Local Environment Attachment and the Possibility of Using Citizen Science Approaches

to Measure Firefly Populations in Time and Place

DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

By

Yang Xing

Graduate Program in Environmental Science

The Ohio State University

2012

Dissertation Committee:

Professor Richard Moore, Advisor

Professor Jeremy Bruskotter

Professor Joe Kovach

Copyright by

Yang Xing

2011

Abstract

While the number of conservation projects has increased domestically and worldwide, many environment education programs have failed to fulfill their goals of encouraging the citizens to actively adopt pro-environment behaviors. To investigate the potential correlation between people’s environment attachment and people’s tendency to perform pro-environment behaviors, a survey was conducted in the rural part of Wayne

County, OH in 2009. The result of the survey research shows a significant correlation between people’s attachment to the natural environment and their tendency to participate in certain kinds of pro-environment behaviors. Such finding supplements the previous research on the relationship between place attachment and pro-environment behaviors.

The survey results from my 2009 survey show that these local citizens tend to associate fireflies with good environment quality. A literature review yielded little evidence to support or reject such hypothesis. One major reason for the lack of research on the relationship between fireflies and the natural environment was because of the lack of suitable technology to monitor firefly activities in the field. I developed a new timed sequential digital photographic method to monitor firefly flashing activities in their natural habitats. Such method has potential for engaging citizens into environment education programs. I used this method to collect data on the West Badger Farm near

ii

Wooster, OH in 2009. The results showed that this method could capture the flashing activities of different firefly species and was sensitive to the changes of the flashing activities. The two species of fireflies I studied showed similar responses to climatic factors, but different responses to landscape types and farming practices. The data also suggested that these two firefly species were active at the same time during the night, contrary to previous studies that classified them into different active groups (“early- active” vs. “late-active”).

iii

Dedication

This document is dedicated to the fireflies and the hope that they can be used as an

indicator to improve environmental quality

iv

Acknowledgments

Most of my appreciation goes to my advisor, Richard Moore. I could not make it to this point without his thorough support through all these years I have been in the

Environmental Science Graduate Program. Maurea Al-khouri, the program administrative secretary, was helpful in arranging dates and rooms and keeping me up to date on deadlines.

I thank my other dissertation committee members, Jeremy Bruskotter, and Joe

Kovach. They helped me to form my dissertation’s topic and to conduct the research. Dr.

Kovach’s help in being my advisor temporarily when my previous advisor retired was invaluable during the transition when my previous advisor retired. The committee, including the Graduate School representative Dr. Tim Rhodus, all gave invaluable advice on improving the structure and organization of chapters. Dr. Mary Beth Averill, my writing coach, helped me learn improved writing techniques and take the committee’s recommendations and transform my first dissertation draft into its present form.

I thank Lois Grant (HCRD-OARDC) for helping me get all the information on supplies procurement for the research at OARDC and letting me use her office. I thank

Deana Hudgins (HCRD-OARDC) for sharing with me the GIS data of the North Fork

v

Subwatershed area. I thank Dave McCartney (HCRD-OARDC) for helping me with the necessary equipment.

I appreciate the help given to me by Deb Stinner and Bob Napier (Organic Food and Farming Education and Research Program-OARDC) on the West Badger Farm research and Matthew Mariola (OARDC) who taught me how to apply for the IRB approval.

The Tokyo Genji Botaru Firefly Research Institute (東京ゲンジボタル研究所) shared their suggestions on how to take photographs of fireflies in the field. The following people assisted me in data collection at various stages of this study: Richard

Moore (OSU-OARDC), Xiaoping Wei (ESGP-OARDC), OARDC Summer Intern

Program students (alphabetically by surname: Brandon Beachy, Sydni Franks, Mandee

Glsago, Chloe Schrock, Meggan Spencer, and Raina Workman).

Many people have provided me with their experiences and knowledge on fireflies.

Among others I thank James Lloyd (University of Florida), Lynn Faust (Great Smoky

National Park), Creighton Freeman (Museum of biodiversity-OSU), and Andrew Moiseff

(University of Connecticut),

My sincere appreciation goes to my parents: Baochang Xing and Lanying Yang for the unconditional support they provided me all these years. I am also grateful to all my friends, for their personal assistance and support.

vi

Vita

May 27, 1981……………………..Born-Beijing, China

2003………………………………B.S. Life Science, Peking University

2003 to 2005……………………...Graduate Research Associate

Ohio State Biochemistry Program

The Ohio State University

2005………………………………M.S. Biochemistry, The Ohio State University

2005 to 2007……………………...Graduate Teaching Associate

Biology Program

The Ohio State University

2007 to present……………………Graduate Research Associate

Ohio Agricultural Research and Development Center

The Ohio State University

Fields of Study

Major Field: Environmental Science

vii

Table of Contents

Abstract ...... ii

Dedication ...... iv

Acknowledgments...... v

Vita ...... vii

Table of Contents ...... viii

List of Tables ...... xiii

List of Figures ...... xv

CHAPTER 1 ...... 1

FIREFLIES AND CITIZEN SCIENCE PROJECTS, ...... 1

LINKING PEOPLE TO NATURE ...... 1

1.1. Introduction ...... 1

1.2. Logic behind the Structure of the Dissertation...... 3

1.3. The Common Theme of Promoting Citizen-based Conservation Programs Using

Fireflies as the Thread ...... 6

viii

1.3.1. Citizen science as means to promote conservation ...... 10

1.3.2. Research on fireflies as an ideal target for citizen science ...... 22

CHAPTER 2 ...... 38

THE INFLUENCE OF ENVIRONMENTAL ATTACHMENT ON PEOPLE’S

WILLINGNESS TO PERFORM PRO-ENVIRONMENTAL BEHAVIOR: ...... 38

A CASE STUDY IN THE RURAL COMMUNITY OF NORTH FORK

SUBWATERSHED, WAYNE COUNTY, OH ...... 38

2.1. Introduction ...... 38

2.1.1. The Challenge Faced by Conservation Programs ...... 39

2.1.2. Place Attachment ...... 42

2.1.3. Community Attachment ...... 43

2.1.4. Attachment to the Environment ...... 45

2.1.5. Pro-environmental Behavior...... 48

2.1.6. Proposed Research ...... 51

2.2. Method ...... 54

2.2.1. Description of Study Area ...... 55

2.2.2. Prior Similar Research Done in the Study Area ...... 56

2.2.3. Survey Instrument for This Study ...... 59

ix

2.2.4. Data Collection ...... 63

2.2.5. Data Analysis ...... 65

2.3. Results ...... 66

2.3.1. Components of Attachment ...... 66

2.3.2. Pro-environmental Behaviors ...... 69

2.3.3. Relationship of Pro-environmental Behaviors, Attachment Factors, and

Demographics ...... 71

2.4. Discussion ...... 73

2.4.1. Existing Models ...... 75

2.4.2. A New Model ...... 76

2.4.3. Limitations ...... 78

2.4.4. Comparison to the 2003 Study ...... 79

CHAPTER 3: ...... 81

A NEW TIMED SEQUENTIAL DIGITAL PHOTOGRAPHIC METHOD ...... 81

FOR MONITORING BIOLUMINESCENT FLASHING ACTIVITY OF FIREFLY

Photinus pyralis AND Photuris pennsylvanica (Coleoptera: Lampyridae) ...... 81

3.1. Introduction ...... 81

3.2. Timed Sequential Digital Photographic Method ...... 84

x

3.3. Results ...... 86

3.3.1. Field observations ...... 86

3.3.2. Data collected ...... 87

3.3.3. Estimating the population density of fireflies...... 91

3.4. Discussion ...... 94

CHAPTER 4 ...... 98

LANDSCAPE STUDY ON COMPARING FIREFLY FLASHING ACTIVITIES . 98

IN CONVENTIONAL AND ORGANIC FIELDS...... 98

4.1. Introduction ...... 98

4.2. Methods ...... 101

4.3. Results ...... 105

4.3.1. Association of climatic factors with firefly flashing activity ...... 105

4.3.2. The association of farming practices on firefly flashing activity ...... 108

4.3.3. Comparison P. pennsylvanica and P. pyralis in terms of their responses to the

environment ...... 116

4.4. Discussion ...... 122

4.4.1. Limitations and suggestions for further research ...... 122

4.4.2. Implications for agricultural monitoring and citizen science ...... 124

xi

CHAPTER 5 ...... 126

A REEXAMINATION OF THE CONCEPT OF EARLY-ACTIVE VS. LATE-

ACTIVE BY COMPARING THE PEAK PERIODS OF BIOLUMINESCENT

FLASHING ACTIVITY OF FIREFLIES Photinus pyralis AND Photuris pennsylvanica (Coleoptera: Lampyridae) ...... 126

5.1. Introduction ...... 126

5.2. Method ...... 130

5.3. Results ...... 131

5.4. Discussion ...... 132

References ...... 136

Appendix A: Survey ...... 160

xii

List of Tables

Table 1. Citizen science as a scientific method...... 18

Table 2. Response items related to pro-environmental behaviors ...... 61

Table 3. Response items related to attachment ...... 62

Table 4. Socioeconomic variable summary...... 64

Table 5. Factor loadings and internal consistency of attachment items...... 68

Table 6. Factor loadings and internal consistency of local level pro-environment behavior items...... 70

Table 7. Factor loadings and internal consistency of national level pro-environment behavior items...... 70

Table 8. Correlation between environment attachment (EA) and each type of pro- environmental behavior (PEB). (Two tail Pearson’s r) (*p<.05) ...... 71

Table 9. Correlation between Feeling Attachment (FA) and each type of pro- environmental behavior (PEB). (Two tail Pearson’s r) (*p<.05.) ...... 72

Table 10. Correlation between Human Attachment (HA) and each type of pro- environmental behavior (PEB). (One tail Pearson’s r) (*p<.05.) ...... 72

xiii

Table 11. Correlation between Safety Attachment (SA) and each type of pro- environmental behavior (PEB). (One tail Pearson’s r) (*p<.05.) ...... 72

Table 12. Correlation between Problem Attachment (PA) and each type of pro- environmental behavior (PEB). (One tail Pearson’s r) (*p<.05.) ...... 72

Table 13. Correlation between Environment Attachment (EA) and Social Demographic

Factors (SDF). (One tail Pearson’s r) (*p<.1. **p<.05.) ...... 73

Table 14. Example of data collected using the timed sequential digital photographic method for P. pyralis and P. pennsylvanica flashes counts on the West Badger Farm during the summer of 2009...... 88

Table 15. P. pennsylvanica’s flashing activity on the Organic Hay field changes over the whole season...... 89

Table 16. P. pyralis’s flashing activity changes over night...... 90

Table 17. Farming practices that may have had an important impact on the landscapes of the selected plots in the West Badger Farm where the firefly data was collected during the firefly season of 2009...... 113

xiv

List of Figures

Figure 1. Question asking people's perceived correlation between different organisms and environment/water quality in the 2009 survey...... 23

Figure 2. Perceived relationships between common organisms and environment quality.

Organisms are organized according to their average score (with standard deviation) from a survey conducted in North Fork Subwatershed in Wayne County, OH. Firefly ranked fourth highest...... 24

Figure 3. No. of publications using each organism as the keyword. Organisms are organized according to the number of peer reviewed papers from a search conducted using the Environment Complete Database on The Ohio State University’s website.

Firefly ranked second lowest...... 25

Figure 4. The distribution of firefly species across the United States that produce “flashed signals.” The numbers in the figure legend indicate number of flashing species known to occur in each state (Thancharoen, 2008)...... 30

Figure 5. Firefly distribution over the world (shown in light color)

(http://animals.nationalgeographic.com/animals/printable/firefly.html)...... 30

xv

Figure 6. Life cycle of the Photuris firefly in the Maryland region (McLean et al., 1972).

Note: Figure used by permission from The American Biology Teacher ...... 34

Figure 7. Continuum of tendency to perform created by combining people's intention and their actual behavior...... 50

Figure 8. Map of the Sugar Creek Watershed...... 57

Figure 9. Map of the North Fork Subwatershed...... 58

Figure 10. Final model for the relationship between attachment to the natural environment and people’s tendency to perform pro-environmental behavior...... 77

Figure 11. P. pennsylvanica’s flashing activity on the Organic Hay field changes over the whole season...... 89

Figure 12. P. pyralis’s flashing activity changes over night...... 90

Figure 13. The different landscape types in the West Badger Farm in Wooster, OH. ... 103

Figure 14. Correlation between 5cm soil temperature and air temperature. Note: weather data downloaded from the weather station (http://www.oardc.ohio- state.edu/newweather/stationinfo.asp?id=1)...... 104

Figure 15. P. pennsylvanica flashes per second per photo change over several climatic factors...... 107

Figure 16. Average 5cm soil temperature (°C) of different parcels with standard deviations...... 109

Figure 17. Box plot of P. pennsylvanica flash density among different landscapes. The black lines in the middle of the boxes represent the medians of all the data points. The

xvi

upper and lower boundaries of the boxes show the75% (upper quartile) and 25% (lower quartile) of the data sets. The small circles on the top of the boxes are potential outliers, which were not included in the data when calculating the 25% and 75% boundaries. .. 110

Figure 18. P. pennsylvanica flashes per second per photo change with date on different landscapes. Boxes represent events during the firefly season...... 112

Figure 19. P. pyralis flashes per second per photo change over climatic factors...... 118

Figure 20. Boxplot of P. pyralis flash density change among different landscapes. The black lines in the middle of the boxes represent the medians of all the data points. The upper and lower boundaries of the boxes show the75% (upper quartile) and 25% (lower quartile) of the data sets. The small circles on the top of the boxes are potential outliers, which were not included in the data when calculating the 25% and 75% boundaries ... 119

Figure 21. Comparison of P. pyralis and P. pennsylvanica flashes per second per photo on different landscapes. Dashed line represents P. pyralis and solid line represents P. pennsylvanica...... 121

Figure 22. Firefly flash density change over time during the night...... 132

Figure 23. Graph of photonic luminosity function (black) including CIE 1931 (solid),

Judd-Vos modified (dashed), and Sharpe, Stockman, Jagla & Jägle 2005 (dotted); and scotopic luminosity function, CIE 1951 (gray).

(http://en.wikipedia.org/wiki/File:Luminosity.png) ...... 134

xvii

CHAPTER 1

FIREFLIES AND CITIZEN SCIENCE PROJECTS,

LINKING PEOPLE TO NATURE

1.1. Introduction

This dissertation is composed of the introduction plus four independent chapters that cover both natural science and social science. Related topics include entomology, landscape ecology, organic farming, digital photography, citizen science, and behavioral science. These seemingly unrelated concepts are united with a common theme of citizen science based conservation programs. The thread I used to tie them together is fireflies.

Each chapter is trying to answer a specific question at different levels or from different perspectives on conservation programs and their present or future relationship to preserving fireflies.

Chapter 2 deals with a general problem—people’s attachment to the environment and if such attachment has a significant correlation with pro- environmental behavior, using a survey questionnaire. Most conservation programs contend with the issue of how to engage people to perform pro-environmental behaviors, so the specific case examined in this dissertation may shed light on this general problem. The result of one particular question asked in the survey mentioned in Chapter 2 indicates that a gap exists between

- 1 - scientific research and public interest in terms of the firefly’s relation with its natural habitat. To help fill such a gap, the third chapter describes a new timed sequential digital photographic method I developed for monitoring firefly flashing activities in their natural habitat. The fourth chapter compares the flashing activities of fireflies in different landscapes near the rural agricultural community of Wooster, OH. Chapters 3 and 4 are more specific than Chapter 2 since they deal with particular species of an insect (firefly), and how fireflies may be used as indicators of organic agricultural practices and varying landscapes, a strategy that may be adopted by a wide range of conservation programs.

The fourth chapter utilizes the technique described in Chapter 3, which makes the firefly behavioral comparisons easier for academic and citizen scientists. Chapter 5 further contributes to the existing knowledge about fireflies by presenting a finding that challenges the traditional concepts of “early-active” and “late-active” firefly species.

Since I successfully implemented the new technology described in Chapter 3 to conduct this simple and reliable scientific study, Chapter 5 serves as an example for environment organizations and interested citizens who may want to perform similar conservation projects.

In this introduction, I will first explain the logic behind how I constructed this dissertation. Then for each chapter I will use one to several paragraphs to describe how each chapter is accomplishing a specific goal in regard to improving citizen science- based conservation programs and how fireflies are used as the thread to tie them all

- 2 - together. Finally, I will give some background information related to the topics involved in each chapter.

1.2. Logic behind the Structure of the Dissertation

The key issue in developing an effective citizen science program is the balance between creating a scientific program with high standards (scientific rigor) and involving the local people in something that has meaning to them. The emphasis of citizen science programs has expanded from informal science education to benefit solid scientific research during the past 30 years (California and the World Ocean '02, Magoon, &

American Society of Civil Engineers, 2005; Brossard, Lewenstein, & Bonney, 2005;

Bauer, Petkova, & Boyadjieva, 2000; Spiro, 2004; Bonney et al., 2009; Baretto,

Fastovsky, & Sheehan, 2003; McCaffrey, 2005), mainly due to technological advancement (Silvertown, 2009). Citizen science developed within the context of monitoring ecosystems using volunteers (Ballard, Pilz, Jones, & Getz, 2005; Cooper,

Dickinson, Phillips, & Bonney, 2007; Firehock &West, 2001). Some well-known citizen science projects include the Audubon Society’s Christmas Bird Count, the International

Water Association’s World Water Monitoring Day, Cornell Laboratory of Ornithology’s eBird, NestWatch, Project FeederWatch, the Whale Shark Photo-identification Library,

World Wide Fund for Nature’s Budburst, and the Boston Museum of Science’s Firefly

Watch.

Most citizen science-based conservation programs depend on their volunteers to collect data by monitoring the environment at a large scale for a long period of time.

- 3 - Thus, volunteer participation is critical for the program to be successful. However, the factors that influence volunteer’s participation in citizen science based conservation programs have not been well studied (Measham, 2008; Bruyere, 2007).

I propose a new model that links people’s tendency to perform pro-environment behaviors to their attachments to various factors, especially the natural environment. The model uses people’s “intention” as an estimator of their tendency to perform certain behaviors. According to Fishbein & Ajzen’s (1975) Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB), people’s intention is affected by attitudes, social norms and perceived behavior control. Since “attachment” can be influenced by both attitude and social norms, this study investigates the relation between attachment and tendency to perform pro-environmental behaviors directly. After going through the literature I found limited research about attachment to the natural environment, which I hypothesize to have significant correlation with pro environment behaviors. Therefore, I developed a survey to test my hypothesis. Once the positive correlation between attachment to the natural environment and people’s willingness to perform pro- environment behaviors was established, I took the next step to investigate how to design a specific conservation program focusing on people’s attachment to the natural environment.

Fireflies are good candidates for connecting the local community to the natural environment, with a potential link between firefly activity and organic farming. I knew from the survey that plenty of interest on fireflies exists among the farmers in the North

- 4 - Fork Subwatershed. To test the association of fireflies with different crop types, I set up a landscape study at the West Badger Farm.

Although much research exists about fireflies throughout history, most of it focuses on the mechanisms of firefly bioluminescence. A lack of research on the relationship between fireflies and their natural habitats is evident. Most firefly habitat studies are from Japan, where aquatic fireflies are traditionally linked with good water quality. In North America, a void of research is apparent about the relationship between the native terrestrial fireflies and the natural environment. To fill the need for better technology to study fireflies in the field, I developed a timed sequential photographic method to record firefly flashing activities in the field. I tested the new technology by comparing data collected using it on two different species of fireflies. The results showed that the new method is sensitive to the change in firefly flashing activities.

While working on developing the new method and analyzing the data collected using this method, I noticed an interesting phenomenon that may contradict a previous statement made by other firefly researchers. Lall, Seliger, Biggley, & Lloyd (1980) separated 55 of the North American firefly species into two general groups (early-active vs. late-active) in terms of when they start flashing. The onset times of each firefly species flashing activity were determined by direct field observation. After I plotted my data for both P.pyralis (an early-active species) and P.pennsylvanica (a late-active species) onto the same chart, both species showed peak activity at about the same times

(10-15min from end of civil twilight). Such results were not expected since my direct

- 5 - field observation seemed to confirm that P.pyralis started flashing before

P.pennsylvanica. In Chapter 5 I tried to explain the difference between direct field observation and the photographic record.

1.3. The Common Theme of Promoting Citizen-based Conservation Programs Using

Fireflies as the Thread

Chapter 2 presents the results from a survey study conducted in an agricultural community in Wayne County, OH, based on Parker, Moore, & Weaver’s (2007) work.

Parker et al. found a correlation between traditionalism (represented by ethnicity) and land tenure and conservation behavior, but did not distinguish other factors that may work as potential indicators of people’s adoption of conservation practices. To further explore indicators of people’s likelihood to perform pro-environmental behaviors, I proposed a model utilizing people’s attachments to various factors to predict their tendency to perform pro-environment behaviors. The results from the survey supported my hypothesis that a positive correlation exists between people’s attachment to the natural environment and their tendencies to perform certain types of pro-environmental behaviors. By pointing out that people’s attachments to the environment may work as indicators of their future adoption of conservation practices, this study may help conservation practitioners to better design their programs.

One particular item in my 2009 survey questionnaire asked people to associate different organisms (including the firefly) with the quality of the environment. The firefly was ranked 4th highest in a list of 20 organisms, which shows that the general public has

- 6 - noteworthy interest in fireflies and their relationships with the environment. A database search using the same list of organisms as keywords yielded another ranking showing that, compared to the general public, the scientific community has much less interest in fireflies, as evidenced by the low number of publications on firefly ecology compared to other species. This contrast demonstrates that a need for more studies focusing on fireflies, especially on their relationships with the environment, exists.

Chapter 3 describes the new timed sequential digital photographic method that I developed to monitor firefly flashing activity in the field. Researchers have used filming technology and digital videography to study the flashing patterns and light communication of fireflies in the past (Buck, 1968; 1978; 1988; Copeland, 1994;

Copeland, Moiseff, & Faust, 2008). Photographers have taken photos of firefly flashes, too (http://digitalphoto.cocolog-nifty.com/digitalphoto/cat4164851/index.html).

However, I only found one researcher in the past who had utilized photography to study firefly populations (Kirton, Nada, Khoo, & Phon, 2011). Before developing this new method, I tried a few traditional methods to study the firefly population. Some methods such as hand sorting and floating were labor intensive and failed to yield usable data; others, like mark and recapture, may be considered by some citizen science groups to be destructive to the firefly population. I got the idea of using digital photography to record firefly flashing activity from Copeland et al. (2008)’s research using digital videography to record firefly flashes in both wooded areas and the laboratory. He analyzed the data by examining each individual frame of a short video, a very time consuming endeavor. I

- 7 - went one step further by collecting a few seconds’ data on one photo with the help of a long-time exposure function on advanced digital cameras. This method proved to be reliable and sensitive to changes in the firefly flashing activities. In addition, the photo records also captured the difference in flashing patterns in two different firefly species.

This photographic method, developed to monitor firefly flashing activity without disturbing the fireflies, thus provides a nearly perfect example of non-destructive conservation research methodology. This method is specifically designed to utilize the firefly’s bioluminescence characteristic. However, the goal of designing research methods that entail little or no disturbance can be applied to all conservation programs.

Fireflies are not the only organisms that can light up in the dark.

“Bioluminescence” as a phenotypic characteristic is found in many organisms including bacteria (Harvey, 1939), algae (Johnson, 1985), fungi (Wassink, 1978; Airth, Foerster, &

Behrens, 1966), crustaceans (Cormier, Crane, & Nakano, 1967; Johnson & Shimomura,

1978; Tsuji, 1978), cephalopods (Robinson & Young, 1981; Shimomura, 1980; Inoue,

Kakoi,& Goto, 1976), insects (firefly), and even fish (Hansen & Herring, 1977; Herring

& Morin, 1978; Shimomura, 1980; Cormier, 1967; Inoue, Okade, Kakoi, & Goto, 1977;

Tsuji, Haneda, Lynch, & Sugiyama, 1971; Tsuji, Barnes, & Case, 1972). At least 30 different bioluminescence systems have evolved independently with distinguishably different functions and biochemical reactions (Hastings, 1983). This digital photographic method can be directly applied to studies focusing on any bioluminescence systems.

- 8 - In Chapter 4, I present data from my investigation of different landscape types’ associations with firefly flashing activities. Moore (personal communication) had observed an uneven distribution of firefly populations over agriculture landscapes. My study was designed to test whether such observations were valid and if fireflies have the potential to be used as an indicator of different farming practices (organic farming vs. conventional farming). My review of research literature about fireflies failed to yield conclusive results on the relationship between fireflies and agricultural landscapes. Thus, this study may fill a gap in the fields of both conservation biology of fireflies and organic farming in landscape ecology.

I used the new timed sequential digital photographic method described in Chapter

3 to monitor firefly populations in the field by recording their flashing activities. Flashing activity results were grouped according to different climatic factors and landscape types and compared to each other. Among other findings, the analysis revealed different patterns among organic farming and conventional farming practices in terms of firefly flashing activity. Although inconclusive about whether the difference was caused by organic or conventional agriculture itself or some component of these as production types, a difference was observed on these landscape types. This research provides an example of human activity’s associations with the native species’ behaviors and may serve as evidence to support conservation practices such as organic farming over conventional farming. Fireflies were chosen for this study for two main reasons: first, as shown in the survey, local community members associated fireflies with good

- 9 - environments; second, the flashing activities of fireflies makes possible monitoring them without disturbing their activities in their natural habitats.

In Chapter 5 I present a finding that contradicts a common assumption in firefly studies. The results of the new timed sequential digital photographic method collected with two different firefly species showed that their flashing activities peaked at the same time, while traditionally they were categorized as early-active and late- active species.

This study serves as an example of a simple yet interesting experiment that can be integrated into a citizen science-based conservation program that focuses on educating citizens about general knowledge about the environment and biology.

1.3.1. Citizen science as means to promote conservation

The main theme in this dissertation is citizen science. Citizen science basically is the idea of relying on members of the public who do not necessarily have specific scientific training to help collect and analyze data (Bonney & LaBranche, 2004; Bonnet et al., 2009; Ballard et al., 2005; Brossard et al., 2005; McCaffrey, 2005; Oberhauser,

2008; Silvertown, 2009). The original purpose of such an approach was to help scientific researchers since most citizen science programs were volunteer-based and could provide many observations at little cost (Cohn, 2008). This is still the prevalent purpose today. In addition, scientists have found out another by-product of citizen science, namely informal science education (Bonney et al., 2009). Most volunteers involved in citizen science projects are not necessarily doing it to learn something particular about the project, however, as they participate in the program and get in touch with the different

- 10 - components of the research, most of them will pick up some new information as part of the process. Because of the hands-on experience and person to person interaction, the new knowledge they obtain tends to be well understood and remembered (Trumbull,

Bonney, Bascom, & Cabral, 2000; Brossard et al., 2005).

Citizen science and conservation

Previously, some of the famous citizen science projects like the Christmas Bird

Count or Citizen’s QHEI by the Ohio EPA, required some kind of formal training so the data collected by the volunteers would meet a certain quality standard. This procedure of pretraining, while still necessary in most cases, has become confounded as the development of internet and personal computers has put previously sophisticated technology used solely by scientists in the hands of the general public. Some examples of such important technological breakthroughs include GPS, digital cameras, cell phones, and other mobile devices. Because of the user friendly interfaces, quality data such as latitude and longitude can be recorded with just a single click, stimulating a wave of

Volunteered Geographic Information (VGI) (Goodchild, 2007). Examples of volunteer- based projects include Google Earth, Flickr, and Wikipedia. Although the accuracy of the user created contents may vary considerably, certain basic information is of a fairly high quality. In many cases, humans work as individual sensors for the project with the aid of various types of mobile equipment. Because of the large number of people available, the potential of a network composed of human sensors is very promising. Especially for population centers like cities and municipal districts, where geographic features are being

- 11 - modified constantly by humans, a network of human sensors composed of local residents is the most convenient and timely way to monitor the environment. If the network of human sensors is sufficiently large, keeping the data fairly accurate, even with the potentially unstable influence caused by their anonymous and voluntary nature, is possible. For example, the potential problem of missing data caused by random participants dropping off can be minimized when multiple persons are inputting many replicating data; the potential mistakes caused by inaccurate data can be corrected by constant updates contributed by other participants.

