134 14.9
0
0
22:0 (P-value<0.0001)a
ES 2012
nm/na
%
3/53
5.7
0/1
0
LS 2012
nm/na
%
63/312 20.2
1/7
14.3
66:1 (P-value<0.0001)
Crop: near HB
0/9
0
5/53
9.4
1/29
3.5
20/283
7.1
Crop: near NH
2/9
22.2
2/21
9.5
1/14
7.1
15/254
5.9
Marked ratio by year
a
LS 2011
5:4 (P-value = 0.74)
21:16 (P-value = 0.41)
P-YDOXHVEDVHGRQȤ2 goodness-of-fit test (d.f. = 1)
b
Ratio of total marked flies between HB and NH in field margin or crop in 2011 and
2012
51
Table 3.2 SADIE (Spatial Analysis with Distance IndicEs) summary statistics of Early
Susceptible (ES) and Late Susceptible (LS) in 2011/2012. Ia = index of aggregation; ‫ݒ‬j =
mean index of gap clustering; ‫ݒ‬i = mean index of patch clustering; P = probabilities
associated with indices.
Time
Iaa
Pba
‫ ݒ‬jc
Pj
‫ ݒ‬id
Pi
ES 2011
1.118
0.325
-1.057
0.327
1.142
0.259
LS 2011
3.141
<0.001
-3.988
<0.001
2.928
0.003
ES 2012
2.216
0.008
-2.114
0.018
2.174
0.015
LS 2012
1.866
0.034
-1.866
0.042
1.504
0.021
a
Spatially random arrangement when the index of aggregation (Ia) is near to unity (i.e.
between -1.5 and 1.5), aggregated arrangement when values are larger than unity, and
regular arrangement when values are smaller than unity
b
Probabilities associated with indices
c
Mean index of gap clustering (i.e., clustering gap, vj<-1.5, or a low density of counts
near each other)
d
Mean index of patch clustering (i.e., clustering patch, vi>1.5, or high density of counts
near each other)
52
Figure 3.1 Monitoring traps for D. suzukii WUDSFDSWXUHVZHUHDPRGLILHGµFOHDU¶WUDS(Lee
et al., 2012) made of a bottomless 946 ml clear plastic deli container (DM32R, Solo Cup
Company, Lake Forest, IL) with ten 3.5-mm holes near the top, and nested over a plastic
cup (D32, Solo, Urbana, IL) containing ~100 ml apple cider vinegar (ACV) (5% acidity,
Fred Meyer Apple Cider Vinegar, Kroger Co., Cincinnati, OH). A 6.5 × 9 cm doublesided yellow sticky card (ASTO103, Alpha Scents Inc., West Linn, Oregon) was placed
on top of the mesh that was positioned between the two cups.
53
Figure 3.2 Mean D. suzukii (+SE) captured per plot (n=3) in Early Susceptible (ES) and
Late Susceptible (LS) 2011 and 2012 in (A) HB (Himalaya blackberry) and NH (nonhost) field margins and (B) crop by HB and NH. Significant differences are denoted with
DQDVWHULVNĮ above the bars.
54
Figure 3.3 SADIE (Spatial Analysis with Distance IndicEs) contour maps created in
Surfer® overlaid with traps (small dots) of 3 plots near HB in the south and 3 plots near
NH in the north and the crop boundaries denoted in a dotted line in Early Susceptible
(ES) 2011 (A), Late Susceptible (LS) 2011 (B), Early Susceptible 2012 (C), and Late
Susceptible 2012 (D). The dark areas denote a clustering patch (vi>1.5) or high density of
counts near each other. The light gray areas denote a clustering gap (vj<-1.5) or low
density of counts near each other. The white areas denote a random distribution pattern
(vi<1.5 and vj>-1.5).
55
Figure 3.3
56
CHAPTER 4
Reduced spray programs for Drosophila suzukii management in berry crops
Jimmy Klick, Wei Q. Yang, Jana C. Lee, Denny J. Bruck
Pest Management Science
John Wiley & Sons Inc.
350 Main Street
Malden, MA 02148
USA
Manuscript currently in review
57
Abstract
Since the arrival of Drosophila suzukii (Matsumura) (Diptera: Drosophilidae), field
applications of broad-spectrum insecticides have significantly increased to protect
susceptible fruit from infestation in berry crop production. Field studies were conducted
from 2011 to 2013 to determine whether alternate row middle or border treatment
reduced spray programs could manage D. suzukii as well as complete sprays and have
less of an impact on non-target arthropods. Four raspberry sites and one blueberry site
were alternate row middle and border sprayed, respectively. Captures of D. suzukii were
compared to conventional complete spray programs. In both reduced spray trials, no
differences in mean adult numbers and larvae of D. suzukii were detected between
treatments. Mean counts immediately after sprays (i.e., 3±12 d after treatment) were also
similar in complete and alternate row sprays. Both reduced spray strategies had
significantly more Stethorus spp.; additionally, alternate row sprays had significantly
more Psyllobora spp. No difference in fruit knockdown by complete or border spray was
observed. These reduced pesticide strategies are additional tools to consider in D. suzukii
IPM programs that reduce amount of spray area, application time, and input costs while
conserving natural enemies.
Keywords: Border spray, alternate row middle spray, blueberry, raspberry, natural
enemies, fruit knockdown
Introduction
Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) is an invasive pest of small and
stone fruits in the Americas and Europe (Walsh et al., 2011; Cini et al., 2012; Deprá et
al., 2014). Female flies cause direct damage by ovipositing into susceptible ripe fruit (Lee
et al., 2011b). Eggs develop into larvae that feed on fruit flesh, rendering fruit
unmarketable. To prevent fruit loss and to meet zero to low tolerance infestation levels
set by packing plants, growers currently apply broad-spectrum insecticides multiple times
during the harvest season (Bruck et al., 2011). They are faced with several challenges
such as knocking mature fruits off of plants, managing insecticide pre-harvest and
restricted entry intervals (PHI and REI), impacting natural enemies (Roubos et al., 2014a)
and risking possible secondary pest outbreaks, all of which increase production costs.
58
Reduced insecticide strategies such as spraying alternate row middles versus every row
middles (complete sprays) and border sprays are possible tools to curtail these challenges
(VanEe et al., 2000; Roubos et al., 2014b).
The alternate row middle method, henceforth alternate row, involves skipping an
alley so that only one side of each plant row is treated (Lewis & Hickey, 1964). During
the next application, the spray equipment travels down these skipped alleys and treats the
previously non-sprayed side of the rows so that, after two applications, both sides of each
planting row are treated. This reduced spray strategy uses the same rate and volume as
complete sprays (i.e., same active ingredient coverage on the entire field delivered at two
separate applications). Complete sprays refer to full coverage of the crop field (i.e., both
sides of each plant row treated). Alternate row sprays have been used on mobile insect
pests such as plum curculio in peaches (McVay et al., 1994; Lan et al., 2003).
Furthermore, at least 72% of all apple growers in Pennsylvania used alternate row sprays
to manage an array of pests, with fruit damage only reported from the apple budmoth
(Platynota idaeusalis W.) (Hull et al., 1983). The advantages of spraying alternate rows
include an approximately 50% reduction of input costs such as fuel, labor, tractor wear,
and amount of insecticides; reduced environmental impact; and conservation of natural
enemies. In apples treated with alternate row sprays, the phytophagous mite predator,
Stethorus punctum L. (Coleoptera: Coccinelidae) was conserved (Asquith & Colburn,
1971), and in citrus, biological control of scales was enhanced (DeBach et al., 1955;
Ripper, 1956). A possible disadvantage of alternate row sprays compared to every row
sprays is an increased risk of pest attack by leaving one side of each plant row untreated
at each application.
In border sprays (DeBach & Bartlett, 1951), pesticide is applied to crop plants in the
field border at the same rate and volume as complete field sprays, while leaving the
center of the field untreated. Border sprays are typically effective against pests migrating
into the field from field margins (Lafleur & Hill, 1987; Ferguson et al., 2000) and against
µedge oriented¶ colonizers (Reardon & Spurgeon, 2003). Border sprays have been used to
manage apple maggot, codling moth (Trimble & Solymar, 1997; Trimble & Vickers,
2000), and plum curculio (Chouinard et al., 1992; Vincent et al., 1997) in apple orchards,
59
alfalfa weevil in alfalfa (Roberts et al., 1987), and strawberry bud weevil in
strawberries (Kovach et al., 1999). Systemic insecticides have been applied to potato
borders for Colorado potato beetle (Blom et al., 2002) and an attract and kill applied to
cucumber borders for melon fly management (Prokopy et al., 2003). Possible advantages
of border sprays include reduced fruit knockdown within the field, reduction of
insecticide inputs, fewer environmental impacts, and conservation of natural enemies
(Trimble & Solymar, 1997). A disadvantage includes a greater risk of leaving the center
of a treatment plot vulnerable to pest attack.
We hypothesize that reduced spray strategies of alternate row and border sprays will
be as effective as complete field applications at managing the highly mobile D. suzukii
(Mitsui et al., 2010) and will conserve natural enemies. Mobility of D. suzukii was tested
by a preliminary mark-release-recapture study using fluorescent dusts that showed D.
suzukii moved approximately 67±87 m in 36 h (J.C. Lee, unpublished). Field margins
with non-FURSKRVWVVXFKDVµ+LPDOD\D¶EODFNEHUU\Rubus armeniacus F.) may also
provide refuge for overwintering adults and a source for invasion of the cultivated
raspberry fields when ripe (Klick et al., 2014a). Our objectives were to determine
whether reduced spray strategies in western Oregon berry crops would manage D. suzukii
and have less impact on non-target arthropods.
Materials and methods
We tested the more conservative reduced spray strategy, alternate row sprays, in a highly
preferred crop, raspberry (Lee et al., 2011b; Burrack et al., 2013; Bellamy et al., 2013;
Atallah et al., 2014), and the less conservative strategy, border sprays, in a less preferred
crop, blueberry (Bellamy et al., 2013).
