Swede Midge, Contarinia Nasturtii (Diptera: Cecidomyiidae

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Graduate College Dissertations and Theses Dissertations and Theses

2015 Swede Midge, Contarinia Nasturtii (diptera: Cecidomyiidae), Response To Brassica Oleracea In Simulated Intercropping Systems Gemelle Laureen Brion University of Vermont

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Recommended Citation Brion, Gemelle Laureen, "Swede Midge, Contarinia Nasturtii (diptera: Cecidomyiidae), Response To Brassica Oleracea In Simulated Intercropping Systems" (2015). Graduate College Dissertations and Theses. 351. https://scholarworks.uvm.edu/graddis/351

This Thesis is brought to you for free and open access by the Dissertations and Theses at ScholarWorks @ UVM. It has been accepted for inclusion in Graduate College Dissertations and Theses by an authorized administrator of ScholarWorks @ UVM. For more information, please contact [email protected]. SWEDE MIDGE, CONTARINIA NASTURTII (DIPTERA: CECIDOMYIIDAE), RESPONSE TO BRASSICA OLERACEA IN SIMULATED INTERCROPPING SYSTEMS

A Thesis Presented

Gemelle Brion

The Faculty of the Graduate College

The University of Vermont

In Partial Fulfilment of the Requirements For The Degree of Master of Science Specializing in Food Systems

May, 2015

Defense Date: February 27, 2015

Thesis Examination Committee: Yolanda H. Chen, Ph.D., Advisor David S. Conner, Ph.D., Chairperson Deborah A. Neher, Ph.D. Cynthia J. Forehand, Ph.D., Dean of the Graduate College Abstract Monoculture agriculture has developed as a result of the Western agricultural growth model, which emphasizes reduced on-farm labor and maximum yield. As a result soil health, which is reliant on a diversity of soil-dwelling organisms, is compromised, pest problems are intensified, and biodiversity is lost when vast land areas are devoted to simplified vegetation schemes. There has been a tremendous rise in interest in alternative cropping schemes. The traditional practice of intercropping has received renewed interest as the emphasis on agricultural growth shifts from a purely development-based model to one of conservation and enhanced biodiversity. Although intercropping has shown promising results in controlling specialist herbivorous insects, how intercropping works is not known. Theories that explain the underlying mechanism of intercropping success include chemical repellency and physical masking. We tested these two theories by creating a simulated intercropping system in mesocosm cages in a laboratory environment. We tested twenty intercrops that varied in their vegetation type, size, and phylogenetic distance for their ability to repel an insect pest that recently invaded into North America, the swede midge (Contarinia nasturtii), from its host plant, Brassica oleracea. We found that different non-host plant treatments significantly influenced larval abundance, which indicates that C. nasturtii responded to some aspect of the varying plant combinations. We found that phylogenetic distance did not influence larval densities. Additionally, non-host plant height and leaf area of non- host plants did not influence larval densities. We found that vegetation type significantly affected larval densities. Brassica oleracea planted in combination with groundcover non-host plants had the fewest number of larvae, followed by B. oleracea planted in combination with vegetables. The highest number of larvae was found on B. oleracea plants planted in combination with herb non-host plants. Our research did not support a chemical repellency or visual masking theory of intercrop success.

Table of Contents

Chapter 1: Literature Review ...... 1 1.1 Intercropping ...... 4 1.2 Benefits of Intercropping ...... 6 1.3 Challenges of Intercropping ...... 7 1.4 Intercropping Design Considerations ...... 8 1.5 Competition and Facilitation in Intercropping Systems ...... 9 1.6 Success of Intercropping as a Means of Insect Pest Control ...... 9 1.7 Insect Behavior in Intercropping Systems ...... 10 1.8 How Intercropping Works: A Current Debate ...... 12 1.9 Plant Chemistry and Herbivory ...... 13 1.10 Insect Host-Finding Behavior ...... 14 1.11 Insect Response to Plant Physical Cues ...... 16 1.12 Insect Response to Plant Chemical Cues ...... 17 1.13 Using Plant-Insect Interactions to Develop Sustainable Agricultural Practices 17 1.14 Conclusion ...... 18 Chapter 2: Journal Article ...... 22 2.1 Materials and Methods ...... 27 2.2 Results ...... 35 2.3 Discussion ...... 36 2.4 References ...... 39 Tables ...... 43 Figures...... 46 Appendix ...... 52 Comprehensive Bibliography ...... 53

Chapter 1: Literature Review The current agricultural production model in the United States has developed as a means of increasing food production at a lower cost (Gardner, 2006). Farming equipment has taken the place of manual labor, which had historically been a major limitation in farming expansion and profitability (Conkin, 2009). Equipment advances allowed for larger tracts of land to be farmed (Conkin, 2009). With the goal of efficiency and reducing the amount of human labor required to have a successful farming operation came the simplification of vegetation on the farm (Conkin, 2009). Monoculture, which is growing a single crop species over the entirety of a farmed land unit, accounts for the majority of agricultural operations in the United States (Gardner, 2006). Between cropland simplification and mechanistic advances, a larger crop yield per acre is achievable and a smaller portion of the population is required to be involved in agricultural production in the United States (Conkin, 2009). Productivity has increased and labor needs have decreased, achieving the purpose of cropland simplification and mechanization of agricultural production.

There are however ecological consequences to land simplification. Sustained soil health, which is reliant on a diversity of soil-dwelling organisms, is compromised, pest problems are intensified, and biodiversity is lost when vast land areas are devoted to simplified vegetation schemes (Innis, 1997). Alternatives to monoculture agriculture can be found in traditional indigenous farming systems (Innis, 1997; Perrin, 1976).

Intercropping is a common farming system used all over the world by indigenous populations. The survival of intercropping over thousands of years in many different regions is a testament to the sustainability of the practice. Small rural farmers have been 1

able to farm a piece of land for hundreds of years while maintaining soil fertility (Innis,

1997). The concern over soil degradation and ecological simplification of modernized farming practices has led to an interest by agriculturalists to better understand traditional agricultural practices (Perrin, 1976). In addition, these practices have been shown to offer a sustainable and low-input form of insect pest control, which is supported by governments around the globe that have shown interest in shifting the focus of agricultural production away from a growth and development perspective to one of sustainability, conservation, and species preservation (UNCED, 1992).

There are benefits and drawbacks to traditional farming practices. Case studies of intercropping in Asia, Africa, and Latin America have shown intercropping to be more profitable to smallholder farmers than monocropping (Innis, 1997; Perrin, 1976). Plants are chosen for intercropping that have been tested on the farm over many generations.

Plant combinations that have been selected over many hundreds of years of on-farm trial are those that utilize diverse resource pools or that reduce pest outbreaks, both of which benefit the overall yield of the intercropped plants within the system (Feike, Chen,

Graeff-Hönninger, Pfenning, & Claupein, 2010; Innis, 1997). The yield of each crop in an intercropping system is not always higher than in a monocrop of the same plant. The combined yields of several different plants on equivalent acreage as a monocrop of each of the species are higher (Innis, 1997). Several crops grown in combination also reduces market and grower risk to smallholder farmers (Feike et al., 2010; Perrin, 1976). Soil management is improved by better utilizing space, water, and soil nutrients and pest pressure can be reduced through intercropping with the proper selection of plants (Perrin,

1976; Vandermeer, 1989). Both of these benefits reduce inputs, which increases the

overall return of each crop. Intercropping systems are currently labor intensive (Feike et al., 2010; Perrin, 1976). Manual labor is typical on smallholder operations whether monocropping or intercropping, so the labor expense to implement intercropping and monocropping systems is similar (Innis, 1997). The variety of planting combinations and possible layout of the plants complicates the ability to reduce labor costs in multiple cropping systems in developed countries but the savings in agricultural inputs could offset this cost and provide additional employment opportunities (Morgan & Murdoch,

2000).

Increasing on-farm vegetational diversity has great potential in solving ecological imbalances created by agricultural simplification (Andow, 1991; Innis, 1997;

Vandermeer, 1989). Solving these ecological imbalances aids in the maintenance of soil fertility and can decrease pest pressure (Andow, 1991; Innis, 1997; Vandermeer, 1989).

Ecological interactions in cropping systems include plant-plant interactions, plant- microbe interactions, plant-insect interactions, and interactions between the natural enemies of plant pathogens and insects (Andow, 1991). Intercropping designs that maximize temporal and spatial overlap have the greatest amount of biodiversity because all of the ecological interactions are occurring at the same time (Andow, 1991) and biological diversity may be maximized by increasing the number of plants in the intercropping combination (Innis, 1997).

