Terrestrial Arthropod Community and Indicators of Biotic Integrity for Iowa Tallgrass Prairie Jessica Marie Orlofske Iowa State University

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Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations

2008 Terrestrial arthropod community and indicators of biotic integrity for Iowa tallgrass prairie Jessica Marie Orlofske Iowa State University

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Recommended Citation Orlofske, Jessica Marie, "Terrestrial arthropod community and indicators of biotic integrity for Iowa tallgrass prairie" (2008). Retrospective Theses and Dissertations. 15391. https://lib.dr.iastate.edu/rtd/15391

This Thesis is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Terrestrial arthropod community and indicators of biotic integrity for Iowa tallgrass prairie

Jessica Marie Orlofske

A thesis submitted to the graduate faculty

in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

Major: Ecology and Evolutionary Biology

Program of Study Committee: Diane M. Debinski, Major Professor Matthew E. O’Neal Brent J. Danielson Dianne H. Cook

Iowa State University

Ames, Iowa

2008

1454697 2008 ii

TABLE OF CONTENTS

ABSTRACT iii

CHAPTER ONE. GENERAL INTRODUCTION Background 1 Objectives 16 Justification 17 Thesis Organization 17 Literature Cited 18 Tables and Figures 21

CHAPTER TWO. ARTHROPOD COMMUNITY OF REMNANT, RESTORED, AND RECONSTRUCTED IOWA TALLGRASS PRAIRIE: A COMPARISON Abstract 25 Introduction 26 Methods 28 Results 31 Discussion 36 Conclusions 40 Acknowledgements 40 Literature Cited 42 Tables and Figures 44

CHAPTER THREE. TERRESTIAL ARTHROPOD INDICATORS FOR ECOLOGICAL RESTORATION OF IOWA TALLGRASS PRAIRIE Abstract 69 Introduction 70 Methods 72 Results 74 Discussion 76 Conclusions 80 Acknowledgements 81 Literature Cited 82 Tables and Figures 84

CHAPTER FOUR. GENERAL CONCLUSIONS 101 Literature Cited 103

APPENDIX. SUPPLEMENTAL FIGURES FOR CHAPTER TWO 104

ACKNOWLEDGEMENTS 117

iii

ABSTRACT The tallgrass prairie has become one of the most endangered ecosystems in North America. Thus, there have been attempts to restore and reconstruct native tallgrass prairie. Arthropods, the most diverse taxonomic group on the prairie, have not received adequate attention. A comprehensive arthropod survey in Iowa prairies has not been attempted since the 1930’s, and therefore lacks information regarding recent prairie restoration efforts. Arthropods can also provide valuable information related to ecosystem function or biotic integrity when used as bioindicators. However, effective, reliable arthropod bioindicators have not been clearly identified. A survey of arthropods using sweep net transects was conducted on a cross-section of Iowa prairies among three prairie types: remnants, isolated restorations/ reconstructions and landscape-scale integrated reconstructions. We compared the arthropod community across sampling years, sites, and site types. We used Indicator Species Analysis to identify families of insects and spiders that could be used as indicators of biotic integrity or restoration success. Arthropod communities differed slightly between years, and between prairie types. Convergence among prairies of different anthropogenic types may mean restoration efforts have been successful for the establishment of the native arthropod community. Alternatively, decades of human disturbance at the regional scale may have reduced or eliminated prairie restricted taxa. Both of these explanations may actually be accurate. Four insect families and one spider family were identified as indicators of remnant prairies, with additional taxa demonstrating some affinity to remnant sites. Indicator taxa we identified provide further support for previously identified indicators, such as ants (Formicidae), but also include taxa not previously recorded as prairie bioindicators.

CHAPTER ONE. GENERAL INTRODUCTION

BACKGROUND

To study ecology means to study a suite of interacting factors. It is difficult to isolate one particular organism and still understand it in an ecological context. We strive to understand not just the individual organism but also the connections among and between the organisms and the environment. One area of study that results from the complexity of interaction between organisms and their environment is the study and testing of bioindicators. Bioindicators have been defined as resident species or taxa that reflect abiotic and biotic environmental conditions, represent environmental change in a particular habitat, community or ecosystem, or correlate with the diversity patterns of other species (Dufrene and Legendre 1997, McGeoch 1998, Rainio and Niemelä 2003, Hodkinson and Jackson 2005). Bioindicators are important in ecology because oftentimes they indicate connections that would be difficult to recognize, test, or measure directly. The application and identification of bioindicators is considered by McGeoch (1998) to be a subdiscipline of conservation biology, since bioindicators have received the most attention when applied to a multitude of conservation issues. Applications of bioindicators, however, are not limited to conservation biology, but also include biogeography (Luff et al. 1989, Sadler and Dugmore 1995), restoration ecology (Shepherd and Debinski 2005a), and climateological studies (Kremen et al. 1993). The use of bioindicators in ecological studies began as early as the 1910s and 1920s for use in the evaluation of water quality, particularly in streams affected by anthropogenic disturbance and pollution (Hilsenhoff 1977, Kimberling et al. 2001, Carignan and Villard 2002). There is some indication that studies of bioindicators, although not defined as such, began even earlier (Paoletti 1999). Since these initial studies, there have been refinements in the use of aquatic organisms as indicators. The number of potential bioindicators has grown, and the concept of bioindicators has extended beyond aquatic systems to the terrestrial landscape. Perhaps the reason bioindicators have and continue to receive attention is their ability to provide scientists and conservationists with information that would be otherwise 2 impossible, difficult, time-consuming, or expensive to obtain from alternative methods (Carignan and Villard 2002). In many ways the practice of conservation biology is triage, which requires reliable, cost-effective tools such as bioindicators to make decisions (Soulé 1985). Bioindicators can integrate information from several parameters at once and provide perpetual information since they occupy the habitat continuously, unlike information obtained from point samples of chemical or physical parameters (Hodkinson and Jackson 2005). Unfortunately, it takes time and resources to identify and test potential indicators in a variety of habitats and systems for various conservation questions.

Types of Bioindicators

The bioindicator literature is riddled with definitions and terminology. The rapid development of this area necessitates that scientists working with bioindicators need to specify the type of indicator and identify the factor to which it is responding. According to reviews by McGeoch (1998) and Paoletti (1999), indicators can be used for a broad range of ecological issues including habitat alteration, destruction, restoration, contamination, vegetation patterns, climate change, species diversity, agricultural practices, and sustainability. Each application requires different information, and different indicators should be used. McGeoch (1998) suggests three types of indicators: environmental, ecological, and biodiversity. Environmental indicators are used to signify abiotic (chemical or physical) characteristics of an area or habitat. They can be used to detect the presence of materials such as pesticides, heavy metals, and other pollutants. Ecological indicators are used to represent environmental stressors on the biotic community, such as the presence of particular organisms following restoration (Longcore 2003). Biodiversity indicators are taxa that are used to represent the overall diversity of an area or diversity of related or even unrelated taxonomic groups. Hodkinson and Jackson (2005) adapted McGeoch’s (1998) categories of indicators by classifying the impact factor or habitat characteristic. They identified four impact factors that bioindicators are used to indicate: physical environment, chemical environment, habitat quality or conservation values among sites, and ecological status of a site through time. 3

Indicators of the physical environment reflect alterations in temperature (mean, range, extremes), precipitation patterns, ultraviolet radiation, and soil compaction. In aquatic systems, these physical attributes include current, substrate type, and depth. The chemical parameters that may be detected include pH, heavy metal pollutants, pesticides, and fertilizers. Habitat quality and conservation value is the most ambiguous of the four factors they identify. Hodkinson and Jackson (2005) did not define habitat quality directly, but implied that it incorporates biodiversity, condition, and structure (see Table 2 in Hodkinson and Jackson 2005). Their final factor is habitat change through time and management. This factor is broad, and encompasses a wide range of anthropogenic impacts, along with accompanying restoration and reclamation efforts. It seems reasonable that this factor could be further divided into two components: the perceived negative impacts with a suite of indicators that are either tolerant or intolerant to that change, and the perceived positive impacts of recovery with a suite of indicators that respond positively to the management practices.

Scale of Indicator Response

Beyond simply defining the type of indicator or impact factor is consideration of the criteria of the organism/taxon to be used for bioindication. The responses of individual animals, species, populations, or entire communities have all been used for a variety of bioindicator studies (Hodkinson and Jackson 2005). Chemical and physical changes to the environment over a relatively short period, may best be described by the responses of individual animals based on their morphology, physiology, and behavior (Hodkinson and Jackson 2005). In some cases, examination of many individuals of the same species for these perturbations is also necessary (Hodkinson and Jackson 2005). More commonly, however, the species or population is used as an ecological indicator or for questions related to habitat change (Hodkinson and Jackson 2005). Distribution patterns and the abundance of the indicator characterize the effect of the impact on the environment in question (Hodkinson and Jackson 2005). Community-level responses based on multiple species can provide the most detailed perspective on change in their 4 environment (Hodkinson and Jackson 2005). A single species can only represent a small range of conditions; therefore, multiple species can be used to study questions of habitat, landscape, and ecosystem change (Carignan and Villard 2002). Typically, not all species are utilized but more than one species is found to respond to the impact or alteration, usually on a broader scale (Hodkinson and Jackson 2005). Noss (1990) even suggests that indicators should be selected from different taxonomic levels depending on the research question. The combination of indicator, impact factor, and level of response are summarized in Table 1.

Terrestrial Indicators

Application of bioindicators have been slow to transition from aquatic to terrestrial systems. Aquatic systems possess characteristics that aid in the identification of distinctly delineated indicators and the factors they are representing. Aquatic systems possess fewer taxa than typical terrestrial systems and have fewer variable abiotic components, and the organisms have stronger associations with the physical and chemical properties of the system (McGeoch 1998). In aquatic systems the presence or absence of particular organisms can be clearly related to pH, chemical contamination, temperature changes, oxygen levels and other physical and chemical characteristics of the water body (Hodkinson and Jackson 2005). This relationship is not as straightforward in terrestrial systems given the greater diversity, fewer quantifiable abiotic factors, and potentially more mobile organisms (McGeoch 1998).

Selection of Terrestrial Indicators

The on-going debate in the bioindicator literature focuses on the selection and testing of proposed bioindicators for all factors and levels. Early bioindicators were selected on the basis of personal or public preference (Carignan and Villard 2002). Later methods included some measure of habitat preference or restriction, owing to the fact that more selective species could be better potential indicators (Carignan and Villard 2002). Various multivariate and mathematical methods have also been employed to identify potential indicators (Dufrêne and Legendre 1997, Carignan and Villard 2002). Noss (1990) used a list of criteria for 5 evaluating potential indicators. McGeoch (1998) proposed a nine-step process for the identification and testing of potential indicators as well as a list of suggested criteria for the selection of bioindicators by type. Hodkinson and Jackson (2005) also provide a five-point list of criteria for bioindicator selection. Methods not restricted to the selection of a single species but rather those that examined species composition and richness, trophic composition, and organism abundance and condition as indicators were proposed by Karr (1991). Later, Kimberling et al. (2001) examined the response of a pool of candidate taxa and guilds (feeding or functional groups) to identify the most parsimonious indicators. These disparate methods are summarized in Table 2. There is no consensus, however, and bioindicators continue to be proposed and selected from a variety of approaches, although as Carignan and Villard (2002) point out selection can be based on both qualitative and quantitative criteria. McGeoch (1998), points out that many past (and current) bioindicator studies do not test their indicators in the context in which they propose to use them. Further, many of these studies do not supply guidelines for the application of the indicator to the conservation or ecological question (McGeoch 1998, Hodkinson and Jackson 2005). There is a tradeoff between selecting and testing potential indicators given the urgency of conservation need (McGeoch 1998). Often researchers publish their potential indicators before they are adequately tested to address a conservation question of immediate importance (McGeoch 1998). It is also difficult to allocate time and financial resources to a method or tool that is supposed to save time and resources. McGeoch (1998) rightly implores researchers to do careful and thorough work testing proposed bioindicators.

Biotic/ Ecological Integrity

Bioindicators are typically employed to measure properties of a habitat or ecosystem that are difficult to measure directly. One of these properties is biotic integrity. Much like defining an organisms’ niche, biotic integrity is a combination of many components that are equally hard to define for each particular habitat or ecosystem. Biotic integrity has been defined as “the ability to support and maintain a balanced, integrated, adaptive community 6 of organisms having a species composition and functional organization comparable to that of natural habitat in the region” (Karr 1991). This definition is hindered by the lack of representative reference sites for many habitat types. Additionally, many habitats lack baseline data prior to human disturbance. There is also an assumption of a “biotic integrity climax” or steady-state that is not ecologically sound and promotes misconceptions by the public concerning biotic integrity (Carignan and Villard 2002). Natural processes such as disease, parasitism, predation, competition, migration, and stochasticity need to be incorporated into our evaluation of biotic integrity. These processes are part of the biotic integrity but can cause a reduction in the potential bioindicators (Carignan and Villard 2002). Yet, biotic integrity is a more holistic goal for a conservation or management program, since diversity alone is a poor surrogate for the overall status of a habitat or ecosystem.

Indices of Biotic Integrity

Bioindicators are a measure of biotic integrity. Multimetric indices of bioitic integrity are another method that have been proposed and successfully used in aquatic systems (Hilsenhoff 1977, Kimberling et al. 2001). Indices of biotic integrity are often used to evaluate current conditions, compare the quality of different sites of the same habitat (i.e., streams; Hilsenhoff 1977), evaluate changes over time (i.e., restoration/ timber management; Kimberling et al. 2001, Allegro and Sciaky 2003), and identify the cause of degradation (Karr 1991). Multimetric indices benefit from examining more than one component of the habitat or area by recognizing what each component represents in the system (Karr 1991). This is accomplished via “tolerance values.” Hilsenhoff (1977, 1987, 1988) used a ranking of stream quality to determine which taxa were sensitive to organic pollution or the resulting decrease in dissolved oxygen and could tolerate particular levels of organic pollution. In a similar fashion, Kimberling et al. (2001) determined which characteristics (taxa or guilds) of arthropods changed consistently with human disturbance. When examining both of these approaches, it is clear that some selected arthropods, which are sensitive to pollution or disturbance, could serve as bioindicators. Indices of biotic integrity may therefore make use 7 of bioindicator studies by incorporating potential indicators into their quantitative evaluations of habitat quality.

Inventory versus Monitoring

Bioindicators can play a role in both inventory and monitoring programs. Many conservation questions inquire about the current status of the biodiversity of an area or habitat. For these purposes, one may initiate an inventory. Inventories often describe the distribution of species, populations, communities, guilds, and ecosystems (Kremen et al. 1993). Monitoring, in contrast, is meant to identify changes over time caused by natural or anthropogenic factors (Kremen et al. 1993). Biodiversity indicators can be used for inventory purposes when they represent taxa that may be more difficult to observe directly. Ecological indicators can be used to indicate change in a habitat or ecosystem as an alternative to sampling or measuring the entire community. Both activities, inventory and monitoring, should be hypothesis driven and used to generate data for original research questions (Noss 1990).

Invertebrates as Terrestrial Indicators

The list of current and proposed terrestrial bioindicators are as diverse as the habitats, conservation issues, management techniques, and sampling methods with which they are associated. Organisms from a wide array of taxonomic levels have been suggested or used as indicators (Kremen et al. 1993). Depending on the system, habitat, management practice and other variables, a strong argument could be made for the application of bioindicators from any taxonomic group. Invertebrates - specifically arthropods - offer some unique advantages over other groups of bioindicators, but with concomitant challenges.

