Arthropod Abundance and Diversity in Miscanthus x giganteus, Panicum virgatum, and
Other Habitat 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 Miscanthus x giganteus, Panicum virgatum, 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 bioenergy crop fields, such as pesticide use or annual tilling, can impact arthropod biodiversity 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 arthropods 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 habitats, followed by abandoned agriculture, switchgrass, and lastly miscanthus.
Flying insects 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 leaf 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 biofuel grasses at the
Wilds compared to the Ridges Land Lab. This current study shows that cellulosic ethanol 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 family 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 Biofuels: Cellulosic Ethanol and Biodiesel ...... 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. Biomass 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 electricity. Long term use of coal 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 plants 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 gasoline replacements come from biofuel sources such as ethanol. Biodiesel is produced from oils or fats using transesterification (usually from soybeans), or from pure plant 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 combustion 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 nutrient 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 farm has very different implications than changing pasture 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 species 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 grassland 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 net energy gain, 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 Wood Microscopic Crop Name Soybean Switchgrass Miscanthus Crop Residue Oil Palm Grain Residue Algae Annual Perennial Perennial Wastes from Annual Straw from Perennial C4 C4 C4 timber harvest Micro-crop Type of Crop C3 cereal crops C3 Grain Leaf/stem Stem and processing Algae lipids Oil seed etc. Oil Seed Starch Cellulose 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 sand 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 Fertilizer 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 Pesticides needed needed pesticides Global 18 (Europe) 2.9 (seed), 14 (fruit), 2.9 Average Yield 5.2 dry 14 dry 38 (North America) - - 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 corn ethanol 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 electricity generation 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. Natural gas 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 greenhouse gas emissions and economic activity.
1.2.2 Available American Cropland
In order 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 insect populations in Germany 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 herbicide 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 hybrid. 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 rhizome 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. forbs and other grassy type weeds).
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 Miscanthus sinensis. 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 cultivars 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, mammals, 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 sustainable biofuel 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 prairie 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 animal grazing
(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 wildlife preserve in partnership with 30 the Columbus Zoo and Aquarium and animals 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 decomposition.
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), Entognatha (Collembolans), Malacostraca (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 Isopoda) 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 Entomobryomorpha) 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).
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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.
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3.1.3 Impact of Habitat Type on Arthropod Diversity
Diversity was calculated using the Shannon index (H) (Southwood and Henderson
2000) (eq. 1):