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Recreation Specialization and Reports of Potential Impact Behaviors among Birders Attending Birding Festivals


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RECREATION SPECIALIZATION AND RE PORTS OF POTENTIAL IMPACT BEHAVIORS AMONG BIRDERS A TTENDING BIRDING FESTIVALS BY HENRY R. BIRELINE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2005

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Copyright 2005 by Henry R. Bireline

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Dedicated to those that believed in me…and to those that didn’t.

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iv ACKNOWLEDGMENTS The successful completion of this thesis would not have been possible without the help and support of numerous loved ones. I would like to thank my advisor, Dr. Stephen Holland, and my committee members, Dr. John Confer and Dr. Taylor Stein, for their guidance, expertise and friendship. I am i ndebted to my assistants, Krista Anderson, Suzie Gould, Chris Lennon and Joshua Watson for their hard work and professionalism, which was critical to my success. Add itionally, I would like to thank Dr. Stephen Humphrey and the staff at the School for Natural Resources and the Environment. I appreciate the encouragement and flexibility from Santa Fe Community College, so I could work full-time while working on my master’s degree. I especially want to thank my colleagues in the Zoo Animal Tec hnology Program. They are like family to me and I am touched by their generous support. Certainly, I want to recognize several peopl e that continually motivate me in my life. I am a better person because of them and they will always serve as a source of inspiration. They are Mom, Shannon, Gra ndma Carolyn, Russ, Dr. Ron Serfoss, Dr. Alan Maccarone, Mary and Craig Chambers, th e late George and Mildred Rewerts. I’d like to thank them for always believing in me. Finally, I want to thank Cla udia Hardy for the type of love others can only dream about. I am fortunate to be blessed with such a wonderful gift from God.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES............................................................................................................vii ABSTRACT....................................................................................................................... ix CHAPTER 1 INTRODUCTION........................................................................................................1 Objectives..................................................................................................................... 4 Definitions.................................................................................................................... 5 2 LITERATURE REVIEW.............................................................................................8 Recreation Specialization.............................................................................................8 Potential Impact Behaviors.........................................................................................12 3 METHODS.................................................................................................................19 Hypothesis Statement.................................................................................................19 Survey Instrumentation...............................................................................................19 Study Areas.................................................................................................................19 Participants.................................................................................................................20 Sampling Strategy.......................................................................................................20 Specialization Variables.............................................................................................21 Potential Impact Behavior Variables..........................................................................22 Demographic Variables..............................................................................................25 Data Analysis..............................................................................................................26 4 RESULTS...................................................................................................................31 Dimensional Indexes..................................................................................................33 Potential Impact Behaviors.........................................................................................37 Relationships and Results of Hypothesis Testing.......................................................40

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vi 5 DISCUSSION.............................................................................................................55 Summary of Results....................................................................................................55 Potential Implications.................................................................................................56 Pertinent Issues to Consider........................................................................................58 Limitations..................................................................................................................60 Conclusions.................................................................................................................61 APPENDIX A ON-SITE BIRDER RECREATION SURVEY IN FLORIDA..................................62 B FLORIDA BIRDING FEST IVALS – SPRING 2004................................................66 C ON-SITE BIRDER RECREATION SURV EY: VERBAL CONSENT SCRIPT......67 D POST-SURVEY CONTACT INFORMATION........................................................68 LIST OF REFERENCES...................................................................................................69 BIOGRAPHICAL SKETCH.............................................................................................74

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vii LIST OF TABLES Table page 1 Participant Interviews at Each Study Site................................................................21 2 Items Used to Construct a Specialization Indexa.....................................................23 3 Potential Impact Behavior Variables........................................................................24 4 Frequency Summary of 'Other' Methods of Observing Birds..................................25 5 Reliability Analysis for Special ization Dimensions (Z-scores)...............................27 6 Reliability Analysis for Overa ll Specialization Index (Z-scores)............................28 7 Correlation Matrix of Individual Recreation Specialization Items..........................29 8 Socio-demographic Character istics of Participants..................................................32 9 Means and Standard Deviations for Se gmented Recreation Specialization Index and Education...........................................................................................................33 10 One Way Analysis of Variance for Recr eation Specialization Index on Level of Education..................................................................................................................33 11 Frequency Summaries for Experience Specialization Items....................................34 12 Frequency Summaries for Equipment and Economic Commitment Specialization Items.................................................................................................35 13 Frequency Summaries for Centrality to Lifestyle Specialization Items...................36 14 Frequency Distributions (Percentage) for Reports of Potential Impact Behaviors..39 15 Frequency Distribution (Percentage) for Reports of Group Noise Level................39 16 Means and Standard Deviations for Se gmented Experience Index and Nineteen Dependent Variables................................................................................................41 17 One Way Analysis of Variance for E xperience Index on Nineteen Dependent Variables...................................................................................................................42

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viii 18 Means and Standard Deviations for Segmented Equipment and Economic Commitment Index and Ninet een Dependent Variables..........................................44 19 One Way Analysis of Variance for Equipment and Economic Commitment Index on Nineteen Dependent Variables..................................................................45 20 Means and Standard Deviations for Se gmented Centrality to Lifestyle Index and Nineteen Dependent Variables..........................................................................48 21 One Way Analysis of Variance for Cent rality to Lifestyle Index on Nineteen Dependent Variables................................................................................................49 22 Means and Standard Deviations for Se gmented Recreation Specialization Index and Nineteen Dependent Variables..........................................................................51 23 One Way Analysis of Variance for Recr eation Specialization Index on Nineteen Dependent Variables................................................................................................52

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ix Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science RECREATION SPECIALIZATION AND RE PORTS OF POTENTIAL IMPACT BEHAVIORS AMONG BIRDERS A TTENDING BIRDING FESTIVALS By Henry R. Bireline May 2005 Chair: Stephen Holland Major Department: Natural Resources and Environment Recreation specialization theory has been useful in understanding the behavior of outdoor recreationists. The theory has been associated with a greater interest and involvement in conservation as participants move on a continuum that ranges from the general to the specialized. As recreational opportunities conti nue to evolve, it is essential to consider the potential impacts of partic ipant behavior. Consequently, the purpose of this study was to collect self -reported information from bi rdwatchers and investigate significant relationships betw een recreation specialization and their potential impact behaviors. Data for this study were collected from a total of 184 birders who completed onsite interviews at three separate birding fe stivals in central and north Florida with a response rate of 83%. This study utilized three i ndividual dimensional indexe s and an overa ll recreational specialization index to assess any relationship between partic ipant self-reported impact

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x behaviors. Results indicated statistically significant relations hips among all four indexes and several potential impact be haviors. Specifically, the anal ysis showed that some selfreported potential impact behaviors increased as the specialization continuum went from the general to the specialize d. This contradicted the st udy’s hypothesis that advanced birders would report the lowest frequency of potential impact behaviors. When looking further at the issue of severi ty of potential impacts, this study seemed to support an advanced birder belief that the perceive d benefits of observing birds outweigh the perceived liabilities of birders’ actions. Recreation specialization theory may not be appropriate for use in determining if participant behavior in the field reflects the concern for wildlife. Someone’s concern for birds does not necessarily equate with beha viors that reduce huma n impact. However, this study does indicate the importance of communication from managers as birders become more specialized. Educational pr ograms may need to focus more on potential impact concerns. Additionally, ways to motiv ate birders to reduce impacts may need to be addressed in conjunction with educational activities.

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1 CHAPTER 1 INTRODUCTION Millions of people engage in watching w ildlife every year. Birdwatchers (also known as birders) represent 80 percent of th is population (American Birding Association 1996), making them an important subset of outdoor recreationists. Traditionally classified as nonconsumptive wildlife enthusia sts, birders are committed participants who devote large amounts of time and money to th eir activity. They drive ecotourism and have influenced the development of recrea tion areas throughout North America (Baicich et al. 1999). States such as Texas and Florida have sponsored ambitious birding programs to help fill the demand for nonc onsumptive recreational opportunities. Extensive birding trails are maintained throughout these two states. As more people participate in outdoor recreation program s, there is a significant need for information that assesses their impact Baicich et al. (1999) reported that birding is growing in popularity faster than hi king and backpacking. Additionally, they suggested that aging baby boo mers would significantly increa se the population of birders in the coming years. Cordell et al. (1990) pr edicted that birding and other related forms of wildlife watching (i.e.,, photogr aphy) would increase 82% by 2040. This increase in activity can have a pos itive impact. Most communities desire the economic benefit of attracting tourists. Kerli nger and Brett (1994) stat ed that birding has been especially rewarding in small town s and rural areas such as Hawk Mountain, Pennsylvania. Birders, who are attracted to the local raptors, add four mill ion dollars to the economy annually. Additionally, Duffus a nd Dearden (1990) noted that activities like

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2 birdwatching might stimulate positive attitudes towards c onservation, thereby benefiting wildlife and habitat preservation initiatives. Despite the positive attribut es of birdwatching, the notion of birders as true nonconsumptive enthusiasts ha s been rejected. Birder s are unlike traditional consumptive recreationists (i.e., hunters), in that they are not killing and removing animals from a population. However, potentia l impact behaviors and the negative effects of nonconsumptive outdoor re creation have been well doc umented (Boyle and Samson, 1983). Wilkes (1977) noted that nonconsump tive users consume resources along spatial, visual and physical dimensions. An array of actions such as illegal motor or bicycle use, illegal parking, litter, excessive noise, improper human wa ste disposal, pet use, vandalism to property, vandalism to the environment (pulling up plants, carving into trees) and trespassing off trails can be used as indicat ors of impact behavior. Wilkes (1977) has been quoted saying, “Point Pelee National Park in Ontario has been hammered by birdwatchers” (p.346). Boyle and Samson (1985) suggest that ac tivities like birding may present more risks to wildlife than other recreational pur suits. They described how some birders competitively pursued birds in order to complete checklists of achievement. McFarlane (1994) suggested advanced bird ers had motivations similar to advanced hunters in that each group has specific goals of pursuing and “bagging” prey. Burger et al (1995) observed people chase hawks, owls and small birds at the Forsythe National Wildlife Refuge (New Jersey) in order to get a closer view. Klein et al., (1995) noted significant changes in distributions of waterbirds due to vehicular traffic at the Ding Darling National Wildlife Refuge (Flori da), a popular area for birding.

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3 People are crowding popular sites in Nort h America, such as Cape May, New Jersey and High Island, Texas at certain times of the year in order to observe bird migrations (Baicich et al. 1999). Oftentimes, managers are challenged with the issue of providing access to increasing bi rder populations, while at th e same time protecting the birds and their habitat. Consequently, managers may fi nd it useful to learn more about recreation specialization among birders, so they can create strategies to reduce potential impacts. Although there have been many studies usi ng recreation specialization theory and many on human disturbance to wildlife, to my knowledge, there are no studies that attempt to link recreational specialist groups and any corresponding impact behaviors. Wellman et.al (1982) may have come the clos est with a study anal yzing specialization theory and attitudes towards depreciative behaviors in canoe ists. The research proposed in this investigation will attempt to descri be relationships between specialized birder groups and their self-reported impact behaviors. Social scientists have found recreation sp ecialization theory to be useful in understanding behaviors of r ecreationists. Bryan (1977) conceptualized recreation specialization theory in order to differentiate behaviors in trout fi sherman. He theorized that trout fisherman would progress on a continuum of be havior that goes from the general to the specialized. The value of this theory becomes significant to a manager because it can be used to help predict certain types of participati on in an activity. Knowing the degree of specialization means mana gers may need to provide a vari ety of opportunities to the same type of recreationist. In the case of bird watching, managers have developed viewing

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4 opportunities from cars, walking trails and b linds. Furthermore, initiatives such as backyard-habitat programs, birding festival s and birding competitions suggest that managers have recognized variation in bi rder specialization. Since these types of specialized programs are used to attract birder s into the activity, it seems plausible that recreation specialization theory can also be used to predict potentially negative behaviors carried out by the participants. Objectives This research focused on data collected fr om interviews during birding festivals in the state of Florida. One category of inform ation concentrated on i ndicators that classify individuals on a degree of bi rder specialization. Previ ous recreation specialization studies such as Bryan (1977), Wellman et.a l (1982), Virden and Schreyer (1988) and McFarlane (1994) served as models for the development of this study. Another category of information concentrat es on self-reported participation in activities that potentially have (either direct or indirect) negative impacts on birds. The impact behaviors are sub-divided by those that the birding community deems negative and by those that have been scientifically documented to bring about potentially negative responses in birds. A final category of information will concentrate on birder demographics. The reports of impact behaviors will be recorded and statistically analyzed to see if there is a relationship between degrees of specialization among birders. The primary objectives of this project are the following: 1. Identify four categories of birders (cas ual, novice, intermediate and advanced) 2. Record their personal reports of potential impact behaviors

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5 3. Determine any significant relationship (if any) between categories of birders and their self-reported poten tial impact behaviors. If recreation specialization theory is relate d to potential impact behaviors, it would be incorrect to assume that an increase in potential impact behavior s is ‘progress’ on the specialization continuum. Consequently, one might expect an inverse relationship between recreation specialization and potential impact behaviors. In this case, advanced birders should report the lo west frequency of potential impact behaviors and this hypothesis will be tested in this study. Definitions By utilizing previous recreational specia lization frameworks, a model was created to describe the relationship between specific categories of birders and their reports of potential impact behaviors (Figure 1). Units of analysis were i ndividual birders who participated in an intercept interview and are distinguished on a sp ecialization continuum as casual, novice, intermediate and advanced. Specialization was defined using a multidimensional construct incorporating bird ing experience, equipment and economic commitment and the role birding plays in one’s life (centrality to lifestyle). Other variables studied were the reports of potential impact behaviors. Like Wellman et.al (1982), this study viewed imp act behaviors as a re lative concept that depends upon the values of th e group within which the act occurs. Consequently, acts that birders considered deviant and acts that have been proven to have either direct or indirect negative impacts to birds were reco rded. For example, the American Birding Association’s (ABA) Code of Birding Ethics (2004) states that birders should stay on trails, keep a distance from birds (and their nests), limit the use of recordings for attracting birds and respect the regulations of the area.

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6 Previous scientific studies are also used to define potential im pact behaviors when potentially negative bird reacti ons were observed in the field. For example, Burger et.al (1995) recorded a wide variety of responses to ecotourist disturbances in coastal habitats. Due to variables such as the number of people, viewing distances and methods of observation, some of the negative bird re sponses to humans included abandonment of suitable foraging sites, interruption of in cubation, separation of parents from young and disturbance of prey species. In the following chapter, literature will be presented that will examine the potential impact behavior definitions and review th e recreation specialization theory. Besides serving a bibliographic function, the incl usion of preceding research will aid in contextualizing this study within the evol ving body of material on these subjects.

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7 Specialization Dimensions Index Potential Impact Behaviors Figure 1: Research model Equipment & Economic Commitment Centrality To Lifestyle Defined By Both Peer Group and Scientific Observatio n Recreation Specialization Index Experience ANOVA

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8 CHAPTER 2 LITERATURE REVIEW Recreation Specialization Bryan (1977, 1979) was the first to con ceptualize the theory of recreation specialization. In an effort to categorize individuals in outdoor recreation activities, Bryan (1979) stated that recr eation specialization occurred as “a continuum of behavior from the general to the particular, reflected by equipment and skills used in the sport and activity setting preferences” (p.29). He s uggested that positive reinforcement caused participants to repeat their behavior in a recreational activ ity. Additionally, Bryan noted that as involvement in an activity increas ed, motivation for continuance moved away from external rewards to more introspective rationale. Using indicators such as equipment, skills attitudes and site preferences, Bryan (1977) categorized trout fisherman on a degree of angling sp ecialization. After compiling the results, Bryan categorized four ty pes of anglers. They were from general to specialized: occasional fishermen, genera lists, technique specialists, and techniquesetting specialists. Despite some difficulties (such as disti nguishing between cert ain respondents, like the technique specialist and th e technique-setting specialist) there was enough evidence to suggest the use of recreati on specialization as a valid theo retical construct. Fishermen were going from the general to the specialize d. For example, fishermen moved into more specialized experiences over ti me, and they became more "socialized" into the fishermen

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9 fraternity. Their attitudes a nd values shifted from attaini ng a "bag-limit" to preservation and enjoyment of the setting. Additionally, sp ecialists became more resource dependent. Bryan’s (1979) monograph proposed logica l frameworks of specialization for various outdoor activities su ch as, photography, backpack ing, mountain climbing, skiing, canoeing, birdwatching and hunting. Alt hough not empirically grounded, it was accepted as having the potential to explain participant variability within an activity. Furthermore, it opened the door for more meticulous testing from other scientists. Bryan (2000) later revisited recreation specialization theory in an effort to stimulate discussion and consideration of new ap plications for the 21st century. He reflected on issues such as the drive to specialize and the potential hazar ds of specialization (i.e., addiction). Additionally, he initiated disc ussions about applying specializ ation theory to non-leisure activities such as career manage ment and personal relationships. The ability to apply recrea tion specialization theory to a variety of outdoor recreational activities ma kes it popular with leisure researcher s. For example, it has been used in studies of boating (D onnelly et al. 1986; Cottrell et al. 2004), sailing (Kuentzel and Heberlein 1997; Aversa 1986), backpack ing (Virden and Schreyer 1988), hunting (Kuentzel and Heberlein 1992), camping (M cFarlane 2004), fishing (Chipman and Helfrich 1988) and birding (Sco tt et.al 1999; Hvenegaard 2002). McFarlane (1994) used specialization theo ry to investigate motivations behind birding. The logic behind her study was that by knowing the shifts of goals and motivations, managers could make bette r decisions about wildlife recreation involvement. Several hypotheses were test ed that addressed birder specialization, satisfaction, motivations and differential effect s on motivations. Indicators of birding

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10 specialization included past expe rience, economic commitment and centrality to lifestyle. Results showed that there was a specialization of birdwatchers that she categorized as casual, novice, intermediate and advanced. Goals of birders (traditiona lly thought of as nonconsump tive recreationalists) were found to be similar to hunters (consumptive recreationalists). They had multidimensional motivations of affiliative goals, appreciati ve goals, conservation goals and achievement goals. Furthermore, advanced birders s howed a primary motivation of achievement, whereas casual birders tended to have a pr imary motivation to support conservation. Evidence suggested that specia lization was associated with goal-orientation shifts. One of the few studies to address specia lization and negative behaviors in outdoor recreationists was done by Wellman, et.al (1982). In this study, canoeists favoring mild whitewater rapids were sent questionnaires that examined attitudes of depreciative behaviors. Additionally, ques tions addressing canoeing invest ment, past experience and centrality to lifestyle were us ed to indicate levels of speci alization. Using a modification of Bryan’s (1979) hypothesis, th e authors tested to see if highly specialized canoeists would have different attitudes towards depr eciative behavior. Furthermore, like Bryan, they hypothesized that high-level canoeists w ould have greater concern for conservation. The authors noted significant methodologica l and theoretical issues that likely contributed to their findings of only limited support for the hypothesis. Because research (Hvenegaard 2002) has pa rtially supported greater interest and involvement in conservation in the more spec ialized recreationists, Bryan’s (1979) theory might be used to see if participant behavior in the field reflects a greater concern for conservation. Casual and novice birders might be expected to behave with the least

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11 concern for the environment and therefore carry out more potential impact behaviors. On the other hand, if McFarlane’ s (1994) assessment of adva nced birder motivation is correct (the achievement of viewing birds), one might expect the advanced birders to carry out more potential impact beha viors in their effort to “bag” a bird for their life list. It should be noted that recr eation specialization theory c ontinues to evolve. Scott and Godbey (1994) moved away from the tr aditional outdoor recreat ion setting by using the specialization construct in the social worl d of contact bridge. Looking at the social worlds of social bridge a nd serious bridge, the authors focused on the meaning of participation and how it was reflected in each st yle of play. The results of the analysis showed that the typical recr eation specialization trends did not apply. The authors stressed that in some cases, bridge player s resisted specializati on along the continuum. They suggested a closer look at how the will of the participant affects the process of specialization. While most studies have developed recreati on specialization theory from attitudinal and/or behavioral factors (McIntyre 1989; W illiams et al. 1990; Choi et al. 1994; Bricker and Kerstetter 2000), Ditton et al. (1992) re -conceptualized recr eation specialization theory from a social worlds perspective. They thought this was necessary after noticing that Bryan’s (1977) definition of specializa tion was a tautology (i.e., a perpetually true statement because it contains all logical po ssibilities). Feeling that the portion of the definition, “…reflected by equipment and skills used in the sport and activity setting preferences,” was an ex planation, the authors felt obliged to rework the circular reasoning of Bryan. Consequently, a conceptual fram ework of social worlds was described as segmenting into subworld types. The inters ecting subworlds along w ith their individual

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12 members would then be arranged along a c ontinuum. A series of propositions and hypotheses were developed linking Bryan’s (1977) previous wo rk. Finally, testing using angler data and subsequent results supporte d the re-conceptualizat ion of the theory. Scott and Schafer (2001) re-conceptu alized Bryan’s (1977) recreation specialization theory by rejecting single additive index measures and using a threedimensional model of behavior, skill and comm itment. Lee and Scott (2004) tested the model using confirmatory factor analysis a nd found that the use of a three-dimensional model improved the characterization of pa rticipants in the birding activity. Consequently, they suggested co llecting data from all three di mensions, so that distinct dimensional impacts were not lost in the proc ess of combining variables into an index. Eubanks et al. (2004) used recreation speci alization theory to observe data from several birder sub-populations for the purpose of explori ng the complexities of the birding social world. While significant group differences in demographic characteristics were few, there were significant differen ces in birder behaviors, motivations and economic activity. Due to the results, the authors cautioned against the use of broad generalizations to describe an average birder, particularly if the research limits the number of birder groups being studied. Potential Impact Behaviors The effect of nonconsumptive outdoor re creation on wildlife resources has been well documented (Boyle and Samson 1983). As the demand for nonconsumptive recreational opportunities (such as birding) gr ows, managers can expect challenges in maintaining a balance betw een accessibility to recr eational opportunities and environmental protection.

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13 In a rare study that combines both ecologi cal and social aspect s of tourism-related wildlife disturbance, Kazmierow et al. (2000) addressed the difficu lty of defining and evaluating ‘unacceptable’ impacts. While sc ientific quantitative analysis of bird reactions to human activities can be considered an objectiv e means of measuring impact, there is also a subjective (qual itative) facet that plays a role on what level of impact is considered ‘unacceptable’. For example, Dela ney et al. (1999) studied the impacts of helicopter noise on owls. The authors found it necessary to recommend buffer zones in order to protect the birds from disturban ce. While this recommendation may seem like an obvious action for the noise intensity emitte d from a helicopter, the authors also found that chainsaws were actually more disturbi ng to the owls when used at comparable distances. This example is significant si nce some birders hold the opinion that it is acceptable to play audio recordings of owl voca lizations to attract c onspecifics for better identification. Since this type of noise inte nsity has not been well studied, a subjective value judgment is likely playing a role in bird er activities and could potentially be having a negative impact on the birds. The results from Kazmierow et al. (2000) suggest that models for measuring wildlife disturbances include more than quantitative data. It is generally assumed that other type s of outdoor recreati on activities impact ecosystems and wildlife more than birdwatc hing. For example, Richardson and Miller (1997) reviewed recommendations for raptor protection and found literature associating the sport of rock-climbing with severe impacts to birds of prey. While most climbers are not in direct contact with bi rds, the shouting and noise gene rated from the activity can be enough to cause some birds to abandon their nests. In a study of foraging shorebirds Thomas et al. (2003), found beachgoers with fr ee ranging dogs to be highly disturbing to

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14 natural bird behaviors. Enforcement of bu ffer zones were recommended for both of these types of activities, but managers may find it more appropriate to give birders more latitude if they have less impact. Unlike hunters and fisherman, birders don’t fit a traditional co nsumptive role by purposely removing animals from a population. Consequently, they are sometimes called nonconsumptive recreationists. However, it is important to recognize that birders are not truly nonconsumptive users. Wilkes (1977) illustrated this argument stating the consumptive nature of all recreationalists al ong spatial, visual and physical dimensions. He noted facility installation, overcrowding, trampling of vege tation and litter as just a few of the examples of disturbance. Boyle and Samson (1985) suggested that ac tivities like birding potentially present more risks to wildlife than other recreationa l pursuits. They described the importance of achievement for some birders in that birders actively pursue wildlife for their checklists, including some species that may be rare or unusual. In a thorough study of responses to ecot ourism, Burger et.al (1995) discussed a variety of coastal bird speci es and found a significant range of problems associated with human-bird interactions. De scriptions of problems focuse d mostly on encounters relating to duration and distance. Feeding, reproduction, migration, parenting, hab itat selection, nesting and incubation were all negatively a ffected by ecotourism (mainly birdwatching). Despite some evidence of short-term habitu ation to human activit y, Rees et al. (2005) found similar reactions to approach distances and frequency of dist urbances in Whooper swans. Feeding behaviors decreased as alert activity increased. Furthermore, habituation to human activity over longer pe riods of time was not supported.