The use of terrestrial arthropods has the following advantages:

1. Diversity. Arthropods are the most diverse members of the planets’ biota. Among the animals, insects may represent more than 80% of known species (Pearson and Cassola 1992). In some habitats, the dominance by terrestrial arthropods can be even higher (Kremen et al. 1993). If the goal of a research program is to assess conservation priority from the biodiversity perspective, it makes sense to examine the most diverse taxa (Kremen et al. 1993). Arthropod diversity can also make the ecological connections more difficult to identify, as simple systems are sometimes far more interpretable, as well as adding to taxonomic difficulties (see disadvantage 1).

2. Distribution. Arthropod distribution can be more finely patterned (compared to vertebrates and vascular plants), but also overlap with other taxonomic groups (Kremen et al. 1993, Andersen et al. 2004). Arthropod distributions also reflect the ecological processes of seasonal change, successional patterns, and patch dynamics (Kremen et al. 1993).

3. Sensitivity. Arthropods exhibit sensitivity to disturbance and rapidly respond to conditions at the individual, species, population, and community level (Andersen et al. 2004). Arthropods can reflect change with greater detail because of their high fecundity and short generation times (Ward and Larivière 2004). Under unfavorable conditions arthropods may disappear, and when conditions change they can rapidly recolonize (Kremen et al. 1993).

4. Functional Roles. Arthropods display a diversity of functional roles and ecological niches in ecosystems (Kremen et al. 1993, Kimberling et al. 2001, Andersen et al. 2004). These roles include pollination, soil formation and fertility, plant productivity, organic decomposition, regulation of other organisms via predation and parasitism, as well as serving as prey for many other organisms (Ward and Larivière 2004).

5. Varying Life History Traits. Arthropods have diverse life history strategies, varying body sizes, vagilities, growth rates, dispersal patterns, and ecological preferences (Kremen et al. 1993, Hodkinson and Jackson 2005). These specific life history qualities can be associated with environmental conditions (Ward and Larivière 2004). Taxa with multiple life-stages may be useful for some ecological applications, while taxa with direct development may more clearly correlate with specific environmental attributes.

6. Large Populations. Arthropods often possess large population sizes, therefore it is usually not difficult to get an adequate sample size for statistical analysis (Kremen et al. 1993).

7. Ease of Sampling. Arthropods are relatively easy to sample with a variety of methods that can be standardized to address a wide array of ecological questions (Kimberling et al. 2001, Andersen et al. 2004).

8. Ease of Specimen Preservation. Arthropods can be maintained for long periods of time in reference collections, which aids in identification and the deposition of vouchers (Kremen et al. 1993).

9. Fewer Regulations. Arthropod collection has fewer regulations prohibiting the collection and preservation of specimens compared with the collection of vertebrates (Kremen et al. 1993).

Despite the many assets of using terrestrial arthropods as indicators, researcher’s attempting to identify and use terrestrial arthropods as indicators must overcome the following obstacles:

1. Taxonomic Difficulty. Since arthropods are so diverse, it is difficult to quickly and reproducibly sort and identify the abundant specimens obtained from many of the customary collection methods (New 1998, Ward and Larivière 2004). Arthropods, and many other 10 groups of organisms, also suffer from a lack of trained taxonomists adding to the difficulty of identifying specimens (New 1998, Ward and Larivière 2004).

2. Undescribed Taxa. Arthropods are probably the most diverse group of organisms, a title that they will likely retain as many new species may yet be unknown and undescribed (Ward and Larivière 2004). This potential for undiscovered species is also not consistent across the landscape, but is focused in areas of high biodiversity, such as the tropics, complicating the conservation issues that bioindicators were designed to help solve.

3. Limited Specific Knowledge. The diversity of arthropod life history strategies, although of great benefit to biodiversity and bioindicators studies, results in a lack specific knowledge concerning ecological roles, patterns of diversity and distribution, and even responses to environmental conditions (Andersen et al. 2004, Ward and Larivière 2004).

4. Limited Public Support and Trained Resource Professionals. Arthropods often do not receive the attention and financial support of the public, elected officials, and funding agencies (Ward and Larivière 2004). In addition, many land-managers and agency officials are not aware that arthropods could be incorporated into monitoring and management policies (Andersen et al. 2004). This, however, has changed for the better over the past few decades.

5. Lack of Standardized Methods. There are as many different methodologies, from collection and sampling methods to sorting strategies and identifications (e.g., higher taxonomic groups, to species, to morphospecies) as proposed bioindicators. Collection protocols have been developed for many arthropods and habitats (New 1998), but they are not conducted consistently across sites and between years. Therefore, the development of arthropod indicators suffers from a lack of consistent, clear, reproducible methods of sampling and analysis (Ward and Larivière 2004).

6. Lack of Baseline Data. In many habitats and areas, historical accounts of arthropods may be incomplete or nonexistent. This lack of historical or baseline data makes it difficult to monitor current and future changes in the habitat, and design restoration goals.

Various solutions to these complications have been proposed in the bioindicators literature. Yet, each of these options has advantages and disadvantages that need to be considered in the context of the conservation or management goals.

Single taxa

One of the proposed solutions to the taxonomic barrier is to focus on a single taxon (species, genus, or family) for bioindicator programs (Andersen et al. 2004). The main advantage of focusing on one taxon is reduced time and cost associated with collection, identification, and specimen sorting. Many single species or single taxon studies have been motivated by specialists working on that taxon rather than the bioindicator qualities of the particular taxon (Hodkinson and Jackson 2005). Single taxon studies also suffer from lack of replication and are too specific for broad scale conservation programs (Hodkinson and Jackson 2005).

Morphospecies

Another potential solution to the taxonomic impediment of using arthropods as bioindicators is the use of taxonomic surrogacy: the identification of morphospecies (MSP) or recognizable taxonomic units (RTUs), rather than identifying each specimen to the species level (Ward and Larivière 2004). This approach saves time and can allow non-experts or parataxonomists to perform the majority of specimen sorting and preparation, saving the trained taxonomist’s valuable time (Ward and Larivière 2004). This technique also has some serious drawbacks. The identification of MSP is highly subjective and each laboratory assistant may lump or split the specimens differently, and even if all workers designated the same MSP, a taxonomist would still have to examine the 12 specimens to determine the actual number of species. This is further complicated by sexual dimorphism, which could arbitrarily increase the number of species; likewise cryptic species could decrease the number of recorded species. It is also difficult to coordinate MSP across studies and time (Ward and Larivière 2004). The use of MSP could also disguise invasive species in a particular habitat since they may be undifferentiated from other native arthropods. Another concern with the use of MSP is that without actual taxonomic information it is nearly impossible to retrieve ecological or natural history information regarding the specimen. This is especially relevant for ecological indicators, since their connection to the habitat is of importance. True identification is less important for biodiversity indicators, whose selection is based more on their diversity and distribution patterns in relation to other organisms in the same system or habitat.

Higher taxa

Another attempt to reduce the time and cost associated with invertebrate collection and inventory is to identify the specimens to a higher taxonomic level, such as order or family (Hodkinson and Jackson 2005). This practice, however, may not be as informative, especially in more complex and diverse terrestrial systems (Ward and Larivière 2004). Higher taxonomic identification usually results is some loss of resolution since these levels contain species with varying life histories and sensitivities (Ward and Larivière 2004), although depending on the type of indicator and impact factor, there may not be any advantage to lower taxonomic resolution (McGeoch 1998). In any case, one cannot assume without examining the data whether higher taxa would be effective for the particular objective.

Functional Groups / Guilds

Functional groups as bioindicators represents another approach. A functional group or guild is a collection of presumably unrelated species or higher taxa that perform similar functions within their community (Hodkinson and Jackson 2005). Rather than focusing 13 solely on the taxonomic status of the organism, preference is given to its ecological role, or function. This can help connect the diversity of a habitat with the arthropods’ roles in the ecosystem. Functional groups, guilds, and trophic levels can all be used in addition to taxonomic identification (McGeoch 1998). With some taxa, functional groups can be determined based on morphological characteristics, which would reduce the requirement for identification by taxonomic specialists (Kremen et al. 1993).

Multiple taxa

Groups of species can be more useful for bioindicator programs. For example, aquatic systems are evaluated using many organisms rather than just one species (McGeoch 1998). Instead of focusing on one species or group, or trying to collect information on all species or groups, the selection of multiple species with unique characteristics and affinities to environmental characteristics can be used to better monitor changes and reduce interpretation errors (Carignan and Villard 2002). Multiple species can demonstrate different food preferences, feeding habits, body sizes, fecundity, voltinism, development time, and vagilities within the same habitat, providing a more complete assessment of the conservation question (Hodkinson and Jackson 2005). The multiple taxa approach can also benefit from the inclusion of selected higher taxa and even functional groups and guilds (Kremen et al. 1993, Carignan and Villard 2002). Paoletti (1999) suggests that more dependable results can come from the examination of select species, higher taxa, and guilds that include richness, abundance, and dominance data. Hodkinson and Jackson (2005) also recommend measuring “important species” such as keystone species, in their environment. A shortcoming of this method is that every time you add another component to the collection of analysis, you create more time-consuming surveys and more taxonomic hurdles.

Current Terrestrial Arthropod Indicators

The combination of diverse research questions, habitats, taxonomic precedence and preference, selection methods, and impact factors, has resulted in various terrestrial arthropod taxa and assemblages being proposed as bioindicators. Some of the most recent are summarized in Table 3. Few of current terrestrial arthropod bioindicator studies consistently treat one habitat or ecosystem. This has hampered the development of conservation tools as it spreads researchers and resources across the physical and intellectual landscape. Examining one ecosystem in greater detail may offer greater insight into the identification and application of bioindicators. The prairies and grasslands of North America offer a prime location both for the study of bioindicators and an immediate need for their application.

Prairies

The North American grassland, temperate grassland biome, or prairie, once approximately covered an area from eastern Iowa west to the Rocky Mountains, north into several Canadian provinces, including southern portions of Manitoba, Saskatchewan, and Alberta, and south into Texas (Savage 2004). This biome is recognized by the dominance of non-woody vegetation, primarily grasses, including Big bluestem (Andropogon gerardii), Little bluestem (Schizachyrium scoparium), Buffalo grass (Buchloe dactyloides), Needle- and-thread grass (Hesperostipa comata), Indian grass (Sorghastrum nutans) and Sideoats grama (Bouteloua curtipendula; Jones and Cushman 2004). However, a variety of specialized forb species occur throughout the grassland, including compass plant and relatives (Silphium spp.), coneflowers (Ratibita spp. and Echinacea spp.), and milkweeds (Asclepias spp.; Jones and Cushman 2004). Prairies can be divided into several smaller categories, or ecoregions, along a precipitation and topographical gradient across the continent. These ecoregions have specific vegetation characteristics, including plant species composition and growth form (Jones and Cushman 2004, Savage 2004). Prairies lie in a continuum between short-grass prairie in the 15 west nearest the Rocky Mountains to mixed-grass prairie in the center of the continent, and tall-grass prairie in the eastern reaches of the biome (Jones and Chapman 2004). Additional divisions can be made based on local conditions such as soil type and depth to water table (Coupland 1961). The current range and distribution of prairies and their associated communities is determined by a suite of interactions in the biotic and abiotic environment. These factors primarily include climate, disturbance, and topography. Prairie established where precipitation was insufficient to support larger, woody vegetation, or where disturbances, including animal grazing and fire precluded the development of forest species (Wells 1970). The gently rolling topography that is common in the North American prairies aided in the rapid spread of disturbances, like fire, across the landscape (Wells 1970). Grasslands are also home to a variety of arthropods, including butterflies, grasshoppers, beetles, and spiders (Jones and Cushman 2004). Particular species of insects are endemic, rare, and endangered, like the Regal fritillary (Speyeria idalia) (Shepherd and Debinski 2005b) and the American burying beetle (Nicrophorus americanus) (Lomolino et al. 1995). The tall-grass prairie is perhaps the most widely recognized subdivision of the North American grassland biome (Hamilton 2005). The characteristics of tall-grass prairie, such as rich soil, relatively flat topography, and consistent rainfall, made it prime agricultural land (Hamilton 2005). Agriculture, and elimination of the disturbance regime, typically fire, has resulted in a vast reduction in tall-grass prairie since European settlement (Hamilton 2005). Currently, tall-grass prairie vies for the spot as one of the most endangered ecosystems in North America (Hamilton 2005). Small patches of less-impacted remnant prairies are scattered across the former range of the tall-grass prairie (Hamilton 2005). This is especially true in Iowa, where less that 0.1% of the original tall-grass prairie remains (Smith 1998). The endangered status of tall-grass prairie may be one reason for a growing interest in ecological restoration. One definition for ecological restoration is “the process of repairing or recreating natural ecosystems that have been damaged by the actions of humans” (Shepherd and Debinski 2005a). Ecological restoration is hampered by a lack of communication between researchers and restoration practitioners who are often private citizens, as well as a 16 lack of clearly defined goals, and methodologies to achieve the goals (Shepherd and Debinski 2005a). Particularly in prairies, much attention is paid to the plant community and the establishment of native plant species (Panzer and Schwartz 1998). Yet, the goal of the restoration should be to return the function of the natural system, not just the composition (Shepherd and Debinski 2005a).

Prairie Indicators

Terrestrial arthropod indicators may be used as one method of prairie evaluation. Research by Shepherd and Debinski (2005a) on Lepidoptera and Jonas et al. (2002) on Coleoptera and Orthoptera, represent of few of the studies that examined selected taxa in the evaluation of grasslands. Studies by Kimberling et al. (2001) in shrub steppe and Longcore (2003) in coastal sage scrub also demonstrate the utility of arthropod communities to evaluate restoration of other types of habitats. My examination of a broader selection of prairie arthropods across a variety of Iowa prairie types will aid in the identification of essential prairie bioindicators.

OBJECTIVES

The development of arthropod indicators for tall-grass prairie is hindered by a lack of baseline arthropod data, standardized sampling methodology, and limited selection of arthropod taxa for indicators purposes. The primary objective of this research is to address each of these challenges. We collected baseline invertebrate data across a gradient of natural and reconstructed tall-grass prairies in Iowa using standardized sampling techniques. Using statistical approaches and the ecological characteristics of the individual taxa, we selected potential bioindicators from the arthropod community. Higher taxa that are identified as potential indicators can then be used for further detailed study.

JUSTIFICATION

The recognition of anthropogenic influence on the planet, the loss of worldwide biodiversity, habitat fragmentation and degradation, pollution and contamination, invasive species, and a whole host of other ecological and conservation biology questions can be informed by bioindicators, necessitating the challenge of their development for terrestrial systems (Kremen et al. 1993, Marc et. al. 1999). The endangerment of tall-grass prairie ecosystems and the subsequent attempts at restoration by a variety of organizations and individuals provide the ideal motivation and cooperation necessary for the development of terrestrial arthropod bioindicators. According to McGeoch (1998), ecological indicators are the most important area of current bioindicator development. This research can be used as a model for ecological indicators studies in other prairie types (short-grass, mixed-grass), and even other terrestrial ecosystems.

THESIS ORGANIZATION

This thesis is composed of an introductory chapter (chapter one) and three additional chapters each written as separate publications for appropriate journals. The second chapter of this thesis contains the results of the baseline prairie invertebrate surveys conducted from 2006 – 2007 and shows the broad relationships among arthropod taxa within different types of Iowa prairie. The next chapter details the preliminary selection of bioindicator taxa without a priori selection. The final chapter provides a general conclusion and a synthesis of the individual chapters.

