Arthropod Abundance and Diversity in x giganteus, virgatum, and

Other Types in Southeastern Ohio

A thesis presented to

the faculty of

the Voinovich School of Leadership and Public Affairs of Ohio University

In partial fulfillment

of the requirements for the degree

Master of Science

Taylor L. Snelick

May 2018

© 2018 Taylor L. Snelick. All Rights Reserved. 2

This thesis titled

Arthropod Abundance and Diversity in , , and

Other Habitat Types in Southeastern Ohio

by

TAYLOR L. SNELICK

has been approved for

the Program of Environmental Studies

and the Voinovich School of Leadership and Public Affairs by

Kelly S. Johnson

Associate Professor of Biological Sciences

Mark Weinberg

Dean, Voinovich School of Leadership and Public Affairs

3

ABSTRACT

SNELICK, TAYLOR L., M.S., May 2018, Environmental Studies

Arthropod Abundance and Diversity in Miscanthus x giganteus, Panicum virgatum, and

Other Habitat Types in Southeastern Ohio

Director of Thesis: Kelly S. Johnson

Bioenergy could help reduce CO2 emissions from agriculture that contribute to climate change, while at the same time supply energy to a growing population. Varying levels of inputs within crop fields, such as use or annual tilling, can impact arthropod and abundance. The research presented here examines the impact of habitat type (Miscanthus x giganteus, Panicum virgatum, abandoned agriculture, and forested edge) on the diversity and abundance of in small

(The Ridges Land Lab) and larger (The Wilds) planted plots in southeastern Ohio. A variety of collection methods (sweep nets, flight traps, and Berlese funnels) were used over a three month period to collect arthropods from different trophic groups. Overall,

25,390 arthropods were captured with the highest abundance consistently seen in forested edge , followed by abandoned agriculture, switchgrass, and lastly miscanthus.

Flying found in the forested edge were three fold more abundant than those found in miscanthus plots, with intermediate levels in switchgrass and abandoned agriculture.

Dominant flying arthropod groups included hoppers, flies and rove beetles.

Abundance of litter arthropods was almost two fold higher in switchgrass than in miscanthus plots: dominant taxa included oribatid mites, ants, ground beetles, and collembolans. Taxonomic richness and Shannon diversity were lower in litter samples 4 compared to flight/ sweep samples. Compared to forested edges, miscanthus supported fewer omnivores, pollinators, and predator/parasites. Detritivorous arthropod abundances did not differ across habitat types. No significant differences were noted between arthropod diversity and abundance between the larger fields of grasses at the

Wilds compared to the Ridges Land Lab. This current study shows that cellulosic crop type does have an impact on arthropod communities; with miscanthus consistently supporting the least diverse and lowest arthropod abundances compared to more diverse natural areas such as forested edges. This project is meant to be a relative measure of arthropod diversity and abundance in two different size field settings in Southeastern

Ohio and results may be different in other field settings.

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DEDICATION

This thesis is dedicated to my parents, Lisa Ann and John Gregory Snelick, whose love, unselfish support, and example over my lifetime laid the foundations for the discipline

necessary to complete this work.

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ACKNOWLEDGMENTS

This thesis could not have been completed without the knowledge and wisdom provided to me from my advisors, Kelly Johnson, Sarah Davis, and Arthur Trese as well as the support of other faculty and staff at the Voinovich School. I thank you all for your continued support over the course of this project. The tremendous amount of field work and arthropod identification could also not have been done without the help from undergraduate assistants, Tristan Hoffman, Lillian Rudolf, and Monica Ciszewski.

I thank my roommates and friends over the past two years for keeping me sane through this process as well as listening to me practice my presentations and speeches over and over again; Nina Fuller and Johanna Ansel. I thank my partner, Scotty Farey, for his unfailing love, support and continuous encouragement as I completed my degree.

My has raised me to be the person I am today and without their support I would not have made it through my undergraduate and graduate careers. My family’s love for the outdoors and all living things is what embedded in me love for the environment in the first place. I thank my dad for letting me use his car as I traveled to and from college, and my mom for letting me store my bugs in her freezer every time I came home. I thank my youngest sister, Brooke Snelick, for sitting with me as I sorted my arthropods for countless hours that could have been spent playing games with her instead. I have had the pleasure of seeing my sister, Jordan Snelick, transformed into a student professional herself at the Voinovich School as we attended our last year of college together; she also created the ArcGIS maps for this thesis.

Thank you, all. 7

TABLE OF CONTENTS

Page

Abstract ...... 3 Dedication ...... 5 Acknowledgments...... 6 List of Tables ...... 9 List of Figures ...... 10 Chapter 1: Literature Review ...... 11 1.1 Introduction to : and ...... 11 1.2 Current Trends in Biofuel Crop Production ...... 16 1.2.1 Development of Biofuel Policies Abroad and in the US ...... 16 1.2.2 Available American Cropland ...... 17 1.3 Global Arthropod Declines ...... 18 1.4 Arthropod Community Dynamics in Biofuel Feedstocks ...... 19 1.4.1 Miscanthus x giganteus ...... 20 1.4.2 Panicum virgatum ...... 21 1.4.3 Abandoned Agriculture and Forested Areas ...... 22 1.5 Decision Making and Adaptive Management...... 23 Chapter 2: Arthropod Abundance and Diversity in Miscanthus x giganteus, Panicum virgatum, and Other Habitat Types in Southeastern Ohio ...... 26 2.1 Introduction ...... 26 2.2 Methods...... 28 2.2.1 Study Areas ...... 28 2.2.2 Experimental Design ...... 31 2.2.3 Sampling Methods ...... 32 2.2.4 Arthropod Identification and Counting ...... 34 2.2.5 Statistical Methods ...... 34 Chapter 3: Results ...... 36 3.1 Summer Sampling Event: The Ridges Land Lab ...... 37 3.1.1 Impact of Habitat Type on Total Arthropod Number ...... 37 3.1.2 Impact of Habitat Type on Family Level Richness ...... 39 3.1.3 Impact of Habitat Type on Arthropod Diversity...... 43 8

3.1.4 Impact of Habitat Type on Trophic Groups ...... 45 3.2 September Sampling Event: The Wilds ...... 47 3.2.1 Impact of Habitat Type and Site on Arthropod Abundance ...... 48 3.2.2 Impact of Habitat Type on Family Level Richness ...... 49 3.2.3 Impact of Habitat Type on Diversity ...... 50 Chapter 4: Discussion ...... 51 4.1 Summer Sampling Event ...... 51 4.1.1 Arthropod Abundance and Family Richness related to Habitat Type ...... 51 4.1.2 Arthropod Diversity Related to Habitat Type ...... 53 4.1.3 Trophic Group Response to Habitat Type ...... 54 4.2 September Sampling Event ...... 56 4.2.1 Diversity and Abundance between The Wilds and The Ridges Land Lab .. 56 Chapter 5: Limitations, Recommendations, and Conclusions ...... 58 5.1 Limitations and Recommendations...... 58 5.2 Conclusions ...... 59 References ...... 61 Appendix: Tables for diversity and abundance of Athropods ...... 68

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LIST OF TABLES

Page

Table 1. Crop Comparision Chart ...... 15 All other tables are compiled in the Appendix for brevity in presentation.

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LIST OF FIGURES

Page

Figure 1. The Ridges Land Lab Site Aerial View...... 29 Figure 2.The Wilds Site Aerial View...... 30 Figure 3. Biofuel Crop Arrangement at The Ridges Land Lab...... 31 Figure 4. The Ridges: Flight Trap Abundance...... 38 Figure 5. The Ridges: Berlese Abundance...... 39 Figure 6. The Ridges: Flight Trap Rarefaction ...... 40 Figure 7. The Ridges: Berlese Rarefaction...... 41 Figure 8. The Ridges: Flight Trap Family Richness...... 42 Figure 9. The Ridges: Berlese Family Richness...... 42 Figure 10. The Ridges: Flight Trap Shannon Diversity...... 44 Figure 11. The Ridges: Berlese Shannon Diversity...... 45 Figure 12.Trophic Group Abundances ...... 47

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CHAPTER 1: LITERATURE REVIEW

This section focuses on the need for a paradigm shift to encourage biodiversity in all aspects of biofuel production by industrial farmers and local farmers alike. The first section, Introduction to Biofuels: Cellulosic Ethanol and Biodiesel, reviews how biofuels are used in today’s transportation systems. The second section reviews funding within the

US for biofuel production and the current status of dedicated biofuel crops currently in agriculture. The third section summarizes previously studied commonalities of arthropod biodiversity characteristics within the habitat types studied here (Miscanthus x giganteus,

Panicum virgatum, abandoned agriculture, and forested edge). The last section of the literature review calls on the importance of adaptive management within agricultural practices both industrial and small scale. This review of literature should provide contextual background knowledge for this research project.

1.1 Introduction to Biofuels: Cellulosic Ethanol and Biodiesel

From heat and power to fuels for transportation, biomass has been used by humanity for thousands of years. Biomass is most commonly referred to as the solid material from any biological organism that can be harvested or collected (Davis, 2014).

Coal has historically been used to heat houses and produce . Long term use of and fossil fuels over the past five decades has increased CO2 emissions all over the planet and in turn has increased public and government support for more studies into alternative fuel sources (EIA, 2013). Alternative fuel sources such as bioenergy derived from could help reduce CO2 emissions that contribute to climate change, while at the same time supplying energy to a growing population (Sartori et. al., 2006). 12

Today bioenergy crops range from corn to the production of advanced cellulosic feedstocks such as switchgrass and miscanthus to photosynthetic algae (Table 1).

Different feedstocks can produce different types of fuel; diesel replacement comes from biofuel sources such as biodiesel and replacements come from biofuel sources such as ethanol. Biodiesel is produced from oils or fats using transesterification (usually from ), or from pure oil typically derived from vegetable oils (EIA, 2013).

Ethanol is produced from the fermentation of sugars within grains (usually corn) or cellulosic sources (plant tissue) and is an alcohol that has been added to gasoline fuels for decades. Not only does ethanol come from renewable resources, but it has an increased oxygen concentration which results in a more complete and a decrease in exhaust emissions (Regulbuto, 2009). Ethanol from corn and biodiesel from soybeans are the two most common biofuels on the market in the US today and although these are the easiest sources to convert fuel from, they are probably the worst environmentally (Table

1).

