University of Florida Thesis Or Dissertation

DEVELOPMENT AND APPLICATION OF INTEGRATED PEST MANAGEMENT STRATEGIES TO MANAGE KEY ARTHROPOD PESTS AND BENEFICIALS IN ORGANIC ZUCCHINI SQUASH

LORENA LOPEZ

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2019

To my grandparents Blanca and Piry for being proud of me until the end of their days

ACKNOWLEDGMENTS

I would like to gratefully acknowledge the University of Florida Entomology and

Nematology Department for their partial funding of my doctoral degree. I would also like to thank the USDA-SARE Graduate Student Grant program and FDACS-Specialty Crop Block

Grant Program (SCBGP) for their financial support of my research. I would like to thank my major professor, Dr. Oscar E. Liburd for his endless support. His advice helped me to grow as a student and as a professional. I thank my committee members, Dr. Tesfa Mengistu and Dr. Babu

Srinivasan for their guidance in using molecular techniques for virus detection, Dr. Daniel

Carrillo for his advice in maintaining my mite colonies, and Dr. Sabine Grunwald for her guidance in running geostatistical analysis.

I especially want to thank all past and present members of the Small Fruit and Vegetable

IPM Laboratory at the University of Florida for their help during field and lab work. I thank the staff and workers at the University of Florida’s Plant Science, Research and Education Unit

(PSREU), in particular Buck Nelson for his assistance maintaining the plants for my research. I would like to thank Charley Andrews from his guidance and great environment to work in at the

Hammock Hollow Farms. I also thank Dr. Edzard van Santen and Dr. Salvador Gezan for their statistical guidance.

Finally, the relentless support of my family and friends deserves special recognition during my doctoral studies. I want to thank my parents and my sister for their unconditional and infinite support, my loving boyfriend who always push me towards my goals, my best friends from Colombia who were always there to make me laugh when overwhelmed, my friends in

Florida who cheered me up when down, and last but not least, thanks to my pup for keeping me company during countless nights of work.

TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 8

LIST OF FIGURES ...... 10

ABSTRACT ...... 13

CHAPTER

1 INTRODUCTION ...... 15

2 LITERATURE REVIEW ...... 17

Pest and Disease Management ...... 17 Conservation Biological Control ...... 20 Augmentation Biological Control...... 22 Spatio-Temporal Analysis ...... 24 Justification ...... 26 Objectives ...... 28

3 MONITOR THE ESTABLISHMENT OF INSECT VECTORS AND PLANT VIRUSES IN SQUASH ...... 30

Materials and Methods ...... 31 Study Site ...... 31 Plant Culture ...... 31 Experimental Design ...... 32 Sampling ...... 34 Statistical Analysis ...... 36 Results...... 37 Aphids and Aphid-Transmitted Viruses ...... 38 Aphids in squash, marigolds, and cowpeas (2015 experiments) ...... 38 Aphids in squash, marigolds, and alyssum (2017 experiments) ...... 40 Aphid-transmitted viruses ...... 42 Whiteflies ...... 43 Whiteflies in the 2015 experiments ...... 43 Whiteflies in the 2017 experiments ...... 44 Squash silverleaf (SSL) disorder ...... 46 Cucurbit leaf crumple virus (CuLCrV) ...... 46 Thrips ...... 46 Thrips on the squash during the 2015 experiments ...... 47 Thrips on the squash during the 2017 experiments ...... 48 Thrips on the companion plants ...... 49

Plant Dimensions and Yield ...... 49 Discussion ...... 50

4 EVALUATE THE EFFECT OF COMPANION PLANTS AND AMBLYSEIUS SWIRSKII INTRODUCED IN ZUCHINNI SQUASH CROPS ...... 88

Materials and Methods ...... 89 Plant Culture ...... 89 Experimental Design ...... 90 Sampling ...... 91 Statistical Analysis ...... 92 Results...... 92 Naturally Occurring Predators ...... 93 Naturally Occurring Parasitoids ...... 96 The Introduced Biological Control Agent, Amblyseius swirskii ...... 99 Discussion ...... 99

5 IDENTIFY TEMPORAL AND SPATIAL DISTRIBUTION PATTERNS OF KEY INSECT PESTS AND A PREDATORY MITES SPECIES IN A SQUASH CROP WITH 25% COMPANION PLANT DENSITY USING GEOSTATISTICAL TECHNIQUES ...... 118

Materials and Methods ...... 120 Study Site ...... 120 Plant Culture ...... 120 Experimental Design ...... 121 Sampling ...... 123 Geostatistical Analysis: Ordinary Kriging ...... 124 Results...... 127 Spatio-Temporal Distribution Patterns ...... 127 Variography ...... 130 Model Performance ...... 131 Squash Cultivars, Silverleaf Index, and Yield ...... 132 Discussion ...... 133

6 ASSESS THE SIDE-EFFECT OF TWO BIOINSECTICIDES ON A. SWIRSKII MITES UNDER LABORATORY AND GREENHOUSE CONDITIONS ...... 154

Materials and Methods ...... 156 Mite Colonies ...... 156 Experimental Design ...... 157 Laboratory Experiments ...... 158 Greenhouse Experiments ...... 160 Statistical Analysis ...... 161 Results...... 162 Laboratory Experiments ...... 162 Greenhouse Experiments ...... 166

Discussion ...... 168

7 CONCLUSION...... 188

APPENDIX

DATA DISTRIBUTION CRITERIA FOR PEST AND BENEFICIAL ARTHROPODS ...... 192

LIST OF REFERENCES ...... 197

BIOGRAPHICAL SKETCH ...... 205

LIST OF TABLES

Table Page

3-1 Percentage (n = number) of samples showing positive results for viral infection during the fall of 2015...... 59

3-2 Percentage (n = number) of samples showing positive results for viral infection during the fall of 2017...... 60

3-3 Averaged height and width per squash or companion plant...... 61

3-4 Mean number of leaves per squash plant from six plants per plot in 2015 and four plants per plot in 2017...... 62

4-1 Mean number (±SE) of predators collected per yellow sticky trap over a six-week (spring) and a five-week (fall) period during the 2015 experiments...... 105

4-2 Mean number (±SE) of predators collected per pan trap over a four-week period during the 2015 experiments. T ...... 106

4-3 Mean number (±SE) of predators collected per yellow sticky trap over a five-week period during the 2017 experiments...... 107

4-4 Mean number (±SE) of predators collected per pan trap over a five-week period during the 2017 experiments...... 108

4-5 Mean number (±SE) of parasitoids collected per yellow sticky trap over a six-week (spring) and a five-week (fall) period during the 2015 experiments...... 109

4-6 Mean number (±SE) of parasitoids collected per pan trap over a four-week period during the 2015 experiments...... 110

4-7 Mean number (±SE) of parasitoids collected per yellow sticky trap over a five-week period in 2017 experiments...... 111

4-8 Mean number (±SE) of parasitoids collected per pan trap over a five-week period during the 2017 experiments...... 112

5-1 Number of Amblyseius swirskii motiles (immatures, adult males and females) counted prior to release into the field...... 140

5-2 Descriptive statistics including mean, maximum (Max), minimum (Min), standard error (SE), median, and skewness for sweetpotato whitefly egg and immature, Amblyseius swirskii motile, and aphid numbers per squash leaf ...... 141

5-3 Summary of semivariogram parameters for ordinary kriging interpolation analysis used for mean numbers of sweetpotato whitefly eggs and immatures, its predator Amblyseius swirskii, and aphids present in the squash during fall 2018...... 142

5-4 Summary of mean (ME), root mean square (RMSE), and root mean square standardized errors (RMSSE) used for evaluation of model accuracy in estimating mean numbers of sweetpotato whiteflies, Amblyseius swirskii mites, and aphids on squash leaves...... 143

6-1 Decision making scheme used as reference to evaluate the effects of Azera and M- Pede on Amblyseius swirskii females, nymphs, and larvae during laboratory and greenhouse experiments...... 175

6-2 Number of Amblyseius swirskii motiles (immatures, adult males and females) counted prior to release into the greenhouse...... 176

6-3 Pesticide classification for Amblyseius swirskii females and immature stages (nymphs and larvae) using the adapted evaluation scheme for laboratory and greenhouse experiments...... 177

LIST OF FIGURES

Figure Page

3-1 Plot and treatment arrangement for 2015 experiments...... 63

3-2 Plot and treatment arrangement for 2017 experiments...... 64

3-3 Arbitrary index used for Squash silverleaf (SSL) ratings during 2015 and 2017 experiments ...... 65

3-4 Mean (±SE) number of apterae aphids sampled by in situ counts ...... 66

3-5 Mean (±SE) number of winged aphids sampled in spring 2015 ...... 67

3-6 Mean (±SE) number of aphids sampled in fall 2015...... 68

3-7 Mean (±SE) number of apterae aphids sampled in spring 2017 ...... 69

3-8 Mean (±SE) number of winged aphids sampled in fall 2017...... 70

3-9 Mean (±SE) number of apterae aphids sampled in fall 2017 ...... 71

3-10 Mean (±SE) number of whitefly adults collected by yellow sticky traps in 2015...... 72

3-11 Mean (±SE) number of whitefly adults recorded in spring 2017 ...... 73

3-12 Mean (±SE) number of adult whiteflies collected in fall 2017 ...... 74

3-13 Averaged Squash silverleaf (SSL) disorder index (±SE) rated in 2015...... 75

3-14 Averaged Squash silverleaf (SSL) disorder index (±SE) rated in 2017...... 76

3-15 Mean (±SE) number of thrips collected in spring 2015 ...... 77

3-16 Mean (±SE) number of thrips collected in fall 2015 ...... 78

3-17 Mean (±SE) number of Frankliniella bispinosa collected in spring 2017 ...... 79

3-18 Mean (±SE) number of Frankliniella bispinosa collected in fall 2017 ...... 80

3-19 Mean (±SE) number of thrips recorded by in situ counts in the companion plants in 2015...... 81

3-20 Mean (±SE) number of thrips recorded by in situ counts in the companion plants in 2017...... 82

3-21 Total marketable yield, total unmarketable yield, and total fruit injured by pickleworms (±SE) harvested in 2015...... 83

3-22 Total marketable yield, total unmarketable yield, and total fruit injured by pickleworms (±SE) harvested in 2017...... 84

3-23 Average, maximum, and minimum temperature (°C), percentage of relative humidity (%RH), and total rain (mm) for 2015...... 85

3-24 Average, maximum, and minimum temperature (°C), percentage of relative humidity (%RH), and total rain (mm) for 2017...... 86

3-25 Cowpea infested with hundreds of apterae and winged aphids...... 87

4-1 Mean (±SE) number of the predatory mites, Amblyseius swirskii, recorded per leaf disc (4-cm2) during 2017...... 113

4-2 Mean (±SE) number of parasitoids collected in spring 2015 ...... 114

4-3 Mean (±SE) number of parasitoids collected in fall 2015 ...... 115

4-4 Mean (±SE) number of parasitoids collected in spring 2017 ...... 116

4-5 Mean (±SE) number of parasitoids collected in fall 2017 ...... 117

5-1 Plot and treatment arrangement for 2018 on-farm experiments...... 144

5-2 Sampling point randomization and geo-referenced grid used in fall 2018...... 145

5-3 Population densities of sweetpotato whitefly eggs, immatures, and predatory mite Amblyseius swirskii motiles (immatures, adult males and females) on squash leaves ....146

5-4 Spatial distribution of the sweetpotato whitefly eggs and immatures, and Amblyseius swirskii motiles (immatures, adult males and females) recorded per squash leaf...... 147

5-5 Spatial distribution of aphids collected in two experimental plots and the relationship between aphid numbers measured and predicted per leaf for control and treatment plots ...... 148

5-6 Relationship between sweetpotato whitefly eggs measured and predicted values for each week during a five-week sampling period in fall 2018...... 149

5-7 Relationship between sweetpotato whitefly immatures measured and predicted values for each week in a five-week sampling period in fall 2018...... 150

5-8 Relationship between Amblyseius swirskii motiles measured and predicted values for each week in a five-week sampling period in fall 2018...... 151

5-9 Insect and mite population densities, SSL ratings, and yield collected per plots and cultivars...... 152

5-10 Average, maximum, and minimum temperature (°C), and percentage of relative humidity (%RH) for the squash season in fall 2018...... 153

6-1 Treatment set-up for 2018 evaluations of insecticide residual effects on A. swirskii...... 178

6-2 Experimental arrangement for the laboratory experiment conducted in fall 2018...... 179

6-3 Experimental arrangement for the greenhouse experiment conducted in fall 2018...... 180

6-4 Mean (±SE) mortality of Amblyseius swirskii ...... 181

6-5 Mean (±SE) mortality of Amblyseius swirskii females, nymphs, and larvae across insecticides and release days during laboratory experiments...... 182

6-6 Mean (±SE) mortality of Amblyseius swirskii females, nymphs, and larvae between insecticides and release days during laboratory experiments...... 183

6-7 Mean (±SE) mortality of Amblyseius swirskii over time at each release day during laboratory experiments...... 184

6-8 Mean (±SE) number of Amblyseius swirskii adults, immatures (larvae and nymphs), and eggs among insecticides and release days during the greenhouse experiments...... 185

6-9 Mean (±SE) numbers of Amblyseius swirskii adults, immatures (larvae and nymphs), and eggs between insecticides and release days during greenhouse experiments...... 186

6-10 Mean (±SE) mortality of Amblyseius swirskii over time at each release day during greenhouse experiments...... 187

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

DEVELOPMENT AND APPLICATION OF INTEGRATED PEST MANAGEMENT STRATEGIES TO MANAGE KEY ARTHROPOD PESTS AND BENEFICIALS IN ORGANIC ZUCCHINI SQUASH

Lorena Lopez

May 2019

Chair: Oscar E. Liburd Major: Entomology and Nematology

Florida is a major producer of zucchini squash (Cucurbita pepo L., Cucurbitaceae) and produced 18% of the US squash in 2016, valued at about $30 million dollars. Key insect pests including the sweetpotato whitefly (Bemisia tabaci Genn., B biotype, Hemiptera: Aleyrodidae), the melon and the cowpea aphid (Aphis gossypii Glover and Aphis craccivora C.L.Koch,

Hemiptera: Aphididae), attack zucchini squash and transmit viral diseases that together cause yield losses up to 80%. Aphids transmit viruses of economic importance and reports of whitefly- transmitted viruses in Florida squash have increased in the last few years. Pesticides are generally used for insect and insect-transmitted disease management but the development of insecticide resistance and their adverse effects on non-target organisms are major concerns. This project evaluated a combination of non-pesticidal approaches including cultural practices, augmentation and conservation biological control to manage key pests in organic squash with the ultimate goal of reducing the amount of chemical inputs in the cropping system, limiting the adverse effects of insecticides on non-target organisms, and maintaining environmental quality.

The effects of the African marigold (Tagetes erecta L., Asteraceae), cowpea (Vigna unguiculata

L. (Walp.), Fabaceae), and the sweet alyssum (Lobularia maritima (L.) Desv, Brassicaceae) used

as companion plants, together with the predatory mite, Amblyseius swirskii Athias-Henriot

(Acari: Phytoseiidae) against key insect pests and its effects on viral incidence in squash production were assessed. The outcomes included the development of integrated pest and disease management strategies utilizing companion plants and the predatory mite Amblyseius swirskii

Athias-Henriot (Acari: Phytoseiidae) for organic squash and cucurbit growers in Florida.

CHAPTER 1 INTRODUCTION

Squash production in the US continues to increase from 199 million dollars in cash receipts in 2016 to more than 235 million dollars in 2017 (USDA, 2018). Although most of the squash in the US is produced conventionally, certified organic squash accounts for 24% of the cash receipts from US squash production, valued at 48 million dollars in 2016 (USDA, 2018).

From 2015 to 2016, a 2% increase in the certified organic acreage and a 19% increase in certified organic squash production were reported for the US (USDA, 2016a, 2016b).

Florida ranks second among all states in squash production after California. In 2017,

Florida contributed 17% of the US squash production, valued at 39 million dollars (USDA,

2018). Most squash is produced for fresh market from approximately 3,035-harvested ha on approximately 200 squash farms throughout the state. In 2016, organic squash was harvested from 111-ha from nine certified organic farms in Florida (USDA, 2018), which contributed 5% of the cash receipts from US squash production. Regardless, organic squash demand continues to grow.

Major areas of squash production in Florida include Dade, Broward, Palm Beach, and

Collier counties in the south and Alachua, Columbia, and Gilchrist counties in north Florida

(Mossler & Nesheim, 2014). An additional 400 growers produce other types of cucurbits such as crookneck squash, straightneck squash, scallop squash, acorn, and spaghetti squash for an estimate of ~ 600 cucurbit growers in Florida (Mossler & Nesheim, 2014; USDA, 2014).

Summer squash (Cucurbita pepo L., Cucurbitaceae) is attacked by various species of whiteflies, aphids, and thrips. Florida squash farmers are challenged by insect pest pressure, insect-transmitted viruses, and other diseases caused by fungi and bacteria. The use of large amounts of chemical inputs in the field is expensive and increases the potential for pests’

resistance. By reducing the consumption of insecticides, the cost of production can be significantly reduced (Nyoike & Liburd, 2010).

Flowering companion plants introduced in the field can attract beneficial arthropods that can potentially suppress pest populations. The damage caused by these pests has been studied, but a detailed description about the insect pest complex of squash in Florida, their establishment as the crop ages, and the effect of abiotic factors on their populations and the associated parasitoids and predatory insects in the system is not available. Neither is information showing the effect of companion planting in Florida squash. Similarly, the effect of low-risk chemicals on non-target organisms, such as predators, that may be used for pest control in squash cropping systems have not been studied

Due to its short production cycle, squash is an excellent candidate to include in intercropping and rotation systems (Hooks et al., 2010), and these practices can help to lower pest infestations on squash (Wang, 2012). The use of complimentary techniques including the use of companion plants and the release of biological control agents, such as predatory mites, against insect pests attacking zucchini squash are evaluated in the present study as cost-efficient techniques for producers growing conventional or organic squash. A combination of non- pesticidal approaches including cultural and biological pest management practices (e.g. augmentative biological control) for management of insects can change the way squash cropping systems are managed, and enhancing their adoption by growers, can ultimately lead to reductions in production costs, limiting the adverse effects of insecticides on non-target organisms, and maintaining environmental quality.

CHAPTER 2 LITERATURE REVIEW

Zucchini squash (Cucurbita pepo L. sub. pepo, Cucurbitaceae) is a type of summer squash with bush growth habits that grow best in temperatures between 24 and 29 °C. Squash is a monoecious annual plant that requires approximately 65 days from seed to maturity (Mossler &

Nesheim, 2014). Except for synthetic pesticides and fertilizers, production practices are similar between conventional and organic squash growers in Florida (C. Andrews pers. com.). For ease of cultivation, zucchini squash is seeded or transplanted in double-row raised beds covered in plastic mulch. Raised beds are typically between 76 to 100-cm wide and distance between plants and rows vary from 25 to 38-cm apart (Stephens, 2012). Plant density under closest spacing is

36,250 plants per ha. Squash requires 2.5-cm of water weekly and 95% of the squash grown in

Florida is irrigated, mostly through drip irrigation, and commonly fertigated (i.e., fertilized through the irrigation system) starting two to three weeks after planted/transplanted. Contrary to winter squash, zucchini squash is harvested when immature (20 – 25-cm in size) and hand- picked during multiple harvest spaced three to four days apart (Seal et al., 2016; Mossler &

Nesheim, 2014).

Pest and Disease Management

The damage caused by major insect pests in Florida squash jeopardizes plant development and the production of quality fruit. Major insect pests include the melon and cowpea aphids (Aphis gossypii Glover and A. craccivora C.L.Koch, Hemiptera: Aphididae), sweetpotato whiteflies (Bemisia tabaci Genn., biotype B, Hemiptera: Aleyrodidae), western flower thrips (Frankliniella occidentalis Pergande, Thysanoptera: Thripidae), melon thrips

(Thrips palmi Karni, Thysanoptera: Thripidae), and common blossom thrips (Frankliniella schultzei Trybom, Thysanoptera: Thripidae) (Seal et al., 2016; Mossler & Nesheim, 2014).

Conventional and organic squash growers share similar pest infestations. Other cucurbit growers in the state of Florida and Georgia share similar pest species (O. E. Liburd pers. com).

Whitefly- and aphid- transmitted viruses can cause losses up to 80% annually in U.S. squash production. Aphids transmit many viruses with great economic impact that affect squash including Papaya ringspot virus W (PRSV-W, Potyviridae: Potyvirus), Watermelon mosaic virus

(WMV, Potyviridae: Potyvirus), Zucchini yellow mosaic virus (ZYMV, Potyviridae: Potyvirus), and Cucumber mosaic virus (CMV, Bromoviridae: Cucumovirus) (Nyoike & Liburd, 2010).

Whiteflies (B. tabaci, B biotype) transmit the Cucurbit leaf crumple virus (CuLCrV,

Geminiviridae: Begomovirus), that has been reported in Florida (Akad et al., 2008; Nyoike et al.,

2008). In addition, the Squash silverleaf (SSL) is a physiological disorder that results in decreased photosynthesis and yield reductions caused by immature sweetpotato whiteflies

(Jimenez et al., 1995).

PRSV-W, WMV, and ZYMV are plant viruses from the genus Potyvirus consisting of one rod-shaped flexuous particle and single-stranded RNA genome. Potyviruses are non-persistently transmitted by aphids and are acquired in a matter of seconds from plants during aphids’ host- finding behavior or “probing” during which aphids sample the epidermal cells of plants to find a suitable host (Hull, 2009; Agrios, 2005). Potyvirus particles are attached to the aphids’ stylet tips and can be transmitted to healthy plants in seconds or minutes. Aphids begin to lose the ability to infect shortly after acquisition as they continue the exploratory probing feeds (Hull, 2009). CMV infects more plant species than any other virus in the world and it was the first identified species for the genus Cucumovirus (Agrios, 2005). CMV is transmitted by aphids in a non-persistent manner as Potyviruses and its particles are isometric with a genome including three single- stranded RNAs each existing in a separate but identical particle (Ng & Falk, 2006).

CuLCrV belongs to the genus Begomovirus, a group of whitefly-transmitted viruses.

CuLCrV, as most Begomoviruses, consist of two circular single-stranded DNA genomes (DNA-

A and DNA-B) of about equal size, each genome enclosed in a geminate particle (Agrios, 2005).

Contrary to Potyviruses and Cucumoviruses, Begomoviruses are persistently transmitted meaning its particles are ingested by the whiteflies from the infected plants, pass through the gut and reach the salivary glands, usually via the hemolymph. Whiteflies need to feed on the infected plants for a few minutes to acquire the virus and can transmit the virus for hours or their entire life span (Hogenhout et al., 2008). Virus mode of transmission determines insect-plant-virus interactions because acquisition and transmission times can vary immensely between non- persistently and persistently transmitted viruses. Therefore, insect and insect-transmitted disease management tactics should be modified based on the mode of action of the viruses present in the target crop (Hogenhout et al., 2008).

Whitefly and aphid populations and plant viruses are usually managed using insecticides that are applied on a weekly basis (Nyoike & Liburd, 2010); however, the development of resistance against these insecticides is always a major concern. Moreover, spraying chemical pesticides on a calendar basis (every 7–10 days) for pest control can be expensive, have negative effects on non-target organisms, especially pollinating agents and natural biological control organisms, and tend to negatively affect human health and the environment (Frank & Liburd,

2005).

Mossler and Nesheim (2014) reported that approximately 30% of initial cost of production is from the use of chemical pesticides. One of my goals is to promote less dependency on chemical pesticides and develop a more sustainable system incorporating cultural

tactics; thus, increasing grower’s profitability, and subsequently maintain the natural stability of the soil and environment.

Conservation Biological Control

Conservation biological control lies in the fostering of natural enemies that are already present in the crop system. Due to agricultural intensification, the overall complexity of the landscape is reduced, and habitat modifications through companion planting are often required to harbor beneficial arthropods into the agroecosystem (Tscharntke et al., 2007).

Companion planting is defined as the introduction of non-crop plants with intrinsic characteristics into the agroecosystem. These plants may be attractive to predator and parasitoid species and possess characters such as extra floral nectaries, domatia, long blooming periods, among others (Parker et al., 2013; Riesselman, 2009). The use of companion plants, also called, insectary plants, or living mulches, depending on the location within the crop, is becoming a common cultural practice in organic vegetable production (Parker et al., 2013).

Due to its deterrent effects on certain insect pests, African marigolds (Tagetes erecta L.,

Asteraceae) have been used in several studies as companion plants, cover crops, and as insectary plants to enhance beneficial arthropods in vegetable cropping systems (Jankowska et al., 2012;

Wang, 2012; El-Gindi et al., 2005). Field studies in onion, tomato, and eggplant crops have shown that intercropping using marigold plants contributes to insect pest management by increasing the density of natural enemies present in the crop canopy (Gundannavar et al., 2007).

Silveria et al. (2009) intercropped onion with marigold plants and recorded an increase in the abundance of insect natural enemies and lower pest numbers in onion plants that were closer to the marigolds. Jankowska et al. (2012) also reported lower numbers of aphids (Brevicoryne brassicae L., Hemiptera: Aphididae), sweetpotato whiteflies (B. tabaci), and diamondback moth

(Plutella xylostella L., Lepidoptera: Plutellidae) on carrot when intercropped with marigold.

Another companion plant that has potential in agricultural cropping systems is cowpea

(Vigna unguiculata (L.) Walp., Fabaceae). The extra floral nectaries on cowpeas can increase beneficial arthropods including hoverflies, insect parasites and parasitoids, lady beetles, minute pirate bugs, ground beetles, and predatory mites (Koptur & Pena, 2015; Wang, 2012). When cowpeas were grown as companion plants in zucchini squash, natural enemy species increased

(Letourneau, 1990). Similarly, cowpeas intercropped with corn and squash increased numbers of beneficial insects including Trichogramma spp. (Hymenoptera: Trichogrammatidae) wasps and the minute pirate bug (Orius spp., Hemiptera: Anthocoridae). Cowpeas have the added ability to fix nitrogen into the soil and can serve as an additional source of income for growers (Wang,

2012).

The perennial herb, sweet alyssum (Lobularia maritima (L.) Desv., Brassicaceae), a potential companion plant has been largely investigated as a cost-effective insectary plant for attracting aphid predators and parasitoids (Gontijo et al., 2013; Gillespie et al., 2011; Skirvin et al., 2011; Bugg et al., 2008). Chaney (1998) demonstrated that within-field plantings of sweet alyssum led to a reduction in the number of Myzus persicae Sulzer (Hemiptera: Aphididae) on lettuce, suggesting that within-field habitat manipulations may enhance biological control in vegetable field crops. In fact, intercropping with sweet alyssum has been adopted by some commercial broccoli and lettuce growers in California because of the biological control services provided by the beneficial insects attracted to the flowering plants (Brennan, 2013, 2016).

Similarly, Rohrig et al. (2008) planted sweet alyssum in areas adjacent to cornfields (Zea mays

L., Poaceae) in Florida and found it to be highly attractive to several braconid parasitoid species.

To our knowledge, this is the only investigation of sweet alyssum in Florida prior to our studies.

Not only insect predators and parasitoids can benefit with the introduction of insectary plants but pollinators, which are vital for squash production, can also benefit from the introduction of these plants. Similarly, flowering companion plants offer shelter and pollen sources that may enhance the establishment and dispersal of predatory mites (Calvo et al., 2011;

Xu & Enkegaard, 2010). Amblyseius swirskii have been shown to move 1-m away from the release plant, within 24 hours (Lopez et al., 2017) in other vegetable crops in Florida. However, there is a lack of information regarding A. swirskii performance in squash crops.

Augmentation Biological Control

Augmentative biological control is defined as the mass release of natural enemies for control of pests. It is an environmentally and economically sound alternative to chemical control in several agricultural systems (van Lenteren & Bueno, 2003). Augmentative biological control programs traditionally include releases of parasitoids to alleviate aphid and whitefly infestations in vegetable crops; however, the use of commercially available predatory mites has become popular within the last two decades (Lopez et al., 2017).

The predatory mite, A. swirskii quickly became one of the most successful biocontrol agents after its introduction into the market in 2005 and is now released in more than 50 countries (Calvo et al., 2015). It is an effective predator of major pests found in Florida squash production, such as sweetpotato whitefly (B. tabaci, biotype B), western flower thrips (F. occidentalis), melon thrips (T. palmi), and common blossom thrips (F. schultzei) (Buitenhuis et al., 2015; Kutuk et al., 2016; Xu & Enkegard, 2010).

Amblyseius swirskii is well adapted to several vegetable crop hosts including pepper, cucumber, and eggplant (Farkas et al., 2016; Stansly & Natwick, 2010; Stansly & Castillo, 2009;

Nomikou et al., 2002). Calvo et al. (2011) demonstrated the effectiveness of A. swirskii in suppressing the sweetpotato whitefly and F. occidentalis populations in greenhouse-grown

cucumber plants. Whitefly nymphs were suppressed more than 99% when A. swirskii was present compared to an exponential increase of up to more than 200 nymphs per leaf when A. swirskii was absent. Moreover, the presence of A. swirskii resulted in significant thrips suppression of more than 98% irrespective of the presence of whiteflies. Authors concluded that predatory mite abundance was highest in the treatment combining A. swirskii, whitefly, and thrips. The option of targeting two pests with a single natural enemy has positive implications for biocontrol and resembles pest-predator complexes in field conditions (Messelink et al., 2010).

In experiments to compare the effectiveness of several mite species, Messelink et al.

(2006) found that A. swirskii performed better suppressing F. occidentalis in cucumber compared with Euseius scutalis Athias-Henriot (Acari: Phytoseiidae) and Neoseiulus cucumeris Oudemans

(Acari: Phytoseiidae), the last being the predatory mite commonly used for augmentative biological control of thrips in cucumber and other vegetable crops. In a study conducted in

Florida’s cucumber crops, Kakkar et al. (2016) demonstrated that A. swirskii provided effective control of T. palmi and F. schultzei under laboratory and semi-field conditions (shade house), and field trials. Their results demonstrated that A. swirskii may rival the effectiveness of chemical control strategies generally used for management of these pests. Despite the availability of studies showing the performance of A. swirskii in cucumber crops, little research has been conducted using this predatory mite in squash cropping systems. Likewise, few studies have evaluated mites as a potential predator in sprayed field conditions.

Further reduction in whiteflies and thrips numbers could be achieved by incorporating A. swirskii with organically approved insecticides that offer minimal risks to biological control agents and that are commonly used by squash growers in Florida. Razze et al. (2016) investigated the effect of organic pesticides on the whitefly predator Delphastus catalinae Horn

(Coleoptera: Coccinellidae) in squash. Authors determined a delay on D. catalinae releases is needed when used together with Pyganic® and M-Pede® (soap concentrate) because coccinellid populations were reduced one and three days after application of these pesticides. Similar studies have investigated the effects of conventional insecticides on A. swirskii population (e.g., Amor et al., 2012; Colomer et al., 2011) and inorganic insecticides such as sulfur (Gazquez et al., 2011); however, the effects of bioinsecticides commonly used in Florida’s squash production, such as

M-Pede or Azera® on A. swirskii population has not been evaluated. Studying the side-effects of these bioinsecticides on A. swirskii population will offer useful information for further integration of biological control agents and low-risk pesticides in squash crops.

In the present study, the purpose of releasing A. swirskii in the squash system is to use it as a complementary tactic to companion plants and to increase biological control activity within the system. While parasitoids and larger predators such as syrphids, big eyed bugs, and Orius spp. can feed on lepidopteran pests (e.g., melonworms and pickleworms) and aphid species; A. swirskii can seek out sweetpotato whiteflies and thrips species.