LITERATURE CITED

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Jonas, J.L., M.R. Whiles, and R.E. Charlton. 2002. Aboveground Invertebrate Responses to Land Management Differences in a Central Kansas Grassland. Environ. Entomol. 31(6): 1142-1152. Jones, S.R. and R.C. Cushman. 2004. The North American Prairie. Peterson Field Guides. Houghton Mifflin Company. Karr, J.R. 1991. Biological Integrity: A long-neglected aspect of water resources management. Ecological Applications. 1(1): 66-84 Kimberling, D. N., J.R. Karr, and L.S. Fore. 2001. Measuring Human Disturbance Using Terrestrial Invertebrates in the Shrub-steppe of eastern Washington (U.S.A). Ecological Indicators 1: 63-81. Kremen, C, R.K. Colwell, T.L. Erwin, D.D. Murphy, R.F. Noss, and M.A. Sanjayan. 1993. Terrestrial Arthropod Assemblages: Their use in Conservation planning. Conservation Biology. 7(4): 796-808. Lomolino, M.V., J. C. Creighton, G. D. Schnell, and D. L. Certain. 1995. Ecology and Conservation of the Endangered American Burying Beetle (Nicrophorus americanus). Conservation Biology. 9(3): 605-614. Lomov, B. D.A. Keith, D.R. Britton, and D.F. Hochuli. 2006. Are butterflies and moths useful indicators for restoration and monitoring? A pilot study in Sydney’s Cumberland Plain Woodland. Ecological Management and Restoration. 7(3): 204- 210. Longcore, T. 2003. Terrestrial Arthropods as Indicators of Ecological Restoration Success in Coastal Sage Scrub (California, U.S.A.). Restoration Ecology. 11(4): 397-409. Luff, M. L., M.D. Eyre and S.P. Rushton. 1989. Classification and ordination of habitats of ground beetles (Coleoptera, Carabidae) in north-east England. Journal of Biogeography. 16: 121-130. Marc, P., A. Canard, and F. Ysnel. 1999. Spiders (Araneae) useful for pest limitation and bioindication. Agriculture, Ecosystems and Environment. 74: 229-273. McGeoch, M.A. 1998. The selection, testing and application of terrestrial insects as bioindicators. Biol. Rev. Cambridge Philosophical Society 73: 181-201. New, T.R. 1998. Invertebrate Surveys for Conservation. Oxford University Press. Noss, R.F. 1990. Indicators for Monitoring Biodiversity: A Hierarchical Approach. Conservation Biology. 4(4): 355-364. Panzer, R. and M. W. Schwartz. 1998. Effectiveness of a Vegetation-Based Approach to Insect Conservation. Conservation Biology 12:693-702. Paoletti, M.G. 1999. Using bioindicators based on biodiversity to assess landscape sustainability. Agriculture, Ecosystems, and Environment. 74:1-18. Pearson, D.L. and F. Cassola. 1992. World-wide species richness patterns of tiger beetles (Coleoptera: Cicindelidae): Indicator Taxon for biodiversity and Conservation Studies. Conservation Biology 6(3): 376-391. Rainio, J. and J. Niemelä. 2003. Ground beetles (Coleoptera: Carabidae) as bioindicators. Biodiversity and Conservation. 12: 487-506. Rodriguez, J. P., D. L. Pearson, and R. Barrera. 1998. A test for the adequacy of bioindicator taxa: are tiger beetles (Coleoptera: Cicindelidae) appropriate indicators for monitoring the degradation of tropical forests in Venezuela? Biolological Conservation. 83: 69-76. 20

Sadler, J.P. and A.J. Dugmore. 1995. Habitat distribution of terrestrial Coleoptera in Iceland as indicated by numerical analysis. Journal of Biogeography. 22: 141-148. Savage, C. 2004. Prairie: A Natural History. Greystone Books. Shepherd, S, and D.M. Debinski. 2005a. Evaluation of isolated and integrated prairie reconstructions as habitat for prairie butterflies. Biological Conservation.126: 51-61. Shepherd, S. and D. Debinski. 2005b. Reintroduction of Regal Fritillary (Speyeria idalia) to a Restored Prairie. Ecological Restoration 23: 244-250. Smith, D.D., 1998. Iowa Prairie: original extent and loss, preservation and recovery attempts. Journal of the Iowa Academy of Science. 105: 94-108. Sommaggio. D. 1999. Syriphidae: can they be used as environmental bioindicators? Agriculture, Ecosystems and Environment. 74: 343-356. Soulé, M.E. 1985. What is Conservation Biology? BioScience 35 (11): 727-734. Villa-Castillo, J. and M.R. Wagner. 2002. Ground Beetle (Coleoptera: Carabidae) species assemblage as an indicator of forest conditions in northern Arizona ponderosa pine forest. Environmental Entomology. 31(2): 242-252. Ward, D.F. and Marie-Claude Larivière. 2004. Terrestrial invertebrate surveys and rapid biodiversity assessment in New Zealand: lessons from Australia. New Zealand Journal of Ecology. 28(1): 151-159. Wells, P.V. 1970. Postglacial Vegetational History of the Great Plains. Science. 167: 1574- 1582.

TABLES AND FIGURES

Table 1. Comparison of alternative definitions of bioindicators, impact factors, and level of indicator response (Hodkinson 2005, McGeoch 1998)

Indicator Type Impact Factor Level of Response Environmental Physical Individual Species Chemical Individual Species Ecological Habitat Quality Species Community Habitat Change Species Community Biodiversity Habitat Quality Species Community 22

Table 2. Bioindicator selection method and references.

Reference Summary of Bioindicator Selection Method

A list of qualitative criteria for the selection of bioindicators. The 7 point list includes: 1) sensitivity to change, 2) broadly distributed, 3) occurs across different degrees of the impact factor, 4) results independent of Noss 1990 sample size, 5) easy and inexpensive to collect and analyze, 6) detectable differences between natural variation and that created by the impact factor, and 7) ecologically relevant.

A mathematical formula that uses within species comparisons to construct the site typology, and the Dufrêne and indicator value for any given species independent of the Legendre other species sampled. The indicator species is therefore 1997 defined as the most characteristic species (taxa) of a category of sites.

A systematic procedure aimed at guiding the entire study of bioindicators, including the selection of the indicator. This procedure focuses specifically on the identification of specific objectives, definitions or the question, and testing the relationship between the proposed indicator and the McGeoch ecological characteristic it is assumed to be indicating. 1998 Although lacking in specific statistical or analytical methodology for indicator selection, it does provide an essential framework for bioindicator studies. Also included is a list of additional theoretical criteria for the selection of bioindicators.

A procedure based on two quantitative criteria: frequency Carignan and of occurrence among areas with contrasting levels of the Villard 2001 particular trait of interest, and evaluation of the habitat specialization.

A statistical approach that incorporates multivariate analysis and regression of taxa and guilds represented in Kimberling et. the invertebrate sampling. Those taxa or guilds that vary al. 2001 predictably with ecological characteristic under consideration are included in a multimetric index.

A qualitative outline of criteria for the selection of Hodkinson bioindicators. These criteria focus on well-known, and Jackson representative, easy to identify, readily collected 2005 arthropods, as well as the consideration of economic and aesthetic appeal. 23 Reference Kimberling et. al. 2001 Longcore 2003 Marc et. al. 1999 Jonas et. al 2002 Dufrêne and Legendre 1997 Rainio and Niemelä 2003 Allegro and Sciaky 2003 Villa-Castillo and Wagner 2002 Rodríquez et. al. 1997 Pearson and Cassola 1992 Selection Method of Bioindicator Muiltivariate, Regression Multivariate Ordination and Cluster Analysis Literature Review Literature Review Multivariate Ordination and Cluster Analysis McGeoch 1998 criteria, previous research data Quantitative Multivariate, Indicator Species Analysis Noss 1990 criteria Noss 1990 criteria Habitat/ Ecosystem Shrub-Steppe Coastal Sage Scrub Various Grassland Gradient of open habitats in Belgium Various Poplar Forest Ponderosa Pine Forest Tropical Forests Global Impact Factor Habitat Quality/ Restoration Habitat Quality/ Restoration Chemical, Physical, Habitat Quality Habitat Quality/ Restoration Habitat Quality Physical, Chemical, Habitat Quality/ Restoration Habitat Quality Habitat Quality Habitat Quality Indicator Type Ecological Ecological Ecological/ Environmental Ecological Ecological Ecological, Environmental, Biodiversity Ecological Ecological Ecological Biodiversity Taxa Table 3. Literature review of terrestial invertebrate bioindicators Arthropod community Arthropod community Araneae Coleoptera Coleoptera: Carabidae Coleoptera: Carabidae: Cicindelinae 24 Reference Iperti 1999 Bouyer 2007 Halffter and Favila 1993, Favila and Halffter 1997 Bohac 1999 Frouz 1999 Sommaggio 1999 Andersen et. al. 2004, Andersen 1997 Lomov et. al. 2006 Shepherd and Debinski 2005 Bouyer 2007 Jonas et. al. 2002 Selection Method of Bioindicator Literature Review Qualitative, Literature Review Noss 1990 criteria Literature Review Literature Review Literature Review Literature Review Literature Review Literature Review Qualitative, Literature Review Literature Review Habitat/ Ecosystem Global African Savannah Tropical Forest Various, Agriculture Various Various, Agriculture Various Woodland Grasslands African Savannah Grassland Impact Factor Physical Habitat Quality Chemical, Physical, Habitat Quality Chemical, Physical, Habitat Quality Chemical, Physical, Habitat Quality Habitat Quality/ Restoration Habitat Quality Habitat Quality/ Restoration Habitat Quality Habitat Quality/ Restoration Indicator Type Environmental Ecological/ Biodiversity Biodiversity Ecological/ Environmental Ecological/ Environmental Ecological/ Environmental Ecological Ecological Ecological Ecological/ Biodiversity Ecological Taxa Table 3. Literature review of terrestial invertebrate bioindicators (continued). Coleoptera: Coccinellidae Coleoptera: Scarabaeidae Coleoptera: Staphylinidae Diptera Diptera: Syrphidae Hymenoptera: Formicidae Lepidoptera Lepidoptera (Butterflies) Lepidoptera: Nymphalidae Orthoptera

CHAPTER TWO. ARTHROPOD COMMUNITY OF REMNANT, RESTORED, AND RECONSTRUCTED IOWA TALLGRASS PRAIRIES: A COMPARISON

A paper to be submitted to Restoration Ecology

Jessica M. Orlofske1, Wayne J. Ohnesorg2, Diane M. Debinski1

1Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, Iowa 50011 USA 2Department of Entomology, Iowa State University, Ames, Iowa 50011 USA

ABSTRACT

The icon of the American Midwest, the tallgrass prairie has become one of the most endangered ecosystems in North America. Thus, attempts to restore and reconstruct native tallgrass prairie have been undertaken. Arthropods, the most diverse taxonomic group on the prairie, warrant greater attention on our remnant and restored tallgrass prairies. A general arthropod survey in Iowa has not been attempted since the 1930’s, and therefore lacks information regarding recent prairie restoration efforts. A survey of arthropods, including insects and spiders families, was conducted using sweep net transects on a cross-section of Iowa prairies among three prairie types: remnants, isolated restorations/ reconstructions and landscape scale integrated reconstructions. Richness and abundance of arthropod families differed slightly, although not significantly, between years and prairie types. Similarity among prairies of different anthropogenic types may mean restoration efforts have been successful for the establishment of the native arthropod community. Alternatively, decades of human disturbance at the regional scale may have reduced or eliminated prairie restricted taxa. Both of these explanations may be accurate; restoration efforts may be successful in maintaining a diverse community of native arthropods, however, prairie endemics may have already been extirpated.

INTRODUCTION

The tallgrass prairie may be the most widely recognized subdivision of the North American grassland biome (Hamilton 2005). The characteristics of tallgrass prairie, such as rich soil, relatively flat topography, and consistent rainfall, made it prime agricultural land (Hamilton 2005). Conversion to agriculture directly reduced the amount of tallgrass prairie habitat, and the elimination of natural disturbances that once maintained prairies, primarily fire and animal grazing, reduced the ecological integrity of remaining prairie areas (Hamilton 2005). As a result of these changes to the landscape and pressures from urban growth, industry, and intensified agricultural practices, tallgrass prairie vies for ranking as one of the most endangered ecosystems in North America (Hamilton 2005). Small patches of less- impacted remnant prairies are scattered across the former range of the tallgrass prairie (Hamilton 2005). In Iowa, less that 0.1% of the original tallgrass prairie remains (Smith 1998). The endangered status of tallgrass prairie may be one reason for a growing interest in ecological restoration in both the public and private sectors. One definition for ecological restoration is “the process of repairing or recreating natural ecosystems that have been damaged by the actions of humans” (Shepherd and Debinski 2005a). Early tallgrass prairie restorations focused mainly on the re-establishment of the native plant community (Panzer and Schwartz 1998). Yet, the goal of the restoration should be to return the function or biotic integrity of the natural system, not just the vegetation composition (Shepherd and Debinski 2005a). The community of native, prairie arthropods is one component of a diverse and functional prairie ecosystem that has not been adequately incorporated into restoration and conservation goals. The prairie arthropod community is overwhelmingly diverse compared to other animal taxa and provides critical ecosystem services such as pollinating plants, enhancing soil formation and fertility, increasing plant productivity, and organic decomposition (Kremen et al. 1993, Andersen et al. 2004, Ward and Larivière 2004). Arthropods occupy an important position in terrestrial food webs by regulating other organisms via predation and parasitism, and providing prey for many other organisms (Ward and Larivière 2004). The restablishment of many native vertebrates, including birds and 27 mammals, not only depend on the availability of plants, but also on arthropods as a food source. Arthropods do not, by themselves, represent the function of the prairie, but are a key component in restoring trophic connections and nutrient cycles. The importance of arthropods to the function of the tallgrass prairie ecosystem suggests that, if natural function (biological and ecological processes) is our management or restoration goal, maintaining native arthropod communities should be a conservation objective. Several obstacles prevent arthropods from being included in restoration processes. The primary impediment is the lack of a basic understanding of the historical and modern arthropod community in tallgrass prairie. In many areas, historical accounts of arthropods may be nonexistent or incomplete. This lack of historical or baseline data makes it difficult to monitor changes in the habitat and to establish restoration goals. Hendrickson (1930) provides one historic account of insects in Iowa prairies: “Because of the general interest to all of its citizens in the original conditions of a state, records of the fauna of native prairie at various intervals of time add to the history to the state. These needs and interests suggested that a general survey of the insect fauna of some of the larger tracts of prairie in the several parts of Iowa, together with the associations of the species with plant communities, would be of value.” At Hendrickson’s time, the tallgrass prairie in Iowa was already in decline. The impacts on remaining prairie since the 1930s have been drastic, yet few comprehensive arthropod surveys have occurred to document the changes to the arthropod community. Nor has any comparison been made between isolated remnant prairies and those prairies that have been reconstructed from agricultural fields. Current prairie arthropod studies focus mainly on particular taxa, such as grasshoppers (Orthoptera), ground beetles (Coleoptera), and butterflies (Lepidoptera) (Jonas et al. 2002, Shepherd and Debinski 2005a), types of sites (i.e. remnants (Panzer 1988)), or the effects of specific management practices, such as prescribed fire or grazing (Panzer and Schwartz

2000, Panzer 2002, Vogel et al. 2007). (Hendrickson 1930) The goal of this study is to connect arthropod data to the biotic integrity of the tallgrass prairie ecosystem. The main objective is to describe the current diversity and distribution of arthropods, insect and spider families, in Iowa tallgrass prairies. We examine both seasonal and annual trends in the arthropod communities. Another objective is to 28 compare anthropogenic categories of prairie relevant to the restoration community. We compare remnant prairies, isolated restored prairies, and also two large-scale integrated reconstructions. Equipped with information on arthropod presence at different prairie types, we can begin to investigate the functioning of tallgrass prairies at a fundamental level. These data can then be used as a baseline to quantify future changes.