Intercropping has shown promising results in reducing insect pest abundance in agricultural fields and there are additional derived benefits of diverse planting schemes

(Vandermeer, 1989; Innis, 1997; Schoonhoven et al., 2005). Diversifying the vegetation of agricultural fields can increase species diversity and abundance beyond the vegetative

community (Jackson & Jackson, 2002; Kristiansen et al., 2006), which supports proper ecosystem functioning. Intercropping is an example of a mixed cropping strategy that can help to restore ecological functioning of farming operations that may otherwise lack diversity (Jackson & Jackson, 2002).

Research that aids our understanding of these complex and sophisticated systems needs to be performed in order to develop multiple cropping systems that can be used on small and large scale operations and within the framework established for mechanized agricultural operators. The intercropping systems practiced by smallholder farmers throughout the world have been developed through centuries of trial and error and have been developed within the ecological and environmental scope of individual geographic regions (Feike et al., 2010; Innis, 1997; Perrin, 1976). If there is a greater understanding of the ecological interactions that influence the success of different plant combinations, the development of intercropping systems that maximize productivity for different plant combinations and addressing specific resource concerns or pest pressure issues can be developed more rapidly (Perrin, 1976).

1.1 Intercropping Intercropping is growing more than one crop in close enough proximity that the crops are interacting agronomically (Schoonhoven et al., 2005). There is a timing and spatial component to intercropping (Vandermeer, 1989; Andow, 1991). Intercropping can include strip cropping, trap cropping, repellent intercropping, and relay intercropping

(Kristiansen et al., 2006) because all of these practices include a planting scheme that places plants near each other spatially and the plants are not completely separated temporally (Vandermeer, 1989; Andow, 1991). Field borders, hedgerows, barrier strips

(filter strips and buffer strips) and green manures are agricultural practices that have the ability to diversify agricultural vegetation but are not classified as intercropping strategies

(Kristiansen et al., 2006). Strip cropping involves planting different crop species in alternating strips (Munz, Feike, Chen, Claupein, & Graeff-Hönninger, 2014). Strip cropping is a diverse planting scheme that takes into account ease of harvesting, as the strips are typically the width of planting and harvesting equipment (Munz et al., 2014).

Trap cropping is planting a crop that is more attractive to an insect pest than the host plant (Holden, Ellner, Lee, Nyrop, & Sanderson, 2012). The trap crop is typically a sacrifice crop and additional pest control methods are oftentimes used on the trap crop to keep pest population numbers down and reduce spill over to the target crop (Holden et al.,

2012). Repellent intercropping is planting a crop that has a repellent effect on an insect pest near the host crop of the insect pest (Vandermeer, 1989; Schoonhoven et al., 2005).

Relay intercropping is different than other intercropping systems due to the timing of cash crop and intercrop planting (Wang et al., 2014). In a relay intercropping scheme, the intercrop is planted before or after the planting of the cash crop with some time period of overlap that the plants are growing together in the field (Wang et al., 2014). Annuals and perennials may be used in an intercropping system, though intercropping an annual and a perennial may be difficult for planting and harvesting equipment (Vandermeer,

1989). Intercropping is not a new technique. Farmers have been practicing some form of mixed cropping for several thousand years (Innis, 1997) and intercropping research has been taking place for several decades (Vandermeer, 1989). There are a number of derived benefits in implementing an intercropping system (Vandermeer, 1989;

Schoonhoven et al., 2005) and interest in ecologically sound agricultural practices has led

to a resurgent interest in intercropping (Lithourgidis, Dordas, Damalas, & Vlachostergios,

2011; Wezel et al., 2014).

1.2 Benefits of Intercropping Depending on the benefit of implementing an intercropping system, some crop interactions can be beneficial to both plants in the intercropping system (de la Fuente,

Suárez, Lenardis, & Poggio, 2014; Li et al., 2014), while other interactions are beneficial to the cash crop but not necessarily beneficial to the intercrop (Sharma & Banik, 2015).

Some of the benefits of intercropping include: increased productivity, resource efficiency, pest control, and socio-economic benefits (Vandermeer, 1989). There are plant species that are able to modify the abiotic environment in a way that is beneficial for another plant species, which translates into a yield increase for one or more plants involved in the interaction (Li et al., 2014). Changing the abiotic environment includes increasing nutrient availability, providing protection from environmental extremes, and modifying the belowground moisture (Butterfield, 2009). Additionally, continual cover systems reduce soil erosion, and increase soil structure, which can increase crop yields (Wezel et al., 2014). Resource efficiency can be improved if two or more plants perform well together because less land is taken up by growing the crops together (Vandermeer, 1989).

If one of the derived benefits of the intercropping system is weed control, a reduction in time and labor may occur, which would increase the resource efficiency (Vandermeer,

1989). Intercropping can reduce pest infestations, including disease, weed, and insect pests (Kristiansen et al., 2006). The intercrop may either limit weed infestation by out competing with weed species or through allelopathy that limits weed growth without affecting the cash crop (Liebman & Dyck, 1993).

Diversifying the farming operation can lead to socio-economic benefits as well

(Innis, 1997). Planting more than one crop reduces the risk of relying on a single crop for the farm’s income, both in terms of potential crop devastation and in diversifying markets

(Innis, 1997). The reduction in pest pressure and increase in nutrient assimilation may also reduce the need for external inputs, such as fertilizer and pesticides (Ren et al., 2014).

Despite these benefits, there are hesitations to implementing an intercropping system

(Wezel et al., 2014).

1.3 Challenges of Intercropping Intercropping is labor intensive, which is one of the main management issues associated with the practice (Feike et al., 2010; Perrin, 1976). The western industrial model of agricultural growth has reduced the amount of labor required on agricultural operations because labor had previously been an element of farm management that greatly reduced opportunities for growth and expansion of farming operations (Conkin,

2009). Harvesting and planting equipment in developed countries is standardized for single crop planting, so additional time and resources will be required to plant and harvest crops in a mixed planting scheme (Lithourgidis et al., 2011). Designing an intercropping system that solves a stated resource concern or pest management issue is another major challenge to implementing intercropping systems (Vandermeer, 1989).

The design must manage competition for resources between crop plants (Wezel et al.,

2014) and be effective at the intended outcome of the practice (Vandermeer, 1989). All design issues are associated with selecting appropriate plant species and seeding densities for the intercropping system and managing the time it takes to create a successful intercropping system (Lithourgidis et al., 2011). Traditional intercropping schemes are

complex and sophisticated systems developed over hundreds of years of trial and error on the farm (Innis, 1997). New designs that can be used for crops grown in the United

States can borrow from traditional knowledge as well as modern understanding of agronomic interactions and ecological understanding.

1.4 Intercropping Design Considerations Several designs exist for intercropping systems including mixed cropping, row intercropping, strip intercropping, and intercropped borders (Vandermeer, 1989;

Schoonhoven et al., 2005). Mixed cropping is growing more than one crop at the same time without a row arrangement (Vandermeer, 1989). Strip intercropping is growing several rows of more than one type of plant (Munz et al., 2014), while row intercropping is growing more than one crop at the same time in a row formation (Schoonhoven et al.,

2005). Intercropped borders are perimeter crops that surround at least one other crop type (Khan, Midega, Bruce, Hooper, & Pickett, 2010). All types of intercropping systems require special attention to seeding rate and spatial allowances to maximize growth potential and benefits of each crop type (Sullivan, 2003). The arrangement and spacing of strip and row intercropping can vary depending on the intercrop’s function

(Sullivan, 2003). For insect pest control, a row intercrop design is typically used

(Vandermeer, 1989). This design allows for the intercropped plants to either be planted within the spacing allotment between host plants (additive intercropping) or creates additional space for the intercropped plants (substitutive intercropping) (Parsons, Dixon,

& Colbo, 2007). Competition for resources between the host plant and the intercrop are more likely with additive intercropping but careful selection of plants can reduce this risk

(Parsons et al., 2007).

