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This is to certify that the
thesis entitled

RISK PERCEPTION, SOCIAL NETWORKS, AND MEDIA
FRAMES ASSOCIATED WITH HUMAN-CORMORANT
INTERACTIONS IN THE GREAT LAKES

presented by

BRET A. MUTER

has been accepted towards fulﬁllment
of the requirements for the

MS. degree in Fisheries and Wildlife

 

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5/08 K:IProjIAcc&Pres/CIRC/Dateoue.indd

 

RISK PERCEPTION, SOCIAL NETWORKS, AND MEDIA FRAMES ASSOCIATED
WITH HUMAN -CORMORANT INTERACTIONS IN THE GREAT LAKES

By

Bret A. Muter

A THESIS
Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of
MASTER OF SCIENCE
Fisheries and Wildlife

2009

ABSTRACT

RISK PERCEPTION, SOCIAL NETWORKS, AND MEDIA FRAMES ASSOCIATED
WITH HUMAN-CORMORANT INTERACTIONS IN THE GREAT LAKES

By

Bret A. Muter

The dramatic recovery of the double-crested cormorant (Phalacrocorax auritus) in the
Great Lakes has been accompanied by public concern about the bird’s potential effects on
the environment, recreation, and economy. Contention exists in regard to the perceived
extent of these risks within and among the stakeholder groups who inﬂuence, or are
affected by, cormorant management. To better understand stakeholder interactions and
perceptions of risk related to cormorants, I (a) assess risk perceptions within a social
network of agency professionals (n = 47) and non-govemmental stakeholders (n = 66)
engaged in human-cormorant conﬂicts around northern Lake Huron, (b) characterize the
structure of the social network, and (c) evaluate the nature of cormorant-related
newspaper coverage (n = 140 articles) in the Great Lakes from 1978 to 2007. Social
networks and mass media are two important channels in which information about
cormorant-related risks is communicated, and as a result, inﬂuence stakeholders’ risk
perceptions about cormorants. If human-cormorant conﬂicts in the Great Lakes are to be
alleviated, agency professionals may need to look to beyond current management tools
that are primarily based on reducing cormorant abundance. I present theoretical,
methodological, and practical implications from this research which may provide agency
professionals with new human-dimensions tools and insights to integrate with existing

strategies for cormorant management.

ACKNOWLEDGEMENTS

This research and my overall experience as a graduate student in the Department
of Fisheries & Wildlife at Michigan State University would not have been possible
without the support of countless individuals, agencies, and organizations. First and
foremost, thank you to the Fishery Research Program of the Great Lakes Fishery
Commission for funding and supporting this research. I am also grateful to the Saginaw
Field and Stream Club and Novi Chapter of Safari Club International for their generous
scholarship support during my master’s program.

One of the most rewarding aspects of working on this project was meeting with
people who are involved with cormorant management and research throughout the Great
Lakes. Thank you to all of the agency professionals, anglers, birders, business owners,
and others who volunteered their time to participate in my study. Without your
willingness to sit down with me to share your views, this project would not have been
possible.

Thank you to the Michigan Interagency Cormorant Committee for taking an
interest in my work and keeping me engaged with current cormorant-happenings in the
state. I would also like to acknowledge: Pete Butchko and Tony Aderman (U SDA-
Wildlife Services), Chip Weseloh (Canadian Wildlife Service), and Karen Cleveland
(MDNR) for ﬁelding my countless questions about the technicalities of cormorant
management in both the US. and Canada.

Special thanks to Anthony Wilson (USDA-Wildlife Services), Nancy Seefelt
(Central Michigan University), Tommy King (USDA-National Wildlife Research

Center), Steve Elliott (Ontario Ministry of Natural Resources), and Tiffanie Hamilton

iii

(MSU) for taking me out to visit cormorant colonies in the Les Cheneaux Islands, Beaver
Island Archipelago, and the North Channel in Ontario. My two and a half years dedicated
to studying human dimensions issues related to these birds would not have been complete
without these opportunities to see (and smell) the birds up close!

A huge thank you to my undergraduate assistants: Jacqueline Billelo, Alyssa
Hansen, and Taaja Tucker for their many hours spent tediously coding newspaper articles
and entering survey data.

I am grateful for the support of my past and present lab members: Krishnan
Sudharsan, Amy Smith, Brent Rudolph, Shauna Hanisch, and Jessica Kahler. Thank you
for your friendship, for co-conspiring crazy antics in the lab with me, as well as for your
always constructive feedback on my papers and presentations.

I am especially indebted to my graduate committee — Dr. Maria Lapinski, Dr.
Shawn Riley, and Dr. Meredith Gore. Shawn and Meredith, thank you for your
encouragement and mentorship, and for entrusting me with a project of this scale. It’s
been an incredible experience and I look forward to continue working with you both
during the Ph.D.

And last, but far from least, thank you to my friends and family for your patience
and support throughout this process and for telling me when I needed to take a break. I

couldn’t have done this without you!

iv

TABLE OF CONTENTS

LIST OF TABLES ........................................................................................................... viii
LIST OF FIGURES ............................................................................................................. x
INTRODUCTION ............................................................................................................... 1
Double-Crested Cormorants ............................................................................................. l
Approaches to HWC Management .................................................................................. 4
Risk as a Framework for HWCs ...................................................................................... 5
Thesis Organization .......................................................................................................... 8
REFERENCES .................................................................................................................... 9
CHAPTER 1: Inﬂuence of social networks on stakeholder perceptions of risk associated
with human-cormorant conﬂict in northern Lake Huron .................................................. 13
INTRODUCTION ............................................................................................................. 1 3
CONCEPTUAL BACKGROUND .................................................................................... 14
Social Network Analysis ................................................................................................ 14
Social Network Contagion Theory of Risk Perception .................................................. 15
Study Objectives ........................................................................................................... 19
METHODS ........................................................................................................................ 19
Study Population & Location ......................................................................................... 19
Sampling Frame ............................................................................................................. 20
Data Collection ............................................................................................................... 21
Data Analysis ................................................................................................................. 23
RESULTS .......................................................................................................................... 25
Risk Perception .............................................................................................................. 25
MRQAP Matrix Regression ........................................................................................... 26
DISCUSSION .................................................................................................................... 27
REFERENCES .................................................................................................................. 31
CHAPTER 2: Analyzing the structure and inﬂuence of a network of stakeholders
engaged in human-cormorant conﬂict: Implications for risk communication .................. 42
INTRODUCTION ............................................................................................................. 42
Objectives ....................................................................................................................... 43
NETWORK STRUCTURE & POSITIONAL MEASURES ............................................ 43
Network Structure .......................................................................................................... 44
Actor Attributes .............................................................................................................. 45
METHODS & ANALYSIS ............................................................................................... 47
RESULTS .......................................................................................................................... 48
Network Structure .......................................................................................................... 48
Actor Centrality Scores .................................................................................................. 48
Group Centrality Scores ................................................................................................. 49
Cliques ............................................................................................................................ 50
DISCUSSION .................................................................................................................... 50

REFERENCES .................................................................................................................. 56

CHAPTER 3: From victim to perpetrator: Evolution of risk frames about human-

cormorant conﬂict in the Great Lakes .............................................................................. 64
ABSTRACT ....................................................................................................................... 65
INTRODUCTION ............................................................................................................. 65
CONCEPTUAL BACKGROUND & HYPOTHESES ..................................................... 68
Media, Framing, & Risk ................................................................................................. 68
Risk Frames .................................................................................................................... 69
Hypotheses ..................................................................................................................... 71
METHODS ........................................................................................................................ 72
Sampling Frame ............................................................................................................. 72
Coding Protocol .............................................................................................................. 73
Risk Frames .................................................................................................................... 73
Intercoder Reliability ...................................................................................................... 74
Data Analysis ................................................................................................................. 75
RESULTS .......................................................................................................................... 75
Risk Frames .................................................................................................................... 76
Stakeholder Groups ........................................................................................................ 77
Cormorant-Related Risks ............................................................................................... 77
Attributions of Responsibility ........................................................................................ 78
DISCUSSION .................................................................................................................... 79
REFERENCES .................................................................................................................. 83
CHAPTER 4: Summary of research ﬁndings: Implications for theory, methods,
and practice ........................................................................................................................ 92
THEORETICAL IMPLICATIONS ................................................................................... 94
Factors of Wildlife-Related Risk Perception ................................................................. 94
Social Network Contagion Theory of Risk Perception .................................................. 95
Networks & Risk Behaviors ........................................................................................... 96
Issue Contentiousness .................................................................................................... 96
METHODOLOGICAL IMPLICATIONS ......................................................................... 97
Boundary Speciﬁcation of Network Sampling .............................................................. 97
Mixed Methods of Data Collection ................................................................................ 98
Institutional Review Board (IRB) Issues ....................................................................... 98
Coding Scheme .............................................................................................................. 99
PRACTICAL IMPLICATIONS ...................................................................................... 100
Managing Cormorant-Related Risk Perceptions .......................................................... 100
HWC-Related Risk Communication ............................................................................ 101
Identifying Intentional & Unintentional Risk Messengers in HWC Networks ........... 102
REFERENCES ................................................................................................................. 103
APPENDICES ................................................................................................................. 106
Appendix A: Interview Guide ...................................................................................... 106
Appendix B: Questionnaire .......................................................................................... 112
Appendix C: Research Participant Information & Consent Form ............................... 120

vi

Appendix D: Additional Risk Perception Results ........................................................ 123

Appendix E: Additional Sociograms ............................................................................ 128
Appendix F: Content Analysis Protocol ....................................................................... 131
Appendix G: Content Analysis Codebook ................................................................... 144

vii

Table 1.1

Table 1.2

Table 1.3

Table 1.4

Table 2.1

Table 2.2

Table 2.3

Table 3.1

Table 3.2

LIST OF TABLES

Deﬁnitions of eight factors of wildlife-related risk perception adapted
from Gore, Knuth, Curtis, & Shanahan (2006; 2007a; 2007b) to assess risk
perceptions related to human-cormorant conﬂict around northern Lake
Huron, August 2008-August 2009 ............................................................ 36

Respondents’ mean ratings on questionnaire items used to assess risk
perceptions related to human-cormorant conﬂict around northern Lake
Huron, August 2008—August 2009. Scores can range from 0 (indicating
low perceived risk) to 6 (indicating high perceived risk) .......................... 37

Frequency of agency professional and non-governmental stakeholder
groups engaged in human-cormorant conﬂict around northern Lake
Huron, August 2008—August 2009. ........................................ , .................. 38

Multiple regression quadratic assignment procedure (MRQAP) results for
models aimed at predicting cormorant-related risk perceptions of network
actors engaged in human-cormorant conﬂict around northern Lake Huron,
August 2008—August 2009 ........................................................................ 39

Matrix of interactions between agency professional and non—governmental
stakeholder groups engaged in human-cormorant conﬂict around northern