Spatio-Temporal Analysis

The fragmentation of farmlands has resulted in a scattered resource distribution that strongly enhances the importance of landscape features in determining the spatial patterns of pests inside and outside agricultural systems. The distribution of host plants (crop plants) that influence the foraging flights of herbivores; influence the spatial patterns of predators and parasitoids as well as the distribution of non-crop plants within or around the field (e.g., Sciarreta

& Trematerra, 2014; Park & Obrycki, 2004). However, pests’ spatial fluctuations are often generalized or overlooked when pest management programs are put in place.

Geostatistics analyzes and predicts unknown values based on spatial phenomena such as data coordinates and spatial autocorrelation. Environmental scientists have used ordinary kriging

for optimal interpolation at many places for mapping. It is one of many geostatistical estimators and by far the most commonly used in the practice in disciplines such as animal population ecology or precision agriculture (Webster & Oliver, 2001). Estimations from ordinary kriging are weighted linear combinations of the data within the neighborhood of each unsampled point.

Ordinary kriging minimizes estimates’ variance by combining directionality, spatial autocorrelation (tendency for points near each other to have similar values), and stochastic variation (randomness) into a semivariogram model. Semi-variances calculated as half the variance of the differences between nearby sample points and as function of the distance between them constitute semivariograms (Bolstad, 2012). With information about pest infestation levels in multiple locations within a cropping system, infestation levels at unsampled locations can be estimated using semivariogram models from ordinary kriging and identify pests’ spatial structure. The spatial structure of insect pests is of great value for management programs since it can reveal high-risk areas and can help optimize suppression strategies by choosing the most appropriate control method, rate, and timing.

The use of geostatistical tools to study spatial distribution of insects is not a new tool in pest management (Nyoike, 2012). Spatial analysis was used to investigate the impact of site- specific spraying versus whole field spraying methods to control Eurygaster integriceps Puton

(Hemiptera: Scutelleridae), a key pest of wheat. With the use of semiovariograms, Karimzadeh et al. (2011) determined that E. integriceps had an aggregated distribution whereas its predators

Chrysoperla carnea Stephens, (Neuroptera: Chrisopidae) and Coccinella spp. (Coleoptera:

Coccinellidae) were randomly distributed. Despite these differences, authors concluded that site- specific spraying has potential to control E. integriceps on wheat. Prey-predator interactions in corn fields have also been investigated using spatio-temporal approaches. Interactions among

corn leaf aphids (Rhopalosiphum maidis Fitch, Hemiptera: Aphididae), lady beetles (Harmonia axyridis Pallas, Coleomegilla maculata DeGeer, and Coccinella septempunctata L.; Coleoptera:

Coccinellidae), and environmental factors were mapped and compared by Park and Obrycki

(2004). They found that corn leaf aphids and all lady beetle species were aggregated during the peak population period and randomly distributed early and late in the season. Conversely, environmental factors such as soil moisture and elevation showed no correlation with the pest’s and its predators’ distribution patterns.

Geostatistics includes promising tools that can help to determine the distribution patterns of beneficial arthropods within the cropping system and identify relationships with the spatial distribution of their potential prey.

Justification

Squash production in Florida is seriously threatened due to the damage inflicted by major pests and the lack of sustainable strategies for their management. The use of large amounts of chemical inputs in the field is expensive and increases the potential for pests’ resistance (Razze et al., 2016). Aphids and sweetpotato whiteflies injure squash directly and transmit various damaging viruses. Reports of squash fields infected with whitefly-transmitted viruses used to be sporadic, but it has become more common in recent years in Florida causing significant yield losses

(McAvoy, 2016). A similar situation occurred in Georgia where CuLCrV wiped out 1/3 of the squash production in 2016 (R. Srinivasan pers. com.). Vector management using systemic or contact insecticides has little influence on disease incidence (Mossler & Nesheim, 2011). Viruses are usually transmitted before aphids acquire the insecticide lethal dose and immature whiteflies occur on the lower side of the leaves where they hardly come into contact with the insecticides

(Nyoike et al., 2008). In some situations, the use of insecticides may worsen viral incidence by disturbing the aphids and increasing spread of the viruses. Extension programs in Florida have

warned against managing these hemipteran pests (aphids and whiteflies) exclusively with pesticides and emphasized the low effectiveness of spraying to control aphids (Mossler &

Nesheim, 2014). Thus, additional strategies are needed for sustainable management of insect vectors.

This project seeks to develop a pest management program using complimentary techniques including the use of African marigold, cowpea, or sweet alyssum as companion plants and the release of the predatory mite A. swirskii for management of insect key pests and viral diseases in squash. This approach includes incorporating the companion plants without additional set-up or maintenance, following the grower’s growing practices together with a single release of A. swirskii with the ultimate purpose of increasing biological control activities and providing additional feeding and ovipositional resources for beneficial insects to subsequently improve the sustainability of squash production.

African marigold, cowpea, and sweet alyssum are inexpensive, easy to establish in the field and their flowers can generate additional income for the grower. These companion plants are attractive to pollinators that are critical to ensure good and adequate fruit development in squash production. Moreover, African marigolds and sweet alyssums increase predatory and parasitoid species including hoverflies (Diptera: Syrphidae) and Orius spp. (Hemiptera:

Anthocoridae) that suppress whitefly, thrips, and aphid populations. Both plant species have been successfully used as companion plants for management of insect pests in organic systems in other states (Wang, 2012; Skirvin et al., 2011) and are compatible with the release of biological control agents.

The release of A. swirskii will be used as a complementary technique to help reduce key insect pest populations and this predatory mite may also benefit from the use of companion

plants (Henry et al., 2011). As a generalist predator, A. swirskii can feed on nectar or pollen and their populations can be maintained by providing these food sources in the field until prey is available. Thus, the need for multiple releases during the growing season could be eliminated and the cost of augmenting A. swirskii would be minimized.

By incorporating geostatistical techniques, the distribution patterns of insect pests and A. swirskii can be determined during on-farm trials. Geostatistical techniques will allow us to track the movement of beneficial species around the companion and crop plants and determine their effects on pest numbers and viral incidence. The most appropriate arrangement to incorporate these techniques at a larger scale will be identified in order to make more accurate recommendations and compare pest management costs with the grower’s practices.

The combination of techniques we propose can be adopted not only by organic squash growers but also by conventional growers and other cucurbit producers in Florida and the rest of the southern U.S. (e.g., Georgia) that are attacked by similar insect pests and share similar disease pressure. Enhancing natural enemies that can suppress insect pests will reduce the number of insecticide applications, the production costs can be significantly reduced, and the exposure of pollinators and farmers to toxic chemicals will be minimized.

Objectives

The overall goal of this study is to evaluate the potential of three companion plant species, in absence or presence of A. swirskii, for biological control of key insect pest populations and its effect on viral incidence in organic zucchini squash. The objectives include:

1. Monitor the establishment of insect vectors and plant viruses in squash.

a. Identify and monitor key aphid, whitefly, and thrips species complex and relate their abundance to plant phenology, season, and weather for the zucchini squash crop.

b. Monitor the establishment of plant viruses in organic zucchini agro-ecosystem.

c. Determine the effect of key pest species and plant viruses on zucchini marketable yield.

2. Evaluate the effect of companion plants and A. swirskii releases in zucchini squash crops.

a. Determine if companion plants used as refugia within organic squash cropping system can cause the build-up of natural enemies that can suppress key pests.

b. Evaluate the combined effects of companion planting and release of the predatory mite A. swirskii for management of insect pest populations in organic squash production.

3. Identify temporal and spatial distribution patterns of key insect pests and a predatory mite species in a squash crop with 25% companion plant density using geostatistical techniques.

a. Identify spatial and temporal distribution patterns of insect pests, insect- transmitted viruses, and A. swirskii present in a squash cropping system.

b. Evaluate the effect of A. swirskii on sweetpotato whitefly populations when released on selected squash plants within the cropping system.

4 Assess the side-effects of two bioinsecticides on A. swirskii mites under laboratory and greenhouse conditions.

a. Evaluate the sublethal effects of insecticide exposure on different developmental stages of A. swirskii.

b. Identify the appropriate release time for A. swirskii after insecticide application.

CHAPTER 3 MONITOR THE ESTABLISHMENT OF INSECT VECTORS AND PLANT VIRUSES IN SQUASH

In 2006, a survey of Florida squash growers showed that 70% used only pesticides to manage insect pests (USDA, 2006). The use of insecticides continues to be the common management tactic used by squash growers against major insect pests such as the melon and cowpea aphids (Aphis gossypii Glover and A. craccivora C.L.Koch, Hemiptera: Aphididae), the sweetpotato whitefly (Bemisia tabaci Genn., B biotype; Hemiptera: Aleyrodidae), and thrips

(Thripidae) (Nyoike & Liburd, 2010). However, total reliance on chemicals is not a sustainable pest management strategy due to the problems associated with pest resistance and its effects on non-target organisms.

Aphids transmit most of the economically important viruses that infect squash including

Papaya ringspot virus (PRSV-W, Potyviridae: Potyvirus), Watermelon mosaic virus (WMV,

Potyviridae: Potyvirus), Zucchini yellow mosaic virus (ZYMV, Potyviridae: Potyvirus), and

Cucumber mosaic virus (CMV, Bromoviridae: Cucumovirus) (Nyoike and Liburd 2010).

Sweetpotato whiteflies transmit the Cucurbit leaf crumple virus (CuLCrV, Geminiviridae:

Begomovirus), Squash vein yellowing virus (SqVYV, Potyviridae: Ipomovirus), and Cucurbit yellow stunting disorder virus (CYSDV, Closteroviridae: Crinivirus) (McAvoy, 2016; Razze et al., 2016; Akad et al., 2008). Aphid-transmitted viruses are usually transmitted in a nonpersistent manner and are acquired within seconds with no latent period needed before transmitting the virus to healthy plants through probing or feeding. In contrast, whiteflies need to feed on infected plants for several minutes to acquire the virus and after a latent period that can last from minutes to hours can transmit the virus to healthy plants (Whitfield et al., 2015).

There are differences in viral incidence between spring and fall seasons in Florida mainly because whitefly pressure is typically high during the fall season. Whitefly-transmitted viruses

are easier to detect during the fall season when the whitefly pressure is higher, whereas aphid- transmitted symptoms can be observed on either season as the aphid populations changes throughout the year (Mossler & Nesheim, 2011).

Reports documenting the damage caused by these pests are available, but a detailed description about their establishment as the crop ages, the effect of abiotic factors on their populations and how viruses spread as pest abundance increases in the system needs to be studied as well as the effect of companion planting on pest populations attacking Florida squash.

Materials and Methods

Study Site

Two year-round cycles of experiments were conducted in 2015 and 2017 at the

University of Florida’s Plant Science Research and Education Unit (PSREU) in Citra, FL, 48-km away from the University of Florida (Gainesville, FL). Each cycle of experiments comprised two squash seasons. In North-Florida, the spring season starts by planting squash from late February to early March and last until late May, whereas the fall season usually starts in late September and lasts until early or mid-November.

An area 44-m wide × 52-m long (0.24-ha) was used for the experiments in 2015. A greater area (41-m wide × 84-m long or 0.35-ha) was designated for 2017 experiments. Samples collected during the experiments were processed at the Small Fruit and Vegetable IPM

Laboratory at the University of Florida (Gainesville, FL).

Plant Culture

Browntop millet (Urochloa ramosa (L.) Nguyen, Poaceae) served as summer cover crop and were tilled into the soil at least two weeks before planting the companion plants during both years.

Zucchini squash ‘Cash Flow’ (Siegers Seed Co., LaBelle, FL) was used as cash crop in

2015 and 2017 experiments. In 2015, the African marigold (Tagetes erecta L., Asteraceae)

‘Crackerjack’ (Stokes Seeds, Buffalo, NY) and cowpeas (Vigna unguiculata (L.) Walp.,

Fabaceae) ‘Mississippi Silver’ (Urban Farmer, Westfield, IN) were used as companion plants. In

2017 the companion plant, African marigold was re-used; however, cowpea was replaced with sweet alyssum (Lobularia maritima (L.) Desv., Brassicaceae) ‘Tall White’ (Urban Farmer,

Westfield, IN), since our first-year study revealed that cowpea harbored a substantial number of aphids, which could potentially spread viruses. All plants were sown in double rows at 35-cm intervals and fertigated during both years.

In 2015 and 2017, plants were drip irrigated and fertigated weekly after germination using a 6–0–8 plus micro blend by Mayo Fertilizer Inc. (Mayo, FL). A rotation of the organic fungicides Regalia® (Marrone Bio Innovations, Davis, CA) and DoubleNickel55® (Certis USA,

LLC., Columbia, MD) was used weekly starting the second week after planting against downy and powdery mildew. To synchronize the maturity periods of all plant species, companion plants were grown from seeds 3-4 weeks before planting the squash.

Experimental Design

The experimental design was a randomized complete block with five treatments and four replications in 2015 (Fig. 3-1). Each plot was 6-m × 4.4-m separated by 7-m of bare soil (buffer zone) on all sides. Each plot comprised three raised beds covered with black plastic (18-cm high and 91-cm wide, 1.06-m apart). Plants were sown in double rows of 22 plants per row, at 30-cm intervals. Treatments were defined by the type of companion plant grown in the middle row and were as follows: 1) marigold used as companion plant; 2) cowpea used as companion plant; 3) marigold and cowpea (mix) used as companion plants; 4) no companion plant but the use of spinosad (Entruts®; Dow AgroSciences, Indianapolis, IN) in the squash plants for insect control

(positive control); and 5) no companion plant and squash plants without any type of pest management (negative control). Entrust was applied twice to the squash plants in the positive control treatment. Data collected in 2015 showed that Entrust had no suppressive effect on whitefly populations; therefore, M-Pede® (Gowan Company, Yuma, AZ) was used during the

2017 field experiments.

Based on the results obtained in 2015, modifications were made in 2017 to optimize treatment effectiveness and efficiency. In 2017, plot size was 5.5-m × 4.2-m with buffer zones of

6-m extending west to east and 7-m extending north to south. Each plot comprised three raise beds (1.06-m apart). Plants were sown in double rows of 18 plants per row. Squash, marigolds, and alyssums were maintained as described above.

In 2017, experimental design was a randomized complete block with seven treatments and four replications (Fig. 3-2). Similar to 2015, treatments were defined by the type of companion plant grown in the middle row and the presence or absence of predatory mites as follows: 1) marigold used as companion plant; 2) sweet alyssum used as companion plant; 3) marigold used as companion plant and A. swirskii released on the squash; 4) sweet alyssum used as companion plant and A. swirskii released on the squash; 5) no companion plant only A. swirskii released on the squash; 6) no companion plant or A. swirskii, only the use of M-Pede in the squash for insect management (positive control); and 7) no companion plant and squash plants without any type of pest management (negative control). This type of treatment arrangement helped to determine if planting marigolds or sweet alyssum as companion plants with squash will give us additional benefits in terms of pests’ suppression compared to the use of

A. swirskii or M-Pede alone. M-Pede, an insecticidal soap concentrate was applied twice to the squash in the positive control, and a cover spray using Entrust was applied once to the entire

field to suppress high numbers of whiteflies. The effect of these treatments was compared to the absence of any type of pest management.

The height (soil to the highest flower) and width (two opposite leaves) of the squash and companion plants per plot was measured twice during the season, four weeks after planting and one week before crop termination.

Sampling

Destructive sampling and in situ counts of pest and beneficial arthropods were conducted on randomly chosen plants. Winged and apterae aphids were sampled from six squash plants and six companion plants per plot (24 squash plants per treatment and 24 companion plants per treatment) in 2015. In 2017, four squash plants (16 plants per treatment) and three companion plants per plot (12 plants per treatment) were sampled. The leaf-turn method was used weekly and consisted on gently turning over three leaves per plant and counting the number of aphids observed (Nyoike & Liburd, 2010). This method was used in both years starting three weeks after planting the squash until final harvest. The number of leaves per squash plant was recorded during the in situ counts.

Winged aphids were monitored by in situ counts and the use of two clear pan traps

(PackerWare®) per plot in 2015. One pan trap was used per plot in 2017 experiments. Each pan trap contained approximately 250-ml of 5% detergent solution (Colgate-Palmolive Co., New

York, NY). The detergent solution was refilled, collected and transported weekly to the laboratory for counting, starting three weeks after planting.

Adult whiteflies were monitored weekly using three 28-cm × 23-cm yellow sticky traps

(Great Lakes IPM, Vestaburg, MI) per plot in 2015 and two sticky traps per plot in 2017. Sticky traps were left in the field for 48 hours and the numbers of adult whiteflies were recorded in the laboratory. Additionally, adult whiteflies found in the pan traps mentioned above were recorded.

Immature whiteflies were monitored weekly by collecting three leaves from six squash plants

(72 leaves per treatment) in 2015 and three leaves from four squash plants (48 leaves per treatment) in 2017. One 4-cm diam. leaf discs was taken from each leaf using a cork borer in the laboratory and the number of immature whiteflies was recorded using a dissecting microscope

(Razee et al., 2016). Whitefly monitoring started three weeks after planting and until the end of the season in both years. Alternatively, adult and immature thrips were counted together in the leaf samples collected and the sticky traps.

Weather data including daily average, minimum, and maximum temperature (°C), percentage of relative humidity (%RH), and rain (mm) were obtained through the Florida

Automated Weather Network (FAWN, University of Florida, Gainesville, FL). Measurements from the PSREU weather station at 60-cm above the ground were used for reference.

During both years, one leaf from two plants per plot showing disease symptoms was excised and transported to the laboratory in a cooler and then stored at -17 °C until processed. In

2015, ELISA was conducted with samples from spring and fall. In 2017, only samples from fall

2017 were assayed. Destructive sampling was conducted four weeks after planting and one week before squash termination. Leaf samples were assayed for four aphid-transmitted cucurbit viruses

(PRSV, WMV, ZYMV, and CMV) and one recently reported whitefly-transmitted virus (CuLCrV) using a double or triple antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA or TAS-ELISA) and PCR, respectively (Nyoike et al., 2008).

Reagent sets for ELISA assays were obtained from Agdia Inc. (Elkhart, IN) as well as positive and negative controls to warrant assay reliability. The substrate (p-Nitrophenyl

Phosphate, PNPP) absorbance (optical density) was measured at 405 nm wavelength using a spectrophotometer to estimate virus concentration. Four times the mean plus the standard

deviation of the negative control absorbance values was used as a cut-off value to distinguish virus presence (> cuff-off value or positives) from absence (< cuff-off value or negatives).

To conduct PCR, liquid N was used for sample disruption of ~ 0.2-g of plant tissue per sample and DNeasy Plant Mini Kit (Qiagen Inc., Germantown, MD) was used for DNA extraction. Apex Hot Start 2X blue master mix (Genesee Scientific Co., San Diego, CA) and

CuLCrV-specific primers from the DNA-B component (CuLCrV V1324, 5′-

TTCTTCTGGTAAAATATGGC-3′ and CuLCrV C2370, 5′-CGACGAGATATGTCAACG3′,

Hagen et al. 2008) obtained from Integrated DNA Technologies Inc. (IDT, Coralville, IA) were used to direct the amplification of an expected ~ 1-kb fragment from sample tissue. PCR- amplified DNA was separated by electrophoresis and visualized under UV light. Whitefly- transmitted virus was assayed only during the fall when symptoms were observed.

Additionally, Squash silverleaf (SSL) disorder caused by the feeding of the immature stages of sweetpotato whiteflies was monitored weekly by randomly selecting six squash plants per plot in 2015 and 2017 and scoring them with an arbitrary index from 0-5 where 0 = a healthy plant and 5 = all leaves were completely silvered (Fig. 3-3; modified from Yokomi et al., 1990).

Total marketable yield was estimated in 2015 and 2017 by harvesting and weighting in the field all fruits per plot until crop termination. Unmarketable overgrown squash and fruit showing injuries from pickleworms or viruses was weighed separately. Total marketable, total unmarketable yield, and total fruit injured by pickleworms were compared among treatments.

Statistical Analysis

In both 2015 and 2017, repeated measures analysis was performed for all response variables by fitting either a generalized linear mixed model (GLMM) or a linear mixed model

(LMM) that considered the repeated nature of the data. The number of insect pests per plot collected by destructive sampling, in situ counts, pan traps, and sticky traps, were fitted using a

GLMM as implemented in the PROC GLIMMIX procedure following either a Poisson distribution with LAPLACE adjustment or a negative binomial distribution to correct over- dispersion when needed. This model considered the fixed effect factors of treatment, week, and their interaction. In addition, random effects of block and block within week were considered.

The repeated measurements were considered by including a random factor of plot, corresponding to a compound symmetry structure. The Appendix summaries the model distributions and random effects used for each of the variables analyzed.

Averaged SSL indexes, plant size, and squash yields per plot were compared among treatments by using the PROC MIXED procedure and degrees of freedom were adjusted using the Kenward-Rogers correction. No transformation was used for these variables. The LMM considered the fixed effect factors of treatment, week, and their interaction, together with a random effect of block. The repeated measurements were modeled using an autoregressive error structure of order 1 for each plot.

Comparisons of means among treatments at each week for both GLMM and LMM, were obtained by requesting LSMEANS from each procedure. Data from squash plants and companion plants were analyzed separately. All models were fitted using SAS 9.4 (SAS

Institute, Cary, NC, 2013). Descriptive statistics were used to compare viral incidence among treatments for fall 2015 and fall 2017 due to low number of samples collected and low viral incidence observed.

Results

A total of 147 insect morphospecies from 64 families in the orders Coleoptera, Diptera,

Hemiptera, Hymenoptera, Lepidoptera, Odonata, Orthoptera, and Thysanoptera, were collected from the experiments in 2015 and 2017. Plant-feeding species accounted for 34% (50) of the species, but only eight of them were pests of concern in zucchini squash crops including the

melon aphid (Aphis gossypii Glover, Hemiptera: Aphididae), sweetpotato whiteflies (Bemisia tabaci Genn., Hemiptera: Aleyrodidae), thrips (Thysanoptera), melonworms (Diaphania hyalinata L., Lepidoptera: Crambidae), and pickleworms (D. nitidalis).

Aphids and Aphid-Transmitted Viruses

Several aphid species (Hemiptera: Aphididae) were collected during the experiments in

2015 and 2017 including the spirea aphid (Aphis spiraecola Pach), the waterlily aphid

(Rhopalosiphum nymphaeae L.), the apple-grass aphid (R. insertum Walker), the rusty plum aphid (Hysteroneura setariae Thomas), the oil palm aphid (Schizaphis rotundiventris Signoret), the polygonum aphid (Capitophorus hippophaes Walker), and the root aphid (Tetraneura nigriabdominalis Sasaki). The most common aphid species were the melon aphid and the cowpea aphid (A. gossypii Glover and A. craccivora Koch, respectively). Most winged aphids were collected using pan traps, whereas most of apterae aphids were recorded during the in situ counts or in leaf samples.

Aphids in squash, marigolds, and cowpeas (2015 experiments)

In the experiments conducted during 2015, cowpea aphids were recorded in high numbers in the cowpeas and some aphids were also present in the squash. Higher aphid pressure was observed during the spring compared to the fall season for both apterae and winged aphids

(Fig. 3-4, 3-6).

The number of apterae aphids sampled by in situ counts differed over time. There was a significant week-by-treatment interaction for densities of apterae aphids recorded per squash leaf

(F20,120 = 3.85, P < 0.0001) and companion leaf (F10,102 = 7.12, P < 0.0001) using in situ counts in spring 2015.

During the spring of 2015, the highest numbers of apterae aphids recorded during in situ counts were found four weeks after planting (WAP) in the squash plants next to the cowpeas,

followed by the squash planted with marigolds+cowpeas, and marigolds as companion plants.

The lowest number of aphids were recorded four WAP in the squash plants where no pest management tactic was implemented. Low numbers of apterae aphids were found in the following weeks with an increase on aphid numbers eight WAP in the squash treated with

Entrust (Fig. 3-4A). Moreover, in spring 2015 cowpeas had the highest numbers of apterae aphids when sampled four WAP, followed by the marigolds and cowpeas planted together. The numbers of aphids inhabiting the marigolds remained low during the entire sampling period (Fig.

3-4B). No apterae aphids were collected in pan traps during spring 2015.

There was no significant week-by-treatment interaction for winged aphids recorded by in situ counts on the squash plants or collected by pan traps in spring 2015. The highest numbers of winged aphids were recorded three and five WAP when in situ counts were conducted in the squash planted next to cowpeas and marigolds+cowpeas. Squash plants with no pest management implemented showed the lowest numbers of winged aphids during the entire sampling period (Fig. 3-5A). Similarly, marigolds planted together with cowpeas and cowpeas alone showed the highest numbers of winged aphids recorded in the companion plants (Fig. 3-

5B).

Regarding the winged aphids collected by pan traps in the spring of 2015, the highest number of winged aphids were collected four WAP in the treatment with marigolds as companion plants, followed by the treatment with cowpeas (Fig. 3-5C).

There was a significant week-by-treatment interaction for densities of apterae aphids recorded per squash leaf (F14,60 = 2.74, P = 0.003) when using in situ counts in fall 2015. The highest numbers of apterae aphids found during in situ counts were recorded four and five WAP in the squash with marigolds as companion plants and the squash treated with Entrust,

respectively. The squash planted next to marigolds mixed with cowpeas and marigolds only as companion plants showed the lowest numbers of aphids four and five WAP, respectively.

Among all treatments, lowest numbers of aphids were recorded during the last two weeks of sampling (Fig. 3-6A).

No significant week-by-treatment interaction was found for apterae aphids on companion plants during the fall of 2015 when in situ counts were conducted.

In fall 2015, a different pattern of winged aphid populations was observed when in situ counts were conducted. High numbers were recorded in the squash treated with Entrust four

WAP, followed by the squash with no pest management five WAP, whereas the lowest numbers of winged aphids were recorded in the squash from all treatments, six and seven WAP (Fig. 3-

6B). No winged aphids were recorded in the companion plants by conducting in situ counts during the fall of 2015. The number of winged aphids collected with pan traps during the fall of

2015 seemed to have low numbers across treatments over the entire sampling period (Fig. 3-6C).

Aphids in squash, marigolds, and alyssum (2017 experiments)

During the 2017 experiments, higher aphid pressure was observed during the spring compared to the fall of 2017 for both apterae and winged aphids (Fig. 3-7, 3-9). Most of the collected aphids were identified as melon aphids or a mix with the less common species mentioned above.

There was no significant week-by-treatment interaction for densities of aphids recorded by in situ counts or collected by pan traps during the spring of 2017. When in situ counts were performed, the highest number of apterae aphids was recorded seven WAP in the squash were A. swirskii was released but no companion plant was used (Fig. 3-7A). The highest numerical number of apterae aphids collected by pan traps were found six and seven WAP in the squash where A. swirskii was released and alyssum was used as companion plant (Fig. 3-7B). Low

numbers of apterae aphids were recorded in all treatments during the previous weeks for both sampling methods. Hardly any apterae aphids were found in the companion plants when performing in situ counts in the spring of 2017.

There was no significant week-by-treatment interaction for densities of winged aphids collected by pan traps in spring 2017. Following the same pattern observed with the apterae aphids, the highest number of aphids was collected three WAP in the treatment with marigolds plus A. swirskii released in the squash, followed by the treatment with marigolds only (no A. swirskii). The treatment with M-Pede applications showed the lowest numbers of winged aphids throughout the sampling period (Fig. 3-8A). No winged aphids were recorded during the in situ counts conducted in the squash and companion plants during the spring of 2017.

The number of aphids sampled differed over time during the fall of 2017. There was a significant week-by-treatment interaction for densities of apterae aphids recorded by in situ counts in fall 2017 (F30,258 = 4.17, P < 0.0001). The highest number of apterae aphids were found eight WAP in the squash where A. swirskii was released and planted next to marigolds and marigolds plus A. swirskii, whereas the lowest number of aphids was observed in the squash where A. swirskii was released and alyssum was used as companion plant. Low numbers of apterae aphids were recorded in the previous weeks (Fig. 3-9A). When in situ counts were performed directly into the companion plants, the highest number of apterae aphids were found in the marigolds from the treatment with marigolds plus A. swirskii six WAP (Fig. 3-9B).

There was no significant week-by-treatment interaction for densities of apterae aphids collected by pan traps in fall 2017; however, most of the aphids recorded during this season were collected using pan traps. Numbers of apterae aphids started to increase at week four and peaked five WAP with the highest numbers recorded in the treatment with marigolds as companion plant

and no A. swirskii released in the squash, followed by the treatment where no pest management tactic was implemented. The squash treated with M-Pede showed the lowest numbers of apterae aphids per trap throughout the entire sampling period (Fig. 3-9C).

There was a significant week-by-treatment interaction for densities of winged aphids recorded by in situ counts in fall 2017 (F30,258 = 4.71, P < 0.0001); however, high numbers of winged aphids fluctuated between treatments along weeks. Four WAP the squash with A. swirskii released and no companion plant showed the highest number of aphids, then five WAP the squash treated with M-Pede showed slightly higher numbers of winged aphids that were only surpassed by the treatment with marigolds plus A. swirskii on week eight (Fig. 3-8B).

There was no significant week-by-treatment interaction for densities of winged aphids collected by pan traps in fall 2017. The treatment with alyssum planted as companion plant showed the highest number of aphids in the first week of sampling decreasing to zero in the following week, whereas the treatment where M-Pede was sprayed showed the lowest number of winged aphids throughout the sampling period (Fig. 3-8C).

Aphid-transmitted viruses

Except for CMV, three aphid-transmitted viruses including WMV, ZYMV, and PRSV were detected at low incidence in fall 2015. PRSV showed the highest incidence and was present in samples from all treatments, ZYMV was detected in treatments where companion plants were planted or no pest management was implemented, and WMV was only detected in one sample from squash planted next to cowpeas (Table 3-1). Only one sample from the treatment including cowpeas showed positive results for all three viruses. Similarly, ELISA showed low incidence of aphid-transmitted viruses in fall 2017 with up to three samples positive in the treatment where no companion plant was used but A. swirskii was released (Table 3-2).

Whiteflies

Sweetpotato whiteflies (Bemisia tabaci Genn., Hemiptera: Aleyrodidae) were found infesting the zucchini squash during 2015 and 2017. Marigolds, cowpeas, and alyssum were not used by whiteflies as a host plant during the 2015 and 2017 experiments since no oviposition or immature stages were recorded on the plants.

Whiteflies in the 2015 experiments

Higher whitefly pressure was observed during the fall of 2015 compared to the spring season (Fig. 3-10). Hardly any whitefly adults were collected on yellow sticky traps during the spring of 2015 and there was no significant week-by-treatment interaction or significant differences among treatments for densities of adult sweetpotato whiteflies collected by yellow sticky traps in fall 2015. However, high numbers of whiteflies were collected three WAP with the highest numerical number in the treatment with Entrust followed by the treatment with no pest management. High numbers (>20 whiteflies/trap) were maintained during the remaining sampling periods (Fig. 3-10A). No whitefly adults were collected in the pan traps during the

2015 experiments.

There was no significant week-by-treatment interaction or significant differences among treatments for densities of whitefly immatures recorded in leaf discs during the spring and fall of

2015. In spring 2015, the squash planted next to marigolds showed the highest numerical number of whitefly immatures five WAP whereas the lowest number was recorded in the squash planted next to the cowpeas (Fig. 3-10B). High numbers of immatures whiteflies were recorded during the sampling period in fall 2015. The highest numbers of whiteflies were recorded for all treatments seven WAP with the squash planted next to the cowpeas with the leading value. In that same week, the lowest number was recorded in the squash with no pest management implemented (Fig. 3-10C).

Whiteflies in the 2017 experiments

A different whitefly population pattern was observed in 2017 with higher numbers of adult and immature whiteflies during the spring compared to the fall season (Fig. 3-11, 3-12).