1.5 Competition and Facilitation in Intercropping Systems It is important when designing an intercropping system to select plants that have complementary growth habits so that the likelihood that they will be competing for resources is minimized (Lithourgidis et al., 2011). In addition, plants with strong allelopathic properties should be tested for their effect on the other plants in the intercropping system before planting (Albuquerque et al., 2011). Plants with different root depths and habits may complement each other by using resources at different locations in the soil (Lithourgidis et al., 2011). Canopy cover of each intercrop should be considered along with light requirements of each plant so that unnecessary shading does not occur (Su et al., 2014). Canopy cover can additionally act as a protective feature (Su et al., 2014). Height can also influence light availability and can provide physical protection to neighboring plants (Mauro, Sortino, Mauromicale, & Mauromicale, 2014).

The nutrient requirements of each of the intercrops should be carefully considered so that competition for limiting nutrients does not occur (Ehrmann & Ritz, 2014). Crops that increase the nutrient availability of oftentimes limiting nutrients, such as nitrogen in legumes, are considered favorable intercrops (Ehrmann & Ritz, 2014). Competition and facilitation are the two main factors that have influenced the design of intercropping systems thus far (Ehrmann& Ritz, 2014). When standardizing intercropping systems for a pest control benefit, plants that provide the greatest potential to control the targeted pest should be considered in addition to the characteristics of the intercrop and cash crop that could influence competition (Schoonhoven et al., 2005; Ehrmann& Ritz, 2014).

1.6 Success of Intercropping as a Means of Insect Pest Control There have been successes in implementing an intercropping system to control insect pests (Vandermeer, 1989; Innis, 1997; Schoonhoven et al., 2005). However, 9

inconsistencies in intercropping success remain, with the developed system sometimes reducing the number of insect pests and sometimes having no effect or increasing the number of insect pests on the host crop (Lithourgidis et al., 2011; Schoonhoven et al.,

2005; Andow, 1991). Differing host finding behavior between generalist and specialist insect pests explains some of the variability in intercropping success but even specialist insect pests are not always deterred by mixed cropping systems (Lithourgidis et al., 2011,

Schoonhoven et al., 2005, Andow, 1991). In multiple literature surveys, herbivore densities were shown to decrease in diversified planting schemes within agricultural settings in greater than 50% of the studies (Lithourgidis et al., 2011, Schoonhoven et al.,

2005) while herbivore densities increased in a polyculture situation in less than 18% of surveyed studies (Lithourgidis et al., 2011, Schoonhoven et al., 2005). Additional studies show no change in insect abundance at all. Cases of lower herbivore abundance have been shown to occur most often in studies of specialist insect pests while generalist insect densities often increase in diversified plantings (Schoonhoven et al., 2005). Diversified plantings provide more host options to generalist insect pests, thereby increasing the density of generalist herbivores (Schoonhoven et al., 2005).

1.7 Insect Behavior in Intercropping Systems The ability of host plant chemistry and the appearance of the host plant, including size, color, and morphology, to influence specialist herbivorous insect host acceptance has been well documented (Rosenthal & Berenbaum, 1992). It is unclear whether chemical and physical properties of non-host plants influence host plant acceptance in polyculture systems. Several hypotheses attempt to explain host finding behavior of herbivorous insects in intercropping systems.

The two main cues an insect pest could be responding to in an intercropping system are visual cues or chemical cues (Finch & Collier, 2012; Poveda & Kessler, 2012).

Physical obstruction is one theory behind the success of intercropping systems. In this theory, the insect pest is unable to find its host plant because the physical size of the intercrop masks the host plant (Perrin, 1976). Other types of visual camouflage could be at play, including the color of the intercrop, the background created by an intercrop, and the intercrop’s interruption of the insect pest’s flight path (Finch & Collier, 2000).

Another theory is the masking of host plant odors. The release of non-host odors in close proximity to the host plant may mask the odor of the host plant, which interrupts the insect pest’s host finding ability (Perrin, 1976; Tahvanainen & Root, 1972). Similarly, the volatiles produced by non-host plants may have a repellent property which deters the insect pest (Poveda & Kessler, 2012). A final theory associated with plant volatiles is that of the host plant volatiles changing with a changing plant community. Host plants are unable to metabolize some of the chemical compounds it takes up from the soil

(Rovira 1969). An intercrop that releases root exudates can alter the host plant’s chemical makeup and potentially the chemical compounds released by the host plant by supplying the soil with chemical compounds the host plant accepts. This change in volatile chemistry could confuse the insect pest (Rovira, 1969).

Hypotheses more broadly relating to insect behavior in monoculture and polyculture situations include the Resource Concentration Hypothesis and the Enemies

Hypothesis. The Resource Concentration Hypothesis states that when resources are concentrated in an area, specialist phytophagous insects are more likely to find the resource and remain in the area (Root, 1973). Enemies Hypothesis proposes that

complex environments reduce the number of specialist phytophagous insects that enter and remain in the area (Root, 1973). These hypotheses relate to specialist insect pests and do not necessarily hold true for generalist insect pests (Schoonhoven et al., 2005).

1.8 How Intercropping Works: A Current Debate Poveda and Kessler (2012) argue that volatiles emitted by intercropped plants repel (repellent intercropping) or attract (trap cropping) the insect pest which, in either case, reduces pest infestation of the host plant. There is evidence that insects are stimulated by certain volatile compounds that make up the chemical bouquet emitted by their host plant (Christensen & Hildebrand, 2002), but it is still unclear whether the volatiles released by the surrounding vegetation have the ability to repel insect pests or if the insect pest is able to detect these chemical compounds at all (Christensen &

Hildebrand, 2002). Previous studies support a chemical deterrence theory in intercropping systems. Tahvanainen and Root (1972) showed that masking host plant odors can occur with the release of non-host odors in close proximity to the host plant.

Research performed by Dethier et al. (1960) and Uvah and Coaker (1984) suggests that the volatiles produced by non-host plants may have a repellent property which deters the insect pest. A modern example of a highly successful intercropping strategy that relies on the chemical repellency approach to deter insects is the push-pull system developed to protect cereal grains in Africa from a number of Lepidopteran stem borers (Khan et al.,

2010). Researchers sought plants to be used as trap crops based on their release of chemical compounds that are highly attractive to the stem borers and are released in greater amounts (Khan, Pickett, Berg, Wadhams, & Woodcock, 2000). A repellent intercrop was identified by knowledge that the volatiles of the repellent intercrop, Melinis

minutiflora, attract Cotesia sesamiae, a natural enemy of the targeted herbivorous insect.

Further research showed that the same chemicals emitted for signaling also had a repellent effect on female stem borer moths (Khan et al., 2000).

On the other side of the intercropping debate, Finch and Collier propose that the volatiles released by the intercropped plant are not the source of insect deterrence from its host plant but rather it is the physical structure of an intercrop that confuses the insect pest and keeps it from its host plant (Finch and Collier, 2012). They argue that specialist insects are only able to respond to volatiles emitted by their host plant and that intercropping works by confusing an insect pest with more than one vegetation option

(Finch and Collier, 2000). Previous studies have shown that the pattern of vegetation versus bare soil (Finch & Collier, 2012; Perrin, 1976) and the color of the intercrop

(Finch and Kienegger 1997) may influence insect host plant acceptance. Understanding plant-plant and plant-insect interactions can aid in our understanding of the complex interactions occurring in intercropping systems.

1.9 Plant Chemistry and Herbivory A plant’s chemical make-up can influence insect interactions by encouraging insect visitation or by warding off insect visitors (Schoonhoven et al., 2005). Attractive chemical compounds are emitted from plants as VOCs from various plant parts, including leaves, stems, and floral structures (Farré-Armengol, Filella, Llusia, & Peñuelas, 2013).

Attractive compounds can be released for pollination services (Farré-Armengol et al.,

2013) or to attract carnivorous insects and parasitoids of herbivorous insects (Pickett et al., 2003). Compounds produced to defend plants from herbivory are called defensive compounds and include volatiles that indirectly protect the plant by attracting antagonists

of herbivorous insects (indirect defenses) and allelochemicals that are directly harmful to herbivorous insects (direct defenses) (Gols, 2014). Herbivory induces qualitative and quantitative changes in secondary metabolite production in plants (Gols, 2014). Non- volatile allelochemicals produced in response to insect feeding can be toxic to the insect by interfering with metabolic processes, slowing down the development of insects, reducing the amount of herbivory by changing feeding behavior, or reducing the capacity of an insect to assimilate nutrients (Schoonhoven et al., 2005). Herbivory and oviposition can also induce the production of volatiles that attract antagonists of herbivores (Gols,

2014). Carnivorous insects and parasitoids of herbivorous insects are attracted to the emitted volatiles and use the chemical cues released by plants to locate their prey (Gols,

2014). Herbivore-induced plant volatiles (HIPVs) and oviposition induced plant volatiles

(OIPVs) are specific both to the emitting plant species and to the feeding or ovipositing insect (Reymond, 2013; Schoonhoven et al., 2005). Information about the type and density of the attacking insect is transferred to neighboring plants using HIPV and OIPV signaling (Schoonhoven et al., 2005). Chemical signaling may occur primarily for the protection of the emitting plant, but neighboring plants are able to respond to emitted

HIPVs and OIPVs by escalating their own chemical defenses (Pickett et al., 2003;

Reymond, 2013).

