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Title:
Human-wildlife conflict across urbanization gradients : spatial, social, and ecological factors
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Book
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English
Creator:
Gilleland, Amanda
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University of South Florida
Place of Publication:
Tampa, Fla
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Subjects / Keywords:
Urban Wildlife
Fragmentation
Landscape
Ecology
Attitudes
Dissertations, Academic -- Geography & Env Sci & Policy -- Masters -- USF   ( lcsh )
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non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: As suburban and exurban residential developments continue to multiply in urban areas, they encroach on wildlife habitats leading to increased human-wildlife interactions. The animals involved in direct conflict with homeowners are often relocated or exterminated by the homeowners. Often the homeowners contact state licensed wildlife trappers to eliminate the problem animal. In this study I examined how landscape, ecological, and social factors influence the incidence of human-wildlife conflict of thirty two residential areas in the Tampa, Florida metropolitan area. These residential areas, totaling over 300 km2, are part of the urban development gradient representing a range of urban land use from the urban core to exurban residential areas. This study consisted of four phases. In the first three phases, I investigated which landscape, ecological, and social factors contribute to homeowner conflict with wild animals on their property. In the last phase, I combine the significant factors contributing to human-wildlife conflict from the first three phases to build a more complete model. A spatial analysis of the locations of human-wildlife conflict events recorded by licensed wildlife trappers showed the most significant development and landscape factors affecting human-wildlife conflict reporting in a residential area were human population density and total area of natural habitat immediately adjacent to the residential area. A survey of the relative abundance of conflict prone animals living near and in remnant patches of habitat in suburban residential areas revealed that greater abundance was not correlated with the reported conflict of that species within that residential area. Species that were social, omnivorous, and had some flexibility in home range size were involved most often in conflict in highly urbanized environments. Species that were less social, and were not omnivorous, were not significantly involved in human-wildlife conflict in highly urbanized residential areas. These species tended to be restricted to intermediately urbanized areas like suburban and exurban residential areas. Several social factors were also significant contributors to human-wildlife conflict as revealed through personal interviews with suburban homeowners in Hillsborough and Pasco counties. Interviews confirmed that most people have positive attitudes toward wildlife, but some form of conflict was reported by thirty four percent of suburban residents, although only seventeen percent of those perceived it as a problem worth spending money to solve. Analysis of the attitudes of residents who reported having experienced problems associated with wildlife on their property, revealed significant negative correlations with statements of environmental concern and concern for the treatment of animals. Using all the significant variables from the physical landscape, ecological evaluation, and the human attitude study in the suburbs, I developed a statistical model of human-wildlife conflict across the urbanization gradient. While the model has marginal success in terms of practical application for prediction, it is quite valuable for defining the importance of these variables in relation to conflict with certain types of species across the gradient. This set of papers collectively defines relationships between variables existing in urban, suburban, and exurban residential areas and human-wildlife conflict. These factors should be considered when planning new residential areas to minimize human-wildlife conflict while maximizing the residents' enjoyment of natural areas and species within the residential area.
Thesis:
Dissertation (PHD)--University of South Florida, 2010.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
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by Amanda Gilleland.
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Title from PDF of title page.
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Document formatted into pages; contains X pages.

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ABSTRACT: As suburban and exurban residential developments continue to multiply in urban areas, they encroach on wildlife habitats leading to increased human-wildlife interactions. The animals involved in direct conflict with homeowners are often relocated or exterminated by the homeowners. Often the homeowners contact state licensed wildlife trappers to eliminate the problem animal. In this study I examined how landscape, ecological, and social factors influence the incidence of human-wildlife conflict of thirty two residential areas in the Tampa, Florida metropolitan area. These residential areas, totaling over 300 km2, are part of the urban development gradient representing a range of urban land use from the urban core to exurban residential areas. This study consisted of four phases. In the first three phases, I investigated which landscape, ecological, and social factors contribute to homeowner conflict with wild animals on their property. In the last phase, I combine the significant factors contributing to human-wildlife conflict from the first three phases to build a more complete model. A spatial analysis of the locations of human-wildlife conflict events recorded by licensed wildlife trappers showed the most significant development and landscape factors affecting human-wildlife conflict reporting in a residential area were human population density and total area of natural habitat immediately adjacent to the residential area. A survey of the relative abundance of conflict prone animals living near and in remnant patches of habitat in suburban residential areas revealed that greater abundance was not correlated with the reported conflict of that species within that residential area. Species that were social, omnivorous, and had some flexibility in home range size were involved most often in conflict in highly urbanized environments. Species that were less social, and were not omnivorous, were not significantly involved in human-wildlife conflict in highly urbanized residential areas. These species tended to be restricted to intermediately urbanized areas like suburban and exurban residential areas. Several social factors were also significant contributors to human-wildlife conflict as revealed through personal interviews with suburban homeowners in Hillsborough and Pasco counties. Interviews confirmed that most people have positive attitudes toward wildlife, but some form of conflict was reported by thirty four percent of suburban residents, although only seventeen percent of those perceived it as a problem worth spending money to solve. Analysis of the attitudes of residents who reported having experienced problems associated with wildlife on their property, revealed significant negative correlations with statements of environmental concern and concern for the treatment of animals. Using all the significant variables from the physical landscape, ecological evaluation, and the human attitude study in the suburbs, I developed a statistical model of human-wildlife conflict across the urbanization gradient. While the model has marginal success in terms of practical application for prediction, it is quite valuable for defining the importance of these variables in relation to conflict with certain types of species across the gradient. This set of papers collectively defines relationships between variables existing in urban, suburban, and exurban residential areas and human-wildlife conflict. These factors should be considered when planning new residential areas to minimize human-wildlife conflict while maximizing the residents' enjoyment of natural areas and species within the residential area.
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Human-Wildlife Conflict Across Urbanization Gradients: Spatial, Social, and Ecological Factors by Amanda H. Gilleland A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Geography College of Arts and Sciences University of South Florida Co-Major Professor Robert Brinkmann, Ph.D. Co-Major Professor Graham A. Tobin, Ph.D. Janice Chism, Ph.D. Jianguo Ma, Ph.D. Elizabeth Strom, Ph.D. Date of Approval: April 29, 2010 Keywords: Urban Wildlife, Fragment ation, Landscape, Ecology, Land Use Copyright 2010, Amanda H. Gilleland

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Dedication To David and Emily, thank you for all your support and patience.

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Acknowledgements I would like to give speci al thanks to Dr. Graham Tobin and Dr. Robert Brinkmann for adopting me by becoming my co -major professors after I was orphaned by my original major professor. I greatly appreciate your suppor t and encouragement through that tough transition and all you have given since. I also would like to give a very specia l thank you to Dr. Elizabeth Strom, Dr. Janice Chism, and Dr. Jianguo Ma for all their helpful advice and encouragement throughout the course of this study. Thank you for being such wonderful and inspiring teachers and role models. For my inspiration to become a scientist and a teacher, I would like to thank Dr. Christopher Marsh, Dr. William Rogers, and Dr Paula Mitchell. Dr. Marsh was a biology professor during my first tour of duty as an undergraduate. His passion for animal behavior was contagious and I fear I caught a terminal case! Dr. Rogers also shared that same infectious enthusiasm for animal be havior that made him a source of great inspiration as the advisor for my masters research. Through her love of insects, Dr. Mitchell taught me that we should value th e contributions of every species to the biosphere and apprecia te life on all levels.

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i Table of Contents List of Tables................................................................................................................. ....iv List of Figures....................................................................................................................vi Abstract....................................................................................................................... .....viii Chapter 1: The Mailbox Serpent 1.1 Introduction: The Paradox of a Suburban Conservation Area...........................1 1.2 Brief Dissertation Overview..............................................................................4 1.3 The Broader Impact...........................................................................................5 Chapter 2: Conceptual Framework and Methodology.........................................................8 2.1 Introduction.................................................................................................. .....8 2.2 The Pattern-Oriente d Approach to the Study of Human-wildlife Conflict...........................................................................................................10 2.2.1 Land Use and Urbanization..................................................................10 2.2.2 Theore tical Underpinnings Con cerning Fragmentation........................13 2.2.3 Methodol ogy Associated with the Pattern-Oriented Approach............18 2.2.3.1 The Gradient Paradigm to Landscape Study...........................18 2.2.3.2 Literature Review of Methodologies Used in Past Research...................................................................................19 2.3 The Species-Oriented Approach....................................................................22 2.3.1 Urban Ecology.....................................................................................22 2.3.2 Fragment Size and Wildlife.................................................................26 2.4 The Human Dimension of Human-Wildlife Conflict...................................28 2.4.1 Human-Wildlife Conflict.....................................................................28 2.4.2 Risk Species........................................................................................ .29 2.4.3 Approach es to Understanding Huma n Values of Wildlife..................32 2.5 Conclusion...................................................................................................34 Chapter 3: The Effect of Development and Landscape Patterns on the Incidence of Human-Wildlife Conflict Across an Urbanization Gradient.......................................36 3.1 Introduction.................................................................................................36 3.2 Methods.......................................................................................................38 3.2.1 Introduction........................................................................................38 3.2.2 Study Area.........................................................................................39 3.2.3 Reports of Conflict.............................................................................41 3.2.4 The Urbanization Gr adient and Conflict............................................45 3.2.5 Landscape Variables..........................................................................46

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ii 3.3 Results........................................................................................................50 3.3.1 Conflict Reports and Conflict Prone Species.....................................50 3.3.2 Levels of Urbanization and Conflict..................................................50 3.3.3 Landscape Variables and Conflict.....................................................52 3.4 Discussion...................................................................................................56 Chapter 4: The Effect of Behavioral Characteristics and Relative Abundance of Conflict Prone Species on Repor ted Human-wildlife Conflict in Suburban Tampa.........................................................................................................................62 4.1 Introduction.................................................................................................62 4.2 Methods.......................................................................................................65 4.2.1 Introduction...................................................................................... ..65 4.2.2 Study Ar eas for Biodiversity and Char acteristic Evaluation of Conflict-Prone Species.......................................................................65 4.2.3 Study Areas for Relative Abundance Surveys...................................66 4.2.4 Evaluati on of Diversity of Species in Conflict Reports Across the Urban Gradient............................................................................. 68 4.2.5 Evalua tion of Behavioral Characte ristics of Conflict-Prone Species Across the Urbanization Gradient........................................69 4.2.6 Relative Abundance Surveys Using Detection Stations....................71 4.3 Results................................................................................................... ......74 4.3.1 Biodi versity in Conflict Report s Across the Urbanization Gradient..............................................................................................74 4.3.2 Evalua tion of Behavioral Characte ristics of Conflict Prone Species Across the Urbanization Gradient.......................................76 4.3.3 Index of Relative Abundance in Suburban Remnant Patches...........83 4.4 Discussion...................................................................................................85 4.4.1 Urban Exploiters, Adapters and Human-Wildlife Conflict...............85 4.4.2 Relative Abundance in Remnant Patches and Conflict Reporting...........................................................................................87 Chapter 5: The Effect of Human Valu es and Perceptions of Wildlife on Human-wildlife Conflict Reporting in Suburban Tampa............................................89 5.1 Introduction.................................................................................................89 5.2 Methods.......................................................................................................92 5.2.1 Introduction...................................................................................... ..92 5.2.2 Study Area.........................................................................................93 5.2.3 Survey of Human Attitudes Towards Wildlife in Suburban Residential Areas...............................................................................94 5.2.4 Survey Analyses.................................................................................98 5.3 Results................................................................................................... ....100 5.3.1 Conf lict Across the Urbanization Gradient and Tolerance..............100 5.3.2 Survey Participant Demographics and Conflict...............................101 5.3.3 Attit ude types and Residential Area Average Expenditures............102 5.3.4 A ttitudes Toward Wildlife and Personal Experiences and Expenditures....................................................................................104

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iii 5.4 Discussion.................................................................................................107 5.4.1 Introduction...................................................................................... 107 5.4.2 Personal Attitudes and Decisions Concerning Pests....................108 Chapter 6: A Model of Human Wildlife Conflict Including Landscape, Ecological, and Social Factors......................................................................................................112 6.1 Introduction...............................................................................................112 6.2 Methods.....................................................................................................113 6.2.1 Introduction...................................................................................... 113 6.2.2 Study Area.......................................................................................113 6.2.3 Pulling Together the Major Contribu tors to Human-Wildlife Conflict Reporting...........................................................................114 6.2.4 Cross Validation of the Model for Prediction..................................117 6.3 Results................................................................................................... ....118 6.3.1 The Model of Human-Wildlife C onflict at the Residential Level................................................................................................118 6.3.2 Results of Cross Validation of the First Order Linear Model.........121 6.4 Discussion.................................................................................................121 6.4.1 Explanatory Variables of the Model................................................121 6.4.2 Limitations of the Model.................................................................123 6.4.3 Using the Model to Reduce Conflict...............................................124 Chapter 7: Reducing Human-Wildlife Conflict in Urban Areas.....................................128 7.1 Research Conclusions with Broader Implications....................................128 7.2 Looking to the Past to Predict the Future..................................................131 7.3 Agenda 21 and Localized Efforts for Sustainability.................................133 Literature Cited............................................................................................................... .135 Appendices.......................................................................................................................146 Appendix A: Resident Survey........................................................................146 Appendix B: Res earch Packet Letter Mail ed to Licensed Wildlife Trapper Volunteers...................................................................150 About the Author...................................................................................................End Page

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iv List of Tables Table 3.1: Inclusive list of vertebrate animal species appearing on conflict reports in the st udy area excluding wild boar and alligators.........................................51 Table 3.2: Descriptive sta tistics for one-way ANOVA for differences in conflict density at three development levels (alpha = 0.05)...........................................52 Table 3.3: The average of landscape variables measurements for each residential area development level. The average for the dependent variable for e ach development level is given in the last row...........................53 Table 3.4: Correlations between all landscape variables and conflict density..................54 Table 3.5: Descriptive sta tistics for the standard linear regression model........................55 Table 4.1: Proportion of all c onflict reports attributed to the top five offending species....................................................................................................... ........70 Table 4.2: A brief summary of behavioral char acteristics that may contribute to success in urban environments..........................................................................82 Table 4.3: Relative abundance index means for raccoons, Opossums, and Armadillos in each of the three suburban residential areas and the corresponding si gnificance values for between groups differences. denotes significant differences at alpha <0.05...............................................84 Table 5.1: Homeowner survey questions re garding personal information, expenditures, and attitudes................................................................................97 Table 5.2: Definitions of basic attitude t ypes as categorized in the survey of suburban residents. (Original terms and descriptio ns of types taken from Kellert and Clark, 1991.)..................................................................................98 Table 5.3: The demographic averages of re sidents who completed the survey in each residential area........................................................................................1 02

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v Table 5.4: A summary of responses con cerning the enjoyment of nature and wildlife in residents residential area. Variable s were coded on a 5 point scale of strongly agree (1), neutral (3), and strong ly disagree (5). In this table strongly agree and agree were collapsed and reported as agree, strongly disagree a nd disagree were collapsed and reported as disagree.......103 Table 5.5: Expenditures related to wildlif e in three suburban residential areas..............103 Table 5.6: Percentage of residents surveyed in each residential area that matched attitude type definitions...................................................................................10 4 Table 5.7: Results of t tests for averages of attitude types among residents who perceived conflict and those who did not.......................................................106 Table 6.1: Descriptive statis tics for the linear regression model of human-wildlife conflict across the urbanization gradient.......................................................119

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vi List of Figures Figure 1.1: A conceptual framework for the study of human-wildlife conflict...................4 Figure 2.1: Research area in yellow, H illsborough County and southern Pasco County..............................................................................................................13 Figure 2.2: A hypothetical model of human-wildlife conflict in urbanizing areas............35 Figure 3.1: Locations of residential areas within the study area of Hillsborough County and Pasco County, Florida are represen ted by gray circles. Tampa is marked with a white circle. County boundary data source: LABINS. ..................................................................................................... ....40 Figure 3.2: Digital orthophotos illustrating thre e development levels across the urban gradient of Tampa, Florida. Map data source LABINS. .....................42 Figure 3.3: A sub-sample of residential areas illustrati ng landscape variables and residential area bounda ries. Red = interior habitat remnant patch, blue = water bodies, green = re sidential area border, ora nge = adjacent exterior habitat patch, and beige = golf links. ..............................................................49 Figure 3.4: Study area with black dots re presenting all human-wildlife conflict points...............................................................................................................51 Figure 3.5: Normal probability pl ot of regression residuals..............................................55 Figure 4.1: The Tampa Florida metropolitan area with yellow push pins showing the locations of three suburban residential areas where I surveyed relative abun dance. The black dots repr esent human-wildlife conflict points involving medium sized mammalian species in the study area. (map source: Google Earth)............................................................................67 Figure 4.2: Photographs of t ypical remnant patch habitats in suburban and exurban residential ar eas within the study area of Hillsborough and Pasco county, Florida. Dominant species are longleaf pine ( Pinus palustris) loblolly pine (Pinus taeda) cypress ( Taxodium sp.), and saw palmetto ( Serenoa repens) ............................................................................................68 Figure 4.3: A track detecti on station freshly reset.............................................................72

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vii Figure 4.4: Raccoon tracks (center) and opo ssum (top right) in a track detection station in suburban Tampa...............................................................................72 Figure 4.5: The number of conflict reports from each of the three development levels for the majo rity of wild species in the reports. Bats, frogs and snakes were of unspecified species ................................................................75 Figure 4.6: The nine-banded armadillo (Dasypus novemcinctus). Photo source: Tom Fiedel, 2008, with permission of free use..............................................76 Figure 4.7: Opossum (Didelphus virginiana) Photo source: Cody Pope, 2007 with Permission of free use.....................................................................................7 8 Figure 4.8: A juvenile raccoon ( Procyon lotor) Photo source: Dmetryo S. Public Domain, permission of free use......................................................................80 Figure 4.9: The eastern gray squirrel ( Sciurus carolinensis) Photo source: Anonymous, under permission of free use ...................................................81 Figure 5.1: The study areas in the Tampa, Florida region. Red diamonds represent the residential areas included in the homeowner surveys. Black dots are individual co nflict events from randomly selected zip codes throughout the study area. The yellow circle is downtown Tampa................95 Figure 6.1: Map of the study areas in th e Tampa, Florida region. Gray dots represent the resi dential areas included in data collection for the regression model. Downtown Tampa is marked with a white circle.............115 Figure 6.2: Normal probability plot of the standardized residuals of the linear model.............................................................................................................120

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viii Human-Wildlife Conflict Across Urbanization Gr adients: Spatial, Social, and Ecological Factors Amanda H. Gilleland ABSTRACT As suburban and exurban residential deve lopments continue to multiply in urban areas, they encroach on wildlife habitats leadi ng to increased human-wildlife interactions. The animals involved in direct conflict with homeowners are often relocated or exterminated by the homeowners. Often the homeowners contact state licensed wildlife trappers to eliminate the problem animal. In this study I examined how landscape, ecological, and social factors influence the inci dence of human-wildlife conflict of thirty two residential areas in the Tampa, Florid a metropolitan area. These residential areas, totaling over 300 km2, are part of the urban developmen t gradient representing a range of urban land use from the urban core to exurban residential areas. This study consisted of four phases. In the first three phases, I i nvestigated which landscape, ecological, and social factors contribute to homeowner conflict with wild animals on their property. In the last phase, I combine the significant f actors contributing to human-wildlife conflict from the first three phases to build a more complete model. A spatial analysis of the locations of human-wildlife conflict events recorded by licensed wildlife trappers showed the most significant development and landscape factors affecting human-wildlife conflic t reporting in a residentia l area were human population density and total area of natural habitat imme diately adjacent to the residential area. A

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ix survey of the relative abundan ce of conflict prone animals living near and in remnant patches of habitat in suburban residential ar eas revealed that great er abundance was not correlated with the reported conflict of that species within that residential area. Species that were social, omnivorous, and had some fl exibility in home range size were involved most often in conflict in hi ghly urbanized environments. Sp ecies that were less social, and were not omnivorous, were not significantly involved in human-wildlife conflict in highly urbanized residential areas. These species tended to be restricted to intermediately urbanized areas like suburban and exurban residential areas. Several social factors were also signif icant contributors to human-wildlife conflict as revealed through personal interviews w ith suburban homeowners in Hillsborough and Pasco counties. Interviews confirmed that most people have positive attitudes toward wildlife, but some form of conflict was reported by thirty four percent of suburban residents, although only seventeen percent of those perceived it as a problem worth spending money to solve. Analysis of the attitudes of residents who reported having experienced problems associated with wild life on their property, revealed significant negative correlations with statements of environmental concern and concern for the treatment of animals. Using all the significant variables fr om the physical landscape, ecological evaluation, and the human attitude study in the suburbs, I developed a statistical model of human-wildlife conflict across the urbanizati on gradient. While the model has marginal success in terms of practical ap plication for prediction, it is quite valuable for defining the importance of these variables in relation to conflict with cert ain types of species across the gradient. This set of papers collectively defines re lationships between variables

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x existing in urban, suburban, and exurban residential areas and huma n-wildlife conflict. These factors should be considered when planning new residential areas to minimize human-wildlife conflict while maximizing the residents enjoyment of natural areas and species within the residential area.

