COLONIZATION PATTERNS AND DIAPAUSE ECOLOGY OF COLORADO POTATO (LEPTINOTARSA DECEMLINEATA), INTERACTION WITH NEONICOTINOID RESISTANCE

By

Anders S. Huseth

A dissertation submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

(Entomology)

at the

UNIVERSITY OF WISCONSIN − MADISON

2013

Date of final oral examination: 04-29-2013

This dissertation is approved by the following members of the Final Oral Committee: Russell L. Groves, Associate Professor, Entomology Claudio Gratton, Associate Professor, Entomology Que Lan, Professor, Entomology David B. Hogg, Professor, Entomology Amanda J. Gevens, Assistant Professor, Plant Pathology

i

Acknowledgements

I thank my advisor, Russ Groves, for his support throughout the course of this project. I also thank my committee members, Claudio Gratton, David Hogg, Que Lan, and Amanda

Gevens for their kind criticism and insight throughout the development of this project. I would like to also thank Paul Esker for participating as an instrumental committee member early in my career. I thank Jeff Wyman, Tom German, Walt Goodman, Phil Pelliteri, and Bryan Jensen for valuable constructive conversations that were instrumental in the development of this project. I would like to especially thank Scott Chapman and Ken Frost for field support and serving as a sounding board for my ideas through thick and thin. I would like to thank current and former

Groves lab members – Carol Groves, Shahideh Nouri, JP Soto-Arias, Chen Zhang, David

Lowenstien, Natalie Hernandez, and Sara(h) Schramm for being have all been important resources and friends through the years. I especially would like to thank the following potato producers for supporting my research: Steve and Andy Dierks of Coloma Farms, Nick Sommers and Randy Cherney of Plover River Farms, Don and John Hamerski of Hamerski Farms, and TJ

Kennedy of Heartland Farms. I also thank the employees at the Hancock Agricultural Research

Station, Hancock, WI for invaluable assistance over the years. Finally, I thank my wonderful family and friends for support throughout this work.

ii

Abstract

Rationale: In 2011, Wisconsin farmers grew 25.5 thousand hectares of cultivated potato worth an estimated 267 million dollars. Since 1995, systemic neonicotinoids have been used on approximately 85% of these acres to manage the , Leptinotarsa decemlineata (Say) and other key pests. As a result of long-term reliance, neonicotinoid resistance in Colorado potato beetle has become common. In the spring of 2008 and 2009, growers reported changes in the colonization timing of Colorado potato beetle. Specifically, it was suggested that were either extending or delaying their arrival times in commercial fields. Observed changes in beetle ecology typically occurred where neonicotinoid resistance had previously been documented in past seasons and may be an indication of an evolving relationship between insecticide resistance and changes in diapause patterns. A long colonization period resulted in the presence of several life stages of this in the crop simultaneously. Where protracted or delayed emergence occurred, many growers chose to manage these multiple life stages with high-risk, foliar applications. With increasing input costs growers may avoid proactive resistance management strategies, continuing to use generic neonicotinoid compounds paired with inexpensive, high risk foliar insecticide applications to manage resistant populations and maintain profit margins.

Project Goal: To better understand the relationship between neonicotinoid use, Colorado potato beetle resistance, and environmental fate of neonicotinoids in the Central Sands agroecosystem.

Objectives: I) To define the influence of previous (year) potato fields and adjacent diapause on field scale Colorado potato beetle abundance. II) To use a common garden experiment to examine relationships between insecticide resistance, emergence phenology, and beetle fitness in field collected beetle populations. III) To document in-plant

iii concentration and environmental fate of neonicotinoid insecticides when systemically applied in potato

Impact and Outcomes: An improved understanding of insecticide application methods and their effects on insect resistance management, insect ecology, and the surrounding environment will improve the long-term viability of systemic insecticides, which have become a keystone in our management program. Deliverable outcomes will inform sustainable, environmentally sound management plans for potato production systems and other specialty crops where systemic applications are commonplace.

iv Table of Contents

Acknowledgments...... i

Thesis Abstract...... ii

Chapter 1: Literature Review...... 1 Problem defined...... 2 Biology and Ecology...... 3 Systemic pest management and neonicotinoids...... 7 Insecticide resistance...... 8 Environmental fate of neonicotinoids in Wisconsin...... 11 Research rationale...... 12 References...... 14

Chapter 2: Effects of landscape composition and rotation on Colorado potato beetle, Leptinotarsa decemlineata (Say) abundance in cultivated potato...... 23 Abstract...... 24 Introduction...... 25 Materials and Methods...... 27 Results...... 36 Discussion...... 38 References...... 46 Tables...... 52 Figures...... 59 Supplemental Material...... 61

Chapter 3: Effect of insecticide management history on emergence phenology and neonicotinoid resistance in Leptinotarsa decemlineata (Coleoptera: Chysomelidae)...... 62 Abstract...... 63 Introduction...... 64 Materials and Methods...... 69 Results...... 77 Discussion...... 82 References...... 90 Tables...... 99

v

Figures...... 106 Supplemental Material...... 110

Chapter 4: Insecticide residues and leaching of systemic neonicotinoids in cultivated potato: implications for insect resistance management and environmental fate...... 116 Abstract...... 117 Introduction...... 119 Materials and Methods...... 123 Results and Discussion...... 131 References...... 139 Tables...... 147 Figures...... 150 Supplemental Material...... 156

Chapter 5: Concluding remarks and future directions...... 159 Summary...... 160 Future directions...... 165 Project impact and outcomes...... 167 1

Chapter 1: Literature Review

2 Problem defined: The Colorado potato beetle, Leptinotarsa decemlineata (Say), has been a significant pest of potato in Wisconsin since 1866. For the past 18 years, potato growers in the state have relied almost exclusively upon a small suite of insecticides classified as the neonicotinoids (Mode of Action group 4a, IRAC 2013) to control Colorado potato beetle. The widespread adoption and limited rotation of active ingredients has led to insecticide resistance in localized populations in the state. This insecticide resistance combined with observed changes in the emergence behavior of the insect from overwintering has resulted in multiple, resistant life stages simultaneously present in the field. Because these different Colorado potato beetle life stages are not all equally susceptible to residual concentrations of neonicotinoids present after planting, extra foliar applications are often necessary to achieve adequate control. These additional inputs (e.g. carbamates, pyrethroids, and organophosphates) directly impact non-target organisms, worker safety, increase the risk of environmental contamination, and are expensive for the grower to apply. As a result, there is a need to further develop new IPM strategies, both chemically and non-chemically based, where localized populations of resistant beetles exist.

These new strategies, or insecticide resistance management tactics, will require an improved understanding and a more complete characterization of Colorado potato beetle overwintering biology and colonization patterns into potato fields. Here, we investigated spatially explicit, colonization models to improve established scouting procedures, documented the emergence phenology of resistant and susceptible populations, and related the in-plant concentrations of the neonicotinoid insecticides in potato with the environmental fate of these same active ingredients.

The development of novel control tactics in this region will improve the sustainability of overall management by reducing the need for additional insecticide sprays thereby limiting non-target impacts and reducing grower input costs. By combining improved crop scouting strategies and 3 control tactics with novel insecticide technologies, we can better integrate fundamental, research-

based information about Colorado potato beetle population biology into a more ecologically

sound, prescriptive IPM program for Wisconsin potato producers.

Below is a brief review of Colorado potato beetle biology and a discussion this pest’s

ecology in the context of Midwest potato production. This review has three primary aims: 1) to

provide a biological and ecological background of the insect in a potato-centric agroecosystem,

2) to outline the culture of systemic insecticide management in potato and associated impacts on

insecticide resistance development, and 3) to describe quality impacts resulting from

insecticide use in Wisconsin potato. To conclude, this review summarizes areas of research need

in potato pest management with a specific emphasis on Wisconsin and the upper Midwest

region. Observational and survey data from both government and non-government agencies were

contributed for this review. Though not exhaustive, an additional objective of this review is to provide relevant background information on fundamental aspects of Colorado potato beetle biology and ecology, crop colonization, and insecticide resistance development important for the development of research hypotheses described later in this document.

Biology and Ecology: Colorado potato beetle is considered to be among the most destructive pests impacting Solanaceous crop production (eggplant, tomato, and potato) in North

America (Gauthier et al. 1981). Physiologically very dynamic in its survivability, the Colorado potato beetle flourishes in many extreme climatic regions throughout Europe, Asia, and North

America (Casagrande 1987, EPPO 2006, Piiroinen et al. 2011). Northern most populations occur in Russia at 62ºN latitude (approximate location of 62ºN parallel in N. America: Southern tip of

Greenland; Baffin Island, Nunavut; Denali Nat’l Park, Alaska) (EPPO 2006). Range expansions into temperate regions is not thought to be limited by summertime low temperatures (Boman et 4 al. 2008, Lyytinen et al. 2009), but by high winter mortality during the diapause stage of this

life cycle (Tauber and Tauber 2002, Hiiesaar et al. 2006).

Reproductively, Colorado potato beetles have the ability to be extremely prolific and

fecund as overwintered and summer adults. Individual females can produce between 500-1,000

and may remain reproductively viable for 55 to 120 days under optimal conditions (~20°C)

(Peferoen et al. 1981). Eggs are most frequently deposited in masses of approximately 20-60

eggs per mass on ventral leaf surfaces of Solanum spp. (Peferoen et al. 1981). Colorado potato beetle larvae progress through a series of four instars over a period of 10 to 20 days depending on host plant quality and environmental conditions (Gauthier et al. 1981, Doležal et al. 2008).

The final instar crawls from the potato canopy and burrows into the soil for pupation that lasts approximately 10 days after which they emerge as an adult beetle (Gauthier et al. 1981). In a typical summer season, Wisconsin potato beetle populations undergo two, successive full generations per year (Kung et al. 1992). The summer of 2012 was unseasonably warm and long, anecdotal observations by growers in the Central Sands suggested that beetle populations throughout the region completed a fully functional third generation. Although surprising to

Wisconsin growers, studies from Europe suggest similar trends in population dynamics are occurring on potato and further speculate changing climatic patterns may influence this transition from bivoltinism to multivoltinism in Colorado potato beetle (Kocmánková et al. 2010). Using a combination of developmental threshold parameters for Colorado potato beetle and high resolution spatio-temporal modeling techniques in CLIMEX, Kocmánková et al. (2010, 2011) predicted an increasing incidence of fully functional third generations in growing regions throughout Europe. In an effort to provide a conservative portrayal of climate change, the authors chose to include three different Global Climate Models (GCM) to project distributions 5 (HadCM-high, NCAR-PCM-high, and ECHAM-high). Using estimates based on the HadCM- high global climate scenario, the authors suggest that by 2050, 45% more acreage will experience three generations of Colorado potato beetle when compared to present levels.

Although differences exist among GCMs, analysis of overlapping prediction regions may provide estimates of the arable acreages expected to be affected. Predictions generated in Europe may be useful to explain grower observations in Wisconsin where Colorado potato beetle populations persisted later into the growing season, often requiring more intensive chemical management to maintain control.

Colonization and cultural control: In the spring of each year, adult Colorado potato beetle populations emerge from diapause and emigrate from areas surrounding previous season’s potato crop to colonize newly planted potato (Gibson et al. 1925, Weber et al. 1995). The majority of beetle populations are thought to interact with potato at the local landscape scale, often colonizing potatoes at distances less than 400 meters from previous season’s potato

(Sexson and Wyman 2005). Annual rotation in space is a common practice among commercial producers nationwide as a durable, non-chemical management strategy to reduce abundance of colonizing beetle populations (Voss et al. 1988, Weber and Ferro 1993, Weiz et al. 1994, Follett et al. 1996, Sexson and Wyman 2005, Boiteau et al. 2008). Long-distance rotation also prolongs the time between plant emergence and colonization time allowing for more vigorous plant growth prior to colonization (Ng and Lashomb 1983, Lashomb and Ng 1984, Boiteau et al. 2003,

Boiteau et al. 2008). In addition to manipulation of host plant availability in space (rotation), growers may delay planting until soil temperatures increase (above 13°C or 55°F) thereby lessening direct defoliation damage to slow growing young plants early in the season (Lamp and 6 Zhao 1993, Brewster and Allen 1997, Smith 1998, Kennedy and Storer 2000, Onstad et al. 2001,

Carrière et al. 2006, Park et al. 2006).

Although rotation over distance has been considered the key cultural management tool for this pest, additional studies have suggested management of the insect in their preferred overwintering may be an underutilized management tactic (Kung et al. 1992, Voss and

Ferro 1990, Weber and Ferro 1994b). In temperate potato production regions, late season dispersal from potato is influenced by a combination host plant quality and photoperiod cues

(deWilde 1969, Hsiao 1981, Hoy et al. 1998). As potato plants senesce, adult beetles disperse in short flights toward prominent, dark, vertical landscape features, such as windbreaks and forested field edges (Voss and Ferro 1990, Weber and Ferro 1994a, Wyman et al. 1994, Follett et al.1996, Noronha and Cloutier 1999, Boiteau 2005). Adult beetles overwinter in the soil along these field edges consisting of hedgerows or woodlots commonly found surrounding irrigated potato in Wisconsin (Milner et al. 1992, Kung et al. 1992). When springtime soil temperatures exceed 11°C, adult beetles gradually begin to emerge from their overwintering burrows (de Kort

1990). During the winter dormancy period, adult insects atrophy their flight muscles as a nutritive resource; as a result emerged adults are physiologically incapable of long distance, post- diapause flights prior to feeding (de Kort 1990, Voss and Ferro 1990, Boiteau et al. 2003).

Overwintered adults walk from diapause habitats in search of suitable Solanaceous host plants nearby including cultivated potato (Gibson et al. 1925, Wegorek et al. 1967, Thiery and Visser

1995, Weber et al. 1995). Walking Colorado potato beetles can be effectively controlled by strategic deployment of potato trap crops, plastic lined trenches, or narrow seeded buffer crops at the edges of fields (Weber et al. 1994b, Boiteau et al. 2008, Szendrei et al. 2009). Often, strategic 7 positioning cultural controls between overwintering habitats and newly planted potato

significantly increases the efficacy of trap crops (Wyman et al. 1994).

Systemic pest management & neonicotinoids: In-plant delivery of insecticides, both transgenic

and conventional, has become one of the most widely adopted arthropod management

technologies in IPM programs (James 2010, Jeschke et al. 2011). Flexibility in application type,

diversity of active ingredients and more focused control of herbivorous have driven

widespread adoption of systemic insecticides in nearly every major commodity group worldwide

(Shelton et al. 2002, Jeschke and Nauen 2008). One of the most popular pest management

classes, the neonicotinoids, has occupied approximately 24% of the total global insecticide

market share since 2008 (est. revenue: 1.17 b USD; Jeschke et al. 2011). Neonicotinoid

insecticides have registrations in an estimated 120 countries worldwide, partially due to an

exceptionally wide range of activity against piercing-sucking pests such as aphids, whiteflies,

leafhoppers, planthoppers, and (Jeschke et al. 2011). As systemic seed treatments, these

compounds also have excellent activity on several economically important coleopteran pests,

including the Colorado potato beetle, corn rootworm (Diabroctica spp.), and wireworms

(Agriotes spp.) (Elbert et al. 2008). The state of Wisconsin currently holds 164 different neonicotinoid registrations for field, forage, fruit, vegetable, turf, and ornamental crops (6 acetamiprid, 18 clothianadin, 4 dinotefuran, 108 imidacloprid, 1 thiacloprid, 26 thiamethoxam;

Agrian, 2013). Systemic delivery of insecticidal active ingredients has often been classified as an

EPA-designated, reduced risk alternative, that limits impacts to non-target organism, decreases additional pesticide use, limits acute and chronic exposure to humans, and shows positive economic benefits to growers (Shelton et al. 2002, Tomizawa and Casida 2005, Elbert et al.

2008, US-EPA 2012). 8 While much attention has been directed to the positive attributes of systemic insecticides, an increasing body of literature increasingly suggests significant negative impacts to non-target organisms and the environment at multiple spatial and temporal scales (Blacquière et al. 2012,

Casida 2012, Krupke et al. 2012, Gill et al. 2012, Segraves and Lundgren 2012, Starner and Goh

2012). To date, examination of negative impacts (e.g. biological, environmental, food safety, economic) related to systemic insecticides have only been extensively studied for a handful of active ingredients generally related to major agricultural commodities (Albajes et al. 2003,

Girolami et al. 2009, Ohnesorg et al. 2009, Kong et al. 2011, Marzaro et al. 2011). Many intensively managed specialty crops grown on smaller acreages rely on systemic delivery systems for management of key arthropod pests; yet, effects of insecticide resistance and impacts to associated agroecosystems are not well studied.

Insecticide resistance. The evolutionary response to toxins within the Solanaceae plant family may contribute to Colorado potato beetle’s capacity to metabolize insecticides (Ferro 1993). To date, economic management of this insect has been challenged by resistance to an estimated 54 distinct compounds in every major class of insecticides (Hofmaster et al. 1967; Forgash 1985;

Ioannidis et al. 1991; Stewart et al. 1997; Noronha et al. 2001; Stankovic et al. 2004, Alyokhin et al. 2008, Jiang et al. 2012). Resistance development to multiple insecticide classes may be enhanced by several physiological mechanisms, chronic exposure intervals, inter-population gene flow, and localized dispersal (Grafius 1995). Management of resistant populations has resulted in more frequent applications, tank mixing of different insecticides, often resulting in considerable negative economic impact to growers (Grafius 1997).

Since 1995, in-furrow, systemic neonicotinoid applications have been the most widely adopted insecticide use pattern for Colorado potato beetle control. Systemic neonicotinoids 9 maximize in-plant distribution and persistence within the potato plant (Baker et al. 2007), but

also increases selection pressure over the entire population resulting in the potential for

insecticide resistance (Olson et al. 2000; Zhao et al. 2000). Costs of resistance are often defined

by a reduction in population scale fertility. Baker et al. (2008) found fecundity to be one third

less in imidacloprid (neonicotinoid) resistant Colorado potato beetle. Overwintering mortality

may be as great as 90%, further enhancing selection pressure with resistant beetles (Milner et al.

1992).

Systemic neonicotinoids in potato: In the upper Midwest, season long management of

Colorado potato beetle is a critical component of potato production (Hare 1990). Since 1995, nearly 90% of production acres have utilized an in-furrow or at-plant systemic neonicotinoid insecticide for management of colonizing populations and early summer generations of Colorado potato beetle. Unfortunately, long-term reliance on this mode of action class has resulted in localized Colorado potato beetle tolerance to neonicotinoid insecticides in discrete areas of potato production regions in the lower 48 states (Mota-Sanchez et al. 2006, Alyhokhin et al.

2008, Groves 2008, Szendrei et al. 2012). Over time, continued development of insensitivity to neonicotinoids resulted in reduced efficacy, the necessity of foliar rescue applications, and greater grower expense (Grafius 1997, Alyhokhin et al. 2008). Although numerous studies have evaluated the physiological impacts associated with Colorado potato beetle resistance to the systemic neonicotinoids, very little research has focused on the ecological and environmental implications associated with management of resistant populations using these tools.

Efficacy of the systemic neonicotinoid insecticides is linked to timing of pest arrival and subsequent colonization of the crop. In temperate regions, Colorado potato beetle arrives in the crop shortly after emergence from overwintering. Diapause is a genetically determined behavior 10 of an insect’s lifecycle designed to synchronize its biology with seasonal variation in the environment (Tauber et al. 1986). Insects inhabiting more dynamic or unstable environments with unpredictable resources may extend diapause for longer periods, resulting in delayed emergence (Corley et al. 2004). For Colorado potato beetle, population scale selection for individuals that emerge after high peaks of in-plant insecticide concentration subside may explain localized erosion of neonicotinoid control and temporal variability of crop colonization.

Current evidence suggests several of Wisconsin’s resistant populations are smaller, less fit, and may emerge over a longer period (Huseth and Groves 2010). New research in other agronomic crops reveals that neonicotinoid insecticide concentrations are often both spatially and temporally variable throughout the growing season (Olson et al. 2004; Byrne et al. 2005a, 2005b,

2007, 2010; Castle et al. 2005). In potato pest management, heterogeneous toxin distributions of the insecticides in plants create refuges where insects encounter low-dose exposure that drives insecticide resistance development in Colorado potato beetle (Hoy et al. 1998). Anecdotal observations by Wisconsin and Minnesota potato producers indicate Colorado potato beetle populations in areas of high resistance may colonize the crop over a longer period of time often resulting in season long management issues. Population scale selection for later emergence appears to coincide with reduced, or trailing in-plant insecticide levels. Over time, the continual exposure of late emerging, tolerant populations will be driven by insecticide refugia at multiple scales in space and time resulting in accelerated resistance to neonicotinoids (Olson et al. 2004;

Alyokhin et al. 2007). If true, rapid natural selection may fix the protracted emergence trait in the gene pool. Linking colonization of the crop with temporal concentration of the insecticide may provide valuable insight into more effective deployment strategies for systemic insecticides. The long-term impacts of these dynamic emergence patterns is unknown, but may compromise the 11 efficacy of current, and more importantly, future systemic registrations. Furthermore, identifying other factors (e.g. rain events, soil microbial communities, misapplication) influencing within or among plant variability will provide critical insight into alternative mechanisms of refuge development.

Environmental fate of neonicotinoids in Wisconsin: The Wisconsin Department of

Agriculture, Trade and Consumer Protection – Environmental Quality section (WI DATCP-EQ) currently conducts regulatory action for the mitigation and prevention of groundwater contamination by pesticides and nutrients. Environmental Quality staff use data collected from regularly collected groundwater samples to inform regulatory decisions for numerous agrochemical and industrial contaminants.

In 2008, WI DATCP-EQ released an annual report indicating detections of the neonicotinoid insecticide thiamethoxam from groundwater wells throughout the state (WI-

DATCP 2010). Of the 398 total water samples analyzed in 2008, twenty tested positive for thiamethoxam (0.638–7.85 µg/L). Over two consecutive years 2008-2009, several wells produced positive detections of thiamethoxam. At the present time, no current groundwater enforcement standards exist for neonicotinoids in the state (U.S. EPA 2003; Jeff Postle-WI-

DATCP, personal communication).

Movement, or leaching, of neonicotinoids into groundwater may be related to the common delivery method for these insecticides. For the grower, an at-plant application not only increases the uniformity of insecticide distribution in the plant but also limits non-target exposure to workers, beneficial arthropods, and the environment. Little is known about what amount of insecticide that leaches beyond the root zone from these types of applications in potato. Widespread use of systemic insecticides in potato coupled with the recent detection of 12 neonicotinoids in groundwater supports the hypothesis that current plant protection strategies

may contribute to these detections. An additional goal of this project will be to directly compare

different systemic delivery methods and measure their ability to limit, or reduce insecticide loss

below the root zone. Documenting Colorado potato beetle phenology, systemic insecticide

expression patterns, insecticide leaching, and compromised groundwater quality will provide a

critical foundation for integrated approaches to limit insecticide resistance development and

more importantly reduce environmental contamination with neonicotinoids.

Research Rationale: Modern specialty crops agriculture has been characterized as high input production systems existing within intensive, highly modified landscapes. Generally, commercial potato agroecosystems consist of aggregations of irrigated, agricultural fields dominating landscapes interspersed with highly fragmented non-crop habitats. In Wisconsin, an estimated

63,000 acres (>90% statewide production) of potatoes are grown in three discrete regions: The

Antigo Flats, Central Sands, and Lower Wisconsin River valley (USDA NASS, 2013). In these regions, fifty years of concentrated, high-intensity potato production have not only created local economies centered around agriculture (Keene and Mitchell 2010), but also has resulted in considerable negative impact to surrounding ecosystems at multiple scales (Rothschild et al.

1982, Saad 2008, Shrestha et al. 2010). Crop producers in the near future will likely be challenged to more effectively balance improved production practices that increase profitability, while remaining diligent stewards of the land. One significant new challenge to sustainable potato production includes a balance between grower profitability with more stringent residue limits, food safety, and phytosanitary regulations (FQPA, FSMA, GAP/GHP standards).

Additionally, growers and pest practitioners are increasingly pressured to reduce agronomic inputs to improve the health of farmers, communities, and the environment (carbon emission 13 abatement/offset, FIFRA, SDWA). Annual pest management practices (e.g. arthropods, pathogens, nematodes, and weeds) remain a key target area to improve food safety by reducing agrochemical residues on goods for direct consumption and minimize non-target impacts to the broader ecosystem.

Economic management of specialist herbivores in high value commodity cropping systems, like potato, remains a considerable concern for growers, pest practitioners, and researchers alike. Since 1995, the neonicotinoid class of systemic insecticides have been used extensively to manage early season insect pests in potato: Colorado potato beetle, Leptinotarsa decemlineata (Say); Potato leafhopper, Empoasca fabae (Harris); Green peach aphid, Myzus persicae (Sulzer); and Potato aphid, Macrosiphium euphorbiae (Thomas). Long-term reliance on this class of insecticides for arthropod management in the potato agroecosystem has resulted in losses in product efficacy as well as increased environmental contamination in groundwater resources of these compounds in the environment. This project examines the widespread use of systemic neonicotinoids in a major specialty crop, cultivated potato, as a potential driver of insecticide resistance, delayed emergence from dormancy, and variable colonization patterns of the specialist herbivore, Colorado potato beetle. Furthermore, this project reports on the effects of groundwater quality resulting from leaching of these systemic insecticides in cultivated potato. An increased understanding of how insecticide delivery methods may adversely affect the and ecology of key pests in potato, as well as their impacts upon the surrounding environment will provide crucial insight into development of more biologically based sustainable application of pest management tools in potato.