There was a significant week-by-treatment interaction for densities of whitefly adults collected with yellow sticky traps (F24,72 = 1.89, P = 0.02) and pan traps (F24,72 = 2.22, P = 0.004) in spring 2017. Starting at week five there was an increase in the numbers of adult whiteflies collected by yellow sticky cards, with the highest numbers seven WAP in the treatment including

M-Pede applications and the treatment with no pest management. The lowest number observed seven WAP was found in the treatment where A. swirskii was released. Yellow sticky traps from the treatment with A. swirskii released (no companion plants) showed the lowest numbers of adult whiteflies throughout the season and the lowest numbers of adult whiteflies overall the sampling period were three and four WAP (Fig. 3-11A).

Adult whiteflies collected from pan traps showed a different tendency over the five-week sampling period. The highest numbers of whiteflies were observed five WAP with the highest numbers from the treatment with no pest management, marigolds as companion plant, and M-

Pede applications. The lowest numbers of adult whiteflies were recorded from pan traps located in the treatment where A. swirskii was released. This treatment showed low numbers of adult whiteflies during most weeks of the sampling period (Fig. 3-11B).

There was a significant week-by-treatment interaction for densities of whitefly immatures recorded on leaf discs (F14,72 = 18.2, P < 0.0001) in spring 2017. Low numbers of whitefly immatures were recorded in the squash during the first three weeks of sampling. Immature numbers increased six and seven WAP with the highest numbers in squash with alyssum as companion plant and alyssum together with A. swirskii release in the squash. The lowest

numbers of immature whiteflies were recorded in the squash planted together with marigolds and

A. swirskii release (Fig. 3-11C). However, these differences were not statistically significant.

There was no significant week-by-treatment interaction or significant differences among treatments for densities of whitefly adults collected with yellow sticky traps or pan traps in fall

2017. High numbers of whitefly adults were recorded in the yellow sticky cards throughout the sampling period with a peak three WAP in the treatment with alyssum and alyssum plus A. swirskii release. The treatment with alyssum and marigold used as companion plants maintained high numbers of adult whiteflies overall whereas the treatment with M-Pede applications showed the lowest numbers of whiteflies during all the sampling period (Fig. 3-12A).

There was no clear distribution pattern observed in the numbers of adult whiteflies collected using pan traps, but similarly to the yellow sticky cards, the treatment with alyssum as companion plant showed high whitefly numbers during most weeks of sampling whereas the treatment with M-Pede applications showed the lowest numbers four, six, and seven WAP (Fig.

3-12A-B).

There was a significant week-by-treatment interaction for densities of whitefly immatures recorded on leaf discs (F24,90 = 1.86, P = 0.02) in fall 2017. The numbers of whitefly immatures are somewhat consistent with the numbers of adult whiteflies collected by the yellow sticky traps. High numbers of immatures were found on the squash in weeks three and four for most treatments. Squash planted with alyssum and alyssum plus A. swirskii release showed the highest numbers of immature whiteflies four and five WAP whereas the squash treated with M-Pede and the treatment with A. swirskii release and no companion plant showed significantly lower numbers of immatures during those same weeks (Fig. 3-12C).

Squash silverleaf (SSL) disorder

No significant differences were found among treatments for the averaged SSL index in spring and fall 2015. Low SSL incidence (below 1.5, Fig. 3-13A) was observed during the spring with plants showing secondary veins silver (Fig. 3-3). Nonetheless, high SSL ratings were observed during the fall with ratings above 3 in treatments where cowpeas were included (Fig. 3-

13B). This means most plants showed extended silvering between primary and secondary veins

(Fig. 3-3).

There were no significant differences among treatments for the averaged SSL index in spring 2017. All treatments showed ratings between 2 and 2.5 (Fig. 3-14A) meaning that most rated plants showed leaves with veins silvered and a netted appearance (Fig. 3-3). Similar low ratings were recorded during fall 2017 but significant differences were observed during this season (F6,30 = 3.77, P = 0.006). All ratings were below 2 meaning that most plants showed the same pattern observed during the spring; however, the treatment where M-Pede was sprayed showed an average closer to 1 (Fig. 3-14B) where plants showed no netted appearance and only secondary veins silver (Fig. 3-3).

Cucurbit leaf crumple virus (CuLCrV)

PCR conducted to screen for CuLCrV showed that it was present in 83% (33 out of 40) of the samples tested in fall 2015. The virus was detected in samples from all treatments at similar incidence across treatments (Table 3-1). Likewise, CuLCrV was detected in 63% (38 out of 56) of the samples assayed in fall 2017. CuLCrV incidence was not influenced by treatments (Table

3-2).

Thrips

The thrips species identified during the experiments included Frankliniella schultzei, F. fusca, and F. bispinosa (Thysanoptera: Thripidae). There was higher abundance of thrips in 2015

compared with 2017, and higher thrips numbers were recorded during the spring compared to the fall season in both years.

Thrips on the squash during the 2015 experiments

Thrips species were counted and analyzed together in 2015. There was a significant week-by-treatment interaction for densities of F. bispinosa collected by yellow sticky traps in spring 2015 (F20,60 = 3.47, P < 0.0001). The highest numbers of thrips were collected four WAP in the treatment with cowpeas as companion plants, followed by the treatment with mixed marigolds and cowpeas. The lowest number of thrips at week four was recorded in the treatment with no pest management technique implemented. The following weeks the numbers of thrips remained under 500 thrips per trap and the lowest numbers collected were found in all treatments six WAP (Fig. 3-15A).

The same distribution pattern was observed in the number of thrips collected using pan traps in spring 2015. The treatment with cowpeas as companion plants showed the highest number of thrips six WAP followed by the treatment with no pest management. In previous weeks the numbers of thrips remained under 200 thrips per trap for all treatments but increased during the last week of sampling (Fig. 3-15B).

No significant week-by-treatment interaction was identified for thrips densities in fall

2015. The numbers of thrips collected with yellow sticky traps were highest six WAP in treatment were Entrust was applied whereas the lowest numbers were obtained in treatment with marigolds used as companion plants (Fig. 3-16A). The numbers of thrips registered in pan traps were higher in all treatments five and six WAP compared to previous weeks. Overall the sampling period, pan traps from the treatment with marigolds showed the lowest thrips numbers

(Fig. 3-16B).

Thrips on the squash during the 2017 experiments

Most thrips in 2017 were identified as F. bispinosa, the dominant species during both spring and fall seasons; thus, only numbers of F. bispinosa were used for the analyses. There was a significant week-by-treatment interaction for densities of F. bispinosa collected by yellow sticky traps (F24,84 = 2.81, P = 0.0002) and pan traps (F24,105 = 2.16, P = 0.004) in spring 2017.

The number of thrips collected by yellow sticky traps was highest six WAP in the treatment where A. swirskii was released but no companion plant was used, whereas it was lowest in the treatment with release of the predatory mite, A. swirskii and marigold as companion plant.

Overall treatments, the low numbers of thrips were observed during week five (Fig.3-17A).

Conversely, the number of thrips collected by pan traps showed the highest values five WAP with the major value from the treatment with release of A. swirskii and marigold as companion plant, followed by the treatment with release of A. swirskii and no companion plant (Fig. 3-17B).

There was a significant week-by-treatment interaction for densities of F. bispinosa collected by yellow sticky traps (F24,72 = 1.86, P = 0.02) and pan traps (F5,90 = 242.4, P < 0.0001) in fall 2017. When the yellow sticky traps were examined, the treatment with no pest management showed the highest numbers of thrips five WAP followed by the treatment where

M-Pede was applied. The lowest numbers of thrips were collected from all treatments four WAP

(Fig. 3-18A).

The highest numbers of thrips collected using pan traps fluctuated from the treatment with alyssum three WAP, then the treatment with marigolds five WAP and then again high numbers were collected from the treatment with alyssum six WAP. The lowest number of thrips was collected in pan traps from the treatment were A. swirskii was released and alyssum was used as companion plant from the forth throughout the seventh WAP (Fig. 3-18B).

Thrips on the companion plants

High numbers of thrips were found in marigold flowers (alone or mixed with cowpeas) overall seasons whereas alyssum (alone or together with A. swirskii release) inflorescences showed low thrips numbers (Fig. 3-19, 3-20).

There was a significant week-by-treatment interaction for numbers of thrips in fall 2015

(F8,48 = 4.24, P = 0.0002) with highest numbers found in marigolds planted alone three, four, and five WAP followed by marigolds mixed with cowpeas during the same weeks. Low numbers of thrips were recorded in cowpeas overall the sampling period, with the lowest numbers three and five WAP (Fig. 3-19B).

There was a significant week-by-treatment interaction for numbers of thrips (F12,125 =

2.17, P = 0.01) in spring 2017. Low numbers of thrips were recorded across treatments; however, more numbers of thrips were recorded in treatments including marigolds especially when A. swirskii was released in the squash planted next to marigolds during week five. Overall the sampling period, low numbers of thrips were found in treatments where alyssum was used as companion plant (Fig. 3-20A).

There was no significant week-by-treatment interaction or significant differences among treatments for thrips numbers in spring 2015 (Fig. 3-19A) and fall 2017 (Fig. 3-10B). However, the same tendencies mentioned above were observed with high numbers in marigold flowers, intermediate numbers in cowpea flowers, and low numbers in alyssum inflorescences.

Plant Dimensions and Yield

There were significant differences for squash plant with among treatments in spring 2017

(F6,18 = 4.20, P = 0.007). Wider squash plants were measured in treatments with marigolds planted as companion plants and release of A. swirskii, compared to treatments were alyssum was planted as companion plant together with the release of the predatory mite and the treatment

with no pest management. Squash plants from all other treatments showed intermediate sizes

(Table 3-3). Squash plant size (height and width) was not significantly different among treatments in 2015 and fall 2017 despite the presence of the companion plants (Table 3-3).

Likewise, the number of leaves per plant measured weekly showed no significant differences among treatments during 2015 and 2017 (Table 3-4).

No significant differences were observed for total fruit injured by pickleworms, marketable, and unmarketable yield in 2015 experiments. However, the unmarketable fruit was almost the same amount as the marketable fruit in both the spring and fall season. Additionally, the marketable yield was approximately 50% less in fall compared to the spring 2015 whereas the total fruit injured by pickleworms increased considerably during the same season (Fig. 3-21).

On the other hand, overall yield in 2017 was quite different. There were significant differences in marketable (F6,24 = 5.04, P = 0.001) and unmarketable yield (F6,22 = 3.10, P = 0.02) in spring 2017. Both marketable and unmarketable yield showed the same tendency with highest yield in the positive control were M-Pede was applied followed by the treatment with marigold as companion plants and release of A. swirskii. The lowest yield was recorded in the negative control were no pest management was implemented (Fig. 3-22A).

No significant differences in overall yield were found among treatments in fall 2017.

Nonetheless, the same tendency observed in 2015 was repeated in 2017 where unmarketable yield increased considerably across treatments and there was a reduction in marketable yield as well (Fig. 3-22B).

Discussion

Aphid establishment in squash during the 2015 experiments was mainly driven by the presence of cowpeas in spring 2015, and cowpeas and marigolds in fall 2015. Aphids were present in the squash in high numbers by the beginning of the sampling period (three weeks after

planting, WAP) suggesting that they colonized the plants at a very early developmental stage when plants had less than five true leaves and were less than 25-cm high (Table 3-3, 3-4).

Rainfall appeared to cause reductions in aphid populations six and seven WAP during the spring and six WAP during the fall season (Fig. 3-23). However, warm temperatures throughout the sampling period were optimal for aphid development and reproduction (20 ± 6 °C). In Florida females reproduce year-round without mating (Capinera 2000), thus, populations are always ready to colonize newly planted crops.

Cowpeas were highly attractive to cowpea aphids (A. craccivora) during the 2015 experiments. High numbers of winged and apterae aphids were recorded mostly during the spring of 2015, and fungus proliferation occurred due to continuous secretion of sap on top of the leaves and plastic mulch (Fig. 3-24). Mixing cowpeas with marigolds continue to harbor large numbers of aphids. Cowpea aphids (A. craccivora) are not commonly found in cucurbits, but high numbers of aphids on the cowpeas caused a spill-over effect on the squash planted near cowpeas alone or cowpeas mixed with marigolds. These findings were consistent across sampling methods (in situ counts and pan traps) and is the primary reason why cowpeas were not considered for the 2017 experiments.

Despite the diversity of aphid species identified in 2017, most of the species are not pests of cucurbits. Except for the melon aphid, aphid species like the root aphid, the rusty plum aphid, and the cowpea aphid are commonly found in Florida feeding on grasses, weeds or other crops

(e.g. cowpeas) and are non-colonizing aphids in the squash (S. Halbert, pers. com.). However, a few of these aphid species are reported as potential vectors of plant viruses like the apple-grass aphid and the polygonum aphid and even though populations are not established in the squash, they could potentially transmit viruses to the plants. In our 2015 studies, low incidence of

infection with aphid-transmitted viruses was recorded in the squash overall treatments, but most of the samples showing viral infection were found in the treatments with high numbers of aphids due to the presence of cowpeas. Therefore, it is important to monitor non-colonizing aphid species as well and consider them under efforts to control key aphid pests of squash like melon aphids.

No clear establishment pattern was observed for apterae and winged aphids during spring and fall of 2017 due to inconsistent numbers recorded across sampling methods (in situ counts and pan traps). Only winged aphids collected in pan traps during the fall of 2017 were higher in the treatment where alyssum was planted as companion plant, but this can be related to the high mobility and dispersal capacity of winged aphids as well as the non-colonizing nature of most aphid species collected during the 2017 experiments.

Marigolds were observed harboring significantly larger populations of aphids compared to other companion plants such as alyssum planted alone. Yet, the spill-over effect observed between cowpeas-aphids and squash in 2015 was not observed for marigolds-aphids and squash in 2017. This could be related to differences in the infestation levels between 2015 and 2017. In

2017, aphid infestation levels were moderate (< 100 aphids per companion plant) whereas in

2015, hundreds of aphids could be counted on a single cowpea or marigold plant saturating and damaging the companion plants very rapidly forcing the aphids to search for neighboring plant hosts.

The potential of marigolds as a trap crop for management of aphids has been evaluated by Jankowska et al. (2009). Authors reported that the total numbers of cabbage aphids

(Brevicoryne brassicae L., Hemiptera: Aphididae) in cabbage intercropped with marigolds was

2-7 times less than in monoculture. In the present study, marigolds seemed to play a similar role

as trap crop for aphids during 2017 experiments. The potential of marigolds as a trap crop for melon aphids and other aphid species in squash crops, could have important benefits for disease management programs considering the mode of virus transmission involved in aphid-virus interactions. Aphids can transmit multiple plant viruses at the same time within short periods of time because the virus is attached to the tip of their stylets. Viral particles are easily inoculated into the tissues of healthy plants when aphids probe new hosts as a method to examine the quality of the plant (Mauck et al., 2012). Due to aphids’ probing behavior, traps crops could potentially reduce squash viral infection as the aphids probe and feed on the non-crop plants and deplete their viral inoculum (Mauck et al., 2012; Zavaleta & Gomez, 1995).

Whitefly populations colonized the squash at early stages of the crop just like aphids, yet, no clear establishment pattern was observed across treatments in 2015. High numbers of immature stages were recorded among treatments during the fall with an increase in the last two weeks of sampling. This increase on whitefly populations could be associated with unusual warm temperatures fluctuating between 30 and 20 °C until early November (Fig. 3-23).

High numbers of whitefly immatures feeding on the squash in fall 2015 worsened SSL symptoms resulting on multiple plants showing extensive silvering between primary and secondary veins. Similarly, high CuLCrV incidence was observed overall treatments in fall 2015.

Contrary to the SSL disorder caused by immature feeding, CuLCrV is transmitted by whitefly adults causing plant stunting, and severe leaf and fruit malformations. CuLCrV together with high SSL incidence appeared to have a detrimental effect on plant fitness. The combination of aphid- and whitefly-transmitted diseases together with high insect pest infestations seemed to cause a 50% reduction in marketable yield during the fall compared with the spring of 2015

when no viral diseases were observed, and low aphid and whitefly infestation levels were recorded.

In the spring of 2017, the lowest numbers of adult whiteflies recorded in treatments where A. swirskii was released (no companion plants), appeared to be related to a biological control service provided by the predatory mite. Immature whiteflies in the same treatment did not show the lowest values, but showed low abundances compared to other treatments.

Amblyseius swirskii feeds on whitefly eggs, first and second instar nymphs (Soleymani et al.,

2016). Substantial reductions in eggs and immature stages due to predator feeding, can explain reductions in whitefly adult numbers. The same reduction in whitefly immatures was observed in fall 2017 when A. swirskii was released without the presence of companion plants. Whiteflies immatures were close to zero the week when the predatory mites were released (four WAP), and low numbers continue to occur during the following weeks. The same tendency was observed in the treatment with A. swirskii introduction and marigolds used as companion plants. Whitefly adults and immatures also showed a reduction in numbers similar to the spring recordings; however, no significant differences were identified among treatments in the fall of 2017.

During the squash season in north-central Florida, it is common to have higher whitefly pressure during the fall compared to the spring season. This tendency was observed in 2015 experiments; however, in 2017 a higher whitefly pressure was observed during the spring with traps collecting over 100 adults at the end of the season. Traps from fall continue to show high numbers (~60 per trap) at the begging of the season, but numbers slowly declined during the following weeks. The decline of whitefly populations during fall 2017 may be related to the presence of A. swirskii and reductions in temperature due to the winter arrival and late planting of the squash (first week of October). Specifically, four WAP, the numbers of whitefly adults

start to decrease in number and this phenomenon overlapped with a cold front that took temperatures under 10 °C and RH close to 60% for a few days. During the following weeks, temperatures increased but continue to be under 20 °C for several days (Fig. 3-24), which may have slowed down egg hatchability and overall whitefly development (McAuslane, 2000).

Less immatures feeding on the squash during the fall of 2017 was reflected in the SSL symptoms with more squash showing mild levels of silvering limited to the secondary veins. The presence of the predatory mite had no apparent effect on the SSL ratings in both spring and fall

2017 and only the squash treated with M-Pede show significantly lower levels of SSL during the fall season. CuLCrV incidence was also lower (63% total samples) compared with the fall 2015

(83% of the total samples) probably because of the low whitefly infestation recorded in fall of

2017 compared to fall of 2015.

Entrust is not labeled for aphid or whiteflies species, but it is commonly used by growers as one of the primary tools for management of the entire insect complex around organic squash production. Entrust was not effective suppressing aphid and whitefly populations during the

2015 experiments and no treatment differences were identified when compared with the positive control where Entrust was applied. M-Pede was used as the alternative pesticide for control treatment in 2017 experiments. It is labeled for management of aphids and whiteflies, and it is more effective suppressing their populations. Consequently, clear treatment differences were observed when numbers of aphids and whiteflies from other treatments were compared with the positive treatment during the 2017 experiments.

There was not a clear establishment pattern identified for thrips species during the experiments. The numbers of F. bispinosa in the pan traps were high one week after the predatory mite release and were not different from the other treatments the following week when

there was a reduction in thrips numbers overall treatments. This inconsistent pattern was observed for thrips numbers in sticky traps and pan traps in 2015 and 2017.

Florida flower thrips or F. bispinosa are native to Florida and are found in multiple weeds and crops grown in the state (Arthurs et al., 2015). Because of the beginning of the strawberry season overlaps with the beginning of the fall squash season, thrips populations start to move across the landscape to reach strawberry crops and land on several crops in their way. Similarly, the strawberry crop termination overlaps with the beginning of the squash season in the spring and large numbers of thrips disperse to neighboring crops in search for food and shelter. Thrips are highly mobile and passive collection methods like clear pan traps may catch more wandering thrips species whereas active collection methods like yellow sticky traps are highly attractive to thrips resulting in higher thrips catch. Thus, the inconsistencies between yellow sticky traps and pan traps.

Only the numbers of thrips present in the companion plants were consistent during all seasons because they were recorded in situ. Marigolds were highly attractive to various thrips species and marigolds used alone or mixed with cowpeas consistently showed the highest numbers of thrips present in flowers across treatments. African marigolds seemed to behave as a trap crop not only for aphids but also for thrips species. It has been reported that native thrips species like the Florida flower thrips pose minor threats to fruiting vegetables such as tomatoes, peppers, and eggplants in densities around 20 – 25 adults per flower. In some cases the presence of Florida flower thrips can be beneficial because they outcompete major thrips pest such as western flower thrips (Frankliniella occidentalis Pergande, Thysanoptera: Thripidae) that can cause damage in tomatoes with more than one adult per flower and more than six adults per flower in peppers and eggplants (Demirozer et al., 2012). Additionally, the Florida flower thrips

served as food source for important predators like minute pirate bugs as it was observed during the present study.

Various studies evaluating the use of living mulches or insectary plants together with squash have shown detrimental effects in yield due to plant competition. As an example, Razze et al. (2016) reported smaller plants and lower yields when squash was intercropped with buckwheat use as a living mulch. The purpose of using buckwheat was to increase natural enemies and pest suppression but competition with the non-crop plants had negative effects on crop development. The lack of significant differences in size and leaf numbers of the squash grown during this study showed evidence that competition between squash and companion plants was minimized by planting the latter using the same approach as the crop plants, on top of raised beds and not in the middle of the beds or occupying additional space between the squash.

Significant differences in size were only observed in spring 2017 and were translated into advantageous yield differences. The biggest squash plants were found planted next to marigolds together with the release of A. swirskii. These plants showed significantly higher yield, compared to the smallest squash plants found in treatments with no pest management. By introducing companion plants this way, not only competition for water, nutrients, and light was reduced, but also additional time and labor was not needed.

The use of A. swirskii without companion plants showed significantly lower numbers of whitefly adults, but it was not reflected in higher marketable yields. Moreover, biological control should not be used as the sole pest management tactic if the entire pest complex around the squash crop is targeted because predatory mites do not feed on aphids. The highest marketable yield was obtained from plants treated with M-Pede followed by the treatment including marigolds as a companion plant with A. swirskii release, and alyssum as a companion plant with

A. swirskii release. Thus, A. swirskii, together with companion planting demonstrated high potential as complementary techniques for pest management in organic squash. Choosing the most appropriate companion plant (between marigolds and alyssum for combination with releases of A. swirskii) should be based on the pest that poses a major threat to the cropping system. For example, if high whitefly and aphid pressure together with high aphid-transmitted viruses are detected in the squash crop, marigolds could be an appropriate companion plant in the cropping system together with A. swirskii. The predatory mites could suppress whitefly populations while marigolds are used as a trap crop for aphids and could mitigate or delay the spread of aphid-transmitted viruses into the squash.

On the other hand, if whiteflies and whitefly-transmitted viruses represent the major threat to the squash crop, alyssum may be an appropriate companion plant together with A. swirskii releases. Alyssum was not used as a host for whiteflies during the experiments and are attractive to whitefly predators and parasitoids such as Orius spp., aphelinid and platygastrid wasps. Also, alyssum is attractive to aphid predators and parasitoids such as syrphid and dolichopodid flies and braconid wasps. Because whitefly infestations and the whitefly- transmitted virus CuLCrV represented major threats to the squash during the experiments, alyssum was chosen as the most appropriate companion plant for the experiments in 2018.

Table 3-1. Percentage (n = number) of samples showing positive results for viral infection during the fall of 2015. Treatments included the use of marigolds or cowpeas as companion plants, the mix between the two, the use of Entrust (spinosad) as positive control and no pest management used as negative control. Treatment %PRSV (na) %ZYMV (na) %WMV (na) %CuLCrV (nb) Marigold 1.25 (1) 1.25 (1) 0 17.5 (7) Cowpea 1.25 (1) 1.25 (1) 1.25 (1) 20.0 (8) Marigold+Cowpea 3.75 (3) 0 0 20.0 (8) Entrust 2.50 (2) 0 0 12.5 (5) No pest management 1.25 (1) 1.25 (1) 0 12.5 (5) an =80 (4 per plot) samples used for ELISA assays bn = 40 (2 per plot) samples used for PCR

Table 3-2. Percentage (n = number) of samples showing positive results for viral infection during the fall of 2017. Treatments included the use of marigolds or cowpeas as companion plants alone or in presence or absence of the predatory mite Amblyseius swirskii (SW), the use of M-Pede (soap concentrate) as positive control and no pest management used as negative control. Treatment %Potyvirus group (n) %CuLCrV (n) Marigold 1.79 (1) 8.93 (5) Alyssum 0 10.71 (6) Marigold+SW 1.79 (1) 7.14 (4) Alyssum+SW 3.57 (2) 12.50 (7) SW 5.36 (3) 8.93 (5) M-Pede 1.79 (1) 10.71 (6) No pest management 1.79 (1) 8.93 (5) n =56 samples (2 per plot) used for ELISA assays and PCR Potyvirus group = PRSV, WMV, ZYMV, and CMV

Table 3-3. Averaged height and width per squash or companion plant. Six plants per plot in 2015 and four plants per plot in 2017 were measured four weeks after planting and one week before crop termination. Back-transformed data and fit statistics for treatment effects are shown (P ≤ 0.05). Squash plants Companion plants Treatment Height (cm) Width (cm) Height Width (cm) (cm) Spring 2015 Marigold 28.23 86.25 50.96 81.38 Cowpea 26.54 78.73 74.46 46.83 Marigold +Cowpea 26.71 84.69 53.50 (c), 66.08 (m) 74.25 (c), 57.33 (m) Entrust 28.73 87.40 No pest management 25.15 79.77 F4,12 = 1.07, F4,15 = 1.56, P = 0.43 P = 0.24 Fall 2015 Marigold 33.20 79.54 52.60 73.77 Cowpea 37.96 86.69 85.41 46.36 Marigold+Cowpea 39.24 90.39 49.74 (c), 76.84 (m) 75.78 (c), 42.55 (m) Entrust 37.93 87.23 No pest management 35.03 79.01 F4,12 = 2.36, F4,15 = 1.83, P = 0.11 P = 0.17 Spring 2017 Marigold 31.37 117.37 86.20 69.22 Alyssum 32.22 117.64 30.32 54.69 Marigold+SW 36.06 143.39 74.14 72.23 Alyssum+SW 34.57 118.26 33.02 57.86 SW only 32.59 118.38 M-Pede 37.30 134.33 No pest management 31.93 116.27 F6,18 = 1.81, F6,18 = 4.20, P = 0.15 P = 0.007 Fall 2017 Marigold 24.75 75.13 82.67 65.92 Alyssum 24.95 73.76 40.25 89.33 Marigold+SW 23.93 74.77 75.00 74.25 Alyssum+SW 23.53 75.08 40.83 89.50 SW only 23.99 75.40 M-Pede 24.80 74.89 No pest management 22.92 69.73 F6,18 = 1.11, F6,18 = 0.39, P = 0.66 P = 0.68 SW = Amblyseius swirskii c = cowpea, m = marigold

Table 3-4. Mean number of leaves per squash plant from six plants per plot in 2015 and four plants per plot in 2017. Weekly Back-transformed measurements are shown and fit statistics for treatment effects (P ≤ 0.05). Season Treatment Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Spring 2015 (F3,38 = 1.70, P = 0.16) Marigold 6.04 7.17 9.46 9.50 10.50 21.54 Cowpea 5.75 7.08 8.79 9.21 10.46 18.08 Marigold+Cowpea 5.75 7.17 8.75 9.21 12.00 19.50 Entrust 5.92 7.58 9.67 9.46 12.08 19.88 No pest management 5.38 7.33 8.42 8.83 10.13 19.04 Fall 2015 (F4,75 = 0.41, P = 0.79) Marigold 6.54 10.92 13.42 10.63 13.17 NA Cowpea 6.58 11.08 12.04 9.92 12.50 NA Marigold+Cowpea 6.46 11.00 12.33 8.71 9.96 NA Entrust 6.58 11.08 12.50 9.83 10.67 NA No pest management 6.67 11.50 13.29 9.46 13.38 NA Spring 2017 (F6,40 = 1.70, P = 0.14) Marigold 6.56 9.63 11.00 15.25 20.75 NA Alyssum 6.88 9.81 12.44 12.50 17.69 NA Marigold+SW 7.19 9.88 11.69 16.19 18.44 NA Alyssum+SW 6.63 9.06 10.56 13.75 19.88 NA SW only 6.06 9.50 11.50 14.88 20.69 NA M-Pede 7.00 9.75 11.81 15.75 21.19 NA No pest management 6.88 8.81 10.44 14.88 20.13 NA Fall 2017 (F6,40 = 0.74, P = 0.61) Marigold 9.31 11.94 14.38 15.13 12.38 19.56 Alyssum 8.81 11.75 15.06 14.25 13.94 17.31 Marigold+SW 9.50 12.25 14.38 15.56 13.13 17.44 Alyssum+SW 8.75 11.94 14.94 14.00 13.50 17.50 SW only 9.44 12.25 14.50 14.31 11.63 17.06 M-Pede 8.88 12.75 14.56 15.06 16.06 17.94 No pest management 9.06 12.25 14.44 13.75 13.50 15.88 SW = Amblyseius swirskii

Figure 3-1. Plot and treatment arrangement for 2015 experiments.

Figure 3-2. Plot and treatment arrangement for 2017 experiments.

Figure 3-3. Arbitrary index used for Squash silverleaf (SSL) ratings during 2015 and 2017 experiments (modified from Yokomi et al. 1990). Symptoms rated from 0 = asymptomatic, 1 = young leaves with secondary veins silver, 3 = leaves with primary and secondary veins silvering, 4 = silvering extends between veins, and 5 = various leaves with complete silvering.

Figure 3-4. Mean (±SE) number of apterae aphids sampled by in situ counts per (A) squash leaf in spring 2015 and (B) companion plant leaf in spring 2015. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-5. Mean (±SE) number of winged aphids sampled in spring 2015 by (A) in situ counts per squash leaf, (B) in situ counts per companion plant leaf, and (C) pan traps. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-6. Mean (±SE) number of aphids sampled in fall 2015. (A) apterae aphids recorded per squash leaf by in situ counts, (B) winged aphids recorded per squash leaf by in situ counts, and (C) winged aphids collected by pan traps. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back- transformed data are shown. ns= not significant.

Figure 3-7. Mean (±SE) number of apterae aphids sampled in spring 2017 by (A) in situ counts and (B) pan traps. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-8. Mean (±SE) number of winged aphids sampled by (A) pan traps in spring 2017, (B) in situ counts fall 2017, and (C) pan traps in fall 2017. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-9. Mean (±SE) number of apterae aphids sampled in fall 2017 by (A) in situ counts per squash leaf, (B) in situ counts per companion leaf, and (C) pan traps. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-10. Mean (±SE) number of (A) whitefly adults collected by yellow sticky traps in fall 2015, (B) whitefly immatures collected in spring 2015, and (C) whitefly immatures collected in fall 2015. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-11. Mean (±SE) number of whitefly adults recorded in spring 2017 by (A) yellow sticky traps, (B) pan traps, and (C)leaf samples for whitefly immatures. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-12. Mean (±SE) number of adult whiteflies collected in fall 2017 by (A) yellow sticky traps, (B) pan traps, and (C) leaf samples for whitefly immatures. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-13. Averaged Squash silverleaf (SSL) disorder index (±SE) rated in (A) spring and (B) fall 2015. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-14. Averaged Squash silverleaf (SSL) disorder index (±SE) rated in (A) spring and (B) fall 2017. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-15. Mean (±SE) number of thrips collected in spring 2015 by (A) yellow sticky traps and (B) pan traps. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-16. Mean (±SE) number of thrips collected in fall 2015 by (A) yellow sticky traps and (B) pan traps. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-17. Mean (±SE) number of Frankliniella bispinosa collected in spring 2017 by (A) yellow sticky traps and (B) pan traps. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-18. Mean (±SE) number of Frankliniella bispinosa collected in fall 2017 by (A) yellow sticky traps and (B) pan traps. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-19. Mean (±SE) number of thrips recorded by in situ counts in the companion plants in (A) spring and (B) fall 2015. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-20. Mean (±SE) number of thrips recorded by in situ counts in the companion plants in (A) spring and (B) fall 2017. Treatments with the same letter within weeks after planting (WAP) are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-21. Total marketable yield, total unmarketable yield, and total fruit injured by pickleworms (±SE) harvested in (A) spring and (B) fall 2015. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-22. Total marketable yield, total unmarketable yield, and total fruit injured by pickleworms (±SE) harvested in (A) spring and (B) fall 2017. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

Figure 3-23. Average, maximum, and minimum temperature (°C), percentage of relative humidity (%RH), and total rain (mm) for (A) spring and (B) fall 2015. Daily averages are shown from the start until the end of the sampling period. WAP = weeks after planting.