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15 Several bird disturbance studies have ta ken place throughout Florida. Klein (1993) studied waterbird responses to visitor activity at Ding Darling National Wildlife Refuge on Sanibel Island, Florida. She noted differe nt responses between species. Some birds reacted significantly to distur bances, while others were more tolerant. Furthermore, reaction to humans outside their vehicles was more significant than automobile traffic. Klein (1993) included several e ducational recommendations that she felt would aid in the management of visitor disturbances. Burger and Gochfeld (1998) noted that an increase in vegetati ve cover could also aid in reducing visitor disturba nce. They observed several sp ecies of wetland birds at the Loxahatchee National Wildlife Refuge near West Palm Beach, Florida. Like Klein’s (1993) study, different species had assorted reactions to th e presence of people. Birds moved away from people, decreased their fora ging behavior and incr eased their vigilance behavior. The authors found that the volume of noise from people affected birds greater than the number of visitors alone. Seve ral species responded by retreating to nearby feeding areas that contained more vegetation and less human activity. Rogers and Smith (1997) studied Florida wa terbird reactions to various types of human disturbances. They found differences in both intraspecific and interspecies reactions to disturbances br ought on by boats, cars, all-terrain vehicles and walking. For example, the study showed that flushing distan ces were greater in wading birds than for shorebirds. Additionally, when compared to their previous study (Rogers and Smith 1995), results suggested that fora ging and loafing birds were just as likely to be disturbed as nesting birds. More than fifty percent (5 of 9) of species we re flushed at greater distances when foraging and loafing. While use of management buffer zones around

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16 nesting colonies are widespread, Rogers a nd Smith (1997) suggested a 100m distance as an adequate safeguard for fo raging and loafing waterbirds. As one can see, disturbance behaviors, whether cognizant or nave, can have a potential impact on nature. Consequently, recreation and ot her stakeholder organizations have created ethical guidelines that aim to educate others about pr oper behavior in the outdoors. For example, the United States Forest Service and the National Outdoor Leadership School partnered together to fo rmalize the creation of a national education program and awareness campaign called ‘Leav e No Trace’ (Marion and Reid 2001). The program has a two-part goal of promoti ng positive recreational experiences while reducing visitor impacts to the environment. The non-profit organization called, Leave No Trace Center For Outdoor Ethics, eventually spawned from the agreement. Th rough research and educational partnerships, they have produced a variety of educationa l materials to help promote responsible outdoor recreation. The Leave No Trace Ou tdoor Skills and Ethics booklet (Pokomy n.d.) highlights seven principles to minimi ze outdoor recreational impact. While all seven principles may be considered beneficial to a broad spectrum of recreationalists, two principles (dispose of waste pr operly and respect wildlife) ma y be particularly important to birders. In regards to waste, the Leave No Trace booklet (Pokomy n.d.) stat es to pack trash, food and litter out of activity areas and prope rly dispose of human wastes. Using bears and birds as examples, Wilkes (1977) referred to the impact of garbage at campsites, stating that it changed distributions of anim als and altered natural behaviors. Although urine is considered more of an odor problem than a health hazard, deer have been

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17 observed defoliating areas of vegetation in search of salt (Pokom y n.d.). In Meyer’s (1994) review of human defeca tion in outdoor settings, she warned of zoonotic diseases that can be transferred between humans and animals. The protozoans Giardia and Crytosporidium can be found naturally in animals and are sometimes blamed for the spread of disease in humans. However, Me yer (1994) referred to significant outbreaks that are likely linked to huma n contamination and stated that animals could be infected by human defecation as well. Ben Lawhon, th e Education Director at Leave No Trace Center For Outdoor Ethics be lieves that when some animal s come into contact with human defecation, they are posi tively reinforced to visit campsites and other areas of human activity for unnatural foods (pers onal phone conversation, October 22, 2004). Leave No Trace statements supporting a prin ciple of respect for animals included: observation of animals at safe distances, avoi dance of vulnerable hab itats and life cycles, and prohibition of feeding animals (Pokomy n.d.). Similarly, the American Birding Association has produced a Code of Birding Ethics (2004) whose principl es state, “In any conflict of interest between birds and birders, the welf are of the birds and their environment comes first”. Despite strong st atements prioritizing bird interests over human interests, very few prohibition rule s are intermingled with more numerous remarks that use encouragement to minimi ze disturbances and promote goodwill. Some of the guidelines ask to limit the use of attrac tion methods such as audio recordings, keep groups small enough to avoid impacting the e nvironment, use flash photography and light from videography sparingly, keep appropriate distances from birds to avoid stress, use natural covers and bird blinds in sensitive areas, and stay on existing pathways. More stringent language is used for principles re ferring to the law and th e rights of citizens.

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18 For example, there are references to ab ide by area regulations and rejection of unauthorized use of private property. Dress codes were not specifically mentione d in the American Birding Association’s Code of Birding Ethics (2004). However, it does ask bird ers to avoid stressing birds. Gutzwiller and Marcum (1997) noted that some birds have considerable reactions to the color of clothing. Results supported the sp ecies-confidence hypothesis, which claims birds prefer colors that matc h their own species and avoid colors that look like other species. The authors noticed l onger approach distances from some species. On the other hand, they also mentioned the possibility of a ttack if a bird feels the need to defend its territory from a ‘rival’ human being wearing th e same color. Regardless of the intent, the study shows that there is a poten tial impact to bird behavior. Since certain actions taken by humans can ha ve a direct and/or indirect effect on wildlife, it is appropriate to study them in a variety of recreationa l opportunities. More importantly, if it is to truly aid managers in the field, research needs to identify which specialization groups are carry ing out the potentially harmfu l activities. Hence, the purpose of this study is to see what type of relationship exists between birder specialization and potenti al impact behaviors.

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19 CHAPTER 3 METHODS Hypothesis Statement This study explores the rela tionships between categories of birders a nd their selfreported potential impact behaviors. Specifi cally, it uses data collected from on-site interviews to address the hypothesis statement: advanced birders should report the lowest frequency of potential impact behaviors The hypothesis will be tested on three dimensional indexes, (identified as Expe rience, Equipment and Economic Commitment and Centrality to Lifestyle) as well as on one overall recreational specialization index. Survey Instrumentation Interviews of participants were based on a survey that consisted of a three-page questionnaire that categorized a total of 26 questions in three sections (Appendix A). Sixteen questions were include d in a recreation specializatio n section; four questions, each with six to eight items addressing birder activities made up the second section; and six questions completed a third section base d on participant demographic information. Study Areas Florida is one of the most popular birding destinations in the United States and it had seven birding festivals scheduled dur ing the Spring 2004 season (Appendix B). Birding festivals were selected for data collec tion because they attract participants with a wide range of birder experience. In order to pre-test the su rvey for formatting errors and practice interview techniques, two pilot studies were c onducted. The first pilot study took place at the Orlando Wetla nds Park Festival in the Or lando/Titusville area and the

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20 second was conducted at the Pelican Island Wild life Festival in the Orlando/Melbourne area. As a result, a decision was made to de crease the font size and format the questions into columns. This decr eased the overall number of pages on the survey without changing the quantity or quality of questions. Data for analysis were collected at three birding festivals in North Florida (Waku lla Birding & Wildlife Festival Wakulla Springs, Welcome Back Songbirds Festival Brooksville, Florida 1st Coast Birding & Nature Festival St. Augustine) until a desi red number of intervie ws were recorded. Interviews were primarily conduc ted near festival registration sites, information tables and vendor booths. Occasionally, interviews took place while birders conducted their observations in the field. Participants While recreation specialization theory is acknowledged for its multidimensionality, most would say participation in birding is at least in part due to an intention to view and/or hear birds. Consequently, participan ts in this study consisted of people aged 18 and over who intended to view bi rds or take part in festival activities related to bird watching. Included in the da ta set were participants who noted that viewing birds was a primary objective. T hose who engaged in other interests and typically did birding as a s econdary activity were also in cluded. Distinctions between birders were made by using a variable that recognized the relative priority of birding versus other pursuits. Sampling Strategy On-site intercept in terviews were conducted in Ap ril and May 2004. A total of 184 birders completed the interviews at various festival sites in Flor ida: 65 (35.3%) at the Wakulla Birding & Wildlife Festival, 52 (28.3%) at the Welcome Back Songbirds

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21 Festival, and 67 (36.4%) at Florida 1s t Coast Birding & Nature Festival (Table 1). A total of 37 potential participants declined to be interviewed, resulting in a response rate of 83.3%, which is typical of on-site intervie w surveys (Babbie 1998, Midanik, et al. 2001) As participants moved through the festival grounds, convenience sampling was used to select candidates for interviews. Prior to subject part icipation, an on-site interviewer communicated pre-screening in formation and questions using a verbal consent script (Appendix C). Table 1: Participant Interviews at Each Study Site Location Frequency (N) Percentage(%) Wakulla Birding & Wildlife Festival Wakulla Springs, Florida 65 35.3 Welcome Back Songbirds Fe stival Brooksville, Florida 52 28.3 Florida 1st Coast Birding & Nature Festival St. Augustine, Florida 67 36.4 If permission was given, the interviewe r proceeded with the interview, which detailed the three-page surve y. Each interaction between interviewer and participant took no more than seven to ten minutes. Contact in formation was given to participants in case they had questions after the survey (Appendix D). A total of five trained interviewers collected data from the three festivals. Specialization Variables Generally, specialization indexes are concep tualized using Brya n’s (1977) original work. Indicators such as part icipation, equipment, skills, at titudes, preference for activity setting and commitment have been used for specialization classifica tion. Using recorded specialization models (Wellman et.al 1982, Virden a nd Schreyer 1988, McFarlane 1994), three dimensions were identified to construc t an overall recreational specialization index

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22 (Table 2). Additionally, as suggested by L ee and Scott (2004), individual indexes were created for each dimension (Table 2). An experience dimension included the vari ables: years of birding experience; frequencies of birding experiences over a week, month and year; self-rated level of birding experience; reported id entification of bird species by sight and sound; number of birds on a life list. An equipment/economic commitment dimens ion included the vari ables: number of birding items owned; equipment replacement value; number of magazine subscriptions; number of books owned. A centrality to lifestyle dimension included the variables: farthest distance traveled for birding; relative priority of birdin g versus other pursuits; degree of birding opportunities that affect choice ; life list maintenance; numbe r of memberships to birding organizations. A reliability analysis indicated that two other variab les tested (typical distance traveled and number of people in a group on a typical birding outing) were unreliable indicators for the centrality to lif estyle index. Conse quently, they were removed. Potential Impact Behavior Variables This study was designed to test the relati onships between recreation specialization indexes and twenty variables of potential imp act behaviors. For ease of organization, variables of potential impact behaviors were subdivided into two categories (Table 3). First, the potential impact behaviors that ha d been defined by peer group codes of ethics (American Birding Assoc. 2004, Pokomy n.d.) incl uded: use of food and/or water; use or wear of attractive colors; use of flash phot ography/video; unauthorized entry on private property; littering; urinating a nd/or defecating in the field; self-rated noise level.

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23 Table 2: Items Used to C onstruct a Specialization Indexa Specialization index dimension a nd variable items Cronbach Alpha Experience 0.829 1. Years of birding experience (Var 6)b 2. Frequency of birding expe rience – past week (Var 7)b 3. Frequency of birding expe rience – past month (Var 8)b 4. Frequency of birding expe rience – past year (Var 9)b 5. Self-rated level of birding experience (Var 10)c 6. Reported identification of bi rd species by sight (Var 11)b 7. Reported identification of bi rd species by sound (Var 12)b 8. Number of birds on life list (Var 13)b Equipment and Economic Commitment 0.757 1. Number of birding items owned (Var 15)d 2. Equipment replacement value (Var 16)b 3. Number of magazine subscriptions (Var 14)e 4. Number of books (Var 17)b Centrality to Lifestylef 0.690 1. Farthest distance traveled to observe birds (Var 1)b 2. Relative priority of birding versus other pursuits (Var 5)g 3. Degree of birding opportunitie s that affect choice (Var 2)h 4. Life list maintenance (Var 3)i 5. Number of memberships to birding organizations (Var 4)b aScale reliability: Cronbach’s alpha = 0.891 bMeasured on an open-ended question cMeasured on a 1-10 scale with 1=No experience and 10=Expert dMeasured by 10-item checklist. Items include: bino culars, field guide, spotting scope, bird call, recording/listening device, life list, audio recordings, computer software, internet, other eMeasured by 11-item checklist. Item s include: Birder’s World, The Auk, Bird Watcher’s Digest, Birding, Wild Bird, Living Bird, Audubon Magazine, Birds and Blooms, Ducks Unlimited Magazine, North American Birds, Other fTypical distance traveled and number of people in a group on a typical birding outing were removed due to unreliability gMeasured by 2-category question. Items included: I take specific trips to observe birds. I do birding as a side activity, on trips taken for other purposes. hMeasured by 4-category question. Items included: I rarely participate in birding outings, I participate in birding outings, but don’t have particular sites that I visit, I participate in birding outings anywhere and everywhere possible, I participate in birding outings and have favorite sites that I visit iMeasured by yes/no variable

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24 Second, the potential impact behaviors th at are defined by scientific observation (Burger et.al 1995) included: vocalized cal ls (pishing); instru ment calls; audio recordings; approaching birds; flushing birds; methods of birding such as cars, boats, walking on trails/boardwalks, off-trail walki ng, bird blinds, observation decks, off-road vehicles, and an ‘other’ variable. To avoid a reluctance to admit to potentia l impact behaviors, the questions were designed to show intensity and/ or frequency. Subsequently, participants should have felt more at ease to answer honestly than if they were asked yes or no questions. Table 3: Potential Impact Behavior Variables Two Categories of Potential Impact Behaviors Potential Impact Behaviors Defined By Peer Groups 1. Use of food and/or water 2. Use or wear of attractive colors 3. Use of flash photography or video with artificial lighting 4. Enter private property 5. Litter in the field 6. Urinate and/or def ecate in the field 7. Self-rated noise level Potential Impact Behaviors Defined By Scientific Observation 1. Use of vocalized calls 2. Use of instrument calls 3. Use of audio recordings 4. Approach birds 5. Flush birds 6. Method of birding car 7. Method of birding boat 8. Method of birding walking 9. Method of birding off-trail walking 10. Method of birding bird blind 11. Method of birding observation deck 12. Method of birding off-road vehicle 13. Method of birding other

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25 All questions addressing potential impact behaviors (Appendix A) asked participants to answer on a Likert-type scal e with the following values: 1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Frequently, 5 = Always A question referring to ‘other’ methods of bird observation was asked as an openended question first, then it was followed up with the Likert-type scale if the initial question was answered. A relati ve minority of participants (37.5%) recorded nine ‘other’ methods of observation (Table 4). Consequent ly, the ‘other’ variable was removed from the data and the final analysis was done on the remaining nineteen potential impact behavior variables. Table 4: Frequency Summary of 'O ther' Methods of Observing Birds ‘Other' Methods (n=184) Frequency Percentage(%) Bicycle 52 28.3 Glider 1 0.5 Horse 4 2.2 Kayak 4 2.2 Motorcycle 1 0.5 Skates 1 0.5 Sking 1 0.5 Tractor 1 0.5 Tree blind 1 0.5 Did not answer / None 118 64.1 Note: The percentages may not sum to 100 due to rounding Demographic Variables Standard demographic variables were integrat ed into this study so that descriptive information about the respondents could be in cluded. Data concentrating on age, sex, race, education, income, marital status and chil dren were collected and analysis was done with basic frequency distributions and descrip tive statistics. All statistics were evaluated at .05 significance.

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26 Data Analysis Data entry and data analysis was perform ed using the Statistical Package for the Social Sciences (SPSS) versi on 12.0. All statistics were evaluated at .05 significance. Once the data were entered into SPSS, some string variables were recoded into numeric variables so they could be included in th e analysis. For example, ‘other’ types of equipment usages were recoded and summed in order to create a new variable. This new variable eventually was summed into a ten-ite m checklist that described the total number of birding items owned by a participant. After measuring the specialization items, Z-scores were utilized to account for different scales and to standardize the variab les (to a mean of 0 and a standard deviation of 1). Z-scores have been beneficial in expl oratory studies (Kerstetter et al. 2001) addressing recreation specializ ation. As suggested by L ee and Scott (2004), unique dimensional indexes were created to see if th ey were individually related to potential impact variables. This was done by additivel y combining the selected variable means (Zscores) into Experience, Equipment and Economic Commitment, and Centrality to Lifestyle dimensions. Reliability analysis of variables in each dimension was examined using Cronbach’s alpha. Measurements of .829 for Experience, .757 for Equipment and Economic Commitment, and .690 for Centrality to Lifestyle suggested that the variables were reliable indicators for their dimensions (Table 5). Since overall recreation specialization i ndexes have been supported by literature (Donnelly et al. 1986, Wellman et.al 1982, Vird en and Schreyer 1988), one was created for this study by additively combining the 17 variable means (Z-scores) in the three dimensions. Reliability analysis of the overall recreation specia lization index using Cronbach’s alpha was .891 (Table 6).

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27 Table 5: Reliability Analysis for Specialization Dimensions (Z-scores) Specialization Item Corrected Item Total Correlation Alpha If Item Deleted Experience 1. Years of birding expe rience (Var 6) 0.396 0.829 2. Frequency of birding experience – past week (Var 7) 0.591 0.804 3. Frequency of birding experience –past month (Var 8) 0.595 0.803 4. Frequency of birding experience – past year (Var 9) 0.541 0.810 5. Self-rated level of birding experience (Var 10) 0.61 0.801 6. Reported identification of bird species by sight (Var 11) 0.667 0.793 7. Reported identification of bird species by sound (Var 12) 0.601 0.802 8. Number of birds on life list (Var 13) 0.427 0.825 Standardized item alpha = .829 (n=177) Equipment and Economic Commitment 1. Number of birding items owned (Var 15) 0.649 0.647 2. Equipment replacement value (Var 16) 0.503 0.727 3. Number of magazine subscriptions (Var 14) 0.554 0.699 4. Number of books (Var 17) 0.513 0.722 Standardized item alpha = .757 (n=181) Centrality to Lifestyle 1. Farthest distance traveled to observe birds (Var 1) 0.451 0.638 2. Relative priority of birding versus other pursuits (Var 5) 0.524 0.606 3. Degree of birding oppor tunities that affect choice (Var 2) 0.387 0.665 4. Life list maintenance (Var 3) 0.398 0.660 5. Number of memberships to birding organizations (Var 4) 0.524 0.631 Standardized item alpha = .690 (n = 181) The inter-item correlation matrix for the recr eation specialization i ndex showed that the dimensions were interrelated (Table 7).

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28 Table 6: Reliability Analysis for Overall Specialization Index (Z-scores) Dimension Specialization Measures Corrected Item Total Correlation Alpha If Item Deleted 1. Years of birding experience (Var 6) 0.391 0.890 2. Frequency of birding expe rience – past week (Var 7) 0.450 0.888 3. Frequency of birding experience – past month (Var 8) 0.423 0.889 4. Frequency of birding experi ence – past year (Var 9) 0.365 0.891 5. Self-rated level of birding experience (Var 10) 0.706 0.879 6. Reported identification of bird species by sight (Var 11) 0.777 0.876 7. Reported identification of bird species by sound (Var 12) 0.686 0.880 8. Number of birds on life list (Var 13) 0.547 0.885 9. Number of birding items owned (Var 15) 0.715 0.879 10. Equipment replacement value (Var 16) 0.537 0.885 11. Number of magazine subscriptions (Var 14) 0.552 0.885 12. Number of books (Var 17) 0.455 0.888 13. Farthest distance traveled to observe birds (Var 1) 0.443 0.888 14. Relative priority of bird ing versus other pursuits (Var 5) 0.527 0.885 15. Degree of birding opport unities that affect choice (Var 2) 0.500 0.886 16. Life list maintenance (Var 3) 0.442 0.888 17. Number of memberships to birding organizations (Var 4) 0.624 0.882 Standardized item alpha = .891 (n = 175) To segment birder levels in each index (a total of four indexes), frequencies of index Z-scores were observed for cut point s and a decision was made to segment the respondents based on the following values: 40% Casual Birder; 30% Novice Birder; 20% Intermediate Birder; 10% Advanced Birder The notion that there are fewer highly specialized participants in a recreational activity is supported by Bryan’s (1977, 1979) theory. In order to decipher a ny relationship between the segmented recreation specialization index and potenti al impact behaviors, all f our segmented indexes were

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29Table 7: Correlation Matrix of Indi vidual Recreation Specialization Items Var 1 Var 2 Var 3 Var 4 Var 5Var 6Var 7Var 8Var 9Var 10Var 11 Var 12Var 13Var 14Var 15Var 16Var 17 Var 1 -Var 2 0.254 -Var 3 0.358 0.217 -Var 4 0.367 0.270 0.276 -Var 5 0.352 0.381 0.363 0.426-Var 6 0.204 0.273 0.240 0.1710.246-Var 7 0.115 0.276 0.083 0.1740.0850.218-Var 8 0.101 0.235 0.009 0.1770.0500.2210.879-Var 9 0.124 0.205 0.036 0.1190.0380.1970.7480.865-Var 10 0.309 0.554 0.376 0.4210.4770.5780.3080.2850.275-Var 11 0.436 0.390 0.403 0.6180.4230.2900.2600.2520.2040.560-Var 12 0.334 0.327 0.302 0.6110.3550.2540.2480.2360.1730.4830.882 -Var 13 0.421 0.207 0.569 0.3890.3890.1700.1240.0710.1190.3840.654 0.556-Var 14 0.202 0.259 0.233 0.6790.4720.1040.2410.2240.1230.3800.399 0.3950.279-Var 15 0.362 0.419 0.568 0.5310.4950.2940.2320.1810.1120.5960.573 0.4940.4570.555-Var 16 0.225 0.372 0.225 0.4310.2710.2090.2150.1930.1790.3950.529 0.4150.3170.3500.499-Var 17 0.168 0.228 0.077 0.3280.3000.1800.1820.1570.0780.3490.478 0.4770.1930.4330.4410.369-Note: See Table 1 for variable definitions

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30 individually tested with a One-way ANOV A analysis. For those potential impact behavior variables found to be significant, least significant difference (LSD) post hoc multiple comparisons were computed. Because this study explored the nature of a relatively small sample of participants, the LSD analysis was expected to be sufficient enough to account for smaller differences in significance. Analysis of demographic data was done to investigate how the respondents in this study compared to other birder demographics (Adams et al. 1997, Wiedner and Kerlinger 1990, Hvenegaard 2002). One-way ANOVA analysis was done to examine significance between education and the recreation specia lization index. Add itionally, a bivariate measurement using the Pearson correlation coefficient was completed to assess the income variable among the continuum of birders. The data analysis used in the study carried out the prim ary objectives and identifying demographic information about the pa rticipants. As seen in the next chapter, demographic results were mostly typical in nature. However, some results of hypothesis testing were atypical.

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31 CHAPTER 4 RESULTS Demographics Results of the demographic statistical an alysis (Table 8) suggested that the interview participants were similar to birder populations that have been described in other literature (Adams et al. 1997, Wiedner a nd Kerlinger 1990, Hvenegaard 2002). The mean age of the respondents was 47 (SD = 13.23, range = 21-76), which is considered middle-aged. A large majority (95.6%) of th e subjects were Caucasian and 44.8% of the total that responded were married with ch ildren. The averag e respondent was well educated with a college education. Over all, 65.7% were colleg e graduates and 23.8% had graduate degrees or beyond. The mean total household income for 2003 was between $40,000 and $49,000. This is above the national per capita aver age of $31,459 (U.S. Department of Commerce 2003). The bivariate Pearson correlation analys is revealed a slight positive co rrelation (.094) between income and the recreation specialization index with a two-tailed significance of .237. In the sample of respondents, women slightly outnumbered men (53.6% to 46.4%). This ratio was not representative of ot her studies (Adams et al. 1997, Wiedner and Kerlinger 1990) that recorded men for over 60% of the respondents. Means and standard deviations for the overall recreation specialization index and education level were computed (Table 9). A One-way ANOVA analysis of education and the recreation specializ ation index did not prove to be significant at .090 (Table 10).

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32 Table 8: Socio-demographic Char acteristics of Participants Socio-demographic Characteristi cs N FrequencyPercentage (%) Gender 181 Male 84 46.4 Female 97 53.6 Age (Mean=47, SD=13.23) 176 18 24 5 2.8 25 34 36 20.4 35 44 27 15.3 45 54 58 33.0 55 64 35 19.9 65 or older 15 8.5 Race / Ethnicity 181 Caucasian 173 95.6 Latino or Hispanic 3 1.7 African American 1 0.6 Other 4 2.2 Marital status and children 181 Single, no children 50 27.6 Single parent, have children 14 7.7 Married, no children 34 18.8 Married, have children 81 44.8 Other 2 1.1 Highest Level of Education 181 High School Graduate or GED 21 11.6 Some College 41 22.7 College Graduate 56 30.9 Some Graduate School 20 11.0 Graduate Degree or Beyond 43 23.8 Level of Income (Mean=$40,000 $49,000) 159 Under $20,000 20 12.6 $20,000 $39,999 42 26.4 $40,000 $69,999 64 40.3 $70,000 $99,999 17 10.7 $100,000 or more 16 10.1 Note: The percentages may not sum to 100 due to rounding

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33 Table 9: Means and Standard Deviations fo r Segmented Recreation Specialization Index and Education Casual Novice Intermediate Advanced Questionnaire Statementa M SD M SD M SD M SD Level of education 4.9 1.275.4 1.305.0 1.45 5.5 1.17 aVariable coded: 1=Eighth grade or less 2 = Some high school 3 = High school graduate or GED 4 = Some college 5 = College graduate 6 = Some graduate school 7 = Graduate school and beyond Table 10: One Way Analysis of Variance for Recreation Specializati on Index on Level of Education Variable and source df SS MS F p Level of Education Between groups 3 11.26 3.753 2.194 0.09 Within groups 177 302.817 1.711 Dimensional Indexes All frequency distributions for variables in the different dimensional indexes are exhibited in Tables 11, 12, and 13. Indexes are identified as Experience, Equipment and Economic Commitment, and Centrality to Lifestyle. Generally, respondents were vari ed in their experience as birders (Table 11), with 35% having five years or less and 20.2% havi ng twenty-six years or more. Overall, birders averaged (mean) fifteen years of bird ing experience. As one might expect, the ability to accurately recall events over time can be difficult. This was exhibited by the mean number of birding outings per week (1.7), in that it was not mathematically expressed in the monthly mean (5.2) and the yearly mean (34.3) frequencies. Respondents reported that they were more skil led at visual identific ation than auditory identification. A mean of 67 species could be identified by sight a nd 20 species could be identified by sound. Additionally, 35% rated themselves 3 or lower on a 10-point scale for birding experience, while 25.7% rated themselves 7 or higher.