Alternate row spray trials in raspberry. Experimental sites and design. A total of four
commercial red raspberry (Rubus idaeus L.) sites, using conventional management
practices, were selected during 2011±2013 harvest seasons (4±6 wk per season) in the
Willamette Valley, Oregon. Each site was arranged in a randomized complete block
design. In 2011, a ~36 ha raspberry farm was selected in Albany, Oregon, henceforth
Farm A, containing three blocks with selectively assigned plots that were each treated
with alternate row or complete sprays. These three experimental units were selectively
60
DVVLJQHGEHFDXVHRIDSDUDOOHOVWXG\7KHILUVWWZREORFNVZHUHµ&DVFDGH%RXQW\¶
raspberry with treatment plots immediately next to each other. The third block was
µ0HHNHU¶UDVpberry with treatment plots spatially separated by ~200 m. Each treatment
SORWLQEORFNRQHZDVaKDRIµ&DVFDGH%RXQW\¶DQGKDGWKUHHDGXOWD. suzukii
monitoring traps and two yellow sticky traps. The treatment plots in the other smaller
blocks were 4±5 ha and each had two adult D. suzukii monitoring traps and one yellow
sticky trap. Traps within each plot were along a single transect and spaced 30±50 m apart.
,QDaKDµ6DDQLFK¶UDVSEHUU\IDUPLQ-HIIHUVRQ2UHJRQKHQFHIRUWK)DUP%KDG
three blocks with randomly assigned treatment plots. Trap numbers were the same across
blocks in 2012 and 2013 trials. Each plot was ~8 ha with eight adult D. suzukii
monitoring traps divided along two transects. In 2013, two of the blocks from Farm B
were selected, omitting one of the low-yielding blocks; and two additional raspberry
IDUPVZHUHVHOHFWHG2QHRIWKHVHIDUPVZDVDVPDOOKDEORFNRIµ&KHPDLQXV¶
raspberry grown under conventional management for U-Pick, henceforth Farm C, which
was ~200 m west of FDUP%7KHRWKHUVLWHZDVDµ0HHNHU¶UDVSEHUU\IDUPKHQFHIRUWK
Farm D, in Talbot, Oregon, with two blocks. Each block was ~10 ha. Farms A and D
were overhead irrigated and Farms B and C were drip irrigated. All 2012 and 2013 sites
had the same number of adult D. suzukii monitoring traps per plot (eight along two
transects) spaced 10±80 m (dependent on plot size).
Monitoring D. suzukii and non-target arthropods. All D. suzukii adults were monitored
with a clear 10-hole trap (Lee et al., 2012) baited with ~150 ml apple cider vinegar (5%
acidity, Fred Meyer Apple Cider Vinegar, Kroger Co., Cincinnati, OH) and a drop of
unscented dish soap to break the surface tension and facilitate drowning. Apple cider
vinegar was refreshed weekly and traps serviced twice per week by recording the total
number of male and female D. suzukii adults caught per trap. Fifty fruit of marketable
quality were collected twice per week during the harvest season throughout the canopy
within a 3 m distance from each adult trap. Fruit samples were brought back to the
laboratory and evaluated for larval presence using the salt extraction method. Fruits were
lightly crushed in a sealable plastic bag to reveal flesh, soaked for 15 min in a 10 brix salt
61
solution (273 g salt per 3.8 liter water), and number of larvae was recorded (Dreves,
2014).
In 2011, non-target arthropods (i.e., natural enemies and common pests) were
monitored during the harvest season at Farm A using yellow sticky cards (Pherocon® AM
No-Bait Traps, Trécé Inc., Adair, OK) placed halfway between the adult D. suzukii
monitoring traps and replaced weekly. Ten leaflets of different size and age were
collected weekly throughout the canopy within 10 m of each yellow sticky trap and
brought back to the laboratory for examination of mites and aphids. In 2012 and 2013,
additional non-target arthropod sampling methods were incorporated into the studies to
increase diversity and abundance of organisms captured compared to 2011. Non-target
arthropod sampling was conducted 7 d post-harvest using yellow sticky cards, leaf
collections, sweep net, vacuum, and beat sheet. Eight non-target arthropod collections per
plot were made in the vicinity of adult D. suzukii monitoring traps. Yellow sticky cards,
as previously described, were in the field for 7 d. Leaves were collected for mites and
aphids, as previously described. Twenty 180° sweeps with a ~40 cm diameter net were
taken by walking ~15 m down the row middle while continuously sweeping from the
plant row on the right down across the row middle to the plant row on the left. Sampling
with vacuum (Shred-N-Vac, ES-2000, Echo Inc., Lake Zurich, IL) was performed by
walking 10 m down a row middle while sampling throughout the top, center, and bottom
canopy on the right side and switching to the left side for another 10 m. Contents from
sweeps and vacuums were collected and each sealed in large sealable plastic bags and
brought to the laboratory along with yellow sticky cards and leaves, arthropods identified
to at least family level (except spiders and microhymenoptera), and numbers recorded.
For beat sheet sampling, a cloth sheet was placed on the bottom row support cables (~0.5
m above ground) near an adult D. suzukii monitoring trap and vigorously shaking the top
row support cables (within the top canopy of the plant row) 50 times. Arthropods were
immediately identified on the beat sheet and recorded. The various collection methods
did not overlap in the same areas (i.e., arthropods were collected from a previously nonsampled area).
62
Border spray trial in blueberry. Experimental site and design. $aKDµ/LEHUW\¶
blueberry (Vaccinium corymbosum L.) site in Albany, Oregon, managed using
conventional practices, was selected during 2012 and 2013. The site was arranged in a
randomized complete block design with three replications in the harvest seasons (7±9
wk). Each block had a randomly assigned border spray and complete spray plot (2.8 ± 5.3
ha). Blocks 1 and 2 were drip irrigated and block 3 was overhead irrigated. In 2013, the
grower installed weed mat and trellis in blocks 1 and 2. Eight monitoring traps of adult D.
suzukii, as previously described, were used per plot with four placed in the crop border
(~5 m into the field, on each side of a plot) and four in the crop interior (40±60 m into the
field from the border trap).
Monitoring D. suzukii, non-target arthropods, and fruit knockdown. Adult and larval D.
suzukii were monitored by trapping and larval extraction methods, respectively, twice per
week, as previously described. Non-target arthropods were collected as previously
described (yellow sticky cards, leaf collections, sweep net, and vacuum). Beat sheet
sampling was not used out of concern for excessive fruit knockdown. Plants near the east
and west adult D. suzukii monitoring traps, representing the crop border and interior of
each plot, were selected to quantify fruit knockdown from each spray strategy. Within 24
h prior to application (border and complete sprays), fruit that dropped naturally or from
hand-harvest was cleared from thHDUHDXQGHUQHDWKWKHVHOHFWHGSODQW¶VFDQRS\DQG
within 24 h after spray applications, fruit knocked down by sprayers was collected,
weighed (g), and recorded.
Insecticide applications. Growers or crop consultants made all pesticide decisions and
applications at the raspberry and blueberry sites based on biweekly reports of D. suzukii
adult and larval counts in the field. In the alternate row spray trial in raspberry, a typical
pre-harvest spray targeting orange tortix (Argyrotaenia franciscana W.) and obliquebanded leafroller (Choristoneura rosaceana H.) (both Lepidoptera: Torticidae) was
applied to every row (i.e., complete spray) with insecticides also effective against D.
suzukii (Bruck et al., 2011). Table 4.1 shows insecticides, rates, cultivars, and mean
number of complete and reduced spray applications per treatment plot at each site. Mean
number of sprays per treatment plot versus total sprays was displayed in Table 4.1
63
because of differences in application numbers between blocks. Raspberry growers
made 1 ± 2 insecticide sprays specifically targeting D. suzukii. Complete and alternate
row sprays were made with a Trellis Boom in 2011 (Farm A), Pul Blast in 2012 (Farm
B), and Pak BlaVW)DUP'DQG3XO%ODVW)DUPV%DQG&LQDOOIURP5HDU¶V
Manufacturing Company, Eugene, Oregon).
Border spray applications in blueberry were made with a cannon sprayer (J-1000,
Jacto Inc., Pompea, Brazil) traveling around the perimeter of the crop and spraying
pesticides up to 30 m into the field. Complete spray applications were made with an overthe-URZ7UHOOLV%RRP5HDU¶V0DQXIDFWXULQJ&RPSDQ\(XJHQH2UHJRQVSUD\HUWKDW
treated two entire plant rows per pass in 2012 and a track-elevated sprayer (TR4 Tracker,
GK Machine Inc., Donald, Oregon) that treated four entire plant rows per pass in 2013.
All insecticide applications (Table 4.1) targeted D. suzukii with the exception of
neonicotinoid applications to control an aphid outbreak in 2012.
Economic analysis. An economic impact scenario of the reduced spray strategies was
estimated on a 4.05 ha plot with two insecticide sprays compared to the complete
application method (Table 4.2). Insecticide cost, machine time, sprayer cost, fruit loss
from knockdown in the 2012 border spray trial, and money saved were included in the
analysis. Table calculations for alternate row, border, and complete sprays were based on
berry economics (Julian et al., 2011). The analyses included: 1) estimated cost of
insecticide material to treat 4.05 ha twice. Insecticide savings are 50% in alternate row
and 70% in border applications based on area sprayed by each method; 2) the machine
time to treat 4.05 ha with an airblast sprayer based on travel speed of 4.8 km h-1 and 0.74
ha treated per hour and the time to treat the same area at 10.9 ha per hour for border
sprays with a cannon sprayer traveling at the same speed. Hectare per hour is the product
of tractor speed (4.8 km h-1), row width (3 m), and efficiency (50%) over a conversion
factor of 8.25 (C.F. Seavert, personal communication). Efficiency is the actual time spent
spraying, excluding filling the tank, traveling to field, adjusting nozzles, and associated
activities; 3) airblast sprayer (alternate row and cover sprays) and cannon sprayer (border
spray) costs to treat 4.05 ha for labor, variable machine cost such as repairs and
maintenance, and fixed machine cost including depreciating interest and insurance. The
64
airblast and cannon sprayers were a 757 L unit and 398 L units with power-take-off,
respectively; 4) fruit knockdown loss in complete spray is based on the difference in fruit
knockdown between border and complete sprays of 41.9 kg ha-1 and blueberry value of
$3.30 kg-1 (average fresh and processed value) in 2012; 5) money saved is the difference
in sprayer and insecticide cost between treatments. Analysis in the border spray trial
includes savings from decreased fruit knockdown.