Negative environmental impacts of bioenergy production can be avoided by emphasizing the importance of conservation of ecosystems, reduced life cycle greenhouse gas (GHG) emissions, and increased net energy gains. The main characterizations for successful bioenergy production as outlined by Davis et al (2013) include, but are not limited to: low input requirements, low soil emissions, low cost, easy establishment and tolerance of variable weather conditions, high use efficiency, and ecosystem service provisions. There is great interest in identifying and combining the 13 conditions in which sustainable bioenergy might be produced, and yet best practices are still being developed and revised.

Land use history and land use changes are an important component in the management swing potential for reducing GHG emissions in agricultural production of energy crops (Davis et al. 2013). There is a challenge to avoid expansion onto forest land and avoid competition with agriculture for food. Changing a once biodiverse forested landscape to a field of corn can affect ecosystem functions and contribute a large flux of

CO2 to the atmosphere that was once stored in the forest canopy; changing a forest to a has very different implications than changing to a corn field (Hertel et. al.,

2010). Biodiversity has many important roles in ecosystem structure and function and eliminating resources such as habitat cover or food could negatively affect an ecosystem

(Semere and Slater, 2006, Thomas and Marshall, 1999, Uchida et. al., 2016).

Most industrial agriculture today is done in large scale mono-cropping which has production advantages because it is easier to process homogeneous biomass products than to separate out a mixture for conversion into fuel. One downside is that a monoculture can reduce habitat diversity for that previously occupied the landscape. On the other hand, intercropping can be used to incorporate two or more crops in the same field to maintain biodiversity and provide other ecological benefits. Larson

(2016) found that planting switchgrass in a pine plantation increases biodiversity compared to traditional pine plantations by providing both young, open pine and habitat, not only for arthropods but for higher trophic levels such as the cotton rat that depend on insects for food. Reptiles, amphibians, and birds could also benefit 14 from more diverse arthropods as food sources. Introducing intercropping in a once monocropped field can be a successful management practice that provides a , has environmental benefits, and is producible without reducing feed crops, all characteristics of a successful alternative fuel source. 15

Table 1: Biomass Crop Comparison Chart (Davis et. al. 2014) Corn Microscopic Crop Name Switchgrass Miscanthus Crop Residue Oil Palm Grain Residue Algae Annual Perennial Perennial Wastes from Annual from Perennial C4 C4 C4 timber Micro-crop Type of Crop C3 cereal crops C3 Grain Leaf/stem Stem and processing Algae lipids Oil etc. Oil Seed Starch Cellulose etc. Biopower, Biopower, Biopower Biopower, Bioethano Fuel Type Biodiesel Lignocellulosic Lignocellulosic Lignocellulosi Lignocellulosi Biodiesel Biodiesel l ethanol ethanol c ethanol c ethanol 54°N- Latitude 52°N-39°S 55°N-17°N 56°N-37°N - - 15°N-12°S - 34°S Tolerates wide Best on Best on Clay Dislikes heavy clay; Once established, range of pH; medium- loam; best on water- Suitable Soils tolerant of most - - best in sandy - textured moderately retentive soils; also soils soils with good soils salt-tolerant good on drainage Low-Moderate 450 Water High, esp. in Moderate Moderate minimum but will High 2,000- requirement Moderate 520-750 - - raceway 670-800 600 use more when 2,500 (mm) systems available Germinates above Optimum Shoots grow above Optimum 24- Temperature 10°-40°C 8-10°C, optimum - - 20-30°C 24-30°C 7°C 28°C 25-30°C N:145-200 N: 0-70 N: 50-168 N: 0-92 N: 114 Needs only N requirement P:26-110 P: 32-155 P: 0-35 P: 0-13 - - P: 14 and P in ratio (kg/ha/yr.) K:25-130 K: 30-320 K 0-45 K: 0-202 K: 149 4-45N:1P Range of Range of Generally not Generally not Range of Pesticide Use - - - Pesticides needed needed pesticides Global 18 (Europe) 2.9 (seed), 14 (fruit), 2.9 Average Yield 5.2 dry 14 dry 38 () - - Unknown 0.44(oil) (oil) (tonnes/ha/yr.) dry Area Currently in 1.6 billion 270 million 160 99 Unknown Unknown 15 - Cultivation tonnes/y tonnes/y (million ha) 16

1.2 Current Trends in Biofuel Crop Production

1.2.1 Development of Biofuel Policies Abroad and in the US

Over the past two decades, biofuel production has experienced a roller coaster of unstable markets in the US because of policy mandates and economic activity. The goal for these policies is to reduce GHG emissions thus reducing the effects of climate change in every region of the world. The Paris Agreement of 2016 is first time the US has ratified an international agreement to reduce GHG emissions. In the US, policies have a large influence on how energy is produced and exactly which type of feedstocks can be utilized to produce energy. A large driver for alternative energy production was the

Energy Policy Act of 2005 which introduced the Renewable Fuel Standard 1 of which a later revision would bring about the Renewable Fuel Standard 2 (RFS 2) of 2010. The

RFS 2 mandated that 36 billion gallons of ethanol be produced by 2022, 15 billion of which could come from but the rest must be from advanced biofuel feedstocks (EPA, 2013). These feedstocks must have at least a 50% reduction of life cycle greenhouse gases produced to be considered advanced.

In the current bioeconomy, advanced cellulosic energy is produced by agricultural residues only (i.e. any material left in a field after a crop has been harvested) and all ethanol produced in the US is from corn grains only (US DOE, 2016). Miscanthus and switchgrass are projected to be two of the most abundant cellulosic feedstocks potentially available by the year of 2040 because of policy mandates requiring an increase in advanced cellulosic fuel sources (US DOE, 2016). Of these sources, miscanthus 17 production is expected to be around 160-370 million dry tons and switchgrass around

161-189 million dry tons by 2040 (US DOE, 2016).

A downside to clean energy policies is they often hurt the economy because CO2 emissions and the economy are closely related. Policy mandates such as the Clean Power

Plan of 2014 (CPP) required a 32% CO2 emissions reduction (relative to 2012 emissions) from units (EPA, 2013). Coal production is declining for a variety of reasons including policies such as the CPP therefore novel bioenergy production systems such as renewable biofuels have a market hole to fill. is replacing coal in most cases and GHG emissions are decreasing, but not enough (EIA, 2017).

Using an alternative fuel source, such as advanced cellulosic biofuels, is one way to move towards separating and economic activity.

1.2.2 Available American Cropland

In to meet fuel standards set forth by the EPA by 2022, land must be used for biofuel production and this often raises concerns with producing enough food for a growing human population. It is unlikely that additional prime agricultural land will be used in response to increased demand for biofuels. In 2012, 74.7 million acres of the total crop land in America was not harvested (U.S. Census Bureau, 2012). Of these unharvested acres, 12.8 million were used for pasture, leaving the remaining 61.9 million acres with the potential to grow biofuel crops (U.S. Census Bureau, 2012). Therefore, there may be significant opportunities to use these “idle” acres to grow advanced energy feedstocks for biomass production (U.S. Census Bureau, 2012). 18

Emery et. al. (2017) examined the spatial distribution of land in the US complying with several key idle land definitions among a variety of studies to identify regions for feedstock production. Among all studies and land definitions compared, Emery et. al.,

(2017) concluded that the most prevalent “idle” land type is abandoned cropland, with

26% of counties in the US containing over 20% land area which may once have been cropland that is no longer in market rotation. With all this in mind, it is important to note that unmanaged abandoned agricultural areas exhibit the highest abundance and diversity of insects relative to managed crop fields such as industrialized food agriculture (Altieri and Schmidt1986, Hendrickx et al., 2007, Diekotter et. al., 2008, Landis and Werling,

2010). A deeper look into the interactions of arthropods in abandoned agriculture, forested areas, miscanthus, and switchgrass will be discussed in the next section of this review.

1.3 Global Arthropod Declines

Hallman et. al., (2017) described a more than 75% decrease in flying populations in over the duration of a 27 year study. The areas of interest used during this study were not agricultural areas, rather 63 different nature protection areas.

What is the cause of this dramatic decline of such an important part of the food web, especially in areas meant to protect these species? The study shows that this decline could not be attributed to habitat type, weather, or land use alone (Robinet and Roques, 2010,

Hallman et. al., 2017). There is also a great level of concern for the consequences of pollinator decline in both natural and agricultural environments. Globally, pollinator populations are declining due to a combination of habitat loss and fragmentation from 19 agriculture, pesticide use, parasites, and stress from transportation of commercially raised bee colonies (Grixti et al., 2009, Cox-Foster et al., 2007, Mullin et al., 2010, Ellis et al.,

2009). In the autumn of 2006, beekeepers across the US reported losing 30-90% of their colonies, a phenomenon today known as “Colony Collapse Disorder” (Ellis, 2009).

Declines in bumble bee populations have serious ecological implications, as well as economic consequences. Likewise, monarch butterflies have experienced a decline by

>80% within the last two decades because of a shortage of milkweed plants, being their offspring’s main source of food (Thogmartin, 2016). Approximately 98% of the loss of more than 861 million milkweed stems disappearing from the Midwestern US since 1999 is attributed to the spread of tolerant corn and soybean crops, some of which can be attributed to the increased market for biofuels (Pleasants, 2017). Agricultural lands are essential in reaching restoration targets for monarchs because they occupy 77% of all potential monarch habitats (Thogmartin, 2016). It is because of these declines that scientists, politicians, and the general public have shown increased interest in the status of arthropods around the world.

1.4 Arthropod Community Dynamics in Biofuel Feedstocks

There are a variety of feedstocks with different biotic and abiotic tolerances available for biofuel production. Replacing poorly performing crops that require many biophysical inputs with better alternatives that can be grown on water-logged or arid lands is a benefit of alternative biofuel sources (Davis, 2014). Different alternative fuel crops may have variable impacts on arthropod communities. Landis and Werling (2010) review the literature on arthropod community dynamics within dedicated biofuel crops 20 extensively. The following sections highlight some of their findings, as well as other literature on community dynamics and commonalities in arthropod community composition within the crops studied here.