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34 Table 11: Frequency Summaries for Experience Specialization Items Experience measures: N M SD Frequency Percentage(%) Years of birding experience 18315.013.77 5 Years or less 64 35.0 6 10 Years 32 17.5 11 20 Years 40 21.8 21 25 Years 10 5.5 26 Years and over 37 20.2 Frequency of birding experience – past week 1821.72.06 0 Outings 52 28.6 1 2 Outings 89 48.9 3 4 Outings 24 13.2 5 6 Outings 9 4.9 7 or more 8 4.4 Frequency of birding experience – past month 181 5.26.97 0 Outings 20 11.0 1 2 Outings 69 38.2 3 6 Outings 55 30.4 7 14 Outings 18 9.9 15 or more 19 10.5 Frequency of birding experience – past year 18234.366.07 0 5 Outings 47 25.8 6 14 Outings 51 28.0 15 34 Outings 41 22.6 35 100 Outings 31 17.0 101 or more 12 6.6 Self-rated level of birding experience 183 4.72.26 1 No experience 14 7.7 2 3 50 27.3 4 6 72 39.3 7 9 44 24.1 10 Expert 3 1.6 Reported identification of bird species by sight 181 66.986.68 4 10 29 16.0 11 25 54 29.9 26 50 50 27.6

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35 Table 11 Continued Experience measures: N M SD Frequency Percentage(%) 51 100 25 13.8 101 or more 23 12.7 Reported identification of bird species by sound 182 20.4 41.35 0 2 25 13.7 3 9 57 31.4 10 49 79 43.4 50 100 16 8.8 101 or more 5 2.7 Number of birds on life list 180 66.5 211.77 0 138 76.7 20 100 19 10.5 101 250 9 5.0 251 or more 14 7.8 Results from the equipment and economic i ndicators showed that most participants had a modest commitment to the birding act ivity (Table 12). Despite a higher mean (4.0), the majority of birder s (36.4%) owned two to three pieces of birding equipment (commonly, binoculars and field guides). Almost 40% of the sample owned two to four bird books (mean = 18.4) and a significant pr oportion of birders ( 29.6%) would have had to pay between $151 and $500 to replace all their equipment. The replacement value variable showed a wide array of financia l commitment as evidenced by a standard deviation near $1700. Even though these stat istics show some economic investment, 62.5% of the participants possessed zero subscriptions to birding magazines. Table 12: Frequency Summaries for Equipment and Economic Commitment Specialization Items Equipment and economic commitment measures: N M SD Frequency Percentage(%) Number of birding items owned 184 4.0 2.16 0 -1 18 9.8 2 -3 67 36.4 4 -5 56 30.4

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36 Table 12 .Continued Equipment and economic commitment measures: N M SD Frequency Percentage(%) 8 -9 16 8.7 Equipment replacement value 182 950.01692.95 $0 50 33 18.1 $51 150 37 20.4 $151 500 54 29.6 $501 2000 34 18.7 $2001 or more 24 13.2 Number of magazine subscriptions 184 0.7 1.32 0 115 62.5 1 2 53 28.8 3 4 10 5.4 5 6 5 2.8 7 8 1 0.5 Number of books 181 18.4 56.4 0 1 26 14.4 2 4 70 38.6 5 10 43 23.8 11 50 31 17.1 51 or more 11 6.1 For most respondents, birding did not play a central role in thei r lives (Table 13). Many (75.4%) viewed birding as a secondary activity when it came to observing birds away from their household. This was supported with the fact that 75.8% did not maintain a life list and over 50% had either no site pref erence for birding or ra rely participated in birding outings. Approximately 20% reported th at the farthest distance they had ever traveled to observe birds was less than 50 miles. Only 33% had one or more memberships to birding organizations. Table 13: Frequency Summaries for Centra lity to Lifestyle Specialization Items Centrality to lifestyle measures : N M SD Frequency Percentage(%) Farthest distance traveled to observe birds 182 1182.71850.87 0 50 Miles 36 19.8

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37 Table 13 Continued Centrality to lifestyle measures : N M SD Frequency Percentage(%) 501 1000 Miles 18 9.9 1001 2000 Miles 22 12.1 2001 Miles or more 36 19.8 Relative priority of birding versus other pursuitsa 183 .25 .43 Take specific trips to observe birds 45 24.6 Birding is a side activity, on trips taken for other purposes 138 75.4 Degree of birding opportunities that affect choice b 182 2.6 1.01 I rarely participate in birding outings 28 15.4 I participate in bi rding outings, but don’t have particular sites that I visit 67 36.8 I participate in birding outings anywhere and everywhere possible 46 25.3 I participate in birding outings and have favorite sites that I visit 41 22.5 Life list maintenancec 182 .24 .43 Yes 44 24.2 No 138 75.8 Number of memberships to birding organizations 182 .52 .99 0 122 67.0 1 42 23.1 2 3 14 7.7 4 6 4 2.2 a Variable coded: 1 = I take specific trips to observe birds. 0 = I do birding as a side activity, on trips taken for other purposes. bVariable coded: 1= I rarely participate in birding outings. 2 = I participate in birding outings, but don’t have particular sites that I visit. 3 = I participate in birding outings anywhere and everywhere possible. 4 = I participate in birding outings and have favorite sites that I visit. cVariable coded: 1 = Yes. 0 = No Potential Impact Behaviors Tables 14 and 15 describe fre quency distributions of self -reported potential impact behaviors using the Likert-type scale described in Chapter 3. Many participants reported low frequencies of behavior. Mo st stated that they had never or rarely participated in the

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38 action in question. For example, only 4.4% of the respondents indicated that they either always or frequently fed birds when bird ing away from the household. Conversely, 77.6% said that they never participated in that type of behavior. Comparable statistics were recorded for several other variables. For example, more than 75% of participants stated that they never litter in field (82.5%), never use or wear colors to attract birds (86.3%), never use audio recordings (84.7%), never use instrument calls (85.8%), and never use flash photography or video with artificial lighting (75.4%). Accounts of entering private property were slightly higher in frequency, with 38.3% stating that it occurs either rarely or sometimes. Responses were even more dispersed when participants considered usi ng vocalized calls (pishi ng) and urinating and defecating in the field. For both variables, approximately 23% said they sometimes perform and four to five percent said they always carry out the behavior. Some disparity was recorded between seem ingly related variables. For instance, 49.2% of birders reported that they either fr equently or always approached birds when birding. However, only 13.1% said they fre quently or always flushed birds by accident or on purpose. The most common method to observe birds wa s to walk on trails and boardwalks. Close to 80% of the respondents said they freque ntly or always utilized that tactic. The use of cars, boats, observation decks and offtrail walking was less prevalent, but they were still used more often than off-road vehicles. The least frequent method of observation was bird blinds. Approximately, 80% of the respondents said they had never used one.

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39 The report of group noise level (Table 15) established that 91.2% of the respondents categorized their noise level betw een one and four on an eight-point scale (with 1 = very quiet and 8 = very loud). Th erefore, birders categorized themselves as quiet to very quiet on a typical birding outing. Table 14: Frequency Distributions (Percen tage) for Reports of Potential Impact Behaviors Questionnaire Statementa NeverRarelySometimesFrequently AlwaysN Use of food and/or water 77.6 5.5 12.6 2.2 2.2 183 Use or wear of attractive colors 86.3 8.2 4.4 1.1 0 183 Use of flash photography or video with artificial lighting 75.4 11.5 9.8 3.3 0 183 Enter private property 60.1 30.6 7.7 1.6 0 183 Litter in the field 82.5 16.9 0.5 0 0 183 Urinate and/or defecate in the field 36.3 26.9 23.1 9.9 3.8 183 Use of vocalized calls 49.2 11.5 22.4 12 4.9 183 Use of instrument calls 85.8 8.7 3.3 1.1 1.1 183 Use of audio recordings 84.7 9.3 4.4 1.6 0 183 Approach birds 9.8 9.3 31.7 38.8 10.4 183 Flush birds 15.3 31.7 39.9 12.6 0.5 183 Method of birding car 6.0 16.4 30.1 38.3 9.3 183 Method of birding boat 24 35 27.3 9.3 4.4 183 Method of birding walking 0.5 4.9 16.4 59.6 18.6 183 Method of birding off-trail walking 9.3 18.6 29 36.6 6.6 183 Method of birding bird blind 80.3 16.9 1.6 1.1 0 183 Method of birding observation deck 16.4 33.9 41 8.2 0.5 183 Method of birding off-road vehicle 78.7 13.7 3.8 3.3 0.5 183 Method of birding otherb 1.4 24.6 47.8 24.6 2.9 69 aVariables coded on a 5-point scale with 1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Frequently, 5 = Always bRemoved from data Table 15 : Frequency Distribution (Percen tage) for Reports of Group Noise Level Questionnaire Statementa 1 2 3 4 5 6 7 8 N Self-rated noise level 10.435.227.518.15.5 2.7 0 0.5 182 aMeasured on a 1-8 scale with 1 = Very quiet and 8 = Very loud

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40 Relationships and Results of Hypothesis Testing As previously mentioned in Chapter 3 (M ethods), a primary objective of this study was to explore the possibility that a rela tionship exists between birdwatchers on a recreation specialization continuum and the poten tial impact behaviors that they report. Based on literature supporting a greater co ncern for the environment in specialized recreationists, a hypothesis was formulated that said advan ced birders should report the lowest frequency of potential impact behavior s. In order to test the hypothesis, four indexes were created utilizing Z-scores and then were segmented using Bryan’s recreation specialization theory (1977, 1979) an d observable points in the data. One-way ANOVA and LSD post hoc multiple comparisons (found on descriptive tables) were used to formulate the following outcomes. Generally, the results of the one-way ANOVA analysis on the three dimensional indexes and the overall recreati onal specialization index reve aled a relationship between some impact behaviors. Out of the 19 pot ential impact behavior s studied, 12 were found to be significant ( .05 level) in at least one of the indexes. Four variables (use of vocalized calls, use of audio recordings, approach birds, method of birding observation deck) were found to be significant among all four indexes. Additionally, LSD post hoc multiple comparisons on all the significant va riables exhibited a trend where self-reported potential impact behaviors in creased as the specializati on continuum went from the general to the specialized. Besides the potential impact behavior variables listed in the previous paragraph, five other variables (enter private property, urinate and/or defecate in the field, method of birding – car, method of birdi ng walking, method of birding – off-trail walking) were

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41 statistically significant in the Experience inde x (Table 16 and 17). In seven of the nine significant variables, the means of the reporte d behaviors increased from casual through advanced birders. Approaching birds was significant from casual through intermediate birders, but not advanced. Viewing birds from an observation deck was significant among all categories except intermediate birder s. Of the ten remaining variables deemed not significant, only one (selfrated noise level) tended to have higher means in the generalized portion of the continuum (mean s of 3.0 and 2.9 in the casual and novice birders and 2.6 and 2.7 in the intermediate and advanced). Table 16: Means and Standard Deviations fo r Segmented Experience Index and Nineteen Dependent Variables Casual Novice Intermediate Advanced Potential Impact Behavior Items M SD M SD M SD M SD Use of food and/or water 1.4 0.92 1.5 0.881.5 1.19 1.4 0.77 Use or wear of attractive colors 1.2 0.62 1.1 0.371.3 0.70 1.2 0.50 Use of flash photography or video with artificial lighting 1.4 0.78 1.5 0.861.4 0.83 1.3 0.67 *Enter private property 1.4ab 0.68 1.4c 0.571.7a 0.85 1.9bc 0.74 Litter in the field 1.2 0.42 1.2 0.411.2 0.37 1.2 0.38 *Urinate and/or defecate in the field 1.8ab 1.01 2.2c 1.202.5a 1.08 3.0bc 1.13 Self-rated noise level 3.0 1.20 2.9 1.332.6 1.12 2.7 1.34 *Use of vocalized calls 1.6a 0.94 2.0b 1.112.7ab 1.38 3.4ab 1.50 Use of instrument calls 1.1 0.59 1.3 0.761.3 0.65 1.4 0.68 *Use of audio recordings 1.1a 0.35 1.1b 0.371.4ab 0.73 1.8ab 1.07 *Approach birds 3.0ab 1.19 3.4ab0.973.8a 0.95 3.5 0.96 Flush birds 2.4 0.88 2.4 0.952.8 0.97 2.7 0.75 *Method of birding car 3.0ab 1.14 3.3 1.063.6a 0.83 3.6b 0.68 Method of birding boat 2.3 1.11 2.3 1.202.4 0.75 2.5 1.17 *Method of birding walking 3.7ab 0.84 4.0a 0.714.0c 0.66 4.4bc 0.60 *Method of birding off-trail walking 2.8a 1.18 3.3a 0.873.2b 1.12 4.0ab 0.62 Method of birding bird blind 1.2 0.53 1.3 0.581.3 0.45 1.4 0.50

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42 Table 16 Continued Casual Novice Intermediate Advanced Potential Impact Behavior Items M SD M SD M SD M SD *Method of birding observation deck 2.2ab 0.88 2.6a 0.792.5 0.96 2.7b 0.81 Method of birding off-road vehicle 1.3 0.77 1.3 0.691.5 0.90 1.2 0.54 Note: Similar superscripts indicate significant differences utilizing LSD post hoc analysis. For example, participants categorized as intermediate birders were significantly more likely to use flash photography than those categorized as casual birders. Significant at the .05 level. Specific one-way ANOVA analysis showed st rong levels of significance (p) for the nine aforementioned variables in the Experience index (T able 17). Four variables (urinate and/or defecate in the field, use of vocalized calls, use of audio recordings, method of birding off-trail walking) were less than 0.001. The othe r five variables had significance levels ranging from 0.002 to 0.027. Table 17: One Way Analysis of Variance fo r Experience Index on Nineteen Dependent Variables Variable and source df SS MS F p Use of food and/or water Between groups 3 0.333 0.111 0.122 0.947 Within groups 179 163.11 0.911 Use or wear of attractive colors Between groups 3 0.932 0.311 0.982 0.402 Within groups 179 56.588 0.316 Use of flash photography or video with artificial lighting Between groups 3 0.418 0.139 0.215 0.886 Within groups 179 115.844 0.647 Enter private property Between groups 3 5.438 1.813 3.76 0.012* Within groups 179 86.3 0.482 Litter in the field Between groups 3 0.215 0.072 0.445 0.721 Within groups 179 28.834 0.161 Urinate and/or defecate in the field

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43 Table 17 Continued Variable and source df SS MS F p Between groups 3 22.915 7.638 6.35 <.001* Within groups 178 214.101 1.203 Self-rated noise level Between groups 3 5.37 1.79 1.167 0.324 Within groups 178 273.009 1.534 Use of vocalized calls Between groups 3 59.391 19.797 14.891 <.001* Within groups 179 237.965 1.329 Use of instrument calls Between groups 3 1.122 0.374 0.845 0.471 Within groups 179 79.239 0.443 Use of audio recordings Between groups 3 10.917 3.639 11.749 <.001* Within groups 179 55.443 0.31 Approach birds Between groups 3 17.999 6 5.347 0.002* Within groups 179 200.864 1.122 Flush birds Between groups 3 5.453 1.818 2.195 0.090 Within groups 179 148.263 0.828 Method of birding – car Between groups 3 10.789 3.596 3.453 0.018* Within groups 179 186.435 1.042 Method of birding – boat Between groups 3 0.686 0.229 0.194 0.900 Within groups 179 210.931 1.178 Method of birding – walking Between groups 3 8.473 2.824 5.109 0.002* Within groups 179 98.948 0.553 Method of birding – off-trail walking Between groups 3 22.781 7.594 7.104 <.001* Within groups 179 191.328 1.069 Method of birding – bird blind Between groups 3 0.741 0.247 0.882 0.452 Within groups 179 50.155 0.28 Method of birding – observation deck Between groups 3 7.022 2.341 3.133 0.027*

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44 Table 17 Continued Variable and source df SS MS F p Within groups 179 133.733 0.747 Method of birding off-road vehicle Between groups 3 0.974 0.325 0.572 0.634 Within groups 179 101.693 0.568 Significant at the .05 level Much like the Experience index, the Equipment and Economic Commitment index also contained 9 significant potential impact behavior variables (Tables 18 and 19). These variables consisted of the original f our variables found among all indexes (use of vocalized calls, use of audio recordings, approach birds, method of birding observation deck), two variables in common with the Experience index (ent er private property, method of birding car) and three other vari ables (use of flash photography and/or video with artificial lighting, flush bird s, method of birding bird b lind). Most (6 of 9) means for statistically significant potential impact behaviors grew as birders became more specialized. However, means of three variab les (use of flash phot ography and/or video with artificial lighting, approach birds, flush birds) decreased from the intermediate to the advanced birders. Table 18: Means and Standard Deviations for Segmented Equipment and Economic Commitment Index and Nine teen Dependent Variables Casual Novice Intermediate Advanced Potential Impact Behavior Items M SD M SD M SD M SD Use of food and/or water 1.5 0.98 1.4 0.781.6 1.09 1.4 1.01 Use or wear of attractive colors 1.2 0.53 1.2 0.481.3 0.75 1.2 0.50 *Use of flash photography or video with artificial lighting 1.3a 0.68 1.4b 0.711.8abc1.09 1.2c 0.63 *Enter private property 1.3abc0.55 1.6a 0.711.7b 0.82 1.7c 0.89 Litter in the field 1.1 0.35 1.2 0.421.2 0.50 1.1 0.32 Urinate and/or defecate in the field 2.0 1.10 2.3 1.232.2 1.11 2.7 1.00

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45 Table 18 Continued Casual Novice Intermediate Advanced Potential Impact Behavior Items M SD M SD M SD M SD Self-rated noise level 2.9 1.15 2.9 1.212.8 1.60 2.5 0.84 *Use of vocalized calls 1.7a 1.06 2.0b 1.102.5a 1.26 3.4ab 1.54 Use of instrument calls 1.1 0.55 1.2 0.611.4 0.89 1.4 0.69 *Use of audio recordings 1.0a 0.26 1.2b 0.451.3ac 0.57 2.1abc1.13 *Approach birds 2.7abc1.05 3.7a 0.993.8b 0.81 3.6c 1.07 *Flush birds 2.3ab 0.88 2.6a 0.872.8b 0.96 2.6 0.90 *Method of birding car 3.1ab 1.10 3.2c 0.933.5a 1.15 3.9bc 0.46 Method of birding boat 2.4 1.15 2.3 1.172.2 0.91 2.7 0.73 Method of birding walking 3.7 0.87 4.0 0.724.1 0.63 4.0 0.62 Method of birding off-trail walking 2.9 1.20 3.4 1.023.1 0.86 3.4 1.07 *Method of birding bird blind 1.1ab 0.44 1.2 0.571.4a 0.59 1.5b 0.51 *Method of birding observation deck 2.3ab 0.96 2.4 0.782.7a 0.88 2.7b 0.65 Method of birding off-road vehicle 1.4 0.83 1.3 0.661.4 0.86 1.3 0.45 Note: Similar superscripts indicate significant differences utilizing LSD post hoc analysis. For example, participants categorized as intermediate birders were significantly more likely to use flash photography than those categorized as casual birders. Significant at the .05 level. As compared to the significant variab les in the Experience index, one-way ANOVA analysis on the relati onships in the Equipment and Economic Commitment index (Table 19) indicated a wider range of significance (p) values. In this case, only three variables (use of vocalized calls, use of audio recordings, approach birds) were less than 0.001 and six variables ranged from 0.005 to 0.037. Table 19: One Way Analysis of Variance for Equipment and Economic Commitment Index on Nineteen Dependent Variables Variable and source df SS MS F p Use of food and/or water Between groups 3 1.4620.487 0.539 0.656 Within groups 179 161.9810.905 Use or wear of attractive colors Between groups 3 0.7030.234 0.738 0.531

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46 Table 19 Continued Variable and source df SS MS F p Within groups 179 56.8160.317 Use of flash photography or video with artificial lighting Between groups 3 6.4672.156 3.515 0.016* Within groups 179 109.7950.613 Enter private property Between groups 3 4.49 1.497 3.07 0.029* Within groups 179 87.2480.487 Litter in the field Between groups 3 0.4560.152 0.951 0.417 Within groups 179 28.5930.16 Urinate and/or defecate in the field Between groups 3 8.6212.874 2.24 0.085 Within groups 178 228.3951.283 Self-rated noise level Between groups 3 3.1111.037 0.671 0.571 Within groups 178 275.2681.546 Use of vocalized calls Between groups 3 52.49917.5 12.793 <.001* Within groups 179 244.8571.368 Use of instrument calls Between groups 3 2.2580.753 1.725 0.163 Within groups 179 78.1020.436 Use of audio recordings Between groups 3 15.9725.324 18.913 <.001* Within groups 179 50.3880.281 Approach birds Between groups 3 43.24514.415 14.692 <.001* Within groups 179 175.6190.981 Flush birds Between groups 3 9.5683.189 3.96 0.009* Within groups 179 144.1480.805 Method of birding car Between groups 3 13.6684.556 4.443 0.005* Within groups 179 183.5561.025 Method of birding boat Between groups 3 4.5021.501 1.297 0.277

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47 Table 19 Continued Variable and source df SS MS F p Within groups 179 207.1161.157 Method of birding walking Between groups 3 4.2361.412 2.449 0.065 Within groups 179 103.1850.576 Method of birding off-t rail walking Between groups 3 8.8422.947 2.57 0.056 Within groups 179 205.2671.147 Method of birding bird blind Between groups 3 2.47 0.823 3.043 0.030* Within groups 179 48.4260.271 Method of birding observation deck Between groups 3 6.48 2.16 2.879 0.037* Within groups 179 134.2740.75 Method of birding off-road vehicle Between groups 3 0.3230.108 0.188 0.904 Within groups 179 102.3430.572 Significant at the .05 level For the Centrality to Lifestyle index, 8 potential impact behavi or variables were significant (Tables 20 and 21). All significant variables found in this subset had also been found to be significant in one or more of the other dimensional indexes. Trends for means in this index were consistent with the other dimensional indexes as well. That is, they increased from casual through advanced birders. Three of the insignificant variables (u se of food and water, use of flash photography or video with artifi cial lighting, self-rated nois e level) in this index had means that were slightly elevated in the cas ual group. The variable identified as selfrated noise level has relatively high means (2.6 to 3.0) in all categories of birders and across all indexes.

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48 Table 20: Means and Standard Deviations fo r Segmented Centrality to Lifestyle Index and Nineteen Dependent Variables Casual Novice Intermediate Advanced Potential Impact Behavior Items M SD M SD M SD M SD Use of food and/or water 1.5 0.93 1.5 1.031.4 0.96 1.4 0.68 Use or wear of attractive colors 1.2 0.44 1.3 0.671.1 0.40 1.4 0.83 Use of flash photography or video with artificial lighting 1.5 0.87 1.4 0.761.4 0.84 1.1 0.46 Enter private property 1.4 0.61 1.6 0.721.6 0.77 1.8 0.86 Litter in the field 1.2 0.39 1.2 0.371.2 0.49 1.2 0.38 *Urinate and/or defecate in the field 2.0ab 1.18 2.0cd1.032.6ac 1.24 2.6bd0.96 Self-rated noise level 3.0 1.33 2.9 1.332.6 1.03 2.7 1.00 *Use of vocalized calls 1.6a 0.96 2.0a1.292.6a 1.13 3.6a 1.22 Use of instrument calls 1.1 0.56 1.3 0.781.2 0.58 1.6 0.77 *Use of audio recordings 1.1a 0.38 1.1b0.331.3b 0.58 2.1ab1.13 *Approach birds 2.9abc 1.15 3.6a1.053.6b 0.96 3.6c 0.68 Flush birds 2.4 0.89 2.5 0.882.7 1.06 2.9 0.74 *Method of birding car 3.1ab 1.05 3.3 1.113.5a 0.97 3.7b 0.81 Method of birding boat 2.4 1.14 2.3 1.222.4 0.83 2.5 0.91 *Method of birding walking 3.7a 0.93 3.9 0.664.2a 0.51 4.1 0.66 Method of birding off-trail walking 3.0 1.15 3.1 1.103.3 1.03 3.5 0.84 *Method of birding – bird blind 1.1ab 0.44 1.2 0.501.4a 0.54 1.5b 0.77 *Method of birding observation deck 2.1abc 0.922.6a0.90 2.7b 0.68 2.7c 0.75 Method of birding – off-road vehicle 1.4 0.781.4 0.89 1.3 0.62 1.2 0.42 Note: Similar superscripts indicate significant differences utilizing LSD post hoc analysis. For example, participants categorized as intermediate birders were significantly more likely to urinate and/or defecate in the field than those categorized as casual birders. Significant at the .05 level. The one-way ANOVA analysis for the Cent rality to Lifestyle index (Table 21) indicated the highest p-value among all the significant variables in any index. The

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49 variable described as method of birding – car had a value of 0.048. Two other variables, method of birding – walking and method of bi rding – bird blind, had p-values at 0.29 and 0.27 respectively. On the other hand, thr ee potential impact behavior variables (vocalized calls, audio recordings, approach bi rds) had significance values that were less than .001. Table 21: One Way Analysis of Variance for Centrality to Lifestyle Index on Nineteen Dependent Variables Variable and source df SS MS F p Use of food and/or water Between groups 3 0.744 0.248 0.275 0.843 Within groups 178 160.311 0.901 Use or wear of attractive colors Between groups 3 1.065 0.355 Within groups 178 56.413 0.317 1.12 0.342 Use of flash photography or video with artificial lighting Between groups 3 2.229 0.743 1.161 0.326 Within groups 178 113.864 0.64 Enter private property Between groups 3 3.517 1.172 2.372 0.072 Within groups 178 87.961 0.494 Litter in the field Between groups 3 0.088 0.029 0.18 0.910 Within groups 178 28.929 0.163 Urinate and/or defecate in the field Between groups 3 13.009 4.336 3.427 0.018* Within groups 177 223.974 1.265 Self-rated noise level Between groups 3 5.537 1.846 1.197 0.312 Within groups 177 272.816 1.541 Use of vocalized calls Between groups 3 70.654 23.551 18.493 <.001* Within groups 178 226.687 1.274 Use of instrument calls Between groups 3 2.99 0.997 2.294 0.080 Within groups 178 77.318 0.434

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50 Table 21 Continued Variable and source df SS MS F p Use of audio recordings Between groups 3 15.693 5.231 18.396 <.001* Within groups 178 50.615 0.284 Approach birds Between groups 3 23.405 7.802 7.122 <.001* Within groups 178 194.974 1.095 Flush birds Between groups 3 5.802 1.934 2.331 0.076 Within groups 178 147.676 0.83 Method of birding car Between groups 3 8.522 2.841 2.681 0.048* Within groups 178 188.621 1.06 Method of birding boat Between groups 3 0.387 0.129 0.109 0.955 Within groups 178 211.107 1.186 Method of birding walking Between groups 3 5.291 1.764 3.074 0.029* Within groups 178 102.121 0.574 Method of birding off-t rail walking Between groups 3 4.564 1.521 1.297 0.277 Within groups 178 208.777 1.173 Method of birding bird blind Between groups 3 2.541 0.847 3.122 0.027* Within groups 178 48.299 0.271 Method of birding observation deck Between groups 3 10.07 3.357 4.584 0.004* Within groups 178 130.353 0.732 Method of birding off-road vehicle Between groups 3 0.582 0.194 0.339 0.797 Within groups 178 101.973 0.573 Significant at the .05 level Finally, for the overall recreation speciali zation index, 9 potential impact behavior variables were significant (T ables 22 and 23). The highest variable means consistently seen among all dimensional indexes and in the overall recreation specialization index