Figure 3-24. Average, maximum, and minimum temperature (°C), percentage of relative humidity (%RH), and total rain (mm) for (A) spring and (B) fall 2017. Daily averages are shown from the start until the end of the sampling period. WAP = weeks after planting.

Figure 3-25. Cowpea infested with hundreds of apterae and winged aphids. Sap secreted on top of the plastic mulch is observed. Photo courtesy of author.

CHAPTER 4 EVALUATE THE EFFECT OF COMPANION PLANTS AND AMBLYSEIUS SWIRSKII INTRODUCED IN ZUCHINNI SQUASH CROPS

Companion planting or intercropping involves introducing other plants within the cropping system together with the cash crop. It has been used to increase the quality of the soil, increase plant diversity in agricultural land, and enhance biological control by beneficial arthropods (Wang, 2012). Insectary plants attractive to beneficial arthropods and plant species that deter pest species are preferably to be used as companion plants because they can help to alleviate pest infestations in crop plants (Wang, 2012).

Squash is considered an excellent candidate to consider for intercropping systems due to its short production cycle (approximately eight weeks) and ease of growing. However, the use of non-crop plants may compete with the crop when they are not arranged properly within the cropping system (Razze et al., 2016). By planting companion plants in separate raised beds, the chances of plant competition are eliminated. Moreover, as companion plants, marigolds, cowpeas, and alyssums can be planted together or a couple of weeks before the cash crop to avoid companion/crop plant competition and to synchronize their blooming periods (Brennan,

2016).

Biological control agents can be released alone or in modified landscapes within vegetable crops to enhance biological control activities such as insect predation resulting from phytoseiids mites. The introduction of insectary plants can offer shelter, oviposition sites and alternative food items to support biocontrol agents in times of prey (pest) scarcity. Thus, companion plants within the cropping system may have a positive effect on Amblyseius swirskii

Athias-Henriot (Acari: Phytoseiidae) populations.

Companion planting has also shown promise as sustainable and cost-effective management tactics against insect pests in vegetable crops. However, the abundance and

diversity of natural enemies attracted to flowering companion plants and neighboring crops, the distance they can travel within the crop, their suppression effects on pests and their effects on viral incidence in squash needs to be studied. These cultural practices in combination with biological control agents for management of major squash pests can lead to a more developed and efficient integrated pest management (IPM) program for squash production.

Materials and Methods

Objective 2 was evaluated together with objective 1 during the experiments conducted in

2015 and 2017. The goal was to investigate if the companion plant species, its combination

(marigold and cowpeas), or its combination with A. swirskii (marigold+SW, alyssum+SW) had a significant effect on beneficial arthropod numbers with potential to suppress insect pests on the squash.

Plant Culture

The African marigolds (Tagetes erecta L., Asteraceae) ‘Crackerjack’ (Stokes Seeds,

Buffalo, NY) are considered a ‘giant’ cultivar of marigolds with 61-cm tall plants, 7-10-cm yellow and orange flowers, and approximately 60 days to reach maturity. They were used for the experiments due to its effectiveness in repelling some insect species, attracting beneficial arthropods, and an added advantage of suppressing root-knot nematode populations attacking the squash (Silveira et al. 2009, Hooks et al. 2010).

Cowpeas (Vigna unguiculata (L.) Walp., Fabaceae) are legumes commonly used as insectary plants to increase the abundance of beneficial arthropods in cropping systems (Wang,

2012). The ‘Mississippi Silver’ cowpea (Urban Farmer, Westfield, IN) is a cultivar with 60-80- cm tall plants that produce small purple flowers, 16-cm long pods, and take 65-70 days to reach maturity. Data collected during the 2015 experiments showed that cowpeas are highly attractive

to aphid species and appeared to become a source of insect infestations. Thus, cowpeas were not be used in 2017.

Sweet alyssum (Lobularia maritima (L.) Desv., Brassicaceae) together with T. erecta were the companion plants tested in 2017 experiments due to sweet alyssum’s ability to attract predators, parasitoids, and other beneficial arthropods (pollinators) in various cropping systems

(Brennan, 2013; Jankowska, 2009). ‘Tall White’ alyssum (Urban Farmer, Westfield, IN) is one of the tallest cultivars with plants up to 50-cm tall, white bulky flowers, and approximately 50 days to reach maturity. African marigolds, cowpeas, and sweet alyssum cultivars with similar plant height to those of the squash plants were preferred.

Zucchini squash (Cucurbita pepo L. sub. pepo, Cucurbitaceae) ‘Cash Flow’ (Siegers

Seed Co., LaBelle, FL) was used as cash crop. This cultivar can attain a height of 45-50-cm and produce large (12 – 15-cm) yellow flowers, 15-cm medium green fruits, and it only takes 50 days to reach maturity. Zucchini squash, African marigolds, cowpeas, and sweet alyssums are easily grown in tropical and subtropical areas under full sun, loamy or sandy soils, and under the warm temperatures (25 – 30 °C) of Florida. Plants were sown in double rows at 35-cm intervals, using drip irrigation and fertigated weekly using a 6–0–8 plus micro blend by Mayo Fertilizer Inc.

(Mayo, FL).

Experimental Design

The experimental designs were the same as described in chapter 3. The same treatments and number of replications used in 2015 and 2017 to evaluate insect pest establishment were used to evaluate the establishment of naturally occurring beneficial arthropods in 2015 and naturally occurring beneficial arthropods plus the augmented predatory mite A. swirskii in 2017.

The predatory mites were purchased in 500-ml bottle shaker formulation (Koppert

Biological Systems, Howell, MI) with vermiculite as bran carrier and mould mites (Tyrophagus

putrescentiae Schrank, Acaridae) as prey mite. Five bran samples (0.5-ml) were checked under the dissecting microscope for five minutes to confirm that the predatory mites were active prior to release. Amblyseius swirskii was released in the field on the day of arrival. Each bed (5-m2) containing squash plants was treated with approximately 20-ml of bran per bed three weeks after planting the squash. Four-ml of bran contains approximately 250 A. swirskii motiles based on preliminary bran counting prior to release. The release rate used was based on the rate recommended for high levels of pest infestations (150–200 mites/m2, BioBest, 2013, Koppert

Biological Systems, 2013).

Sampling

The same techniques used to monitor pest species in objective 1 were used to evaluate objective 2 in 2015 and 2017. Briefly, all natural enemy counts and samples were collected from randomly chosen plants. In 2015, natural enemies were monitored by in situ counts from six squash plants per plot and six companion plants per plot. In 2017, four squash plants per plot and three companion plants per plot were examined for natural enemies during in situ counts.

Numbers of predators and parasitoids were recorded and collected for identification. Weekly counts started three weeks after planting (WAP) the squash. Predators and parasitoids present in the pan traps and yellow sticky traps were recorded.

Leaves collected for sampling immature whiteflies were also searched for A. swirskii in the 2017 experiments. Additionally, three leaves from three companion plants were excised and brought back to the laboratory to monitor movement of predatory mites from the squash to the neighboring flowering companion plants. Numbers of A. swirskii eggs per leaf were recorded.

Nymphs and adult males and females per leaf were recorded together as motiles.

Statistical Analysis

For 2015 and 2017 experiments, repeated measures analysis was implemented to identify if the companion plant species, its combination (marigold and cowpeas), or its combination with

A. swirskii (marigold+SW, alyssum+SW) had a significant effect on beneficial arthropods numbers. All response variables were fitted using a generalized linear mixed model (GLMM) that considered the repeated nature of the data.

The numbers of each natural enemy species, including A. swirskii eggs and motiles per plot collected by destructive sampling, in situ counts, pan traps, and sticky traps, were fitted using a PROC GLIMMIX procedure following either a Poisson distribution with LAPLACE adjustment or a negative binomial distribution to correct over-dispersion when needed. This model considered the fixed effect factors of treatment, week, and their interaction. In addition, random effects of block and block within week were considered. The repeated measurements were considered by including a random factor of plot, corresponding to a compound symmetry structure.

Comparisons of means among treatments at each week for the GLMM were obtained by requesting LSMEANS from the procedure. Data from squash plants and companion plants were analyzed separately. All models were fitted using SAS 9.4 (SAS Institute, Cary, NC, 2013).

Results

Parasitoid wasps and predators accounted for 36% (53) and 20% (29) of the species from a total number of 147 insect morphospecies collected during the 2015 and 2017 experiments.

Without the plant-feeding species discussed in the previous chapter, the remaining 10% (15) of the species were identified as polyphagous species with no apparent harming potential to the squash.

Important predatory species were identified including minute pirate bugs (Orius spp.,

Hemiptera: Anthocoridae), big-eyed bugs (Geocoris spp., Hemiptera: Geocoridae), lady beetles

(Coccinellidae), spiders (Araneae) and the introduced predatory mite A. swirskii. Overall more predatory species were recorded during the spring season compared with the fall.

Naturally Occurring Predators

Marigolds acted as a host for Orius spp. since adults and immature stages of the predators were found in their leaves and flowers during both 2015 and 2017 spring seasons. However, there was no significant week-by-treatment interaction or significant differences among treatments for numbers of minute pirate bugs in 2015 or 2017.

In spring 2015, most Orius spp. individuals were collected using yellow sticky traps with low numbers across treatments and numbers three to four times lower in the treatment with no pest management compared to treatments that included companion plants (Table 4-1). The numbers of minute pirate bugs collected using pan traps showed similar values overall treatments

(Table 4.2).

A similar trend was observed in spring 2017. Minute pirate bugs numbers collected in yellow sticky traps were lower in the treatment with no pest management and the treatment with marigolds as companion plants together with A. swirskii release compared to other treatments

(Fig. Table 4-3). Yet, no significant differences were recorded.

Significant differences among treatments were identified for the numbers of minute pirate bugs collected with pan traps in spring 2017 (Table 4-4). The highest numbers of Orius spp. were collected in the treatment with marigolds planted as companion plant and the release of A. swirskii in the squash followed by the treatments planted with marigolds and no predatory mite released. The lowest numbers of Orius spp. were recorded in traps from treatments with alyssum planted as companion plant together with A. swirskii release, A. swirskii released without

companion plants, and plots treated with M-Pede (Table 4-4). No minute pirate bugs were collected using yellow sticky traps or pan traps during fall 2015 and fall 2017.

Cowpeas were attractive to predator species, especially adult and immature stages of coccinellids including a species in the genera Delphastus. However, there was no significant week-by-treatment interaction or significant differences among treatments for numbers of coccinellids in 2015 regardless of the sampling method (Table 4-1). Coccinellids collected in the yellow sticky traps during the spring were similar among treatments except for the treatment treated with Entrust that showed the lowest number of lady beetles with high numerical variations among samples (Table 4-1). Low numbers of lady beetles were collected using pan traps in both 2015 seasons (Table 4-2) and no coccinellids were collected during the fall of 2015 and overall seasons in 2017 across sampling methods.

Most spiders recorded during the experiments were collected using pan traps. There were no significant week-by-treatment interactions or significant differences among treatments for spider numbers in 2015 and 2017 seasons. No numerical differences were observed in the number of spiders collected in spring 2015, but slightly higher numbers of spiders were recorded in the treatments with marigolds, marigolds mixed with cowpeas, and the treatment with no pest management tactic compared with other treatments in fall 2015 (Table 4-2).

Hardly any spider was collected during fall 2015 and fall 2017 across sampling methods.

Significant differences were identified among treatments for numbers of spiders collected in yellow sticky traps in spring 2017 (Table 4-3) with up to four spiders per traps collected in treatments with marigolds used as companion plants (Table. 4-3). Moreover, spiders collected in pan traps were higher in the treatment with marigolds as companion plants. High variability in spider numbers were observed in pan traps placed at treatments with marigolds as companion

plant together with release of A. swirskii and plot treated with M-Pede (Table 4-4). Yet, no significant differences were detected in the numbers of spiders collected in pan traps.

Most long-legged flies were collected in the yellow sticky traps and at least four species in the genera Condylostylus (Diptera: Dolichopopidae) were collected during the 2015 and 2017 experiments. No significant differences were identified for long-legged flies in 2015, but high numbers were collected in yellow sticky traps over all treatments in the spring with highest values in treatments with marigolds and cowpeas planted together as companion plants.

Contrary, the highest numbers of long-legged flies were observed in the treatment treated with

Entrust followed by the treatment with no pest management in fall 2015 (Table 4-1).

Dolichopopidae is one of the largest families of Diptera with predacious adults reported to feed on fungus gnats, leaf-miner flies, aphids, leafhoppers, thrips, whiteflies, and mites. (Cicero et al.,

2017). Long-legged flies collected in pan traps showed low numbers during the spring 2015. In fall 2015, more long-legged flies were collected in pan traps, but no significant differences were observed across treatments (Table 4-2).

Yellow sticky traps located in the treatment with marigold planted as companion plant showed the highest numbers of long-legged flies in spring 2017. Yet, no significant differences were identified during this season for long-legged fly numbers (Table 4-3). Over all treatments, more long-legged flies were collected in the yellow sticky traps during the fall 2017 and significant differences were identified among treatments with the highest numbers collected in the treatments with marigolds planted alone and marigolds planted with cowpeas as companion plants (Table 4-3).

A different trend was observed in the numbers of long-legged flies collected using pan traps in 2017 when higher numbers were collected in the spring compared to the fall season.

There were significant differences among treatments for numbers of long-legged flies collected using pan traps in spring and fall 2017 (Table 4-4). Long-legged flies were higher in traps from treatments including companion plants and highest when alyssum was planted as companion plant. Lowest numbers were collected from treatments where only A. swirskii release was used

(Table 4-4). Similarly, high numbers of long-legged flies were collected in pan traps from treatments including companion plants and no A. swirskii release and highest numbers were observed when alyssum was used as companion plant (Table 4-4).

Naturally Occurring Parasitoids

Forty-six morphospecies of parasitoid wasps from 12 families were collected during the

2015 and 2017 experiments. For comparisons overtime and across treatments, four datasets were created for analysis based on the parasitoid wasps collected using yellow sticky traps or pan traps. Two datasets included numbers from all morphospecies pooled together as total parasitoid wasps and two more included numbers from morphospecies pooled together per family.

There were significant differences among treatments for the total number of parasitoids collected using yellow sticky traps (F4,72 = 10.53, P < 0.0001) and pan traps (F4,72 = 7.86, P =

0.0001) in spring 2015. Low parasitoid numbers were observed in yellow sticky traps from treatments with Entrust applications and where no pest management was implemented (Fig. 4-

2A). Contrary, highest numbers of parasitoids were collected in pan traps from the treatment with cowpeas as companion plant followed by the treatment with no pest management. The lowest numbers of parasitoids were collected from treatments where marigolds and cowpeas were planted together as companion plants (Fig. 4-2B).

Significant differences among treatments were identified for numbers of parasitoids collected using yellow sticky traps in fall 2015 (F4,60 = 2.92, P = 0.02). Numbers of parasitoids were highest in treatments treated with Entrust followed by treatments including marigolds alone

or mixed with cowpeas. Lowest numbers were collected where only cowpeas were planted as companion plants (Fig. 4-3A). There were no significant differences among treatments for numbers of parasitoids collected in pan traps during the same season (Fig. 4-3B).

There were significant differences among treatments for parasitoid numbers collected in yellow sticky traps in spring 2017 (F6,102 = 4.49, P =0.0004). More parasitoids were collected in yellow sticky traps from treatments that included companion plants except for treatments including alyssum together with A. swirskii release. The latter showed the lowest values of total parasitoids followed by the treatment with M-Pede applications (Fig. 4-4A). No significant differences across treatments were found for total number of parasitoids collected using pan traps in fall 2017 (Fig. 4-4B).

Parasitoid diversity was higher in yellow sticky traps compared to pan traps across all seasons. Platygastridae, Encyrtidae, Pteromalidae, Aphelinidae, and Dryinidae were the most abundant parasitoid families collected in spring 2015 and all showed significant differences in numbers collected using yellow sticky cards (Table 4-5). Parasitoids from these families were significantly higher in treatments including companion plants whereas lowest numbers were collected in treatments with no pest management (Table 4-5). Platygastridae and Encyrtidae were the most abundant families collected using pan traps in spring 2015; however, no significant differences among treatments were observed. Only numerical differences were recorded for

Platygastrid parasitoids with higher numbers in treatments with marigolds and cowpeas planted alone as companion plants (Table 4-6).

In fall 2015, Trichogrammatidae, Platygastridae, and Encyrtidae were most abundant than other parasitoid families and showed significant differences among treatments when yellow sticky traps were used (Table 4-5). Trichogrammatidae was the most abundant parasitoid in the

yellow sticky traps with more than 50 wasps per trap in treatments with no pest management and

Entrust applications. High numbers of platygastrid wasps were collected in most treatments except when cowpeas were planted alone or together with marigolds as companion plants (Table

4-5). When using pan traps in fall 2015, only platygastrid wasps showed significant differences with highest numbers collected in treatments with Entrust applications (Table 4-6).

Trichogrammatidae and Dryinidae were the most abundant parasitoid wasps collected but no significant differences were found for these families (Table 4-6).

In spring 2017, numbers of platygastrid parasitoids showed significant differences with highest numbers in yellow sticky traps from treatments including marigolds planted alone or together with A. swirskii release (Table 4-7). A similar trend was observed for platygastrid wasps collected with pan traps. Platygastridae was the most abundant family overall parasitoid families with highest numbers in treatments including alyssum together with A. swirskii release and treatment with M-Pede applications. Yet, no significant differences were found for this family.

Mymmarydae was the second most abundant parasitoid family collected using yellow sticky traps and pan traps in spring 2017, but no significant differences were found detected.

More mymmarids were collected in yellow sticky traps placed to marigolds or alyssum planted alone whereas more mymmarids were collected in pan traps from plot with no pest management

(Table 4-7, 4-8).

In fall 2017, platygastrid continue to show the highest numbers collected in both yellow sticky cards and pan traps. No significant differences were detected for platygastrids in yellow sticky traps (Table 4-7), but significant differences were found for platygastrids collected in pan traps (Table 4-8). Highest numbers of platygastrid wasps were collected in pan traps from treatments including marigolds planted alone as companion plants followed by treatments where

only A. swirskii was released. Encyrtidae was the second most abundant family in fall 2017.

Encyrtid wasps were only collected in yellow sticky traps and showed significant differences with highest numbers collected in the treatment with M-Pede applications (Table 4-7).

The Introduced Biological Control Agent, Amblyseius swirskii

There were no week-by-treatment interactions or significant differences among treatments for numbers of A. swirskii motiles in spring and fall 2017. The predatory mites released three WAP were found in the leaf samples five WAP only in samples from the squash with A. swirskii release and no companion plants, and the squash planted next to marigolds and

A. swirskii release (Fig. 4-1A). Despite being introduced deliberately in three out of seven treatments evaluated, A. swirskii was also found on leaf samples from other treatments. Six and seven WAP A. swirskii was recorded in squash samples from the remaining treatments. The highest numbers of predatory mites were recorded on the treatment with no companion plant and no pest management whereas the lowest numbers were recorded in the treatments with A. swirskii release together with marigolds and alyssum as companion plants (Fig. 4-1A).

In fall 2017, numbers of A. swirskii motiles fluctuated over time. Three, six, and seven

WAP highest numbers of predatory mites were found on the squash planted next to alyssum and intentional A. swirskii release followed by the squash planted next to marigolds and intentional

A. swirskii release. The lowest numbers of predatory mites were recorded on squash planted together with marigolds and without any pest management tactic (Fig. 4-1B).

Discussion

Because the establishment of key insect pests previously discussed (chapter three) was evaluated together with the effect of companion plants, the establishment of naturally-occurring and artificially-introduced natural enemies (A. swirskii) will be discussed in relation to the numbers of key insect pests colonizing the squash.

All three companion plants evaluated during the study caused the build-up of natural enemies around squash plants. Around 82 morphospecies of beneficial arthropods were identified throughout the seasons. Cowpeas were attractive to adult and immature stages of coccinellids that were observed feeding on high populations of aphids inhabiting the plants. One whitefly-specific beetle from the genera Delphastus was collected around the cowpea treatment and nearby squash plants. However, only a few beetles were collected and there was no evidence that Delphastus spp. had an effect on whiteflies present in the neighboring squash. Despite the important role that cowpeas played as refugia for beneficial arthropods, it also became a reservoir of aphids and viral diseases that were dispersing towards the neighboring squash and putting the crop at risk. Thus, cowpea is not considered an optimal option for companion planting in our squash crop.

Marigolds were also attractive to an important number of parasitoids and predatory species in both 2015 and 2017 studies. High diversity of parasitoid families was collected around marigolds and the most dominant families were constantly collected in treatments with marigolds alone or mixed with cowpeas. Similarly, predators like Orius spp. were drawn to the marigolds in search for food and shelter. We hypothesize that Orius spp. was able to use marigolds as host for reproduction and development because thrips were constantly present in marigold flowers and may have served as the primary food source for this hemipteran predator.

Multiple species of minute pirate bugs are commercially available for control of pest thrips and whiteflies (Olkowski et al., 2003). They were observed in the leaves of the squash planted next to marigolds during the spring season. However, there was no evidence that Orius spp. had any effect on pest species present in the squash mainly because of the low numbers of

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thrips found in the squash and the variability of whitefly numbers in the squash planted next to the marigolds.

Despite the spill-over effect observed between cowpeas-aphids-squash, this effect did not occur between marigolds-thrips-squash or marigolds-aphids-squash interactions. Similar findings were reported by Silveira et al. (2009) who found evidence that marigold strips within onion fields in São Paulo state, Brazil supported black bean aphids (Aphis fabae Scopoli, Hemiptera:

Aphididae) and onion thrips (Thrips tabaci Lind., Thysanoptera: Thripidae) populations that served as food source for the predator Orius insidiosus Say (Hemiptera: Anthocoridae). African marigolds intercropped with field-grown tomatoes in Mexico have shown lower average population of a diverse group of aphid species including cowpea aphids and melon aphids compared with tomato monoculture (Zavaleta & Gomez, 1995). Authors also reported lower incidence of infection with aphid-transmitted virus in tomatoes intercropped with African marigolds probably due to the loss of virus inoculum when feeding on the marigolds. Therefore, we believe that marigolds could have played a role as a trap crop for thrips and aphids within the zucchini squash cropping system.

Multiple studies have assessed alyssum as insectary plant intercropped with cabbage, lettuce, and peppers among others, for management of aphids by attraction of predatory syrphid flies and parasitoid wasps (e.g., braconid wasps) (Brennan, 2016, 2013; Hogg, 2011; Bugg et al.,

2008). This perennial herb is attractive to syrphid flies that use the plant as a host and immature stages can feed on aphids present in the system. In the present study, syrphids flies were observed visiting alyssum flowers but hardly any syrphids were collected by the sampling methods implemented. In contrast, high numbers of long-legged flies were collected throughout

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the study showing high numbers in treatments where alyssum was planted alone or together with release of A. swirskii.

Most dolichopodid species are predator of soft-bodied arthropods and at least four species from the genera Condylostylus were collected during the study. An estimated 162 species of dolichopodis (Cicero et al., 2017) and approximately 20 Condylostylus species are known to

Florida (G. J. Steck, pers. com.). Large populations are commonly established throughout the year in the state and they have been reported to feed on aphids, whiteflies, thrips, and other pest species (Cicero et al., 2017). These flies were observed actively feeding on aphids during the squash season and represented the dominant predator in the study.

In addition to the beneficial species attracted to the alyssum, no major numbers of pest species inhabited the alyssum. Only low numbers of thrips were recorded in the inflorescences, but they were poor hosts for aphids in whiteflies. This was the additional advantage that made alyssum the best companion plant option for the squash and the reason why it was selected for the 2018 studies.

Overall treatments, numbers of predatory mites recovered were lower than expected.

Environmental conditions may have influenced the numbers of A. swirskii collected. For example, important rain events in spring 2017 (more than four rainy days within the week between 10 – 35 mm per day, Fig. 3-24) following the release of the predatory could have limited the establishment of A. swirskii. Likewise, in fall 2017 decrease in temperatures below 20

°C and close to the 10 °C (Fig. 3-24) by the end of the season may have cause the reductions in predatory mite numbers observed seven weeks after planting (WAP).

Low numbers of A. swirskii may also be explained by their high dispersal capacity.

Amblyseius swirskii are highly mobile and can move from plant to plant using the connections

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between the leaves and plastic mulch as bridges (Lopez et al., 2017). Moreover, they can be airborne, especially gravid females in search for prey or alternative food sources. This behavior and the lack of physical barriers between experimental plots may have allowed them to move to other treatments where they were not artificially introduced or to other crops surrounding the squash crop. Thus, the initially population targeted to establish in a smaller area may have thinned numbers across the entire experimental area.

Interactions between A. swirskii, whiteflies, and thrips was complex throughout the study, but inverse relationships were noticed. In spring 2017, treatments where only A. swirskii was released (no companion plant) showed high numbers of A. swirskii motiles and at the same time significantly lowest numbers of adult and immature whiteflies were recorded in those treatments.

A similar trend was observed in treatments including marigolds as companion plants together with A. swirskii release. Likewise, numbers of F. bispinosa collected on the yellow sticky traps in spring 2017 were lowest right after the release of the predatory mite (four WAP) in treatments with marigolds as companion plant together with the release of A. swirskii.

Low infestation levels in these treatments mentioned above were not reflected as reductions in SSL or CuLCrV. However, marketable yield showed high numbers comparable to the positive control with M-Pede applications. The same tendency was observed during fall 2017 with high numbers of predatory mites in treatments where the mite was released together with marigolds or alyssum as companion plant. In these treatments, numbers of thrips were significantly lower compared to the remaining treatments. However, no clear benefits in disease reduction or increased yields were recorded.

Apparent suppression of multiple pests in open-field squash is consistent with previous studies showing that some generalist predatory mites including A. swirskii are efficient

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controlling multiple pest species. Xiao et al. (2012) showed that A. swirskii could disperse from banker plants into Chilli pepper plants and successfully suppress populations of sweetpotato whiteflies, western flower thrips, and Chilli thrips under laboratory and greenhouse conditions.

Amblyseius swirskii could maintain low levels of the three pests for most of the experimental cycle (90 days). Additional studies have also reported good pest suppression by A. swirskii in bell peppers, cucumbers, onions, and ornamentals (e.g., Calvo et al., 2015, 2011; Kumar et al.,

2015; Onzo et al., 2012), but there is lack of studies evaluating the performance of A. swirskii on squash and even less evaluations in open-field crops.

In summary, Amblyseius swirskii appeared to be successful at suppression whitefly and thrips at selected treatments where the predatory mite was deliberately introduced. Nonetheless, combined effects between the presence of A. swirskii, naturally occurring predators such as

Orius spp. and long-legged flies, and changes in temperatures and rainfall may have cause the observed reductions in pest infestation levels. The ultimate purpose of integrated pest management is to understand and manipulate all these factors in order to achieve control of insect pest and complementary of techniques and biocontrol agents was witnessed during this study.

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Table 4-1. Mean number (±SE) of predators collected per yellow sticky trap over a six-week (spring) and a five-week (fall) period during the 2015 experiments. Treatments including the use of marigolds or cowpeas as companion plants, the mix between the two, the use of Entrust (spinosad) as positive control and no pest management used as negative control. Back- transformed data are shown (P ≤ 0.05). Season Treatment/Family Marigold Cowpea Marigold Entrust No pest Treatment effect +Cowpea management Spring Anthochoridae 2.31 ± 0.48 2.57 ± 0.54 2.59 ± 0.53 1.58 ± 0.34 0.41 ± 0.66 F4,87 = 1.22, P = 0.30 (Minute pirate bugs) Coccinellidae 1.13 ± 0.35 1.68 ± 0.48 1.45 ± 0.43 0.06 ± 7.37 1.07 ± 0.33 F4,87 = 0.46, P = 0.76 (Lady beetles) Dolichopodidae 15.95 ± 1.94 15.44 ± 1.88 18.11 ± 2.19 14.99 ± 1.83 15.28 ± 1.86 F4,72 = 0.86, P = 0.49 (Long-legged flies) Fall Coccinellidae 0.00 ± 0.30 0.02 ± 6.13 0.00 ± 0.28 0.00 ± 0.30 0.00 ± 0.26 F4,75 = 0.01, P = 0.99 (Lady beetles) Dolichopodidae 2.72 ± 0.50 2.31 ± 0.48 3.03 ± 0.56 4.45 ± 0.80 3.59 ± 0.65 F4,12 = 1.82, P = 0.18 (Long-legged flies) Means within rows followed by the same letters are not significantly different (P ≤ 0.05).

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Table 4-2. Mean number (±SE) of predators collected per pan trap over a four-week period during the 2015 experiments. Treatments included the use of marigolds or cowpeas as companion plants, the mix between the two, the use of Entrust (spinosad) as positive control and no pest management used as negative control. Back-transformed data are shown (P ≤ 0.05). Season Treatment/Family Marigold Cowpea Marigold Entrust No pest Treatment +Cowpea management effect Spring Anthocoridae 0.71 ± 0.18 1.07 ± 0.24 0.60 ± 0.16 0.75 ± 0.19 0.96 ± 0.23 F4,15 = 0.97, P = 0.44 (Minute pirate bugs) Araneae 0.34 ± 0.13 0.34 ± 0.12 0.26 ± 0.11 0.32 ± 0.13 0.27 ± 0.11 F4,48 = 0.14, P = 0.96 (Spiders) Coccinellidae 0.01 ± 0.01 0.11 ± 0.09 0.01 ± 0.01 0.01 ± 0.01 0.01 ± 0.01 F4,15 = 0.67, P = 0.81 (Lady beetles) Dolichopodidae 0.01 ± 3.57 0.01 ± 4.05 0.3 ± 0.16 0.01 ± 4.40 0.32 ± 0.15 F4,12 = 0.001, P = 0.99 (Long-legged flies) Geocoridae 0.01 ± 0.05 0.13 ± 0.07 0.01 ± 0.06 0.01 ± 1.24 0.01 ± 1.24 F4,60 = 0.0004, P = 1 (Big-eyed bugs) Fall Araneae 0.36 ± 0.11 0.02 ± 1.23 0.31 ± 0.11 0.01 ± 1.02 0.52 ± 0.14 F4,48 = 0.44, P = 0.77 (Spiders) Dolichopodidae 2.71 ± 0.65 3.86 ± 0.90 3.25 ± 0.76 2.77 ± 0.68 2.68 ± 0.65 F4,15 = 0.46, P = 0.76 (Long-legged flies) Means within rows followed by the same letters are not significantly different (P ≤ 0.05).