1.4.1 Miscanthus x giganteus

Miscanthus x giganteus (miscanthus) is a cellulosic tall grass that has been studied for its potential for biofuel production in Europe since the 1960s and has since then been introduced to the US (Lewandowski et. al., 2003). It has a low risk of invasion to surrounding areas because it is a sterile . Miscanthus sequesters more carbon relative to other cellulosic grasses as it grows to be about 4 meters tall. A wide variety of invertebrates inhabit miscanthus stands. In one study on the arthropod community of miscanthus, Semere and Slater (2007) sampled ground beetles, butterflies and other invertebrates in reestablishing miscanthus stands following harvest in England.

It was noted in this study that open canopy stands (i.e. younger stands) influence a larger diversity of insects than older miscanthus stands with closed canopies. Similarly,

Lewandowski et. al. (2003) noted that in their 4 meter tall miscanthus stands, insect abundance was much less compared to younger stands with more weedy diversity (i.e. and other grassy type ).

Most studies that look at arthropod populations in miscanthus focus on the pests that may live in this grass because miscanthus has historically had a role in insect- vectored plant viruses. An extensive 3-year survey in the United Kingdom of invertebrates in miscanthus found, “no major pests” to inhabit the biofuel crop (Semere and Slater, 2007, Landis and Werling, 2010). Many other groups observed different pests 21 that have been known to feed on/live in miscanthus or spread to surrounding crops and damage them. Prasifka et. al., (2009) found that the fall armyworm (Spodoptera frugiperda) can live in miscanthus and the grass can be a potential host for the fall armyworm especially if it is planted by fields of corn. Huggett et al. (1999) reported that the corn leaf aphid, Rhopalosiphum maidis colonized miscanthus in the greenhouse and produced the most offspring on established rhizomatous Miscanthus x giganteus plants relative to seedling stages of . Other studies have found corn leaf aphids to be pests because they can also live in the miscanthus and be reservoirs of insect-vectored plant viruses in surrounding crops (Bradshaw et. al., 2010). Miscanthus can accumulate high silicon content that is not easily digestible for many herbivores and for this reason many times miscanthus is mostly a reservoir for potential pests.

1.4.2 Panicum virgatum

The US Department of Energy has been developing switchgrass, Panicum virgatum as a biomass crop since the early 1990s (McLaughlin & Kszos, 2005). Parrish et. al. (1999) found that in Virginia, newly planted switchgrass seedlings were vulnerable to insects such as grasshoppers, crickets, and corn flea beetles especially when the switchgrass was planted in pre-existing vegetation killed specifically for biofuel establishment. Studying these interactions could influence development of of biofuel crops for resistance to insect susceptibility in the future.

Schaeffer et. al. (2011) characterized the arthropod community associated with switchgrass in a 23 ha field and 0.6 ha field in Nebraska. They found eighty-four families of arthropods within their collection sites and divided them into three categories (i.e. 22 incidental arthropods, potential pests, and beneficial arthropods). In this study

Thysanoptera, Hymenoptera, and Coleoptera were the most abundant orders representing over 80% of the specimens collected. Holguin et. al., (2010) found that diversity of different trophic groups, such as predators and herbivores, varied within switchgrass itself across dates and sampling methods (i.e. pitfall traps and sweep nets).

1.4.3 Abandoned Agriculture and Forested Areas

Arthropod communities in abandoned agriculture and forested areas were examined here in the abandoned agricultural field and forest surrounding the biofuel crop plots. In general, abandoned agriculture or forested areas include fields where crops may have failed and cover crops are used for soil improvement. They could also be land enrolled in Conservation Reserve, Wetlands Reserve, Farmable Wetlands, or

Conservation Reserve Enhancement Programs (U.S. Census Bureau, 2012). These low- input high diversity areas could produce conservation benefits for multiple arthropod groups that contribute to important ecosystem services appreciated by humans (Landis and Werling, 2010, Marshall et. al., 2003). One of these benefits includes biocontrol which is the beneficial predator prey relationship that reduces the need for pesticides.

Biocontrol provided by these living organisms, collectively called “natural enemies,” is especially important for reducing the numbers of pest insects and mites. Natural enemies can also prey on or parasitize arthropod herbivores that could be considered pests because they are eating the biofuel crops thus reducing biomass accumulation. More diverse perennial habitats support greater abundance and diversity of natural enemies than annual monocrops (Werling et. al., 2011, Tscharntke and Geiler, 1995, Gardiner et. al., 2009, 23

Schmidt and Tscharntke, 2005). Other ecosystem services include arthropods as pollinators, food for other organisms, and those at the soil surface that participate in leaf breakdown and nutrient cycling.

In general, increasing biodiversity correlates with decreasing intensity of management practices and landscape design. For example, Gardiner et. al. (2010) found that coccinellid (ladybird beetle) diversity was positively correlated with floral diversity and Larsen and Work (2003) found that carabid (ground beetle) diversity in managed fields declined with more management inputs such as time since burning. At the scale of a single crop, a variety of studies similarly suggest that planting polycultures can reduce pest problems and insect-vectored plant diseases, provide stable ecosystems for the persistence of ecosystem services, and increase biodiversity for conservation purposes

(Siemann et. al., 1999, Spencer et. al., 2009, Werling et. al., 2011, Landis et. al., 2008).

The conversion of idle land such as abandoned agricultural and forested areas to biofuel production systems may have damaging effects on the biota that live here as well as the ecosystem services they provide.

1.5 Decision Making and Adaptive Management

Any kind of energy production or land use changes involves trade-offs in costs and benefits that call for adaptive management to provide a mechanism of continuous improvement to address those tradeoffs. When choosing the best crop to be planted for ethanol development, it is important to consider the life cycle of the crop along with all the inputs and outputs for growth and harvest. Biofuels are a more sustainable and environmentally friendly alternative to petroleum based fuels and necessary to reducing 24 carbon-emissions globally. Biofuels hold the promise of supporting local jobs, driving economies and establishing policies to incentivize the industry (German, 2011). Certain policies cannot be expanded over the entire industry because of the obvious differences between large and small--scale operations and different fuel stocks being used in certain regions. Different communities of arthropods are found in different parts of the world so it is important to study the varying interactions between arthropods and the potential biofuel crops they might inhabit.

Diverse communities of arthropods are an important part of ecosystem resilience because varying members of functional groups (i.e. pollinators, detritivores, and predators) respond to uncertainty in different ways. The higher the species richness in a particular landscape, the more likely there will be differences in environmental sensitivity among species that are functionally similar (Chapin III et. al., 1997). Likewise, communities with greater abundance have a higher chance of returning to equilibrium population densities after sudden changes than would communities with lower abundances (Pimm, 1991).

The objective of this study is to test the hypothesis that arthropod abundance and diversity would be higher in habitats that include more floral resources. To examine the role that habitat type (switchgrass, miscanthus, abandoned agriculture, and forested edge) might have on arthropod community dynamics, we use a combination of sampling methods (flight traps, sweep nets, and Berlese funnels) to comprehensively sample arthropods. This study will add to the growing body of knowledge about the interactions among arthropods and land use changes especially since biofuel expansion could alter 25 these interactions. This can help guide strategies and determine trade-offs at the local scale for more diverse agricultural practices and policies that support biodiversity of arthropods and sustain ecosystem services they provide within these crop types (Groom et. al., 2008, Landis, 2017).

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CHAPTER 2: ARTHROPOD ABUNDANCE AND DIVERSITY IN MISCANTHUS X

GIGANTEUS, PANICUM VIRGATUM, AND OTHER HABITAT TYPES IN

SOUTHEASTERN OHIO

2.1 Introduction

Several policy recommendations have been proposed within bioenergy production systems to ensure that crop choices are evaluated throughout their life cycle for total energy inputs and outputs to assess their sustainability (Groom et. al. 2008, Davis et. al.

2009). Previous studies have found that differences among agricultural practices of bioenergy crops and the surrounding landscape can increase diversity of vegetation thus increasing arthropod abundance and diversity (Semere and Slater, 2006, Thomas and

Marshall, 1999).

Natural habitats that surround biofuel cropping systems influence insect diversity and the provisioning of some ecosystem services such as biological control of pests or overwintering sites for the preservation of biodiversity within ecosystems (Semere and

Slater, 2006, Werling et. al., 2011). Invertebrates found in arable crop fields are important food sources for birds, , and other invertebrates thereby contributing to the health and stability of the ecosystem. Improved management practices that effectively maintain biodiversity and ecosystem services (i.e. contributions of ecosystem structure and function to human well-being (Burkhard et. al., 2014)) are necessary to ensure successful development of environmentally production systems. 27

Restoring native habitat can promote the return of biodiversity that could have otherwise been lost in a community. Hedgerows are used around commercial agricultural fields to include a variety of plant species which provide a continuous sequence of vegetation over the flight seasons of many pollinators (M'Gonigle et al., 2015).

Hedgerows are being replaced with barb wire fences and are often left untouched over the course of many years because farmers are preoccupied with their cash crops. A study conducted by M’Gonigle et al. (2015) in the Central Valley of California found that restorations of hedgerows create the conditions that promote persistence of hymenopteran pollinators local to the area of study. Long term yet small-scale restorations like these are important conservation tools for managers when sustaining diverse pollinator and other arthropod populations in agricultural landscapes.

Novel biofuel crops may contain relatively understudied arthropod groups whose life histories and impacts should be considered to proceed successfully in sustainable crop management. In a study conducted by Werling et al. (2011), the effects of landscape composition and habitat type on insect natural enemies in three different biofuel crops grown in Michigan and Wisconsin - corn, switchgrass, and mixed were examined using 23 by 28 cm unbaited, yellow sticky cards. Corn sites ranged from 3 to 121 ha in size while switchgrass and prairie ranged from 2 to 101 ha. The results suggest that landscapes containing a mix of annual and perennial biofuel crops provide habitat for a wider range of insect natural enemies than those composed of any one type of biofuel crop. 28

The research presented here examined the impact of habitat type (miscanthus, switchgrass, abandoned agriculture, and forested edge) on the diversity and abundance of arthropods including insect families and arachnid groups. Arthropods were sampled over one growing season in two biofuel crops (miscanthus and switchgrass) and compared to two existing habitat types (abandoned agriculture and forested edge). Specifically, the impact of habitat type on: arthropod numbers (abundance), family richness, and diversity using Shannon’s Index were investigated to better understand the dynamics between arthropod community composition and environmental impacts of the four habitat types studied.