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51 were: method of birding – car, method of bird ing – walking, method of birding – off-trail walking, use of vocalized calls and approach birds. Self rated noise level had high statistical means as well (approximately 2.7) However, one-way ANOVA analysis never found it to be statistically significant acro ss any level of recreation specialization. Seven significant variables in the recreati onal specialization index had means that increased from the casual through the advanced birder classifica tion. Means for two variables (approaching birds and urinating and/ or defecating in the field) increased from the casual to intermediate birder, but then decreased slightly in the advanced birder. Table 22: Means and Standard Deviations for Segmented Recreation Specialization Index and Nineteen Dependent Variables Casual Novice Intermediate Advanced Potential Impact Behavior Items M SD M SD M SD M SD Use of food and/or water 1.5 0.961.4 0.83 1.4 1.04 1.5 1.07 Use or wear of attractive colors 1.3 0.631.1 0.42 1.1 0.42 1.4 0.83 Use of flash photography or video with artificial lighting 1.4 0.801.5 0.84 1.5 0.87 1.2 0.50 *Enter private property 1.4ab0.611.5c 0.66 1.8ac 0.79 1.7b 0.87 Litter in the field 1.2 0.411.2 0.42 1.2 0.40 1.1 0.32 *Urinate and/or defecate in the field 1.9ab1.072.1c 1.12 2.8ac 1.17 2.6b 0.96 Self-rated noise level 3.0 1.172.8 1.33 2.7 1.31 2.5 1.07 *Use of vocalized calls 1.6a 0.911.9b 1.18 2.6ab 1.21 3.6ab1.42 Use of instrument calls 1.2 0.601.2 0.74 1.3 0.61 1.5 0.77 *Use of audio recordings 1.1a 0.371.1b 0.33 1.2c 0.50 2.2abc1.08 *Approach birds 2.9abc1.173.5a 1.02 3.7b 0.92 3.6c 1.02 Flush birds 2.4 0.882.4 0.94 2.8 0.91 2.7 0.95 Method of birding car 3.1 1.143.3 0.99 3.4 1.02 3.7 0.65 Method of birding boat 2.3 1.192.4 1.09 2.2 0.93 2.6 0.90 *Method of birding walking 3.7abc0.854.0a 0.76 4.2b 0.50 4.2c 0.69 *Method of birding off-trail walking 2.8ab1.153.2 1.04 3.4a 0.90 3.7b 0.95

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52 Table 22 Continued Casual Novice Intermediate Advanced Potential Impact Behavior Items M SD M SD M SD M SD *Method of birding bird blind 1.1a 0.471.2 0.47 1.3 0.67 1.5a 0.51 *Method of birding observation deck 2.3ab0.882.4 0.872.7a 0.88 2.7b 0.73 Method of birding off-road vehicle 1.4 0.781.3 0.701.4 0.87 1.3 0.58 Note: Similar superscripts indicate significant differences utilizing LSD post hoc analysis. For example, participants categorized as intermediate birders were si gnificantly more likely to enter private property than those categorized as casual birders Significant at the .05 level. Significance in terms of a p-value for variables in the recreation specialization index starts with methods of birding – bird blind (0.044). Th ree other variables (urinate and/or defecate in the field, use of vocalized calls, use of audio r ecordings) differ greatly in that their level of sign ificance is less than 0.001. Table 23: One Way Analysis of Varian ce for Recreation Specialization Index on Nineteen Dependent Variables Variable and source df SS MS F p Use of food and/or water Between groups 3 0.657 0.219 0.241 0.868 Within groups 179162.786 0.909 Use or wear of attractive colors Between groups 3 1.442 0.481 1.535 0.207 Within groups 17956.077 0.313 Use of flash photography or video with artificial lighting Between groups 3 1.41 0.47 0.733 0.534 Within groups 179114.852 0.642 Enter private property Between groups 3 5.827 1.942 4.047 0.008* Within groups 17985.91 0.48 Litter in the field Between groups 3 0.182 0.061 0.376 0.771 Within groups 17928.867 0.161 Urinate and/or defecate in the field

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53 Table 23 Continued Variable and source df SS MS F p Between groups 3 23.842 7.947 6.636 <.001* Within groups 178213.174 1.198 Self-rated noise level Between groups 3 5.021 1.674 1.09 0.355 Within groups 178273.358 1.536 Use of vocalized calls Between groups 3 73.411 24.47 119.559 <.001* Within groups 179223.944 1.251 Use of instrument calls Between groups 3 1.625 0.542 1.232 0.300 Within groups 17978.735 0.44 Use of audio recordings Between groups 3 21.183 7.061 27.976 <.001* Within groups 17945.178 0.252 Approach birds Between groups 3 17.835 5.945 5.293 0.002* Within groups 179201.029 1.123 Flush birds Between groups 3 5.415 1.805 2.179 0.092 Within groups 179148.3 0.828 Method of birding car Between groups 3 7.23 2.41 2.271 0.082 Within groups 179189.994 1.061 Method of birding boat Between groups 3 1.949 0.65 0.555 0.646 Within groups 179209.668 1.171 Method of birding walking Between groups 3 7.378 2.459 4.401 0.005* Within groups 179100.042 0.559 Method of birding off-t rail walking Between groups 3 16.809 5.603 5.083 0.002* Within groups 179197.3 1.102 Method of birding bird blind Between groups 3 2.249 0.75 2.758 0.044* Within groups 17948.647 0.272 Method of birding observation deck Between groups 3 6.48 2.16 2.879 0.037*

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54 Table 23 Continued Variable and source df SS MS F p Within groups 179134.274 0.75 Method of birding off-road vehicle Between groups 3 0.595 0.198 0.348 0.791 Within groups 179102.072 0.57 Significant at the .05 level For each of the four indexes, almost half of the potential impact variables were found to be significant. These statistical tendencies describi ng the relationships between birder specialization and poten tial impact behaviors may seem somewhat surprising. The results seemed to contradict the hypothesis: that advanced bird ers should report the lowest frequency of potential impact behavi ors. More specifi cally, for all of the behaviors found to be statistically signifi cant, the means of the reported behaviors increased from casual through intermediate birder s. For some variables, means continued to rise as birders became more advanced, wh ile others decreased slightly. The following chapter will discuss the results in terms of using recreation specialization theory to describe birder behavior. Furthermore, it will examine issues of acceptable impacts, future research and suggest ways to improve our communication with birders.

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55 CHAPTER 5 DISCUSSION Using Bryan’s (1977) recreati onal specialization theory and related specialization studies (Wellman et.al 1982, Virden a nd Schreyer 1988, McFarlane 1994), it was hypothesized that birder specia lization would be inversely related to the number of potential impact behaviors. That is, as birdwatchers moved on a continuum from the general to specialize d, their number of reported pote ntial impact behaviors would decrease. This hypothesis was tested on th ree dimensional indexes and on one overall recreational index. Surprising ly, the findings of this re search did not support the proposed hypothesis among any of the inde xes. Consequently, the hypothesis was rejected. Summary of Results Not only did the overall recrea tion specialization index pr oduce results contrary to the hypothesis, but there was also substantial parity among the three dimensions that were individually tested. Four stat istically significant variables (u se of vocalized calls, use of audio recordings, approach birds, method of birding observation deck) were shared among all indexes when the potential impact behaviors for the recreation specialization index were grouped into the Experience, Equipment / Economic Commitment and Centrality to Lifestyle dimens ions. Four other variables (m ethod of birding – trails and boardwalks, method of observation – bird bl inds, enter private pr operty, urinate and/or defecate in the field) in the recreation speci alization index were shared between two (of

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56 the three) dimensions, suggesting that these va riables may be more difficult to address in terms of future education and/or management options. Generally, post hoc multiple comparisons on the significant variables showed that self-reported potential impact behaviors increased as the specialization continuum went from the general to the specialized. Speci fically, for all of the behaviors found to statistically significant, the means of the reported behaviors in creased from casual through intermediate birders. For example, in the overall recreati on specialization index, participants categorized as intermediate bi rders were significantly more likely to enter private property than those categorized as casual birders. For some variables, means continued to rise as birders became more advanced, while others decreased slightly. Most means for the significant potential impact behaviors ranged between one and two. Subsequently, the Likert-scale used in this study identified the frequency of behavior as somewhere between never a nd rarely. Higher means on the overall recreation specialization index were f ound for approaching birds, walking on trails/boardwalks, off-trail walking and use of observation decks. Some of the lowest means among birders on this index came from use of audio recordings and use of bird blinds. Potential Implications Perhaps when Bryan (1977) conceptualiz ed the linkage of behavior to the specialization continuum, potenti al negative behaviors (or th e lack of them) were not intended to be part of the quo tient. Additionally, it may be that this research indicates other factors are involved when participants carry out potential impact behaviors. For example, peer pressure and knowledge of ethi cal guidelines were not measured in this study.

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57 Bryan (1979) and Wellman et al. (1982) di scovered evidence that suggested highly specialized recreationists would have a grea ter concern for conservation. Based on the results of this study, Bryan’s (1979) theory ma y not be appropriate for use in determining if participant behavior in th e field reflects the concern for wildlife. Someone’s concern for birds does not necessarily equate with behaviors that reduce human impact. On several occasions, intermediate and advanced birders, who might be expected to behave with the most concern for the environment, carried out a greater number of potential impact behaviors. This research seems to support Boyle a nd Samson’s (1985) report and McFarlane’s (1994) assessment of advanced birder motiv ations. Achievement goals may be driving advanced birders to carry out more potential impact behaviors in their effort to “bag” birds for their life list. Higher means found in this study for approaching birds and offtrail walking may be indicat ors for this explanation. Certainly, wildlife agencies can use this research in managi ng statewide birding trails. It is likely that so me of the participants in this study will also use one of the sections of the Great Florida Birding Trail a nd the results may provide some insight as to how much visitor impact is taking pl ace. If higher means for walking on trails/boardwalks and use of observation decks suggest that facilities are readily being utilized, then lower means may predict probl ems of access or supply. The low mean is notable for the use of bird blinds, especially since they are assumed to have very little impact on wildlife. Perhaps more bird blinds need to be constructed. Learning more about the behaviors of each t ype of birder can help managers assess visitation to sensitive habitats. For exampl e, previously prohibited access to fragile

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58 habitats may be possible if certain groups of birders show that they carry out fewer impact behaviors. At the other extreme, deterrents such as guardrails or increased supervision may be necessary for groups that te nd to be more depreciative. According to this research, specialized birders need just as much (or more) supervision as those categorized as casual or novice. Visitor management techniques may become evident based on the different type of impact behaviors carried out by casual, novice, intermediate, and advanced bird watchers. For example, it may be necessary to provide general literature about excess noise levels and use of flash photography to the casual a nd novice birders. On the other hand, the intermediate and advanced birders may need more targeted communication stressing the negative effects of vocalized calls (pishing) and approach ing birds. The practical applications of this research may help ensure the sustainability of wildlife and/or aid in the administration of high quali ty recreational experiences. Finally, the results of this study have the potential to stimulate further research in the analysis of behaviors that may impact wild life. For example, it might be interesting to find out if birders are living up to their reports of impact behavior when they are watched unobtrusively. Add itionally, different sampling t echniques could be used to evaluate the results of this study. and it might be beneficial to determine whether the results are consistent among other recreational pursuits. Pertinent Issues to Consider Since this was a descriptive study, all impacts were measured using the same scale. However, an important question to consider deals with the degree of impact that is acceptable. Can birders, biologists and othe r outdoor recreation agencies agree on what behaviors have an unacceptable impact on wild life? Kazmierow et al. (2000) referred to

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59 the subjectivity that is inhere nt in assessing what constitute s a potential impact. Methods of observation have different degrees of impact and some of them have been analyzed in research (Klein 1993, Rodgers and Smith 1997). However, any sort of outdoor viewing could be considered an impact to an animal’s spatial and temporal resources. Since this research focuses on the descrip tive nature of the birding activ ity that requires humans to enter the environment for viewing, no delinea tion was made for the degree of impact. One can intuitively speculate that there are some differences in impact. For example, when compared to cars or walking, th e use of bird blinds might be considered the least disruptive method of observation. In terms of a higher potential for impact, flushing birds is likely to be more deprecia tive than using vocali zed calls (pishing). When considering the self-reported behaviors in this study, it seems plausible that at the very least birders are drawing different conclu sions as to the severity of an impact. Additionally, this study seemed to support an advanced birder belief that the perceived benefits of observing birds outweighs the per ceived liabilities of their actions. Future studies comparing participant behavior on a specialization continuum and the degrees of impact would likely be be neficial to managers. Some ‘impacts’ could even be considered a benefit to birds. For example, some birders may consider feeding birds as a posit ive measure to reduce winter mortality. On the other hand, scientists have done research that suggests th at feeding birds can negate any positive effects because it also attracts predators th at reduce bird populations (Madison et al. 2002). Another issue to consider is individual assessment of pot ential impact behaviors. Despite attempts to ensure birders were answering honestly, some respondents may have

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60 been reluctant to admit to thei r participation in po tential impact behaviors. Because the survey questions referred to sensitive topics, there is poten tial for data contamination due to social desirability resp onse bias (Zerbe and Paulhus 1987). Since some potential impact behaviors were reported, the social desirability affect was apparently not pervasive in this study. However, this affect can make it more likely that the participants underestimated their accounts of potential imp act behaviors. Cons equently, birders may have produced a greater impact than they actually reported. Variables considered insignificant in this study may actually be supported in future st udies, especially if unobtrusive observation is us ed to study participants. Limitations There were some limitations to this study. While the total samp le size (n = 184) of participants may be adequate for certain measurements, it may be disadvantageous when using the specialization construc t. After segmenting the par ticipants in this study, there were relatively few (n = 18) advanced bird ers contributing to the data. Subsequently, there may be some potential for reduced reliabi lity for that subset of participants. Doubling the number of interview participants likely would have reduced potential sampling error and would have increased th e likelihood of generali zing the results to larger populations of birdwatchers. Another obstacle to this st udy was the unusual sex ratio of sample participants. Women outnumbered men by 7.2%, which is atypical when co mpared to many studies of birder populations (Adams et al. 1997, Wiedne r and Kerlinger 1990). However, Eubanks et al. (2004) also noted an us ual ratio of females (52%) wh ich included participants who attended birding festivals. It seems plausible that birding festivals limit their attendance to certain types of participants. Male bi rderwatchers who don’t like crowds may avoid

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61 birding festivals altogether. However, the unus ual sex ratio may also be explained by the fact that most participants we re selected near merchant a nd informational booths. Studies indicate women are more likely to partic ipate in shopping activi ties (Dholakia 1999), which may have had an effect on the sample. Additionally, the intercept interview sampling strategy has rarely been used for m easuring recreation speci alization. If this technique limits access to some birders, it may be related to the uncommon sex ratio in this study. Conclusions If managers are going to continue to find a balance between recreational opportunities and environmental protection, they will need to find ways to evaluate those activities that potentially impact wildlife. In the case of birding, millions of people are located along the recreational specialization continuum. Even though this activity is oftentimes considered a nonconsumptive, low impact pursuit, the pa rticipants in this study reported behaviors that potentially im pact birds. To improve our evaluative measures, it would seem beneficial for stakeh olders to come to a stronger agreement on what is acceptable behavior and to what de gree is a behavior considered unacceptable. Finally, the results of this study sugges t the importance of communication as birders become more specialized. Managers may need to focus educational programs away from identification techniques and mo re on potential imp act concerns. More importantly, ways to motivate birders to reduce impacts should be addressed in conjunction with educational activities.

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APPENDIX A ON-SITE BIRDER RECREATION SURVEY IN FLORIDA

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66 APPENDIX B FLORIDA BIRDING FEST IVALS – SPRING 2004 Jan 17-19 Everglades BirdFest Everglades National Park (954) 776-5585 Feb 28 Orlando Wetlands Park Fest. Orlando/Titusville (407) 568-1706 March 14 Pelican Island Wildlif e Fest. Orlando/Melbourne (772) 562-3909 April 2-4 Big “O” Birding Fest. Moore Haven (Lake Okeechobee) (863) 946-0300 April 15-17 Wakulla Birding & Wildlife Fest. Wakulla Springs (850) 487-0516 April 24 Welcome Back Songbi rds Fest. Brooksville (352) 754-6722 May 13-16 FL 1st Coast Bird. & Nature Fest. St. Augustine (800) 653-2489

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67 APPENDIX C ON-SITE BIRDER RECREATION SURV EY: VERBAL CONSENT SCRIPT Hello. My name is ____________. I’m working to collect data for a graduate study with the University of Florida. We’re cooper ating with the ___________ Birding Festival to better understand birders and their activities. Th e information we are collecting will help manage Florida lands for na ture-based recreation. Our study will be based on anonymous surveys, such as this one, which ask questions based on birder characteristics, activities and ac tions. You must be at least 18 years old or older to participate in this study. The ques tionnaire takes approxi mately 10 minutes and is completely confidential. Are you able to assist in our study by answering these survey questions? ( If the answer is yes, continue, if no, t hank the individual for his/her time and terminate the conversation .) Thank you for your willingness to participate. You do not have to answer any question you do not wish to answer, and you may disc ontinue participation or withdraw your answers at any time without consequence. There is no anticipated risk or direct benefit to participants. Unfortunately, I cannot compensate you for your time, but your participation is greatly appreci ated. If you have any questions regarding this project, you may contact me, Henry Bireline at 352262-7890 and/or Dr. Holland at 352-392-4042 ext. 1313. Questions or concerns about research participants' rights may be directed to the UFIRB Office at 352-392-0433. May I begin the survey? (If answer is no, thank the individual and terminate the conv ersation. If yes, continue.) (See Attachment 2 for a copy of the on-site survey). (Complete the survey with willing participants.) (See Attachment 3 for a copy of the contact information). (Give the individual a copy of the contact information.) Here is a copy of the contact information for questions regarding this project. Thank you for particip ating. Your time is gr eatly appreciated and is extremely helpful to our study.

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68 APPENDIX D POST-SURVEY CONTACT INFORMATION If you have any questions regarding this project, you may contact the graduate student, Henry Bireline at 352-262-7890 or Dr. Holland at 352-392-4042 ext. 1313. Questions or concerns about re search participants' rights ma y be directed to the UFIRB Office at 352-392-0433.

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69 LIST OF REFERENCES Adams, C.E., Leifester, J.A., and Herron, J.S.C. (1997). Understanding wildlife constituents: birders and waterfowl hunters. Wildlife Society Bulletin 25(3), 653660. American Birding Association. (1996). American Birding Association Conservation Web Page -The growth of birding, and th e economic value of bi rders -part 6: 1996 national Survey of fishing, hunting and wildlife-associ ated recreation. http://americanbirding.or g/programs/consecond6.htm 23 October 2004. American Birding Association. (2004). Amer ican Birding Association’s Principles of Birding Ethics Web Page – Code of Birding Ethics. http://www.americanbirding.org/abaethics.htm 23 June 2004. Aversa, Jr., A. (1986). Notes on entry routes into a sport/recreationa l role: the case of sailing. Journal of Sport and Social Issues 10, 49-59. Babbie, E.R., (1998). The Practice of Social Research, Eighth Edition Belmont, CA: Wadsworth Publishing. Baicich, P.J.,Butcher, G.S., and Green, P. (1999) Trends and issues in birding. In K. Cordell, C.J. Betz, J.M. Bower, D.B.K. English, S.H. Mou, J.C. Bergstrom, R.J. Teasley, M.A. Tarrant, J. Loomis (Comps.), Outdoor Recreation in American Life: A National Assessment of Demand and Supply Trends. (pp. 242-245). Champaign, IL: Sagamore Publishing. Boyle, S.A., and Samson, F.B. (1983). Nonconsumptive outdoor recreation: an annotated bibliography of human-wildlife in teractions. U.S. Department of the Interior, Fish and Wildlife Se rvice, Washington, D.C. 113pp. Boyle, S.A., and Samson, F.B. (1985). Effects of nonconsum ptive recreation on wildlife: a review. Wildlife Society Bulletin 13, 110-116. Bricker, K., and Kerstetter, D. (2000). Le vel of specialization and place attachment: An exploratory study of white water recreationists. Leisure Sciences 22, 233-257. Bryan, H. (1977). Leisure value systems and recreational specializa tion: the case of trout fisherman. Journal of Leisure Research 9, 174-187.

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70 Bryan, H. (1979). Conflict in the great outdoors. Social Stud ies No. 4, Bureau of Public Administration, University of Alabama. 98pp. Bryan, H. (2000). Recreati on specialization revisited. Journal of Leisure Research, 32 (1), 18-21. Burger, J., and Gochfeld, M. (1998). Effect s of ecotourism on bird behavior at the Loxahatchee National Wildlife Refuge, Florida. Environmental Conservation 25, 13-21. Burger, J., Gochfeld, M., and Niles, L.J. (1995). Ecotourism and birds in coastal New Jersey: contrasting responses of birds, tourists, and managers. Environmental Conservation 22(1), 56-65. Chipman, B.D., and Helfrich, L.A. (1988). Recreation specializati on and motivations of Virginia river anglers. North American Journal of Fisheries Management 8, 390398. Choi, S., Loomis, D., and Ditton, R. (1994) Effect of social group, activity, and specialization on recreation substitution decisions. Leisure Sciences 16, 143-159. Cordell, H.K., Bergstrom, J.C., Hartma nn, L.A., and English, D.B.K. (1990). An analysis of the outdoor recreation and wilderness situation in the United States: 19892040. GTR RM-189. Fort Collins, CO: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station. Cottrell, S.P., Graefe, A.A., and Confer, J.J. (2004). Recreation speci alization: hierarchy of boating subactiv ities revisited. World Leisure 46,(4)35-47. Delaney, D.K., Grubb, T.G., Beier, P., Pater, L.L., and Reiser. (1999). Effects of helicopter noise on Mexican spotted owls. Journal of Wildlife Management 63, 60-76. Dholakia, R.R. (1999). Going shopping: ke y determinants of shopping behaviors and motivations. International Journal of Retail and Distribution Mnagement, 27(4), 154-165. Donnelly, M.P., Vaske, J.J., and Graefe, A.R. (1986). Degree and range of recreation specialization: Toward a typology of boating re lated activities. Journal of Leisure Research 2, 81-95. Duffus, D.A., and Dearden, P. (1990). Nonconsumptive wildlife-or iented recreation: a conceptual framework. Biol ogical Conservation, 54, 213-231.

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71 Eubanks, T.L. Jr., Stoll, J.R., and Ditton, R. B. (2004). Understanding the diversity of eight birder sub-populations : socio-demographic characteristics, motivations, expenditures and net benefits. Journal of Ecotourism 3(3), 151-172. Gutzwiller, K.J. and Marcum, H.A. (1997). Bird reactions to observer clothing color: implications for distance-sampling techniques. Journal of Wildlife Management 61(3), 935-947. Hvenegaard, G.T., (2002). Birder speci alization differences in conservation involvement, demographics, and motivations. Human Dimensions of Wildlife 7, 21-36. Kazmierow, B.J., Hickling, G.J., and Boot h, K.L., (2000). Ecological and human dimensions of tourism-related wildlife dist urbance: White herons at Waitangiroto, New Zealand. Human Dimensions of Wildlife 5(2), 1-14. Kerlinger, P., and Brett, J. (1994). Hawk mountain sanctuary: a case study of birder visitation & birding economi cs. In R. Knight and K. Gutzmiller (Eds.), Wildlife &Rrecreationists: Coexistence Through Management &Research. Washington, D.C.: Island Press. Kerstetter, D., Confer, J.J ., and Graefe, A.R. (2001). An exploration of the specialization concept within the context of heritage tourism. Journal of Travel Research 39,(3), 267-274. Klein, M.L. (1993). Waterbird behavior al response to human disturbances. Wildlife Society Bulletin 21, 31-39. Klein, M.L., Humphrey, S.R., and Percival, H.F. (1995). Effects of ecotourism on distribution of waterbirds in a wildlife refuge. Conservation Biology 9(6), 14541465. Kuentzel, W.F., and Heberlein, T., (1992). Do es specialization affect behavioral choices and quality judgments among hunters? Leisure Sciences 14, 211-226. Kuentzel, W.F., and Heberlein, T., (1997). Social status, self-development, and the process of sailing specialization. Journal of Leisure Research 29(3), 300-319. Lee, J.-H., and Scott, D., (2004) Measur ing birding specialization: A confirmatory factor analysis. Leisure Sciences 26, 245-260. Madison, A.L., Robel, R. J., and Jones, D.P ., (2002). Hunting mortality and overwinter survival of northern bobwhites rela tive to food plots in Kansas. Wildlife Society Bulletin 30(4), 1120-1127.

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72 Marion, J.L., and Reid, S.E., (2001) Developm ent of the U.S. Leave No Trace Program: An historical perspective. http://www.lnt.org/ about/history.html 21 October 2004. McFarlane, B.L. (1994). Specializati on and motivations of birdwatchers. Wildlife Society Bulletin 22, 361-370. McFarlane, B.L. (2004). Recreation specia lization and site choice among vehicle-based campers. Leisure Sciences 26, 309-322. McIntyre, N. (1989). The personal meaning of participation: E nduring involvement. Journal of Leisure Research 21, 167-179. Meyer, K. (1994). How to Shit in the Woods. Berkeley, CA: Ten Speed Press. Midanik, L.T., Greenfield, T.K. and Rogers, J.D., (2001). Reports of alcohol-related harm: telephone versus face-to-face interviews. Journal of Studies on Alcohol 62, 74-78. Pokomy, T. (n.d.) Leave No Trace Outdoor Skills and Ethics, North America Edition. http://archive.lnt.org /LNTPublications/NA.pdf 21 October 2004. Rees, E.C., Bruce, J.H., and White, G.T., (2005). Factors affecting the behavioural responses of whooper swans ( Cygnus c. cygnus ) to various human activities. Biological Conservation 121(3) 369-382. Richardson, C.T., and Miller, C.K., (1997). Recommendations for protecting raptors from human disturbance: a review. Wildlife Society Bulletin 25(3), 634-638. Rogers, J.A. Jr., and Smith, H.T. (1995). Se t-back distances to protect nesting bird colonies from human dist urbance in Florida. Conservation Biology 9, 89-99. Rogers, J.A. Jr., and Smith, H.T. (1997). Bu ffer zone distances to protect foraging and loafing waterbirds from huma n disturbance in Florida. Wildlife Society Bulletin 25, 139-145. Scott, D., Baker, S.M., and Kim, C. (1999). Motivations and commitments among participants in the Great Texas Birding Classic. Human Dimensions of Wildlife 4(1), 50-67. Scott, D., and Godbey, G. (1994). Recreati on specialization in the social world of contact bridge. Journal of Leisure Research 26(3), 275-295. Scott, D., and Schafer, C.S., (2001) Recr eation specialization: A critical look at the construct. Journal of Leisure Research 33, 319-343.