A concept similar to citizen scientist-based research is participatory action research, which is usually at a smaller scale than the citizen science projects and does not limit the volunteers to the data collecting step. Instead volunteers get involved in all the steps of the whole project and are very interested in the answers to the research questions.

Viewing the participatory action research as the next step of citizen science is appropriate since it requires more contribution from the volunteers (Cooper et al., 2007). Likewise, one could view citizen science as a simple version of the participatory approach.

Citizen science and participatory action research also have great potential for helping resolve social conflicts by including all or almost all stakeholders in the program and offering the flexibility of accommodating to the various needs of each stakeholder

(Oberhauser, 2008; Silvertown, 2009). Stakeholders can participate in the program from the beginning stage of asking the research questions to the ending phase of proposing possible solutions. A citizen science approach is especially suitable for solving

- 12 - environmental problems since such problems often involve many stakeholders with potentially different social economic statuses and with different interests (Cooper et al.,

2007). Because in citizen science, stakeholders participate in the program rather than merely passively accepting advice from the scientists, stakeholders understand the principles and final outcomes more easily, which facilitates their engagement in solutions

(Brossard et al., 2005; Bonney et al., 2009). When local people have the power to make modifications to the final solutions, they will also be more willing to negotiate the terms of the research and even to make modifications (Conrad, 2011).

Combined with Traditional Ecological Knowledge (TEK), citizen science and participatory research can help both the researchers and the local residents to understand complex environmental problems and find potential solutions (Susanne, 2010). TEK ideas in the more formalized sense (because native people have had them as part of their culture) emerged out of anthropology such as in the work of Darrell Posey (1981) and became formalized through the work of the International Conservation Union (Johannes,

1989, Williams & Baines, 1993). It is defined as “a cumulative body of knowledge, practice, and belief, evolving by adaptive processes and handed down through generations by cultural transmission, about the relationship of living beings (including humans) with one another and with their environment” (Berkes, Colding, & Folke, 2000).

TEK is especially useful in terms of providing historical data about local species where scientific baseline records are lacking (Brooke, 1993; Inglis, 1993; Stevenson, 1996;

Huntington, 2000; Berkes et al., 2000; Pierotti & Wildcat, 2000). Some researchers have

- 13 - challenged the validity of TEK due to the way it was acquired (Becker & Ghimire, 2003;

McGregor, 2004), however, there is growing opinion in the scientific community to accept TEK as complementary to scientific knowledge (Colorado & Collins, 1987;

Corsiglia & Snively, 1995; Salmon, 1996; Richards, 1997; UNEP, 1998; Berkes et al.,

2000).

Since TEK are mainly maintained in oral format (Huntington, 2000), scientists interested in this knowledge primarily rely on questionnaires, workshops, and field work to collect the information from the local residents. This basically is what a citizen science project would be conducted. The main difference between TEK and science is:

TEK observations were made by the local residents who depend on the natural resources and the observations tend to be qualitative, local-based, over a long period of time; while scientific observations traditionally were made by outside professional scientists and the observations tend to be quantitative, cover a large area, and short-term (Kimmerer, 2002).

Thus citizen science can be viewed as a bridge that connects TEK and Scientific

Ecological Knowledge (SEK).

Environmental problems, after all, are human problems. One should not forget that conservation science is naturally often a crisis discipline, which means most often the goal of this discipline is to solve different environment problems retrospectively rather than prospectively. A citizen science approach helps scientific research on a larger scale, recruiting the public in informal environmental education and influencing participants’ attitudes and behaviors. As the participants get more involved with citizen science

- 14 - projects, by either interacting directly with the researchers or going through the required training, they will get more chances to learn about the principles of science and learn to adopt scientific methods in their daily lives. A more scientifically literate populace can understand various challenges better, thus make more rational decisions to support appropriate research to solve problems faced by humanity (Wieman, 2007). With the help of such powerful tools, conservation scientists can tackle more difficult problems with more options (Bonney & LaBranche, 2004; Bhattacharjee, 2005; Sullivan et al.,

2009; Weaver, Moore, & Parker, 2011).

Citizen science and characteristics of science

People use science to find answers to questions we have regarding the world we live in. Science’s characteristics help ensure the results of the observations, measurements, and theories to be accurate. The fundamental basis for scientific research is observable evidence, logical reasoning, and specific theories. To be qualified as science, a claim need to be based on a specific hypothesis and this hypothesis must be falsifiable and replicable. Scientists as individual humans can make mistakes and have value biases. The accumulation of human knowledge is dependent on the objectivity of science to maintain a methodology which leads to the advancement of knowledge

(http://evolution.berkeley.edu/evolibrary/home.php).

Although citizen science as a specific term is relatively new in the scientific community, its concept actually preceded the modern concept of professional scientists.

Until the late 19th century, most scientific research was conducted by people who did not

- 15 - get paid for their research but rather used their day job to support their lives (Silvertown,

2009). As a result, only those who possessed enough wealth and knowledge can make significant achievements, such as Benjamin Franklin (1706-1790) and Charles Darwin

(1809-1888). Modern citizen scientists are comparable to the “scientists” from the early days in terms of the equipment they have access to and the knowledge they acquire. It is no wonder that citizen scientists are now actively involved in all types of scientific research including climate change, invasive species, conservation biology, ecological restoration, water quality monitoring, population ecology and monitoring (Silvertown,

2009).

Many professional scientists are suspicious of the results yielded by citizen scientists since there is an obvious tension between the passion of the practitioners of citizen science and the "objectivity" of science. Others are also concerned that enthusiastic citizens may utilize their scientific knowledge inappropriately which may lead to disturbance and even destruction of sensitive local species (Iguchi, 2009). Those concerns may be valid, but they are not reasons to reject citizen science as a whole.

Instead, we argue most disadvantages of citizen science projects can be overcome by careful design and standardization (Silvertown, 2009).

Besides the apparent benefit of public education (Trumbull et al., 2000; Brossard et al., 2005; Bonney et al., 2009), the main purpose of citizen science remains as a way to collect data for scientific research (Bonney & LaBranche, 2004; Bonney et al., 2009;

Ballard et al., 2005; Brossard et al., 2005; McCaffrey, 2005; Oberhauser, 2008;

- 16 - Silvertown, 2009). Thus it falls under the category of scientific method and it needs to fulfill the requirements of a scientific method. To decide whether citizen science is a good science method, we first need to consider what scientific method is and how to evaluate it. According to Offutt

(http://www.cs.gmu.edu/~offutt/classes/phd/ScientificMethod.pdf), to qualify as science, an idea must be tested using a specific procedure that is open to the inspection of the public. This process must be based solely on objectively observed evidence. I listed the major components of the scientific method, its system of measurement and how citizen science does on these items in the following Table 1.

Citizen science is particularly useful in answering questions which cover large geographic regions and/or last for long period of time. One such example is the study of phenology, which has benefited greatly from the participation of the lay public (Mayer,

2010). One of the reasons for the phenologists’ easy acceptance of citizen science is the nature of the data required by this type of research: large amount of simple observations.

A normal person with minor training can produce quality data through space and time.

Citizen science is suited for studies that monitor common species over time and space. The number one rule for ensure the quality of the data collected by citizen science project is to keep the requirement on the participants as simple as possible. However, if the main purpose of the project is to educate the participants, complex design provides better teaching opportunities through the frequent interactions between the educator and the participants (Trumbull et al., 2000).

- 17 -

Table 1. Citizen science as a scientific method.

Component of System of How citizen science corresponds scientific method measurement Observation Clear, precise, Most participants are amateur observers with basic and daily skills, who are suitable for simple and straight measurable forward tasks. The amount of training and supporting materials will increase significantly if the participants are asked to produce data that requires high skill levels and knowledge. However, local populations will excel in nominal categories of classification (ex. Fireflies that have a “long flash with a J-curve” versus those that have a “short whitish flash”) which is sometimes called qualitative research but is actually on a continuum with quantitative measures which also have biases (such as microwave and electromagnetic waves biased to a certain type of light) and are constantly being refined. Hypothesis Testable and Usually formed by professional scientists who chose falsifiable to use citizen science to collect large amount of data. Thus the task of asking the right question, A.K.A. forming a testable and falsifiable hypothesis falls on the shoulder of the scientists. Experimentation Reliable and The participants need to be trained so they can make repeatable standardized observations. The results are more reliable if they do not need to make subjective judgment calls. Conclusion Appropriate Once collected and reported back from the statistics participants, the data will be analyzed by professional statisticians to eliminate anomalies. The large size of most data sets created by citizen science projects have good signal-to-noise ratio, thus provide strong patterns that are easy to interpret, Thus this process will be the same as other scientific method.

- 18 - Richard Moore raised the issue that citizen scientists may cause potential disturbances to the ecosystem without realizing the consequences of their activities. A case worth mentioning is the problems with the Genji/Heike Fireflies of Japan where they mastered how to reproduce them and how to change the streambeds to foster their growth. Relatively speaking the niches of these species is more general. The citizen scientists ended up introducing them into a very narrow ecological mountain niche where they out competed a local variety. Such unfortunate consequence is the result of misunderstanding among the participants about the relationship between different firefly species. To prevent similar ecological disaster from happening, it is necessary to require the organizers of citizen science projects to take on the role of educators and effectively communicate with the participants regarding the potential consequences of their behavior.

In summary, to ensure a citizen science project qualifies as a scientific method, experts from multiple disciplines are required throughout the whole process of designing, conducting, monitoring, and evaluating. One needs: a research scientist to ensure the project’s scientific integrity by developing method to collect quality data, interpreting the data and publish the result; an educator to ensure the effectiveness of communication with the participants by clearly explaining the project, testing the protocol, collecting feedbacks, and developing comprehensive materials; a statistician to analyze the data; and an evaluator to ensure measurable objectives and assess the project based on these objectives. Because the data yielded using citizen science are usually coarse and large

- 19 - scale, it is more suitable for computing indices of relative abundance than estimating absolute abundance.

Many citizen science projects have been criticized for their non-random site selection due to the aggregated volunteers living near population centers like cities

(Conrad, 2011). This problem is not a serious one for studies conducted in the cities or communities where the volunteers live. Also, at a larger geographic scale, the observations from different locations can still be compared with valid assumptions about the presence of systematic errors or sampling biases. Since any method or strategy will have its own limitations, the reason to point out the weaknesses of such local approaches is not to dismiss their use but rather to make sure we choose the right options for particular circumstances. Finding a universal solution for all kinds of situations is impossible; we have to deal with the environment issues with the resources available to us (McCaffrey, 2005).

Other researchers (Galloway, Tudor, & West, 2006) have questioned the reliability of the data collected by volunteers. Depending on the type of data being collected and the skill level of the volunteers, reliabilities may vary greatly. Basically the unreliability of data increases when the data collection process requires the judgment calls by the volunteer (in other words, subjective measurements). For example, volunteers generate similar counts of oaks as the professionals do, while reporting different results for the shapes of the tree crowns (Galloway et al., 2006).

- 20 - Social science has had a better relationship with the public in the past than the natural sciences have had. However, the traditional ways social scientists interact with the public are usually through different kinds of surveys, interviews, and focus groups. Under such circumstances members of the public are treated more like sources of information than cooperating participants. Such procedures used to be justified by stating that the public did not have sufficient knowledge to understand and further participate in a study

(Cohn, 2008). However, such statements may not necessarily hold true for all citizens on all scientific studies. Citizen science thus has emerged as a result of scientists using members of the public as sources of information and as a way for the scientific community to educate interested citizens (Brossard et al., 2005; Bonney et al., 2009).

A gap exists between scientific research and policy making. While scientific researchers acknowledge that uncertainty is unavoidable in scientific findings, policy makers require certainty (Sabatier, 1986; Denis, Lehoux, Hivon, & Champagne, 2003;

Lubell, 2004; Schaefer & Bielak, 2006). The scientific community is discovery-oriented and flexible in terms of dealing with individual cases. In contrast, policy-making is mission- oriented and requires relative rigidity in order to be enacted. The scientific community’s commitment to active communication, education, and cooperation with society and policy makers is essential. Only after the public and policy makers truly understand the important role played by uncertainty in scientific studies, can they start to truly appreciate the results produced by scientific studies and be willing to work with scientists to make better policies according to the results (Bradshaw, 2000).

- 21 - 1.3.2. Research on fireflies as an ideal target for citizen science

For the research in this dissertation, fireflies were selected for a number of reasons. First, fireflies include species that, in North America, have a high level of cultural attachment for people, although not as high as in some other countries like Japan.

Second, fireflies have a high degree of landscape locality. They do not migrate much, so they may be nearly ideal for testing their behavior in relationship to the specific landscape types. Third, a gap exists between the cultural attachment and scientific research on firefly ecology in the US. Much of the research on fireflies has been based on luminescence to the neglect of firefly behavioral and landscape ecology.

Cultural attachment to fireflies

Citizen science works well if there is a high level of cultural attachment to a species or focus on particular environmental problems, both of which seem to be preconditions for effective citizen science. How can one determine that a need exists for more research on a particular subject? In the field of conservation programs, a major factor has to do with the interest of the public, whose support is crucial for the success of any conservation program. Much research has been focused on the species that draw most of the public attention as one can see by looking at Figures 1, 2, and 3.

In the summer of 2009 I conducted a survey that was conducted in the North Fork

Subwatershed in Wayne County, OH. The details about the survey study are summarized in chapter 2. One question in the survey measured people’s perceptions of different

- 22 -

Figure 1. Question asking people's perceived correlation between different organisms and environment/water quality in the 2009 survey.

organisms’ sensitivity to the quality of the environment. The original question is shown in Figure 1. Out of the 192 households being sampled, 110 of them filled out the survey and 76 of them answered this particular question. Their responses are summarized in

Figure 2.

As one can see from Figure 2, organisms like earthworm and bee were rated higher than slug and potato beetle. One might conclude that people tend to associate beneficial organisms with a good environment and pests with a bad environment.

Continuing with this thought, one would expect more research being done on the organisms toward the ends of the spectrum, a.k.a. the first and last few. However, after I

- 23 -

Figure 2. Perceived relationships between common organisms and environment quality. Organisms are organized according to their average score (with standard deviation) from a survey conducted in North Fork Subwatershed in Wayne County, OH. Firefly ranked fourth highest.

performed a literature search in the Environment Complete Database

(http://search.ebscohost.com) using the organisms as the keywords, the results were not particularly similar to those shown in Figure 2.

In Figure 3, the organisms are grouped into three tiers: the first tier containing only trout has the most publications associated with it. Compared to all the other organisms, trout is the only vertebrate in the list, which might explain the huge difference between it and all the other organisms. The second tier includes aphid, bee, mosquito, butterfly, snail, and earthworm. All of the second tier animals except snail were located

- 24 -

Figure 3. No. of publications using each organism as the keyword. Organisms are organized according to the number of peer reviewed papers from a search conducted using the Environment Complete Database on The Ohio State University’s website. Firefly ranked second lowest.

either at the very left or very right part of Figure 2. This finding agrees with an intuitive feeling that scientific research would reflect people’s interest as more have been done on the species that are associated with extremely good or bad environment qualities. The interesting part of the comparison of Figures 2 and 3, however, comes from the few organisms that moved from both ends in the first figure to the lower end of the second figure. Such a position change represents a mismatch of the public interest and academic research. Compared to other mismatched organisms like slug and potato beetle, the

- 25 - firefly stands out as the one species that moved the longest distance between these two figures. By comparing these two figures, one may reasonably argue that the level of study on the firefly’s ecological role has not reflected the public’s interest in them in the past, perhaps indicating a need for research and conservation programs focusing on fireflies.

In order to measure how much a person values the presence of fireflies as well as how many people in the population value the presence of fireflies, I designed the above matrix question aiming to systematically evaluate such opinions by comparing fireflies among other common small animals people may encounter in their daily lives. Although very preliminary, the survey results from our study conducted in the North Fork

Subwatershed of Wayne County, OH, showed that people ranked fireflies right next to earthworms, butterflies, and bees. Surprisingly, farmer participants rated fireflies ahead of dragonflies and lady bugs.

A wide degree of variation in cultural appreciation of fireflies is present. On one extreme, firefly catching was a common pastime in China and Japan. In fact, it was so popular, that the Japanese formed official firefly festivals from as early as the 1960s

(http://www.fussakanko.jp/pa0206.html) and people have taken them very seriously.

Such activities also spread to Korea at the 1990s (http://english.firefly.or.kr/main.html) and Taiwan at 2008 (http://rural.swcb.gov.tw/news/news-1.asp?nid=381). People living in these areas usually associated fireflies with uncontaminated soil and water (Suzuki,

2002). Every year, tourists bring in millions of dollars to the local community as a result

- 26 - of firefly festivals. In fact, nearly all Japanese equate fireflies with environmental quality for two reasons. First, the knowledge was passed between generations in the form of traditional poems such as Hotaru Koi “Hotaru, hotaru, kochi no mizu wa oishi yo (firefly, firefly, the water over here tastes better).” This poem relates to the rice paddy ecology of good cool water needed for rice production and the fact that fireflies were part of the rice paddy ecology. Second, most fireflies in Japan are aquatic and prey on snails during their aquatic larval stage (personal communication with Richard Moore). Pesticides have killed most of the insects in rice paddies and streams since the 1960’s, so people have lamented the resulting loss of fireflies and have tried to restore their populations (Yajima,

2007).

Throughout history, fireflies in China have been an important cultural focus, which appears to have been a precondition for effective citizen science efforts there.

People in ancient China collected fireflies to use them as a substitute for candles during the night. Fireflies’ mystical flashing invoked many rituals, myths, and fairytales. The earliest written record of fireflies was found in one of China’s Book of Odes (Shi Jing), which dated back to 1500-1000 B. C. (Yemang, Yang, & Yang, 2001). Another Chinese record of utilizing the fireflies as a light source is dated to around A.D. 300 in the Tsin

Dynasty. A poor child named Che Yin captured fireflies in a bag and used the light to illuminate the book so he could continue studying during the night Because of his diligence, he became a very knowledgeable scholar and a government official later (Fang,

1974).

- 27 - In early India’s (200 B.C.) holy writings, the firefly’s light was always used as a symbol of ephemeral pleasure and insignificance, probably because of its small scope and lack of heat. Fireflies also hold cultural significance in Japan since people there believe that fireflies are dead people’s spirits. People of all ages participate in Obon Festival, which is specifically designated for firefly viewing since they symbolize the spirits of the dead. As compared to how fireflies are regarded in parts of Asia, the Western world has neither the tradition of celebrating fireflies nor do westerners associate fireflies with water quality, although Gaius Plinius Secundus, (better known as Pliny the Elder) (A.D.

23-79), noticed the relationship between fireflies and agriculture in his Book XVIII,

Chap. 26 (Harvey, 1957).

In contrast, firefly research in the United States has centered around the light- producing chemical compounds. The OSU Extension Fact sheet on fireflies focuses on how to sell firefly luciferin and luciferase, two rare chemicals used in research on cancer, multiple sclerosis, cystic fibrosis and heart disease (http://ohioline.osu.edu/hyg- fact/2000/2125.html). The "Firefly Project” to buy fireflies is led by the Sigma-Aldrich

Corporation, which sells a number of products derived from fireflies

(http://www.sigmaaldrich.com/catalog/Lookup.do?N5=All&N3=mode+matchpartialmax

&N4=firefly&D7=0&D10=firefly&N1=S_ID&ST=RS&N25=0&F=PR). Subsequently, the genes for luciferase and luciferin have been cloned and used as a marker for cell metabolism monitoring.

- 28 - Although researchers have established a new citizen science project called

“Firefly Watch” at the Science Museum in Boston, Tufts University and Fitchburg State

College (https://www.mos.org/fireflywatch/) to monitor firefly behavior, this type of citizen science is mostly lacking in the US. With the exception of the work by Lloyd

(http://entnemdept.ufl.edu/lloyd/firefly/), little research on firefly behavioral ecology in the US and Europe has been done.

Fireflies and landscape ecology

Landscape ecology focuses on the relationships between spatial patterns and ecological processes. Accordingly, landscapes are spatially heterogeneous geographic areas characterized by diverse interacting patches or ecosystems. According to Lloyd

(2003), about 200 species of fireflies exist in North America as shown in Figure 4 In

Ohio, the most recent list of fireflies stated that there are 8 genera and 24 species (Marvin

Jr., 1965). Marvin, Jr.’s, work is an update of an older list by Harzard (1929), which included 7 genera and 11 species of fireflies. Fireflies are usually found in moist and vegetated areas. People can find fireflies near creek washouts, hurricane blow downs, under power lines and over old fields; some special species can only be seen in isolated pockets in undisturbed areas (Lloyd, 2003).

About 2000 species in 100 genera of fireflies all over the world have been described in the literature, as shown in Figure 5. All fireflies belong to the Family

Lampyridae (Lloyd, 1978). South America and Asia are regions with the greatest

- 29 -

Figure 4. The distribution of firefly species across the United States that produce “flashed signals.” The numbers in the figure legend indicate number of flashing species known to occur in each state (Thancharoen, 2008).

Figure 5. Firefly distribution over the world (shown in light color)

(http://animals.nationalgeographic.com/animals/printable/firefly.html).

- 30 - abundance of species (Lawrence & Newton, 1982). Because of the lack of systematic updates and revisions, very likely many more unknown species exist in the jungles of the

Amazon and Southeast Asia (Lloyd, 1978; Viviani, 2001).

The life histories of several common firefly genera such as Photuris and Photinus have been studied and described before (Carlson, 1985; Williams, 1917; Hess, 1920;

Keiper & Solomon, 1972; McLean, Buck, & Hanson, 1972; Bushman, 1984). Some species’ life histories are much more complex than others (see Figure 6). Fireflies, especially in the larval stage, have been known as predators for a long time (Winkler,

1964; Keiper & Solomon, 1972). The larvae mainly prey on soft-bodied soil organisms like cutworms and snails. Some species of aquatic fireflies require a particular type of snail as their prey (Yajima, 2007).

However, in the case of Photuris pennsylvanica and Photinus pyralis, the larvae are not nearly so picky. They have a broad spectrum of prey: researchers have used cut beef and liver as well as dog food to feed them in the lab (McLean et al., 1972).

Apparently the only condition they require is to be able to use their mandibles to pierce the a soft-bodied creature and inject their poison to paralyze it. Then they will use their digestive secretions to liquefy the prey and drink the liquid. Sometimes several firefly larvae will work as a group to attack an earthworm too big for a single larva (McLean et al., 1972).

Since Photuris pennsylvanica and Photinus pyralis are such broad spectrum predators, one may reasonably assume a positive relationship between firefly populations

- 31 - and their prey, after controlling the influence of other factors like the temperature, moisture, and vegetation types. Thus, by monitoring the fluctuation of a firefly population, one may get a general idea about the soil ecosystem. Such an idea of associating fireflies with the quality of an ecosystem has been circulating among both academics and the public; however, no formal study has been done specifically designed to test such a hypothesis. As a preliminary, Chapter 4 in this dissertation proposes such a study.

Challenges exist in the study of the life cycle of North American fireflies. Some

Photuris species will perform their mating rituals on the top of trees, thus limiting the opportunity for direct observation (Lloyd, 1969). Since the larval stages of fireflies are diverse, studying firefly larvae is difficult. The larvae of P. pyralis rarely get out of soil

(McLean et al., 1972), thus finding them is quite difficult. The larvae of some species such as Cratomorphini fireflies are arboreal which means they live on the trees (Viviani,

2001). Aquatic fireflies go through the larval stage in water, although there are no reports of aquatic fireflies in North America.

Another problem researchers may encounter is the relatively short season during which the adults emerge and are active. Some researchers have tried to raise firefly larvae in the laboratory so they can make observations and experiments on both larvae and adults all year round (McLean et al., 1972; http://www.byteland.org/firefly/).

However, successful protocols of raising fireflies in the lab have not been published.

- 32 - Research on firefly landscape and behavioral ecology

A review of the firefly ecology literature reveals a lack of research on landscape and behavioral ecology. Scientists in North America have tended to emphasize luminescence at least partially due to the commercialization of luciferase as a biochemical reagent used by big pharmaceutical companies. A Google Scholar search produced 82 articles using the terms “firefly” and “luminescence” while a search for

“firefly” and “behavior” yielded only 32 articles, lending credence to the apparent topically lop-sided scientific approach to fireflies favoring luminescence.

Due to the lack of scientific studies on firefly ecology and behavior, few articles have been written on the spatial distribution or diet of fireflies and their eggs and larvae.

In fact, disagreements on even the very basic ecology of the common fireflies still exist; for example, is the life cycle one year, two years, or both (McLean et al., 1972; Keiper &

Solomon, 1972)?

Tracing back to Lloyd’s (2003) work on identifying the 200-300 species in North

America, most of the work done about fireflies focused on their anatomical features instead of their behaviors. Studies on their flashing patterns were mostly conducted in the lab (Forrest & Eubanks, 1995; Lloyd, 1981; 1984a; 1984c; 1990a; Moiseff, 2000). In terms of fireflies' flashing behaviors, such phenomena have been associated with many different functions including mating (McDermott, 1910; 1911; 1917), illumination

(Lloyd, 1968), aggressive mimicry (Lloyd, 1965; Wickler, 1968), and warning (Branham,

2003).

- 33 -

Figure 6. Life cycle of the Photuris firefly in the Maryland region (McLean et al., 1972). Note: Figure used by permission from The American Biology Teacher

- 34 - Temperature and background illumination levels were found to influence the initiation and pattern of the firefly flashes (Buck, 1937a; Dreisig, 1975; Edmunds, 1963).

At least three Photuris species in Florida are found to require low illumination to initiate flash at low temperature. The relationship between flash intervals and temperature was found to be more complex than people would assume: Edmunds (1963) and Dreisig

(1975) found that the timing of the flashing patterns is affected by the temperature and time of the day. Edmunds (1963) argued that the relationship between flash intervals and temperature was non-linear, in which the frequency distribution of the flash intervals was skewed toward the longer flash intervals as temperature increased (the mean of the measurements are larger than the median). He suggested using more sophisticated statistical analysis to deal with such kinds of skewed data. In addition, the distribution of firefly flash intervals over different temperatures, at least in P. pyralis is not a simple normal distribution as Buck (1973b) proposed. Some Photuris species have been reported to have multiple flashing patterns, with the flying males switching from one pattern to another during the night (Lloyd, 1990; Forrest & Eubanks, 1995). Edmunds’ findings have posed a certain challenge for using flashing intervals to identify firefly species and to further count and monitor the population’s exact size. However, since the current study is only concerned with the trend of long term change of the firefly population, having a very accurate measurement of the exact number of firefly individuals is not necessary. As long as the record can show the increase and decrease of the firefly population, the photographic method I suggested can still be adopted. The effect of temperature certainly

- 35 - should be included in the study when comparing population data from year to year, but again, as long as the data I collected comes from across the whole firefly active season, minor changes from day to day will average out.

Certain firefly species will flash in unison (synchronously) (Buck, 1935). Such phenomena are more common in East Asia than here in North America (Lloyd, 1984a;

Copeland, 1994). People have proposed many kinds of mechanisms to explain synchronous flashing such as incidental or sex-related (Buck, 1935). However, a final conclusion is still lacking. The most recent hypothesis on the origin of the flash in fireflies proposed that the flash first evolved as a warning signal for unpalatability in the larvae, and then evolved to the role of sexual signaling (Branham, 2003). Different flashing patterns have been adopted by different species to enhance the chance of within species breeding. As time goes by, the flashing patterns evolved along carnivorous behavior between predacious fireflies (Photuris) and their prey (Photuris, Photinus, etc.)

(Lloyd, 1981).