Lake Huron, August 2008—August 2009. An “X” placed in a cell indicates
there are ties among actors between the two groups .................................. 61

Top 20 degree, betweenness, and closeness centrality scores identiﬁed for
actors in a network of agency professionals and non-governmental
stakeholders involved in human-cormorant conﬂict around northern Lake
Huron, August 2008—August 2009 ............................................................ 62

Average degree, betweenness, and closeness centrality scores and clique
membership for each stakeholder group involved in human-cormorant
conﬂict around northern Lake Huron, August 2008—August 2009 ........... 63

Logistic regression analyses describing the effect of article date on an
article’s inclusion of stakeholder groups involved in human-cormorant
conﬂict in the Great Lakes Basin from 1978—2007 ................................... 88

Logistic regression analyses describing the effect of article date on an
article’s inclusion of individual risks from cormorants in the Great Lakes
Basin from 1978-2007 ............................................................................... 89

viii

Table 3.3

Table 3.4

Table A.l

Table A2

Table A.3

Table A.4

Logistic regression analyses describing the effect of article date on an
article’s inclusion of individual risks from cormorants in the Great Lakes
Basin from 1978—2007 ............................................................................... 9O

Logistic regression analyses describing the effect of article date on an
article’s inclusion of the stakeholder groups assigned with responsibility

for addressing human-cormorant conﬂicts in the Great Lakes Basin from
1978—2007 .................................................................................................. 91

Cormorant-related risk perceptions of agency professionals and non-
governmental stakeholders engaged in human-cormorant conﬂict around
northern Lake Huron, August 2008—August 2009 ................................... 124

Cormorant-related risk perceptions of Canadian and US. actors engaged
in human-cormorant conﬂict around northern Lake Huron, August 2008—
August 2009 ............................................................................................. 125

Cormorant-related risk perceptions of local and non-local stakeholders

engaged in human-cormorant conﬂict around northern Lake Huron,
August 2008—August 2009 ...................................................................... 126

Cormorant-related risk perceptions of clique actors (i.e., belong to one or
more cliques) and non-clique actors (i.e., do not belong to any cliques)
engaged in human-cormorant conﬂict around northern Lake Huron,
August 2008-August 2009 ...................................................................... 127

ix

Figure 1.1

Figure 2.1

Figure 2.2

Figure 3.1

Figure A.1

Figure A.2

LIST OF FIGURES

Map of study area: northern Lake Huron in Michigan, US. and Ontario,
Canada ........................................................................................................ 41

Sociogram showing directional ties of agency professionals (n = 47,
represented by gray nodes) and non-governmental network actors (n = 66,
represented by white nodes) engaged in human-cormorant conﬂict around
northern Lake Huron, August 2008—August 2009 ..................................... 59

Sociogram of 113 network actors engaged in human-cormorant conﬂict
around northern Lake Huron (August 2008—August 2009) and grouped
according to their stakeholder afﬁliation ................................................... 6O

Predicted probability of each risk frame through time (i.e., article date).
The predicted probability of both neutral and victim frames declined over
time, while the predicted probability of the perpetrator increased over

time ............................................................................................................ 87

Sociogram showing directional ties of Canadian actors (n = 25,
represented by gray nodes) and US. network actors (n = 88, represented
by white nodes) engaged in human-cormorant conﬂict around northern
Lake Huron, August 2008 -August 2009 ................................................ 129

Sociogram showing directional ties of local actors (n = 61, represented by
gray nodes) and non-local network actors (n = 52, represented by white
nodes) engaged in human-cormorant conﬂict in northern Lake Huron,
August 2008—August 2009 ...................................................................... 130

INTRODUCTION

Human-wildlife interactions are increasingly common worldwide as human and
wildlife populations expand and interact; some of these interactions may lead to human-
wildlife conﬂicts (HWCs) (Conover, 2002). Conﬂicts transpire when either people or
wildlife cause, or are believed to cause, harmful effects to the other. HWCs can have
adverse consequences on the health and safety of both humans and wildlife, as well as
environmental, economic, cultural, social, and psychological effects and impacts on the
diverse stakeholders involved (Decker, Lauber, & Siemer, 2002; Riley et al., 2002).

Managing HWCs poses substantial challenges for wildlife professionals (Fall &
Jackson, 2002) in large part because HWCs tend to include an increasing diversity of
stakeholders with conﬂicting views on how wildlife should be managed and involve a
great degree of uncertainty about how to manage for biological and human dimensions
(Messmer, 2000). Additionally, there is an increasing trend of conﬂicts between people
and wildlife species that were historically rare, but are now perceived by some
stakeholders as overabundant (Decker & Chase, 1997). Common examples of such
species include white—tailed deer (Odocoileus virginianus) (e.g., Storm, Nielsen,
Schauber, & Woolf, 2007), Canada geese (Branta canadensis) (e.g., Conover & Chasko,
1985), and beaver (Castor canadensis) (e.g., Jonker, Organ, Muth, Zwick, & Siemer,

2009)

Double-Crested Cormorants
Double-crested cormorants (Phalacrocorax auritus) are at the center of a HWC in the

Great Lakes Basin. Double-crested cormorants (hereafter referred to as cormorants) are

one of 38 species of cormorants and shags found worldwide (Sullivan, Curtis, Chipman,
& McCullough, 2006) and the most abundant and widely distributed of the six North
American species (Hatch & Weseloh, 1999). Cormorants are large, piscivorous, colonial-
nesting waterbirds distributed throughout North America. Similar to other ﬁsh-eating
birds, cormorants were nearly extirpated in the Basin by the 19703 from the extensive use
of commercial contaminants like dichloro-diphenyl-trichloroethane (DDT) and
polychlorinated biphenyls (PCBs) (Weseloh, 1995). Federal regulations of these chemical
compounds (e.g., the Environmental Protection Agency banned commercial use of DDT
in 1972, and PCBs in 1979), as well as additional state, provincial, and federal
protections, including the Migratory Bird Treaty Act of 1918 (in the US.) and the 1997
Fish and Wildlife Conservation Act (in Ontario, Canada), helped cormorant numbers
rebound considerably. Basin populations increased from an estimated 89 to 38,000
nesting pairs between 1970 and 1991 and reached record highs of approximately 115,000
pairs by 2000 (Weseloh, Pekarik, Havelka, Barrett, & Reid, 2002). The increasing
abundance of cormorants in the Basin has resulted in the birds being perceived as
overabundant (Wire & Cuthbert, 2006).

The cormorant’s dramatic recovery has been accompanied by growing public
concern about the bird’s potential effects on recreational ﬁsheries (e. g., Fielder, 2009;
Lantry, Eckert, Schneider, & Chrisman, 1999; Rudstam, VanDeValk, Adams, Coleman,
Fomey, & Richmond, 2004), aquaculture and ﬁsheries stock (e.g., Johnson & Rakoczy,
2004; MDNR, 2005), island vegetation (e.g., Herbert, Duffe, Weseloh, Senese, &
Haffner, 2004; Lemmon, Bugbee, & Stephens, 2004), other colonial-nesting waterbirds

(e.g., Weseloh et al., 2002; Wires, Cuthbert, Trexel, & Joshi, 2001), and ﬁshing-related

tourism (e.g., Sullivan et al., 2006) in the Basin. Stakeholder concerns about these
perceived threats played a vital role in inﬂuencing federal policy decisions about
cormorant management (Wires & Cuthbert, 2006), including the US. Fish and Wildlife
Service’s (USFWS) Public Resource Depredation Order (PRDO) (Sullivan et al., 2006).
Formalized in 2003, the PRDO authorizes the US. Department of Agriculture - Wildlife
Services (U SDA-WS), federally-recognized tribes, and state ﬁsh and wildlife agencies in
24 states — including seven of the eight states that border the Great Lakes — to coordinate
and partake in lethal and non-lethal control activities when deemed necessary to protect
public resources, which include ﬁsheries (Sullivan et al., 2006).

Management activities, such as harassment, nest destruction, egg-oiling, and
lethal shooting, aimed at population control have triggered public concern and
displeasure with management (Bedard, 1995). Cormorants have exceeded wildlife-
stakeholder acceptance capacity (i.e., the frequency and nature of human-wildlife
interactions deemed acceptable by stakeholders) (Carpenter, Decker, & Lipscomb, 2000)
for several stakeholder groups, including recreational anglers and aquaculturists (Taylor
& Dorr, 2003). Contention exists, however, in regard to the perceived extent of these
threats within and among the stakeholder groups who inﬂuence, or are affected by,
management. Special consideration is warranted when developing management strategies
to alleviate human-cormorant conﬂicts (HCCs) in the Basin because contention persists
despite more than ﬁve years of management activities. A key need for cormorant
management is insight about stakeholder dynamics from which effective information and

HCC-related communication can be developed (Weseloh & Lewis, 1997).

Approach es to H WC Management

Conover (2002) identiﬁed three fundamental approaches to HWC management that draw
heavily upon principles of wildlife damage management. First, there are wildlife-centered
approaches that emphasize either removing the problem-causing individual(s) or
modifying wildlife behavior. These techniques can include lethal methods, such as
culling and egg oiling, as well as non-lethal methods like fertility control, translocation,
and harassment. Second, there are habitat-centered approaches that aim to alter the
impacted resource, change how it is managed, or modify the habitat or landscape that
contains the resource. Examples of these techniques include planting types of crops that
are less susceptible to wildlife damage, using unpalatable species of plants for suburban
landscaping, or altering harvest schedules to reduce wildlife damage. Finally, there are
human-centered approaches that intend to change human behaviors or perceptions so
people are more willing to tolerate damage (Conover, 2002). Resolving HWCs almost
always requires more than reducing the population of a species causing, or perceived to
be causing, damage. Conover (2002) advocated integrated approaches that draw from all
of the previously deﬁned strategies to ensure management is economically,
environmentally, and socially sustainable. These integrated approaches can provide
agencies with new alternatives for management.

Thus far, cormorant management in the Basin has primarily taken a population, or
wildlife-centered, approach. Management has focused on reducing cormorant abundance
through lethal shooting, egg-oiling, and harassment in localized areas of high cormorant
density (Sullivan et al., 2006). Habitat-centered approaches, such as changing ﬁsh

stocking strategies (e.g., time of day and/or year ﬁsh are stocked) to avoid cormorant

predation have also been applied in select locations throughout the Basin (e.g., Thunder
Bay, Michigan) (MDNR, 2005; 2009). Human-centered approaches for cormorant
management have been minimal; however, agency professionals are involving small
groups of stakeholder (e. g., anglers) in cormorant harassment efforts in impacted
communities (MDNR, 2005; 2009). Despite these efforts, debate about management
persists and much uncertainty remains about how to sustainably manage cormorants in
the Basin.