Data analysis. All statistical analyses were made in R (R Core Team, 2013) using
RStudio (RStudio, 2012) with Į = 0.05. Cochran-Mantel-Haenszel chi-squared test for
count data was used to determine if sums of each gender were in excess in 2 × 2 tables
for each block (Ramsey & Schafer, 2002))LVKHU¶V([DFW7HVWIRUFRXQWGDWDZDVXVHG
for small sample sizes (Ramsey & Schafer, 2002). The linear mixed effects model fit by
restricted maximum likelihood (REML) to determine differences between treatments of
mean adults and larvae across the entire season (collection date and traps) were used for
the alternate row spray trials. In the model, treatments were fixed effects and blocks were
random effects. As only 1±2 treatment sprays were made, a separate analysis was
performed using the same model but only with mean counts between 3±12 d after sprays
to assess efficacy within the insecticide residual period (Bruck et al., 2011). Henceforth,
this will be referred to as µAfter Spray¶.
The border spray trial was a completely randomized block design in a two factorial
experiment. There were two levels each within treatment (border and complete sprays)
and trap position (border and interior traps). Linear mixed effects model fit by REML
was used to detect differences in mean adults captured across the harvest season with
treatment and trap position as fixed effects and treatment plots nested within blocks as
random effects (larval counts were either zero or too low to permit analysis). A drop in
deviance test was performed to fit the most appropriate model (Ramsey & Schafer,
2002). The model with the lowest Akaike information criterion (AIC) and non-significant
difference between other models was deemed most appropriate using ANOVA. When the
full model was most appropriate, linear combinations of coefficients were used to answer
treatment and trap position questions. All P-values are reported with 95% confidence
intervals (CI) and Bonferroni adjusted when two comparisons were made (Į = 0.025).
65
Natural log-transformation was used when normality or equal variance assumptions
were not met. Log10 (x + 1)-transformation was used to transform 0, when present in the
dataset. Estimates and confidence intervals were back-transformed, in the case of
transformed data, and presented in tables along with the original means and standard
errors.
Individual non-target arthropods collected 7 d post-harvest in 2012 and 2013 were
averaged across collection types (sweep, vacuum, beat sheet, yellow sticky cards, and
leaf) and all traps within a treatment plot, to assess the overall impact of treatments. For
example, anthocorids from all collection methods and trap captures within a treatment
plot were combined and expressed as mean number per plot during post-harvest. This
was done to detect plot level population changes, regardless of collection method, and to
boost otherwise low counts.
Only sufficiently large counts of non-target arthropods were included in the analysis.
If the mean number of a non-target arthropod was less than 1.0 per treatment plot, the
arthropod was not included in the analysis because counts were deemed too low to draw
any firm conclusions. In alternate row trials, non-target arthropods were averaged across
collection type (i.e., mean arthropod per treatment plot) and statistically analyzed as
previously described for D. suzukii adults and larvae. In border spray trials, post-harvest
non-target arthropods were averaged across collection type and trap positions (border and
interior) (i.e., mean arthropod per trap position within a treatment plot) and statistically
analyzed as previously described for D. suzukii adults. Fruit knockdown collected after
insecticide applications in the border spray trials were averaged across collection periods
and for each trap position (i.e., fruit knockdown per trap position within a treatment plot)
and analyzed as previously described for D. suzukii and non-target arthropods.
Results
Alternate row spray trials in raspberry. Adults and larvae of D. suzukii. Adult D.
suzukii were not separated by gender based on Ȥ2 test. No significant differences in mean
adult and larval counts throughout the harvest season or during the After Spray period (3±
12 d after treatment application) were detected between alternate row and complete spray
66
treatments from 2011 to 2013 at four cultivated raspberry farms in the Willamette
Valley, Oregon (Table 4.3).
Non-target arthropods: natural enemies and common pests. In 2011, we observed 0.73
times as many Stethorus spp. individuals captured in alternate row spray, compared to
complete spray (P-value = 0.003, CI = 0.57, 0.90). In 2013, alternate row sprayed plots
had approximately four times more Stethorus spp. counts than complete sprayed plots (Pvalue = 0.01, CI = 1.72, 8.33) and about twice as many Psyllobora spp. (Coleoptera:
Coccinelidae) counts (P-value = 0.033, CI = 1.08, 2.86) compared to counts found in
complete spray plots (Table 4.4). Predatory mites (Mesostigmata: Phytoseiidae) were
numerically higher in alternate row spray in 2012 and 2013 (Table 4.4). No significant
differences between alternate row and complete spray were found in the following natural
enemies (Table 4.4): microhymenoptera (Hymenoptera: Parasitic Apocrita - suborder),
predatory thrips (Thysanoptera: Aeolothripidae), spiders (Araneae), rove beetles
(Coleoptera: Staphylinidae), lacewings (Neuroptera: Chrysopidae and Hemerobiidae),
and anthocorids (Hemiptera: Anthocoridae); and in the following common pests (Table
4.5): cucumber beetle (Coleoptera: Chrysomelidae), boxelder bug (Hemiptera:
Rhopalidae), and pest mites (Acari: Tetranychidae).
Border spray trial in blueberry. Adults and larvae of D. suzukii. In 2012, gender was
not separated based on Ȥ2 test; however, gender was evaluated separately in 2013 because
the odds in favor of an excess of females were 0.75 times greater in border spray plots (Pvalue = 0.026, CI = 0.59, 0.96). No significant differences in mean adult counts were
detected between border and complete spray treatments during the 2012 and 2013 harvest
VHDVRQVRIDFXOWLYDWHGµ/LEHUW\¶EOXHEHUU\IDUPLQthe Willamette Valley, Oregon (Table
4.6). In 2012, the effect of trap position on trap counts varied with treatment. Adults
captured in complete spray plots were estimated to be 68% lower in interiors compared to
borders (P-value = 0.017, CI = 0.12, 0.88) (Table 4.7). At last collection of the 2012
harvest season, two larvae were found in fruit collected from the border (n = 50) and two
larvae from the interior (n = 50) of one of the border spray plots. At the end of the 2013
harvest season, one larva was found in fruit collected from the border (n = 50) and five
67
larvae from the interior of border spray plots (n = 200). A single larva was found in
fruit collected from the interior (n = 50) of a complete spray plot.
Non-target arthropods: natural enemies and common pests. In 2013, natural enemies
captured in border spray plots were estimated to have about four times more Stethorus
spp. than in complete spray plots (P-value = 0.045, CI = 1.04, 14.29) (Table 4.6). Since
trap position varied with treatment, there were marginally fewer Stethorus spp. in
complete spray interiors than borders (P-value = 0.081, CI = 0.15, 1.48) (Table 4.7).
Although there was no effect of treatment on microhymenoptera (Table 4.6), trap position
varied with treatment. In 2012, complete spray plots had an estimated 51% fewer
microhymenoptera in the interior than in the border (P-value = <0.001, CI = 0.38, 0.64)
(Table 4.7). In 2013, interiors were estimated to have 48% fewer microhymenoptera than
borders (P-value = <0.001, CI = 0.42, 0.64) (Table 4.7). No significant differences
between border and complete spray were found in the following natural enemies:
predatory thrips, lacewings, and predatory coccinelids (Coleoptera: Coccinelidae); and in
the following common pests: cucumber beetles (Table 4.6).
Fruit knockdown. There was marginal evidence of more fruit knockdown in complete
spray compared to border spray treated plots in 2012 (P-value = 0.082, CI = -0.33,
19.07). A mean weight of 16.4 g (±6.5 SE) of blueberries was knocked down in complete
spray plots and only 5.1 g (±2.5 SE) in border spray plots. In 2013, only 1.2 g (±0.3 SE)
and 1.5 g (±0.3 SE) were knocked down in complete and border spray plots, respectively.
Discussion
This study demonstrated that alternate row and border sprays provided control of D.
suzukii similar to complete spray applications and prevented yield loss, thereby showing
that reduced spray application strategies are important management tools for this pest.
Reduced spray treatments resulted in higher numbers of natural enemies and lowered
input costs. The hypothesis of minimizing D. suzukii populations with reduced sprays
was supported because of likely D. suzukii mobility within field and movement from field
margins into the cultivated crop (Mitsui et al., 2006; Klick et al., 2014a). No differences
in adult and larval counts were detected in the alternate row trials in raspberry. We
suspect within-field movement is high and flies from untreated rows move to treated crop
68
rows. Fly movement from field margins into blueberries most likely was reduced with
the use of border sprays in the low-pressure D. suzukii year of 2012. The integration of
complete sprays may be necessary in a high-pressure D. suzukii year, as in 2013. It is
possible more females were trapped in 2013 border spray plots because they are more
resilient to insecticides than males (Bruck et al., 2011).
The lack of rain enabled longer residual activity of insecticides (Van Timmeren &
Isaacs, 2013), which would be important in fields receiving lower insecticide inputs (i.e.,
reduced spray strategies). The effect on D. suzukii adults and larvae during the residual
period of the insecticides (i.e., After Spray) was similar in complete and alternate row
spray plots. Mean D. suzukii counts from After Sprays (3±12 d after treatment
application) more accurately depict treatment effect rather than mean counts from the
entire harvest season. Only 1±2 insecticide treatment applications specifically targeting
D. suzukii were made during the harvest season, and residual activities of the insecticides
(e.g., malathion, zeta-cypermethrin) persist for 10±14 d at best (Bruck et al., 2011). The
After Spray analysis of D. suzukii adults and larvae was not performed in the border
spray trial because of frequent treatment applications (approximately every 7 d).