1.10 Insect Host-Finding Behavior There are several situations that would necessitate a host plant location by an herbivorous insect, including migration, dispersion, locally depleted food resources, and adult emergence following pupation far from food resources (Schoonhoven et al., 2005).

In natural habitats, insects search for their host plant in diverse stands of non-host

vegetation (Price et al., 2011). Schoonhoven et al. (2005) acknowledged this difficulty but were able to create a generalized list of the sequence of events that occur in host-plant selection, which describes the process in seven phases. The first phase is no contact with a plant. This is followed by the perception of visual or olfactory plant cues. The third phase is response to plant cues, which reduces the distance between the plant and the insect (how this is carried out depends on the mobility of the insect). Contact with the plant occurs in the fourth phase followed by contact testing of the plant surface. The sixth phase describes damage to the plant in order to test the tissue contents. Finally, the plant is accepted or rejected (Schoonhoven et al., 2005). What is known for all insect species is that insects are stimulated by plant cues, visual or olfactory (Price 2011), and that the memory of occurrence and the stimulatory effect of plant cues are processed in the insect’s central nervous system (Pfeiffer & Homberg, 2014). Host plant seeking is random in some insect species and directed in others (Price et al., 2011). Random seeking is used when plant cues are insufficient or when the insect does not have the capacity to detect stimuli (Kareiva & Shigesada, 1983; Loxdale & Lushai, 1999). In these cases, an insect is motivated to seek a host plant through biochemical changes that activate a section of the central nervous system and motivate the insect towards movement (Ritzmann & Büschges, 2007). In random movement, the direction of travel appears unrelated to final host plant acceptance (Loxdale & Lushai, 1999). When an insect is able to detect environmental cues and visual or olfactory cues of the host plant are available, directed movement may take place (Price et al., 2011). Directionality can be perceived by the host plant cues alone, or can be determined by a combination of host plant cues and environmental factors (Price et al., 2011). In addition to host plant visual

and olfactory cues, orientation can be directed by prevailing wind direction (anemotaxis) and the light direction (photomenotaxis). The importance of visual or olfactory cues of the host plant and/or anemotaxis and photomenotaxis to locate host plants differs in different insect species (Schoonhoven et al., 2005). Directional or random movement occurs until contact with the host plant is established and movement may continue until a host plant is accepted by the insect (Price et al., 2011).

1.11 Insect Response to Plant Physical Cues In the absence of plant odor, it has been shown that plant physical characteristics influence host finding behavior (Prokopy & Owens, 1983; J.L. Reeves, Lorch, &

Kershner, 2009; Justin L. Reeves, 2011). Visual plant cues that an insect could be responding to include the color, size, and shape of plants (Finch & Collier, 2000). Plant color is something that remains relatively constant in various environmental conditions, so it is thought that the consistency of reflected light could provide insects with a reliable host plant location mechanism (Schoonhoven et al., 2005). The argument against using color as a visual cue is that all plants fall within a short spectral wavelength (500-580 nm), so differentiation between plants may be difficult for insects relying solely on the spectral signal of plants (Schoonhoven et al., 2005). The size of the whole plant and the shape of plant parts have additionally been shown to be important visual host finding cues (Harris,

Rose, & Malsch, 1993; Hodgson & Elbakhiet, 1985; Mackay & Jones, 1989; Reeves et al., 2009). Reeves (2011) suggests that size, shape, and color work synergistically to direct an insect to its host plant and that no single physical characteristic is more important in host finding behavior than another characteristic. Whether the plant is growing horizontally or vertically has additionally been shown to influence host finding

behavior (Harris et al., 1993). Color may be detected at near and far ranges from the host plant but the size and shape of plants are only perceptible to insects at close range

(Schoonhoven et al., 2005). Changes in the physical characteristics of host plants have also been shown to impact predation and parasitism, so plant physical characteristics are influential in the composition of the local insect community (Price et al., 2011).

1.12 Insect Response to Plant Chemical Cues Insects are dependent on olfaction for environmental sensing, including host location ability (Krieger & Breer, 1999). Olfactory signals from the host plant are more variable in the environment than visual cues but they can be detected at great distances from the host plant (average of 5-30 meters) (Schoonhoven et al., 2005). Plants emit volatiles at differing rates and the volatiles diffuse in the air column once released from plants. Concentration of volatiles in the air is dependent on air movement and release rate (Bruce & Pickett, 2011). The concentration of plant-emitted volatiles that an insect requires for response is unknown (Schoonhoven et al., 2005). Volatiles emitted by plants are specific to the plant species, so chemical cues are thought to better indicate the presence of a specific plant species to an insect (Bruce & Pickett, 2011). It is likely that insects respond to both visual and olfactory cues in host plant location to maximize the benefits of each strategy (Schoonhoven et al., 2005).

1.13 Using Plant-Insect Interactions to Develop Sustainable Agricultural Practices Agricultural fields are controlled environments that are often subject to annual variation in community composition and structure, high nutrient inputs, and high disturbance (Gaba, Fried, Kazakou, Chauvel, & Navas, 2014). Studying the ecology of agricultural fields is difficult because there is an enormous amount of variation in

management techniques over diverse landscapes and in a number of different types of agricultural operations that combined could change the agricultural ecosystem within a short time frame (Bommarco, Kleijn, & Potts, 2013). Even without a universally defined ecosystem type in agricultural settings, ecological interactions lend new possibilities to agricultural management techniques that are less intensive and are lower input alternatives to conventional agricultural practices (Tittonell, 2014). The natural history of a farming operation can provide a framework for the type of practices that would best fit the operation given the natural environment that once existed in that location or ecological management options can be incorporated into an agricultural environment without mimicking the surrounding ecosystem (Rader et al., 2014). Studies in plant-plant competition and facilitation have led to agricultural management practices that use these interactions to develop pest and weed control strategies (Gols, 2014; Haramoto &

Gallandt, 2004; Miresmailli & Isman, 2014). Insect control methods have also been developed from emerging research in plant-insect ecology (Kristiansen et al., 2006;

Schoonhoven et al., 2005).

1.14 Conclusion There has been increased societal and political interest in implementing ecologically sound pest management strategies (Terry, 2014). Because organic products are required to use ecologically sound agricultural practices for pest control and soil maintenance (Code of Federal Regulations, 2000), social interest can be measured in the

United States by considering the increases in organic production and consumption. The number of organic operations has grown from 6,949 in 2001 to 12,880 operations in 2011

(Greene, 2013). During the same time period, there was a 67% increase in the number of

certified organic acres (Greene, 2013) (Edlich et al., 2007). Per year, the number of organic farmers is increasing at a rate of 12% (Edlich et al., 2007). Additionally, the market for organic products has grown in recent years, with an estimated 19% increase in organic sales from 2012 to 2014 (Greene, 2014). More of the mainstream public is purchasing organic products (Greene, 2014; Jones, 2005) and this is thought to be due to both an interest in ecologically-based farming strategies and human and environmental health concerns associated with conventional practices (Jones, 2005). The passage of the

Organic Foods Production Act (OFPA) in 1990 was a major milestone in moving towards standardized practices that can be implemented by farmers in the United States to increase biological diversity (Youngberg & DeMuth, 2013). Passage of OFPA also gave relevancy to a system of practices that had previously been considered fringe (Youngberg

& DeMuth, 2013). Two years following the passage of OFPA, the United Nations

Conference on Environment and Development (UNCED) in 1992 emphasized the importance of increasing biodiversity in agricultural systems worldwide. During the

1992 UNCED, it was suggested that agricultural development be shifted from a purely growth and yield based model to one of sustainability (UNCED 1992).