14

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Chapter 2: Effects of landscape composition and rotation distance on Colorado potato beetle (Coleoptera: Leptinotarsa decemlineata) abundance in cultivated potato

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Abstract: Knowledge of the Colorado potato beetle’s, Leptinotarsa decemlineata (Say), relationship to previous potato crops has contributed to the development of a pest management strategy focused upon crop rotation. Previous investigations revealed that potato rotations exceeding 0.4 km were effective in reducing colonization in current season potato. The current study examines the relationship between beetle abundance in potato and distance from multiple, previous year potato fields in Wisconsin (USA), and integrates information about the influence of natural habitats adjacent to previous season potato. Colorado potato beetle count data was collected in 1998 and 2008 and distance to previous potato, field areas, and landscape classes were estimated using maps from 1997 and 2007. Poisson regression was used to relate counts to combinations of distance and local landscape characteristics calculated for all fields within 1,500 meters of sampled potato. In 1998, beetle counts measured in current season potato declined significantly with increasing distance from previous potato fields and field size did not influence these counts. However, there was no relationship between beetle abundance and distance to prior year potatoes in 2008. In both years, increased proportions of surrounding habitats, previously described as preferred for diapause sites (e.g., wooded field boundaries), did not relate significantly to counts. However, grassland habitat was negatively correlated with counts.

Results indicate that distance from previous potato remains an important factor to reduce the magnitude of colonization. This analysis further suggests that certain landscape components (e.g. grassland) may influence infestation, which may be useful for refining future IPM programs.

Key Words: Colorado potato beetle, IPM, crop rotation, diapause, GIS

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The Colorado potato beetle, Leptinotarsa decemlineata (Say) (Coleoptera:

Chrysomelidae), is an annual pest of potato in North America (Gauthier et al. 1981). In the spring of each year, Colorado potato beetle populations emigrate from previous season’s potato crop to colonize newly planted potato (Gibson 1925, Weber et al. 1995). In Wisconsin, the majority of beetle populations are thought to interact with potato at the local landscape scale, typically colonizing potatoes at distances less than 400m from previous seasons potato (Sexson and Wyman 2005). Specifically, commercial potato producers use crop rotation over distance and among years as a durable, non-chemical management strategy for Colorado potato beetle

(Voss et al. 1988, Weber and Ferro 1993, Weiz et al. 1994, Follett et al. 1996, Sexson and

Wyman 2005, Boiteau et al. 2008). Manipulation of host plant availability in space (rotation) and time (delayed planting) are common management strategies used to lessen defoliation caused by the Colorado potato beetle (Lamp and Zhao 1993, Brewster and Allen 1997, Smith 1998,

Kennedy and Storer 2000, Onstad et al. 2001, Carrière et al. 2006, Park et al. 2006).

Areawide management models are often generated from precise, small-scale observations at the field level that are used to infer relationships about the large-scale distribution (e.g. regional level) and abundance of pests (Carrière et al. 2006). Models of large-scale pest dynamics, at the agroecosystem level, include multiple assumptions which may or may not be valid, resulting in landscape-scale pest management recommendations with limited utility (Jeger

1999, Carrière et al. 2006). In a heterogeneous landscape, such as the Wisconsin vegetable producing Central Sands eco-region, it is thought that Colorado potato beetle can be effectively managed with areawide, rotation management programs (Sexson and Wyman 2005). Long- distance rotation has been documented to reduce Colorado potato beetle abundance and increase the time between emergence and colonization (Ng and Lashomb 1983, Lashomb and Ng 1984, 26

Boiteau et al. 2003, Boiteau et al. 2008). However, the areawide concept has not been fully implemented at the regional scale of potato production in Wisconsin for two reasons. First, an absence of government or producer-based regulatory compliance has not incentivized self- regulation by growers in the region. Second, smaller potato producers often cannot independently implement sufficient rotational distances, due to a lack of sufficient acreage

(Boiteau et al. 2008).

Although rotation over distance has been considered a critical cultural management component for control of Colorado potato beetle, additional studies have further suggested that overwintering habitat preference of Colorado potato beetle may also be important (Kung et al.

1992, Voss and Ferro 1990, Weber and Ferro 1994b). In temperate potato production regions, late season Colorado potato beetle dispersal from potato is influenced by photoperiod and host plant quality (deWilde 1969, Hsiao 1981, Hoy et al. 1996). As potato plants senesce, adult beetles disperse in short flights toward prominent, dark, vertical landscape features, such as windbreaks and forested edges (Voss and Ferro 1990, Weber and Ferro 1994a, Wyman et al.

1994, Follett et al.1996, Noronha and Cloutier 1999, Boiteau 2005). In Wisconsin, adult beetles overwinter in the soil typically along these field edges consisting of hedgerows or woodlots

(Milner et al. 1992, Kung et al. 1992). In the spring, adults begin emerging as soil temperatures exceed 11°C (de Kort 1990). Following emergence adults are physiologically incapable of long distance flights (de Kort 1990, Voss and Ferro 1990, Boiteau et al. 2003). Overwintered adults walk from diapause habitats in search of suitable host plants nearby, commonly cultivated potato

(Gibson et al. 1925, Wegorek et al. 1967, Thiery and Visser 1995, Weber et al. 1995). Walking

Colorado potato beetle can be effectively controlled by strategic deployment of potato trap crops 27

at the edges of fields (Weber et al. 1994). Positioning trap crops between potential overwintering

habitats and newly planted potato increases the efficacy of trap crops (Wyman et al. 1992).

The timing and magnitude of colonization is also affected by landscape complexity

within the agroecosystem (Boiteau et al. 2008). A prolonged interval prior to colonization is

advantageous to the producer because it reduces the duration of time over which the pest must be

managed. An improved understanding of how landscape complexity surrounding potato

influences Colorado potato beetle colonization, will provide new, and potentially useful

information to supplement our current areawide management programs. Here we examined how

non-crop habitats surrounding previous year’s potato and rotation distance influenced Colorado

potato beetle colonization in Wisconsin. A Geographic Information System (GIS) based

approach was used to explore and relate relative field abundance of Colorado potato beetle adults

to rotation distance and land use data in the agroecosystem. We hypothesized that previous

year’s potato and surrounding local landscapes would serve as the principal source of colonizing

Colorado potato beetle in the landscape and further that; (1) the magnitude of field infestations in

the current season potato would decline as distance from previous year’s potato increased, (2) a larger proportion of potato area in the previous year combined with shorter rotation distances would increase Colorado potato beetle abundance in the current season, (3) source fields with a high proportion of surrounding habitat suitable for Colorado potato beetle overwintering, would influence Colorado potato beetle counts in current season potato.

Materials and Methods

Experimental site. A portion of the data used in this study are described in an earlier

study and additional information about field and region selection can be accessed in Sexson and

Wyman (2005). Briefly, thirty-nine potato fields were identified in 1998 from within a discrete 28 potato agroecosystem comprised of approximately 25,000 ha (63,000 acres) of mixed cropping systems and natural spaces in southern Portage County, Wisconsin (Fig. 1). All potato acreage from the 1997 and 1998 growing seasons was identified from field maps provided by growers.

Geographically referenced point data collected by Sexson and Wyman (2005) was digitized and projected into a GIS using Wisconsin Transverse Mercator, 1983.

In the spring of 2008, potato fields were selected from a much larger area, approximately

185,600 ha (458,680 acres) in size, that included the greater ‘Central Sands’ processing vegetable production region (Fig. 1). In 2008, grower records were used to identify fields in potato cultivation both in the previous (2007) and current (2008) production year. Sixteen potato fields were randomly chosen from all identified current season potato candidates (n=56). Field edges for both 2007 and 2008 were identified from aerial photography and digitized into a geographic information system (ESRI ArcGIS 9.2).

Identical to sample site selection in 1998, field edges from 2008 were buffered 3 meters inward to ensure sampling would occur within the potato crop. Buffered edges were divided into

16 equidistant sample points based on field edge length and exported into TSC1 Asset Surveyor software version 3.1 (Trimble Navigation Limited, Sunnyvale , CA). Points were projected into

NAD 1983 and uploaded into a backpack GPS with sub-meter accuracy (Trimble ProXL receiver and TSC1 Asset Surveyor Datalogger; Trimble Navigation Limited, Sunnyvale , CA). The GPS unit was used weekly for navigation to sample points and to record data in the field. Information was uploaded into the Asset Surveyor software and post-processed for differential correction using base station data downloaded from the Blue River, WI base station (BLRW) located 38 km from the research region (NOAA 2008). 29

Insect sampling. At each date and sample point, ten randomly chosen plants were evaluated for early colonization pressure using visual inspection for the presence of colonizing, adult stages (Weisz et al. 1996, Zehnder et al. 1990). Count data was recorded on the GPS unit as a sum of each life stage per ten plants for each weekly sampling point.

The majority of fields in 1998 were managed with a systemic, at-plant insecticide (25 of

36 fields), typically a neonicotinoid. In 2008, the majority of sampled fields (14 of 18 fields) were managed with a foliar insecticide program targeting larval stages. Preliminary examination of data indicated average Colorado potato beetle abundance varied by insect management practice (systemic or foliar insecticide use patterns) in each year. In turn, a fixed-factor main effect was included in all subsequent analyses to test the significance of insect management.

Seasonal alignment. In 1998, Colorado potato beetles were counted at sample locations over a single, one week period (26 May to 5 June) in the spring of the growing season, whereas adult beetles were counted weekly at four time points in 2008 (2 June to 27 June). We used an accumulation of degree-days to account for between-year, seasonal variation in sampling dates and align the 1998 data set with the 2008 data set so that comparisons could be made among years. Several studies have utilized accumulated simple degree-days to align annual variation when describing post-diapause Colorado potato beetle emergence from overwintering (Lashomb et al. 1984, Tauber et al. 1994).

30

Simple degree-days were calculated in 2008 as:

( ) [ ]

where Tmax is the daily maximum temperature, Tmin is the daily minimum temperature and Tbase is the ambient air temperature threshold for Colorado potato beetle (10°C, McMaster and Wilhelm

1997, Boiteau et al. 2008, Malloux et al 1988). For both 1998 and 2008, degree-days were calculated from ambient air temperatures logged by the UW-Extension’s Automated Weather

Observation Network station at the Hancock Agricultural Research Station, which is centrally located in the study region (UW-EX 2008). Downloaded data was used to calculate daily degree- days from January 1 for each year. Accumulated degree-days were calculated in R version 2.11.1 using the cumsum function (R Development Core Team 2010). The 2008 sampling week that best aligned with 1998 was selected post hoc for comparative analyses. This study assumes insects measured in both years were early colonizers based on seasonal alignment of accumulated degree-days.

Spatial distribution of potato fields and habitat assessment. Potato fields in the study area were each assigned a unique identifier. Fields were also designated as either a sample field

(current year potato) or a candidate source field (previous year potato). Two separate land use layers were created for the 1998 and 2008. Potato field boundaries were merged with a vector data layer derived from a mosaic of Portage, Waushara, and Adams County, Wisconsin land use layers. Each layer was projected into a common datum (Wisconsin Transverse Mercator 1983), 31

visually validated using aerial photography and checked for spatial integrity with topological

structuring (ArcGIS 9.1).

Land use layers were aggregated from 24 independent classes into nine biologically

relevant classes constituting stable landscape features (Anderson et al. 1976). Datasets were each

assessed for classification accuracy by year with either USDA or County generated orthorectified

aerial photography (Adams Co. 2000 & 2005, Portage Co. 2000, Waushara Co. 2000, National

Agriculture Imagery Program 2000 & 2008).

Rotation distance was defined as the distance, in meters, between a current season potato field centroid and a previous season potato field centroid (Generate Near Distance, ArcGIS). The geometric center (centroid) of target fields was used to reduce complexity of irregularly shaped fields. Distance metrics were calculated as the linear distance from each counted, current-season production field to all possible previous potato fields. The contribution from multiple fields best represents spatial structure within the intensive potato production agroecosystem (Weisz et al.

1996). A maximum search distance of 1,500m from sink to source fields was used as this is consistent with the longest estimated colonization distance reported for early-season adult

Colorado potato beetle (Weisz et al. 1996, Boiteau et al. 2008).

To define the non-crop habitats surrounding source fields, the area of each of the nine land use classes within an extent of 200 meters was quantified (Intersect, ArcGIS). This analysis distance was chosen for several reasons. First, Colorado potato beetle are more likely to utilize these local, non-crop habitats than those further away. This local neighborhood effect fits documented Colorado potato beetle diapause distribution in non-crop habitat in climatically similar regions of the USA (Weber and Ferro 1993). Furthermore, we chose to analyze habitats at this local scale based upon previous arthropod habitat studies in potato and adjacent non-crop 32 habitats (Werling and Gratton 2008, 2010) where interactions occurred over short distances.

Non-crop habitat components surrounding all irrigated fields within the standardized tri-county land use layer were similarly analyzed to determine habitat composition across all potential potato fields within the growing region.

GIS data for each field (i.e. field areas, land use areas, and rotation distances) was exported from the ArcGIS file geodatabase and Proc Sort and Proc Merge (SAS 9.3.1) procedures were used to reshape and aggregate land use data from individual polygon attributes to the field level. All remaining data management and analysis was performed in R, version

2.11.1 (R Development Core Team 2010) using the base distribution package. Functions used in the analysis are available in the base package of R unless otherwise noted. Preliminary statistics were generated examining the average habitat composition surrounding fields in 1997, 2007 and for all irrigated fields in the growing region using the tapply function.

Calculation of distance and local landscape characteristics. To better understand relationships between the Colorado potato beetle abundance, distance from previous year potato and habitat composition, we simplified landscape complexity by making three specific modeling assumptions. First, we assumed that previous year’s potato less than 1,500 meters away from current year potato was the principal source of Colorado potato beetle in the landscape (Weisz et al. 1996, Boiteau et al. 2005). Second, forested habitats adjacent to previous year’s potato serve as potentially important overwintering habitats in temperate regions (Wyman et al. 1994,Weber and Ferro 1993, Noronha and Cloutier 1999). Finally, grass-based, non-crop areas may be a significant annual source of beetles based upon anecdotal observations by Wisconsin potato growers. 33

Four input variables were built to describe potato beetle colonization as a function of

distance from multiple previous potato fields (Supplementary Table 1). Components used in each

metric were linear distance between sample field and each previous potato field within 1,500 m.

All metrics used an inverse distance weighting strategy for calculation.

For example:

∑ ( )

dist = ∑ ( )

where d is the linear distance between the sampled field and a previous potato field, and this value was calculated for all sample – previous year field combinations. Metrics dist2 and dist2a used a squared, inverse weighting function thereby increasing the importance of closer previous potato fields. Metrics dista and dist2a had each previous potato field area (ha) inversely weighted and incorporated into the numerator of the metric. Weighted previous potato field area was designed to increase the importance of larger fields (Supplementary Table 1).

Area of forest, grassland and transportation corridor (minimally managed grassy ditches) habitats (ha) were summed for all previous year potato fields. All paired combinations plus the three components together were summed resulting in seven unique habitat area totals. Each of seven area totals was relativized as the ratio of measured habitat to field area. The seven combinations of these three habitats represent areas that have previously been suggested as suitable or preferred habitats for Colorado potato beetle diapause (Wyman et al. 1994,Weber and

Ferro 1993). 34

Statistical analysis. Poisson regression models were used to test the effect of non-crop overwintering habitat and rotation distance on mean adult Colorado potato beetle counts in potato (McCullagh and Nelder 1989). Preliminary analyses examined how year and management and their interaction related to Colorado potato beetle abundance. These analyses indicated fixed factors for year and management would satisfactorily account for differences in counts from

1998 and 2008. Analyses also indicated an interaction term between year and insect management was not required. The first series of models were used to examine if the distance between previous and current year potato related to observed Colorado potato beetle abundance. We chose to model the response, Colorado potato beetle count data (1998 and 2008), as total field count (adult beetles per 160 plants) with an offset for sample points per field (Venerables and

Ripley 2002). The Poisson regression model used has the form:

( )= X’β + log(fi) + ei

X’β = β0 + β1 x1i + β2 x2i + β3 x3i. + β4 x3i* x2i

where β0 is the intercept and β1, β2, β3,and β4 represent the regression coefficients for year, insect management, distance to previous potato, and the distance by year interaction, respectively. The term fi represents the sample number per field. Four models were fit, each with a different distance metric (β3 for x3 = dist, dist2, dista, or dist2a) to determine if distance alone or weighted by previous potato area influenced Colorado potato beetle abundance.

A second series of models were used to examine if the proportion of selected non-crop habitat surrounding previous potato influenced Colorado potato beetle abundance. This second 35

set of models had four regression coefficients corresponding to the intercept (β0), year (β1), insect management (β2), and a local landscape characteristic (β3). Here again, seven different models were fit, each with a different local landscape characteristics to determine if higher Colorado beetle counts were associated with specific landscape attributes or combinations of landscape attributes.

Finally, a series of models were developed to explore if including a combination of distance and local landscape characteristics would better describe Colorado potato beetle counts.

The four local landscape characteristics parameters describing the greatest amount of Colorado potato beetle count variability (i.e. Grassland, Forest + Grassland, Grassland + Transportation, and Forest + Grassland + Transportation) were selected and combined with the distance metric that described the greatest variability in beetle count (i.e. dist2). The final set of models had regression coefficients corresponding to the intercept (β0), year (β1), insect management (β2), distance metric (β3), local landscape characteristics (β4), distance metric by year interaction (β5), and the local landscape characteristics by distance interaction (β6). In these models, the same distance metric was always used, but each model contained a different local landscape characteristic (β4) (i.e. Grassland, Forest + Grassland, Grassland + Transportation, Forest +

Grassland + Transportation).

Poisson regression models were fit in R using the glm function with a log-link and an offset for sample number (family: quasipoisson) (package MASS: Venerables and Ripley 2002,

Zeileis et al. 2007). Parameter estimates (±SE) and (F) test statistics were extracted using the summary function. Each tested model was evaluated by analysis of deviance using the anova function. Test statistics compared reductions in residual deviance for each parameter added to the model sequentially. Goodness-of-fit estimates were calculated as pseudo-R2 values (pseudo-R2 = 36

1-(variance of residuals/total variance)) from deviance estimates (Faraway 2005). All tested full model variables from the third set of models were correlated directly to count data using

Pearson’s product-moment correlation with the function cor.test function (method “pearson”).

Results

Landscape characteristics. Our analysis of potential overwintering habitats of Colorado potato beetle characterized the proportion of each land use type available for diapause within 200 m of previous year’s potato. Land use data extracted from a GIS allowed for the identification of nine habitat types that commonly surround irrigated agricultural fields in the Central Sands region of Wisconsin (Table 1). Dominant habitat components were irrigated cropland, non- irrigated cropland and mixed deciduous forest.

Colorado potato beetle counts. The sampling interval in 2008 occurred much later in the calendar year than when counts were taken in 1998. Counts taken in the 1998 season occurred between 181-229 accumulated degree-days (26 May to 5 June). During 2008, the sampling interval occurred nearly two weeks later between 195-232 accumulated degree-days

(16 June to 21 June). Mean field count in 1998 averaged 2.5±2.7 adult Colorado potato beetle/per 160 plants (min. 0.63, max. 13.4) and 5.3±2.7 adult Colorado potato beetle/per 160 plants (min. 1.1, max. 9.7) in 2008. Colorado potato beetle count means differed significantly between years (F = 11.26; df = 50; P = 0.00155). Mean field count in sample locations treated with foliar insecticides averaged 2.7±1.4 adult Colorado potato beetle/per 160 plants (min. 0.38; max. 4.6) in 1998 and 5.6±2.6 adult Colorado potato beetle/per 160 plants (min. 1.1; max. 9.7) in

2008. Mean adult Colorado potato beetle counts in fields treated with at-plant, systemic insecticides averaged 2.1±2.9 adult Colorado potato beetle /per 160 plants (min. 0.63; max. 13.4) in 1998 and 4.3±3.2 adult Colorado potato beetle/per 160 plants (min. 1.3; max. 7.9) in 2008. 37

Fields managed with foliar insecticides did not differ significantly from those managed with

systemic insecticides (F = 0.79; df = 49; P = 0.378). The year by insect management interaction was not significant (F = 0.0029; df = 48; P = 0.957). Insect management parameters were not significant in any instance when tested in full models (Tables 3, 4, and 5).

Effect of distance to previous potato. In 1998, the average distance to all possible previous potato fields within the 1,500 m extent was 995 m (±339; min. 89; max. 1498) and in

2008 this distance averaged 895 m (±362; min. 382; max 1497) (Table 2). Among the proposed rotation distance models included in this analysis, models examining distance described the most variability in Colorado potato beetle counts (Table 3). The mean Colorado potato beetle count per field regressed best against the inverse distance weight parameter, dist2. The resulting model described approximately 38.9% of variation in count with a significant interaction parameter of dist2 and year (F = 8.59; P = 0.0052). The parameter, dist, described a similar amount of CPB count variation at 38.5%. The interaction between of dist and year was also significant (F =

2.793; P = 0.00752). Model parameters including a source field area component, dista and dist2a

parameters, were not significant (Table 3).

Effect of overwintering habitat adjacent to previous potato. Seven models were

generated to explore the relationship between relativized landscape parameters describing non-

crop diversity surrounding previous potato fields within 1,500 m and associated Colorado potato

beetle counts. Model fits described between 27.1% and 28.1% of the total variance in Colorado

potato beetle counts (Table 4). No local landscape described a greater proportion in adult count

and all landscape characteristics performed similarly.

Combining distance and local landscape characteristics. Models examining both

landscape and distance together described between 44.2% and 46.5% of the total variation in 38

Colorado potato beetle counts (Table 5). All models containing both the dist2 parameter and dist2 X year interaction were significant, however the local landscape characteristics alone were not significant. All local landscape characteristics containing Grassland were negatively correlated with Colorado potato beetle count and were significant at the P < 0.1 threshold (Table

6). Correlation of Grassland +Transportation to Colorado potato beetle count was highly significant (r = -0.3; t = -2.225; df = 50; P = 0.0306).

Discussion

Several studies have reported that rotation away from the nearest, previous year’s potato crop to be an effective strategy to reduce Colorado potato beetle colonization and associated damage (Lashomb and Ng 1984, Voss et al. 1988, Follett et al. 1996, Sexson and Wyman 2005,

Boiteau et al. 2008). , larvae, and adult stages of the Colorado potato beetle lifecycle have been measured to describe colonization and damage in potato (Lashomb and Ng 1984, French et al. 1993, Weisz et al. 1996, Blom and Fleischer 2001, Boiteau et al. 2008). Here, adult counts were modeled to represent the typical life stage scouted by growers early in the season. Specific to Wisconsin, Sexson and Wyman (2005) illustrated that adult Colorado potato beetle count varied with rotation distance from the nearest previous potato using a categorical distance analysis. Results of that study indicated beetle abundance was significantly less when current season potato was rotated greater than 400m from previous potato. We have further refined the

Wisconsin model by examining beetle abundance as a continuous variable and developed a distance metric that integrated colonization risk from multiple, previous potato fields (Weisz et al. 1996). In many cases, distances between sample fields to multiple, previous potato fields were very similar (Table 2), providing little justification for the single nearest potato field modeling strategy (Boiteau et al. 2008). Weisz et al. (1996) also estimated the maximum dispersal distance 39

for post-diapause, adult Colorado potato beetle to be 1,500m. This distance informed our search

criteria for selecting fields to be included in the calculation of our distance metric. The use of our

distance metric as a continuous variable yielded a relationship between beetle abundance and

distance to previous potato for the 1998 dataset that was consistent with the findings of Wyman

and Sexson (2005).

In the current study, we observed a significant distance by year interaction indicating the

relationship between Colorado potato beetle counts and distance to previous potato varied

between years of this study (Table 3). Specifically, distance to previous potato related to beetle

counts in 1998, but not in 2008. Since sample field distances to all possible previous potato fields

were very similar between years, this suggests that other factors could influence Colorado potato beetle abundance. In the current study, we initially used distance metrics that integrated the contribution of multiple previous year potato fields as predictors of Colorado potato beetle abundance in the current season potato. However, this approach ignored the spatial context of a potato field and assumed the landscapes surrounding sample fields, farms, and regions were comparable. It has been reported that colonization success in the potato agroecosystem may be influenced by a variety of factors such as insect management practices, soil conditions, rotation crops, diapause habitat availability, area of previous potato, crop phenology and landscape

(Ushatinskaya 1978, Lashomb and Ng 1984, Kung et al. 1992, Weber and Ferro 1993, Weisz et al. 1994 & 1996, Boiteau et al. 2008). Therefore we expanded our modeling approach to include measures of previous potato acreage and suitable overwintering habitats surrounding previous potato.