An unexpected outcome of this research was the effect of trap position in complete
spray blueberries. In 2012, traps in borders (~5 m into the field) of complete spray plots
had significantly higher D. suzukii and microhymenoptera counts than traps placed in
interiors (40±60 m into the field). In addition, higher D. suzukii counts in the borders
occurred less than 5 d after applications, whereas interior traps had 0 to very low counts
(data not shown). This suggests that placing monitoring traps in borders may not be an
accurate indicator of a plot-wide effect from a complete spray. Insects in border areas of
complete spray plots may have less insecticide exposure than insects in interior areas.
Although border traps do not necessarily estimate plot-wide adult D. suzukii populations
accurately, they are still valuable indicators of early pest presence and level of pressure. It
is unclear why fly captures in trap positions were similar in border spray plots. Perhaps
the cannon sprayer (i.e., border spray) provided better penetration and coverage into
border plant canopies than the vertical boom sprayers (i.e., complete spray) improving
insecticide exposure to D. suzukii. Another possibility is that complete spray plots were
69
exposed to higher D. suzukii pressure than border-spray plots. Indeed, block 3, which
was overhead irrigated, had an outlier trap in the complete spray plot with consistently
high counts throughout the harvest seasons.
To reduce crop risk, the alternate row spray interval can be shortened (Lewis &
Hickey, 1972); and border sprays can be integrated with complete sprays to overcome
higher pest pressure (estimated using degree day models and monitoring traps) or to
µclean up¶ a field (Vincent et al., 1999; Trimble & Vickers, 2000). Level of insecticide
residual activity may also influence crop risk, which varies between production regions,
as risk is influenced by weather. For example, western Oregon likely has longer
insecticide residual activity (Bruck et al., 2011) than North Carolina because of lower
humidity and less rainfall in the summer (Burrack et al., 2013). Other factors possibly
impacting insecticide efficacy include the method of irrigation, inactive ingredients such
as additives, stickers, spreaders, and ultraviolet light breakdown (Van Timmeren &
Isaacs, 2013). Overhead irrigation is suspected of reducing spray residuals and creating a
more ideal habitat of higher humidity and moisture for D. suzukii (Tochen et al., 2014a),
thus increasing risk.
The reduced spray strategies lowered the effect on natural enemies. The conservation
of a phytophagous mite predator, Stethorus spp., in alternate row sprays was consistent
with previous work in apple orchards (Lewis & Hickey, 1972). This is the first report of
conserving Psyllobora spp. by using alternate row sprays in raspberries and Stethorus
spp. conservation in border-sprayed blueberries. Despite conservation of Stethorus spp.
no differences were detected in pest mite densities (Acari: Tetranychidae), which are
secondary pests of raspberry (Bounfour & Tanigoshi, 2001).
We did not detect differences in pest densities from one section of the field to
another, unlike in other studies (Vincent et al., 1997; Trimble & Vickers, 2000). Trimble
and Vickers (2000) reported that oblique-banded leafroller (OBLR) damage levels were
greater in the field center in one of the years of applying border spray treatments in an
apple orchard. OBLR is a major contamination pest of raspberry and managed with a preharvest spray applied to both sides of each plant row, as was done in this study. Two
blocks in 2012 were treated with neonicotinoid for a secondary pest outbreak of aphids
70
(Hemiptera: Aphididae), which was not effective on D. suzukii adults in direct-spray
laboratory bioassays (Bruck et al., 2011), but has shown efficacy against adult and
immature stages in semi-field and field trials (Van Timmeren & Isaacs, 2013) and
curatively for post-infested fruit (Wise et al., 2014). Honeydew from aphids can reduce
fruit quality (Oatman & Platner, 1972). A single neonicotinoid application for aphid
control to the entire border spray plot late in the 2013 season (Table 4.1) was made after
D. suzukii larvae were detected. Larval densities did not change and remained very low
after treatment.
More microhymenoptera were found in borders of complete spray plots in 2012 and
in borders of both treatment plots in 2013, suggesting possible movement from
surrounding field margins into the crop. If natural enemies migrate into the field from
field margins (Longley et al., 1997), then border sprays may also affect them. Van
Driesche et al. (1998) reported that leafminer parasitism in apple orchards was only
higher in 2nd generation parasitoids but not in succeeding generations that were border
sprayed (Van Driesche et al., 1998), suggesting there may be a lag effect of border sprays
on natural enemy populations. Poor predation of cottony cushion scale occurred in
California citrus by predacious Vedalia beetle (Coleoptera: Coccinelidae) when DDT was
treated in two rows surrounding treatment plots (four trees) when compared to untreated
control (DeBach & Bartlett, 1951), as the beetles were also affected by the border sprays.
Another study revealed that parasitism of apple maggot was unaffected by border spray
treatments when compared to complete sprays, regardless of plot size (Van Driesche et
al., 1998). Border sprays seem to thus affect natural enemies differently and are perhaps
dependent on the mobility of the organism. It is important that monitoring occur not just
in field borders, but also in interiors, to assess natural enemies, pest pressure, and
treatment efficacy on the entire plot.
Blueberry fruit knockdown and loss seem highly dependent on sprayer type and
cultural plant management practices including trellising and pruning, row width, plant
size, and cultivar architecture characteristics such as having a compact growth habit. In
2012, an over-the-row Trellis Boom sprayer was attached to a tractor, rows were
untrellised, and plants were four years oOGDQGRQH\HDUIURPPDWXULW\µ/LEHUW\¶
71
blueberries are notoriously difficult to prune as they produce long shoots that grow into
the row middle by harvest, increasing the likelihood of drop. Hand-pickers and deer
likely confounded fruit knockdown data, as only marginal differences were detected. In
2013, the grower upgraded to a track-elevated sprayer and trellised the rows, which
greatly reduced fruit knockdown in complete spray plots. Plots were treated immediately
after fruit was picked to reduce fruit knockdown by the sprayer. The effect of the cannon
sprayer on fruit knockdown appeared minimal, and there was no position effect detected
in treated borders compared to untreated interiors of border spray plots.
Based on the findings presented, reduced spray strategies may be implemented in
low-risk and low-pressure situations and perhaps integrated with other non-insecticide
pest management tools (Edson et al., 1998; Atanassov et al., 2003). The appropriate plot
size for border spray treatments using a cannon sprayer is between 2 and 5 hectares.
Extensive monitoring at least twice per week is important to understand the dynamics and
effects of the reduced spray treatments on adult and larval D. suzukii populations (Kleiber
et al., 2014). Further work is needed to assess the seasonal and long-term impacts of
reduced sprays on non-target arthropods, rather than just post-harvest effects.
Pest pressure from D. suzukii varies during the season (Van Timmeren & Isaacs,
2013), with low populations in winter (Dalton et al., 2011), and the highest populations
from mid-VXPPHUWRIDOOLQPRVWUHJLRQV,QWKHERUGHUVSUD\WULDOWHQµ/LEHUW\¶
blueberries in containers placed along the field margin of each block as untreated controls
did not serve as a good indicator of D. suzukii pressure due to low trap counts. Crop risk
is greater in reduced spray strategies compared to complete spray strategies because
approximately 50±70% of the crop is untreated at each application. Manipulating
temporal and spatial factors that affect D. suzukii populations may reduce this risk.
Knowledge of high-density and low-density D. suzukii areas (Klick et al., 2014a) and
crop ripening phenology (Lee et al., 2011b) could facilitate integration of reduced spray
strategies into a D. suzukii management program, such as reduced spray applications in
low fly density areas onto fruit that ripen in early summer when populations are still low.
Acknowledgements
72
We acknowledge Adam Cave, Austin Cuenca, Evan Dishion, Kelly Donahue,
Christina Fieland, Amanda Lake, Jesse Mindolovich, Danielle Selleck, Scott Shane, Bev
Thomas, Amelia Thornhill, Oscar Vargas, and Jeff Wong for assistance in the laboratory
and field. Thanks to the cooperating raspberry and blueberry growers to permit these
trials in the busy harvest season. Thanks to Jacto Inc. for donating the J-1000 cannon
sprayer for the trial period. Helpful discussions with Leonard Coop, Joe DeFrancesco,
Joe Kleiber, Danielle Lightle, Clark Seavert, and Megan Woltz were greatly appreciated.
Oregon State University Statistical Consulting helped with the experimental design, and
Hannah Tavalire provided statistical analysis advice. We greatly appreciated early draft
reviews by Daniel Dalton and Amy Dreves. Funding was provided by Oregon State
University Agricultural Research Foundation, Oregon Blueberry Commission, WSARE,
USDA SCRI Grant 2010-51181-21167, and USDA CRIS 5358-22000-037-00D. Mention
of proprietary or brand names are necessary to report factually on available data;
however, the USDA neither guarantees nor warrants the standard of the product, and the
use of the name by USDA implies no approval to the exclusion of others that also may be
suitable. This article is in the public domain and not copyrightable. It may be freely
reprinted with customary crediting of source.
73
Table 4.1 Insecticide applications in the alternate row trials (Farms A-D) of raspberry
and border spray trials (Farm E) of blueberry during pre-harvest (p) and harvest (h)
seasons. The rate (kg AI ha-1 and liter ha-1), number of plots per cultivar, mean number of
complete sprays (C) per complete spray plot, and mean number of sprays per reduced
spray plot (alternate row = AR, border spray = B). Note: complete sprays were applied in
pre-harvest to AR plots and integrated during the 2013 season in B plots. For example, at
raspberry Farm A, 0.03 kg zeta-cypermethrin was mixed in 748 liters of water ha-1 and
DSSOLHGRQFHDV&WRWZRµ&DVFDGH%RXQW\¶DQGRQHµ0HHNHU¶&DQG$5SORWVLQSUHharvest 2011.