Providing insights about the human-dimensions of cormorant management can
provide agency professionals and decision-makers with vital information to develop new
and modify existing human-centered approaches; such information can also be integrated
with wildlife and habitat-based approaches to more effectively manage HCCs in the
Basin. Expanding the breadth and depth of knowledge about the human dimensions of
HCCs can inform the revision process and content of Michigan’s cormorant
Environmental Assessment (EA) in 2010 and the USFWS’s national Environmental
Impact Statement (EIS) in 2014. Human-dimensions inquiry may also aid the state,
provincial, tribal, and federal agencies involved in cormorant management as they
explore options for regional management throughout the Mississippi F lyway by
highlighting stakeholder attitudes towards cormorants and their management. Empirical
inquiry about the perceptions of stakeholders engaged in, or affected by, HCCs is

paramount to recognizing these beneﬁts for management.

Risk as a Framework for H WCs

The notion of risk has been characterized in many ways; most deﬁnitions include a

technical (i.e., assessed probabilities or incidence of a particular hazard and its
consequences) and a subjective component (e. g., value-laden beliefs about a hazard)
(Renn, 1998). Risk theories and methodologies are being applied in human-dimensions
inquiry and HWC management (Gore et al., 2009). HWCs often result in part because of
stakeholder risk perceptions — or instinctive evaluations of risk (Slovic, 1987) — from
exposure to wildlife, or risks to wildlife and their associated habitat (Decker et al., 2002).
Wildlife-related risks are diverse and multifaceted, and can include risks to human health
and safety (e.g., physical injuries from wildlife attacks, wildlife-vehicle collisions, or
illness related to wildlife exposure), personal property and agriculture (e.g., pets or
livestock killed by predators), aesthetic values (e. g., ornamental plant damage), and to
other ﬁsh and wildlife resources that humans value (e.g., wolves killing moose that
Alaskan hunters like to hunt, cormorants consuming ﬁsh that anglers like to ﬁsh).
Wildlife-related risks also include threats to wildlife health and safety (e. g., sea turtles
becoming entangled in commercial ﬁshing gear; Gilrnan, Kobayahi, Swenarton, Brothers,
Dalzell, & Kinan-Kelly, 2007). Wildlife-related risk perceptions can inﬂuence public
opinions about wildlife and support for management actions (Knuth, Stout, Siemer,
Decker, & Stedman, 1992), affect wildlife-stakeholder acceptance capacity (Riley &
Decker, 2000a; 2000b; Stout, Stedman, Decker, & Knuth, 1993), garner trust or distrust
in management agencies (Kasperson, Jhaveri, & Kasperson, 2001), and incite stakeholder
action (Decker et al., 2002).

There is growing interest among and relevance for wildlife professionals to better
understand stakeholders’ perceptions of risk associated with contentious HWCs, as well

as the mechanisms that inﬂuence those perceptions. Mass media and social networks

have been identiﬁed as two such mechanisms; they serve as important sources of
information and experience for the public about risks and risk events (e. g., Ball-Rokeach
& DeFleur, 1976; Slovic, 1987). As communication channels, these mechanisms can
amplify or attenuate risk perceptions within a community, as well as motivate individuals
and groups to take actions to avoid, tolerate, or modify the risk (Kasperson et al., 1988).
Both mechanisms are especially inﬂuential when personal experience with a risk is
minimal or nonexistent (Kasperson et al., 1988).

Previous research has investigated wildlife-related risk perceptions through
psychometric (e.g., Riley & Decker, 2000a; 2000b; Stout et al., 1993) and sociocultural
(e.g., Gore, Siemer, Shanahan, Schuefele, & Decker, 2005; Muter, Gore, & Riley, 2009)
approaches. Psychometric inquiry emphasizes factors that inﬂuence individuals’ risk
perceptions, including the extent to which an individual worries about a particular risk
and the degree to which they trust those responsible for managing the risk (Slovic, 1987).
Sociocultural approaches consider how peoples’ risk perceptions and responses to
hazards are shaped by their worldviews, social interactions, or experiences of everyday
life (Bickerstaff, 2000; Marris, Langford, & O’Riordan, 1998). Sociocultural approaches
look at societal inﬂuences, such as the mass media, that affect individual and group
perceptions of risk and responses to risk-events (Sjoberg, 1998). Research integrating
these two paradigms of risk perception is missing from the wildlife management
literature.

My research aims to address this need by integrating principles from both
psychometric and sociocultural theories of risk perception to inform the human

dimensions of cormorant management. To this end, I (a) assess perceived risks within a

network of stakeholders engaged in HCCs around northern Lake Huron, (b) characterize
the social network, and (c) evaluate the nature of cormorant-related media coverage in the
Great Lakes over time. In addition to having important practical implications for
cormorant and HWC management, this research provides important theoretical insight
into how social network structure both inﬂuences, and is inﬂuenced by, stakeholder risk

perceptions.

Thesis Organization

This thesis is organized into four chapters. In Chapter 1, I test a framework proposed by
Scherer & Cho (2003) that integrates elements of psychometric and sociocultural theories
of risk perception to better understand how risk perceptions associated with HCCs around
northern Lake Huron are inﬂuenced by interactions among stakeholders in their social
network. In Chapter 2, I describe the structure of the social network and discuss practical
implications for wildlife-related risk communication. In Chapter 3, I analyze the risk-
related content of newspaper coverage about cormorants in the Great Lakes from 1978 to
2007 and discuss the use of risk frames in content analysis to inform risk communication.
In the ﬁnal chapter, I summarize major ﬁndings and discuss theoretical, methodological,

and practical implications from my research and suggest directions for future inquiry.

REFERENCES

Ball-Rokeach, S. J., DeFleur, M. L. (1976). A dependency model of mass-media effects.
Communication Research, 1, 3—21.

Bedard, J., Nadeau, A., & Lepage, M. (1995). Double-crested cormorant culling in the
St. Lawrence River estuary. Colonial Waterbirds, 18, 78—85.

Bickerstaff, K. (2000). Risk perception research: socio-cultural perspectives on the public
experience of air pollution. Environment International, 30, 827—840.

Carpenter, L. H., Decker, D. J., & Lipscomb, J. F. (2000). Stakeholder acceptance
capacity in wildlife management. Human Dimensions of Wildlife, 5, 5—19.

Conover, M. R. (2002). Resolving human-wildlife conﬂicts: The science of wildlife
damage management. Boca Raton: CRC Press LLC.

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12

CHAPTER 1

INFLUENCE OF SOCIAL NETWORKS ON STAKEHOLDER
PERCEPTIONS OF RISK ASSOCIATED WITH HUMAN-CORMORANT
CONFLICT IN NORTHERN LAKE HURON

There is interest among wildlife professionals to increase understanding of
stakeholder perceptions of risk associated with HWCs, as well as mechanisms that
inﬂuence those perceptions (Gore et al., 2009). Stakeholder risk perceptions may not
align with expert assessments of wildlife-related risks; however, these perceptions
inﬂuence public attitudes and behaviors related to wildlife management (Knuth, Stout,
Siemer, Decker, & Stedman, 1992). Research on wildlife-related risk has
overwhelmingly been informed by the psychometric and sociocultural paradigms.
Psychometric studies have identiﬁed factors inﬂuencing individuals’ risk perceptions
associated with wildlife, such as demographic variables, attitudes, and wildlife
stakeholder acceptance capacity (e.g., Riley & Decker, 2000a; 2000b; Stout, Stedman,
Decker, & Knuth, 1993; Vaske, Timmons, Beaman, & Petchenik, 2004). Sociocultural
research has explored how public responses to and perceptions of wildlife-related risks
are shaped by inﬂuences of everyday life, such as the mass media (e.g., Gore, Siemer,
Shanahan, Schuefele, & Decker, 2005; Muter, Gore, & Riley, 2009). Little research has
integrated elements from both perspectives into a single framework to account for how
these elements both inﬂuence, and become inﬂuenced by, stakeholder’s wildlife-related
risk perceptions.

HWCs can generate concerns within and across affected communities and often

become contentious issues that require management intervention (Minnis & Peyton,

13

1995; Schusler, Chase, & Decker, 2000). The stakeholders and agency professionals who
are involved with, or affected by, HWCs may develop a complex web, or network, of
social interactions (Conover, 2002). Social networks are composed of actors (e. g.,
individuals, groups, or organizations) and their connections (i.e., ties) with one another.
Social network analysis (SNA) is the study of “relationships among social entities, and
the patterns and implications of these relationships” (Wasserman & Faust, 1994, p. 3).
Social networks have been used to describe diverse interactions and relationships among
actors including kinship, transfer of resources, communication, and exertion of inﬂuence
(Wasserman & Faust, 1994).

Theories of risk perception and social networks have been individually applied in
human dimensions inquiry; however, no research has integrated both into a wildlife
management context. I aim to help ﬁll this void by investigating risk perceptions and
social network structure of agency professionals (e.g., federal, state, provincial, and tribal
ﬁsheries and wildlife managers) and non-governmental stakeholders (e.g., anglers,
birders, and business owners) engaged in HCCs around northern Lake Huron. I conclude
this chapter with a discussion about the theoretical and practical implications for risk

communication related to contentious HWCs.

CONCEPTUAL BACKGROUND
Social Network Analysis
SNA has been applied to a variety of natural resource management issues and has proved

especially useful in helping to characterize and understand relationships among diverse

stakeholder groups (e.g., Bodin, Crona, & Emstson, 2006; Prell, Hubacek, & Reed,

14

2009). SNA has been used to identify functions of networks in community-based natural
resources management (e.g., Lauber, Decker, & Knuth, 2008) and to evaluate the efﬁcacy
of collaborative natural resource planning (e.g., Mandarano, 2009). SNA has informed
stakeholder-engagement selection processes (e.g., Prell, Hubacek, Quinn, & Reed, 2008;
Prell et al., 2009) and been used to explore communication, knowledge, and advice
exchanges among stakeholder groups such as farmers (Issac, Erickson, Quashie-Sam, &
Timmer, 2007) and charter-boat ﬁshing captains (Mueller, Taylor, Frank, Robertson &
Grinold, 2008). Two gaps in the existing literature include the application of social
network methods to HWCs and wildlife-related risk perception. SNA may serve as an
effective framework for integrating the psychometric and sociocultural perspectives of
risk to explore stakeholder risk perceptions associated with HWCs. If effective, this
framework may have management implications for how agency professionals interact and
communicate with stakeholders involved in contentious HWCs, as well as offer new
theoretical insight into: (a) how wildlife-related risk perceptions are formed, and (b) the

relationship between wildlife-related risk perception and risk behavior.

Social Network Contagion Theory of Risk Perception

Social networks serve as important channels in which people share, receive, and
exchange information about risk and risk-related events (Kasperson et al., 198 8). People
observe and interact with members of their personal and professional networks to
determine if risks are socially acceptable; in turn, these networks may facilitate
ampliﬁcation or attenuation of risk perceptions throughout a community, as well as

motivate individuals and groups to take actions to avoid, tolerate, or modify the risk

15

(Kasperson et al., 1988). Social contagion — the diffusion of tangible or intangible ideas,
practices, or technologies through relationships among actors within a network (Borgatti
& Foster, 2003; Rogers, 2003) —— arises from these social interactions which help people
manage and interpret uncertainty (Burt, 1987).