Increasing the diversity and the abundance of organisms on the farm has been shown to increase the overall health of the soil, plant community, and ecological functioning of the farm, which may lead to increased yields, healthier, more productive soils, and reductions in external inputs such as fertilizer and pesticides (Jackson &

Jackson, 2002). Studying the ecological interactions between agricultural organisms provides insight into how alternative pest management strategies may be standardized.

The alternative farming practice of diversifying vegetation has been shown to deter insect

pests (Innis, 1997; Schoonhoven, Loon, & Dicke, 2005; Vandermeer, 1989). It is important to understand aboveground and belowground plant community dynamics and insect-plant interactions in order to further the development of guiding principles in diversified planting schemes.

Intercropping is a practice that uses the ecological interactions of the organisms on the farm to control for insect pests. There is a reduction of inputs required for intercropping systems, lending to the sustainability of the practice. Understanding the underlying mechanisms of how intercropping works could lead to wider acceptance of the practice. Currently intercropping is not understood well enough to predict the success it will have on a given insect pest. More research needs to be performed in the area of intercropping in order to make the practice an attractive option for farmers, who would require more predictability and a clearer framework for implementation. Current intercropping systems have been developed for specific pests, but broad application can only be achieved if there is an understanding of the insect-plant interactions that occur when an insect experiences intercropping situations. Intercropping has the ability to contribute to a sustainable food system by offering growers of agricultural products an option that reduces inputs.

There is opportunity for growth in food production, which includes implementing practices that are ecologically sound while using the latest agricultural technologies and understanding ecological interactions of the organisms on the farm. Societal interest in producing foods in a way that protects human health and increases biological diversity is increasing. The importance of sustainable food production to the society may be seen through the growth in organic sales and organic food production in the United States.

Although there is movement towards a shift in agricultural production methods, there are hesitations, including the ability to provide affordable food to much of the population of the United States (Maupin & Norton, 2010), the availability of markets for organic products (Hornstein 2007), the cost of implementing changes on individual farms, and an increase in time-consuming farm management practices (Terry, 2014).

Chapter 2: Journal Article Modern crop agroecosystems have long been thought to be more vulnerable to insect pest outbreaks because they are almost exclusively grown in a monoculture

(Meehan, Werling, Landis, & Gratton, 2011; Skelton & Barrett, 2005; Tahvanainen &

Root, 1972). In order to reduce the inherent vulnerability of systems grown in a monoculture, there has been a great deal of interest in diversifying cropping systems as a means for insect pest control (Andow, 1991; Innis, 1997; Kristiansen, Taji, & Reganold,

2006; Schoonhoven, Loon, & Dicke, 2005; Vandermeer, 1989). One of the most widely explored practices is intercropping, which involves two or more crops grown in close proximity with each other (Vandermeer, 1989). It has long been known that specific combinations of plant species could influence the ability of insect herbivores to find their host plants (Root 1973, Tahvanainen and Root 1972). Although some intercropping systems have been successfully developed to control insect pests (Innis, 1997;

Schoonhoven et al., 2005; Vandermeer, 1989), the main challenge to more widespread adoption is that the effects are inconsistent (Andow, 1991; Lithourgidis, Dordas, Damalas,

& Vlachostergios, 2011; Schoonhoven et al., 2005). Another major challenge in developing effective intercropping systems to control pests is the lack of a theoretical framework to guide intercrop plant selection. Previously, plants were included in intercropping systems due to agronomic benefits rather than for the purpose of pest control (Innis, 1997; Vandermeer, 1989). Although we know that neighboring plants can influence the behavior of insect herbivores (Barbosa et al., 2009), the key traits of plant species that repel specialist herbivores from their host plants is poorly understood. Plants vary in their physical and chemical characteristics and variations such as plant height, 22

vegetation type, leaf area, and phylogenetic distance may influence host finding behavior of specialist herbivorous insects. Determining which qualities of the intercropped plant are influencing insect host-finding behavior can be a useful tool in developing a clear mechanistic understanding of how intercropping works.

Differing host finding behavior of generalist insect pests and specialist insect pests explains some of the variability in intercropping success (Andow, 1991;

Lithourgidis et al., 2011; Schoonhoven et al., 2005). Several reviews have found that herbivore densities were shown to decrease in diversified planting schemes within agricultural settings in greater than 50% of the studies (Andow, 1991; Lithourgidis et al.,

2011; Schoonhoven et al., 2005) while herbivore densities increased in a polyculture situation in less than 18% of surveyed studies (Lithourgidis et al., 2011; Schoonhoven et al., 2005). Cases of lower herbivore abundance have been shown to occur most often in studies of specialist insect pests while generalist insect densities often increase in diversified plantings (Schoonhoven et al., 2005).

A debate exists regarding the relative importance of volatiles emitted by the non- host plant in repelling insect pests in intercropping systems versus the ability of physical characteristics of non-host plants to mask the host plant. Physical characteristics (Finch

& Collier, 2012), chemical characteristics (Poveda & Kessler, 2012), or vegetation type of the intercrop could be factors that contribute to the success of the intercrop in reducing insect pest abundance. Finch and Collier (2012) propose that physical size rather than the release of volatiles released by the intercropped plant are not the source of insect deterrence from its host plant but rather it is the physical size of an intercrop that confuses the insect pest and keeps it from finding its host plant. Their Appropriate

Inappropriate Landing Theory argues that the proportion of times an herbivorous insect lands on its host plant versus non-host plants determines host plant acceptance and increasing non-host vegetation by intercropping decreases proportional landings (Finch &

Collier, 2012). Under this theory, larger intercrop plants or plants with more leaf area, may be expected to be more effective. In contrast, Poveda and Kessler (2012) argue that volatiles emitted by intercropped plants repel (repellent intercropping) or attract (trap cropping) the insect pest which, in either case, reduces pest infestation on the target crop.

Vegetation type has not been analyzed as a plant characteristic that may influence intercropping success, but vegetables, herbs, and groundcover have all been used in intercropping systems.

We propose that the degree to which the intercrop plant is related to the target cro plant could also influence the success of intercropping systems in reducing pest densities.

Given that specialist insects have been widely shown to respond to the physical and chemical characteristics of their host plants and host specialization is restricted to individual plant families (Schoonhoven et al., 2005), increasing genetic distance of the non-host plant from the host plant in intercropping systems may be a useful measurement for identifying successful intercropping combinations. If host plants are masked from their specialist insect herbivores due to chemicals emitted by the non-host plant in an intercropping system, we could expect that intercrops from different plant families would vary in their repellency because different compounds would be emitted by different intercrops chemical compounds being emitted.

Taxonomically distinct plant families produce different unique classes of chemical compounds (Rosenthal, 1991) and in general, different plants within the same

plant family use compounds with related chemical structures for defense, though some defensive phytochemicals are used across taxa (Dixon, 2001). Phylogenetic distance may be used as a measure of plant relatedness. Phylogenetic distance is a pairwise measure of the number of mutational events between any two given species (Vellend, Cornwell,

Magnuson-Ford, & Mooers, 2010). Because plants emit specific volatile blends

(Rosenthal, 1991) and the molecular structure of secondary compounds produced by a given plant family decreases as the degree of plant relatedness decreases (Conn, Stumpf,

& Conn, 1981), phylogenetic distance of the intercrop from the host plant can be used as a proxy for the measure of different VOCs being emitted Additionally, because specialist insects are specific to a particular plant genus or family (Schoonhoven et al., 2005), if a repellent effect exists with a single member of a plant family, there may be a family-wide repellency to the targeted insect, assuming the emitted volatiles are unique to the repellent plant family.

Swede midge, Contarinia nasturtii (Diptera: Cecidomyiidae), is a specialist herbivore on plants within the family Brassicaceae that has been found in Europe and southwestern Asia and it has recently been introduced to North America (Hallett & Heal,

2001). C. nasturtii feeds on both cultivated and weed species in Brassicaceae (Barnes,

1950; Hallett, 2007). In the United States, Brassica oleracea varieties (kale, collard greens, broccoli, cauliflower, cabbage, Brussels sprouts, and kohlrabi) are the most economically significant host crops (Farnham, 2014). Larvae hatch from the eggs after developing for 4-5 days and feed gregariously on the host plant’s growing tips and shoots

(Chen, Shelton, Hallett, Hoepting, Kikkert, & Wang, 2011). Because larvae feed within the folds of the apical buds, foliar insecticides are largely ineffective at controlling C.

nasturtii (Chen et al., 2011; Wu, Zhao, Taylor, & Shelton, 2006). Contarinia nasturtii’s small size, short reproduction cycle, and the larval protection provided by host plant tissue has made it difficult to control with foliar insecticides (Chen et al., 2011) and alternatives to insecticides do not exist (Abram, Haye, Mason, Cappuccino, Boivin, &

Kuhlmann, 2012; Chen et al. 2011; Wu et al. 2006). Even with insecticide use, crop losses due to the swede midge in Ontario Canada and in portions of the Northeastern

United States have been reported to be as high as 85% and 100% yield losses have been reported in Europe (Chen et al., 2011).