74
Table 4.1
Farm Year
a
Insecticide trade
name
Mustang Max
Active ingredient
Kg AI ha-1 liter ha-1
(AI)
# plots per
cultivara
Mean complete sprays Mean sprays per reduced
(C) per C plotb
spray (AR or B) plotb
zeta-cypermethrin
0.03
748.32
2 CB, 1 M
1p
1 p-C
malathion
2.24
748.32
2 CB, 1 M
1.3 h
1.3 h-AR
A
2011
A
2011 Malathion Aquamul 8
B
2012
Mustang Max
zeta-cypermethrin
0.03
701.55
3S
1 p, 1 h
1 p-AR, 1 h-AR
B
2012
Delegate WG
spinetoram
0.10
701.55
3S
1h
1 h-C
B
2013
Delegate WG
spinetoram
0.10
701.55
2S
1 p, 1 h
1 p-C, 1 h-AR
B
2013
Mustang Max
zeta-cypermethrin
0.03
701.55
2S
1h
1 h-AR
C
2013
Brigade
bifentrhin
0.11
748.32
1 CH
1p
1 p-C
C
2013
Mustang Max
zeta-cypermethrin
0.03
748.32
1 CH
1h
1 h-AR
D
2013
Tundra EC
bifenthrin
0.11
561.24
2M
1p
1 p-C
D
2013
Mustang Max
zeta-cypermethrin
0.03
561.24
2M
1h
1 h-AR
E
2012
Lannate
methomyl
1.01
701.55
3L
1h
1 h-B
E
2012
Mustang Max
zeta-cypermethrin
0.03
701.55
3L
1.7 h
1.7 h-B
E
2012
Imidan 70W
phosmet
1.12
701.55
3L
1h
1 h-B
E
2012
Admire Pro
imidacloprid
0.70
701.55
3L
0.6 h
0.6 h-C
E
2013
Mustang Max
zeta-cypermethrin
0.03
701.55
3L
1 p, 2.7 h
1 p-B, 2.3 h-B, 0.7 h-C
E
2013
Danitol
fenpropathrin
0.34
701.55
3L
2h
1.3 h-B, 0.6 h-C
E
2013 Malathion 8 Aquamul
malathion
1.40
701.55
3L
0.3 h
1 p-B, 1 h-B, 0.3 h-C
E
2013
imidacloprid
0.70
701.55
3L
-
0.3 h-C
Admire Pro
&XOWLYDUVLQFOXGH&% µ&DVFDGH%RXQW\¶UDVSEHUU\0 µ0HHNHU¶UDVSEHUU\6 µ6DDQLFK¶UDVSEHUU\&+ µ&KHPDLQXV¶UDVSEHUU\/ µ/LEHUW\¶
blueberry
b
Means shown because of differences in number of sprays between blocks; p = pre-harvest period, h = harvest season; Treatments: C = Complete spray,
AR = Alternate row spray, B = Border spray
75
Table 4.2 Economic costs associated with alternate row and border spraying compared
to the complete spray method on 4.05 ha.
Insecticide
Machine
Sprayer
Fruit knockdown
Money
costb ($)
timec (hr)
costd ($)
losse ($)
savedf ($)
Alt. row
500.00
2.75
163.26
-
705.20
Complete
1,000.00
5.49
368.46
-
-
300.00
0.46
94.86
-
1601.60
1,000.00
5.49
368.90
628.00
-
Treatmenta
Border
Complete
a
Table calculations for alternate row, border, and complete sprays based on berry
economics.(Julian et al., 2011)
b
Estimated cost of insecticide material to treat 4.05 ha twice. Savings are 50% in
alternate row and 70% in border applications based on area sprayed by each method
c
Machine time to treat 4.05 ha with an airblast sprayer based on travel speed of 4.8 km h1
and 0.74 ha treated per hour and the time to treat the same area at 10.9 ha per hour for
border sprays with a cannon sprayer traveling at the same speed. Hectare per hour is the
product of tractor speed (4.8 km h-1), row width (3 m), and efficiency (50%) over a
conversion factor of 8.25 (C.F. Seavert, personal communication). Efficiency is the actual
time spent spraying
d
Airblast sprayer (alternate row and complete spray) and cannon sprayer (border spray)
costs to treat 4.05 ha for labor, variable machine cost (repairs and maintenance) and fixed
machine cost (depreciating interest and insurance). The airblast and cannon sprayers were
a 757 liter unit and 398 liter unit with power-take-off (PTO), respectively
e
Based on difference in fruit knockdown between border and complete sprays of 41.9 kg
ha-1 and blueberry value of $3.30 kg-1 (average 2012 fresh and processed value) in 2012
f
Money saved is the difference in sprayer and insecticide cost between treatments (border
spray trial includes fruit knockdown savings)
76
Table 4.3 Comparison of mean (±SE) D. suzukii adults and larvae in alternate row and
complete spray plots throughout the harvest season and during the After Spray period (3
± 12 d after treatment application) in 2011, 2012, and 2013 in raspberry. Complete spray
treatment was used as reference group. Estimates represent multiplicative increase in
median counts in the alternate row spray treatment.
Treatment
Adults
Larvae
2011
2012
2013
2011
2012
2013
Alt. rowa
0.6±0.4ab
0.3±0.1a
0.8±0.1a
1.3±0.7a
0.1±0.04a 0.8±0.3a
Complete
0.8±0.2a
0.3±0.1a
1.2±0.2a
0.6±0.2a
0.1±0.05a 1.0±0.3a
Transformation
Log (ln)
Log (ln)
Log (ln)
Log (ln)
Log (ln)
Log (ln)
2
2
4
2
2
4
0.440
1.172
0.367
2.053
1.379
1.223
Harvest
df
Estimate
CI
P-value
0.04, 5.26 0.16, 8.33 0.11, 1.75
0.289
0.762
0.353
0.01,333.33 0.11, 1.72 0.69, 2.17
0.610
0.638
0.389
After Spray
Alt. row
0.10±0.06a 0.07±0.04a 0.30±0.07a
0.15±0.11a 0.06±0.05a 0.12±0.04a
Complete
0.52±0.22a 0.12±0.06a 0.27±0.07a
0.00±0.00a 0.06±0.05a 0.14±0.06a
Transformation Log10(x+1) Log10(x+1) Log10(x+1)
Log10(x+1) Log10(x+1) Log10(x+1)
df
Estimate
CI
P-value
a
2
2
4
2
2
4
7.368
9.640
10.097
11.400
10.000
9.845
3.47, 15.64 8.27, 11.23 8.60, 12.45
0.223
0.410
0.633
7.94, 16.37 8.13, 12.30 8.65, 11.21
0.259
1.000
0.755
Original mean and SE are shown with back-transformed estimates and confidence
intervals (CI) (Į = 0.05).
b
Same lower-case letters within a column are not significantly different (Į = 0.05) based
on linear-mixed effects model.
77
Table 4.4 Comparison of mean (±SE) natural enemies in alternate row and complete spray plots 7 d post-harvest in 2011,
2012, and 2013 in raspberry. Complete spray treatment was used as reference group. Estimates represent multiplicative
increase in median counts in the alternate row spray treatment, in the case of log-transformed data.
Microhymenoptera
Treatment
2011
2012
Pred. mite
Stethorus
2013
2011
2012
2013
2012
2013
Pred. thrips
2012
2013
Spider
Rove
2012
2013
2012
Psyllobora Lacewing Anthocorid
2013
2013
2013
Alt. rowa
15.6±1.7ab 30.8±3.2a 36.5±4.7a 1.2±0.3a 6.7±3.8a 1.7±0.6a
2.3±0.5a 3.3±0.6a 9.0±3.2a 6.1±1.1a
1.6±0.3a
1.0±0.2a
0.6±0.2a 1.9±0.3a 0.7±0.1a 0.9±0.2a
Complete
17.4±2.9a 23.7±3.4a 41.2±6.3a 0.5±0.2b 5.1±2.6a 0.4±0.1b
1.8±0.6a 2.8±0.6a 13.6±2.8a 8.8±1.8a
1.3±0.4a
1.0±0.2a
1.8±0.8a 1.2±0.2b 1.1±0.2a 1.0±0.3a
Log (ln) Log (ln)
Transformation Log (ln) Log (ln) Log (ln)
df
Estimate
CI
P-value
a
-
-
Log (ln)
Log (ln)
-
Log (ln)
Log (ln)
Log (ln)
Log (ln)
2
2
4
2
2
4
2
4
Log (ln) Log (ln)
2
4
2
4
2
4
4
4
1.006
1.291
0.962
0.731
1.583
3.831
1.175
1.422
0.460
0.880
0.835
0.075
0.750
1.748
0.696
0.944
0.41, 2.41 0.66, 2.50 0.58, 1.58 0.57, 0.90 -6.08, 2.91 1.72, 8.33 0.22, 6.25 0.65,3.13 0.07, 3.13 0.35,2.22 0.35, 4.00 -0.28, 0.43 0.04, 12.5 1.08, 2.86 0.35, 1.39 0.23, 3.85
0.979
0.242
0.93
0.003
0.919
0.01
0.719
0.276
0.222
0.73
0.59
0.591
0.707
0.033
0.224
0.916
Original mean and SE, are shown with, in the case of log-transformed data, back-transformed estimates and confidence
intervals (CI) (Į = 0.05). Samples were combined in all collection methods (sweep, vacuum, beat sheet, yellow sticky cards,
and leaf) to assess plot level differences
b
Different letters within a column are significantly different (Į = 0.05) based on linear-mixed effects model
78
Table 4.5 Comparison of mean (±SE) common pests found in alternate row and complete
spray plots 7 d post-harvest in 2011, 2012, and 2013 in raspberry. Complete spray treatment
was used as reference group. Estimates represent multiplicative increase in median counts in
the alternate row spray treatment.