2.2 Methods

2.2.1 Study Areas

The field sites were located in Athens County, Ohio at Ohio University’s Ridges

Land Lab. The Ridges Land Lab is a biologically diverse natural area for research and education in field biology, environmental geography, and ecosystem ecology (Ohio

University, 2018). There are two study sites in the Land Lab: (1), Radar Hill site

(Latitude 39.32414°, Longitude -82.12593°) and (2) Roadside site (Latitude 39.32094°,

Longitude -82.12068°) (Figure 1). Previous land use at the Ridges was an apple orchard

(1930-1970s) at the Roadside site and a pasture for growing straw and

(1940-1970s) at the Radar Hill site (Ohio University, 2018). The Radar Hill site has soil characteristics of Guernsey silt loam with an 8-15% slope. The Roadside site consists of mostly Upshur silty clay loam with an 8-15% slope (US Climate Data, 2016). Average annual precipitation in Athens County is around 39.58 inches and in the summer months 29 precipitation decreases from 4.06 inches in May to 2.95 inches in September. The miscanthus and switchgrass plantings were established in 2013 as part of a separate research project. Both sites were mowed between the grass plantings and the perennial grasses (miscanthus and switchgrass) are harvested every February. Small subsamples of the plots are also collected in the fall to estimate biomass accumulation.

Figure 1: Bird's eye view of the Ridges Land Lab located at Ohio University in Athens County, Ohio. Roadside and Radar Hill sites are labeled as shown.

Samples were also collected at The Wilds management area located on nearly

4,000 ha of reclaimed surface-mined land in Ohio (Latitude 39.8295°, Longitude -

81.7330°) (Figure 2). The Wilds is mostly used as a preserve in partnership with 30 the Columbus Zoo and Aquarium and from all over the world are brought here to roam free (Skousen, 2014). Another conservation effort at the wilds is to restore much of the surface-mined land into native grass prairie and perennial grasses, including miscanthus and switchgrass. An 8 ha area was selected for switchgrass and miscanthus plantings in April of 2013 and both grasses exhibited excellent establishment rates because of suitable rainfall during the succeeding two months after planting (Skousen et. al., 2014). The samples collected here were used to compare arthropod abundance and diversity between larger and smaller (The Ridges) fields of miscanthus and switchgrass.

Figure 2: Bird's eye view of the 8 hectare area dedicated to switchgrass and miscanthus production at the Wilds in Cumberland, Ohio. 31

2.2.2 Experimental Design

At the Land Lab the two study sites (Radar Hill and Roadside) are replicates of each other. Three plots of each biofuel grass species (miscanthus and switchgrass) were planted in 2013 at each site in randomly assigned 10 meter x 10 meter plots (Figure 3).

This provided a total of 6 miscanthus plots and 6 switchgrass plots. Surrounding the plantings is abandoned agricultural land that is a mix of pasture and early successional trees that includes over 500 floral species (Ohio University, 2018). Arthropod samples in the abandoned agriculture and woodland area were collected at the same times as the biofuel crops for consistency in analysis. There were 6 samples in the abandoned field/agricultural area and 6 samples in the woodland area (3 at each site). While at The

Wilds, 6 samples were collected randomly from each field type, the switchgrass and miscanthus, for consistency in analysis with the Land Lab crops.

Figure 3: Experimental design of the Ridges plantings. M=miscanthus, Sw= switchgrass, BL=fallow black locust, W=fallow willow, So= fallow sorghum. Numbers under plot indicate plot identification number. 32

2.2.3 Sampling Methods

Sampling of arthropods began in May of 2017 using several collection methods, including Berlese funnels for leaf litter, sweep netting, and flight intercept traps (Zou et al. 2012). For the Berlese sample, a small amount of leaf litter (0.25 meter squared area) was collected from the surface of the ground in each of the 10m x 10m plots of biofuel grasses and 3 randomly chosen areas in the agriculture and woodland areas. Litter samples were returned to the lab in clear zip lock bags, stored in the fridge for no longer than 2 days, and processed in a Berlese funnel for 48 hours to allow adequate drying time for the grass. Arthropods escaping the heat and light were collected in 70% ethanol. This method intercepts ground dwelling insects and insects involved in leaf litter .

Sweep netting was conducted by an individual walking along a transect in each plot and sweeping a net over the top of the vegetation to collect flying insects and any insects disturbed off the vegetation. Each transect started at an edge of the 10 x 10 meter plot and went entirely though the plot with 20 sweeps (with back and forth strokes counted separately) taken while walking slowly. This method was used in the same manner at random intervals in the agriculture and woodland areas with 20 sweeps to match that of the biofuel crop samples. Insects collected were stored in gallon sized plastic bags, frozen to kill the arthropods and stored to later be processed.

Flight intercept traps were also used to collect insects flying through the plots over a longer period of time. One intercept trap was set up in each biofuel grass plot, 3 in the surrounding abandoned agricultural field, and 3 on the forest edge at each site (total 33 of 24 traps). Each trap consisted of two 48 inch tall plastic poles with black fiber glass window screen suspended in between that has the dimensions 36in by 36in. A basin full of soapy water (3ft long, 8in wide, 2 in deep) was placed at the bottom of each net.

Insects fly into the net and fall into the water. They were collected and preserved in 70% alcohol.

All plots were sampled on sequential 4-day periods. Flight traps were left out for a total of 4 days and checked in the morning of the third day to ensure water was still in the trough and no animals destroyed the traps. Arthropods were collected by all three methods 3 times throughout the summer. Each sampling event took place the third week of each month; flight traps were set out on a Monday and collected on Thursdays and

Berlese and sweep net samples were collected on Wednesdays of the same sampling week. Samples were collected in May, June, and July.

At the Wilds, sampling was not approved from the Wilds Restoration Committee until mid-July 2017. There was concern for the possibility of American burying beetles being caught and killed in the flight intercept traps, since these are left out for 4 days unsupervised, there was no way to ensure these endangered species would not get intercepted in the traps. Therefore, sweep net and Berlese samples were taken one time during the third week in September at the Wilds. Six random samples from each biofuel plot (miscanthus and switchgrass) were collected at the Wilds following the protocol described above. Another collection was carried out at the Ridges Land lab in September of just sweep nets and Berlese funnels in the switchgrass and miscanthus stands to compare against the Wilds samples. 34

2.2.4 Arthropod Identification and Counting

The arthropods harvested from each sampling method were classified to family using a variety of field guides and confirmed with An Introduction to the Study of Insects

Sixth Edition (Triplehorn et.al., 1989). Non-insect groups such as spiders were identified according to The Common Spiders of Ohio Field guide (Bradley, 2012). All samples were carefully transferred to an open plastic petri dish and viewed through a Stereo Star

0.7X to 3.0X microscope and light. Forceps were used to separate clusters of insects when necessary to aid identification. The insects from each sampling method were combined for each plot and stored in 70% alcohol in clear glass containers.

2.2.5 Statistical Methods

Habitat type is the categorical explanatory variable for this experiment. The dependent response variables included: total Arthropod number (abundance), total family richness, arthropod diversity measured by the Shannon Diversity index, trophic group

(omnivores, predator/parasites, herbivores, sucking bugs, pollinators, and detritivores) and selected families. Although diversity is useful in that it accounts for evenness, some ecosystems may contain certain species that naturally have low or high populations. In that case, lower diversity may not necessarily indicate a less natural state for that community. Thus, to obtain the most complete picture, it is important to look at abundance and species richness in addition to diversity. In this study, abundance was calculated as the sum of the total number of arthropods collected in each replicate over the summer sampling dates. It is intended to be a relative measure and not an absolute 35 estimate of all insects at a site. Family richness (richness) is the total number of families collected at a replicate averaged between the three sampling dates in May-July.

One-way ANOVA’s were used to test the Null Hypothesis (H0): Habitat type has no impact on response variable; or conversely, the Alternative Hypothesis (HA): Habitat type has an impact on response variable. The null hypothesis was rejected at any significance value below P=0.05. All data was tested to meet the assumptions of

ANOVA’s, i.e. equal variance and normality (Whitlock and Schluter (2014). This was used to validate the use of ANOVA and also to assess if data transformation was necessary or not. The analysis was considered acceptable based on randomness and normality of residuals. All data was tested to be normal and of equal variance unless specified otherwise in the results section below.

36

CHAPTER 3: RESULTS

Arthropods from 4 classes were collected across all sample methods and dates:

Arachnida (spiders, ticks, and mites), (Collembolans), (pill bugs) and Insecta (insects). All data on per family abundances are compiled in the

Appendix for brevity in presentation (Appendix, Table 3-6). Overall, 25,390 individuals were identified from all collection types and dates over the course of this study. Flight trap and sweep net samples were pooled together as these collection methods collect similar guilds of arthropods, in contrast to the Berlese samples which are more selective for arthropods on the ground and in leaf litter. Insects and non-insect groups (Aranea,

Ixodidae, and ) were identified from 14,328 specimens and represented 13 orders and 67 families captured in flight traps and sweep nets (henceforth referred to as flight traps) (Appendix, Table 3).

Berlese sample diversity and abundance metrics were calculated separately from the flight trap samples. All mites captured in Berlese samples at the Land Lab were from the suborder Oribatida. Insects and non-insect orders (Araneae, Chilopoda, Oribatida,

Ixodida, Pseudoscorpion and ) collected in Berlese funnels were identified from 8,541 individuals representing 11 orders and 21 families (Appendix,

Table 4).

The results section is split into two categories: the summer sampling event and

September sampling event. The September Wilds collection statistics are summarized later in the results section. 37

3.1 Summer Sampling Event: The Ridges Land Lab

3.1.1 Impact of Habitat Type on Total Arthropod Number

The four crop types were compared to determine their impact on the abundance of arthropods, as measured by the total number of arthropods collected per replicate over the summer collection period (Appendix, Tables 3-6). The number of arthropods was affected by habitat type for both flight trap (F-statistic: 16.14 on 3 and 20 df, p-value:

1.447e-05) and Berlese samples (F-statistic: 3.64 on 3 and 20 df, p-value: 0.0304). A

Tukey-HSD test on flight samples showed a statistically significant difference between the forested edge and abandoned agriculture (p=0.0075), miscanthus and abandoned agriculture (p=0.0261), miscanthus and forested edge (p<0.0001), and switchgrass and forested edge (p=0.0006) (Figure 4). The forested edge supported significantly more arthropods (5,881) than abandoned agriculture (3,655), switchgrass (3,021), and lastly miscanthus (1,771) (Appendix, Table 3).