Burt (1987) discussed two models of social contagion: structural equivalence and
cohesion. The structural equivalence model compares the positions of actors and their
functions within a network. Actors who are structurally equivalent have identical or very
similar connections with other network actors, but do not necessarily have direct ties with
one another (Knoke & Yang, 2008). Exact equivalence rarely occurs in real world
networks (Hanneman & Riddle, 2003); however, in theory, the more structurally
equivalent two actors are the more likely they are to adopt similar attitudes or behaviors
(Burt, 1987). Investigations of structural equivalence have primarily focused on
competitive relationships between actors (Burt, 1992). For example, two competing
commercial ﬁshermen may be structurally equivalent if they both market their catch to
the same restaurant chains (i.e., they interact with the same set of actors without
necessarily interacting with one another).

The cohesion model emphasizes the role of communication between actors; the
more frequent communication (i.e., the stronger the tie) between two actors (i.e., a dyad),
the more likely they are to adopt similar attitudes or behaviors. Close physical proximity
of actors may also inﬂuence social contagion (Burt, 1987). Contagion occurs as a result
of interactions among actors who are “mutually inﬂuencing and informing each other”
(Borgatti & Foster, 2003, p. 1005). These interactions — both past and current - aid in the

ﬂow of information and inﬂuence, and affect individual and group decision making

16

(Watts, 2004). Neither the structural equivalence nor the cohesion models have been
applied to a wildlife management context; however, structural equivalence models are
generally applied to groups of expert actors who are “overexposed to information on the
objects being evaluated” (Burt, 1987, p. 1328). Wildlife professionals, for example, may
be overexposed to information on radio-telemetry technologies for studying movements
of small animals (e. g., butterﬂies). Some of these professionals may initially choose not
to adopt the new technology and rely on existing (and perhaps cheaper) alternatives such
as mark-recapture techniques; however, once they notice other professionals in their ﬁeld
applying the new method, they adopt the new method (i.e., innovation). Thus, the
cohesion model seems more conducive to exploration of contagion among networks
including both expert and non-expert actors (e.g., such as the network of agency
professionals and non-governmental stakeholders involved in cormorant management in
northern Lake Huron).

Theories of social inﬂuence and contagion have been applied to diverse
disciplines and innovations ranging from smoking cessation (e.g., Christakis & Fowler,
2008) to corporate philanthropy (e.g., Galaskiewicz & Burt, 1991). Although risk is an
implicit part of these case studies; few studies have explicitly explored if and how risk
perceptions are inﬂuenced by social contagion. Scherer and Cho (2003) adapted Burt’s
(1987) social network contagion theory to analyze the role of risk perceptions associated
with management of an environmental hazard in a community setting. They hypothesized
that an individual’s risk perceptions would be inﬂuenced by the perceptions of others in
their communication network; similarity in risk perceptions of the negative health

impacts posed by a hazardous waste site were related to the frequency of communication

17

between actors. In other words, the more frequently two individuals communicated, the
more likely they were to share similar levels of perceived environmental risk.

Although Scherer & Cho (2003) found that dyadic tie strength predicted similarity
in risk perceptions about a contentious environmental issue (i.e., cleanup of a hazardous
waste site within a community), they found that dyadic tie strength was not a signiﬁcant
predictor of similarity of beliefs about a benign issue (i.e., belief in science). They
speculated that contentious environmental risk issues generate more interpersonal
discussions about risk-related events and activate contagion effects throughout a
community. Theoretical understanding of the antecedents and consequences of wildlife-
related risk perceptions may be greatly enhanced through studying social networks
associated with HWCs (which are often viewed as contentious management issues).

I applied Scherer & Cho’s (2003) social network contagion theory of risk
perception to a network of actors engaged in HCCs. Cormorant management is a .
contentious management issue in the Basin, at least in part, because of the diversity of
stakes and cormorant-related risk perceptions held by stakeholders. A number of
psychometric factors can inﬂuence an individual’s risk perception including experience
and familiarity with the risk (Slovic, 1987), trust in decision makers (Slovic, 1993), and
dread (Sjoberg, 1998). Gore, Knuth, Curtis, and Shanahan (2006; 2007a; 2007b) applied
nine of these factors to HWC in New York: certainty, control, dread, ﬁequency,
naturalness, trust in management, responsiveness of management, seriousness, and
voluntariness. I adapted and applied their deﬁnitions of the ﬁrst eight of these factors to
HCCs (Table 1.1) and explored how each individual factor is inﬂuenced by network

structure (e.g., dyadic tie strength). I excluded voluntariness (i.e., the degree to which a

18

person believes their exposure to wildlife is accidental or deliberate) (Gore etal., 2006;
2007a; 2007b), because HCCs are not typically viewed in the context of direct physical

interactions between humans and cormorants.

Study Objectives

The purpose of this study was to explore how interactions within a social network of
agency professionals (e.g., state, federal, provincial, or tribal ﬁsheries and wildlife
managers) and non-governmental stakeholders (e.g., anglers, bird enthusiasts, and
business owners) inﬂuence risk perceptions associated with cormorant management in
northern Lake Huron. My objectives were to: 1) evaluate cormorant-related risk
perceptions held by network actors, and 2) assess the relationships between cormorant-

related risk perception and dyadic tie strength.

METHODS

Study Population & Location

My study population of interest was agency professionals and non-governmental
stakeholders who were involved in, or affected by, HCC in northern Lake Huron (Figure
1.1). I chose to focus my research efforts in this region for several reasons. First, northern
Lake Huron serves as an important nesting area for more than 100 cormorant colonies in
the Great Lakes Basin (Ridgway, Pollard & Weseloh, 2006; Weseloh et al., 2002).
Second, ﬁshing communities in northern Michigan and Ontario that are close to these

nesting sites (e.g., Thunder Bay, the Les Cheneaux Islands, the North Channel, and

Manitoulin Island) have reported increased HCCs in recent years, evidenced in part by

19

several documented occurrences of illegal, mass cormorant killings (Wires & Cuthbert,
2006) and high-proﬁle coverage about HCCs in the mass media, including the New York
Times (e.g., Wilgoren, 2002, p. 12A). This study area was also easily accessible to
Michigan State University (MSU) and conducive for studying ties within and across
diverse stakeholder groups in both the US. and Canada. Finally, cormorant management
activities such as harassment, egg-oiling, and lethal shooting have been applied

throughout select areas of this region since 2004.

Sampling Frame

I used an adaptive, snowball sampling approach (Goodman, 1961; Thompson & Collins,
2002) to identify study participants and collect data between August 2008 and August
2009. Adaptive sampling designs include any type of sampling procedure that adjusts to
observations made while conducting a study, such as identifying new study participants
based on links from previous respondents (Thompson & Collins, 2002). Snowball
sampling typically begins with a set of actors who hold leadership positions in their
community, organization, or agency (Hanneman & Riddle, 2005). Although the method
may not identify all actors in the network (e.g., isolates), snowball sampling is effective
at identifying hard to ﬁnd populations (Hanneman & Riddle, 2005). Thus, I began with a
group of agency professionals (n = 20) directly involved with cormorant management in
northern Lake Huron. I created this list after making several calls to management
agencies for recommendations on the most appropriate individuals from that agency. As
ﬁsheries and wildlife professionals in state, provincial, tribal, and federal government,

these actors were responsible for making decisions about cormorants and were connected

20

with stakeholders who were actively engaged in HCC in northern Lake Huron. I
interviewed these individuals and asked them to list the names of up to ﬁve agency
professionals and ﬁve non-governmental stakeholders with whom they had discussed
cormorants and their management, speciﬁc to our study area, in the last calendar year.
New names generated from these interviews were compiled into a list for my second
wave of interviews. I repeated this process three times (i.e., through three complete
waves). I stopped conducting interviews during the fourth wave because (1) new actors
nominated during the interviews did not play a major role [in cormorant management] in
their communities (Fink, 1995), (2) study participants were not generating new
information [about cormorant-related risk perception] (Lauber et al., 2008), and (3)

interview resources (e.g., time and funds) were ﬁnite (Hanneman & Riddle, 2005).

Data Collection

Data collection was modeled after Scherer and Cho (2003) and consisted of a semi-
structured face-to-face or telephone interview (Appendix A) (Gubrium & Holstein,
2002), and a 13-item questionnaire (Appendix B) that was handed directly to participants
at the end of the interview. I initially contacted participants by telephone and asked if
they would be willing to schedule a time and place to meet for a face-to-face interview.
Interviews usually took place in the participant’s home or ofﬁce (n = 105, 87%).
Interviews were conducted over the telephone (n = 16, 13%) only if the participant was
unable to meet in person (e.g., interviewee lived out-of-state). Wasserman and Faust
(1994) suggested that interviews can easily be conducted over the telephone and be just

as effective as face-to-face interviews. Although merging data from different collection

21

methods can be problematic, recall issues are typically minimized with salient issues
(Dillman, Sangster, Tamai, & Rockwood, 1996), such as cormorant management.

I conducted 121 interviews that varied from 12 to 113 minutes in length (M = 36
minutes, SD = 16). Each interview was digitally recorded with the participant’s informed
consent (Appendix A). During the interview, I asked participants to list names of actors
with whom they had discussed cormorants in the past year and to address their
connectivity with each actor they listed (e. g., frequency of communication, type of
relationship). Interview questions also queried participants about their (a) sources of
cormorant-related information, (b) cormorant-related risk perceptions, and (c) opinions
about cormorant management.

Questionnaires obtained personal attributes (e.g., age, education, county of
residence) and measured individual factors that may inﬂuence cormorant-related risk
perception (Table 1.2). All risk perception-related items were measured on 7-point scales.
Human dimensions research typically employs either 5 or 7-point scales; however, 7-
point scales are often preferred because of their increased precision (Vaske, 2008).
Questions assessed participants’ perceived likelihood and acceptability of cormorant-
related risks (e.g., risks to the environment, economy, and recreational opportunities in
northern Lake Huron). Finally, I adapted a question posed by Scherer & Cho (2003)
about participant’s belief in science (e.g., “Science is the most rational way to approach
cormorant management”). I encouraged study participants to complete the questionnaire
at the end of the interview so they could be collected in-person; however, if the
participant did not have time to complete the survey immediately after the interview

concluded, I provided them with postage and a self-addressed envelope. Methods used in

22

this research were reviewed and approved by the University Committee on Research

Involving Human Subjects at Michigan State University (IRB # XO7-052).