We developed two distance metrics, dista and dist2a, which incorporated inverse field area to evaluate the potential importance of larger field areas. Our hypothesis was that Colorado 40 potato beetle populations would increase as acreage increases when coupled with weighted distance to current potato. However, previous year potato acreage did not interact with shorter rotation distances to increase average Colorado potato beetle counts in either 1998 or 2008

(Table 3). These observations indicate that greater previous potato acreage did not increase the number of colonizing insects when compared to fields of a smaller size at a similar distance.

Thus, results do not support the field area hypothesis; nearby potato fields of greater size in the previous year did not affect overall Colorado potato beetle abundance. One possible explanation for this result is that acreage of current season potato may have masked the effect of field size in this analysis. Selected study fields in this investigation which occurred in areas of high, previous year potato, tended also to coincide with the greatest density of potato production. Weisz et al.

(1996) reported that higher densities of current year potato in the landscape has the effect of diluting Colorado potato beetle abundance in measured sample fields.

Specific habitats types adjacent to previous potato could, in part, explain the lack of observed relationships between Colorado potato beetle abundance and distance to previous potato in some years. Overwintering (pre-diapause) habitat selection by adult Colorado potato beetle has been documented in several studies and have reported that wooded field boundaries adjacent to potato were principle diapause habitats for the Colorado potato beetle (Voss and

Ferro 1990, Weber and Ferro 1993, Wyman et al. 1994, Follett et al.1996, Hoy et al. 1996,

Noronha and Cloutier 1999). Notably, Noronha and Cloutier (1999) observed that adult Colorado potato beetle dispersed toward field margins where overwintering mortality would be reduced when compared to individuals overwintering within the field and. They hypothesized that the annual migration to adjacent, non-crop habitats was a behavior to avoid the cold, in-field soil temperatures that increase overwintering mortality rates (Noronha and Cloutier 1999). A limited 41 historical association between the Colorado potato beetle and cultivated potato, however, reduces the chance of this strategy being genetically fixed in numerous Colorado potato beetle populations over several regions (Boiteau et al. 2003). Dispersal from managed potato to non- crop habitats is more likely driven by reduced host plant quality (e.g. cultivated potato) as the growing season progresses (May and Ahmad 1983).

In the current study we hypothesized that a higher density of suitable, non-crop habitat would complement the proximity of previous potato habitat by supporting higher populations of

Colorado potato beetle in current season potato (Dunning et al. 1992). However, we found that the inclusion of a local landscape characteristic in our regression models only described a minor proportion (ca. 7%) of the variability in Colorado potato beetle abundance when included with other explanatory variables (i.e. distance metric, management and year) (Table 6). Although these candidate overwintering habitats adjacent to previous potato only described a limited amount of variability in beetle colonization, we did observe a negative relationship between mean Colorado potato beetle count and local landscape characteristics (Table 4). Though not strongly correlated, local landscape characteristics containing Grassland components were negatively correlated to beetle counts (Fig. 2). Landscapes surrounding previous potato in 1997 and 2007 show a large range of non-crop habitats documented to be overwintering habitats for

Colorado potato beetle (Table 1). Negative trends in Colorado potato beetle abundance in association with previous potato fields surrounded by grassland suggests either the potential for reduced overwintering survivorship or perhaps the inability to successfully disperse from or within these grass-based habitats. One potential explanation, suggested by Weisz et al. (1994), results from the Colorado potato beetle’s inability to navigate densely planted crops, such as winter wheat, planted along potato field margins, which significantly reduced spring colonization 42 in potato. Another explanation, suggested by Szendrei et al. (2009), indicates that greater habitat complexity surrounding current potato may reduce Colorado potato beetle abundance. Non-crop habitats with high plant densities may impede successful emigration from diapause habitats resulting in an apparent reduction in Colorado potato beetle abundance. Accounting for habitat diversity between previous and current year potato may further explain differences in Colorado potato beetle abundance. Low beetle counts in both years of the study may have reduced the ability to measure a significant landscape effect. Observed beetle abundance is typical for early colonizing populations in our region. Measures of insect pressure over several weeks may increase the probability of seeing landscape effects. Use of historical scouting data collected by pest practitioners could be a reasonable way to stratify sampling locations into high and low risk fields.

One alternative hypothesis explaining the lack of a relationship between Colorado potato beetle abundance and distance to previous potato in 2008 may be the presence of suitable host plants (e.g. volunteer potato) in the environment. Volunteer potatoes growing in other crops (e.g. corn, carrot) are known to attract Colorado potato beetle (Boydston and Williams II 2005,

Williams II and Boydston 2006). High numbers of volunteer potato may arrest overwintered

Colorado potato beetle populations in previous year potato fields and limit their dispersal to current season potato (Caprio and Grafius 1990, Williams II and Boydston 2006, Metzger et al.

2008). An estimated 106,000 to 460,000 tubers per hectare remain in the soil following commercial potato harvesting, many of which can become volunteer potato plants (Boydston

2001, Lutman 1977, Perombelon 1975). Lutman (1977) documented that sustained temperatures below -2°C are required for adequate winter-kill of small potato tubers not collected during harvest. During the winter of 2007-2008, there were 21 consecutive days where the average soil 43 temperature (5cm) was below zero, however, none of these temperatures fell below the -2°C threshold (-0.37±0.46, min. -1.52, max. -0.01). By comparison in the 1997-1998 winter period, there were 88 consecutive days below zero several of which were below -2°C (-1.15±1.14, min. -

5.95, max. -0.05) (UW-EX 2008). Anecdotally, significant weed management problems arose in several commercial processing vegetable crops (e g. sweet corn, peas, and snap beans) in 2008 associated with volunteer potato plants. Thus, the presence of volunteer potato in the environment may explain differences in beetle response to distance during the 2008 season.

In Wisconsin, the Areawide Management Program proposed by Sexson and Wyman

(2005), has been a cultural management-based approach designed to limit Colorado potato beetle damage at the landscape scale. One challenge to effectively implement this effort has been the lack of coordination necessary to ensure rotation requirements are satisfied. Producers and land managers have anecdotally noted several, unanticipated challenges including a lack of long- range planning among producers (e.g. neighbors), less than ideal spatial arrangement of irrigated fields, or inconsistencies in crop rotation sequences (2, 3 or 4 year rotation schemes) practiced by different operations. A successful Areawide Management Program for the Colorado potato beetle will require coordinated partnerships among state and local extension, pest scouting practitioners, commodity grower groups and the producer themselves (Faust 2008). A lack of multi-agency coordination in Wisconsin has resulted in limited adoption of the Areawide

Management Program for Colorado potato beetle at the regional scale. Development and deployment of an improved Areawide Management Program requires an improved understanding of the factors that explain patterns of Colorado potato beetle dispersal and colonization in potato. A renewed adoption of an Areawide Management Program would also demand greater harmonization of currently used IPM systems being implemented for a variety of 44

pathogen, nematode, weed and insect problems in the potato crop (Faust 2008). One critical

component that could potentially increase the adoption of an Areawide Management Program

would include a reduction in the acreage required to manage Colorado potato beetle with rotation

(Boiteau et al. 2008). Results of this study provide evidence that long distance rotation of potato

from previous potato alone may be insufficient to reduce Colorado potato beetle abundance in all

years. The role of adjacent habitats (e.g. grassland) may play a role in mediating Colorado potato

beetle colonization in Wisconsin.

Conclusions: Several studies have documented that potato rotation over distance can effectively reduce annual Colorado potato beetle colonization. To our knowledge, no studies have attempted to combine the effect of rotation distance and the composition of diapause habitats surrounding the previous year potato crop. We hypothesized that abundance of specific non-crop habitats surrounding the potato crop may increase the amount of Colorado potato beetle which would colonize potato the following season. Local landscape structure surrounding the previous year potato (e.g. grasslands) did influence Colorado potato beetle abundance. High proportions of grassland habitat negatively affected the abundance of Colorado potato beetle in current season potato. Our study demonstrated a weak, negative association between grassland landscapes and Colorado potato beetle abundance. From a pest management perspective, the observed grassland effect may not serve as strong predictor of reduced adult Colorado potato beetle populations. In Wisconsin, two recent studies have shown increased levels upon

Colorado potato beetle eggs by natural enemies when high proportions of grassland areas are prevalent surrounding potato (Werling and Gratton 2008, 2010). Conservation of stable, grassland habitats surrounding commercially irrigated fields may further limit the ability of

Colorado potato beetle to colonize potato by impeding their ability to successfully emigrate from 45 these areas. Additionally, results of this study provide evidence that long distance rotation of potato from previous potato alone may be insufficient to reduce annual Colorado potato beetle abundance. Integration of field size and distance did not significantly describe Colorado potato beetle variation in abundance. The results further suggest that there are limited relationships between local landscape factors and rotation distance when describing Colorado potato beetle abundance in the potato crop 46

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Zeileis, A., C. Kleiber, and S. Jackman. 2007. Regression models for count data in R. Research Report Series (Report 53). Department of Statistics and Mathematics, Wirtschaftsuniversität, Wien. Table 1. Average habitat composition (means±SD) surrounding the first 200 m of 1997 and 2007 potato fields within 1,500 m of sampled potato fields in 1998 and 2008.

1997 Potato (n = 47) 2007 Potato (n = 33) All Irrigated Fields (n = 1762)

Habitat Classification avg. area (%)* min. max. avg. area (%) min. max. avg. area (%) min. max. Irrigated crop land 52.4 ± 20.3 11.6 90.4 60.4 ± 23 8.8 99.2 42.5 ± 25.4 0 99.5 Tables and Figures Non-irrigated crop land 10.5 ± 8.5 0 35.0 9.3 ± 11.6 0 49 11.8 ± 13.5 0 88.1

Pasture 0.2 ± 0.7 0 3.7 0.2 ± 1.4 0 7.8 0.6 ± 2.8 0 40.5

Herbaceous grassland 6.8 ± 7.5 0 32.4 4.7 ± 5.5 0 18.7 7.5 ± 9.1 0 71.4

Mixed deciduous forest 17.2 ± 14.8 0 46.4 13.9 ± 14 0 49.2 21.7 ± 19.4 0 99.4

Coniferous forest 2.7 ± 5.5 0 27.1 3.5 ± 6.7 0 33.1 4.3 ± 8.7 0 57.2

Surface water 0.9 ± 1.3 0 5.0 0.4 ± 1.2 0 6.2 0.3 ± 1 0 10.4

Transportation corridor 5.2 ± 3.5 0 17.5 4.1 ± 3.3 0 15.3 6.2 ± 3.7 0 27.3

Urban - residential 4.2 ± 11.4 0 69.9 3.6 ± 4.8 0 17.7 5 ± 5.9 0 61.5 *Average percent habitat composition surrounding all previous potato within 1,500 m of sampled current year potato fields 52

53

Table 2. Average Colorado potato beetle adult counts (means±SD) and distance between sample field and all possible previous potato fields in 1998 and 2008.

Distance (m) between sample and previous year’s potato fields Pest Average adult Year Field management count (no./160 method plants ±SD) Field Field Field Field Field Field Field Field Field 1 2 3 4 5 6 7 8 9

1998 1 systemic 1.6 (2.9) 760 ------2 systemic 5.8 (5.8) 504 932 ------

3 systemic 6.4 (5.7) 367 760 819 1029 1442 - - - -

4 foliar 3.5 (2.9) 347 808 896 ------

5 foliar 1.7 (2.0) 796 905 1004 1142 1142 - - - -

6 foliar 0.9 (1.4) 1354 ------

7 foliar 1.4 (1.3) 880 1351 1486 ------

8 systemic 0.1 (0.3) 261 523 893 1001 1115 1147 1409 - -

9 systemic 0.6 (0.7) 399 795

10 foliar 2.3 (2.9) 775 932 1042 1048 1104 - - - -

11 systemic 1.4 (2.1) 602 701 753 995 1030 1046 1146 1202 -

12 systemic 3.4 (4.1) 364 395 1028 1129 1439 1448 - - -

13 systemic 1.2 (1.8) 863 1196 1230 1259 - - - - -

14 systemic 0.8 (0.8) 1129 ------

15 systemic 0.6 (1.5) 1639 ------

16 systemic 2.2 (2.9) 478 579 1222 ------

17 foliar 0.4 (0.6) 728 1057 1231 1425 - - - - -

18 systemic 1.2 (1.2) 901 1152 1429 1486 - - - - -

19 foliar 4.3 (4.3) 399 667 1012 1035 1128 1245 1260 1311 1498

20 systemic 3.3 (1.9) 862 1421 ------

21 foliar 3.8 (2.5) 715 1461 ------

22 systemic 0.1 (0.3) 822 1133 1404 ------

23 systemic 0.3 (0.5) 1124 1182 1480 ------

24 systemic 13.4 (6.1) 373 485 828 1100 1118 1279 - - -

25 systemic 1.3 (2.0) 603 1277 1321 ------

26 systemic 0.8 (1.3) 783 1025 1122 1137 1426 - - - -

27 foliar 4.6 (2.0) 588 1089 1282 1255 - - - - -

28 systemic 0.6 (0.6) 439 444 913 1352 - - - - -

29 systemic 3.1 (2.6) 472 1355 ------

30 systemic 0.8 (1.0) 3132 ------

31 foliar 3.1 (2.8) 1772 ------

32 foliar 3.4 (3.2) 89 813 1423 ------

33 systemic 2.7 (2.9) 552 1417 ------

34 systemic 0.4 (0.6) 1470 ------

54 Table 2 continued,

35 systemic 0.1 (0.5) 1052 1395 ------

36 systemic 0.4 (0.6) 1135 ------

2008 37 foliar 0.6 (0.6) 1634 ------38 systemic 1.3 (2) 821 ------

39 systemic 7.9 (10.8) 561 ------

40 systemic 1.9 (2.3) 770 996 ------

41 foliar 8.8 (3.9) 2031 ------

42 foliar 5.8 (2.6) 382 ------

43 foliar 1.6 (2.9) 1068 1354 1403 ------

44 systemic 6.2 (6.8) 805 1243 ------

45 foliar 1.1 (1.8) 539 862 1469 ------

46 foliar 7.7 (6.5) 388 735 1067 1266 - - - - -

47 foliar 6.9 (5.4) 418 527 1131 1392 - - - - -

48 foliar 3.7 (4.6) 674 801 1216 - - - - -

49 foliar 6.0 (4.6) 748 1497 ------

50 foliar 9.7 (4.1) 1665 ------

51 foliar 4.0 (4.2) 417 ------

52 foliar 6.4 (3.1) 499 ------

Table 3. Results of generalized linear model analyses estimating the influence of distance upon Colorado potato beetle counts.

Parameter a dist dista dist2 dist2a

β0 - Intercept 2.14*** (0.442) 1.004*** (0.259) 1.96*** (0.377) 1.003*** (0.259)

β1 - year2008 -0.692 (0.541) 0.588 (0.294) -0.477 (0.471) 0.589 (0.294)

β2 – insect managementsystemic -0.152 (0.25) -0.191 (0.283) -0.177 (0.246) -0.191 (0.283)

β3 – Distance metric -0.00131** (0.000483) -0.000287 (0.000405) -0.0012** (0.000431) -0.00285 (0.000404)

β4- - β3 x year2008 0.00156** (0.000559) 0.000531 (0.00045) 0.00144** (0.000506) 0.000528 (0.000449)

Evaluation

Residual deviance 1260.2 1469.9 1252.2 1470.3

Residual d f. 47 47 47 47 pseudo-R2 0.385 0.282 0.389 0.282

F-statistic 8.404 1.673 8.591 1.661 p-value 0.00567 0.2022 0.0052 0.2037 a Parameter estimate differs significantly from zero (*, P < 0.05; **, P < 0.01; ***, P < 0.001) 55

Table 4. Results of generalized linear model analyses for habitat influence upon Colorado potato beetle counts.

Forest Forest Grassland Forest + Parameter a Forest Grassland Transportation + + + Grassland + Grassland Transportation Transportation Transportation

β0 - Intercept 1.16*** (0.277) 1.17*** (0.271) 1.19*** (0.302) 1.2*** (0.281) 1.18*** (0.282) 1.22*** (0.287) 1.21*** (0.285)

β1 - year2008 0.679* (0.271) 0.639* (0.273) 0.641* (0.289) 0.653* (0.27) 0.671* (0.273) 0.615* (0.278) 0.648* (0.272)

β2 – insect management -0.277 (0.273) -0.268 (0.288) -0.241 (0.282) -0.282 (0.27) -0.273 (0.274) -0.262 (0.27) -0.278 (0.271) (reference: systemic)

β3 – Habitat metric -0.115 (0.097) -0.328 (0.263) -0.632 (0.569) -0.103 (0.0778) -0.103 (0.0857) -0.271 (0.199) -0.093 (0.0702)

Evaluation Residual deviance 1488.9 1485.9 1493.6 1475.2 1486.2 1472.6 1474.3

Residual d f. 48 48 48 48 48 48 48

pseudo-R2 0.273 0.274 0.271 0.28 0.274 0.281 0.28

F-statistic 1.578 1.664 1.347 1.959 1.633 1.979 1.968

p-value 0.2151 0.2033 0.2516 0.1679 0.2074 0.1658 0.1671 a Parameter estimate differs significantly from zero (*, P < 0.05; **, P < 0.01; ***, P < 0.001) 56

Table 5. Generalized linear model analyses for distance and habitat influence upon Colorado potato beetle counts.

Forest Grassland Forest + Parameter Grassland + + Grassland + Grassland Transportation Transportation

β0 - Intercept 2.11*** (0.374) 2.15*** (0.381) 2.11*** (0.396) 2.14*** (0.388)

β1 - year2008 -0.47 (0.445) -0.398 (0.432) -0.404 (0.446) -0.376 (0.435)

β2 – insect managementsystemic -0.202 (0.236) -0.208 (0.231) -0.188 (0.231) -0.201 (0.231)

β3 –dist2 -0.00109* (0.000426) -0.00107* (0.000418) -0.000978* (0.000436) -0.000104* (0.000424)

β4 – Habitat metric 0.132 (0.758) 0.0436 (0.194) 0.182 (0.513) 0.0511 (0.172)

β5- - dist2 x year2008 0.00125* (0.000487) 0.0012* (0.000473) 0.00113* (0.000487) 0.00116* (0.000476)

β6- - dist2 x Habitat metric -0.000769 (0.00105) -0.000264 (0.000274) -0.000763 (0.000699) -0.000257 (0.000242)

Evaluation Residual deviance 1142.1 1105.6 1095.3 1097.3

Residual d.f. 45 45 45 45 pseudo-R2 0.442 0.46 0.465 0.464

F-statistic 0.5505 0.9374 1.186 1.128 p-value 0.462 0.3381 0.2819 0.2939 a Parameter estimate differs significantly from zero (*, P < 0.05; **, P < 0.01; ***, P < 0.001) 57

58

Table 6. Correlation between distance and local landscape characteristics and mean Colorado potato beetle counts.

95% CI Parameter Correlation t-statistic df p-value Lower Upper dist2 -0.11 -0.372 0.168 -0.784 50 0.4365

Grassland -0.268 -0.504 0.00576 -1.964 50 0.0552

-0.238 -0.479 0.0378 -1.73 50 0.0898 Forest +Grassland

-0.3 -0.53 -0.0297 -2.225 50 0.0306 Grassland +Transportation

Forest +Grassland -0.246 -0.486 0.0293 -1.791 50 0.0793 +Transportation *All values calculated using Pearson’s product-moment correlation

59

Sample Fields N 1998 Potato 2008 Potato Portage County

Waushara County

Adams County

Figure 1. Map of potato field sites in the Central Sands potato production region (shaded in grey) of Wisconsin sampled in 1998 and 2008. 60

A) B) ●

● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Average Adult Count (no./160 plants) 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 2.0 2.5 Grassland Grassland + Transportation

Figure 2. Colorado potato beetle counts (no./160 plants) associated with (A) Grassland and (B) Grassland+Transportation habitats surrounding the first 200 m of 1997 and 2007 potato within 1,500 m of sampled 1998 and 2008 potato. Grassland and Grassland+Transportation are relative measures of habitat abundance calculated as summed area of each habitat divided by area of either 1997 or 2007 potato fields. 61

Supplemental Material

Supplemental Table 1. Distance and local landscape characteristics used to model Colorado potato beetle counts in 1998 and 2008.

Parameter Equation Description

Distance

∑ ( ) Weighted distance from sink field to all dist possible previous potato within 1,500m ∑

∑ ( ) Previous potato area weighted distance

dista between current potato and all possible

∑ previous potato within 1,500m

∑ ( ) Squared weighted distance between current dist2 potato and all possible previous potato fields

∑ within 1,500m

∑ ( ) Area weighted distance between current

dist2a potato and all possible previous potato fields

∑ within 1,500m

Landscape

∑ Forest Ratio of forested area to source field area ∑

∑ Grassland Ratio of grassland area to source field area ∑

∑ Ratio of transportation corridor area to source Transportation ∑ field area

Forest + ∑ Ratio of forested + grassland area to source

Grassland ∑ field area

Forest + ∑ Ratio of forested + transportation corridor

Transportation ∑ area to source field area

Grassland + ∑ Ratio of grassland + transportation corridor

Transportation ∑ area to source field area

Forest + ∑ Ratio of forested + grassland + transportation Grassland + ∑ corridor area to source field area Transportation

62

Chapter 3: Effect of insecticide management history on emergence phenology and neonicotinoid resistance in Leptinotarsa decemlineata (Coleoptera: Chrysomelidae)

63 Abstract: Emergence phenology and fitness attributes of several Colorado potato beetle,

Leptinotarsa decemlineata (Say), populations were measured under field and greenhouse

conditions. Anecdotal observations by producers and pest managers in many locations of the

upper Midwest increasingly suggested that selected populations of Colorado potato beetle were

emerging over a longer time period in the spring and were less sensitive to systemic

neonicotinoids in cultivated potato. These changes in emergence phenology may be related to

changes in systemic insecticide concentration over time. Specifically, a prolonged period of adult

emergence in the spring increases the potential of low dose, chronic exposure to systemic

neonicotinoid insecticides in potato. In 2010 & 2011 our objectives were twofold: 1) establish a

common garden experiment to compare the emergence phenology of Colorado potato beetle

populations uniquely managed with variable insecticide inputs and, 2) measure post-dormancy

fitness of emerged adult beetles from among these selected populations. Cumulative adult emergence was modeled with logistic regression. Results from this study found peak emergence for all populations occurred between 100–175 accumulated soil degree-days (base 10°C). Gender ratios of emerging insects were significantly female biased in three different populations. Adult survivorship and average fecundity between populations differed significantly in both years.

Continued increase and spread of neonicotinoid resistance threatens the economic control of

Colorado potato beetle. The long-term impacts of protracted emergence are currently unknown, but may compromise the efficacy of current and future systemic insecticide registrations.

Key Words: Colorado potato beetle, IPM, diapause, phenology, insecticide resistance

64

Insect dormancy, more specifically diapause, is a physiologically driven interruption of development evolved to overcome long-term extreme conditions, often induced by environmental cues such as photoperiod, host-plant quality, and temperature (Lees 1955, Danks

1987, Koštál 2006, Yocum et al. 2011). In temperate potato production regions of the world, winter dormancy is a critical life history strategy of Colorado potato beetle, Leptinotarsa decemlineata (Say), to avoid unfavorable winter conditions (Tauber et al. 1986, 1994;

Ushatinskaya 1978, Yocum et al 2011). In the autumn of each year, adult insects emigrate toward unmanaged, non-crop field edges bordering the senescing potato crop (Solanum tubersosum L.) where they burrow into the soil to overwinter (Weber and Ferro 1993). Following the diapause phase of dormancy, insects enter a post-diapause quiescence phase, awaiting a resumption of favorable climatic conditions (Danks 1987, Tauber et al. 1986, Leather et al. 1993,

Koštál 2006). As soil temperatures increase, adults depart overwintering burrows and colonize suitable host plants, generally cultivated potato (Lefevere and De Kort 1989, Xu and Long

1997).

Colorado potato beetle remains dormant for approximately three months, though several studies have documented long-term dormancy patterns, with some individual insects remaining in an arrested state for one or more years (Isley 1935, Tauber et al. 1986, Senanayake et al. 2000,

Tauber and Tauber 2002). Often, variability in diapause duration can be closely associated with the presence of suitable host plants in the agroecosystem, especially for specialist herbivores like

Colorado potato beetle (Xu and Long 1997, Skinner et al. 2004). Insects inhabiting more dynamic or unstable environments with unpredictable resources may extend diapause for longer periods to better synchronize with hosts, resulting in a delayed dormancy or protracted

65 emergence phenology (Corley et al. 2004). For potato growers, synchronous Colorado potato beetle colonization is more advantageous resulting in a larger proportion of susceptible life stages present within fields. In contrast, asynchronous emergence and subsequent colonization results in extended egg deposition intervals leading to the presence of multiple larval stadia present simultaneously in the crop. Several of the new, reduced-risk insecticides do not possess the same broad spectrum of activity against all Colorado potato beetle stadia. As a result, growers have continued to use foliar applications of the neonicotinoids, organophosphates and carbamates for control of these asynchronous populations with significant non-target impacts to beneficial arthropods, human health, and the environment.