In order to test the key plant qualities that may influence intercropping success, we tested whether physical attributes (height or leaf area), vegetation type (herb, vegetable, or ground cover), and/or phylogenetic distance of a non-host plant influenced

C. nasturtii larval densities in simulated intercrop environments in the laboratory. Using experimental mesocosms, we asked the following questions: 1) Do non-host plants planted as intercrops affect C. nasturtii larval densities on host plants? 2) Does the height of the non-host plant significantly affect larval densities? 3) Does total leaf area of the non-host plant significantly affect larval densities? 4) Is vegetation type associated with larval densities? 5) Does the phylogenetic distance between the host plant and the intercrop influence larval densities?

The Appropriate Inappropriate Landing hypothesis predicts that the size of the intercrop would influence the ability of a specialist herbivore to find its host plant. To support the Appropriate Inappropriate Landing hypothesis, we would expect that non- host plants that are taller or have greater leaf area would reduce midge larval densities more than shorter non-host plants that have less leaf area. In contrast, if the actual

composition of the volatile organic compounds from non-host plants is important for deterrence as suggested by Poveda and Kessler (2012), we expect that C. nasturtii would be more disrupted by non-host plant VOCs with increasing phylogenetic distance from the host plant.

2.1 Materials and Methods To test whether non-host plants planted as intercrops affect C. nasturtii larval densities, we exposed adult midges to simulated monocropping and intercropping systems in pop-up cages. We planted two broccoli plants on either end of a long oval pot.

The middle plant was either a third broccoli plant, which simulated a monoculture system or a non-host intercrop (Table 1), which simulated an intercropping system (Figure 1).

Because root interaction is thought to influence chemical repellency (Rovira, 1969), plants were allowed to transplanted together in the simulated intercrop combination for four weeks to allow for the roots of the host plant and non-host plant to interact.

Contarinia nasturtii colony rearing. We reared a colony of C. nasturtii within large wood-framed cages (0.61m x 0.61m x 0.61m) covered with a fine polypropylene netting (0.64mm x 0.76mm). The front of the cage was covered with Plexiglas to allow easier viewing. Adult midges were maintained in an ovipositional cage within the lab using a daily fresh supply of cauliflower plants, B. oleracea group Botrytis (High

Mowing Organic Seeds, Wolcott, VT), for ovipositing females. In order to reach optimal bud formation and swede midge acceptance, we reared cauliflower plants for 8 weeks until the 8-10 true leaf stage (Chen & Shelton, 2007). The 8-10 true leaf stage is approximately 66% of the cauliflower plant’s full maturity (56 days/85 days * 100).

After the colony plants were exposed to adult midges for 24-hours, the plants were

moved to a separate rearing cage to allow for egg and larval development. Colony plants were watered on a daily basis. Cages were kept at 16L: 8D photoperiod and the room temperature was maintained at a temperature ranging from 24°C to 26°C. The humidity was kept above 40% RH. One to three day old C. nasturtii adults were taken from the colony for use in the laboratory intercropping experiment.

Selection of test plants. Contarinia nasturtii preference, seasonal growth ability, and performance factored into our decision to select B. oleracea group Italica variety

‘Belstar’ as the host plant for the simulated intercropping experiment. Among the many different varieties of B. oleracea, Broccoli, or B. oleracea group Italica, is the most vulnerable cultivar group to C. nasturtii attack (Hallett, 2007). We chose to use the hybrid broccoli variety ‘Belstar’ because it is a commonly used organic variety that performs well in early-, mid-, and late- season plantings in New England (Björkman,

2011). We did not expect cauliflower plants used for rearing purposes to influence C. nasturtii’s response to the broccoli plants.

We selected intercrop plants for the simulated intercropping system based upon the following criteria: 1) plants that produce substances that are known to cause high rates of repellency in Cecidomyiidae species (Kim, Haribalan, Son, & Ahn, 2012), 2) plants that have been shown to successfully deter insects that specialize on Brassica spp. in previous intercropping studies (Asare-Bediako, Addo-Quaye, & Mohammed, 2010;

Hooks & Johnson, 2003; Innis, 1997; Vandermeer, 1989), 3) plants that can be grown in the Northeastern United States within an annual cropping system, and 4) plants that are uniquely positioned within the angiosperm phylogeny (Figure 2) (Stevens, 2012) . From the generated list of greater than fifty plant species, non-host plants were selected that

vary in their height, vegetation type, and phylogenetic distance (Stevens, 2012). The final plant list is shown in Table 1. We made sure to replicate all of the major treatment factors, although it was difficult to select plants to do a full factorial study of vegetation type. A phylogenetic tree of all intercrops and the host plant is shown in Figure 3 and represents evolutionary divergence from the most recent common ancestor.

Seeds were purchased from High Mowing Organic Seeds, Seeds of Change,

Outside Pride, and Horizon Herbs LLC (Table 2). Organic seeds were purchased in order to best simulate conditions found on an organic farming operation. Because intercropping is more frequently promoted as a form of pest control for organic farming operations (Kristiansen et al., 2006), we wanted to increase the likelihood that results could be reproducible in the field and applicable to organic farmers. Though there is no direct evidence that insect herbivores respond differently to conventional versus organic seeds, available plant varieties differ between organic and conventional seeds and conventional seeds are frequently chemically treated, which could have compromised results.

Plant rearing. Given that the quantity and composition of plant volatile emissions vary by plant species, environmental conditions, type of herbivory, location of plant damage, plant size, emitting plant structure, and level of development (Rosenthal,

1991), we attempted to limit the amount of environmental variation by growing plants in a greenhouse under standardized growing conditions. Plants were grown at 24°C under long-day conditions 16L: 8D. We standardized plant maturity prior to midge exposure to the best of our ability (Table 2). We also discarded plants that were diseased or heavily infested with greenhouse pests.

In order to be sure only the vegetative growth of the plant was emitting volatiles and that volatile emission levels were not confounded by the age of the plant, each plant was grown to the same level of maturity before being exposed to C. nasturtii (Table 2).

Percent maturity at exposure was calculated based on the optimal maturity level of cauliflower plants used for rearing purposes and the published calendar days to maturity represented in the seed catalogue where each plant species was purchased (Table 2).

While we considered using plant degree days to standardize plant maturity (Cesaraccio,

Spano, Duce, & Snyder, 2001), we found this approach to be unfeasible because many of the non-host plants lacked degree day information. Additionally, the experimental design accounted for temperature and day length variation, which allowed us to use plant maturity calculations based on calendar days.

Phelan et al. (1995) found that herbivore response to plants grown using conventional soil media and fertilization strategies differed from those grown using organic soil and fertilizers. For this reason, we used growing media and fertilizers that were certified for organic agriculture. Certified organic seeds (Table 1) were started in

Moo Mix soil media (Vermont Natural Ag Products, Inc.), which is a nutrient rich seed- starting soil mix approved for organic production. Seeds were either planted into 6-cell transplant pots (5cm x 5.7cm x 8.3cm), individual square pots (10.2cm x 10.2cm x

12.7cm), or were directly seeded into Panterra Oval Planters (34.6cm x 16.8cm x 12.7cm,

Greenhouse Megastore) with B. oleracea seedlings (Table 2). Lemongrass and wild ginger seedlings were purchased because they were difficult to grow from seed

(Horsford’s Nursery, Charlotte, VT). Plants were grown in the University of Vermont’s main campus greenhouse for differing lengths of time depending on the rate of maturity

for each plant (Table 2). All plants were fertilized by dunking the soil of seedlings into hydrolyzed fish fertilizer (2-4-1) (Neptune’s Harvest) as they were being transplanted.