This whole dissertation is tied together by a thread, the firefly. Fireflies are a good thread for this dissertation’s common theme of citizen science-based conservation programming. Conrad (2011) pointed out that most citizen science-based monitoring programs focused on either environmental quality like water and air or particular species like birds and plants. A close examination of the list of citizen science-based monitoring programs in Conrad’s paper that focus on species suggested that the selected species can be grouped into a few categories: 1) species with high economic value, such as fish

- 36 - (Sultana & Thompson, 2007) and lumber (Nagendra & Gokhale, 2008), 2) indicator species such as macro-invertebrates (Jones et al., 2006; Nerbonneet & Nelson, 2004), and

3) species with high aesthetic value such as songbirds (Evans et al., 2005) and butterfly

(Oberhauser & Solensky, 2004). Usually, a high score in one category is enough for a species to be qualified as a target for citizen science-based conservation programs.

Fireflies have the potential to score high in all three categories.

- 37 -

CHAPTER 2

THE INFLUENCE OF ENVIRONMENTAL ATTACHMENT ON PEOPLE’S

WILLINGNESS TO PERFORM PRO-ENVIRONMENTAL BEHAVIOR:

A CASE STUDY IN THE RURAL COMMUNITY OF NORTH FORK

SUBWATERSHED, WAYNE COUNTY, OH

2.1. Introduction

In this chapter, I examine the relationship between different forms of attachment and people’s willingness to perform pro-environmental behaviors. My hypothesis is that people’s “environmental attachment” will have a positive correlation with their pro- environmental behavior, while the other components of the traditional “place attachment” including “attachment to other people” and “attachment to safety” will not have significant correlation with pro-environmental behaviors.

I review a challenge faced by conservation organizations, namely the low success rate of encouraging people to participate in and adopt pro-environmental behaviors. I also present a brief review of research on the relationship between people’s attachment

(place attachment, sense of place, community attachment, etc.) and their engagement with pro-environmental behaviors, which has given mixed results (Hummon, 1992;

Giuliani & Feldman, 1993; McCool & Martin, 1994; Eisenhauer et al., 2001; Vaske &

- 38 - Kobrin, 2001; Vorkinn & Riese, 2001; Kyle et al., 2004; Brehm et al., 2004; 2006;

Devine-Wright & Howes, 2010; Scannell & Gifford, 2010; 2011). To further explore why people may engage in pro-environmental behavior, in this study I focus on the potential correlation between environment attachment and people’s tendency to perform pro-environmental behaviors. I introduce the past research that inspired this study, such as work on place attachment, sense of place, and community attachment. Since these concepts tended to focus on the emotional bonds among residents instead of the relationship between people and nature, I tried to clarify the different types of attachments and examine their correlations with pro-environmental behaviors individually.

2.1.1. The Challenge Faced by Conservation Programs

As people have started to realize that climate change is real and likely to have lasting impacts, more effort has been put toward various conservation programs (Gosling et al., 2011; Scannell & Gifford, 2011). Both government agencies and grassroots environmental organizations have worked hard to encourage people to participate in their particular programs. In order to reach out to the general public across the country, most traditional conservation programs fall into one of two categories, either incentive-based, such as paying farmers to adopt certain conservation practices (Cooper & Signorello,

2008), or knowledge-based, such as information sessions and workshops (Schaefer &

Bielak, 2006). Yet, such programs have long been criticized for their low efficiency of

- 39 - actually engaging people to adopt pro-environmental behaviors (Wu, 2004; Moon &

Cocklin, 2011).

As a response to the demand of environmental studies and conservation, many nonprofit organizations like Sierra Club, Green Peace, and the World Wildlife

Foundation have been founded to specifically tackle such problems. A variety of ways to approach environmental problems, such as funding related studies, establishing conservation programs, and lobbying for certain environmental policy campaigns, exist.

However, although conservation organizations have adopted many different strategies to form and conduct conservation programs, including organizing rallies and collecting petitions to put pressure on the legislatures, educating citizens about various environmental issues and potential solutions, negotiating and encouraging business community to adopt environmental friendly standards and technologies (Heberlein &

Prouty, 1975; Winett & Nietzel, 1975; Kohlenberg, Phillips, & Proctor, 1976; Hayes &

Cone, 1977; Geller, 1981; 1983; Palmer, Lloyd, & Lloyd, 1976; Darley, 1978; Darley &

Beninger, 1981; Winett, Neale, & Grier, 1979; Winett, Kaiser, & Haberkorn, 1977;

Schindeler, 1977; Sharpe & Fletcher, 1977; Oates, 1999; Mbaiwa, Stronza, & Kreuter,

2011), I have found few actual cases in which people have made actual behavioral changes due to the programs.

One particular factor past research has been focused on is people’s bonds to places. Different constructs such as community attachment, sense of place, and place attachment have been used to describe such bonding. Place attachment is associated with

- 40 - place protective intentions and behaviors (Nordenstam, 1994; Stedman, 2002; Clayton,

2003; Scannell & Gifford, 2010; Vaske & Kobrin, 2001). Some studies have shown contradicting results where place attachment either did or did not encourage protective behaviors or even caused damage to the place (Devine-Wright & Howes, 2010; Edelstein,

1988; Kyle et al., 2004). Brehm et al. (2004, 2006) suggested that one possible cause of such confusing results may be the many dimensions of place attachment itself. Scannell

& Gifford (2011) argued that regardless of the nature of behaviors induced by place attachment, very likely people with stronger attachment to place maybe more engaged in taking care of it.

In this study, however, I try a new approach to measure the association between various types of attachments and people’s behavior with special emphasis on their attachment to the natural environment. In addition to the incentive and knowledge-based approaches used by the traditional programs, in this study I propose that environmental attachment is correlated with people’s intention to perform pro-environmental behaviors

(Vaske & Kobrin, 2001).

This chapter presents a case study to examine how people's attachment to the natural environment is related to their intentions to perform pro-environmental behaviors.

This study also examines other attachment factors that may influence the performance of pro-environmental behavior. By distinguishing different types of pro-environmental behavior and examining different attachment factors' relationships to them, I am trying to establish a correlation between people's attitudes toward the environment and their

- 41 - intentions to perform pro-environmental behavior. I developed this new idea of environmental attachment by combining existing concepts of place attachment and community attachment.

2.1.2. Place Attachment

Place attachment and sense of place have been widely used in many different disciplines, including architecture, anthropology, cultural ecology, environmental psychology, geography, planning, and of course, sociology (Brandenburg & Carroll,

1995; Cross, 2001; Eisenhauer, Krannich, & Blahna, 2001; Relph, 1976; Tuan, 1974;

Williams, Patterson, Roggenbuck, & Watson, 1992). As a result, many different ways exist to assess the level of place attachment due to different foci from all different professions. Not surprisingly, at the early stages of development, the concept of place attachment was indeed tightly bonded to a specific location. People’s attachment to a place was thought to be due to the attractiveness of the natural settings of that particular location (Relph, 1976; Tuan, 1974). Sociologists later focused on interactions among people as a way to define a place and how they are attached to it (Cheng et al., 2003).

Some scholars have actually looked into the relationship between the scale of places and people’s attachments (Hidalgo & Hernandez, 2001). However, not until the 21st century did researchers start to examine how the characteristics of the particular natural environment and people’s attachment to it influence their behaviors (Stedman, 2003;

Brehm et al., 2004).

- 42 - Researchers have investigated the relationship between people and place and people’s attitudes toward their communities, their cultures, and their natural environments. Previous studies have shown that social attachment and attachment to the natural environment are, in fact, different concepts (Brehm et al., 2004; Stedman, 2006).

However, as Stedman (2003) noticed, physical places, as compared to the social constructions of place, were mostly overlooked. When included in different disciplines such as wildlife and recreation management, instead of being singled out, attachment to the natural environment was often integrated into an overall general concept of place attachment or place bonding (Hammitt, 2006). Although people’s behaviors, social interactions, and cultural influences are important in shaping bonds between people and their lands, such relationships usually happen within the natural environment.

2.1.3. Community Attachment

The concept of community attachment was developed in the 1970s by Kasarda &

Janowitz (1974). They modeled the relationship between residents’ attachments to their communities and included factors like the length of residence, age, and the roles one plays in the society. This model helped researchers understand the dynamic changes happening in a local community. For example, Crowe (2010) found even though people’s evaluations of a community are affected by the community’s network structures, their attachment to the community is only affected by their personal networks. This helps to explain the result of another study where single female parents living in a rural

- 43 - community had higher levels of satisfaction but less community attachment compared to their counterparts living in an urban community (Cook, 1988).

Since the early 20th century, many sociologists have studied community attachment as a research topic (Simmel, 1903; Park & Burgess, 1925; Wirth, 1938;

Kasarda & Janowitz, 1974; Buttel, Martinson, & Wilkening, 1979; Riger & Lavrakas,

1981; Fischer, 1982; Goudy, 1990). As the process of urbanization accelerated, people noticed what seemed to be a disintegration of the social structure of traditional local communities (Wilkinson, 1991) that had been studied by anthropologists in various ethnographies of the 1950s and 1960s as well as by sociologists in studies such as the one done in Middletown (Lynd & Lynd, 1929). Scholars had serious debates about the validity of the concept of community. Challenges to a simple concept of community have come from many areas such as the concept of “peri-urban” (Gilg, 1983; Allen,

2003), which does not neatly fit on the rural-urban continuum. The increasing interactions among people who belong to national or even international organizations such as big companies also present a challenge to the definition of community. Internet interest groups have no doubt further blurred the boundaries of the traditional community

(Inglehart & Welzel, 2005). However, interactions among people who live in the same place nonetheless continue to have major influence on residents’ attitudes and behaviors

(Hummon, 1992).

As a result of the changes in how scholars define community, the closely related concept of community attachment is also undergoing many changes as researchers try to

- 44 - figure out what factors will affect people’s connections with society (Kasarda &

Janowitz, 1974). Most of the past studies have focused on interpersonal relations (who people know in a community) as indicators of a people’s attachments to the community

(Goudy, 1990; Kasarda & Janowitz, 1974).

Sociologists working on community attachment issues have had a tendency to put emphasis on social connections while they overlooked the effect of the natural environment on people’s attachment to the local area. Tuan (1977) has confirmed that the length of residence has a major impact on one’s community attachment. However,

Smith & Krannich (2000) have shown that, in many rural communities across the United

States, both new residents and longtime residents feel connected to the local community regardless their differences in the social connections. Thus, in addition to using length of residence to predict association with a community, attachment to the natural environment is one possible explanation for community attachment among new residents. As a result of the lack of research about people’s attachments to their local natural environments, even less research has been conducted about the potential relationship between such attachments and people’s attitudes and behaviors associated with conservation practices and programs.

2.1.4. Attachment to the Environment

Close interactions or lack of interaction between people and the natural environment helps to reinforce (or weaken) the cognitive connections between people and land (Parker, 2006). The relationship between land and people who live on the land

- 45 - is subtle: people’s basic belief systems are constantly influenced by their daily interactions with the environment. For instance, one could propose that a farmer who works on a farm all the time might have a stronger tie to a natural environment than a person who works in an urban area (Kitani et al., 2005). Office workers tend to have a much weaker sense of stewardship towards the land compared to farmers, due to their lack of personal experience with farming activities (Grubbstrom, 2011). On the other hand, an urban resident may develop a strong sense of attachment to the city landscape, while a farmer may not feel connected to the city at all (Parker, 2006).

People’s attitudes toward the environment or rather toward some environmental problems have been studied extensively. Many social demographic factors have been examined in terms of correlation with environmental attitudes (Van & Dunlap, 1980;

Chen et al., 2011). Certain factors like age, education, and political ideology were found to be more relevant than other factors like income, gender, and occupation (Theodori &

Luloff, 2002). Traditional studies on factors that may influence people’s attitudes toward environmental issues have correlated social demographic information with a population’s pro-environment attitudes (Johns & Dunlap, 2001; Van Liere & Dunlap, 1980).

However, other researchers have challenged the usefulness of using social demographic factors as indicators of people’s attitudes toward environmental issues (Fransson &

Garling, 1999). Adding to the confusion about what leads to pro-environmental behaviors is the finding that a higher level of environmental concern does not necessarily lead to the actual performance in conservation behaviors (Bamberg, 2003; Stern &Dietz,

- 46 - 1994; Stern, Dietz, Kalof, & Guagnano, 1995). The connection between attitude and behavior is not direct but rather mediated by intention, which is also influenced by other factors such as social norms and perceived behavior controls (Ajzen, 1991).

The effect of the natural environment on people’s attachments to places or communities is especially valuable when large numbers of people move to different places from time to time for many different reasons such as schooling and job relocation.

For these new residents, attachment to the place may largely come from their feelings toward the natural environment instead of from their feelings about the people in the new place (McCool & Martin, 1994). Thus, one might expect that newcomers’ ideas about land management will be different from the attitudes of long-term residents in a community since long-timers may have extensive social bonds that may influence their decision making processes (Egan & Luloff, 2000). Needless to say, considering opinions of newcomers and long-term residents is crucial when trying to engage a whole community in a conservation program.

Instead of singling out environment attachment as an independent factor, a common practice researchers have adopted is to treat place attachment, community attachment, and sense of place with both physical and social perspectives (Mazumdar &

Mazumdar, 2004). As a result, the concepts of community attachment, place attachment, and sense of place sometimes have become interchangeable, even though there are real differences among them (Hidalgo & Hernandez, 2001). Studies have shown people’s attachment to the natural environment, not to the general place, will evoke their

- 47 - resistance to allowing development of the place (Vorkinn & Riese, 2001). Hidalgo &

Hernandez (2001) also found that people’s attachments to physical places have stronger effects at a small, local scale than at a large, regional scale.

2.1.5. Pro-environmental Behavior

The main goal of this research was to examine the correlation between people’s attachment to the natural environment and their tendencies to perform pro-environmental behaviors. However, pro-environmental behaviors include many different activities, and people may perform only some, but not all of them. For example, a person may want to do trash removal but may never have thought about constructing a buffer zone along a nearby stream.

I have defined pro-environmental behavior based on the concept of environmentally significant behavior. Environmentally significant behavior has two different, but related dimensions. The first is its impact on the natural environment and natural resources; another is behavior with the intention to change the environment

(Stern, 2000). While closely related to each other, these two definitions are not the same.

A behavior with significant impact on the environment may not necessarily be conducted intentionally. Likewise a behavior that one engages in to help the environment will not necessarily yield any impact on the environment. For this study on factors that potentially can change people's behaviors, we adopt the intent-oriented definition, defined from the actor’s standpoint as “behavior that is undertaken with the intention to change (normally, to benefit) the environment” (Stern, 2000, p. 408)

- 48 - Stern (2000) has listed four major categories of pro-environmental behaviors: environmental activism, which includes behaviors like participating in demonstrations; nonactivist behaviors in the public sphere, which include behaviors like supporting public policies and contributing to environmental organizations; private-sphere environmentalism, which includes purchasing behaviors and recycling; and other environmentally significant behaviors that do not fall in the above categories. Since each category of pro-environmental behavior maybe influenced by different factors

(participating in a demonstration about attachment to a park vs. buying organic food due to a concern about health), I decided to distinguish different kinds of pro-environmental behaviors in this study.

In my study, I included a variety of pro-environmental behaviors from picking up trash along the road to constructing buffer zone along the streams. After I collected the responses back, I used principle component analysis to aggregate all the behaviors into different categories and named them as different pro-environmental behavior factors accordingly. These new pro-environmental behavior factors were then correlated with the different types of attachments.

To measure the pro-environmental behaviors in the survey, I asked people if they had considered doing a certain behavior (an intention) or if they had already performed it

(an actual behavior). Instead of using people’s intentions as predictors of their actual behaviors, one can view the two seemingly different concepts of intention and the performance of actual behavior on a continuum of tendency to perform. On one end of

- 49 - the continuum is the mere thought about doing something, which can be treated as the original intention. In the middle of the continuum is the effort one may make to convert the intention into a real behavior, without yet developing the behavior as a habit. Such a transitional stage is an adapted version of the “trying” model (Bagozzi & Warshaw,

1990). The final stage of the continuum is performance of the actual behavior. This continuum is shown in Figure 7.

Figure 7. Continuum of tendency to perform created by combining people's intention and their actual behavior.

The transition from intention to the actual behavior happens mostly within a person’s own mind thus other people can do very little to make any change at that stage.

By using such an approach, I obtained a score for each particular pro-environmental behavior that can tell me the likelihood that a person will perform such a behavior.

- 50 - 2.1.6. Proposed Research

While many conservation programs have been designed by outsiders who do not necessarily has a deep understanding of the local environment and local community, the programs’ general foci have not been particularly successful at local levels. Etkin (2002) mentioned in his study that the conservation policy in Nigeria was based on Westerners’ impression about the so called “primitive farming system” and ignored the local population’s knowledge and dependence on the native species, thus making it difficult to implement conservation practices effectively. By adding the natural environmental attachment to the measurement of community attachment, or singling out the natural environmental attachment from the place attachment commonly used in the past, one may gain a better understanding about how exactly people’s attachments to the natural environment differ from their attachment to the intangible cultural and social values. By parsing out the influence of different attachment factors, one can learn how to utilize the different types of attachment to facilitate and promote various environment conservation programs the local communities would need.

In this chapter I propose a study in which I have added pro-environmental behavior to the social dimensions captured by the community attachment construct. I consider pro-environmental behavior as a separate construct needed to capture the relationship between humans and the natural environment. Since most pro- environmental behavior is performed in response to the status of the natural ecosystem,

- 51 - this addition may help us to better understand the relationship between environment attachment and people's intention to perform pro-environmental behaviors.

In this study, I try to create a new approach to change people’s behavior by emphasizing their attachment to the natural environment. Adding to the incentive and information used by the traditional programs, in this study I propose that environmental attachment has a correlation to people’s intentions to perform pro-environmental behaviors. As a result, programs designed to include environmental attachment potentially would see more behavioral changes among their participants.

This approach is in line with the science community’s attitude toward interdisciplinary projects. In 2007, the National Science Foundation (NSF) prioritized research on "coupled nature and human systems," NSF, 2007. Paragraph 3 emphasized that study of these two areas results in deeper understanding of the close relationship between human society and the natural world that surround us. The NSF suggested that much can be done in terms of research if full cooperation is present between scientists from both social science and natural science to take an interdisciplinary approach in forming conservation programs.

This study provides a new way to examine the potential relationship of various types of attachment, especially environmental attachment, on people’s tendency to perform different kinds of pro-environmental behaviors. In this research, we try to break down the complex dimensions and levels of both place attachment and pro-environmental behaviors suggested by former studies. In doing so, we propose to bridge a gap between

- 52 - attachment and pro-environmental behavior literature. The novelty of this study includes first, deconstructing the quasi-definition of “place attachment” into more specific components such as “environmental attachment” and “local attachment”; second, measuring the pro-environmental behavior by designing a new concept of “tendency to perform pro-environmental behaviors” by combining both people’s actual behavior and their willingness to perform pro-environmental behaviors in the future; and third, correlating the attachment factors individually with a specific tendency to perform pro- environmental behaviors and comparing the differences among the attachment factors.

Thus this study answers the need for investigating the effect of place attachment on pro- environmental behaviors considering the multidimensionality of the components.

The study hypothesis is that an individual’s behavior toward the environment is correlated with that individual’s attachment to environment. To test this idea, we selected an ethnically diverse population living with land adjacent to streams in the North

Fork Subwatershed of the Sugar Creek for our survey. These people were chosen for the reason that, in predominately agricultural areas, most of the land is farm land. The streamside is where the woods are preserved and that is also where the local residents go play, hunt, fish, collect mushrooms and herbs, and enjoy nature. Although a strong bond between the farmers and their land certainly exists, such close daily interaction is not common in the cities. Therefore, I have conducted the study under the assumption that the residents’ attachments to the recreational (stream) area are relevant to the general population. This assumption may need to be tested in future research.

- 53 - 2.2. Method

All adult residents in the North Fork Subwatershed whose property either included part of a headwater stream or had one on the border were included. Thus, I conducted a census of all the households that were identified in the study area. The study population was determined by using ArcGIS to superimpose the headwater streams layer created by Deana Hudgins, who is the GIS specialist with the Sugar Creek Project, and the property owners’ layer, which was obtained with cooperation from the Wayne County

Auditor Jarra Underwood. The total study population as qualified by the criteria mentioned above was 192 households. I collected data from only one person per household (the head of household), although in some cases I surveyed one person from the household living on the property and one person from the household for the property owner. Individual respondents within sampled households were identified by addressing the name of the property owner on an envelope which contained the survey. Nineteen addresses were not valid; 37 were contacted by mail but they did not return their surveys;

26 others declined to participate; so the final number of participants included in our survey was just 110. This sample size provides a +/- 6.1% margin of error at the 95% confidence level, assuming the response distribution is 50%.

With such a small sample size, performing very detailed statistical analysis with many different factors was not practical. Thus, I had to settle for a rather preliminary and simple model of the relationship between people’s participation in conservation programs and their attachment factors.

- 54 - I applied for the IRB (Institutional Review Board) exemption at The Ohio State

University in the summer of 2009 and the application was approved as to be exempted under category 2 by the IRB with the OSU protocol number 2009E0566. The survey research was conducted during the summer of 2009. The study sites selected for this research are located in the North Fork Subwatershed in the Sugar Creek Watershed, which belongs to the Muskingum Basin.

2.2.1. Description of Study Area

The study sites were located in Wayne County, one of the largest dairy counties in

Ohio. Farms in this area produce a variety of agricultural products including crops like corn, soybean, wheat, oats, hay, potatoes, etc., and livestock like cows, chickens, pigs, etc. (2007 Census of Agriculture). The North Fork Subwatershed is located in the north part of the Sugar Creek Watershed (see Figure 8), right after the Upper Sugar Creek

Subwatershed and the Little Sugar Creek Subwatershed. It is adjacent to the part of

Wayne County where the largest non-English speaking and “English as a Second

Language” population reside (2010 Census). At the northwest part of the North Fork

Subwatershed (see Figure 9), the town of Kidron (unincorporated) is a local center of commerce, which holds an agricultural wholesale auction house. The population in this part of Wayne County is a mixture of New and Old Order Amish, and the more conservative Swartzentruber Amish, and non-Amish who are predominantly Mennonite.

There are both grain and dairy farms in this area. The 2003 survey results showed the average total farm size is around 228 acres, while in the 2009 survey the average total

- 55 - farm size was approximately 102 acres. The reason for this decrease in average farm size requires further research. Similar to other subwatersheds in the Sugar Creek Watershed, the North Fork Subwatershed’s farms have intensified production and decreased fallow cycles over the last fifty years and now have about 10-20% more cows. Different from the farmers in the Upper Sugar Creek Subwatershed, which is to the northwest of the

North Fork Subwatershed, who chose to increase their scale of operations by increasing the size of farms, the North Fork Subwatershed’s farmers were more interested in increasing their herd size as a result of adopting the use of milking machines. The rotation patterns of dairy farms have also been modified to meet the increased demand as a response to the increased herd size. This, of course, may result in degradation of the local environment and its natural resources although much of the rotational change has been through rotational grazing, which is usually associated with decreased runoff, so the intensification may actually reduce pollution in this case (Moore, 2009).

2.2.2. Prior Similar Research Done in the Study Area

In 2003, a survey was designed by researchers who were very familiar with the local area due to their extensive work interacting with the local community (Parker, 2006;

Parker et al., 2007; 2009; Parker & Moore, 2008; Moore, Parker, & Weaver, 2008;

Weave et al., 2011). The 2003 survey questions were designed specifically to be sensitive to local customs by showing local photos and places within the survey. The major purpose of the survey, designed by Richard Moore, Mark Weaver, and Jason

Parker, was to learn

- 56 -

Figure 8. Map of the Sugar Creek Watershed.

- 57 -

Figure 9. Map of the North Fork Subwatershed.

- 58 - more about Upper Sugar Creek in terms of land tenure, social networks, intergenerational farm succession, and conservational use among farmers of Wayne County, Ohio. The

2003 survey included all land owners in three Subwatersheds (Upper Sugar Creek, North

Fork, and Little Sugar Creek) whose properties were on or adjacent to the stream

(N=726). The data were collected using a “drop-off, pick-up” (Steele et al., 2001; Riley,

2002) method.

2.2.3. Survey Instrument for This Study

The 2009 survey was designed and modified based on the 2003 survey conducted by other researchers (Parker, 2006; Parker et al., 2007; 2009; Parker & Moore, 2008;

Moore et al., 2008; Weaver et al., 2011). Due to the difference between the previous study objectives and those described herein, certain parts of the existing survey were modified. However, the majority of survey items were retained. The 2003 survey had a number of questions that were relevant to my research goals. Modification of that survey also afforded us the opportunity to see longitudinal dynamic social change between 2003 and 2009 in this rural community. In order to make the new survey’s results comparable to the 2003 survey, certain parts of the questionnaire were kept as similar to the 2003 survey, while new questions were asked where the information was critical to the current research’s focus. At the same time, when using the 2003 questionnaire’s questions, certain limitations of the 2003 study were inherited as well. For example, in the 2003 survey, the conservation practice data were elicited based on a “presence” or “absence” basis and did not examine the extent of use. In the 2009 survey, additional questions

- 59 - were added to measure the extent of certain conservation practices. Also, in the 2003 survey, conservation was measured using nine Best Management Practices (BMPs) (4 practices and 5 preferences) because an exhaustive list of BMPs was not provided.

Although including more questions to measure the pro-environment behavior of the local community would have been ideal, the benefits of keeping the survey close to the original

2003 outweighed the advantages of including more BMP choices. In this (2009) research, the survey items from the questionnaire developed by Jorgensen & Stedman

(2001) were adopted to measure the community attachment of the participants. The measurements of their environmental attachment and participation in conservation programs come from the 2003 survey. The questionnaire instructions have one map of the

Upper Sugar Creek water shed and a map of the North Fork Subwatershed to make sure the respondents will answer the questionnaire according to their experience with the

North Fork Subwatershed.

The survey contained three parts. The first part consisted of eight items (two multiple choice, two short open-ended and four bipolar response scales) that measures people’s tendency to perform various pro-environmental behaviors (See Table 2). The behaviors covered a wide range from read newsletters to volunteering. I included the label I assigned for each behavior, the total number of responses for each item, and the means for the readers’ reference when looking at the results section.

The second part contained 24 items (ten multiple choice, eight open-ended, and

- 60 -

Table 2. Response items related to pro-environmental behaviors

Response item N Mean SD Work on an individual basis to make environmental 86 1.31 .801 improvements on the stream on your propertya Form a small group with immediate neighbors to improve the 82 .40 .645 stream quality based on your own prioritiesa Construct a tree or grass buffer along the streama 85 1.08 .889 Make or improve habitat for fish in the North Forka 83 .83 .762 Attend information meetings on water quality in your 85 .48 .590 communitya Read newsletters, magazines or other publications written by 88 .83 .698 environmental groupsa Become a member of a group whose main aim is to preserve or 84 .20 .460 protect the environmenta Vote for candidates in local elections that support watershed 83 .58 .587 protection and restoration effortsa Sign a petition in support of protecting the environmenta 82 .39 .515 Volunteer time to restore wetlands in your communitya 82 .35 .596 Give money to an environmental groupa 80 .15 .453 Write a letter or call your member of Congress or another 81 .25 .462 government official to support environmental protectiona Roadside trash removal 86 1.34 .745 Make a special effort to buy foods grown without pesticides or 87 2.63 1.339 chemicalsb Make a special effort to buy paper and plastic products that are 85 2.52 1.240 made from recycled materialsb Avoid buying products from a company that you know may be 86 2.84 1.405 harming the environmentb Make a special effort to buy household chemicals such as 86 3.24 1.137 detergent and cleaning solutions that are environmentally friendlyb How often do you recycleb 90 3.13 1.247 How often do you use solar panelb 88 1.74 1.489 How often do you carpoolb 89 1.64 1.199 a. 0=No, 1=Yes, 2=Already doing

b. 1=Never, 2=Annually, 3=Monthly, 4=Weekly, 5=Daily

- 61 - Table 3. Response items related to attachment

Response item N Mean SD Kids in your immediate neighborhood who you know by name.a 104 2.52 .914 People living in your community a 105 2.38 .726 Friends who live in your community a 104 2.08 .952 Relatives who live in your community a 104 1.97 1.27 I feel relaxed when I’m in my community. b 100 4.43 .739 I feel happiest when I’m in my community. b 100 4.28 .805 I really miss this community when I’m away from it for too long.b 100 4.07 .868 I feel that I can really be myself in my community. b 100 4.16 .896 My community reflects the type of person I am. b 100 3.93 .825 My community is the best place for doing the things that I enjoy 100 3.93 .891 most. b As far as I am concerned, there are better places to be than in my 100 2.47 1.06 community. b The schools are good and safe. b 102 4.19 .768 This is a safe place to live. b 101 4.30 .782 I trust my neighbor. b 101 4.50 .755 There is very little crime or drug use here. b 99 3.95 .862 Neighbors help each other in time of need. b 102 4.49 .728 The quality of life is very good. b 100 4.45 .687 Local government is good at responding to problems. b 96 3.58 .959 The local economy is strong. b 100 2.98 .945 It is easy for me to tell a stranger in my community from 100 3.53 .979 somebody who lives here. b I really feel a part of my community (instead of its being just a 100 3.93 .891 place to live). b At the present time, Sugar Creek is polluted. b 90 3.01 .828 Any improvements in stream water quality should begin upstream 87 3.67 .845 so changes can be measured downstream. b The scenic beauty of Sugar Creek should be protected even if 89 3.24 .977 landowners have to change management practices. b The environmental movement does a great deal of good b 87 3.13 .950 The economic viability of Sugar Creek farmers is more important 87 2.93 .925 than environmental quality in the watershed. b The environmental movement does more harm than good b 87 3.38 1.04 a. 1=All, 2=Most, 3=Some, 4=Very few, 5=None.

b. 1=Strongly disagree, 5=Strongly agree.