Understanding the environmental factors that influence insect dormancy and emergence phenology has long been a goal for prediction of annual pest colonization of agricultural crops, and a critical component of effective integrated pest management programs (Tauber and Tauber

1993, Wissinger 1995, Williams and Ferguson 2010). Descriptions of emergence phenology among agricultural pests have typically related accumulating temperature to insect abundance

(Andrewartha 1952, Koštál 2006, Emerson et al. 2009). More recent research provides evidence to suggest other factors, such as insecticide resistance, may affect insect emergence phenology and crop colonization patterns (Carrière et al. 1995, Bovin et al. 2003, 2004).

Over the past two decades, the use of the systemic neonicotinoid insecticides has increased considerably in major and minor agricultural crops (Jeschke and Nauen 2008, Jeschke et al. 2011). Widespread adoption of these insecticides in commercial agriculture has resulted in reports of neonicotinoid resistant insect populations in numerous taxa (Nauen and Denholm

2005, Whalon et al. 2008, Whalon et al. 2012). Though resistance has been documented, little is

66 known about how this widespread adoption may have unanticipated effects on the biology and ecology of pests over time. To date, numerous studies have previously reported declining neonicotinoid concentrations over time in both annual and perennial cropping systems, often focusing on season-long population dynamics of pest species with high reproductive capacity and multiple generations per growing season (Byrne et al. 2005a, 2005b, 2007, 2010; Castle et al. 2005). In cultivated potato, variable concentrations of systemic neonicotinoids in plant tissue following at-plant applications may be one possible explanation for development of Colorado potato beetle resistance (Olson et al. 2004). To our knowledge, few studies have related emergence phenology of a specialist herbivore, such as Colorado potato beetle, to the method in which conventional insecticides are delivered. Moreover, limited information exists describing how insecticide delivery may affect insect life history in an insecticide dependent agroecosystem.

Insecticides have been, and remain a cornerstone for management of four key insect pests of cultivated potato in Wisconsin: Colorado potato beetle; Potato leafhopper, Empoasca fabae

(Harris); Green peach aphid, Myzus persicae (Sulzer); and Potato aphid, Macrosiphium euphorbiae (Thomas). For the past fifteen years, an estimated 85 to 90 percent of all commercial potato acres in Wisconsin utilized an at-plant, systemic neonicotinoid application to manage early season Colorado potato beetle (D. L. Knuteson, personal communication). Although measured resistance to the neonicotinoids has been well documented (Szendrei et al. 2012),

Wisconsin growers continue to rely upon in-furrow, systemic neonicotinoids to manage potato insect pests. Advantages of this use pattern include maximized plant coverage, longer residual within the potato foliage, and limited non-target impacts to beneficial arthropods (Baker et al.

67

2007, Elbert et al. 2008). However, this uniformity and duration of insecticide expression has strongly increased selection pressure over the 18 years of registration of the neonicotinoid class

(Olson et al. 2000; Zhao et al. 2000).

As a result of the long-term reliance on several insecticide classes, many Colorado potato beetle populations are now resistant to nearly all insecticide classes (Radcliffe et al. 1991,

Alyokhin et al. 2008, Whalon et al. 2012). Furthermore, resistance development in Colorado potato beetle may be accelerated by multiple physiological mechanisms, inter-population gene flow, and localized dispersal (Grafius 1995). Historically, management of resistant populations has resulted in more frequent applications, tank mixing of different insecticides, with considerable economic impact to growers (Grafius 1997). Impacts of insecticide resistance are commonly expressed as costs of resistance within populations of insects. Baker et al. (2008) found fecundity to be one third less in neonicotinoid (imidacloprid) resistant Colorado potato beetle populations from Long Island, New York, USA. In a review of Bacillus thuringiensis resistant insects, Tabashnik (1994) concluded that insecticide tolerance in Colorado potato beetle may often result in reduced fecundity, increased overwintering mortality, and prolonged development times; resistance costs that when combined may have a considerable negative effect on population growth potential. In recent years, neonicotinoid resistance of Colorado potato beetle in Wisconsin has become apparent in two ways: first, resistance bioassay data reflects increasing LD50 estimates over time and second, the duration of field level control has decreased significantly in recent years (Huseth and Groves 2011, Szendrei et al. 2012).

Furthermore, anecdotal observations by producers and pest managers further suggest a relationship between protracted emergence and resistant populations. Resistant populations of

68

Colorado potato beetle populations may be better able to withstand the highest titers of in-plant

insecticide by emerging early in the year where more susceptible populations may be emerging

later to temporally avoid these high concentrations. Populations that seem to demonstrate

variable emergence occur in highly intensified portions of Wisconsin’s potato production agroecosystem, where systemic neonicotinoid adoption has been widespread since the registration of imidacloprid in 1995. Acceleration of resistance will occur as late emerging portions of populations are exposed to sub-lethal systemic insecticide doses (Olson et al. 2004).

Over time, the continual exposure of late emerging insects to sub-lethal doses will generate greater resistance levels and compromise the efficacy of current and future systemic registrations. An improved understanding of how resistance may influence pest ecology, specifically emergence phenology, will provide new information to supplement our current understanding of resistance management strategies for systemic use-patterns. In this study, we examined the effects of long-term reliance on three common insecticide delivery methods (e.g. systemic, foliar or mixed application) on adult Colorado potato beetle emergence phenology, fitness, and on insecticide tolerance. We hypothesized that (1) Colorado potato beetle populations exposed to systemic neonicotinoids over several years would emerge from dormancy later and over a longer period of time (2) overwintering mortality would be greater in populations experiencing systemic insecticide applications as a cost of neonicotinoid tolerance,

(3) later emerging insects would be on average smaller and weigh less, and as a direct result of fitness costs related to smaller body size, (4) insects emerging later would be less fecund.

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Methods

Neonicotinoid bioassay. From 2007-2011, baseline imidacloprid susceptibility was measured at 41 locations throughout the seed and commercial potato production regions, near

Antigo and Hancock, Wisconsin, respectively. Consecutive samples from individual fields were often difficult to obtain due to multiple years, crop rotation sequences (e.g., 2-, 3-, or 4-yr potato rotation intervals). As a result, potato fields less than 0.8 km in distance from each other were considered representative of a local Colorado potato beetle population for annual bioassays.

Adult beetles were collected into plastic cups (0.94 L), placed into coolers containing frozen ice packs, and transported to the University of Wisconsin-Madison campus, Madison, WI. Upon arrival, insects were fed greenhouse-grown potato foliage in screen cages maintained in an environmental chamber at 24°C and a photoperiod of 16:8 (L:D) for three days.

Insensitivity to neonicotinoids was assessed with topical imidacloprid bioassays.

Technical grade imidacloprid (97.5%, Bayer Corporation, Kansas City, MO) was dissolved into pesticide grade acetone (Fisher Chemicals, Fair Lawn, NJ), then serially diluted to a range of doses between 0.001-10 ppm. Between five and nine doses were chosen based on preliminary bioassays resulting in 0-100 percent mortality (Zhao et al. 2000, Mota-Sanchez 2006). Adult beetles were divided into equal numbers per dose, each containing no fewer than fifteen insects per replicate. Collected individuals were randomly selected and treated with 1 μL of insecticide solution applied to the first abdominal sternite with a 50 μL syringe equipped with a Hamilton

PB-600 repeating dispenser (Hamilton Company, Reno, NV). Control insects received a 1 μL

dose of pesticide grade acetone alone. Treated insects were placed into 100x15 mm polystyrene

Petri dishes with filter paper (Fisher Scientific, Pittsburgh, PA). Insects were maintained on

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fresh, greenhouse-grown potato foliage in an environmental chamber at 24°C and a photoperiod

of 16:8 (L:D). Bioassay response was measured at day three, five, and seven post-treatment.

Insects were classified as alive, intoxicated, or dead. Intoxicated beetles were unable to grasp the

tip of a pencil with all six legs and walk one body length up the pencil (Zhao et al. 2000).

Intoxicated or dead insects were pooled for subsequent statistical analyses.

Experimental site. The site used for overwintering studies was situated in an unmanaged

grassy area bordering a mixed deciduous field boundary with an easterly aspect at the University

of Wisconsin’s, Hancock Agricultural Experiment Station, Hancock, WI. In 2010, the University of Wisconsin-Soil Testing laboratory analyzed twelve aggregate soil core samples (fifteen 30 cm soil cores homogenized per sample) taken in an unaligned grid pattern from the study site. Soil texture was loamy sand that was on average composed of 83.3±1.5% sand, 10.7±2.4% silt, and

6±1.1% clay. In 2011, the study site was shifted 50 m northward along the same field boundary to ensure no overlap of study areas between years.

Cage study populations. Sequential bioassay data from 2007-2010 was used to choose candidate field locations (and associated Colorado potato beetle populations) with known levels of neonicotinoid sensitivity. From this data set, sample locations were selected within 10 km of the Hancock Agricultural Research Station, Hancock, WI. Growers managing chosen field locations were asked to qualify their Colorado potato beetle management among three categories since first neonicotinoid registration in potato (1995-2010): (1) years of neonicotinoid use for beetle control, (2) annual method of pesticide application (e.g. systemic or foliar), and (3) calendar date of planting and first date of foliar application for Colorado potato beetle. Complete management records were available for some but not all locations for all 15 years. Grower

71 reports were compiled to classify three categories of potato beetle management: systemic, foliar, or mixed application strategies. Sample locations were chosen to include two systemic, one mixed and one foliar population for each season.

In the autumn of 2009 & 2010, insects were collected from four potato fields separated by 4-10 km in Wisconsin’s Central Sands potato production region. Three of four populations were represented in both study years. Adult beetles representing the second, or summer generation from each sample location were collected at random in late August (2009: n≈1,946 individuals per population; 2010: n≈2,416 individuals per population). One population,

Systemic-1, did not have potato within a 0.8 km radius of the field location in the fall of 2010. A

5th population, Systemic-2, was selected as a replacement for the 2010-2011 season with similar levels of measured neonicotinoid resistance. Insects were released into greenhouse screen cages and fed greenhouse-grown potato foliage (cv. Russet Burbank) for one full week prior to release at the common garden location. Additionally, a random sample (n=30 insects) from each population was collected annually for autumn sex ratio and body size measurements.

Outdoor screen cages with open bottoms (1.8x1.8x1.8 m) were fixed in a randomized complete block design consisting of four populations in three replicated blocks (Model #1406A,

BioQuip Products, Rancho Dominguez, CA). Cage edges were buried 15 cm deep to limit insect entry or exit. Populations were evenly divided into groups of 750-900 beetles per cage. Beetles were provided greenhouse-grown potato foliage (cv. ‘Russet Burbank’) and were allowed to diapause naturally in undisturbed soil. To allow natural snow accumulation, field cages were removed after one full week of temperatures below 0°C.

72

Post-dormancy emergence. Following snowmelt, cages were reinstalled and checked weekly for emerging adults. After the first recorded adult, insects were collected directly into plastic cups (0.94 L) every other day from May 1 to June 22, 2010 (52 days) & May 17 to June

30, 2011 (44 days). Sample cups were placed in coolers with freezer packs and driven to the

UW-Madison campus. Individual insects were each weighed, sexed, and measured (total length and width). Daily collections were placed into an environmental chamber maintained at 10°C and 0:24 photoperiod (L:D) for 14 or fewer days after collection. At the end of the 14 day cohort sampling interval, cooled insects were moved to a greenhouse maintained at 21.3±1.1°C (min.

18.3, max 26.1) under natural light. Insects were placed into collapsible screen cages blocked in an identical manner as the field study. Cages each received four potted potato plants which were replaced as needed. Each two-week cohort of adults was assortively mated for a 14 day period.

This uniform 14 day oviposition period allowed for comparison among cohort groups and populations. Egg masses were removed from potato foliage daily. Total number of egg masses and eggs per mass were recorded for each cage.

Following five consecutive observations with zero beetles collected in cages, the sampling frequency was changed to once every seven days. Sampling concluded after four consecutive weeks of zero beetles collected. Each cage footprint then had a random 0.5x0.5x0.3 m (length x width x depth) soil sample extracted and sifted through 5.6 mm sieve size market grade screen (4 meshes per linear inch) and all intact insects and insect parts were collected and counted.

Environmental data. We used an accumulation of soil degree-days to account for between-year, seasonal variation in sampling dates. Several studies have previously described

73 overwintering phenology aligned over multiple years of post-diapause Colorado potato beetle emergence data using accumulated simple soil degree-days (Lashomb et al. 1984, Tauber et al.

1994).

Simple soil degree-days were calculated as:

( ) [ ]

where Tmax is the daily maximum soil temperature, Tmin is the daily minimum soil temperature and Tbase is the soil temperature threshold for Colorado potato beetle (10°C, de Kort

1990, McMaster and Wilhelm 1997, Boiteau et al. 2008, Malloux et al 1988). In the spring of each sample year, soil degree-days were calculated from soil temperatures logged at a depth of ten centimeters by the UW-Extension’s, Automated Weather Observation Network station at the

Hancock Agricultural Research Station (UW-EX 2011). For each study year, downloaded data was used to calculate daily soil degree-days beginning January 1. Additionally, using the same basic formula, simple growing degree-days were calculated from January 1 for 1995-2010 using downloaded minimum and maximum air temperatures. Cumulative soil degree-days (SDD) and cumulative growing degree-days (GDD) were calculated using the cumsum function in R version

2.14.1 (R Development Core Team 2010). The duration of Colorado potato beetle control (e.g. first foliar application GDD minus planting GDD), at each grower location from which Colorado potato populations were collected, was estimated and used as a measure of the time until an economic threshold was reached over 15 years at each field location. These estimates

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documented the erosion of neonicotinoid control producers have experienced over the interval of

time since registration (e.g. 1995).

Statistical analysis. Bioassay dose-response results were analyzed against imidacloprid

concentration with a log10 probit regression analysis (Finney 1971, Robertson et al. 2007, PROC

PROBIT, SAS Institute). Fifty percent lethal dose ratios (LD50) and 95% confidence intervals

were calculated to determine relative neonicotinoid susceptibility of field-collected populations

when compared to a neonicotinoid susceptible field population collected at the University of

Wisconsin’s, Arlington Agricultural Experiment Station, Arlington, WI (Robertson et al. 2007).

Imidacloprid tolerance was considered significantly different if 95% confidence intervals of

lethal dose ratios did not overlap.

Cumulative growing degree-days from planting until the first non-systemic insecticide

application across 15 years were compared with ANOVA. Application records by year were

considered a discrete categorical scale response and analyzed as factor-level responses unless

otherwise noted. Saturated GDD models considered all possible population by year interactions;

non-significant parameter terms were eliminated using sequential F-tests with the drop1 function in R. Accumulated growing degree-days at vine kill was used as an endpoint in analyses for fields that received no further insecticide applications for control of Colorado potato beetle.

Duration of control estimates were regressed directly with year as a continuous variable using

ANOVA. The predictor year was scaled to the first year of use of a neonicotinoid within our populations (e.g. year 1995 equals zero) to improve interpretation of regression coefficients.

Parameters were selected backward from a saturated model containing all possible population x

year interactions with sequential F-tests using the drop1 function in R. An ordinary least squares

75

linear regression approach was used to compare the timing of first emergence for each

population, gender, and year (Murtaugh et al. 2012). Emergence differences between genders

within years were compared using Welch two sample t-tests (Murtaugh et al. 2012). Equality of

proportional survivorship between populations was compared with chi-squared tests using

prop.test (Mead et al. 2002, Dalgaard 2008). Population survivorship between years was

analyzed with Pearson’s chi-squared tests and Yates’ continuity correction using chisq.test in R.

To compare emergence patterns for each population and gender within each year, a

nonlinear regression analysis was used to fit three-parameter, logistic regression growth curves

to cumulative Colorado potato beetle counts over time. The cumulative sum of male and female

Colorado potato beetle captured in each cage was calculated for each sample date for all cages

using the function cumsum in R. The nonlinear model for the estimated cumulative Colorado

th potato beetle emergence (Yij) on the i observation at SDDij after January 1 is:

(( ) )

where Asym is the asymptotic height of the growth curve (e.g. total beetle abundance),

Xmid represents the inflection point of the curve (soil degree-days when cumulative Colorado

potato beetle captures = Asym/2), and Scal is the soil degree-days surrounding peak emergence of a population (≈ 25-75%). Preliminary visual examination of the data indicated differences among populations, genders, and years. Model fitting exercises revealed an overall nonlinear

76

mixed model which failed to converge, thus individual nonlinear models were fit to each level of

population, gender, and year for phenology comparisons.

Initial model fitting assumed within-group errors (εij) were independently distributed as

N(0,σ2). Examination of residual plots for these models indicated a serial accumulation of errors

associated with cumulative Colorado potato beetle captures as SDD increased.

Within-group errors were allowed to be heteroscedastic with the variance model:

( )

δ which corresponds to the variance function g(vij, δ) = |vij| . Here, δ was stratified by

δsij ij population and year, resulting in the variance function of g(vij, δ) = |vij| with s allowing for year and population variation. Nonlinear mixed effects models were fit in R using the gnls function (Package nlme: Pinheiro and Bates 2000) and parameter estimates and confidence intervals were extracted using summary, conf.int, and anova functions. Parameter estimates were considered significantly different if 95% confidence intervals did not overlap.

Male and female Colorado potato beetles were summated across all sample dates for each year and population using the tapply function. Total counts for each population by year tested an equal sex-ratio hypothesis (e.g. 1 male: 1 female) for autumn and spring Colorado potato beetle samples. Likelihood ratio G-tests for categorical data tested the departure from the 1:1 sex-ratio hypothesis approximated on a chi-square distribution (Sokal and Rohlf 1995, Wilson and Hardy

2002). To better understand how variability in size and weight may have influenced emergence patterns of each population, a simple linear regression modeling approach was used to associate

77 differences in gender, size and SDD. Prior to response parameter selection, Pearson’s product- moment correlation was used to determine similarities between measured individual traits: gender, weight, length, and width. Paired measures were all highly correlated, thus we chose to regress only insect weight as a response to individual size data by SDD. Emergence weight differences between populations and gender by SDD were determined by ANCOVA. Finally, total number of females captured, total egg masses deposited over the 14 day oviposition period, and average eggs laid per female from each cohort was assessed using simple linear regression for each population and year. Differences among populations by cohort group were determined by ANOVA. When appropriate, response variables were transformed (log x+1) to satisfy assumptions of normality. Means were separated post-hoc using Tukey’s honestly significant difference tests. All linear model estimates and test statistics were extracted using the lm, aov, cor.test (method “pearson”), anova, TukeyHSD and summary functions in R.

Results

Neonicotinoid bioassays and grower records. From 2007-2011 our laboratory conducted a comprehensive, statewide survey of 41 Colorado potato beetle populations for resistance to neonicotinoids. From these populations a set of five was selected to study the relationship between management history, emergence phenology, and neonicotinoid tolerance

(Table 1). In recent years, potato producers statewide have noted that the number of days over which the at-plant, systemic insecticides provide adequate control has steadily declined. To quantify this loss of efficacy, we asked cooperating growers, from which the five common garden populations were collected, to provide their first date of foliar insecticide application records for the past 15 years since registration of the first neonicotinoid in potato (Fig. 1; Table

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S1). From these data we were able to quantify, in a relative manner, reductions in efficacy of neonicotinoids in Wisconsin potato fields over time. On average, growing degree-days (GDD) at planting for all locations was 43.9±62.1 GDD (min. 0; max. 301.85). When locations were pooled, planting dates over 15 years did not occur on significantly different growing degree-days in the spring (F=0.55; df=15,44; P=0.8949). Independently, selected field locations were planted at significantly different growing degree days over 15 years (F=78.29; df=4,55; P<0.0001).

More important for growers, timing of first non-systemic Colorado potato beetle application averaged 543.3±207.7 GDD (min. 201; max. 1202.4) and timing of the first post-planting applications, over 15 years, was significantly different when all locations were pooled indicating

Colorado potato beetle phenology may result in annually variable colonization events (F=4.028; df=15,44; P=0.000153). Over the same time interval, the length of residual control of the

Colorado potato beetle was highly variable over the 15 year period, occurring on average at

499.4±200.9 GDD (min. 194.7; max. 1181.5) and differing significantly among years (F=5.894; df=15,44; P<0.0001). When considered a continuous variable scaled to years of control since neonicotinoid registration (1995-2010), a significant main effect of population and year existed

(F= 8.211; df= 5,54; P<0.0001; Fig. 1), but a year by population interaction was not significant

(F=1.154; df= 9,50; P=0.342). On average, populations lost 34.88 GDD of neonicotinoid control per year since 1995 (Fig. 1). When Julian days (e.g. calendar days after January one) were regressed against duration of control, populations lost an average of 3.32-d per year since 1995 or about 50-d of control since neonicotinoid registration (F= 15.28; df= 5,54; P<0.0001).

Emergence and survival. Seasonally, 2010 was a much warmer spring earlier in the year when compared with 2011, and first detections of post-dormancy, adult Colorado potato

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beetles differed significantly between years, occurring on average at 74.5 and 37.9 SDD on 1

May 2010 and 17 May 2011 respectively (t=9.706; df =32.01; P<0.0001). Timing of first

emergence of individual populations did not differ significantly in 2010 (F=0.46; df=3,20;

P=0.7114), whereas significant differences among populations were observed in 2011 (F=5.441; df=3,20; P=0.006692). When Julian date was used as a time scale, emergence patterns differed greatly. A 16-d difference was observed in the average first emergence date between years, with first emergence date in 2011 observed to be 37.63 SDD cooler than 2010 (Table S2). Overall, differences existed among years at all major points in cumulative emergence: a 14-d difference

(24.55 SDD cooler) at 25% emergence, an 11-d difference (28.25 SDD) at 50%, a 10-d

difference (40.45 SDD) at 75%, and a 10-d difference (73.3 SDD) at 100% emergence. Although

annual differences in emergence were apparent, little variation in emergence phenology was

observed between populations within the same year (Fig. 2, Table S2). Furthermore, no

significant gender differences in timing of first emergence occurred in either 2010 or 2011.

Colorado potato beetle survivorship was estimated to be 13.8±6.7% (min. 5.4%; max

23.5%) and 17.8±11.2% in 2011 (min. 5.7%; max 34.7%) in 2010, and 2011, respectively, and

these estimates differed significantly between years (χ2=62.31; df=1; P<0.0001). When compared only within sample year, survivorship was significantly different between populations in both 2010 (χ2=173.69; df=3; P<0.0001) and 2011 (χ2=727.94; df=3; P<0.0001). Within population but among years, survivorship was significantly different in all populations:

Systemic-3 (χ2=98.62; df=1; P<0.0001) and Mixed (χ2=86.48; df=1; P<0.0001) and Foliar

(χ2=107.78; df=1; P<0.0001). Between year differences were not calculated for Systemic-1 or

Systemic-2 due to singular annual observations.

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Logistic growth models were developed to describe emergence phenology of Colorado

potato beetle populations with differing insecticide management histories in 2010 and 2011 (Fig.

3). Emergence of male and female insects was modeled individually for each population and the

average pseudo-R2 value for all models was 0.76 (min. 0.35; max 0.96). Model comparisons

between populations and genders suggest peak emergence (Xmid) occurred at similar

accumulated SDD in both years (Figure 4b). In 2010 peak emergence for all populations

occurred between 87.35-186.96 accumulated SDD (6 May-23 May) and 85.16-139.11 SDD (25

May–2 June) in 2011. Estimated soil degree-days for peak emergence were not different between

subsets of male and female Colorado potato beetle in any population (Table 3; Fig. 3).

Cumulative beetle abundance (Asym) estimates did, however, differ greatly between genders and

populations (Table 3; Fig. 4a). Overall emergence survivorship was similar among populations

and genders in 2010, whereas differences in survivorship were very different in 2011 (Table 3;

Fig. 4a). Sifted soil samples taken at the conclusion of each season produced no live or dead

intact beetles.

Insect size and weight. The relationship among measured body size metrics

demonstrated consistent patterns for each population and gender group. Correlation of width to

length for all measured insects was highly significant (r=0.8523; t=86.118; df=2793; P<0.0001).

Furthermore, insect weight was positively correlated to both length (r=0.8009; t=70.698;

df=2793; P<0.0001) and width (r=0.8012; t=70.78; df=2793; P<0.0001). As a result of strong correlations among body characteristics, we chose to model only insect weight with predictors for gender, population, year and SDD. The final ANCOVA model examining these variables together described 33.13% of the total variation in Colorado potato beetle weight (Table 4).

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Gender ratios and fecundity. Colorado potato beetle gender ratios from autumn-

collected populations did not differ significantly between populations (e.g. all 1 m: 1 f) in either

2009 (χ2=2.5007; df=3; P=0.4752) or 2010 (χ2=0.6421; df = 3; P=0.8867) prior to release into cages. In the spring, populations did not differ significantly in their observed gender ratios in either 2010 (χ2=5.8801; df=3; P=0.1176) or 2011 (χ2=6.2654; df=3; P=0.09939). When testing the distribution of genders within each population, only the population collected from the foliar- based, insecticide program significantly departed from a 1:1 gender ratio in 2010 and was female biased 1:1.57 (Table 5). In 2011, populations from the fields designated as Systemic-2 (1:1.25 m:f) and Mixed (1:1.31 m:f) were again significantly female biased (Table 5).