Data Analysis

Social network data are essentially interpreted as dyadic relationships (i.e., relationships
between pairs of actors) (Borgatti & Foster, 2003; Marsden, 1990). I organized data into
sets of two-dimensional adjacency and afﬁliation matrices (Scott, 2000). Adjacency
matrices are square matrices that include the same set of items (e.g., a list of actors’
names) in both the row and column headings. Afﬁliation matrices include different sets
of items (e.g., a list of actors and attributes such as gender or age) in the row and column
headings. My independent variable was dyadic tie strength, measured as the maximum
reported frequency of communication between two actors in the network. Study
participant names were listed in the row and column headings in a 113 x 1 13 matrix,
representing 12,656 possible interactions between all of the actors. Values ranging from 0
(indicating no interaction between the two actors) to 365 (indicating daily interaction
between two actors) were inserted into each of the matrix cells. Reported interactions
between two actors were not always reciprocated (e. g., actor i might report a tie with
actor j, but not vice versa), so I chose to symmetrize the matrix with the maximum
reported value (Scherer & Cho, 2003). This meant that if actor i reported communicating
with actor j six times a year, we also assumed actor j reported a tie of the same strength
with actor i. I took this approach because my snowball sampling procedure limited the
number of actors each participant could nominate to elicit a meaningful, but manageable,

sample size (Knoke & Yang, 2008).

23

Dependent variables (Table 1.2) included: (a) the eight individual risk perception
factors proposed and tested by Gore et a1. (2006; 2007a; 2007b), (b) a 3-item risk
likelihood scale created by averaging the responses on three questions (i.e., how likely is
it that cormorants will have negative effects on the environment, economy, and
recreational opportunities in northern Lake Huron in the next year), (c) a 3-item risk
acceptability scale created by averaging the responses on three questions (i.e., how
acceptable are the risks that cormorants pose to the environment, economy, and
recreational opportunities in northern Lake Huron), and (d) respondent’s belief in
science. All risk items were measured on 7-point scales and were conceptually recoded
from low risk (0) to high risk (6). Non-risk items were also measured on 7—point Likert-
type scales and were coded from strongly disagree (-3) to strongly agree (3).

Control variables included age, education, county of residence, and stakeholder
afﬁliation. I constructed matrices for all dependent variables, as well as age and
education to display the difference in response between two actors. For example, if actor i
was 52 years old and actor j was 62, a “10” would be placed in cell i, j. Matrices for
stakeholder afﬁliation and county of residence used an “exact match” method. This

6619’

meant that if actors i and j were both managers from a state wildlife agency, a would
be placed in cell i, j (Scherer & Cho, 2003).

I used SPSS 17.0 (2008) to compute descriptive statistics for actor attributes (e. g.,
age, education, gender, county of residence) and cormorant-related risk perceptions and
UCINET 6 (Borgatti, Everett, & Freeman, 2002) to describe and analyze all network

data. I did not weight my data because I did not make generalizations to a larger

population (Vaske, 2008). I used multiple regression quadratic assignment procedure

24

(MRQAP) to test the relationships between dependent variables and control variables
(Model 1) and with dyadic tie strength, the independent variable (Model 2). MRQAP is a
type of permutation test for multiple regression coefﬁcients of matrix or network data
(Dekker, Krackhradt, & Snijders, 2005). UCINET 6 (Borgatti, Everett, & Freeman, 2002)
generated standardized beta values. MRQAP is not based on ordinary least squares, so p-

values for changes in R2 are not generated.

RESULTS

Ninety-three percent of participants (n = 113) completed both the interview and
questionnaire. Respondents reported 700 ties out of 12,656 possible interactions between
the 113 actors (network density = 5.53%). Interactions among these 113 actors accounted
for 76% of all reported ties. Respondents were 24 to 72 (M = 52, SD = 11.6) years in age.
All participants had at least a high school diploma or equivalent. Eleven percent of
participants (n = 12) had some college, 3% (n = 3) attended vocational or trade school,
6% (n = 7) had an associate’s degree, 17% (n = 9) had a bachelor’s degree, and 54% (n =
61) had an advanced degree. Seventeen percent of respondents (n = 19) were female.
Primary stakeholder afﬁliations (Table 1.3) included anglers (22%, n = 25), state and
provincial government employees (21%, n = 24), federal government employees (12%, n

= 14), business interests (12%, n = 13), and universities (9%, n = 10).

Risk Perception Results
Certainty (M= 5.35, SD = l.27),ﬁequency (M= 5.18, SD = 1.42), dread (M = 4.32, SD

= 1.91), and seriousness (M = 4.15, SD = 2.12) of cormorant-related risks were factors

25

among the highest concern. Trust (M = 2.96, SD = 2.12) and responsiveness (M = 3.24,
SD = 2.04) of management agencies involved in cormorant management were factors of
the lowest concern. Participants indicated they thought it was somewhat likely (M = 3.67,
SD = 1.91) that cormorants would negatively affect the economy (M = 3.79, SD = 2.01),
recreational opportunities (M = 3.72, SD = 1.99), and the environment (M = 3.51, SD =
2.06) in northern Lake Huron in the next calendar year (Table 1.2). Most respondents
reported these risks as unacceptable (M = 4.12, SD = 1.89). Cormorant-related risks to
recreational opportunities in northern Lake Huron were rated most unacceptable (M =
4.21, SD = 2.06), followed by risks to the economy (M = 4.18, SD = 1.90), and the
environment (M = 3.91, SD = 2.06). Most participants also felt that science was the most

rational way to approach cormorant management (M = 1.29, SD = 1.78).

MRQAP Matrix Regression

Dyadic tie strength was a signiﬁcant predictor for ﬁve out of the eight risk perception
factors (i.e., certainty, dread, frequency, responsiveness, and severity); the more
frequently two actors communicated, the more likely they were to share Similar
cormorant-related risk perceptions as measured by these items (Table 1.4). The negative
coefﬁcients indicate a positive relationship, because the values in the matrices used for
analysis represented the degree of dissimilarity in perceptions between two actors (i.e.,
the larger the number in the matrix, the more dissimilar the two actors) (Scherer & Cho,
2003). Small standardized beta values are also expected from this type of analysis
(Scherer & Cho, 2003) because the analysis is predicting more than 12,000 possible

interactions from 113 actors. Control, naturalness, and trust were the only factors not

26

signiﬁcantly predicted by dyadic tie strength (all of which, however, were approaching
signiﬁcance of p < 0.10).

Dyadic tie strength was a signiﬁcant predictor of perceived likelihood (b = -0.042,
p < 0.001), but not acceptability (b = -0.023, p = 0.053) of cormorant-related risks.
Stakeholder afﬁliation and county of residence were signiﬁcant predictors of both
perceived likelihood (b = 0.094, p < 0.001) and acceptability (b = -0.093, p < 0.001).

Education was the only signiﬁcant predictor (b = 0.280, p < 0.001) for belief in science.

DISCUSSION

Cormorant-related risk perceptions were moderate to high for most respondents. Factors
of greatest concern were items related to individual capacity (e.g., certainty, dread,
frequency, and seriousness) whereas factors of least concern were items related to agency
capacity (e. g., trust and responsiveness) (Gore et al., 2006). These results should be
interpreted with caution however; results differ if responses from agency professionals
are compared to those of non-governmental stakeholders (see Appendix D) as non-
experts tend to have divergent risk perceptions from experts (e.g., Siegrist, Keller,
Kastenholz, Frey, & Wiek, 2007; Slovic, 1987). Comparing and contrasting these groups’
cormorant-related risk perceptions can inform wildlife-related risk communication
efforts. For example, if an objective of cormorant management in northern Lake Huron is
to attenuate cormorant-related risk perceptions among non-governmental stakeholders,
agency professionals could consider management approaches that address individual
capacity to reduce cormorant-related risks. This type of approach might include

disseminating information about how individuals can minimize their exposure to

27

cormorant-related risks (e. g., how to report concerns of cormorant-related risks to the
appropriate management agency, or how to start a volunteer harassment program).

One meaningful result of this work is that social networks are clearly an
important, and often overlooked, mechanism capable of inﬂuencing stakeholder risk
perceptions about HCCs in northern Lake Huron. The more frequently two actors
communicated (i.e., the greater the dyadic tie strength), the more likely they were to share
similar cormorant-related risk perceptions. Increased dyadic tie strength was signiﬁcantly
related to increased similarity of (a) ﬁve out of the eight individual factors (i.e, certainty,
dread, frequency, responsiveness, and severity) proposed by Gore et al. (2006, 2007a,
2007b), and (b) perceived likelihood of cormorant-related risks. The factors of highest
concern described above (i.e., those related to individual capacity) were also those factors
that were signiﬁcantly predicted by dyadic tie strength.

Dyadic tie strength was not a signiﬁcant predictor for (a) the individual factors
control, trust, and naturalness, (b) acceptability of cormorant-related risks, and (c) belief
in science. The latter result is also similar to Scherer & Cho (2003) who speculated that
the social network contagion theory of risk perception may only be applicable to
contentious issues, because non-contentious issues do not generate risk-related
discussions in communities.

Another meaningful ﬁnding is that contagion effects were detected in a mixed
network of expert (e. g., agency professionals) and non-expert stakeholder groups (e. g.,
anglers, bird enthusiasts) involved in HCC. Some (e.g., Burt, 1987) have speculated that
structural equivalence, rather than cohesion, creates more social pressure among experts

to adopt an innovation and is therefore not as effective at predicting expert perceptions. I

28

found evidence to suggest the cohesion model is relevant for both expert and non-expert
stakeholders involved in HCC; however, research is needed to see if contagion effects are
greater and more widespread if the network consisted of only non-expert stakeholder
groups.

This research highlights the importance for environmental risk communicators to
coordinate their risk communication efforts with communities (and their networks),
rather than individuals, in mind (Lundgren & McMakin, 2009). Social networks are an
important channel through which information about cormorant-related risks are
communicated, and as a result inﬂuence stakeholders’ risk perceptions about HCCs. If
deployed strategically, network channels may be used by agency professionals for risk
communication efforts that aim to reduce HCCs to a level deemed acceptable for both
humans and wildlife (Decker et al., 2002; Gore & Knuth, 2009).

Results reinforce the notion that the social network contagion theory of risk
perception is well suited for studying contentious environmental issues. However, the
framework has not deﬁned the criteria for what constitutes a contentious environmental
risk issue, or the threshold at which an issue moves from occurrence to controversial.
Future inquiry should look at participant’s perceptions of issue relevance (e.g., how does
the issue affect them and their family, is issue new or old) to see if this lends insight into
what makes an issue contentious enough to mobilize contagion effects.

Also unclear is the extent to which networks inﬂuence, if at all, the risk-related
behaviors of different stakeholders engaged in HWCs (e. g., letter writing, poaching,
allocation of resources); the network-related relationship between risk perceptions and

risk behaviors warrants additional consideration. Understanding the degree to which

29

social networks mediate the attitude-behavior connection would boost the predictive
ability of the model.