- 62 - six bipolar response scales) that measures people’s attachments, and social demographic information (See Table 3). Again, I included the labels, total number of responses, and the means of each item as a reference for the results section.

The third part contained 12 items (five multiple choice and seven open-ended) specifically related to farmers. The results from this part are not included in my particular study since we are not trying to just focus on farmers. A copy of the survey and the text that accompanied the measurement items is attached in Appendix A.

2.2.4. Data Collection

One hundred ninety-two adult residents or land owners were identified and a printed survey was delivered to them in person or by mail. The surveys were administered using a “drop-off/pick-up” methodology to parallel the 2003 survey by the author and three high school summer interns working for Richard Moore in the summer

OARDC Research Internships Program (ORIP). By hand delivering the self- administered questionnaires to each individual household, we expected better response rates than we would have using the mail method and we saved resources compared to conducting face-to-face interviews (Steele et al., 2001; Parker, 2006). Such a method is ideal for a small local community in a rural area where people live close to each other so the time and cost of administration of the survey can be minimized (Steele et al., 2001).

If no one was at home when we tried to drop-off the survey, a callback was performed a few days later until a contact was made or the house was confirmed as vacant. For people who lived outside of the county, a survey was mailed to their other address asking

- 63 - them to return the filled survey in the pre stamped envelope. Out of the total target 192 households sampled, 110 of them returned the survey partially completed or fully completed. The return rate was about 58%.

The survey included questions about the sociodemographics among the respondents. The questions asked for the position in the household, marital statues, gender, age, years living in the current household, income, education, and number of children under the age of 18. Dummy codes were used to quantify the position in the household (1=head of household, 2= spouse of head of household), marital statues (1= married, 2=single), and gender (1=female. 2=male) for use in Pearson’s r correlation analysis. The results are summarized in Table 4:

Table 4. Socioeconomic variable summary.

Variables Mean SD N Position in the householda 1.15 0.418 92 Marital statuesb 1.13 0.340 91 Genderc 1.93 0.656 77 Age 54.39 12.98 90 Years lived in the current household 39.47 18.59 91 Incomed 2.27 1.34 79 Educatione 2.02 1.23 92 Number of children under the age of 18 1.85 2.82 74 a. 1= head of household, 2= spouse of head of household. b. 1= married, 2=single. c. 1=female, 2=male. d. 1=less than $24,999, 2= $25,000-$49,999, 3=$50,000-$74,999, 4=$75,000-$99,999, 5 =100,000-$124,999, 6=$125,000-$149,999, 7=$150,000-174,999, 8=$175,000-199,999, 9=more than $200,000. e. 1=8th grade, 2=high school, 3=some college, 4=college graduate, 5=graduate degree.

- 64 - 2.2.5. Data Analysis

People’s tendencies to perform pro-environmental behaviors were grouped into subcategories according to Stern (2000)’s recommendations with some modifications.

To account for people’s different levels of willingness to perform certain pro- environmental behaviors, I asked them to specify whether they were a) already doing it, b) willing to do it, or c) not willing to do it. A factor analysis was performed on the result to confirm that the various questions were measuring different types of pro- environmental behaviors. The results were combined linearly to generate a score for each type of pro-environmental behaviors and correlated with the attachment components.

I used IBM®SPSS®Statistics 19.0.0 to conduct factor analysis of both the group of questions designed to measure people’s tendencies to perform pro-environmental behaviors and the group of questions designed to measure people’s attachment to various issues. I followed the recommendations from Costello & Osborne (2005) to regarding the best practices in exploratory factor analysis. I chose to use principal components analysis for both the attachment and behavior data sets. Factors were retained according to the scree test (http://www.statsoft.com/textbook/stathome.html). To evaluate the factor loadings, I used the rotation method of Varimax with Kaiser Normalization. After examining the rotated factor analysis, appropriate names were assigned to the different factors produced by the analysis. I then examined the relative influence of each of the attachment components on pro-environmental behavior. I calculated the score for each

- 65 - factor retained in the factor analysis since there are multiple questions measuring the same construct.

The environmental attachment factor and the tendency to perform factors were first correlated on a one to one basis and then combined with other attachment factors for a series of correlation analysis. The power analysis was conducted using G*Power (Faul et al., 2007).

2.3. Results

Results of data collection and analyses show that participants’ attachments to their environments correlate positively with their tendencies to perform pro-environmental behaviors, as I had generally hypothesized. The factor analysis resulted in the retention of two factors in the local level pro-environment behavior questions, one factor in the national level pro-environment behavior questions and seven factors in the attachment questions. Of the three pro-environment behavioral components tested, both of the two local level pro-environment behavior were significantly correlated with people’s environment attachment, while the national level pro-environment behavior did not show significant correlation with the environment attachment factor. In addition, none of the other types of attachments showed any significant correlation with all three pro- environment behaviors. Details are given in the rest of this section.

2.3.1. Components of Attachment

The factor analysis of various items designed to assess different types of attachment resulted in the retention of seven factors that explained 71.18% of the

- 66 - variance across these items. After rearranging the attachment questions into new groups according to the factor that they mainly load on, I obtained seven groups each representing a different kind of attachment (Table 5). The different components were named according to the questions they included. Each category was treated as a particular kind of attachment. As a result, data analysis yielded five distinct attachments for further investigation. The Local and Other place factors were not used for further analysis because they had fewer than 3 items.

Although the main concern of this paper is the relationship between people’s environmental attachments and their pro-environment behaviors, other forms of attachments may also be related to people’s tendencies to participate in pro- environmental behavior.

I calculated the Cronbach’s alpha for each of the attachment measures to examine the internal consistency within the new groups. The result is shown in the following table. As a general rule, alpha values greater than 0.7 are preferred, though values of 0.6 are acceptable (Nunnally & Bernstein, 1994; DeVellis, 2003). With the exception of the problem factor, our result showed that the Cronbach’s alphas within each attachment factor were greater than 0.7, thus suggesting that their measurements were consistent.

- 67 - Table 5. Factor loadings and internal consistency of attachment items.

Attachment component factors: Cronbach’s Items: Feeling Human Safety Environment Problem Alpha Relaxed .585 .311 .114 -.110 .161 0.8706 Happy .808 .116 .131 -.168 .006 Miss .769 .009 -.083 -.069 .087 Be self .886 .007 .048 -.071 -.039 Reflect self .629 .192 .239 .228 .177 Best place .776 -.089 .176 .081 -.085 Stranger .537 .378 .294 -.026 -.350 Community .485 .411 .282 .138 .056 Kids -.154 -.729 -.187 .099 -.138 0.7601 People -.011 -.731 -.162 .078 -.097 Friends .018 -.742 -.013 .071 -.087 Relatives -.129 -.805 .241 .145 -.027 Trust neighbor .176 .616 .355 .133 -.084 Safe .274 .193 .652 -.017 .466 0.7887 Little crime .124 .069 .854 .103 -.049 Neighbor help .396 .374 .422 .219 -.151 Quality life .548 .191 .609 .154 .073 Scenic -.006 -.014 .027 .828 .216 0.7451 Environment good -.073 -.130 .123 .737 .225 Economy .079 .168 -.448 .583 -.101 Environment bad -.101 -.184 .169 .816 -.075 Schools .240 .179 .439 -.073 .549 0.638 Pollution -.098 -.024 -.108 .405 .683 Upstream .070 .156 .068 .086 .796 Local government Excluded from further analysis Local economy Other place

- 68 - 2.3.2. Pro-environmental Behaviors

People may perform pro-environmental behaviors in some parts of their lives but not in others; for instance, they may recycle their trash, but not plant buffer zones around their fields. To determine the extent to which the participants in my study acted with the environment in mind sometimes, but not all the time, I used a factor analysis on the data I collected about their pro-environmental behaviors. The original items were separated into two groups (Local vs. National) according to the level that is appropriate before the principle component analysis. The reason for distinguishing between local level behavior and national level behavior is that, since we are investigating people’s attachment to the local environment, I suspected that the national level pro-environment behavior may not be as relevant as the local level behavior. The factor analyses of various items designed to assess different types of pro-environmental behaviors resulted in the retention of three factors within the local level behavior and one factor within the national level behavior.

After rearranging the pro-environmental behavior questions into new groups according to the factors that they mainly load on, I obtained four groups each representing a different type of behavior (see Table 6& 7). The different components were named according to the questions they included. Each category was treated as a particular type of pro-environment behavior. As a result, data analysis yielded three distinct behaviors for further investigation. The other items such as Organization, Group, and Farm were not used for further analysis because they either have less than 3 items loaded on them or have a very low internal consistency (Cronbach’s Alpha).

- 69 -

Table 6. Factor loadings and internal consistency of local level pro-environment behavior items. Factors Cronbach’s Items Private Public Other Alpha Organic .867 .063 -.163 0.7729 Badcompany .500 -.012 -.018 Chemicals .542 .161 .039 Paper .689 .132 .150 Habitat .099 .467 .256 0.6656 Group .001 .658 -.007 Volunteer .174 .743 -.090 Buffer .018 .458 .225 Trash -.032 .250 .529 0.3792 Vote .107 .067 .473 Carpool -.048 -.159 .506 Infomeeting Excluded from further analysis Solar Recycle Individual

Table 7. Factor loadings and internal consistency of national level pro-environment behavior items. Items Factor Cronbach’s Alpha Membership .421 0.6084 Petition .647 Money .422 Congress .658 Publication Excluded from further analysis

- 70 - 2.3.3. Relationship of Pro-environmental Behaviors, Attachment Factors, and

Demographics

When I tested my hypothesis about the relationship between environment attachment and people’s performance of pro-environmental behavior, I found that

Environment Attachment was significantly correlated to the two types of Local Level behaviors (Public and Private), but not the National Level behaviors (See Table 8).

Table 8. Correlation between environment attachment (EA) and each type of pro- environmental behavior (PEB). (Two tail Pearson’s r) (*p<.05)

PEB: Correlation: p-value Power (one tail, alpha=0.05) National Level .252 .061 .5974 Local Level Public .293 .032* .7021 Local Level Private .334 .013* .8045

I then tested to see if other attachment factors would have significant influence on the pro-environmental behavior. The results are shown Tables 9 through 12. As one can see, all the other attachment factors did not show any significant correlations with all the pro-environmental behaviors.

- 71 - Table 9. Correlation between Feeling Attachment (FA) and each type of pro- environmental behavior (PEB). (Two tail Pearson’s r) (*p<.05.)

PEB: Correlation: p-value Power (one tail, alpha=0.05) National Level -.051 .709 .0217 Local Level Public -.153 .269 .0029 Local Level Private .176 .203 .3583

Table 10. Correlation between Human Attachment (HA) and each type of pro- environmental behavior (PEB). (One tail Pearson’s r) (*p<.05.)

PEB: Correlation: p-value Power (one tail, alpha=0.05) National Level -.103 .450 0.0081 Local Level Public -.097 .487 0.0095 Local Level Private -.016 .906 .0631

Table 11. Correlation between Safety Attachment (SA) and each type of pro- environmental behavior (PEB). (One tail Pearson’s r) (*p<.05.)

PEB: Correlation: p-value Power (one tail, alpha=0.05) National Level .260 .053 .6216 Local Level Public .161 .245 .3177 Local Level Private .007 .961 .0555

Table 12. Correlation between Problem Attachment (PA) and each type of pro- environmental behavior (PEB). (One tail Pearson’s r) (*p<.05.)

PEB: Correlation: p-value Power (one tail, alpha=0.05) National Level .255 .058 .6065 Local Level Public -.117 .399 .0064 Local Level Private .115 .407 .2084

- 72 - When I performed a regression analysis examining the demographic characteristics’ influence on people’s attachment to the environment, among all the

Social Demographic Factors collected, only the number of children under the age of 18 showed a significant correlation with people’s Environment Attachment (see Table 13).

Table 13. Correlation between Environment Attachment (EA) and Social Demographic Factors (SDF). (One tail Pearson’s r) (*p<.1. **p<.05.)

Social demographic factors: Correlation with EA: p-value Power (one tail, alpha=0.05) House position -0.063 0.308 0.0158 Marital -0.035 0.391 0.0273 Sex -0.162 0.117 0.0022 Children 18 0.226 0.048** 0.511 Income 0.121 0.185 0.229 Education -0.127 0.155 0.0039 Year live 0.003 0.490 0.0526 Two year 0.051 0.344 0.106 Age -0.048 0.353 0.0216

2.4. Discussion

In this study I tried to examine the potential relationship of various types of attachment, especially environmental attachment, with people’s tendencies to perform different kinds of pro-environmental behaviors. By conducting this research, I tried to break down the complex dimensions and levels of both place attachment and pro- environmental behaviors suggested by former studies. In doing so, this study makes a

- 73 - needed connection between the attachment literature and the pro-environmental behavior literature. Although previous studies trying to separate the different dimensions of the construct of place attachment (Vaske & Kobrin, 2001), community attachment (Brehm et al., 2004) exist, and studies on grouping environmentally significant behaviors according to their differences (Dunlap et al., 2000; Stern, 2000) are present in the literature, little research has tried to combine these two fields of studies together and investigate the relationship between a specific type of attachment (e.g., attachment to environment) and a specific type of pro-environmental behavior (e.g., purchasing environment friendly products).

The novelty of this study includes, first, my deconstruction of the quasi-definition of “place attachment” into more specific components such as “environmental attachment” and “local attachment.” Second, I measure the pro-environmental behavior by designing a new concept of “tendency to perform pro-environmental behaviors,” combining both people’s actual behavior and their willingness to perform. Third, I correlate the attachment factors individually with specific tendencies to perform pro-environmental behaviors and compare the differences among the attachment factors. The results show a positive correlation between environment attachment and people’s tendency to perform certain types of pro-environmental behaviors, which confirms other studies on this topic

(Scannell & Gifford, 2010; 2011). At the same time, the results also show no correlation between people’s attachments to other factors relating to pro-environmental behavior.

Thus this study answers the need for investigating the effect of place attachment on pro-

- 74 - environmental behaviors considering the multidimensionality of both the attachment construct and behavioral tendency. The major implication of the positive correlation between environmental attachment and pro-environmental behaviors is that this finding confirmed my hypothesis and is in support of Scannell & Gifford’s (2010) conclusion that the natural part of place attachment, not the civic part, has significant correlation with pro-environmental behaviors.

2.4.1. Existing Models

Several models have been developed to try to explain why a farmer will or will not adopt certain conservation practices. However, models like innovation diffusion

(Roger, 1983; Brown et al., 1981) and farm structure did not yield very promising results

(Tucker & Napier, 2002; Napier et al., 1984; Napier et al., 1986; Sommers & Napier,

1993). Basically, researchers have found that a farmer’s adoption of a conservation practice is influenced by many more factors than are typically included as predictors in any one of these models. Such factors may include, but are not limited to, aesthetics concerns (Erickson et al., 2002), subjective norms (Bultena & Hoiberg, 1983), household life cycle and organization, land tenure, and farm type (Salamon & Farnsworth, 1997).

Generally speaking, studies of rural communities in the United States have lacked a local perspective. Since the traditional research methods and modeling tend to generalize a large group of cases rather than specifically deal with each individual one, the one-size- fits-all model can do well in terms of analyzing the whole society and general economic patterns; however, at a certain level, when more information about the interactions among

- 75 - individuals and between people and their land is needed, such an approach will reach its limit and stop working properly (Goldchmidt, 1978; Napier & Tucker, 2001; Napier &

Bridges, 2002; Napier et al., 2002; Camboni & Napier, 1993; McIntosh & Lee, 2003;

Salamon, 2003).

2.4.2. A New Model

The final version of my model that emerged is shown in Figure 10. Further research is needed to confirm this proposed model. Different from the other research on the relationship between sense of place (community attachment), this model proposes a new concept of attachment to the natural environment, which is shown to have significant correlation with people’s tendencies to perform pro-environmental behaviors. The application of this research is very promising. If future environmental education programs and environmental movement can focus on reconnecting people to the natural environment, the probability of motivating people to participate in various environment- friendly behaviors may be greatly enhanced.

In this study, we emphasize people’s attachment to the natural environment and the potential correlation between such attachment and people’s tendency to perform certain pro-environmental behaviors. In addition to the incentive and information approaches used by the traditional programs, this study proposes that environmental attachment has a correlation with people’s intention to perform pro-environmental

- 76 - Sex

Live here in Tendency to perform the future Attachment to the environment natural behaviors environment

Income

Others Other attachments

Figure 10. Final model for the relationship between attachment to the natural environment and people’s tendency to perform pro-environmental behavior.

behaviors. As a result, programs designed using this new model potentially may see more behavioral changes among their participants. For example, if a practitioner wants to implement a conservation program focusing on encouraging people to protect a natural habitat for an endangered species, according to the results from this study, taking them outdoors to increase their attachment to the habitat may be more effective than educating them in the classroom about the importance of the species and the seriousness of the problem.

- 77 - 2.4.3. Limitations

Though considerably better than what is expected in mailed surveys, the response rate (58%) is substantially lower than other studies that use the drop-off, pick-up method

(Steele et al., 2001). Possible reasons include that summer is busy season for the farmers, the survey administrator’s non local accent and race, and survey fatigue. Researchers in

OARDC have been conducting surveys on different topics in the area around the city of

Wooster for a long time. As a result, the local residents are quite familiar with the concept of questionnaires and potentially suffer from survey fatigue (i.e., they are worn out from participation in previous studies). For example, as early as the drop-off phase of the survey research, quite a few of the residents refused to participate stating that they are not interested in surveys, even before the researchers got a chance to explain the background and purpose of the survey. We also recently learned that a MA student in

Geography was doing research in the North Fork at this time.

The fact that only the environmental attachment has significant correlation with most pro-environmental behaviors doesn’t mean that correlations between other attachments and pro-environmental behaviors do not exist. Since we conducted a single study, we do not have the confidence to make such a conclusion. In order to increase the generalizability of this study, more studies in different communities will be required.

That being said, our findings can help explain some phenomena observed in previous studies. For example, place of residence was found to be not significantly related to people’s attitudes toward the environment (Van & Dunlap, 1980). One could argue that

- 78 - the reason that there is no apparent correlation between these two is because the residents’ choice to live in certain places are affected by different factors such as environmental attachment and community attachment. The significant correlation between environmental attachment and attitude toward environment could be masked by other factors.

2.4.4. Comparison to the 2003 Study

The results of the 2003 survey were analyzed in Parker’s dissertation (2006).

Since the survey was designed mainly to focus on trying to understand the local residents’ perception of local environmental issues, government agencies, and subwatershed organizations, the measurement of people’s conservation attitudes and practices were neither exhaustive nor complementary. While Parker found significant correlations among conversation use and farm size, lease-out all land, and percent of off- farm income, he failed to confirm his original hypothesis that conservation adoption could be predicted by using farm size, farm type, land tenure, and percent of off-farm income as independent variables.

To resolve the inadequacy problem with the 2003 survey, I modified the survey to include a list of conservation behaviors that covers different levels and perspectives. In addition, I investigated the relationship between people’s attachments to different factors and their tendencies to perform pro-environmental behaviors instead of the factors studied in the 2003 survey. The correlation between environmental attachment and

- 79 - tendency to perform pro-environmental behaviors was shown to be significant in my study.

2.4.5. Summary

In summary, this chapter started by introducing a challenge faced by conservation programs, namely the lack of success in terms of engaging citizens to perform pro- environmental behaviors. After reviewing past literature, I proposed that there is a lack of connections between the studies on people’s attachment to the natural environment and their tendencies to perform pro-environment behaviors. This study focused on investigating such relationship by conducting a survey in a rural community in Ohio. The result of the survey partially confirmed my hypothesis that people’s environment attachment does have significant correlation with their tendencies to perform certain pro- environment behaviors but not others. With such results on hand, I compared a few existing models designed to explain factors that influence people’s adoption of conservation practices and proposed my new model focusing on the attachment factors.

This study is quite preliminary and has certain limitations, but nevertheless it will hopefully inspire future studies in the same field.

- 80 -

CHAPTER 3:

A NEW TIMED SEQUENTIAL DIGITAL PHOTOGRAPHIC METHOD

FOR MONITORING BIOLUMINESCENT FLASHING ACTIVITY OF FIREFLY

Photinus pyralis AND Photuris pennsylvanica (Coleoptera: Lampyridae)

3.1. Introduction

Fireflies are one of the few insects that make a good impression on most people, according to a survey I did in the rural community near Wooster, OH. The firefly was ranked fourth in term of perceived association with good environment quality. However, compared to other commonly known invertebrates, studies on fireflies are limited. In only a small portion of the studies about fireflies have researchers reported on their population and habitat. In this chapter, I developed a new timed sequential digital photographic method for monitoring adult firefly populations in their natural habitats that is easy to perform, cheap to set up, and nondestructive to the environment. The new method is sensitive to firefly population change and data collected using this method can be compared across different studies. I describe the setup of the new method and propose that, the new method has the potential to promote future research on adult firefly populations and their relations with the natural environment and human activities.

- 81 - Traditionally, when researchers want to study insects including fireflies, they go to the insect’s natural habitat and collect living or dead samples (Gray, 1933; Menhinick,

1963; Harding, 1966; Sabu, Shiju, Vinod, & Nithya, 2011). Depending on the purpose of the study, the sample collected is then taken back into the laboratory to be observed or tested. This method works well for many studies focusing on the anatomy or molecular biology of individual insects. However, these methods may not be appropriate for studies focusing on the natural behaviors of living insects and their interactions with the environment. For example, some species of fireflies, like the Photuris complex, may flash different patterns in the lab than they do in the field (Branham, 2003). Furthermore, females frequently will not flash in response to other flashes in a confined situation

(personal observation). Thus, a better way to study fireflies’ flashing patterns and mating behaviors is to observe them in the field (Lloyd, 1969).

In the past because of limited conditions, those few studies conducted in the field had to focus on the individual level. Entomologists who specialized in fireflies either followed fireflies in the field and recorded their flashing behaviors (Vencl, 1998) or collected fireflies and studied them in the laboratory (Buck, 1937a; b). Due to the nature of their research methods, they could monitor only one firefly or even one single flash at a time. Despite the limited sample size, such studies yielded a significant amount of information about individual firefly behavior and physiology.

Unfortunately, although we know much about individual fireflies, little work has been done regarding the role fireflies play in the ecosystem at the population level. The

- 82 - most significant characteristic of fireflies is their ability to flash in the dark. Moreover, various studies (Buck, 1935; 1937a; 1937b; 1968; 1978; 1988; Lloyd, 1966; 1984a;

Carlson, 1985; Branham, 1996;) have already shown that the flashing activity of fireflies is a population behavior, affected by the interactions among a group of fireflies.

However, the flashing phenomena of a group of fireflies have received little attention except for the synchronous flashing of the Southeast Asian fireflies, Pteroptyx malaccae

(Buck, 1968). The reason that research on firefly group flashing activity is lacking is simple: most traditional research methods simply cannot record the flashing activity of a whole firefly population in the field (Kirton et al., 2011). Having enough people to follow each individual firefly in the field without seriously disturbing the natural settings would be quite difficult.

Only recently have some researchers started to utilize sophisticated equipment such as digital videography and photometry to study the flashes of fireflies in the field

(Moiseff, 2000). Such methods produce a huge amount of data in a relatively short period of time—one frame can be generated every 33 ms. In order to process these data, special software is required. Even when the required software is present, analysis of the data for only a few minutes is still a time consuming process.

Most methods used by entomologists in the past are not appropriate for a citizen science project. The criteria I am using to define a useful citizen science- based technique for firefly population measurements are the ease of use, the cost-effectiveness, and the nondestructiveness to the environment and to the species being studied. Further,

- 83 - the method must yield reliable data that can be compared among different studies. To this end, I have developed a new method called the "timed sequential digital photographic method" that is both citizen-friendly and gives a fair estimate of the firefly population in association with environmental factors. This method has considerable advantages over other methods such as marked-recapture, digital recording, Berlese funnel, black light, removal sweeping, and the soil washing and floating method

(Madsen, 1962; Menhinick, 1963; Bushmann, 1984; Doane et al., 1987; McLean et al.,

1972; Edwards, 1991; Copeland, 1994; Besbeas et al., 2002; Sabu et al., 2011).

3.2. Timed Sequential Digital Photographic Method

P. pennsylvanica was studied during June 2009 and August 2009 in an Ohio

Agriculture Research and Development Center (OARDC) experiment field lab on The

West Badger Farm located near South Apple Creek Road north of the township of Apple

Creek in Wayne County, Ohio. Free specimens were photographed in the field and the photographic recordings were studied in the office/laboratory in Williams Hall on the

OARDC campus. The flashings of both free-flying males and perched females were photographed using long-exposure techniques. A Nikon Coolpix p6000 digital camera was used to take photos of the plots in this study. Each photo covers one single plot.

Most of the photos were taken during the period of time from right after sunset until almost midnight, at which time the battery usually run out of charge. This period roughly lasts about 2 hours. During the photo-taking period, the camera was set to automatically take one photo every 30 seconds and each photo was exposed for 8 seconds, which is the

- 84 - longest exposure time the camera can handle. About 26.7% of the whole experiment period was recorded on the digital photos. Dividing the period of time by the rate of photo taking, on average this method produced 200-300 photos every night. After finishing the photo-taking process in the field every night, all the photos in the camera were downloaded into the office computer and cataloged according to the date and type of crop on the particular plot. The camera lens was tilted slightly downwards so only the plot under investigation was covered by the photos.

Each photo had the size of 1024 x 768 pixels and resolution of 300 dpi (dot per inch). The bit depth was 24 and the color representation was sGRB. The date and time

(to the minute) were imprinted on the lower right corner of each individual photo. The specific time (to the second) when the picture was taken could be found in the JPEG file by checking the properties of each photo.

The size of each plot where the data for this experiment were collected was about

20 x21m and the camera lens was set on a tripod about 1m above the top of the vegetation. When setting up the camera in the field, I put two markers in each plot to mark the edges of the plot, so that when I adjusted the camera, I could easily tell where the landscape changed. The camera was positioned so the pictures taken did not include other plots. The result of this operation was an irregularly shaped space captured by the picture. Only part of the side close to the camera was captured on the photo (2.5m out of a total of 21m).

- 85 - The entire data collection stage of the project lasted from mid-Jun. to the end of

Aug. After finishing the field work, I analyzed each photo by comparing photos taken immediately before and after each other, to distinguish any differences between firefly flashes. During this process, other interference such as household lights and reflection from the vegetation were eliminated. I then counted firefly flashes on every photo and recorded them into an excel worksheet. Since there were two species of fireflies in this area, their two types of flashing patterns captured by the photos were recorded separately.

P. pyralis’s flash lasts longer and tends to form a “J” shaped line on the photo, while P. pennsylvanica’s flashes were fast and short, leaving a dot on the photo.