Total number of females, eggs and egg masses all differed significantly between populations and populations within year (Table 6). In 2010, total eggs per female averaged

38.5±17.3 (min. 14.2; max. 71.1) and 21.3±26.2 (min. 0.4; max. 95.1). Eggs per female were not, however, significantly different between years (t=1.9024; df=19.1; P=0.07231). Egg counts per female varied significantly as a result of a population by year interaction (Table 6). Average female fecundity differed significantly between sample cohort groups within populations for both 2010 and 2011 (Table 7). Only fecundity of the foliar population in 2011 was not significantly different between cohort groups (Table 7). Eggs per mass did not vary between years (t=-0.3272; df=956.42; P=0.7436), nor did they differ within population or among populations by year (Table 6). The average number of egg masses per female was not significantly different (t=1.9172; 18.214; P=0.07103) and averaged 1.9±0.8 (min. 0.9; max. 3.5) in 2010 and 1.1±1.3 (min. 0.01; max. 4.7) in 2011. However, egg masses per female were significantly different between populations and populations by year (Table 7).

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Discussion

In this study, our common garden and greenhouse studies explored dormancy ecology of

Colorado potato beetle, documented this insect’s seasonal phenology in Wisconsin, and related emergence patterns to long-term insecticide management history. Selected populations for our common garden study showed little relationship between management history and the potential for a multiple year dormancy. Initially, low overall Colorado potato beetle survivorship observed among populations seemed to indicate the potential for multiple season dormancy in Wisconsin.

Soil extraction sampling, used to determine if any live insects attempted to remain in dormancy over multiple-seasons, produced no live beetles. This finding departs somewhat from results obtained in the Northeastern and Western U.S. where small proportions of insects (<7%) were found to diapause for multiple growing seasons (Biever 1990, Tauber and Tauber 2002). In those studies, screen cages were replaced annually to determine the proportion of individuals remaining in diapause for one or more years. Although no multiple year diapause patterns were observed for these Colorado potato beetle populations, we did observe variable emergence and survivorship patterns within sample years.

The spring of 2011 was comparatively, a much cooler and wetter spring than 2010, resulting in a slower accumulation of soil degree-days (SDD). When sample years were standardized by Julian date, insects emerged later in 2011, yet far fewer SDD had accumulated than in 2010 (Fig. 2). Though calendar date of first emergence did not align precisely between sample seasons, cumulative SDD values did approximately align with other dormancy studies conducted in similar climatic regions (Lashomb et al. 1984, Mailloux et al. 1988, Tauber et al.

1994). When cumulative SDD was aligned to account for seasonal variability, the rate of post-

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dormancy emergence was similar between 2010 and 2011 (Fig. 2). Selected populations tended

to achieve the first 50% of total emergence over a much shorter SDD interval than the remaining

50% of observations (Supplemental Table 2). Non-linear modeling estimates showed 2010 had

greater variability in peak emergence with confidence intervals ranging over 72.2 SDD (19 days)

when compared to an estimated 59.45 SDD (8 days) in 2011. In this study, total Julian days over

which peak emergence occurred varied considerably between years, but SDD estimates based on

thermal accumulation generally aligned with the expected emergence phenology previously

described in the Great Lakes region (Mailloux et al. 1988, Tauber et al. 1994). Furthermore,

differences in peak emergence time between genders within population were not significantly

different (Fig. 4b). Analyses of peak emergence suggest little evidence for within-season,

prolonged dormancy patterns.

Though there were no distinct relationships between the three management strategies and

emergence phenology, Colorado potato beetle survivorship was different between populations,

years, and genders. In 2010 survivorship was similar between populations with the exception of

the Systemic-1 where an overall survivorship of just 6.25% (Table 2) was observed. In contrast,

survivorship in 2011 was more highly variable, demonstrating both population and gender-level

differences (Figs. 3 and 4a). The two systemically managed populations in 2011 survived at

differing rates, and the single systemic population, Systemic-2, emerged at a much faster rate and

possessed the greatest overall survivorship among all populations tested. Furthermore, bioassays

of this population revealed the highest estimated LD50 values of any population tested in our statewide survey (Table 1). Although fitness costs related to neonicotinoid tolerance may be one possible explanation for observed levels of mortality in this study, our highly resistant population

84 demonstrated little indication of resistance-related mortality. Though management history did not uniformly explain survivorship differences in either year of the study, average survivorship was similar to a previous dormancy study conducted at the Hancock Agricultural Research

Station, Hancock, WI (Milner et al. 1992). Survivorship estimates described by Milner et al.

(1992) were considerably lower than those observed in other temperate, potato growing regions of the United States (Lashomb et al. 1984, Mailloux et al. 1988, Biever 1990, Tauber et al. 1994,

Tauber and Tauber 2002). Colorado potato beetle survivorship in these studies exceeded 50% in many instances, far exceeding that of our Wisconsin common garden experiments. In some cases, high Colorado potato beetle mortality during the dormant period has been related to soil temperatures below 0°C for several consecutive days. Kung et al. (1992) documented that sustained temperatures below -6°C were required for significant winter-kill of Colorado potato beetles in dormancy and further noted the strong temperature buffering capacity of snow cover which may considerably dampen extreme fluctuations in ambient air temperature. In this study, winter conditions at the common garden location did not approach the estimated killing threshold for Colorado potato beetle. At the HAES common garden site in the winter of 2009-2010, there were 80 total days where the minimum soil temperature (5 cm) was below zero, however, none of these temperatures fell below the -6°C threshold (-0.86±0.82; min. -4.18; max. -0.02). By comparison in the 2010-2011 winter period, there were 130 total days with minimum soil temperatures below zero, none of which fell below the -6°C threshold (-0.77±0.68; min. -3.42; max. 0) (UW-EX 2011). Similarities between results of this, and previous overwintering studies in Wisconsin, suggest diapause mortality may potentially be a more significant factor affecting populations than in other potato production regions.

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Differences in size and weight of emerged Colorado potato beetles collected from cages in this overwintering study indicated some potential costs of resistance as a function of management history. Results suggest that the neonicotinoid-susceptible, foliar-managed populations were, on average, heavier over time than populations exposed to longer-term, systemic insecticide management programs (Table 4). Body size has been closely related to mating success and fecundity in several Chrysomelid species; often results indicate smaller insects of either gender tended to be less fit (Boetel and Fuller 1997, Baker et al. 2007, Alyokhin et al. 2008, French and Hammack 2010, 2011). Connecting declining insect body size and weight with fecundity was a critical component of this study, developing an emerging picture of risk periods for egg deposition within the growing season. Average fecundity of populations in our study was significantly greater in earlier cohort groups, this pattern corresponded with greater weight of insects in 2010, however in 2011, cohorts of two populations (Systemic-3 and Mixed) were more fecund as time progressed (Table 4, Table 7). When cohorts were pooled, eggs per female did not present a clear trend with respect to management or resistance estimates (Table

6). Interestingly, the population with the greatest survivorship, Systemic-2, produced the fewest eggs per female and also possessed the greatest estimates of neonicotinoid insensitivity of all populations (Table 1, Table 6). In Colorado potato beetle, connections between insecticide insensitivity and estimated fecundity have been well documented for several other insecticide mode of action (MoA) classes (Argentine et al. 1989, Trisyono and Whalon 1997, Alyokhin and

Ferro 1999). Moreover, Baker et al. (2007) found imidacloprid resistant Colorado potato beetle populations had fewer fitness costs (fecundity, fertility, and larval development rate) when populations were resampled after five years. Such reductions in fitness costs associated with

86 resistant populations may partially explain our inability to infer any direct relationship between insecticide tolerance and long-term management strategies. This stabilization, or reduction in measurable fitness costs within populations over time, may be one possible explanation for observed fecundity differences among populations over time in this study.

Quantitative thermal accumulation models are useful tools to describe temperature- dependent, arthropod life cycles in seasonally variable environments across different populations, locations, spatial scales, and times (Pruess 1983, Tauber et al. 1994, Murtaugh et al.

2012). Several studies of potato agroecosystems have previously reported on the spring emergence patterns of Colorado potato beetle in relation to accumulating spring temperatures as a potential method of predicting patterns of colonization (Lashomb et al. 1984, Tauber et al.

1986, 1994; Mailloux et al. 1988). In some field-collected Colorado potato beetle populations, adults have demonstrated considerable variation in the duration of dormancy, with some individual insects extending diapause over multiple years (Biever 1990, Tauber and Tauber

2002). Over 10 consecutive growing seasons, Tauber and Tauber (2002) characterized prolonged dormancy of adult Colorado potato beetles within several populations collected from cultivated potato in New York, United States. The authors concluded that small portions of most beetle populations remain in dormancy for one or many years as an evolutionary bet-hedging response that improves persistence of beetles in environments with unpredictable host-plant resources.

Flexible insect herbivore life histories containing traits such as prolonged dormancy are critical adaptions to variable host-plant resources or quality (e.g. plant defense compounds or agricultural toxins) in unstable annual agroecosystems (Hare 1983, Xu and Long 1997, Hoy et al.

1998, Kennedy and Storer 2000). Here, we considered insecticide management to be a

87 contributing factor to overall host-plant quality of cultivated potato that, in turn, may have had direct effects on Colorado potato beetle life history, specifically the duration of dormancy. To our knowledge, no previous study on this species has attempted to directly relate pest management history to selection for modified dormancy or emergence intervals, either within or between seasons. Though long-term systemic neonicotinoid exposure explained only a limited portion of variation in emergence phenology, we feel that this body of work demonstrating a limited management effect furthers our current understanding of implications for long-term insecticide management decisions on pest biology and ecology. In other agricultural pest species, insecticide resistance traits have been closely related to variation in population-level life histories, specifically trade-offs between dormancy and fitness costs (e.g. diapause behavior, weight, development time) in obliquebanded leafroller, Choristoneura rosaceana (Harris) and , Cydia pomonella (L.) (Carrière and Roff 1995, Carrière et al. 1994, 1995; Boivin et al. 2003, 2004). In the Upper Midwest, substantial diapause plasticity of variant, , Diabroctica virgifera vigifera (LeConte), has been widely documented and attributed to insect pest management strategies in simplified agricultural landscapes (Levine et al. 2002,

Gray et al. 2009 and references therein). Variable population-scale life histories in western corn rootworm have been linked to both behavioral and possibly genetic resistance mechanisms to maize-soy crop rotation strategies, presenting considerable challenges to growers attempting to manage this significant economic pest of maize with cultural controls (Onstad et al. 2003,

Knolhoff et al. 2006). Furthermore, many rotation-resistant rootworm populations are increasingly insensitive to transgenic insecticidal traits in maize, generating considerable concern as to the durability of this valuable technology (Onstad and Meinke 2010). A growing body of

88

literature surrounding western corn rootworm, Colorado potato beetle, and several other

significant arthropod pests, emphasize the importance of placing insecticide resistance into an

ecologically-based, management framework supported by a union of information, not only

limited to bioassay data, but also contemporary findings about pest life cycles, agronomic

practices, and structure of agroecosystems (Gould 1983, Gray et al. 2009, Onstad and Meinke

2010, Carrière et al. 2012).

Conclusions. Reduction of neonicotinoid control has been observed in several localized

populations within the potato production agroecosystems for the past five years in Wisconsin

(Huseth and Groves 2011). Furthermore, widespread concern about reduced neonicotinoid

efficacy within the grower community suggests that effective and economical management of

Colorado potato beetle, as a result of resistance, may be more affected than simple bioassay

estimates indicate. In comparison to other regions of the United States, current levels of

neonicotinoid tolerance in Wisconsin are not exceptionally high (Szendrei et al. 2012), yet

trending LD50 estimates coupled with grower observations of reduced, field-level control

indicate significant erosion in efficacy of this widely used chemical MoA class. Several studies have documented the emergence phenology patterns and fitness costs associated with developing resistance in the Colorado potato beetle. To our knowledge, no studies have attempted to combine the effect of long-term insecticide management history with resistance. We hypothesized that survivorship and abundance of selected populations would be directly related to insecticide delivery decisions over the past 15 years. We saw no clear evidence for these relationships between beetle phenology and insecticide delivery or neonicotinoid resistance.

Differences in body size and fecundity were apparent, but did not uniformly correspond to one

89 specific insect management method. From a pest management perspective, long-term reliance on systemic insecticide application methods does not serve as a strong predictor of variable phenology within insects colonizing cultivated potato in Wisconsin.

90

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Tables and Figures

Table 1. Topical bioassay estimates for selected Colorado potato beetle populations.

R- Population Year n Slope±SEM LD 95% CI χ2 df 95% CI 50 ratioa Systemic-1 2007 74 2.57 (0.81) 0.068 (0.021-0.099) 15.97 3 1.8 (1.05-3.21) 2008 74 1.43 (1.1) 0.083 - 10.99 3 2.2 (0.52-9.43) 2009 48 1.27 (0.65) 0.094 (0-0.19) 6.24 3 2.5 (0.96-6.69) 2010 135 0.77 (0.38) 0.15 (0.076-1.06) 3.04 3 3.9 (1.48-10.41) 2011 425 1.63 (0.14) 0.72 (0.59-0.87) 5.63 4 26 (24.55-26.5)

Systemic-2 2007 75 1.64 (0.54) 0.21 (0.046-0.34) 10.7 3 5.7 (2.84-11.46) 2008 75 2.46 (0.8) 0.24 (0.049-0.37) 4.076 3 6.4 (3.26-12.73) 2009 75 4.21 (1.5) 0.8 - 9.68 3 21.6 (14.66-31.92) 2010 150 0.58 (0.17) 2.94 (1.21-28.8) 3.22 8 79.2 (23.87-262.57) 2011 524 1.9 (0.27) 0.62 (0.41-0.94) 17.47 5 22.2 (21.01-23.43)

Systemic-3 2007 75 1.69 (0.51) 0.12 (0.05-0.18) 14.09 3 3.2 (1.92-5.37) 2008 76 4.35 (1.1) 0.33 (0.21-0.41) 5.09 3 8.8 (2.15-35.78) 2009 75 1.01 (0.53) 0.15 - 2.37 3 3.9 (1.93-8.29) 2010 135 0.51 (0.17) 0.24 (0.058-0.76) 6.8 7 6.5 (2.32-18.06) 2011 500 2.03 (0.26) 0.73 (0.51-1.04) 14.15 4 25.5 (24.55-27.98)

Mixed 2007 75 1.43 (0.58) 0.013 (0.0000204-0.03) 8.8 3 0.3 (0.08-1.52) 2008 75 1.25 (0.43) 0.26 (0.15-0.7) 5.19 3 7.1 (3.85-12.95) 2009 75 0.72 (0.93) 0.024 - 8.8 3 0.7 (0.02-17.73) 2010 145 3.85 (0.65) 0.43 (0.34-0.51) 2.12 3 11.6 (8.92-15.2) 2011 525 1.47 (0.11) 0.48 (0.4-0.6) 6.2 5 17.2 (16.8-17.66)

Foliar 2007 74 1.38 (1.46) 0.024 - 9.86 5 0.7 (0-479) 2008 ------2009 75 1.83 (0.15) 0.15 (0.1-0.48) 0.85 3 3.9 (2.22-6.96) 2010 135 1.25 (0.22) 0.081 (0.05-0.12) 11.77 7 2.2 (1.32-3.56) 2011 524 1.81 (0.25) 0.39 (0.27-0.58) 15.78 5 14 (13.5-14.62)

WI- 2007 75 6.93 (1.69) 0.03 (0.025-0.036) 8.26 3 - - Susceptibleb 2008 75 1.43 (0.39) 0.05 (0.025-0.31 3.85 5 - - 2009 75 3.29 (1.36) 0.014 (0.0006-0.021) 3.68 3 - - 2010 135 4.38 (0.75) 0.037 (0.03-0.045) 3.34 7 - - 2011 600 3.13 (0.33) 0.027 (0.028-0.034) 14.11 6 - - a R-ratio: Resistance Ratio comparing LD50 of populations to response of WI-Susceptible population annually. bReference field population

100

Table 2. Percent (means±SD) survivorship for Colorado potato beetle populations released into the common garden experiment at the Hancock Agricultural Research Station, Hancock, WI during 2010 and 2011.

Average No. No. Population percentage released recaptured survivorshipa 2010 Systemic-1 1,952 122 6.3±1.3 Systemic-3 1,734 354 20.4±4.8 Mixed 2,100 256 12.2±6.5 Foliar 1,996 324 16.2±3.9 2011 Systemic-2 2,490 811 32.6±1.9 Systemic-3 1,890 166 9.1±2.3 Mixed 2,529 576 22.8±4.6 Foliar 2,757 186 6.7±1.3 Overall 2010 7,782 1,056 13.8±6.7 2011 9,666 1,739 17.8±11.2 aAverage population survivorship calculated from emergence totals of three replicate cages per season

Table 3. Logistic regressiona parameter estimates (means±95% CI) fitted to cumulative post-dormancy captures of Colorado potato beetles over the 2010 and 2011 growing seasons.

Population Gender Asymptoteb Xmidc Scald AIC R2e

2010 Systemic-1 male 17.7a (15.1-20.4) 146.3c (132.6-159.9) 24.7ab (17.0-32.4) 150.8 0.83 female 21.9ab (16.8-26.9) 151.6bc (125.5-177.8) 32.2ab (15.1-49.3) 189.8 0.68 Systemic-3 male 55.7e (48.2-63.3) 131.0bc (118.2-143.8) 21.2ab (11.5-31.0) 331.1 0.72 female 54.3e (48.8-59.7) 122.5b (114.1-131.0) 17.7a (10.7-24.8) 314.9 0.75 Mixed male 43.2bcde (28.7-57.7) 125.5abc (87.4-163.6) 36.8ab (-5.4-79.0) 297.9 0.35 female 47.0cde (34.4-59.6) 126.1abc (105.8-146.3) 23.6ab (9.9-37.3) 275.9 0.57 Foliar male 39.2d (36.6-43.3) 173.3c (159.6-187.0) 35.7b (27.5-43.9) 297.6 0.88 female 56.2e (50.7-61.8) 168.3c (156.1-180.5) 26.7ab (21.2-32.3) 368.3 0.79 2011 Systemic-2 male 113.1g (106.8-119.3) 123.6b (115.0-132.3) 29.9ab (23.6-36.2) 427.8 0.92 female 142.4h (135.6-149.2) 115.5ab (109.6-121.3) 23.3a (19.4-27.1) 390.8 0.96 Systemic-3 male 27.9b (26.2-29.5) 127.5bc (116.0-139.1) 45.0b (32.6-57.3) 181.3 0.89 female 32.5bcd (25.4-39.6) 119.1abc (102.3-135.9) 29.4ab (22.7-36.1) 155.9 0.82 Mixed male 85.6f (65.2-106.0) 109.5abc (85.2-133.9) 28.2ab (11.8-44.7) 317.2 0.65 female 106.5fg (98.6-114.3) 99.3a (88.8-109.8) 26.6ab (16.0-37.3) 359.6 0.83 Foliar male 29.6bc (24.4-34.8) 122.2abc (100.6-143.8) 33.9ab (19.3-48.5) 220.3 0.73 female 28.0b (24.1-31.9) 125.4abc (106.1-144.6) 36.0ab (21.9-50.1) 196.3 0.77 Parameter estimates followed by the same letter indicate overlapping 95% Confidence Intervals. aSimple logistic curve model: cumulative Colorado potato beetles = Asym/(1 + exp((Xmid – SDD)/Scal))); where SDD is the cumulative soil degree-days (base 10°C) after January 1 when the cage was sampled. bAsymptote of the curve (e.g. maximum Colorado potato beetles caught). cInflection point of the curve (Asym/2). dsoil degree-days surrounding peak emergence of a population (≈ 25-75%). eGoodness of fit = model sums of squares / (model sums of squares + residual sums of squares), as a pseudo-R2 in nonlinear modeling. 101

102

Table 4. Estimates for simple linear regression analysis evaluating the effect of cumulative soil degree-days on post-diapause Colorado potato beetle weight (g).

Parameter Estimatea (Intercept) Systemic-1 0.147***(0.00206) Systemic-2 0.0000941 (0.00209) Systemic-3 -0.00245 (0.00195) Mixed -0.000623 (0.00198) Foliar 0.0091*** (0.00197) SDD -0.0000976*** (0.00000631)

Gendermale -0.027*** (0.00155)

Year2011 -0.00382*** (0.000965)

SDD*gendermale 0.0000283** (0.00000895)

ANCOVA Evaluation R2 0.3313 F-statistic 172.5 df 8, 2786 P value <0.0001 Statistical analysis was performed following a log(x+1) transformation of the data. Estimates are presented on the transformed scale. aParameter estimate differs significantly from zero (*, P < 0.05; **, P < 0.01; ***, P < 0.001)

103

Table 5. G-tests for goodness of fit based on even proportions of male and female Colorado potato beetle (1:1) for spring beetle collections.

Year Population

2010 Systemic-1 Systemic-3 Mixed Foliar Σ males 58 171 117 128 Σ females 64 183 139 196 Total 122 354 256 324 df 1 1 1 1 G 0.295 0.407 1.893 14.378 P value 0.5869 0.5236 0.1689 0.0001

2011 Systemic-2 Systemic-3 Mixed Foliar Σ males 360 83 249 97 Σ females 451 83 327 89 Total 811 166 576 186 df 1 1 1 1 G 10.232 0 10.595 0.344 P value 0.00138 1 0.001134 0.55742 Goodness of fit G-tests follow a distribution of G = 2 ln L approximated by the χ2 distribution. P values < 0.05 indicate significant departure from assumed 1 male:1 female sex ratio.

Table 6. Average fecundity (means±SD) per Colorado potato beetle female over a 14 day oviposition period.

Population Σ females Σ eggs Σ egg masses eggs per mass masses per female eggs per female

2010 Systemic-1 64 2957 145 20.3 ± 0.2 2.3 ± 0.6 47.6 ± 12.5 Systemic-3 183 5594 266 21 ± 3.7 1.5 ± 0.2 30.9 ± 9.5 Mixed 139 6933 328 21.1 ± 0.8 2.6 ± 0.9 54.8 ± 17.3 Foliar 198 4302 216 19.2 ± 3.5 1.1 ± 0.1 20.9 ± 6 2011 Systemic-2 451 718 33 23.2 ± 9.3 0.1 ± 0.1 1.6 ± 2.1 Systemic-3 83 3931 188 21.3 ± 1.2 2.6 ± 1.9 53.5 ± 36.8 Mixed 327 2871 136 21.3 ± 2.4 0.4 ± 0.2 8.5 ± 4.2 Foliar 89 1940 95 20.4 ± 1.5 1.1 ± 0.1 21.7 ± 2.9

ANOVA results Populationa R2 0.598 0.598 0.595 0.056 0.528 0.698 F-value 7.056 7.078 6.975 0.282 5.318 10.96 P value 0.00117 0.00115 0.00124 0.886 0.00479 0.0000886 b Population*year R2 0.873 0.714 0.731 0.0745 0.83 0.884 F-value 15.75 5.702 6.212 0.184 11.16 17.36 P value 0.00000437 0.00192 0.00123 0.985 0.0000042 0.0000027 Summary results are reported as original means and standard deviations, statistical analysis was performed following log(x+1) transformation of the data. aP values calculated using df = 4,19. bP values calculated using df = 7,16. 104

Table 7. Average (means±SD) Colorado potato beetle fecundity per female by cohort group.