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Table 4-3. Mean number (±SE) of predators collected per yellow sticky trap over a five-week period during the 2017 experiments. Treatments included the use of marigolds or cowpeas as companion plants alone or in presence or absence of the predatory mite Amblyseius swirskii (SW), the use of M-Pede (soap concentrate) as positive control and no pest management used as negative control. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. Season Treatment Marigold Alyssum Marigold Alyssum SW only M-Pede No pest Treatment effect /Family +SW +SW management Spring Anthochoridae 0.47 ± 0.2a 0.47 ± 0.2a 0.20 ± 0.20a 0.67 ± 0.20a 0.47 ± 0.20a 0.47 ± 0.20a 0.13 ± 0.20a F6,21 = 0.82, P = 0.56 (Minute pirate bugs) Araneae 0.03 ± 3.66a 0.00 ± 0.21a 0.00 ± 0.00b 0.00 ± 0.00b 0.00 ± 0.00a 0.43 ± 0.28a 0.00 ± 0.06a F6,102 = 9.14, P < 0.0001 (Spiders) Coccinellidae 0.01 ± 2.03a 0.05 ± 2.18a 0.00 ± 0.18a 0.79 ± 0.28a 0.00 ± 0.18a 0.00 ± 0.18a 0.03 ± 5.58a F6,102 = 0.51, P = 0.79 (Lady beetles) Dolichopodidae 8.91 ± 1.15a 6.71 ± 0.93a 5.79 ± 0.81a 6.85 ± 0.93a 6.45 ± 0.85a 6.16 ± 0.86a 5.07 ± 0.69a F6,90 = 1.85, P = 0.09 (Long-legged flies) Fall Dolichopodidae 11.6 ± 1.25a 9.42 ± 1.03b 10.96 ± 1.19a 8.26 ± 0.92ab 5.24 ± 0.61b 10.05 ± 1.10ab 6.96 ± 0.8a F6,90 = 9.03 P < 0.0001 (Long-legged flies) Means within rows followed by the same letters are not significantly different (P ≤ 0.05).

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Table 4-4. Mean number (±SE) of predators collected per pan trap over a five-week period during the 2017 experiments. Treatments included the use of marigold or cowpea as companion plants alone or in presence or absence of the predatory mite Amblyseius swirskii (SW), the use of M-Pede (soap concentrate) as positive control and no pest management used as negative control. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. Treatment Marigold Alyssum Marigold Alyssum SW only M-Pede No pest Treatment /Family +SW +SW management effect Spring

Anthocoridae 0.03 ± 8.79ab 0.03 ± 7.88ab 0.04 ± 10.59a 0.01 ± 0.01c 0.01 ± 0.01c 0.01 ± 0.01c 0.02 ± 6.11b F6,21 = 37.99, P < 0.0001 (Minute pirate bugs) Araneae 0.52 ± 0.17a 0.01 ± 0.27a 0.04 ± 5.12a 0.42 ± 0.16a 0.03 ± 4.3a 0.04 ± 5.35a 0.70 ± 0.21a F6,105 = 0.20, P = 0.97 (Spiders) Dolichopodidae 1.64 ± 0.43a 3.87 ± 0.84abc 2.81 ± 0.64abc 2.25 ± 0.54abc 0.92 ± 0.31abc 2.24 ± 0.54a 1.95 ± 0.49b F6,102 = 4.20, P = 0.0008 (Long-legged flies) Fall

Coccinellidae 0.09 ± 21.23a 0.1 ± 23.31a 0.06 ± 14.78a 0.13 ± 32.81a 0.08 ± 20.18a 0.09 ± 21.82a 0.09 ± 20.55a F6,105 < 0.0001, P = 1 (Lady beetles) Dolichopodidae 0.04 ± 8.16a 0.04 ± 8.97a 0.01 ± 1.19c 0.01 ± 0.94abcd 0.01 ± 0.86abcd 0.01 ± 0.74d 0.10 ± 23.34b F6,90 = 9.6, P < 0.0001 (Long-legged flies) Means within rows followed by the same letters are not significantly different (P ≤ 0.05).

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Table 4-5. Mean number (±SE) of parasitoids collected per yellow sticky trap over a six-week (spring) and a five-week (fall) period during the 2015 experiments. Treatments included the use of marigold or cowpea as companion plants, the mix between the two, the use of Entrust (spinosad) as positive control and no pest management used as negative control. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. Season Treatment/ Marigold Cowpea Marigold+ Entrust No pest Treatment effect Family Cowpea management Spring Aphelinidae 6.45 ± 1.67b 11.93 ± 2.51a 7.09 ± 1.77ab 5.80 ± 1.56b 3.22 ± 1.10b F4,12 = 4.20, P = 0.02 Braconidae 0.67 ± 0.47a 1.33 ± 0.67a 0.33 ± 0.33a 0.33 ± 0.33a 0.33 ± 0.33a F4,12 = 0.82, P = 0.53 Cynipidae 0.63 ± 0.47a 0.63 ± 0.47a 1.58 ± 0.78a 0.95 ± 0.58a 0.63 ± 0.47a F4,12 = 0.57, P = 0.68 Dryinidea 2.66 ± 1.11ab 5.03 ± 1.75a 6.22 ± 2.06a 2.66 ± 1.11ab 1.48 ± 0.76b F4,12 = 3.22, P = 0.05 Encyrtidae 3.33 ± 1.05b 2.33 ± 0.88b 10.67 ± 1.89a 2.67 ± 0.94b 2.67 ± 0.94b F4,12 = 7.51, P = 0.002 Eulophidae 1.82 ± 0.96a 2.35 ± 1.16a 0.78 ± 0.54a 1.04 ± 0.65a 2.08 ± 1.06a F4,12 = 1.01, P = 0.43 Figitidae 1.96 ± 0.84a 1.63 ± 0.76a 1.63 ± 0.76a 0.33 ± 0.33a 0.98 ± 0.58a F4,12 = 0.84, P = 0.52 Ichneumonidae 0.33 ± 0.33a 1.00 ± 0.58a 1.67 ± 0.75a 0.33 ± 0.33a 1.00 ± 0.58a F4,12 = 0.92, P = 0.48 Mymmaridae 7.48 ± 1.78a 8.78 ± 1.97a 8.45 ± 1.92a 5.53 ± 1.48a 7.80 ± 1.83a F4,12 = 0.64, P = 0.64 Pteromalidae 7.29 ± 2.24ab 6.98 ± 2.17ab 8.50 ± 2.54a 2.73 ± 1.11c 3.64 ± 1.35bc F4,12 = 3.28, P = 0.04 Platygastridae 25.45 ± 3.89a 20.56 ± 3.34ab 26.43 ± 4.00a 14.68 ± 2.66b 14.36 ± 2.62b F4,12 = 4.82, P = 0.01 Trichogrammatidae 5.33 ± 1.33a 6.00 ± 1.41a 3.67 ± 1.11a 3.33 ± 1.05a 6.33 ± 1.45a F4,12 = 1.10, P = 0.40 Fall Aphelinidae 9.33 ± 1.76ab 7.67 ± 1.60b 8.00 ± 1.63b 7.67 ± 1.60b 15.67 ± 2.29a F4,12 = 3.50, P = 0.04 Braconidae 2.00 ± 0.82a 2.33 ± 0.88a 2.67 ± 0.94a 4.33 ± 1.20a 4.33 ± 1.20a F4,12 = 1.15, P = 0.37 Cynipidae 0.42 ± 0.00a 0.00 ± 0.00a 0.21 ± 0.26a 0.63 ± 0.00a 0.42 ± 0.00a F4,12 = 0.16, P = 0.85 Diapriidae 2.67 ± 0.94a 0.67 ± 0.47a 0.67 ± 0.47a 2.33 ± 0.88a 3.00 ± 1.00a F4,12 = 1.72, P = 0.20 Dryinidea 5.67 ± 1.37a 4.00 ± 1.15a 5.33 ± 1.33a 5.33 ± 1.33a 6.67 ± 1.49a F4,12 = 0.49, P = 0.73 Encyrtidae 3.21 ± 1.37a 0.00 ± 0.00a 0.58 ± 0.45a 1.46 ± 0.79a 2.34 ± 1.09a F4,12 = 1.49, P = 0.26 Figitidae 1.67 ± 0.75a 1.00 ± 0.58a 1.00 ± 0.58a 1.67 ± 0.75a 2.00 ± 0.82a F4,12 = 0.39, P = 0.80 Mymmaridae 6.67 ± 1.49a 2.67 ± 0.94a 8.33 ± 1.67a 5.33 ± 1.33a 3.67 ± 1.11a F4,12 = 2.72, P = 0.07 Pteromalidae 26.78 ± 3.43a 23.80 ± 3.19a 24.47 ± 3.24a 30.09 ± 3.69a 25.13 ± 3.3a F4,12 = 0.72, P = 0.58 Platygastridae 20.89 ± 2.84a 11.28 ± 2.02b 14.92 ± 2.35ab 20.56 ± 2.81a 20.89 ± 2.84a F4,12 = 3.22, P = 0.05 Trichogrammatidae 47.00 ± 3.96ab 30.33 ± 3.18c 41.33 ± 3.71b 49.33 ± 4.06ab 57.67 ± 4.38a F4,12 = 6.70, P = 0.004 Means within rows followed by the same letters are not significantly different (P ≤ 0.05).

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Table 4-6. Mean number (±SE) of parasitoids collected per pan trap over a four-week period during the 2015 experiments. Treatments included the use of marigold or cowpea as companion plants, the mix between the two, the use of Entrust (spinosad) as positive control and no pest management used as negative control. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. Season Treatment/ Marigold Cowpea Marigold+ Entrust No pest Treatment effect Family Cowpea management Spring Dryinidae 5.15 ± 1.89a 2.34 ± 1.16a 2.81 ± 1.29a 1.87 ± 1.01a 4.68 ± 1.78a F4,12 = 1.27, P = 0.33 Encyrtidae 2.50 ± 1.12a 0.50 ± 0.50a 0.50 ± 0.50a 2.50 ± 1.12a 1.50 ± 0.87a F4,12 = 1.22, P = 0.39 Eulophidae 0.91 ± 0.68a 3.17 ± 1.44a 2.26 ± 1.16a 0.91 ± 0.68a 1.36 ± 0.86a F4,12 = 1.12, P = 0.38 Figitidae 4.00 ± 1.41a 6.50 ± 1.80a 3.00 ± 1.22a 3.00 ± 1.22a 6.00 ± 1.73a F4,12 = 1.17, P = 0.36 Mymmaridae 1.00 ± 0.71a 6.50 ± 1.80a 2.00 ± 1.00a 3.50 ± 1.32a 4.00 ± 1.41a F4,12 = 2.23, P = 0.12 Platygastridae 8.41 ± 2.14a 9.90 ± 2.34a 4.45 ± 1.52a 5.94 ± 1.77a 8.91 ± 2.20a F4,12 = 1.31, P = 0.31 Trichogrammatidae 0.00 ± 0.00a 1.00 ± 0.71a 0.00 ± 0.00a 1.00 ± 0.71a 1.50 ± 0.87a F4,12 = 0.07, P = 0.98 Fall Braconidae 3.84 ± 1.49a 5.28 ± 1.81a 0.48 ± 0.49a 1.92 ± 1.01a 2.40 ± 1.14a F4,12 = 1.99, P = 0.15 Diapriidae 1.00 ± 0.71a 1.00 ± 0.71a 0.00 ± 0.00a 0.50 ± 0.50a 1.00 ± 0.71a F4,12 = 0.10, P = 0.97 Dryinidae 24.41 ± 3.65a 24.91 ± 3.69a 19.43 ± 3.23a 34.37 ± 4.41a 28.89 ± 4.00a F4,12 = 2.33, P = 0.11 Encyrtidae 14.00 ± 2.65a 13.50 ± 2.60a 11.50 ± 2.40a 14.50 ± 2.69a 10.50 ± 2.29a F4,12 = 0.45, P = 0.76 Eulophidae 2.46 ± 1.14a 1.47 ± 0.87a 1.47 ± 0.87a 1.47 ± 0.87a 3.44 ± 1.37a F4,12 = 0.72, P = 0.59 Figitidae 4.38 ± 1.55a 7.31 ± 2.08a 7.31 ± 2.08a 11.21 ± 2.69a 4.87 ± 1.65a F4,12 = 2.04, P = 0.15 Mymmaridae 10.75 ± 2.58a 10.27 ± 2.51a 7.82 ± 2.13a 10.75 ± 2.58a 13.20 ± 2.92a F4,12 = 0.69, P = 0.60 Platygastridae 11.98 ± 2.47c 18.47 ± 3.08abc 17.97 ± 3.04bc 28.96 ± 3.89a 24.46 ± 3.56ab F4,12 = 4.03, P = 0.026 Trichogrammatidae 30.39 ± 4.10a 31.89 ± 4.21a 21.92 ± 3.43a 27.40± 3.87a 33.38 ± 4.32a F4,12 = 1.40, P = 0.29 Means within rows followed by the same letters are not significantly different (P ≤ 0.05).

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Table 4-7. Mean number (±SE) of parasitoids collected per yellow sticky trap over a five-week period in 2017 experiments. Treatments included the use of marigolds or cowpeas as companion plants, in presence or absence of Amblyseius swirskii (SW), the use of M-Pede (soap concentrate) as positive control and no pest management used as negative control. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. Treatment/ Marigold Alyssum Marigold Alyssum SW only M-Pede No pest Family +SW +SW management Spring Dryinidae 4.00 ± 1.41a 3.00 ± 1.22a 5.50 ± 1.66a 2.5 ± 1.12a 3.00 ± 1.22a 5.00 ± 1.58a 1.50 ± 0.87a F6,18 = 1.06, P = 0.41 Encyrtidae 5.50 ± 1.66a 2.00 ± 1.00a 3.50 ± 1.32a 3.00 ± 1.22a 1.50 ± 0.87a 4.00 ± 1.41a 4.00 ± 1.41a F6,18 = 1.00, P = 0.45 Eulophidae 3.00 ± 1.22a 6.00 ± 1.73a 3.50 ± 1.32a 4.50 ± 1.50a 5.00 ± 1.58a 2.00 ± 1.00a 4.00 ± 1.41a F6,18 = 0.83, P = 0.55 Ichneumonidae 4.37 ± 1.56a 4.85 ± 1.65a 4.85 ± 1.65a 2.91 ± 1.24a 3.40 ± 1.35a 4.85 ± 1.65a 3.40 ± 1.35a F6,18 = 0.34, P = 0.90 Mymmaridae 6.33 ± 1.92a 6.82 ± 2.00a 7.79 ± 2.17a 4.38 ± 1.56a 4.87 ± 1.65a 5.84 ± 1.83a 4.38 ± 1.56a F6,18 = 0.59, P = 0.73 Platygastridae 31.96 ± 4.93a 33.93 ± 5.14a 34.91 ± 5.24a 18.69 ± 3.48bc 28.03 ± 4.52ab 17.70 ± 3.37c 27.54 ± 4.46abc F6,18 = 3.48, P = 0.01 Trichogrammatidae 3.49 ± 1.33a 3.98 ± 1.43a 5.48 ± 1.68a 2.49 ± 1.12a 3.98 ± 1.43a 1.00 ± 0.71a 1.99 ± 1.00a F6,18 = 1.24, P = 0.32 Fall Aphelinidae 95.25 ± 10.24a 102.16 ± 10.81a 97.72 ± 10.44a 92.29 ± 9.99a 96.24 ± 10.32a 114.00 ± 11.79a 92.78 ± 10.03a F6,18 = 1.16, P = 0.36 Braconidae 0.43 ± 0.45a 1.71 ± 1.05a 1.71 ± 1.05a 0.86 ± 0.68a 0.43 ± 0.45a 1.28 ± 0.87a 0.86 ± 0.68a F6,18 = 0.59, P = 0.72 Dryinidae 3.45 ± 1.34a 2.96 ± 1.24a 7.40 ± 2.02a 4.93 ± 1.62a 2.47 ± 1.13a 1.48 ± 0.86a 3.45 ± 1.34a F6,18 = 1.83, P = 0.14 Encyrtidae 9.27 ± 2.37b 12.68 ± 2.87b 12.19 ± 2.8b 8.78 ± 2.30b 7.32 ± 2.06b 25.85 ± 4.60a 8.29 ± 2.22b F6,18 = 6.39, P<0.001 Eulophidae 0.92 ± 0.68a 1.84 ± 1.01a 1.38 ± 0.86a 1.38 ± 0.86a 1.84 ± 1.01a 1.38 ± 0.86a 2.31 ± 1.15a F6,18 = 0.26, P = 0.94 Mymmaridae 7.47 ± 1.96a 5.97 ± 1.75a 11.45 ± 2.46a 6.97 ± 1.90a 5.47 ± 1.67a 9.46 ± 2.22a 7.47 ± 1.96a F6,18 = 1.08, P = 0.40 Platygastridae 13.12 ± 2.98a 14.09 ± 3.12a 10.69 ± 2.62a 17.00 ± 3.53a 14.09 ± 3.12a 16.52 ± 3.47a 12.63 ± 2.91a F6,18 = 0.70, P = 0.65 Trichogrammatidae 2.94 ± 1.24a 4.90 ± 1.64a 3.92 ± 1.45a 0.98 ± 0.70a 2.45 ± 1.13a 3.92 ± 1.45a 3.92 ± 1.45a F6,18 = 0.91, P = 0.50 Means within rows followed by the same letters are not significantly different (P ≤ 0.05).

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Table 4-8. Mean number (±SE) of parasitoids collected per pan trap over a five-week period during the 2017 experiments. Treatments included the use of marigolds or cowpeas as companion plants alone or in presence or absence of the predatory mite Amblyseius swirskii (SW), the use of M-Pede (soap concentrate) as positive control and no pest management used as negative control. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. Treatment/Family Marigold Alyssum Marigold+SW Alyssum+SW SW only M-Pede No pest management Spring Dryinidae 7.00 ± 2.65a 3.00 ± 1.73a 10.00 ± 3.16a 4.00 ± 2.00a 7.00 ± 2.65a 11.00 ± 3.32a 4.00 ± 2.00a F6,18 = 1.35, P = 0.28 Encyrtidae 1.00 ± 1.00a 1.00 ± 1.00a 3.00 ± 1.73a 4.00 ± 2.00a 1.00 ± 1.00a 2.00 ± 1.41a 1.00 ± 1.00a F6,18 = 0.70, P = 0.65 Eulophidae 7.00 ± 2.65a 9.00 ± 3.00a 2.00 ± 1.41a 8.00 ± 2.83a 5.00 ± 2.24a 4.00 ± 2.00a 6.00 ± 2.45a F6,18 = 0.90, P = 0.15 Ichneumonidae 3.76 ± 2.03a 2.82 ± 1.73a 2.82 ± 1.73a 1.88 ± 1.38a 1.88 ± 1.38a 6.58 ± 2.82a 2.82 ± 1.73a F6,18 = 0.79, P = 0.58 Mymmaridae 3.94 ± 2.01a 8.87 ± 3.07a 2.96 ± 1.73a 9.85 ± 3.25a 3.94 ± 2.01a 4.93 ± 2.25a 11.82 ± 3.59a F6,18 = 1.71, P = 0.17 Platygastridae 41.00 ± 6.40a 41.00 ± 6.40a 45.00 ± 6.71a 55.00 ± 7.42a 34.00 ± 5.83a 50.00 ± 7.07a 39.00 ± 6.24a F6,18 = 1.13, P = 0.38 Trichogrammatidae 6.68 ± 2.75a 5.72 ± 2.52a 8.59 ± 3.19a 13.36 ± 4.19a 5.72 ± 2.52a 5.72 ± 2.52a 7.63 ± 2.98a F6,18 = 0.99, P = 0.45 Fall Aphelinidae 6.88 ± 2.69a 4.92 ± 2.25a 7.86 ± 2.89a 10.81 ± 3.44a 7.86 ± 2.89a 1.97 ± 1.4a 5.90 ± 2.48a F6,18 = 1.04, P = 0.42 Braconidae 3.00 ± 1.73a 2.00 ± 1.41a 5 ± 2.24a 0.00 ± 0.00a 4.00 ± 2.00a 3.00 ± 1.73a 7.00 ± 2.65a F6,18 = 0.62, P = 0.70 Dryinidae 13.00 ± 3.61a 8.00 ± 2.83a 13 ± 3.61a 7.00 ± 2.65a 6.00 ± 2.45a 7.00 ± 2.65a 8.00 ± 2.83a F6,18 = 0.92, P = 0.49 Eulophidae 11.99 ± 3.47a 20.99 ± 4.60a 13.99 ± 3.75a 17.99 ± 4.26a 20.99 ± 4.60a 11.99 ± 3.47a 15.99 ± 4.01a F6,18 = 0.89, P = 0.51 Ichneumonidae 8.00 ± 2.83a 2.00 ± 1.41a 2 ± 1.41a 5.00 ± 2.24a 2.00 ± 1.41a 3.00 ± 1.73a 2.00 ± 1.41a F6,18 = 1.36, P = 0.28 Mymmaridae 1.00 ± 1.00a 3.00 ± 1.73a 2 ± 1.41a 5.00 ± 2.24a 3.00 ± 1.73a 3.00 ± 1.73a 6.00 ± 2.45a F6,18 = 0.78, P = 0.59 Platygastridae 44.61 ± 10.90a 26.02 ± 7.11b 20.45 ± 5.94b 26.02 ± 7.11b 32.53 ± 8.45ab 29.74 ± 7.88ab 19.52 ± 5.74b F6,18 = 2.66, P = 0.05 Trichogrammatidae 7.94 ± 2.85a 18.86 ± 4.49a 5.96 ± 2.46a 20.85 ± 4.73a 13.90 ± 3.82a 12.91 ± 3.67a 17.87 ± 4.36a F6,18 = 2.09, P = 0.10 Means within rows followed by the same letters are not significantly different (P ≤ 0.05).

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Figure 4-1. Mean (±SE) number of the predatory mites, Amblyseius swirskii, recorded per leaf disc (4-cm2) during (A) spring and (B) fall 2017. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

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Figure 4-2. Mean (±SE) number of parasitoids collected in spring 2015 by (A) yellow sticky traps and (B) pan traps. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

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Figure 4-3. Mean (±SE) number of parasitoids collected in fall 2015 by (A) yellow sticky traps and (C) pan traps. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

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Figure 4-4. Mean (±SE) number of parasitoids collected in spring 2017 by (A) yellow sticky traps and (B) pan traps. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

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Figure 4-5. Mean (±SE) number of parasitoids collected in fall 2017 by (A) yellow sticky traps and (B) pan traps. Treatments with the same letter are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

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CHAPTER 5 IDENTIFY TEMPORAL AND SPATIAL DISTRIBUTION PATTERNS OF KEY INSECT PESTS AND A PREDATORY MITES SPECIES IN A SQUASH CROP WITH 25% COMPANION PLANT DENSITY USING GEOSTATISTICAL TECHNIQUES

The predatory mite, Amblyseius swirskii Athias-Henriot (Acari: Phytoseiidae) has been used for biological control of the sweetpotato whitefly (Bemisia tabaci Genn., Hemiptera:

Aleyrodidae) throughout the world in pepper, cucumber, and strawberry crops. The sweetpotato whitefly is a key insect pest in Florida squash that transmit important plant viruses to multiple cucurbits including squash and in recent years increasing disease pressure has been reported

(McAvoy, 2016). Biological control is desired in both organic and conventional squash production given the intrinsic ability of the sweetpotato whitefly to develop insecticide resistance. Moreover, biological control reduces the use of chemical inputs to the system, it is safe to farmers and consumers, and no have no damaging effects on non-target organisms.

The melon aphid, Aphis gossypii Glover (Hemiptera: Aphididae) is also a key pest in

Florida grown squash. Just like sweetpotato whiteflies, melon aphids develop insecticide resistance in very short periods of time. Thus, alternative management strategies including conservation biological control have been evaluated as means to enhance naturally occurring predators and parasitoids. As an example, insectary plants such as sweet alyssum (Lobularia maritima (L.) Desv., Brassicaceae) have been introduced into cabbage, eggplant, pepper, and cucumber cropping systems to attract predatory flies, predatory bugs, and parasitoids with potential to suppress aphid populations (Ribeiro & Gontijo, 2017; Gontijo et al., 2013; Gillespie et al., 2011; Skirvin et al., 2011; Bugg et al., 2008). Yet, there is little information regarding the performance of A. swirskii for management of whiteflies in squash or the use of sweet alyssum together with squash as refugia for natural enemies.

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Agricultural systems are intrinsically heterogeneous. They contain variable arrangements of microclimatic features, plant communities, and arthropod species (Sciarreta and Trematerra

2014). It is the interaction between all these variables that determines all biological parameters of arthropod pest and natural enemies including survival and dispersal capacity. Moreover, the success of biological control is determined by the ability of the biocontrol agents to disperse and seek out their prey, but spatial and temporal distribution patterns are often overlooked because of analysis complexity. The ability to understand complex processes underlying experimental data is possible today due to new statistical approaches that incorporate spatial and temporal perspectives into data processing (Nyoike, 2012).

Geostatistics is a set of procedures that analyzes spatial dependence by using the spatial variation in direction and distance between samples (i.e., variogram modeling) and predicts spatial phenomena at unsampled locations (i.e., kriging) (Sciarreta & Trematerra, 2014; Park &

Obrycki, 2004). Ordinary kriging quantifies such spatial dependence with semivariograms that can determine insect or mite distribution patterns such as uniformity, randomness, aggregation, and spatial trend. This procedure comprises three steps 1) exploratory data analysis; 2) estimation and modelling of spatial autocorrelation; and 3) estimation of a surface area using interpolation procedures, with the ultimate purpose of identifying pest and beneficial distribution patterns and any correlations among them.

Arthropod interactions within a squash cropping system, as in any other agricultural system, are largely determined by the species spatial distribution patterns and their changes over time, as well as the influence of biotic and abiotic factors on pest and natural enemy dynamics.

Spatial variability studies of A. swirskii and its prey B. tabaci would clarify herbivore – predator interactions and determine how predatory mites disperse from a release point in a squash field

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intercropped with sweet alyssum. Equally, relating whitefly and aphid species distribution patterns with viral disease incidence patterns would elucidate additional herbivore – disease interactions that are vital to develop integrated pest and disease management strategies.

The goal of the study was to identify temporal and spatial distribution patterns of key insect pests and a predatory mite species in a squash crop with 25% companion plant density using geostatistical techniques. This is important to understand how A. swirskii disperse and move throughout the field in response to B. tabaci population as well as how B. tabaci establishment is affected by the presence of the predatory mite. More accurate estimations of pest infestation and plan virus infection during the squash season in Florida and the effect of conservation biological control upon their populations would be part of a pest and disease management program for organic growers in the state.

Materials and Methods

Study Site

An additional four-month cycle of on-farm experiments was conducted from September to November of 2018 at the organic and commercial farm Hammock Hollow Herb Co.

(Hawthorne, FL) 30 miles south from Gainesville. An area of 24-m wide × 37-m long (0.1-ha) was designated for the experiment. Samples collected during the experiments were processed at the Small Fruit and Vegetable IPM Laboratory at the University of Florida (Gainesville, FL).

Plant Culture

Three cultivars of summer squash (Cucurbita pepo L., Cucurbitaceae) were used for the on-farm experiments: green zucchini squash ‘Cash Flow’ (Siegers Seed Co., LaBelle, FL), yellow zucchini squash ‘Gold Rush’ (Harris Seeds, Rochester, NY), and the crookneck, two- toned summer squash ‘Zephyr’ (Johnny’s Selected Seeds, Fairfield, ME). All these squash cultivars take 45-55 days to reach maturity and were sown in plug trays in the greenhouse

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facilities (28 ± 2ºC, 80 ± 5% relative humidity, RH) at the University of Florida’s greenhouse facilities (Gainesville, FL), three weeks before the transplant date. Sweet alyssum (Lobularia maritima (L.) Desv., Brassicaceae) was sown in plug trays under the greenhouse four weeks before the transplant date.

Sweet alyssum and all squash cultivars were planted at the same time in single rows at

60-cm intervals (66 plants per bed), using drip irrigation and fertilized using Nature Safe® (10-2-

8, Griffin Industries LLC, Cold Spring, KY) slow release fertilizer incorporated into the soil plus five side-dressing events using Alaska Fish Fertilizer® (5–1–1, Pennington Seed, Inc., Madison,

GA) during the two weeks following the transplant date. MilStop® (BioWorks Inc., Victor, NY) fungicide was applied weekly for control of powdery mildew starting the week of transplant.

Harvest was conducted two to three times per week for four weeks.

Experimental Design

Two 8.2-m wide × 37-m long plots (0.03-ha) were set up for the experiments. One plot represented the control and the second a single treatment and each plot comprised seven 37-m long raised beds (1.06-m apart, Fig. 5-1). The treatment combination that showed the best results in 2015 and 2017 experiments was the use of sweet alyssum, thus, it was used as companion plant during the on-farm experiments. The treatment was defined by the presence of both sweet alyssum and the release of A. swirskii in the squash as follows: Treatment = 25% of the area occupied by sweet alyssum and A. swirskii released in 23% (105) of the squash plants (mixed cultivars) in the middle part of the plot; Control = only squash planted (mixed cultivars), no sweet alyssum nor A. swirskii released or any other pest management tactic.

Twenty-five percent of the plot area was equivalent to the space occupied by 120 squash plants. Instead, 480 sweet alyssum plants were transplanted. Because sweet alyssum plants were considerably small at the planting date, four plants where transplanted every 60-cm instead of

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one. In the remaining 75% of the area in the treatment, the three cultivars of summer squash mentioned above were used, one cultivar per row, for a total of 342 squash plants transplanted

(158 ‘Cash Flow’, 92 ‘Gold Rush’, and 92 ‘Zephyr’). For the control treatment, 100% of the area was transplanted with squash, 462 plants (198 ‘Cash Flow’, 132, ‘Gold Rush’, and 132 ‘Zephyr’)

(Fig. 5-1).

Amblyseius swirskii was purchased in 10-ml sachet formulation (Koppert Biological

Systems, Howell, MI) with vermiculite as bran carrier and mould mites (Tyrophagus putrescentiae Schrank, Acaridae) as prey mite. Ulti-Mite Swirskii® are sachets made of a 100% industrial compostable foil designed for preventative control in outdoor conditions. Each sachet has a hook and contains ~250 predatory mites. Five bran samples (0.5-ml) from additional sachets were checked under the dissecting microscope to count the number of predatory mites prior to release. Amblyseius swirskii was released in the field on the day of arrival, three weeks after transplanting. Because of the low numbers of predatory mites moving out from the sachets

(Table 5-1), one sachet per plant was placed on 105 squash plants (15 plants per bed) located in the middle part of the treatment.

Four weeks after transplanting the squash, Amblyseius swirskii was released a second time onto the same group of plants due to fire antes moving the bran out of the Ulti-Mite sachets.

Mites were purchased in a 500-ml bottle shaker formulation with a bran carrier and five bran samples (0.5-ml) were checked under the dissecting microscope to count the number of predatory mites prior to release (Table 5-1). The amount of bran used per bed was adjusted based on the mite numbers recorded to follow the rate recommended for high infestations (150 – 200 mites/m2, BioBest, 2013, Koppert Biological Systems, 2013). Approximately 70-ml of bran was sprinkled across 15 squash plants per bed (~5-ml of bran per plant).

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Sampling

Using ArcGIS 10.6.1. (ESRI Inc., Redlands, CA) the experimental designed was generated as well as the stratified sampling grid (Fig. 5-2A) where random sampling points are chosen from a set of cells instead of using a sampling grid with fixed distances (Bolstad, 2012).

Each bed was divided into groups of six plants, squash only in the control and squash intercropped with sweet alyssum in the treatment. One plant was randomly chosen from each group using the tool CREATE RANDOM POINTS and a polygon with multiple 1-m wide × 12- m long cells was used as constraining feature (Fig. 5-2A). In the field, beds were divided into 11 groups of six plants like in the computer-based diagram. Because the exact position of all 924 plants used in the experiment was unknown, the plant closest to the randomly chosen points created in ArcGIS was chosen as a sampling point (Fig. 5-2B). Each plant represented one sampling point, for a total of 154 sampling points (0.6 – 7-m apart), 77 sampling points per plot, and 11 points from each bed.

The sampling grid was geo-referenced using an eTrex Summit GPS receiver (Garmin

International Inc., Olathe, KS). Weekly counts and sample collections were conducted only from plants within 1-m around the geo-referenced points (± 1 plant) during a five-week period and starting two weeks after transplanting the squash.