METHODS

Sites We selected 30 prairie sites in seven counties of central Iowa across three qualitative types: remnants, isolated restorations/reconstructions (referred to as isolated sites), and integrated reconstructions (referred to as integrated sites). Definitions follow Shepherd and Debinski (2005a). Remnant prairies are sites that have never been used for intensive row crop agriculture and have not been used as pastureland for at least 15 years. Restored prairies contain remnant areas and have been actively managed to retard degradation and increase native vegetation composition. Reconstructed prairies contain no remnant native prairie vegetation and are usually replanted from row crop agricultural fields. Integrated reconstructions contain smaller patches of native vegetation combined with large-scale prairie reconstructions. We selected nine remnant sites, ten individual isolated restorations/reconstructions, and eleven patches within two geographically distinct integrated reconstructions (Table 1). Five sites were located within the Neal Smith National Wildlife Refuge (NSNWR) near Prairie City, IA, and six were located at Chichaqua Bottoms Greenbelt (CBG) (Polk County Conservation) near Polk City, IA. (Fig 1.) Native Iowa prairies are variable in specific site characteristics; the sites selected in this study are no exception. Sites were selected to minimize geographical and size variation, however, specific seed mix for planting at restorations/reconstructions and fire prescriptions varied across the sites and types. We did not manipulate management prescriptions at any our sites for the duration of our sampling. Within each prairie type vegetative quality differed, and was accounted for by conducting our own plant surveys to coincide with our arthropod sampling. The landscape surrounding our prairie sites was primarily agricultural, either row 29 crop such as corn (Zea mays) and soybean (Glycine max), or land used as livestock pasture (21 sites). Eight prairie sites had forested stands bordering them on at least one side. Twelve sites, including all the integrated sites, had other prairie reconstructions or restorations adjacent to the areas we used for sampling. One site, a campground, was surrounded primarily by human development. Five sites had two categories of land use directly adjacent to the property and all sites were accessible by roads. Land use types according to site are listed in Table 1. Arthropod Sampling Sweep net transects were used to collect aerial and foliar active arthropods. Three 25m x 2m belt transects were established randomly using a random number table for direction and distance (up to 250m) from the approximate center of the site during each visit to the prairie. Transects were placed at least 10m from the edges, trails, or uncharacteristic features. The vegetation along each transect was sampled by a standard of 20 pendulum sweeps with a 30.5cm diameter canvas sweep net. Arthropods collected in the sweep net were transferred to labeled zip-top bags and placed in a -20º C freezer until sorted and identified in the laboratory. Sweep net sampling occurred once per month at each site from June-August in both 2006 and 2007. Sampling events occurred during approximately the same time of day between 0930 and 1630h on days with appropriate weather conditions. Sweep transects were collected during periods where temperatures were not below 18°C, with less than 60% cloud cover and calm winds (gusts less than 17 kph) (Shepherd and Debinski 2005a). Arthropod Identification Arthropod samples were sorted with all specimens identified to taxonomic order. Following identification, arthropods were stored in ~70% ethanol and retained for further analysis. Arthropods, except for damaged specimens, early instars, Lepidoptera, Psocoptera, Thysanoptera, Collembola, micro-Hymenoptera, Acari, Isopoda, Diplopoda, and Chilopoda were identified to family. Aquatic insect orders, including Odonata, Ephemeroptera, and Plecoptera, and primarily aquatic families of Diptera and Coleoptera, were not included in the analysis. Identifications follow Triplehorn and Johnson (2005). Specimens have been retained by taxonomic specialist for further identification. (Triplehorn and Johnson 2005) 30

Vegetation Sampling Vegetation sampling was conducted at each site along 3 representative 25m random transects between late July and early August. Vegetation was surveyed with a 1m2 quadrat at 5m intervals for a total of 15 plots per site (Haney and Apfelbaum 1994). Species composition (richness), percent cover, and frequency were calculated for each site. Sampling Efficacy To verify that an adequate level of arthropod sampling had been performed, we created taxa (family) accumulation curves for each site (Kimberling et al. 2001). We calculated insect families accumulated every 10 sweeps by dividing each transect in half for a total of 6 subsamples to create the curves. Due to phenological changes in insects across the season, each month of sampling was plotted separately (Appendix 1, Figs. 1-3). Nearly all sites and months reached an asymptote suggesting our sampling was adequate to capture arthropod family diversity. Increased sampling would have likely collected few new insect families, and increased the number of singletons. There appears to be no trend in family accumulation based on site type, therefore we did not alter our sweep survey procedure in 2007. Analysis Data were summarized using R statistical language and environment (R Development Core Team 2007). Richness and abundance were summarized by site, site type, sampling method, arthropod family, and survey period (June, July, August) (Wickham 2007). We used a Kruskal-Wallis test to detect differences in the median richness and abundance between our three prairie categories. (Team 2007) The data were visualized to examine multivariate patterns and gauge the similarity of the arthropod community among sites and site types. Plots were created using non-metric multidimensional scaling (nMDS) on a log-transformed, Bray-Curtis distance matrix using the metaMDS command of the vegan package, with parameters: expand=F, autotransform=F and all other parameter defaults (Oksanen 2007). Bray-Curtis distance was chosen to standardize the abundance values (Faith et al. 1987). (Oksanen Jari 2007) 31

Plant richness at each site was compared using a Kruskal-Wallis test to detect differences in the plant community between our three prairie categories. Plant community data were used to determine whether sites could be grouped based on similar vegetation that was not reflected by our prairie categories. The importance value (Curtis and Macintosh 1951), a sum of the relative percent cover and relative frequency, was calculated for each species per site. Bray-Curtis distances were calculated for site vegetation and hierarchical clustering (hclust) using Ward’s linkage was used to identify clusters of sites based on the plant community data. We used the same nMDS procedure used for the arthropod community on the vegetation data to visualize relationships among the plant communities at our site types.

RESULTS

A total of 56,247 individual insects were collected from 106 families. In 2006, 28,179 insects were collected from 85 families, and 28,068 insects in 95 families were collected in 2007. The total number of spiders collected for both 2006 and 2007 was 3,246 individuals from 12 families. A total of 1,913 individual spiders from 12 families were collected in 2006, and 1,333 spiders in 11 families were collected in 2007. Seasonal trends Insect and spider abundance varied across the sampling season and between sampling years (see Appendix, Figs. 4-11). In 2006, insect abundance was greatest in June (11,258), followed by July (8,683) and August (8,238); family richness followed the same trend: 77, 74, and 69 families respectively. The opposite trend was observed in 2007, August (12,189) had the highest abundance of insects, followed by July (8,145) and June (7,734). In 2007, August had the highest family richness (76), followed closely by June and July (75). Spider abundance and richness in 2006 demonstrated a trend opposite to the insect families. The highest abundance and richness of spiders occurred in August, with 681 individuals in 11 families. The next highest sampling month for spiders was July (657), followed by June (575), with 10 families occurring during both months. Spider abundance and richness observed in 2007 was similar to the pattern in the insects, the highest abundance occurred in 32

August (652) followed by similar values for July (352), and June (329). Spider richness did not vary considerably in 2007; June had 11 families, and August and July each had 10. Annual trends Sampling year affected individual site abundance and richness. Sites with the highest diversity did not necessarily correspond to the highest number of individuals. The maximum number of insects recorded for a site in 2006 was 3,345 at Puccoon Prairie, with the minimum number, 320 at Neal Smith National Wildlife Refuge (NSNWR) 4. The highest insect family diversity in 2006 of 52 families occurred at Stargrass Prairie, with the fewest (24) occurring at Prairie Flower Campground. In 2007, the highest number of individuals occurred at Meetz Prairie (2,038) and the lowest at Sandhill East Prairie (376). The highest diversity was recorded for A.C. and Lela Morris Prairie (51) and lowest at Prairie Flower Campground (29). Spider richness and abundance followed the trend of insect richness and abundance at particular sites across years. In 2006, Puccoon Prairie had the highest number of spider families (10) and Stargrass Prairie had the highest number of individuals (199). The lowest spider richness observed in 2006 occurred at Drobney Prairie and Grant Ridge Prairie (5), while the lowest abundance occurred at NSNWR 1 (25). Three sites each possessed 10 spider families in 2007, one of these sites, Stargrass Prairie, also had the highest abundance (124) of total spiders. The lowest diversity of spiders occurred at Grimes Farm (4) in 2007, with NSNWR 4 having the lowest abundance (16) in 2007. The status of individual insect taxa also varied annually. The 10 most abundant insect families in 2006 were Cicadellidae (Hemiptera: 6,284), Chloropidae (Diptera: 5,586), Chrysomelidae (Coleoptera: 3,221), Formicidae (Hymenoptera: 1,943), Delphacidae (Hemiptera: 937), Miridae (Hemiptera: 853), Psyllidae (Hemiptera: 821), Phalacridae (Coleoptera: 733), Curculionidae (Coleoptera: 709), and Gryllidae (Orthoptera: 667). These 10 families accounted for 77.2% of the total insects collected and identified in 2006. Conversely, six families (Myrmeleontidae, (Neuroptera); Pompilidae and Chrysididae, (Hymenoptera); Geocoridae, (Hemiptera); Rhipiphoridae and Languriidae, (Coleoptera)) were only represented by one individual. In addition, 26 families had 10 or fewer individuals collected, accounting for 0.4% of total insects collect and identified. 33

The rank and contribution of insect families changed in 2007. The 10 most abundant families in 2007 were Cicadellidae (Hemiptera: 5,090), Aphididae (Hemiptera: 4,480), Chrysomelidae (Coleoptera: 4,445), Formicidae (Hymenoptera: 1,652), Chloropidae (Diptera: 1,596), Miridae (Hemiptera: 1,259), Curculionidae (Coleoptera: 1,073), Alydidae (Hemiptera: 820), Pentatomidae (Hemiptera: 719), and Gryllidae (Orthoptera: 663). These 10 families accounted for 77.7% of the total insects collected and identified in 2007. In 2007, the number of singleton families doubled to 12 (Biphyllidae, Buprestidae, Eucinetidae, Leiodidae, Phengodidae, Scirtidae, Silvanidae, and Tenebrionidae, (Coleoptera); Anthomyziidae and Empididae, (Diptera); and Aradidae and Cicadidae, (Hemiptera)). Likewise, the number of families contributing 10 or fewer individuals to the total increased to 37 representing 0.5% of the total insects sampled. Spider abundance and richness varied by year. In 2006, Thomisidae (580) and Salticidae (558) accounted for 59.5% of the total individuals counted. Theridiosomatidae (1), Lycosidae (4), and Clubionidae (5) all had fewer than 10 individuals and composed 0.5% of the total spider abundance. Two spider families in 2007, Salticidae (504) and Araneidae (407), had the highest number of individuals counted; this represented 68% of the total. One family, Clubionidae (8) had fewer than 10 individuals for 0.6% of total spiders that year. Comparisons of Prairie Types We compared insect and spider richness and abundance among prairie site types. To eliminate the effect of the unequal number of sites in each category, standardized total richness and abundance were compared. Overall, there were only slight differences in richness and abundance between site types and between integrated sites for insects and spiders. Based on a Kruskal-Wallis test statistic, none of the comparisons were statistically significant at the 95% confidence level (df=2, critical value = 5.99). Although comparisons were not statistically significant, the values for standardized richness and abundance did vary among site types. Remnant sites had higher total richness and relative richness of insect taxa in both years of the study (Table 2). Isolated sites had similar values for insect richness during both years, however by standardizing the richness, isolated sites had slightly higher richness values than integrated sites. In addition to richness, remnant prairies had a higher relative abundance in 2006, and nearly the same relative 34 abundance as integrated sites in 2007. Isolated sites followed remnants and had higher relative abundance in 2006, however, integrated sites had higher relative abundance than isolated sites in 2007. We compared the two geographically distinct sets of integrated sites to quantify variation within the integrated category. NSNWR had higher total richness, and standardized richness than CBG for both sample years. NSNWR had lower total and relative abundance in 2006, but higher total and relative abundance in 2007 (Table 3). The spider community can also be compared across the site categories. Spider richness and standardized richness was approximately the same across site types and years. Relative spider richness was intermediate at remnants for both years. Relative spider abundance was highest at isolated sites followed by remnants and integrated sites in 2006 and 2007 (Table 4). Spider communities varied between integrated sites. Richness was higher at NSNWR in 2006, but CBG was higher in 2007. Total and relative spider abundance was higher at CBG in both years (Table 5). The arthropod community, represented by insect and spider families, differed between sites and types. Although comparisons of richness and abundance among site types did not differ significantly, the identity of the arthropods that contributed to the richness and abundance did. The most abundant insect taxa occur at most sites (Figs. 2 & 3). The majority of insect families occurred at a subset of sites; few insect families were restricted to sites of only one type (Figs. 4 & 5). Insect taxa that occurred only at one site type were typically singleton taxa that occurred at only one site of that particular type. These taxa also differed between years. There was no overlap in taxa restricted to a single site type for both years, suggesting these taxa may be outliers rather than indicative of a particular site type. Although distribution of insect taxa seems to be irrespective of site type, abundances differed for the same taxa depending upon the site or site type. Spider families displayed a similar pattern to insect families in distribution across sites and site types (Figs. 6 & 7). Dominant families occurred at all sites, with less abundant families occurring at fewer sites, but not restricted to any one site type. Abundance of spider 35 families differed depending on site type (Figs. 8 & 9), but only rare taxa were restricted to one site type and were inconsistent across years. Richness and abundance of taxa alone do not describe the arthropod community. We used ordination techniques to summarize the arthropod community and represent site similarity by relative position on a two-dimensional plot. Sites plotted closely together possess similar arthropod communities than sites plotted further apart. We can also observe the pattern in site types by creating boundaries around site types. nMDS plots for both years show site types overlapping, suggesting some similarity in the arthropod community (Figs. 10 & 11). Remnant sites showed the most similarity to one another in both years based on the size of the remnant polygon, while isolated sites and integrated sites had greater variation. All sites were less divergent in 2007 than in 2006. Ordination of the spider community revealed greater variation within a site type compared with the insect community, and greater similarity of site types (Figs. 12 & 13). The fluctuation diagrams (Figs. 2,3,6,7) can be used to interpret the plotting of sites on the nMDS plot based on individual taxa and their abundance. The plant community at isolated sites and integrated sites was similar while remnant sites differed slightly from the other categories. Remnant prairies had higher plant richness than other site types (Table 6), however, the difference was not significant (Kruskal-Wallis test, df=2, critical value=5.99). Hierarchical cluster analysis showed two main clusters; each with two smaller clusters for both years of plant data separately (Figs. 14 & 15). Sites of all three types are represented in each cluster. Additionally, the clusters were not consistent for both years. Only in 2007, did all the remnant sites reside in the same main cluster, suggesting a slight difference in the plant community of remnants compared to the other two categories combined. This distinction between remnants and the other two categories was also observed in the nMDS plot for the 2007 vegetation data (Fig. 16). Overall, the plant communities support our prairie types, suggesting the major difference among the sites is between remnants and isolated and integrated sites combined.