Cohort Group Evaluation Population 1 2 3 4 5 df F P 2010 Systemic-1 310.3a ± 128.8 (6)a 39.1ab ± 26.8 (25) 16.5b ± 15.2 (32) - - 2,6 6.954 0.0274 Systemic-3 67.4a ± 33.9 (34) 27ab ± 12.6 (86) 8.4b ± 6.5 (57) 0b ± 0 (4) 198.7a ± 95 (3) 4,10 52.21 <0.0001 Mixed 122.5a ± 66.4 (39) 47ab ± 6.1 (56) 15.3b ± 24.6 (41) 0b ± 0 (3) - 3,8 13.52 0.00169 Foliar 176.9a ± 118.3 (14) 52.8a ± 25.1 (39) 1.2b ± 1.3 (109) 7b ± 6.6 (26) 0b ± 0 (10) 4,10 19.18 0.00011 2011 Systemic-2 0b ± 0 (187) 1b ± 1.3 (234) 13.9a ± 10.2 (30) - - 2,6 13.34 0.00619 Systemic-3 16.4b ± 7.6 (38) 117.2ab ± 161.1 (45) 137.5a ± 22.6 (7) - - 2,6 3.77 0.0869 Mixed 0.6b ± 0.7 (184) 15.3ab ± 9.2 (135) 101.8a ± 101.4 (8) - - 2,6 21.83 0.00176 Foliar 7.9 ± 6.9 (33) 41.9 ± 27.7 (47) 48.8 ± 72 (9) - - 2,6 1.57 0.284 Means within a row followed by the same letter are not significantly different (P<0.05, Tukey’s HSD). Data are reported as original means and standard deviations, statistical analysis was performed following log(x+1) transformation of the data. anumber of females collected per cohort group. 105

106

● ●

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 200 400 600 800 1000 1200 Cumulative degree-days of control (base = 10 C) 0 5 10 15 Years of neonicotinoid use

Figure 1. Duration of Colorado potato beetle control with neonico- tinoid insecticides over 15 years of use (1995-2010) at five selected field locations in the Central Sands potato production region of Wisconsin. Duration of control is a relative measure calculated as: GDD of first Colorado potato beetle management minus GDD at planting. 107 1 2010

0.75

0.5

0.25 Systemic-1 Systemic-3 Mixed Foliar

0 100 200 300 400 500 May June 1 2011 Proportion emergence 0.75

0.5

0.25 Systemic-2 Systemic-3 Mixed Foliar

0 100 200 300 400 500 May June July Cumulative soil degree-days (base = 10 C)

Figure 2. Proportion emergence of Colorado potato beetle populations plotted against cumulative soil degree-days (base 10°C after 1 January). 108 2010 Systemic-1 Systemic-3 150 Female Male

100 ● ● ● ● ● ● ● ●●● ● ● 50 ● ● ● ● ● ● ●●● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ●●●● ●●●● ● ● ●● ● ● 0 ●●●●●●●● ● Mixed Foliar 150

100

● ● ● ● ● 50 ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ●●● ●●●● 0 ●●● ●●●● 100 200 300 400 500 100 200 300 400 500 May June May June 2011 Systemic-2 Systemic-3 150 ● ●●● ●● ● ● ● ● ● ●● ●●●● 100 ● ● ● ●● ● ●

Cumulative Colorado potato beetles ● ● ● ● ●● 50 ●● ● ● ●● ● ● ●●●● ● ● ● ● ●● ●●● ● ● ●●●● ●●●● 0 ● ●●●● Mixed Foliar 150

● ● ● ● 100 ●● ● ● ● ● ● ● ● ●● ● ● 50 ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ● ●●● ● ●●● ●● ● ● ● ●● ●●● ●● ● 0 ●●●●● ●● ●● 100 200 300 400 500 100 200 300 400 500 May June July May June July Cumulative soil degree-days (base = 10 C)

Figure 3. Cumulative emergence of five Colorado potato beetle populations plotted against cumulative soil degree-days (base 10°C after 1 January). Results of simple logistic nonlinear least-squares regression analysis are shown as best fit lines for each population and gender. 109

Asymptote Xmid A) female B) Systemic-1 male

Systemic-3

2010 Mixed

Foliar

Systemic-2

Systemic-3

2011 Mixed

Foliar

0 50 100 150 100 125 150 175 Cumluative Colorado potato beetles Cumluative soil degree-days (base = 10 C)

Figure 4. Estimates (means±95% CI) for logistic curve models fitted to cumulative Colorado potato beetle counts for males (squares) and females (circles) for the spring of 2010 and 2011. Asymptote (A) represents an estimate of overall survivorship for each gender and populations. Xmid (B) represents estimated cumulative soil degree- days of peak emergence for each gender and population. 110

Supplemental Material

- - - - Plant 2.3 (98) 8.8 (106) 2.1 (100) 0.9 (117) 26.4(95) 24.7(105) 20.9(112) 22.9(114) 30.9(102) 21.1(108) 17.6(103) 51.6(109)

01 ) 14 8)

( 85) ( 91) ( 83) ( 81) ( 77) ( 62) ( 83) ( 78) ( 63) ( 61) ( 61)

( 1 - - - .5 ( 81 .5 550.8 570.8 608.1 448.4 411.3 194.7 391.1 456.3 359.4 210.5 309.3 Di ff erence 788.1 11

2 -

12 ) 88 ) 79 ) 66 ) 02 ) 97 ) 98 ) 89 ) 78 ) 69 ) 249 )†

( 2 ( 1 ( 1 ( 1 ( 2 ( 1 ( 1 ( 1 ( 1 ( 1 - - - S pr ay 380 (167) 355 (167) Systemic 807.7 397.8 487.2 212.7 551.7 595.3 659.7 473.1 422.6 200.8 .4 ( 1202 .4

17 ) 07 ) 05 ) 05 )

- - - Plant 21 (101) 0.9 (1 6.1 (1 6.7 (1 2.1 (1 19.5(111) 30.9(101) 20.6(104) 45.7(106) 24.5(106) 51.6(115) 24.7(108) 11.3(101)

44 )

( 81) ( 72) ( 85) ( 89) ( 82) ( 94) ( 68) ( 70) ( 88) ( 68) ( 60)

- - - - 396.8 457.3 516.4 465.9 523.5 672.7 285.3 444.4 670.7 324.9 309.3 Di ff erence 1068.9 (1

1 -

97 ) 246 )† (1

( 186) ( 186) ( 188) ( 186) ( 201) ( 197) ( 197) ( 175) ( 182) - - - - S pr ay 355 (167) Systemic 475.5 554.7 396.8 508.9 542.3 702.2 480.4 693.1 328.4 311.7 .5 ( 1086 .5

tle management history 1995-2010. history management degree-days (base 10°C) potato b ee tle Colorado Growing

07 )

10 7) - - - - Plant 0 (1 3.5 ( 17.6(102) 31.1(116) 31.2(104) 22.4(109) 51.6(114) 25.9(112) 29.5(107) 26.4(114) 14.5(108) 45.7(107)

199 9 200 3 200 4 200 9 199 5 199 6 199 7 200 0 200 1 200 5 200 7 201 0 199 8 200 2 200 6 200 8

Y ea r pplemental Table 1. Su pplemental

111

( 62) ( 48) ( 42) ( 36) ( 35) ( 75) ( 35)

------507.3 537.1 432.7 310.5 370.2 818.8 350.9 Di ff erence ca tion. pp li

( 204) ( 211) ( 199) ( 191) ( 195) ------ee tle. S pr ay Foliar 668 (194) 551.7 625.4 700.9 466.6 672.1 1043.1 (230) tato b po tato

( 155) ( 169) ( 149) ( 151) ( 152) ( 155) ( 160) ------Plant 224.2 200.8 118.1 163.7 235.3 156.1 301.9 icotinoid systemic insecticide on icotinoid systemic a

tion for Colorado Colorado ca tion for

( 83) ( 83) ( 83) ( 68) ( 80) ( 76) ( 75) ( 61) ( 61) ( 53) ( 86) ( 74)

( 105) ( 102) es vine kill.ents date of 645 (81) 206 (59) 537.1 529.3 497.3 380.7 516.9 376.8 498.3 421.8 305.1 348.1 591.7 502.9 Di ff erence 813.4 627.7

( 211) ( 202) ( 199) ( 186) ( 200) ( 200) ( 189) ( 195) ( 177) ( 173) ( 191) ( 188) ( 175) ( 174) ( 171) Spray value repr value . Spray S pr ay Mixed 824 (212) ee tle 638.1 559.1 616.2 554.7 685.7 530.3 554.6 523.2 414.3 232.4 536.4 397.8 462.7 313.1 396.8

12 ) 14 ) and planting cumulative degree-day season. (Julian planting cumulative growing date) within on and

11 7) ( 1 ( 1 ( 113) Plant ca ti 8 21 41 0.9 ( 10.5(107) 10.5(109) 22.1(119) 24.5(113) 19.5(111) 56.4(111) 48.7(118) 40.7(119) 51.6(115) 25.9(112) 33.6(109) 26.4(114)

day planted ner ece ived andday potato date)(Julian when was crop 01 ) - 14 6) 72 ) 74 )

- - - - .4 ( 87 .4 406 ( 311 ( 718.2 (93) 391.8 (83) 534.7 (87) 358.8 (59) 328.6 (72) 486.2 (79) 460.7 (86) 460.4 (86) Di ff erence 675.6 (1 10

3 -

07 ) 89 ) 91 ) 99 ) 98 ) 89 ) 89 ) 74 ) 88 ) n first ce betw ee nappli spray first foliar (2

16 7) 16 7) - - - - Spray 380 ( 355 (

Systemic 406.9 (1 485.4 (1 677.9 (1 481.3 (1 741.1 400.6 (1 565.6 (1 313.1 (1 537.8 (1 (249)† 1105

Cumulative growing degree growing Cumulative degree-day growing potatodate) (Julian appli when first r ece ived crop foliar Cumulative Differen h spray threshold b †Field didpotato Colorado for not r eac h spray a b c

112

Supplemental Table 2. Percentage Colorado potato beetle emergence by cumulative soil degree-day and Julian datea.

Percentage emerged Population First 25% 50% 75% 100% Totalb observation 2010 Systemic-1 74.5 (121) 115.6 (135) 162.4 (141) 210.3 (145) 526.6 (171) 452.1 (50) Systemic-3 87.9 (123) 109.6 (133) 129.1 (137) 182.4 (143) 526.6 (171) 438.7 (48) Mixed 74.5 (121) 100 (125) 129.1 (137) 162.4 (141) 428.4 (163) 353.9 (42) Foliar 74.5 (121) 145.4 (139) 182.4 (143) 269.2 (149) 557.6 (173) 483.1 (52) 2011 Systemic-2 38 (137) 107.2 (149) 127.6 (151) 169.9 (155) 456.3 (181) 418.3 (44) Systemic-3 38 (137) 84.4 (145) 127.6 (151) 169.9 (155) 456.3 (181) 418.3 (44) Mixed 38 (137) 73.6 (143) 107.2 (149) 127.6 (151) 429.1 (179) 391.1 (42) Foliar 46.9 (139) 107.2 (149) 127.6 (151) 195.1 (157) 404.3 (177) 357.4 (38) 2010 Average 77.9 (121.5) 117.7 (133) 150.8 (139.5) 206.1 (144.5) 509.8 (169.5) 431.9 (48) 2011 Average 40.3 (137.5) 93.1 (146.5) 122.5 (150.5) 165.6 (154.5) 436.5 (179.5) 396.2 (42) Differencec 37.6 (16) 24.6 (13.5) 28.3 (11) 40.5 (10) 73.3 (10) 35.7 (6) aJulian date enclosed in parentheses following SDD value. bTotal equals 100% emergence minus first observation. cDifference equals 2010 average minus 2011 average values for percentage emergence and total emergence.

Supplemental Table 3. Average (means±SD) Colorado potato beetle traits.

Weight (g) Length (mm) Width (mm) Population Sample Gender n

Mean SD Min. Max Mean SD Min. Max Mean SD Min. Max

2009-2010 Systemic-1 Autumn Male 17 0.131 0.024 0.0921 0.171 9.25 0.63 7.94 10.06 6.04 0.44 5.19 6.86 Female 13 0.145 0.028 0.1006 0.221 9.48 0.59 8.62 10.84 6.23 0.39 5.66 7.12 Both 30 0.137 0.026 0.0921 0.221 9.35 0.62 7.94 10.84 6.12 0.42 5.19 7.12

Spring Male 58 0.111 0.021 0.0652 0.149 8.91 0.6 6.78 9.92 5.94 0.39 4.79 6.71 Female 64 0.142 0.025 0.0771 0.201 9.64 0.65 8.04 12.64 6.37 0.37 5.26 7 Both 122 0.127 0.028 0.0652 0.201 9.3 0.73 6.78 12.64 6.16 0.44 4.79 7

Systemic-3 Autumn Male 15 0.123 0.021 0.0804 0.166 9.16 0.66 7.98 10.17 6.07 0.38 5.36 6.7 Female 15 0.15 0.023 0.119 0.195 9.76 0.48 8.9 10.48 6.5 0.34 6.01 7.06 Both 30 0.137 0.025 0.0804 0.195 9.46 0.65 7.89 10.48 6.28 0.42 5.36 7.06

Spring Male 171 0.113 0.02 0.0616 0.163 8.84 0.53 7.24 10.34 5.88 0.36 4.98 6.95 Female 183 0.141 0.026 0.0833 0.209 9.53 0.54 8.21 10.74 6.38 0.39 5.24 7.29 Both 354 0.127 0.027 0.0616 0.209 9.2 0.63 7.24 10.74 6.14 0.45 4.98 7.29

Mixed Autumn Male 18 0.132 0.025 0.0929 0.175 9.17 0.83 7.7 10.49 5.99 0.49 5.22 6.8 Female 12 0.155 0.025 0.112 0.191 9.49 0.64 8.41 10.34 6.31 0.42 5.71 7.18 Both 30 0.141 0.027 0.0929 0.191 9.3 0.76 7.7 10.49 6.12 0.48 5.22 7.18

Spring Male 117 0.121 0.022 0.0501 0.171 9.14 0.64 7.28 10.88 6.1 0.43 4.76 6.81 Female 139 0.148 0.028 0.0692 0.23 9.7 0.54 7.52 11.34 6.53 0.42 5.18 7.95 Both 256 0.135 0.029 0.0501 0.23 9.45 0.65 7.28 11.34 6.34 0.48 4.76 7.95

113

Supplemental Table 3 continued,

Foliar Autumn Male 17 0.142 0.017 0.116 0.172 9.41 0.39 8.69 10.08 6.19 0.28 5.59 6.75 Female 13 0.171 0.017 0.147 0.208 10.01 0.27 9.59 10.41 6.62 0.18 6.34 6.93 Both 30 0.156 0.022 0.116 0.208 9.67 0.45 8.69 10.41 6.38 0.32 5.59 6.93

Spring Male 128 0.115 0.022 0.0674 0.181 8.99 0.54 7.49 10.17 5.99 0.4 4.91 7.42 Female 196 0.139 0.026 0.0681 0.208 9.62 0.52 8.06 11.04 6.45 0.39 5.22 7.3 Both 324 0.13 0.027 0.0674 0.208 9.38 0.61 7.49 11.04 6.26 0.46 4.91 7.42

2010-2011 Systemic-2 Autumn Male 18 0.133 0.01 0.111 0.148 9.23 0.29 8.68 9.76 6.08 0.17 5.75 6.36 Female 12 0.15 0.023 0.115 0.189 9.65 0.49 9.09 10.68 6.41 0.32 5.92 6.99 Both 30 0.14 0.018 0.111 0.189 9.39 0.43 8.68 10.68 6.21 0.29 5.75 6.99

Spring Male 360 0.113 0.018 0.0577 0.161 9.13 0.45 6.52 10.13 5.98 0.3 4.73 6.98 Female 451 0.138 0.02 0.0805 0.191 9.77 0.41 8.1 10.84 6.45 0.28 5.49 7.21 Both 811 0.127 0.023 0.0577 0.191 9.48 0.53 6.52 10.84 6.24 0.37 4.73 7.21

Systemic-3 Autumn Male 12 0.106 0.027 0.062 0.132 8.81 0.58 7.5 9.62 5.84 0.47 4.81 6.44 Female 18 0.122 0.021 0.881 0.172 9.24 0.7 8.43 10.66 6.24 0.48 5.71 7.23 Both 30 0.116 0.026 0.062 0.172 9.07 0.68 7.5 10.66 6.08 0.51 4.81 7.23

Spring Male 83 0.108 0.022 0.0611 0.15 8.98 0.5 7.41 10.34 5.91 0.31 5.03 6.57 Female 83 0.135 0.023 0.0913 0.207 9.66 0.52 8.53 10.74 6.41 0.36 5.59 7.16 Both 166 0.121 0.026 0.0611 0.207 9.32 0.61 7.41 10.74 6.16 0.42 5.03 7.16

Mixed Autumn Male 14 0.115 0.026 0.0697 0.15 8.85 0.86 6.89 9.81 5.87 0.44 5.03 6.4 Female 16 0.136 0.029 0.07 0.186 9.34 0.78 7.48 10.61 6.22 0.55 5.06 7.08 Both 30 0.126 0.029 0.0697 0.186 9.11 0.84 6.89 10.61 6.06 0.52 5.03 7.08

Spring Male 249 0.111 0.02 0.0581 0.168 9.06 0.53 7.08 10.05 5.98 0.43 4.81 9.42 Female 327 0.138 0.026 0.0577 0.217 9.74 0.56 6.36 10.81 6.47 0.37 5.1 7.41 Both 576 0.127 0.027 0.0577 0.217 9.45 0.64 6.36 10.81 6.26 0.46 4.81 9.42 114

Supplemental Table 3 continued,

Foliar Autumn Male 15 0.115 0.015 0.0966 0.137 9.42 0.24 9.11 9.97 6.26 0.26 5.95 6.91 Female 15 0.151 0.01 0.121 0.175 10.13 0.29 9.48 10.51 6.84 0.37 6.34 7.91 Both 30 0.133 0.022 0.0966 0.175 9.77 0.45 9.11 10.51 6.55 0.43 5.95 7.91

Spring Male 97 0.13 0.021 0.0734 0.184 9.54 0.48 7.31 10.67 6.31 0.3 5.22 6.95 Female 89 0.157 0.026 0.0913 0.218 10.13 0.36 8.91 10.74 6.69 0.31 5.52 7.13 Both 186 0.143 0.027 0.0734 0.218 9.82 0.52 7.31 10.74 6.49 0.36 5.22 7.13 n represents individuals randomly selected in autumn samples or total number of individuals emerged in the spring of each sampling year 115

116

Chapter 4: Insecticide residues and leaching of systemic neonicotinoids in cultivated potato: implications for insect resistance management and environmental fate

117 Abstract: Since 1995, systemic neonicotinoid insecticides have been a critical component of arthropod management in potato, Solanum tuberosum (L.). Recent detections of neonicotinoids in groundwater has generated questions about the sources of these contaminants, and commodities of greatest concern in Wisconsin agriculture. Delivery of neonicotinoids to crops typically occurs at planting time often as a seed, or in-furrow treatment to manage early season insect herbivores. One such pest in potato which has spurred the repetitive use of these at plant insecticides is the Colorado potato beetle, Leptinotarsa decemlineata (Say), which has become resistant to the neonicotinoids. An outcome of this project links the commonly used strategies for control of L. decemlineata with neonicotinoid contamination of groundwater resources. In 2010,

2011 and 2012 our objectives were twofold: to 1) characterize the temporal, in-plant concentrations of neonicotinoids and the response of L. decemlineata to four methods of pesticide delivery and 2) document the temporal patterns of neonicotinoid leachate into groundwater resources following similar insecticide delivery. During the spring of 2010 and

2011, systemic neonicotinoid treatments of imidacloprid and thiamethoxam were applied at planting in a randomized complete block design to potato. After plot establishment and plant emergence, L. decemlineata life stages were counted and plant tissue was assayed weekly for nine consecutive weeks using ELISA. In a second experiment, leaching loss of thiamethoxam from potato was measured using pan lysimeters from three at-plant treatments and one foliar application treatment. Insecticide concentration in leachate was assessed for six consecutive months with LC/MS. Results illustrate variation in the temporal patterns of neonicotinoids present in potato over time. Furthermore, below-ground losses of insecticide in leachate tended to occur later in the growing season after plant . Findings from this study suggest

118 leaching of neonicotinoids from potato may be far greater following harvest of the crop when compared to other times during the growing season.

Keywords: IPM, neonicotinoid insecticides, groundwater contamination, Colorado potato beetle

119 The neonicotinoid class of insecticides are among the most broadly adopted, conventional management tools for insect pests of annual and perennial cropping systems (Jeschke et al.

2011). Benefits of the neonicotinoid class (IRAC Mode 4a) of compounds include flexibility of application, diversity of active ingredients, and activity on several orders of herbivorous arthropods (Elbert et al. 2008). Moreover, growers have readily adopted neonicotinoids for two specific reasons: first, these compounds are fully systemic in-plants after soil application and second, several new generic formulations have recently become available which have incentivized their continued use in many crops (Elbert et al. 2008, Jeschke and Nauen 2008,

Jeschke et al. 2011). Since 2001, the United States Environmental Protection Agency (EPA) has classified several neonicotinoids as either conventional reduced-risk pesticides or organophosphate alternatives (US-EPA 2010). EPA certification often requires replacement of older, broad-spectrum pesticides with newer, more specific products for management of key economic pests. Critical attributes of replacement insecticides include documented reductions in human and environmental risk when compared to older, broad spectrum pesticides. Specifically,

EPA classified reduced-risk pesticides must: 1) limit impacts to non-target organisms, 2) reduce potential as groundwater contaminants, 3) lower application rates, and 4) decrease likelihood for pest resistance development (EPA 2012). Though agriculturists and regulatory agencies have accepted neonicotinoid insecticides, 15 years of widespread, repetitive uses of this chemical class has resulted in several insect resistance management issues as well as unanticipated environmental impacts.

While considerable attention has been focused on the positive attributes of the neonicotinoids, an increasing body of research suggests substantial negative impacts not only in terms of pest resistance development, but also impacts on non-target organisms and surrounding

120 ecosystems at multiple spatial and temporal scales (Blacquière et al. 2012, Casida 2012, Krupke et al. 2012, Gill et al. 2012, Segraves and Lundgren 2012, Starner and Goh 2012). Moreover, recent studies have documented the negative influence of neonicotinoids on pollinator population health (both native and managed) which, in turn, created substantial concern about the long-term sustainability of these pesticides in agriculture (Miranda et al. 2011, Cresswell et al. 2012a,

2012b; Gill et al. 2012, Henry et al. 2012, Stoner and Eitzer 2012, Tapparo et al. 2012, Tomé et al. 2012). Exposures to pollinators reportedly occur through chronic, sub-lethal contact with low concentrations of neonicotinoid residues in pollen, nectar, waxes, and guttation drops of common crop plants (Chauzat et al. 2006, Girolami et al. 2009, Laurent and Rathahao 2003, Mullin et al.

2010). Gill et al. (2012) demonstrated that low concentrations (10 μg L-1) of imidacloprid significantly reduced colony-level health in (Bombus terrestris). Low concentrations tested by the authors are consistent with those found in nectar and pollen of flowering crops further supporting the direct crop-pollinator toxicological pathway hypothesis (Laurent et al.

2003, Dively and Kamel 2012, Stoner and Eitzer 2012). Though they have received much less attention, many closed pollination crops also rely on neonicotinoids and may have considerable undocumented risks for non-target organisms through indirect pathways in the agroecosystem.

Since 1995, the majority of potato production acres have received at-plant systemic neonicotinoid insecticides to manage founding populations and early summer generations of L. decemlineata. Repetitive use over a period of 18 years has resulted in widespread resistance to this class in select populations of L. decemlineata throughout the United States and Europe

(Mota-Sanchez et al. 2006, Alyhokhin et al. 2007, Groves 2008, Sladan et al. 2012, Szendrei et al. 2012). Where resistance occurs, growers continue to apply systemic neonicotinoids for control of L. decemlineata with limited success, often applying supplemental foliar applications

121 of organophosphate or carbamate insecticides to maintain populations below economic injury levels. Although the mechanisms of insecticide resistance have been extensively studied in this insect, very few studies have focused on the influence of specific pest management practices and resistance development in L. decemlineata. Research in other annual crops has shown that in- plant concentrations of the neonicotinoid insecticides are both spatially and temporally variable throughout the growing season (Olson et al. 2004, Byrne et al. 2005b, 2007, 2010); and diminishing in-plant concentrations often closely coincide with increased arthropod herbivory and economic damage to the crop (Byrne et al. 2005a, Castle et al. 2005). These heterogeneous distributions of the neonicotinoid insecticides in potato may elicit dynamic physiological and behavioral responses that in turn accelerate insecticide resistance development in L. decemlineata (Hoy et al. 1998). The long-term impact of these variable, in-plant concentrations is unknown, but may well compromise the efficacy of future systemic insecticide registrations for L. decemlineata that behave similarly in potato. Furthermore, the identification of other factors (e.g. rain events, soil microbial communities, application method) that affect within, or among plant neonicotinoid concentrations, will provide additional insight into the rate of resistance development resulting from spatio-temporal patterns of refugia present in treated plants. Linking factors (e.g. rain events or delivery method) that affect in-plant concentration may also explain leaching losses of these water soluble insecticides from the root zone of the crop, and determining this loss potential may be critical for both pest management and mitigation of groundwater contamination.

The environmental fate of the neonicotinoids associated with different delivery methods has been previously assessed for a portion of the compounds in this class, and often related to degradation and movement processes in soil, leachate, and runoff (Gupta et al. 2002, Papiernik et

122 al. 2006, Chiovarou and Siewicki 2008, Gupta et al. 2008, Miranda et al. 2011, Starner and Goh

2012). The leaching potential of the neonicotinoids into groundwater, as well as persistence in the plant canopy, is related to the delivery method of the compound to the crop (Gupta et al.

2002, Juraske et al. 2009). In potato production, at-plant seed treatment and in-furrow applications have been adopted as the principal form of insecticide delivery which provides the longest interval of control, while also reducing non-target impacts and limiting exposure to applicators when compared to foliar application methods. The now widespread and extensive use of these systemic neonicotinoid insecticides, coupled with the recent detection of thiamethoxam in subsurface wells (Fig. 1, Table 1), supports the hypothesis that potato pest management systems may contribute a portion of the documented neonicotinoid contaminants reported in

Wisconsin. In this study, we examined the temporal patterns of neonicotinoid concentrations in plants, and the response of L. decemlineata herbivory in these different insecticide delivery treatments. Furthermore, we investigated the influence of different systemic insecticide delivery methods on the resulting neonicotinoid leachate concentrations captured in below cultivated potato maintained under commercial potato management conditions. Specifically, we 1) documented the temporal imidacloprid and thiamethoxam concentrations in plants resulting from four, systemic insecticide delivery methods under field conditions using enzyme-linked immunosorbant assay (ELISA) over two years, 2) simultaneously measured the response of a moderately resistant L. decemlineata population to each treatment under field conditions, and 3) analyzed leachate captured below the different systemic and foliar delivery treatments for thiamethoxam only using liquid chromatography-mass spectrometry (LC/MS) over two consecutive seasons. Results of this study increase our understanding about the influence of insecticide delivery method and the effects pesticide concentrations in plants, resulting pest

123 population dynamics in cultivated potato, as well as the potential for off-site movement of

neonicotinoid insecticides into the surrounding environment.