3.3. Results

Here, I reviewed the direct field observations I made during the firefly season of

2009 on the West Badger Farm while I was conducting the timed sequential digital photographic method. The observations focused mainly on two firefly species: P. pennsylvanica and P. pyralis.

3.3.1. Field observations

P. pennsylvanica and P. pyralis fireflies began flashing around the end of civil twilight and flashed until midnight. Throughout the evening, individual fireflies flew slowly in the field at a height of 2 m or less above the top of the vegetation. P. pennsylvanica is a special species in terms of the flashing pattern. Taxonomists used to distinguish other firefly species by observing their species-specific flashing patterns in the field (Barber, 1951; Lloyd, 1966). However, P. pennsylvanica individuals, both male

- 86 - and female, have complex flashing patterns. While it was believed that P. pennsylvanica did have its own species-specific flashing patterns, they have been also known to mimic other firefly species’ flashing patterns (Lloyd, 1965, 1980). Although the new timed sequential digital photographic method used in this study was designed to estimate the dynamics of the P. pennsylvanica and P.pyralis population in their natural habitat, the results using this method do not give the total population in absolute numbers as if the data had been obtained by direct field observation; rather, the timed sequential digital photographic method measured the number of flashes in the field of view of the camera.

Previous research has confirmed that there is a linear relationship and high correlation between number of fireflies and the digital photographic records in laboratory conditions

(Kirton et al., 2011).

There were no trees on the farm and the land was relatively flat. Although individual fireflies could be seen at a distance of up to 20 m in the field, the dense vegetation, along with the reflections of the moon, household lights, and automobile headlights from the crop leaves, made distinguishing a firefly flash on the digital photos more difficult if the flash was further away from the camera lens. P. pennsylvanica and

P.pyralis normally flew in and out of the stationary field of view. From the grassy driveways that bordered the crop fields on all four sides, fewer flashes could be observed compared to the field.

3.3.2. Data collected

- 87 - Table 14 shows part of the data collected using the timed sequential digital photographic method on the West Badger Farm for P. pennsylvanica and P. pyralis in

2009.

Table 14. Example of data collected using the timed sequential digital photographic method for P. pyralis and P. pennsylvanica flashes counts on the West Badger Farm during the summer of 2009.

5-min 5-min 5-min 5-min Exposure photo P.pyralis P.pennsylvanica car Date Time (second) Crop count count count count 19 Jun Conventional 2009 22:20 8 soybean 10 1 1 0 19 Jun Conventional 2009 23:00 8 soybean 10 0 12 1

The whole dataset contains more than 20,000 photos, which is too big to be included in this chapter. Even after I aggregated the data into five minutes intervals, there are still more than 2,000 records. I photographed fireflies flashing on six different crop types during this period.

With the raw data on hand, one can make several types of calculations depending on the kind of question one asks. For example, if we want to know how P. pennsylvanica’s flashing activity on the Organic Hay field changes over the whole season, we can combine all the data collected during one night into a single data point (see Table

15) and plot these new data against the date (See Figure 11).

- 88 - Table 15. P. pennsylvanica’s flashing activity on the Organic Hay field changes over the whole season.

Date P. pennsylvanica flashes per photo per second on the Organic Hay field 21 Jun 2009 0.014500 22 Jun 2009 0.046577 28 Jun 2009 0.10265 5 Jul 2009 0.021458 12 Jul 2009 0.064236 19 Jul 2009 0.13114 26 Jul 2009 0.18713 2 Aug 2009 0.12213 9 Aug 2009 0.096490 16 Aug 2009 0.058468 23 Aug 2009 0.00044643 30 Aug 2009 0.00043103

Figure 11. P. pennsylvanica’s flashing activity on the Organic Hay field changes over the whole season. - 89 - If we want to know how P. pyralis’s flashing activity changes over the night, we can combine all the data we collected in the same half hour since twilight of each night into a single data point (see Table 16) and plot these new data against the hours (see

Figure 12).

Table 16. P. pyralis’s flashing activity changes over night.

Half hour into the night P. pyralis flashes per photo per second 1 (0-30min) 0 2 (31-60min) 0.0094903 3 (61-90min) 0.027079 4 (91-120min) 0.0027467 5 (121-150min) 0.00081503 6 (151-180min) 0.00040562 7 (181-210min) 0.00046693 8 (211-240min) 0

Figure 12. P. pyralis’s flashing activity changes over night. - 90 - In fact, we did use the data collected using this new timed sequential digital photographic method for the studies mentioned in chapter 4 and chapter 5 of this dissertation. Chapter 4 utilized the data to examine the influence of different landscape types over the P. pennsylvanica’s flashing activity. While Chapter 5 used the data to compare the two species’ flashing activity changes over night.

3.3.3. Estimating the population density of fireflies

One major advantage of this new timed sequential digital photographic method is that we can monitor the dynamic changes of firefly population in their natural habitat on a large scale with minimum disturbance. So it is necessary to investigate the relationship between the number of flashes we recorded on the digital photos and the actual number of fireflies in the field. Since we are using the timed sequential digital photographic method to collect data in the format of digital photographic records, the number of flashes on the photos can not be directly used as an estimation of the actual numbers of fireflies in the camera’s field of view.

There are three factors we need to consider regarding this relationship: the size of the land covered by the camera’s field of view; the flashing intervals of each firefly specie; and the percentage of fireflies that flash during the same flashing interval. Even though we did not set up a controlled lab experiment to measure the actual relationship between the digital recordings and actual numbers of fireflies for this particular study, a rough estimation of the population density can still be obtained by borrowing the conclusion of Kirton et al. (2011), and make adjustments to related parameters.

- 91 - In Kirton et al. (2011)’s study, they performed a linear regression between the average count in the photographic image and the density of fireflies. These two sets of data have a high correlation (R2 = 0.94) and the relationship between the number of manual counts of bright spots in images and the stocking density of fireflies can be represented by the formula:

P. tener Image counts= .16xStocking density+1.12 (1)

The fireflies used in their study are Pteroptyx tener Olivier, which has a flashing interval of 0.27 seconds (Case, 1980). The laboratory experiment they conducted used a

Canon EOS 5D digital camera with a Canon Zoom Lens 28–105mm (ISO 3200 equivalent, f.l. 50mm, f. 4.5, 0.5s) to take photos at a container with the size of

25×25×30cm.

For our study, P. pyralis has a flashing interval of 6-7 seconds (Case, 2004).

P.pennsylvanica has flashing intervals of various lengths (Emerson, 1935; Lloyd, 1969).

The flashing intervals I calculated using my direct field observation records showed that the P.pyralis specie had an actual flashing interval of 7.9 seconds, and the P. pennsylvanica specie had an actual flashing interval of 2.4 seconds. The exposure period

I used was 8 seconds. The size of land covered by my camera’s field of view is about

20×20×1m divided by 2.

To adopt the linear regression model from Kirton et al. (2011)’s study to estimate the population density of the two species of fireflies in our study, I followed the following steps:

- 92 - a) Reverse the original formula (1) to use image counts as the independent variable and use stocking density as the dependent variable:

P. tener Stocking density=6.25xImage count-7 (2)

b) Include a coefficient in formula (2) to standardize the size of land covered by each photo:

P. tener Fireflies per m2=100xImage count-112 (3)

c) Include a specie specific coefficient in formula (3) to standardize the ratio of flashing interval to exposure time:

P. tener Fireflies per m2=100xImage count-112 (4)

This coefficient for P. tener is 1 since Kirton et al. mentioned in their lab experiment that the fireflies were not moving in the confined container and two flashes were recorded as one on the images. In other words, each firefly could only be recorded once at most during the 0.5 second exposure time.

P. pyralis Fireflies per m2=99xImage count-111 (5)

This coefficient for P. pyralis is 0.99 since each P. pyralis can only flash 1.01 times during the 8 seconds of exposure time. 8 seconds was used because it is the longest possible time I could record with a camera. The earliest that a second flash would have been possible if it had flashed at the beginning would be after 7.9 seconds. Of course, there is some individual variation.

P. pennsylvanica Fireflies per m2=30xImage count-34 (6)

- 93 - This coefficient for P. pennsylvanica is 0.3 since each P. pennsylvanica can flash

3.33 times during the 8 seconds of exposure time. However, they can also flash less frequently.

d) Because the data I have for both P. Pyralis and P. pennsylvanica is in the format of number of flashes per photo per second. Another coefficient is needed before calculating the population densities:

P. pyralis Fireflies per m2=3.96xImage count-0.555 (7)

P. pennsylvanica Fireflies per m2=1.2xImage count-0.17 (8)

We can then use formula (7) and (8) to estimate the population density per m2 of

P. pyralis and P. pennsylvanica respectively. For example, the maximum count of P. pennsylvanica on the organic wheat field on July 30th, 2009 was 3.725 counts per photo, which gives us an estimated population density of 4.3 per m2, while the maximum count of P. pyralis on the organic field on July 9th, 2009 was 0.5125 counts per photo, which gives us an estimated population density of 1.475 per m2.

3.4. Discussion

LeBuhn et al. (2003) described a good invertebrate monitoring method as one that is simple, repeatable, and easy to incorporate into other concurrent research objectives.

In a preliminary study I conducted in 2008, part of the procedure involved caging the captured insects. Since the fireflies were sensitive to the environment, the longer they were kept in the insect cage, the more of them died. The mortality rate was positively correlated with the temperature during the day, which was important in the instances

- 94 - when I had to keep the insects in a cage for an additional day due to low population counts. However, if I just released the fireflies on the night of their capture, regardless of the total number of the marked individuals, a risk that none of the marked ones would be recaptured the next time would always exist, which would have made the calculation of the total population unsolvable, because of the zero in the equation. The mark and recapture method potentially could have a great impact on the natural firefly population, since part of the process required handling and keeping the fireflies away from their natural habitat, resulting in massive death and disturbance. I would suggest a less intrusive approach like marking and releasing the fireflies in the field to avoid removing the fireflies from their natural habitat for an extended period of time. A group of three persons with well-defined responsibilities should be able to perform the whole “capture- identify-mark-record-release” procedure in the field. Nevertheless, because this method depends on the skill of the firefly catcher, the results may be hard to standardize.

In contrast, the new timed sequential digital photographic method I developed can serve the same function of monitoring wild firefly populations while posing minimum impact on them. This new method is easy for a lay person to learn and conduct and the required equipment is affordable, if not readily available, for most people. With this new data collection method in hand, firefly researchers may have an easier time engaging citizens in firefly monitoring and conservation programs. This method can be applied to almost any kind of landscapes as long as the camera station can be set up. Since the data

- 95 - yielded can be easily standardized given the sizes of the plots and landscapes, different projects using this method can be compared across the country.

The number yielded by the digital photographic method has a unit of “flashes per photo per second,” which is similar to the “flash rate” concept proposed by Lloyd (2000) with some modifications. The original “flash rate” is the simple inverse of a firefly’s interflash interval in the units of flashes per second. The results of my study are different from the “flash rate” in two major ways. First, I’m measuring the total flashes of all the fireflies in a clearly defined area, while the “flash rate” is associated with an individual firefly. Second, my results were based on photos, while the “flash rate” was based on field observations.

A limitation of my new photographic method is that the flash pattern of

P.pennsylvannica may mimic that of other fireflies, in this case, P.pyralis, which may make my counts somewhat less accurate than the mark and recapture method (Lloyd,

1975; 1980; 1981; 1984). However, reduced firefly mortality and increased ease of observation may outweigh this limitation.

In this chapter, I introduced a new timed sequential digital photographic method for monitoring adult firefly populations. The method was used to examine the flashing activities of two firefly species P. pennsylvanica and P. pyralis and was proved to be able to reflect the same general trend of the firefly population changeover the night. In addition, this new method can also reflect the different scales of the two firefly species’ flashing activity, as described in Chapter 5. Traditional insect population estimation

- 96 - methods such as mark and recapture involve catching and keeping fireflies, which tends to interrupt the population and add mortality, while the new method is not as intrusive since it does not require physical contact with the fireflies. This new method is also simple to learn and only requires the observer to have a digital camera. Such minimum requirements are valuable to citizen scientists who cannot afford expensive equipment.

For various environmental organizations, introducing this simple method to their members may increase their participation rate by making the volunteers feel more involved with scientific research.

- 97 -

CHAPTER 4

LANDSCAPE STUDY ON COMPARING FIREFLY FLASHING ACTIVITIES

IN CONVENTIONAL AND ORGANIC FIELDS

4.1. Introduction

Since fireflies are named for their ability to flash using bioluminescence, naturally most firefly researchers have focused on bioluminescence (Bartholinus, 1643; Boyle,

1671; Lloyd, 1968; Wet, 1985; Gould, 1988; Ford, 1995). However, few studies exist on the relationship between fireflies and the natural environment. In this chapter, I used the timed sequential digital photographic method described in chapter 3 to conduct a landscape ecology study on two commonly found fireflies (Photuris. pennsylvanica and

Photinus pyralis) at the West Badger Farm in Wooster, OH. I tested three hypotheses with this experiment: first, firefly activities are associated with climatic factors such as temperature, humidity, and landscape type; second, farming practices (organic farming vs. conventional farming) are associated with firefly flashing activity; and third, the two firefly species have similar responses to the climatic factors and landscape types at West

Badger Farm.

The lack of firefly behavioral and ecological studies in the US is notable. In addition, some discrepancy between the major thrust of scientific research

- 98 - (bioluminescence) and how local people perceive fireflies seems to be present. Most scientific research has focused on the genetic, protein, and biochemical reaction aspects of bioluminescence, while citizens tend to associate fireflies with good environmental quality. The science of fireflies seems to have different foci internationally. In Japan, several researchers (Kazama et al., 2007; Takeda, Amano, Katoh, & Higuchi, 2006) have conducted studies on the relationship between fireflies and their habitats because of the great public interest in fireflies within that society.

Little research has been done on the relationship between fireflies and their habitats in North America. In the past, entomologists such as Lloyd (1966, 1968, 1969,

1975, 1978, 1980, 1981, 1984a, 1984b, 1984c, 1990a, 1990b, 2001, 2003, 2006), who have studied fireflies, have noted what seemed to be a positive correlation between firefly populations and the quality of their habitats. Most of the fireflies Lloyd studied preferred humid and warm climates with natural vegetation and few human activities. Richard

Moore, Benjamin Stinner, and Marc Branham conducted preliminary research in 1995 trying to locate a preferred larval stage habitat and shifting field locations of adults

(personal communication). However, after careful examination of the related literature, similar to literature searches done by Moore and Stinner (personal communication), I failed to find any formal study focusing on the relationship between fireflies and landscape types. The closest research I came across was Edmunds’ (1963) study on the relationship between temperature and firefly flashing intervals, Kazama et al.’s (2007) study using Geographical Information System (GIS) and hydrological simulation to

- 99 - investigate habitats suitable for fireflies, and Iguchi’s (2009) study on the impact of introduced populations on native populations.

The later two studies were conducted in Japan where the fireflies are aquatic, as compared to the terrestrial species in North America. Lloyd just mentioned his observation, not supported by data. Thus empirical evidence supporting a positive correlation between firefly abundance and particular types of landscape is lacking, although Moore videotaped adult abundance in different fields on Amish farms in

Holmes County. If one can confirm a positive correlation between firefly abundance and certain landscapes such as organic fields then local citizens in conservation programs could use fireflies as a flagship species in citizen science studies.

Fireflies may be useful as flagship species in rural areas where they occur. As mentioned in chapter 1, in the North Fork Subwatershed of the Sugar Creek Watershed fireflies were ranked fourth in terms of perceived association with good environment quality by the local farmers. Knowing citizens’ views of fireflies is important because knowing people’s preferences for certain species is useful in planning conservation education programs. The idea of flagship species not only focuses on such species’ ecological functions in the ecosystem, but also the attractiveness and distinctness of the species (Bowen-Johns, & Entwistle, 2002; Roberge & Angelstam, 2004; Ozaki et al.,

2006). Samways et al. (1995, p. 491) defined flagship species as “known charismatic species that serve as a symbol or focus point to raise environmental consciousness.”

Since a typical ecosystem usually contains many species that interact with each other on

- 100 - multiple levels, picking a few species that can easily draw attention from the public is an effective and manageable strategy. Examples of flagship species include the giant panda from China and the Africa elephant (Kontoleon & Swanson, 2003; Stephenson &

Ntiamoa-Baidu, 2010). A flagship species may not necessarily be an indicator species or keystone species, both of which are used to indicate particular qualities within their environment (Davic, 2003; Robert, 2003; Groom et al., 2006; Moore, 2010). While ecologists’ and biologists’ studying the roles of indicator species and keystone species is important for the scientific understanding of ecological structure and function, the exotic, beautiful, or interesting flagship species are critical for rallying support from the public

(Roberge & Angelstam, 2004; Cunningham & Cunningham, 2009).

4.2. Methods

Data were collected using the timed sequential digital photographic method described in chapter 3. Kirton et al. (2011) documented that in a laboratory test there was a linear relationship and high correlation between stocking density and manual counts of bright spots in images using the digital photographic method.

My experiment was conducted on the West Badger Farm, located to the southeast of the city of Wooster and the main campus of Ohio Agriculture Research and

Development Center (OARDC), to the north of Apple Creek, on Apple Creek Road. The

OSU Organic Program has set up their experiments with mixed parcels of conventional and organic crops on the north side of the West Badger Farm. Their research has focused

- 101 - on the effect of organic farming on the yield of different crops

(http://extension.osu.edu/~news/story.php?id=3510).

Of the seven plots in my study area (see Figure 13), I collected data from six. On the edge of the West Badger Farm, right next to the Apple Creek Road was a native prairie which used to be the dominant natural landscape in this area before agricultural development. A narrow grass buffer zone was present between the plot and the road.

Next to the native prairie was a plot of mixed hay and clover, a common crop for dairy farmers in this area. This particular plot was harvested 2-3 times during the firefly season. The other landscape types were oats field, wheat field and soybean field, all common crops in this area. The hay/clover plot, oats plot and the wheat plots were organic fields that received no tillage, chemical fertilizers, pesticides or herbicides. On the other two fields (wheat and soybean), conventional farming practices were used. The cluster originally was set up to include an organic corn field as well. However, I excluded this plot from the study because in that particular year the corn planting had been delayed until well after my research had begun. As a result, when the firefly study started the corn plot was still barren. Since there was no vegetation on the field, this plot was incomparable to all the other fields which already had been covered by crops. In addition to the effect of different farming practices and landscape types, this study also investigated the firefly flashing activity’s change over time. I needed to compromise between sampling a diverse universe of landscape types and sampling each type frequently, so I decided to sample each of the six landscape types once per week in a

- 102 - regular rotation. The weekly population survey method has been used by other researchers such as Yuma (2007) and Forest & Eubanks (1994) with a demonstrated minimal change in firefly population density during a week. A typical sampling rotation sequence was organic hay, organic wheat, conventional wheat, conventional soybeans, organic oats, and native prairie.

Figure 13. The different landscape types in the West Badger Farm in Wooster, OH.

To test the association of climatic factors with firefly flashing activity, I used weather information of the local area recorded by the OSU weather station located on the campus of OARDC (http://www.oardc.ohio-state.edu/newweather/hourlyinfo.asp?id=1).

This dataset included date, time, precipitation, air temperature, solar radiation, humidity,

- 103 - 5 cm soil temperature, 10 cm soil temperature, scalar wind speed, wind direction, and the standard deviation of the wind direction. Each parameter was measured every 5 minutes.

Because of the different time scales between the weather dataset and the firefly datasets I collected, I reformatted the firefly data into data points five minutes apart. In addition, because the firefly

Figure 14. Correlation between 5cm soil temperature and air temperature. Note: weather data downloaded from the weather station (http://www.oardc.ohio- state.edu/newweather/stationinfo.asp?id=1).

data were collected every day after sunset when the weather permitted, solar radiation and precipitation measurements were not directly relevant to the firefly activity, so I

- 104 - excluded these factors from the analysis. Furthermore, air temperature, 5 cm soil temperature, and 10 cm soil temperature have a high correlation, thus I only investigated the relationship between fireflies and one of the three temperature parameters, 5 cm soil temperature. Figure 14 shows that the air temperature and 5cm soil temperature at West badger Farm are highly correlated with each other.

4.3. Results

The main results on this study were as follows: Climatic factors (wind speed, humidity, and temperature) do not seem to have a linear correlation with firefly flashing activities. Although firefly flashing activity seemed to peak around 23 °C, the differences among all the crop landscape types were so small that the influences of all climatic factors were not considered when comparing the landscape types. Firefly flashing activity on different landscape types suggested a trend of increase from conventional farming to organic farming to native prairie. In addition, crop management practices such as harvesting and herbicide application appear to have certain association with changes in firefly flashing activities. The two different species of fireflies responded similarly to the climatic factors but not to the landscape types.

4.3.1. Association of climatic factors with firefly flashing activity

When considering the climatic factors’ correlation with firefly flashing activity, I focused on three particular climatic factors: wind speed, humidity, and 5cm soil temperature. The results are shown in Figure 15. Since P. pennsylvanica and P. pyralis are two different species, their responses to the three climatic factors may or may not be

- 105 - the same. However, that comparison will be discussed in the third part of the results. I focused on P. pennsylvanica in the figures for the first and second parts of the results for the sake of simplicity.

After grouping the data points for the two different species together, I first investigated the potential associations of wind speed, humidity, and 5 cm soil temperature on the flashing density for the two species (see Figure 15). Wind speed did not seem to have a significant association with either species’ flashing performance. However, since no data for a high wind event were present, one cannot draw conclusions about what fireflies’ flashing activity might be under such conditions. Fireflies are not very good flyers; they may not be able to take off when the wind is too strong. With the current data, one may conclude, however, that when the wind is less than 6 m/s, fireflies did not change their flashing patterns due to wind speed.

For humidity, although both firefly species maintained a fairly stable flashing density across the range of humidity that the weather station had measured, the higher flash density only appeared when the humidity was relatively high (> 80%). However, the difference in flashing activity between low humidity and high humidity conditions was relatively small. As for the current study, one may conclude that within this particular range of humidity, there was no significant variance among firefly activities.

In looking at the 5cm soil temperature and the firefly flash density, one can see that apparently flashing activity for both species of fireflies peaked around 23 °C.

- 106 -

Figure 15. P. pennsylvanica flashes per second per photo change over several climatic factors.

- 107 - To draw better conclusions about the association of 5 cm soil temperature and firefly flashing activity, we needed to compare the average temperature of each landscape group, as discussed in the next section. In summary, my first hypothesis, that firefly activities are associated with climatic factors such as temperature, has been confirmed; however, within the range of available data, firefly activity did not appear to be associated with wind speed, and humidity.

4.3.2. The association of farming practices on firefly flashing activity

Since the 5cm soil temperature is the only factor that seemed to have a correlation with differences in the firefly flashing frequency, when investigating the differences among the landscape types, I singled out 5 cm soil temperature to see if any correlation existed between the soil temperature and the different plots. One way to study this was to average the daily temperatures for each plot as shown in Figure 16.

From Figure 16 one can see that the 5cm soil temperatures of all six different landscape types are not significantly different from each other in terms of their averages and standard deviations. As mentioned earlier, fireflies’ flashing activity is correlated with the soil temperature. However, the fireflies’ flashing activity may not be solely associated with soil temperature. The fireflies’ flashing activities followed the change of the soil temperature, but only to the point of a general trend of going up and down. Since the differences among the relative heights of the peaks may be associated with some other factors, I compared the influence of the landscape types alone on the firefly flashing activity.

- 108 -

Figure 16. Average 5cm soil temperature (°C) of different parcels with standard deviations.

After converting all the data into the desired format, I first made some initial figures to see if there was any significant variation among the different landscape types in term of firefly activity (see Figure 17). Since data points with value of zero will make the means very low, I plotted the medians instead. The figure shows that the native prairie landscape plot had the highest upper quartile (more flashes on this field) and the organic fields, except for the organic wheat, had higher upper quartiles than the conventional fields. The R program calculated the outliers as shown in the figure.

- 109 -

Flashes per second per photo second per Flashes

Figure 17. Box plot of P. pennsylvanica flash density among different landscapes. The black lines in the middle of the boxes represent the medians of all the data points. The upper and lower boundaries of the boxes show the75% (upper quartile) and 25% (lower quartile) of the data sets. The small circles on the top of the boxes are potential outliers, which were not included in the data when calculating the 25% and 75% boundaries.

- 110 - In order to further investigate the potential relationship between firefly flash density and the landscape types, I plotted the firefly flash density (flashes per second per photo) of each day for each different landscape type, as shown in Figure 18. Readers should keep in mind that, the main thing to focus on is the overall patterns of the firefly flash density on each individual field. The scale change from one plot to another should not be ignored, since the peak on one field may represent 1000 flashes and the peak on another field may represent 100 flashes. Such scale difference is especially important when considering the reasons behind the apparent differences among the landscapes.

When looking at Figure 18, one can see two common features across the six different landscape types: first, the firefly flash activity reached the low point around the first week of July; second, the firefly flash activity reached the high point during the last week of July or the first week of August. My original hypothesis was that firefly activity would follow a normal distribution with the peak activity in the middle of the firefly season (mid July). When considering the sudden drop of firefly activity in the first week of July, I looked back at the other events that happened during the same period for a possible explanation. During the 2009 firefly season when the data were collected in the field, certain events took place that may have some impact on the plots and firefly activities. These events are listed in Table 17 to help interpret the change of the firefly flashing activity in the data set.

- 111 -

Figure 18. P. pennsylvanica flashes per second per photo change with date on different landscapes. Boxes represent events during the firefly season.

- 112 -

Table 17. Farming practices that may have had an important impact on the landscapes of the selected plots in the West Badger Farm where the firefly data was collected during the firefly season of 2009.

Date Plot Event 21 Jun 2009to Organic hay (OH) Straw removed from the 27 Jun 2009 field. 05 Jul 2009to Conventional soybean (CS) and Sprayed using herbicide. 11 Jul 2009 Conventional Wheat (CW) 26 Jul 2009to Conventional wheat (CW), Organic wheat Crop was harvested. 01 Aug 2009 (OW) , and Organic hay (OH) 23 Aug2009to Organic wheat (OW) Soil was tilled. 29 Aug 2009

The first event happened during 21 Jun 2009 to27 Jun 2009. Straw was removed from the organic hay field, and right after the event, P. pennsylvanica flashing activity decreased. The second event happened during 05 Jul 2009 to11 Jul 2009. After the conventional soybean field was sprayed with the herbicide Roundup, firefly flashing activity dropped sharply; there is a good chance that the shifting of the firefly activities was influenced by the chemicals. Whether the firefly flashing activity was reduced because of emigration caused by land cover removal (killing of the weeds) or firefly flashing activity was a result of death due to direct poisoning was unclear, but no pesticides were combined with the Roundup (Cox, 1998). The third event happened during 26 Jul 2009 to 01 Aug 2009. Three plots (organic wheat, conventional wheat, and organic hay) were harvested; an immediate decrease in the P. pennsylvanica fireflies’ flashing activity followed the harvests. I suspected that as these crops providing firefly - 113 - habitat were removed, fireflies would move to adjacent field which still had land covers.

To confirm this hypothesis, I took a chronological approach and examined the data from the organic wheat and native prairie parcels. One can see the firefly activities on these two fields peaked later than the three fields that were harvested. Although soil was tilled in the organic wheat field on 27 Aug 2009, at this time most fireflies had already died out since the end of August was very close to the end of the firefly season.

The analysis above was based on the relative firefly activity peaks on different landscape types throughout the firefly season. This kind of analysis is particularly useful when the purpose is to see the effect of the different events on the movements of the firefly flashing activity among the fields. However, because the absolute flashing activity densities were not necessarily the same for each peak shown in the figures, one must go back to the figures for each individual plot to find out how landscape was correlated with absolute flashing activity density.

Among all the six different landscapes, there was one conventional wheat field and one organic wheat field. Since the only difference between these two plots was the farming practice (conventional vs. organic), they were ideal for the comparison. P. pennsylvanica fireflies’ activities peaked at about the same time on both the conventional and organic field. However, the difference between the heights of the peaks on these two plots was huge. The flashing density on the organic field at peak (0.79 flashes per second per photo) was much higher than that on the conventional plot at peak (0.15 flashes per

- 114 - second per photo). After the harvest event, both plots’ firefly activities seemed to drop down to a minimum level.