Whitefly eggs and immatures were monitored by collecting two leaves and one flower from one squash plant on each of the sampling points. Leaf area was measured with a LI-3100C

LI-COR area meter (LI-COR, Inc., Lincoln, NE). Squash leaves had an average area of 302.8 ±

31.2-cm2. Each squash leaf was split in half and the abaxial side was checked under a dissecting microscope. The number of eggs and immature whiteflies, and A. swirskii motiles (immatures, adult males and females) present in ½ of each leaf and entire flowers was recorded. The inside and outside of the flowers were also checked for whiteflies and predatory mites.

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Samples collected weekly included sweet alyssum leaves together with inflorescences and had an average area of 16.5 ± 0.8- cm2. Sweet alyssum samples were examined for whiteflies and predatory mites to determine if there is movement of A. swirskii from the squash to the neighboring flowering companion plants. Winged and apterae aphids found in the squash leaves or sweet alyssum were recorded only during the last week of sampling due to low numbers observed during previous weeks.

Viral incidence was monitored by collecting one leaf from one squash plant at each sampling point in the last week of sampling. Excised leaves were transported to the laboratory in a cooler and then stored at -17 °C until processed. Leaf samples were assayed for three aphid- transmitted cucurbit viruses (PRSV-W, WMV, and CMV) using a double or triple antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA or TAS-ELISA) (Nyoike et al.,

2008). Samples showed no infection with aphid-transmitted viruses; thus, no maps were created for viral diseases.

Squash silverleaf (SSL) disorder was monitored weekly by scoring the squash plants at each sampling point with an arbitrary index from 0-5 where 0 = a healthy plant and 5 = all leaves were completely silvered (Fig. 3-3; modified from Yokomi et al., 1990).

Weather data including daily average, minimum, and maximum temperature (°C) and percentage of relative humidity (%RH) were measured using two HOBO Pro v2 temperature data loggers (Onset Computer Co., Bourne, MA) at 60-cm above the ground, one on each plot.

Geostatistical Analysis: Ordinary Kriging

Ordinary kriging analysis was performed to track and compare the movement of whiteflies, aphids, and A. swirskii among treatments. The numbers of insects and mites per leaf

(numbers recorded in ½ of each leaf × 2) were used for analysis. Hardly any predatory mites or whiteflies were found in the flowers, thus, data from flowers were not included in the analysis.

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Variables used to calculate the spatio-temporal metrics included: 1) numbers of whitefly eggs per leaf for each of five weeks, 2) numbers of whitefly immatures per leaf for each of five weeks, 3) number of A. swirskii motiles (immatures, adult males and females) per leaf for each of five weeks, and 4) numbers of aphids per leaf (last week of sampling only).

Coordinates from the geo-referenced sampling points were attached to all data variables from each week separately (one data set for each of the five weeks). The geo-referenced sampling point data collected in the Geographic Coordinate System (GCS) North American

Datum 1983 (NAD83) was then imported into ArcGIS 10.6.1. and projected to NAD83

Universal Transverse Mercator (UTM) zone 17, coordinate system (Fig. 5-2C).

Descriptive statistics including mean, maximum and minimum values, standard error, median, and skewness were calculated for all variables. Whitefly, aphid, and predatory mite populations were positively skewed or asymmetrical (Table 5-2) indicating that variables’ distributions were not normal (symmetrical distribution) (Gotelli & Ellison, 2013). Therefore, log-transformation (log(xi + 1)) was applied to all variables before variography to meet assumptions of normality. Data transformations, semivariograms, and distribution maps were generated using the Geostatistical Wizard in ArcGIS 10.6.1.

The spatial structure of the insect pests and the predatory mite data was determined using semivariograms, a type of graphical representation that shows spatial correlation of sample points in relation to their neighboring points (Park & Obrycki, 2004). The semivariogram function can be defined as:

(5-1)

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where ℽ(h) is the semivariance at distance h or lag distance, Z(xi) and Z(xi + h) are measured values at xi and xi + h and N(h) is the total number of sample pairs within h. The three important components of a semivariogram are the range (the distance at which a variogram reaches a maximum; the distance beyond which samples are not spatially correlated), the sill (the semivariance when the range is reached), and the nugget (is the semivariance when the distance equals zero) (Bolstad, 2012; Park & Obrycki, 2004).

Temporal and spatial variability was identified using prediction maps and semivariograms for each week separately. Heuristic fitting was conducted to identified optimal semivariogram parameters for each variable. Among semivariogram models, exponential model showed optimal fitting for most variables; thus, exponential models were used for all semivariograms. All semivariogram were modeled using a maximum of five neighbors and a minimum of two neighboring points and 12 number of lags in four sectors (45° offset) to predict at unsampled locations for all variables. Table 5-3 shows detailed semivariogram parameters for each variable.

The degree of spatial dependence for each variable was classified following the classification scheme proposed by Dai et al. (2007). Nugget to sill ratios were calculated using the parameters from the semivariograms modeled (Table 5-3) and classification was assigned as follows: strong, moderate, and low spatial dependence with nugget to sill ratios lower than 25%, between 25 – 75%, and more than 75%, respectively.

Cross-validation was conducted using the Geostatistical Wizard in ArcGIS 10.6.1. to check the performance of semivariogram models in kriging. The mean (ME), the root mean square (RMSE), and the root mean square standardized (RMSSE) prediction errors from the

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cross-validation procedure (Table 5-4), and coefficients of determination (R2, Fig. 5-5, 5-8) were used to evaluate the prediction performance of the semivariogram models at each week.

Results

Sweetpotato whitefly infestation levels were high since the beginning of the sampling period indicating that whiteflies established at early stages of the crop. Higher population densities of whitefly eggs and immatures were recorded overtime in the control plot compared to the treatment plot (Fig. 5-3). Highest densities of whitefly eggs were recorded in the control and treatment plots at the beginning of the sampling period (three weeks after planting, WAP) followed by an increase in whitefly immatures four WAP. Highest densities were observed in the control plot with three to four times more whitefly immatures compared to the treatment plot four and five WAP, respectively (Fig. 5-3).

Population densities of A. swirskii recorded were low overtime with a maximum of five mites per leaf at week four. Highest numbers of predatory mites were recorded three and four

WAP in the treatment plot where they were deliberately released. Numbers peaked after the second release event four WAP (10/24/2018) and similar numbers of A. swirskii motiles were recorded in the control plot where they were not originally introduced. Reductions in the numbers of whitefly eggs were recorded during the weeks when A. swirskii showed higher numbers and the weeks following predatory mite release (Fig. 5-3). Predatory mites were collected from both plots until the end of the sampling period. Lowest numbers of predatory mites were recorded in the squash six and seven WAP in both plots (Fig. 5-3).

Spatio-Temporal Distribution Patterns

At a more detailed spatial scale, high numbers of whitefly eggs were collected from squash leaves in the control plot at week three, showing one “hot spot” with up to 80 whitefly eggs per leaf in the southeast area close to the buffer zone (Fig. 5-4A). Likewise, moderate

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density of whitefly eggs was found in the southwest portion and throughout the middle part of the treatment plot with up to 40 eggs per leaf. Less than five eggs were recorded in squash leaves from the north and south corners of the treatment plot were the alyssum was planted (Fig. 5-4A).

There was no spatial pattern identified for whitefly immatures since less than five immatures per leaf were collected three WAP in the entire experimental area (Fig. 5-4B).

Twenty-four hours after the first A. swirskii release event (10/16/2018) the distribution pattern of the predatory mites in the treatment plot was similar to the spatial distribution of the whitefly eggs (Fig. 5-4C). Predatory mites were able to cross the 8.2-m of bare soil buffer zone between plots within 24 hours. Amblyseius swirskii individuals were collected from squash leaves in the control plot and a scatter distribution was observed with up to seven mites per leaf

(Fig. 5-4C). Increased predatory mite migration to the control plot was recorded in the following weeks.

The week of the second A. swirskii release (10/23/2016) in the treatment plot (four

WAP), “hot spots” were identified within the area of release with a maximum mite density of 29 mites per squash leaf (Fig. 5-4D). Predatory mite migration to the control plot continue to increase four WAP with higher densities in the southeast area of the plot which is closer to the buffer zone. A substantial increase in the densities of whitefly immatures was observed in both plots four WAP. Higher numbers were detected in the entire control plot whereas lower numbers were observed where alyssum was planted in the treatment plot and moderate density where A. swkirskii was released (Fig. 5-4E). As the populations of A. swirskii peaked in the treatment plot, a change in the spatial distribution of whitefly eggs was observed four WAP with less numbers in the middle area of the treatment plot were the predatory mites were released. More whitefly eggs were registered in the north and south edges of the plot where less predators were

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estimated. Numbers of whitefly eggs in the control plot remained high in the same area where the predatory mites were moving into (Fig. 5-4F).

Five WAP, whitefly eggs started to decrease in the control plot and their spatial distribution shifted showing more eggs in the north and south areas (Fig. 5-4G). The north area of the control plot also showed the lowest numbers of A. swirskii motiles five WAP and a scattered pattern was identified for the middle and south area of the plot (Fig. 5-4I). No major differences in spatial distribution or infestation levels was observed for whitefly eggs in the treatment plot or immature whiteflies between weeks four and five (Fig. 5-4H).

An inverse relationship between numbers of predatory mites and whitefly eggs was also identified in the treatment plot 5 WAP. Lower numbers of whitefly eggs were recorded in areas were higher numbers of predatory mites were present and as the mites start to disperse in the squash field. The same distribution pattern was observed for whitefly immatures.

During the last two weeks of sampling (six and seven WAP), the same areas occupied by whitefly eggs and immatures showed a continuous reduction in numbers as the A. swirskii mites dispersed completely throughout both the control and the treatment plot (Fig. 5-4J-O). A second

“hot spot” was identified for A. swirskii motiles six WAP with up to 19 mites per leaf in the southwest corner of the control plot (Fig. 5-4J). The numbers of whitefly eggs were significantly reduced in that area seven WAP and the numbers of predatory mites were reduced to less than 3 mites per leaf over the entire area (Fig. 5-4M-O).

Low aphid population densities were found in both the control and the treatment plot six

WAP. All leaf samples were negative for infection with CMV, PRSV, and WMV. However, one

“hot spot” was found for aphid populations densities with up to 12 aphids per squash leaf in the southeast corner of the control plot. Likewise, the highest numbers of aphids were found in the

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southeast corner of the treatment plot next to the buffer zone. The remaining squash and alyssum planted in the treatment plot showed aphids numbers below two per leaf (Fig. 5-5A).

Variography

Based on the classification scheme proposed by Dai et al. (2007), high nugget to sill ratios (> 75%) were obtained in semivariograms for whitefly eggs indicating that random distribution patterns were identified for whitefly eggs during weeks when lowest densities were recorded (up to 20 eggs per leaf, seven WAP) as well as weeks when highest densities were recorded (up to 103 eggs per leaf, three and four WAP) (Table 5-3). Strong spatial structure determined as nugget to sill ratio lower than 25% was identified only when intermediate densities of whitefly eggs were recorded (11 – 50 eggs per leaf) five and six WAP regardless of the plot (Table 5-3). The nugget (variance within the smallest distance measured) to sill (the semivariance at the distance beyond which samples are no longer correlated) ratio indicates the percentage of the variance found at a distance smaller than the smallest distance measured, in other words, it represented the percentage of the variance accounted in the model (Aidoo et al.,

2015; Dai et al., 2007).

Low to zero variability in the estimated densities of whitefly immatures at spatial scales smaller than measured (low nugget) indicated that sampling points within the range (1 – 5-m) had very similar if not equal values three, four, and five WAP. This was true for whitefly immatures in the treatment plot at all weeks except seven WAP and whitefly immatures in the control plot three, four, and five WAP (Table 5-3). A gradual reduction in spatial dependence with increased distance was identified in these cases suggesting a clumped distribution pattern.

Conversely, a total absence of spatial structure was identified for whitefly immatures when highest (control plot, five WAP) and lowest numbers were recorded (treatment plot, seven WAP)

(Table 5-3).

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A strong spatial structure was identified for A. swirskii population in the treatment plot four WAP (Table 5-3). This is the same time and area where the highest numbers of predatory mites were collected. Likewise, strong spatial dependence was found for intermediate numbers of the predatory mites recorded in both the control and treatment plots five WAP, and the control plot six WAP. Low nugget to sill ratios were calculated in those cases meaning that most of the variation in the data was captured within the range. Contrary, pure nugget effect (nugget equals the sill) was identified for estimated densities of A. swirskii motiles in the treatment plot six

WAP indicating lack of spatial structure (Table 5-3). This is the same time and area where a “hot spot” for predatory mites was estimated (Fig. 5-4J).

A moderate spatial dependence (nugget to sill ratio between 50 and 60%) was identified for population densities of aphids in the control and the treatment plot seven WAP (Table 5-3).

Model Performance

Overall weeks and plots, regression models showed that hardly any variance in the predicted values (< 1%) was explained by the densities of whitefly eggs measured (Fig. 5-6).

Similarly, more than 98% of the variance in the whitefly immature predicted values was not explained by the measured values (Fig. 5-7). Linear regression showed that less than 1% of the variance in the aphid predicted values was explained by the measured values in the control and treatment plots (Fig. 5-5B, C). The highest coefficients of determinations among all variables and sampling events were obtained for A. swirskii motiles in the treatment plot four and five

WAP (Fig.5-8). However, these coefficients continue to be low (< 5%) indicating poor performance of the models fitted during the kriging procedure.

This is consistent with the prediction errors obtained from the cross-validation procedures. Most of the root mean square errors (RMSEs) calculated for whitefly eggs across weeks showed high values whereas the root mean square standardized errors (RMSSEs) showed

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low values (≤ 0.75). This indicates that the prediction values are likely far from the measured values for whitefly eggs and the kriging variances are not very accurate. Only the model fitted for whitefly eggs in the treatment plot five WAP showed higher accuracy (RMSSE = 0.95) for the kriging variances (Table 5-4).

High kriging variance accuracy was only observed in the model fitted for whitefly immatures from the control plot seven WAP (Table 5-4). Most semivariogram models for whitefly immatures showed very high RMSE values with low variance accuracy or low RMSE values with over optimistic values (RMSSE greater than 1) for the variability of the predicted values (Table 5-4). Contrary, all semivariogram models for A. swirskii included low RMSEs meaning that predicted values are likely to be close to the measured values. However, all

RMSSE values above 1 indicated that variability of the predicted values could have been overestimated. Lastly, in the case of aphids, variances for the predicted values seemed to be reliable for aphid estimations in the treatment plot only (Table 5-4).

Squash Cultivars, Silverleaf Index, and Yield

The numbers of whitefly eggs, immatures, and A. swirskii motiles were pooled together overall weeks to compare recorded numbers between experimental plots and among squash cultivars. Squash cultivars did not appear to influence the spatial distribution of whitefly eggs, immatures, and A. swirskii mites. Hardly any whiteflies and predatory mites were found inhabiting sweet alyssum plants.

Mean numbers of whitefly eggs and immatures were two to three times higher in the squash cultivar ‘Zephyr’ compare to ‘Cash Flow’ and ‘Gold Rush’ (Fig. 5-6A). Additionally, whitefly egg and immature densities recorded in ‘Zephyr’ squash planted in the treatment plot was approximately 50% lower compared to densities recorded in the control plot (Fig. 5-6A).

This reduction in whitefly immatures was reflected in lower average SSL index. Most ‘Zephyr’

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squash in the treatment plot were rated around index 2 (Fig.5-6B) meaning that most rated plants showed leaves with veins silvered and a netted appearance (Fig. 3-3). ‘Zephyr’ squash planted in the control plot were rated close to index 3 (Fig.5-6B), thus, most plants had leaves with primary and secondary leaves silver (Fig. 3-3).

No major numerical differences were observed between whitefly egg and immature numbers recorded in ‘Cash Flow’ and ‘Gold Rush’ cultivars within the same plot. However, approximately 30% less whitefly eggs and immatures were collected in ‘Cash Flow’ and ‘Gold

Rush’ squash planted in the treatment plot compared to the control plot (Fig. 5-6A). ‘Gold Rush’ squash showed the highest SSL ratings among cultivars, but no major numerical differences were observed compared to ‘Cash Flow’ or between control and treatment plots (Fig. 5-6B).

Sweetpotato whitefly infestation level, the presence of sweet alyssum or A. swirskii releases had no apparent effect on the squash total yield. Despite showing the highest numbers of whitefly eggs and immatures, ‘Zephyr’ squash planted in the control plot presented the highest total marketable yield followed by ‘Cash Flow’ squash planted in the treatment control (Fig. 5-

6C). The ‘Gold Rush’ cultivar had the lowest total marketable yields in both control and treatment plots. Pickleworms borrowing the fruit were more commonly found in ‘Cash Flow’ green zucchinis and ‘Gold Rush’ yellow zucchinis compared to the half-tone summer squash

‘Zephyr’ regardless of the plot (Fig. 5-6C).

Discussion

Amblyseius swirskii was released in squash plants in the middle of the treatment plot with the hope that they would move north and south of the plot regardless of the plant host (squash or alyssum). The predatory mites demonstrated high dispersal capacity within squash rows and between experimental plots. Squash plants were big enough to create leaf bridges when the sampling period started allowing mite ambulatory dispersal. Within 24 hours, predatory mites

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moved to squash plants planted north and south of the plot and given the lack of physical barrier between experimental plots, A. swirskii was able to cross the buffer zone within 24 hours as well.

Phytoseiid mites such as A. swirskii, can take advantage of wind currents as a way of dispersal especially gravid females in search for other plant hosts (Lopez et al., 2016; Hoy, 2011).

Schotzko and O’Keeffe (1989) studied the most commonly used semivariogram models and patterns of distribution in insect investigations. They described semivariograms of random distribution as linear with little or no slope and the localize variance equal to the sill. Clumped or aggregated distribution patterns on the other hand, have a gradual reduction in spatial dependence with increased distance until the sill is reached. Likewise, Dai et al. (2007) classified the degree of spatial dependence of a variable based on the nugget to sill ratio from the semivariogram modeled. Authors entitled strong, moderate, and low spatial dependence to variables with ratios lower than 25%, between 25 – 75%, and more than 75%, respectively.

In this study, A. swirskii distribution in the field was random at the beginning of the season when the mites were limited to the middle area of the plots, and at the end of the season when the lowest numbers of predatory mites were collected. Moderate spatial dependence was identified when low densities of A. swirskii were used for predictions. Low predatory mite densities during these weeks may be related to the intrusion of fire ants into the sachets on week three and the reduction in temperature registered through the entire last week of sampling (Fig.

5-10).

Amblyseius swirskii lay their eggs in the bran and many larva and nymph stages take shelter in the bran. Therefore, movement of bran out of the sachets by fire ants could reduce substantially the release of the predatory mites over time and jeopardize the establishment of the predator. Fire ants are omnivorous predators and have been reported to feed on many insect pests

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(e.g., aphids, cucumber beetles, lepidopteran larvae) in cotton and soybean cropping systems, but they are also intraguild predators because they are feeding on many beneficial arthropod species

(e.g., spiders, Orius spp., syrphid larvae, Geocoris spp.) (Eubanks, 2001). Imported fire ants are voracious predators and could be feeding on the eggs and other stages of A. swirskii released in the squash indicating intraguild predation. However, the movement of bran was rapid (within 24- h of A. swirskii release) and mostly observed when the predatory mites were released using sachets. Fire ants were observed around the bran sprinkled onto the plants during the second release event (four WAP), but no major bran movement by the fire ants was observed then.

The hypothesis for the changes in fire ant behavior related to the type of A. swirskii release method (sachets versus loose bran sprinkled onto squash leaves) is the difference in the rate of dispersal of the predatory mites between release methods. During the study, A. swirskii was observed to rapidly adventure out of the bran in search for food and shelter after the loose bran is spread onto the squash leaves leaving the bran empty (only eggs remain). In contrast, A. swirskii in the sachets were observed to disperse in lower numbers and most stayed inside.

Sachets are used as a slow release method to maintain populations of the predatory mites in the field for longer periods (four to six weeks) by offering prey (e.g., T. putrescentiae mites) and shelter as a preventative technique (Hoy, 2011). This could explain why aggressive predators like fire ants could find A. swirskii mites concentrated into the sachets as a suitable food source.

Lack of spatial dependence to moderate spatial dependence was also identified for whitefly eggs at the beginning and the end of the season. This is probably due to the highest aggregation of whitefly eggs three WAP (control plot) in “hot spots” leaving many zero counts in the remaining sampling points as well as the lowest numbers collected seven WAP showing many zero counts in most of the sampling points. The same pattern was observed in the control

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plot four WAP where the “hot spots” were resilient. Semivariograms modeled with data that has very large or very small counts result in noise that may mask spatial structure and produce nugget effects (Liebhold et al., 1993).

Strong spatial dependence was identified for A. swirskii four, five and six WAP when higher population densities were measured and major movement within and between experimental plots was observed. Predatory mite distribution in the treatment plot was clumped four WAP when the population peaked and dispersal of A. swirskii throughout the entire plot was recorded. Similar semivariogram parameters and spatial structure was identified for the mites on week five. However, lower temperatures during this week (< 15°C for multiple days) may have influenced a reduction in A. swirskii numbers throughout the field.

Six WAP, distribution patterns in the field shifted and lower population densities of A. swirskii were estimated in the treatment plot compared to the control plot. Spatial dependence was not detected in the treatment plot and the semivariograms calculated were pure nugget effect with a nugget to sill ratio of 100% (nugget equal to the sill) meaning that no variation in the data was captured within the range (8-m). Temperatures increased during week six and so did the numbers of A. swirskii in the control plot. A clumped distribution pattern and strong spatial dependence was identified for the predatory mites in the control plot despite the aggregation of

A. swirskii motiles mostly on the southwest area of the plot.

Spatial structure was detected for whitefly egg densities when moderate whitefly egg numbers were recorded and in the same weeks when spatial dependence was identified for A. swirskii mites. Whitefly eggs were aggregated along the north and south areas of the treatment plot which coincided with areas were lower densities of predatory mites were collected. The same pattern was observed five and six WAP when spatial structures were detected for both the

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prey and the predator. The densities and distribution pattern of whitefly eggs seemed to be influence by the presence and dispersal of its predator A. swirskii. Since the beginning of the sampling period, spatial distribution in the field shifted following inverse patterns suggesting an inverse relationship between these two variables. However, both whiteflies and predatory mites did not move into the companion plants and distribution patterns extending north and south of the plots could also be related to avoidance of the alyssum plants.

Amblyseius swirskii feeds mostly on whitefly eggs and can also feed on first and second instar whitefly immatures (Soleymani et al., 2016). During the study, all instar immatures were counted together. Yet, predatory mites preying on eggs and first instar immatures only, can cause a reduction in the overall numbers of whitefly immatures. Strong spatial dependence was detected for whitefly immatures in the control plot four WAP when highest numbers were recorded over the entire area and immatures were aggregated into “hot spots” in the middle area of the plot. Conversely, the treatment plot showed “hot spots” in the north and south areas of the plot where lower numbers of predatory mites were present. This displacing distribution pattern observed between A. swirskii and immature whiteflies was persistent in the treatment plot during weeks four, five, and six when strong to moderate spatial dependence was detected for whitefly immatures.

Spatial range (i.e., distance at which data are spatially correlated) varied between 1 – 5-m over the whole sampling period when strong spatial structure of the variables was detected. Low spatial ranges indicated that plants within those distances (1-m = one squash plant, 5-m = four to five plants) had similar numbers of whitefly eggs, immatures and A. swirskii motiles. Spatial autocorrelation range can be used to determine appropriate sampling intervals for whiteflies, aphids, and A. swirskii. However, sampling intervals that low are not practical for field studies

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because they would be labor intensive and time consuming. Semivariogram models that showed moderate spatial structure computed more variable ranges from 1 – 20-m. Most semivariograms modeled for the remaining variables were linear meaning that spatial correlation range could not be identified.

Kriging prediction analysis can overestimate large measured values and underestimate low measured values. Therefore, the use of multiple cross-validation parameters should be used to evaluate prediction performance of semivariogram models (Atkinson & Lloyd, 2010). High

ME and RMSE values were calculated for whitefly egg and immature estimations indicating that ordinary kriging had low accuracy in predicting these variables. When kriging variances are accurate RMSSE should be close to 1 (Atkinson & Lloyd, 2010), but most RMSSE values for whitefly populations were below 0.75. This could be attributed to the presence of very large numbers of whiteflies measured in just a few leaves and many zero counts in most other squash leaves. In the case of A. swirskii motiles, ME and RMSE were substantially lower compared to whitefly models. Nonetheless, multiple A. swirskii models computed RMSSE values beyond 1 meaning that overestimations in predicting predatory mite numbers could have occurred.

Even though squash cultivar had no apparent effect on A. swriskii movement, numerical differences in the infestations levels among cultivars was observed for whiteflies. ‘Zephyr’ and

‘Cash Flow’ are high-yielding cultivars that showed low SSL ratings and higher yields despite high whitefly infestations. ‘Zephyr’ squash is very attractive to farmers and consumers due to their green-yellow tone, but it was observed to be highly attractive to whiteflies as well probably due to the light green color of their leaves that make the plants easily detected by the whiteflies.

Several plants were observed stunted and deformed when infested with high numbers of whiteflies and, in presence of whitefly-transmitted viruses, fruit quality can be at risk. ‘Cash

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Flow’ and ‘Gold Rush’ are more sturdy cultivars, but ‘Gold Rush’ fruit production was slower compared to the other two cultivars.

Overall, A. swirskii was capable of suppressing whitefly populations and inoculated mites in the treatment plot seemed to influence whitefly populations in the entire field. Hardly any predatory mite was recorded moving into the alyssum. This was unexpected because sweet alyssum has been reported as a good host for A swirskii in previous studies. Henry et al. (2011) evaluated the potential of multiple ground covers used in agro-ecosystems in Florida as banker plants for A. swirskii and reported that the alyssum cultivar “Snow Princess” showed potential as host for the predatory mite. Sweet alyssum may have influenced the distribution of A. swirskii and whiteflies by avoidance of the alyssum plants, but the presence of alyssum had no apparent effect on the densities of whiteflies and predatory mites in the neighboring squash plants.

However, lower densities of aphids were recorded in the treatment plot where the alyssum was planted compared to the control with squash monoculture. This reduction in aphid numbers could be related to the presence of alyssum which is attractive to parasitoids and predators (i.e., braconid wasps, syrphid and dolichopodid flies, among others) that feed on aphid species.

Further monitoring efforts to identify naturally occurring beneficial insects in the alyssum with potential to suppress aphids are needed.

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Table 5-1. Number of Amblyseius swirskii motiles (immatures, adult males and females) counted prior to release into the field. Each sample consisted of 0.5-ml of bran examined under a disecting miroscope on the day of arrival for sachets (10/16/2018) and shaker bottle (10/23/2018). Formulation Sample Bran weight (g) No. of A. swirskii motiles Ulti-Mite 1 1.13 50 (sachets) 2 1.37 5 3 1.22 10 4 0.14 21 5 0.12 34 Average 0.79 24 Swirskii-Mite 1 1.4 13 (shaker bottle) 2 0.01 17 3 0.01 22 4 0.044 7 5 0.05 19 Average 0.3028 16

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Table 5-2. Descriptive statistics including mean, maximum (Max), minimum (Min), standard error (SE), median, and skewness for sweetpotato whitefly egg and immature, Amblyseius swirskii motile (immatures, adult males and females), and aphid numbers per squash leaf over a five-week sampling period in fall 2018. Variable Plot Sampling week (date) Mean Min Max SE Median Skewness Whitefly Control 3 WAP (10/17/2018) 24.66 0.00 278.00 4.36 13.00 4.22 eggs Treatment 3 WAP (10/17/2018) 12.92 0.00 11.00 2.55 0.00 2.42 Control 4 WAP (10/24/2018) 28.75 0.00 2.00 3.93 0.00 2.20 Treatment 4 WAP (10/24/2018) 8.04 0.00 103.00 1.40 2.00 1.99 Control 5 WAP (10/31/2018) 10.08 0.00 6.00 2.13 0.00 2.85 Treatment 5 WAP (10/31/2018) 5.64 0.00 37.00 1.08 0.00 3.31 Control 6 WAP (11/07/2018) 8.29 0.00 196.00 1.79 14.00 4.12 Treatment 6 WAP (11/07/2018) 9.70 1.00 164.00 1.56 20.00 1.48 Control 7 WAP (11/14/2018) 12.88 0.00 21.00 2.50 0.00 3.79 Treatment 7 WAP (11/14/2018) 5.90 0.00 54.00 1.22 2.00 3.35 Whitefly Control 3 WAP (10/17/2018) 0.71 0.00 67.00 0.20 8.00 3.60 immatures Treatment 3 WAP (10/17/2018) 0.30 0.00 32.00 0.12 0.00 4.07 Control 4 WAP (10/24/2018) 28.19 0.00 89.00 3.58 3.00 2.37 Treatment 4 WAP (10/24/2018) 14.27 0.00 117.00 1.83 34.00 1.25 Control 5 WAP (10/31/2018) 39.30 0.00 5.00 3.34 0.00 0.85 Treatment 5 WAP (10/31/2018) 9.18 0.00 58.00 1.56 3.00 2.35 Control 6 WAP (11/07/2018) 10.97 0.00 72.00 1.87 4.00 2.28 Treatment 6 WAP (11/07/2018) 4.36 0.00 11.00 1.31 0.00 4.01 Control 7 WAP (11/14/2018) 12.53 0.00 99.00 2.68 3.00 2.64 Treatment 7 WAP (11/14/2018) 4.21 0.00 75.00 1.22 3.00 2.53 A. swirskii Control 3 WAP (10/17/2018) 0.18 0.00 18.00 0.06 0.00 2.87 motiles Treatment 3 WAP (10/17/2018) 1.82 0.00 54.00 0.64 2.00 4.49 Control 4 WAP (10/24/2018) 1.38 0.00 64.00 0.46 0.00 3.83 Treatment 4 WAP (10/24/2018) 2.27 0.00 7.00 0.58 0.00 3.48 Control 5 WAP (10/31/2018) 0.44 0.00 144.00 0.12 7.00 2.46 Treatment 5 WAP (10/31/2018) 1.27 0.00 113.00 0.30 1.00 2.31 Control 6 WAP (11/07/2018) 0.56 0.00 10.00 0.27 0.00 6.21 Treatment 6 WAP (11/07/2018) 0.69 0.00 57.00 0.16 1.00 2.67 Control 7 WAP (11/14/2018) 0.81 0.00 59.00 0.24 0.00 3.58 Treatment 7 WAP (11/14/2018) 0.52 0.00 5.00 0.12 0.00 2.65 Aphids Control 7 WAP (11/14/2018) 3.08 0.00 24.00 0.51 2.00 2.60 Treatment 7 WAP (11/14/2018) 2.00 0.00 27.00 0.58 0.00 3.56 WAP = weeks after planting