Treatment
Pest mites
Boxelder bug Cucumber beetle
2012
2013
2012
2013
Alt. rowa
328.8±180.9a
47.6±23.2a
1.3±0.3a
3.8±0.6a
Complete
301.8±185.0a 57.48±25.4a
2.1±0.8a
4.5±0.6a
Transformation
df
Estimate
CI
P-value
a
Log (ln)
Log (ln)
Log10(x+1)
Log (ln)
2
4
2
4
1.412
0.267
9.747
0.827
0.27, 7.14
0.02, 4.00
1.04, 91.03
0.47, 1.47
0.465
0.248
0.965
0.408
Original mean and SE are shown with back-transformed estimates and confidence intervals
(CI) (Į = 0.05). Samples were combined in all collection methods (sweep, vacuum, beat sheet,
yellow sticky cards, and leaf) to assess plot level differences
b
Same lower-case letters within a column are not significantly different (Į = 0.05) based on
linear-mixed effects model
79
Table 4.6 Comparison of mean (±SE) D. suzukii adults throughout the harvest season and natural enemies and common
pests 7 d post-KDUYHVWLQDQGLQERUGHUDQGFRPSOHWHVSUD\SORWVLQµ/LEHUW\¶EOXHEHUU\&RPSOHWHVSUD\WUHDWPHQW
was used as reference group. Estimates represent multiplicative increase in median counts in the border spray treatment.
Treatment
Natural enemies
Drosophila suzukii
Adults
Malesa
2012
Females
2013
Microhymenoptera
Stethorus Pred. thrips
Common pest
Lacewing
Pred. coccinelid
Cucumber beetle
2012
2013
2013
2012
2012
2013
2012
2013
Borderb
0.4±0.1ac
0.6±0.1a
1.0±0.1a
15.2±2.9a
12.6±1.6a
6.0±1.0a
3.5±0.6a
1.2±0.3a
1.4±0.4a
3.0±0.5a
8.5±1.4a
Complete
0.5±0.1a
0.7±0.2a
0.7±0.1a
18.5±3.1a
10.9±1.9a
3.1±0.5b
3.0±0.5a
0.3±0.2a
0.7±0.3a
2.5±0.6a
5.9±1.2a
Full
Reduced
Reduced
Full
Reduced
Full
Reduced
Reduced
Reduced
Reduced
Reduced
Log (ln)
Log (ln)
Log (ln)
Log (ln)
Log (ln)
Log(ln)
Log (ln)
Log10(x+1)
Log10(x+1)
Log (ln)
Log (ln)
Model
Transformation
df
Estimate
CI
P-value
a
4
2
2
4
2
4
2
2
2
2
2
1.689
1.490
1.739
0.631
1.202
3.831
1.166
14.872
13.061
1.244
1.610
2.97, 74.47
4.66, 36.57
0.27, 5.56
0.73, 3.57
0.400
0.381
0.601
0.124
0.51, 5.56 0.14, 16.67 0.28, 11.11 0.32, 1.27
0.291
0.545
0.327
0.139
0.85, 1.70
0.151
1.04, 14.29 0.31, 4.35
0.045
0.665
Gender were analyzed separately based on Ȥ2 tests in 2013
Original mean and SE are shown with back-transformed estimates and confidence intervals (CI) (Į = 0.05). Natural enemy
and common pest samples were combined in all collection methods (sweep, vacuum, yellow sticky cards, and leaf) to assess
plot level differences
c
Different letters within a column are significantly different (Į = 0.05) based on linear-mixed effects model
b
80
Table 4.7 Comparison of mean (±SE) D. suzukii adults throughout the harvest season
and natural enemies 7 d post-harvest in 2012 and 2013 collected from border (~5 m into
the field) and interior (40±60 m into the field) trap positions of border and complete spray
SORWVLQµ/LEHUW\¶EOXHEHUU\7KHUHGuced model applied in 2013 microhymenoptera did
not permit treatment separation. Border trap was used as reference group. Estimates
represent multiplicative increase in median counts in the interior traps.
Trap position
Natural enemies
Drosophila suzukii
Adults
Microhymenoptera
2012
2012
Stethorus
2013
Border Complete Border Complete
2013
Border Complete
Border trapa
0.4±0.1ab 0.7±0.2a 15.9±3.9a 25.3±5.3a 15.3±2.0a 4.8±1.1a 4.3±0.8a
Interior trap
0.4±0.1a 0.2±0.1b 14.5±4.4a 11.6±2.0b 8.2±1.1b 7.2±1.6a 2.0±0.4a
Model
Full
Full
Full
Full
Reduced
Full
Full
Transformation Log (ln) Log (ln) Log (ln) Log (ln) Log (ln) Log (ln) Log (ln)
df
Estimate
CI
P-value
4
4
4
4
5
4
4
1.172
0.319
0.874
0.494
0.522
1.775
0.465
0.42, 3.24 0.12, 0.88 0.67, 1.14 0.38, 0.64 0.42, 0.64 0.56, 5.64 0.15, 1.48
0.615
0.017
0.147
a
0.0007
0.0005
0.157
0.081
Original mean and SE are shown with back-transformed estimates and confidence
intervals (CI) that were Bonferroni adjusted for two comparisons (Į = 0.025). Natural
enemy samples were combined in all collection methods (sweep, vacuum, yellow sticky
cards, and leaf) to assess plot level differences
b
Different letters within a column are significantly different (Į = 0.05) based on linearmixed effects model
80
81
CHAPTER 5
Marking Drosophila suzukii with rubidium or 15N
Jimmy Klick, Wei Q. Yang, Denny J. Bruck
Journal of Economic Entomology
10001 Derekwood Lane,
Suite 100
Lanham, MD 20706
USA
Manuscript accepted
81
82
Abstract
Drosophila suzukii has caused significant economic damage to berry and stone fruit
production regions. Markers that are systemic in plants and easily transferred to track
organisms are needed to trace D. suzukii exploitation of host resources and trophic
interactions. High and low concentrations of the trace element, rubidium (Rb), and the
stable isotope, 15N, were tested to mark D. suzukii larvae feeding on fruits of enriched
strawberry plants grown in containers under greenhouse conditions. Fly marker content
and proportion of flies marked 1, 7, and 14 d after emergence from enriched fruits and fly
dry mass were analyzed. Nearly 100% of the flies analyzed 14 d after emerging from 15N
enriched plants were marked, whereas only 30±75% and 0±3% were marked 14 d after
emerging from high and low Rb concentration plants, respectively. Rapid Rb decay,
strong 15N persistence, and the economics of using these markers in the field to elucidate
D. suzukii pest ecology are discussed.
Keywords: Rubidium, 15N, insect marking, strawberry, Drosophilidae, spotted wing
drosophila
Introduction
Drosophila suzukii Matsumura (Diptera: Drosophilidae) larvae feed on the interior of
ripening berry and stone fruits, causing significant economic losses in production regions
of Europe and the Americas (Walsh et al., 2011; Cini et al., 2012; Deprá et al., 2014).
Insect marking tools can be used to understand movement and dispersal of pests and
trophic interactions (Hagler & Jackson, 2001), which may lead to improved integrated
pest management (IPM) (Dorn et al., 1999; Jeger, 1999; Carriere et al., 2006; Klick et al.,
2014a, 2015). An ideal marker for field experiments is inexpensive, environmentally
friendly, easily applied, acquired and persistent, and clearly identifiable (Hagler &
Jackson, 2001). Protein marking is one such tool and has been successfully used to mark
D. suzukii in the laboratory (Klick et al., 2014b) and resident flies in a mark-capture study
in the field (Klick et al., 2014a). Traceable proteins cannot be incorporated into plants.
Systemic marking tools are required to determine what plant hosts are being utilized by
resident flies in nature and to understand particular aspects of pest ecology. The trace
element, rubidium (Rb), and the stable isotope, 15N, have been successfully used to mark
83
resident arthropods that have fed on enriched hosts in the field (Stimmann, 1974;
Nowatzki et al., 2003; Tillman et al., 2007; Hood-Nowotny & Knols, 2007). Natural
background levels of Rb and 15N are low. Small insects absorb the non-toxic mark from
the environment (Berry et al., 1972; Steffan et al., 2001). Our objective was to compare
the suitability of rubidium and 15N to help determine trophic interactions and sink-source
relationships in complex and simple landscapes. We address this by determining 1) the
persistence of these markers and percentage marked in adult D. suzukii that emerge from
marked fruits of treated strawberry plants and 2) the effect of these markers on fly mass
(as an indicator of fitness).
Materials and methods
Marking D. suzukii. On 25 May 2012, twenty-five strawberry (Fragaria x ananassa
µ7RWHP¶SODQWV with green fruits were transplanted from the field (Oregon State
University Botany Farm, Corvallis, Oregon) to 4.1 liter containers (21.6 cm × 17.1 cm,
Anderson Die & Manufacturing, Portland, Oregon), arranged in a randomized block
design, and grown under greenhouse conditions (16L: 8D photoperiod at 13±24 °C). To
prevent feral D. suzukii from infesting fruits, fine-mesh netting (No-See-Um, Eastex
Products, Holbrook, MA) bags were sealed over each plant before fruit turned color. The
soil of each plant was drenched with a 250 ml solution five times over a 2 wk period
(approximately every 3 d) with one of the following treatments: deionized water
(control), 210 ppm N from 15N enriched NH4NO3 (5 atom%, Isotec Inc., Miamisburg,
OH), 500, and 5,000 ppm RbCl (99.8% trace metals basis, Sigma-Aldrich, St. Louis,
MO). Treatments were replicated four times. The water treatment was replicated eight
times to provide a set of controls (n = 4) in Rb and 15N analysis. Henceforth, treatments
will be referred to as control, 15N, 500, and 5,000 ppm Rb.