One ﬁnal unanswered question is whether stakeholders form different social
networks for different contentious environmental topics. Burt (1987) noted that physical
proximity among social entities can inﬂuence contagion and the formation of
communication networks. Results presented herein suggest physical proximity (i.e.,
county of residence) is a signiﬁcant predictor for inﬂuencing risk perceptions related to
HCCs. Therefore, it is possible that some of the inﬂuential, local actors for cormorant
management in northern Lake Huron are also inﬂuential actors for other contentious
ﬁsheries and wildlife issues (e. g., wolf management in Michigan’s Upper Peninsula, ban
on the spring bear hunt in Ontario). Regardless, managers may ﬁnd it advantageous to
take a proactive approach and provide risk-information to inﬂuential stakeholders in a
network at the onset of emerging HWCs to curtail risk ampliﬁcation within communities.
Future research should investigate the degree to which the actors of HCC-related
networks overlap with actors involved in other HWC-related networks in northern Lake

Huron.

30

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35

Table 1.1. Deﬁnitions of eight factors of wildlife-related risk perception adapted from
Gore, Knuth, Curtis, & Shanahan (2006; 2007a; 2007b) to assess risk perceptions
related to human-cormorant conﬂict around northern Lake Huron, August 2008—
August 2009.

 

 

 

 

 

 

 

 

 

 

Factor Adapted Deﬁnition

Certainty How convinced an individual is of the causes of cormorant-related risks and
how to avoid them

Control The degree of personal control an individual feels they have over avoiding
effects of exposure to cormorant-related risks

Dread Feelings of concern, worry or anxiety about the effects of exposure to
cormorant-related risks

Frequency How rare (e.g., catastrophic) or common (e.g., chronic) an individual believes
the effects of exposure to cormorant-related risks to be

Naturalness The extent to which an individual believes cormorant-related risks are
augmented by natural and human phenomenon

Responsiveness Perceived ability of management agencies to respond to cormorant related
risks in a timely and sufﬁcient manner

Seriousness Perceived severity of the effects of exposure to cormorant-related risks

Trust The extent that an individual believes the management agencies involved in

 

cormorant management will manage cormorant-related risks

 

36

 

Table 1.2. Respondents’ mean ratings on questionnaire items used to assess risk
perceptions related to human-cormorant conﬂict around northern Lake Huron, August
2008—August 2009. Scores can range from 0 (indicating low perceived risk) to 6
(indicating high perceived risk).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Questionnaire Item n Mean SD
[Certainty] 1f the cormorant population increases, human-cormorant l 13 5.35 1.27
interactions will increase.

[Control] I feel that l have control over the risks from cormorants. 112 3.88 1.84
[Dread] I worry about the risks from cormorants. 113 4.32 1.91
[Frequency] Managing the risks from cormorants in northern Lake 1 12 5.18 1.42
Huron will continue to be important in the future.

[Natural vs. Man-Made] Problems involving cormorants are increased 1 13 3.58 2.28
by man-made factors.

[Responsiveness] If there is a problem with cormorants, the resource 1 13 3.24 2.04
agencies responsible for management will respond accordingly.

[Seriousness] Cormorant management should be a top priority for 113 4.15 2.12
ﬁsheries and wildlife managers in northern Lake Huron.

[Trust] I trust the resource agencies involved in cormorant management 112 2.96 2.12
to manage cormorants appropriately.

Risk Likelihood Scale (3 items: Alpha = 0.94) 112 3.67 1.91
How likely do you think it is that recreational opportunities in northern 113 3.72 1.99
Lake Huron will be negatively affected by cormorants in the next year?

How likely do you think it is that the environment of northern Lake 112 3.51 2.06
Huron will be negatively affected by cormorants in the next year? ‘

How likely do you think it is that the economy of northern Lake Huron 112 3.79 2.01
will be negatively affected by cormorants in the next year?

Risk Acceptability Scale (3 items: Alpha = 0.94) 112 4.10 1.89
The risks posed by cormorants to recreation in northern Lake Huron are 112 4.21 2.06
acceptably low.

The risks posed by cormorants to the environment in northern Lake 112 3.91 2.06
Huron are acceptably low.

The risks posed by cormorants to the economy in northern Lake Huron 112 4.18 1.90
are acceptably low.

Belief in Science (1 item) 112 1.29 1.78
Science is the most rational way to approach cormorant management. 112 1.29 1.78

 

 

 

 

37

 

Table 1.3. Frequency of agency professional and non-governmental stakeholder groups
engaged in human-cormorant conﬂict around northern Lake Huron, August 2008—
August 2009.

 

 

 

 

 

 

 

 

 

 

 

Agency Professionals n % gtztlfgrgljzrsmemal n %
federal government 14 21 .2 anglers 25 22.1
former government 3 2.7 animal rights 1 0.9
state/provincial government 24 12.4 aquaculture 2 1.8
tribal resource interests 6 5.3 bird interests 3 2.7
business interests 13 1 1.5
commercial ﬁshermen 5 4.4
other professionals 5 4.4
policy 2 1.8
university 10 8.8

 

 

 

 

 

 

38

 

Table 1.4. Multiple regression quadratic assignment procedure (MRQAP) results for
models aimed at predicting cormorant-related risk perceptions of network actors
engaged in human-cormorant conﬂict around northern Lake Huron, August 2008—

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

August 2009.
Dependent Variables Model I Model 2 Model Fit (R2)
b 1 p-value b [ p-value

Certainty

Age .042 .171 .043 .168 .003

County .000 .502 .006 .430

Education -.004 .519 -.005 .517

Stakeholder Afﬁliation -.009 .336 -.007 .390

Dyadic Tie Strength -.025 .039 .003
Control

Age .035 .123 .035 .123 .005

County -.012 .232 ~.OO9 .309

Education .020 .244 .020 .265

Stakeholder Afﬁliation -.045 .020 -.043 .021

Dyadic Tie Strength -.019 .090 .005
Dread

Age .003 .443 .003 .445 .008

County -.070 .001 -.O64 .002

Education .010 .354 .009 .388

Stakeholder Affiliation -.041 .045 -.038 .049

Dyadic Tie Strength -.O30 .017 .009
Frequency

Age -.021 .349 -.020 .366 .010

County -.O2l .001 -.076 .001

Education -.O39 .291 -.O39 .278

Stakeholder Afﬁliation -.038 .087 -.036 .099

Dyadic Tie Strength -.023 .048 .011
Naturalness

Age .044 .049 .044 .049 .027

County .01 l .237 .016 .163

Education .150 .001 .149 .001

Stakeholder Afﬁliation -.033 .045 -.031 .041

Dyadic Tie Strength -.021 .052 .028
Responsiveness

Age .011 .303 .01 l .294 .007

County -.019 .102 -.01 1 .218

Education .071 .005 .070 .006

Stakeholder Afﬁliation -.033 .041 -.030 .046

Dyadic Tie Strength -.O39 .002 .009

 

 

 

 

 

 

 

39

 

Table 1.4. (Con’t). Multiple regression quadratic assignment procedure (MRQAP)
results for models aimed at predicting cormorant-related risk perceptions of network
actors engaged in human-cormorant conﬂict around northern Lake Huron, August

2008—August 2009.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

, Model I Model 2
Dependent Variables Model Fit (R2)
b Lp-value b p-value

Severity

Age .051 .074 .051 .077 .032

County -. 108 .000 -.103 .000

Education -.007 .487 -.008 .475

Stakeholder Afﬁliation -.1 14 .000 -.l 12 .000

Dyadic Tie Strength -.024 .049 .033
Trust

Age .030 .092 .030 .088 .016

County -.055 .003 -.051 .002

Education .085 .002 .084 .006

Stakeholder Afﬁliation -.052 .002 -.050 .005

Dyadic Tie Strength -.018 .084 .016
Belief in Science

Age .016 .342 .016 .313 .077

County .027 .106 .028 .096

Education .275 .000 .28 .000

Stakeholder Afﬁliation .003 .455 .003 .470

Dyadic Tie Strength -.005 .354 .077
Risk Likelihood Scale

Age .014 ' .304 .014 .271 .020

County -.O85 .000 -.079 .000

Education .032 .149 .031 .141

Stakeholder Afﬁliation -.092 .000 -.090 .000

Dyadic Tie Strength -.026 .034 .021
Risk Acceptabillty Scale

Age .028 .198 .028 .177 .024

County -.102 .000 -.097 .000

Education .041 .128 .040 .128

Stakeholder Afﬁliation -.085 .001 -.083 .000

Dyadic Tie Strength -.023 .053 .024

 

 

 

 

 

 

 

40

 

Figure 1.1. Map of study area: northern Lake Huron in Michigan, US. and Ontario,
Canada

 

41

CHAPTER 2

STRUCTURE AND INFLUENCE OF A STAKEHOLDER NETWORK
INVOLVED IN HUMAN-CORMORANT CONFLICT: IMPLICATIONS
FOR RISK COMMUNICATION

Effective communication is often considered to be one of the biggest weaknesses
of wildlife professionals and management agencies (e. g., Brunson, 1992; Decker et al.,
2002; Lautenschlager & Bowyer, 1985; Shanahan, Decker, & Pelstring, 2001) even
though it remains one of the most important dimensions of wildlife management. In
contentious wildlife management scenarios, the stakes of effective communication are
raised and the implications of deﬁciency magniﬁed by the increased diversity of affected
stakeholders and complexity of their interests. Ineffective communication can damage
agency image and negatively impact relationships with the public (Decker et al., 2002).
Understanding patterns of information and opinion sharing among and between
stakeholder groups can help depict communication processes and outcomes to agency
professionals, ultimately contributing to more meaningful methods of stakeholder
engagement.

SNA is one method available to help identiﬂ and map interactions among diverse
stakeholder groups (Bodin et al., 2006). The method has been used to characterize
stakeholder interactions as a factor of successful collaboration in natural resources
management (e.g., Lauber et al., 2008), and to identify actors for stakeholder engagement
processes (e.g., Prell et al., 2008; 2009). Ultimately, SNA unveils how the arrangement of
actors in a network can inﬂuence the degree to which information and other resources are

exchanged and mobilized within the network. This insight would be highly useful for

42

communication about contentious wildlife management issues where risks to people and
wildlife are present, such as HWCs. SNA may also help identify entry points for risk
messages, maximize communication efforts, and predict how stakeholder groups may
react to changes in management — all to the beneﬁt of improved communication with
stakeholders (Mueller etal., 2008). The extant literature is devoid of studies applying

SNA concepts to HWCs with implications for risk communication.

Objectives

I analyzed the structure of the network of agency professionals (e.g., state, federal,
provincial, or tribal ﬁsheries and wildlife managers) and non-governmental stakeholders
(e.g., anglers, birders, businesses) involved in HCC around northern Lake Huron.
Speciﬁcally, my research objectives were to (a) describe the overall structure of the
network, (b) document interactions between stakeholder groups, (c) locate and
characterize well-positioned (i.e., inﬂuential) networks actors, and (d) identify cliques
found within the network. I end the chapter with a discussion of the practical implications

for risk communication efforts associated with HWC management.