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Chapter 1 The Mailbo x Serpent 1.1 Introduction: The Paradox of a Suburban Conservation Area Many evenings at dusk I will see one or two bats flitting about my suburban residential area. They are so quick and agile that trying to keep them in sight becomes a challenge. Often in the middle of the night I am awakened by owls calling in the darkness. In the early hours of the morning as I walk my golden retriever I hear bird songs emanating from the nearby oaks, and I once witnessed a brief assault by a hawk on a nesting pair of mocking birds. Wildlife is present in the suburbs; one only needs to remain alert and observant to notice the vari ety of species coexisting with us. However only certain, highly adaptable, species remain in close proximity to human settlements like mine. Within two kilometers of my residence there are over forty small undeveloped habitat fragments, some of those are wetla nd conservation sites, and one a 7,300 hectare Wilderness Preserve, but there are also numerous other residential areas, four relatively large shopping centers, several churches, two schools, and a hospital construction site. This is a snapshot of suburban Florida. In October 2008 a headline in the St. Petersburg Times read Suburban serpent strikes back, certainly a line to get ones attention (Nguyen, 2008). The article described how a mail carrier was bitten by an eastern diamondback ratt lesnake that was inside a mailbox in a New Tampa community. The mail carrier spent a couple of days in the 1

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hospital (Nguyen, 2008) before being released. T h e article reports two other residents that were bitten by rattlesnakes recently in the same suburban area. The New Tampa community in question coexists with a plet hora of wildlife habitat fragments labeled conservation areas by real esta te agents, and is in close proximity to the 1369 hectare Hillsborough River State Park, the 6475 h ectare Lower Hillsborough Flood Detention area, and several large shopping centers, churches, schools and gol f courses. This is also a snapshot of suburban Florida. Conservation areas abound in and around suburban and exurban residential areas in the Tampa, Florida region and are in fact hot selling points in the real estate industry. Sometimes the so-called conservation areas are wetland mitigation sites. Others are protected properties purchased by th e public through the Environmental Lands Acquisition and Protection Program (ELAPP). While many re sidents are attracted to undisturbed wooded areas like these and enjoy th e closeness and opportun ities to interact with nature, other residents find that as time passes, the living arrangement with wild species may be too close for comfort. Along with the opportunity for interaction comes increased chance of human-wildlife c onflict within human communities. Conflict caused by certain animals, like insects and mice, are relatively easy to solve with poisons and mouse traps that a resident can pick up at the local market. Conflict with larger, less common animals ma y not be so simple. These conflicts have created a certain demand for w ildlife trappers in urbanize d areas around the Country. The number of licensed wildlife trappers au thorized to operate in Hillsborough County currently stands at one hundred eighty eight. This may be indicative, to some degree, of the level of human-wildlife conflict in this re gion considering that it is approximately one 2

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trapper for every ten square kilom eters. Desp ite the growing number of reported conflicts in urban, suburban, and exurban areas there is little research that considers all of the major components that influence the patterns of these phenomena. My research is based upon theoretic al models taken from landscape ecology, wildlife ecology, and human perceptions of w ildlife. In this study, I examine how the ecological characteristics of cer tain species, and the landscape attributes associated with development, influence the pattern of hu man-wildlife c onflict reporting. In addition, I examine how homeowners value of wildlife and attitudes towards wildlife influence their perceptions of human wildlife interactio ns. The goal of my research is to develop a more inclusive statistical model of human-wildlife conflict applicable to urbanizing regions using a new three a pproach conceptual framework, shown in Figure 1.1., which incorporates landscape patterns, the ecology of conflict-prone species and human values. This three approach framework should provi de a more complete set of explanatory variables affecting human-wildlife conflict in urbanized areas. There are several objectives to this work: 1) to identify landscape patterns of development in and around human residential areas that influence the level of humanwildlife conflict; 2) to determine which species are conflict-prone in relation to different levels of urbanization and to evaluate ecologi cal characteristics and relative abundance of non-rat mammalian, conflict-prone species at different levels of urbanization; 3) to investigate human values of w ildlife at different levels of urbanization and to determine the influence those values have on the incide nce of reported conflict; and 4) to develop and test models of human-wildlife conflict in corporating landscape, ecological, and social variables possibly for prediction of human-wildlife conflict. 3

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Landscape Pattern oriented approach Species oriented approach Conflic t p rone s p ecie Human Dimension Social Approach Human-wildlife Conflic t Figure 1.1 : A conceptual framework for the study of human-wildlife conflict. 1.2 Brief Dissertation Overview This dissertation is divided into seven chapters. In Chapter Two, I describe and evaluate each part of the conceptual fram ework shown in Figure 1.1 through a review of the literature relevant to conflict in urbanizing areas a nd through an evaluation of the methodologies applied to the human-wildlife co nflict studies. Methods involved in each of the four phases of this study are described in more detail within relevant chapters. In Chapter Three, I investigate the eff ect of landscape patterns of development and habitat fragmentation on the incidence of human-wildlife conflict in human residential areas across th e urbanization gradient. In Chapter Four, I evaluate the ecological characteristics of species that I term 4

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conflict-prone and determ ine if the type of conflict-prone species varies at different levels of urbanization. I describe the rela tionship between relativ e abundance of conflictprone species in habitat fragments and incide nce of human-wildlife conflict in human residential areas. In Chapter Five, I explore societal values and perceptions of wildlife interactions and the influence those values and percepti ons have on wildlife conflict reporting at differing levels of urbanization. Chapter Six incorporates significant landscap e, ecological, and social variables to develop a statistical models for prediction of human-wildlife conflict at different levels of urbanization. In the concluding chapter, Chapter Seven, I review and synthesize the findings of this dissertation research. I revisit and evalua te the effectiveness of approaching the study of human-wildlife conflict us ing the conceptual framework pr esented at the beginning of this study, and evaluate the hypothetical model formulated at the onset. Finally, I explore the contributions and limitati ons of this research and de fine opportunities for future investigation. 1.3 The Broader Impact Landscape ecology is a relatively new branch of ecology and was born as a human-related science (Nevah and Lieberma n, 1994; Farina, 2006) with roots in physical geographic and ecological science. Accord ing to Farina (2006), there has been tremendous progress in empirical work in th e field of landscape ecology but theoretical development still shows permanent fragility. 5

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In this study I investigated human-wildli fe conflict across the urban region in order to gain empirical support for my sugge sted conceptual framework that a three dimensional approach is needed to fully understand certain environmental phenomena (Figure 1.1). Many environmental issues cu rrently under investigation would benefit from applying this three dimensional approa ch incorporating the physical landscape, the non-human species ecological perspective, and the human dimension. I also determined if theoretical concepts like me tapopulation theory and source sink dynamics apply to the perpetuation of human-wildlife conflict in the seemingly isol ated islands of habitat that are surrounded by the urban matrix. Seldom are the incidents of human-wildli fe conflict as dramatic as the mailbox viper story. Most are stories of armadillos digging up flower beds and raccoons breaking into garbage bins. Some are odd stories of frogs turning up in toilet bowls and black racer snakes in the fireplace. E ach time one of the rogue animals is caught by a trapper the animal must be disposed of in what is considered a humane fashion. It is currently unlawful for a trapper to relocate the animal s they catch. Trappers have told me in interviews that there have been misunders tandings by many residents concerning this point. The residents assume that since the prof essional at their door is a wildlife trapper the animal will be trapped and then releas ed somewhere else. Some residents become very upset that they still ha ve to pay for a service that is not what they originally intended. By approaching the problem of huma n-wildlife conflict from all three perspectives a clearer picture emerges. Perhaps the impact of some of these factors can be reduced, relieving residents of the aggravat ion and expense of dealing with problem 6

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wildlife and hopefully improving attitud es to wards wildlife in general. Better understanding should also save time and resources of wildlife management personnel when managed populations are involved. 7

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Chapter 2 Conceptual Framew ork and Methodology 2.1 Introduction In ecological research, environmental impacts on an organism, or a population, should be evaluated from multiple perspect ives. Considering the case of the mailbox viper mentioned in Chapter One, the nonhuman species involved in the incident inhabited the area long before humans tran sformed the landscape into a suburban neighborhood. Prior to development, the e nvironment was upland forest, seasonally ponded wetlands, and permanent wetlands, but it is now a landscape mosaic composed of residences with manicured lawns, swimming pools and suburban streets mixed in with tattered remnants of the forest that once was. This type of land transformation creates a multitude of ecosystem boundaries that is a catas trophe for species that are edge sensitive but a bonanza for species that thrive in th e ecotone. Changing environments leading to threatening processes for a sp ecies population, exogenous pro cesses, include habitat loss or degradation, landscape modification, limited resources, and numerous other variables. The newspaper article about the snake focuses on the humans involved and thus evaluates the incident at that scale. If the incident is evaluated on the neighborhood scale by including the human victim as just one of many species involve d in the ecological community, the picture looks quite different Since humans have an ecological niche much greater than the mailbox viper, this scale is inappropriate from the vipers 8

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perspective. In fact, upon clos e inspection one realizes that the incident really would be most appropriately studied at the scale of the vipers hom e range. We would need to evaluate habitat loss and fragmentation that affect the vipers home range and how the viper population adapted to the changes in the landscape caused by human settlement. We would also have to examine remaining reso urces available in the fragmented habitats that are left and whether or not the new land use, in this case the human neighborhood, provides supplemental resources to the remaini ng wild species. Thus, an evaluation of the exogenous processes like landscape changes, ha bitat loss and fragmentation, and resource availability, may give better clue s to the causes of this partic ular incident. Of course, we must not forget the victim, the mailman. The mailman in this case was in fact an unsuspecting visitor in the home range of the viper. While a headline that reads Uni nvited mailman gets bitten by surprised exwoodland host is a more accurate announcement of the event, it is not as sensational or appealing to readers as the original headline, which seems to give anthropocentric feelings of revenge to a suburban serpent. From an academic standpoint there are a myri ad of variables playing a part in this event. However, I believe they all fit into the three broad approaches to the study of conflict as proposed in Figure 1.1: i) the study of anthropogenic fragmentation of the rattlesnakes habitat which fits within the pattern-oriented approach, ii) the study of the interactions with human speci es which fits into a category of the human dimension, and iii) the ecological evaluation of the relative abundance of th e rattlesnakes population and availability of the remaining resources for wh ich individual rattlesnakes compete. In the next three sections, I discuss each of these approaches in greater detail, including brief 9

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background, and a literature review of the th eories and m ethodologies applied and used in past research in each of the three areas. I di scuss how each of these approaches applies to the study of human-wildlife conflict and explain how all three of these approaches should be utilized to gain a clearer understandi ng of where and under what conditions humanwildlife conflict is most prevalent. 2.2 The Pattern-Oriented Approach to th e Study of Human-Wildlife Conflict The first approach to the study of human-w ildlife conflict is the pattern oriented approach. Pattern oriented approaches focus on physical geography and landscape patterns, as defined by the researcher, and their correlation with measures of species occurrence and measures such as overall biodiversity (Fis cher and Lindenmayer, 2007). This approach originates from the theo ry of island biogeography and includes many ecological models including the patch-matrix model, the metapopulation model, and an application of percolat ion theory. An advantage of using a pattern oriented approach is that of scale, in that large scale patterns can be effectively corr elated with groups of species to infer causality (Farina, 2006; Fischer and Lindenmayer, 2007). 2.2.1 Land Use and Urbanization A growing human population, now at 6.8 bi llion (US Census Bureau, 2010), is taking a tremendous toll on many aspects of the environment, especially the transformation of natural habitats for huma n exploitation. In the United States, even though the population is increasi ng relatively slowly, the pro portion of citizens living in areas classified as urban has grown rapidly. According to the U.S. Census Bureau (2000), 10

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the term urban refers to areas with a human population density greater than 620 individuals per km2. This is the definition used in most fields, including ecology (McDonnell and Pickett, 1990). In 1989 74 perc ent of the population of the United States resided in urban areas. Now that figure is up to eighty percent (McDonnell et al., 1997; Dreier et al., 2004). If the additional population growth in urban areas were added to residential areas inside already established urban boundaries, th is might be sustainable for surrounding habitats and much better for the eco nomics of the urban area. However, the growth that is seen in most highly urbanized cities in the last twenty years follows the trend of the city incorporating more and more of the surroundi ng land not just for residents but for businesses and other uses. Th e population of the Un ited States, currently at 308 million (US Census Bureau, 2010), is projected to reach 400 million by 2050 (U.S. Census Bureau, 2010). This will add 100 m illion people, most likely in urban and suburban areas if the current developm ent trend continues as it is today. Many refer to this relatively unplanned, ongoing urban and suburban expansion as urban sprawl. Urban sprawl is loosely defi ned by Wright (2005) as a far-flung urbansuburban network of low density residential areas, shopping malls, industrial parks, and other facilities loosely laced together by multi-lane highw ays. Nivola (1999) uses the phrase hyper-extended American metropolis to describe the sprawling landscape. Urban sprawl has in fact become a major pr oblem in most large American metropolitan areas (Dreier et al., 2004). In the Unite d States from 1960 to 1980, 22 million acres of forest and agricultural lands were converted to urban land use (McDonnell et al., 1997). One of the many negative repercussion of urban sprawl is the impact it has on natural environments. Where there are housing developments, strip malls, cars and roads 11

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there is pollution and the fragm entation of na tural habitats. According to many scientists, the rapid growth of the population out from the cities in suburban, and exurban areas is largely responsible for wildlif e habitat loss and fragmentatio n (Lassila, 1999; Beatley, 2000). Fragmentation may be defined as the di vision of landscape into patches of habitat by roads and road construction, agricultural la nds, or residential areas (Wright, 2005). As housing developments, strip malls, business park s and the roads that lead to them are developed they cut natural areas into smaller and smaller fragments. Smaller and smaller fragments mean less habitat and resources for native species, and plac e the biodiversity of the local area in jeopardy. In fact, Timot hy Beatley (2000) argued that while there are multiple threats to biodiversity in the Unite d States, one of the most significant is destruction of habitat and much of it is the direct result of urbanization. Many agree that this habitat loss is the result of wasteful patt erns of low-density developments that could be avoided with better planning (Beatley, 2000; Dreier et al., 2004; Berube et al., 2006). In 1995, Noss et al. documented endangered ecosystems across the United States and found that the greatest losses were in places where population and land use pressures were the highest, most notably the South and West. This corresponds to the American metropolitan regions that have shown the mo st urban growth (Berube, 2006; Dreier, et al., 2004). Sprawling development has been a problem in parts of Hillsborough and Pasco Counties, Florida, the study area for this pr oject, see Figure 2.1. The Tampa metropolitan area has seen one of the highest growth rates in the country. In fact, according to the U.S. Census bureau (Sprawl City website, 2007) Tampa was ranked the seventh most sprawling city out of the 100 la rgest cities in the U.S. ba sed upon their sprawl index of 12

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m ileage of sprawl to population gain ratio. In total square miles of sprawl, Tampa was listed eighth in the top 100 with 358.7 total square miles ( 929 total square kilometers). The Tampa area is significant because the na tional average for that same time frame was 145.5 square miles (376.84 square kilometers ) (Sprawl City website, 2007). While the resident population grew signi ficantly, the total sprawl was close to eleven times higher than the percent sprawl that should be at tributed to the corresponding population gain. 01 02 0 5 KilometersStudy area boundary including part of Hillsborough & Pasco Counties, Florida Hillsborough County Pasco County Pinellas CountyAmanda H Gilleland 2010 Data Source: Land Boundary Information System Figure 2.1: Research area in yellow, Hillsborough County and southern Pasco County, Florida. 2.2.2 Theoretical Underpinnings Concerning Fragmentation As time has progressed and land development excelerated, scientists were compelled to turn from the traditional st udy of undisturbed land to study the effects of 13

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fragm entation on ecosystems. Until the 1960s the primary foci of ecological and wildlife research were on large tracts of undisturbed la nd. There were many reasons for this trend; early ecologists followed the teachings of George Perkins Marsh (1864) and Aldo Leopold (1941) who held people as separate fr om nature and viewed natural systems as balanced only if they were undisturbed by humans. Another reason is that most endangered animals and plants are typically found in undisturbed areas because they do not fair well coexisting with people (Noss, 1991). Much of the theoretical ba sis of fragmentation studies comes from the seminal work, the Theory of Island Biogeography (MacArthur and Wilson, 1967). Island biogeography has two basic principles. First, the closer an island is to the mainland, the higher the probability that species from the mainland will migrate to the island and provide a source for populating or repopulat ing the island. Second, the probability of species extinction on an island is a function of island size. In e ssence island biogeography states that large patches with high connectivity and proximity to a larger, source habitat foster a healthy ecosystem in structure and f unction. This model has since been viewed as analogous to mainland fragmented forest environments that ar e basically islands in a sea of developed land. Using the th eory of island biogeography as a new framework, smaller forested remnant patches have become a majo r focus for research and many theories have been born. Human caused fragmentation usually conjur es up images of vegetation remnants surrounded by inhabitable environments. However, the fragments as islands analogy is flawed in several ways (Harris, 1984; Connor and McCoy, 1979; Forman and Godron, 1981; Simberloff and Abele, 1982). Fi rst, terrestrial habitat isla nds are different from true 14

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islands in that the surrounding boundary m ay l ack sharpness, and gradual gradients in the landscape may be conducive to movements of some species between the patch and the surrounding matrix (Foreman and Godron, 1981). The surrounding matrix is often inhabited by opportunistic species and thus th e habitat island and its resident populations are not isolated in the same se nse as with true islands. Many studies provide evidence that this makes the habitat fragment vulnerabl e to invasion by exotic and opportunistic generalist species. The overall bi odiversity of the fragment, especially in the ecotone (the transition area between two ecosystems), may be increased, at least temporarily, with a multitude of invasive species. The invasive species often displace the native species. In fact, native biodiversity has been shown in many studies to decline with increasing development and fragmentation (Miller & Hobbs, 2002; Faeth, 2005; McKinney, 2006). This phenomenon may be a contri buting factor to the problem of human-wildlife conflict in urbanizing areas because non-native sp ecies and invasives tend to be highly opportunistic, which may make them prone to conflict on private property. Second, island biogeography theory ignores dynamic linkages and interactions between the forested system and the non-fo rested matrix (Harris, 1984; Koelle and Vandermeer, 2005). One interaction that is comp letely different is that true islands benefit from immigration of species from the nearby continent or neighboring islands, a source effect, whereas remnant habitat frag ments often suffer loss of species to the surrounding matrix, a sink effect, especially in urban and suburban environments. Therefore the fragment becomes the source and the developed matrix becomes the sink. This may be especially true for conflict-p rone species in suburban and exurban Tampa where I have estimated that hundreds of individuals are trapped each year. 15

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Several con ceptual frameworks for in corporating the heterogeneity of the landscape and its effect on eco logical process were devel oped based larg ely on island biogeography theory. One of these was th e metapopulation model developed by Richard Levins in 1970. The metapopulation model focuses on a set of subpopulations across landscapes that are in reproductive contact wi th each other through dispersal. Thus if one subpopulation goes extinct, it may eventually be recolonized by a nearby subpopulation, provided there is continued opportunity for movement between both areas. This model brings to light the importance of connectivity of habitats. If a metapopulation is to persist in nature, the subpopulations must be connect ed (i.e. movement through the matrix from one to another must be possibl e and not too energetically expe nsive). If movement is too costly from an energetic standpoint, as when th e terrain is too difficu lt to navigate and/or resources are absent along the way, then the populations become re productively isolated from each other and the metapopulation dynami c ceases to exist. Should catastrophe befall the isolated populations, then extinction is imminent. This theory is of great importance wh en evaluating the dynamics of animal movements among fragmented habitats in suburban and exurban landscapes. If the fragments are resource rich and the individuals of the populati ons are free to traverse the developed suburban or exurban matrix then the metapopulation dynamic could remain in quasi-equilibrium indefinitely. Another theory of importance in studying fragmented habitats is percolation theory. Percolation theory was developed or iginally from the study of liquids flowing through material aggregates (Stauffer, 1985). For example, water flowing down a hill will flow freely and evenly if the hill has a perfectly smooth surface. If the hill is not smooth 16

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there will be places where water will flow quickly or more sl owly, and possibly collect or puddle. This theory has applica tions in many areas such as soil erosion where nutrients flow over an eroded hillside and may collect in certain areas, which will then support growth of a vegetation patch, which will, in tu rn, catch and collect more nutrients as they flow down the hill. This theory has also been applied to the study of landscape models in terms of understanding the connectivity of heterogeneous systems (With, 1997; ONeill, 2005; Farina, 2006). One hypothesis resulting from computer simulations of percolation theory applied to random computer simulated landscapes is that if the landscape is represented as a square grid with units of habitat patches randomly scattered among cells of the grid, the entire landscape becomes continuous once the habitat patches (cells) exceed 0.5928, the percolation threshold (Gardner et al., 1987; Farina, 2006). This means that once the landscape grid has 59.28 percent of its total area covere d by habitat patches, the habitat patches are then relatively conn ected from one side of the landscape to another. Percolation theory could provide a cr itical threshold for human wildlife interactions if the total area of suitable ha bitat for certain species within and directly surrounding residential areas exceeds 59 percent of the total land area of the residential areas in question. If the hab itats prove suitable for thos e species determined to be conflict-prone then the chance for human wildlife conflict will likely increase as interactions increase on private property. These two cornerstone theories, metapopul ation and percolat ion, provide strong theoretical underpinnings for the study of the movement patterns of wildlife through heterogeneous suburban and e xurban residential areas. For example, many residential 17

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areas in the study area for this dissertation are sim ilar to the area of New Tampa where the mailbox viper incident took place. These residential areas have a multitude of small fragmented source habitats th at are in relatively close pr oximity to each other and to larger natural conservation ha bitats, thus a metapopulation dynamic could exist between many of the fragments, possibly including the large conservation area as a source. I also assert that percolation theory can be app lied to fragment areas inside the boundaries of residential areas to predict whether or not adap table species will be able to freely traverse the developed matrix. 2.2.3 Methodology Associated with the Pattern-Oriented Approach 2.2.3.1 The Gradient Paradigm to Landscape Study The spatially changing effects of urbani zation on human-wild life conflict can be effectively studied using the gradient paradigm concept. The gradient paradigm essentially treats environmental variation as having spatial order and environmental patterns related to the stru cture and function of ecologi cal systems at all scales (McDonnell and Pickett, 1990). This me thodology was first proposed by Whittaker (1967) as applied to the study of plant comm unities, and has often been used as an approach to ecological study (Blair, 1996; LeLay et al, 2001; Crooks, 2002; Atwood et al, 2004; Angold et al, 2006). It is particularly well suited to the analyses of urbanization effects because urban areas typically have a highly developed urban center surrounded by concentric rings of decreasing developm ent. Examining human-wildlife interactions and conflict in terms of spatial developmen t and settlement would be ideal if newly created fragments could be monitored for conflict from the moment the neighboring 18

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developm ent is settled. Landscape, ecological a nd social characteristics could be recorded over time. Studying conflict using the gradient c oncept will allow an analysis of multiple patches adjacent to and within different le vels of human development, human density, and other variables along the urban to rural gr adient. Theoretically, patches existing in an urban area with high human density will show different levels of ecological stress and human-wildlife conflict than patches in areas of low human density like rural settlements, all other variables (size, area to edge ratio, prior land use, etc) held constant. This difference should give a relative index of the effect development level has on humanwildlife conflict. 2.2.3.2 Literature Review of Methodologies Used in Past Research Using the urban gradient as a backdrop for comparing increased fragmentation and its effect on wildlife conflict would be extraordinarily time consuming if not for recent technological developments. Fragment ation in urbanizing areas is more easily observed and analyzed due to technologica l advances like geographic information systems (GIS) and remote sensing. GIS co mbines mapping, analytical, and storage capacities that allow researcher s to link empirical data with mapping locations for ease of analysis. The progression of urban expansi on and wildlife habitat fragmentation can be carefully georeferenced, documented, and analyzed. GIS has become a very important tool in ecological studies, es pecially those involving change s in land cover, and surveys of biodiversity and abundance (Zipperer et al., 1997; LeLay et al ., 2001; Atwood et al., 2004). Using this technology, research in the sp atial analysis of la ndscape variables in relation to wildlife ecology has beco me more efficient and manageable. 19

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In an attem pt to predict human-carnivore conflict caused by wolf depredation of livestock in Wisconsin and Minnesota Treves et al. (2004), used historical data of depredation sites, and recent estimates of wolf density and range obtained from each states Departments of Natural Resources. Depredation sites were georeferenced in GIS and multiple landscape variables were recorded for each location. The landscape variables recorded included size of farm a nd livestock density, land cover classification, human population density per square kilometer, prey density in area, and road density. A subsample of the landscape variables were ground truthed and reco rded by researchers visiting a subset of affected farms. The rese archers used a matched-pair design to analyze the data, comparing conflict sites with neighbo ring sites with simila r characteristics that were not affected by wolf depredation. The methods used in this human-wolf conflict study presen t an interesting analysis of spatial data using a matched pair design instead of the traditional logistic regression, as in the Le Lay et al. (2001) study. The researchers argue that comparing regions with a long history of wolf resi dence with regions where wolves arrived relatively recently would not control for experience of wolves, exposure to wolves, and differences in wolf control. The matched pairs design using nei ghboring areas allowed the researchers control of t hose variations. This could al so be a problem with urban adapter species in remnant patches near older residential developments if the individuals have become habituated to the presence of people over time. The gradient paradigm should help to control this effect as deve lopment typically works its way out from the urban center. Obviously reside ntial development does not always follow this trend so verification is important for specific cases. Time of resident exposure to wildlife could 20

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also influence conflict reporting, but this has to be evaluated by a resident survey because people m ove in and out of re sidential areas regularly. The landscape variables measured in th e human-wolf conflict study were clearly important, but many spatial and social vari ables were not addressed. For instance, distance from farm to forested habitats and other farms, and preventative measures taken by farmers (husbandry practices) were not included in the study. Social variables were not included in the linear model of risk, but ma y contribute to the problem if citizens in certain areas have different attitudes towards wolves or towards the governmental agency presiding over depredation cases. Using raster GIS, Sitati, et al. (2003), assigned humanelephant conflict incidents to cells of a map of the TransMara region in Southwest Africa. The researchers used correlation analysis and logistic regression to analyze spatia l patterns involved in humanelephant conflict. They found that this me thod was effective in identifying spatial predictors of potential conflict with simple landscape data and human density estimates. Sitati, et al. (2003) asserted that although their logistic model relied primarily on landscape data like land cover, distance to ro ads, and distance to villages, it was robust enough to use for prediction of conflict in other areas across the continent. The TransMara study did not include ecolo gical variables in the model and the only social aspect involved the locations of village markets and human density of the village. This simplified their model quite a bit, and in the case of human-elephant conflict was probably justified. However, in a study of human-wildlife conflict in urbanizing areas, ecological characteris tics, like behavior patterns involved in foraging and reproduction patterns of the focal species, must be considered in relation to the limited 21

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resourc es of the remaining natural habitat. That is why this study will incorporate more than landscape variables alone. 2.3 The Species-Oriented Approach The second approach to this study of human-wildlife conflic t is the species oriented approach. Speciesoriented approach es are often centered on individual species, which are believed to respond uniquely to their environmen t (Fischer and Lindenmayer, 2007). The major advantage of this approach is that it gives detailed insights into the way the individuals of a population respond biologically to changes in their environment. This approach is important in a human-species conflict study as it helps enlighten the important ecological factors cont ributing to the conflict. Most studies using this approach tend to focus on just one or two species at a ti me, as it is difficult, if not impossible, to evaluate all species in an ecosystem. Th is study will focus on a few species that frequently are the subjects of conflict reports in the study area. 2.3.1 Urban Ecology Landscape ecologists, conservation biologi sts and scientists from a variety of disciplines have taken a recent interest in urban ecosystems in an integrated way and these studies are important for several reason s. First, humans dominate most ecosystems in one way or another, either directly or indirectly (Vitousek 1997). Second, including human activities and disturbances into eco logical models of di ffering systems makes models of environmental problems like habita t conservation more realistic. Third, there are many unknown aspects concerning how humans and their built environments affect 22