On 18 June, when ripe fruit was present, each plant was moved from the greenhouse
into a transparent cage (22 × 22 × 27 cm) topped with fine-mesh netting. Five mature (3±
15 d old) laboratory-reared D. suzukii adults (as described in Bruck et al., 2011) of each
gender were added to each cage and placed in an incubator room at 22 °C, 35% RH, and
16L: 8D photoperiod in a randomized block design. Flies were removed after 70 h of
exposure. All leaves were removed and fine-grain white sand (0.15 mm, Unimin, New
84
Canaan, CT) added to the soil surface to facilitate detection of emerged D. suzukii. The
first emergence of adults occurred 7 d after the start of fly exposure; 8-17 d after start of
exposure, a mean of 27 (± 9 SD) adult flies per plant (N = 20) emerged and were
collected in respective treatment tubes (32-121BF, Genesee Scientific, San Diego, CA)
with 2 cm3 of Drosophila cornmeal diet (Drosophila Stock Center, San Diego, CA)
0DUNRZ2¶*UDG\ZKLFKZDVUHIUHVKHGHYHU\G$mean subset of 18 (± 10
SD) adult flies were harvested from each replicate at 1, 7, and 14 d post-emergence,
killed by freezing, and stored individually in 1.5 ml microcentrifuge tubes at -80 °C. Each
sample was dried at 60 °C for 48 h and weighed on a microscale (C-35, Orion Cahn®,
Thermo Electron Corporation, Waltham, MA) prior to mark analysis.
Analysis of Rb-marked D. suzukii. Each fly sample was digested in 6 ml of
concentrated HNO3 using a microwave (Multiwave 3000, Anton Paar) for 40 min (20
min microwave and 20 min cool down) at 140±190 °C and 20 bar pressure. Water (18.2
M-Ohm) was used to quantitatively transfer to conical centrifuge tubes with a final
volume of 50 ml and HNO3 concentration of 15% (vol/vol). Rb measurements were made
by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) using a Thermo Scientific
X-Series II. Instrument drift was monitored and corrected with an indium (In) internal
standard added to every solution to yield a final concentration of 1 ppb In. For the
samples, 3 ml aliquots of digested sample were pipetted into 14 ml tubes spiked with In
and diluted to 5 ml with 1% (vol/vol) HNO3. Rb standards were diluted from a
commercial standard (Sigma-Aldrich, St. Louis, MO) to make a working range of 0.02 to
20 ppb Rb. The standards also contained 1 ppb In and 5% HNO3. The higher acid
concentration in the standards was necessary for proper uptake and washout of Rb (Rb in
a pure solution of 1% HNO3 had delayed uptake and washout). Any suppression from the
higher acid concentration was corrected by the In internal standard. Apple leaves (SRM
1515, National Institute of Standards and Technology) containing a known amount of Rb
were analyzed to verify the analytical accuracy. Fourteen apple leaf samples were
analyzed. Rb recovery was very good and ranged from 91-115%. Results from the ICPMS for the fly samples were measured as SSW5EDQGFDOFXODWHGWRȝJ5ESHUJUDPRID.
suzukii.
85
Analysis of 15N-marked D. suzukii. Individually-dried whole flies were encased in 8
× 5 mm tin capsules (D1006, Elemental Microanalysis Ltd, Okehampton UK) and
processed by the Oregon State University Stable Isotope Research Unit using an
elemental analyzer and Isotope Ratio Mass Spectrometer.
Data Analysis. Statistical analyses were made in R v3.0.3 (R Core Team, 2013) with an
Į level of 0.05, or a Bonferroni-adjusted Į level of 0.006 and 0.017 for analyses
involving nine (Rb marker content) and three (Rb effect on fly dry mass) comparisons,
respectively (Ramsey & Schafer, 2002). Linear mixed effects models fit by restricted
maximum likelihood were used to estimate differences between treatments in marker
content and dry mass within each gender (Crawley, 2013). Analyses were performed
separately for each gender because persistence and mark content varied in male and
female flies. The marker content model included treatment by date and treatment by age
as fixed effect and fly tube nested within date and nested within container as random
effect. Age was included as interaction because the effect of treatment on marker content
was expected to change with age. Response variables were natural-log transformed if
assumptions of normality and equal variance were not met. The effect of treatment varied
by age and by date; therefore, vectors of linear combinations of model coefficients were
created to estimate differences in means between treatments. Estimates and confidence
intervals were back-transformed, where applicable, and reported with non-transformed
means and standard deviations. An individual fly sample was scored as marked if the
marker value exceeded the mean value of the control flies plus three times the standard
deviation of controls (Stimmann, 1974). Cochran-Mantel-Haenszel chi-squared tests were
used to determine if marked: non-marked flies exceeded null expected ratios while
accounting for emergence date (Ramsey & Schafer, 2002). The dry mass model included
treatment by date of emergence as fixed effect with fly age as covariate and fly tube
nested within date of emergence as random effect. Age was included as a covariate to
account for the variance due to age. A drop in deviance test was performed to fit the most
appropriate model (Ramsey & Schafer, 2002).
86
Results
Both marker types were detected in flies that emerged from fruits of enriched strawberry
plants. Rb content in emerged flies decreased rapidly, whereas 15N remained persistent
and detectable in nearly all flies for the entire trial period (14 d) (Tables 5.1 and 5.2). All
(38) 1 d old flies that emerged from fruits with 500 and 5,000 ppm Rb were considered
marked and had more Rb than controls (Tables 5.1 and 5.2). Only flies from the high
concentration (5,000 ppm Rb) had more Rb and a greater marked: non-marked ratio than
controls throughout the entire trial period (14 d) (Tables 5.1 and 5.2). The percentage of
females marked with Rb 14 d after emerging from the high concentration fruits was 75%
or 2.5 times that of males from the same treatment (Table 5.1). Detailed statistical outputs
of treatment comparisons are presented in Table 5.2.
All flies (except 1 out of 124) analyzed for 15N were considered marked after
emergence from enriched fruits at all time periods tested (Table 5.1). Female and male
flies that emerged from fruits treated with 15N were estimated to have 7 (P-value <
0.0001, CI = 1.06, 1.08) and 8% (P-value < 0.0001, CI = 1.07, 1.09) more 15N atom% per
D. suzukii than controls, respectively, regardless of age. Since no control and nearly
100% of 15N flies were considered marked at all time periods, no statistical comparisons
were possible (i.e., the odds ratio could not be calculated) (Table 5.1). The treatments had
no effect on female and male dry mass.
Discussion
The 15N mark was highly persistent in flies that emerged from enriched plants, but Rb
rapidly decayed with time in flies from the low concentration and slightly less so in flies
from the high concentration treatments. In other studies, rapid loss of Rb occurred 2±4 d
after lygus and western corn rootworm stopped feeding on enriched plants (Fleischer et
al., 1986; Nowatzki et al., 2003), but persisted for up to 27 d in Medfly (Van Steenwyk et
al., 1992). Food source may affect Rb decay as the rate of Rb loss correlated with KCl in
food of Drosophila spp. and Megaselia scalaris (Fairbanks & Burch, 1968). Furthermore,
KCl is physiologically similar to the RbCl used in this study and was abundant in
excretions of insects (Ramsay, 1953).
87
Similar to our findings, all treated aphids that fed on 15N enriched oat plants
remained marked 10±16 d after transfer to non-enriched oats (Nienstedt & Poehling,
2000). Several factors may explain why 15N was persistent in flies: nitrogen is retained
from food as proteins to make tissue and muscle in immature arthropods (Speight et al.,
2009), nitrogen can be resorbed (Mira, 2000), and insects typically retain signatures of
larval foods as adults (Hood-Nowotny & Knols, 2007).
The markers tested at given concentrations did not affect fly dry mass. However,
similar Rb concentrations tested in other studies have been shown to have adverse effects
on insects. High concentrations of Rb (6,000 ppm to diet) affected development,
fecundity and longevity of tufted apple bud moth (Knight et al., 1989), and
concentrations above 5,000 ppm reduced survivorship in blueberry leaftier (Polavarapu et
al., 1992). D. suzukii had a similar amount of Rb as Medfly (Van Steenwyk et al., 1992).
Spra\LQJRULQMHFWLQJȝJ5EPORQFRIIHHIUXLWUHVXOWHGLQ0HGIOLHVZLWK±
ȝJ5EJZKLFKGLGQRWKDYHDQ\DGYHUVHELRORJLFDOHIIHFWV$GYHUVHHIIHFWVRI15N
have not been reported.
Costs of D. suzukii analysis for Rb and 15N were seven and eight-fold higher,
respectively, than egg protein marking (Klick et al., 2014a,b). However, 15N and Rb may
be used to answer other research questions, such as the origin of a fly and trophic
interactions, but may be limited in scale by the high costs. Field marking material costs
may be offset if the rate of decay of 15N is shown to be much slower than egg protein. Rb
was less favorable than 15N as a marker because of shorter persistence and the risk of
negative effects on insect biology. Future work should determine the role of other host
material on marker effect and the persistence of 15N in D. suzukii. The 15N mark
successfully labeled D. suzukii via enriched plants and was highly persistent without any
known adverse biological effects; hence, providing a tool for tracing pest exploitation of
host resources and other trophic interactions.
Acknowledgements
We acknowledge Molly Albrecht, Kelly Donahue, Amanda Lake, and Scott Shane for
technical assistance. Thanks to Jadwiga Giebultowicz, George Hoffman, Joe Kleiber,
Gail Langellotto, Jana Lee, and Bob Van Steenwyk for helpful discussions; and Amy
88
Dreves for reviewing an early draft of this manuscript. We are grateful to Suean Ott
and Carolyn Scagel for digesting Rb samples and Andy Ungerer and the Oregon State
University (OSU) W.M. Keck Collaboratory for ICP-MS assistance. We appreciate the
help of David Myrold and the OSU Stable Isotope Research Unit for 15N analysis.
Thanks to Hannah Tavalire for statistical consultation and manuscript review. Funding
was provided by the Agricultural Research Foundation, USDA SCRI Grant 2010-5118121167, and USDA CRIS 5358-22000-037-00D.