NETWORK STRUCTURE & POSITIONAL MEASURES

Key measures of network structure include density and centralization. Position-related
measures of individual actors include membership in cliques and three types of actor
centrality (i.e., degree, betweenness, and closeness). Each of these concepts is deﬁned

below.

43

Network Structure
Density is a network measure representing the number of reported ties, expressed as a
percentage of the maximum number of possible interactions among all network actors
(Wasserman & Faust, 1994). Density scores range from 0 (i.e., 0%), which indicates a
completely disconnected network (i.e., no ties exist among any of the actors), to 1 (i.e.,
100%), which indicates a fully connected network (i.e., all actors are directly tied to one
another). High density networks facilitate information exchange (Pretty & Ward, 2001)
and diffusion of innovations (Abrahamson & Rosenkopf, 1997); however, they also have
the potential of becoming too cohesive, which makes it difﬁcult for new actors and
information to permeate into the network (Redman & Kinzig, 2003). Although density is
a commonly used measure of network structure (Marsden, 1990), its interpretation is
limited because different sampling procedures and sample sizes produce different density
values. For example, Mandarano (2009) identiﬁed a density of 95% for an information
exchange network comprised of eight environmental organizations in New York and
New Jersey. Prell et al. (2009) found a density of 2% for a network of 147 actors
involved in management issues at Peak District National Park. Density tends to decrease
with larger sample sizes and when the number of ties an actor can nominate is restricted
(Scott, 2000). In this study of 113 actors, the highest density that could be obtained is
approximately 9% (because I limited each actor to nominating a maximum of 10 other
actors).

The concept of centralization is related to density, and is a better measurement of
the overall cohesiveness of a network (Scott, 2000). Networks that are highly centralized

(i.e., scores closer to 1, or 100%) have one, or few, actors holding the majority of ties in

44

the network. One advantage of highly centralized networks is that you only need to target
a few actors to access the entire network; however, highly centralized networks are
vulnerable to collapse when important actors exit the network (Prell et al., 2009). This is
especially problematic for contentious natural resource issues, such as HWCs, that

require long-term planning and stability of important actors.

Actor Attributes
Knowledge of the characteristics of individual network actors contextualizes
relationships among different type of actors (e.g., agency professionals vs. non-
governmental stakeholders, local vs. non-local actors, actors from different stakeholder
groups), as well as identiﬁes the most inﬂuential individuals within the network. One
actor attribute that is useful to characterize is whether or not an actor is local or non-local
(Lauber et al., 2008). Local actors live and/or work in communities engaged in HCCs.
Local actors are generally non-governmental stakeholders, for example anglers, business
owners, and commercial ﬁshermen. Non-local stakeholders live and work outside of the
communities engaged in HCCs, such as agency professionals or university-afﬁliated
actors. Lauber et al. (2008), for example, found that local stakeholders were important for
exchanging ideas and exerting inﬂuence within networks of local and non-local
stakeholders involved in community-based management initiatives in New York.

Degree centrality refers to the number of actors an individual is directly tied to
(Brass & Burkhardt, 1992). Actors with high degree centrality have many ties and are
typically the most visible actors in a network (Knoke & Yang, 2008). For example, a

local agency professional who is responsible for implementing management activities

45

(e.g., egg—oiling, lethal shooting) in the communities affected by HCCs may have high
degree centrality, because he or she regularly interacts with both local non-governmental
stakeholders and non-local agency professionals. As a result of their popularity, actors
with high degree centrality usually have access to diverse resources and sources of
information. According to Prell et al. (2009), actors with high degree centrality are
important for assembling networks to take action; however, they will not always be able
to inﬂuence those with whom they interact.

Betweenness centrality is another measure of actor centrality that describes how
often an individual actor is positioned between two unconnected actors (Brass &
Burkhardt, 1993). Individuals with high betweenness centrality function as information
brokers. They can facilitate and control exchanges between less central actors (Scott,
2000). Brokers are often responsible for bringing new information into a network (Burt,
2003) and are viewed as important for long term planning as they have ties that reach
beyond single communities (Bodin et al., 2006). An agency professional, for example,
might interact with both anglers and animal-rights activists about HCCs even though the
two groups do not interact. As a result, that agency professional can choose to share, or
withhold, information received from one group with the other.

Closeness centrality refers to an actor’s capacity to independently reach all other
actors in the network (Freeman, 1979). Actors with high closeness centrality scores can
interact easily with all network actors (Knoke & Yang, 2008). These individuals are also
capable of quickly and efﬁciently disseminating information throughout a network
(Rowley, 1997). An actor afﬁliated with a university, for example, might be able to share

new information about cormorants easily because he or she is well-connected to a variety

46

of agency professionals and non-governmental stakeholders throughout northern Lake
Huron.

Cliques are another network feature that describes groups of closely connected
actors. Cliques are cohesive groups of three or more individuals who are directly
connected to every other member of the clique. In other words, they can all reach each
other in one step (Knoke & Yang, 2008; Haythornthwaite, 1996). Cliques may overlap as
any individual actor may be a member of multiple cliques (Wasserman & Faust, 1994).
Maximum clique size is limited by sampling restrictions. In this study, participants were
asked to name up to 10 actors with whom they have talked to about cormorant
management in the last calendar year; so the largest clique size in the network described
herein is 11 members (i.e., the number of actors a person could nominate plus one).
(Knoke & Yang, 2008; Wasserman & Faust, 1994). Clique membership has been used to
study risk-related behaviors, such as smoking among adolescents (Ennett & Bauman,

1993)

METHODS & ANALYSIS

1 created a 113 x 113 matrix with study participant names listed in the row and column
headings (see Chapter 1 for a full overview of methods); the matrix represented 12,656
possible interactions between all of the actors. Values ranging from 0 (indicating no
interaction between the two actors) to 365 (indicating daily interaction between two
actors) were inserted into each of the matrix cells. The matrix was not symmetrized
(unlike the matrix in Chapter 1) so that I could identify the direction of reported ties. I

used UCINET 6 (Borgatti, Everett, & Freeman, 2002) to analyze the matrix, compute

47

network measures (i.e., density and centralization) and actor centrality scores, and to
identify cliques. Actor centrality scores were entered into SPSS 17.0 (2008) to calculate
mean scores. I used NetDraw (Borgatti, Everett, & Freeman, 2002) to create sociograms,

or visual representations of the network.

RESULTS

Network Structure

Fifty-four percent (n = 61) of respondents were local actors; the remaining 46% (n = 52)
were considered non-local. Respondents reported 700 ties out of 12,656 possible
interactions between the 113 actors (network density = 5.53%).These interactions (Figure
2.1) accounted for 76% of all reported ties. Network centralization was 2.72%. The
sociograrn (Figure 2.2) displaying actors grouped according to their stakeholder
afﬁliation illustrates that some stakeholder groups (e.g., federal, state, and provincial
government, anglers, universities, and business interests) are more greatly represented
and have more ties within the network than others; however, most of these ties are within
and amongst these more represented groups. Table 2.1 displays a matrix of dichotomous

interactions between stakeholder groups.

Actor Centrality Scores

Fifty-ﬁve percent of the top 20 (n = 11) degree centrality scores were held by agency
professionals: 30% were state or provincial government actors and 25% (n = 5) were
federal government actors. Other high degree centrality scores were held by anglers

(20%, n = 4), universities (15%, n = 3), and business interests (10%, n = 2). The t0p 20

48

degree, betweenness, and closeness centrality scores are displayed for central network
actors in Table 2.2.

Seventy percent (n = 14) of the top 20 betweenness centrality scores were held by
agency professionals including state and provincial government (40%, n = 8), federal
government (20%, n = 4), tribal interests (5%, n = 1), and former government (5%, n =
1). High betweenness centrality scores among non-governmental actors were held by
universities (15%, n = 3), anglers (10%, n = 2), and business interests (5%, n = 1).

Sixty—ﬁve percent (n = 13) of the top 20 closeness centrality scores were held by
agency professionals including state and provincial government (35%, n = 7), federal
government (20%, n = 4), former government (5%, n = 1), and tribal interests (5%, n =
1). Other high closeness centrality scores were held by anglers (15%, n = 3), business

interests (10%, n =2), universities (5%, n = 1), and other professionals (5%, n = 1).

Group Centrality Scores

Federal government actors held the highest degree (M = 446) and closeness centrality (M
= 50) scores. Although both federal and state/provincial government actors had high
betweenness centrality, former government actors (e. g., retired actors) demonstrated the
greatest betweenness centrality (M = 434). Agency professionals had higher centrality
scores than non-governmental stakeholders (Table 2.3). Universities, other non-
governmental professionals, business interests, and anglers were the most central non-

governmental stakeholder groups.

49

Cliques

There were many cliques (n = 140) among the 113 network actors. Approximately 79%
(n = 89) of actors were members of at least one clique. Ten agency professionals were
members of 10 or more cliques (max = 50); only three non-governmental stakeholders
were members of 10 cliques. F ifty-one percent (n = 71) of the cliques contained three
actors; 38% (n = 54) contained four actors; and 11% (n = 15) contained ﬁve actors.
Agency professionals, on average, were members of more cliques than non-governmental
stakeholders (Table 2.3); however, the majority of the cliques (61%, n = 85) consisted of
both agency professionals and non-governmental stakeholders; 31% (n = 44) consisted of

only agency professionals; and 8% (n = 11) consisted of only non-governmental

stakeholders.

DISCUSSION
The underlying social structure of agency professionals and non-governmental
stakeholders engaged in HCCs around northern Lake Huron is dynamic and intricate.
Network density and centralization were both relatively low indicating that: (a) new
actors can readily enter the network (at least peripherally); (b) new information and
resources can be easily exchanged; and (c) there are numerous actors who hold central, or
inﬂuential, positions within the network. Thus, the structure of the network is fairly
resilient to minor changes (e. g., actors entering or exiting the network) — a useful trait for
networks involved in long-term management issues, like cormorant management.
Federal, state, and provincial government agencies, anglers, business interests,

and universities were the most represented stakeholder groups in the network. These

50

groups held the majority of positions and ties within the network, tended to belong to
more cliques, and typically had higher centrality scores. Conversely, animal rights,
aquaculture, policy, and bird interests were the least represented stakeholder groups.
Actors from these latter groups held fewer positions and ties within the network, tended
to belong to fewer cliques, and were generally less central in the network. According to
Prell et al. (2009), these less central stakeholder groups “represent areas of the network
where more tie-formation can be encouraged through inclusive dialogue” (p. 513).
Stakeholder engagement processes could deliberately target these underrepresented
groups.