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the plants and anim als that co exist in that environment ove r the long term (Parlang, 1998; Foster et al., 2002). Long term studies of pl ant and animal species living in urban areas are important to the understand ing of how these species adap t to the changing landscape. As the urban landscape spreads out farther from the urban core, natural areas become fragmented. Within many of these urban, suburban, and exurban fragments wild species are present, but until relatively recently have gone mostly undocumented. Documentation of flora and fa una in urbanizing and urbanize d areas was scarce until the nineties when the new field of urban ecology really began to grow. In the last several years great strides have been made in th e empirical study of urban wildlife ecology including surveys of biodiver sity, community interactions, and human conflict with avian and mammalian species (McDonnell and Pickett, 1990; Zipperer et al., 1997; Angold et al., 2006; Baker and Harris, 2007). The urban biodiversity surveys that have been published recently show a surpri singly long list of native a nd non-native species (Kloor, 1999; Crooks, 2002;). Some species adapt very well to traversing, or even living in the human built matrix. Blair (1997) termed these species urban exploiters, and described them as being adept at exploiting changes caused by urbani zation. Kark et al. ( 2006) published a study that characterized the avian urban exploiter as social, sedentary (the majority being non-migratory), and with a diet that was pre-adapted to a human environment. These characteristics seem typical of many urban species populations in cities around the world and may be the result of biotic homogeniz ation. Biotic homogenization is a phenomenon that refers to the occurrence of a sma ll number of species with those exploiter characteristics dominating a large number of highly human-dominated environments 23

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around the world (McK inney and Lockwood, 1999; McKinney, 2002). One example is the adaptation of pigeons ( Colomba livia ) to urbanized environments because of enhanced feeding and breeding opportunities. In regard to feeding, 100 percent of highly urbanized bi rd species studied in Jerusalem were granivores (included grain and seeds in their diet) and fifty percent of those species were also omnivorous (consuming plant and animal material, including human refuse). These species are capable of exploi ting food resources from orna mental landscaping valued by urban society. In a suburban and exurban setti ng where residents sometimes invest quite a bit of money in ornamental vegetation, this may be a foraging behavior that could contribute to conflict. Some species may be categorized as subur ban adapters (Blair, 1996; Kark et al., 2006). They are described as either native or non-native species persisting in areas with intermediate urbanization and have the abil ity to exploit a portion of the ornamental vegetation that can be found at moderate leve ls of urbanization. Adapters tend to be less social and feed more often on invertebrate s (Kark et al., 2006). In Jerusalem only 40 percent of the bird species classified as adap ters included seeds in their diets and none of the bird species were omnivorous (Kark et al., 2006). The general trend is that omnivorous bird species are more abundant in urbanized areas (an exception being Singapore; Lim and Sodhi 2004) while insectivores and ot her invertebrate feeders are dominant in more sub-natural areas (Blair, 1996; Clergeau et al ., 1998; Lim and Sodhi, 2004; Kark et al., 2006). The need for invert ebrate food resources tended to keep the adapters out of highly urbanized settings. In this study I anticipated finding that these characteristics also applied to urban and suburban and exurban species in the Tampa 24

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m etropolitan region. I expected the conflict repor ts in urban areas would show that the conflict-prone species were exploiter omni vores and that conflict-prone species in suburbia and exurbia would likely be the insec tivores and invertebrate feeders because of the high number of natural fragments scatte red throughout the residential areas in those areas. Other species, however can not adapt becau se they persist only in areas that are dominated by native vegetation, usually found in the most natural ha bitats. These species may be extirpated (become locally extinct), sometimes very quickly, as urbanization increases. Blair (1996) termed these species u rban avoiders and noted that these species would be particularly sensitive to human caused changes in the landscape and thus persist only in more undisturbed areas. If the urban avoiders are native species that require native, undisturbed habitats to persist over time, then chronic urban sprawl will be detrimental to these species. While the above studies involving exploite rs, adapters, and av oiders collected data only on avian species, I assert that these terms also apply to mammalian species. According to Baker and Harris (2007), bats hedgehogs, and voles, all insectivores, decreased their use of household gardens as urbanization increased as did moles, though they consume invertebrates most frequentl y. This agrees with the general conclusion from the data of urban bird species that insectivores and invertebrate consumers are dominant in more sub-natural areas rather than more urbanized areas. In the study by Baker and Harris (2007), rabbits, also herbi vores, decreased their use of household gardens as urbanization increased. In the same study foxes and grey squirrels, both generalists and opportunistic omnivores, in creased use of gard ens with increased 25

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urbanization. This helps support the hypothesi s that urban exploite rs are most often om nivores. 2.3.2 Fragment Size and Wildlife Remnant patch and fragmentation st udies documenting the species-area relationship, the importan ce of size and shape of th e fragment, extinction and recolonization within fragments have been de bated in relation to the conservation of species (Forman and Godron, 1981; Simberloff and Abele, 1982). Many conservationists promote the bigger is better idea in regard to reserve size and species persistence. Other scientists argue that smaller habitat fragme nts can have surprising ecological value and should also be protected with the same ent husiasm. In fact, there has been an ongoing debate over the importance of the single large or several small reserve habitats, referred to as SLOSS. Single large habitats clearly have great value as larger mammals require larger home ranges for grazing or hun ting prey, but smaller species do not require as much space for home range. Thus smaller fragment s may support smaller mammals quite well. Crooks (2002) studied the relative sensitivities of carnivores to habitat fragmentation and found that body mass was positively related to home range size. This relationship was proposed by Swihart et al (1988) and in fact we nt so far as to present the general formula for home range size equal to body mass rais ed to 1.4 power. However, studies on many terrestrial mammals show that home range va ries widely depending on sex and age of the animal, and most recently, the level of devel opment in their envir onment. Recent studies have shown significant differences in home range sizes of raccoon populations living in 26

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urban, suburban, and rural environments with m aximum ranges of 52.8, 37.2, and 182.4 ha respectively (Prange, et al, 2004). It is interesting that home ranges were smallest in suburban settings. In one of the first st udies of the distribution of urban raccoon populations, Slate (1985) reporte d that suburban residential areas provide supplemental resources for raccoons. The supplemental resour ces either inadvertently or purposefully provided by suburbanites are the most obvious contributor to highe r population density. There are however some medium sized car nivores, spotted skunks, weasels and badgers, that are usually onl y found in the largest tracts of undisturbed land. These mustelids are so specialized in diet and habitat that coexistence with humans seems unlikely. Crooks (2002) showed that at least one relatively large carnivore, the coyote, was uniquely well adapted to persisting in fragme nted habitats with an area less than one km2. Crooks also uses the term fragmentationenhanced predators to refer to domestic cats and opossums because they were found to persist in highest relative abundance in smaller (< 0.4 km2) more isolated fragments that ar e close (0-50m) to the urban edge. Species such as raccoons, striped skunks, opossums, and domestic cats were shown to move through the urban matrix freely. Other studies have also investigated sensitivities of certain focal species to fragmentation (Andren, 1994; McCoy and Mu shinski, 1999; Crooks, 2002; Riley et al., 2003). These studies, and many others like them, focus on a particular wildlife species or species groups, particularly avian, and evaluate the ecologi cal trends in response to habitat fragmentation giving us useful information about populations and their responses to the landscape. Most of these studies did not integrate the human dimension of settlement and attitudes, though th ere have been a few exceptions. 27

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2.4 The Human Dimen sion of Human-wildlife Conflict 2.4.1 Human-Wildlife Conflict As a society we have a tendency to se t ourselves apart from nature. We spend billions of dollars each year trying to separate ourselves and protect ourselves and our belongings from the forces of nature. We settle into environments that are subject to tornados, hurricanes, floods; natural phenomena that are be yond our control. We spend billions researching pathogens, their life hist ory patterns, and methods of transmission in an effort to thwart infection. We have di scovered the effectiveness of antibiotics and watched as pathogens evolved resistance to the antibiotics pr oving the unpredictability of an open, natural system. Whether it is physic al or biological we cannot fully isolate ourselves from the dangers that nature can send our way. We are part of the natural world; a species just like a ny other, living and interacti ng with other species and the abiotic components in our environment. Part of our interactions with ot her species revolves around competition. We compete with wildlife for space or other reso urces like food whenever and wherever our home ranges overlap. As part of the biot a, we need access to resources in our environment to enhance our own survival, and when that access or our level of access is threatened, either directly or indirectly by wildlife, human-wildlife conflict may be a result and our instinctive action may be to retaliate. There are many complex variables involved in where conflict with other animals occurs and under what conditions it is most intense. Probably the most complex of the va riables is that the human reaction to wildlife is very individualistic, and certa inly very difficult to predict. Many studies dealing with livestock ranches and farmlands suffering livestock 28

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depreda tion have evaluated conservation st rategies in relation to farmers attitudes towards wildlife in the United States (D ecker and Brown, 1982; Conover and Decker 1991: Conover, 1994; Conover 1998), however co mparable studies involving wildlife conflict with urbanites and suburbanite s are few and are only recently emerging (Messmer, 1997; Lepczyk et al, 2003; Jonker, et al, 2006). The study of rural ag riculture and wildlife has been important historically because peoples food source and/or income was directly affected and answers were, a nd still are, needed in a timely manner. Therefore studies of the species in conflict with agriculture have been intense throughout recent history and are ongoing. Often farmers are motivated to stop problem animals as soon as possible, even if it involves complete eradication. This often puts farmers at odds with people who want to protec t wildlife species, especially if the species is endangered or threatened. Since U.S. citizens lived mostly in ru ral areas until around the mid twentieth century, (Drier et al, 2004; Adams et al., 2006; ), the frequency of wildlife conflicts with urbanites in the U.S. was not enough to attrac t much attention and th e scientific study of those few conflicts was not viewed as economi cally or politically important. This coupled with the preferential study of undisturbed areas left a ga p in the ecology literature until the late 1980s. 2.4.2 Risk Species According to Launay (1997), risk is define d as an association to an event whose occurrence or consequence on space or popula tions depends on fact ors that cannot be controlled. Le Lay et al. (2001) used Launays definition and proposed that wildlife 29

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expansion in an urban area m ay sometimes represent a risk to humans. Risk assessments of natural hazards comb ine 2 main aspects: the probability of occurrence and the vulnerability to the risk (Tobin and Montz, 1997). These same aspects involved in geophysical events also apply to the risk of human-wildlife conflict. According to Le Lay et al., (2001), probability of occurrence can be equated with wildlife potential which they define as the distributi on and the activities of species in the urban areas. They define vulnerability in the cont ext of human-wildlife conflict as having 4 components: epidemiological (distribution of sensitive people), ecological, sociological (tolerance), and economical. The researchers divided wildlife potentials into three main categories: 1) feeding site di stribution, 2) br eeding site distribution, and 3) special site distribution (roosting, nesting, etc). Wildlife potentials in their study are designed to focus on one species at a time and incorpor ate all ecological information about that species life history pattern th at may be important for mana gement of that particular species. They suggest obtaining this informa tion from local experts like wildlife officials and veterinarians. The vulnerabil ities are related to any aspect of the settlement such as pets, livestock, possessions, buildings, etc. All these variables were then used to estimate a logistic regression model that describes the effect each va riable has on the measure of conflict. Risk can either be real or perceived, and this is particularly true in the case of wildlife species living near human settlement s. According to Tobin and Montz (1997), the perception of risk is the subjectiv e value to which people react and respond and some risks become socially amplified and some become socially attenuated. For instance, when the Florida Fish and Wildlife Conservation Commission proposed 30

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introducing a new Florida pa nther subpopulation in Northe rn Florida to create a m etapopulation dynamic with the south Florid a population, the local people began to panic, even though there have been no a ttacks on humans by Florida panthers ever reported (Florida Wildlife Conservation Commission, 2006). This fear was somewhat fueled by the media. One newscast showed a ma n holding up his little girl to the camera while he dramatically vowed that no panther was going to have the chance to attack his daughter while he was around to stop it (Williams, 2004). Given that panthers are not only very shy but elusive and avoid humans if at all possible (Logan and Sweanor, 2001) this was clearly a case of social amplifica tion of a potential ris k. Citizens of the same state, however, seem completely unconcerned that there are wild alligators living in their back yards, even though there are often repor ts of human injuries caused by alligators throughout the region. The perceptio n of risk of injury by alligators seems to be socially attenuated. Oddly enough alligators in Florida are coexisting relativel y well with people considering the potential for da ngerous conflict. The success is possibly a result of high management by State wildlife officials. For instance, each county is allowed to license only one independent wildlife trapper to be trained and certified by the state to take nuisance alligators from their natural habitat and there are strict rules concerning these interactions. Most other urban wildlife do not benefit from these regulations, in fact in 2008 the Florida Fish and Wildlife Conserva tion Commission (FFWCC) turned over its regulatory authority of wildlife trappers to the Department of Agriculture. Now all the wild species listed in Table 2.1 fall under th e category of pests a nd are governed by the 31

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departm ent of agriculture, unless they are cross-listed as threat ened, endangered, or a species of special concern, or species that fall under some other federal protections (migratory waterfowl, raptors, etc.). Now it se ems the fate of most urban species lies in the hands of the residents, as the policy for reported pests is capture and humane disposal; no relocation. Many suburban and exurban residents value the sightings of w ildlife for aesthetic reasons; however, negative consequences of these interactions can be important for the future of wildlife sustainability. Negative consequences may include but are not limited to human-wildlife conflicts such as wildlif e trespassing onto private property, wildlife causing property damage, wildlife harming pets livestock or humans directly via injury or disease, and wildlife wastes littering hu man built environments. If residents interpret these interactions with wildlife as negative or experience costly pr operty damage, then they may be less tolerant of interactions with wild species in the future, no matter how benign. The negative feelings carried over from a previous experience may also influence their decision making concerning native specie s that are valuable for ecosystem function and the residents may unknowingly jeopardize local balances in their haste to eradicate a pest. These consequences may result in changing attitudes toward native wildlife that would hinder conservation proposals in the future. 2.4.3 Approaches to Understanding Human Values of Wildlife Human-wildlife conflict by definition requires at least two participants the wild species and the human. Wild animals may in advertently damage pr ivate property while foraging but these incidents may not be repor ted by the property owne r if tolerance for 32

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wild species is relatively high. Residents at titudes toward wildlife can be an im portant factor in evaluating the reasons peop le report conflict with wildlife. Investigations of attitudes and perceptions of wildlife have b een reported in the literature in order to determine the publics n eeds and use patterns in regard to wildlife conservation policy. This study will attempt to determine if there is a correlation between variables of level of urbani zation, residents value of w ildlife, property value, and wildlife tolerance as measured by co nflict reporting and surveys. Jonker et al. (2006) found that response patterns of attitudes towards beavers among Massachusetts residents did not diffe r significantly between urban and rural responders. However, the areas surveyed that were mostly suburban showed more negative attitudes than either urban or rural. The researchers noted two reasons for this result. First, they explained that the classificat ion of rural in their ca se probably would be more accurate if they had classified it as e xurban because much of the recent immigration into the rural areas was due to flight from urban sprawl. In this way they make a distinction between a rural environment and a rural culture. In fact it has recently been argued in some studies that rural culture is diminishing across the United States (Jonker, 2006). Thus even though the areas might be c onsidered rural the residents that make up the majority are from an urban area and th ey bring their urban cultural background with them. Second, they note that the suburban areas experienced unusua l flooding during the year of data collection and b eaver problems were in the media significantly more often than in the other areas. This negative media coverage could have contributed to risk amplification in the minds of residents and contributed to more negati ve interpretations of the interactions with beavers. 33

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2.5 Conclusion In the past researchers have used th e species oriented approach to study inte ractions of wildlife with people, most often simply determining where the home range of the populations overlap with human settlement in time and space. Sometimes the research focused on foraging behaviors and/or habitat selection. Mo re recently landscape studies have contributed valu able insight with the help of GIS technology. In the last decade or so, several researchers have attemp ted to document the tolerance of people for wild species. In this study, all three sets of variables; landscape, ecological, and social will be incorporated in the creation of a more complete model of human-wildlife conflict across an urbanizing area. I present a basic flowchart, Figure 2.2, which outlines how these components may interact. Each of the three areas of consideration, landscap e, ecological, and human, are color coded accordingly. Variables within each area are briefly described and the hypothesized outcome related to those variables is illustrated by the flow of the chart. In the next three chapters each of these major components will be examined in detail and Chapter Six will summarize the most important variables contributing to the incident of human-wildlife conflict reporting. 34

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Increased Human settlement Reduced Wildlife Habitats Neighborhoods without water, food, and safe haven resources for wildlife Neighborhoods with water, food, and safe haven resources for wildlife Opportunistic, adaptable species freely traverse matrix from source Avoider species relocate Increased development Exploiter species live within new human neighborhood Increased opportunity for human-wildlife interaction Human Values and perceptions Positive Negative Neutral No reported conflict Landscape Human No conflict No conflict Ecological Reported Conflict Figure 2.2: A hypothetical model of human-wildlife conflict in urbanizing areas. 35

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Chapter 3 The Effect of Develop ment and Landscape Patterns in Residential Areas on the Incidence of Human-Wildlife Conflict across the Urbanization Gradient 3.1 Introduction Urbanized areas are expanding farther each decade into a part of the landscape that was until recently left to wild specie s. With urban expansi on native biodiversity is threatened by conversion and fragmentation of natural habitats (Blair, 1996; Beatley, 2000; Crooks, 2002). In the late 1990s many Am ericans seemed concerned that urban growth needed to be more efficient, social ly sound, and sustainable for the environment. These concerns gave rise to the philos ophy of smart growth, a new method of urban development leading to more compact me tropolitan regions (Danielson et al., 1999; Downs, 2005). However not all regions adopt ed this philosophy, and rapid, inefficient growth continued in many areas across the country (Beatley, 2000; Lawrence, 2005). It is safe to assume that suburban and exurban developments in many regions will continue with the same patterns of land consumpti on (Lawrence, 2005), which brings residents nearer the wild lands and wildlife. Pr oximity of living space between humans and wildlife increases the chance that humans will interact, both in positive and negative ways, with wild animals (Conover et al., 1995). Human wildlife conflict in urbanizing ar eas, where eighty percent of Americans 36

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live (McDonnel et al., 1997, Drei er et al., 2004), can have a negative effect on the way Am ericans perceive wildlife and these negati ve feelings can be transferred to other species and hinder conservation efforts on a larger scale. From an economic standpoint from 1990 2000 US households in urban areas spent $5.5 billion and 1.6 billion hours each year to solve wildlife problems (USDA, 2002). For these reasons, among others, it is important to discover what fact ors contribute to human wildlife conflicts in urbanized areas so that wildlife managers can make a concerted effort to reduce conflict. At the local level, in some resident ial areas homeowners are spending several hundred dollars each year to either deter wild animals from entering their property or to have them removed. Preliminary interviews with wildlife trappers indicated that the majority of human-wildlife conflict was attr ibuted to mid-sized mammals that either dug up residents lawns or attempted to take up residence around or within residents homes. I refer to these mid-sized mammals as conflic t-prone species. Anecdotal comments from trappers were that some neighborhoods had high levels of conflic t with homeowners while in other residential areas it seemed that almost no conflict existed. This raises the question, why do some re sidential areas have more conflict with wildlife than others? One reas on could be the landscape di fferences among residential areas. Some residential areas may have more re sources needed for the persistence of wild species than others. Metapopulation theo ry, developed by Richard Levins in 1970, focuses on a set of subpopulations across landscap es that are in reproductive contact with each other through dispersal. Thus if one s ubpopulation goes extinct, it may eventually be recolonized by a nearby subpopulation, provide d there is continued opportunity for movement between both areas. This model may be of great importance when evaluating 37

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the dynam ics of animal movements especially among fragmented habitats in suburban and exurban landscapes. If the habitat fragments within a residential area are resource rich and the individuals of th e populations are free to traver se the developed suburban or exurban matrix then the metapopulation dynamic could remain in quasi-equilibrium indefinitely allowing the wild sp ecies populations to persist. Based upon this logic, I hypothesized reside ntial areas in urbanized environments that had significantly more internal remnant patch area would show higher rates of human-wildlife conflict than those with less in ternal patch area. I also hypothesized that residential areas with significant shared e dge with larger tracts of undisturbed natural habitat immediately adjacent to the neighborhood would show more human-wildlife conflict than those residential ar eas that were more isolated. The purpose of this study was to exam ine landscape patterns within and around urban, suburban and exurban/rura l residential areas in order to identify which landscape variables contribute to humanwildlife conflict. I also sought to discover if there were differences in the incidence of human-wildlife conflict at different levels of development across the urbanization gradient (i.e urban, suburban, exurban/rural). 3.2 Methods 3.2.1 Introduction To evaluate how landscape variable s and development patterns may affect human-wildlife conflict, spatial analysis of points of conflict were combined with measurements of major landscape variables w ithin each of thirty two residential areas across the urban gradient using ArcGIS 9.2 and Google Earth software. The landscape 38

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m easurements were then used to create a regression model to determine the relative contributions that each variable makes to the incidence of human-wildlife conflict. 3.2.2 Study Area The study area ranged from central downtown Tampa, Hillsborough County, Florida, to north of the c ounty line into the southern portion of Pasco County. The map shown in Figure 3.1 shows the region with the study area boundary outlined in black. Although the Tampa area is bordered to the west by Tampa Bay, the gradient pattern spans out to the north, south and east. For the study area, I chose to use a gradient area ranging from the denses t residential development in the downtown area to the northern exurbs. I chose this area for three r easons. First, this part of Tampa follows a typical development pattern expected in the urban gradient. Second, one area in particular, New Tampa, has shown tremendous suburban growth within the past twenty years. Third, the newer suburban areas were developed with wetland conservation laws in mind. Thus many neighborhoods have highly frag mented and isolated wetlands scattered throughout. I randomly selected zip codes within the study boundary from which to draw specific residential areas to include in the an alysis of human wildlife conflict. For this study the operational definition of a resi dential area was a di stinct, relatively homogeneous, human residential matrix that was bounded by either water bodies, perimeter forests that extended beyond the resi dential area, other physical structures or behaviorally isolating structures that would impede or pr event mid-sized conflict prone species from crossing. Physical structures in cluded walls or solid fences. The perimeter 39

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forests were also referred to as adjacent exte rior habitat patches. Behaviorally isolating structures included interstates, four lane highways, and wide two lane highways that extend beyond the residential area, as these st reets would have higher traffic volume than ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ( Hillsborough County Pasco County Figure 3.1: Locations of residential ar eas within the study area of Hillsborough County and Pasco County, Florida are represented by gray circles. Downtown Tampa is marked with a white circle. County boundary data source: LABINS. residential area streets. Th e higher trafficked streets and highways hinder many individual animals from crossing, and is mo re of a boundary deterrent than the narrow residential development streets within the residential area. Within each zip code, I defined residential areas that fit this definition and outlined the boundaries using ArcGIS 9.2. Half of these residential areas were included in the building of the model of human01020 5KilometersNeighborhood sites in the Study AreaPinellas County Manatee CountyTampa A. H. Gilleland 2010 40

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wildlife conflict and half were reserved as a valid ation group for the m odel. The urban residential areas include d in the analysis had human population densities ranging fr om 1,000 residents/mi2 to 5,047.4 residents/mi2 (United States Census Bureau, 2000) with the majority of urban resi dential areas having few or no natural areas. Suburban residential areas included in th e study area had human population densities ranging from 601.4 residents/mi2 to 826.7 residents/mi2. Many suburban residential areas had public greenspaces such as parks and gol f courses as well as fragmented habitat patches. Exurban/rural resi dential areas included in th e study area had human population densities ranging fr om 208.2 residents/mi2 to 407.1 residents/mi2. Exurban/rural residential areas had some public greenspaces in the form of small parks and occasional golf courses. These residentia l areas generally had relativel y large areas of fragmented habitat patches and agri cultural land. Figure 3.2 s hows orthophotographs of representative topography of residential areas in each development level. Except for the urban residential areas clos est to the city center, most residential areas had seasonally ponded wetland areas, permanent wetlands, and retention ponds which corresponded to most, if not all in so me cases, of the habitat fragments left standing in those areas. 3.2.3 Reports of Conflict During the course of this study, I defi ned a human-wildlife conflict point as a report recorded by a licensed wildlife trap per in which the homeowner wanted some action taken to remove or deter a wild anim al from the homeowners property. Until 2009 the Florida Fish and Wildlife Conservati on Commission (FFWCC) granted licenses for 41