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Table 5-3. Summary of semivariogram parameters for ordinary kriging interpolation analysis used for mean numbers of sweetpotato whitefly eggs and immatures, its predator Amblyseius swirskii, and aphids present in the squash during the growing season in fall 2018. Exponential semivariogram models were used for all variables. Values in red indicate strong spatial dependence (nugget:sill < 25%) and values in blue indicate low spatial dependence (nugget:sill > 75%) based on the classification scheme used as reference (Dai et al., 2007). Variable Plot Sampling week Range Nugget Sill Nugget: Lag (date) (m) Sill size Whitefly Control 3 WAP (10/17/2018) 9 1.044 2.896 36.05 0.716 eggs Treatment 3 WAP (10/17/2018) 9 1.962 2.473 79.34 1.563 Control 4 WAP (10/24/2018) 8 1.229 1.542 79.70 1 Treatment 4 WAP (10/24/2018) 2 0.915 1.623 56.38 0.374 Control 5 WAP (10/31/2018) 1 0.39 2.052 19.01 0.19 Treatment 5 WAP (10/31/2018) 1 0 1.011 0.00 0.38 Control 6 WAP (11/07/2018) 1.575 0.086 1.37 6.28 1 Treatment 6 WAP (11/07/2018) 8 1.058 2.319 45.62 1 Control 7 WAP (11/14/2018) 5 1.68 1.68 100.00 3.156 Treatment 7 WAP (11/14/2018) 8 1.08 1.507 71.67 1 Whitefly Control 3 WAP (10/17/2018) 2.192 0.222 0.472 47.03 0.182 immatures Treatment 3 WAP (10/17/2018) 2.841 0 0.166 0.00 0.251 Control 4 WAP (10/24/2018) 1 0.044 1.007 4.37 0.186 Treatment 4 WAP (10/24/2018) 5 0 2.041 0.00 1 Control 5 WAP (10/31/2018) 1 1.119 1.128 99.20 0.179 Treatment 5 WAP (10/31/2018) 5 0 1.853 0.00 1 Control 6 WAP (11/07/2018) 7.758 1.133 1.835 61.74 1 Treatment 6 WAP (11/07/2018) 2 0 1.166 0.00 1 Control 7 WAP (11/14/2018) 8 1.653 2.142 77.17 0.878 Treatment 7 WAP (11/14/2018) 5 1.29 1.29 100.00 1 A. swirskii Control 3 WAP (10/17/2018) 1 0.071 0.131 54.20 0.181 motiles Treatment 3 WAP (10/17/2018) 12 0.389 0.948 41.03 1.665 Control 4 WAP (10/24/2018) 2 0.438 0.622 70.42 1.37 Treatment 4 WAP (10/24/2018) 4 0 1.062 0.00 1.794 Control 5 WAP (10/31/2018) 2.096 0 0.204 0.00 1 Treatment 5 WAP (10/31/2018) 12 0.097 0.696 13.94 1 Control 6 WAP (11/07/2018) 8 0.001 0.282 0.35 0.957 Treatment 6 WAP (11/07/2018) 8 0.3 0.3 100.00 1 Control 7 WAP (11/14/2018) 7.054 0.247 0.368 67.12 1 Treatment 7 WAP (11/14/2018) 8 0.16 0.24 66.67 1 Aphids Control 7 WAP (11/14/2018) 3.399 0.461 0.873 52.81 0.283 Treatment 7 WAP (11/14/2018) 20 0.478 0.83 57.59 3.432 WAP = weeks after planting

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Table 5-4. Summary of mean (ME), root mean square (RMSE), and root mean square standardized errors (RMSSE) used for evaluation of model accuracy in estimating mean numbers of sweetpotato whiteflies, Amblyseius swirskii mites, and aphids on squash leaves. Variable Plot Sampling week (date) ME RMSE RMSSE Whitefly Control 3 WAP (10/17/2018) 10.474 42.18 0.57 eggs Treatment 3 WAP (10/17/2018) -0.508 22.02 0.47 Control 4 WAP (10/24/2018) 2.516 33.64 0.546 Treatment 4 WAP (10/24/2018) 0.437 13.5 0.665 Control 5 WAP (10/31/2018) 2.468 19.63 0.393 Treatment 5 WAP (10/31/2018) -0.474 9.667 0.95 Control 6 WAP (11/07/2018) -0.625 16.89 1.194 Treatment 6 WAP (11/07/2018) 1.939 13.64 0.645 Control 7 WAP (11/14/2018) 1.380 22.66 0.642 Treatment 7 WAP (11/14/2018) -0.784 10.96 1.012 Whitefly Control 3 WAP (10/17/2018) -0.024 1.842 1.44 immatures Treatment 3 WAP (10/17/2018) -0.083 1.054 1.75 Control 4 WAP (10/24/2018) 1.219 33.89 0.758 Treatment 4 WAP (10/24/2018) 4.509 16.55 0.455 Control 5 WAP (10/31/2018) 7.848 31.64 0.465 Treatment 5 WAP (10/31/2018) 1.026 14.08 1.271 Control 6 WAP (11/07/2018) 0.667 17.02 0.755 Treatment 6 WAP (11/07/2018) -1.283 11.6 1.808 Control 7 WAP (11/14/2018) -1.302 23.7 0.83 Treatment 7 WAP (11/14/2018) -1.601 10.79 2.075 A. swirskii Control 3 WAP (10/17/2018) 0.024 0.521 1.05 motiles Treatment 3 WAP (10/17/2018) -0.541 5.655 2.397 Control 4 WAP (10/24/2018) 2.139 3.965 1.515 Treatment 4 WAP (10/24/2018) 0.342 4.078 0.601 Control 5 WAP (10/31/2018) -0.093 0.996 1.452 Treatment 5 WAP (10/31/2018) -0.076 2.268 1.459 Control 6 WAP (11/07/2018) -0.228 2.321 3.513 Treatment 6 WAP (11/07/2018) -0.028 1.456 1.578 Control 7 WAP (11/14/2018) -0.206 2.144 2.175 Treatment 7 WAP (11/14/2018) -0.081 1.1 1.536 Aphids Control 7 WAP (11/14/2018) -0.235 5.017 2.452 Treatment 7 WAP (11/14/2018) -0.603 4.605 0.958 WAP = weeks after planting

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Figure 5-1. Plot and treatment arrangement for 2018 on-farm experiments.

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Figure 5-2. Sampling point randomization and geo-referenced grid. A) Stratified points created in ArcGIS for the 2018 on-farm experiments, B) plants selected in the diagram based on the randomly created points, and C) geo-referenced sampling grid (Orthoimage of Alachua county, FL; source: Land Boundary Information System, LABINS; scale = 1”=100’).

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Figure 5-3. Population densities of sweetpotato whitefly eggs, immatures, and predatory mite Amblyseius swirskii motiles (immatures, adult males and females) on squash leaves collected over a five-week period in fall 2018. WAP = weeks after planting.

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Figure 5-4. Spatial distribution of the sweetpotato whitefly eggs and immatures, and Amblyseius swirskii motiles (immatures, adult males and females) recorded per squash leaf collected from control and treatment plots over a five-week sampling period in fall 2018. WAP = weeks after planting. .

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Figure 5-5. Spatial distribution of aphids collected in two experimental plots and the relationship between aphid numbers measured and predicted per leaf for control and treatment plots during the last week of sampling (7 WAP) in fall 2018 experiments. Coefficients of determination (R2) are shown. WAP = weeks after planting.

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Figure 5-6. Relationship between sweetpotato whitefly eggs measured and predicted values for each week during a five-week sampling period in fall 2018. The coefficient of determination (R2) is shown. WAP = weeks after planting.

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Figure 5-7. Relationship between sweetpotato whitefly immatures measured and predicted values for each week in a five-week sampling period in fall 2018. The coefficient of determination (R2) is shown. WAP = weeks after planting.

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Figure 5-8. Relationship between Amblyseius swirskii motiles measured and predicted values for each week in a five-week sampling period in fall 2018. The coefficient of determination (R2) is shown. WAP = weeks after planting.

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Figure 5-9. Insect and mite population densities, SSL ratings, and yield collected per plots and cultivars. A) sweetpotato whitefly eggs and immatures, and Amblyseius swirskii motiles (immatures, adult males and females), B) Squash silverleaf disorder (SSL), and C) total yield.

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Figure 5-10. Average, maximum, and minimum temperature (°C), and percentage of relative humidity (%RH) for the squash season in fall 2018. Daily averages are shown from the start until the end of the sampling period. WAP = weeks after planting.

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CHAPTER 6 ASSESS THE SIDE-EFFECT OF TWO BIOINSECTICIDES ON A. SWIRSKII MITES UNDER LABORATORY AND GREENHOUSE CONDITIONS

Sweetpopato whiteflies (Bemisia tabaci Genn., B biotype; Hemiptera: Aleyrodidae) are the squash growers’ major pest of concern followed by melon aphids (Aphis gossypii Glover,

Hemiptera: Aphididae). Various parasitoid species feed on whitefly nymphs as well as several predators such as mirid bugs, minute pirate bugs, and predatory mites including Amblyseius swirskii Athias-Henriot (Acari: Phytoseiidae) (Stansly & Natwick, 2010). Reducing the effects of insecticides on biological control agents and naturally occurring beneficial arthropods is important to provide sustainable strategies for organic squash growers to manage key insect pests, and their associated viral diseases. If effective tactics are identified, the suppression of pest’s population by a synergy of complementary strategies may be achieved.

The effects of various insecticides used in vegetable production on A. swirskii have been evaluated. Most of the assessed products are limited to conventional cropping systems (synthetic pesticides) and are not used in organic squash production. These chemicals include abamectin

(Avid®), metaflumizone (Alverde™), chlorantraniliprole (Altacor®), emamectin benzoate

(Affirm®), fenpyroximate (Portal®), methoxyfenozide (Runner®), flonicamid (Teppeki®)

(Fernandez et al., 2017; Lopez et al., 2015; Amor et al., 2013; Colomer et al., 2010; Gradish et al., 2010) among others. The effects of only a few inorganic pesticides such as sulfur (Gazquez et a., 2011) and a few bioinseticides (Kim et al., 2018) on A. swirskii have been assessed.

Spinosad (Entrust®) is one of the most commonly used pesticide in organic production in

Florida but has been recently reported to be ineffective on insect populations attacking squash and it is not labeled for control of sweetpopato whiteflies, although it is labelled for use in squash

(Razze et al., 2016). M-Pede® and Azera® are bioinsecticides that are labelled for organic

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production of many vegetable crops in the state including squash and has gain popularity in the last decade.

M-Pede is a soap concentrate with the active ingredient of potassium salts and fatty acids.

It is approved for use on organic squash and has been adopted in the last few years by organic squash growers in Florida as a result of the poor performance of the former most common insecticide, spinosad (O. E. Liburd pers. com). It is label for control of soft-bodied insects including thrips, aphids and sweetpopato whiteflies in open field and greenhouse grown cucurbits. As an insecticide/miticide/fungicide, M-Pede is also labeled to control less problematic pests in squash like broad mites and spider mites, and powdery mildew that, in contrast with mite pests, is a major issue during the final stage of the squash season.

Azera is a botanical insecticide released in 2011 to the market. It is approved for organic use and contains a mix of pyrethrins and azadirachtin as active ingredient. Pyrethrins are a solvent extract from chrysanthemum flowers (Chrysanthemum spp., Asteraceae) that is very safe for humans and is very fast acting on insects causing immediate paralysis (Yu, 2008).

Azadirachtin is a secondary metabolite from neem tree seeds (Azadirachta indica Juss.,

Meliaceae), also known as neem seed oil, that has molting disruption properties and behavioral effects on insects (Schmutterer, 1990). Azera controls insects by quick knock-down, ingestion, and has insect growth regulation activity. It is labeled for a wide variety of soft-bodied insects including whiteflies, thrips and melonworms, and some pest mites such as spider mites.

The effects of both bioinsecticides on commercially available natural enemies, mostly parasitoid species, have been studied; however, there are no reports regarding the toxicity of the bioinsecticides M-Pede and Azera on A. swirskii. The goal of this study is to evaluate the effects

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of Azera and M-Pede on different developmental stages of A. swirskii to identify their compatibility with the predatory mite for use in organic squash.

Materials and Methods

Experiments were conducted from October to December of 2018 in the greenhouse and laboratory facilities at the University of Florida’s Entomology and Nematology Department

(Gainesville, FL) and samples were processed in the Small Fruit and Vegetable IPM Laboratory.

Mite Colonies

Amblyseius swirskii was purchased on August 2018 in a bottle shaker formulation

(Koppert Biological Systems, Howell, MI) to initiate a laboratory colony. The predatory mite colony was maintained in an incubator chamber (24°C, 75 ± 3% RH) in 10 × 10-cm trays used as arena with a wax surface surrounded with water-soaked cotton. Water was added daily to keep the cotton soaked and prevent mites from scaping the arena. Ten gravid A. swirskii females were placed on each tray to establish the colony and new arenas were set up weekly. Cotton threads were provided as shelter for A. swirskii individuals (Hoy & Cave, 1985). Predatory mites were reared for at least three generations before used in the experiments.

A newly established laboratory colony of mould mites (Tyrophagus putrescentiae

Schrank, Acari: Acaridae), maintained on a 1:6 mix of brewer’s yeast (Fisher Scientific,

Pittsburgh, PA) and wheat germ (Continental Mills, Inc., Seattle, WA) as shelter, served as a food source for the predatory mite colony. Mould mites were reared in concealed bottles stored in trays with soapy water in the bottom to avoid the scape of the mites. They were maintained in an incubator chamber at 24°C and 75 ± 3% RH. Additional mix of wheat germ, yeast, and 1-ml of water was added to the colony weekly. The mix was sieved to separate the mites from the wheat germ and an excess of T. putrescentiae individuals were brushed onto the colony arenas

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every two days as prey for A. swirskii. Tyrophagus putrescentiae were chosen to serve as prey during the experiments due to its ability to develop rapidly under laboratory conditions.

Experimental Design

The experimental design was a randomized design with incomplete blocks and three sets of replicates over time for both laboratory and greenhouse experiments. Treatment combinations were based on the insecticide evaluated and the day of predatory mite release, as follows: 1) M-

Pede® (Gowan Company, Yuma, AZ) and A. swirskii released 1-day after insecticide application; 2) M-Pede and A. swirskii released 3-days after insecticide application; 3) M-Pede and A. swirskii released 5-days after insecticide application; 4) Azera® (Valent BioSciences

LLC, Raleigh, NC) and A. swirskii released 1-day after insecticide application; 5) Azera and A. swirskii released 3-days after insecticide application; 6) Azera and A. swirskii released 5-days after insecticide application; 7) water and A. swirskii released 1-day after application; 8) water and A. swirskii released 3-days after application; and 9) water and A. swirskii released 5-days after application. The same treatments were evaluated during both laboratory and greenhouse trials.

A pre-established greenhouse colony of sweetpopato whiteflies (Bemisia tabaci Genn., B biotype, Hemiptera: Aleyrodidae) was maintained on cotton plants (22 ± 2°C, 72 ± 6% RH). A mix of whitefly immatures and broadleaf cattail pollen (Typha latifolia L., Thyphaceae)

(NutriMite™, BioBest Group, Westerlo, Belgium), was provided as food for the A. swirskii individuals tested during the laboratory and greenhouse experiments.

A set of guidelines concerned with the evaluation of the side-effects of plant protection products is available for mass-reared predatory mites such as Phytoseiulus persimilis Athias-

Henriot, Amblyseius potentillae Garman, and Typhlodromus pyri Sch. (Acari: Phytoseiidae)

(Condolfi et al., 2000; Oomen et al., 1991). However, there are no standardized guidelines in

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place for A. swirskii, reason why a modified version of the P. persimilis guidelines for laboratory and semi-field conditions, and classification scheme were followed for the experiments (Oomen et al., 1991).

Table 6-1 shows the classification scheme followed in this study to classify the insecticides as harmless or harmful to A. swirskii. Insecticides were classified as harmless or harmful based on laboratory experiments without reference from greenhouse results only when mortality rates were consistent for both 1-day residues and aged residues (3- and 5-days release) tests. Laboratory results together with greenhouse results were used for decision making on insecticide classification only when laboratory tests were inconsistent (Table 6-1). For greenhouse experiments, the maximum number of A. swirskii from all stages recorded per squash leaf in the control treatment were used as reference for comparison with numbers of A. swirskii recorded on squash treated with Azera and M-Pede. Thus, the percentage of A. swirskii suppression was calculated between numbers of A. swirskii recorded in the control versus Azera treated plants and control plants versus M-Pede treated plants.

Laboratory Experiments

A laboratory study was conducted to determine the effects of exposure to M-Pede and

Azera residues on A. swirskii. One hundred and eighty-nine A. swirskii individuals were evaluated per experiment and the experiment had three replicates over time, for a total of 567 A. swirskii individuals evaluated. Three life stages including larvae (three-legged mites), nymphs, and visibly gravid females were tested. Twenty-one individuals were used per treatment, seven larvae, seven nymphs, and seven gravid females for a total of 63 mites per stage tested on each experiment and 189 mites per stage overall replicates.

Leaf discs 1.7-cm diam. in size were made from whitefly-infested squash and placed with the abaxial side upward on water-soaked cotton (Fig. 6-1A). Groups of 5 – 6 leaf discs were

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placed inside 14-cm diam. petri dishes used as arenas. Leaf discs without predators were sprayed

(day 0) using a Potter Spray Tower (Burkard Scientific Ltd., Uxbridge, UK) following the maximum field recommended rates for squash production: 2% v/v for M-Pede and 147.4 ml/ha for Azera.

Amblyseius swirskii from the laboratory colony were used for the laboratory experiments.

Six-legged larvae (~1 – 1.5 days old), nymphs (~2 – 3 days old), and adult females (~5 – 6 days old) were handled gently with a fine sable-hair brush and transferred individually to the leaf discs. Only one mite occupied one leaf disc. Medium-size plastic trays were used to separated petri dishes from different treatments (Fig. 6-1B) and were maintained in an incubator chamber

(24°C, 75 ± 3% RH). Fig. 6-2 shows the experimental arrangement for laboratory experiments inside the incubator chamber.

Eggs and immature whiteflies were present in the leaf discs during the laboratory experiments. Additionally, a mist of cattail pollen was added to the leaf discs every two days to make sure food was always available for the predatory mites. Water was added daily to the cotton to prevent the mites from escaping the leaf discs.

The experiment was replicated over time in sets starting on 11/21/2018 (set 1),

11/28/2018 (set 2), and 12/05/2018 (set 3). Each set was carried out within 10 days. Amblyseius swirskii mortality was recorded at 24-h, 48-h, 72-h, 96-h, and 120-h after exposure to the insecticide residues (1-, 3-, or 5-days after insecticide application). Predatory mites released one day after insecticide application were checked until day six, mites released three days after application were checked until day eight, and mites released five days after application were checked until day 10. The number of dead and run off mites were recorded and obviously dead

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A. swirskii individuals were removed during counting. The criterion for survival was the ability to walk after being touched gently with a fine sable-hair brush.

Greenhouse Experiments

A greenhouse experiment was established to determine the effects of exposures to M-

Pede and Azera residues on A. swirskii released on fully grown squash infested with whiteflies.

Zucchini squash plants (‘Cash Flow’) were transplanted in 1-L plastic pots and fertilized weekly using Alaska Fish Fertilizer® (5–1–1, Pennington Seed, Inc., Madison, GA). Four-weeks old squash plants were used for the experiments.

The experiment had three replicates over time (sets) starting on 10/16/2018 (set 1),

10/31/2018 (set 2), and 11/20/2018 (set 3). Each set was carried out within 15 days. Forty-five squash plants were used per set for a total of 135 plants assessed overall replicates. Two hundred whitefly adults from the pre-established colony were released for every 45 plants two weeks before the start of each experiment to infest the squash and give the whiteflies time to lay eggs and immatures to develop.

Cages (60-cm deep × 60-cm wide × 120-cm long) were placed inside a greenhouse (20 ±

2°C, 72 ± 5% RH, Fig. 6-1C) in three benches, three cages per bench and one group of five flowering plants was placed inside each cage (Fig. 6-1D), each cage representing one treatment combination. The treatments were randomly assigned to each cage at the beginning of each set

(Fig. 6-3). Plants within cages were sprayed using 1-L spray bottles (Uline, Milton, ON, Canada) and approximately 400-ml of insecticide per cage until leaves dripped.

Amblyseius swirskii were purchased in a 500-ml bottle shaker formulation with a bran carrier at the beginning of each greenhouse experimental set. Five bran samples (0.5-ml) were checked under the dissecting microscope to count the number of A. swirskii motiles (immatures, adult males and females) prior to release (Table 6-2). The amount of bran used per plant was

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adjusted based on the mite numbers recorded. Approximately 2-ml of bran (~50 mites) were sprinkled onto each squash plant (scattered among all leaves) on the day of arrival for treatments with 1-day release time. Bottle shakers were maintained in an incubator chamber (24°C, 75 ± 3%

RH) to be used for releases in treatments with 3- and 5-days release times.

Eggs and immature whiteflies were present in squash during the greenhouse experiments.

In addition, a mist of cattail pollen was added to the leaves every two days to make sure food was always available for the predatory mites. Trays underneath the pots were filled constantly with water to prevent the mites from scaping the plants.

Destructive sampling was conducted by cutting one entire plant per treatment every two days (nine plants examined per day) for a ten-day period (2, 4, 6, 8, and 10 days) for each treatment combination. Predatory mites released 1-day after insecticide application were checked until day 10, mites released 3-days after application were checked until day 13, and mites released 5-days after application were checked until day 15. By the end of the sampling period all plants were examined. Six leaves and one flower were chosen randomly from all plant stratum to be examined under a dissecting microscope. Both adaxial and abaxial sides of the leaves were examined as well as the inner and outer sides of the flowers. Numbers of A. swirskii eggs, immatures (larvae and nymphs) and adults per leaf or flower were recorded.

Eight leaves of different sizes were randomly collected from each set and their leaf area was measured with a LI-3100C LI-COR area meter (LI-COR, Inc., Lincoln, NE). Squash leaves sampled had an average of 130.1 ± 11.2-cm2.

Statistical Analysis

In the fall 2018 experiments, repeated measures analysis was performed to identify if the treatment combinations had significant effects on A. swirskii. All response variables were analyzed by fitting either a linear mixed model (LMM) or a generalized linear mixed model

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(GLMM) that considered the repeated nature of the data. Amblyseius swirskii larva, nymph, and female mortality from laboratory experiments were analyzed by using the PROC MIXED procedure and degrees of freedom were adjusted using the Kenward-Rogers correction. Data were log-transformed (log(x+1)) prior to analysis. The LMM considered the fixed effect factors of insecticide, release day, hours after release (24-, 48-, 72-, 96-, and 120-h) and their interaction.

The repeated measurements were modeled by including a random factor of tray and using an autoregressive error structure of order 1 for each tray.

Amblyseius swirskii egg, immature, and adult numbers from greenhouse experiments, were fitted using a GLMM as implemented in the PROC GLIMMIX procedure following a negative binomial distribution to correct over-dispersion. This model considered the fixed effect factors of insecticide, release days, sampling days or days after release (2, 4, 6, 8, 10 days) and their interaction. In addition, random effects of block and block within week were considered.

The repeated measurements were considered by including a random factor of cage, corresponding to a compound symmetry structure.

Comparisons of means among treatments at each week for both GLMM and LMM, were obtained by requesting LSMEANS from each procedure. Data from each predatory mite stage was analyzed separately. All models were fitted using SAS 9.4 (SAS Institute, Cary, NC, 2013).

Results

Laboratory Experiments

Amblyseius swirskii mites were observed to run off from the leaf discs in some occasions.

Most predatory mite larvae were observed to settle easily in the leaf discs during the sampling period and A. swirskii females that were found laying eggs within 24-h (data not shown). No major differences were found between dead and run off mites (dead by drowning), thus, run off mites were considered dead and were analyzed together with counts of dead mites.

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No significant interactions were found among insecticide, release days, and hours after release (24- to 120-h) for mortality of A. swirskii females and nymphs. Overall treatment combinations, predatory mite female and nymph mortality gradually increased over time with lower mortality 24-h after exposure and higher mortality 120-h after exposure in the leaf discs

(Fig. 6-4A, B). Azera showed highest initial mortality (~60%) within 48-h after exposure for both A. swirskii adults and nymphs released 1-day after insecticide application. Variable mortality rates were recorded for both females and nymphs of the predatory mite released 3- and

5-days after Azera application, respectively, with rates as low as 20% mortality 24-h after exposure and as high as 70% mortality at 120-h (Fig. 6-4A, B). No differences were recorded for mortality of A. swirskii females and nymphs exposed to M-Pede residues and the control (water).

There was a significant three-way factor interaction among insecticide, release days, and hours after release (24- to 120-h) for A. swirskii larvae (F16,70 = 3.04, P = 0.0006). Predatory mite larvae exposed to Azera residues showed significantly highest initial (within 48-h) and overall

(24- to 120-h) mortality when released 1-day after treatment, ranging from 58 to 86% mortality compared to mite larvae released 1-day after water application in the control with an average mortality of 20% (Fig 6-4C). High mortality (~45%) was also recorded within 72-h of exposure to Azera when larvae was released 3- and 5-days after insecticide application followed by an increase in mortality 120-h after application. Lowest mortality (~22%) for larvae exposed to

Azera was recorded 24-h after exposure when A. swirskii was released 5-days after treatment.

Larvae of A. swirskii exposed to M-Pede residues showed low mortality (< 15%) within

48-h of exposure when larvae were released 1- and 3-days after insecticide application, followed by an increase to moderate mortality (22 – 30%) after 72-h of exposure (Fig 6-4C). Low initial mortality (<22%) was recorded within 48-h for A. swirskii larvae released 5-days after M-Pede

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application, but a gradual and significant increase in mortality was observed after 72-h (Fig 6-

4C).

The same tendencies were observed for A. swirskii female, nymph, and larva mortality overall hours after release. No significant insecticide-by-release day interactions were found for females and nymphs of the predatory mite. The highest numerical mortality (58%) was recorded when females were released 1-day after Azera application, followed by females released 3- and

5-days after treatment with 36% female mortality. Amblyseius swirskii females exposed to water and M-Pede residues in all release days (1-, 3-, and 5-days) showed less than 30% mortality (Fig.

6-5). Likewise, high numerical mortality was recorded for A. swirskii nymphs exposed to Azera in all release days compared to nymphs exposed to water or M-Pede residues. Approximately 57 to 46% of A. swirskii nymphs exposed to Azera residues died when released 1- to 5-days after treatment. Contrary, up to 28% of nymphs were killed by M-Pede or water treatment (Fig. 6-5).

There was a significant insecticide-by-release day interaction for A. swirskii larvae (F4,18

= 4.12, P = 0.01). Azera residues killed up to 73% of the tested larvae when released 1-day after treatment with similar high mortality when released 3- (54%) and 5-days (43%) after treatment.

This is an indication that Azera had adverse effects on predatory mite larvae compared to other stages. Approximately 14% of A. swirskii larvae was killed after exposure to M-Pede residues when released 1-day after treatment with the insecticide. Seven percent and 28% of A. swirskii larvae mortality was observed when mites were released 3- and 5-days after treatment with M-

Pede. This could be related to the rapid degradation of leaf discs and fungus proliferation making leaf discs inhospitable.

Significant differences between insecticides were identified for A. swirskii nymph (F2,17 =

6.60, P = 0.007) and larva mortality (F2, 18 = 42.65, P < 0.0001) overall release days and overall

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hours after exposure. Approximately 50% of the tested A. swirskii nymphs were killed by residual exposure to Azera compared to the M-Pede and the control with less than 22% of nymph mortality (Fig. 6-6A). For A. swirskii larvae, more than 50% of the larvae were killed by exposure to Azera followed by M-Pede residues with 15% larval mortality and less than 10% mortality recorded in the control (Fig. 6-6A).

No significant differences were found among release days (1-, 3-, and 5-days) for all A. swirskii stages overall insecticides tested and overall hours after release. However, approximately 20% of the A. swirskii nymphs and larvae was killed when released 1-day after insecticide application compared to 29% when the immature mite stages were released 5-days after insecticide application (Fig. 6-6B).

Furthermore, significant release day-by-hours after release interactions were found for A. swirskii female (F8,71 = 2.18, P = 0.03) and larva mortality (F8,71 = 4.21, P= 0.0003) overall insecticides. The highest A. swirskii female mortality rates were recorded for all release days 96- and 120-h after exposure whereas moderate mortality (30 to 35%) was recorded 72-h after exposure when females were released 1- and 3-days after insecticide application. The lowest mortality was recorded 24-h after exposure when predatory mite females were released 3- and 5- days after insecticide application with up to 15% female mortality (Fig. 6-7A). A similar trend was observed for A. swirskii larvae. Highest larval mortality was recorded 72-, 96-, and 120-h after insecticide exposure when predatory mite larvae was released 5-days after insecticide application with up to 57% mortality whereas moderate larval mortality (< 35%) was recorded at the same sampling time when A. swirskii larvae were released 1- and 3-days after insecticide application. Lowest A. swirskii larva mortality was recorded 24-h after insecticide exposure when larvae were released 3- and 5-days after insecticide application with approximately 8%

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mortality, followed by larvae in the same treatments 48-h after exposure with less than 15% mortality (Fig. 6-7C). No significant release day-by-hours after release interaction was found for

A. swirskii nymphs (Fig. 6-7B).

Based on the mortality rates recorded during the laboratory experiments (Table 6-3),

Azera residues were harmful for all A. swirskii stages especially to larvae whereas M-Pede residues were harmless to all stages of the predatory mite. Mortality rates among A. swirskii stages and tests were consistent.

Greenhouse Experiments

Amblyseius swirskii established on the squash in both adaxial and abaxial sides of the leaves and predatory mite numbers increased in the crontol over the ten-day sampling period.

Leaves from the medium and lower strata seemed to be preferred by A. swirskii compare to newly opened leaves and hardly any A. swirskii mites or eggs were recorded in the squash flowers.

No significant insecticide-by-release day interaction was found for numbers of A. swirskii females, nymphs, and larvae recorded in the squash leaves overall sampling days. The highest number of predatory mite nymphs were recorded in the squash from the control treatment when mites were released 3-days after treatment followed by the squash treated with Azera when A. swirskii was released 5-days after insecticide application. The highest number of nymphs in squash treated with M-Pede were recorded when mites were released 3-days after insecticide application (Fig. 6-8). The highest numbers of A. swirskii larvae were recorded in the squash from the control treatment 1- and 3-days after release followed by squash treated with M-Pede when the predatory mites were released 1-day after insecticide application. The lowest numbers of predatory mite larvae were found in squash treated with Azera when mites were released 3- and 5-days after insecticide application (Fig. 6-8).

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Overall release days and sampling days, there were no significant differences between insecticides for numbers of A. swirskii adults, immatures, and eggs recorded in the treated squash. Nonetheless, all stages of the predatory mites were numerically higher in the squash from the control treatment. Also, numbers of A. swirskii immatures and eggs were approximately

30% and 25% higher in squash from the control compared to the squash treated with Azera or

M-Pede (Fig. 6-9A).

Likewise, there were no significant differences among release days (1-, 3-, and 5-days) for numbers of A. swirskii adults, immatures, and eggs recorded in the squash overall sampling days and insecticides. High numbers of predatory mites from all stages were found in the squash when the release day was 1-day after insecticide application; moreover, the highest number of A. swirskii immatures were recorded in the squash when the mites were released 3-days after insecticide application. Lowest numbers of A. swirskii adults and larvae were recorded when mites were released 3- and 5-days after insecticide treatment (Fig. 6-9B).

Despite the lack of significant differences among release days, there were significant release day-by-sampling day interactions for all stages of A. swirskii (adults: F8,72 = 3.76, P =

0.0009; immatures: F8,72 = 4.98, P < 0.0001; eggs: F8,72 = 2.91, P = 0.007). Highest numbers of

A. swirskii adults were recorded four days after release in the squash were mites were released 3- days after insecticide application with approximately 40% more mites compared to other release days. Eight days after exposure, numbers of A. swirskii adults also peaked when mites were released 1-day after insecticide application with 50% more adults compared to other release days

(Fig. 6-10A).

Numbers of A. swirskii immatures and eggs followed the same increase patterns as the adult predatory mites. Immatures were also higher when mites were released 3-days after

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insecticide treatment only up to six days after exposure. Starting eight days after mite exposure to insecticides, numbers of A. swirskii immatures were highest on the squash where predatory mites were released 1-day after insecticide application probably due to emergence of recently laid eggs. Lowest numbers of A. swirskii immatures were recorded two days after exposure in all release days (Fig. 6-10B).