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73 Thomas, K., Kvitek, R.G., and Bretz, C. (2003). Effects of human activity on the foraging behavior of sanderlings Calidris alba Biological Conservation 109(1), 67-71. United States Department of Commerce Bureau of Economic Analysis (2003). Per capita personal income. http://www.bea.gov/bea/ regional/spi/drill.cfm 23 October 2004. Virden, R.D., and Schreyer, R. (1988). R ecreation specialization as an indicator of environmental preference. Environment and Behavior, 20(6), 721-739. Wellman, J.D., Roggenbuck, J.W. and Smith, C.A. (1982). Recreation specialization and the norms of depreciative behavior among canoeists. Journal of Leisure Research, 14(4), 323-340. Wiedner, D., and Kerlinger, P. (1990). Econom ics of birding: a national survey of active birders. American Birds 44, 209-213. Williams, D.R., Schreyer, R., and Knopf, R. (1990). The effect of the experience use history on multidimensional structure of motivations to participate in leisure activities. Journal of Leisure Research 22, 36-54. Wilkes, B. (1977), The myth of the nonconsumptive user. The Canadian Field Naturalist 91(4), 343-349. Zerbe, W.J., and Paulhus, D. L. (1987) So cially desirable res ponding in organizational behavior: a reconception. Academy of Management Journal 12(2),250-264.

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74 BIOGRAPHICAL SKETCH Henry Bireline (nickname: Buz) was born July 27, 1969, in Danville, Illinois. After graduating from high school in 1987, he briefly attended his hometown community college and promptly quit to take a role in the workplace. In an effo rt to explore his love for animals, he later attended the Zoo Animal Technology Program at Santa Fe Community College in Gainesville, Florida a nd earned an Associate of Science degree (with honors) in 1992. In 1994, he again graduated with honors from Friends University (Wichita, Kansas) earning a Bachelor of Scie nce in zoo science. He worked in the conservation and zoo fields, caring for a wide variety of animals. Eventually he found his way back to Santa Fe Community College where he currently teaches in the Zoo Animal Technology Program and serves as th e Assistant Director at the SFCC Teaching Zoo. Henry was inspired to work on his master ’s degree part-time while working fulltime in the zoological industry and teaching 16 -19 credit hours. In 2002, he took eight months off from both work and graduate sc hool to walk the entire distance of the Appalachian Trail (2,170 miles). Henry completed his master’s degree in May 2005.


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Title: Recreation Specialization and Reports of Potential Impact Behaviors among Birders Attending Birding Festivals
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Copyright Date: 2008

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Permanent Link: http://ufdc.ufl.edu/UFE0010560/00001

Material Information

Title: Recreation Specialization and Reports of Potential Impact Behaviors among Birders Attending Birding Festivals
Physical Description: Mixed Material
Copyright Date: 2008

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Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
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RECREATION SPECIALIZATION AND REPORTS OF POTENTIAL IMPACT
BEHAVIORS AMONG BIRDERS ATTENDING BIRDING FESTIVALS
















BY

HENRY R. BIRELINE


A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF
FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2005

































Copyright 2005

by

Henry R. Bireline



























Dedicated to those that believed in me... and to those that didn't.















ACKNOWLEDGMENTS

The successful completion of this thesis would not have been possible without the

help and support of numerous loved ones. I would like to thank my advisor, Dr. Stephen

Holland, and my committee members, Dr. John Confer and Dr. Taylor Stein, for their

guidance, expertise and friendship. I am indebted to my assistants, Krista Anderson,

Suzie Gould, Chris Lennon and Joshua Watson for their hard work and professionalism,

which was critical to my success. Additionally, I would like to thank Dr. Stephen

Humphrey and the staff at the School for Natural Resources and the Environment.

I appreciate the encouragement and flexibility from Santa Fe Community College,

so I could work full-time while working on my master's degree. I especially want to

thank my colleagues in the Zoo Animal Technology Program. They are like family to me

and I am touched by their generous support.

Certainly, I want to recognize several people that continually motivate me in my

life. I am a better person because of them and they will always serve as a source of

inspiration. They are Mom, Shannon, Grandma Carolyn, Russ, Dr. Ron Serfoss, Dr.

Alan Maccarone, Mary and Craig Chambers, the late George and Mildred Rewerts. I'd

like to thank them for always believing in me.

Finally, I want to thank Claudia Hardy for the type of love others can only dream

about. I am fortunate to be blessed with such a wonderful gift from God.
















TABLE OF CONTENTS



A C K N O W L E D G M E N T S ................................................................................................. iv

LIST OF TABLES ................................................... vii

A B S T R A C T ........................................................................................................ ............ ix

CHAPTER

1 IN TR O D U C T IO N ........ .. ......................................... ..........................................1.

O bjectiv e s ........................................................................ ................................. . .4
D efi n itio n s ....................................................................... ................................. . 5

2 LITERATURE REVIEW ....................................................................................8...

R recreation Specialization .................................................................... ...............8...
P potential Im pact B ehaviors......................................... ........................ ............... 12

3 M E T H O D S .............. ................................................ .................................... . 19

Hypothesis Statement .............................. ............................................ 19
Survey Instrum entation .. ..................................................................... ............... 19
S tu d y A re a s ............................................................................................................... .. 1 9
P a rtic ip a n ts ................................................................................................................ 2 0
Sampling Strategy .................... .. ........... ............................... 20
Specialization V ariables .... ............................................................... .. ............. 2 1
Potential Impact Behavior Variables..................................................................... 22
D em graphic V ariables ..................................................................... ................ 25
D ata A n aly sis .............................................................................................................. 2 6

4 R E S U L T S ................................................................................................................. .. 3 1

D im ensional Indexes ............... ................ .............................................. 33
P potential Im pact B ehaviors.............................................. ...................... ................ 37
Relationships and Results of Hypothesis Testing.................................................. 40





v









5 D ISCU SSION ............................................................................... . ................. 55

Summary of Results.............................. .......... ....................... 55
P potential Im plications ...................... ................................................................ 56
P ertinent Issues to C onsider......................................... ....................... ................ 58
L im stations .................................................................................. ....................... 60
C conclusions .................................................................................. ........................61

APPENDIX

A ON-SITE BIRDER RECREATION SURVEY IN FLORIDA................................62

B FLORIDA BIRDING FESTIVALS SPRING 2004 ..................... ..................... 66

C ON-SITE BIRDER RECREATION SURVEY: VERBAL CONSENT SCRIPT......67

D POST-SURVEY CONTACT INFORMATION ............................. ..................... 68

L IST O F R E F E R E N C E S ...................................................................................................69

BIO GR APH ICAL SK ETCH .................................................................... ................ 74















LIST OF TABLES


Table page

1 Participant Interview s at Each Study Site ........................................... ................ 21

2 Items Used to Construct a Specialization Indexa ................................ ................ 23

3 Potential Im pact B behavior V ariables................................................... ................ 24

4 Frequency Summary of 'Other' Methods of Observing Birds...............................25

5 Reliability Analysis for Specialization Dimensions (Z-scores) ..............................27

6 Reliability Analysis for Overall Specialization Index (Z-scores) .........................28

7 Correlation Matrix of Individual Recreation Specialization Items .......................29

8 Socio-demographic Characteristics of Participants............................. ................ 32

9 Means and Standard Deviations for Segmented Recreation Specialization Index
an d E du catio n ........................................................................................................... 3 3

10 One Way Analysis of Variance for Recreation Specialization Index on Level of
E d u c atio n .............................................................................................................. .. 3 3

11 Frequency Summaries for Experience Specialization Items................................34

12 Frequency Summaries for Equipment and Economic Commitment
Specialization Item s ................ ............... ............................................. 35

13 Frequency Summaries for Centrality to Lifestyle Specialization Items................36

14 Frequency Distributions (Percentage) for Reports of Potential Impact Behaviors ..39

15 Frequency Distribution (Percentage) for Reports of Group Noise Level .............39

16 Means and Standard Deviations for Segmented Experience Index and Nineteen
D dependent V ariables .............. .... .............. ................................................ 41

17 One Way Analysis of Variance for Experience Index on Nineteen Dependent
V a riab le s ............................................................................................................... .. 4 2









18 Means and Standard Deviations for Segmented Equipment and Economic
Commitment Index and Nineteen Dependent Variables....................................44

19 One Way Analysis of Variance for Equipment and Economic Commitment
Index on N ineteen D dependent V ariables............................................. ................ 45

20 Means and Standard Deviations for Segmented Centrality to Lifestyle Index
and N ineteen D dependent V ariables ..................................................... ................ 48

21 One Way Analysis of Variance for Centrality to Lifestyle Index on Nineteen
D dependent V ariables .............. .... .............. ................................................ 49

22 Means and Standard Deviations for Segmented Recreation Specialization Index
and N ineteen D dependent V ariables ..................................................... ............... 51

23 One Way Analysis of Variance for Recreation Specialization Index on Nineteen
D dependent V ariables .............. .... .............. ................................................ 52















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

RECREATION SPECIALIZATION AND REPORTS OF POTENTIAL IMPACT
BEHAVIORS AMONG BIRDERS ATTENDING BIRDING FESTIVALS

By

Henry R. Bireline

May 2005

Chair: Stephen Holland
Major Department: Natural Resources and Environment

Recreation specialization theory has been useful in understanding the behavior of

outdoor recreationists. The theory has been associated with a greater interest and

involvement in conservation as participants move on a continuum that ranges from the

general to the specialized. As recreational opportunities continue to evolve, it is essential

to consider the potential impacts of participant behavior. Consequently, the purpose of

this study was to collect self-reported information from birdwatchers and investigate

significant relationships between recreation specialization and their potential impact

behaviors.

Data for this study were collected from a total of 184 birders who completed on-

site interviews at three separate birding festivals in central and north Florida with a

response rate of 83%.

This study utilized three individual dimensional indexes and an overall recreational

specialization index to assess any relationship between participant self-reported impact









behaviors. Results indicated statistically significant relationships among all four indexes

and several potential impact behaviors. Specifically, the analysis showed that some self-

reported potential impact behaviors increased as the specialization continuum went from

the general to the specialized. This contradicted the study's hypothesis that advanced

birders would report the lowest frequency of potential impact behaviors. When looking

further at the issue of severity of potential impacts, this study seemed to support an

advanced birder belief that the perceived benefits of observing birds outweigh the

perceived liabilities of birders' actions.

Recreation specialization theory may not be appropriate for use in determining if

participant behavior in the field reflects the concern for wildlife. Someone's concern for

birds does not necessarily equate with behaviors that reduce human impact. However,

this study does indicate the importance of communication from managers as birders

become more specialized. Educational programs may need to focus more on potential

impact concerns. Additionally, ways to motivate birders to reduce impacts may need to

be addressed in conjunction with educational activities.














CHAPTER 1
INTRODUCTION

Millions of people engage in watching wildlife every year. Birdwatchers (also

known as birders) represent 80 percent of this population (American Birding Association

1996), making them an important subset of outdoor recreationists. Traditionally

classified as nonconsumptive wildlife enthusiasts, birders are committed participants who

devote large amounts of time and money to their activity. They drive ecotourism and

have influenced the development of recreation areas throughout North America (Baicich

et al. 1999). States such as Texas and Florida have sponsored ambitious birding

programs to help fill the demand for nonconsumptive recreational opportunities.

Extensive birding trails are maintained throughout these two states.

As more people participate in outdoor recreation programs, there is a significant

need for information that assesses their impact. Baicich et al. (1999) reported that birding

is growing in popularity faster than hiking and backpacking. Additionally, they

suggested that aging baby boomers would significantly increase the population of birders

in the coming years. Cordell et al. (1990) predicted that birding and other related forms

of wildlife watching (i.e.,, photography) would increase 82% by 2040.

This increase in activity can have a positive impact. Most communities desire the

economic benefit of attracting tourists. Kerlinger and Brett (1994) stated that birding has

been especially rewarding in small towns and rural areas such as Hawk Mountain,

Pennsylvania. Birders, who are attracted to the local raptors, add four million dollars to

the economy annually. Additionally, Duffus and Dearden (1990) noted that activities like









birdwatching might stimulate positive attitudes towards conservation, thereby benefiting

wildlife and habitat preservation initiatives.

Despite the positive attributes of birdwatching, the notion of birders as true

nonconsumptive enthusiasts has been rejected. Birders are unlike traditional

consumptive recreationists (i.e., hunters), in that they are not killing and removing

animals from a population. However, potential impact behaviors and the negative effects

of nonconsumptive outdoor recreation have been well documented (Boyle and Samson,

1983). Wilkes (1977) noted that nonconsumptive users consume resources along spatial,

visual and physical dimensions. An array of actions such as illegal motor or bicycle use,

illegal parking, litter, excessive noise, improper human waste disposal, pet use, vandalism

to property, vandalism to the environment (pulling up plants, carving into trees) and

trespassing off trails can be used as indicators of impact behavior. Wilkes (1977) has

been quoted saying, "Point Pelee National Park in Ontario has been hammered by

birdwatchers" (p.346).

Boyle and Samson (1985) suggest that activities like birding may present more

risks to wildlife than other recreational pursuits. They described how some birders

competitively pursued birds in order to complete checklists of achievement. McFarlane

(1994) suggested advanced birders had motivations similar to advanced hunters in that

each group has specific goals of pursuing and "bagging" prey. Burger et al (1995)

observed people chase hawks, owls and small birds at the Forsythe National Wildlife

Refuge (New Jersey) in order to get a closer view. Klein et al., (1995) noted significant

changes in distributions of waterbirds due to vehicular traffic at the Ding Darling

National Wildlife Refuge (Florida), a popular area for birding.









People are crowding popular sites in North America, such as Cape May, New

Jersey and High Island, Texas at certain times of the year in order to observe bird

migrations (Baicich et al. 1999). Oftentimes, managers are challenged with the issue of

providing access to increasing birder populations, while at the same time protecting the

birds and their habitat. Consequently, managers may find it useful to learn more about

recreation specialization among birders, so they can create strategies to reduce potential

impacts.

Although there have been many studies using recreation specialization theory and

many on human disturbance to wildlife, to my knowledge, there are no studies that

attempt to link recreational specialist groups and any corresponding impact behaviors.

Wellman et.al (1982) may have come the closest with a study analyzing specialization

theory and attitudes towards depreciative behaviors in canoeists. The research proposed

in this investigation will attempt to describe relationships between specialized birder

groups and their self-reported impact behaviors.

Social scientists have found recreation specialization theory to be useful in

understanding behaviors of recreationists. Bryan (1977) conceptualized recreation

specialization theory in order to differentiate behaviors in trout fisherman. He theorized

that trout fisherman would progress on a continuum of behavior that goes from the

general to the specialized.

The value of this theory becomes significant to a manager because it can be used to

help predict certain types of participation in an activity. Knowing the degree of

specialization means managers may need to provide a variety of opportunities to the same

type of recreationist. In the case of bird watching, managers have developed viewing









opportunities from cars, walking trails and blinds. Furthermore, initiatives such as

backyard-habitat programs, birding festivals and birding competitions suggest that

managers have recognized variation in birder specialization. Since these types of

specialized programs are used to attract birders into the activity, it seems plausible that

recreation specialization theory can also be used to predict potentially negative behaviors

carried out by the participants.

Objectives

This research focused on data collected from interviews during birding festivals in

the state of Florida. One category of information concentrated on indicators that classify

individuals on a degree of birder specialization. Previous recreation specialization

studies such as Bryan (1977), Wellman et.al (1982), Virden and Schreyer (1988) and

McFarlane (1994) served as models for the development of this study.

Another category of information concentrates on self-reported participation in

activities that potentially have (either direct or indirect) negative impacts on birds. The

impact behaviors are sub-divided by those that the birding community deems negative

and by those that have been scientifically documented to bring about potentially negative

responses in birds.

A final category of information will concentrate on birder demographics. The

reports of impact behaviors will be recorded and statistically analyzed to see if there is a

relationship between degrees of specialization among birders.

The primary objectives of this project are the following:

1. Identify four categories of birders (casual, novice, intermediate and advanced)

2. Record their personal reports of potential impact behaviors









3. Determine any significant relationship (if any) between categories of birders and
their self-reported potential impact behaviors.

If recreation specialization theory is related to potential impact behaviors, it would

be incorrect to assume that an increase in potential impact behaviors is 'progress' on the

specialization continuum. Consequently, one might expect an inverse relationship

between recreation specialization and potential impact behaviors. In this case, advanced

birders should report the lowest frequency of potential impact behaviors and this

hypothesis will be tested in this study.

Definitions

By utilizing previous recreational specialization frameworks, a model was created

to describe the relationship between specific categories of birders and their reports of

potential impact behaviors (Figure 1). Units of analysis were individual birders who

participated in an intercept interview and are distinguished on a specialization continuum

as casual, novice, intermediate and advanced. Specialization was defined using a multi-

dimensional construct incorporating birding experience, equipment and economic

commitment and the role birding plays in one's life (centrality to lifestyle).

Other variables studied were the reports of potential impact behaviors. Like

Wellman et.al (1982), this study viewed impact behaviors as a relative concept that

depends upon the values of the group within which the act occurs. Consequently, acts

that birders considered deviant and acts that have been proven to have either direct or

indirect negative impacts to birds were recorded. For example, the American Birding

Association's (ABA) Code of Birding Ethics (2004) states that birders should stay on

trails, keep a distance from birds (and their nests), limit the use of recordings for

attracting birds and respect the regulations of the area.









Previous scientific studies are also used to define potential impact behaviors when

potentially negative bird reactions were observed in the field. For example, Burger et.al

(1995) recorded a wide variety of responses to ecotourist disturbances in coastal habitats.

Due to variables such as the number of people, viewing distances and methods of

observation, some of the negative bird responses to humans included abandonment of

suitable foraging sites, interruption of incubation, separation of parents from young and

disturbance of prey species.

In the following chapter, literature will be presented that will examine the potential

impact behavior definitions and review the recreation specialization theory. Besides

serving a bibliographic function, the inclusion of preceding research will aid in

contextualizing this study within the evolving body of material on these subjects.













Potential Impact Behaviors


Experience


Equipment &
Economic
Commitment


Recreation
Specialization
Index


< ANOVA


Defined By Both
Peer Group and
Scientific
Observation


Centrality To
Lifestyle


Figure 1: Research model


Specialization Dimensions


Index















CHAPTER 2
LITERATURE REVIEW

Recreation Specialization

Bryan (1977, 1979) was the first to conceptualize the theory of recreation

specialization. In an effort to categorize individuals in outdoor recreation activities,

Bryan (1979) stated that recreation specialization occurred as "a continuum of behavior

from the general to the particular, reflected by equipment and skills used in the sport and

activity setting preferences" (p.29). He suggested that positive reinforcement caused

participants to repeat their behavior in a recreational activity. Additionally, Bryan noted

that as involvement in an activity increased, motivation for continuance moved away

from external rewards to more introspective rationale.

Using indicators such as equipment, skills, attitudes and site preferences, Bryan

(1977) categorized trout fisherman on a degree of angling specialization. After

compiling the results, Bryan categorized four types of anglers. They were from general

to specialized: occasional fishermen, generalists, technique specialists, and technique-

setting specialists.

Despite some difficulties (such as distinguishing between certain respondents, like

the technique specialist and the technique-setting specialist) there was enough evidence

to suggest the use of recreation specialization as a valid theoretical construct. Fishermen

were going from the general to the specialized. For example, fishermen moved into more

specialized experiences over time, and they became more "socialized" into the fishermen









fraternity. Their attitudes and values shifted from attaining a "bag-limit" to preservation

and enjoyment of the setting. Additionally, specialists became more resource dependent.

Bryan's (1979) monograph proposed logical frameworks of specialization for

various outdoor activities such as, photography, backpacking, mountain climbing, skiing,

canoeing, birdwatching and hunting. Although not empirically grounded, it was accepted

as having the potential to explain participant variability within an activity. Furthermore,

it opened the door for more meticulous testing from other scientists. Bryan (2000) later

revisited recreation specialization theory in an effort to stimulate discussion and

consideration of new applications for the 21st century. He reflected on issues such as the

drive to specialize and the potential hazards of specialization (i.e., addiction).

Additionally, he initiated discussions about applying specialization theory to non-leisure

activities such as career management and personal relationships.

The ability to apply recreation specialization theory to a variety of outdoor

recreational activities makes it popular with leisure researchers. For example, it has been

used in studies of boating (Donnelly et al. 1986; Cottrell et al. 2004), sailing (Kuentzel

and Heberlein 1997; Aversa 1986), backpacking (Virden and Schreyer 1988), hunting

(Kuentzel and Heberlein 1992), camping (McFarlane 2004), fishing (Chipman and

Helfrich 1988) and birding (Scott et.al 1999; Hvenegaard 2002).

McFarlane (1994) used specialization theory to investigate motivations behind

birding. The logic behind her study was that by knowing the shifts of goals and

motivations, managers could make better decisions about wildlife recreation

involvement. Several hypotheses were tested that addressed birder specialization,

satisfaction, motivations and differential effects on motivations. Indicators of birding









specialization included past experience, economic commitment and centrality to lifestyle.

Results showed that there was a specialization of birdwatchers that she categorized as

casual, novice, intermediate and advanced.

Goals of birders (traditionally thought of as nonconsumptive recreationalists) were

found to be similar to hunters (consumptive recreationalists). They had multidimensional

motivations of affiliative goals, appreciative goals, conservation goals and achievement

goals. Furthermore, advanced birders showed a primary motivation of achievement,

whereas casual birders tended to have a primary motivation to support conservation.

Evidence suggested that specialization was associated with goal-orientation shifts.

One of the few studies to address specialization and negative behaviors in outdoor

recreationists was done by Wellman, et.al (1982). In this study, canoeists favoring mild

whitewater rapids were sent questionnaires that examined attitudes of depreciative

behaviors. Additionally, questions addressing canoeing investment, past experience and

centrality to lifestyle were used to indicate levels of specialization. Using a modification

of Bryan's (1979) hypothesis, the authors tested to see if highly specialized canoeists

would have different attitudes towards depreciative behavior. Furthermore, like Bryan,

they hypothesized that high-level canoeists would have greater concern for conservation.

The authors noted significant methodological and theoretical issues that likely

contributed to their findings of only limited support for the hypothesis.

Because research (Hvenegaard 2002) has partially supported greater interest and

involvement in conservation in the more specialized recreationists, Bryan's (1979) theory

might be used to see if participant behavior in the field reflects a greater concern for

conservation. Casual and novice birders might be expected to behave with the least









concern for the environment and therefore carry out more potential impact behaviors. On

the other hand, if McFarlane's (1994) assessment of advanced birder motivation is

correct (the achievement of viewing birds), one might expect the advanced birders to

carry out more potential impact behaviors in their effort to "bag" a bird for their life list.

It should be noted that recreation specialization theory continues to evolve. Scott

and Godbey (1994) moved away from the traditional outdoor recreation setting by using

the specialization construct in the social world of contact bridge. Looking at the social

worlds of social bridge and serious bridge, the authors focused on the meaning of

participation and how it was reflected in each style of play. The results of the analysis

showed that the typical recreation specialization trends did not apply. The authors

stressed that in some cases, bridge players resisted specialization along the continuum.

They suggested a closer look at how the will of the participant affects the process of

specialization.

While most studies have developed recreation specialization theory from attitudinal

and/or behavioral factors (McIntyre 1989; Williams et al. 1990; Choi et al. 1994; Bricker

and Kerstetter 2000), Ditton et al. (1992) re-conceptualized recreation specialization

theory from a social worlds perspective. They thought this was necessary after noticing

that Bryan's (1977) definition of specialization was a tautology (i.e., a perpetually true

statement because it contains all logical possibilities). Feeling that the portion of the

definition, ".. .reflected by equipment and skills used in the sport and activity setting

preferences," was an explanation, the authors felt obliged to rework the circular reasoning

of Bryan. Consequently, a conceptual framework of social worlds was described as

segmenting into subworld types. The intersecting subworlds along with their individual









members would then be arranged along a continuum. A series of propositions and

hypotheses were developed linking Bryan's (1977) previous work. Finally, testing using

angler data and subsequent results supported the re-conceptualization of the theory.

Scott and Schafer (2001) re-conceptualized Bryan's (1977) recreation

specialization theory by rejecting single additive index measures and using a three-

dimensional model of behavior, skill and commitment. Lee and Scott (2004) tested the

model using confirmatory factor analysis and found that the use of a three-dimensional

model improved the characterization of participants in the birding activity.

Consequently, they suggested collecting data from all three dimensions, so that distinct

dimensional impacts were not lost in the process of combining variables into an index.

Eubanks et al. (2004) used recreation specialization theory to observe data from

several birder sub-populations for the purpose of exploring the complexities of the

birding social world. While significant group differences in demographic characteristics

were few, there were significant differences in birder behaviors, motivations and

economic activity. Due to the results, the authors cautioned against the use of broad

generalizations to describe an average birder, particularly if the research limits the

number of birder groups being studied.

Potential Impact Behaviors

The effect of nonconsumptive outdoor recreation on wildlife resources has been

well documented (Boyle and Samson 1983). As the demand for nonconsumptive

recreational opportunities (such as birding) grows, managers can expect challenges in

maintaining a balance between accessibility to recreational opportunities and

environmental protection.









In a rare study that combines both ecological and social aspects of tourism-related

wildlife disturbance, Kazmierow et al. (2000) addressed the difficulty of defining and

evaluating 'unacceptable' impacts. While scientific quantitative analysis of bird

reactions to human activities can be considered an objective means of measuring impact,

there is also a subjective (qualitative) facet that plays a role on what level of impact is

considered 'unacceptable'. For example, Delaney et al. (1999) studied the impacts of

helicopter noise on owls. The authors found it necessary to recommend buffer zones in

order to protect the birds from disturbance. While this recommendation may seem like

an obvious action for the noise intensity emitted from a helicopter, the authors also found

that chainsaws were actually more disturbing to the owls when used at comparable

distances. This example is significant since some birders hold the opinion that it is

acceptable to play audio recordings of owl vocalizations to attract conspecifics for better

identification. Since this type of noise intensity has not been well studied, a subjective

value judgment is likely playing a role in birder activities and could potentially be having

a negative impact on the birds. The results from Kazmierow et al. (2000) suggest that

models for measuring wildlife disturbances include more than quantitative data.

It is generally assumed that other types of outdoor recreation activities impact

ecosystems and wildlife more than birdwatching. For example, Richardson and Miller

(1997) reviewed recommendations for raptor protection and found literature associating

the sport of rock-climbing with severe impacts to birds of prey. While most climbers are

not in direct contact with birds, the shouting and noise generated from the activity can be

enough to cause some birds to abandon their nests. In a study of foraging shorebirds

Thomas et al. (2003), found beachgoers with free ranging dogs to be highly disturbing to









natural bird behaviors. Enforcement of buffer zones were recommended for both of these

types of activities, but managers may find it more appropriate to give birders more

latitude if they have less impact.

Unlike hunters and fisherman, birders don't fit a traditional consumptive role by

purposely removing animals from a population. Consequently, they are sometimes called

nonconsumptive recreationists. However, it is important to recognize that birders are not

truly nonconsumptive users. Wilkes (1977) illustrated this argument stating the

consumptive nature of all recreationalists along spatial, visual and physical dimensions.