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00 20 4 0.1 KilometersAn Urban Residential Neighbood, Tampa, FloridaA. H. Gilleland 2010 Data Source: Land Boundary Information System 00 20 4 0.1 KilometersA portion of a Suburban Residential Neighbood, Tampa, FloridaA. H. Gilleland 2010 Data Source: Land Boundary Information System 00 20 4 0.1 KilometersA portion of an Exuburban Residential Neighbood, Tampa, FloridaA. H. Gilleland 2010 Data Source: Land Boundary Information System Figure 3.2: Digital Orthophotos illustrating three development levels across the urban gradient of Tampa, Florida. Clockwise left to right, urban, suburban, and exurban Map data source LABINS. 42

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wildlife trapping to interested individuals and companies. Beyond the original application paperwork for the license, FFW CC did not require any more documentation from trappers, so no reports were ever filed with the FFWCC (FFWCC, n.d.). Therefore the only way to obtain these records was direc tly from the trappers. FFWCC listed all licensed wildlife trappers and their contact information on their website (FFWCC, n.d.). It is important to note that jurisdiction over regulating wild life trappers has since passed from FFWCC to the United States Depart ment of Agriculture (USDA) as nuisance animals have been reclassified officially by the government as pests and not wildlife. This change of regulatory agency occurred just after my data collection period in January 2009. There were 307 licensed trappers oper ating in Hillsborough and Pasco Counties of which I successfully contac ted 42 via telephone. Twenty -four of the 42 were self proclaimed weekend trappers only. The vast majority of the weekend trappers only trapped wild boar, Sus scrofa, for personal profit. Most of these boar trappers either did not keep any records at all or were reluctant to share their information. Packets including a letter of introduction and basic information about the study were mailed to trappers who agreed to pa rticipate, or consid er participating (see Appendix B). If the trapper agreed to partic ipate, I requested they set an appointment time with me for data collection, or mail th eir trapping data whichever was convenient for them. As it turned out most of the trapping wo rk went to a relatively small number of full time small business trappers and corporate trappers. The trappers working with larger trapping companies used commercial advertisin g in directory yellow pages and localized 43

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community newspapers that were widesp read throughout both Hillsborou gh and Pasco counties in which they operated. The trappe rs that worked for corporate trapping companies kept reports that were detailed and consistent when compared with other independent and part time trappers who kept records for their own reference only. The record keeping for independent and part tim e trappers ranged from personal computer spreadsheets to note cards kept in shoe boxes. Luckily, the corporate trappers were not as reluctant to participate in the research as th e independents, and in the end I worked with twelve full time wildlife trappers who volunt eered to give me access to their trapping reports for the time period of June 2007 through December 2008. Though this number seems a small percentage, only four percent of the 307, I feel confident that it realistically represents a relatively larger portion of the actual trapping work being conducted in the region, as most of the weekend trappers referred me to these trapping companies. I recorded pertinent information from a ll conflict reports within randomly selected zip codes including the block address where the animal was trapped, number and common name of the animals trapped, date of service, and any additional comments that were recorded in the report. I took data poi nts for all mammal species appearing in the reports, but I removed rats and mice to a separate file, as they were not to be included in the analysis. I did not include rat species because many people who experience conflict with these rodents tend to handle it themse lves by using mouse traps or poisons easily purchased at the local market. For that re ason conflict with rats and mice would be underrepresented using only wildlife trapper re ports. I also removed bird species and reptiles from the analysis because together th ese species made up less than two percent of all conflict reports. I was caref ul to record only the block number for each address as this 44

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m aintained confidentiality of customers. No names or any other identifying information was recorded to insure anonymity of the trappers customers. 3.2.4 The Urbanization Gradient and Conflict Once the data from the conflict reports were compiled and organized, a GIS map georeferencing all conflict reports was created. I downloaded digital orthophotos (DOQQS) true color (RGB) maps for the year 2006 of the study area from Southwest Florida Water Management District website (SWFWMD, n.d.). The DOQQS used NAD 1983 HARN State Plane projected coordina te system provided for use through SWFWMD by the Land Boundary In formation System (LABINS) and had a resolution of six meters. The conflict report informa tion was geocoded using Google Earth 5.0 software and ArcGIS 9.2 (ESRI, 2005) yieldi ng maps with each c onflict point marked. Using the GIS map of the study area with all conflict points geocoded, I cross referenced the conflict points occurring in the 32 residential areas previously outlined. For each residential area, I recorded all conf lict information obtained from the trappers and each residential area was classified based upon human population density as urban, suburban, or exurban/rural. Si nce the residential areas varied in size, I used conflict density (total conflict reports in the residentia l area divided by the size of the residential area in km2 ) as the parameter for the dependent va riable. In order to determine if there was a significant difference in conflict density among the three development classifications, a one-way between groups anal ysis of variance (ANOVA) was performed using PASW 18.0 software (formally SPSS). 45

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3.2.5 Landscape Variables Landscape variables in each residential area that may contribute to conflict were defined and measured. During analysis, the zoom capabilities and resolution of Google Earth was best discerning some of the details of the landscape variables of interest, but I used the DOQQS maps and ArcGIS for measur ements of the landscape variables. The unit of measurement in landscape data should be universal in all landscapes, and where urbanization is concerned, should effectively link ecological a nd social patterns (Zipperer et al., 1997). The patch was the unit used in this study to refer to all habitat fragments under consideration. A patch is defined as a relatively homogeneous area that differs from its surroundings (Foreman, 1995). The background matrix, or the surroundings in this study was the developed landscape, excl uding greenspaces. A ll patch units were categorized as one of two types: a remnant patch, or a planted patch (Zipperer et al., 1997). A remnant patch was operationally defined as an area that e ither was not cleared during site development and existed before de velopment or an area th at is growing back after previously being cleared either fo r development or agriculture and is now unmanaged by people, (Zipperer et al., 1997). A planted patch is defined as a patch created by human landscaping a nd is highly managed by people, including greenspaces. The landscape variables in each reside ntial area that may affect human-wildlife conflict (dependent variable) related to a particular patch included: 1. The development classification of th e residential area based on human population density. These were urban, suburban, or exurban/rural as defined earlier in accord ance with the US Census bureaus record for each 46

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2. The hum an population density for each re sidential area obtained from the US Census bureaus record for each zip code (US Census, 2000). 3. The total area of each residential area in square kilometers. 4. The perimeter of each resident ial area in kilometers. 5. The area of all adjacent habitat patc hes immediately exterior to the residential area in square kilometers. 6. The distance in kilometers of edge sh ared between home lots and adjacent habitat patches that are exterior to the residential area. Referred to as shared edge exterior. 7. The distance, in kilometers, of any natural corridor leading to another remnant patch of equal or larger size th at is exterior to the residential area. 8. The percentage of the perimeter that is shared with adjacent exterior habitat. This was meant to give an index of direct connectivity for the comparison of residential areas. 9. The total area of all remnant patches interior to the residential area in square kilometers. 10. The total number of all remnant patches interior to the residential area. 11. The average size of internal remnant patches. 12. The percentage of remnant area which was calculated as the total area of internal remnant patches divided by the area of the residential area. 13. The distance of edge shared by home lo ts and interior remnant patches in kilometers. Referred to as shared edge interior. 47

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14. The area of all p lanted patches (inclu des crop and agricultural land) within the residential area in square kilometers. 15. The number of fresh water bodies (r etention ponds, natural ponds, etc). 16. The total area of fresh water bodies within the residential area in square kilometers. 17. The area of golf course links within the residential area in square kilometers. For each of the landscape variables measured as area, I created data layers in the DOQQS map as shown in Figure 3.3. All measurem ents were saved in properties for each polygon and were color coded for display. The values for landscape variables within each of the thirty two residential areas were analyzed using PASW 18.0 software. Pear son correlations were performed to detect bivariate correlations between the independent variables in or der to insure there was no significant effect due to multicollinearity, and also to define strength of correlation between each independent variable and incidenc e of wildlife conflict. Whenever bivariate correlations between independent variables gr eater than 0.7 were de tected, I eliminated the independent variable that had the lowest correlation value with the dependent variable (Pallant, 2007). After all bivariate correlations over 0.7 were removed; I ran a standard linear regression analysis to determine which of the landscape variab les contributed most significantly to the model of conflict. Using the result of th e first standard regression, I chose the landscape variables with correlati on values greater than 0.25 and parameter coefficients with significance less than 0.1 (P allant, 2007). I then pe rformed hierarchical 48

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Figure 3.3: A sub-sample of residential areas illustrating landscape variables and residential area boundaries. Re d = interior habitat remnant patch, blue = water bodies, green= residential area borde r, orange= adjacent exterior habitat patch, and beige = golf links. multiple regression analysis holding the most significant variable constant in the first block and then used only those variables that fit the criteria mentioned earlier for the second block. I compared the standard linear model with the hierarchical model for R square value, significance and parsimony. To determine if the model was adequate for prediction of human-wildlife conflict in other residential areas with similar environments, validation calculations were performed using new residential areas in the Tampa area that were not included in the pr evious analysis. Validation of the linear model was 012 0.5KilometersA Sub-Sample of Neighborhoods in the Study AreaA. H. Gilleland 2010 Data Source: Land Boundary Information System 49

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accom plished by cross validation procedures as described by Mendenhall and Sinchic (2003), using the R2 prediction equation. 3.3 Results 3.3.1 Conflict Reports and Conflict Prone Species In the time period beginning June 2007 through December 2008, 619 conflict reports were generated among the 12 wildlife tr appers who participated in the study. The location of each conflict point was geocoded (Figure 3.4) and those located within the designated residential areas were included for analysis. The da ta from the conflict reports revealed an unexpected variet y of species, and that certain species of mammals are involved in conflict far more often than ot hers. Table 3.1 shows a list of the animal species appearing on conflict reports and the pe rcentage of reported conflict represented by each species over a peri od of eighteen months. It was interesting, and somewhat unexpect ed, to discover that wildlife trappers were called upon most often for rat and mice problems. I believe these trapping events are indicative of many homeowners reluctance to in teract with wildlife at all, even small rodents. The other most frequent offende rs were armadillos, raccoons, opossums, and squirrels. 3.3.2 Levels of Urbanization and Conflict Each residential area was classified into development level urban, suburban, or exurban/rural depending on the U.S. Census da ta on population density for that zip code. A one way between-groups analysis of varian ce was conducted at alpha = 0.05 to explore 50

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5 miHillsborough CountyPascoCounty Pinellas County Tampa Figure 3.4: Study area with black dots representing all human-wildlife conflict points. Table 3.1: An inclusive list of animal species appearing on conflic t reports in the study area, excluding wild boar and alligators. Non-native species that has expanded its range into Florida. Animal Percentage of total reported conflict Armadillo ( Dasypus novemcinctus)* 24.5 Bat (unspecified species) 0.48 Bees (unspecified species) < 0.1 Bobcat ( Lynx rufus ) 0.16 Domestic Chickens (unspecified breed) < 0.1 Deer ( Odocoileus virginianus) 0.48 Goats (unspecified breed) 0.32 Gulls (unspecified species) 0.16 Muscovy Ducks ( Cairina moschata) < 0.1 Nutria ( Myocaster coypus ) 0.13 Opossum ( Didelphis virginiana) 14.5 Pigeon (unspecified species) 0.32 Pocket gopher ( Geomys pinetis) < 0.1 Raccoon ( Procyon lotor) 15.8 Rabbit ( Sylvilagus floridanus ) 0.32 Rat (unspecified species) 25.8 Skunk ( Mephitis mephitis) 0.16 Snakes (unspecified species) 1.8 Squirrel ( Sciurus carolinensis) 15 Vulture (Coragyps atratus) < 0.1 Yellow jackets ( Vespula unknown sp.) < 0.1 51

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the im pact of development level on conflic t reporting. Descriptive statistics for each development level is found in Table 3.2. Ther e was no significant difference in conflict density among the three deve lopment levels (p = 0.424). Table 3.2: Descriptive statistics for one-way ANOVA fo r differences in conflict density at three development levels (alpha = 0.05). Development Level Number of residential areas, N Mean conflict density Standard deviation Minimum Maximum Urban 10 1.1955 1.0833 0.0997 2.7677 Suburban 15 0.7958 1.0083 0.0000 4.1884 Exurban/rural 7 0.6045 0.5773 0.0000 1.2300 3.3.3 Landscape Variables and Conflict All landscape variables were measured and recorded for each residential area. Averages of these landscape measurements for each development level are shown in Table 3.3. In Table 3.3, the total area of all remnant patches in square kilometers is combined with the total number of remnant patches in the residential area to become average size of interior remnant patches. Pearson correlations were analyzed be tween all landscape variables (bivariate) and between each landscape variable and conf lict density. At least one of the pair of landscape variables with strong (> 0.7) biva riate correlation was removed from the analysis or the two were combined into one distinct new independent variable. Correlations between all remain ing landscape variables and co nflict density are given in Table 3.4. 52

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Table 3.3: The average of landscape variable measuremen ts for each residential area development level. The average for the dependent va riable for each development leve l is given in the last row. Average of all residential areas in each development level Urban Suburban Exurban Rural Human population density = residents / km2 1669.11 277.84 128.05 Residential area in km2 8.96 9.46 12.69 Percentage of residential area that was remnant patch 0.05 0.34 0.32 Distance of residential area edge shared with exterior patch in km 0.0 2.71 3.49 Distance of residential area edge shared with internal remnant patches in km 2.79 7.63 6.30 Size of interior remnant patches in km2 0.04 0.19 0.23 Area of adjacent exterior habitat in km2 0.0 16.11 8.73 Distance of residential area edge shared with natural corridor(s) in km. 0.0 2.01 2.47 Area of fresh water bodies within residential areas in km2 0.74 0.76 1.36 Number of fresh water bodies within the residential area 35.6 46.9 56.7 Distance of residential area perimeter in km 12.40 13.72 15.34 Percentage of residential area perimeter that is shared with exterior adjacent habitat 0.0 0.22 0.18 Area of residential area classified as planted patch in km2 0.06 0.83 1.15 Number of conflict reports / km2 (conflict density) within residential areas 1.20 0.80 0.60 The landscape variables that had correlat ions higher than 0.25 were used in a standard linear regression analysis to test for their effect on conflict density. The result was that there were only two significant landscape variab les; human population density and area of adjacent habitat patches. In or der to discover if other variables were significant when holding huma n population density constant, I performed hierarchical multiple regression. Again the only landscape va riable that was significant was area of adjacent habitat patch. The hierarchical mode l had a higher p value than the first order regression model and the model R value was not improved. The standard linear regression model 53

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Table 3.4: Correlations between landscape variables and conflict density. Landscape variable Correlation with conflict density (R) Population density (in thousand) 0.287 Percentage of residential area that is remnant patch -0.235 Distance in shared edge with exterior habitat patch 0.134 Percentage of the residential area perimeter that is shared with exterior habitat 0.149 Distance in shared edge with interior remnant patch -0.138 Number of interior remnant patches -0.090 Remnant patch area -0.152 Area of planted patches -0.123 Average remnant patch size -0.262 Area of adjacent habitat patches 0.345 Distance of corridor edge 0.109 Area of Fresh water -0.145 that included human population density and ar ea of adjacent habitat yielded the most parsimonious model (R2 = 0.288, p = 0.007). Table 3.5 shows de scriptive statistics for the standard linear regression model, whic h resulted in the prediction equation: E(y) = 0.280 + 0.231x1 + 0.021x2 Where x1 is the population density for the residential area, and x2 is the area of adjacent undisturbed habitat. A normal probabi lity plot of the regression standardized residuals, shown in Figure 3.4, demonstrates that a plot of the model residuals produced a relatively straight line as would be expect ed from the model when there is no major deviation from normality. Thus the data did not violate normality assumptions. A practical interpretation of the regression equa tion is that for every 386.1 people added to the population density per square kilometer (1,00 0 per square mile) of a residential area; 54

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the prediction equation estim ates that conf lict density is increased by 0.231 reports per square kilometer. When human population is held constant every additional square kilometer of adjacent habitat ex terior to the residential area raises conflict density by 0.021 reports per square kilometer. Table 3.5: Descriptive statistics for the standard linear regression model. Standard linear regression R2 = .288, p = 0.007 Coefficients Model Standardized Beta Unstandardized B Sig. Tolerance VIF Constant 0.280 Population density .431 0.231 0.014 0.909 1.10 Area of adjacent Habitat patch .476 0.021 0.007 0.909 1.10 Figure 3.5: Normal probability plot of regression residuals. 55

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Cross validation of the m odel, showed that the prediction equation showed an R2 drop that was slightly outside the range of acceptance (R2 change > 0.1). While the model equation yielded significant explanatory vari ables contributing to human-wildlife conflict within residential areas of large tracts of urbanized landscape, it was not reliable for prediction of conflict incidence within single residential areas. 3.4 Discussion At the onset of this study, I hypothesized that exurban/rura l residential areas would have significantly less human-wildlife conflict than urban and suburban residential areas. The data revealed there was no signi ficant difference in th e density of conflict reporting among the three development classi fications. Thus, conflict reporting was statistically the same in urban residential areas, suburban residen tial areas, and exurban residential areas, although the average was twi ce as high in urban residential areas (1.20) as exurban/rural reside ntial areas (0.61). There were limitations related to this research. Having sel ected the zip codes randomly, one limitation was that the zip code s that were included in the study had only seven residential areas that fit the category of exurban/ru ral (human population density less than 193 people per square kilometer or 500 people per s quare mile). Of these seven, only two residential areas had resident de nsities less than 135.14 people per square kilometer (350 people per square mile). Of th e two, one of those residential areas had no conflict reported during the 18 month study peri od. In fact, when examining the conflict maps of all conflict reported by trappers, not just those ra ndomly selected, no residential area with less than 77.2 residents per square kilometer (200 residents per square mile) 56

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reported any conflict with wildlife. While thes e were not selected for inclusion in the analysis, these very low density residential areas are few and only exist on the outermost fringes of the metropolitan area. I am, however, unwilling to make the conclusion that a very low human population density would predict no conflict with wild life. In informal conversations with wildlife trappers, it was s uggested that residents in the more rural portions of Hillsborough and Pasco counties, where there is a large proportion of farmland, take care of any wildlife problems that may arise personally and would not consider calling a professional trapper. There is also the elemen t of cost that would be a consideration in whether to choose trapper services. Trappers typically charge between $100 to $200 for each trip, and more if animal-proofing servic es or repair services are rendered. Since conflict in this study was defined as incidence of tra pper reports per km2 within a residential area, the residents who handle nui sance animals on their own, without aid of a trapper, are unknown and are not represented in this study. Human population density and area of habitat immediately adjacent to the residential areas were the only two landscape va riables that had a significant effect on conflict reporting, according to the model. According to the model, neither total internal remnant patch area within the residential area, nor total development edge contact was a significant contributor to conflict reporting as I originally hypothesized. At the start of the study, I also hypothesized that ad jacent habitat would be sign ificant in combination with a significant amount of shared edge of adjacent habitat with homeowner property. However, shared edge with residences wa s not a significant vari able in the model. Though there was no difference in the average values of conflict reports between the 57

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developm ent levels (urban, suburban, and exurban/rural), the c onflict reporting was positively correlated with human population density. It seems intuitive that as human resident density increases so would the possibility of interactions with wildlife and so would conflict with wildlife. The increas e in human-wildlife c onflict as population increases is so gradual across the gradient that no significant threshol ds are detected. The model also reveals that as the area of adjacent habitat increases so does conflict reporting. The metapopul ation hypothesis asserts that as wildlife populations in remnant patches decreases, patches will be recolonized by individuals from the adjacent forest to keep the population in the patch in quasi-equilibrium. In this study, the significance of the area of undisturbed habitat immediately adjacent to the residential area as a predictor of human-wildlife conflict suggests that there may be a metapopulation dynamic existing between the remnant patches within the residentia l area and the much larger natural habitat immediately adjacent to the residential area. The fact that animals involved in conf lict within these re sidential areas are trapped at a relatively high rate, compared w ith other residential areas that do not have natural habitat in close proximity, may also s uggest a source-sink system is at work. The undisturbed adjacent habitat could be the source of individuals into the residential area. A residential area that has regul ar trapping of animals would be a sink as individuals are taken out of the residential area. In fact, several suburban and exur ban residential areas that had the largest adjacent forests also had higher conflict with wildlife, especially in the scattered clusters of development where house density was higher. Perhaps if suburban and exurban residential areas with si gnificant areas of exterior adjacent forest would designate transition greenspace to buffer the residential area from the wild lands, 58

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conflict could be reduced. Buffer areas or zones are areas that surround and protec t sensitive areas to better protect the species within them (Hylander et al. 2002; Lindenmayer and Fischer, 2006). Three important purposes of buffer areas is to limit the impact of human disturbance on native ecosystems, minimize edge effects, and to maximize native species richness inside the protected area (Baker, 1992; Cockle a nd Richardson, 2003) and they have been shown to be successful (Mwalyosi, 1991; Sanchez-Azofeifa et al., 2003; Lindenmayer and Fischer, 2006). Buffer zones have b een recommended for large reserves and protected areas as a way to protect biodive rsity from the rapid encroachment of human settlement. Wittemeyer et al. (2008), examin ed 306 protected areas in 45 countries in Africa, Asia, North and South America, and found human settlement around the borders of protected areas showed a growth rate twi ce that of rural areas nearby that were not bordering protected areas. They suggested th e creation of large multi-use buffer zones surrounding the core habitats and corridors. They asserted that these buffers would facilitate effective protection for biodiv ersity while allowing human settlement to continue near the borders. In the case of less formally protected tracts of natural habitat, like those near urbanizing landscapes in Tampa, Florida, these buffers would have to be part of the planning process as the resident ial areas are still in the design stages. In an urbanized setting community planne rs could consider strategically placing parks and common areas around the perimeter of the development in the areas adjacent to the natural habitat as much as possible, inst ead of scattered around the interior, to serve as a multi-use buffer zone. In sections where a buffer is not possible sections of wildlife proof fencing could be installed to assure the animals coming into the residential area are 59

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funneled toward the buffer instead of si mp ly traveling directly through residents property. Carefully placed and well designed multi-use buffer zones could enhance opportunities for viewing wildlife, enjoyed by many residents, while alleviating some of the conflict problems that may otherwise be en countered if the animal traveled directly onto homeowner property. While buffer areas should alleviate some of the conflict problems in suburban and exurban neighborhoods, it can not be viewed as the overall cure. Certainly many changes will most likely be needed to work together to reduce the problem significantly. The R square value of the model re veals that the model paramete rs explain 28.8 percent of the variation in conflict reporting across the urba nization gradient. Upon first glance this may seem a relatively low value for prediction, but upon closer examination I believe it to be an accurate representation of the effect of landscape variables on the phenomenon of human-wildlife conflict in urba nized areas. I concluded that th e models ability to predict the realistic variability in total conflict density, using only la ndscape variables, was actually better than expected. However, us ing cross validation I determined that the model was lacking in predictive ability at th e statistical level and required modification. I believe the weakness of the model for predic tion is because there are other factors, outside the realm of physical la ndscape, that could possibly ha ve an effect on whether or not conflict is reported. The most obvious fact ors include behavior pa tterns of the animals involved and perhaps abundance of wildlife wi thin the remnant habitats in and around residential areas, but also the mind set of th e residents themselves. After all, it is a conscious decision on the part of the homeowner and/or reside nt whether or not to call a wildlife trapper to come out to take care of an animal problem on their property. These 60

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two areas, e cological and human values, will be e xplored in greater detail in the chapters to come and the significant contributors will be added into the model to make a more complete model that is useful for prediction. 61