Highest numbers of A. swirskii larvae was recorded four and eight days after exposure in the squash from treatments with 1- and 3-days as release days. This is consistent with the treatments where high numbers of adult predatory mites were recorded, including gravid females. Moderate numbers of A. swirskii eggs were recorded six and ten days after exposure regardless of the release day, and lowest numbers of predatory mite eggs were recorded in the squash two days after exposure when A. swirskii was released 5-days after insecticide application

(Fig. 6-10C).

Discussion

Organic growers are limited in the pest management tools they can implement since most pest management practices are developed for conventional growers and are often not permitted in organic production. Because of these limitations, organic squash growers commonly use

Entrust (spinosad) for whitefly suppression despite not being label for B. tabaci and not being effective against them (Razze et al., 2016). Both Azera and M-Pede bioinsecticides have been reported to be effective suppressing B. tabaci populations and other major key pests in squash like aphids and thrips (Razze et al., 2016). Similarly, suppression of B. tabaci by predatory mites such as A. swirskii has been reported in multiple vegetable cropping systems (e.g., Calvo et al.,

2015, 2011; Abou-Awad et al., 2014; Kumar et al., 2015; Onzo et al., 2012; Van Maanen et al.,

2010). Biological control is desired in organic squash production, but the use of biological control agents as a unique tool for pest management may not provide adequate pest suppression

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(Hoy, 2011). Yet, evaluations of organic insecticide compatibility with the predatory mite A. swirskii are lacking.

This is the first study reporting the residual effects of Azera and M-Pede on A. swirskii.

Exposure to M-Pede residues had minimal detrimental effects on all stages of the predatory mites regardless of the time of release (1-, 3- or 5-days after treatment). These findings were consistent across laboratory and greenhouse experiments since mortality rates and numbers of predatory mites established in full grown plants treated with M-Pede were comparable with the control treatment. Similar findings were reported by Stanyard et al. (1998) who evaluated the toxicity of

M-Pede on the predatory mite Amblyseius fallacis Garman (Acari: Phytoseiidae). The phytoseiid mite is used in apple trees for the control of the European red mite (Panonychus ulmi Koch,

Acari: Tetranychidae) and direct applications of M-Pede showed little if any detrimental effects to the predatory mite. However, when the frequency of M-Pede applications increased (more than two applications) due to red mite outbreaks, A. fallacis populations were severely affected

(Stanyard et al., 1998).

In the present study, low rates of A. swirskii mortality and establishment of predatory mite populations in M-Pede treated squash may be related to the low persistence of its active ingredient (AI). Potassium salts of fatty acids, also known as pesticidal soaps, is not very persistent in the environment and have a soil half-life of one day. Pesticidal soaps disrupt the cuticle and break down cell membranes resulting in rapid dead of insect and mites (Yu, 2008) and may cause substantial reductions in predatory mite numbers when exposed to fresh residues or direct spray. Residues of M-Pede had no such effect on A. swirskii populations; however, further studies to evaluate the effect of direct exposure of M-Pede to A. swirskii are needed in case of secondary pest outbreaks after predatory mite release.

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Unexpected high mortality rates were recorded when A. swirskii was released into the leaf discs 5-days after insecticide treatment. The hypothesis for these rates of mortality is that leaf disc degradation may have cause rapid dead and mite to run off. Despite maintaining the leaf discs constantly watered to avoid desiccation, temperature and relative (RH) was high during the laboratory studies. This was because optimal conditions for A. swirskii development include temperatures around 24°C and RH above 70% (Lee & Gillespie, 2011). Environmental conditions were perfect for fungus proliferation and rapid degradation of squash leaf discs was observed for treatments where predators were released with 5-days after treatment. Insecticide application may have exacerbated leaf degradation since discs treated insecticides were observed to degrade at a faster rate compared to discs sprayed with distilled water. Fungus presence in the leaf discs may have made the discs unsuitable for A. swirskii survival.

Residues of Azera had detrimental effects on all stages of A. swirskii. Amblyseius swirskii larvae was more negatively affected than females and nymphs with mortality rates from 49 to

73% in laboratory experiments. The pyrethrin component present in the AI of Azera targets the nervous system of insects and mites; it is very fast acting and cause immediate paralysis. The second component of Azera, azadirachtin has molting disruption properties. It inhibits the release of various hormones related to molting such as ecdysone thereby disrupting molting processes

(Yu, 2008). Nerve inhibition together with molting disruption activity may be related to Azera’s detrimental effect on A. swirskii larval stage. Additionally, larval stage is more susceptible to insecticide toxicity due to lower body sclerotization (Capinera, 2008). Lower numbers in A. swirskii immatures were also found in squash plants in the greenhouse studies but not at the same extend.

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As expected, substantially highest mortality for all A. swirskii stages was observed when mites were released 1- and 3-days after treatment, but this was only observed when leaf discs were treated with Azera. Females and nymphs of the predatory mite released 1-day after treatment showed numerically higher mortality rates when exposed to residues of Azera compared to the control. Amblyseius swirskii larvae mortality were significantly higher when released into leaf discs 1-day after treatment with Azera compared to the control and M-Pede treated leaf discs. This was observed when all factors evaluated (insecticide and release days) were considered.

In the present study, A. swirskii was able to establish in the squash plants under greenhouse conditions regardless of the release time, but unclear increase patterns were observed. This may be the product of the rapid life cycle of the predatory mite during the laboratory and greenhouse experiments. Once eggs are laid, it took 1 – 1.5-days for A. swirskii larvae to emerge. Larvae can molt into protonymphs approximately 24-h after emergence. The time that takes protonymphs develop into deutonymphs can vary depending on food quality and availability (Soleymani et al., 2011). Protonymphs and deutonymphs were not identify separately during this study. Males develop faster into adults than females, but generally females molt into adults four to five days after larva emergence and disperse in search for mate and food (Hoy,

2011; Park et al., 2011). In this study, obviously gravid females (fully-developed egg observed inside the mite) were recorded five to six days after oviposition.

Based on this rapid life cycle, peaks of A. swirskii adults and eggs four days after release in the greenhouse may be due to the development of the pool of eggs and immatures introduced onto the squash plants. Immature increases were observed six days after release, which is consistent with the previous peak in adults and reproductive females. A second peak of A.

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swirskii adults and eggs was then observed eight days after release probably as a result of the development into adults of all the immatures recorded on day six. This hypothesis assumes that most of the predatory mites released on the plants survived. An estimate of A. swirskii numbers was made based on the bran samples examined on the day of bottle shaker arrival. However, the real number of predatory mite adults, immatures, and eggs released onto each squash plant was unknown. Additionally, the environmental chamber in the laboratory and the greenhouse maintained similar environmental conditions throughout the experiments (24°C, 75 ± 3% RH and 20 ± 2°C, 72 ± 5% RH, respectively) and the same food source was offered to the predatory mites in both experiments; thus, similar developmental times could be expected during the experiments.

No significant differences in the numbers of A. swirskii established in the squash plants were found when mites were released 1-, 3-, and 5-days after treatment in greenhouse experiments. These results were unexpected. By delaying the time of release for biological control agents like A. swirskii probability for survival is increased as well as chances of success in suppressing the target pest. Castagnoli et al. (2002) showed the effects of botanicals insecticides in the predatory mite Amblyseius andersoni Chant (Acari: Phytoseiidae), an important pest mite predator in apple orchards and vineyards in Italy. Authors reported that higher numbers of A. andersoni survived when they were not directly sprayed or exposed to fresh residues of pyrethrins and azadirachtin. Higher numbers of the predatory mite were observed when exposed to aged residues in fully-grown plants under semi-field conditions and were able to reproduce over time. Similarly, the whitefly predatory lady beetle (Delphastus catalinae Horn, Coleoptera: Coccinellidae) was reported to be more susceptible to residues of

Pyganic (pyrethrins) and M-Pede in squash under laboratory and greenhouse conditions when

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released 1- and 3-days after treatment compared to beetles released 5-days after insecticide application (Razze et al., 2016). The present laboratory studies showed that A. swirskii should not be released 1- or 3-days after treatment with Azera to avoid predatory mite mortality. Further studies are needed to determine the appropriate release time for A. swirskii after M-Pede or

Azera applications under semi-filed and field conditions.

Based on the insecticide classification scheme, Azera should be considered a harmful compound to A. swirskii especially to larvae stages. If it is strictly necessary to use Azera before

A. swirskii releases, predatory mites should not be released 1- nor 3-days after treatment with the insecticide to avoid predatory mite mortality as precaution.

Increased predatory mite dispersal could be a side-effect of Azera since it has been reported that predatory mites exposed to residues of pyrethrins (one of the components in the AI of Azera) tend to escape the treated leaves to avoid the chemical compound (Castagnoli et al.,

2002). This repellent effect could be related to A. swirskii run off behavior observed in Azera treated leaf discs. Nevertheless, the effects of pyrethrins alone may not be the same as its combination with azadirachtin. The latter has also been reported as a feeding deterrent and can cause behavioral changes in predators (Razze et al., 2016).

Based on the insecticide classification scheme, M-Pede can be considered harmless to all stages of A. swirskii. No detrimental effects were recorded even when A. swirskii was released 1- day after treatment with M-Pede. However, as precautionary measure, predatory mites should be released with a wider window of time to avoid detrimental effects, thus, A. swirskii should be released at least 3-days after treatment with M-Pede. Classifications in this study are based solely on the laboratory experiments because no significant patterns were observed between

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insecticides under greenhouse conditions. Further studies are needed to clarify the effect of both bioinsecticides under field conditions.

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Table 6-1. Decision making scheme used as reference to evaluate the effects of Azera and M-Pede on Amblyseius swirskii females, nymphs, and larvae during laboratory and greenhouse experiments. Criteria to evaluate results are given as percentage of mortality. Scheme adapted from Oomen et al. 1991. Experiment Toxicity test Mortality Mortality Mortality Mortality Mortality Laboratory 1-day residues <30% >30% - < 98% >30% - < 98% >30% - < 98% >99% Aged residues (3- and 5-days release) <30% <30% >30% - < 98% <30% >99% Greenhouse 1-day residues NA <30% NA >30% - < 98% >99% Aged residues (3- and 5-days release) NA <30% NA >30% - < 98% >99% Classification Harmless Harmless Harmful Harmful Harmful NA = not applicable because laboratory mortality rates are consistent

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Table 6-2. Number of Amblyseius swirskii motiles (immatures, adult males and females) counted prior to release into the greenhouse. Each sample consisted of 0.5-ml of bran examined under a disecting miroscope on the day of arrival for the shaker bottles. Date of arrival Sample No. of A. swirskii motiles in No. of A. swirskii motiles in 0.5-ml 2-ml 10/26/2018 1 8 55 2 9 39 3 6 58 4 8 49 5 7 47 Average 7.6 49.6 11/1/2018 1 13 52 2 17 68 3 22 88 4 7 28 5 19 76 Average 15.6 62.4 11/21/2018 1 25 100 2 14 56 3 9 36 4 11 44 5 12 48 Average 14.2 56.8 Overall average 56.3

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Table 6-3. Pesticide classification for Amblyseius swirskii females and immature stages (nymphs and larvae) using the adapted evaluation scheme for laboratory and greenhouse experiments. Percentage of suppression are based on the numbers of predatory mites per leaf recorded on the control plants versus the predatory mites recorded per leaf on insecticide treated squash. Azera M-Pede Water % Mortality % Mortality % Mortality Experiment Toxicity test Females Nymphs Larvae Females Nymphs Larvae Females Nymphs Larvae Laboratory 1-day residues) 58% 57% 73% 26% 13% 14% 20% 8% 3%

Aged residues 29% 45% 49% 28% 18% 18% 24% 25% 12% (3- and 5-days release) % Suppression % Suppression Adults Immatures Adults Immatures Greenhouse 1-day residues 14% 34% NA 0% 42% NA

Aged residues 50% 25% NA 42% 42% NA (3- and 5-days release) Classification Harmful Harmful Harmful Harmless Harmless Harmless NA = not applicable because larvae were recorded together with nymphs as immatures during greenhouse experiments

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Figure 6-1. Treatment set-up for 2018 evaluations of insecticide residual effects on A. swirskii. A) petri dishes with leaf discs drying after insecticide application during laboratory experiments, B) petri dishes separated by treatment, C) cage arrangement during greenhouse experiments, and D) squash plants inside the cages. Photo courtesy of author.

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Figure 6-2. Experimental arrangement for the laboratory experiment conducted in fall 2018. Treatments were defined based on the combination between insecticide and Amblyseius swirskii release time. The experiment was replicated over time (sets) starting on 11/21/2018 (set 1), 11/28/2018 (set 2), and 12/05/2018 (set 3). Dotted black lines represent benches inside the incubator and continuous colored lines represent each tray with an assigned treatment.

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Figure 6-3. Experimental arrangement for the greenhouse experiment conducted in fall 2018. Treatments were defined based on the combination between insecticide and Amblyseius swirskii release time. The experiment was replicated over time (sets) starting on 10/16/2018 (set 1), 10/31/2018 (set 2), and 11/20/2018 (set 3). Dotted black lines represent benches inside the greenhouse and continuous colored lines represent each cage with an assigned treatment.

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Figure 6-4. Mean (±SE) mortality of Amblyseius swirskii A) females, B) nymphs, and C) larvae for the three-way interaction among insecticides (Azera, M-Pede, and water as control), release days (1-, 3-, 5-days after treatment), and hours after release (24-, 48-, 72-, 96-, and 120-h) during laboratory experiments. Bars with the same letter across all treatments are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns= not significant.

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Figure 6-5. Mean (±SE) mortality of Amblyseius swirskii females, nymphs, and larvae across insecticides and release days during laboratory experiments. Bars with the same letter across treatments are not significantly different (P ≤ 0.05). Back-transformed data are shown.

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Figure 6-6. Mean (±SE) mortality of Amblyseius swirskii females, nymphs, and larvae between A) insecticides and B) release days during laboratory experiments. Bars with the same letter across insecticides are not significantly different (P ≤ 0.05). Back- transformed data are shown. ns = not significant.

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Figure 6-7. Mean (±SE) mortality of Amblyseius swirskii A) females, B) nymphs, and C) larvae over time at each release day during laboratory experiments. Means were pooled together overall insecticides. Bars with the same letter across hours after release are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns = not significant.

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Figure 6-8. Mean (±SE) number of Amblyseius swirskii adults, immatures (larvae and nymphs), and eggs among insecticides and release days during the greenhouse experiments. Back-transformed data are shown. ns = not significant.

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Figure 6-9. Mean (±SE) numbers of Amblyseius swirskii adults, immatures (larvae and nymphs), and eggs between A) insecticides and B) release days during greenhouse experiments. Back-transformed data are shown. ns = not significant.

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Figure 6-10. Mean (±SE) mortality of Amblyseius swirskii A) adults, B) immatures (larvae and nymphs), and C) eggs over time at each release day during greenhouse experiments. Means were pooled together overall insecticides. Bars with the same letter within days are not significantly different (P ≤ 0.05). Back-transformed data are shown. ns = not significant.

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CHAPTER 7 CONCLUSION

This study represents the second successful attempt to establish A. swirskii populations on zucchini squash. Establishment of A. swirskii populations in crop plants have been achieved in other cucurbits such as cucumbers for control of thrips (Kakkar et al., 2016), but only once has been reported the establishment of reproductive populations of the predatory mite in zucchini squash crops in Spain for control of B. tabaci and spread of tomato leaf curl New Delhi virus

(Tellez et al, 2017). Amblyseiues swirskii is known to prefer plant hosts with glabrous leaves or leaves that may offer specialized shelters like domatia on pepper plants (Xiao et el., 2012). The presence of trichomes is preferred by most phytoseiid mites (Hoy, 2011); however, high density of glandular trichomes like the ones found on newly unfolded squash leaves are avoided by most phytoseiids such as A. swirskii. This was confirmed during greenhouse experiments when hardly any A. swirskii mites settled on young squash leaves.

Refugia increased natural enemies around the squash; however, there was a lack of movement of the natural enemy populations towards the squash crop when companion plants were used alone. Marigolds used as companion plants seemed to play a role as trap crop since it was attractive to high numbers of thrips and no spill-over effect of the pest was observed in the neighboring squash. High numbers of Orius spp. were also attracted to the marigolds due to the presence of the thrips. Additionally, when marigolds were used as companion plant together with

A. swirskii released in the squash, suppression of whiteflies populations in the squash was observed. Sweet alyssum used as companion plant together with A. swirskii released in squash also showed suppressive effects on whitefly populations present in the squash crop. Suppressive effects when using both marigolds and sweet alyssum together with predatory mites were comparable to the use of A. swirskii alone with the additional advantage of predators and

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parasitoids attracted to the companion plants with potential to suppress other squash pests like aphids and thrips.

Suppression of whitefly populations was reflected in lower Squash silverleaf (SSL) ratings and higher total marketable yield in selected plots in 2017. However, high incidence of the whitefly-transmitted cucurbit leaf crumple virus (CuLCrV) during the fall season appeared to have a significant effect on squash yield overall treatments causing approximately 50% lower yields compared to the spring season during both 2015 and 2017.

The applications of Entrust seemed to have no effect on the sweetpopato whitefly or cowpea aphid populations attacking the squash. The numbers of parasitoids and predatory species appeared not to be affected by the Entrust applications. Similarly, M-Pede seem to have little if any detrimental effect on most predatory species and parasitoids. This confirms the status of low-risk chemicals for both Entrust and M-Pede and their compatibility with integrated pest management programs as a safe technique to be used together with introduction or conservation of natural enemies in organic squash cropping systems. Nonetheless, Entrust should not be used for control of whiteflies nor aphids. M-Pede can be used as an effective alternative for suppression of these key pests.

Cowpeas used as refugia increased natural enemies around the squash crop; however, they were highly attractive to cowpea aphids that were observed to move towards neighboring squash. Higher numbers of aphids were recorded in the squash planted next to the cowpeas in

2015 and a slightly higher incidence of the aphid-transmitted virus papaya ringspot virus (PRSV) was recorded. Therefore, cowpeas are not recommended as companion plant or trap crop within squash cropping systems.

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Spatial-temporal distribution patterns were determined for whiteflies and A. swirskii populations during the squash fall season in 2018. However, semivariogram model accuracy was poor for analysis including data from the start and the end of the season. This may be related to the extremely high counts in a few sample points and multiple zero counts in many other sampling points. This type of data can create inaccurate estimations and obscure variables’ spatial structure. Moreover, the closeness of some sampling points (0.6 – 2-m) may have limited model accuracy. Strong to moderate spatial structure was obtained when ranges between 2 and 9- m were used in semivariogram modeling.

Amblyseius swirskii successfully suppressed whitefly populations during the 2018 fall season. Inoculated predatory mites in the treatment plot seemed to influence whitefly distribution patterns in the entire field including the control plot. The presence of alyssum had no apparent effect on the densities of whiteflies in the neighboring squash plants. Sweet alyssum did not serve as a plant host for A. swirskii during the 2018 experiments since no predatory mites were found in the plants. However, high numbers of Orius spp. were observed inhabiting and reproducing on the sweet alyssum flowers during 2017 and 2018 experiments.

Lower densities of aphids were recorded in the treatment plot where the alyssum was planted compared to the control plot including squash monoculture during the 2018 experiments.

This reduction in aphid numbers could be related to the presence of sweet alyssum that is attractive to parasitoids and predators (i.e., braconid wasps, syrphid and dolichopodid flies, among others) that feed on aphid species. Nevertheless, further monitoring efforts to identify naturally occurring beneficial insects in the alyssum with potential to suppress aphids are needed.

This is the first study evaluating residual toxicity of Azera and M-Pede on A. swirskii.

According with our findings, not all bioinsecticides tested could be safely integrated with A.

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swirskii releases unless modifications on release schedule are enforced. Releases of A. swirskii 1- day after treatment with Azera should be avoided. Residues of this botanical insecticide showed detrimental effects on A. swirskii larval stages and it could cause substantial reductions to the overall number of A. swirskii adults for the next generation. M-Pede on the other hand, was harmless to all stages of the predatory mites under laboratory conditions. Amblyseius swirskii could be release in the squash after M-Pede applications. However, predatory mite releases should be schedule with precaution because the appropriate time frame for A. swirskii releases

(1-, 3- or 5-days after treatment) was not identified under greenhouse conditions.

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APPENDIX DATA DISTRIBUTION CRITERIA FOR PEST AND BENEFICIAL ARTHROPODS

Table A-1. Summary of distributions (Poisson or Negative binomial) and random effects used in the PROC GLIMMIX procedure for each variable per season (spring 2015, fall 2015, spring 2017, and fall 2017) and sampling technique during the 2015 and 2017 experiments. The criteria for choosing the model distribution was based on the Pearson Chi-Square/DF value as follows: Pearson Chi-Square/DF ≤ 1 = Poisson distribution, Pearson Chi-Square/DF > 1 = Negative binomial distribution. Random effects were tested for each variable before analysis including None, BLOCK, BLOCK*TRT, WEEK*BLOCK. Random effects included for final analysis were chosen based on the covariance parameter estimates (estimates = 0 then random effect not included, estimates > 0 then random effect included). Variables used for analysis include apterae aphids (APH_Ap), winged aphids (APH_Ala), sweetpotato whiteflies (WF), thrips (THR), Florida flower thrips (Frankliniella bispinosa, Fb), predatory mites Amblyseius swirskii (SW), Orius spp. (ORI), coccinellids (COC), dolichopodids (DOL), pooled number of parasitoid wasps (HYM), and spiders (SPI). Season Sampling Variable Pearson Chi- Distribution Random effects technique Square/DF Spring Leaf discs APH_Ap 0.538 Poisson BLOCK 2015 Spring Leaf discs ORI 0.500 Poisson BLOCK*TRT 2015 Spring Leaf discs THR 0.973 Poisson BLOCK BLOCK*TRT 2015 Spring Leaf discs WF 2.265 Negative binomial BLOCK*TRT 2015 Spring In situ APH_Ala 3.882 Negative binomial BLOCK*TRT WEEK*BLOCK 2015 counts Spring In situ COC 0.456 Poisson BLOCK*TRT 2015 counts Spring In situ HYM 0.229 Poisson BLOCK*TRT WEEK*BLOCK 2015 counts Spring In situ ORI 1.618 Negative binomial BLOCK*TRT WEEK*BLOCK 2015 counts Spring In situ SPI 0.313 Poisson BLOCK BLOCK*TRT 2015 counts WEEK*BLOCK Spring Pan traps APH_Ala 6.394 Negative binomial None 2015 Spring Pan traps COC 0.763 Poisson BLOCK*TRT WEEK*BLOCK 2015 Spring Pan traps DOL 1.261 Negative binomial BLOCK BLOCK*TRT 2015 WEEK*BLOCK Spring Pan traps ORI 1.125 Negative binomial BLOCK*TRT 2015 Spring Pan traps SPI 0.918 Poisson BLOCK WEEK*BLOCK 2015 Spring Pan traps THR 43.792 Negative binomial BLOCK*TRT 2015 Spring Sticky APH_Ala 15.782 Negative binomial WEEK*BLOCK 2015 traps Spring Sticky COC 4.573 Negative binomial BLOCK 2015 traps

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Table A-1. Continued Season Sampling Variable Pearson Chi- Distribution Random effects technique Square/DF Spring Sticky DOL 10.138 Negative binomial BLOCK WEEK*BLOCK 2015 traps Spring Sticky HYM 8.488 Negative binomial WEEK*BLOCK 2015 traps Spring Sticky ORI 4.119 Negative binomial BLOCK 2015 traps Spring Sticky SPI 1.704 Negative binomial None 2015 traps Spring Sticky THR 154.081 Negative binomial BLOCK BLOCK*TRT 2015 traps WEEK*BLOCK Spring Sticky WF 1.180 Negative binomial None 2015 traps Fall Leaf discs APH_Ala 1.104 Negative binomial WEEK*BLOCK 2015 Fall Leaf discs APH_Ap 0.969 Poisson BLOCK*TRT WEEK*BLOCK 2015 Fall Leaf discs ORI 0.276 Poisson WEEK*BLOCK 2015 Fall Leaf discs SW 0.613 Poisson BLOCK BLOCK*TRT 2015 Fall Leaf discs THR 0.177 Poisson None 2015 Fall Leaf discs WF 32.253 Negative binomial BLOCK BLOCK*TRT 2015 WEEK*BLOCK Fall In situ APH_Ala 3.266 Negative binomial BLOCK 2015 counts Fall In situ APH_Ap 3.757 Negative binomial WEEK*BLOCK 2015 counts Fall In situ HYM 0.592 Poisson BLOCK*TRT WEEK*BLOCK 2015 counts Fall In situ SPI 0.367 Poisson BLOCK 2015 counts Fall In situ WF 7.751 Negative binomial WEEK*BLOCK 2015 counts Fall Pan traps APH_Ala 1.012 Negative binomial WEEK*BLOCK 2015 Fall Pan traps DOL 3.414 Negative binomial BLOCK*TRT WEEK*BLOCK 2015 Fall Pan traps HYM 1.427 Negative binomial BLOCK*TRT WEEK*BLOCK 2015 Fall Pan traps ORI 0.233 Poisson BLOCK 2015 Fall Pan traps SPI 0.764 Poisson WEEK*BLOCK 2015 Fall Pan traps THR 0.979 Poisson BLOCK*TRT WEEK*BLOCK 2015 Fall Sticky APH_Ala 27.765 Negative binomial None 2015 traps Fall Sticky COC 2.173 Negative binomial None 2015 traps Fall Sticky DOL 4.144 Negative binomial BLOCK BLOCK*TRT 2015 traps

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Table A-1. Continued Season Sampling Variable Pearson Chi- Distribution Random effects technique Square/DF Fall Sticky HYM 11.785 Negative binomial BLOCK WEEK*BLOCK 2015 traps Fall Sticky ORI 1.427 Negative binomial None 2015 traps Fall Sticky SPI 1.507 Negative binomial None 2015 traps Fall Sticky THR 42.057 Negative binomial BLOCK*TRT WEEK*BLOCK 2015 traps Fall Sticky WF 56.258 Negative binomial BLOCK BLOCK*TRT 2015 traps WEEK*BLOCK Spring Leaf discs APH_Ala 0.471 Poisson BLOCK*TRT 2017 Spring Leaf discs APH_Ap 2.021 Negative binomial None 2017 Spring Leaf discs ORI 0.321 Poisson None 2017 Spring Leaf discs SPI 0.264 Poisson None 2017 Spring Leaf discs SW 0.324 Poisson BLOCK 2017 Spring Leaf discs THR 0.381 Poisson None 2017 Spring Leaf discs WF 5.634 Negative binomial BLOCK BLOCK*TRT 2017 WEEK*BLOCK Spring In situ APH_Ala 0.113 Poisson None 2017 counts Spring In situ APH_Ala 0.802 Poisson BLOCK*TRT WEEK*BLOCK 2017 counts Spring In situ HYM 0.340 Poisson BLOCK*TRT WEEK*BLOCK 2017 counts Spring In situ ORI 1.461 Negative binomial BLOCK*TRT WEEK*BLOCK 2017 counts Spring In situ SPI 0.428 Poisson WEEK*BLOCK 2017 counts Spring In situ WF 1.946 Negative binomial BLOCK*TRT WEEK*BLOCK 2017 counts Spring Pan traps APH_Ala 1.074 Negative binomial None 2017 Spring Pan traps APH_Ap 0.386 Poisson BLOCK BLOCK*TRT 2017 WEEK*BLOCK Spring Pan traps COC 0.388 Poisson BLOCK 2017 Spring Pan traps DOL 1.671 Negative binomial BLOCK 2017 Spring Pan traps Fb 7.862 Negative binomial None 2017 Spring Pan traps ORI 0.647 Poisson BLOCK*TRT 2017 Spring Pan traps SPI 0.564 Poisson None 2017 Spring Pan traps WF 2.587 Negative binomial BLOCK BLOCK*TRT 2017 WEEK*BLOCK

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Table A-1. Continued Season Sampling Variable Pearson Chi- Distribution Random effects technique Square/DF Spring Sticky APH_Ala 3.399 Negative binomial None 2017 traps Spring Sticky APH_Ap 2.057 Negative binomial None 2017 traps Spring Sticky COC 2.550 Negative binomial BLOCK 2017 traps Spring Sticky DOL 6.439 Negative binomial WEEK*BLOCK 2017 traps Spring Sticky HYM 4.106 Negative binomial BLOCK 2017 traps Spring Sticky SPI 1.571 Negative binomial BLOCK 2017 traps Spring Sticky THR 27.465 Negative binomial BLOCK BLOCK*TRT 2017 traps Spring Sticky WF 18.252 Negative binomial BLOCK BLOCK*TRT 2017 traps WEEK*BLOCK Fall Leaf discs APH_Ala 0.589 Poisson BLOCK*TRT 2017 Fall Leaf discs APH_Ap 1.039 Negative binomial BLOCK*TRT WEEK*BLOCK 2017 Fall Leaf discs HYM 0.200 Poisson None 2017 Fall Leaf discs SW 0.229 Poisson WEEK*BLOCK 2017 Fall Leaf discs THR 0.086 Poisson BLOCK 2017 Fall Leaf discs WF 2.568 Negative binomial BLOCK WEEK*BLOCK 2017 Fall In situ APH_Ap 2.928 Poisson BLOCK*TRT WEEK*BLOCK 2017 counts Fall In situ SPI 0.312 Poisson WEEK*BLOCK 2017 counts Fall In situ THR 0.649 Poisson BLOCK*TRT 2017 counts Fall Pan traps APH_Ala 0.281 Poisson BLOCK*TRT 2017 Fall Pan traps APH_Ap 1.133 Negative binomial BLOCK*TRT 2017 Fall Pan traps COC 0.810 Poisson None 2017 Fall Pan traps DOL 0.682 Poisson BLOCK WEEK*BLOCK 2017 Fall Pan traps Fb 0.614 Poisson BLOCK WEEK*BLOCK 2017 Fall Pan traps HYM 1.506 Negative binomial BLOCK 2017 Fall Pan traps ORI 0.295 Poisson BLOCK*TRT 2017 Fall Pan traps SPI 0.263 Poisson BLOCK 2017 Fall Pan traps WF 1.142 Negative binomial BLOCK*TRT 2017

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Table A-1. Continued Season Sampling Variable Pearson Chi- Distribution Random effects technique Square/DF Fall Sticky APH_Ala 4.034 Negative binomial None 2017 traps Fall Sticky APH_Ap 1.800 Negative binomial None 2017 traps Fall Sticky DOL 4.491 Negative binomial BLOCK WEEK*BLOCK 2017 traps Fall Sticky HYM 8.652 Negative binomial BLOCK BLOCK*TRT 2017 traps WEEK*BLOCK Fall Sticky SPI 1.019 Negative binomial None 2017 traps Fall Sticky THR 7.708 Negative binomial BLOCK BLOCK*TRT 2017 traps WEEK*BLOCK Fall Sticky WF 14.372 Negative binomial BLOCK BLOCK*TRT 2017 traps

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BIOGRAPHICAL SKETCH

Lorena Lopez was born and raised in Cali, Colombia. She received her bachelor’s degree in biology with a major in entomology from the University of Valley in 2011. In fall 2012,

Lorena moved to the United States to pursue her master’s degree at the University of Florida’s

Gulf Coast Research and Education Center (Wimauma, FL) working on biological control of pest mites in high-tunnel pepper production. She graduated with her MSc in entomology and nematology in August 2014. Lorena moved to Gainesville, FL in fall 2014 and joined the Small and Vegetable IPM Laboratory at the University of Florida’s entomology and nematology

Department to pursue her doctoral degree under the supervision of Dr. Oscar Liburd. Her research included regulation of the above-ground pest complex attacking organic zucchini squash by implementing sustainable practices such as companion planting and conservation and augmentation of biological control agents. Lorena received her PhD in entomology in May 2019.

Lorena’s interests include biological control, acarology, and the use of sustainable practices in agricultural systems. Her future career goals are to conduct research and extension services related to IPM to contribute to the grow of sustainable agriculture.

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