Next, I compared the only two conventionally farmed crops included in the study, namely, the conventional soybean and conventional wheat fields. As mentioned in the last comparison, since these two fields are right next to each other, the chances that fireflies would migrate from one plot to the other during the firefly season were good.

The trends of the firefly activities were similar to each other on the two conventional fields. After the herbicide spraying event, the P. pennsylvanica flashing activity on the conventional soybean field dropped down to near zero and the P. pennsylvanica flashing activity on the conventional wheat field started to peak. Right after the wheat was harvested from the conventional wheat field, the flashing activity on the conventional field dropped to near 0 and the flashing activity on the conventional soybean field peaked.

On the edge of West Badger Farm is a patch of native prairie that has been preserved for research purposes since 2000. Native prairie used to be an important landscape type along with woods and forestry before the early settlers converted the land into the agricultural landscape one sees there today. Presumably native prairie was a key natural habitat of the fireflies, although this assumption is hard to test, since few areas of native prairie exist today in this part of Ohio. Using native prairie as a control landscape type makes sense in all ecosystem research in Ohio. The native prairie patch on the West

Badger Farm contains a variety of tall grasses and has been mowed yearly to prevent it

- 115 - from evolving into woodland. My hypothesis is that when the vegetation is in such an ideal state of biological system complexity with indigenous plants, the firefly flashing density will be the highest in this native prairie plot compared to all the other agricultural landscape types. For the sake of simplification, this study compared the native prairie plot with the organic hay/clover plot, which I considered having a similar landscape. The most meaningful finding from the comparison of native prairie with the organic hay plot is that I have confirmed that the timing of peaks of firefly flashing activity on native prairie and organic hay were similar, although the height of the peak on native prairie

(0.31 flashes per second per photo) was much higher than that of the peak on organic hay

(0.19 flashes per second per photo). In summary, my second hypothesis, that farming practices (organic vs. conventional) will have significant correlation with firefly flashing activity, has been confirmed. Of course, someone could say that perhaps it was because the fireflies were attracted to the insects on these plants rather than the plants themselves.

4.3.3. Comparison P. pennsylvanica and P. pyralis in terms of their responses to the environment

P. pyralis and P. pennsylvanica are two firefly species commonly found in Ohio.

As I would argue in chapter 5, the two species are similar in terms of their peak activity time but a big difference in their population sizes exists. In this section, I further compare the two species’ flashing activities on the different landscape plots. This comparison is meaningful because although the two species may have similar responses to the light conditions (the change from daylight to twilight to dark) and time (both time

- 116 - in one day and throughout the season), they may still have different responses to the landscapes. I will outline P. pyralis in a similar logic to what I have explained for P. pennsylvanica.

First, Figure 19 shows the correlation of climatic factors on the P. pyralis firefly’s activity. The results are that the climatic factors’ associations with P. pyralis’ flashing activity are similar to those of P. pennsylvanica. The trends in all three cases of P. pyralis shown in Figure 19 were similar to the case of P. pennsylvanica shown in Figure

15; however the flashing activity peak of P. pyralis (0.086 flashes per second per photo) is about one-fourth that of P. pennsylvanica (0.36 flashes per second per photo).

Next, Figure 20 shows the flashing activity density of P. pyralis as box plots for the six landscapes. There are important differences in the firefly activity between P. pennsylvanica and P. pyralis among the six different landscape types. At the first look, the two species of fireflies show very distinct patterns among the landscapes. While P. pennsylvanica species has the lowest density in the wheat field (both organic and conventional) as shown in Figure 17, the P. pyralis species has the highest density instead in Figure 20. The box plots also show that farming practice (organic vs. conventional) has a larger impact on the P. pyralis flashing activity than on the P. pennsylvanica flashing activity.

- 117 -

Figure 19. P. pyralis flashes per second per photo change over climatic factors.

- 118 -

Flashes per second per photo second per Flashes

Figure 20. Boxplot of P. pyralis flash density change among different landscapes. The black lines in the middle of the boxes represent the medians of all the data points. The upper and lower boundaries of the boxes show the75% (upper quartile) and 25% (lower quartile) of the data sets. The small circles on the top of the boxes are potential outliers, which were not included in the data when calculating the 25% and 75% boundaries

- 119 - Finally, I plotted the flashing activities of both species together on each of the six plots (Figure 21). After comparing the flash activities of these two firefly species on different landscapes, I found that except for the two conventional fields, the peak activity of P. pennsylvanica always follows the peak activity of P. pyralis. Moore (personal communication) suggested that this phenomenon might be due to the fact that P. pennsylvanica may prey on P. pyralis. So when the population of P. pyralis peaked on one field, P. pennsylvanica followed P. pyralis to that field. As a result of the predation, the P. pyralis population decreased. I suggest the reason why there was no such phenomenon on the two conventional fields is due to the application of herbicide on them.

In summary, the two firefly species’ flashing activities have similar correlations with the three climatic factors, but their flashing activities were quite different on each landscape type. As a general trend, P.pyralis usually peaked earlier than

P.pennsylvanica, but the absolute value of P.pennsylvanica’s flashing activity peak was much higher than that of P.pyralis.

- 120 -

Figure 21. Comparison of P. pyralis and P. pennsylvanica flashes per second per photo on different landscapes. Dashed line represents P. pyralis and solid line represents P. pennsylvanica.

- 121 - 4.4. Discussion

The first hypothesis of this study, that firefly activities are associated with climatic factors, such as temperature, has been confirmed; however, firefly activity does not appear to be associated with wind speed or to vary significantly with humidity. The second hypothesis, that farming practices (organic vs. conventional) have a significant correlation with firefly flashing activity, has been confirmed. With respect to the third hypothesis, that P. pennsylvanica and P. pyralis have similar responses to the climatic factors and landscape types at West Badger Farm, I found that the two firefly species’ flashing activities have similar correlations with the three climatic factors, but their flashing activities were quite different on each landscape type.

Although some of the results of this study confirm prior research, most of the conclusions are new. The association of firefly flashing activities with temperature confirms the previous observations made by other researchers (Edmund, 1962). This study contributed the new information that firefly flashing activity varies with agricultural landscape type and that farming practices such as herbicide application and harvesting are associated with decreased firefly flashing activity. Another new finding is the differences among flashing activities of P. pennsylvanica and P. pyralis on a given landscape type.

4.4.1. Limitations and suggestions for further research

There are several limitations to this study that suggest the need for further research. First, in this study, I found a relationship between firefly flashing activity and

- 122 - different crop types, which may indicate that fireflies are sensitive to the particular type of crops. However, since my study was done on small plots located quite close to each other, more research on larger plots more isolated from each other is needed to solidify this conclusion. In addition, because I could not afford to sample different landscape types far apart from each other, I could not eliminate the effect of migration from plot to plot.

Second, while I worked hard to separate out the effects of climatic factors from landscape types, in the real world collecting data on all the climatic factors at sites where the firefly data were collected was impossible. I did not investigate the association of climatic factors such as soil type, nearby man-made infrastructures, or the plots’ distance from water sources. In addition, firefly flashing activity may be a result of complicated interactions between fireflies and climatic factors, not just the factors studied one at a time.

Third, I concluded that at low wind speeds, fireflies do not change their flashing patterns due to wind speed. Such a statement may not hold true in other areas where the wind speed is much faster than Ohio or in much windier weather than what the fireflies I studied were subjected to.

Fourth, the study was limited in that my collection of data on each plot occurred only once a week and different plots were measured on different days of the week. Since

I collected data on different plots on different days, one needs to assume that the climatic

- 123 - factors did not follow a weekly pattern. Ideally observations of the plots should be made more frequently and all on the same day.

4.4.2. Implications for agricultural monitoring and citizen science

As more farmers switch to organic farming either in respond to the consumer demand for healthier food or to conserve the natural habitat, having an easy way to monitor their progress in terms of converting from conventional farming to organic would be helpful. In the particular area where this study was conducted, fireflies are fairly common and familiar to local people. Results of my study suggest that fireflies have potential for a new role as organic farming indicators. The results of my study suggest that the presence and frequency of firefly flashing activity may be a good indicator of agricultural practices and thus, good to use for monitoring agricultural landscapes.

Flashing activity as a method to monitor and compare the quality and status of various landscape types has great potential. The results from this research, however, are preliminary due to limited data. I have made every effort to keep the resource requirements for conducting such research as low as possible, so few barriers should exist that would prevent interested citizen scientists such as farmers or school classes from adopting my methods. Nevertheless, the right attitude toward rigor in scientific research and persistency is still essential for these methods to yield quality data. Easy and sensitive methods are needed by all kinds of entities ranging from regulatory agencies to environmental enthusiasts, and from grass root conservation groups to responsible

- 124 - farmers. Depending on the specific aims one would like to focus on, future experiments can be designed to tackle only one variable at a time to eliminate other factors' interference. Since all the data can be collected in a photographic format, all individual research data (which are very likely to be at a small local scale) can be combined into a database by users contributing data online to a central database. Maintenance of such an ongoing database made possible by Web 2.0 and used by all interested parties to study the ecosystems at a regional or even global level will result in more credible conclusions from firefly studies.

- 125 -

CHAPTER 5

A REEXAMINATION OF THE CONCEPT OF EARLY-ACTIVE VS. LATE-

ACTIVE BY COMPARING THE PEAK PERIODS OF BIOLUMINESCENT

FLASHING ACTIVITY OF FIREFLIES Photinus pyralis AND Photuris

pennsylvanica (Coleoptera: Lampyridae)

5.1. Introduction

That the flashing patterns and light color emitted by different firefly species are different is a well-established observation. According to Lloyd (2003), fireflies in North

America can be separated into two groups according to the time when their flashing activity starts during the night (Lall et al., 1980). Early flashers who start their flashing activity within 30 min after sunset are called early-active species while late flashers who start their flashing activity later at night are called late-active species. This difference between early-active and late-active species has been the basis of a number of studies focusing on the relationship between firefly activity periods and the spectral distribution of their light (Lall et al., 1988; Seliger, Buck, Fastie, & McElory, 1964; Hamman &

Seliger, 1982). The published studies seem to confirm a correlation between longer wavelength (yellow light) and early-active species. However, after comparing the data collected on several plots throughout the flashing period (see Chapter 4) using the timed

- 126 - sequential digital photographic method, I found no significant difference between the starting time of P. pyralis (emitting yellow light) and P. pennsylvanica (emitting green light). In this chapter, I challenge the traditional early-active/late-active classification system based on prior researchers’ field observations. Specifically I tested the commonly accepted hypothesis that P. pyralis is an early-active species and P. pennsylvanica is a late-active species.

I found two main species in the field where the experiment was conducted (West

Badger Farm, OARDC, Wayne County, Ohio) and identified them according to several insect identification books and websites as P. pyralis and one species belong to Photuris complex. According to the Bug Guide website (http://bugguide.net/node/view/63819), P. pyralis is described as

10-14mm long, Large for a Photinus. Blackish-brown finely, densely rugose (wrinkled) elytra, side margins and suture of elytra yellow. Pronotal disk pinkish with a black spot. Pronotum convex. Underside: Ventral abdominal segments six and seven large and occupied by light organ in male. Abdominal sternites of male have distinct. Female flightless, or “seldom” flies, as it does have normal wings. Flash is distinctive: male hovers about 0.6m (2 feet) above ground, then drops vertically, gives single prolonged flash as is ascending, then flash diminishes. Flashing occurs at dusk, earlier in evening than most other fireflies.

Photuris species, on the other hand, are quite different. Williams (1917) described the morphological features of P. pennsylvanica as follows:

The adult beetle is elongate and rather flattened; the head is somewhat retracted under the prothorax, the antennae eleven jointed, slender and tapering, and the eyes large. The thorax has the disc convex, with broad thin margins, and is rounded anteriorly and along the sides and subtruncate posteriorly. The legs are slender, the outer tarsal claw is bifid; the elytra are rather acute at the tip and extend well beyond the extremity of the abdomen. The general color of the head is dull yellow, with a black area on the posterior part of the vertex. The pronotum

- 127 - is dull yellow with the disc red and a median black stripe, while the rest of the thorax is very dark brown. The legs are paler at the base of the joints and at the apex of the femora, while the elytra are brown or piceous, with the suture, side margins, and a narrow tapering stripe on the disc, pale brownish. The abdomen is blackish brown with the posterior border of the fifth and all of the remaining sternites, yellowish. The luminous organs are-yellowish and are situated on the sixth and seventh sternites. They are larger in the male. The body is clothed with fairly abundant yellowish pile, which is darker on the legs and most conspicuous dorsally. The pronotum and the elytra are densely and rather coarsely punctate. The length varies from II to I5 mm.

However, identifying the particular species of Photuris is extremely difficult because hardly any morphological differences exist among species. P. pennsylvanica has been thought to be the only Photuris species in this area, although this belief has been criticized as a “malpractice” (Lloyd, 1984b, p.368). Generally, Photuris can be separated into two groups: Photuris congener group, which seems not to prey on other species such as Photinus and has sometimes been misclassified in the Photinus genus. This congener group contains Photuris frontalis, Photuris divisa, and Photuris brunnipennis in the U.S., and other species in Latin America. Most of the other group (P. pennsylvanica-versicolor group) is predacious. However, instead of using aggressive mimicry to lure their prey, some species in the P. pennsylvanica-versicolor group may become scavengers or may catch other insects on weed seed heads (Lloyd, 1984b). Both the larvae and adults of P. pennsylvanica are predacious. The larvae are not picky about the type of food they eat: they apparently will eat any soft bodied worms in their paths. In the lab they were found to eat dog food and dead worms. That they may scavenge on dead animals such as birds and mammals in the wild is suspected (McLean et al., 1972; Lynch, 2000).The P. pennsylvanica success rate of predation in the field, however, is rather low. According to

- 128 - Lloyd (1975)’s observation, this might be due to the fact that the Photuris populations usually exceed those of contemporaneous, synoptic Photinus and Pyractomena. I have seen Photuris females eat both Photinus and Photuris males when they were confined in a cage, but I haven’t seen such phenomena in the field.

Researchers have relied heavily on the different flashing patterns of the fireflies for taxonomic purposes. Photuris species, however, make the use of flashing patterns for identification very frustrating since this group of fireflies can mimic other species’ flash patterns and change their own flashing patterns throughout the night. Lloyd (1975) has proposed that the female fireflies of Photuris species use mimicry technology to lure other species’ males for food. However, the males of the P. pennsylvanica-versicolor species complex have also been found to mimic other species’ male’s flashes (Lloyd,

1980). The reason for such phenomena is unclear (Lloyd, 1980). Though Lloyd (1980) has hypothesized that the males are trying to increase their chances of getting noticed by their own females. Regardless the reason behind the mimicry, any attempt to use flashing patterns to distinguish Photuris species individuals, either male or female, has failed.

Seliger & McElroy (1960, 1961, and 1964) measured the light spectra of 20 different firefly species in vitro using photoelectric recording spectrometry. Their experiment showed that green emission of P. pennsylvanica was produced when combining P. pennsylvanica luciferase with P. pyralis luciferin and yellow-green emission of P. pyralis was produced when combining P. pyralis luciferase with P.

- 129 - pennsylvanica luciferin. They concluded that the species specific enzyme is responsible for the variations in the emitted light.

In this chapter, I will present flashing activity data of two different firefly species and compare the results with my field observations. The comparison suggests that the seemingly different starts of flashing times for P. pyralis and P. pennsylvanica firefly species may be a misperception caused by relative population sizes and by human eye sensitivity shifts when the light conditions change.

5.2. Method

A Nikon Coolpix p6000 digital camera was used to take photos of the plots in this study. Each photo has a resolution of 1024x768 pixels and covers one single plot. Most of the photos were taken during the period of time from right after sunset until almost midnight, at which time the battery usually run out of charge. This period roughly lasts about 2 hours. I took a photo every 30 seconds; each photo has an exposure time of 8 seconds, which is the longest exposure time the camera can handle. Dividing the period of time by the rate of photo taking, on average there were 200-300 photos produced every night. After finishing the photo-taking process in the field every night, all the photos in the camera were downloaded into the office computer and cataloged according to the date and type of crop on the particular plot. For more details on the methods, see Chapter 3.

The entire data collection stage of the project lasted from mid-Jun. to the end of

Aug. After finishing the field work, I examined all the photos and analyzed each photo by comparing photos taken immediately before and after each other, to distinguish any

- 130 - differences between firefly flashes. During this process, other interference such as household lights and reflection from the vegetation were eliminated. I then counted firefly flashes on every photo and recorded them into an excel worksheet. Since there were two species of fireflies in this area, their two types of flashing patterns captured by the photos were recorded separately. P. pyralis’s flash lasts longer and tends to form a

“J” shaped line on the photo, while P. pennsylvanica’s flashes were fast and short, leaving a dot on the photo.

5.3. Results

Figure 22 shows the relative frequency of P. pyralis and P. pennsylvanica flashes over time, beginning at civil twilight. One can see that these two species have very high correlation with each other in terms of their flash density patterns over time. The main difference one can see is the scale. P. pennsylvanica flash densities were consistently higher than P. pyralis flash densities, indicating that the total population of P. pennsylvanica was much greater than the total population of P. pyralis. The data collected show very similar flash patterns for both species, thus disproving the commonly accepted hypothesis that P. pyralis is an early-active species and P. pennsylvanica is a late-active species.

- 131 -

Figure 22. Firefly flash density change over time during the night.

5.4. Discussion

Previous studies and observations suggested that P. pyralis is an early-active species that reaches its peak activity around sunset and then gives way to the P. pennsylvanica species (the late-active) (Lloyd, 1966). However, our results showed a different story. Traditionally, most data on fireflies collected by researchers in the field have come from observations made by using the naked eye. Other instruments, like the count wheel and the flash light, are commonly used to aid the observer. Although human eyes are capable of distinguishing firefly flashes in the dark, there are still some limitations that may hinder discoveries about fireflies’ habits and behaviors.

The typical human eye can see the visible spectrum range from 380 to 750nm (as shown in Figure 23) and reaches the maximum sensitivity around 555nm (Starr, Evers, &

- 132 - Starr, 2008). Specifically, when the intensity of light is low, human eyes will adapt to the dark environment and shift the maximum sensitivity to around 507nm because of the different properties possessed by the cone cells and rod cells in the human eye. The cone cells are the ones that are responsible for color vision and they do not function very well under low light conditions. As a result, night vision relies mainly on rod cells, which do not discriminate among colors. Also, when looking at things, human eyes tend to move rapidly to bring the most interesting objects into the center of the field of view, which has the highest resolution (Schutz, Braun, Gegenfurtner, & Kerzel, 2008). Because of complex eye-brain coordination, sometimes humans construct a whole picture with partial information (Krantz, 2008). When looking at a scenario, our visual attention tends to move from a broad range (less focused mode) to a narrow range (more focused mode).

As a result, the sensitivity of our attention is constantly changing. Such a dynamic adjustment is a great advantage of human eyes since it can help us recognize the changes in our surroundings and selectively pay more attention to the things that interest us the most. However, when one is trying to faithfully record environmental detail at twilight and in the dark, human sight mechanisms present a challenge for repeatable data collection (Erikson, 1985; Lall et al., 1980). The single most important problem associated with using human eyes as the detection equipment is there is no easy way to double check the reliability of each individual observation.

- 133 -

Figure 23. Graph of photonic luminosity function (black) including CIE 1931 (solid), Judd-Vos modified (dashed), and Sharpe, Stockman, Jagla & Jägle 2005 (dotted); and scotopic luminosity function, CIE 1951 (gray). (http://en.wikipedia.org/wiki/File:Luminosity.png)

After reviewing the photographic record, I would argue that the traditional early- active/late-active dichotomy way to separate flashing fireflies into taxonomic groups might be a false perception caused by the special features of the human eyes, assuming that the duration and intensity of the flash are not related. Even though the so called early-active P. pyralis fireflies were less active late in the night, their activity never ceased completely. The seemingly overwhelming P. pennsylvanica fireflies simply masked the P. pyralis flashes for the human eyes to distinguish in the field. Also the human eye’s maximum sensitivity may change according to the light conditions so one just can’t see the yellow-green light of P. pyralis as well as the green light P. pennsylvanica in the dark. Future studies will be needed to confirm these results by

- 134 - investigating firefly flashing activities of other mixed populations of both supposedly early-active and late-active firefly species in other places to see if they are active at the same period.

- 135 -

References

Airth, R. L, Foerster, GE, &Behrens, PQ. (1966). The luminous fungi. In: Johnson FH, Haneda Y (eds) Bioluminescence in progress. Princeton University Press, Princeton, pp 203-223.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes 50:179-211.

Allen, A. (2003). Environmental planning and management of the peri-urban interface: Perspectives on an emerging field. Environment and Urbanization, 15, 1, 135.

Bagozzi, R. P., & Warshaw, P. R. (1990). Trying to consume. Journal of Consumer Research, 17, 127–140.

Ballard, H., Pilz, D., Jones, E.T., & Getz, C. (2005). Training Curriculum for Scientists and Managers: Broadening Participation in Biological Monitoring. Corvalis, OR: Institute for Culture and Ecology.

Bamberg, S. (2003). How does environmental concern influence specific environmentally related behaviors? A new answer to an old question. Journal of Environmental Psychology. 23 p. 21–32.

Barber, H. S. (1951). North American fireflies of the genus Photuris. Smith- son. Misc. Collect. 117: 1-58.

Baretto, C., Fastovsky, D. & Sheehan, P. (2003). A Model for Integrating the Public into Scientific Research. Journal of Geoscience Education. 50 (1). 71-75.

Bartholinus, C. (1643). De corporibus naturalibus simplicibus eorumque mixtione et mixtionem consequentibus. Rostochii: Hallervord.

- 136 - Bauer, M., Petkova, K., & Boyadjieva, P. (2000). Public Knowledge of and Attitudes to Science: Alternative Measures That May End the "Science War". Science Technology and Human Values. 25 (1). 30-51.

Becker, C. D., Ghimire, K. (2003). Synergy between traditional ecological knowledge and conservation science supports forest preservation in Ecuador. Conservation Ecology, 8(1): 1

Berkes, F., Colding, J., & Folke, C. (2000). Rediscovery of Traditional Ecological Knowledge as Adaptive Management. Ecological Applications, 10, 5, 1251-1262.

Besbeas, P., Freeman, S.N., Morgan, B.J.T., & Catchpole, E.A. (2002). Integrating mark- recapture-recovery and census data to estimate animal abundance and demographic parameters.Integrating Mark-Recapture-Recovery and Census Data to Estimate Animal Abundance and Demographic Parameters.

Bhattacharjee, Y. (2005). Citizen scientists supplement work of Cornell researchers. Science 308: 1402–1403.

Bonney, R. & LaBranche, M. (2004). Citizen Science: Involving the Public in Research. ASTC Dimensions. 13.

Bonney, R., Cooper, C.B., Dickinson, J., Kelling, S., Phillips, T., Rosenberg, K.V., &Shirk, J.. (2009). Citizen Science: A Developing Tool for Expanding Science Knowledge and Scientific Literacy. BioScience 59(11), 977-984

Bowen-Johns, E. &Entwistle, A. (2002). Identifying appropriate flagship species: the importance of culture and local contexts. Oryx. 36(2).

Boyle, . (1671). De qualitatibus rerum cosmicis. Lond.

Bradshaw, J. (2000). John Veit Wilson, Setting Adequacy Standards: how governments define minimum incomes, Bristol, Policy Press, 1998, 142 pp., £11.95 pbk. Journal of Social Policy, 29, 3, 505-536.

Brandenburg, A. M.; Carroll, M. S. (1995). Your place or mine? The effect of place creation on environmental values and landscape meanings. Society and Natural Resources. 8, p. 381–398.

Branham, M.A. &Greenfield, M.D.. (1996). Flashing males win mate success. Nature, 381: 745-746.

- 137 - Branham. (2003). The origin of photic behavior and the evolution of sexual communication in fireflies (Coleoptera: Lampyridae). Cladistics, 19(1), p. 1.

Brehm, J. M., Eisenhauer, B. W., & Krannich, R. S. (2004). Dimensions of community attachment and their relationship to well-being in the amenity-rich rural West. Rural Sociology. 69, p. 405–429.

Brehm. (2006). Community attachments as predictors of local environmental concern: The case for multiple dimensions of attachment. American Behavioral Scientist, 50(2), p. 142.

Brooke, L. F. (1993). The participation of indigenous peoples and the application of their environmental and ecological knowledge in the Arctic Environmental Protection Strate- gy. Volume 1. Inuit Circumpolar Conference, Ottawa, On- tario; Canada.

Brossard, D., Lewenstein, B., & Bonney, R. (2005). Scientific Knowledge and Attitude Change: The Impact of a Citizen Science Project. International Journal of Science Education. 27 (9). 1099-1121.

Brown, L. A., Brown, M. A., & Craig, C. S. (1981). Innovation diffusion and entrepreneurial activity in a spatial context: conceptual models and related case studies. Research in Marketing, 4.

Bruyere, B., (2007). Identifying the motivations of environmental volunteers. Journal of Environmental Planning and Management, 50(4), p. 503-516.

Buck, JB. (1935). Synchronous flashing of fireflies experimentally induced. Science, 81(2101), p. 339.

Buck, JB. (1937a). Studies on the firefly. I. The effects of light and other agents on flashing in Photinus pyralis, with special reference to periodicity and diurnal rhythm. Physiological Zoology, 10(1), p. 45.

Buck, J.B. (1937b). Studies on the firefly. II. The signal system and color vision in Photinus pyralis. Phys- iol. Zool., 10: 412-419.

Buck, J. (1968). Mechanism of Rhythmic Synchronous Flashing of Fireflies. Fireflies of Southeast Asia may use anticipatory time-measuring in synchronizing their flashing. Science, 159(3821), p. 1319.

Buck, J. (1978).Toward a functional interpretation of synchronous flashing by fireflies. American naturalist, p. 471.

- 138 -

Buck, J. (1988). Synchronous Rhythmic Flashing of Fireflies. II. Quarterly review of biology, p. 265.

Bultena, G. L. and E. O. Hoiberg. (1983). Factors affecting farmers’ adoption of conservation tillage. J. Soil Water Conserv. 38(3):281–284

Bushmann, L. L. (1984). Larval biology and ecology of Photuris fireflies (Lampyridae:Coleoptera) in North-Central Florida. J. Kansas Entomol. Soc. 57: 7-16.

Buttel, F. H., Martinson, O. B., & Wilkening, E. A. (1979). Size of place and community attachment: A reconsideration. Social Indicators Research, 6, 4, 475-485.

California and the World Ocean '02, Magoon, O. T., & American Society of Civil Engineers. (2005). California and the World Ocean 02: Revisiting and revising California's ocean agenda. Reston, Va: American Society of Civil Engineers.

Camboni, S. and T. L. Napier. (1993). Factors affecting use of conservation farming practices in east central Ohio. Agric. Ecosystem Environ. 45:79–94.

Carlson, AD. (1985). Flash communication in fireflies. Quarterly review of biology, p. 415.

Case, J.F. (1980). Courting behavior in a synchronously flashing firefly, Pteroptyx tener. Biological Bulletin, 159, 613–625.

Case, J.F. (2004). Flight Studies on Photic Communication by the Firefly Photinus pyralisIntegr. Comp. Biol. 44(3):250-258

Chen, X., Hull, V., Liu, J., Peterson, M. N., Lee, G. D., Lu, C., & Hong, D. (2011). Effects of attitudinal and sociodemographic factors on pro-environmental behaviour in urban China. Environmental Conservation, 38, 1, 45-52.

Cheng, A. S., Kruger, L. E., & Daniels, S. E. (2003).Place as an integrating concept in natural resource politics: Propositions for a social science research agenda. Society and Natural Resources. 16, p. 87–104.

Clayton, S. (2003). Environmental identity: Conceptual and operational definition. In S. Clayton & S. Opotow (Eds.), Identity and the natural environment: The psychological significance of nature (pp. 45-65). Cambridge, MA: MIT Press.

- 139 - Cohn, J. P. (2008). Citizen Science: Can Volunteers Do Real Research? Bioscience, 58, 3, 192-197.