DISCUSSION

We assessed the patterns of arthropod diversity at prairies in three general categories with varying management practices and site history. We observed fluctuations in the arthropod community between years and throughout the sampling season. Seasonality and variation between years would have influenced all sites equally, and can be interpreted based on arthropod ecology and climatic effects. Our collection methods focused on adult arthropods since the adults are the most readily identified. Seasonal changes in distribution could be attributed to a generally short adult lifespan (Triplehorn and Johnson 2005). Adult survivorship is expected to be low due to predation form higher trophic levels (Triplehorn and Johnson 2005). Many arthropods have variable phenologies (Triplehorn and Johnson 2005), such that they are present for only short periods of time throughout the summer season. Alternatively, some arthropods are present during the entire season, but increase in abundance over time and might only be detected later in the season. Arthropods were likely influenced by weather patterns. Although we attempted to minimize variation for our sampling events, 2006 overall was much drier and hotter than 2007. All of these factors likely influenced the arthropod population dynamics we reported. Arthropod diversity varied within the same site and between sampling years, which may also be due to the variance in arthropod abundances and weather patterns. In addition, arthropod diversity may have been affected by management practices both on the prairie and in the areas surrounding our sites. We did not put any constraints on management activities during our study. Several sites were burned immediately before we started sampling in 2006 (Doolittle, Judson, Marietta, Morris, Briggs Woods, Grant Ridge, Richards Marsh, and Stargrass), and others were burned in whole or in part before sampling began in 2007 (Sandhill East, Reichelt Unit, Judson, and Engeldinger Marsh). One site is hayed annually in late July through early August (Moeckly Farm), at this particular site we were unable to collect sweep net samples in August 2006. The omission of this site in 2006, however, did not affect the overall patterns in the results. Prairie arthropods may also reflect changes in agricultural practices in surrounding land areas. The landscape of Iowa is dominated by agricultural production; our sites represent a typical prairie-agriculture interface. Agricultural fields in Iowa typically rotate between 37 corn (Zea mays) and soybean (Glycine max) production. Each of these crops is accompanied by a regimen of disturbance and chemical applications. The proximity of these fields to our prairies may have altered the arthropod community at individual sites between sampling years. The effects of cropland management at our individual prairies would not be uncharacteristic of other prairies in the state and region. The effect of agriculture on prairies is presumed to be negative, but few have studied the effects on the community other than selected arthropod taxa (i.e. butterflies) (Obrycki et al. 2001). In addition to agriculture, other landscape features may have an important role in shaping arthropod communities at prairie remnants and restorations (Davis et al. 2007) Ecological communities, including arthropod communities, are typically dominated by a few abundant taxa, with many taxa found in much lower abundance (Gotelli 2008). This was observed in central Iowa prairies. Approximately 10% of the insect families accounted for more than 75% of the individual insects collected in each season. Only two spider families (~17% of the total number of families) in each year account for more than half of all spider specimens collected. Many of these dominant taxa occurred at every site and in relatively high abundance. The dominant insect families share several characteristics: they are taxonomically large families, primarily generalist herbivores, and are typical of grassland ecosystems. A majority of the insect taxa in each year are not common and are difficult to classify. The rarest insect families, however, appear to be specialist predators or herbivores, or taxa that are not adapted to prairie ecosystems (i.e., Buprestidae and Silvanidae) (Triplehorn and Johnson 2005)). Spiders are typically generalist predators (Foelix 1996, Ubick et al. 2005), but vary in technique employed to acquire prey. Active hunters, Salticidae (Ubick et al. 2005), and web-building spiders, Araneidae (Ubick et al. 2005, Summerville et al. 2007), can utilize prairie habitat effectively. The less common spider families require more specialized habitat requirements or employ hunting activities that reduce incidence of capture with sweep netting. The taxonomic accumulation curves suggest that we achieved adequate sampling to characterize the foliar active arthropod community. Additional taxa may have been obtained with more vigorous collection effort, but this likely would have added to our list of singleton families and would not have been informative for the general application of our results. 38

The arthropod communities at each of our prairie site types followed a similar pattern of diversity as the overall arthropod community. Arthropods collected at sites of each type included the large, generalist herbivore families of insects and the most abundant spider families. We did not observe any taxa that occurred only on one site type with consistent patterns in both years; however, some taxa were more abundant on one site type. We compared insect and spider richness and abundance across site types, and although remnants had higher relative abundance in 2006 and richness in 2006 and 2007, the site types did not differ significantly. Site type similarity was also reflected in the overlapping polygons in the nMDS plots. Sites within the same type, such as integrated sites, showed more variability within the site type than between site type in the insect community ordination, however this was based on the nMDS plots and not quantified. Analysis of the spider community with nMDS displayed greater similarity among site types. The patterns of insect and spider diversity at our site types contrast with our expectation that site types would be significantly different from one another. Further taxonomic resolution may be required to identify species or genera that are specific to one site type. Additional identification of several insect families is currently on-going and can be used to assess this prediction. Yet, the trend in the community of arthropods at the family level may suggest some alternative hypotheses. These alternatives could be supported by the additional taxonomic data. Our preliminary expectation that site types should be different because restorations and reconstructions may lack components of the intact, remnant ecosystem calls into question the efficacy of ecological restoration. As stated earlier, the central goal of ecological restoration is returning the habitat to the native condition. Significant differences between remnant prairies relative to types our restoration and reconstruction sites would deem them unsuccessful. As our first alternative, we could predict similarity since all of our sites are tallgrass prairie, rather than comparing remnants to non- prairie habitat. Our data suggest, at the family level, that restoration and reconstruction efforts are approximating the native, remnant community. In addition, earlier work comparing remnant, isolated, and integrated sites by Shepherd and Debinski (2005a), suggests that integrated restoration efforts may more be effective in meeting the goals of ecological restoration than isolated restorations. Our data support this proposition, since 39 abundance and richness values were not significantly different from remnant sites, and ordination of the integrated site types overlapped with both remnant prairies and isolated restorations/reconstructions. Our second alternative explanation for the trend in our pattern of arthropod families is that remnant-restricted taxa may have already been extirpated from our remnant sites. The loss of remnant-dependent arthropods would increase measures of similarity between remnant and restored sites (Shepherd and Debinski 2005a). Although remnant prairies have experienced less direct-human disturbance than areas that have been converted to agriculture, these sites have not escaped the indirect impacts of agriculture, industry, urban sprawl and habitat fragmentation. Many native, remnant prairies are small and exist in a matrix of agriculture that may not support native arthropods or their dispersal (Summerville et al. 2007). Since we lack adequate historical records, it would be difficult to test this hypothesis directly. Plants provide a slightly different picture of our prairie site types. While plant richness did not differ significantly between our site types, the ordination of the plant community showed greater differences between our site types than the arthropod community. Once again, this seems counter-intuitive, especially with regard to the explanation of the arthropod community. There are several possibilities that explain the discrepancy between the plant and arthropod community. Remnant prairies in Iowa were not established to preserve tallgrass prairie, rather they exist in areas with marginal agricultural value. Most current restorations and reconstructions utilize habitats that previously supported agricultural production, and thus they may lack the unique conditions that exist on remnant prairies. Remnants may contain tallgrass prairie plant species that while locally abundant at particular microhabitats, may be absent from other prairie sites. A second possibility involves restoration efforts. Commercially available prairie seed mixes are the foundation for many restoration efforts. Restorations frequently lack plants that are difficult to cultivate, collect, or require specialized associated mycorrhizae (Urbanska et al. 1997). Typically seed mixes of higher diversity are much more expensive, so cost becomes a limiting factor to prairie plant diversity. Our data seem to support this second alternative since the plant community at restorations and reconstructions sites were more similar than remnant sites. 40

Plants, for their utility in distinguishing prairie types, may still seem like the logical metric by which to measure restoration success. However, arthropods provide additional biological information. Resource professionals can establish native vegetation, but typically do not actively relocate arthropods, with the exception of rare species (i.e. Speyeria idalia in Iowa (Shepherd and Debinski 2005b)). Arthropods, however, provide restoration practitioners with an independent means of evaluating and monitoring prairie habitats, especially because of the diverse and specialized roles of arthropods in prairie ecosystems. Future research on species level responses may provide us with additional insight regarding the connection between arthropods and prairie biotic integrity.

CONCLUSIONS

Even at the family taxonomic level, arthropod communities at tallgrass prairies are diverse, representing many different functions, life-histories, and adaptations. The diversity is robust to prairie types, but is useful for our understanding of prairie integrity. Arthropod data provide evidence that prairie restoration and reconstruction efforts may be successful for the conservation of some members of the arthropod community, while simultaneously creating an awareness of our assumptions about the pristine condition of remnant areas typically used as the benchmark for restoration programs.

ACKNOWLEDGEMENTS

We are grateful for the generosity of the landowners, land mangers, and agency officials for allowing us to use their prairies: P. Drobney (NSNWR Smith National Wildlife Refuge), B. Lammers, C. Hildebrand, D. Howell, J. Goerndt, J. Pearson, J. Judson, K. Hansen, K. Cantu, K. Van Zante, M. Cosgrove, M. Meetz, L. Meetz, M. Stegmann, S. Peterson, S. Lekwa, S. Rolfes, L. Lown (Chichaqua Bottoms Greenbelt), S. Moeckly and M. Moeckly. We would like to thank Greg Van Nostrand, Dana Woolley, Heather Gilliland, and MJ Hatfield for their assistance in the field and laboratory. The authors also thank Christopher Tyrrell and Sarah Orlofske for comments to this manuscript and Dr. Dianne Cook (ISU) for statistical assistance. This project was funded by the Iowa Science 41

Foundation, The Nature Conservancy: Nebraska Chapter’s J.E. Weaver Competitive Grants Program, Prairie Biotic Research, Inc, and the Iowa Department of Natural Resources: Iowa Wildlife Diversity Grant.

LITERATURE CITED

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Panzer, R. and M. W. Schwartz. 1998. Effectiveness of a Vegetation-Based Approach to Insect Conservation. Conservation Biology 12:693-702. Shepherd, S. and D. Debinski. 2005a. Evaluation of isolated and integrated prairie reconstructions as habitat for prairie butterflies. Biological Conservation 126:51-61. Shepherd, S. and D. Debinski. 2005b. Reintroduction of Regal Fritillary (Speyeria idalia) to a Restored Prairie. Ecological Restoration 23:244-250. Smith, D. D. 1998. Iowa Prairie: Original Extent and Loss, Preservation and Recovery Attempts. Journal of the Iowa Academy of Science 105:94-108. Summerville, K. S., A. C. Bonte, and L. C. Fox. 2007. Short-Term Temporal Effects on Community Structure of Lepidoptera in Restored and Remnant Tallgrass Prairies. Restoration Ecology 15:179-188. Team, R. D. C. 2007. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Triplehorn, C. A. and N. F. Johnson. 2005. Borror and Delong's Introduction to the Study of Insects. Seventh Edition edition. Thomson, Belmont Ubick, D., P. Paquin, P. E. Cushing, and V. R. (eds). 2005. Spiders of North America: an identification manual. American Arachnological Society. Urbanska, K. M., N. R. Webb, and P. J. Edwards. 1997. Restoration Ecology and Sustainable Development. Cambridge University Press. Vogel, J. A., D. Debinski, R. R. Koford, and J. R. Miller. 2007. Butterfly responses to prairie restoration through fire and grazing Biological Conservation 140:78-90. Ward, D. F. and M.-C. Larivière. 2004. Terrestrial invertebrate surveys and rapid biodiversity assessment in New Zealand: lessons from Australia. New Zealand Journal of Ecology 28:151-159. Wickham, H. 2007. ggplot: An implementation of the Grammar of Graphics in R.

TABLES AND FIGURES 93.59016 94.56933 94.22528 93.01455 93.03893 93.66538 92.96203 92.86495 94.58819 93.75297 93.79725 93.26985 93.47042 92.96981 93.56695 93.54342 93.69135 Longitude 41.704 42.1495 41.7654 42.4135 41.5602 42.0972 41.7825 41.7706 41.6895 41.8006 42.4366 42.0104 41.9668 42.0227 42.0964 42.0586 41.7494 Latitude 25 15 6.25 8.33 7.08 8.33 8.33 7.08 6.25 16.67 41.68 16.67 16.67 10.42 33.33 29.14 18.75 Hectares 40 15 20 17 40 20 40 25 20 17 80 72 15 60 36 45 100 Acres b L F F F F C C C C C C C C U C,L C,F F, P Land Use Polk Polk Polk Story Story Story Story Story Jasper Jasper Jasper Guthrie Guthrie County Webster Marshall Marshall Hamilton a ISO ISO ISO ISO ISO ISO ISO ISO REM REM REM REM REM REM REM REM REM Type PF LS GF DP BC CB RU SH MF GR ME DO BW JUD MAR MOE MOR Abbr. Site Table 1. Summary of prairie sites. Doolittle Prairie State Preserve Judson Prairie Liska-Stanek Prairie State Preserve Drobney Prairie Marietta Sand Prairie State Preserve Moeckly Prairie A.C. and Lela Morris Prairie Reichelt Unit, Stephen's State Forest Sheeder State Preserve Big Creek Wildlife Management Area Briggs Woods Park Colo Bogs Wildlife Management Area Grant Ridge Grimes Farm Conservation Area McFarland Park Meetz Prairie Prairie Flower Campground

45 93.61572 93.55438 93.27412 93.27884 93.29609 93.27374 93.27586 93.39378 93.35555 93.36486 93.38097 93.38731 93.34504 Longitude 41.753 41.774 41.736 41.773 42.3275 41.9946 41.5536 41.5377 41.5557 41.5748 41.5946 41.7741 41.7861 Latitude int int int int int int int int int int int 31.25 10.42 Hectares 75 25 int int int int int int int int int int int Acres b P P C C C C C C C C C C,F F, P Land Use Polk Polk Polk Polk Polk Polk Story Jasper Jasper Jasper Jasper Jasper County Hamilton a INT INT INT INT INT INT INT INT INT INT INT ISO ISO Type TF ST PC SE N1 N2 N3 N4 N5 EM RM SW AIR Abbr. 2 2 2 2 Site 2 2 1 1 1 1 1 Neal Smith National Wildlife Refuge Chichaqua Bottoms Greenbelt C: Row crop, F: Forest, L: Livestock Pasture, P: Prairie, U: Urban REM: Remnant, ISO: isolated restoration/reconstruction, INT: integrated reconstruction Table 1. Summary of prairie sites (continued). Richards Marsh Natural Resource Area Stargrass Prairie NSNWR 1 NSNWR 2 NSNWR 3 NSNWR 4 NSNWR 5 "Airport" CBG Engeldinger Marsh CBG Puccoon CGB Sandhill East Unit CGB Sandhill West Unit CGB Turtlehead Fen CGB 1 2 a b

46 SD 349.3 244.2 470.0 922.3 208.5 941.5 Mean 943.1 960.8 922.3 857.2 941.5 1015.8 Abundance Total 9142.0 8544.0 9608.0 9265.0 9429.0 10465.0 SD 3.2 5.8 8.1 4.3 5.6 6.0 44.7 44.9 38.6 37.7 38.7 39.3 Mean Richness 77.0 83.0 75.0 76.0 75.0 75.0 Total 2006 2007 2006 2007 2006 2007 Year Isolated Remnant Integrated Site Types Table 2. Comparison of insect family richness and abundance across site types.

SD 295.3 225.0 569.0 1141.4 Mean 665.4 827.7 1078.2 1017.0 Abundance Total 3327.0 5429.0 6102.0 5036.0 SD 6.9 6.9 4.5 4.9 40.4 42.3 37.3 37.3 Mean Richness 64.0 68.0 63.0 66.0 Total 2006 2007 2006 2007 Year CBG NSNWR Integrated Site Table 3. Comparison of insect family richness and abundance between integrated sites: Neal Smith National Wildlife Refuge (NSNWR) and Chichaqua Bottoms Greenbelt (CBG).