38

Figure 4: Mean and standard deviation for abundance of arthropods caught in fight/sweep traps during the summer. Blue dots represent outliers of the data.

Berlese sample Tukey-HSD test revealed a significant difference between the switchgrass and miscanthus treatment (p=0.0227) while no other significant differences were detected among other treatment types (Figure 5). Interestingly, switchgrass had the highest abundance of Berlese arthropods (2,479) followed by abandoned agriculture

(2,269), forested edge (2,077), and miscanthus (1,716) (Appendix, Table 4).

39

Figure 5: Mean and standard deviation of the total number of arthropods caught in Berlese samples in each habitat type during the summer at the Ridges.

3.1.2 Impact of Habitat Type on Family Level Richness

Taxonomic richness is the count of the number of different taxonomic groups found in a community and does not always correspond to diversity, especially with different sample sizes. One cannot simply divide the number of taxa found by the number of individuals sampled in order to correct for different sample sizes. Doing so would assume that the number of taxa increases linearly with the number of individuals present, which is not always true. By plotting the number of taxa as a function of the number of individuals collected one can visualize the most common taxa found first, as the curve grows rapidly, then the curve plateaus as the most rare taxa remain to be detected (Gotelli and Colwell, 2001). Only high sample sizes in which the rarefaction curve reaches an asymptote will yield a reliable estimate of the total richness of a community (Soberon and

Llorente 1993). Rarefaction curves representing the taxa accumulated against the pooled 40

sample size of each treatment are shown in Figure 6 and 7. Notice that rarified numbers

of individuals found in a treatment are generally lower than observed, and as expected

each rarefaction line reaches an asymptote, indicating thorough sampling (Soberon and

Llorente, 1993).

Figure 7: Rarefied family accumulation curve showing the number of families caught in flight/sweep traps against the number of individuals collected for each treatment type. M=miscanthus, A=abandoned agriculture, SW=switchgrass, F=forested edge.

41

Figure 6: Rarefied family accumulation curve showing the number of families caught in Berlese samples against the sample size for each treatment type.

Family richness per treatment replicate was averaged over the 3-month period

(Appendix, Table 7). The number of arthropod families collected by the flight traps was affected by habitat type (F-statistic: 20.11 on 3 and 20 df, p-value: 2.978e-06). A Tukey-

HSD test indicated that forested edge habitats significantly differed from abandoned agriculture (p=0.0179), switchgrass (p=0.0107), and miscanthus (p=0.0001). In addition, miscanthus significantly differed from the abandoned agriculture (p=0.0012) and switchgrass (0.0021). Family richness was statistically highest in the forested edge habitat (28 ± 1.378) followed by abandoned agriculture (23 ± 2.562), switchgrass (23 ±

3.619), and miscanthus (17 ± 1.643) (Figure 8).

No significant differences between habitats were detected for Berlese family richness (F-statistic: 2.029 on 3 and 20 df, p-value: 0.142, Appendix Table 7, Figure 9).

42

Figure 8: Mean and standard deviation of family richness measures per habitat type for flight/sweep samples during the summer sampling event.

Figure 9: Mean and standard deviation of family richness per habitat type for Berlese samples during the summer sampling event.

43

3.1.3 Impact of Habitat Type on Arthropod Diversity

Diversity was calculated using the Shannon index (H) (Southwood and Henderson

2000) (eq. 1):

퐻 =− 푝푖 ln(푝푖)

Where pi = the proportional abundance of i-th family (ni /N); i = i-th family; ni = abundance of each family; N= the total number of all individuals and S = observed number of family (family richness). The Shannon diversity index (diversity) is a commonly used method to characterize species (in our case family) diversity in a community, it accounts for both evenness and number of families (Magurran, 1988). It will have a higher value when many families contain similar numbers of individuals and usually ranges from 1.5 - 3.4; higher number = more diverse (Magurran, 1988).

A one-way ANOVA was run on the mean diversity index between the three sample dates per replicate after testing for normality of the data set (Appendix, Table 7).

Insect diversity based on flight net sampling did not show any significant differences among samples (ANOVA p= 0.0569, f-statistic=2.962 on 3 and 20 df). Figure 10 shows flight sample diversity data that although not significant, differences can be seen in the forested edge which had the highest diversity; miscanthus had the lowest and abandoned agriculture and switchgrass in between.

Shannon diversity based on Berlese sampling returned a significant result

(ANOVA p=0.00825, F-statistic: 5.177, on 3 and 20 df). A Tukey-HSD test was ran on the Berlese ANOVA and it was determined that miscanthus significantly differs from the abandoned agriculture (p=0.00867) and the forested edge plots (p=0.0257). Berlese 44 samples collected in the miscanthus had significantly lower Shannon diversity than the abandoned agriculture and forested edge plots which indicates uncertainty is very low in the miscanthus (Figure 11). This is largely because the orders Oribatida and

Entomobryomorpha comprised over 89% of the arthropods collected in miscanthus

Berlese samples, hence the reduced uncertainty (Appendix, Table 4). Figure 11 shows the

Berlese sample diversity variations between treatment types, with miscanthus being the lowest and significantly different from abandoned agriculture and forested edge.

Figure 10: Mean and standard deviation for flight/sweep sample Shannon diversity by habitat type during the summer sampling event. 45

Figure 11: Mean and standard deviation for Berlese sample Shannon diversity by habitat type during the summer sampling event.

3.1.4 Impact of Habitat Type on Trophic Groups

To understand the potential role that habitat type may have on different arthropod taxa, all arthropods were classified by trophic levels according to the feeding habit and functionality in the ecosystem of the Ridges Land Lab: omnivores, predator/parasites, herbivores, sucking bugs, pollinators, and detritivores (Triplehorn et. al., 1989). All collection methods were pooled together and abundance by trophic group was summarized per replicate over the three month summer sampling period. Crop type had a significant effect on all trophic group abundances, except for detritivores, with reported p-values located in Appendix, Table 9.

Pollinators and herbivorous insects were the least abundant trophic groups found over the course of this study (Figure 12). Pollinators were most abundant in the forested edge habitats (Appendix, Table 9). Pollinator and herbivorous insect group distributions were not normally distributed and therefore logarithmically transformed to meet the 46 assumptions of linear models. Significant differences are noted for pollinator abundances between the forested edge and each of miscanthus (p<0.0001), switchgrass (p=0.0004) and abandoned agriculture (p=0.0006). The forested edge habitats held the highest number of herbivores (Appendix, Table 9) with significant differences between forest and miscanthus (p<0.0001), switchgrass (p=0.0012), and abandoned agriculture (p=0.0065).

Miscanthus and abandoned agriculture herbivore abundances also differed (p=0.0327).

Plant sucking bugs use their sucking and piercing mouthparts to feed on plant sap and are often considered pests in agricultural ecosystems (Bradshaw et. al., 2010,

Stefanovska et. al., 2017). In this study, a significant difference was found in sucking bug populations only between miscanthus and abandoned agriculture as the family cicadellidae represented over 22% of the families caught in the abandoned agriculture while only 6.21% were present among miscanthus families. About (7.6±0.5) sucking bugs were found per sample in the miscanthus compared to (43.3±4.2) found per sample in the abandoned agriculture.

Detritivores play an important role in leaf litter decomposition and contribute to the energy flow and nutrient cycling of agricultural ecosystems (Zangerl et. al., 2013). No significant differences were shown for detritivorous arthropod groups between treatments

(Appendix, Table 9).

The two most abundant arthropod groups present in the treatments were omnivores and predator/parasites (Appendix, Table 9). The omnivorous insect data was not normal so was log transformed to meet the assumptions of linear models. The most abundant omnivore groups were found in the forested edge followed by abandoned 47 agriculture, switchgrass, and lastly miscanthus (Appendix, Table 9). Omnivorous insects in miscanthus differed from abandoned agriculture (p=0.0011) and the forested edge

(p=0.0006). Predators and parasites were the most abundant group found in this study with the most found in forested edge followed by switchgrass, abandoned agriculture, and finally miscanthus (Appendix, Table 9). A Tukey-HSD test revealed differences between the forested edge and every other treatment type: switchgrass (p=0.0011), abandoned agriculture (p<0.0001), and miscanthus (p<0.0001).

Figure 12: Abundance of trophic groups for each habitat type. M=Miscanthus, SW=Switchgrass, A=Abandoned Agriculture, F= Forest, Sites O=Roadside and H=Radar Hill.

3.2 September Sampling Event: The Wilds

The Wilds collection data (from September) was analyzed separately from the summer months to allow for comparisons between the miscanthus and switchgrass samples at the two sites with different plot sizes. No flight traps were at The Wilds as 48 explained in section 2.2.3. Sweep net and Berlese samples were statistically analyzed separately from each other here. In Berlese samples, 2,224 individuals were captured in

September between the Ridges Land Lab and The Wilds, comprising 9 orders and 17 families of insects and non-insect groups (Isopoda, Aranea, Orbatida,

Entomobryomorpha, and Pseudoscorpiones) (Appendix, Table 5). In sweep-net samples, fewer individuals were found (297), representing 8 orders and 28 families of insects and non-insect groups (Aranea and Ixodida) (Appendix, Table 6).

3.2.1 Impact of Habitat Type and Site on Arthropod Abundance

A two-way ANOVA was run on the miscanthus and switchgrass data between the

Wilds and Ridges Land Lab, with Site and Treatment as the two categorical independent variables. The dependent response variables were the same as explained previously. This analysis was to see if there were differences between habitat types as well as site. The

Berlese samples for abundances were not normally distributed after a Shapiro Test was conducted so a Kruskal-Wallace test was used in place of the ANOVA. Abundance of arthropods was summarized per replicate at each site (Appendix, Table 8) and there were no significant differences between treatments and sites for the Berlese (Kruskal-Wallis chi-squared = 5.5891, df = 5, p-value = 0.3483) or sweep net samples (F-statistic: 2.593 on 5 and 18 df, p-value: 0.06181).