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Chapter 4 The Effect of Behavioral Ch aracteristics and Relative Ab undance of Conflict Prone Species on Reported Human-wild life Conflict in Suburban Tampa 4.1 Introduction Recent research in urban landscapes has shown that biodiversity decreases with increasing urbanization (Beatley, 2000; Shochat, 2004; Faeth et al., 2005; Clergeau et al., 2006; McKinney 2006). In fact, not only does biod iversity tend to decline in highly urban areas, but biotic homogenization has been observed in many urban metropolises around the world (Hobbs and Mooney, 1997; Crooks et al., 2004). Biotic homogenization is a pattern in which a small number of highly ad aptable species, that are pre-adapted to successfully coexist in high density human environments, replace native species within that environment. Several researchers have hypot hesized that this is due, at least in part, to the behavioral characteristic s of certain species (Blair, 1996; Shochat, 2004; Kark et al., 2006). These behavioral characteristics that c ontribute to successful existence in urban environments have been investigated in seve ral avian studies (Blair 1996; Shochat, 2004; Kark et. al., 2006; Shochat et al., 2006). In a Northern Calif ornia study on biodiversity of avian species, Blair (1996) divided the bi rd community along an urbanization gradient extending from undisturbed areas ou tside the city to the highl y developed city center. Blair (1996) found that certain avian species efficiently expl oit the resources in highly 62

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urban areas and term ed those species as u rban exploiters. In 2006, Shochat et al., termed the same types of species as urban commensals because they believed the species were not only capable of exploiting resources within urba n areas, they were dependant upon the resources provided by the human built environment. Blair (1996) also found certain types of av ian species persisted more successfully in areas of intermediate development, like those found in the suburbs and termed those species suburban adapters. Kark et al., 2006 took this one step fa rther in a study of avian species in Jerusalem, and outlined differences in behavior al characteristics between urban exploiters and urban adapters. They found that exploiters differed primarily from adapters in social structure, migratory status, and dietary preferences. Expl oiters were more social, nonmigratory, and more omnivorous. For this st udy, I propose that this same generalized suite of characteristics can be applied to mammalian species in urban areas as well as avian species. If this is true, I expected to see species with urban exploiter characteristics more often involved in conflict in highly urba n residential areas because their adaptive ability to exploit human resources allows them to persist in these areas and brings them into increased contact with ur ban residents. I also expected to find species with urban adapter characteristics more often involv ed in conflict in suburban and exurban residential areas rather than in urban residential areas. In the previous chapter, I investigat ed the impact the physical landscape and development patterns had on conflict reporti ng and found that the si gnificant landscape variables only explain twenty eight percent of the variability of conf lict among residential areas. Obviously other variables contribute to human-wildlife conflict. In this chapter 63

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hum an-wildlife conflict is investigated from a species-oriented approach. The behavior patterns are categorized as urban exploiter or adapter, according to the definitions given by Blair (1996) and Kark et al (2006), to determine if the same suite of traits that were found in avian urban exploiter and adapter sp ecies also applies to urban and suburban mammalian species. Increasing th e understanding of urban e xploiter and urban adapter behavior patterns may shed some light on ways to reduce residents conflict with these species. Other than predisposed behavioral pattern s, one ecological factor that may also contribute to human-w ildlife conflict is an overabundance of animals living within or near a human settlement. Interactions with human residents may be frequent and conflict may be more likely if the abundant animal is of the urban exploiter or urban adapter type. This phase of the study investigates a possi ble relationship between conflict reporting within residential areas and both the beha vior patterns of animals and the relative abundance of certain conflict-prone species in residential area remnant patches. Conflictprone species are termed here as wild mammalian species in which conflict reporting by residents is disproportionately large wh en compared with other species. At the onset of this study, I made seve ral hypotheses. First, I hypothesized that I would see a decreasing number of species repr esented in conflict reports with increasing urbanization because biodiversity would decr ease with increasing urbanization. In other words, I expected to see a decreased number of species involved in c onflict in residential areas closer to the urban cen ter. Second, I hypothesized that reports of human-wildlife conflict in urban residential areas would consist primarily of species with characteristics similar to those described as urban exploiters in avian studies because those species have 64

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a genera lized suite of characteristics that a llows them to persist in highly urbanized environments. Third, I hypothesized that species with characteristic s similar to those described as urban adapters would be involve d in conflict signifi cantly more often in suburban and exurban residential areas than in high density urban residential areas. I believed this to be the case because adapter sp ecies still require a ce rtain level of natural habitat or access to undisturb ed areas and/or native species Fourth, I hypothesized that residential areas with higher relative abundan ce of conflict prone species within remnant patches would also have higher levels of reported conflict. 4.2 Methods 4.2.1 Introduction In order to detect a change in spec ies diversity across the urban landscape, I compared the diversity of vertebrate species represented in conf lict reports for urban, suburban, and exurban residential areas. Us ing the species oriented approach, the characteristic behavior pattern s of species that are most of ten involved in conflict within the study area are evaluated from the literatur e. Relative abundance of species traveling within remnant patches of select suburban re sidential areas is also compared to detect possible correlations with the incidence of human-wildlife conflict reporting of those species. 4.2.2 Study Areas for Biodiversity and Characte ristic Evaluation of Conflict Prone Species The incidence of conflict reporting was documented in th irty two residential areas 65

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within eighteen random ly selected zip codes across the urbanization gradient in central and north Hillsborough County, Florida and south Pasco County, Florida as described in Chapter Three (refer to Figure 3.1). Resident ial areas were operat ionally defined as a distinct, relatively homogeneous, human resi dential matrix that was bounded by either physical structures or behavior ally isolating structures that would impede or prevent midsized conflict prone species from crossing. P hysical structures included walls or solid fences, and water bodies or perimeter forest s that extended beyond the residential area. These forests were also referred to as adj acent exterior habitat patches. Behaviorally isolating structures included interstates, four lane highways, and wide two lane highways that extend beyond the residentia l area, as these streets woul d have higher traffic volume than residential area streets. The higher traffic streets and highways hinder many individual animals from crossing, and these are more of a boundary deterrent than the narrow residential development streets within the residential area. Using the conflict records obtained from wildlife trappers, the num ber of conflict report s for each species in each residential area was documented and each conflict event was geocoded and marked on GIS maps (Figure 4.1). 4.2.3 Study Areas for Rela tive Abundance Surveys From the thirty two residential areas sele cted in Chapter Three, I selected three residential areas in which to evaluate the relative abundance of mammalian wildlife within remnant patches of the residential areas. Two of these residential areas were in the New Tampa area, north Hillsborough County, and the other was in south Pasco County (Figure 4.1). These areas were chosen because of the strong similarities in most of the 66

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landscap e features that were evaluated in Chapter Two. They were not significantly different in any landscape variables that we re analyzed earlier in the study. Remnant patches were similar in all three residential areas, consisting of natu ral conservation areas composed of relatively small permanent wetlands, seasonally ponded wetlands, and remnants of upland pine forest characterized by longleaf pine ( Pinus palustris) loblolly pine (Pinus taeda) saw palmetto (Serenoa repens) and other various native and invasive understory (Figure 4.2). 5 kmHillsborough County Pasco County Pinellas County Tampa Figure 4.1: The Tampa, Florida metropolitan area with yellow push pins showing the locations of three suburban residential areas where I surveyed relativ e abundance. The black dots represent human-wildlife conflict points involving medium-sized mammalian species in the study area. The white diamond is downtown Tampa (map source: Google Earth). All three residential area s had the same development classification, suburban, and had similar human population densities be tween 232 and 307.7 residents per square 67

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kilom eter (601 and 797 residents per square mile). In fact, these three suburban residential areas were the most closely ma tched of all thirty two residential areas originally selected, but the one importan t difference among them was conflict density. One residential area, identified as HG, had the highest conflict density of all the residential areas included in the study of human-wildlife conflict (conflict density = 4.19), one residential area, iden tified as HI, had very litt le conflict density (0.249), and the other residential area, identified as FW had no conflict dens ity reported during the eighteen month reporting period. Comparing human-wildlife conflic t among these three matched residential areas should control for landscape variables while evaluating possible differences in relative abundance of wildlife. Figure 4.2: Photographs of typical remnant patch habitats in suburban and exurban residential areas within the study area of Hillsborough and Pasco Counties, Florida. Dominant species are longleaf pine ( Pinus palustris) loblolly pine (Pinus taeda) cypress ( Taxodium sp.), and saw palmetto (Serenoa repens). 4.2.4. Evaluation of Diversity of Species in Conflict Repor ts Across the Urban Gradient Using the conflict reports obtained from licensed wildlife trappers operating in the study area, I compared the numbers of conflict reports for all wild species within each 68

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developm ent level: urban (human populat ion density > 386.1 residents per square kilometer or 1,000 residents per square m ile); suburban (human population density < 386.1 but > 193.1 residents per square kilometer, or 500 residents per square mile); and exurban/rural (human population density < 193.1 residents per square kilometer, or 500 residents per square mile). I wanted to determ ine two things: first, if there was decreasing diversity of species represen ted in conflict reports with increasing urbanization, and second, if certain species were involved in a hi gher incidence of conf lict at one level of development versus another. I performed a Ch i-square test to test for significance in differences between the number of species represented in conflic t reports at each development level, urban, suburban, and exurba n/rural. I performed one-way analysis of variance for mean conflict reporting for each wi ld species at the three development levels to determine significant differe nces. If significant differen ces were detected, I then performed Tukeys HSD post hoc test to exam ine within which development levels the differences were found and the significance level of each. 4.2.5 Evaluation of Behavioral Characteristic s of Conflict-Prone Species Across the Urbanization Gradient Based upon the results reported by Kark et al., (2006), behavior al characteristics that may contribute to a populations successf ul persistence in urban residential areas, and therefore may predispose the individuals to more frequent interactions with residents, include: 1. Diet : Urban exploiters tended to be more omnivorous. Urban adapters tended to be more specialized in their dietary pr eferences (frugivores, insectivores). 69

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2. Sociality : Urban exploiters tend ed to be m ore gregarious than adapters. 3. Migration and movement patterns : Urban exploiters tended to be sedentary species that either maintain den sites or have little en ergetic investment in finding new den sites on a regular basis. 4. Behavioral flexibility : Urban exploiters should demons trate flexibility in behavior patterns like foraging, breeding, and home range size to adapt to the resource availability of the highly urbanized landscape and species populations with higher densities. As shown in Table 4.1, five species made up 96 percent of all sp ecies involved in human-wildlife conflict across the urban grad ient. Since rat and m ouse traps are easily obtained and many households remove these an imals themselves without the aid of a wildlife trapper the conf lict reported for these rodents is most likely underrepresented at all development levels, therefore, I removed them from the characteristic evaluation. Table 4.1 : Proportion of all conflict reports attributed to the top five offending species. Common name (species) Frequency of conflict reports Proportion of reports Rats & mice (unspecified species) 159 25.8 Nine-banded Armadillos (Dasypus novemcinctus) 151 24.5 Raccoons (Procyon lotor) 97 15.8 Gray Squirrels (Sciurus carolinensis) 93 15.0 Virginia Opossum (Didelphis virginiana) 90 14.5 An assessment of behavioral characteris tics including diet preferences, sociality, sedentariness, and home range size for each of the remaining top four offending species 70

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was performed to determine if their characte r istics fit the hypothe sized definitions for urban exploiters and urban adap ters as defined by Blair ( 1996) and Kark et al., (2006). Based upon a literature review, characte ristics were assessed for each species accordingly. The average rate of conflict ev ents for each species at each residential development level (urban, suburban and exur ban/rural) were compared using ANOVA to determine if conflict-prone species with urba n exploiter characteristics are reported more often in urban residential areas and those with urban adapter characteristics were reported more often in suburban residential areas as hypothesized. 4.2.6 Relative Abundance Surveys Using Detection Stations Relative abundance for conflict-prone species was obtained from track surveys at track detection stations (Conner et al., 1983; Crooks, 2002). Relative abundance is a method of obtaining species abundance info rmation for comparison purposes at each sampling point only when a population or density estimate is not needed. In this case the purpose was to determine if the relative a bundance of certain speci es was significantly higher in one residential area s remnant patches versus the other residential areas remnant patches. Track detection stations were set up in random remn ant patches in each of the three preselected reside ntial areas and set equidistant from the remnant patch edge. Each track detection station was a one meter di ameter, one centimeter deep circle of fresh play sand (Figure 4.3). Each track station was checked for animal tracks (Figure 4.4) and reset daily for four consecutive days each season (Connor et al., 1983, Crooks, 2002), once during the wet season (June September) wh en average monthly rainfall is equal to or greater than seven inches and once during the dry seas on (November April) when 71

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monthly rainfall is less than three inches (Ali et al., 2007), for two consecutive years. I chose to sample tracks duri ng the warm /wet season and during the cold/dry season because in central Florida these two seasons ar e the most distinct (Ali et al., 2007), and I believed these shifts in precipitation and temperature would have the most impact ecologically. This survey schedule gave a total of 368 point visits with an average of 132 point visits for each residential area over the two year period, December 2007 through December 2009. Figure 4.3: A track detection station freshly reset. Figure 4.4: Raccoon track (center) and opossum (top right). 72

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Tracks were identified to species and th e number of visits was recorded. A visit was defined as at least one track of a speci es per station per ni ght (Conner, 1983; Crooks, 2002). The track index (T) for each season was calculated for each residential area (j) as: T = vj/(sjnj) Where vj is the number of stations visited by a species in residential area j, sj is the number of stations in residential area j, and nj is the number of nights that stations were in operation in residential area j. T represents the visitation percentage for a species per track station in a residential area per night and an index of relative abundance. It was not appropriate to compare opo ssum indices of relative abundance to raccoon or squirrel indices of relative abundance as these are different species and do not respond to track detection stat ions in the same way and therefore an interspecies comparison would be incorrect. Thus the indi ces of relative abundance do not indicate more or less of one particular species over another species, but it is useful to compare raccoon abundance indices across the three different areas. A relative index of species conflict for each of the four species in the three suburban residential areas was calculated base d upon the average track index (a measure of relative abundance) of the species in the residential areas remnant patches compared to the percentage of complaints listed for that species in that residential area. This gave an indication if some residential areas have disp roportionate conflict reporting in relation to relative abundance. A species conflict index (C ) represented by the ratio of relative abundance index to conflict reports can be obtained by: C = (rj/Rj) : T 73

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Where rj is the number of conflict reports for a species in residential area j, and Rj is the total number of conflict reports in residentia l area j and T is the relative abundance index for that species in residential area j. The three suburban residential areas were compared to see if there was any correlation of rela tive abundance for a species with conflict reporting of that species usi ng Pearson correlation. I also checked if offending species were disproportionately reported and if so in which residential area or residential areas was reporting disproportionate. If all other landscape values ar e similar for the residential areas for which species conflic t to abundance are compared, a nd it is demonstrated that a residential area has significantly greater conflict reporting for a species than another, then it can be inferred that human perceptions and tolerances of the sp ecies is causing the difference in that residential area. 4.3 Results 4.3.1 Species Diversity in Conflict Reports across the Urban Gradient Across the Tampa metropolitan region, a wi de variety of wild species are causing difficulty for some homeowners. Reports of human-wildlife conflict in the residential areas included in the study were composed of eighteen vertebrate species and two invertebrate species. As shown in Table 3.1, th ere were twenty total species appearing on all conflict reports over the eighteen months reporting time evaluated in this study. Of these, 19 species were reported in exurban/ rural areas (excludes pigeons), 17 species were reported in suburban areas, and only six species were reported in the most urban areas. A Chi-square test conf irmed that the difference in biodiversity values within conflict reports was significant among different levels of development. The most urban 74

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residential areas (hum an population de nsities averaging 4,232 residents/mi2) had significantly less biodiversity in conflict reports than bot h suburban (human population density averaging 720 residents/mi2) and exurban residentia l areas (human population density averaging 332 residents/mi2). The biodiversity of spec ies within conflict reports in suburban and exurban residential areas was statistically the same. An evaluation of species involved in c onflict reports revealed some interesting differences across development levels (Figure 4.5). The most obvious was the conspicuous absence of armadillos in urban re sidential areas despite the fact that it was one of the top four offending species. Conflict reports for each species across the urbanization gradient0 5 10 15 20 25 30 35 40Ar m a d illos Opo ss ums Raccoons Sq ui rre l s Bats Deer Fr o gs Sn ak esWild speciesNumber of conflict reports Urban Suburban Exurban/rural Figure 4.5: The number of conflict reports from each of the three development levels for the majority of wild species in the reports. Bats, frogs and snakes were of unspecified species. I conducted an ANOVA to test for differe nces in mean conflict reports for armadillos ( Dasypus novemcinctus) in urban, suburban and exurban/rural development levels (n=32), and found differences were significant (p = 0.03). Tukeys HSD post hoc 75

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test revealed armadillo conflict reporting in urban residential areas (mean 0.10) to be significantly lower (p = 0.02) from armadillo conflict reporting in exurban/rural residential areas (mean 4.43). I followed the same procedure across development levels for opossums (Didelphis virginiana) raccoons (Procyon lotor) and squirrels (Sciurus carolinensis) I found there was no significant difference in reports for opossums across the gradient at the alpha leve l of 0.05 (p = 0.13). There was no significant difference in conflict reporting of raccoons (p = 0.78) or squirrels (p = 0.92) across the urbanization gradient. 4.3.2 Evaluation of Behavioral Characteristic s of Conflict Prone Species Across the Urban Gradient Seventy percent of all c onflict reports throughout the urbanized area consist of only four species, only twenty percent of the species biodiversity reported. These four conflict prone species: armadillos, opossum, raccoons, and squirrels, have certain behaviors and characteristic s in common that may predispose them to a more urban lifestyle. Each is reviewed below. Nine-banded armadillos. Nine-banded Armadillos ( Dasypus novemcinctus ) are mid-sized burrowing mammals belonging to the same superorder ( Xenarthra) as the anteaters and sloths (Montgomery, 1985). They are recognized easily by their outer scutes, a series of external armor-like plates made of dermal bone (Figur e 4.6). They typically forage at dusk or during the night, and are the onl y species of the top four c onflict prone species that are not omnivorous. Armadillos are mainly insectiv ores and invertebrate consumers (Breece 76

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and Dusi, 1985; W irtz et al., 1985; Sike s et al., 1990; McDonough and Loughry, 1997). In fact, examination of stomach contents show that armadillos consume animal material 98 percent of the time in fall, winter, a nd spring (Breece and Dusi, 1085). On occasion, during summer months, armadillos consume foods outside this category, but the incidence was estimated to be less than five percent of their di et (Hamilton, 1946; Breece and Dusi, 1985; Sikes et al., 1990). Figure 4.6: The nine-banded armadillo ( Dasypus novemcinctus). Photo source: Tom Fiedel, 2008, with permission of free-use. Armadillos are mostly solitary, especially when foraging, but individuals do have overlapping home ranges (Breece and Dusi, 1985; McDonough and Loughry, 1997). Home range size was variable ranging from 1.4 ha (Breec e and Dusi, 1985; Layne and Glover 1997) to a maximum of 13.8 ha (La yne and Glover 1997). Home ranges are reportedly smaller in moist habitats, and indi viduals with overlapp ing home ranges seem to forage in relatively close proximity to each other without signs of antagonism (Layne and Glover, 1997), though indi viduals still remain rela tively asocial (McDonough and Loughry, 1997). In the literature there was insufficient evidence that armadillos have the predisposition to contract their home ra nge size when populati on densities are high, 77

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which m ay be an important factor in ad apting to highly urbanized environments. Opossums. Opossums ( Didelphis virginiana ) of the order Didelphimorphia are the only marsupials found in North America. They are mid-sized marsupials with a prehensile tail that is an adaptation to their semi-arboreal lifestyle (Figure 4.7) (Meier, 1985; Harmon et al., 2005). Opossums are relatively solitary with the exception of family groups of females with young and juvenile offspring (Meier, 1985; Harmon et al., 2005). This species is an opportunistic generalist in its foraging habits, feeding on insects, invertebrates, fruit and other plant material and scavenging vertebrates. Opossums have been documented scavenging pet food, human trash receptacles and road kill (Meier 1985; Harmon et al., 2005). Figure 4.7: Opossum ( Didelphus virginiana). Photo source: Cody Pope, 2007, with permission of free-use. It has been found that opossum home ranges in urban environments are significantly smaller, 0.41 17.61 ha., than home ranges of their rura l counterparts, 7.278

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78 ha (Gillette, 1980; Allen et al, 1985; Harm on e t al., 2005), which confirms that their movement patterns are somewhat flexible in urban environments. Opossums are also somewhat flexible in their daily moveme nt patterns. Urban individuals travel significantly shorter distances on average each night and den site changes are significantly closer together from one day to the next, al though they use a favorite den site forty percent of the time (Allen et al., 1985; Sunquist et al., 1987; Harmon et al., 2005). All in all, the movement patterns involv ed in den site selection and foraging make the urban opossum significantly more sedentary than rural opossums. Raccoons. Raccoons ( Procyon lotor) of the order Carnivora are mid-sized mammalians belonging to the same family, Procyonidae as coatis and kinkajous (Figure 4.8). Raccoons are generalist opportunists when it comes to foraging (Hoffman and Gottschang, 1977; Rosatte et al., 1991). They ha ve been observed in undisturbed habitats foraging on a wide variety of plant and anim al material (Urban, 1970; Rosatte et al., 1991; Pedlar et al., 1997). In suburban and urban environments, r accoons are notorious for breaking into trash receptacles, pet food storage bins, and using other anthropogenic food sources (Rosatte et al., 1991; Prange et al. 2003; Prange et al., 2004; ODonnell and DeNicola, 2006). Female raccoons tend to live longer and have larger litter sizes in urban environments than rural and undisturbed habi tats, thus suggesting that food sources in urban and suburban habitats may be more reli able (Rosatte et al., 1991; Prange et al., 2003; Prange et al., 2004) Females appear to lead a mostly solitary existence but are not territorial, though sometimes females forage in small groups (Pedlar, 1997), while adult 79

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Figure 4.8: A juvenile raccoon ( Procyon lotor) Photo Source: Dmetryo S. (Public domain) free-use permission. males form small bachelor groups that are somewhat territorial (Prange et al., 2004; ODonnell and DeNicola, 2006; Gejrt et al., 2008). The male coalitions are made of two to four adult males that tend to stay t ogether, including denning and foraging, throughout the year (Gejrt et al., 2008) Raccoons live in significantl y higher densities in urban environments than rural (Pedlar et al., 1997; Prange et al. 2003; ODonnell and DeNicola, 2006) and their home range sizes are significantly smaller in urban and suburban areas, 21.4 37.2 ha, than in rural areas 71.2 182.4 ha (Hoffman and Gottschang, 1977; Gejrt and Fritzell, 1997; Pran ge et al., 2004). Eastern Gray Squirrel: The eastern gray squirrel ( Sciurus carolinensis ) of the order rodentia is a medium sized mammal belonging to the Scuridae family along with marmots, chipmunks and prairie dogs (Figure 4.9) (Whittaker and Elma n, 1980). Squirrels are diurnal arboreal rodents that forage mostly for nuts, seeds, acorns, fruits, mushrooms and small eggs under natural conditions (Lewis, 1980; Whitta ker and Elman, 1980; Newman and Caraco, 1987; Spritzer, 2002). Squirrels do engage in opportunistic foraging on occasion 80

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(Spritzer, 2002). I have observed gray squirr els on an urban college cam pus eating out of trash cans, eating potato chips from a discar ded bag, and one squirr el was doing its best to drag a hot dog bun up the side of an oak tree. Figure 4.9: The eastern gray squirrel (Sciurus carolinensis). Photo source: anonymous, permission under free-use license. Squirrels are nonterritorial and hom e ranges do overlap extensively among individuals especially in hi gh density urban populations (Thompson, 1978; Lewis, 1980,). Squirrels use their home range evenly throughout and there is little intraspecific aggression concerning home range use (Lewis, 1980). Home range size is quite variable in the literature. Home range varies from 0.49 ha up to 5.1 ha (Doebel and McGinnes, 1974; Thompson, 1978). Intensive studies of s quirrel social behavi or revealed that squirrels have a social hierarchy system, or pecking order, where age is the dominant factor (Pack et al., 1967; Thompson, 1978; Lewis, 1980; Brown, 1986). I have briefly summarized these behavior patterns for all four species in Table 4.2. Exploiters and adapters According to McDonough and Loughry (2005) armadillos preferred habitat is 81