He noted facility installation, overcrowding, trampling of vegetation and litter as just a

few of the examples of disturbance.

Boyle and Samson (1985) suggested that activities like birding potentially present

more risks to wildlife than other recreational pursuits. They described the importance of

achievement for some birders in that birders actively pursue wildlife for their checklists,

including some species that may be rare or unusual.

In a thorough study of responses to ecotourism, Burger et.al (1995) discussed a

variety of coastal bird species and found a significant range of problems associated with

human-bird interactions. Descriptions of problems focused mostly on encounters relating

to duration and distance. Feeding, reproduction, migration, parenting, habitat selection,

nesting and incubation were all negatively affected by ecotourism (mainly birdwatching).

Despite some evidence of short-term habituation to human activity, Rees et al. (2005)

found similar reactions to approach distances and frequency of disturbances in Whooper

swans. Feeding behaviors decreased as alert activity increased. Furthermore, habituation

to human activity over longer periods of time was not supported.









Several bird disturbance studies have taken place throughout Florida. Klein (1993)

studied waterbird responses to visitor activity at Ding Darling National Wildlife Refuge

on Sanibel Island, Florida. She noted different responses between species. Some birds

reacted significantly to disturbances, while others were more tolerant. Furthermore,

reaction to humans outside their vehicles was more significant than automobile traffic.

Klein (1993) included several educational recommendations that she felt would aid in the

management of visitor disturbances.

Burger and Gochfeld (1998) noted that an increase in vegetative cover could also

aid in reducing visitor disturbance. They observed several species of wetland birds at the

Loxahatchee National Wildlife Refuge near West Palm Beach, Florida. Like Klein's

(1993) study, different species had assorted reactions to the presence of people. Birds

moved away from people, decreased their foraging behavior and increased their vigilance

behavior. The authors found that the volume of noise from people affected birds greater

than the number of visitors alone. Several species responded by retreating to nearby

feeding areas that contained more vegetation and less human activity.

Rogers and Smith (1997) studied Florida waterbird reactions to various types of

human disturbances. They found differences in both intraspecific and interspecies

reactions to disturbances brought on by boats, cars, all-terrain vehicles and walking. For

example, the study showed that flushing distances were greater in wading birds than for

shorebirds. Additionally, when compared to their previous study (Rogers and Smith

1995), results suggested that foraging and loafing birds were just as likely to be disturbed

as nesting birds. More than fifty percent (5 of 9) of species were flushed at greater

distances when foraging and loafing. While use of management buffer zones around









nesting colonies are widespread, Rogers and Smith (1997) suggested a 100m distance as

an adequate safeguard for foraging and loafing waterbirds.

As one can see, disturbance behaviors, whether cognizant or naive, can have a

potential impact on nature. Consequently, recreation and other stakeholder organizations

have created ethical guidelines that aim to educate others about proper behavior in the

outdoors. For example, the United States Forest Service and the National Outdoor

Leadership School partnered together to formalize the creation of a national education

program and awareness campaign called 'Leave No Trace' (Marion and Reid 2001). The

program has a two-part goal of promoting positive recreational experiences while

reducing visitor impacts to the environment.

The non-profit organization called, Leave No Trace Center For Outdoor Ethics,

eventually spawned from the agreement. Through research and educational partnerships,

they have produced a variety of educational materials to help promote responsible

outdoor recreation. The Leave No Trace Outdoor Skills and Ethics booklet (Pokomy

n.d.) highlights seven principles to minimize outdoor recreational impact. While all

seven principles may be considered beneficial to a broad spectrum of recreationalists, two

principles (dispose of waste properly and respect wildlife) may be particularly important

to birders.

In regards to waste, the Leave No Trace booklet (Pokomy n.d.) states to pack trash,

food and litter out of activity areas and properly dispose of human wastes. Using bears

and birds as examples, Wilkes (1977) referred to the impact of garbage at campsites,

stating that it changed distributions of animals and altered natural behaviors. Although

urine is considered more of an odor problem than a health hazard, deer have been









observed defoliating areas of vegetation in search of salt (Pokomy n.d.). In Meyer's

(1994) review of human defecation in outdoor settings, she warned of zoonotic diseases

that can be transferred between humans and animals. The protozoans Giardia and

Crytosporidium can be found naturally in animals and are sometimes blamed for the

spread of disease in humans. However, Meyer (1994) referred to significant outbreaks

that are likely linked to human contamination and stated that animals could be infected by

human defecation as well. Ben Lawhon, the Education Director at Leave No Trace

Center For Outdoor Ethics believes that when some animals come into contact with

human defecation, they are positively reinforced to visit campsites and other areas of

human activity for unnatural foods (personal phone conversation, October 22, 2004).

Leave No Trace statements supporting a principle of respect for animals included:

observation of animals at safe distances, avoidance of vulnerable habitats and life cycles,

and prohibition of feeding animals (Pokomy n.d.). Similarly, the American Birding

Association has produced a Code of Birding Ethics (2004) whose principles state, "In any

conflict of interest between birds and birders, the welfare of the birds and their

environment comes first". Despite strong statements prioritizing bird interests over

human interests, very few prohibition rules are intermingled with more numerous

remarks that use encouragement to minimize disturbances and promote goodwill. Some

of the guidelines ask to limit the use of attraction methods such as audio recordings, keep

groups small enough to avoid impacting the environment, use flash photography and light

from videography sparingly, keep appropriate distances from birds to avoid stress, use

natural covers and bird blinds in sensitive areas, and stay on existing pathways. More

stringent language is used for principles referring to the law and the rights of citizens.









For example, there are references to abide by area regulations and rejection of

unauthorized use of private property.

Dress codes were not specifically mentioned in the American Birding Association's

Code of Birding Ethics (2004). However, it does ask birders to avoid stressing birds.

Gutzwiller and Marcum (1997) noted that some birds have considerable reactions to the

color of clothing. Results supported the species-confidence hypothesis, which claims

birds prefer colors that match their own species and avoid colors that look like other

species. The authors noticed longer approach distances from some species. On the other

hand, they also mentioned the possibility of attack if a bird feels the need to defend its

territory from a 'rival' human being wearing the same color. Regardless of the intent, the

study shows that there is a potential impact to bird behavior.

Since certain actions taken by humans can have a direct and/or indirect effect on

wildlife, it is appropriate to study them in a variety of recreational opportunities. More

importantly, if it is to truly aid managers in the field, research needs to identify which

specialization groups are carrying out the potentially harmful activities. Hence, the

purpose of this study is to see what type of relationship exists between birder

specialization and potential impact behaviors.














CHAPTER 3
METHODS

Hypothesis Statement

This study explores the relationships between categories of birders and their self-

reported potential impact behaviors. Specifically, it uses data collected from on-site

interviews to address the hypothesis statement: advanced birders should report the lowest

frequency ofpotential impact behaviors. The hypothesis will be tested on three

dimensional indexes, (identified as Experience, Equipment and Economic Commitment

and Centrality to Lifestyle) as well as on one overall recreational specialization index.

Survey Instrumentation

Interviews of participants were based on a survey that consisted of a three-page

questionnaire that categorized a total of 26 questions in three sections (Appendix A).

Sixteen questions were included in a recreation specialization section; four questions,

each with six to eight items addressing birder activities made up the second section; and

six questions completed a third section based on participant demographic information.

Study Areas

Florida is one of the most popular birding destinations in the United States and it

had seven birding festivals scheduled during the Spring 2004 season (Appendix B).

Birding festivals were selected for data collection because they attract participants with a

wide range of birder experience. In order to pre-test the survey for formatting errors and

practice interview techniques, two pilot studies were conducted. The first pilot study

took place at the Orlando Wetlands Park Festival in the Orlando/Titusville area and the









second was conducted at the Pelican Island Wildlife Festival in the Orlando/Melbourne

area. As a result, a decision was made to decrease the font size and format the questions

into columns. This decreased the overall number of pages on the survey without

changing the quantity or quality of questions. Data for analysis were collected at three

birding festivals in North Florida (Wakulla Birding & Wildlife Festival Wakulla

Springs, Welcome Back Songbirds Festival Brooksville, Florida 1st Coast Birding &

Nature Festival St. Augustine) until a desired number of interviews were recorded.

Interviews were primarily conducted near festival registration sites, information tables

and vendor booths. Occasionally, interviews took place while birders conducted their

observations in the field.

Participants

While recreation specialization theory is acknowledged for its multi-

dimensionality, most would say participation in birding is at least in part due to an

intention to view and/or hear birds. Consequently, participants in this study consisted of

people aged 18 and over who intended to view birds or take part in festival activities

related to bird watching. Included in the data set were participants who noted that

viewing birds was a primary objective. Those who engaged in other interests and

typically did birding as a secondary activity were also included. Distinctions between

birders were made by using a variable that recognized the relative priority of birding

versus other pursuits.

Sampling Strategy

On-site intercept interviews were conducted in April and May 2004. A total of 184

birders completed the interviews at various festival sites in Florida: 65 (35.3%) at the

Wakulla Birding & Wildlife Festival, 52 (28.3%) at the Welcome Back Songbirds









Festival, and 67 (36.4%) at Florida 1st Coast Birding & Nature Festival (Table 1). A

total of 37 potential participants declined to be interviewed, resulting in a response rate of

83.3%, which is typical of on-site interview surveys (Babbie 1998, Midanik, et al. 2001)

As participants moved through the festival grounds, convenience sampling was

used to select candidates for interviews. Prior to subject participation, an on-site

interviewer communicated pre-screening information and questions using a verbal

consent script (Appendix C).

Table 1: Participant Interviews at Each Study Site
Location Frequency (N) Percentage(%)
Wakulla Birding & Wildlife Festival Wakulla 65 35.3
Springs, Florida
Welcome Back Songbirds Festival Brooksville, 52 28.3
Florida
Florida 1 st Coast Birding & Nature Festival St. 67 36.4
Augustine, Florida



If permission was given, the interviewer proceeded with the interview, which

detailed the three-page survey. Each interaction between interviewer and participant took

no more than seven to ten minutes. Contact information was given to participants in case

they had questions after the survey (Appendix D). A total of five trained interviewers

collected data from the three festivals.

Specialization Variables

Generally, specialization indexes are conceptualized using Bryan's (1977) original

work. Indicators such as participation, equipment, skills, attitudes, preference for activity

setting and commitment have been used for specialization classification. Using recorded

specialization models (Wellman et.al 1982, Virden and Schreyer 1988, McFarlane 1994),

three dimensions were identified to construct an overall recreational specialization index









(Table 2). Additionally, as suggested by Lee and Scott (2004), individual indexes were

created for each dimension (Table 2).

An experience dimension included the variables: years of birding experience;

frequencies of birding experiences over a week, month and year; self-rated level of

birding experience; reported identification of bird species by sight and sound; number of

birds on a life list.

An equipment/economic commitment dimension included the variables: number of

birding items owned; equipment replacement value; number of magazine subscriptions;

number of books owned.

A centrality to lifestyle dimension included the variables: farthest distance traveled

for birding; relative priority of birding versus other pursuits; degree of birding

opportunities that affect choice; life list maintenance; number of memberships to birding

organizations. A reliability analysis indicated that two other variables tested (typical

distance traveled and number of people in a group on a typical birding outing) were

unreliable indicators for the centrality to lifestyle index. Consequently, they were

removed.

Potential Impact Behavior Variables

This study was designed to test the relationships between recreation specialization

indexes and twenty variables of potential impact behaviors. For ease of organization,

variables of potential impact behaviors were subdivided into two categories (Table 3).

First, the potential impact behaviors that had been defined by peer group codes of ethics

(American Birding Assoc. 2004, Pokomy n.d.) included: use of food and/or water; use or

wear of attractive colors; use of flash photography/video; unauthorized entry on private

property; littering; urinating and/or defecating in the field; self-rated noise level.









Table 2: Items Used to Construct a Specialization Indexa
Specialization index dimension and variable items Cronbach Alpha
Experience 0.829
1. Years of birding experience (Var 6)b
2. Frequency of birding experience past week (Var 7)b
3. Frequency of birding experience past month (Var 8)b
4. Frequency of birding experience past year (Var 9)b
5. Self-rated level of birding experience (Var 10)c
6. Reported identification of bird species by sight (Var 11)b
7. Reported identification of bird species by sound (Var 12)b
8. Number of birds on life list (Var 13)b
Equipment and Economic Commitment 0.757
1. Number of birding items owned (Var 15)d
2. Equipment replacement value (Var 16)b
3. Number of magazine subscriptions (Var 14)e
4. Number of books (Var 17)b
Centrality to Lifestylef 0.690
1. Farthest distance traveled to observe birds (Var 1)b
2. Relative priority of birding versus other pursuits (Var 5)9
3. Degree of birding opportunities that affect choice (Var 2)h
4. Life list maintenance (Var 3)i
5. Number of memberships to birding organizations (Var 4)b
aScale reliability: Cronbach's alpha = 0.891
b Measured on an open-ended question

'Measured on a 1-10 scale with l=No experience and 10=Expert
dMeasured by 10-item checklist. Items include: binoculars, field guide, spotting scope, bird call,
recording/listening device, life list, audio recordings, computer software, internet, other
eMeasured by 11-item checklist. Items include: Birder's World, The Auk, Bird Watcher's Digest, Birding,
Wild Bird, Living Bird, Audubon Magazine, Birds and Blooms, Ducks Unlimited Magazine, North
American Birds, Other
fTypical distance traveled and number of people in a group on a typical birding outing were removed due to
unreliability
gMeasured by 2-category question. Items included: I take specific trips to observe birds. I do birding as a
side activity, on trips taken for other purposes.
hMeasured by 4-category question. Items included: I rarely participate in birding outings, I participate in
birding outings, but don't have particular sites that I visit, I participate in birding outings anywhere and
everywhere possible, I participate in birding outings and have favorite sites that I visit
'Measured by yes/no variable









Second, the potential impact behaviors that are defined by scientific observation

(Burger et.al 1995) included: vocalized calls (pishing); instrument calls; audio

recordings; approaching birds; flushing birds; methods of birding such as cars, boats,

walking on trails/boardwalks, off-trail walking, bird blinds, observation decks, off-road

vehicles, and an 'other' variable.

To avoid a reluctance to admit to potential impact behaviors, the questions were

designed to show intensity and/or frequency. Subsequently, participants should have felt

more at ease to answer honestly than if they were asked yes or no questions.

Table 3: Potential Impact Behavior Variables
Two Categories of Potential Impact Behaviors
Potential Impact Behaviors Defined By Peer Groups
1. Use of food and/or water
2. Use or wear of attractive colors
3. Use of flash photography or video with artificial lighting
4. Enter private property
5. Litter in the field
6. Urinate and/or defecate in the field
7. Self-rated noise level
Potential Impact Behaviors Defined By Scientific Observation
1. Use of vocalized calls
2. Use of instrument calls
3. Use of audio recordings
4. Approach birds
5. Flush birds
6. Method of birding car
7. Method of birding boat
8. Method of birding walking
9. Method of birding off-trail walking
10. Method of birding bird blind
11. Method of birding observation deck
12. Method of birding off-road vehicle
13. Method of birding other









All questions addressing potential impact behaviors (Appendix A) asked

participants to answer on a Likert-type scale with the following values: 1 = Never, 2 =

Rarely, 3 = Sometimes, 4 = Frequently, 5 = Always

A question referring to 'other' methods of bird observation was asked as an open-

ended question first, then it was followed up with the Likert-type scale if the initial

question was answered. A relative minority of participants (37.5%) recorded nine 'other'

methods of observation (Table 4). Consequently, the 'other' variable was removed from

the data and the final analysis was done on the remaining nineteen potential impact

behavior variables.

Table 4: Frequency Summary of 'Other' Methods of Observing Birds
'Other' Methods (n=184) Frequency Percentage(%)
Bicycle 52 28.3
Glider 1 0.5
Horse 4 2.2
Kayak 4 2.2
Motorcycle 1 0.5
Skates 1 0.5
Sking 1 0.5
Tractor 1 0.5
Tree blind 1 0.5
Did not answer / None 118 64.1
Note: The percentages may not sum to 100 due to rounding

Demographic Variables

Standard demographic variables were integrated into this study so that descriptive

information about the respondents could be included. Data concentrating on age, sex,

race, education, income, marital status and children were collected and analysis was done

with basic frequency distributions and descriptive statistics. All statistics were evaluated

at .05 significance.









Data Analysis

Data entry and data analysis was performed using the Statistical Package for the

Social Sciences (SPSS) version 12.0. All statistics were evaluated at .05 significance.

Once the data were entered into SPSS, some string variables were recorded into numeric

variables so they could be included in the analysis. For example, 'other' types of

equipment usages were recorded and summed in order to create a new variable. This new

variable eventually was summed into a ten-item checklist that described the total number

of birding items owned by a participant.

After measuring the specialization items, Z-scores were utilized to account for

different scales and to standardize the variables (to a mean of 0 and a standard deviation

of 1). Z-scores have been beneficial in exploratory studies (Kerstetter et al. 2001)

addressing recreation specialization. As suggested by Lee and Scott (2004), unique

dimensional indexes were created to see if they were individually related to potential

impact variables. This was done by additively combining the selected variable means (Z-

scores) into Experience, Equipment and Economic Commitment, and Centrality to

Lifestyle dimensions. Reliability analysis of variables in each dimension was examined

using Cronbach's alpha. Measurements of .829 for Experience, .757 for Equipment and

Economic Commitment, and .690 for Centrality to Lifestyle suggested that the variables

were reliable indicators for their dimensions (Table 5).

Since overall recreation specialization indexes have been supported by literature

(Donnelly et al. 1986, Wellman et.al 1982, Virden and Schreyer 1988), one was created

for this study by additively combining the 17 variable means (Z-scores) in the three

dimensions. Reliability analysis of the overall recreation specialization index using

Cronbach's alpha was .891 (Table 6).









Table 5: Reliability Analysis for Specialization Dimensions (Z-scores)
Specialization Item Corrected Item Total Alpha If Item
Correlation Deleted
Experience
1. Years of birding experience (Var 6) 0.396 0.829
2. Frequency of birding experience past week 0.591 0.804
(Var 7)
3. Frequency of birding experience past month 0.595 0.803
(Var 8)
4. Frequency of birding experience past year 0.541 0.810
(Var 9)
5. Self-rated level of birding experience 0.61 0.801
(Var 10)
6. Reported identification of bird species by 0.667 0.793
sight (Var 11)
7. Reported identification of bird species by 0.601 0.802
sound (Var 12)
8. Number of birds on life list (Var 13) 0.427 0.825
Standardized item alpha = .829 (n=1 77)

Equipment and Economic Commitment
1. Number of birding items owned (Var 15) 0.649 0.647
2. Equipment replacement value (Var 16) 0.503 0.727
3. Number of magazine subscriptions (Var 14) 0.554 0.699
4. Number of books (Var 17) 0.513 0.722
Standardized item alpha = .757 (n=181)

Centrality to Lifestyle
1. Farthest distance traveled to observe birds 0.451 0.638
(Var 1)
2. Relative priority of birding versus other
pursuits (Var 5)
3. Degree of birding opportunities that affect 0.387 0.665
choice (Var 2)
4. Life list maintenance (Var 3) 0.398 0.660
5. Number of memberships to birding 0.524 0.631
organizations (Var 4)
Standardized item alpha =. 690 (n = 181)

The inter-item correlation matrix for the recreation specialization index showed that the

dimensions were interrelated (Table 7).









Table 6: Reliability Analysis for Overall Specialization Index (Z-scores)
Corrected Item Alpha If Item
Dimension Specialization Measures Corret D l ted
Total Correlation Deleted
1. Years of birding experience (Var 6) 0.391 0.890
2. Frequency of birding experience past week (Var 7) 0.450 0.888
3. Frequency of birding experience past month 0.423 0.889
(Var 8)
4. Frequency of birding experience past year (Var 9) 0.365 0.891
5. Self-rated level of birding experience (Var 10) 0.706 0.879
6. Reported identification of bird species by sight 0.777 0.876
(Var 11)
7. Reported identification of bird species by sound
(Vat 12) 0.686 0.880
(Var 12)
8. Number of birds on life list (Var 13) 0.547 0.885
9. Number of birding items owned (Var 15) 0.715 0.879
10. Equipment replacement value (Var 16) 0.537 0.885
11. Number of magazine subscriptions (Var 14) 0.552 0.885
12. Number of books (Var 17) 0.455 0.888
13. Farthest distance traveled to observe birds (Var 1) 0.443 0.888
14. Relative priority of birding versus other pursuits 0.527 0.885
(Var 5)
15. Degree of birding opportunities that affect choice 0.500 0.886
(Vat 2) 0.500 0.886
(Var 2)
16. Life list maintenance (Var 3) 0.442 0.888
17. Number of memberships to birding organizations 0.624 0.882
(Var 4)
Standardized item alpha = .891 (n = 175)

To segment birder levels in each index (a total of four indexes), frequencies of

index Z-scores were observed for cut points and a decision was made to segment the

respondents based on the following values: 40% Casual Birder; 30% Novice Birder; 20%

Intermediate Birder; 10% Advanced Birder. The notion that there are fewer highly

specialized participants in a recreational activity is supported by Bryan's (1977, 1979)

theory.

In order to decipher any relationship between the segmented recreation

specialization index and potential impact behaviors, all four segmented indexes were













Table 7: Correlation Matrix of Individual Recreation Specialization Items
Var 1 Var 2 Var 3 Var 4 Var 5 Var 6 Var 7 Var 8 Var 9 Var 10 Var 11 Var 12 Var 13 Var 14 Var 15 Var 16 Var 17


Var 1
Var 2
Var 3
Var 4
Var 5
Var 6
Var 7
Var 8
Var 9
Var 10
Var 11
Var 12
Var 13
Var 14
Var 15
Var 16
Var 17


0.254
0.358
0.367
0.352
0.204
0.115
0.101
0.124
0.309
0.436
0.334
0.421
0.202
0.362
0.225
0.168


0.217
0.270
0.381
0.273
0.276
0.235
0.205
0.554
0.390
0.327
0.207
0.259
0.419
0.372
0.228


0.556 --
0.395 0.279
0.494 0.457
0.415 0.317
0.477 0.193


0.276
0.363
0.240
0.083
0.009
0.036
0.376
0.403
0.302
0.569
0.233
0.568
0.225
0.077


Note: See Table 1 for variable definitions


0.246 --
0.085 0.218 --
0.050 0.221 0.879 --
0.038 0.197 0.748 0.865 --
0.477 0.578 0.308 0.285 0.275
0.423 0.290 0.260 0.252 0.204
0.355 0.254 0.248 0.236 0.173
0.389 0.170 0.124 0.071 0.119
0.472 0.104 0.241 0.224 0.123
0.495 0.294 0.232 0.181 0.112
0.271 0.209 0.215 0.193 0.179
0.300 0.180 0.182 0.157 0.078


0.560
0.483
0.384
0.380
0.596
0.395
0.349


0.882
0.654
0.399
0.573
0.529
0.478


0.555 --
0.350 0.499 --
0.433 0.441 0.369


0.426
0.171
0.174
0.177
0.119
0.421
0.618
0.611
0.389
0.679
0.531
0.431
0.328









individually tested with a One-way ANOVA analysis. For those potential impact

behavior variables found to be significant, least significant difference (LSD) post hoc

multiple comparisons were computed. Because this study explored the nature of a

relatively small sample of participants, the LSD analysis was expected to be sufficient

enough to account for smaller differences in significance.

Analysis of demographic data was done to investigate how the respondents in this

study compared to other birder demographics (Adams et al. 1997, Wiedner and Kerlinger

1990, Hvenegaard 2002). One-way ANOVA analysis was done to examine significance

between education and the recreation specialization index. Additionally, a bivariate

measurement using the Pearson correlation coefficient was completed to assess the

income variable among the continuum of birders.

The data analysis used in the study carried out the primary objectives and

identifying demographic information about the participants. As seen in the next chapter,

demographic results were mostly typical in nature. However, some results of hypothesis

testing were atypical.














CHAPTER 4
RESULTS

Demographics

Results of the demographic statistical analysis (Table 8) suggested that the

interview participants were similar to birder populations that have been described in other

literature (Adams et al. 1997, Wiedner and Kerlinger 1990, Hvenegaard 2002). The

mean age of the respondents was 47 (SD = 13.23, range = 21-76), which is considered

middle-aged. A large majority (95.6%) of the subjects were Caucasian and 44.8% of the

total that responded were married with children. The average respondent was well

educated with a college education. Overall, 65.7% were college graduates and 23.8%

had graduate degrees or beyond.

The mean total household income for 2003 was between $40,000 and $49,000.

This is above the national per capital average of $31,459 (U.S. Department of Commerce

2003). The bivariate Pearson correlation analysis revealed a slight positive correlation

(.094) between income and the recreation specialization index with a two-tailed

significance of .237.

In the sample of respondents, women slightly outnumbered men (53.6% to 46.4%).

This ratio was not representative of other studies (Adams et al. 1997, Wiedner and

Kerlinger 1990) that recorded men for over 60% of the respondents.

Means and standard deviations for the overall recreation specialization index and

education level were computed (Table 9). A One-way ANOVA analysis of education and

the recreation specialization index did not prove to be significant at .090 (Table 10).









Table 8: Socio-demographic Characteristics of Participants
Socio-demographic Characteristics N Frequency Percentage (%)
Gender 181
Male 84 46.4
Female 97 53.6
Age (Mean=47, SD=13.23) 176
18-24 5 2.8
25-34 36 20.4
35 -44 27 15.3
45 -54 58 33.0
55 -64 35 19.9
65 or older 15 8.5
Race / Ethnicity 181
Caucasian 173 95.6
Latino or Hispanic 3 1.7
African American 1 0.6
Other 4 2.2
Marital status and children 181
Single, no children 50 27.6
Single parent, have children 14 7.7
Married, no children 34 18.8
Married, have children 81 44.8
Other 2 1.1
Highest Level of Education 181
High School Graduate or GED 21 11.6
Some College 41 22.7
College Graduate 56 30.9
Some Graduate School 20 11.0
Graduate Degree or Beyond 43 23.8
Level of Income (Mean=$40,000 $49,000) 159
Under $20,000 20 12.6
$20,000 $39,999 42 26.4
$40,000 $69,999 64 40.3
$70,000 $99,999 17 10.7
$100,000 or more 16 10.1
Note: The percentages may not sum to 100 due to rounding









Table 9: Means and Standard Deviations for Segmented Recreation Specialization Index
and Education
Casual Novice Intermediate Advanced
Questionnaire Statementa M SD M SD M SD M SD
Level of education 4.9 1.27 5.4 1.30 5.0 1.45 5.5 1.17
aVariable coded: l=Eighth grade or less 2 = Some high school 3 = High school graduate or GED 4 = Some
college 5 = College graduate 6 = Some graduate school 7 = Graduate school and beyond

Table 10: One Way Analysis of Variance for Recreation Specialization Index on Level of
Education
Variable and source df SS MS F p
Level of Education
Between groups 3 11.26 3.753 2.194 0.09
Within groups 177 302.817 1.711

Dimensional Indexes

All frequency distributions for variables in the different dimensional indexes are

exhibited in Tables 11, 12, and 13. Indexes are identified as Experience, Equipment and

Economic Commitment, and Centrality to Lifestyle.