Although no significant differences were calculated between sites and treatments for the abundance of arthropods, The Wilds exhibited higher averages in both the miscanthus and switchgrass for both collection methods, with the exception of the switchgrass Berlese samples, between sites. The switchgrass Berlese samples at the wilds 49 had an average abundance of 81.666 ± 45.474 which is slightly lower than the switchgrass Berlese samples at the Ridges Land Lab being 113.5 ± 57.068. The Wilds conducted a harvest of the switchgrass in late July so this could have impacted the arthropod abundances. The Wilds switchgrass sweep samples (20.333 ± 11.621) were higher in abundance than the Ridges Land Lab switchgrass sweep samples (16 ± 1.581).

The Wilds miscanthus showed the highest average abundance of arthropods in Berlese samples (110.333 ± 50.338) followed by The Ridges Land Lab miscanthus Berlese samples (65.166 ± 9.579). The Wilds miscanthus sweep samples showed higher abundance averages (14.5 ± 6.833) than the Ridges Land Lab miscanthus sweep samples

(5.33 ± 1.966).

3.2.2 Impact of Habitat Type on Family Level Richness

Family level richness was summarized as the total number of families caught per sample. Again, the Berlese samples were not normally distributed after a Shapiro Test was conducted so a Kruskal-Wallace test was used. The September family level richness was summarized per replicate per collection method and is noted in Appendix, Table 6.

Family level richness was not significantly different in either habitat type between sites for Berlese (Kruskal-Wallis chi-squared = 5.5891, df = 5, p-value = 0.348) or sweep net samples (F-statistic: 2.593 on 5 and 18 df, p-value: 0.0618).

Numerically, The Wilds miscanthus field generally held more family richness in the sweep net samples (5.166 ± 2.316) and Berlese samples (8 ± 1.673) than at the Ridges

Land Lab (sweep= 2.5 ± 1.378, Berlese= 4 ± 1.549). The Wilds switchgrass field exhibited higher rates of family richness for sweep net samples (6.666 ±3.502) and 50

Berlese samples (6.333 ± 1.211) compared to The Ridges Land Lab as well (sweep= 5.2

± 0.836, Berlese= 5.666 ± 1.366).

3.2.3 Impact of Habitat Type on Diversity

The Berlese samples for diversity had a non-normal distribution so a Kruskal-

Wallace test was used instead of an ANOVA. Four plots had a Shannon-diversity index of 0 as there were less than 5% taxa collected in these samples so they were removed from calculations. Overall, there were no significant difference in the Shannon diversity index between sites and treatments for both the Berlese samples (Kruskal-Wallis chi- squared = 8.01, df = 5, p-value = 0.1557) and the sweep net samples (F-statistic: 2.401 on

5 and 14 df, p-value: 0.0902) during September.

The Shannon diversity index averages were higher at The Wilds than at the

Ridges for both sample types. Sweep net sample average diversity is as follows in declining order: The Wilds switchgrass (1.512 ± 0.782) followed by the Wilds miscanthus (1.407 ± 0.480), the Ridges switchgrass (1.400 ± 0.127), and the Ridges miscanthus (0.662 ± 0.580). Berlese sample diversity is as follows in declining order as well: the Wilds switchgrass (1.323 ± 0.234), the Wilds miscanthus (1.315 ± 0.211), the

Ridges switchgrass (1.144 ± 0.219), and finally the Ridges miscanthus (0.839 ± 0.503).

51

CHAPTER 4: DISCUSSION

The statistical analysis for this project revealed that cellulosic ethanol crop type and habitat type has an impact on arthropod communities; with different trophic groups having different relationships with each habitat type. Arthropods in different guilds responded to treatments differently, as well as those sampled by different collection methods (sweep net, flight trap, and Berlese samples). Arthropods collected in flight trap/sweep samples were found in greatest abundance and Shannon diversity in the forested edge, with the lowest abundance and diversity in miscanthus and intermediate levels in abandoned agriculture and switchgrass. Ground dwelling arthropods captured in

Berlese samples had highest abundance in switchgrass fields, lowest in miscanthus and intermediate levels in abandoned agriculture and forested edge cover types. Overall

Shannon diversity for Berlese samples was highest in abandoned agriculture, lowest in miscanthus and intermediate levels in switchgrass and forested edge. No significant differences in arthropod diversity or abundance were detected between miscanthus and switchgrass plantings of different sizes between the Ridges Land lab and The Wilds.

These findings are discussed at length below.

4.1 Summer Sampling Event

4.1.1 Arthropod Abundance and Family Richness related to Habitat Type

Conserving or increasing species richness is often incorporated into the goals of conservation studies either indirectly or directly (May 1988), and current and background rates of species extinction are calibrated against patterns of species richness (Simberloff

1986). Increasing the number of families found in arable crop fields is likely to contribute 52 to the overall stability of the ecosystem as different feeding or trophic guilds carry out different tasks along multiple scales (Elmqvist, 2003). Arthropod abundance is also important in the context of foraging resources for birds and other higher trophic levels.

Three treatment types (miscanthus, switchgrass, and abandoned agriculture) were found to be statistically different from the forested edge which is in agreement with our hypothesis that more insects would be found in the forested edge because of edge effects and the generally more diverse ecosystem these areas provide (Chacoff and Aizen, 2005).

These data also reflect previous studies that suggest that more environmentally diverse areas can influence more arthropod number and family richness (Duelli et al., 1999;

Ward et al., 2001, Hendrickx et. al., 2007, Diekotter et al., 2008, Robertson et.al., 2011).

Likewise, M’Gonigle et. al., (2015) found that restorations to hedgerows consisting of native, perennial and tree plantings not only facilitate recolonization of pollinating insects from adjacent source populations but they also create conditions that promote pollinator persistence local to the area. This suggests that the arthropod communities found in biofuel plantings such as miscanthus and switchgrass would benefit from having diverse plant communities (i.e. hedgerows, mixed prairie, forested areas) nearby (Ponisio et.al.,

2016, Hendrickx et. al., 2007).

As reported for other ecosystems (e.g., Eisenhauer et al., 2010), mites and collembolans dominated the Berlese arthropod communities as a whole for this study

(Appendix, Table 4). The only significant difference between Berlese abundance data was between the biofuel crops miscanthus and switchgrass. In contrast, Zangerl et. al.,

2013 conducted a study on the role of arthropod communities in miscanthus and 53 switchgrass plantings and concluded that abundances of detritivorous below ground taxa did not significantly differ between miscanthus and switchgrass. A possible explanation between the discrepancies in our data sets could be that the previous land use under the biofuel plantings in our study was abandoned agriculture and for the Zangerl study

(2013) previous land use was recently dedicated monoculture agriculture before being converted to biofuel plantings. As mentioned in the literature review, historical land use conditions can have effects on current land uses (Hertel et. al., 2010).

4.1.2 Arthropod Diversity Related to Habitat Type

The Shannon-Wiener index of diversity considers both species richness and evenness. It represents the proportion of a species (in our case family) relative to the total number of species present. The Shannon index increases with richness and evenness, and puts more weight on the richness than on evenness (Magurran, 1988). Different numbers for Shannon diversity between habitat types signifies that different kinds of communities of insects are represented. Analyzing family richness and evenness among individual families using the Shannon index is important especially in our study where different abundances (i.e. evenness) of arthropods were statistically significant in both sampling methods.

The diversity of ground level soil invertebrate populations is related to plant diversity (Tilman, 1982; Siemann et al., 1998; Symstad et al., 2000). Growing perennial warm season grasses (miscanthus and switchgrass) has been shown to improve soil properties like water storage and soil organic content (Blanco, 2010) thus stimulating populations of collembolans and other ground dwelling arthropods (Hopkin 1997). The 54 number of arthropods contained in a specific family in Berlese samples was significantly different among the biofuel grass habitat types for this study. Chauvat et. al. (2014) monitored changes in ground dwelling Collembolan species on metal contaminated soils in France. They found 20-fold more individuals under three year old miscanthus and switchgrass stands than under stands. Consistent with our results, Cauvet et. al.

(2014) also found distinctly different assemblages of these collembolan life forms between switchgrass, miscanthus, and wheat. Biofuel crop identity and habitat type appears to be an important factor in shaping soil faunal communities as previously reported (Landis and Werling, 2010, Robertson et. al., 2012, Holgin et. al., 2010). No significant differences were recorded for Shannon diversity metrics in flight trap samples.

Assemblages of families were similar between habitat types for above ground insects.

4.1.3 Trophic Group Response to Habitat Type

A total of 6 honeybees and no bumblebees were caught during the course of this experiment while most of the hymenopterans caught were ichneumonid wasps

(Appendix, Table 3). The low abundance of pollinators found in this study is consistent with known rates of pollinator decline (Schmuck et al., 2001, Brittain and Potts, 2011,

Whitehorn et al., 2012, Stanley and Stout, 2013) and these declines have serious ecological implications. Pollinator services appreciated by humans within agricultural ecosystems are worth billions of dollars each year within crops that make up 35% or more of the global food supply (Moroń et al, 2008). The biofuel grass plantings supported the lowest abundance of arthropods over the course of this study. Perennial C4 grasses such as switchgrass and miscanthus are a poor food source for herbivorous arthropods 55 and provide little to no benefit for pollinators (Haddad et al., 2001). The forested edge in our study held the highest abundance of pollinators and this indicates that increasing available habitat for this trophic group through a change in crop choices or proximity to forested edge can provide them with better connections of resources (M'Gonigle et. al.,

2015).

The main goal of growing biofuel crops is to produce the most biomass to convert to a useable fuel and herbivorous or sucking arthropods can damage these yields tremendously (Nabity et. al., 2012). The silica and present in the cell walls of C4 perennial grasses act as a natural deterrent to these trophic groups as they cannot easily chew and digest this organic matter. Most C4 plants rely on these physical defenses to deter herbivores (Onoda et al., 2011) yet breeding practices to increase biomass and enhance conversion into fuel minimize these physical traits (Nabity et.al.,2012). Sucking

(phloem feeders with piercing mouthparts) and herbivorous arthropods were found in most abundance in the abandoned agriculture and forested edge around the biofuel grasses (Appendix, Table 9). This indicates that these trophic groups can reside in fields close to the biofuel crops and if natural defenses against these arthropods are bred out of the C4 grasses, serious biomass degradation from herbivores and sucking bugs from the surrounding area could be seen within the crops (Nickel and Hildebrandt, 2003).