SD 30.6 17.1 50.1 30.2 20.2 16.9 67.0 49.4 75.0 51.1 50.9 34.3 Mean Abundance Total 603.0 446.0 750.0 511.0 560.0 377.0 SD 1.1 1.1 1.1 1.9 1.4 1.6 7.0 6.8 6.9 7.4 7.6 6.7 Richness Mean 10.0 11.0 10.0 11.0 11.0 11.0 Total 2006 2007 2006 2007 2006 2007 Year Isolated Remnant Integrated Site Types Table 4. Comparison of spider family richness and abundance across site types.

SD 6.9 13.9 17.0 17.4 36.6 23.0 62.8 43.7 Mean Abundance Total 183.0 115.0 377.0 262.0 SD 1.5 1.1 1.5 1.9 7.8 6.6 7.5 6.8 Mean Richness 11.0 10.0 11.0 11.0 Total Year 2006 2007 2006 2007 CBG NSNWR Integrated Site Table 5. Comparison of spider family richness and abundance between integrated sites: Neal Smith National Wildlife Refuge (NSNWR) and Chichaqua Bottoms Greenbelt (CBG).

Table 6. Average plant richness at prairie site types. Site Type Year Richness Mean SD 2006 19.7 4.0 Remnant 2007 39.1 11.6 2006 14.5 4.6 Isolated 2007 29.7 9.0 2006 12.1 3.7 Integrated 2007 30.1 9.2

Figure 1. Map of central Iowa prairie locations used in this study.

Figure 2. Fluctuation diagram of insect family abundances collected June-August 2006 at prairie sites. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. The first nine sites are remnants shown in bold text, the next 10 are isolated sites shown in gray text, the final 11 are integrated sites shown in plain text.

Figure 3. Fluctuation diagram of insect family abundances collected June-August 2007 at prairie sites. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. The first nine sites are remnants shown in bold text, the next 10 are isolated sites shown in gray text, the final 11 are integrated sites shown in plain text.

Figure 4. Insect family abundance divided among three prairie site types for insects collected June-August 2006. Each black dot represents the abundance at an individual site each month. Insect abundance was summed across all sites of each type: remnant, isolated sites, and integrated sites, and taxa are ordered from highest to least abundant.

Figure 5. Insect family abundance divided among three prairie site types for insects collected June-August 2007. Each black dot represents the abundance at an individual site each month. Insect abundance was summed across all sites of each type: remnant, isolated sites, and integrated sites, and taxa are ordered from highest to least abundant.

Figure 6. Fluctuation diagram of spider family abundances collected June-August 2006 at prairie sites. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. The first nine sites are remnants shown in bold text, the next 10 are isolated sites shown in gray text, the final 11 are integrated sites shown in plain text.

Figure 7. Fluctuation diagram of spider family abundances collected June-August 2007 at prairie sites. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. The first nine sites are remnants shown in bold text, the next 10 are isolated sites shown in gray text, the final 11 are integrated sites shown in plain text.

Figure 8. Spider family abundance divided among three prairie site types for spiders collected June-August 2006. Each black dot represents the abundance at an individual site each month. Spider abundance was summed across all sites of each type: remnant, isolated sites, and integrated sites, and taxa are ordered from highest to least abundant.

Figure 9. Spider family abundance divided among three prairie site types for spiders collected June-August 2007. Each black dot represents the abundance at an individual site each month. Spider abundance was summed across all sites of each type: remnant, isolated sites, and integrated sites, and taxa are ordered from highest to least abundant.

Figure 10. nMDS plot of insect family data collected June-August 2006 by site type using log-transformed abundance values and Bray-curtis distance, stress = 18.30. Sites of the same 52 type are displayed with a labeled polygon, REM: remnant sites, ISO: isolated sites, and INT: integrated sites.

Figure 11. nMDS plot of insect family data collected June-August 2007 by site type using log-transformed abundance values and Bray-curtis distance, stress = 20.51. Sites of the same type are displayed with a labeled polygon, REM: remnant sites, ISO: isolated sites, and INT: integrated sites.

Figure 12. nMDS plot of spider family data collected June-August 2006 by site type using log-transformed abundance values and Bray-curtis distance, stress = 20.82. Sites of the same type are displayed with a labeled polygon, REM: remnant sites, ISO: isolated sites, and INT: integrated sites.

Figure 13. nMDS plot of spider family data collected June-August 2007 by site type using log-transformed abundance values and Bray-curtis distance, stress = 25.40. Sites of the same type are displayed with a labeled polygon, REM: remnant sites, ISO: isolated sites, and INT: integrated sites.

Figure 14. Hierarchical cluster analysis of 2006 plant survey data using log-transformed abundance values and Bray-curtis distance and Ward’s linkage. Remnant sites are labeled in bold, isolated sites in gray, and integrated sites in plain text.

Figure 15. Hierarchical cluster analysis of 2007 plant survey data using log-transformed abundance values and Bray-curtis distance and Ward’s linkage. Remnant sites are labeled in bold, isolated sites in gray, and integrated sites in plain text.

Figure 16. nMDS plot of plant survey data collected July-August 2007 by site type using log- transformed abundance values and Bray-curtis distance, stress = 19.46. Sites of the same type are displayed with a labeled polygon, REM: remnant sites, ISO: isolated sites, and INT: integrated sites.

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CHAPTER THREE. TERRESTIAL ARTHROPOD INDICATORS FOR ECOLOGICAL RESTORATION OF IOWA TALLGRASS PRAIRIE

A paper to be submitted to Ecological Indicators

Jessica M. Orlofske1, Wayne J. Ohnesorg2, Diane M. Debinski1

1Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, Iowa 50011 USA 2Department of Entomology, Iowa State University, Ames, Iowa 50011 USA

ABSTRACT

Ecological indicators have been used to detect chemical and physical environmental parameters, monitor habitat quality, or assess conservation priority. Terrestrial systems, such as the tallgrass prairie, however, need ecological indicators that integrate information about ecological function, processes, and biotic integrity. The tallgrass prairie has become one of the most endangered ecosystems in North America and there is growing interest in prairie management and restoration. Arthropods can provide valuable information related to ecosystem function and biotic integrity when used as bioindicators. However, effective, reliable arthropod bioindicators of tallgrass prairie have not been clearly identified. A survey of arthropods was conducted using sweep net transects on a cross-section of Iowa prairies among three prairie types: remnants, isolated restorations/ reconstructions and landscape- scale integrated reconstructions. We used indicator species analysis to identify families of insects and spiders that could be used as indicators of biotic integrity or restoration success. Four insect families, Formicidae (Hymenoptera), Otitidae (Diptera), Cixiidae (Hemiptera), and Tettigonidae (Orthoptera), and one spider family Thomisidae (Araneae) were identified as indicators of remnant prairies, with additional taxa demonstrating some affinity to remnant sites. Indicator taxa we identified provide further support for previously identified indicators, such as ants (Formicidae), but also include taxa not previously recorded as prairie bioindicators, like crab spiders (Thomisidae). 70

INTRODUCTION

Bioindicators are resident species or taxa that reflect abiotic and biotic environmental conditions, represent environmental change in a particular habitat, community or ecosystem, or correlate with the diversity patterns of other species (Dufrêne and Legendre 1997, McGeoch 1998, Rainio and Niemelä 2003, Hodkinson and Jackson 2005). Bioindicators convey information that would be difficult or expensive to obtain with alternative methods, and they can integrate ecological qualities and track changes over time. Ecological indicators, a group of bioindicators defined by McGeoch (1998) have been used to detect chemical and physical environmental parameters, monitor habitat quality, or assess conservation priority among sites (Hodkinson and Jackson 2005). Yet, terrestrial systems need ecological indicators that integrate information about the ecological function and processes, along with biotic integrity. Ecologists and conservation biologists are beginning to recognize ecological function and biotic integrity as priorities for management and restoration programs (Karr 1991, Kimberling et al. 2001). Prairies have been the focus of intensive restoration efforts (Packard and Mutel 1997). Perhaps the near extinction of this most widely recognized subdivision of the North American grassland biome (Hamilton 2005) has stimulated interest in prairie management and restoration. Currently, the tallgrass prairie vies for being one of the most endangered ecosystems in North America due to conversion to agriculture and pressures from urban growth and industry (Hamilton 2005). Only small patches of less-impacted remnant prairies are scattered across the former range of the tallgrass prairie (Hamilton 2005). In Iowa, less than 0.1% of the original tallgrass prairie exists (Smith 1998). Management and restoration success for the prairie, as well as other ecosystems, is typically measured by the establishment and maintenance of the native plant community (Panzer and Schwartz 1998, Longcore 2003). Plants alone cannot represent nutrient cycles, trophic connections, and other ecosystem processes. Clearly, prairie management and restoration could benefit from the development of ecological indicators, especially those that incorporate animal community response.

The use of arthropods as bioindicators is well supported (Pearson and Cassola 1992, Kremen et al. 1993, Longcore 2003, Andersen et al. 2004, Ward and Larivière 2004) and arthropods have been successfully used as traditional bioindicators in a wide variety of applications both terrestrial and aquatic (McGeoch 1998, Hodkinson and Jackson 2005). Arthropods may better represent the function of the prairie, because they are key components in food-webs, nutrient cycles, plant reproduction, and soil formation processes. Previous research on prairie arthropods has focused generally on responses to management practices, specifically prescribed fire (Panzer and Schwartz 2000, Panzer 2002) or the status of individual arthropod taxa (Jonas et al. 2002, Shepherd and Debinski 2005). Panzer et al. (1995) provide a preliminary list of remnant-dependent insects that may qualify as potential ecological indicators. The list was constructed based on published accounts of arthropods in prairies, museum records, anecdotal evidence, and personal observations. The Panzer et al. (1995) list of taxa was compared to arthropods collected (using unstandardized methods) at a variety of remnant prairies and non-prairie sites. Remnant prairies were not compared to prairie restorations and reconstructions. However, this comparison is important to many conservation professionals and prairie enthusiasts. Additionally, Panzer et al.’s (1995) methodology focused on a “core” group of arthropod taxa that were already believed to be restricted to prairie remnants. Thus, they may have overlooked important taxa that are currently unknown or understudied. We would argue that a more comprehensive understanding of prairie arthropod habitat specificity and resilience is needed prior to defining holistic, ecological indicators for tallgrass prairie. The goal of this study is to identify prairie arthropod bioindicators, families of insects and spiders, for the evaluation of quality (biotic integrity) and as a measure of restoration progress for tallgrass prairie. The focus of our study is to objectively select potential prairie arthropod bioindicators based upon standardized collection methods distributed across the greater arthropod community over three relevant prairie types: remnants, isolated restorations/reconstructions, and integrated reconstructions. We compare our results to the previously proposed prairie remnant indicator taxa (Panzer et al. 1995).

METHODS

73 to the property and all sites were accessible by roads. Land use types according to site are listed in Table 1. Arthropod Sampling Sweep net transects were used to collect aerial and foliar active arthropods. Three 25m x 2m belt transects were chosen during each visit to the prairie. Transect locations were assigned randomly using a random number table for direction and distance (up to 250 m) from the approximate center of the site during each site visit. Transects were placed at least 10m from the edges, trails, or uncharacteristic features. The vegetation along each transect was swept with a 30.5cm diameter canvas sweep net. Each transect was standardized to 20 pendulum sweeps. Arthropods collected in the sweep net were transferred to labeled zip-top bags and placed in a -20º C freezer until sorted and identified in the laboratory. Sweep net sampling occurred once per month at each site from June-August in both 2006 and 2007. Sampling events occurred during the same time interval and between 0930 and 1630h on days with appropriate weather conditions. Sweep transects were collected during periods where temperatures were not below 18°C, with less than 60% cloud cover and calm winds (gusts less than 17 kph) (Shepherd and Debinski 2005). Arthropod Identification Arthropod samples were sorted with all specimens identified to the taxonomic order. Arthropods were stored in ~70% ethanol and retained for further analysis. Arthropods, except for severely damaged specimens, early instars, Lepidoptera, Psocoptera, Thysanoptera, Collembola, micro-Hymenoptera, Acari, Isopoda, Diplopoda, and Chilopoda were identified to family. Aquatic insect orders, including Odonata, Ephemeroptera, and Plecoptera, and primarily aquatic families of Diptera and Coleoptera, were not included in the analysis to focus on arthropods, which use the terrestrial landscape for most lifestages. Identifications

follow Triplehorn and Johnson 2005. Specimens have been retained for further analysis. (Triplehorn and Johnson 2005) Analysis Indicator species analysis (ISA) (Dufrêne and Legendre 1997) was used to identify insect and spider families restricted to each prairie type. The indicator value is composed of a measure of specificity and fidelity to a habitat (Dufrêne and Legendre 1997, McGeoch and 74

Chown 1998). The indicator value of each taxa was determined individually based on the following equation:

IndValij = Aij X Bij X 100

Aij = Nindividualsij/Nindividualsj

where Nindividualsij is the mean number of taxon i across sites of group j,

and Nindividualsi is the sum of the mean numbers of individuals of taxon i over all groups.

Bij = Nsitesij/Nsitesj

where Nsitesij is the number of sites in group j where taxon i is present,

and Nsitesj is the total number of sites in that group. The data matrix was log transformed to reduce skewness from arthropod abundance values. Data from each sampling year were analyzed separately to compare the consistency of site ! type association between years. We used the duleg function in the labdsv package (Roberts 2007) of the R Statistical Program Language and Environment (R Development Core Team 2007) to calculate ISA and perform a permutation test for each taxa. The statistically significant insect indicator taxa for each year were visualized using non-metric multidimensional scaling (nMDS) of log-transformed, pairwise Bray-Curtis distances using function metaMDS, (vegan package (Oksanen 2007) with expand=F, autotransform=F and all other parameter defaults. Bray-Curtis distance was chosen to standardize the abundance values (Faith et al. 1987). (Team 2007)

RESULTS

The sweep net samples contained a total of 56,247 individual insects from 106 families. According to year, 28,179 insects were collected from 85 families in 2006, and 28,068 insects in 95 families were collected in 2007. The total number of spiders collected for both sampling years was 3,246 from 12 families. A total of 1,913 individual spiders were collected from 12 families in 2006, and 1,333 spiders were collected in 11 families in 2007. Insects Indicator species analysis identified specific arthropod families that were indicative or associated with a particular site type for each sampling year. Several families were consistent indicators of one site type for both years, but some families switched between site types. In

2006, five insect families, Alydidae and Anthocoridae (Hemiptera); Elateridae (Coleoptera); Formicidae (Hymenoptera); and Otitidae (Diptera) were statistically significant (α = 0.05) remnant indicators. Five additional families, Acanaloniidae and Cixiidae (Hemiptera); Bombyliidae and Calliphoridae (Diptera); and Tettigonidae (Orthoptera) were marginally significant (α = 0.10) remnant indicators. One family, Coccinellidae (Coleoptera) was a significant indicator of isolated sites and two additional families, Aphididae and Tingidae (Hempitera), were marginally significant. There were no significant or marginally significant indicators of integrated sites in 2006 (Table 2, Fig. 2 & 3) Although abundance values were consistent in both years, insect family diversity increased slightly in 2007, and so did the number of potential indicators (Table 3, Fig. 4 &5). Remnant indicators included nine families Cantharidae (Coleoptera); Cixiidae and Miridae (Hemiptera); Formicidae, Megachilidae, and Mutillidae (Hymenoptera), Muscidae, Otitidae, and Tachinidae (Diptera). In addition, 10 families were marginally significant Anthomyzidae, Chloropidae, Dolichopodidae, Sacrophagidae, and Tabanidae (Diptera); Anthribidae (Coleptera); Lygaeidae and Membracidae (Hemiptera); Vespidae (Hymenoptera), Tettigonidae (Orthoptera). Aphididae (Hemiptera) and Sepsidae (Diptera) were significant indicators of isolated sites with Scarabaeidae (Coleoptera) and Tingidae (Hemiptera) as marginally significant indicators. Three taxa were identified as indicators of integrated sites in 2007: Gryllidae (Orthoptera) was significant and Hemerobiidae (Neuroptera) and Melyridae (Coleptera) were both marginally significant. Comparing the indicators in both years, remnants shared two significant taxa, Formicidae (Hymenoptera); and Otitidae (Diptera) as well as one marginally significant taxa, Tettigonidae (Orthoptera), and one taxa that was significant in 2007 and marginally significant in 2006, Cixiidae (Hemiptera). Isolated restoration/reconstruction also had consistent indicators in both years. Aphididae (Hemiptera) was significant in 2007 and marginally significant in 2006. Tingidae (Hemiptera) was marginally significant in both years. Indicators were only significant for integrated sites in 2007. Spiders Selected spider families were identified as potential indicators of prairie types in addition to the insect families. Remnant sites contained one significant family, Dictynidae, 76 and one marginally significant family, Thomisidae in 2006. Isolated sites had one significant family, Salticidae. Integrated sites had one marginally significant family, Lycosidae, in 2006 (Table 4, Fig. 6 & 7). Thomisidae was a significant potential remnant indicator in 2007. Isolated sites were characterized by Philodromidae (α=0.05) and Lycosidae (α=0.10) in 2007. No significant spider families were identified for integrated sites in 2007 (Table 5, Fig. 8 & 9). The only significant taxa with a consistent pattern in both years was the potential remnant indicator, Thomisidae. In our nMDS plots (Figs. 10 & 11), the community of indicators at isolated and integrated sites were more similar to each other compared to the community of indicators at remnants for both sample years. The indicators changed between the years resulting in a slight shift in the plots for each individual year. We performed a separate ISA analysis using just two categories, remnants and combined isolated and integrated sites to determine whether the representative taxa would change. The reclassification did not alter the significant or marginally significant taxa for remnant sites. The taxa that formerly indicated integrated sites were reclassified as indicators of the combined restorations/reconstructions, however none of the resulting combined-site indicators were significant or marginally significant.