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hardwood forests despite the fact that they are often found in close proxim ity to humans. According to Layne and Glover (1997), armad illos prefer field-woodland but are also found in open groves and park-like areas with large trees and widely spaced buildings. Table 4.2: A brief summary of behavioral characteris tics that may contribute to success in urban environments. Animal Dietary preferences Social behavior Home range size Other behaviors Armadillo Insects and invertebrates Solitary foragers Overlapping home ranges -Non migratory home range 5.7 +-1.7 ha Naturally prefer forested and semi-open habitat mostly nocturnal but diurnal in winter if needed Prolific rooting & burrowing Opossum Omnivorous (insects, invertebrates, fruit, grains, scavenge) Mostly solitary, except females with young offspring Variable 51-100 ha 22-78 ha 16.3-122 ha Mostly nocturnal, Smaller home range in urban areas. Raccoon Very omnivorous, (Fish, reptiles, insects, eggs, invertebrates, pet food, refuse Some social males form small coalitions and mostly solitary females urban 25.2-52.8 ha Suburban 21.437.2 ha Rural 71.2-182 -Mostly nocturnal nonterritorial females male groups are somewhat territorial Squirrel Seeds, nuts, fruits, berries, fungus, eggs Somewhat social with pecking order 1.5 8 acres with extensive overlap in rural habitats. 0.5 ha average minimum home range. May contract range by 50% at high densities diurnal easily use dew for water source Taken together these armadillo characteristics seem to most closely fit those of an urban adapter rather than expl oiter, as Kark et al., (2006) desc ribed adapters as less social, and more likely to feed on invertebrates than exploiter species. Raccoons, opossums and squirrels, on th e other hand, are all highly omnivorous (Pedlar, et al., 1997; Spritzer, 2002; Prange, et al., 2004), and show some flexibility in the 82

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ability to co ntract home range size in high density environments. Raccoons are somewhat social in urban environments with relate d females foraging in small groups and males forming small bachelor groups (Pedlar et al., 1997; Gehrt et al., 2008). Squirrels are relatively social with extensively overlapping home ranges, and they establish a pecking order within groups (Pack et al., 1967; Thompson, 1978; Lewis, 1980; Brown, 1986). Based upon these characteristics, a flexible omnivorous diet, relative sociality, and flexibility in home range cont raction, these three species s hould be catego rized as urban exploiters. 4.3.3 Index of Relative Abundance in Suburban Remnant Patches Armadillos raccoons, squirrels, and opossums make up the top four conflict prone species across the study ar ea with a combined total se venty percent of all conflict reports. In all three study areas squirrels were ubiquitous, yet seldom visited the track stations set up within remnant patches, thus th ey had to be excluded from the track station analysis. Since rat and mous e traps are easily obtained and many households remove these animals themselves, I removed rats and mice from the track station analysis believing them to be underrepresented in the conflict reports. The relative abundance indices of raccoons, opossums, and armadillos were included in the comparison. A one-way between groups analysis of variance (ANOVA) was conducted to determine if the relative abundance inde x of raccoons, opossums, and armadillos in remnant patches was significantly different among the three suburba n residential areas that were surveyed. I ran one ANOVA for each species to compare the three residential areas: one comparing the raccoon indices, one comparing the opossum indices and one 83

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com paring the armadillo indices. I used Levenes test to ensure that homogeneity of variance assumption was not violated in any test. There were no vi olations detected. There was a statistically si gnificantly difference in rela tive abundance at the p < 0.05 level for all three ANOVA (raccoon indexe s, p = 0.000; opossum indexes, p = 0.032; armadillo indexes, p = 0.004). I also performed Tukeys HSD post hoc test after each ANOVA to determine which groups diffe red from each other (Table 4.3). As seen in Table 4.3, raccoon relative a bundance index was signi ficantly different in remnant patches in all thr ee suburban residential areas (p < 0.00), with residential area FW having the highest mean index. Indices of opossum relative abundance was only different between residential area HI and FW (p = 0.03) and again residential area FW had the highest relative abundance index. Indi ces of armadillo relative abundance was significant between residential areas HG and HI (p = 0.00) an d residential areas FW and HG (p = 0.01) and residential area HG ha d the highest relative abundance index. Table 4.3: Relative abundance index means for raccoons, Op ossums, and Armadillos in each of the three suburban residential areas and the corresponding significance values for between groups differences. denotes significant differences at alpha <0.05. Residential area Raccoon Mean Index Tukey HSD Between groups (significance) Opossum Mean Index Tukey HSD Between groups (significance) Armadillo Mean Index Tukey HSD Between groups (significance) HG 0.1627 HG & HI* (.000) 0.0850 HG & HI (.412) 0.1560 HG & HI* (.004) HI 0.0148 HI & FW* (.000) 0.0462 HI & FW* (.026) 0.0365 HI & FW (.771) FW 0.2868 FW & HG* (.001) 0.1392 FW & HG (.204) 0.0555 FW & HG* (.012) Table 4.3 shows that resi dential area FW had a si gnificantly higher relative abundance index for raccoons than HG and HI residential areas (lowest abundance); 84

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however, there were no conflic t reports concerning raccoons during the study period in the FW residential area while conflict reports were highest for raccoons in the HG residential area, where raccoon abundance was significantly lower. When relative abundance of raccoons was tested for correla tion with conflict reporting of raccoons in the three residential areas, Pearson R = 0.05, a very small correlation result, which was not significant (p = 0.88). This provided evidence that in these three suburban residential areas abundance of raccoons is not correlate d with conflict repor ting of raccoons. The same was found for the other two species. A bundance was not signifi cantly correlated to conflict reporting for armadillos p = 0.46 (R = 0.24) and R could not be calculated for Opossum as there were no conflict reports for that species in any of the areas though abundance was relatively high in the FW resi dential area and moderate in the HI residential area. 4.4 Discussion 4.4.1 Urban Exploiters, Adapters an d Human-Wildlife Conflict It has been shown that biodiversity declines with increasing urbanization (Beatley, 2000; Shochat, 2004; Faeth et al ., 2005; Clergeau et al., 2006; McKinney 2006) and I expected that the species diversity repr esented within conflict reports would reflect this general trend. I did find this hypothesis to be supported as the diversity of species reported was significantly less in urban re sidential areas than in both suburban and exurban residential areas. The species divers ity was the same in conflict reports in suburban and exurban residential areas howev er. Based on my analyses, human-wildlife conflict in urbanized areas also follows the sa me general trend that we see in invasion 85

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biology studies where a few species m anage to dominate in the urban environment leading to a phenomenon known as biotic homogenization (Hobbs and Mooney, 1997; Crooks et al.,2004). Blairs study on avian spec ies (1997) termed th ese species urban exploiters. I proposed that conflict-pr one mammalian species found in the highly urbanized areas of Tampa would have the sa me generalized exploiter characteristics of being more social, more omnivorous, and I a dded that home range size might also play a part. I found the wild species in this st udy that make up a high proportion (seventy percent) of conflict reports did in fact f it with the characteristics described by Blair (1997) and Kark et al., (2006) for sociability and diet and also that they have some flexibility in contracting their home range size in dense environments, though these assessments were based upon literature review and not my own empirical evidence. I determined that raccoons, opossum and squirrels all have a majority of the characteristics for urban exploiters. Kark et al., (2006) proposed that urban ad apters would be species less able to be successful in highly urbanized environments but would be successful in intermediately urbanized environments one finds in the subur bs. They specifically found that the species feeding on invertebrates declined with increas ing urbanization. In the literature review, I found that armadillos are insect and invertebrate feeders and are solitary. I could not find any evidence from the literature that armadillos have the capacity to contract their home range in high densities. I therefore concl uded that armadillos fit into the category of urban adapters. According to Blair (1996), suburban adapters as he called them, would be able to exploit the additional resources, like ornamental vegetation, provided in an intermediately developed suburban and exurba n areas, but not persis t in highly urbanized 86

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areas. In the analysis of conf lict reports across the urban gradient, I found that arm adillos did appear significantly less often in conflict reports in urban residential areas and more often in exurban residential areas as woul d be expected from an urban adapter. There was no significant difference in conflict reporting acro ss the gradient for raccoons, opossums, or squirrels, as would be expected for urban exploiter species that are able to persist th roughout the urban gradient. Being an exploiter does not exclude the species from suburban and exurban environmen ts and I expected the exploiters to be prevalent throughout the urbanization gradient Therefore the hypothesi s that reports of conflict in urban residential ar eas would consist primarily of species with urban exploiter characteristics was supported. The hypothe sis that species wi th urban adapter characteristics, in this case armadillos, would be involved in conflict more often in suburban and exurban residential areas than in urban residential areas was also supported. 4.4.2 Relative Abundance in Remnant Patches and Conflict Reporting I surveyed remnant patches within thr ee suburban residential areas with very similar landscape features (eva luated in chapter three) for relative abundance of wildlife and generated abundance indices for conf lict prone species. The relative abundance indices for raccoons were found to be significantly different in all three suburban residential areas under study. Opossum and armadillo relative abundance was significantly higher in on e of the three residential areas. The higher abundances in certain residential areas did not however correspond with higher conflict reporting in those same residential areas. For instance, raccoon relativ e abundance was highest in the residential area identified as FW, but conflict reporting for that residential area was the lowest for 87

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raccoons. A cross the board, there was no co rrelation between re lative abundance of animals in remnant patches of a residential area and conflict reporting of that animal in that residential area. Therefore, abundance had no statistical eff ect on conflict reporting in the suburban residential areas of Tampa, Florida that were included in this study. The results of the relative abundance anal ysis, leads me back to the hypothesis that human values and perceptions in a residen tial area play a vital ro le in contributing to human-wildlife conflict in all residential areas. This idea is explored in greater detail in Chapter Five. 88

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Chapter Five The Effect of Residents Attitudes toward Wildlife on Human-wildlife Conflict Reporting in Suburban Tampa, Florida 5.1 Introduction Across the globe, many scientists involved in ecological research are in agreement that the natural world is in the midst of the sixth great extinction. Study after study has reported that the rate of extinction today is mu ch higher than the natural rate (Noss et al., 1995; Abell et al., 1999; Lassila, 1999; Beatley, 2000). In fact some estimate the current extinction rate to be as high as one thousand times the natura l rate. This is not just a global problem; it is also an American problem According to the U.S. Fish and Wildlife Service (1999) the three states with the hi ghest numbers of threatened and endangered species are Hawaii (298 species listed), California (260 spec ies listed), and Florida (102 species listed) (Beatley, 2000). No t coincidentally these are al so states that have seen very high population growth in recent year s (Beatley 2000; Beatley, 2002; Berube et al., 2006). Entire ecosystems are at risk largel y because of suburban and exurban growth pressures in Florida, from the unique Florid a scrub ecosystems in central Florida to sea grass meadows on the coasts (Lassila, 1999; Beatley, 2000; Whitney, Means and Rudlow, 2004). While a large number of native species are declining in areas of rapid development and human population growth, certa in species are adapting quite well and, 89

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in fact, causing problem s for some homeowners across the country. These species are certainly not in danger of extinction by any stretch of the imagination, some would call them overabundant. However, since conservatio n policies are formulated only when there is a majority of public support, the effect that backyard conflict can have on personal attitudes toward wildlife and therefore, public will, must not be overlooked. Human-wildlife conflict in urbanizing areas is quite complex. As demonstrated in Chapter Three, certain lands cape factors do contribute to the incidence of conflict. Human population density and the total ar ea of natural habitat patches immediately adjacent to a residential area contributed significantly to conflict in th e residential area. In Chapter Four evidence was provided that while the number of conflict reports was statistically the same across the urbanizati on gradient (urban, suburban, exurban), the diversity of species within the conflict reports was signifi cantly lower in more urban residential areas. The species most often re presented in conflict reports from heavily developed urban areas consisted signifi cantly of species with urban exploiter characteristics. In addition I found that report ing of conflict prone species in a residential area was not correlated with the relative abundance of that species in the residential area. These results related to human-wildlife conflict in the urban environment, but there is still one large piece of the puzzle yet to be inve stigated, the human dimension. This may be the most complex piece of the puzzle, and perhaps the most difficult to unravel. Perhaps the most important part is the attitudes and basic values that residents have concerning wildlife in their residential areas. After all, the residents are the ones who decide whether to spend money to deter wildlife from entering their property or to call a wildlife trapper to remove an animal that they consider to be a pest or a nuisance. 90

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Historically, Americans valued wild life and natural resources for their instrumental, or practical value (Butler et al., 2003). Recent research suggests that American values and attitudes toward w ildlife are changing (Adams et al., 1997; Manfredo et al., 1999; Butler et al., 2003; Layden et al., 2003; J onker et al., 2006). Manfredo et al., (1999) has proposed that public attitudes have become more protectionist and less utilitarian. According to Adams, et al., (1997), wildlife agencies were experiencing an increase in nonconsumptive wi ldlife recreation and Jonker et al., (2006) reported a decrease in the proportion of pe ople participating in traditional hunting and fishing activities. This tre nd is observed in decreasing fishing and hunting license applications (Eisenhauer, 2007). What values and perceptions are involv ed in these decisions? Social norms and personal attitudes predispose an individual to certain behaviors (Fulton et al., 1996; Manfredo et al., 1999; Friedland, 2002; Jonker et al., 2006). Attitudes are more variable than core values, and they change more easily with experience. According to the Theory of Reasoned Action (Ajzen and Fishbein, 1980), an individuals voluntary behavior is predicted by his/her attitude toward that be havior and how he/she thinks other people would view him/her if they performed the behavior. Applying th is theory, one would expect a suburban resident to decide how he/she feels about an armadillo digging up his/her flower bed according to the social norm of his/her peers and/or neighbors combined with their personal attitude toward wild animals. In Chapter Four I painted a portrait of a conflict-prone sp ecies, the urban exploiter across the gradient and the urban adapters in th e suburbs. Can a portrait of a conflic t-prone resident be painted? In some residential areas, many residents experi ence the same types of interactions with 91

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wildlife on their property, yet som e residents perceive it as a problem and some do not. A suite of attitude variables c ould be assessed by comparing th e attitudes of residents who report conflict after having expe rienced wildlife interactions on their property, and those residents who dont report conflict after having the same type of experience. This phase of the study attempted to identify differences in attitudes toward wildlife among suburban residents in Hillsborough and Pasco counties, Florida and to determine how these attitudes are related to conflict reporting in suburban residential areas. At the onset of this study I hypothesized that: 1) Exurban residents would be more tole rant of wildlife than suburban and urban residents as measured by conflict reports. 2) The number of conflict reports would be highly correlated across the urbanization gradient with property damage and/or money spent to deter and/or remove animals. 3) There would be a strong correlation be tween personal wildlife values and conflict reporting among residents. 5.2 Methods 5.2.1 Introduction In order to assess tolerance for w ildlife among urban, suburban, and exurban residents, I compared the spatial incidence of conflict reports, described in Chapter Three, for 32 residential areas representing each of the develo pment classifications, urban, suburban, and exurban/rural. From those residential areas three suburban residential areas were selected in which to conduct door to door su rveys of residents in order to determine their attitudes toward w ildlife. I then examined the relationships 92

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between residents attitudes, experience and expenditures involving wildlife and the incidence of hum an-wild life conflict reporting. 5.2.2 Study Area I surveyed residents of three residential areas that were a sub-sample of the 32 residential areas analyzed for human-wildlife conf lict in north Hillsborough and south Pasco counties (Figure 5.1). These reside ntial areas were part of the previous study of the effect of landscape variables on hu man-wildlife conflic t (Chapter Three). For this study, a residential area was operationally defined as a distinct, relatively homogeneous, human residential matrix that was bounded by eith er water bodies, perimeter forests that extended beyond the residential area, or other phys ical structures or behaviorally isolating structures that would impede or prevent mid-sized conflict prone species from crossing. Physical structures included walls or solid fences. The perimeter forests were also referred to as adjacent exterior habitat patches. Be haviorally isolating structures included interstates, four lane highways, and wi de two lane highways that extend beyond the residential area, as these stre ets would have higher traffic volume than residential area streets. The higher trafficked streets and highways hinder many individual animals from crossing, and is more of a boundary deterrent than the narrow residential development streets within the residential area. The level of conflict for each residential area was based on conflict reports voluntarily obtained from wildlife trappers licensed by the Florida Fish and Wildlife Conservation Commissi on (FFWCC) during the period of June 2007 through December 2008 (Figure 5.1). After anal yzing the 32 residential areas to compare conflict I found there was no difference in conf lict reporting across the gradient. Thus I 93

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decided to focus resident surveys on specific re sidentia l areas that had high conflict, low conflict, and zero conflict. The surveys of attitudes toward wildlife were conducted in three suburban residential areas. The three residential areas were selected specifically because the landscape variables that were significant to conflict reporting (population density and area of adjacent remnant habitat) for all three residential areas were the most closely matched of the residential areas incl uded in the study, within one to two standard deviations of each other, so as to control for as many significant va riables not related to human values as possible. Human p opulation density ranged from 232.2 and 307.72 residents per square kilometer for all three re sidential areas with tw o standard deviations of 88.6 (601.4 and 797.0 per square mile, two s .d. = 229.4) and the total area of habitat remnants immediately adjacent to the residential areas were 71.55 km2 for two of the residential areas, and 53.24 km2 for the other residential area, all within one standard deviation of each other (1 s.d. = 29.05). All three residential areas were adjacent to relatively large natural areas that had exte nded corridors that c onnected with other forested habitat as well. Relative abundance of mammalian species within remnant fragments was significantly different, but this was found to have no correlation with human-wildlife conflict within the residentia l areas (Chapter Four). However, conflict reporting among the three residential areas was significan tly different. 5.2.3 Survey of Human Attitude Towards Wi ldlife in Suburban Residential areas To measure the attitudes that residents had toward wildlife, I conducted surveys. These surveys were conducted in person, door to door, at randomly selected homes within each residential area. Homes were rando mly selected by alterna ting turning left or 94

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5 miHillsborough CountyPascoCounty Pinellas County Tampa Figure 5.1: The study areas in the Tampa, Florid a region. Red diamonds represent the residential areas included in the home owner surveys. Black dots are individual conflict events from randomly selected zip codes throughout the study area. The yellow circle is downtown Tampa. (map source: Google Earth). right at each block intersection and I then surveyed every other house. The survey packets contained a cover letter a nd the questionnaire (Appendix A). In order to ensure that the person res ponding to the survey was the person making the decisions about actions take n for or against wildlife, I asked that the interview be completed by a person who was at least 18 ye ars old and who was most responsible for property landscape and/or pest control. I read the cover letter to each participant but I did not record any personally identifiable inform ation other than the st reet and block number of the residence. The survey questions focused on: 1) basi c attitudes toward and value of wildlife 95

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of the interviewee; 2) frequenc y of interviewees c onflict with wild anim als; 3) amount of money spent to either attract or repel wild animals, and 4) frequency of conflict reported to an agency or animal re moval business (Table 5.1). General information about the interviewees age, gender and education level was collected as well as number of pets, number of children, age of the youngest child living at the residence, highest level of education in the household, and the type of re sidential area in which the participant spent his or her childhood. The socio-economic status of residents was inferred by examining the mean market value assesse d by the county appraisers office for all homes located on the streets that were included in the survey. In the current economy and real estate market these home values may be considered unusually low, however, it remains a viable comparison between the residential areas as the change in home values have some consistency throughout the Tampa area. Questions related to attitudes toward wildlife and observations of wildlife were closed ended, partially agree/di sagree questions and partially based on a five point Likert scale ranging from one to five. Respondents were asked to agree or disagree with statements of wildlife values best f itting their feelings towards wildlife. Measurement of human attitudes toward a nd perceptions of wildlife can be very complex, with a range that flows from the active avoidance of animals because of fear to the actual worship of nature and wildlife (Kellert and Be rry, 1980; Kellert, 1991). Kellert and Clark (1991) grouped all of these perceptions and attitudes into twelve basic attitude types or personal values toward wildlife. Definitions for these twelve values are displayed in Table 5.2. Kellert and Clark (1991) defined twelve values, but I combined utilitarian consumption, utilitarian habitat, and dominionistic into one category that will 96

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be called utilitarian. Fo r the purposes of this study th e combined utilitarian value category was adequate to describe the perception Table 5.1: Homeowner survey questions regarding personal information, expenditures, and attitudes. Homeowner Survey questions Possible responses Are you the homeowner at this address? Yes No Do you have one or more pets? Yes No What is the number of children in the household? 0 1-2 3-4 >4 How would you categorize the place where you grew up? Urban (city) suburban exurban rural dont know How would you categorize the place where you live now? Urban suburban exurban rural dont know What is the range of household annual income? (Optional) less than $25,000 $25,000 $44,999 $45,000 $65,000 over $65,000 What is the highest level of education in your household? High School Diploma Associate degree Bachelors degree Masters degree Doctorate Professional cert. Overall I enjoy the presence of wild animals on my property. Strongly agree agree neutral disagree strongly disagree Overall I do not enjoy the presence of wild animals on my property. Strongly agree agree neutral disagree strongly disagree I enjoy the natural areas in my neighborhood. Strongly agree agree neutral disagree strongly disagree I enjoy seeing wild animals in and near the natural areas in my neighborhood. Strongly agree agree neutral disagree strongly disagree Over the last 12 months how much money have you spent to attract wildlife to your property? $0 $1 $25 $26 $50 $51$100 over $100 Over the past 12 months how much money have you spent to repel wildlife from your property or to repair damage to your personal property? $0 $1 $25 $26 $50 $51$100 over $100 Over the past 12 months how often have you tried to rid your property of the presence of wildlife? about 1 time each week about 1 time each month about 1 time every 6 months about 1 time each year never Please check which of the following best describes your feelings towards wildlife (or respond agree or disagree). I have a strong interest and affection for all wildlife and the outdoors. I have a strong concern for the well-being of the environment and natural habitats. I have a strong interest and affection for only certain types of animals or pets. I have concern for the treatment of animals and a strong ethical opposition to cruelty towards animals My primary interest is in the physical attributes and biological functioning of animals. My primary interest is in the beauty of certain animals and their characteristics. My primary interest is in fishing and hunting of wild animals I actively avoid wild animals if possible. I am not interested in wild animals. 97

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of wildlife in terms of practical value or usefulness to humans. In this study, I used these nine defin itions to categorize the values of people surveyed in suburban residential areas. I comp ared the average values of the residents in each of the three residential areas to try to detect an overall differe nce at the residential area level. I also compared individual values of personal conflict in all three suburban residential areas combined with personal valu es toward wildlife to detect differences on an individual level. Table 5.2: Definitions of basic attitude types as categorized in the survey of suburban residents. (Original Terms and descriptions of types taken from Kellert and Clark, 1991.) Attitude Type Definition Naturalistic The resident agrees that he/she has a st rong interest and affection for all wildlife and the outdoors. Ecologistic The resident agrees that he/she has a strong concern for the well-being of the environment and natural habitats. Humanistic The resident agrees that he/she has a strong interest and affection for only certain species of animals or pets. Moralistic The resident agrees that he/she has a co ncern for the treatment of animals and a strong ethical opposition to cruelty towards animals. Scientistic The resident agrees that their primary inte rest is in the physical attributes and biological functioning of animals and their pl ace in the environment. Aesthetic The resident agrees that their primary inte rest is in the beauty of certain animals and their characteristics. Utilitarian The resident agrees that their primary interest is in fishing and hunting of wild animals. Negativistic The resident agrees that he/she actively avoids wild animals if possible. Neutralistic The resident agrees that he/she has no interest in wild animals. 5.2.4 Survey Analyses Personal information like respondents ag e range category, average real estate 98

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value, num ber of children, ages of youngest ch ild, educational background, basic wildlife value category, and classification of devel opment level where person spent majority of childhood were averaged for each resident ial area and compared using ANOVA. All significant differences in personal information between residential areas were then cross referenced with the frequency of conflic t reporting in those residential areas. Answers to survey questions related to basic attitude type were scored with a participants response of agree coded as one neutral coded as 0.5, and disagree coded as zero. The total score for each of the attitude types (Table 5.2) was divided by the number of respondents who participated in the survey for each residential area, giving an index mean value for each attitude type in that residential area. The index mean value (an indication of agreement with an attitude type) for each attitude type within each residential area was analyzed using ANOVA to de termine differences in attitude averages for each residential area with alpha level set at 0.05. All significant differences in residents attitudes from one residential area to another were then cross referenced with the level of conflict in each residential area. Responses to questions that were base d on a five point Like rt scale regarding enjoyment of natural areas and wildlife were condensed into three an swer scores, agree, neutral or disagree (coded as one, 0.5 and zero respectivel y), and then scores were averaged for each residential area. The aver age scores for each residential area (with high, low, and zero conflict reporting) we re analyzed using ANOVA. The range of money spent to attract wildlif e to the property and to repe l wildlife from the property were analyzed for distribution differences among the three residen tial areas using the Kruskal-Wallis test with alpha level set at 0.05. 99