Omnivores and predator/parasites were the most abundant trophic groups caught over the course of this experiment. Of these groups, carabid and staphylinid beetles as well as ground mites (Oribatida) were the three most abundant families caught per treatment type (Appendix, Table 3). One explanation for the abundance of staphylinids is 56 that these insects are scavengers and are naturally attracted to the smell of decaying organic matter that was probably present in our flight traps left out over the course of four days with dead bugs inside. Predatory arthropods, such as Aranea and Coleoptera, are unlikely to be found in habitats with less overall abundance of arthropods as that is their main food resource. Predatory populations also keep herbivorous insect populations in check while at the same time providing migratory birds and other vertebrates like frogs and small mammals a food resource (Tscharntke and Greiler, 1995, Gardiner et al.,

2009). It should be noted that two forcep flies (Meropeidae, Order Mecoptera) males were caught over the course of this experiment in the forest edge flight intercept traps.

Forcep flies are somewhat rare and unusual insects. Only three species are known, with each one of ancient origin from North America, Brazil, and Australia; this indicates that they were around when all the continents were still one Pangea. It is unknown if this insect has been caught in Athens county before.

4.2 September Sampling Event

4.2.1 Diversity and Abundance between The Wilds and The Ridges Land Lab

During the one time collection period between The Wilds and The Ridges Land

Lab, no statistical significances were found between treatments and sites for any of the diversity metrics (abundance, richness, and Shannon diversity). This could be due to a variety of considerations including but not limited to: sample size, sampling method, field types bordering edge, and non-replication of samples. The non-significance between treatments and sites could simply be because the grass types considered are the same at both sites so arthropod communities in this one time sampling event were similar. All 57 diversity metrics (except abundance in Berlese switchgrass samples) were numerically higher at the Wilds than at the Ridges which might be indicative of the larger field size at

The Wilds than at the Ridges (Hendrickx et. al., 2007, Bruhl and Linsenmair, 2003).

58

CHAPTER 5: LIMITATIONS, RECOMMENDATIONS, AND CONCLUSIONS

5.1 Limitations and Recommendations

Our multiple collection methods were meant to sample the sites as comprehensively as possible but a number of families are sure to have been missed. Also, we only sampled during one summer season, so it is unknown what happens in the spring or autumn. Sweep net samples are a fast and easy method used to measure relative abundance and family richness (Missa et.al., 2009) but as the miscanthus and switchgrass grew, sweep netting became less and less efficient on capturing taxa in the canopy of the grasses. For most taxa, species diversity will increase with sampling intensity, simply because more rarer species will be encountered if the period, frequency, and number of trapping occasions is increased (New, 1996). Correct identification from graduate and undergraduate students involved in this study was of upmost importance, yet supervising the placement of every taxon was unreasonable so a mistake could have been made at one point or another. In many fields of ecology and conservation information has traditionally been exposed at the species level. Timms et al. (2012) argues that higher level taxonomic resolution (such as family-level) does not substantially affect the interpretation of patterns in diversity or composition compared to species level data.

Research opportunities posed by new biofuel production systems are increasingly important and nearly endless as dynamics among biotic organisms constantly change through time. Our findings represent one snapshot of a community of arthropods in

Southeast Ohio and results may vary for different locations. Other factors could have been included in the linear models used to find significance in treatment type such as the 59 height of the grasses and changes in community composition over time. Factors that may have affected the results include, but are not limited to: field size, field types bordering edge, distance from field edge (edge effects), proximity to roads, forest, streams, weather conditions in the sampling year, rotation of the biofuel crops, or proximity to a compost facility located nearby. These factors were difficult to control for during the course of this study as use of the Land lab was graciously donated for this project from members of the

Land Lab committee and Dr. Sarah Davis who is in charge of the biofuel grasses themselves.

5.2 Conclusions

This study showed that land cover type has different effects on different guilds of insects. For above ground insects, the greatest abundance and diversity was seen in forested edge and abandoned agriculture habitat types compared to the dedicated monocropped biofuel grasses. This study also showed that ground dwelling insects involved in leaf litter decomposition respond to their environment in different ways and previous and current land use can influence diversity and abundance of these arthropods.

As noted in the literature, increased diversity of floral resources is correlated with increased diversity of the living organisms that depends on these resources for food and shelter (Semere and Slater, 2006, Thomas and Marshall, 1999, Gardiner et. al. 2010,

Landis and Werling, 2010). In turn, increased diversity of beneficial arthropod groups, such as predators and pollinators, can to increased crop yields and higher profitability in arthropod pollinated crops (Veddler et. al., 2008). Increased ecosystem diversity to increased resilience allowing the ecosystem to recover from 60 disturbances over time (Chapin III et. al., 1997, Hoffmann, 2005, Groom et. al., 2008,

Dale et. al., 2013). Natural enemies acting as natural pest deterrents are also preserved when more families of the same trophic group are present in an ecosystem (Tscharntke and Geiler, 1995, Schmidt and Tscharntke, 2005, Marris 2009, Gardiner et. al., 2009,

Werling et. al., 2011). Cultivating advanced biofuels for alternative energy will alter the interactions in species as small as arthropods; preemptive attempts at acknowledging these changes can reduce severe consequences during crop production. To increase success of the biofuel market, it is of upmost importance to consider surrounding landscape diversity and the spillover of arthropods from adjacent habitats (Landis and

Werling, 2010). In landscapes currently dominated by annual crops, the inclusion of new perennial biofuel crops could increase arthropod abundance and diversity. In already diverse landscapes, such as marginal or abandoned land not currently in crop rotation, the introduction of biofuel crops could decrease foraging resources for arthropods. Some of these interactions will be beneficial, others harmful, and many impacts will take years to be fully realized.

61

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APPENDIX: TABLES FOR DIVERSITY AND ABUNDANCE OF ATHROPODS

Table 3: Summer Sampling Event: Flight and Sweep Abundances pooled over a three month sampling period. Percentages are included to show relative abundance of each family in each treatment type above 1% relative abundance. Total Number Number Number Number 144 Total Flight Trap Number found in found in found in found in and Sweep Net Found in Abandoned Forested Miscanthus Switchgrass Samples ALL Agriculture Edge (36 (36 Samples) (36 samples) fields (36 Samples) samples) Total # of Arthropods 14328 1771 3021 3655 5881 Order Family

Orthoptera Rhaphidophoridae 28 11 2 9 6 Acrididae 131 14 39 (1.29%) 55 (1.50%) 23 Tettigoniidae 5 0 0 1 4 Gryllidae 119 25 (1.41%) 17 46 (1.26%) 31 Coleoptera Elateridae 165 23 10 28 104 (1.77%) Coccinellidae 18 6 6 2 4 Cantharidae 28 4 6 4 14 Cicindelidae 10 0 4 6 0 Carabidae 1007 248 (14.00%) 215 (7.12%) 167 (4.57%) 377 (6.41%) Mordellidae 175 1 12 7 155 (2.64%) Lampyridae 3 0 1 0 2 Cerambycidae 20 18 (1.02%) 0 1 1 Buprestidae 34 5 7 3 19 Curculionidae 121 14 15 20 72 (1.22%) Scarabidae 85 2 13 13 57 Chrysomelidae 306 34 32 (1.06%) 35 205 (3.49%) Scolytidae 83 7 18 17 41 Silphidae 25 4 6 12 3 Staphylinidae 2302 432 (24.39%) 308 (10.20%) 129 (3.53%) 1433 (24.37%) Diptera Asilidae 2 0 1 0 1 Syrphidae 58 19 5 5 29 Rhagionidae 5 0 4 0 1 Phoridae 481 60 (3.39%) 89 (2.95%) 85 (2.33%) 247 (4.20%) Tabanidae 52 2 20 24 6 Chrysopidae 3 0 0 3 0 Sciomyzidae 13 1 11 0 1 Tipulidae 462 27 (1.52%) 40 (1.32%) 100 (2.74%) 295 (5.02%) Dolichopodidae 1142 98 179 (5.93%) 385 (10.53%) 480 (8.16%) Chironomidae 130 2 12 9 107 (1.82%) Sarcophagidae 17 5 8 0 4 Table 3 Continued: 69

Calliphoridae 33 1 5 12 15 Ceratopogonidae 370 76 (4.29%) 75 (2.48%) 126 (3.45%) 93 (1.58%) Simuliidae 102 11 40 (1.32%) 4 47 Muscidae 136 18 (1.02%) 36 (1.19%) 43 (1.18%) 39 Drosophilidae 291 22 (1.24%) 60 (1.99%) 68 (1.86%) 141 (2.40%) Culicidae 1161 80 (4.25%) 296 (9.80%) 675 (18.47%) 110 (1.87%) Hymenoptera Vespidae 28 3 5 6 14 Ichneumonidae 443 38 (2.15%) 86 (2.85%) 74 (2.02%) 245 (4.17%) Chrysididae 27 1 6 2 18 Apidae 6 0 1 1 4 Tenthredinidae 5 0 0 0 5 Halictidae 30 6 3 5 16 Formicidae 869 142 (8.02%) 307 (10.16%) 199 (5.44%) 221 (3.76%) Sphecidae 206 38 (2.15%) 40 (1.32%) 48 (1.31%) 80 (1.36%) Hemiptera Pentatomidae 53 3 32 (1.06%) 9 9 Lygaeidae 12 0 3 6 3 Reduviidae 12 1 3 5 3 Cercopidae 139 8 43 (1.42%) 53 (1.45%) 35 Miridae 70 5 34 (1.13%) 12 19 Aradidae 6 0 0 0 6 Cicadellidae 1986 110 (6.21%) 562 (18.60%) 838 (22.93%) 476 (8.09%) Tingidae 5 1 2 2 0 Membracidae 14 0 0 2 12 Aphididae 409 42 (2.37%) 93 (3.08%) 94 (2.57%) 180 (3.06%) Mecoptera Meropeidae 2 0 0 0 2 Lepidoptera Moths 129 5 31 (1.03%) 36 57 Nymphalidae 2 0 0 0 2 Dermaptera Labiidae 1 0 0 0 1 Blattodea Blattidae 6 0 1 1 4 Mantodea Mantidae 5 1 1 2 1 Isopoda 34 11 10 9 4 Aranea Orb Weavers 237 12 33 (1.09%) 51 (1.40%) 141 (2.40%) Jumping Spiders 61 10 14 19 18 Opilliones 36 12 4 5 15 Crab Spiders 24 4 8 2 10 Wolf Spiders 333 47 (2.65%) 102 (3.38%) 75 (2.05%) 109 (1.85%) Ixodida Ixodidae 12 1 5 3 3