DISCUSSION

Our investigation of potential bioindicators for the evaluation of tallgrass prairie habitat demonstrates that the majority of arthropod families are not particularly well-suited indicators of our prairie site types. This analysis does not exclude any of these taxa as indicators of prairie habitats in general when compared to other non-prairie habitats. This could be useful when assessing the value of marginal habitats for conservation efforts. We were successful in identifying a conservative list of preliminary arthropod bioindicators taxa for resource management and further analysis. Four taxa showed consistent significant or marginally significant trends in occurrence at remnants sites in both years of our study: ants (Formicidae), katydids (long-horned grasshoppers; Tettigonidae), plant hoppers (Cixiidae), and picture-wing flies (Otitidae).

Ants have been proposed as indicator taxa in other habitats, for a variety of restoration and reclamation efforts, including mine reclamation (Andersen 1997, Agosti et al. 2000, Andersen et al. 2004). The designation as indicators of biotic integrity for tallgrass prairie underscores the important role of ants in prairies. Ants contribute to soil quality with the construction of subterranean tunnels, can be important herbivores and scavengers, and potentially constitute a large portion of arthropod biomass in prairie habitats (Trager 1998). Our findings contrast with the assertion by Panzer et al. (1995) that ants would be poor indicators because they occupy a variety of prairie types. Further identification of the ants may reveal which genera or species are responsible for the overall trend of ant preference for remnant sites. Fortunately, many resources are available in both printed and electronic format to assist landowners and landmanagers with identifying ants in prairies relative to other taxa (i.e., www.antweb.org, (Agosti et al. 2000)). Ants can also be collected with a variety of techniques. Ants in our samples were collected as part of bulk samples that included many other arthropod taxa. It is also possible to selectively sample ants (litter sifting, bait cards, pitfall traps, etc. (New 1998)), further reducing time and effort spent sorting arthropod samples. Grasshoppers, specifically katydids, are large, easy to collect, herbivorous insects common in prairies (Capinera et al. 2004, Triplehorn and Johnson 2005). As potential indicators, katydids may provide information about the vegetation characteristics of a site since they feed on and oviposit in plant tissues (Triplehorn and Johnson 2005). Katydids are easily identified even to lower taxonomic levels and produce characteristic songs for individual species (Triplehorn and Johnson 2005). Although not as easily recognized as bird song, katydid song may provide one alternative method for data collection that eliminates destructive sampling and by-catch of other insect taxa. Several families of plant hoppers occur in abundance in tallgrass prairies (Hamilton 2005). Based on our analysis, one of these families, Cixiidae, has potential indicator qualities. Cixiidae have not been as well studied as other plant hopper families (i.e., Cicadellidae), especially in prairie ecosystems, and merit further study. The plant hopper families that have been studied in greater detail support plant-host specific genera and species as reliable prairie quality indicators (Hamilton 2005). 78

The true flies (Diptera) compose one of the largest, most diverse insect orders (Triplehorn and Johnson 2005). Many families of flies, including the picture-wing flies (Otitidae) have not been studied in great detail in tallgrass prairies. The association of Otitidae with remnant sites is uncertain, and should motivate additional study of this insect family, and perhaps several others (i.e., Bombyliidae and Tachinidae). The identification of this potential indicator belonging to such a large, diverse order, suggests the importance of terrestrial flies in prairie ecosystems. Spiders are important insect predators in many ecosystems (Foelix 1996, Marc et al. 1999). Although spiders are typically generalist predators, hunting strategy varies by taxa (Foelix 1996, Marc et al. 1999, Ubick et al. 2005). Spiders in the family Thomisidae, crab spiders (Ubick et al. 2005), are often camouflaged to blend in with the surrounding environment. In prairies, these spiders are located on plants, including stems and flowers. Crab spiders were identified by our analysis as potential indicators of remnant prairies. The vegetation structure and abundance of floral resources may contribute to crab spider association with remnant sites. The characteristic hunting strategy, body shape, and coloration helps make these spiders easy to identify, and sweep netting is an effective method of collection. Isolated and integrated sites had fewer associated taxa and potential indicators. Predatory lady beetles (Coccindellidae) and their typical prey: herbivorous aphids (Aphididae) both occurred more frequently and in greater abundance at restored prairies. Aphids are generally host-specific plant feeders (Triplehorn and Johnson 2005) and many native aphids occur on prairie sites. Aphids may occur in greater abundance on plant species more frequently planted in prairie seed mixes used in restorations (e.g., Solidago spp., Ratibita spp., Monarda spp.), and lady beetles may track prey resource availability (Ohnesorg 2008). All ladybeetles, both native and exotics, were included for the family level analysis. Lacebugs (Tingidae) were also associated with restored prairies, but this designation may be due to high abundance values at one restored prairie. In an effort to be conservative with our list of potential indicator taxa, we focused on significant and marginally significant taxa that showed affinities for the same site type during both years of sampling. An additional category of arthropod families may merit further

79 examination without broadening our list of taxa to unrealistic levels. Some taxa were associated with the same site type in both sampling years. Several of these remnant taxa include bees in the families Halictidae and Megachilidae. In addition to their importance as pollinators in prairie ecosystems, bees could be incorporated into monitoring programs for biotic integrity. Bees require not only floral resources but also nesting habitat (Kremen et al. 2002). Observing the presence of particular bees at prairies may suggest that these habitats contain sufficient resources for sustaining native bee populations, although home ranges sizes and dispersal for many bee species are still largely unknown. Large broadly distributed families, such as Chrysomelidae (Coleoptera), Cercopidae, Lygaeidae and Miridae (Hemiptera), may not be reliable indicators at the family level, but selected genera or species within these groups may be responsible for the overall trend toward remnant sites. One shortcoming of only identifying our taxa to family is that some of the specificity of particular genera and species is masked by common, ubiquitous taxa or obviated by species with contrasting life history strategies within these families. We may be able to recommend additional indicator taxa pending further taxonomic resolution. This additional information could also be used to improve identification materials further enhancing the taxa’s utility as bioindicators. We collected 11 insect families in common with the families of species nominated by Panzer et al. (1995). Although they focused on species, their families are comparable. Our analysis and Panzer et al. (1995) corroborate the orthropteran family, Tettigonidae, as being indicative of remnant prairies. Panzer et al. (1995) include three families of plant hoppers: Cicadellidae, Cercopidae, and Issidae which we found to have no significant restriction to remnant prairies in our analysis. Cixiidae, Membracidae, and Acanaloniidae, however, are other families of plant hoppers, which in our analysis did show some association with remnant sites. Similarly, Panzer et al. (1995) recommended bees in the family Apidae as indicators of remnants, while in our analysis Apidae were associated with both integrated sites (2006) and remnants (2007). Bees in the families Megachilidae and Halictidae were associated with remnants in both sampling years in our analysis. Our data and Panzer et al. (1995) corroborate the Hemiptera families Scutellaridae and Lygaeidae as having species restricted to remnants sites. Our analysis suggests that, at least at the family level, Acrididae 80

(Orthoptera), Heteronemiidae (Phasmatidae in Panzer et al. 1995), and Pentatomidae (Hemiptera), are not restricted to remnant sites. Our comparison of insect families to those proposed in Panzer et al. (2005) had both similarities and differences. Both analyses identified the katydids as remnant indicators, providing more justification for their inclusion in prairie monitoring programs. In several cases, we did not identify the same insect family, but did observe trends in similar taxa, including plant hoppers and bees. Our results differed from Panzer et al. (1995) with respect to three taxa; Heteronemiidae, Acrididae, and Pentatomidae. We did not find these three families to be associated with remnant prairies. Inconsistency between our study and Panzer et al. (2005) may be a result of taxonomic resolution, but some relationships should be robust even at the family level if those remnant-dependent taxa are influencing the trend. Habitat variation between central Iowa and northeastern Illinois and southeastern Wisconsin may also account for changes in the observed trend in some arthropod taxa.

CONCLUSIONS

We identified four insect families: Formicidae, Tettigonidae, Cixiidae, and Otitidae; and one spider family: Thomisidae, as potential indicators of remnant prairies. Formicidae are used as indicators in other ecosystems for a variety of conservation programs (Ward and Larivière 2004). The ecological importance of ants in prairie ecosystems also supports their use as prairie bioindicators. Tettigonidae and other plant hopper taxa are supported by our analysis to be indicators and have already been incorporated into some tallgrass prairie studies (Nemec and Bragg 2007). True flies often receive little attention in tallgrass prairie ecosystems; fly taxa in general and Otitidae specifically may require further study. Thomisidae may utilize prairie resources differently from other spider hunting strategies, and may be useful as prairie indicators. Our study provides an independent assessment of previously proposed indicator or remnant-dependent taxa, and identifies both consistencies and inconsistencies. Our data corroborate the application of katydids and the further investigation of plant hoppers and bees, but do not support the use of walkingsticks, stinkbugs, and short-horned grasshoppers as indicators, at least at the family level. Direct

81 application of some of our indicator taxa may not be possible without further study; however, katydids, ants, and plant hoppers could be of immediate use as indicators in restoration and monitoring programs. Although annual census data from the three summer months was used in this study, monitoring programs could adopt less frequent sampling. Further refinements will improve the application of bioindicators in tallgrass prairie ecosystems.

ACKNOWLEDGEMENTS

The authors wish to thank the landowners, land mangers, and agency officials for allowing us to use their prairies: P. Drobney (Neal Smith National Wildlife Refuge), B. Lammers, C. Hildebrand, D. Howell, J. Goerndt, J. Pearson, J. Judson, K. Hansen, K. Cantu, K. Van Zante, M. Cosgrove, M. Meetz, L. Meetz, M. Stegmann, S. Peterson, S. Lekwa, S. Rolfes, L. Lown (Chichaqua Bottoms Greenbelt), S. Moeckly and M. Moeckly. We also acknowledge Greg Van Nostrand, Dana Woolley, Heather Gilliland, and MJ Hatfield for their assistance in the field and laboratory. The authors also appreciate comments from Christopher Tyrrell and Sarah Orlofske regarding this manuscript and statistical assistance from Dr. Dianne Cook (ISU). This project was funded by grants from the Iowa Science Foundation, The Nature Conservancy: Nebraska Chapter’s J.E. Weaver Competitive Grants Program, Prairie Biotic Research, Inc, and the Iowa Department of Natural Resources: Iowa Wildlife Diversity Grant.

LITERATURE CITED

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TABLES AND FIGURES

93.59016 94.56933 94.22528 93.01455 93.03893 93.66538 92.96203 92.86495 94.58819 93.75297 93.79725 93.26985 93.47042 92.96981 93.56695 93.54342 93.69135 Longitude 41.704 42.1495 41.7654 42.4135 41.5602 42.0972 41.7825 41.7706 41.6895 41.8006 42.4366 42.0104 41.9668 42.0227 42.0964 42.0586 41.7494 Latitude 25 15 6.25 8.33 7.08 8.33 8.33 7.08 6.25 16.67 41.68 16.67 16.67 10.42 33.33 29.14 18.75 Hectares 40 15 20 17 40 20 40 25 20 17 80 72 15 60 36 45 100 Acres b L F F F F C C C C C C C C U C,L C,F F, P Land Use Polk Polk Polk Story Story Story Story Story Jasper Jasper Jasper Guthrie Guthrie County Webster Marshall Marshall Hamilton a ISO ISO ISO ISO ISO ISO ISO ISO REM REM REM REM REM REM REM REM REM Type PF LS GF DP BC CB RU SH MF GR ME DO BW JUD MAR MOE MOR Abbr. Site Table 1. Summary of prairie sites. Doolittle Prairie State Preserve Judson Prairie Liska-Stanek Prairie State Preserve Drobney Prairie Marietta Sand Prairie State Preserve Moeckly Prairie A.C. and Lela Morris Prairie Reichelt Unit, Stephen's State Forest Sheeder State Preserve Big Creek Wildlife Management Area Briggs Woods Park Colo Bogs Wildlife Management Area Grant Ridge Grimes Farm Conservation Area McFarland Park Meetz Prairie Prairie Flower Campground

85 93.61572 93.55438 93.27412 93.27884 93.29609 93.27374 93.27586 93.39378 93.35555 93.36486 93.38097 93.38731 93.34504 Longitude 41.753 41.774 41.736 41.773 42.3275 41.9946 41.5536 41.5377 41.5557 41.5748 41.5946 41.7741 41.7861 Latitude int int int int int int int int int int int 31.25 10.42 Hectares 75 25 int int int int int int int int int int int Acres b P P C C C C C C C C C C,F F, P Land Use Polk Polk Polk Polk Polk Polk Story Jasper Jasper Jasper Jasper Jasper County Hamilton a INT INT INT INT INT INT INT INT INT INT INT ISO ISO Type TF ST PC SE N1 N2 N3 N4 N5 EM RM SW AIR Abbr. 2 2 2 2 Site 2 2 1 1 1 1 1 Neal Smith National Wildlife Refuge Chichaqua Bottoms Greenbelt C: Row crop, F: Forest, L: Livestock Pasture, P: Prairie, U: Urban REM: Remnant, ISO: isolated restoration/reconstruction, INT: integrated reconstruction Table 1. Summary of prairie sites (continued). Richards Marsh Natural Resource Area Stargrass Prairie NSNWR 1 NSNWR 2 NSNWR 3 NSNWR 4 NSNWR 5 "Airport" CBG Engeldinger Marsh CBG Puccoon CGB Sandhill East Unit CGB Sandhill West Unit CGB Turtlehead Fen CGB 1 2 a b