Experimental procedure. The intercrop studies were conducted in the laboratory under full spectrum grow lights, 16L: 8D. . We tested fifteen of the same simulated intercropping treatments at one time. The major considerations that prevented us from testing all of the treatments at the same time included: limited laboratory space, limited number of C. nasturtii adults at a given point in time, and a limited number of observation cages. Testing replicates of the same intercrop at different times allowed us to account for daily temperature and humidity variation as well as variation among C. nasturtii generations. We monitored the temperature and humidity throughout the study to ensure that the laboratory environment did not fluctuate significantly over the course of the study period.

Each replicate consisted of an oval pot planted as a monocrop or as an intercrop, using the non-host crop listed under Table 1. For each set of exposed simulated intercrop pots, one monocrop pot was exposed to C. nasturtii according to the same methods and was considered the experimental control. At the appropriate maturity level (Table 2) plants in oval pots were placed in the center of (35cm x 35cm x 43.2cm) mesh collapsible cages (Bioquip, Rancho Dominguez, CA). The oval pot was situated in the mesh cage with the long edge of the oval pot perpendicular to the long edge of the observation cage

(Figure 1). We released four male and four female C. nasturtii into the experimental cages, where they remained for three days, which is the average life span of adult C. nasturtii (Readshaw 1968). Observation cages were placed side by side on a laboratory table with the plastic observation window acting as a divider so that there was limited the

air flow and odor exchange between cages (Figure 1). Odors from each intercrop were controlled between treatments by shaking out debris left from previous plants and allowing the cages to remain empty for two hours between different plant treatments.

Larval counts and plant measurements. After three days, the plants were removed and placed in growth chambers (24°C under long-day conditions 16L: 8D) for ten days, which is enough time for C. nasturtii larvae to fully develop but right before larvae drop to the soil to pupate (Readshaw, 1968). We visually inspected all plants, both host and non-host plants, for larvae. Larval counts were performed by individually removing larvae from all shoot structures with a paintbrush wetted with water. Because

C. nasturtii larvae are predominantly found in the folds of meristematic growth

(Readshaw, 1968), the terminal bud of the host plant was removed and dissected under a dissecting microscope after all other larvae on the plant shoot were removed. Larvae found in the growing tips were counted individually and all larval numbers for the entire plant were added and recorded in a spreadsheet. For each cage, we calculated the average number of larvae per broccoli plant. We assumed that there would not be a difference in the survival between larvae laid on the host plant in monocrop versus the intercrop simulation.

In order to determine whether the height of the intercrop treatment influenced larval abundance, we measured the height of each intercrop plant from the base of the plant to the tallest point of the plant. We also determined whether the relative amount of leaf area of the intercrop plant to the host plant influenced total larvae density. We measured total leaf area using a leaf area meter (LI-3100C Area Meter, LI-COR

Biosciences) and then calculated a leaf area ratio of each intercrop to host crop.

Phylogenetic distance. In order to test whether the degree of relatedness between the (non-host or intercrop?) to the host crop influenced larval numbers, we calculated the phylogenetic distance between each intercrop andB. oleracea. We constructed an unrooted phylogenetic tree using sequence data from two coding regions

(rbcL and matK) in chloroplast DNA for all test species from the Genbank database

(Appendix). For some intercrop species, sequence data was not available for both gene regions; in these cases, we selected a congeneric species where both sequences were available. Sequences were aligned using the MAFFT (Katoh et al., 2002) plug-in in

Geneious v.7.0 (Biomatters, Ltd.). Phylogenetic relationships among species were inferred from the concatenated matrix of the two genes using MrBayes v.3.2.2 (Ronquist and Huelsenbeck, 2003). We used jModelTest2 (Darriba et al., 2002) to determine appropriate models of nucleotide evolution for each region, we selected the GTR+I+G substitution model for the entire dataset, which was partitioned by gene to allow for independent parameter estimation. The Markov chain Monte Carlo (MCMC) algorithm was run for 10 million generations with one cold and three heated chains, starting with randomly generated trees. The output of this analysis was visually inspected using Tracer v1.5 (Rambaut and Drummond, 2004) and the first 10% of the sampled trees were discarded as burn-in. The resulting data from the four runs were combined to generate a majority-rule consensus tree and posterior probability support values. Pairwise percent identity values for all species were calculated in Geneious using the sequence data from the two-gene matrix.

Data analysis. In order to test whether there was a significant difference in larval numbers on the host plant, B. oleracea group Italica, we tested whether average larvae

abundance per plant differed among the treatments using an ANOVA (Figure 4) in JMP

Pro 11.2 (SAS Institute, Cary, NC). Following a square root transformation to correct for the over dispersion in the data, the residuals for the count data followed a normal distribution, enabling us to use an ANOVA. We used a Dunnett’s Test to compare means between the control group and each intercrop treatment. The Dunnett’s Test was used to determine whether each intercrop treatment was significantly different than the control treatment. To answer which intercrop treatments resulted in lower C. nasturtii larval densities, we performed a Tukey Test. The Tukey Test allowed us to visualize which intercrop treatments were more similar to each other and to the control treatment.

In order to determine whether the physical size of the intercrop influenced larval density on the host plant, we performed three ANCOVA tests comparing the square root of larval counts to the height of the intercrop, the total leaf area of the intercrop, and the proportion of the leaf area of each intercrop to the leaf area of the host plant. In order to test whether the vegetation type (herb, vegetable, or groundcover) of the intercrop influenced larval abundance, we grouped the treatments by plant categories and examined if vegetation type influenced larval abundance using an ANOVA to compare means

(Figure 5). Because the average larval counts were not normally distributed, we performed a square root transformation. In order to test whether plant relatedness influenced larval abundance per plant, we regressed the square root of average larval counts against phylogenetic distance (Figure 6). . , usingused the pairwise percent identity values calculated in the phylogenetic analysis for the bivariate regression.

2.2 Results Contarinia nasturtii adults oviposited on their host plant in a majority of treatments, which indicates that adult midges were able to successfully mate within the mesocosm cages and the conditions within the mesocosm cages were suitable for C. nasturtii host plant acceptance. Additionally, eggs developed and hatched on plants in the growth chamber, indicating that growth chamber conditions were conducive to C. nasturtii growth and development.

We first questioned whether non-host plants planted as intercrops affect C. nasturtii larval densities on host plants. We found that larvae densities significantly varied between treatments (p < 0.01). Two intercrop treatments had significantly higher larval densities and two intercrop treatments had significantly lower larval densities than the control treatment (Table 3). Mean larval density found broccoli plants grown next to

Asarum canadense (p < 0.05) and Salvia officinalis (p < 0.01) treatments were significantly higher than the control mean while the Lobularia maritima (p < 0.01) and

Nigella damascena (p < 0.01) treatments had mean larval counts that were significantly lower than the control mean (Table 3). We only found larvae on B. oleraceae. Although we searched non-host plants, we were unable to detect larvae on non-host plants.

We questioned whether the height or leaf area of the non-host plant significantly affects larval densities. Neither the height of the intercrop (p=NS), the leaf area of the intercrop (p= NS), nor the proportion of leaf area of the intercrop to the host plant (p= NS) showed significant association with larval abundance on B. oleracea.

We questioned whether vegetation type was associated with larval densities.

Vegetation type of the non-host species significantly (p < 0.01) influenced larval

abundance on the host plant in our study (Figure 5). Brassica oleracea planted next to groundcover vegetation for all treatments type had the lowest mean larval abundance, followed by vegetable intercrop treatments. The highest larval abundance was on host plants in herb intercrop treatments (Table 4).

We questioned whether the phylogenetic distance between the host plant and the intercrop influenced larval densities. We did not find that phylogenetic distance of the intercrop treatments to the host plant significantly influenced larval numbers on the host plant (p=0.09). Contrary to our expectations, there was a positive trend of increasing larval densities to increasing phylogenetic distance of the non-host plant from the host plant (Figure 6). The positive trend between phylogenetic distance and larvae density remained even when analyzing the dataset without the two closest related non-host plants,

I. umbellata and L. maritima.

2.3 Discussion Intercropping has been considered to be a promising but oftentimes elusive pest management strategy. Although there has been considerable interest in understanding how successful intercropping systems function, the plant attributes and the particular plant species that would be ideal as intercrops for a primary target species have largely been overlooked. In our simulated intercropping experiments, we found that particular plant species influenced the number of C. nasturtii larvae on the targeted broccoli plants.