Materials and Methods

This study has been divided into two components examining neonicotinoid use patterns in

potato. First, a set of experiments measuring imidacloprid and thiamethoxam residues within

potato plant tissue over time, hereafter referred to as neonicotinoid concentration in plant tissue.

Second, an experiment measuring only thiamethoxam concentration in water leaching from

below commercial potato receiving different systemic insecticide deliveries and a foliar

treatment, called neonicotinoid leachate.

Experimental site and design. Neonicotinoid concentration in plant tissue. Experiments were conducted at the University of Wisconsin - Hancock Agricultural Research Station,

Hancock, Wisconsin (44.11726°N, -89.539797°W). The cultivar ‘Russet Burbank’ was chosen as a long season potato cultivar commonly grown in Wisconsin’s production system.

Experiments were planted on 27 April, 2010 and 28 April, 2011. A 0.2 ha field was planted at a rate of one seed piece per 0.3 m with a 1 m row spacing. Soil composition was loamy sand with

< 2% organic matter and a pH of 7. Best management practices for weed, disease, irrigation, and nutrient management for potato in Wisconsin were used (Boerboom et al. 2010). Two neonicotinoid insecticides (imidacloprid and thiamethoxam) and three different application methods were included in each year of this study. In 2010, application methods included a conventional in-furrow, polyacrylamide impregnation, and 1st hilling neonicotinoid spray + soil surfactant. In 2011, the hill spray treatment was replaced with a conventional pre-plant seed treatment application. Annual experiments included the specified combinations of insecticide application methods plus an untreated control (n=4 treatments year-1). Plots were arranged in a

124 randomized complete block design with four replications, and the study was terminated when all plots exceeded 90% defoliation or following senescence.

Neonicotinoid leachate. In 2011 and 2012, lysimeter experiments were conducted 6 km east of Coloma, Wisconsin at Coloma Farms Inc., (44.021997°N, -89.597958°W). Experiments were planted on 20 May 2011 and 11 May 2012. A randomized complete block design with four treatments and an untreated control was established using the potato cultivar, ‘Russet Burbank’.

Plots were 0.067 ha in size and planted at a rate of one seed piece per 0.3 m with a 0.76 m row spacing. Each year, experiments were nested within a different 32 ha commercial potato field, and maintained under commercial management practices by the producer, with the exception of insecticide inputs. The decision to locate these experiments in commercial fields was, in part, based upon access to a center pivot irrigation system to best duplicate water inputs and irrigation consistent with commercial potato production in Wisconsin. All other inputs and production strategies (e.g. tillage, fumigation, fertility, and disease management) were conducted by the producer with equipment and products consist with the broader industry. Prior to planting in each season, a tension plate lysimeter (25.4 x 25.4 x 25.4 cm) was buried at a depth of 75 cm below average field level. Lysimeters were constructed of stainless steel with a porous stainless steel plate affixed to the top to allow water to flow into the collection basin over each sampling interval Experimental blocks were connected with 9.5 mm copper tubing to a primary manifold and equipped with a vacuum gauge. A predefined, fixed suction was maintained under regulated vacuum at 15.5±2.5 lb per in2 (107±17 kPa) with a twin diaphragm vacuum pump (model

UN035.3 TTP, KnF, Trenton, NJ) and a 76 L portable air tank. Each treatment block was equipped with a data-logging rain gauge (Spectrum Technologies, Inc. model # 3554WD1) recording daily water inputs at a five minute interval. Data was offloaded with Specware 9 Basic

125 software (Spectrum Technologies, Inc., Plainfield, IL, USA) and aggregated into daily irrigation

or rain event totals using the aggregate and dcast function in R (package: plyr, Wickham 2011).

Irrigation event records were obtained from the grower to identify days and estimated inputs of water application throughout the growing season.

Insecticides and application. Neonicotinoid concentration in plant tissue. Insecticide

treatments of imidacloprid (Admire® Pro and Gaucho® 600, Bayer, Research Triangle Park, NC)

and thiamethoxam (Platinum® 75SG and Cruiser® 5FS, Syngenta, Greensboro, NC) were

selected to represent both the majority of at-plant potato applications and two currently labeled

insecticides with the highest documented levels of insensitivity to L. decemlineata. Insecticide

products were commercially formulated and maximum labeled rates (thiamethoxam: 140 g

active ingredient ha-1 or imidacloprid: 261 g active ingredient ha-1) for potato in Wisconsin were

applied (Boerboom et al. 2010).

A CO2 pressurized, backpack sprayer with a single nozzle boom was used to deliver an

application volume of 94 liters ha-1 at 207 kPa through a single extended range flat-fan nozzle

(TeeJet XR80015VS, Spraying Systems, Wheaton, IL) for in furrow applications. Spray

applications were directed onto seed pieces in the furrow at a speed of one meter per second and

furrows were immediately closed following application. Polyacrylamide horticultural copolymer

granules (JCD-024SM, JRM Chemical, Cleveland, OH) were impregnated at an application rate

of 16 kg ha-1. Imidacloprid (2.84 mL) and thiamethoxam (0.834 g) were each diluted in 250 mL

of deionized water and 100 µL of blue food coloring was incorporated into solution to ensure

uniform mixing (brilliant blue FCF). Insecticide solutions were mixed with 75 g polyacrylamide

then stirred until the liquid was absorbed and a uniform color was observed. Impregnated

granules were vacuum dried in the absence of light for 24 hours at 20°C. Treated granules were

126 divided into even quantities per row (9.8 g per 5.7 m imidacloprid, 9.6 g per 5.7 m thiamethoxam) and evenly distributed into the two center rows for each treatment respectively.

Flanking rows received an at-plant, in-furrow application of the same compound and rate.

Insecticide applications for hill spray treatments occurred simultaneously with fertilizer side dress (21-0-0-24S) and first hilling occurred on 17 May 2010. A Harriston 2010 potato hilling implement was modified with extended range flat fan nozzles and were mounted 30 cm above the hill to apply a banded spray of soil surfactant at a rate of 0.766 L ha-1 (Harriston Industries,

Minto, ND; TeeJet TP-4001E, Spraying Systems, Wheaton, IL). Soil surfactant (IrrigGold®,

Aquatrols, Paulsboro, NJ) was applied at a rate of 0.5% in water and a full rate of each insecticide mixed and applied directly to potato hills. Surfactant and insecticide was covered with a hilling implement and 1.89 cm of water was immediately applied with overhead irrigation.

Seed treatments were applied in 130 mL of water per 23 kg of suberized cut seed pieces 24 hours prior to planting. A CO2 pressurized backpack sprayer with a single nozzle boom delivering an application volume of 102.2 L ha-1 at 207 kPa through a single, extended range flat-fan nozzle

(TeeJet XR80015VS, Spraying Systems, Wheaton, IL).

Neonicotinoid leachate. Systemic insecticide and polyacrylamide treatments were applied as described previously in the above neonicotinoid concentration in plant tissue section with only thiamethoxam. Additionally, a single, foliar treatment of thiamethoxam (Actara® 25WG,

Syngenta, Greensboro, NC) was applied using a CO2 pressurized backpack sprayer with a single nozzle boom delivering an application volume of 187.1 L ha-1 at 207 kPa through four, extended range flat-fan nozzles (TeeJet XR80015VS, Spraying Systems, Wheaton, IL) spaced at 45.2 cm.

Applications were followed approximately seven days later with a second equivalent rate of

127 thiamethoxam thiamethoxam (Actara® 25WG, Syngenta, Greensboro, NC) (Boerboom et al.

2010).

Beetle Sampling and Damage. During the 2010 and 2011 season, plots were visually

assessed for L. decemlineata defoliation estimates and direct counts were obtained of different

life stages. Potato yield and quality estimates were also obtained from experimental treatments at

the completion of experiments in each year. Counts were conducted on a weekly interval from

90% stand emergence until plant senescence. Ten randomly selected plants from each plot were

visually assessed for the presence of L. decemlineata life stages. Adult beetles and egg clusters were counted directly. Larval life stages were classified into two groups, small larvae (1st and 2nd instars) and large larvae (3rd and 4th instars) on each of ten plants. Here we reported only small larvae life stages.

Tissue collection and storage. To measure neonicotinoid concentrations in plants over time, leaf tissue collection began on 2 June 2010 at 90% plant emergence. Sampling occurred weekly until all plots exceeded 90% defoliation or until plant senescence for a total of nine consecutive weeks. One terminal leaflet was selected from mid-canopy from three randomly selected plants in each plot. Samples were immediately placed on ice until processing. To reduce chances of false positive signals as a result of misapplication in the field (e.g. maintenance spray tank contamination), a second set of untreated plants were grown under greenhouse conditions as an additional untreated control. The potato cultivar ‘Russet Burbank’ was grown in the greenhouse and sampled concurrently with the field experiments in each season. Immediately following collection, a size 4 cork borer (0.52 cm2) was used to remove four random cores from each individual leaf while avoiding primary venation. Leaf discs from each individual plant were

128 placed into pre-weighed 1.5 mL microcentrifuge tubes (Eppendorf North America, New York,

NY), weighed and frozen at -80ºC until chemical analysis.

Chemical extraction and quantification. Neonicotinoid concentration in plant tissue.

Thiamethoxam and imidacloprid residue were measured by ELISA (Envirologix Inc, Portland,

ME, imidacloprid kit, cat #006; Beacon Analytical Systems Inc., Saco, ME, thiamethoxam plate, cat #CPP-022) according to the manufacturers specifications with the following modifications.

Reported sensitivity ranges were 0.2-6 µg imidacloprid L-1 and 0.05-2 µg thiamethoxam L-1.

Prior to analysis of field collected samples, the assay was calibrated to account for background effects of potato tissue (Byrne et al. 2005a, 2005b, 2007, 2010; Castle et al. 2005). Untreated leaf extracts amended with insecticides were used to determine the recovery efficiency of imidacloprid and thiamethoxam assay kits from potato foliage (Byrne et al. 2005b, Castle et al.

2005). Untreated leaf disc samples were macerated in 200 µL methanol to produce pure leaf extract. Two separate sets of five, 400 µL serial dilutions of pure leaf extract were prepared in phosphate buffered saline solution (PBS) containing 0.05% Triton X-100 beginning with a 2% leaf extract (x2, x10, x20, x50, x100 dilutions). Each dilution series was spiked with standard calibrators supplied in each ELISA kit (0.2 µg imidacloprid L-1 and 0.05 µg thiamethoxam L-1) to produce samples containing identical concentrations of each compound (Byrne et al. 2005b).

Results of this initial experiment suggested pure leaf extract should be diluted to less than 5%.

For the 2% and 5% plant extract concentration group, five separate dilution series of both imidacloprid and thiamethoxam were prepared in 100 µL D.I. water between 0.1 and 10 µg compound L-1. To each dilution series an equal volume of diluted plant extract was added to produce proper extract background (Byrne et al. 2005b). Results from this preliminary

129 experiment indicated background levels of plant extract would not interfere with the sensitivity range of the ELISA kit.

At the conclusion of nine week sample interval in each year, all samples were removed from the freezer and prepared for assay using a methanol extraction procedure. Samples were homogenized in 400 µL methanol with pellet pestles (K749520, Kontes, Vineland, NJ).

Homogenates were shaken vigorously overnight at room temperature and then centrifuged at

10,000 × g for 5 minutes to pellet the particulate matter. Supernatants were diluted 80-fold in

PBS containing 0.05% Triton X-100 and used directly for quantification by ELISA. Samples outside the sensitivity range of the assay were diluted further and retested. All results were quantitatively compared using a spectrophotometer (VersaMax microplate reader, Molecular

Devices, LLC, Sunnyvale, CA). End-point absorbance values were obtained for samples at an optical density of 450 nm to determine insecticide concentration of each sample with respect to the standard curve. Internal standards provided by the manufacturer served as a comparison to both standard curves and to determine unintended binding of other plant metabolites.

Neonicotinoid leachate. Lysimeters were sampled on a bi-monthly frequency beginning in June and concluding in October of 2011 and November of 2012. Total leachate volume was recorded for each treatment. A 500 mL subsample was taken from each plot into a 0.5 liter glass vessel and immediately placed on ice and held then at 4-6°C in the laboratory prior to analysis. Bi- monthly samples were homogenized into a 400 mL monthly sample as percent volume per volume dependent on total catch measured in the field. Neonicotinoid residues from six monthly water samples were extracted from leachate samples using automated solid phase extraction.

Residues were identified, quantified, and confirmed by liquid chromatography mass

130 spectrometry (LC/MS) by the WI DATCP-Bureau of Laboratory Services under Standard

Operating Procedure #1009 and procedures outlined therein.

Data Analysis. To determine the impact of different neonicotinoid treatments on

insecticide residue detected in the plant over time, we reported the mean concentration over a

nine-week sequence. All data manipulation and statistical analyses of in-plant residues, leachate

concentrations, and pest counts were performed in R, version 2.15.2 (R Development Core Team

2012) using the base distribution package. Functions used in the analysis are available in the base

package of R unless otherwise noted. To avoid simple pseudoreplication, individual leaf residue

values and plot subsamples were pooled into an experimental unit level mean for each

observation week prior to statistical analysis (Hurlbert 1984). Plot means for each week in each

year of analyses were subjected to a repeated-measures analysis of variance (ANOVA) using a

linear mixed-effects model to determine significant delivery (i.e. treatment), date, and delivery x

date effects (P<0.05). Because the magnitude of residues were markedly different between

imidacloprid and thiamethoxam and given that our comparison of interest was at the insecticide

delivery treatment level, insecticide concentrations were analyzed separately for each year and

active ingredient. Mixed-effects models were fit using the lme function (package nlme: Pinheiro and Bates 2013). Empirical autocorrelation plots from unstructured correlation model residuals were examined using the ACF function. Correlation among within-group error terms were structured and examined in three ways first, unstructured correlation, second, with compound symmetry using the function corCompSymm and third, with autoregressive order one covariance using the function corAR1. Since models were not nested, fits of unstructured, compound symmetry, and autoregression order one covariance were compared using Akaike’s information criterion statistic with the function anova (test = “F”). Data were transformed with natural

131 logarithms before analysis to satisfy assumptions of normality, however untransformed means

are graphically presented. Data analysis of both pest counts and residue concentration in water

leachate followed the same general repeated-measures procedure as outlined above. In 2012, a

single lysimeter in the Polyacrylamide treatment of the leachate study malfunctioned and these

observations were dropped from subsequent analyses leading to an unbalanced replicate number

(n=3) in that year. Water input data collected from tipping bucket samplers were averaged across

block by day and aggregated as cumulative water inputs using the cumsum function. All

summary statistics and model estimates were extracted using aggregate, summary, and anova

functions.

Results and Discussion

Groundwater detections. Positive neonicotinoid detections from the Wisconsin

Department of Agriculture, Trade and Consumer Protection-Environmental Quality Section (WI-

DATCP-EQ) surveys over the 2008-2012 interval are summarized in Table 1. These annual

surveys, administered by WI-DATCP-EQ, occur at specific locations with historical point source

groundwater contamination (e.g. manure or chemical spills) or at regions with high risk of non-

point source agrochemical leaching. Specifically, two agriculturally intensive production regions

of the state, the Central Sands and Lower Wisconsin River valley, are thought to be at high risk

for groundwater contamination and are frequently monitored for the presence of common

agrochemicals (Fig. 1). These regions have well-drained, sandy soils and easily accessible

groundwater for irrigation that has driven agricultural intensification focused on vegetable

production. Commercial potato dominates the production sequence, but is also rotated with many

other specialty crops such as: carrots, onions, peas, pepper, processing cucumber, sweet corn,

and snap beans. Unfortunately, the unique soil and water characteristics supporting a profitable

132 specialty crop production system are also particularly vulnerable to groundwater contamination with soluble agricultural products (Mossbarger and Yost 1989, Kraft et al. 1999, Saad 2008).

Regulatory exceedences of nitrates and herbicide products (e.g. triazines, triazinones, and chloroacetamide) have been commonplace for several years (Kraft et al. 1999, Postle et al.

2004), but recent detections of neonicotinoid contaminants have created new groundwater quality concerns (WI-DATCP 2010). Beginning in the spring of 2008, two wells had detections of 1.25 and 1.47 µg L-1 thiamethoxam in Grant and Sauk Counties, WI (ID #10 & 17, Fig. 1).

Subsequent sampling later that season identified six additional locations for a total of 17 positive thiamethoxam detections that year (Table 1). Since these early detections, the WI-DATCP

(2011) has intensified the area and timeframe over which this surveillance of neonicotinoids in subsurface water resources has taken place in an effort to define the extent of contamination in the state. Following the initial 2008 detections, thiamethoxam, imidacloprid, and clothianadin residues have been repeatedly detected at 23 different monitoring well locations over a five-year period. Although the sampling effort was not uniformly distributed within the state, detections often correspond to areas where intensive irrigated agricultural production occurs. As an indication of specialty crop production intensity, we used county-level potato abundance to better describe trends in historical neonicotinoid detections. Observed frequency and magnitude of neonicotinoid detections did not consistently correspond to potato abundance (Table 1).

Although the contribution of potato production to the observed detections was not clear, regulatory agencies have continued to pursue this interaction by increasing their frequency of sampling where potato occurs at a high density, specifically the Central Sands and Wisconsin

River Valley. Groundwater sampling strategies have provided a useful timeline of non-point source pollution events in subsurface water resources. Identifying the origin of non-point source

133 pollutants in the state is complicated by the diversity of neonicotinoid registrations, application methods and formulations; currently Wisconsin has 164 different registrations for field, forage, tree fruit, vegetable, turf, and ornamentals crops (6 acetamiprid, 18 clothianadin, 4 dinotefuran,

108 imidacloprid, 1 thiacloprid, 26 thiamethoxam; Agrian, 2013).

Neonicotinoid residues in plant tissue. Increased insensitivity to neonicotinoids in populations of L. decemlineata throughout Wisconsin has renewed interest in technologies to increase the magnitude and interval of pesticide expression as an Insecticide Resistance

Management strategy. Imidacloprid and thiamethoxam concentrations were monitored over nine weeks using serological techniques for neonicotinoids in plants (Byrne et al. 2007, 2010).

Residues associated with all application methods declined sharply over the four weeks following emergence from soil, with the exception of the side dress treatment in 2010 (Fig. 2).

Concentrations varied differentially among treatment methods through time for thiamethoxam in

2010 (treatment x day interaction, F=2.5; d.f.=24,105; P=<0.0001) and 2011 (F=6.5; d.f.=24,105; P=<0.0001). Results for imidacloprid residue concentrations were also significantly different for treatments over time in 2010 (treatment x day interaction, F=6.5; d.f.=24,105;

P=<0.0001) and 2011 (F=4.3; d.f.=24,105; P=<0.0001). Residues of both insecticides declined sharply between 36-50 days after planting in 2010 and between 43-50 days in 2011 (Fig. 2).

Similar declines in neonicotinoid concentrations have been documented for several different application methods (e.g. seed, in-furrow, drip, and drench) in annual herbaceous crops (Nault et al. 2004, Butler et al. 2011) as well as perennial tree and vine crops (Castle 2005, Byrne 2005a,

2005b, 2007). This rapid reduction in concentration is intriguing as these declines closely correspond with expansion of the potato canopy in early June. Low doses of these insecticides at the time of canopy expansion increases crop vulnerability to direct damage by insect herbivores

134 and potential for pathogen transmission (Hoy et al. 1998, Mason et al. 2000, Butler et al. 2011).

Furthermore, the non-uniform distribution of the neonicotinoid insecticides in plants creates refugia during the season resulting in selection pressure for accelerated insecticide resistance development (Hoy et al. 1998, Gressel 2011). Concentration of insecticides were variable both within and between treatments season-long (Fig. 3). Average residue concentration for imidacloprid was 6.2 µg g-1(±8.9; min. 0.5; max 106.6) in 2010 and 9.1 µg g-1 (±11.6; min. 0.4; max 13.3) in 2011. Average thiamethoxam residue concentration was 1.4 µg g-1 (±2.1; min. 0.1; max 13.3) in 2010 and 1.4 µg g-1 (±2.3; min.0.1; max 21.3) in 2011. High densities of small larvae of L. decemlineata were observed in the untreated plots (Fig. 4) in both years of the study and these stages occurred concurrently with detection of low insecticide doses (Fig. 2).

Furthermore, clear differences in the levels of control were apparent between the active ingredients and delivery methods, as numbers of small larvae varied between treatments through time in 2010 (treatment x day interaction, F=8.7; d.f.=42,165; P=<0.0001) and again in 2011

(F=2.4; d.f.=42,165; P=<0.0001).

Two alternative delivery methods, the side dress and impregnated polyacrylamide treatments, were included in these investigations to determine if the duration of high insecticide concentrations could be extended further into the growing season. Side dress applications were once common with older systemic compounds such as disulfoton (Di-Syston® 15G) and aldicarb

(Temik® 15G), but since fell from favor with registration of in-furrow neonicotinoids. In our study, full rate side dress applications of neonicotinoids showed little benefit in extending the interval of insect control or increase residual concentrations of insecticides in the plant. We observed an overall reduction in the residual concentration of either active ingredient associated with the side dress use pattern. Interestingly, this method of neonicotinoid insecticide delivery is

135 currently being utilized for the management another season long pest of potato, the potato psyllid, Bactericera cockerelli (Sulc) (Goolsby et al. 2007, Butler et al. 2011). To achieve adequate control of this novel pest in potato, many producers are now experimenting with split applications of the neonicotinoid insecticides incorporating both an in-furrow and a side dress components.

Polyacrylamide gels are commonly used in horticultural and nursery applications as a soil conditioning agent to improve water retention for plant growth (Johnson 1984, Johnson et al.

1985, Landis and Haas 2012). In our study, polyacrylamide treatments had the highest observed residue levels for both insecticides and the greatest average concentration (Figs. 2 & 3).

Polyacrylamide treatments controlled small larvae for both insecticides in both years (Fig. 4).

Delivery of soluble agronomic products with polyacrylamide and other soil conditioning agents have been researched for several years. In several studies these gels were used as a medium to carry plant nutrients in agricultural applications (Pill and Watts 1983, Henderson and Hensley

1985, Hanafi et al 2002). Bres and Weston (1993) documented impregnation of polyacrylamide with ammonium could positively increase total nitrogen concentration in tomato (Solanum lycopersicum) and promote water retention when compared to standard nutrient delivery methods when grown in the greenhouse. We documented several positive trends for polyacrylamide impregnation with insecticides. Commercial application of impregnated gels could be accomplished as many growers in the state are currently equipped to apply dry granular additives at planting. Moreover, experimentation with different types of commercially available polymers could further refine delivery of insecticides. For large-scale applications, naturally derived starch-based polysaccharides made from corn or wheat (Zeba®, Absorbent Technologies

Inc., Beaverton, OR) may be a suitable alternative to inorganic polyacrylamide products.

136 Neonicotinoid losses and concentrations in leachate. The neonicotinoid insecticide thiamethoxam was included in field experiments to investigating the potential for leaching losses associated with different types of pesticide delivery. Specifically, formulations of thiamethoxam were applied as foliar and at plant systemic treatments in commercial potato over two years and at two different irrigated fields. We hypothesized that thiamethoxam would be most vulnerable to leaching early in the season when plants were small and episodic heavy rains are common. In turn, we observed greatest insecticide losses following vine-killing operations much later in the growing season (Fig. 5). Detections of thiamethoxam in lysimeters varied between treatments through time in 2010 (treatment x day interaction, F=2.1; d.f.=20,88; P=0.0131) and again in

2011 (F=1.8; d.f.=20,87; P=0.0384). Overall trends suggested that on average, impregnated polyacrylamide delivery produced the greatest amount of thiamethoxam leachate late in each growing season (Fig. 5).

Early season rainfall was not exceptionally heavy in either year of this experiment (Fig.

6). The accumulation of leachate detections in lysimeters likely is reflected by the steady application of irrigation water and rainfall. One clear exception to this pattern occurred in 2012 at 155-156 days after planting when 89 mm of rain fell within a 24-hour period. Peak detections of thiamethoxam in this year (2012) began to trend upward following this rain event, however the timing of similar detections across treatments in 2011 occurred at about the same time. One additional explanation may be that increased levels of pesticide losses are associated with plant death or senescence. In each year of this study, the largest proportion of pesticide detections in leachate occurred shortly after vine killing in potato. Vine killing in commercial potato production is a common practice designed to aid the tubers in developing a periderm. Perhaps the rapid loss in root function following plant death permits excess pesticide to be solubilized and

137 washed through the soil profile more quickly. In both seasons of this study, however, large episodic rain events did not occur early in the growing season. These results do appear, however, to document low to moderate levels of leaching losses that occur throughout the season even when the crop is managed at nominal evo-transpirative need.