89
Table 5.1 Mean ȝJ5EJD. suzukii (Rb marking) and 15N atom% D. suzukii (15N marking) (± SD), ratio of marked: nonmarked, and percent marked (%) in female and male D. suzukii 1, 7, and 14 d after emergence from fruits of strawberry plants
enriched with Rb or 15N.
Mean marker content (± SD)a
Treatment
1
No. d after emergence
7
Rb marking
Female
Control
15.31 ± 10.96b
14.27 ± 5.21b
500 ppm Rb
167.23 ± 123.90a 13.70 ± 13.02a
5,000 ppm Rb 608.66 ± 126.37a 66.96 ± 44.94a
Male
Control
14.41 ± 5.23c
17.06 ± 5.55b
500 ppm Rb
136.76 ± 55.13b
19.79 ± 13.92b
5,000 ppm Rb 1,080.64 ± 998.35a 178.63 ± 393.87a
Marked: non-markedb
Percent marked (%)
14
No. d after emergence
1
7
14
No. d after emergence
1
7
14
8.56 ± 9.16b
14.65 ± 9.03b
75.83 ± 49.99a
1: 8b 0:22 b 1: 25b
11: 0a 1:22 b 1: 31b
7: 0a 5:2 a 21: 7a
11
100
100
0
4
71
4
3
75
8.04 ± 7.83b
15.38 ± 8.60b
32.24 ± 17.85a
0: 7b 0:13 b 0: 30b
12: 0a 1:12 a 0: 20b
8: 0a 7:4 a 13: 31a
0
100
100
0
8
64
0
0
30
15
N marking
Female
Control
15
N
0.37 ± 0.0008b
0.40 ± 0.0144a
0.37 ± 0.0007b
0.39 ± 0.0109a
0.37 ± 0.0007b
0.39 ± 0.0089a
0: 7
10: 1
0: 30
20: 0
0: 26
28: 0
0
91
0
100
0
100
Male
Control
15
N
0.37 ± 0.0005b
0.41± 0.0032a
0.37 ± 0.0006b
0.40 ± 0.0095a
0.37 ± 0.0006b
0.40 ± 0.0107a
0: 5
6: 0
0: 19
28: 0
0: 20
31: 0
0
100
0
100
0
100
a
Different letters within the same gender of a marker and same column are significantly different using linear mixed effects
model. Statistical output is presented in Table 5.2
b
Different letters within the same gender of a marker and same column are significantly different based on Cochran-MantelHaenszel chi-squared test. Since no flies were considered marked in the control and nearly 100% marked in the 15N treatment,
no statistical comparisons were possible (i.e., the odds ratio could not be calculated)
90
Table 5.2 Output of statistical comparisons for Rb marker content and ratio of marked: non-marked 1, 7, and 14 d after
emergence from fruits of strawberry plants enriched with Rb. Estimates represent a multiplicative increase in median marker
content in the 500 or 5,000 ppm Rb treatments.
Treatment comparison
1 d after emergence
dfa Estimate
Rb marker content
Female
7 d after emergence
14 d after emergence
95% CI
P
Estimate
95% CI
P
Estimate
95% CI
P
0.0006*
2.40
0.82-7.03
0.0230NS
b
500 - control
37
15.08
3.02-75.27
<0.0001**
8.43
1.60-44.51
5,000 - control
37
72.07
13.09-396.74
<0.0001**
10.64
2.22-51.12
0.0001*
10.01
3.66-27.34
<0.0001**
5,000 - 500
37
4.78
0.89-25.62
0.0100NS
1.26
0.27-5.94
0.6629NS
4.17
1.39-12.54
0.0005*
500 - control
36
8.47
1.73-41.36
0.0004*
3.03
0.25-36.67
0.2025NS
1.09
0.12-9.52
0.9201NS
5,000 - control
36
149.15
27.34-813.58
<0.0001**
46.45
4.00-539.96 <0.0001**
29.53
2.86-305.30
0.0002*
5,000 - 500
36
17.62
3.04-102.20
<0.0001**
15.33
1.22-192.25
27.38
2.67-280.70
0.0002*
Male
Rb marked: non-markedc
Female
Ȥ2
0.0033*
Ȥ2
Ȥ2
500 - control
1
11.67
0.0006*
0.83
0.3613NS
0.30
0.5827NS
5,000 - control
1
8.13
0.0044*
9.16
0.0025*
19.59
<0.0001**
5,000 - 500
1
Na
Na
7.51
0.0062*
21.30
<0.0001**
Male
500 - control
1
12.35
0.0004*
0.88
0.3496NS
Na
Na
5,000 - control
1
8.77
0.0031*
6.34
0.0118*
8.21
0.0042*
5,000 - 500
1
Na
Na
3.40
0.0654NS
5.63
0.0177*
Back-transformed estimates and confidence intervals (CI); NS, non-significant; *, P-value < 0.006; **, P-value < 0.0001
a
One less df in males because males were missing from one of the emergence dates
b
Linear mixed effects model with a Bonferroni-adjusted Į level of 0.006 for nine comparisons
c
Cochran-Mantel-Haenszel chi-squared test with an Į level of 0.05
91
CHAPTER 6
Conclusion
Jimmy Klick
92
Spotted wing drosophila, Drosophila suzukii (Diptera: Drosophilidae), is a global
threat to small and stone fruits production. The lack of biological control, large
monocultures, high production standards, global trade of fruits, expansive host range, and
pest biology and ecology created the perfect storm for D. suzukii to establish as a global
pest. Insecticides, applied as complete cover sprays are currently the primary technique
used for protecting susceptible fruit from infestation (Beers et al., 2011; Bruck et al.,
2011; Van Timmeren & Isaacs, 2013). However, environmental and non-target concerns,
high potential of developing insecticide resistance, and IPM are driving research towards
developing sustainable management tools.
Drosophila suzukii pressure is dependent on the population density exerted on a crop
and typically varies temporally (i.e., by year or time of season) and spatially (i.e., local or
regional). Understanding factors that influence fly pressure facilitates risk assessment.
Some of these factors include weather, landscape, crop, and microclimate. For example in
the Willamette Valley of Oregon, a mild winter (more spring survivors), a landscape
abundant with crop and non-crop D. suzukii hosts (increased oviposition, refuge, and
food sites throughout the season), a crop that ripens late in the season when populations
are highest, soft fruit (easier to oviposit), and a field that is overhead irrigated (high
humidity) is a high-risk scenario. In contrast, a cold winter (fewer spring survivors), a
landscape abundant with non-hosts (fewer resource sites throughout the season), an early
ripening crop when populations are still recovering from winter, firm fruit (more
challenging to oviposit), and a drip irrigated field (low humidity) is a low-risk scenario.
Proactive growers could further reduce risk by making conditions unfavorable for D.
suzukii and implementing additional management tools such as sanitation, physical
barriers (e.g., netting), pruning to open canopy, timely harvesting, and post-harvest cold
storage. These methods along with enhancement, protection, and implementation of
biological control and other management tactics (e.g., attract-and-kill, bait sprays) are
currently under development and will play an increasing role in achieving the long-term
goal of reducing insecticides by providing growers holistic management strategies for D.
suzukii. The ideal D. suzukii management program involves multiple tools across the
entire year. Although little published literature currently exists on alternative
93
management practices, a possible IPM scenario in Oregon throughout the year may
look like this: suspected overwintering sites could be the focus of spring mass trapping,
localized bait sprays, or attract-and-kill efforts followed by the use of physical barriers or
border sprays that intercept D. suzukii before moving into a crop. During the harvest
season, alternate row sprays, frequent harvests, drip irrigation, maintaining an open
canopy, and utilizing sanitation practices to minimize breeding sites could be practiced to
lower the risk by manipulating the environment to be less conducive to D. suzukii.
Improved monitoring efforts with the use of an effective and selective lure and trap
design paired with a predictive model (estimating activity and events), along with
seasonal sampling of larvae for assessing damage are vital to understand risk, measure
treatment effect, and for detection throughout the year. Post-harvest methods of cold
storage and irradiation may prevent larval development in infested fruit and treatment of
unpicked or dropped fruit (e.g., kaolin clay protective film on fruit or fruit crushing) may
reduce oviposition and fly densities. Research is underway around the globe to develop
these future strategies and will greatly improve pest knowledge and management.
The work herein showed that a landscape with alternate hosts in non-crop areas is part
of a high-risk scenario because higher fly densities were reported in those non-crop areas.
Protein marking flies in this mark-capture study showed that flies move from adjacent
non-crop areas into the crop. Although low numbers of marked individuals were
recovered and it is not clear if flies visited or originated from the non-crop areas,
conclusions of movement from non-crop to crop were supported by fly density data from
other researchers. To address the latter shortcoming, 15N marking tools that are systemic
in plants showed high persistence in flies reared from enriched strawberries in a
greenhouse and could be used to determine origin of a fly in the field and help understand
additional pest ecology questions.
Reduced spray strategies, such as border and alternate row sprays, may be more
easily implementable in low-risk scenarios. As long as adult and larval D. suzukii
populations are monitored extensively (e.g., twice per week, one trap per hectare, bait
replaced weekly), growers could possibly adapt the reduced insecticide application
strategies to lower insecticide inputs and conserve natural enemy fauna, which are the
94
overarching goals in IPM programs. Further efforts are needed to evaluate reduce
spray methods across a wider spectrum (e.g., variable spatial and temporal scales,
different crops and pest pressure) before widespread implementation can be
recommended. These methods could be the first step in D. suzukii management on the
long path towards reducing insecticides and impact on natural enemies. There is still little
understanding on D. suzukii movement and exploitation of non-crop hosts. Early ripening
non-crop hosts may have a larger impact on population densities, especially if the
phenology between non-crop and crop hosts is similar. We only looked at adjacent field
margins, but understanding how favorable landscape factors at different spatial scales
affects crop invasion is also important.
95
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