Colorado, P & Collins, D. (1987). Western scientific colonialism and the reemergence of native science. Practice: Journal of Politics, Economics, Psychology, Sociology and Culture (winter): 50–65.

Conrad, C. C. (2011). A review of citizen science and community-based environmental monitoring: issues and opportunities. (Report). Environmental Monitoring and Assessment, 176(1-4).

Cook, C. (1988). Components of Neighborhood Satisfaction. Environment and Behavior, 20,2, 115-149.

Cooper, C.B., Dickinson, J., Phillips, T., & Bonney, R. (2007). Citizen Science as a Tool for Conservation in Residential Ecosystems. Ecology and Society. 12 (2).

Cooper, J., & Signorello, G. (2008). Farmer Premiums for the Voluntary Adoption of Conservation Plans. Journal of Environmental Planning and Management, 51(1), 1-14.

Copeland. (1994).The occurrence of synchrony in the North American firefly Photinus carolinus (Coleoptera: Lampyridae). Journal of Insect Behavior, 8(3), p. 381.

Copeland, J., Moiseff, A., & Faust, L. (2008). Landing distance in a synchronic North American firefly. Physiological Entomology, 33, 2, 110-115.

Cormier, M. J., Crane, J. M. J., & Nakano, Y. (1967). Evidence for the identity of the luminescent systems of Porichthys porosissimus (fish) and Cypridina hilgendorfii (crustacean). Biochemical and Biophysical Research Communications, 29, 5, 747- 52.

Corsiglia, J. & Snively, G. (1995). Global lessons from the traditional science of long resident peoples. Pages 25–51 in Snively G, MacKinnon A, eds. Thinking Globally about Mathematics and Science Education. Vancouver, British Columbia (Canada): University of British Columbia Centre for the Study of Curriculum and Instruction.

Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research, and Application, 10(7)

- 140 -

Cox,C.,(1998). Herbicide Fact Sheet: Glyphosate, (Roundup), Journal of Pesticide Reform, 18(3).

Cross, J. E. (2001). Protecting our place: Establishing and maintaining community attachments in the face of population growth and change. Unpublished doctoral dissertation, University of California-Davis.

Crowe, J. (2010). Community attachment and satisfaction: The role of a community's social network structure. Journal of Community Psychology, 38, 5, 622-644.

Cunningham & Cunningham. (2009).Principles of Environmental Science, 2009, McGraw Hill

Darley, J. (1978). Energy conservation techniques as innovations and their diffusion. Energy and Buildings, 1, 339-343.

Darley, J. M., & Beninger, J. R. (1981). Diffusion of energy-conserving innovations. Journal of Social Issues, 37(2), 150-171.

Davic, R. D., (2003). Linking Keystone Species and Functional Groups: A New Operational Definition of the Keystone Species Concept. Conservation Ecology.

Denis, J. L., Lehoux, P., Hivon, M., & Champagne, F. (2003). Creating a new articulation between research and practice through policy? The views and experiences of researchers and practitioners. Journal of Health Services Research & Policy, 8, 44-50.

DeVellis, R. F. (2003). Guidelines in Scale Development. In Scale Development: Theory and Applications. Thousand Oaks, CA: Sage.

Devine-Wright, P., & Howes, Y. (2010). Disruption to place attachment and the protection of restorative environments: A wind energy case study. Journal of Environmental Psychology, 30, 271-280.

Doane, J.F., O.O. Olfert, & M.K. Mukeri., (1987). Extraction precision of sieving and brine flotation for removal of wheat midge (Sitodiplosis mosellana) (Diptera, Oecidomyiidae) cocoons and larvae from soil. J. Econ. Entomol., 80 (1987), pp. 268–271

Dreisig, H. (1975). Environmental control of the daily onset of luminescent activity in glow- worms and fireflies (Coleoptera: Lampyridae). Oecologia, 18: 85-99.

- 141 -

Dunlap, R. E., VanLiere, K. D., Mertig, A. G., & Jones, R. E. (2000). Measuring endorsement of the New Ecological Paradigm: A revised NEP scale. Journal of Social Issues, 56, 425–442.

Edelstein, M. R. (1988). Contaminated communities: The social and psychological impacts of residential toxic exposure. Boulder, CO: Westview.

Edmunds, L. E., JR. (1963). The relation between temperature and flashing intervals in adult male fireflies, Photinus pyralis. Ann. Entomol. Soc. Am., 56: 716-718.

Edwards, C. A. (1991). The assessment of populations of soil-inhabiting invertebrates. Agriculture, Ecosystems & Environment, 34, 145-176.

Egan, A. F. & Luloff, A. E. (2000). The exurbanization of America’s forests: Research in rural social science. Journal of Forestry. 98 p. 26–30.

Eisenhauer, B. W., Krannich, R. S., & Blahna, D. J. (2001).Attachments to special places on public lands: An analysis of activities, reasons for attachments, and community connections. Society and Natural Resources. 13 p. 421–441.

Emerson, G. A. (1935). Some Effects of Ether on Bioluminescence in the Lampyrid, Photuris pennsylvanica. Proc Soc Exp Biol Med. 33:36—40

Erickson, D., R. Ryan, & R. De Young. (2002). Woodlots in the rural landscape: Nonindustrial private landowner motivations and management attitudes in a Michigan case study. Landscape Urban Plan. 58:101–112.

Erikson. (1985).Allocation of attention in the visual field. Journal of Experimental Psychology Human Perception, 11(5), p. 583.

Etkin, N. L. (2002). Local Knowledge of Biotic Diversity and its Conservation in Rural Hausaland, Northern Nigeria1. Economic Botany, 56, 1, 73-88.

Evans, C., Abrams, E., Reitsma, R., Roux, K., Salmonsen, L. & Marra, P. P. (2005), The Neighborhood Nestwatch Program: Participant Outcomes of a Citizen-Science Ecological Research Project. Conservation Biology, 19: 589–594.

Fang, X. (1974). Jin shu: [10 ce 130 juan]. Beijing: Zhonghua shu ju.

- 142 - Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175-191.

Firehock, K. & West, J. (2001). A brief history of volunteer biological water monitoring using macroinvertebrates. Journal of the North American Benthological Society. 14 (2) 197-202.

Fischer, Claude S. 1982. To Dwell Among Friends: Personal Networks in Town and City. Chicago: University of Chicago Press.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: an introduction to theory and research. Reading, Mass.: Addison-Wesley Pub. Co.

Ford, SR. (1995). Does the sulfhydryl or the adenine moiety of CoA enhance firefly luciferase activity? Biochimica et Biophysica Acta (BBA)/Protein Structure and Molecular Enzymology, 1252(2), p. 180.

Forrest, T. G., & Eubanks, M. D. (1995). Variation in the Flash Pattern of the Firefly, Photuris versicolor quadrifulgens (Coleoptera: Lampyridae). Journal of Insect Behavior, 8, 1, 33.

Fransson, N. & Garling, T. (1999).Environmental concern: Conceptual definitions, measurement methods, and research findings. Journal of Environmental Psychology. 19. p. 369–382.

Galloway, A., Tudor, M., & West, H. (2006). The Reliability of Citizen Science: A Case Study of Oregon White Oak Stand Surveys. Wildlife Society Bulletin, 34,5, 1425- 1429.

Geller, E.S. (1981). Evaluating energy conservation programs: Is verbal report enough? Journal of Consumer Research, 8, 331–334.

Geller, E.S. (1983). The energy crisis and behavioral science: A conceptual framework for large scale intervention. In A.W. Childs &G.B. Melton (Eds.), Rural psychology. New York: Plenum Press.

Gilg, A. W. (1983). Where town meets country: problems of peri-urban areas in Scotland. Applied Geography, 3, 2, 167.

Giuliani, M. V. & Feldman, R. (1993). Place attachment in a developmental and cultural context. Journal of Environmental Psychology, 13, 267-274.

- 143 -

Goldschmidt, W. (1978). As you sow: Three studies in the social consequences of agribusiness. Glencoe, IL: The Free Press

Goodchild, M. (2007). Citizens as sensors: the world of volunteered geography. Geojournal, 69, 4, 211-221.

Gosling, S. N., Warren, R., Arnell, N. W., Good, P., Caesar, J., Bernie, D., & Smith, S. M. (2011). A review of recent developments in climate change science. Part II: The global-scale impacts of climate change. Progress In Physical Geography, 35(4), 443-464.

Goudy, W. J. (1990). Community attachment in a rural region. Rural Sociology. 55. p. 178–198.

Gould, SJ. (1988). Firefly luciferase as a tool in molecular and cell biology. Analytical Biochemistry, 175(1), p. 5.

Gray, HE. (1933). On the enumeration of insect populations by the method of net collection. Ecology, 14(4), p. 356.

Groom, M. J., Gary K. Meffe & C. Ronald Carroll. (2006). Principles of Conservation Biology. Sunderland, Massachusetts, Sinauer Associates, Inc.

Grubbstrom, A. (2011). Emotional bonds as obstacles to land sale-Attitudes to land among local and absentee landowners in Northwest Estonia. Landscape and Urban Planning, 99, 1, 31-39.

Hamman, J. P., & Seliger, H. H. (1982). The chemical mimicking of the mechanical stimulation, photoinhibition, and recovery from photoinihibition of bioluminescence in the marine dinoflagellate,Gonyaulax polyedra. Journal of Cellular Physiology, 111, 3, 315-319.

Hammitt. (2006). Place bonding for recreation places: Conceptual and empirical development. Leisure Studies, 25(1), p. 17.

Hansen, K, & Herring, PJ. (1977). Dual bioluminescent systems in the angler-fish genus Linophryne (Pisces: Ceratioidea) J. Zool Lond 182:103-124.

Harding, WC. (1966). Blacklight trap standards for general insect surveys. Bulletin of the Entomological Society of America, 12(1), p. 31.

- 144 - Harvey. (1939). Bioluminescence. Transactions of the Faraday Society, 35, p. 233.

Harvey, E.N., (1957). A history of luminescence. Am. Philos. Soc. Philadelphia . 44, 669.

Hazard, F. O. (1929). The Lampyridae of Ohio. Masters Thesis. Dept. of Zoo. and Ent., The Ohio State University. 36-50.

Hastings. (1983). Biological diversity, chemical mechanisms, and the evolutionary origins of bioluminescent systems. Journal of Molecular Evolution, 19(5), p. 309.

Hayes, S. C., & Cone, J. D. (1977). Reduction of residential electricity use: Information, payments, and feedback. Journal of Applied Behavior Analysis, 10, 425-435.

Heberlein, T. A., & Prouty, M. (1975). Public opinions about Madison's limited road salt experiment: Report to City of Madison, Council on the Environment, and the Streets Departments. Madison: Dept. of Rural Sociology, University of Wisconsin.

Herring, PJ & Morin, JG (1978). Bioluminescence in Fishes. In: Herring PJ(ed) Bioluminescence in Action. Academic Press, London, pp273-329.

Hess, W. N. (1920). Notes on the biology of some common Lampyridae. Biol. Bull. 38: 39-76.

Hidalgo, M. C. & Hernandez, B. (2001). Place attachment: conceptual and empirical questions. Journal of Environmental Psychology, 21, 273-281.

Hummon, D.H. (1992). Community attachment: Local sentiment and sense of place. In I. Altman & S.M. Low (Eds.), Place attachment (pp. 253-278). New York: Plenum.

Huntington, H. P. (2000). Using Traditional Ecological Knowledge in Science: Methods and Applications. Ecological Applications, 10, 5, 1270-1274.

http://bugguide.net/node/view/63819 http://digitalphoto.cocolog-nifty.com/digitalphoto/cat4164851/index.html http://evolution.berkeley.edu/evolibrary/home.php http://rural.swcb.gov.tw/news/news-1.asp?nid=381

- 145 - http://www.fussakanko.jp/pa0206.html http://www.statsoft.com/textbook/stathome.html http://english.firefly.or.kr/main.html

Iguchi, Y. (2009). The ecological impact of an introduced population on a native population in the firefly Luciola cruciata (Coleoptera: Lampyridae). Biodiversity and Conservation, 18(8), p. 2119-2119-2126.

Inglehart, R., & C. Welzel. (2005). Modernization, cultural change, and democracy : the human development sequence. Cambridge University Press, New York, NY.

Inglis, J. T. (1993). Traditional ecological knowledge: concepts and cases. Canadian Museum of Nature, Ottawa, Ontario, Canada.

Inoue S, Kakoi H, & Goto T. (1976). Squid bioluminescence III. Isolation and structure of Watasenia luciferin. Tetrahedron Lett. 34: 1971-1974.

Inoue S, Okade K, Kakoi H, & Goto T. (1977). Fish bioluminescence I. Isolation of a luminescent substance from a myctophid fish, Neoscopelus microchir, and identification of it as Oplophprus luciferin. Chem Lett. 20: 257-258.

Johannes, R. E., editor. (1989). Traditional ecological knowl- edge: a collection of essays. International Conservation Union (IUCN), Gland, Switzerland.

Jones, R. & Riley E. Dunlap. (2001). The Social Bases of Environmental Concern: Have They Changed Over Time? In R. Scott Frey (ed.), The Environment and Society Reader. Boston: Allyn and Bacon, pp. 164-179. (Reprint of Jones and Dunlap, 1992).

Johnson, CH. (1985). Compartmentalization of algal bioluminescence: autofluorescence of bioluminescent particles in the dinoflagellate Gonyaulax as studied with image- intensified video microscopy and flow cytometry. The Journal of Cell Biology, 100(5), p. 1435.

Johnson, FH. & Shimomura O. (1978). Introduction of the Cypridina system. In: Deluca M (ed) Methods of Enzymology, 57. Academia Press, New York, p 331-364.

Jones, F. C., Baird, D., Bowman, M., Cameron, G., Craig, B., Cutler, B., Diamond, J., Whitelaw, G. (2006). Performance of Ontario's Benthos Biomonitoring Network:

- 146 - Impacts on Participants' Social Capital, Environmental Action, and Problem- solving Ability. Environments, 34(1), p.37. Jorgensen, B. S., & Stedman, R. C. (2001). Sense of place as an attitude: lakeshore owners attitudes toward their properties. Journal of Environmental Psychology, 21, 233-248.

Kasarda, J. D. & Janowitz, M. (1974). Community attachment in mass society. American Sociological Review, 39. 328-339.

Kazama, S., Matsumoto, S., Ranjan, S. P., Hiroshi Hamamoto, & Masaki Sawamoto, (2007). Characterization of firefly habitat using a geographical information system with hydrological simulation, Ecological Modeling, 209(2-4), 392-400.

Keiper, R. R. & Solomon, L. M.. (1972). Ecology and yearly cycle of the firefly Photuris pennsylvanica (Coleoptera: Lampyridae). N. Y. Entomol. Soc. 80: 43-47.

Kimmerer, R. W. (2002). Weaving Traditional Ecological Knowledge into Biological Education: A Call to Action. Bioscience, 52, 5, 432-438.

Kirton, L., Nada, B., Khoo, V., & Phon, C. (2011). Monitoring populations of bioluminescent organisms using digital night photography and image analysis: a case study of the fireflies of the Selangor River, Malaysia. Insect Conservation and Diversity.

Kitani S., Hasebe, T., Nomura N.,& Moore R. (2005). Effects of Image Formation of Rural Lifescape on Consciousness and Willingness to Protect Rural Farming Village.[The Japanese Journal of Rural Economics,7(5),100-113]

Kohlenberg, R., Phillips, T., and Proctor, W. (1976). A behavioral analysis of peaking in residential electrical-energy consumers. Journal of Applied Behavior Analysis, 9, 13-18.

Kontoleon, A., & Swanson, T. (2003). The Willingness to Pay for Property Rights for the Giant Panda: Can a Charismatic Species Be an Instrument for Nature Conservation? Land Economics, 79, 4, 483-499.

Krantz, JH. (2008). Did I really see that? The complex relationship between the visual stimulus and visual perception. J Voice. 22(5):520-32

Kyle, G. T., Graefe, A., Manning, R. E., & Bacon, J. (2004). Effect of involvement and place attachment on recreationists’ perceptions of setting density. Journal of Leisure Research, 36, 209-231

- 147 -

Lall, A. B., Seliger, H.H., Biggley, W. H., & Lloyd, J. E., (1980) Ecology of colors of firefly bioluminescence, Science 210,560–562

Lall, A. B., Strother, G. K., Cronin, T. W., & Seliger, H. H. (1988). Modification of spectral sensitivities by screening pigments in the compound eyes of twilight- active fireflies (Coleoptera: Lampyridae). Journal of Comparative Physiology. A, Sensory, Neural, and Behavioral Physiology, 162, 1, 23-33.

Lawrence, J. F., & Newton, A.F.. (1982). Evolution and classification of beetles. Annu. Rev. Ecol. Syst. 13: 261-290.

LeBuhn, G.,et. al. (2003). A standardized method of monitoring Bee Populations-The Bee Inventory (BI) Plot. Available from http://online.sfsu.edu/beeplot/

Lloyd, J.E. (1966). Studies on the flash communication system in Photinus fireflies. Univ. Michigan Mus. Zool. Misc. Publ., 130: 1-96.

Lloyd, JE. (1968). Illumination, another function of firefly flashes. Entomological news, 79, p. 265.

Lloyd, J. E. (1969). Flashes of Photuris fireflies: their value and use in recognizing species. Florida Entomol. 52(1): 29-35.

Lloyd, J. E. (1975). Aggressive mimicry in Photuris fireflies: signal repertories in femmes fatales. Science 187: 452-3.

Lloyd, J. E. (1978). Insect bioluminescence, pp. 241-272. In P. S. Herring [ed.], Bioluminescence in Action. Academic Press. New York.

Lloyd, J. E. (1980). Male Photuris fireflies mimic sexual signals of their females’ prey. Science 210(4470): 669-671.

Lloyd, J. E. (1981). Firefly mate rivals mimic their predators and vice versa. Nature 290: 498-500.

Lloyd, J. E. (1984a). Evolution of a firefly flash code. Florida Entomologist 67: 228-239.

Lloyd, JE. (1984b) Occurrence of aggressive mimicry in fireflies. Florida Entomologist, p. 368.

- 148 - Lloyd, JE.(1984c) On deception, a way of all flesh, and firefly signaling and systematics. Oxford Surveys in Evolutionary Biology, 1, p. 48.

Lloyd, J. E. (1990a). Firefly semiosystematics and predation: a history. Florida Entomologist 73(1): 51-66.

Lloyd, J. E. (1990b). Checklist and keys to fireflies of east-central Alabama. Stridulator (F. S. Arant Entomology Club, Department of Entomology, Auburn University 4(3): 9-21.

Lloyd, JE. (2001). On research and entomological education V: a species concept for fireflyers, at the bench and in old fields, and back to the Wisconsian glacier. Florida Entomologist, p. 587.

Lloyd. (2003).On research and entomological education VI: Firefly species and lists, old and now. Florida Entomologist, 86(2), p. 99.

Lloyd, J.E. (2006). Stray light, fireflies, and fireflyers. In C. Rich & T. Longcore (Editors), Ecological Consequences of Artificial Night Lighting (pp. 345-364). Washington, DC: Island Press.

Lubell, M. (2004). Collaborative Watershed Management: A View from the Grassroots. Policy Studies Journal, 32(3), p. 341.

Lynch, T. (2000) http://www.byteland.org/firefly/firefly_notebooks.html

Lynd, Robert S. & Helen M. Lynd. (1929). Middletown: A Study in Contemporary American Culture. New York: Harcourt, Brace, and Company.

Madsen, HF. (1962). Black light traps. California agriculture - California Agricultural Experiment Station.

Marvin, JR, DE. (1965). A list of fireflies known or likely to occur in Ohio; with special notes on species of Ellychinia’2. Ohio journal of science, 65(1), p. 37.

Mayer, A. (2010). Phenology and Citizen Science. Bioscience, 60, 3, 172-175.

Mazumdar, S., & Mazumdar, S. (2004). Religion and place attachment: a study of sacred places. Journal of Environmental Psychology, 24, 385–397

- 149 - Mbaiwa, J., Stronza, A., & Kreuter, U. (2011). From Collaboration to Conservation: Insights From the Okavango Delta, Botswana. Society & Natural Resources, 24(4), 400-411.

McCaffrey, R.E. (2005). Using Citizen Science in Urban Bird Studies. Urban Habitats. 3 (1). 70-86.

McCool, S. F. & Martin, S. R. (1994). Community attachment and attitudes towards tourism development. Journal of Travel Research. 32. 29–34.

McDermott, FA. (1910). A note on the light emission of some American Lampyridae. The Canadian entomologist, 42, 357

McDermott, FA. (1911). Some further observations on the light emission of American Lampyridae: the photogenic function as a mating adaptation in the Photinini. The Canadian entomologist, 43, 399.

McDermott, FA. (1917). Observations on the light emission of American Lampyridae: the photogenic function as a mating adaptation. Fifth paper. The Canadian entomologist, 49, 53.

McGregor, D. (2004). Coming full circle: indigenous knowledge, environment, and our future. American Indian Quarterly, 28(3 & 4), 385-410

McIntosh, W. and Z. Lee.( 2003). Correlates of dairy farm household expenditures. Paper presented at the 66th Annual Meeting of the Rural Sociological Society, Montreal, Quebec, Canada, July 27–30.

McLean M., Buck, J., & Hanson, F.F.. (1972). Culture and larval behaviour of photurid fireflies. The Am. Midl. Nat. 87: 133-145.

Measham, T., (2008) Environmental Volunteering: motivations, modes and outcomes. Australian Geographer, 39(4), p. 537-552.

Menhinick, E.F.. (1963), Estimation of Insect Population Density in Herbaceous Vegetation with Emphasis on Removal Sweeping. Ecology, 44(3). pp. 617-621

Moiseff. (2000). A new type of synchronized flashing in a North American firefly. Journal of Insect Behavior, 13(4), p. 597.

- 150 - Moon, K., & Cocklin, C. (2011). A landholder-based approach to the design of private- land conservation programs. Conservation Biology : the Journal of the Society for Conservation Biology, 25(3), 493-503.

Moore,R., J.S. Parker, & M.Weaver. (2008) Agricultural Sustainability and Water Pollution: Lessons from the Sugar Creek Farmers in Ohio. Culture and Agriculture 30(1&2): 3-16.

Moore, Richard. (2009). Integrating the Social and Natural Sciences in the Sugar Creek Method. In Sustainable Agroecosystem Management: Integrating Ecology, Economics, and Society. Edited by Bohlen, Patrick and Gar House. Boca Raton, Florida, USA: CRC Press Taylor and Francis Group. 21-40

Moore, E. L. (2010). An index of biotic integrity for macroinvertebrates and salamanders in primary headwater habitat streams in Ohio. Columbus, Ohio: Ohio State University.

Nagendra, H., & Gokhale, Y. (2008). Management Regimes, Property Rights, and Forest Biodiversity in Nepal and India. Environmental Management, 41(5), p. 719-733.

Napier, T. L., C.S . Thraen, A. Gore, and W. R. Goe. (1984). Factors affecting adoption of conventional and conservation tillage practices in Ohio. J. Soil Water Conserv. 39(May-June):205–209.

Napier, T. L., S. M. Camboni, and C. S. Thraen. (1986). Environmental concern and the adoption of farm technologies. J. Soil Water Conserv. 41(March–April):109–113.

Napier, T. L. and M. Tucker. (2001). Use of soil and water protection practices among farmers in three Midwest watersheds. Environ. Manage. 27(2):269–279

Napier, T. L. and T. Bridges. (2002). Adoption of conservation production systems in two Ohio watersheds: A comparative study. J. Soil Water Conserv. 57(4):229– 235.

Napier, T. L., M. Tucker, B. Sohngen, and S. Napier. (2002). Weather projections for production decisions-making: A multiple watershed study. In Revitalization of agriculture in global environment, ed. J. Tvrdon, 13–30. Prague, Czech Republic: Czech Agricultural University.

Nerbonne, J., & Nelson, K., (2004). Volunteer Macroinvertebrate Monitoring in the United States: Resource Mobilization and Comparative State Structures. Society & Natural Resources, 17(9), p. 817-839.

- 151 -

Nordenstam, B. J. (1994). When communities say NIMBY to their LULUS: Factors influencing environmental and social impact perception. Paper presented at the 14th Annual Meeting of the International Association for Impact Assessment, Quebec, Canada

NSF (2007) http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=13681

Nunnally, J.C., & Ira H. Bernstein. (1994). Psychometric theory. 3rd ed, McGraw-Hill series in psychology. New York: McGraw-Hill

Oates, J. F. (1999). Myth and reality in the rain forest: how conservation strategies are failing in West Africa. University of California Press, Berkeley.

Oberhauser, K. S., & Solensky, M. J. (2004). Monarch butterfly biology & conservation. Ithaca: Cornell University Press.

Oberhauser, K. (2008). Citizen Science: Creating a Research Army for Conservation. AMERICAN ENTOMOLOGIST -LANHAM-, 54(2), 103-104.

Ozaki, Kenichi, Masahiro Isono, Takayuki Kawahara, Shigeo Iida, Takuma Kudo & Kenji Fukuyama. (2006). A Mechanwestic Approach to Evaluation of Umbrella Species as Conservation Surrogates. Conservation Biology, 20(5), 1507-1515.

Palmer, M.H., Lloyd, M.E., &Lloyd, K.E. (1978). An experimental analysis of electricity conservation procedures. Journal of Applied Behavior Analysis, 10, 665–672.

Park, Robert E. and Ernest W. Burgess. 1925. The City. Chicago: University of Chicago Press.

Parker, J. S., (2006) Tenure in the Sugar Creek Watershed: A contextual analysis of land tenure and social networks, intergenerational farm succession, and conservation use among Anabaptist farmers of Wayne County, Ohio. Department of Anthropology, Ohio State University, Columbus.

Parker, J. S., Moore, R., & Weaver, M., (2007). Land Tenure as a Variable in Community Based Watershed Projects: Some Lessons from the Sugar Creek Watershed, Wayne & Holmes County, Ohio. Society and Natural Resources, 20(9): 815-833.

- 152 - Parker, J. S., & Moore, R., (2008). Conservation Use and Quality of Life in a Rural Community: An Extension of Goldschmidt's Findings. Southern Rural Sociology 23(1):235-265.

Parker, J. S., Moore, R., & Weaver, M., (2009). Developing Participatory Models of Watershed Management in the Sugar Creek Watershed (Ohio, USA). Water Alternatives 2(1):82-100.

Pierotti, R., & Wildcat, D. (2000). Traditional Ecological Knowledge and Wisdom - Traditional ecological knowledge: The third alternative (commentary). Ecological Applications: a Publication of the Ecological Society of America, 10, 5, 1333.

Posey, D. A. (1981). Ethnoentomology of the Kayapó Indians of central Brazil: wasps, warriors and fearless men. Journal of Ethnobiology, 1(1), 165-174.

Relph, E. (1976).Place and placelessness. London: Pion Limited,

Richards, RT. (1997). What the natives know: Wild mushrooms and forest health. Journal of Forestry: 5–10.

Riley, P. J. and G. Kiger. (2002). Increasing survey response: The drop-off=pick-up technique. Rural Sociol. 22(1):6–9.

Riger, Stephanie and Paul J. Lavrakas. 1981. "Community Ties: Patterns of Attachment and Social Interaction in Urban Neighborhoods." American Journal of Community Psychology 9:55-66.

Roberge, J. & Angelstam, P. (2004). Usefulness of the Umbrella Species Concept as a Conservation Tool. Conservation Biology, 18(1), 76-85

Robinson BH, & Young RE. (1981). Bioluminescence in pelagic octopods. Pacific Science 35:39-44.

Rogers, E. M. (1983). Diffusion of innovations. New York: Free Press.

Sabatier, P.A. (1986). Top-Down and Bottom-Up Approaches to Implementation Research: a Critical Analysis and Suggested Synthesis. Journal of Public Policy, 6, pp 21-48

Sabu, T. K., Shiju, R. T., Vinod, K., & Nithya, S. (2011). A comparison of the pitfall trap, Winkler extractor and Berlese funnel for sampling ground-dwelling

- 153 - arthropods in tropical montane cloud forests. Journal of Insect Science (online), 11.