Generally, respondents were varied in their experience as birders (Table 11), with

35% having five years or less and 20.2% having twenty-six years or more. Overall,

birders averaged (mean) fifteen years of birding experience. As one might expect, the

ability to accurately recall events over time can be difficult. This was exhibited by the

mean number of birding outings per week (1.7), in that it was not mathematically

expressed in the monthly mean (5.2) and the yearly mean (34.3) frequencies.

Respondents reported that they were more skilled at visual identification than auditory

identification. A mean of 67 species could be identified by sight and 20 species could be

identified by sound. Additionally, 35% rated themselves 3 or lower on a 10-point scale

for birding experience, while 25.7% rated themselves 7 or higher.









Table 11: Frequency Summaries for Experience Specialization Items
Experience measures: N M SD Frequency Percentage(%)
Years of birding experience 183 15.0 13.77
5 Years or less 64 35.0
6 10 Years 32 17.5
11 20 Years 40 21.8
21 25 Years 10 5.5
26 Years and over 37 20.2
Frequency of birding experience 182 1.7 2.06
past week
0 Outings 52 28.6
1 2 Outings 89 48.9
3 4 Outings 24 13.2
5 6 Outings 9 4.9
7 or more 8 4.4
Frequency of birding experience 181 5.2 6.97
past month
0 Outings 20 11.0
1 2 Outings 69 38.2
3 6 Outings 55 30.4
7 14 Outings 18 9.9
15 or more 19 10.5
Frequency of birding experience 182 34.3 66.07
past year
0 5 Outings 47 25.8
6 14 Outings 51 28.0
15 34 Outings 41 22.6
35 100 Outings 31 17.0
101 or more 12 6.6
Self-rated level of birding experience 183 4.7 2.26
1 No experience 14 7.7
2-3 50 27.3
4-6 72 39.3
7-9 44 24.1
10 Expert 3 1.6
Reported identification of bird species 181 66.9 86.68
by sight
4-10 29 16.0
11 -25 54 29.9
26 50 50 27.6









Table 11 Continued
Experience measures: N M SD Frequency Percentage(%)
51 100 25 13.8
101 or more 23 12.7
Reported identification of bird species 182 20.4 41.35
by sound
0-2 25 13.7
3 -9 57 31.4
10-49 79 43.4
50- 100 16 8.8
101 or more 5 2.7
Number of birds on life list 180 66.5 211.77
0 138 76.7
20- 100 19 10.5
101 -250 9 5.0
251 or more 14 7.8

Results from the equipment and economic indicators showed that most participants

had a modest commitment to the birding activity (Table 12). Despite a higher mean

(4.0), the majority of birders (36.4%) owned two to three pieces of birding equipment

(commonly, binoculars and field guides). Almost 40% of the sample owned two to four

bird books (mean = 18.4) and a significant proportion of birders (29.6%) would have had

to pay between $151 and $500 to replace all their equipment. The replacement value

variable showed a wide array of financial commitment as evidenced by a standard

deviation near $1700. Even though these statistics show some economic investment,

62.5% of the participants possessed zero subscriptions to birding magazines.

Table 12: Frequency Summaries for Equipment and Economic Commitment
Specialization Items
Equipment and economic commitment
measures: N M SD Frequency Percentage(%)
Number of birding items owned 184 4.0 2.16
0-1 18 9.8
2 -3 67 36.4
4 -5 56 30.4









Table 12 .Continued
Equipment and economic commitment
measures: N M SD Frequency Percentage(%)
8 -9 16 8.7
Equipment replacement value 182 950.0 1692.95
$0 -50 33 18.1
$51 150 37 20.4
$151 500 54 29.6
$501 -2000 34 18.7
$2001 or more 24 13.2
Number of magazine subscriptions 184 0.7 1.32
0 115 62.5
1 2 53 28.8
3-4 10 5.4
5-6 5 2.8
7-8 1 0.5
Number of books 181 18.4 56.4
0-1 26 14.4
2-4 70 38.6
5 -10 43 23.8
11 -50 31 17.1
51 or more 11 6.1

For most respondents, birding did not play a central role in their lives (Table 13).

Many (75.4%) viewed birding as a secondary activity when it came to observing birds

away from their household. This was supported with the fact that 75.8% did not maintain

a life list and over 50% had either no site preference for birding or rarely participated in

birding outings. Approximately 20% reported that the farthest distance they had ever

traveled to observe birds was less than 50 miles. Only 33% had one or more

memberships to birding organizations.

Table 13: Frequency Summaries for Centrality to Lifestyle Specialization Items
Centrality to lifestyle measures: N M SD Frequency Percentage(%)
Farthest distance traveled to
observe birds 182 1182.7 1850.87
0 50 Miles 36 19.8









Table 13 Continued
Centrality to lifestyle measures:
501 1000 Miles
1001 2000 Miles
2001 Miles or more
Relative priority of birding
versus other pursuits
Take specific trips to observe birds
Birding is a side activity, on trips
taken for other purposes
Degree of birding opportunities
that affect choice b
I rarely participate in birding
outings
I participate in birding outings, but
don't have particular sites that I
visit
I participate in birding outings
anywhere and everywhere possible
I participate in birding outings and
have favorite sites that I visit


Life list maintenancec


N M SD Frequency
18


183 .2:





182 2.6


182


No
Number of memberships to
birding organizations


Percentage(%)
9.9
12.1
19.8


5 .43


24.6

75.4


1.01


15.4


36.8

25.3

22.5


24.2
75.8


.24 .43




.52 .99


0 122 67.0
1 42 23.1
2-3 14 7.7
4-6 4 2.2
a Variable coded: 1 = I take specific trips to observe birds. 0 = I do birding as a side activity, on trips
taken for other purposes.
bVariable coded: 1= I rarely participate in birding outings. 2 = I participate in birding outings, but
don't have particular sites that I visit. 3 = I participate in birding outings anywhere and everywhere
possible. 4 = I participate in birding outings and have favorite sites that I visit.
'Variable coded: 1 = Yes. 0 = No


Potential Impact Behaviors


Tables 14 and 15 describe frequency distributions of self-reported potential impact

behaviors using the Likert-type scale described in Chapter 3. Many participants reported

low frequencies of behavior. Most stated that they had never or rarely participated in the









action in question. For example, only 4.4% of the respondents indicated that they either

always or frequently fed birds when birding away from the household. Conversely,

77.6% said that they never participated in that type of behavior. Comparable statistics

were recorded for several other variables. For example, more than 75% of participants

stated that they never litter in field (82.5%), never use or wear colors to attract birds

(86.3%), never use audio recordings (84.7%), never use instrument calls (85.8%), and

never use flash photography or video with artificial lighting (75.4%).

Accounts of entering private property were slightly higher in frequency, with

38.3% stating that it occurs either rarely or sometimes. Responses were even more

dispersed when participants considered using vocalized calls (pishing) and urinating and

defecating in the field. For both variables, approximately 23% said they sometimes

perform and four to five percent said they always carry out the behavior.

Some disparity was recorded between seemingly related variables. For instance,

49.2% of birders reported that they either frequently or always approached birds when

birding. However, only 13.1% said they frequently or always flushed birds by accident

or on purpose.

The most common method to observe birds was to walk on trails and boardwalks.

Close to 80% of the respondents said they frequently or always utilized that tactic. The

use of cars, boats, observation decks and off-trail walking was less prevalent, but they

were still used more often than off-road vehicles. The least frequent method of

observation was bird blinds. Approximately, 80% of the respondents said they had never

used one.









The report of group noise level (Table 15) established that 91.2% of the

respondents categorized their noise level between one and four on an eight-point scale

(with 1 = very quiet and 8 = very loud). Therefore, birders categorized themselves as

quiet to very quiet on a typical birding outing.

Table 14: Frequency Distributions (Percentage) for Reports of Potential Impact
Behaviors


Questionnaire Statementa
Use of food and/or water
Use or wear of attractive colors
Use of flash photography or video
with artificial lighting
Enter private property
Litter in the field
Urinate and/or defecate in the field
Use of vocalized calls
Use of instrument calls
Use of audio recordings
Approach birds
Flush birds
Method of birding car
Method of birding boat
Method of birding walking
Method of birding off-trail
walking
Method of birding bird blind
Method of birding observation
deck
Method of birding off-road
vehicle
Method of birding other
aVariables coded on a 5-point scale with 1
bRemoved from data


Never Rarely Sometimes Frecuentlyv Always


77.6 5.5 12.6
86.3 8.2 4.4

75.4 11.5 9.8


60.1
82.5
36.3
49.2
85.8
84.7
9.8
15.3
6.0
24
0.5

9.3
80.3


30.6
16.9
26.9
11.5
8.7
9.3
9.3
31.7
16.4
35
4.9

18.6
16.9


16.4 33.9


78.7
1.4


13.7
24.6


Never, 2 = Rarely, 3


7.7
0.5
23.1
22.4
3.3
4.4
31.7
39.9
30.1
27.3
16.4

29
1.6

41

3.8
47.8


2.2 2.2 183
1.1 0 183


0 183


1.6
0
9.9
12
1.1
1.6
38.8
12.6
38.3
9.3
59.6

36.6
1.1

8.2


24.6


0
0
3.8
4.9
1.1
0
10.4
0.5
9.3
4.4
18.6


6.6 183
0 183

0.5 183

0.5 183
2.9 69


Sometimes, 4 = Frequently, 5


Always


Table 15 : Frequency Distribution (Percentage) for Reports of Group Noise Level


Questionnaire Statementa 1 2 3 4 5
Self-rated noise level 10.4 35.2 27.5 18.1 5.5
aMeasured on a 1-8 scale with 1 = Very quiet and 8 = Very loud


6 7 8
2.7 0 0.5










Relationships and Results of Hypothesis Testing

As previously mentioned in Chapter 3 (Methods), a primary objective of this study

was to explore the possibility that a relationship exists between birdwatchers on a

recreation specialization continuum and the potential impact behaviors that they report.

Based on literature supporting a greater concern for the environment in specialized

recreationists, a hypothesis was formulated that said advanced birders should report the

lowest frequency of potential impact behaviors. In order to test the hypothesis, four

indexes were created utilizing Z-scores and then were segmented using Bryan's

recreation specialization theory (1977, 1979) and observable points in the data. One-way

ANOVA and LSD post hoc multiple comparisons (found on descriptive tables) were used

to formulate the following outcomes.

Generally, the results of the one-way ANOVA analysis on the three dimensional

indexes and the overall recreational specialization index revealed a relationship between

some impact behaviors. Out of the 19 potential impact behaviors studied, 12 were found

to be significant (< .05 level) in at least one of the indexes. Four variables (use of

vocalized calls, use of audio recordings, approach birds, method of birding observation

deck) were found to be significant among all four indexes. Additionally, LSD post hoc

multiple comparisons on all the significant variables exhibited a trend where self-reported

potential impact behaviors increased as the specialization continuum went from the

general to the specialized.

Besides the potential impact behavior variables listed in the previous paragraph,

five other variables (enter private property, urinate and/or defecate in the field, method of

birding car, method of birding walking, method of birding off-trail walking) were









statistically significant in the Experience index (Table 16 and 17). In seven of the nine

significant variables, the means of the reported behaviors increased from casual through

advanced birders. Approaching birds was significant from casual through intermediate

birders, but not advanced. Viewing birds from an observation deck was significant

among all categories except intermediate birders. Of the ten remaining variables deemed

not significant, only one (self-rated noise level) tended to have higher means in the

generalized portion of the continuum (means of 3.0 and 2.9 in the casual and novice

birders and 2.6 and 2.7 in the intermediate and advanced).

Table 16: Means and Standard Deviations for Segmented Experience Index and Nineteen
Dependent Variables
Casual Novice Intermediate Advanced
Potential Impact Behavior M SD M SD M SD M SD
Items
Use of food and/or water 1.4 0.92 1.5 0.88 1.5 1.19 1.4 0.77
Use or wear of attractive
colors 1.2 0.62 1.1 0.37 1.3 0.70 1.2 0.50
Use of flash photography
or video with artificial 1.4 0.78 1.5 0.86 1.4 0.83 1.3 0.67
lighting
*Enter private property 1.4ab 0.68 1.4c 0.57 1.7a 0.85 1.9bc 0.74
Litter in the field 1.2 0.42 1.2 0.41 1.2 0.37 1.2 0.38
*Urinate and/or defecate
in the field 1.8ab 1.01 2.2c 1.20 2.5a 1.08 3.0bc 1.13
Self-rated noise level 3.0 1.20 2.9 1.33 2.6 1.12 2.7 1.34
*Use of vocalized calls 1.6a 0.94 2.0b 1.11 2.7ab 1.38 3.4ab 1.50
Use of instrument calls 1.1 0.59 1.3 0.76 1.3 0.65 1.4 0.68
*Use of audio recordings 1.1a 0.35 1.1b 0.37 1.4ab 0.73 1.8ab 1.07
*Approach birds 3.0ab 1.19 3.4ab 0.97 3.8a 0.95 3.5 0.96
Flush birds 2.4 0.88 2.4 0.95 2.8 0.97 2.7 0.75
*Method of birding car 3.0ab 1.14 3.3 1.06 3.6a 0.83 3.6b 0.68
Method of birding boat 2.3 1.11 2.3 1.20 2.4 0.75 2.5 1.17
*Method of birding -
walking 3.7ab 0.84 4.0a 0.71 4.0c 0.66 4.4bc 0.60
*Method of birding -
off-trail walking 2.8a 1.18 3.3a 0.87 3.2b 1.12 4.0ab 0.62
Method of birding -


1.2 0.53 1.3 0.58 1.3 0.45 1.4 0.50


bird blind









Table 16 Continued
Casual Novice Intermediate Advanced
Potential Impact Behavior M SD M SD M SD M SD
Items
*Method of birding -
observation deck 2.2ab 0.88 2.6a 0.79 2.5 0.96 2.7b 0.81
Method of birding -
off-road vehicle 1.3 0.77 1.3 0.69 1.5 0.90 1.2 0.54
Note: Similar superscripts indicate significant differences utilizing LSD post hoc analysis. For example,
participants categorized as intermediate birders were significantly more likely to use flash photography
than those categorized as casual birders.
* Significant at the .05 level.


Specific one-way ANOVA analysis showed strong levels of significance (p) for the

nine aforementioned variables in the Experience index (Table 17). Four variables

(urinate and/or defecate in the field, use of vocalized calls, use of audio recordings,

method of birding off-trail walking) were less than 0.001. The other five variables had

significance levels ranging from 0.002 to 0.027.

Table 17: One Way Analysis of Variance for Experience Index on Nineteen Dependent
Variables
Variable and source df SS MS F p
Use of food and/or water
Between groups 3 0.333 0.111 0.122 0.947
Within groups 179 163.11 0.911
Use or wear of attractive colors
Between groups 3 0.932 0.311 0.982 0.402
Within groups 179 56.588 0.316
Use of flash photography or video with
artificial lighting
Between groups 3 0.418 0.139 0.215 0.886
Within groups 179 115.844 0.647
Enter private property
Between groups 3 5.438 1.813 3.76 0.012*
Within groups 179 86.3 0.482
Litter in the field
Between groups 3 0.215 0.072 0.445 0.721
Within groups 179 28.834 0.161
Urinate and/or defecate in the field









Table 17 Continued
Variable and source
Between groups
Within groups
Self-rated noise level
Between groups
Within groups
Use of vocalized calls
Between groups
Within groups
Use of instrument calls
Between groups
Within groups
Use of audio recordings
Between groups
Within groups
Approach birds
Between groups
Within groups
Flush birds
Between groups
Within groups
Method of birding car
Between groups
Within groups
Method of birding boat
Between groups
Within groups
Method of birding walk
Between groups
Within groups
Method of birding off-ti
Between groups
Within groups
Method of birding bird
Between groups
Within groups
Method of birding obse
Between groups


SS
22.915
214.101


ing


rail walking


blind


rvation deck


3 5.37
178 273.009

3 59.391
179 237.965

3 1.122
179 79.239

3 10.917
179 55.443

3 17.999
179 200.864

3 5.453
179 148.263

3 10.789
179 186.435

3 0.686
179 210.931

3 8.473
179 98.948

3 22.781
179 191.328

3 0.741
179 50.155

3 7.022


MS
7.638
1.203

1.79
1.534

19.797
1.329

0.374
0.443

3.639
0.31

6
1.122

1.818
0.828

3.596
1.042

0.229
1.178


2.824
0.553

7.594
1.069

0.247
0.28


F
6.35


<.001*


1.167 0.324


14.891


<.001*


0.845 0.471


11.749


<.001*


5.347 0.002*



2.195 0.090


3.453



0.194


5.109


7.104


0.018*



0.900


0.002*


<.001*


0.882 0.452


2.341 3.133 0.027*









Table 17 Continued
Variable and source df SS MS F R
Within groups 179 133.733 0.747
Method of birding off-road vehicle
Between groups 3 0.974 0.325 0.572 0.634
Within groups 179 101.693 0.568
* Significant at the .05 level

Much like the Experience index, the Equipment and Economic Commitment index

also contained 9 significant potential impact behavior variables (Tables 18 and 19).

These variables consisted of the original four variables found among all indexes (use of

vocalized calls, use of audio recordings, approach birds, method of birding observation

deck), two variables in common with the Experience index (enter private property,

method of birding car) and three other variables (use of flash photography and/or video

with artificial lighting, flush birds, method of birding bird blind). Most (6 of 9) means

for statistically significant potential impact behaviors grew as birders became more

specialized. However, means of three variables (use of flash photography and/or video

with artificial lighting, approach birds, flush birds) decreased from the intermediate to the

advanced birders.

Table 18: Means and Standard Deviations for Segmented Equipment and Economic
Commitment Index and Nineteen Dependent Variables
Casual Novice Intermediate Advanced
Potential Impact Behavior M SD M SD M SD M SD
Items
Use of food and/or water 1.5 0.98 1.4 0.78 1.6 1.09 1.4 1.01
Use or wear of attractive
colors 1.2 0.53 1.2 0.48 1.3 0.75 1.2 0.50
*Use of flash photography
or video with artificial 1.3a 0.68 1.4b 0.71 1.8abc 1.09 1.2c 0.63
lighting
*Enter private property 1.3abc 0.55 1.6a 0.71 1.7b 0.82 1.7c 0.89
Litter in the field 1.1 0.35 1.2 0.42 1.2 0.50 1.1 0.32
Urinate and/or defecate in
the field 2.0 1.10 2.3 1.23 2.2 1.11 2.7 1.00









Table 18 Continued

Potential Impact Behavior
Items
Self-rated noise level
*Use of vocalized calls
Use of instrument calls
*Use of audio recordings
*Approach birds
*Flush birds
*Method of birding car
Method of birding boat
Method of birding -
walking
Method of birding -
off-trail walking
*Method of birding -
bird blind
*Method of birding -
observation deck
Method of birding -
off-road vehicle


Casual

M SD

2.9 1.15
1.7a 1.06
1.1 0.55
1.0a 0.26
2.7abc 1.05
2.3ab 0.88
3.1ab 1.10
2.4 1.15

3.7 0.87

2.9 1.20

1.1ab 0.44

2.3ab 0.96


Novice Intermediate


M

2.9
2.0b
1.2
1.2b
3.7 a
2.66a
3.2c
2.3

4.0

3.4

1.2

2.4


SD

1.21
1.10
0.61
0.45
0.99
0.87
0.93
1.17

0.72

1.02

0.57

0.78


Advanced


M SD M SD


2.8
2.5a
1.4
1.3ac
3.8b
2.8b
3.5a
2.2

4.1

3.1

1.4a

2.77a


1.60
1.26
0.89
0.57
0.81
0.96
1.15
0.91

0.63

0.86

0.59

0.88


2.5
3.4ab
1.4
2.1abc
3.6c
2.6
3.9bc
2.7

4.0

3.4

1.5b

2.7b


0.84
1.54
0.69
1.13
1.07
0.90
0.46
0.73

0.62

1.07

0.51

0.65


1.4 0.83 1.3 0.66 1.4 0.86 1.3 0.45


Note: Similar superscripts indicate significant differences utilizing LSD post hoc analysis. For example,
participants categorized as intermediate birders were significantly more likely to use flash photography
than those categorized as casual birders.
* Significant at the .05 level.

As compared to the significant variables in the Experience index, one-way

ANOVA analysis on the relationships in the Equipment and Economic Commitment

index (Table 19) indicated a wider range of significance (p) values. In this case, only

three variables (use of vocalized calls, use of audio recordings, approach birds) were less

than 0.001 and six variables ranged from 0.005 to 0.037.

Table 19: One Way Analysis of Variance for Equipment and Economic Commitment
Index on Nineteen Dependent Variables
Variable and source df SS MS F p
Use of food and/or water
Between groups 3 1.462 0.487 0.539 0.656
Within groups 179 161.981 0.905
Use or wear of attractive colors
Between groups 3 0.703 0.234 0.738 0.531









Table 19 Continued
Variable and source
Within groups
Use of flash photography or video with
artificial lighting
Between groups
Within groups
Enter private property
Between groups
Within groups
Litter in the field
Between groups
Within groups
Urinate and/or defecate in the field
Between groups
Within groups
Self-rated noise level
Between groups
Within groups
Use of vocalized calls
Between groups
Within groups
Use of instrument calls
Between groups
Within groups
Use of audio recordings
Between groups
Within groups
Approach birds
Between groups
Within groups
Flush birds
Between groups
Within groups
Method of birding car
Between groups
Within groups
Method of birding boat
Between groups


df
179



3
179

3
179

3
179


SS
56.816



6.467
109.795

4.49
87.248

0.456
28.593


3 8.621
178 228.395


3.111
275.268


3 52.499
179 244.857


2.258
78.102

15.972
50.388


3 43.245
179 175.619


9.568
144.148

13.668
183.556


MS
0.317



2.156
0.613

1.497
0.487

0.152
0.16

2.874
1.283

1.037
1.546

17.5
1.368

0.753
0.436

5.324
0.281

14.415
0.981

3.189
0.805

4.556
1.025


F p


3.515 0.016*



3.07 0.029*



0.951 0.417



2.24 0.085



0.671 0.571



12.793 <.001*



1.725 0.163



18.913 <.001*



14.692 <.001*



3.96 0.009*



4.443 0.005*


3 4.502 1.501 1.297 0.277









Table 19 Continued
Variable and source df SS MS F 12
Within groups 179 207.116 1.157
Method of birding walking
Between groups 3 4.236 1.412 2.449 0.065
Within groups 179 103.185 0.576
Method of birding off-trail walking
Between groups 3 8.842 2.947 2.57 0.056
Within groups 179 205.267 1.147
Method of birding bird blind
Between groups 3 2.47 0.823 3.043 0.030*
Within groups 179 48.426 0.271
Method of birding observation deck
Between groups 3 6.48 2.16 2.879 0.037*
Within groups 179 134.274 0.75
Method of birding off-road vehicle
Between groups 3 0.323 0.108 0.188 0.904
Within groups 179 102.343 0.572
* Significant at the .05 level

For the Centrality to Lifestyle index, 8 potential impact behavior variables were

significant (Tables 20 and 21). All significant variables found in this subset had also

been found to be significant in one or more of the other dimensional indexes. Trends for

means in this index were consistent with the other dimensional indexes as well. That is,

they increased from casual through advanced birders.

Three of the insignificant variables (use of food and water, use of flash

photography or video with artificial lighting, self-rated noise level) in this index had

means that were slightly elevated in the casual group. The variable identified as self-

rated noise level has relatively high means (2.6 to 3.0) in all categories of birders and

across all indexes.









Table 20: Means and Standard Deviations for Segmented Centrality to Lifestyle Index
and Nineteen Dependent Variables


Casual


Novice Intermediate


Advanced


Potential Impact Behavior
Items
Use of food and/or water
Use or wear of attractive
colors
Use of flash photography or
video with artificial
lighting
Enter private property
Litter in the field
*Urinate and/or defecate in
the field
Self-rated noise level
*Use of vocalized calls
Use of instrument calls
*Use of audio recordings
*Approach birds
Flush birds
*Method of birding car
Method of birding boat
*Method of birding -
walking
Method of birding -
off-trail walking
*Method of birding -
bird blind
*Method of birding -
observation deck
Method of birding -
off-road vehicle


M SD M SD M SD M SD

1.5 0.93 1.5 1.03 1.4 0.96 1.4 0.68


1.2 0.44 1.3 0.67


1.5 0.87 1.4 0.76

1.4 0.61 1.6 0.72
1.2 0.39 1.2 0.37

2.0ab 1.18 2.0cd 1.03


1.1 0.40 1.4 0.83


1.4 0.84 1.1 0.46

1.6 0.77 1.8 0.86
1.2 0.49 1.2 0.38


2.6ac 1.24 2.6bd


0.96


3.0 1.33 2.9 1.33 2.6 1.03 2.7 1.00
1.6a 0.96 2.0a 1.29 2.6a 1.13 3.6a 1.22
1.1 0.56 1.3 0.78 1.2 0.58 1.6 0.77


1.1a
2.9abc


0.38
1.15


1.1b 0.33
3.6a 1.05


0.58
0.96


2.1 ab
3.6c


1.13
0.68


2.4 0.89 2.5 0.88 2.7 1.06 2.9 0.74


3.1ab
2.4


1.05
1.14


3.3 1.11
2.3 1.22


3.5a 0.97
2.4 0.83


3.7b 0.81
2.5 0.91


3.7a 0.93 3.9 0.66 4.2a 0.51 4.1 0.66

3.0 1.15 3.1 1.10 3.3 1.03 3.5 0.84


1.1ab


0.44


1.2 0.50 1.4a 0.54 1.5b


2.1abc 0.92 2.6a 0.90

1.4 0.78 1.4 0.89


0.77


2.7b 0.68 2.7c 0.75

1.3 0.62 1.2 0.42


Note: Similar superscripts indicate significant differences utilizing LSD post hoc analysis. For example,
participants categorized as intermediate birders were significantly more likely to urinate and/or defecate in
the field than those categorized as casual birders.
* Significant at the .05 level.