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Table 4: Summer Sampling Event: Berlese Abundances pooled over a three month period. Percentages are included to show relative abundance of each family in each treatment type above 1% relative abundance. The Ridges Land Lab: Berlese Abundance

Total Number Number Number Number Number found in 72 Total Berlese found in found in Ab. found in Found Miscanthus Samples Switchgrass Agriculture Woodland in ALL (18 (18 samples) (18 Samples) (18 samples) fields Samples)

Total # of 8541 1716 2479 2269 2077 Arthropods Order Family

Staphylinidae 36 8 6 13 9 Chrysomelidae 24 2 4 3 15 Coleoptera Curculionidae 6 0 2 1 3 Carabidae 514 16 102 (4.11%) 148 (6.52%) 248 (11.94%) Formicidae 204 12 70 (2.82%) 76 (3.35%) 46 (2.21%) Hymenoptera Sphecidae 34 4 8 13 9 Cicadellidae 60 0 10 22 28 Aphididae 61 16 10 15 20 Hemiptera Pentatomidae 21 3 6 3 9 Tingidae 7 1 1 1 4 Diptera Culicidae 7 1 2 0 4 Wolf/Running 12 0 5 2 5 spider Aranea Orb Weaver 26 3 18 3 2 Jumping Spiders 29 3 6 13 7 Chilopoda Chilopoda 19 8 2 4 5 1210 1537 1328 1259 Oribatida Oribatida 5334 (70.51%) (62.00%) (58.53%) (60.62%) Ixodida Ixodidae 11 1 5 2 3 Thysanoptera Thysanoptera 603 98 (5.71%) 261 (10.53%) 151 (6.65%) 93 (4.48%) 170 Entomobryoidea 901 254 (10.25%) 280 (12.34%) 197 (9.48%) (9.91%) Entomobryomorpha 148 Isotomoidea 566 152 (6.13%) 165 (7.27%) 101 (4.86%) (8.62%) Pseudoscorpiones Pseudoscorpions 66 12 18 26 (1.15%) 10

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Table 5: The Wilds Berlese Family Abundances from one collection date. Percentages are included to show relative abundance of each family in each treatment type above 1% relative abundance. September Sampling Event: Berlese Samples Total Number Number found Number found 24 Total Berlese Found in in Miscanthus in Switchgrass Samples ALL (12 Samples) (12 samples) fields Total # of Arthropods 2224 1053 1171 Order Family

Carabidae 231 91 (8.64%) 140 (11.96%) Coleoptera Chrysomelidae 6 6 0 Staphylinidae 1 0 1 Formicidae 20 15 (1.42%) 5 Hymenoptera Sphecidae 5 5 0 Pentatomidae 4 2 2 Hemiptera Cercopidae 1 0 1 Isopoda Armadillidae 14 8 6 Jumping Spiders 1 0 1 Aranea Wolf Spiders 13 9 4 Oribatida Oribatida 1309 676 (64.20%) 633 (54.06%) Thysanoptera Thysanoptera 183 68 (6.46%) 115 (9.82%) 235 86 (8.17%) 149 (12.72%) Entomobryomorpha Isotomidae 171 71 (6.74%) 100 (8.54%) Pseudoscorpiones Pseudoscorpions 30 16 (1.52%) 14 (1.20%)

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Table 6: The Wilds Sweep Abundances from one collection date. Percentages are included to show relative abundance of each family in each treatment type above 1% relative abundance. September Sampling Event: Sweep Net Samples Total Number found in Number found in 24 Total Sweep Number Miscanthus (12 Switchgrass (12 Samples Found in Samples) samples) ALL fields Total # of Arthropods 297 119 178 Order Family

Coccinellidae 7 4 (3.36%) 3 (1.69%) Cicindelidae 7 0 7 (3.93%) Coleoptera Mordellidae 33 23 (19.33%) 10 (5.62%) Curculionidae 1 1 0 Chrysomelidae 2 2 (1.68%) 0 Phoridae 29 11 (9.24%) 18 (10.11%) Sciomyzidae 4 0 4 (2.25%) Diptera Chironomidae 17 5 (4.20%) 12 (6.74%) Muscidae 3 0 3 (1.68%) Drosophilidae 4 0 4 (2.25%) Ichneumonidae 8 0 8 (4.49%) Hymenoptera Formicidae 4 1 3 (1.69%) Pentatomidae 10 2 (1.68%) 8 (4.49%) Lygaeidae 5 5 (4.20%) 0 Cercopidae 48 24 (20.17%) 24 (13.48%) Hemiptera Miridae 4 0 4 (2.25%) Cicadellidae 75 25 (21.01%) 50 (28.09%) Aphididae 14 6 (5.04%) 8 (4.49%) Lepidoptera Moths 1 0 1 Mantodea Mantidae 1 1 0 Orb Weavers 7 2 (1.68%) 5 (2.81%) Aranea Jumping Spiders 7 1 6 (3.37%) Crab Spiders 3 3 (2.52%) 0 Ixodida Ixodidae 3 3 (2.52%) 0

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Table 7: Summer Sampling Event Diversity Indices The Ridges Land Lab: Diversity Indices Diversity Metric S H1 A Collection Method FS B FS B FS B Treatment Replicate Site

Miscanthus 2 O 18 8 2.0170 1.0259 490 290 Miscanthus 11 O 18 6 2.2353 0.8325 369 333 Miscanthus 13 O 14 6 2.2206 0.8326 226 233 Switchgrass 3 O 22 8 2.4461 1.3311 430 395 Switchgrass 7 O 23 8 2.4424 1.0669 382 458 Switchgrass 12 O 18 9 2.0811 1.3903 331 422 Abandoned Agriculture 1 O 20 9 2.4018 1.1148 409 548 Abandoned Agriculture 2 O 24 7 2.5702 1.1721 569 418 Abandoned Agriculture 3 O 22 7 2.3913 1.0090 496 402 Forested Edge 1 O 27 7 2.5951 1.3676 863 278 Forested Edge 2 O 28 7 2.6346 1.2748 1237 284 Forested Edge 3 O 27 6 2.5661 1.0711 1265 295 Miscanthus 1 H 15 5 2.2685 0.9532 205 266 Miscanthus 10 H 17 5 2.1123 1.0374 264 263 Miscanthus 12 H 17 5 2.4955 0.8399 217 331 Switchgrass 5 H 22 5 2.2394 0.9739 531 384 Switchgrass 6 H 21 7 2.3558 1.1365 465 332 Switchgrass 15 H 29 7 2.4613 1.0581 882 487 Abandoned Agriculture 1 H 26 7 2.5296 1.4068 709 301 Abandoned Agriculture 2 H 25 8 2.2004 1.4297 804 295 Abandoned Agriculture 3 H 20 8 1.8257 1.3816 668 306 Forested Edge 1 H 30 6 2.5107 1.2200 956 426 Forested Edge 2 H 27 11 2.5104 1.3897 727 374 Forested Edge 3 H 26 6 2.3669 0.9176 833 420 Each value is a mean of 3 sampling dates except for arthropod abundances which are summed Diversity Indices S=Number of Families H1=Shannon-Weiner index of diversity, A=Abundance Totals FS= Flight/sweep pooled samples, B=Berlese Samples Site: H= Radar Hill, O= Roadside

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Table 8: September Sampling Event Diversity Indices The Wilds: Diversity Indices Diversity Metric S H1 A Treatment Site Replicate B S S B S B M Wilds 1 9 6 1.7045514 1.5815982 12 64 M Wilds 2 9 4 1.2406843 1.2226948 11 81 M Wilds 3 8 9 1.9439982 0.9730279 22 168 M Wilds 4 6 5 1.3950246 1.2844265 21 72 M Wilds 5 10 2 0.5623351 1.4711982 4 179 M Wilds 6 6 5 1.5992213 1.3618513 17 98 SW Wilds 1 8 6 1.5106939 1.4714066 25 107 SW Wilds 2 7 9 2.030387 1.4834553 32 82 SW Wilds 3 5 8 1.9084466 1.3561542 29 38 SW Wilds 4 6 1 0 1.4129608 3 57 SW Wilds 5 5 5 1.5229551 1.358705 9 47 SW Wilds 6 7 11 2.1019103 0.8583121 24 159 M H 1 5 1 0 1.094001 4 76 M H 10 3 3 0.8675632 0.4593948 6 75 M H 12 6 1 0 1.61854 4 62 M O 2 5 4 1.2148897 1.0755874 9 65 M O 11 3 2 0.5623351 0.4433067 4 50 M O 13 2 4 1.332179 0.3488321 5 63 SW H 5 4 0 0 1.0431622 0 55 SW H 6 6 4 1.2326433 1.3186726 14 103 SW H 15 8 5 1.3378607 1.3857777 15 218 SW O 3 6 6 1.4729378 1.2920938 16 117 SW O 7 5 6 1.5654451 0.835191 18 117 SW O 12 5 5 1.3954987 0.9908945 17 71 Notes: Each plot with a (0) Shannon index score had fewer than 5 individuals caught Diversity Indices S=Number of Families H1=Shannon-Weiner index of diversity, A=Abundance Totals Site: H= Radar Hill, O= Roadside, Wilds= The Wilds, Cumberland, Ohio B=Berlese samples, S=Sweep samples

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Table 9: Average Abundance by Trophic Group during Summer Sampling Event from all collection methods (flight trap, sweep net, Berlese traps) pooled. Habitat types with the same letter in each row are not significantly different. Miscanthus Switchgrass Abandoned Forested P-Value

Agriculture Edge

Omnivores 17 c 33 bc 61 ab 64 a 0.00026

± 0.9493 4.0242 4.8888 4.1013

Predator/Parasite 95 b 127 b 108 b 189 a <0.0001

± 5.6406 2.5041 3.8425 3.3474

Herbivores 5 c 8 bc 9 b 24 a <0.0001

± 0.5631 0.5016 0.3600 1.6886

Sucking 7 a 31 ab 43 b 32 ab 0.0104

± 0.5101 2.4317 4.1546 2.7054

Pollinators 1 b 2 b 2 b 12 a <0.0001

± 0.235211 0.265819 0.22618 0.432745

Detritivores 13 a 17 a 18 a 12 a 0.427

± 1.0876 1.1275 1.4227 1.2811

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