Salamon, S., & Farnsworth, R. L. (1997). Family factors affecting adoption of sustainable farming. Journal of Soil & Water Conservation, 52(4).

Salamon, S. (2003). From Hometown to Nontown: Rural Community Effects of Suburbanization.Rural Sociology, 68, 1, 1-24.

Salmon E. (1996). Decolonizing our voices. Winds of Change (summer):70–72.

Samways, M.J., Stork, N.E., Cracraft, J., Eeley, H.A.C., Foster, M., Lund, G. & Hilton- Taylor, C. (1995) Scales, planning and approaches to inventoring and monitoring. In: Global Biodiversity Assessment, ed. V.H. Heywood & R.T. Watson, pp. 475– 517. Cambridge, UK: Cambridge University Press.

Scannell, L. & Gifford, R., (2010) Identity, Place, and Environmental Behaviour. The relations between natural and civic place attachment and pro-environmental behavior. Journal of Environmental Psychology, 30, 3, 289-297.

Scannell, L. & Robert Gifford. (2011). Personally Relevant Climate Change: The Role of Place Attachment and Local Versus Global Message Framing in Engagement Environment and Behavior.

Schaefer, K. A., & Bielak, A. T. (2006). Linking water science to policy: results from a series of national workshops on water. Environmental Monitoring and Assessment, 113, 1-3.

Schindeler, (1977). N. Personal communication to W.E. Sharpe. (Cited in Sharpe & Fletcher, 1977).

Schutz, A. C., Braun, D. I., Gegenfurtner, K. R., & Kerzel, D. (2008). Improved visual sensitivity during smooth pursuit eye movements. Nature Neuroscience, 11,10, 1211-1216.

Seliger, H. H., & McElroy, W. D., (1960). Spectral emission and quantum yield of firefly bioluminescence. Arch Biochem Biophys. 88:136-41.

Seliger, H. H., McElroy, W. D., White, E.H., Field, G.F., (1961). Stereo-specificity and firefly bioluminescence, a comparison of natural and synthetic luciferins. Proc Natl Acad Sci U S A. 47:1129-34.

- 154 - Seliger, H. H., Buck, J. B., Fastie, W. G., & McElroy, W. D., (1964). The spectral distribution of firefly light. J Gen Physiol. 48:95-104.

Sharpe, W.E., &Fletcher, P.W. (1977). The impact of water saving device installation on resource conservation (Research Publication 98). University Park, Pennsylvania: Pennsylvania State University, Institute for Research on Land and Water Resources.

Shimomura, O. (1980) Chlorophyll-derived bile pigment in bioluminescent euphausiids. FEBS Lett 116: 203-206.

Silvertown, J. (2009). A New Dawn for Citizen Science. Trends in Ecology & Evolution. 24 (9). p. 467-471

Simmel, G (1903 [1997]), The Metropolis and Mental Life’ in D Frisby & M Featherstone (eds), Simmel on Culture, Sage, London, pp.174-186.

Smith, M. D. & Krannich, R. S. (2000). Culture clash revisited: Newcomer and longer- term residents’ attitudes toward land use, development, and environmental issues in rural communities in the Rocky Mountain West. Rural Sociology. 65. 396–421.

Sommers, D. G. & T. L. Napier. (1993). Comparison of Amish and non-Amish farmers: A diffusion=farm structure perspective. Rural Sociol. 58(1):130–145.

Spiro, M. (2004). What should the citizen know about science? Journal of the Royal Society of Medicine, 97 (1).

Starr, C., Evers, C. A., & Starr, L. (2008). Biology: Concepts and applications. Australia: Brooks/Cole-Thomson Learning.

Stedman, R. C. (2002).Towards a social psychology of place: Predicting behavior from place-based cognitions, attitude, and identity. Environment and Behavior. 34. p. 405–425.

Stedman, R. C. (2003). Is it really just a social construction? The contribution of the physical environment to sense of place. Society and Natural Resources. 16. p. 671–686.

Stedman. (2006),Understanding place attachment among second home owners. American Behavioral Scientist, 50(2), p. 187.

- 155 - Steele, J., Bourke, L., Luloff, A. E., Liao, P.-S., Theodori, G. L., & Krannich, R. S. (2001). The drop-off/pick-up method for household survey research. Journal of the Community Development Society, 32, 2.)

Stephenson, P. J., & Ntiamoa-Baidu, Y. (2010). Conservation planning for a widespread, threatened species: WWF and the African elephant Loxodonta africana. Oryx, 44, 2, 194-204.

Stern, P. C.& Dietz, T. (1994).The values basis of environmental concern. Journal of Social Issues. 50. p. 65–84.

Stern, P. C., Dietz, T., Kalof, L., & Guagnano, G. A. (1995).Values, beliefs, and proenvironmental action: Attitude formation toward emergent attitude objects. Journal of Applied Social Psychology. 25. p. 1611–1636.

Stern, P. C., Dietz, T., Abel, T., Guagnano, G.A., & Kalof, L.. (1999). A value-belief- norm theory of support for social movements: The case of environmental concern. Human Ecology Review 6:81-97.

Stern, P.C. (2000). Toward a coherent theory of environmentally significant behavior. Journal of Social Issues, 56(3), 407-424.

Stevenson, M. G. (1996). Indigenous knowledge in environ- mental assessment. Arctic49:(3)278-291.

Sullivan, B. L., Wood, C. L., Iliff, M. J., Bonney, R. E., Fink, D., & Kelling, S. (2009). eBird: A citizen-based bird observation network in the biological sciences. Biological Conservation, 142(10), p. 2282-2292.

Sultana, P., & Thompson, P. (2007). Community Based Fisheries Management and Fisher Livelihoods: Bangladesh Case Studies. Human Ecology, 35(5), p. 527-546.

Susanne, M. S. (2010). Renovating Science Education. European Education, 22, 2, 3-5.

Suzuki, H. (2002).Genetic Diversity, Geographic Differentiation and Artificial Disturbance of the Japanese Firefly, Luciola Cruciata (Coleoptera, Lampyridae). Research report from the national institute for environmental studies Japan, 171, p. 243.

Takeda, M., Amano, T., Katoh, K., & Higuchi, H., (2006). The Habitat Requirement of the Genji-Firefly Luciola cruciata (Coleoptera : Lampyridae), a Representative

- 156 - Endemic Species of Japanese Rural Landscapes. Biodiversity and Conservation, 15(1), 191-203.

Thancharoen, A. (2008). Building Twilight Light Sensors to Study the Effects of Light Pollution on Fireflies. The American Biology Teacher, 70(2), p. 7.

Theodori, G. L.& Luloff, A. E. (2002). Position on environmental issues and engagement in proenvironmental behaviors. Society and Natural Resources. 15. p. 471–482.

Trumbull, D. J., Bonney, R., Bascom, D., & Cabral, A. (2000). Thinking Scientifically during Participation in a Citizen-Science Project. Science Education, 84, 2, 265- 75.

Tsuji FI, Haneda Y, Lynch RV, & Sugiyama N. (1971). Luminescence cross-reactions of Porichthys luciferin and theories on the origin of luciferin in some shallow-water fishes. Comp Biochem Physiol 40A; 163-179.

Tsuji FI, Barnes AT, & Case, JF. (1972). Bioluminescence in the marine teleost, Porichthys notatus, and its induction in a non-luminous form by Cypridina (Ostracod) luciferin. Nature 237: 515-516.

Tsuji FI. (1978). Cypridina luciferin and luciferase. In: Colowick SP, Kaplan NO (eds) Methods in Enzymology, 57 (DeLuca MA, ed). Academic Press, New York, pp 364-372.

Tuan, Y. (1974). Topophilia: A study of environmental perception, attitudes, and values. Englewood Cliffs, NJ: Prentice Hall.

Tuan, Y. (1977). Space and place: The perspective of experience. Minneapolis: University of Minnesota Press.

Tucker, M. and T. Napier. (2002). Preferred sources and channels of soil and water conservation information among farmers in three Midwestern U.S. watersheds. Agric. Ecosyst. Environ. 81:297–313.

UNEP United Nations Environment Programme. (1998). Report of the fourth meeting of the parties to the convention on biodiversity. Nairobi (Kenya): United Nations Environment Programme. UNEP/CBD/COP/4/27.

Van, L. K. D. & Dunlap, R. E. (1980).The social bases of environmental concern: A review of hypotheses, explanations and empirical evidence. Public Opinion Quarterly. 44. p. 181–197.

- 157 -

Vaske, J. J., & K. C. Kobrin. (2001). Place attachment and environmentally responsible behavior. The Journal of Environmental Education 32:16-21.

Vencl. (1998), Proximate mechanisms of sexual selection in the firefly Photinus pyralis (Coleoptera: Lampyridae). Journal of Insect Behavior, 11(2), p. 191.

Viviani. (2001), Fireflies (Coleoptera: Lampyridae) from Southeastern Brazil: habitats, life history, and bioluminescence. Annals of the Entomological Society of America, 94(1), p. 129.

Vorkinn, M., & Riese, H. (2001). Environmental concern in a local context: the significance of place attachment. Environment & Behavior, 33, 249–263.

Wassink, EC. (1978). Luminescence in fungi. In: Herring PJ(ed) Bioluminescence in Action. Acdemia Press, London, pp 171-197.

Wet, JRD. (1985),Cloning of firefly luciferase cDNA and the expression of active luciferase in Escherichia coli. Proceedings of the National Academy of Sciences, 82(23), p. 7870.

Weaver, M., Moore, R., & Parker, J. S., (2011) Chapter 13 A Case Study of Farmer-led Watershed Groups: The Sugar Creek Partners, Ohio. In The Citizen Effect: Multiple Pathways to Solving Watershed Problems, L. Morton (Ed.).

Wieman, C. (2007). Why Not Try a Scientific Approach to Science Education?. Change: the Magazine of Higher Learning, 39, 5, 9-15.

Wickler, W. (1968). Mimicry in Plants and Animals. World University Library, McGraw-Hill Book Co., New York.

Wilkinson,, K. P. (1991). The community in rural America. Middletown, WI: Social Ecology Press.

Williams, D. R., Patterson, M. E., Roggenbuck, J. W., & Watson, A. E. (1992). Beyond the commodity metaphor: Examining emotional and symbolic attachment to place. Leisure Sciences. 14. p. 29–46.

Williams, F. X. (1917). Notes on the life-history of some North-American Lampyridae. J. New York Entomol. Soc. 25: 11-33.

- 158 - Williams, N. M., & G. Baines, editors. (1993). Traditional ecological knowledge: wisdom for sustainable develop- ment. Centre for Resource and Environmental Studies, Australian National University, Canberra, Australia.

Winett, R.A., Kaiser, S., & Haberkorn, G. (1977). The effects of monetary rebates and feedback on electricity conservation. Journal of Environmental Systems, 6, 329– 341.

Winett, R.A., Neale, M.S., & Grier, H.C. (1979). The effects of self-monitoring and feedback on resi- dential electricity consumption. Journal of Applied Behavior Analysis, 12, 173–184.

Winett, R. A., & Nietzel, M. T. (1975). Behavioral ecology: Contingency management of consumer energy use. American Journal of Community Psychology, 3, 2, 123- 133.

Winkler, J.R. (1964). A book of beetles. Spring Books, Greenford, Middlesex, England.

Wirth, Louis. 1938. "Urbanism as a way of life." American Journal of Sociology 44:1-24.

Wu, J. (2004). Using Sciences to Improve the Economic Efficiency of Conservation Policies. Agricultural and Resource Economics Review, 33(1), 18-23.

Yajima, M. (2007), Breeding fireflies at Tama Zoo: An ecological approach, Der Zoologische Garten, 77(2), Pages 84-95

Yemang, Yang, X., & Yang, G. (2001). Shi jing. Beijing: Wai wen chu ban she.

Yuma, M. (2007). ORIGINAL ARTICLE: Effect of rainfall on the long-term population dynamics of the aquatic firefly Luciola cruciata. Entomological Science, 10, 3, 237-244.

- 159 -

Appendix A: Survey

- 160 - Dear Watershed Resident,

We are contacting you because you live in or own property within the North Fork Subwatershed of the Sugar Creek Watershed. The Sugar Creek is a river that originates just north of Smithville and goes through Kidron on its way to the Muskingum River at New Philadelphia, draining an area of land (called a “watershed”) that is approximately 350 square miles. The North Fork Subwatershed includes areas between Kidron and Mount Eaton, draining an area of approximately 17 square miles.

About 8 years ago the Ohio Environmental Protection Agency (EPA) had released a study concluding that the Sugar Creek ranked as one of the most impaired streams in the state. They have been working on watershed restoration plans for all rivers and streams in Ohio. We performed a survey between the years 2000 and 2003 in an effort to start discussions about the future of the Sugar Creek with the views of those of us who live and work in this watershed. Thanks for your help on that and the water quality improvements being made on the North Fork Watershed.

Our goal was to collect information on what local residents think should be done regarding the North Fork Subwatershed, and to assist local residents in furthering their goals, their values, and their vision of its future. We think it is important to do a follow-up survey to see the changes of people’s attitude about pollution, water quality, and farming during this 8-year period. In addition, we will respond to all of you who might be interested in joining a local watershed group or making changes individually along your section of the stream.

We helped people living in the Kidron area to measure the nitrate in their wells-both before and after the new waste water treatment plant was put in. We also cooperate with the Wayne County SWCD on the North Fork Task Force.

Funding for this survey comes from an OARDC Seed Grant. Our hope is that the results will help to improve future policy locally and in the State of Ohio.

The survey will take you approximately 30 minutes to complete. Attached is a map of the North Fork Subwatershed; have fun finding your place in the area. We think that local people in this area have the creativity and ability to improve our common quality of life. Thank you very much for your help. By completing this survey, you are providing a local perspective on the issues relating to the North Fork Subwatershed. All information that you provide to us will be used for statistical analysis only and will remain strictly confidential. Your participation in this study is completely voluntary, but our results will be most useful if we hear from everyone who receives a questionnaire. If you want additional information on issues of environment conservation in the North Fork, if you want to explore what you might do as an individual living alongside the streams, or if you are interested in joining the local watershed group, please contact us.

If you have questions or comments about this survey, please contact my advisor, Dr. Richard Moore.

Sincerely,

Richard Moore Yang Xing Professor, Human and Graduate Student, Community Resource Environment Science Development/OARDC Tel. Graduate Program, (330) 202-3538 The Ohio State University, Columbus, Ohio 43210 Tel. (330) 202-3538. (OVER)

- 161 -

- 162 - North Fork

Subwatershed

(OVER)

- 163 -

What improvements would you like to see in the future in the North

Fork watershed of Sugar Creek?

______

______

______

______

______

______

______

______

______.

- 164 - How to complete your survey:

This survey is divided into 3 parts, Part 1, Part 2 and Part 3. We ask all people to complete Part 1 & Part 2. If you are a farmer and/or own a farm, we ask that you also complete Part 3. There are two columns of questions on each page; Please start with the left column and move to the right column of each page. When you are finished, place your survey into the bag or envelope provided and leave it on your front door. Please leave it sticking out from under your door, hanging from the doorknob, or somewhere convenient for you and easy for us to find.

Types of questions in the survey: There are 3 kinds of questions on the survey Some will ask you to use a 5-point scale to “rate” your answer by selecting one of the numbers to show how strongly you feel about your answer. For Example: How important are farming magazines to you? (1=Not Important, 5=Very Important)

Some ask you to select from a list by checking options provided below. For Example: What activities do you perform daily? Please check all that apply.

Some ask you to fill-in a brief answer.

At any point during the survey, we ask you to add your comments on the side or the back of the survey. Your comments can be about anything you think is important for us to know, especially if you found a particular question difficult or poorly put together. (OVER)

- 165 - Part 1

Doing Already Yes No 1. What are you willing to do in order to improve the water/environment quality in the

watershed?

Work on an individual basis to make environmental improvements on the stream on your property

Form a small group with immediate neighbors to improve the stream quality based on your own priorities

Construct a tree or grass buffer along the stream

Make or improve habitat for fish in the North Fork

Attend information meetings on water quality in your community

Read newsletters, magazines or other publications written by environmental groups

Become a member of a group whose main aim is to preserve or protect the environment

Vote for candidates in local elections that support watershed protection and restoration efforts

Sign a petition in support of protecting the environment

Volunteer time to restore wetlands in your community

Give money to an environmental group

Write a letter or call your member of Congress or another government official to support environmental protection

Roadside trash removal

Other, please specify ______

Disagree Strongly Neutr Agree Strongly 2.Tell us your views of the following statements

al

On a scale of 1 to 5, with 1 being “Strongly Disagree” and 5 “Strongly Agree”, please assess your views of the following statements by circling your choice: At the present time, Sugar Creek is polluted. 1 2 3 4 5

Any improvements in stream water quality should begin upstream so changes can be measured downstream. 1 2 3 4 5 The scenic beauty of Sugar Creek should be protected even if landowners have to change management 1 2 3 4 5 practices. The economic viability of Sugar Creek farmers is more important than environmental quality in the watershed. 1 2 3 4 5 I would be willing to pay higher prices in order to protect the environment. 1 2 3 4 5 I would be willing to pay higher taxes in order to protect the environment 1 2 3 4 5 I would be willing to accept cuts in my standard of living to protect the environment. 1 2 3 4 5

The environmental movement does a great deal of good 1 2 3 4 5 The environmental movement does more harm than good 1 2 3 4 5 3.Who should make future decisions regarding Sugar Creek? Please check all that apply.

Federal officials State officials Local officials A coalition of local Individuals who own Other, please explain______

citizens and officials property along the streams

- 166 - 4. How much do you trust each of the following agencies or 7. Different living organisms have different tolerance levels organizations working in your community? for the environment. How do you perceive the sensitivity to On a scale of 1 to 5, with 1 being “do not Do Trust the environment/water quality for the following species? trust” and 5 “trust very much”, please assess your trust of the following not very agencies by circling your choice:

trust Much Very Bad Neutral GoodVery Environment On a scale of 1 to 5, with 1 EPA 1 2 3 4 5 being “Very Bad Environment” and 5 “Very Good US Department of Agriculture 1 2 3 4 5 Environment”, please assess Environment your view of the following Ohio Department of Agriculture 1 2 3 4 5 species by circling your choice:

Soil and Water Conservation District 1 2 3 4 5

Muskingum Watershed Conservancy 1 2 3 4 5 District For example: 1 2 3 4 5 Leech Wilderness Center at Wilmot 1 2 3 4 5 Salamander 1 2 3 4 5

Ohio State University Extension 1 2 3 4 5 Trout 1 2 3 4 5

OARDC Experiment Station 1 2 3 4 5 Midges 1 2 3 4 5

Farm Bureau 1 2 3 4 5 House Fly 1 2 3 4 5

Ohio Department of Natural Resources 1 2 3 4 5 Snail 1 2 3 4 5 (ODNR) Earthworm 1 2 3 4 5 County Health Department 1 2 3 4 5 Firefly 1 2 3 4 5 County Commissioners 1 2 3 4 5 Mayfly 1 2 3 4 5 North Fork Task Force 1 2 3 4 5 Dragonfly 1 2 3 4 5 Township Trustees 1 2 3 4 5 Stonefly 1 2 3 4 5

Mosquito 1 2 3 4 5 5. Please describe any positive or negative experiences you Slug 1 2 3 4 5 have had with these agencies, or make comments: Lady Beetle 1 2 3 4 5

Butterfly 1 2 3 4 5 ______Crayfish 1 2 3 4 5

Bee 1 2 3 4 5

6. Please list any other agencies/organizations that you have Grasshopper 1 2 3 4 5 interacted with. Aphid 1 2 3 4 5

Potato Beetle 1 2 3 4 5

______Caddis fly 1 2 3 4 5

(OVER) - 167 - 8. To what extent do you identify with each of the following 3. How many people do you know in the following social groups? categories?

Do not Stronglyidentify with All them of Most of them Some of them fewVery None them of On a scale of 1 to 5, with 1 being “do not On a scale of 1 to 5, with 1 being “All of

identify with” and 5 “strongly identify identifywith them” and 5 “None of them”, please give

with”, please indicate the extent to which us your views on each of the following:

you identify yourself as: Kids in your immediate neighborhood who 1 2 3 4 5

you know by name. Hunters 1 2 3 4 5 People living in your community 1 2 3 4 5 Fishermen 1 2 3 4 5 Friends who live in your community 1 2 3 4 5 Relatives,wholive in your community 1 2 3 4 5 Gardeners 1 2 3 4 5 Bird watchers 1 2 3 4 5 Farmers/Livestock producers 1 2 3 4 5 4. How often do you use the following Persons of faith 1 2 3 4 5 tools/technologies/facilities?

Gun rights advocates 1 2 3 4 5 Never Annually Monthly Weekly Daily On a scale of 1 to 5, with 1 Property rights advocates 1 2 3 4 5

being “Never” and 5

“Daily”, please let us know

Conservatives 1 2 3 4 5 how often you use each of Liberals 1 2 3 4 5 the following: Conservationists 1 2 3 4 5 Landline telephone 1 2 3 4 5 Environmentalists 1 2 3 4 5 Cell phone 1 2 3 4 5

Part 2 Computer 1 2 3 4 5

Finally, we need to ask a few questions about your Internet 1 2 3 4 5 background. This information, as with all information in this survey, will be used for statistical analysis only and will Restaurants 1 2 3 4 5 remain strictly confidential. Recycle 1 2 3 4 5 1. Which of the following values are important to you? Solar panel 1 2 3 4 5

Important Not Important Very On a scale of 1 to 5, with 1 being Medical services 1 2 3 4 5

“Not Important” and 5 “Very Important”, please give us your

Carpool 1 2 3 4 5 views on each of the following: Religious faith and values 1 2 3 4 5 5. Which of the following values are important to you?

Important Not Very Economic security 1 2 3 4 5 On a scale of 1 to 5, with 1 being Important

“Not Important” and 5 “Very Family ties 1 2 3 4 5 Important”, please give us your

views on each of the following: The good of the community 1 2 3 4 5 Religious faith and values 1 2 3 4 5 Conservation of natural resources 1 2 3 4 5 Economic security 1 2 3 4 5 2. How do you define your community in terms of Family ties 1 2 3 4 5

The good of the community 1 2 3 4 5 geographic boundaries?(For example: within 1 mile of my Conservation of natural resources 1 2 3 4 5 house)______

- 168 - 6. Do you agree or disagree with the following statements about your community?

Disagree Strongly Agree Strongly On a scale of 1 to 5, with 1 being “Strongly Disagree” and 5 “Strongly Agree”, please give

us your views on each of the following:

I feel relaxed when I’m in my community. 1 2 3 4 5 I feel happiest when I’m in my community. 1 2 3 4 5

I really miss this community when I’m away from it for too long. 1 2 3 4 5

I feel that I can really be myself in my community. 1 2 3 4 5

My community reflects the type of person I am. 1 2 3 4 5

My community is the best place for doing the things that I enjoy most. 1 2 3 4 5

As far as I am concerned, there are better places to be than in my community. 1 2 3 4 5

The schools are good and safe. 1 2 3 4 5

This is a safe place to live. 1 2 3 4 5

I trust my neighbor. 1 2 3 4 5

There is very little crime or drug use here. 1 2 3 4 5

Neighbors help each other in time of need. 1 2 3 4 5

The quality of life is very good. 1 2 3 4 5

Local government is good at responding to problems. 1 2 3 4 5

The local economy is strong. 1 2 3 4 5

It is easy for me to tell a stranger in my community from somebody who lives here. 1 2 3 4 5

I really feel a part of my community (instead of its being just a place to live). 1 2 3 4 5

7. Do you have any previous experience with a conservation program? If so can you describe the experiences in a few words?

Never Annually Monthly Weekly Daily 8. How often do you perform the following behaviors?

On a scale of 1 to 5, with 1 being “Never” and 5 “Daily”, please give us your views on

each of the following:

Make a special effort to buy foods grown without pesticides or chemicals 1 2 3 4 5

Make a special effort to buy paper and plastic products that are made from recycled 1 2 3 4 5

materialsAvoid buying products from a company that you know may be harming the environment 1 2 3 4 5

Make trips to town/shopping center 1 2 3 4 5

Make a special effort to buy household chemicals such as detergent and cleaning solutions 1 2 3 4 5

that are environmentally friendly

(OVER)

- 169 - 9. What social group(s) do you belong to? (check all that apply) 21. Which best describes your Ethnic heritage?(Check one)

Farmer Bureau Oat threshing ring African American German Scotch Irish

North Fork Task Force Corn silo filling ring Asian American Irish Swiss

Fraternal Organization Church quilting bee Hispanic/Latino Middle Eastern White

Women Club School board (Parochial) English Native American

Hunting/Fishing Organization School board (Public) French Other, please specify______

Veterans Organization School quilting bee 22. What is the occupation of the person responding to the survey? (check one)

Craftsman Organization Political Organization Farmer Domestic Homemaker

Chamber of Commerce Arts Organization Skilled Tradesman Factory worker Ohio Trapper Association Garden/Outdoor/Nature Organization

Construction worker Small/Home Business Other, please specify ______owner

Professional Retired

10. Who is the person answering this survey? Are you a: Other, please specify ______

Head of household

23. What is your religious affiliation? (check one) Spouse of head of household Apostolic Mennonite Other, please specify:______Lutheran New Order Amish

11. Marital Status 12. Sex of respondent Methodist Old Order Amish Married Female

Not Married Male Presbyterian Swartzentruber Amish

Roman Catholic Other, please specify 13. Number of children 14. Number of years you have ______under the age of 18 ______lived in the community ______24. What is your annual income? (check one)

15. How many local 16. Do you expect to be living in organizations are you a member this community 2 years from Less than $24,999 $125,000 - $149,999 of______now?______

17. Age of the head of 18. Do you own your property or $25,000 - $49,999 $150,000 - $174,999 household_____ do you rent it?______

$50,000 - $74,999 $175,000 - $199,999 19. Your education level: 20. Do your children go to:

8th Grade Public school $75,000 - $99,999 more than $200,000

High School Charter school Thank you for sharing this information and your views with Some College Parochial school us. We will use this information for statistical analysis only, College Graduate Amish one-room school and your responses will remain strictly confidential. If you are a farmer or own a farm, please go on to complete Section Graduate Degree Other, please specify ______3. If you are a non-farmer, you have now completed the

survey. However, please use the last page of the survey to make any additional comments you wish to make. 170

Part 3 8. About how many total acres do you usually cultivate in one year? _____ Please complete this section if you are a farmer, a retired farmer, or live on a farm. 9. Ten years from now, what do you plan to do with your 1. Please list farmland? (check one) conservation practices Continue farming by myself

that you are interested Already

Doing Continue farming by my children or spouse in. Please check all

Yes

No without selling that apply.

Lease or rent out the land to another farmer Grass waterways without selling

Buffer strips Sell to my children, or other relatives Managed grazing Sell to another farmer Sell for development Livestock exclusion fencing Subdivide part for development but keep some No-till of it for farming

Conservation cropping Other, please explain______

Cover crops 10. In the past, have you received technical information regarding conservation practices for your farm? Grass/legumes rotation NO contour strip cropping YES, please specify from whom______Manure management 11. In the past, have you received financial assistance Manure trading for conservation practices for your farm? NO Water quality trading YES, please specify from whom______Other, please specify ______12. In the spaces below, please estimate the percent of 2. About how many days per year does the head of gross sales from each of the following farm products household/spouse of the head of household work off- provide. farm for wages or salary? What is the job? Corn Poultry Days per year Off-farm job Soybeans Sheep work off-farm Head of household Wheat Hay Spouse of head of household Oats Fruits

3. What percent of your total net household income Dairy Vegetables comes from off-farm work? (check one) 0 - 10% 51 – 60% Beef Other

11 – 20% 61 – 70% Hogs

21 – 30% 71 – 80% Thank you for your cooperation! If you have any additional 31 – 40% 81 – 90% comments on any of the questions we asked, please use the remaining space on this page. 41 – 50% 91 – 100%

4. How many years have you and your spouse operated your farm? _____ 5. How many acres of farmland do you own that is farmed? _____

6. How many acres of land do you rent for agricultural purposes? _____

7. How many acres of land do you lease or rent-out to others for agricultural purposes? _____

171