Table 2. Insect families (2006) as indicators of prairie type ** p=0.05, * p=0.10. Remnant Isolated Integrated Indicator Indicator Indicator Family Value Family Value Family Value Acanaloniid* 0.33 Anthicid 0.10 Acridid 0.37 Agromizid 0.11 Anthomyiid 0.05 Andrenid 0.14 Alydid** 0.42 Aphid* 0.42 Berytid 0.29 Anthocorid** 0.46 Carabid 0.15 Cerambycid 0.20 Anthomyzid 0.07 Chrysidid 0.10 Chrysopid 0.34 Apid 0.29 Coccinellid** 0.48 Geocorid 0.09 Asilid 0.26 Colletid 0.20 Gryllid 0.37 Bombyliid* 0.36 Curculionid 0.39 Heteronemiid 0.18 Calliphorid* 0.22 Delphacid 0.34 Melyrid 0.26 Cantharid 0.34 Drosophilid 0.14 Nabid 0.29 Cercopid 0.30 Issid 0.29 Pipunculid 0.21 Chloropid 0.35 Lampyrid 0.30 Pompilid 0.09 Chrysomelid 0.35 Languriid 0.10 Rhipiphorid 0.09 Cicadellid 0.34 Mutilid 0.52 Scarabaeid 0.04 Cixiid* 0.38 Myrmeleontid 0.10 Sphecid 0.14 Clerid 0.27 Pentatomid 0.37 Tephritid 0.36 Cydnid 0.08 Phalacrid 0.41 Derbid 0.09 Ptilodactylid 0.12 Dermestid 0.11 Reduviid 0.33 Dictyopharid 0.34 Sepsid 0.27 Dolichopodid 0.32 Staphylinid 0.12 Elaterid** 0.44 Stratiomyid 0.21 Ephydrid 0.21 Tingid* 0.38 Formicid** 0.42 Halictid 0.31 Latridiid 0.35 Lygaeid 0.36 Megachilid 0.26 Meloid 0.26 Membracid 0.41 Mirid 0.39 Mordellid 0.29 Muscid 0.34 Nitidulid 0.18 Otitid** 0.61 Phorid 0.30 Psyllid 0.38 Rhagionid 0.11 Sacrophagid 0.34 Sciomyzid 0.20 Scutellerid 0.21 Syriphid 0.36 Tabanid 0.07 Tettigonid* 0.42 Thyreocorid 0.27 Vespid 0.23

Table 3. Insect families (2007) as indicators of prairie type ** p=0.05, * p=0.10. Remnant Isolated Integrated Indicator Indicator Indicator Family Family Family Value Value Value Anthicid 0.13 Andrenid 0.09 Acridid 0.37 Acanaloniid 0.23 Anthomyiid 0.10 Apid 0.15 Alydid 0.30 Aphidid** 0.30 Chrysopid 0.34 Anthocorid 0.31 Aradid 0.10 Cicadellid 0.35 Anthomyzid* 0.22 Coccinellid 0.37 Clerid 0.16 Anthribid* 0.24 Delphacid 0.36 Drosophilid 0.17 Asilid 0.27 Lampyrid 0.34 Eucinetid 0.09 Berytid 0.34 Latridiid 0.22 Gryllid** 0.46 Biphyllid 0.11 Leiodid 0.10 Hemerobiid* 0.27 Bombyliid 0.24 Mordellid 0.34 Issid 0.30 Buprestid 0.11 Phengodid 0.10 Meloid 0.11 Calliphorid 0.23 Piesmatid 0.10 Melyrid* 0.28 Cantharid** 0.56 Platystomatid 0.13 Nabid 0.34 Carabid 0.19 Rhipiphorid 0.10 Pentatomid 0.35 Cerambycid 0.14 Sacarabaeid* 0.26 Phalacrid 0.34 Cercopid 0.38 Sciomyzid 0.10 Phorid 0.23 Cholorpid* 0.36 Sepsid** 0.37 Psyllid 0.37 Chrysomelid 0.34 Silvanid 0.10 Staphylinid 0.12 Cicadid 0.11 Stratiomyid 0.21 Therevid 0.51 Cixiid** 0.44 Tingid* 0.35 Xylomyiid 0.91 Colletid 0.27 Coreid 0.15 Curculionid 0.38 Dictyopharid 0.36 Dolichopodid* 0.41 Elaterid 0.19 Empidid 0.11 Flatid 0.16 Formicid** 0.39 Halictid 0.34 Heteronemiid 0.15 Lygaeid* 0.44 Megachilid** 0.39 Membracid* 0.42 Mirid** 0.40 Muscid** 0.42 Mutillid** 0.33 Nitidulid 0.17 Otitid** 0.55 Pipunculid 0.23 Psephenid 0.11 Reduviid 0.26 Rhagionid 0.17 Sacrophagid* 0.42 Sciritid 0.11 Scutellerid 0.06 Sphecid 0.08 Syrphid 0.33 Tabanid* 0.28 Tachinid** 0.38 Tenebrionid 0.11 Tephritid 0.34 Tettigonid* 0.48 Thyreocorid 0.36 Vespid* 0.23

Table 4. Spider families (2006) as indicators of prairie type ** p=0.05, * p=0.10. Remnant Isolated Integrated Family Indicator Value Family Indicator Value Family Indicator Value Dictynid** 0.46 Anyphaenid 0.09 Clubionid 0.10 Oxyopid 0.03 Araneid 0.35 Lycosid* 0.27 Tetraganthid 0.21 Linyphiid 0.38 Theridiosomatid 0.11 Philodromid 0.26 Thomisid* 0.38 Salticid** 0.42

Table 5. Spider families (2007) as indicators of prairie type ** p=0.05, * p=0.10. Remnant Isolated Integrated Family Indicator Value Family Indicator Value Family Indicator Value Araneid 0.36 Clubionid 0.11 Anyphaenid 0.21 Dictynid 0.18 Lycosid* 0.25 Linyphiid 0.28 Philidromid** 0.55 Oxyopid 0.28 Salticid 0.35 Thomisid** 0.44 Tetragnathid 0.28

Figure 1. Map of central Iowa prairie locations used in this study.

Figure 2. Bar chart depicting the abundance by site type of significant and marginally significant insect taxa in 2006.

Figure 3. Bar chart depicting the number of sites of each prairie type where significant and marginally significant insect taxa occurred in 2006. Dashed vertical line indicate the total number of sites in each type: remnant (9), isolated (10), and integrated (11).

Figure 4. Bar chart depicting the abundance by site type of significant and marginally significant insect taxa in 2007.

Figure 5. Bar chart depicting the number of sites of each prairie type where significant and marginally significant insect taxa occurred in 2007. Dashed vertical line indicate the total number of sites in each type: remnant (9), isolated (10), and integrated (11).

Figure 6. Bar chart depicting the abundance by site type of significant and marginally significant spider taxa in 2006.

Figure 7. Bar chart depicting the number of sites of each prairie type where significant and marginally significant spider taxa occurred in 2006. Dashed vertical line indicate the total number of sites in each type: remnant (9), isolated (10), and integrated (11).

Figure 8. Bar chart depicting the abundance of significant and marginally significant spider taxa in 2007.

Figure 9. Bar chart depicting the number of sites of each prairie type where significant and marginally significant spider taxa occurred in 2006. Dashed vertical line indicate the total number of sites in each type: remnant (9), isolated (10), and integrated (11).

Figure 10. nMDS plot of insect family indicators collected in 2006 by site type using log- transformed abundance values and Bray-curtis distance, stress = 19.51. Sites of the same type are displayed with a labeled polygon, REM: remnant sites, ISO: isolated sites, and INT: integrated sites.

Figure 10. nMDS plot of insect family indicators collected in 2007 by site type using log- transformed abundance values and Bray-curtis distance, stress = 19.67. Sites of the same type are displayed with a labeled polygon, REM: remnant sites, ISO: isolated sites, and INT: integrated sites.

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CHAPTER FOUR. GENERAL CONCLUSIONS

McGeoch (1998) states: “Research is not conservation biology unless it has application for management.” We successfully achieved our primary objectives, although there are opportunities to further synthesize our research. The results of this project meet the requirement of research in conservation biology by providing reasonable guidelines for natural resource professionals and prairie biologists as well as proposing areas of future research. (McGeoch 1998) Our primary objective, addressed in Chapter 2, was to compare the arthropod community (insects and spiders) at three prairie types. We described a diverse arthropod community of 106 insect and 13 spider families. These data provide a new standard in prairie arthropod communities. Among our site types, the arthropod community was similar. The similarity in arthropod diversity, at the family level, suggest that prairie restoration and reconstruction efforts have been effective for reestablishment of tallgrass prairie, or it may indicate that decades of human disturbance have degraded the arthropod community, perhaps permanently. Resource professionals should benefit from our description of the arthropod community. We demonstrated how a few, easily obtained arthropod specimens identified to the family level can provide an independent assessment of prairie quality. The goal of Chapter 3 was to identify selected arthropod taxa to serve as indicators of biotic integrity in tallgrass prairies. The arthropod families identified as bioindicators could be incorporated into monitoring and conservation planning programs. The proposed indicator taxa also provide the basis for further taxonomic resolution to identify specific genera or species responsible for the family-level indicator status independent of taxonomic precedence. We identified four insect families: Formicidae, Tettigonidae, Cixiidae, and Otitidae; and one spider family: Thomisidae, as potential indicators of remnant prairies. Formicidae are used as indicators in other ecosystems for a variety conservation programs (Andersen 1997, Agosti et al. 2000, Andersen et al. 2004). The ecological importance of ants in prairie ecosystems also supports the use of Formicidae as prairie bioindicators. Tettigonidae and planthopper families related to Cixiidae are just now being incorporated 102 into some tallgrass prairie studies (Nemec and Bragg 2007). True flies often receive little attention in tallgrass prairie ecosystems, therefore, fly taxa in general and Otitidae specifically may merit further examination. The crab spiders (Thomisidae) may utilize prairie resources for hunting strategies differently from other spider families, and may be useful as prairie indicators. Our study provides an independent assessment of previously proposed indicator or remnant-dependent taxa, and identifies both consistencies and inconsistencies. Our data corroborate the application of katydids, and further investigation of hoppers and bees, but possibly the abandonment of walkingsticks, stinkbugs, and short-horned grasshoppers at least at the family level. Direct application of some of our indicator taxa may not be possible without further study; however, katydids, ants, and plant hoppers could be of immediate use at the family level as indicators of restoration success. The first step in incorporating arthropods into restoration and management programs is to collect baseline data for prairie sites, and then monitor indicator populations over time and after management practices, such as mowing or prescribed burning. This is not the final chapter on prairie arthropods, rather it is the preface. Our research provides baseline data that will be a useful starting point for other prairie arthropod studies. In addition, it raises new questions that need testing, such as the efficacy of our indicators at lower taxonomic levels and in areas extending beyond central Iowa. The needs of the natural areas management community will also dictate further refinements in our application of arthropod indicators.

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LITERATURE CITED

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APPENDIX ONE. SUPPLEMENTAL FIGURES FOR CHAPTER TWO

Figure 1. Taxa (family) accumulation curves for insect families collected in sweep net transects in June 2006. Insect families were counted the first time they were encountered and accumulated every 10 sweeps by dividing each transect in half for a total of 6 subsamples and 60 sweeps to determine taxa (family) accumulation curves. Sites are listed in order of total richness after 60 sweeps and in the approximate position of the representative line. Sites MAR, RU, SE, SW, and TF are not shown since subsamples were pooled prior to specimen identification.

Figure 2. Taxa (family) accumulation curves for insect families collected in sweep net transects in July 2006. Insect families were counted the first time they were encountered and accumulated every 10 sweeps by dividing each transect in half for a total of 6 subsamples and 60 sweeps to determine taxa (family) accumulation curves. Sites are listed in order of total richness after 60 sweeps and in the approximate position of the representative line.

Figure 3. Taxa (family) accumulation curves for insect families collected in sweep net transects in August 2006. Insect families were counted the first time they were encountered and accumulated every 10 sweeps by dividing each transect in half for a total of 6 subsamples and 60 sweeps to determine taxa (family) accumulation curves. Sites are listed in order of total richness after 60 sweeps and in the approximate position of the representative line. Site MOE is not shown since no sweep net samples were obtained at that site in August 2006.

Figure 4. Insect abundance by prairie site collected June-August 2006. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. Insect abundance was summed across each site. Site names have been abbreviated. Remnant sites shown in bold text, isolated sites shown in gray text, and integrated sites shown in plain text.

Figure 5. Insect abundance by prairie site collected June-August 2007. The size of the gray box is proportional to the abundance of each taxa at the appropriate site.Insect abundance was summed across each site. Site names have been abbreviated. Remnant sites shown in bold text, isolated sites shown in gray text, and integrated sites shown in plain text.

Figure 6. Spider abundance by prairie site collected June-August 2006. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. Spider abundance was summed across each site. Site names have been abbreviated. Remnant sites shown in bold text, isolated sites shown in gray text, and integrated sites shown in plain text.

Figure 7. Spider abundance by prairie site collected June-August 2007. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. Spider abundance was summed across each site. Site names have been abbreviated. Remnant sites shown in bold text, isolated sites shown in gray text, and integrated sites shown in plain text.

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Figure 8. Total abundance of insect families collected June – August 2006. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. Insect abundance was summed across all sites and taxa are ordered from highest to least abundant.

Figure 9. Total abundance of insect families collected June – August 2007. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. Insect abundance was summed across all sites and taxa are ordered from highest to least abundant.

Figure 10. Total abundance of spider families collected June – August 2006. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. Spider abundance was summed across all sites and taxa are ordered from highest to least abundant.

Figure 11. Total abundance of spider families collected June – August 2007. The size of the gray box is proportional to the abundance of each taxa at the appropriate site. Spider abundance was summed across all sites and taxa are ordered from highest to least abundant.

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ACKNOWLEDGEMENTS

I am sincerely grateful to many people for their individual and collective contributions to my research, my academic program, and quality of life. I am most grateful to my family: my parents Carole and David for being the foundation of my outstanding education and a constant source of inspiration and encouragement and to my sister Sarah for challenging me and keeping me informed of parasite and vertebrate research. I am especially grateful to my husband, Christopher Tyrrell, for his patience, understanding, guidance, and willingness to assist with botanical, computational, and statistical needs. Thank you for sharing your talents with me. I also want to thank my network of friends and colleagues at Iowa State University, University of Wisconsin-Stevens Point, and across the country. I am indebted to my collaborators, lab and field assistants, and fellow lab members. I would like to thank Wayne Ohnesorg for cooperating in our joint conservation biology/ agroecosystem project. We found a way to look at two different, equally important, questions about the same system, and had a lot of fun along the way. I am grateful to Greg Van Nostrand, Dana Woolley, Heather Gilliland, and Anna McDonald for their help in the field and in the lab. I also want to thank, Jenny Hopwood, Scott Sauer, James Trager, and Adam Wallner for their expertise with identification and biology of particular arthropod taxa. I want to thank MJ Hatfield, not only for her help in the lab and field, but also for her enthusiasm, passion for arthropods, and never letting me do less than my best. This project would not have been possible without interested and cooperative landowners and land managers. Thank you for the privilege to work at the most beautiful prairies in central Iowa. I hope my project can improve our understanding and appreciation of this marvelous ecosystem! I appreciate the guidance and advice from my committee and advisor, Dr. Diane Debinski, Dr. Matthew O’Neal, Dr. Brent Danielson, and Dr. Dianne Cook. I also appreciate the support I have received from my department: Ecology, Evolution and Organismal Biology, as well as the Entomology Department, the Ecology and Evolutionary Biology Program and fellow graduate students, especially Jim Church, Becky Parsons, Kevin Day, and Chelsea Berns.