Untreated control plots also yielded low-level detections of thiamethoxam throughout both seasons. To better understand these insecticide losses, we sampled water directly from the center pivot irrigation system providing irrigation directly to the potato crop. Samples were taken directly from lateral spigots mounted on the well heads while the systems were operational. In both years, samples revealed low concentrations of thiamethoxam present in the groundwater at two time points in the season (Table 2) from which irrigation water was being drawn. These positive detections of low-dose thiamethoxam concentrations being unintentionally applied directly to the crop through irrigation is new information for producers in the Central Sands of

Wisconsin. Although systemic neonicotinoids have recently been detected from surface water runoff and catch basins associated with irrigated orchards (Hladik and Calhoun 2012, Starner and

Goh 2012), to our knowledge no other study has documented the occurrence of neonicotinoids in subsurface groundwater being recycled through operating irrigation wells. Currently, the known exposure pathways for insecticide residues are most often associated with direct application or systemic movement of insecticides in floral structure and guttation water (Hopwood et al. 2012).

The implications for non-target effects resulting from these groundwater contaminants could be immense considering the scale of irrigation ongoing in the Central Sands potato agroecosystem in Wisconsin. Although such impacts have yet to be documented directly, new comprehensive reviews of neonicotinoid environmental impacts have demonstrated numerous other unanticipated impacts occurring at the ecosystem scale (Sánchez-Bayo et al. 2013). Implications

138 for area-wide application of neonicotinoid insecticides through irrigation water applications may

have considerable unanticipated or undocumented environmental impacts for non-target

organisms through chronic low-dose exposure to insecticides.

Conclusions. To gain a better understanding of the seasonal cycles of neonicotinoids in

the potato system, this study used two experimental approaches to document the in plant

concentrations of these pesticides in the plant canopy and the leaching potential of selected

neonicotinoid application methods. Results presented here benefit both potato producers and

regulators by identifying trends in leachate losses for these commonly used, water-soluble

insecticides and characterizing the potential for low dose exposure in plants that may influence

resistance development. We observed variable concentrations of neonicotinoid residues within

plant canopies over nine consecutive weeks following crop emergence from the soil. Control of

L. decemlineata was adequate for all treatments aside from side-dress applications applied at second hilling of the crop. Insects were maintained below spray thresholds for approximately five consecutive weeks following crop emergence. Resurgence of L. decemlineata occurred near

the end of the first generation in 2010 demonstrating loss of efficacy as a result of low dose

concentrations of neonicotinoids in the potato canopy. Lysimeter experiments documented loss

of thiamethoxam following the application of vine desiccants at the conclusion of the potato

production season. Leachate losses did vary among the different delivery methods over time

indicating some variability in the patterns of pesticide leaching throughout the season.

Documentation of several neonicotinoids in irrigation water indicates a new candidate pathway

for non-target environmental impacts of these insecticides.

139

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Zhao, J.-Z., B. A. Bishop, and E. J. Grafius. 2000. Inheritance and synergism of resistance to imidacloprid in the Colorado potato beetle (Coleoptera: Chrysomelidae). J. Econ. Entomol. 93: 1508-1514.

147 Tables and Figures 4.97 . 0.67 . 1.32 0.05 5.12 . 0.68 . 0.94 2.04 . . 1.02 0.88 0.26 . 0.23 . 0.43 0.56 ) 1 -

- - - - ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± thiamethoxam

1.25 1.50 0.69 2.41 0.67 5.31 1.61 1.31 1.26 3.00 2.97 0.52 1.08 1.25 1.81 0.63 0.21 0.88 0.32 1.92 1.40 4.34 . 0.81 . 0.09 0.69

------± - - - ± ± - - - ± - - ±

imidacloprid 0.78 0.54 2.77 0.33 0.34 Average Average concentration (µg Liter 0.10 0.03 . 0.24 . . 0.36 0.19

- ± ± ------± - ± ± - ± ± ± - ± ± -

clothianadin 0.54 0.25 3.43 0.54 0.73 0.41 0.63 0.62 0.30 e 1 5 23 n positive samples 2 1 9 1 2 2 2 1 3 1 2 4 1 4 1 7 5 2 9 1 2 1 4 d

6 6 9 6 7 7 8 15 10 16 17 20 16 17 10 17 10 12 8,9 2,5,6 17,18 11,12 19,20 11,12,13 11,12,13 Well ID 19,20,21,23

c 0.5 0.0 0.1 0.3 0.1 8.2 0.0 1.0 0.6 0.8 0.0 0.0 0.1 0.9 0.4 0.0 0.0 0.0 0.1 14.0 11.0 10.9 13.8 14.4 11.1 12.8 potato percent

b 5,436 9,582 row 21,385 47,827 25,795 31,931 29,447 24,894 33,375 14,402 40,571 24,871 39,322 74,566 38,840 45,309 33,576 27,693 38,309 7 40,138 45,324 46,686 36,676 (ha) crops 101,527 110,979 107,214

0 1 7 a 18 29 30 22 87 34 49 33 13 47 343 328 356 188 213 area (ha) 2,617 2,630 3,989 4,188 4,184 4,066 7,364 4,536 potato ms Positive (means±SD) neonicotinoid detections in groundwater from detections neonicotinoid 2008-2012, (means±SD) inPositive groundwater of of Wisconsin State Department County Adams Grant Iowa Richland Sauk Waushara Ada Dane Iowa Richland Sauk Adams Brown Dane Grant Iowa Sauk Waushara Adams Brown Dane Grant Iowa Portage Sauk Waushara Agriculture Trade Trade Consumer and Protection. Agriculture Table 1. Year 2008 2009 2010 2011

Table 1. continued,

2012 Adams 4,263 27,037 13.6 1,3,4,6 6 0.52 ± 0.30 0.51 ± 0.26 0.27 ± Dane 11 115,501 0.0 8 1 0.67 ± . - - Grant 4 72,920 0.0 10 1 0.26 ± - - Iowa 369 40,764 0.9 12 2 0.24 ± 0.28 ± . 0.44 ± . Juneau 907 28,542 3.1 14 2 0.42 ± 0.18 - 0.20 ± . Portage 7,622 46,337 14.1 15 2 - 0.47 ± . 0.47 ± . Waushara 5,904 38,999 13.1 21,22,23 13 - 0.68 ± 0.88 1.51 ± 0.72 N = 23 67 25 30 68 Five year summary Average: 0.62 ± 0.63 0.79 ± 0.83 1.59 ± 1.51 Range: (0.21-3.43) (0.26-3.34) (0.20-8.93) aAcreage estimates generated from USDA National Agricultural Statistics Service – Cropland Data Layer, 2008-2012. bRow crops class is the sum of the following crop areas (ha): maize, soy, small grains, wheat, peas, sweet corn, and miscellaneous vegetables and fruits. cPercent potato calculated as the potato area grown annually divided by total areable row crop acreage (other row crops + potato) dWell identification numbers correspond to point references in Figure 1. ePositive neonicotinoid detections extracted from long-term, nested groundwater wells maintained by the WI-DATCP Groundwater Program. 148

149

Table 2. Thiamethoxam concentration from irrigation water, 2011 and 2012.

Days after Date Concentration (μg Liter-1)a planting

28 June 2011 39 0.310 1 September 2011 114 0.327 10 July 2012 60 0.533 15 August 2012 96 0.580 aSamples obtained from irrigation pivots while under operation in potato fields containing lysimeter experiments.

150

N 0 5025 100 Km Portage

15 Brown

22 7 19 14 20-21 5 23 Waushara Adams 6 2 4 Juneau 3 1

Sauk

Richland 16 17-18 8 10 11-13 Dane Iowa 9 Grant

Figure 1. Positive thiamethoxam residue detections in groundwater 2008-2012. Numbering corresponds to Well ID in Table 1. Dark grey shaded region indicates the Central Sands potato production region. Light grey delimits the Lower Wisconsin River potato production region. Positive detections were obtained from either established agrochemical monitoring wells or private well samples submitted to the Wisconsin Department of Agriculture, Trade and Con- sumer Protection (DATCP) – Environmental Quality division in collaboration with the Wiscon- sin DATCP Bureau of Laboratory Services. 151 Imidacloprid 40 A. Impregnated polyacrylamide In-furrow Seed treatment Side dress 30 Untreated control

20

10

0

40 B. -1

30

20

10 Figure 2. Average neonicotinoid residue concentration in potato 0 foliage for A) imidacloprid concen- Thiamethoxam tration 2010, B) imidacloprid concentration 2011, C) thiame- 8 C. Impregnated polyacrylamide In-furrow thoxam concentration 2010, and D) Seed treatment Side dress thiamethoxam concentration 2011. insecticide concentration (µg gram tissue ) 6 Untreated control Note, side dress application was replaced with seed treatment appli- 4 cation in 2011. (means ± SEM) 2 Average 0 8 D.

6

4

2

0 40 60 80 100 Days after planting 152 Imidacloprid A. Impregnated polyacrylamide 100 In-furrow Seed treatment Side dress 75

50

25

0 36 43 50 57 64 71 78 85 92 B. 100

75 -1 50 Figure 3. Neonicotinoid residue 25 concentration measured in potato foliage for A) imidacloprid concen- tration 2010, B) imidacloprid 0 43 50 57 64 71 78 85 92 99 concentration 2011, C) thiame- Thiamethoxam thoxam concentration 2010, and D) C. Impregnated polyacrylamide thiamethoxam concentration 2011. 20 In-furrow Seed treatment Box plots show pooled variation for Side dress all treatments at each sample date. 15 Dotted lines designate the mean residue concentration averaging over 10 Insecticide concentration (µg insecticide gram tissue ) all sample dates and treatments.

5

0 36 43 50 57 64 71 78 85 92

20 D.

15

10

5

0 43 50 57 64 71 78 85 92 99 Days after planting 153

imidacloprid A. Imp. polyacrylamide Seed treatment In-furrow Side dress 150 thiamethoxam Imp. polyacrylamide Seed treatment In-furrow Side dress untreated Control 100

50

0

B.

150 Small larvae (means ± SEM) per ten plants Small larvae (means ± SEM) per 100

50

0

40 60 80 100 Days after planting

Figure 4. Mean estimates of small larvae per ten plants among neonicotinoid delivery treatments in A) 2010 and B) 2011 at the Hancock Agricultural Experiment Station, Hancock, Wisconsin. 154

Untreated control vine kill A. (113) 20 Foliar Seed treatment In-furrow Impregnated polyacrylate

15

10 -1

5

Figure 5. Average thiamethoxam recovered for in-furrow and foliar 0 treatments in A) 2011 and B) 47 61 91 123 154 184 Days after planting 2012. Dotted lines indicate the date that the producer applied vine vine kill B. (128) desiccant prior to harvest. Lysim- 20 thiamethoxam concentration (µg insecticide L ) eter studies continued in undis- turbed soil following vine kill.

(means ± SEM) 15 Average

10

5

0 49 79 110 141 171 202 Days after planting 155

10 1200 A. Total Irrigation Rain

7.5 900

vine kill

5.0 600

Figure 6.Water inputs and

2.5 300 leachate volume collected in lysimeters studies in A) 2011 and Cumulative water input (mm) B) 2012. Lines indicate cumula- tive water measured in tipping bucket rain gauges installed in 0 0 plots each season. Bars indicate average leachate collected in 10 1200 B. vine kill lysimeters on a bi-weekly sam- pling frequency. Rug plots on top of each figure indicate days that 7.5 900 overhead irrigation or rainfall occurred in each season. Average (means ± SEM) lysimer collection volume (L)

5.0 600

2.5 300

0 0 0 50 100 150 Days after planting

156 Supplemental Material

Supplementary Table 1. Effect of insecticide delivery method on neonicotinoid concentration over nine weeks using ANOVA, 2010 and 2011. Compound Year Parametera F dfb P

imidacloprid 2010 intercept 269.1 1 <0.0001 delivery 138.7 3 <0.0001 days after plant 5.5 8 <0.0001 delivery x days after plant 2.5 24 0.0009 2011 intercept 845.9 1 <0.0001 delivery 285.6 3 <0.0001 days after plant 12.4 8 <0.0001 delivery x days after plant 4.3 24 <0.0001 thiamethoxam 2010 intercept 36.1 1 <0.0001 delivery 115.9 3 <0.0001 days after plant 16.3 8 <0.0001 delivery x days after plant 4.9 24 <0.0001 2011 intercept 363.1 1 <0.0001 delivery 166.3 3 <0.0001 days after plant 35.5 8 <0.0001 delivery x days after plant 6.5 24 <0.0001 aParameter terms for fitted objects were added sequentially using anova.lme. bResidual error = 105.

157

Supplementary Table 2. Effect of insecticide delivery and compound on L. decemlineata small larvae abundance in potato using ANOVA, 2010 and 2011.

Year Parameter F dfa P 2010 intercept 148.1 1 <0.0001 days after planting 14.2 6 <0.0001 delivery 5.7 7 <0.0001 delivery x days after plant 8.7 42 <0.0001 2011 intercept 408.6 1 <0.0001 days after planting 6.7 6 <0.0001 delivery 27.2 7 <0.0001 delivery x days after plant 2.4 42 0.0001 aResidual error = 165.

158

Supplementary Table 3. Effect of insecticide delivery on thiamethoxam leachate residue recovered by lysimeters in potato using ANOVA, 2011 and 2012.

Year Parameter F df P 2010ab intercept 65.3 1 <0.0001 days after planting 5.4 4 0.0006 delivery 22.4 5 <0.0001 delivery x days after plant 2.1 20 0.0131 2011c intercept 174.2 1 <0.0001 days after planting 12.2 4 <0.0001 delivery 6.5 5 <0.0001 delivery x days after plant 1.8 20 0.0384 a2010 residue detections were fit with an autoregressive moving average (ARMA) correlation structure. bResidual error = 87. cResidual error = 88.

159

Chapter 5: Concluding remarks and future directions

160 In Wisconsin, potato producers have found that control of early season Colorado potato is important to reduce season-long defoliation pressure. As a result, growers and pest practitioners have been eager to adopt solutions that effectively control founding populations of Colorado potato beetle. From1970-1990 soil applied carbamate (aldicarb, carbofuran) and organophosphate (disulfoton, phorate) insecticides were common at-plant or side-dress applications to manage early season generations of Colorado potato beetle. In Wisconsin, contamination of groundwater, coupled with widespread insecticide resistance, led to a voluntary retraction of specific insecticide registrations (aldicarb) and declining use of the other systemic compounds. With few alternative options, management of Colorado potato beetle relied on a weekly rotation of foliar pyrethroids and carbamates for season-long control. This sequence of active ingredients continued into the early 1990’s until a large proportion of commercial potato began to experience field-scale failures principally associated with the use of the synthetic pyrethroid class. At this time, producers were applying an increasing number of applications with as many as 7-9 foliar applications of synthetic pyrethroids required to achieve even a modest level of crop protection. This trajectory was changed swiftly when, in 1995, a new class of systemic insecticides, the neonicotinoids (IRAC MoA 4a), was registered in potato for at-plant application. This new mode of action class had exceptional activity on several key insect pests of potato (Colorado potato beetle, potato leafhopper, and colonizing aphids). Since 1995, the neonicotinoids have become the cornerstone of early season potato beetle management throughout the potato growing community. Continual use of this insecticide class in the 18 years since registration has now resulted in a considerable erosion of Colorado potato beetle control.

Over the past five years, growers continue to utilize at-plant systemic neonicotinoids for control of potato leafhopper and colonizing aphid species, while expecting limited activity on potato

161 beetle. One common solution for problematic early season beetle populations has been to apply a systemic neonicotinoid at-plant followed by repeated foliar tank mixes of phosmet (Imidan®, organophosphate) and endosulfan (Thiodan®, organochlorine). Unfortunately, the use of several different active ingredients as tank mixes within a single generation of pests is known to accelerate the selection pressure for resistant insects. Fixation of resistance genes in the population will further compromise efficacy and durability of these insecticides and future registrations.

Colorado potato beetle insecticide resistance is a process operating at multiple, interrelated scales, from the individual to the ecosystem. Past potato beetle resistance research can often be categorized into one of three areas: physiological detoxification mechanisms, genes driving expression of those mechanisms, and field-level response to chronic exposure. These studies frequently examined the negative effects of resistance from the potato production perspective, measuring costs of resistance as it relates to direct economic losses for the producer.

Emphasis on the crop leaves about 75% of the resistant insect’s life cycle unstudied, which explains our limited understanding about how insecticide resistance may influence survivorship, , dispersal, or diapause beyond the crop. An increased understanding of how insecticide use may adversely affect resistance development, the physiology of resistance and the ecology of Colorado potato beetle will provide crucial insight into the development of more biologically-based, sustainable applications of current and novel pest management tools in potato. Here, we pursued two primary research areas: first, to continue improvement of systemic insecticide management of Colorado potato beetle while reducing chemical losses into the environment, and second, to better determine the influence of annual potato rotation and diapause habitat composition on Colorado potato beetle colonization patterns.

162 Specifically, this thesis had three primary areas of emphasis: 1) to describe the diapause

ecology of Colorado potato beetle and relate this to the temporal patterns of systemic

neonicotinoid concentrations in potato (Insecticide use); 2) to characterize the emergence

phenology of Colorado potato beetle populations with different histories of neonicotinoid

exposure (Phenology); and 3) to relate insect abundance to landscape composition (Crop colonization). These three objectives contribute to an improved understanding of neonicotinoid resistance, environmental fate of insecticides, and population dynamics at scales previously unexplored in the Colorado potato beetle system.

Crop colonization: To better understand the contribution of distance of annual potato rotation on measured beetle abundance, insect counts were modeled in relation to the area of previous year potato with a blend of geospatial (GIS) and statistical techniques. Additionally, to understand if habitat quality surrounding previous year potato affected insect abundance, high quality habitat surrounding identified previous year fields we defined and related to these count data. To determine field-level colonization risk, beetle scouting data was integrated with field locations of previous potato, and digital land use layers into a statistical analysis for two separate years of insect counts (Chapter 2). Models indicated that distance from, or proximity to previous year’s potato distance was important in some, but not all years. Area of previous year’s potato was also not strongly significant in either year of analysis. Moreover, we found minimal statistical evidence that habitat of high quality surrounding previous year potato influenced beetle abundance. Grassland habitats and transportation ditches were, however, negatively associated with abundance of beetles. Though strong relationships were not observed, outcomes include the need for more research-based information about potato rotation and the influence of habitats on beetle abundance.

163 Insecticide use: To determine the temporal variability in both above and below ground neonicotinoid concentrations, two different assay techniques were used to compare several different insecticide delivery methods. First, an enzyme-linked immunosorbant assay (ELISA) was optimized to measure the concentration of imidacloprid and thiamethoxam in potato foliage over time following the different insecticide delivery treatments. Insects colonizing the potato plots were also counted to document the response of a resistant population (HAES) to the insecticide concentrations measured by our assay. One key result of this research was the identification of a point in the growing season (50 days after planting) when neonicotinoid concentrations fell considerably (Chapter 4). This below average concentration in all systemic treatments corresponded with rapid canopy expansion. A second key observation was the large variability of insecticide concentrations that existed early in the season with measurements ranging from near zero to 106 μg g tissue-1 in the same plot. These data clearly illustrate that spatial insecticide refugia exist among plants and could have considerable influence upon the rate of insecticide resistance acting upon specialist herbivores as well as colonizing insects that persistently transmit plant pathogens including Potato leafroll Polerovirus, Aster Yellows

Phytoplasma, and Zebra Chip, (PLRV, PPT, ZC).

In a second component, liquid chromatography-mass spectrometery (LC/MS) was used to document leaching of systemic thiamethoxam from under commercial production conditions in collaboration with Wisconsin Department of Agriculture, Trade and Consumer Protection. Using vacuum style, pan lysimeters buried beneath potato, leachate was captured on a bi-monthly basis from among several different thiamethoxam application methods. Leachate analyses documented variable insecticide losses over time. One important result was this observation that the greatest losses occurred in the potato crop once vine killing had occurred in autumn for all treatments

164 (Chapter 4). A second important finding of this research component was the detection of low, but measurable detections of neonicotinoids in the groundwater used for irrigation. Although there appears to be a low risk of acute toxicity with these low insecticide concentrations in groundwater, sub-leathal effects are difficult to measure over shorter time periods (e.g. greater pest resistance, residues on produce, species diversity); the cumulative effects of these chronic, low-doses may have a substantial impact on the long term health of the Central Sands agroecosystem.

Phenology: To determine if the sequence of insect management tactics could select for either delayed diapause, or extended periods of emergence from overwintering, Colorado potato beetle populations managed under three very different management regimes (i.e. systemic, foliar, or mixed insecticide application history) were compared . Specifically, emerging insects were collected every other day in the spring and each individual insect was measured and sexed. Using these insect capture records, estimated differences in overall survivorship and rate of emergence were modeled using a non-linear strategy (Chapter 3). Using this approach, direct comparisons between insecticide management histories were possible. Observed insect counts demonstrated that management history was unable to explain variability in the patterns of emergence phenology for the selected populations. Although management history was not a significant predictor of variable emergence from overwintering, we did observe that neonicotinoid resistant populations tended to emerge earlier and at a greater rate than susceptible populations.

Furthermore, insects that emerged earlier were more fecund than those remaining in the soil for longer periods.

165 Future directions:

Crop colonization: With some certainty, growers and pest management practitioners in the Central Sands expect infestations of Colorado potato beetle, which explains in part, the use of systemic neonicotinoids on 85% of potato acres planted annually. Though field level risk of colonization is high throughout the growing region, distributions of Colorado potato beetle infestation within fields are often very uneven. In Chapter 2, we generated an estimate of

Colorado potato beetle infestation by aggregating scouting points (N=16 per field) into an overall mean abundance to estimate colonization risk. Although this approach defined a field-level risk, more useful information may be gained from measurements at the point-level. Use of independent counts and their adjacent landscapes may produce improved information about the probability for Colorado potato beetle infestations. Using a more refined statistical approach, such as a zero-inflated Poisson (ZIP) mixture model coupled with a conservative parameter selection strategy with Bayesian Information Criterion, count data taken in 1998 and 2008 could be used to generate a fine-scale risk model. Using the ZIP approach, researchers could perhaps better interpret the contribution of zero counts with a logit distribution while interpreting measured count data with the Poisson modeling component. Validation of this modeling exercise would be completed with the direct comparison of observed and predicted counts generated from parameters of opposite year model parameters. With the addition of a few years of data collected in the same way, the stability of the 1998 and 2008 modeling strategy could be tested and improved.

Insecticide use: Wisconsin vegetable growers continue to rely heavily on neonicotinoid insecticides for the control of damaging populations of key insect pests through a combination of in-ground and foliar applications (Chapter 4). In 2010, the WI-DATCP, Environmental Quality

166 section released an annual report indicating localized detections of the neonicotinoid insecticide, thiamethoxam, from groundwater wells. Positive detections of neonicotinoids in groundwater are an emerging concern confronting both agricultural and regulatory groups in Wisconsin. Should these detection levels of thiamethoxam continue to increase, the widespread use of at-plant neonicotinoids in potato production may be in jeopardy of targeted use restrictions. New research to document the timing and spatial extent of these contaminations in operating irrigation wells is needed.

To determine the spatial scales of variation in neonicotinoid detection, a hierarchical variance components model using a nested ANOVA with 4 levels of random effects: test region and well site nested within region. Inclusive models could consider both within and among well sites separately for each time period to determine whether spatial patterns of detection differ by time period tested. Similar patterns of detection among spatial scales over time periods would suggest that groundwater contamination of neonicotinoids is very uniform and independent of cropping history above ground. Conversely, dissimilar patterns would suggest that contaminations are more discrete in occurrence, and may well be linked to localized agricultural practices implemented on the landscape above the test wells.

Phenology: Objectives from Chapter 3 highlighted variability in the emergence phenology of different populations of Colorado potato beetle. One considerable pitfall of this study resulted from the limited number of replicates available among insecticide management groups. Logistically, obtaining a sufficient number of insects from each group is often problematic for several reasons such as crop rotation, late season insecticide decisions, and low densities of insects. Improvement on the common garden idea may involve selection of several populations of systemic and foliar management histories. To avoid low densities for several

167 types of management, the experimental design could be simplified into a pairwise comparison of a systemic, conventional management program to an alternative management strategy. One key advantage of these management treatments is that insect abundance is generally quite high late in the growing season, especially small market gardens and highly resistant populations. Moreover, an increase in the number of populations and replication within population may significantly enhance the power to test for significant differences in patterns of emergence within a common garden study.

Project impact and outcomes: My research project tested hypotheses that further our understanding of the biology and ecology one of a key pest of commercial potato, the Colorado potato beetle. This project sought to better understand effective management of this pest with a foundation based upon sound ecological principles in the field and resistance assessments generated in the laboratory. I have tried to balance the development of short-term management solutions for resistant beetle populations with research to improve our understanding of insect pest populations within the broader agroecosystem that will lead to the development of long- term, sustainable, management solutions.