This indicates that species identity of the intercrop plant can alter the attractiveness of the host plant for a specialist insect pest. We also found that different plant species showed different levels of repulsion and vegetation type was most strongly associated with the

repulsive effect. The treatments with the lowest numbers were L. maritima and N. damascena.

Given that the groundcover vegetation type had the greatest repulsive effect, it is likely that the amount of vegetation that is covering the ground between host plants influences host finding behavior. Visual camouflage of intercrop plants has been documented in previous studies (Finch & Kienegger, 1997; Smith, 1976) and is based on the idea that specialist insects have an easier time finding their host plants against a background of bare soil. The color of the intercrop and the amount of cover may influence the masking of the host plant (Finch & Collier, 2000). Finch and Kienegger

(1997) showed that the color of the intercrop was an important component in host finding ability. They used both living and desiccated clover plants as intercrops to test the repellency against the cabbage root fly (Delia radicum), the diamondback moth (Plutella xylostella), and the large white butterfly (Pieris brassicae) and found no difference in larval numbers between the desiccated plants and bare soil (Finch & Kienegger, 1997).

Smith (1976) noted that specialist insects prefer a background of bare soil than between- row vegetation.

Specialist insects locate their host plants by responding to visual and chemical components of their host plant. Specific chemical compounds emitted as VOCs are sought by the specialist insect and these chemical blends are unique to plant species.

Because it is unclear whether insects are able to detect non-host volatiles and whether there is a repulsive effect if they are able to detect non-host volatiles, it is unclear whether phylogenetic distance can be used to construct diverse plant communities that are able to repel herbivorous insects within agricultural settings. We were unable to show a

relationship using phylogenies as a guiding principle as there was not a significant relationship between larval abundance and relatedness of the intercrop used in each treatment to the host plant.

Our research supports neither the theory of chemical repellency suggested by

Poveda and Kessler (2012) nor the theory of physical obscuration suggested by Finch and

Collier (2011). If physical obscuration was supported, we would have seen a correlation between plant height or leaf area and larval abundance. There were different levels of repellency between different plant species but there was no trend in phylogeny or in plant height or leaf area with larval abundance. A visual camouflage theory would best explain the correlation between groundcover repellency and larval numbers.

Our study indicates that groundcover is more successful at repelling C. nasturtii as intercrop plants than herbs or vegetables. This information is useful to begin to narrow down possible intercrop choices. We tested a wide range of potential intercrop plants within simulated intercropping systems in the laboratory. It is highly possible that these patterns may not be entirely consistent in the field.

When properly designed, intercropping systems can be an effective and economical form of insect pest control. However, more experimental guidance is needed in so that a clear methodological approach to designing a plant community that has the ability to ward off insect pests in an agricultural setting is possible. Research in the area of insect-plant interactions has provided much support in understanding the underlying mechanisms behind intercropping success. Additional research is needed to understand how these complex ecological interactions may be applied to field settings.

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Tables Table 1

Non-host Plants Common Vegetation Phylogenetic Name Scientific Name Plant Family Type Distance Sage Salvia officinalis Lamiaceae Herb 30.26 Leeks Allium porrum Amaryllidaceae Vegetable 37.91 Lycopersicon Tomatoes esculentum Solanaceae Vegetable 28.32 Fagopyrum Buckwheat esculentum Polygonacea Groundcover 35.33 Alyssum Lobularia maritima Brassicaceae Groundcover 3.98 Chamaemelum Chamomile nobile Asteraceae Herb 29.04 Candytuft Iberis umbellata Brassicaceae Groundcover 5.10 Clover Trifolium pratense Fabaceae Groundcover 31.03 Cymbopogon Lemongrass flexuosus Poaceae Herb 45.82 Ginger Asarum canadense Aristolochiaceae Herb 29.77 Pepper Capsicum annuum Solanaceae Vegetable 28.24 Squash Cucurbita pepo Cucurbitaceae Vegetable 24.83 Abelmoschus Okra esculentus Malvaceae Vegetable 22.14 Basil Ocimum basilicum Lamiaceae Herb 30.09 Sorrel Rumex acetosa Polygonacea Herb 32.84 Valerian Valeriana officinalis Valerianaceae Herb 31.69 Nigella Nigella damascena Ranunculaceae Herb 29.86 Coriander Coriander sativum Apiaceae Herb 27.80 Oats Avena sativa Poaceae Groundcover 46.78 Petroselinum Parsley crispum Apiaceae Herb 27.39 Note. Phylogenetic distance is the percent difference in DNA base pairs for rbcL and matK genes from the host plant, broccoli.

Table 2

Plant Maturity Calculation and Planting Procedure Approx. Days of Common Days to Growth Before Planting Name Maturity Introduced to Midges Procedure Seed Company High Mowing Sage 90 59 TP, 6-cell pot Seeds High Mowing Leeks 135 89 TP, 6-cell pot Seeds High Mowing Tomatoes 85 56 TP, 10.2cm pot Seeds High Mowing Buckwheat 55 36 DP Seeds Alyssum 160 106 TP, 10.2cm pot Outside Pride Chamomile 75 50 TP, 10.2cm pot Seeds of Change Candytuft 160 106 TP, 10.2cm pot Outside Pride High Mowing Clover 160 106 TP, 10.2cm pot Seeds Lemongrass - - SD, DP Horsford's Nursery Ginger - - SD, DP Horsford's Nursery High Mowing Pepper 85 56 TP, 10.2cm pot Seeds High Mowing Squash 50 33 DP Seeds High Mowing Okra 55 36 TP, 10.2cm pot Seeds High Mowing Basil 70 46 TP, 6-cell pot Seeds High Mowing Sorrel 120 79 TP, 6-cell pot Seeds Valerian 75 50 TP, 10.2cm pot Outside Pride Horizon Herbs Nigella 95 63 TP, 6-cell pot LLC High Mowing Coriander 55 36 DP Seeds High Mowing Oats 55 36 DP Seeds High Mowing Parsley 70 46 TP, 6-cell pot Seeds High Mowing Broccoli* 70 46 TP, 6-cell pot Seeds Note. SD=seedling. DP=directly planted into oval pots with broccoli seedlings. TP=transplanted into oval pot, followed by the type of pot originally seeded. Days to maturity published in the referenced seed catalog. Days of growth before being introduced to midges=days to maturity x 0.66. *Broccoli is the host plant.

Table 3 Significant Treatments Treatment Mean Larvae Standard Deviation Significance Value Sage 4.30 ± 2.33 < 0.0001 Ginger 3.16 ± 1.71 0.0236 Alyssum 0.44 ± 0.54 0.0017 Nigella 0.40 ± 0.58 0.0011

Table 4 Vegetation Type Results Plant Type Mean Standard Deviation Groundcover 1.08 ±0.94 Vegetable 2.07 ±1.53 Herb 2.16 ±1.85

Figures

Figure 1.Monocrop (a) and intercrop (b) simulation set-up. B=broccoli. NHI=non-host intercrop.

Figure 2. Phylogenetic tree of food-based plant families. *Plant families represented in this study.

Figure 3. Phylogenetic tree of host and non-host plants. Cymbopogon flexuous sis the grounding node.

Figure 4. ANOVA of larvae density by treatment.

Figure 5. ANOVA of larvae density by vegetation type.

Figure 6. Bivariate regression of larvae density by phylogenetic distance. Solid line represents best fit line.

Appendix Appendix Accession Numbers for Genes Used in Phylogenetic Analysis Plant Species rbcL gene matK gene Fagopyrum esculentum AB093087 JN187116 Noccaea oppositifolia EU371819 HE616647 Juglans nigra U92851 U00437 Lindera benzoin FJ408866 AY337732 Litchi chinensis EU720564 AY724361 Lobularia maritima NC009274 NC009274 Malus baccata var. baccata GU363775 JQ391376 Matricaria matricarioides AF151481 HM850160 Morus alba AY257531 JN407320 Musa velutina FJ871653 JX978673 Nigella damascena FJ626504 HM850201 Ocimum basilicum AF315306 Z37424 Olea europaea AJ429335 DQ673304 Petroselinum crispum U58575 HM850248 Rubus idaeus KM036845 U06825 Rumex acetosa KF509934 AY395559 Salvia officinalis JQ934074 AY570431 Solanum lycopersicum AM087200 KJ652188 Trifolium pratense JN894446 HM850419 Vaccinium macrocarpon U61316 L12625 Valeriana officinalis AY362532 L13934 Vitis riparia KJ841042 AF119174

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