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I tested for a correlation between reside nts who have experienced problems with wildlife and their attitude type regarding w ildlife. To do this, surveys from all three residential areas were divided into two groups. Group one consisted of residents who answered that in the past twelve months they had removed a wild animal from their property or had spent money to repair damage to their property cau sed by wildlife. Group two consisted of all residents who had not had the problems expressed by group one. I used independent samples t test to test fo r differences between the two groups and the percentage of each group belonging to each attitude type. In other words, I tested to see if there was a difference in the percentage of the positive conflict group (group one) that agreed to naturalistic attitudes versus the percentage of th e no conflict group (group two) who agreed to a naturalistic attitude. I also checked for correlations between the negative experiences (group one) or neut ral/positive (group two) experience with wildlife and positive answers to enjoyment of animals and nature questions. Some of the official conf lict reports (private company data) had inferences to the attitude toward the offending animal of the person filing the complaint about wildlife damage. Unfortunately, the desc riptions were not detailed enough to be included in the analysis. 5.3 Results 5.3.1 Conflict Across the Urbanization Gradient and Tolerance Originally I proposed that exurban residents would be more tolerant of wildlife than suburban residents as measured by conf lict reports obtained fr om licensed wildlife trappers. After analyzing conflict reports at al l three development levels, I concluded that 100

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there was no significant difference among aver age conflict reporting at any of the three developm ent levels; urban, suburban, or exurban (mean was 1.2, 0.80, and 0.60 respectively; F = 0.88 and p = 0.42). Therefor e, based upon conflict reports provided by the wildlife trappers participating in this study, average tolerance for wildlife was the same in all development levels. Based upon the fact that c onflict reporting was the same at all three development levels, I chose to find closely matched re sidential areas in terms of the physical landscape, within the suburban areas that had dissimilar conf lict levels for comparison of human attitudes toward wildlife. The three re sidential areas included in the analysis will be referred to as HC for the high conflict residential area, LC for the low conflict residential area and ZC for the residential ar ea with zero conflict. The three residential areas had conflict reporting densities of 0.93 reports/km2, 0.25 reports/km2, and 0.0 reports/km2 respectively. 5.3.2 Survey Participant Demographics and Conflict The door to door surveys resulted in th e participation of 82 suburban households out of 182 attempts, giving a response rate of 45.05 percent. Residential area HC, LC and ZC had response rates of 48.9, 47.9, and 39.1 per cent respectively. Su rvey participant demographics for each residential area are shown in Table 5.3. There were some significant differences in the development le vel in which the homeowners grew up, the highest level of education within th e household, and the average house value. The surveyed sample of residential area HC had significantly lower education levels than the surveyed sample of resi dential area LC and ZC (p = 0.08, and p = 0.09 respectively). 101

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Table 5.3: The Demographic averages of residents who completed the survey in each residential area. Households with children (Percentage) Households with pets (Percentage) Highest Education Level in household (Percentage) Average House value (in thousand) {median/range} Grew up urban (%) Survey site High School B.S. B.A. M.S M.A. M.D. Ph.D. HC (n=23) 61 70 35 48 17 0 174.3 {164/ 80} 44 LC (n=34) 68 74 11 60 18 11 203.9 {196, 81} 18 ZC (n=25) 60 100 8 60 28 4 190.0 {171.5/ 125} 8 Denotes statistical significance, p < 0.10. The surveyed sample of residential ar ea HC also had a higher percentage of residents who grew up in an urban residential area than residential area ZC (p = 0.07), but HC was only significantly different from residential ar ea LC at p = 0.22, which was outside the acceptable level of significance fo r this study. The sample area of residential area HC had significantly lower home values than residential area LC (p = 0.02). 5.3.3 Attitude Types and Residential Area Average Expenditures Residents were asked questions related to enjoyment of nature and wildlife. The responses from each residential area are summar ized in Table 5.4. The responses to these questions showed some vari ability among residential areas but differences were not significant at the 0.05 alpha level. I found that with surveys of all th ree residential areas combined, ninety percent of residents held fa vorable attitudes toward wildlife and natural areas within their residentia l areas while 97.6 percent of residents were favorable or neutral. These percentages are based on the su rvey responses to the questions given in Table 5.4. Based upon results of a Kruskal-Wallis test, there was no significant difference 102

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am ong the three residential areas in the distribut ion of the range of m oney spent either to attract wildlife or to deter/repel wildlife p = 0.72, and p = 0.10 respectively at 0.05 alpha level (Table 5.5). Also there was no differen ce between residential areas in the average amount of money spent to repair damage done to their property by wildlife. In combining the survey data from all three re sidential areas, I found that 34 percent of residents expressed spending mone y in the last twelve months to either repel or remove wildlife from their property or to repair damage to their property. Table 5.4: A summary of responses concerning the enjoym ent of nature and wildlife in residents neighborhood. Variables were coded on a 5 point scale of strongly agree (1), neutral (3), and strongly disagree (5). In this table strongly agree and agree were collapsed and reported as agree, strongly disagree and disagree were collapsed and reported as disagree. Area HC Area LC Area ZC Survey statement Agree % Neutral % Disagree % Agree % Neutral % Disagree % Agree % Neutral % Disagree % Overall I enjoy the presence of wild animals on my property. 74% 17% 8% 82% 12% 6% 80% 16% 4% Overall I enjoy the natural areas of my neighborhood. 100% _ 100% _ 100% _ I enjoy seeing wild animals in and near the natural areas of my neighborhood. 78% 21% 91% 6% 3% 96% 4% Table 5.5: Expenditures related to wildlife in thre e suburban residential survey sites. Range of money spent to attract wildlife (Percentage per category) Range of money spent to repel or deter wildlife (Percentage per category) Number of times tried to rid property of wildlife (annually) (Percentage per category) Survey Site $0 $1$25 $26$50 $51 $100 > $100 $0 $1$25 $26$50 $51 $100 > $100 Once /wk Once /mo Twice /year never HC 56 26 13 4 0 91 4 4 0 0 0 0 17 83 LC 53 14 20 5 5 82 5 3 6 3 0 3 35 62 ZC 60 20 8 4 8 64 68 8 0 0 0 8 12 80 103

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The responses to questions related to basic attitude t ypes given in Table 5.1, were averaged for each residential area and ANO VA was used to determine if there were differences between the three residential areas. Table 5.6 shows the percentage of residents surveyed that agreed that their ow n feelings matched with the definitions of these attitudes. There were many overlaps as some residents felt their feelings matched several attitudes and they did not feel the need to choose only one. The only attitude type that showed a significant difference in pe rcentage of attitude type among the three residential areas was Utilitarian. Residentia l areas HC and ZC had significantly higher proportions of the residents that agreed with the statement My primary interest is in hunting and fishing of wild animals, than residential area LC (means were 0.30, 0.36, and 0.06 respectively; p = 0.01). The vast majori ty of the residents who agreed with the utilitarian attitude type were fishermen (85 percent). Table 5.6: Percentage of residents surveyed in each residential area that matched attitude type definitions. Residential area and percentage of each attitude type Attitude Type HC LC ZC Naturalistic 91 91 88 Ecologistic 96 88 96 Humanistic 35 35 40 Moralistic 100 85 92 Scientistic 65 56 60 Aesthetic 61 62 56 Utilitarian* 30 6* 36 Negativistic 52 50 32 Neutralistic 22 12 24 *Showed a significant difference between residential areas (p = 0.01). 104

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5.3.4 Attitudes Toward Wildlife and Pe rsonal E xperiences and Expenditures Overall averages of attitudes showed very little difference when examined at the residential area level. When examined at th e level of individual residents however, a different picture emerges. I combined data from all three residentia l areas and created two categories of residents. Group one consisted of those who spent money to repel animals from their property, or to repair damage to their property, or took action to rid their property of a wild animal in the past 12 m onths. This group consisted of 34 percent of those interviewed. Group two consisted of t hose residents who had spent no money to repel or remove wildlife or repair damage to property. Group one was labeled positive for personal conflict. Group tw o was labeled no conflict. I used independent sample t tests to test for differences between the two groups (positive conflict vs. no conflict) and the percentage of resi dents in each attitude type category separately (ie nine sepa rate attitude types, nine sepa rate t tests). For example, of all residents who belonged to the conflict group (group one), I found 83% agreed with the naturalistic attitude and of all residents belonging to the no conflict group, I found that 94% agreed with the naturalist ic attitude type. I then te sted to see if there was a significant difference in the percentage of each group with naturalistic attitudes. I repeated this procedure with all attitude types and found signi ficant differences for two of the nine attitude types; ec ologistic and moralistic (Table 5.7). I performed Pearson correlations to detect relationships betw een the group who experienced conflict and enjoyment of nature and wild life and between th group who experienced co nflict and the basic attitude types. Several significant findings em erged. First, positive personal conflict 105

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Table 5.7: Results of t tests for averages of attitude types am ong residents who perceived conflict and those who did not. Attitude type & group Mean Std. Deviation t Statistic Significance Naturalistic Perceived conflict No conflict 0.83 0.94 0.384 0.233 1.48 P = 0.147 Ecologistic* Perceived conflict No conflict 0.83 0.98 0.384 0.147 2.08 P = 0.046* Humanistic Perceived conflict No conflict 0.45 0.32 0.506 0.471 1.14 P = 0.257 Moralistic* Perceived conflict No conflict 0.76 1.0 0.435 0.0 2.985 P = 0.006* Scientistic Perceived conflict No conflict 0.59 0.60 0.501 0.494 0.153 P = 0.879 Aesthetic Perceived conflict No conflict 0.52 0.64 0.509 0.484 1.09 P = 0.278 Utilitarian Perceived conflict No conflict 0.17 0.25 0.384 0.434 0.756 P = 0.452 Negativistic Perceived conflict No conflict 0.45 0.45 0.506 0.503 0.039 P = 0.969 Neutralistic Perceived conflict No conflict 0.24 0.15 0.435 0.361 1.01 P = 0.317 significant at alpha level = 0.05 or less. had a relatively strong negative correlation w ith the statement I enjoy the presence of wild animals on my property, (r = -0.472, p =0.001). Personal conflict also had a moderately strong negative correlation with th e statement I enjoy seeing wild animals in and near the natural areas of my nei ghborhood, r = -0.246 (p = 0.01). Second, positive personal conflict was negatively correlated wi th two attitude types, ecologistic and moralistic. The ecologistic attitude type was defined as having a strong concern for the environment and natural habitats. Personal conf lict was moderately negatively correlated 106

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with the ecologistic type, r = -0.282 (p = 0.01). Personal conflict was m ore strongly negatively correlated with the moralistic attitude type, r = -0 .413 (p = 0.001). The moralistic attitude type was defined as I have a concern for the treatment of animals and a strong ethical opposition to cruelty to animals. 5.4 Discussion 5.4.1 Introduction Human attitudes towards wildlife have gone through many changes throughout history. Early in our history, animals served as food or predator (Aiello and Wheeler, 1995; Turner and Anton, 1997; Stiner, 2002; Toussaint et al., 2003;), and were also our competitors for food and resources. Over time, th anks to our larger brains diet (Aiello and Wheeler, 1995; Stiner, 2002), competition fo r food and resources was greatly reduced and humans expanded their range across the glob e. Our natural predators were extirpated in and around large human settlements and with reduced threats our population began to grow exponentially (Brain, 1981). Nonexistant populations of top predators have caused mesopredator release and some of these highl y opportunistic species have come to the forefront of human-wildlife conflict in urbanized areas. The nuances of our relationships with animals have changed th rough the centuries, but the pr imary themes of predation and competition remain, though now we refer to our competitors as pests and nuisance animals. The relatively recent development of w ildlife conservation involves a complex relationship that is contrary to our anti-pr edator, anti-competitor instincts which may be the reason why it is sometimes quite controve rsial. In a democracy, peoples attitudes 107

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toward wild anim als and conservation are very important to the future of conservation policy. Education about the importance of anim als in all areas from microhabitats to major ecosystems is a cornerstone for successful conservation policy. Relying on instinct alone, people do not welcome animals like snakes, spiders and bobcats because our evolutionary history has program med us to fear these creatures. Our instincts lead us to decisions and actions of the pest management approach not a wildlife conservation approach. These animals do, however take a vital role in ecosystem balance across the globe and without these fearsome creatures ecosystems would be overrun with herbivore species and the base of the food chain woul d be decimated. This perspective can be gained only through education in ecology and ecosystem science. At the beginning of this study I predicte d that exurban reside nts would be more tolerant of wildlife than suburban and urba n residents as measured by conflict reporting. As it turned out, there were no statistical diffe rences in the inciden ce of conflict reports across the urban gradient. Therefore I inferred that tolerance of wildlife must also be similar across the gradient, as residents intoleran ce of wild animals should be reflected by the number of conflict reports. 5.4.2 Personal Attitudes and Decisions Concerning Pests In this investigation of human attitudes toward wildlife, I focused on three suburban residential areas and found that 97.6 pe rcent of those interviewed had favorable attitudes toward wildlife, even though 34 pe rcent of the residents proclaimed some conflict ranging from mild, shooi ng away an armadillo from my flower bed, to conflict leading to more severe actions, like poisoni ng animals. Of the nine attitude types I 108

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considered all but utilitarian, negativistic and neutralistic to be favorable. I considered utilita rian to be a neutral category as it is indicative that a person values the practical usefulness of animals which is not necessarily negative. I considered negativistic also a neutral category as it involve d describing oneself as activel y avoiding wild animals and neutralistic was simply stated as not interested in animals. I found that the sample of residents surveyed in the residential area with the highest human-wildlife conflict density was also the reside ntial area sample with significantly less educated re sidents, lower home values, and a higher percentage of residents who grew up in urban residentia l areas. This was the demographic of the subsection of the residential area that I randomly surveyed. I think lower home value in the surveyed section is an indicator of owner socioeconomic status and is most likely an artifact resulting from lower education levels and not related to conflict directl y. I believe that education leve ls and experience with animals while growing up however are indicative of how important education in ecology or environmental science and/or experience with wild animals can be in understanding other species niches in our world and their c ontribution. For instance non-poisonous snakes make up the majority of species in the re sidential areas under study and are vitally important in controlling rodent populations. A legitimate fear of poisonous snakes does not need to be applied to all snakes occu rring in the neighborhood, especially since the poisonous snakes that we should be wary of are easily identified. Understanding may lead to less conflict and greater tolerance. Along these lines, I also found that among those surveyed, the residents who had experienced personal conflict (spent money to re pel or rid their proper ty of wildlife) were 109

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less likely to have an ecol ogistic (concern for the envir onm ent and natural habitats) attitude type or a moralistic (concern for treatment of an imals and opposed to animal cruelty) attitude type as these were negatively correlate d with personal co nflict. Again, I believe this supports the idea that reside nts with a better understanding of ecology and animal behavior may be less likely to spend money to repel or remove animals from their property. The knowledge may make them more tolerant. The negative correlation of personal conflict and eco logistic and moralistic attitude types does provide some evidence to support my hypothesis that there was a strong correlation between persona l wildlife values and the in cidence of conflict. I also discovered that enjoyment of the presence of wild animals on ones property was negatively correlated with the personal c onflict. I think both th ese results can be interpreted as unfortunate in that it is qu ite possible that the perceived conflict may be changing the residents attitude toward wildlife and enjoymen t of wildlife instead of a preset attitude causing the resident to perc eive and or report a conflict. These are negatively correlated relationships and there is really no way to tell which came first the attitude or the conflict without more in depth interviews. In a Massachusettes study of human-beaver conflict, Jonker et al., (2006) found similar re sults. They concluded that survey respondents who experienced beaver-related problems had negative or less favorable attitudes toward beaver than peopl e who did not have problems. Either way, I believe that educating resident s is the key. Perhaps the atti tude can be changed through environmental education or perhaps the conf lict can be reduced by educating residents about tightly securing garbage can lids and ot her practical steps to deter conflict prone species. 110

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In addition, surveyed residents were aske d if they would like to m ake comments at the end of the survey. The majority of co mments, 64 percent, that residents gave were related to why they felt the need to spend m oney to repel or remove wildlife. Comments most often included comments to give an ex planation that the animal (opossum) was wrecking my flower bed, and I killed an armadillo that was a pestnot anymore and snakes scare me and I worry they will bi te. These comments also support my conclusion that some form of ecological educ ation might relieve a portion of conflict in suburbia. The trend of less education and lower home values being positively correlated with personal conflict becomes illuminated only through personal interviews as these conflicts were mostly (93 percent) unrepor ted to wildlife trappers and were handled directly by the homeowner. A ll but two of the conflicts revealed through the surveys were handled directly by the homeowner and not referred to a trapper. One reason these residents did not obtain trappe r services may be due to the cost involved. Since these residents did live in a subsection of the re sidential area with lower house values, money may have been an issue where it may not have been an issue for residents with higher income levels (and more expensive homes). I believe the decision to have a trapper handle a wild animal problem may be cost prohibitive for many families as a typical full time trapper charges $100-$200 per trip or more if repairs are needed. Based upon the results of the resident surveys ecological and environmental education appears to be important. One w ould hope that by educating residents about animal behavior and wild species place in th e environment we can improve perspectives and attitudes toward wildlife and reduce conflict with wild animals to a certain degree. 111

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Chapter Six A Model of Human-Wildlife Conflict Includi n g Landscape, Ecological, and Social Factors 6.1 Introduction In Chapter Three, I discussed landscape factors that were th e most significant in reported conflict: the area of adjacent hab itat patches and the human population density. In Chapter Four, I determined that ther e was no significant correlation between the relative abundance of wildlife within the habi tat fragments of a residential area and the conflict reported to wildlife trappers in that residential area. The types of animals present in the residential area were shown to be significant. Across the urban gradient animals with the characteristics of omnivory, socialit y, and some flexibility in the home range size were the ones who contributed most to c onflict reports in urba n and suburban areas. These findings agreed with the studies done in other urban areas with avian species (Blair, 1996; Kark et al., 2006). These conflict prone species seem to have been tailor made to exploit the resources provided by the human built environment and way of life. Opossum, squirrels, raccoons, and armadillos ar e but a few species that were predisposed to certain behavior patterns that allowed successful coexistence with people, albeit in the shadows and preferably at a distance. Sometim es that distance is not far enough to avoid conflict with humans. The study of human attitudes toward wildlif e, presented in Chapter Five, revealed 112

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that m ost suburban residents have a positive attitude toward wild animals in their residential area, but there was some conflict. Of those surveyed, about 34 percent of residents reported some conflict and those residents had a significantly lower proportion of positive attitude types. 6.2 Methods 6.2.1 Introduction In order to get a more complete pict ure of the relationships of landscape, ecological and social variables with the incidence of human-wildlife conflict, I combined the most significant variables from the landscape study discussed in Chapter Three, the ecological study discussed in Chapter Four, and the study of human attitudes discussed in Chapter Five, in order to formulate a mode l of human-wildlife conflict across the urban gradient of Tampa, Florida. 6.2.2 Study Area The study area ranged from central downtown Tampa, Hillsborough County, Florida, to north of the c ounty line into the southern por tion of Pasco County (Figure 6.1). The region is composed of different leve ls of development with the highest density of development at the urban center and decreasing developm ent with distance from the city center. This pattern pr ovided an urban development gradient where the highest density of human residents and older resident ial areas are close to the city center and newer, less densely developed resi dential areas are farther away. The urban areas included in the study area were residential with human 113

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population densities rangi ng from 1,000 residents/mi2 to 5,047.4 residents/mi2 (United States Census Bureau, 2009) with the major ity of the highest density urban residential areas having very little or no natural areas or public greenspaces. Suburban residential areas included in the st udy area had human population densities ranging from 601.4 residents/mi2 to 826.7 residents/mi2. Many suburban residential areas had public greenspaces such as parks and golf courses as well as fragmented habitat patches. Exurban/rural residential areas included in the study area had human population densities ranging from 208.2 residents/mi2 to 407.1 residents/mi2. Exurban/rural re sidential areas had some public greenspaces in the form of small parks and few had golf courses and generally had relatively large areas of fragmented habitat patches a nd agricultural land. Except for the urban residential areas clos est to the city center, most residential areas had seasonally ponded wetland areas, permanent wetlands, and retention ponds which corresponded to most, if not all in so me cases, of the habitat fragments left standing in the area. 6.2.3 Pulling Together the Major Contributors to Human Wildlife Conflict Reporting The regression modeling procedure of Chapter Three revealed the two most significant landscape predictors of conflict were the human population density and the total area of habitat immediately adjacent to the residential area. The most significant predictor of conflict in the ecological study was the type of animals in the residential area. The most significant pr edictors related to the human dimension were house values, education level, and percentage of resident s who have non-ecologistic or non-moralistic attitudes toward wildlife in their residential area. 114

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! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ( Hillsborough County Pasco County Figure 6.1: Map of the study areas in the Tampa, Florida region. Gray dots represent the residential areas included in data collection for the regression model. Downtown Tampa is marked with a white circle. From the previous studies, the independent variables that were significant to the incidence of conflict were ente red in as data to build the regression model with conflict reporting density (total conflict reports in th e residential area divi ded by the size of the residential area) as the depe ndent variable. The values fo r the independent variables within each of the 32 residential areas we re analyzed using PASW 18.0 software. The landscape measurements of adjacent habita ts and population densities were already known from analysis in Chapter Three. The pr esence or absence of an imal species fitting urban exploiter and urban adapter characteri stics in each residential area was evaluated 01020 5KilometersNeighborhood sites in the Study AreaPinellas County Manatee CountyTampa A. H. Gilleland 2010 115

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using species diversity infor mation obtaine d within the conflict reports from each residential area. The species diversity list in each residential area was cross referenced with the top four conflict prone species for the Tampa area. These species were armadillos, opossums, raccoons, and squirrels. The presence or absence of each of these species was indicated in the data by a one or zero respectively. From the significant variables of the human dimension study, house values were estimated based on the average of the asking prices of the houses for sale within the residential area. Education levels were obtai ned from the U.S. census 2000 reports for the zip code in which the residential area exists The parameter was coded as the percentage (in decimal form) of residents w ith a BA/BS degree or higher. I created an index of residents attitu des to represent human attitudes towards wildlife in the model. The proportion of th e suburban residents that had less positive attitudes toward wildlife (34 percent) was also the group th at included the residents who reported conflict in the door to door surveys. Seventeen percent of the thirty four percent of residents that reported nega tive attitudes also reported that they spent money to deter, or remove wildlife from their property, t hus 5.78 percent of suburba n residents reported conflict with wildlife. The index calculation was base d upon the estimate of 5.78 percent of the population density for each residential area as having negative attitudes toward wildlife. Obviously, this pa rameter would have to be estimated for each region as attitudes toward wildlife are not the same and shifts in th e proportion of negative attitudes would be expected. To build the model, first I used Pearson correlations to detect bivariate correlations between the independent variab les in order to reduce multicollinearity. 116

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Whenever bivariate correlations between i ndependent variables greater than 0.7 were detec ted, I eliminated the variable that had the lowest correlation value with the dependent variable (Pallant, 2007). Strengt h of correlation between each independent variable and incidence of wildlife conflict was defined and the variable s with correlations greater than 0.25 were used in the first standard linear regression. I ran a standard linear regression analysis to determine which of the variables contributed most to the model of conflict. Using the result of the standard re gression, I chose the variables with correlation values greater than 0.25 and parameter coeffi cients with significan ce less than 0.25. After removing the independent variables that did not fit these criteria, a first order linear regression was calculated. I ev aluated the model based upon R square value, significance of the model ANOVA, variance inflation factor, and tolerance. I checked for outliers by evaluating Mahalanobis distan ce and maximum Cooks distan ce. I also inspected the normal probability plot of the regression standardized residuals to ensure normality assumptions were not violated. 6.2.4 Cross Validation of the Model for Prediction During data collection, I marked off approxi mately half the resi dential areas in the study area and saved them as a validation se t. After the most parsimonious model was defined, I translated the prediction equation and applied it to the validation set. The purpose of this technique was to determine if the prediction equa tion resulting from the regression model was reliable for prediction of the incidence of human-wildlife conflict in other residential areas acro ss the urban gradient. Once the predicted values of conflict were obtained from the results of the pred iction equation, I used R square prediction 117