The one-way ANOVA analysis for the Centrality to Lifestyle index (Table 21)

indicated the highest p-value among all the significant variables in any index. The









variable described as method of birding car, had a value of 0.048. Two other variables,

method of birding walking and method of birding bird blind, had p-values at 0.29 and

0.27 respectively. On the other hand, three potential impact behavior variables

(vocalized calls, audio recordings, approach birds) had significance values that were less

than .001.

Table 21: One Way Analysis of Variance for Centrality to Lifestyle Index on Nineteen
Dependent Variables


Variable and source
Use of food and/or water
Between groups
Within groups
Use or wear of attractive colors
Between groups
Within groups
Use of flash photography or video with
artificial lighting
Between groups
Within groups
Enter private property
Between groups
Within groups
Litter in the field
Between groups
Within groups
Urinate and/or defecate in the field
Between groups
Within groups
Self-rated noise level
Between groups
Within groups
Use of vocalized calls
Between groups
Within groups
Use of instrument calls
Between groups
Within groups


df SS


0.744
160.311

1.065
56.413



2.229
113.864

3.517
87.961

0.088
28.929


3 13.009
177 223.974


5.537
272.816


3 70.654
178 226.687

3 2.99
178 77.318


MS

0.248
0.901

0.355
0.317



0.743
0.64

1.172
0.494

0.029
0.163

4.336
1.265

1.846
1.541

23.551
1.274

0.997
0.434


F 1

0.275 0.843




1.12 0.342



1.161 0.326



2.372 0.072



0.18 0.910



3.427 0.018*



1.197 0.312



18.493 <.001*



2.294 0.080









Table 21 Continued
Variable and source
Use of audio recordings
Between groups
Within groups
Approach birds
Between groups
Within groups
Flush birds
Between groups
Within groups
Method of birding car
Between groups
Within groups
Method of birding boat
Between groups
Within groups
Method of birding walking
Between groups
Within groups
Method of birding off-trail walking
Between groups
Within groups
Method of birding bird blind
Between groups
Within groups
Method of birding observation deck
Between groups
Within groups
Method of birding off-road vehicle
Between groups
Within groups
* Significant at the .05 level


df SS MS


3 15.693
178 50.615

3 23.405
178 194.974


5.802
147.676

8.522
188.621


3 0.387
178 211.107


5.291
102.121


3 4.564
178 208.777

3 2.541
178 48.299

3 10.07
178 130.353

3 0.582
178 101.973


5.231
0.284

7.802
1.095

1.934
0.83

2.841
1.06

0.129
1.186

1.764
0.574

1.521
1.173

0.847
0.271

3.357
0.732

0.194
0.573


F p


18.396 <.001*



7.122 <.001*



2.331 0.076



2.681 0.048*



0.109 0.955



3.074 0.029*



1.297 0.277



3.122 0.027*



4.584 0.004*



0.339 0.797


Finally, for the overall recreation specialization index, 9 potential impact behavior

variables were significant (Tables 22 and 23). The highest variable means consistently

seen among all dimensional indexes and in the overall recreation specialization index









were: method of birding car, method of birding walking, method of birding off-trail

walking, use of vocalized calls and approach birds. Self rated noise level had high

statistical means as well (approximately 2.7). However, one-way ANOVA analysis never

found it to be statistically significant across any level of recreation specialization.

Seven significant variables in the recreational specialization index had means that

increased from the casual through the advanced birder classification. Means for two

variables (approaching birds and urinating and/or defecating in the field) increased from

the casual to intermediate birder, but then decreased slightly in the advanced birder.

Table 22: Means and Standard Deviations for Segmented Recreation Specialization
Index and Nineteen Dependent Variables


Casual


Novice Intermediate


Advanced


Potential Impact Behavior
Items
Use of food and/or water
Use or wear of attractive
colors
Use of flash photography or
video with artificial
lighting
*Enter private property
Litter in the field
*Urinate and/or defecate in
the field
Self-rated noise level
*Use of vocalized calls
Use of instrument calls
*Use of audio recordings
*Approach birds
Flush birds
Method of birding car
Method of birding boat
*Method of birding -
walking
*Method of birding -
off-trail walking


M SD M

1.5 0.96 1.4

1.3 0.63 1.1

1.4 0.80 1.5

1.4ab 0.61 1.5c
1.2 0.41 1.2

1.9ab 1.07 2.1c
3.0 1.17 2.8
1.6a 0.91 1.9b
1.2 0.60 1.2
1.1a 0.37 1.1b
2.9abc 1.17 3.5a
2.4 0.88 2.4
3.1 1.14 3.3
2.3 1.19 2.4

3.7abc 0.85 4.0a

2.8ab 1.15 3.2


SD

0.83

0.42

0.84

0.66
0.42

1.12
1.33
1.18
0.74
0.33
1.02
0.94
0.99
1.09

0.76

1.04


M SD M SD


1.4

1.1

1.5

1.8ac
1.2

2.8ac
2.7
2.6ab
1.3
1.2c
3.7b
2.8
3.4
2.2

4.2ab

3.4a


1.04

0.42

0.87

0.79
0.40

1.17
1.31
1.21
0.61
0.50
0.92
0.91
1.02
0.93

0.50

0.90


1.5

1.4

1.2

1.7b
1.1

2.6b
2.5
3.6ab
1.5
2.2abc
3.6c
2.7
3.7
2.6

4.2c

3.7 b


1.07

0.83

0.50

0.87
0.32

0.96
1.07
1.42
0.77
1.08
1.02
0.95
0.65
0.90

0.69

0.95









Table 22 Continued
Casual Novice Intermediate Advanced
Potential Impact Behavior M SD M SD M SD M SD
Items
*Method of birding -
bird blind 1.1a 0.47 1.2 0.47 1.3 0.67 1.5a 0.51
*Method of birding -
observation deck 2.3ab 0.88 2.4 0.87 2.7a 0.88 2.7b 0.73
Method of birding -
off-road vehicle 1.4 0.78 1.3 0.70 1.4 0.87 1.3 0.58
Note: Similar superscripts indicate significant differences utilizing LSD post hoc analysis. For example,
participants categorized as intermediate birders were significantly more likely to enter private property than
those categorized as casual birders
* Significant at the .05 level.

Significance in terms of a p-value for variables in the recreation specialization

index starts with methods of birding bird blind (0.044). Three other variables (urinate

and/or defecate in the field, use of vocalized calls, use of audio recordings) differ greatly

in that their level of significance is less than 0.001.

Table 23: One Way Analysis of Variance for Recreation Specialization Index on
Nineteen Dependent Variables
Variable and source df SS MS F p
Use of food and/or water
Between groups 3 0.657 0.219 0.241 0.868
Within groups 179 162.786 0.909
Use or wear of attractive colors
Between groups 3 1.442 0.481 1.535 0.207
Within groups 179 56.077 0.313
Use of flash photography or video with
artificial lighting
Between groups 3 1.41 0.47 0.733 0.534
Within groups 179 114.852 0.642
Enter private property
Between groups 3 5.827 1.942 4.047 0.008*
Within groups 179 85.91 0.48
Litter in the field
Between groups 3 0.182 0.061 0.376 0.771
Within groups 179 28.867 0.161
Urinate and/or defecate in the field









Table 23 Continued
Variable and source
Between groups
Within groups
Self-rated noise level
Between groups
Within groups
Use of vocalized calls
Between groups
Within groups
Use of instrument calls
Between groups
Within groups
Use of audio recordings
Between groups
Within groups
Approach birds
Between groups
Within groups
Flush birds
Between groups
Within groups
Method of birding car
Between groups
Within groups
Method of birding boat
Between groups
Within groups
Method of birding walking
Between groups
Within groups
Method of birding off-trail walking
Between groups
Within groups
Method of birding bird blind
Between groups
Within groups
Method of birding observation deck
Between groups


SS
23.842
213.174


3 5.021
178 273.358

3 73.411
179 223.944

3 1.625
179 78.735

3 21.183
179 45.178

3 17.835
179 201.029

3 5.415
179 148.3

3 7.23
179 189.994

3 1.949
179 209.668

3 7.378
179 100.042

3 16.809
179 197.3

3 2.249
179 48.647


MS
7.947
1.198

1.674
1.536

24.47
1.251

0.542
0.44


F
6.636



1.09


P
<.001*



0.355


119.559 <.001*



1.232 0.300


7.061 27.976
0.252


5.945
1.123

1.805
0.828

2.41
1.061

0.65
1.171

2.459
0.559

5.603
1.102

0.75
0.272


<.001*


5.293 0.002*



2.179 0.092



2.271 0.082



0.555 0.646



4.401 0.005*



5.083 0.002*



2.758 0.044*


3 6.48 2.16 2.879 0.037*









Table 23 Continued
Variable and source df SS MS F_
Within groups 179 134.274 0.75
Method of birding off-road vehicle
Between groups 3 0.595 0.198 0.348 0.791
Within groups 179 102.072 0.57
* Significant at the .05 level

For each of the four indexes, almost half of the potential impact variables were

found to be significant. These statistical tendencies describing the relationships between

birder specialization and potential impact behaviors may seem somewhat surprising. The

results seemed to contradict the hypothesis: that advanced birders should report the

lowest frequency of potential impact behaviors. More specifically, for all of the

behaviors found to be statistically significant, the means of the reported behaviors

increased from casual through intermediate birders. For some variables, means continued

to rise as birders became more advanced, while others decreased slightly. The following

chapter will discuss the results in terms of using recreation specialization theory to

describe birder behavior. Furthermore, it will examine issues of acceptable impacts,

future research and suggest ways to improve our communication with birders.














CHAPTER 5
DISCUSSION

Using Bryan's (1977) recreational specialization theory and related specialization

studies (Wellman et.al 1982, Virden and Schreyer 1988, McFarlane 1994), it was

hypothesized that birder specialization would be inversely related to the number of

potential impact behaviors. That is, as birdwatchers moved on a continuum from the

general to specialized, their number of reported potential impact behaviors would

decrease. This hypothesis was tested on three dimensional indexes and on one overall

recreational index. Surprisingly, the findings of this research did not support the

proposed hypothesis among any of the indexes. Consequently, the hypothesis was

rejected.

Summary of Results

Not only did the overall recreation specialization index produce results contrary to

the hypothesis, but there was also substantial parity among the three dimensions that were

individually tested. Four statistically significant variables (use of vocalized calls, use of

audio recordings, approach birds, method of birding observation deck) were shared

among all indexes when the potential impact behaviors for the recreation specialization

index were grouped into the Experience, Equipment / Economic Commitment and

Centrality to Lifestyle dimensions. Four other variables (method of birding trails and

boardwalks, method of observation bird blinds, enter private property, urinate and/or

defecate in the field) in the recreation specialization index were shared between two (of









the three) dimensions, suggesting that these variables may be more difficult to address in

terms of future education and/or management options.

Generally, post hoc multiple comparisons on the significant variables showed that

self-reported potential impact behaviors increased as the specialization continuum went

from the general to the specialized. Specifically, for all of the behaviors found to

statistically significant, the means of the reported behaviors increased from casual

through intermediate birders. For example, in the overall recreation specialization index,

participants categorized as intermediate birders were significantly more likely to enter

private property than those categorized as casual birders. For some variables, means

continued to rise as birders became more advanced, while others decreased slightly.

Most means for the significant potential impact behaviors ranged between one and

two. Subsequently, the Likert-scale used in this study identified the frequency of

behavior as somewhere between never and rarely. Higher means on the overall

recreation specialization index were found for approaching birds, walking on

trails/boardwalks, off-trail walking and use of observation decks. Some of the lowest

means among birders on this index came from use of audio recordings and use of bird

blinds.

Potential Implications

Perhaps when Bryan (1977) conceptualized the linkage of behavior to the

specialization continuum, potential negative behaviors (or the lack of them) were not

intended to be part of the quotient. Additionally, it may be that this research indicates

other factors are involved when participants carry out potential impact behaviors. For

example, peer pressure and knowledge of ethical guidelines were not measured in this

study.









Bryan (1979) and Wellman et al. (1982) discovered evidence that suggested highly

specialized recreationists would have a greater concern for conservation. Based on the

results of this study, Bryan's (1979) theory may not be appropriate for use in determining

if participant behavior in the field reflects the concern for wildlife. Someone's concern

for birds does not necessarily equate with behaviors that reduce human impact. On

several occasions, intermediate and advanced birders, who might be expected to behave

with the most concern for the environment, carried out a greater number of potential

impact behaviors.

This research seems to support Boyle and Samson's (1985) report and McFarlane's

(1994) assessment of advanced birder motivations. Achievement goals may be driving

advanced birders to carry out more potential impact behaviors in their effort to "bag"

birds for their life list. Higher means found in this study for approaching birds and off-

trail walking may be indicators for this explanation.

Certainly, wildlife agencies can use this research in managing statewide birding

trails. It is likely that some of the participants in this study will also use one of the

sections of the Great Florida Birding Trail and the results may provide some insight as to

how much visitor impact is taking place. If higher means for walking on

trails/boardwalks and use of observation decks suggest that facilities are readily being

utilized, then lower means may predict problems of access or supply. The low mean is

notable for the use of bird blinds, especially since they are assumed to have very little

impact on wildlife. Perhaps more bird blinds need to be constructed.

Learning more about the behaviors of each type of birder can help managers assess

visitation to sensitive habitats. For example, previously prohibited access to fragile









habitats may be possible if certain groups of birders show that they carry out fewer

impact behaviors. At the other extreme, deterrents such as guardrails or increased

supervision may be necessary for groups that tend to be more depreciative. According to

this research, specialized birders need just as much (or more) supervision as those

categorized as casual or novice.

Visitor management techniques may become evident based on the different type of

impact behaviors carried out by casual, novice, intermediate, and advanced bird watchers.

For example, it may be necessary to provide general literature about excess noise levels

and use of flash photography to the casual and novice birders. On the other hand, the

intermediate and advanced birders may need more targeted communication stressing the

negative effects of vocalized calls (pishing) and approaching birds. The practical

applications of this research may help ensure the sustainability of wildlife and/or aid in

the administration of high quality recreational experiences.

Finally, the results of this study have the potential to stimulate further research in

the analysis of behaviors that may impact wildlife. For example, it might be interesting

to find out if birders are living up to their reports of impact behavior when they are

watched unobtrusively. Additionally, different sampling techniques could be used to

evaluate the results of this study. and it might be beneficial to determine whether the

results are consistent among other recreational pursuits.

Pertinent Issues to Consider

Since this was a descriptive study, all impacts were measured using the same scale.

However, an important question to consider deals with the degree of impact that is

acceptable. Can birders, biologists and other outdoor recreation agencies agree on what

behaviors have an unacceptable impact on wildlife? Kazmierow et al. (2000) referred to









the subjectivity that is inherent in assessing what constitutes a potential impact. Methods

of observation have different degrees of impact and some of them have been analyzed in

research (Klein 1993, Rodgers and Smith 1997). However, any sort of outdoor viewing

could be considered an impact to an animal's spatial and temporal resources. Since this

research focuses on the descriptive nature of the birding activity that requires humans to

enter the environment for viewing, no delineation was made for the degree of impact.

One can intuitively speculate that there are some differences in impact. For

example, when compared to cars or walking, the use of bird blinds might be considered

the least disruptive method of observation. In terms of a higher potential for impact,

flushing birds is likely to be more depreciative than using vocalized calls (pishing).

When considering the self-reported behaviors in this study, it seems plausible that at the

very least birders are drawing different conclusions as to the severity of an impact.

Additionally, this study seemed to support an advanced birder belief that the perceived

benefits of observing birds outweighs the perceived liabilities of their actions. Future

studies comparing participant behavior on a specialization continuum and the degrees of

impact would likely be beneficial to managers.

Some 'impacts' could even be considered a benefit to birds. For example, some

birders may consider feeding birds as a positive measure to reduce winter mortality. On

the other hand, scientists have done research that suggests that feeding birds can negate

any positive effects because it also attracts predators that reduce bird populations

(Madison et al. 2002).

Another issue to consider is individual assessment of potential impact behaviors.

Despite attempts to ensure birders were answering honestly, some respondents may have









been reluctant to admit to their participation in potential impact behaviors. Because the

survey questions referred to sensitive topics, there is potential for data contamination due

to social desirability response bias (Zerbe and Paulhus 1987). Since some potential

impact behaviors were reported, the social desirability affect was apparently not

pervasive in this study. However, this affect can make it more likely that the participants

underestimated their accounts of potential impact behaviors. Consequently, birders may

have produced a greater impact than they actually reported. Variables considered

insignificant in this study may actually be supported in future studies, especially if

unobtrusive observation is used to study participants.

Limitations

There were some limitations to this study. While the total sample size (n = 184) of

participants may be adequate for certain measurements, it may be disadvantageous when

using the specialization construct. After segmenting the participants in this study, there

were relatively few (n = 18) advanced birders contributing to the data. Subsequently,

there may be some potential for reduced reliability for that subset of participants.

Doubling the number of interview participants likely would have reduced potential

sampling error and would have increased the likelihood of generalizing the results to

larger populations of birdwatchers.

Another obstacle to this study was the unusual sex ratio of sample participants.

Women outnumbered men by 7.2%, which is atypical when compared to many studies of

birder populations (Adams et al. 1997, Wiedner and Kerlinger 1990). However, Eubanks

et al. (2004) also noted an usual ratio of females (52%) which included participants who

attended birding festivals. It seems plausible that birding festivals limit their attendance

to certain types of participants. Male birderwatchers who don't like crowds may avoid









birding festivals altogether. However, the unusual sex ratio may also be explained by the

fact that most participants were selected near merchant and informational booths. Studies

indicate women are more likely to participate in shopping activities (Dholakia 1999),

which may have had an effect on the sample. Additionally, the intercept interview

sampling strategy has rarely been used for measuring recreation specialization. If this

technique limits access to some birders, it may be related to the uncommon sex ratio in

this study.

Conclusions

If managers are going to continue to find a balance between recreational

opportunities and environmental protection, they will need to find ways to evaluate those

activities that potentially impact wildlife. In the case of birding, millions of people are

located along the recreational specialization continuum. Even though this activity is

oftentimes considered a nonconsumptive, low impact pursuit, the participants in this

study reported behaviors that potentially impact birds. To improve our evaluative

measures, it would seem beneficial for stakeholders to come to a stronger agreement on

what is acceptable behavior and to what degree is a behavior considered unacceptable.

Finally, the results of this study suggest the importance of communication as

birders become more specialized. Managers may need to focus educational programs

away from identification techniques and more on potential impact concerns. More

importantly, ways to motivate birders to reduce impacts should be addressed in

conjunction with educational activities.















APPENDIX A
ON-SITE BIRDER RECREATION SURVEY IN FLORIDA











On-Site Birder Recreation Survey in Florida

Date: Location

Section 1: Recreation Specialization

All replies will be kept completely anonymous.

1. How many years have you been birding? __

2. How many times have you been away from
your household and participated in birding
outings or trips?

In the past week

In the past month

In the past year

3. What is the typical distance you travel and
participate in birding activities?

miles

4. What is the farthest distance you have traveled
and participated in birding?

miles

5. Which statement describes you best?

___ I take specific trips to observe birds.

____ I do birding as a side activity, on trips taken
for other purposes

6. On a scale of 1-10, how do you rate your
experience as a birder (with 1= No experience
and 10 = Expert)? __

7. Which of the following statements, describes
you best?

__ I rarely participate in birding outings

__ I participate in birding outings, but
don't have particular sites that I visit

__ I participate in birding outings
anywhere and everywhere possible

__ I participate in birding outings and have
favorite sites that I visit


8. Without using a field guide, how many bird
species can you identify?

By sight

By sound

9. Do you maintain a life list of birds you have identified?

Yes __ No (go to #11)

10. How many bird species do you have on your
birding life list?

11. Currently, how many subscriptions to birding
magazines do you own?

Birder's World
The Auk
Bird Watcher's Digest
Wild Bird
Living Bird
__ Birding
Audubon Magazine
Birds and Blooms
Ducks Unlimited Magazine
North American Birds
Other (Please specify):

12. How many birding books do you own (including
field guides)? __

13. Are you a member of any birding group or
organization?

If yes, how many? __

Please list names:

14. Do you own the following birding equipment?
(Please mark if yes)

Binoculars
Field Guide
Spotting Scope
Bird Call
Recording / Listening Device
Life List
Audio recordings (CD's, Tapes, Albums)
Computer Software
Internet
Others) (specify)

15. If you had to replace all of your birding equipment,
how much would you have to spend?











16. How many people are in your group on a
typical birding outing or trip (include
yourself)? __

Section 2: Birder Activities

17. When birding, how often do you use the
following methods to observe birds?

N = Never
R = Rarely
S = Sometimes
F = Frequently
A = Always


A car


A boat


N R S F

1 2 3 4

1 2 3 4


Walking (trails,
boardwalks) 1

Off-trail walking 1


2 3 4

2 3 4


A bird blind 1 2 3 4 5


19. When birding, how often do you do the following?

N R S F A

Approach birds 1 2 3 4 5

Flush birds 1 2 3 4 5
(accidentally or deliberately)

Use flash 1 2 3 4 5
photography or video
with artificial lighting

Enter private
A property without 1 2 3 4 5
the owner's permission
5 (accidentally or deliberately)

5 Litter in the field 1 2 3 4 5
(accidentally or deliberately)


5 Urinate and/or
defecate in the
5 field when facilities
are not available


1 2 3 4 5


Observation deck 1

Off-road vehicle
(no roads) 1

Other: 1


2 3 4


2 3 4

2 3 4


18. When birding, how often do you use the
following methods to attract birds to you?

N R S F A


20. Rate your group's noise level on a typical
birding outing or trip.

1 2 3 4 5 6 7 8


Very quiet Quiet


Section 3:


Loud Very loud


Participant Information


Again, all replies will be kept completely anonymous
This section is for statistical purposes only.


Food and/or water 1
(in the field)

Vocalized calls
(Pishing, whistles) 1

Instrument call 1
(Duck, turkey)

Audio recordings 1

Use or wear
attractive colors 1
(Red for hummingbirds)


2 3 4 5 21. Which of the following describes your present
situation?


2 3 4 5

2 3 4 5


-_ Single, no children
-_ Single parent, have children
Married, no children
Married, have children
Other


2 3 4 5 22. What is the year of your birth?


2 3 4 5


19

23. Gender:


1 2 3 4 5 Male


Other:


Female










24. Which of these best describes your race or
ethnic group?

American Indian or Alaskan Native
Latino or Hispanic
Asian or Pacific Islander
Caucasian
African American
Other (specify)

25. What is the highest level of education you
have completed?

__ Eighth grade or less
__ Some high school
__ High school graduate or GED
Some college
__ College graduate
__ Some graduate school
Graduate degree or beyond

26. What was your approximate total household
income, before taxes, in 2003?

Less than $10,000
S $10,000 to $19,999
$20,000 to $29,999
$30,000 to $39,999
$40,000 to $49,999
$50,000 to $59,999
$60,000 to $69,999
$70,000 to $79,999
$80,000 to $89,999
$90,000 to $99,999
$100,000 or More














APPENDIX B
FLORIDA BIRDING FESTIVALS SPRING 2004


Jan 17-19 Everglades BirdFest


Feb 28


Orlando Wetlands Park Fest.


March 14 Pelican Island Wildlife Fest.


April 2-4 Big "0" Birding Fest.


Everglades National Park
(954) 776-5585

Orlando/Titusville
(407) 568-1706

Orlando/Melbourne
(772) 562-3909

Moore Haven (Lake Okeechobee)
(863) 946-0300


April 15-17


April 24


May 13-16


Wakulla Birding & Wildlife Fest.


Welcome Back Songbirds Fest.


FL 1st Coast Bird. & Nature Fest.


Wakulla Springs
(850) 487-0516

Brooksville
(352) 754-6722

St. Augustine
(800) 653-2489

















APPENDIX C
ON-SITE BIRDER RECREATION SURVEY: VERBAL CONSENT SCRIPT

Hello. My name is I'm working to collect data for a graduate study with
the University of Florida. We're cooperating with the Birding Festival to
better understand birders and their activities. The information we are collecting will help
manage Florida lands for nature-based recreation.

Our study will be based on anonymous surveys, such as this one, which ask questions
based on birder characteristics, activities and actions. You must be at least 18 years old or
older to participate in this study. The questionnaire takes approximately 10 minutes and
is completely confidential. Are you able to assist in our study by answering these survey
questions? (If the answer is yes, continue, if no, thank the individual for his/her time and
terminate the conversation.)

Thank you for your willingness to participate. You do not have to answer any question
you do not wish to answer, and you may discontinue participation or withdraw your
answers at any time without consequence. There is no anticipated risk or direct benefit to
participants. Unfortunately, I cannot compensate you for your time, but your
participation is greatly appreciated. If you have any questions regarding this project, you
may contact me, Henry Bireline at 352-262-7890 and/or Dr. Holland at 352-392-4042
ext. 1313. Questions or concerns about research participants' rights may be directed to the
UFIRB Office at 352-392-0433. May I begin the survey? (If answer is no, thank the
individual and terminate the conversation. If yes, continue.)

(See Attachment 2 for a copy of the on-site survey). (Complete the survey / i/h willing
participants.)

(See Attachment 3 for a copy of the contact information). (Give the individual a copy of
the contact information.) Here is a copy of the contact information for questions
regarding this project. Thank you for participating. Your time is greatly appreciated and
is extremely helpful to our study.














APPENDIX D
POST-SURVEY CONTACT INFORMATION

If you have any questions regarding this project, you may contact the graduate

student, Henry Bireline at 352-262-7890 or Dr. Holland at 352-392-4042 ext. 1313.

Questions or concerns about research participants' rights may be directed to the UFIRB

Office at 352-392-0433.















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BIOGRAPHICAL SKETCH

Henry Bireline (nickname: Buz) was born July 27, 1969, in Danville, Illinois.

After graduating from high school in 1987, he briefly attended his hometown community

college and promptly quit to take a role in the workplace. In an effort to explore his love

for animals, he later attended the Zoo Animal Technology Program at Santa Fe

Community College in Gainesville, Florida and earned an Associate of Science degree

(with honors) in 1992. In 1994, he again graduated with honors from Friends University

(Wichita, Kansas) earning a Bachelor of Science in zoo science. He worked in the

conservation and zoo fields, caring for a wide variety of animals. Eventually he found

his way back to Santa Fe Community College where he currently teaches in the Zoo

Animal Technology Program and serves as the Assistant Director at the SFCC Teaching

Zoo.

Henry was inspired to work on his master's degree part-time while working full-

time in the zoological industry and teaching 16-19 credit hours. In 2002, he took eight

months off from both work and graduate school to walk the entire distance of the

Appalachian Trail (2,170 miles). Henry completed his master's degree in May 2005.