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m ethod of validation (Mendenha ll and Sincich, 2003). The acceptable range of R square difference was set at 0.10. 6.3 Results 6.3.1 The Model of Human-Wildlife C onflict at the Residential Level At the residential area level, seven variables significantly distinguished conflict reporting density in univariate tests. Human population de nsity was significant until I added in the attitude index toward w ildlife. The two variables showed some multicollinearity as population density was part of the equation for calculating the parameter value for the index of negative attitudes toward wildlife. Thus, human population density was combined with attitude proportion in an indirect way. In order to avoid multicollinearity problems, population dens ity of the residential area was removed as a separate variable. The other variables that were found to be significant were total area of adjacent habitats, education leve l of the residents, house values, presence or absence of opossum, raccoons, and squirrels (Table 6.1).The most parsimonious model is shown in the following equation: E(y) = -0.756 + 1.12x1 + 0.005x2 + 2.62x3 + 0.46x4 + 0.054x5 + 0.38x6 + 0.001x7 Where x1 is a parameter representi ng education level, x2 is a parameter representing area of adjacent natural habitat in square kilometers, x3 is a parameter representing attitudes toward wildlife, x4 is a parameter representing presen ce (1) or absence (0) of opossum in 118

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the res idential area, x5 is a parameter representing pres ence or absence of raccoon in the residential area, x6 is a parameter representing presen ce or absence of squirrel in the residential area, and x7 is a parameter representing averag e house values in the residential area as based upon MLS listings. Table 6.1: Descriptive statistics for the linear regression model of human-wildlife conflict across the urbanization gradient. Standard linear regression R2 = .680, p < .001 Coefficients Model Standardized Beta Unstandardized B Sig. Tolerance VIF Constant -0.756 Education level .223 1.12 0.13 0.687 1.46 Area of adjacent habitat patch .119 .005 0.23 0.758 1.32 Attitude type .361 2.62 .01 0.848 1.18 Opossum .312 .469 .02 0.842 1.80 Raccoon .036 .054 .25 0.555 2.19 Squirrel .257 .386 .15 0.456 1.39 House value .241 .001 .09 0.716 1.18 This model represents 68 percent of the variability w ithin the range of reported conflict in the residential areas investigated in this study (R2 = 0.680. p < 0.001). Table 6.1 below gives descriptive statistics for th e model. I evaluated the model based upon R2 value of 0.68, and significance of the model p < 0.001. The presence or absence of raccoon in the residential area had the highe st value of significance to the model but when it was removed the R2 value for the model declined, so it was left in the model parameters. The variance inflat ion factors (VIF) for the variable parameters were all less than 10 which indicated there was no problem with multicollinearity. Tolerance values 119

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were all abo ve 0.1 which is a good indicati on that there are no multiple correlations among the independent variables. I checked for outliers by evaluating Mahalanobis distance which was 20.71 at maximum which was less that the critic al value indicating there were no outliers beyond the third standard deviati on (critical value for seven independent variables was 24.32). Cook s distance was 0.211, indicating that the standardized residuals were also within three standard devi ations (Pallant, 2007). I also inspected the normal probability plot of the regression standa rdized residuals to ensure normality assumptions were not violated (F igure 6.2). The standardized residual plot yielded a relatively straight line further indicating that the normality assumption was not violated. Figure 6.2: Normal probability plot of the standardized residuals of the linear model. 120

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6.3.2 Results of Cross V alidation of the First Order Linear Model Cross validation was applied using th e randomly selected, but predetermined validation data set. Validation pred iction values were tested and R2 prediction was 0.56. I compared this with the model R2 that was 0.680 and found the difference just outside the 0.1 limit for prediction usefulness (Mendenhall and Sincich, 2003). In the practical application for predicting human-wildlife c onflict in a new reside ntial area, the model consistently slightly overestimat ed the incidence of conflict. 6.4 Discussion: 6.4.1 Explanatory Variables of the Model As stated earlier, the explanatory (ind ependent) variables included: 1) Area of adjacent habitat; 2) education level of reside nts in the residential area; 3) house values within the localized section of the residential area; 4) a measure of the proportion of negative attitudes toward wildlife; 5) presen ce or absence of opossum; 6) presence or absence of raccoons; and 7) pr esence or absence of squirre ls. Combining all seven of these gave the highest prediction of the va riability of conflict while conserving a low significance value. The education level was the most unstable variable as measured by the residuals statistics and I believe a practical interpretati on is needed. The education levels in relation to personal attitude seemed somewhat unpr edictable. More w ealthy areas of the residential area, as measured by higher home values, correlated somewhat with higher proportion of residents with a 4 year college degree. Since the sections with lower home values tended to have fewer college graduates, I could not adequately differentiate 121

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whether the correlation effect was due to higher hom e va lue or higher education. Further and more in depth interviews, in which ever yone is asked their livelihood, college major, and an evaluation of environmental awareness would be needed to determine the extent and direction of correlation that education level has with human-wildlife conflict reporting. House value was also a somewhat complex variable and tended to be less stable as other variables were added in and remove d from the model. First, house values were and are related to income level which once again could be affected by education. Second, house value was also specifically stated by a few residents during the interview to be a major concern in this economy and the ex tent of damage perc eived by the resident caused by wildlife may be more problematic to those in more expensive homes. This could be directly related to co st as well as possible issues wi th the residential area home owners association. However I did not ask these questions sp ecifically so this is based upon limited discussions with a sma ll proportion of those interviewed. As I determined the relative abundan ce of species populations in and around residential areas was not correlated with conflic t at the residential area scale, it was not included in the model. This seems counterin tuitive, but throughout the study area the relative abundance of a particular species may have been statistically different from one residential area to the next but conflict was not correspondingly so. I believe this is in part due to the relatively hi gh population densities of urban exploiter species throughout the urban gradient. Population densities in remnant patches appear to be relatively high compared to their rural counterparts, though using a measure of relative abundance to indicate total abundance or dens ity would be inappropr iate, thus I used the term appear. 122

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The apparen t higher density of urban populat ions for squirrels, raccoons and opossums that was seen in this study is supported in the literature (Thompson, 1978; Gillette, 1980; Lewis, 1980; Allen et al., 1985; Pedlar et al., 1997; Prange et al., 2003; Harmon et al., 2005; ODonnel and DeNicola, 2006). Seventy pe rcent of all conflic t was a combination of four top offenders; opossum, armadillos, raccoons and squirrels. Thus the difference that the abundance may or may not make se ems to be in which proportions each conflict prone species occupies in the reports and not the total number of reports. Armadillos were significantly absent from urbanized areas with human densities above 386.12 people per square kilometer (1,000 people per squa re mile). This makes sense when one considers that they are solitary foragers a nd prefer habitat with trees and open fields, which are frequently unavailable in a highly urbanized area. T hus I have classified them as suburban adapters. Since they did not appe ar on highly urbanized reports of conflict, they became insignificant when evaluating th e conflict across the gradient and were dropped from the model. Raccoons were also le ss significant in the residential areas with very high human densities and so the significance was also less but not so much so that I dropped them from the model. 6.4.2 Limitations of the Model Prediction adequacy of the model ba sed upon the average of all 12 validation residential areas was just outside the range of acceptability. As each prediction of conflict was calculated one new residential area at a ti me, the predicted values were consistently overestimated. As with any model, predictive ability is usually based upon the size of the sample to be predicted and also relies on th e fact that the individual components to be 123

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predic ted all fall well within the same range as those used to formulate the prediction equation. These are the major limitations invo lved with using regr ession for prediction and should always be considered (P arlange,1998; Mendenhall and Sincich, 2003). Though the model is limited in its predictive ability, it still provides valuable and significant information about to what extent th ese variables contribute to the incidence of conflict reporting. 6.4.3 Using the Model to Reduce Conflict This study is the first of its kind to incorporate three approaches; pattern oriented approach, the species oriented approach, and the human dime nsion, to formulate a model of explanatory variables affecting human co nflict with urban species. Considering the limitations of all models for practical predic tion of phenomena as complex as this, this particular model will be very useful in evaluating relative conflict density for comparisons between residential areas at the planning stages. As I said in the previous section prediction adequacy was outside accepta ble levels, but it may not be valuable to know what the prediction of conflict density will be this year in a particular residential area, as the landscape, the animal types, and the residents are all in place and typically will not change significantly. I believe the real value of this model will be at the planning stages of a community. The R2 of 0.680 is interpreted as 68 % of the variation in humanwildlife conflict reporting is explained by the landscape, ecological, and social variables that were included in the model. For instan ce, adjacent habitat c ontributes to conflict density (number of conflict reports per squa re kilometer) by a factor of .005 for every square kilometer added to adja cent habitat. This is an in dication of the importance of 124

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surrounding natural areas to wildli fe persistence in the reside ntial areas included in this study of conflict in the T ampa region. In Chapter Two I discussed metapopulati on theory and I hypothesized that it may play an important role in wildlife abundance in suburban and exurban areas. I believe the landscape portion of this study supports that hypothesis. The adjacent habitat may act as a source habitat for wild species immigrati on into the suburban residential area. The suburban residential area may act as a sink for individuals who ar e captured by trappers or otherwise trapped and/or ha rmed by residents. As individu als in the sink are lost the source habitat supplies new individuals for re colonization. This keeps a quasi-equilibrium metapopulation dynamic between the suburban resi dential area and the adjacent habitat. This information could be very useful should a community planner seek to reduce conflict. For instance transition areas, buffer zones, in the form of multi-use greenspace in between existing large chunks of natural ha bitat and residents homes would decrease the wild traffic through residents lawns. If designed properly, it could also be used to attract more wild animals into the transition greenspace, which so many residents confessed in my interviews to enjoy (100 perc ent to be exact). Incorporating these ideas into the landscape design of the residentia l community could add green value to the properties, and increase the interest of envi ronmentally friendly prospective homeowners. The less stable elements of this model involved the human related variables, education level, house value, and negative attitudes. These cont ributing factors are complex and can not be planned for in a dvance as they depend upon the individual humans moving into the nei ghborhood. Localized attitudes of residents toward wildlife would need to be considered. For instance the proportion of homeowners that have a 125

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negativ e attitude toward wild life may be higher in one urba nized region than another and therefore the quantitative effect that attitudes have on the in cidence of conflict reporting may also be higher. Other regions of the country could bene fit from understanding how the significant factors included in this model work together to contribute to humanwildlife conflict. The coefficients presented here are specific to the Tampa region but the overall concept and relationships can be generalized to other ur ban areas. One would need to consider the limiting factors related to the landscape for wildlife species in the area, to hypothesize which landscape features contribute most to persistence in a residential area. For example, water resources were not a significan t factor in suburban Tampa as we have a relatively large quantity of water reservoirs, and natural we tlands throughout the area. This may not be the case in a suburb in P hoenix, and therefore water supply may be highly significant in wild population persis tence within human communities. Specific animal species in a residential area would al so vary form one region to another but the concept that the conflict-prone type most likel y to be involved, the ur ban exploiters, is the important factor to consider in relation to the incidence of human-wildlife conflict. However, I believe the source sink system would apply to human settlements in any region that are adjacent to large natural areas and therefore the area of adjacent natural habitat would be an importan t factor to the incidence of conflict in every region. This study revealed specific factors th at contribute to human-wildlife conflict throughout the urbanized gradient of Tampa, Florida, but it also supported my idea that the study of human-wildlife conflict is most effective when landscape, ecological and social factors are evaluated together. I believe the biggest challenges for future 126

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resea rchers will be to focus in on human attitudes towards wildlife and what factors predispose certain individuals to those attitudes. I believe th e challenges for planners and wildlife managers are to consider the layout of homes in relation to wild areas and to initiate community education workshops to help people identify things that they can do to attract desirable species to their homes but deter others. 127

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Chapter Seven Reducing Human-Wild life Conflict in Urban Areas 7.1 Research Conclusions with Broader Implications This collection of research papers de monstrates the complex interactions of variables involved in humanwildlife conflict in urbanize d areas. Several important factors that were prev iously unknown have been revealed as well as directions for future study, all with implications for the future of wildlife conservation. First, the vast number of human-wildlife conflicts ac ross the urban gradient was su rprisingly high considering that I received 619 reports from only a small percentage (four pe rcent) of wildlife trappers working in the two counties. A lthough by anecdotal reports the trappers who participated in this study ma de up the larger proportion of all trapping done in the region, there were well over one hundred trappers w ho did not participate in the study whose annual trapping rate is yet unknown. Also the fact that over five percent of the human homeowner population across the Tampa region is also making efforts to deter or remove wildlife from their property without the aid of wildlif e trappers adds an unknown multitude to the tally of conflict. There are many aspects related to human-wildlife conflict that remain unclear, but one thing is clear: the reality of the incidence of humanwildlife conflict in urbanized areas is much greater and more persistent than has ever been expressed. 128

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The broader implications related to th eoretical questions in landscape ecology were not easily addressed in the urbanized landscape. The remnant patches in suburban and exurban residential areas never reached the 59 percent threshold re quired to test the percolation hypothesis related to human-wildlife conflict reporting. The highest percentage of remnant patches to residentia l area size was 51 percent. In the study sample of landscape factors, in highly urbanized residential areas where human population density was greatest over 772.2 people per sq uare kilometer (over 2,000 residents per square mile) there were no remnant patche s to measure. Though I did see a strong positive correlation between distance from the city core and increasing area of total remnant patches in the residential area, there was no significant effect of remnant area on conflict reporting. However, th e residential areas where the remnant patches would cross the 59 percent threshold only appear to exist in highly rural residentia l areas, far from the urban core. Highly rural reside ntial areas however show ve ry low levels of conflict reporting, which may seem to contradict the percolation threshold hypothesis. There are confounding effects from the human decision process in this case about whether or not to call on a trapper. Base d on informal conversations with wildlife trappers, rural residents are mo re disinclined to use trapper services. This seems to have more to do with a residents willingness to handle the prob lems with wildlife him/herself rather than bear the cost of paying a trapper to take care of it. Given that the rural fringes of a metropolitan area would be the perfect pl ace to test the percol ation threshold effect on human-wildlife conflict, future research studies would need a better measure of conflict than using trapper re ports. I would recommend a comb ination of conflict reports from trappers and extensive interviews with residents. 129

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In Chapter Two, I discussed the possibl e importance of meta population theory to the perpetuation of conflict be tween residents and conflict pr one species. One of the most significant landscape variables was the area of ha bitat patches adjacent to the residential area. This result supported my hypothesis that metapopulation dynamics may be important to the persistence of human-wildlife conflict in urbanized environments. The larger neighboring habitat patches could be acting as a sour ce of conflict prone individuals as they are removed from the re sidential areas by trappers. This hypothesis requires direct testing of move ments of wild species in and out of the remnant patches. The study of conflict from three persp ectives, as presented in Figures 1.1 and Figure 2.2, was shown in this study to be th e most successful way to evaluate the significant factors contributi ng to human-wildlife conflic t reporting across the urban gradient. Using landscape factors alone yiel ded a prediction model with an R square value of 0.29. The study of abundance and beha vioral characteristics supplied valuable information that abundance did not seem to c ontribute to conflict in a significant way in urbanized areas, but behavioral characteristic s of the species were strongly correlated with being involved in conflict. However presence or absence of a conflict-prone type in the residential area was not enough informati on to formulate a prediction model of any significance. The best model came from comb ining significant factors from all three approaches with an R square value of 0.68 and p < 0.001 significance. Further evaluation of human attitudes and how they contribute to conflict would most likely yield a more accurate model useful for prediction. 130

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7.2 Looking to the Past to Predict the Future A philosopher once said that our histor y is the key to our future. Perhaps by reviewing our past and looking at our presen t experiences objectiv ely, we can reach a better understanding of our relationships with other species including large carnivores, our natural predators, and herbivores, our natural competitors. Perhaps we can get a clearer picture of what is to come and how to improve the chances that we can coexist peacefully with other species. In a recent study by Sergio et al. (200 6) it was found that areas where top carnivores were present showed significantly greater biodivers ity than control site areas without top carnivores, thus indicating a healthier ecosystem This could be explained by what is called the interfer ence hypothesis that explains how the presence of a top carnivore can limit the populati on growth of other opportunistic predator species (Sergio et al., 2006). A case study could be the co mplete extermination of pumas (with the exception of the Florida panther) and wolv es in the Eastern United States by people beginning in the 1500s. Both pumas and wolves were viewed as bad animals to the early European colonists and they began exterm inating them as soon as they arrived in an area. By the late 1800s most pumas and wolves were completely extirpated in many areas and severely reduced in most other areas of the eastern states (Logan and Sweanor, 2001). Without the Eastern pumas and red wolv es as indigenous top predators we have seen unusually high populations of larger prey species, like white-tail deer, in many areas. In fact, in those areas man has replaced the puma and wolf as the top predator. We have also seen mesopredator release and an expansion of invasive mesopredators into eastern ecosystems. With the absence of wolv es, coyotes have expanded their territories 131

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farther than ever before and are becom ing thought of as a pest species in many areas as far south as central Florida. Coyotes are omnivores so instead of taking the place of wolves in the niche of top carnivore, they have usurped on the niches of many species and this has caused problems in many eco systems. Many other species have expanded their range in the absence of a top pred ator and expanded their niche to exploit supplemental resources in the wake of human development and settlement. So in our efforts to eradicate our pred ators and competitors without forethought as to how it affects the rest of the world we have inadvertently done ourselves and our local ecosystems harm. Now we seek to reintroduce these top predators and spend public funds to bolster and manage and pr otect their populations. Of cour se all American are not on board with these policies even though we have a better understanding of ecosystem linkages. According to news reports, the reside nts of the greater Yellowstone area are in a constant battle of conservation between thos e who want the wolf population to persist and those who want them eradicated (P lummer, 1990; Hamann, 1997; Yardley, 2009). If we return our attention to the mail box serpent story discussed in chapter two, the perpetrator rattlesnake, while not a top pr edator, is certainly a predator of importance to the nearby wetland ecosystem. There are multiple populations that interact and depend upon the rattlesnake population in one way or another. The particular residential area where the incident took place has a rather la rge adjacent habitat immediately next to residents back yards. If the parameters defined by my conflict model had been used during the planning of that re sidential area perhaps the snake bite could have been avoided. Now however we obviously can not ch ange the spatial ar rangement of a well established residential area, but we can call for more conscientious planning in the future 132

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and m aybe even more importantly call for edu cation of our residents, especially in high conflict residential areas. One might ask that if the population of raccoons is so high why should we be concerned with reducing the conflict? I believ e it is important on many levels but mainly reducing conflict can help change attitudes, even towards rat tlesnakes. I have evidence of this from my study and many others have s upported the idea that in creased conflict is significantly correlated with more negative attitudes towa rds wildlife (Layden et al., 2003; Adams, et al., 2006; Jonker et al., 2006). If people are not concerned with conserving species they may not be concerned with conserving habitat either. There have been many studies (Crooks, 2002; Treves et al., 2003; Sitati et al., 2003; Fisher and Lindenmeyer, 2007) that show any conservation policy is much more successful if it has the honest support of the local people, this certainly would also apply to urban and suburban areas as well as other more isolated regions. 7.3 Agenda 21 and Localized Efforts for Sustainability Timothy Quinn, Chief habitat scientist w ith the Department of Fish and Wildlife is quoted as saying "In the future, we're a ll going to be urban biologists." Since 80 percent of Americans are reported to live in urbanized areas it looks as though his prediction has a high likelihood of becoming r eality. Much of the land transformation and habitat fragmentation that is occurring at present is occurring across the urbanization gradient. Many organizations, conservationist s, wildlife management agencies, and government officials, are beginning to real ize the importance of local attitudes and actions toward conservation. Agenda 21 is a rela tively detailed action plan set forth at the 133

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United Nation Conference on Environm ent and Development in Rio de Janeiro (United Nations, 1992). It called for localized efforts toward sustainability at the local level and recognized the importance that local governments play in sustainability of environments. Chapter 28 in particular spells out the Basis for Action: Because so many of the pr oblems and solutions being addressed by Agenda 21 have their roots in local activities, the participation and cooperation of local authorities will be a determining factor in fulfilli ng its objectives. Local authorities construct, operate and maintain economic, social and environmental infrastructure, oversee planning processes, establish local environmental po licies and regulations, and assist in implementing national and subnat ional environmental policies. As the level of governance closest to the people, they play a vital role in educating, mobilizing and responding to the public to promote sustainable development, (Section 28.1, p 233). This is not only a call to action for local au thorities but also a call to all Americans for local action. For local action to take place there has to be pe ople at all levels who are willing to change the way we have always done things. There have to be people who are not only willing to read about how we coul d do better for the environment and wild species but who are also willing to take st eps to see it done, and to do it themselves, despite the fact that it is different or inconvenient. 134

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Appendix A: Survey for Residents Dear Hom eowner, I am a graduate student at the University of South Florida (USF) in Tampa. In my research, I am attempting to map areas of Hillsborough and Pasco counties where people often encounter and/or interact with wild animals. I also would like to document the general perceptions that people have toward s the wild animals they may encounter in their neighborhoods. This survey asks questio ns about these intera ctions that you may have experienced over the past 1 year. The questions asked are intended to he lp me discover where and when wild animals are interacting with residents in Hillsborough & Pasco Counties. The only personal information asked will concern the age groups of people in your household, and education level. I will just n eed to confirm that you are th e homeowner at this address and that you are 18 to 69 years of age in order to participate. I will use the information provided by homeowners to map out neighborhoods that have significant interactions with w ildlife. Please do not give your name, social security number, or any other identifying inform ation as this information is not necessary for my research. Any personal information (such as your address) will not be used in any way or passed along to anyone. Thank you very much for your participati on in this study. Please feel free to contact me at 813-974-7597 if you have any questions. Thank you 146

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Survey Questions for H omeowners age 18-69 years: 1. Please print the address of your residence below: 2. Are you the homeowner at this address? yes no 3. Do you have one or more pets? Yes No 4. What is the number of children in the household? 0 1-2 3-4 >4 5. What is the age of the youngest child? 0-2 years 2-5 years 6-9 years over 9 years 6. How would you categorize the place where you grew up? Urban (city) suburban exurban rural dont know 7. How would you categorize th e place where you live now? Urban suburban exurban rural dont know 8. What is the range of house hold annual income? (Optional) less than $25,000 $25,000 $44,999 $45,000 $65,000 over $65,000 9. What is the highest level of education in your household? High School Diploma Associate degree Bachelors degree Masters degree Doctorate Professional certification 10. How often have you identified the followi ng animals on your property in the past year? Raccoons: more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Armadillos: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Opossums: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Squirrels: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Vultures: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Birds (non-vultures): more than 3 times per week 1-3 times per week 1-3 times per month less than 1 147

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per month 0 Snakes: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Mice: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Stray Cats: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Stray Dogs: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Alligators: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Deer: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Tortoise/turtles: more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Frogs: : more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 Please list any other animals below: ________________: more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 ________________: more than 3 times per week 1-3 times per week 1-3 times per month less than 1 per month 0 11. Overall I enjoy the presence of wild animals on my property. Strongly agree agree neutral disagree strongly disagree Optional comment:____________________________________________________________ 12. Overall I do not enjoy the presen ce of wild animals on my property. Strongly agree agree neutral disagree strongly disagree Optional comment:____________________________________________________________ 13. I enjoy the natural areas in my neighborhood. Strongly agree agree neutral disagree strongly disagree Optional comment:____________________________________________________________ 14. I enjoy seeing wild animals in and n ear the natural areas in my neighborhood. Strongly agree agree neutral disagree strongly disagree Optional comment:____________________________________________________________ 15. Please check which of the following best describes your feelings towards wildlife. I have a strong interest and affection for all wildlife and the outdoors. 148

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I have a strong concern for the well-being of the environm ent and natural habitats. I have a strong interest and affection fo r only certain types of animals or pets. I have concern for the treatment of animals and a strong ethical opposition to cruelty towards animals My primary interest is in the physical attributes and biological functioning of animals. My primary interest is in the beauty of certain animals and their characteristics. My primary interest is in fishing and hunting of wild animals I actively avoid wild animals if possible. I am not interested in wild animals. 16. Over the last 12 months how much money have you spent to attr act wildlife to your property? $0 $1 $25 $26 $50 $51-$100 over $100 17. Over the past 12 months how much money have you spent to repe l wildlife from your property or to repair damage to your personal property? $0 $1 $25 $26 $50 $51-$100 over $100 18. Over the past 12 months how often have you tried to rid your prope rty of the presence of wildlife? about 1 time each week about 1 time each month about 1 time every 6 months about 1 time each year never 149

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Appendix B: Research packet letter mailed to licens ed wildlife trapper volunteers 150

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About the Author Amanda H. Gilleland grew up in the southern United States. She earned a bachelors degree in biology from the Universi ty of South Carolina, and a masters degree in biology from Winthrop University. She curre ntly lives on the gulf coast of Florida. End Page