Social networks serve as vital channels for information about cormorant-related
risks for both agency professionals and non-governmental stakeholders. Agency
professionals in the network, however, seem to serve as sources of connorant—related
information (rather than seekers of cormorant-related information). This is evidenced by
the number of directional ties leading to agency professionals from non-governmental
stakeholders (rather than vice versa). In the future, agency professionals may want to
reciprocate more ties with non-governmental stakeholders (i.e., engage in more two-way
communication).

Because risk communication efforts may be most successful if messages are
tailored to speciﬁc stakeholder groups and disseminated through the primary
communication channels these stakeholders use (Decker et al., 2002), agency
professionals could consider using existing networks as a source for disseminating risk
messages (Lundgren & McMakin, 2009). HWC-related networks span geographic and

political boundaries, as well as connect divergent stakeholder groups; consideration of

51

social networks while designing communication programs may provide managers with
new tools to address wildlife—related risk perceptions. Testing the efﬁcacy of social
networks as a source of information for wildlife-related risks would compliment existing
work evaluating the impact of other materials (e.g., brochures, magnets) commonly used
by wildlife professionals (Gore, Knuth, Scherer, & Curtis, 2008).

Deﬁning network structure has two primary management implications
(Haythomthwaite, 1996). First, managers may strategically integrate themselves into
central network positions by identifying central actors and groups with whom they would
need to establish relationships. This approach may be challenging, yet desirable for (a)
agency professionals who are new to HCC-related networks and who want to integrate
themselves into the network, or (b) existing agency professionals who ﬁnd themselves
isolated from HCC-related networks and/or desire a leadership position in the network. In
both instances, agency professionals can actively seek out highly central non-
governmental stakeholders in effort to foster new relationships, garner stakeholder trust
in cormorant management, and improve the agency’s image (Decker et al., 2002). They
can also be aware that their central location in a network will carry certain responsibilities
(e. g., addressing stakeholder questions and concerns about cormorants and management).

Second, wildlife professionals may rely on existing central actors (rather than
trying to foster new relationships or create new actor positions) as entry points for
disseminating risk information (Haythomthwaite, 1996). In the HCC-network, this might
mean relying on local agency professionals (i.e., those who are already based in the
communities where HWCs occur) to initiate and disseminate risk communication efforts

rather than non-local agency professionals — even if they are higher in the chain of

52

command. Resultant cost and time savings could boost agency efﬁciency. Comparing this
approach to more traditional, targeted interventions such as mass informational
campaigns which are not guaranteed to reach their intended audience adds value to the
network approach (Lundgren & McMakin, 2009).

This latter approach (e. g., relying on existing actors) seems most appropriate
within the context of cormorant management around northern Lake Huron. Agency
professionals (both local and non-local) are already well-positioned in central roles in the
network; however, central actors identiﬁed through SNA may or may not be aware of
their power and inﬂuence. This is one reason why it is essential that these actors are
aware of their role in the network and are also able to effectively communicate about
cormorant-related risks. Additional consideration should be given to the cormorant-
related risk perceptions of central actors. Thinking speciﬁcally about those individual’s
perceptions may predict the type of frame those individuals use when spreading
cormorant-related information throughout the network. Future research should evaluate
the effectiveness (i.e., speed of message diffusion, accurateness of information over time)
of using social networks for disseminating risk information about HWCs.

Actor centrality scores indicated which inﬂuential agency professionals and non-
governmental stakeholders are best positioned to disseminate risk information and
cultivate new, external relationships. If the objective of the risk communication
intervention is to reach disconnected stakeholder groups (e.g., bird and policy interests in
the network presented herein) managers should consider selecting actors with high
betweeness centrality scores (e.g., actors 0005, 0007, 0031, 0048, and 0001), because of

their ability to serve as information brokers (e.g., Prell et al., 2008). In situations of crisis

53

(e. g., cormorants are found to transmit Newcastle disease to poultry), however,
individuals with high closeness centrality scores (e.g., actors 0005, 0007, and 0001) may
be particularly vital for quickly diffusing information throughout the network (Lundgren
& McMakin, 2009). Actors who hold high scores across all three centrality measures
(e.g., actors 0001, 0005, 0007, and 0042) may be able to accomplish multiple tasks
simultaneously (i.e., reaching a larger proportion of network actors, while also branching
unconnected stakeholder groups, and quickly diffusing information throughout the
network).

HCCs have been occurring in northern Lake Huron and throughout the Great
Lakes Basin for decades. In the 19705, cormorants were portrayed as victims of human-
corrnorant interactions; whereas today, cormorants are perceived as perpetrators of
environmental, recreational, and economic risks (Muter et al., 2009). Given the dynamic
nature of cormorant management and social networks in general, actors with high
betweenness centrality may play essential roles in long-term planning and sustainability
of future HCC management.

The overall structure of a network may change whenever established actors leave
or whenever new actors enter a network (Wasserman & Faust, 1994). Deﬁning the
structure of networks of long-term issues, like cormorant management, may be useful to
predict and respond to changes in overall structure, especially when central actors leave a
network (e.g., retire). As actors phase themselves out of a network (whether immediately
or gradually), the connecting ties they hold will eventually break down. Agency
professionals may want to attempt to restore those connections or attempt to develop

connections with those groups before they dissolve and become unconnected.

54

One last unanswered question relates to the extent in which inﬂuential network
actors are central because of their occupation and related responsibilities. In other words,
are agency professionals central network actors simply because they are tasked with
managing HCCs? Are job titles better predictors of centrality than individual personality
traits? Research is needed to assess characteristics of both agency professionals and non-

governmental actors with varying degrees of centrality to address this question.

55

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58

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59

governmental network actors (n = 66, represented by white nodes) engaged in human-cormorant conﬂict around northern Lake

Figure 2.1. Sociogram showing directional ties of agency professionals (n = 47, represented by gray nodes) and non-
Huron, August 20084August 2009.

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60

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Figure 2.2. Sociogram of 113 network actors engaged in human-cormorant conﬂict around northern Lake Huron (August

2008—August 2009) and grouped according to their stakeholder afﬁliation.

Table 2.1. Matrix of interactions between agency professional and non-governmental

stakeholder groups engaged in human-cormorant conﬂict around northern Lake Huron,
August 2008-August 2009. An “X” placed in a cell indicates there are ties among
actors between the two groups.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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anglers X - - - X - X - - X X - -
animal rights - - - - - - X - - - X - X
aquaculture - - X - X - - - - - - - -
bird interests - - - - - - - - - - x - -
business interests X - X - X X X X X - X - -
commercial ﬁshermen - - - - X X - - - - X X X
federal government X X - X X - X X X X X X X
former government - - - - X - X X X - X X -
other professionals - X - - X - X X X - X - X
policy X - - - - - X - - - X - -
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tribal interests X - - - - X X X - - X X X
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61

 

Table 2.2. Top 20 degree, betweenness, and closeness centrality scores identiﬁed for
actors in a network of agency professionals and non-governmental stakeholders
involved in human-cormorant conﬂict around northern Lake Huron, August 2008—

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

August 2009.
1D Stakeholder Local or Degree Betweenness Closeness
Afﬁliation Non-Local Centrality Centrality Centrality

0008 angler local - 755 54
0020 angler local 1014 479 52
0032 angler local 806 - -
0033 angler local 949 356 51
0037 angler local - - 51
0040 angler local 620 - -
0089 angler local 502 - -
0041 business interests local 540 - 51
0069 business interests local 462 393 52
0001 federal gov non-local 673 1 133 63
0007 federal gov local 1 183 1420 67
0012 federal gov local 1339 - -
0031 federal gov non-local - 1 196 56
0038 federal gov local 719 518 -
0045 federal gov local 1086 - 52
0048 former gov non-local - 1175 51
0070 other professionals local - - 50
0002 state/provincial gov non-local - 934 S6
0003 state/provincial gov non-local - 519 -
0005 state/provincial gov local 701 2761 71
0009 state/provincial gov local - - 54
0022 state/provincial gov non-local - 542 52
0042 state/provincial gov local 907 772 59
0057 state/provincial gov non-local - 450 50
0074 state/provincial gov non-local 511 - -
0075 state/provincial gov non-local - 439 -
0088 state/provincial gov non-local 530 - -
0120 state/provincial gov non-local 459 - -
0018 tribal interests local - 893 55
0030 university non-local 463 362 52
0056 university non-local 455 392 -
0058 university non-local - 573 -
01 16 university local 453 - -

 

62

 

Table 2.3. Average degree, betweenness, and closeness centrality scores and clique
membership for each stakeholder group involved in human-cormorant conﬂict around
northern Lake Huron, August 2008 — August 2009.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Stakeholder n Degree Betweenness Closeness Clique
Afﬁliation Centrality Centrality centrality Membership
anglers 25 242 83 36 2.6
animal rights 1 9 95 39 3.0
aquaculture 2 70 1 24 0.0
bird interests 3 17 0 26 0.7
business interests 13 222 94 39 2.9
commercial ﬁshermen 5 197 88 35 0.2
federal government 24 446 348 50 10.5
former government 3 267 434 42 4.0
other professionals 5 317 35 46 4.6
policy 2 70 0 47 3.0
state/provincial gov I4 246 301 46 6.5
tribal interests 6 54 175 39 2.7
university 10 271 167 45 3.5

 

 

 

 

 

 

63

 

CHAPTER 3

Muter, B. A., Gore, M. L., & Riley, S. J. (2009). From Victim to Perpetrator: Evolution
of Risk Frames Related to Human-Cormorant Conﬂict in the Great Lakes. Human
Dimensions of Wildlife, 5, 366—379.

64

CHAPTER 3

From Victim to Perpetrator: Evolution of Risk Frames Related to Human-
Cormorant Conﬂict in the Great Lakes

To better understand media coverage and perceptions of risk associated with human—
cormorant conflicts, we adapted the notions of “victim ” and “perpetrator ” to the context
of cormorant-related risks and applied them as risk ﬂames in a content analysis. We
characterized stories about cormorants in 140 US. and Canadian newspaper articles
published between 1978 and 2007 to document how coverage has changed through
time. The total number of stakeholder groups and risks perpetrated by cormorants
identified in coverage increased over our study period, shifting the predominant risk
frame applied to cormorants from victim to perpetrator. We discuss the implications of

this shift and the use of risk frames in content analyses to inform risk communication.

Keywords: double-crested cormorant, framing, human—wildlife conﬂict, media content

analysis, risk perception

INTRODUCTION

Conﬂicts linking humans and wildlife are increasing in frequency and intensity
worldwide (Conover, 2002). Human—wildlife conﬂict (HWC) occurs when the actions of
either humans or wildlife cause, or are perceived to cause, negative effects on the other.
Concern over HWCs is rooted in public perceptions of risk to wildlife and their
respective habitat, as well as risks from exposure to wildlife (Decker, Lauber, & Siemer,

2002). Wildlife pose risks to human health and safety (e.g., zoonotic diseases, wildlife

65

attacks, wildlife—vehicle collisions), personal property, agriculture (e.g., livestock loss
due to depredation), aesthetics (e.g., goose droppings on golf courses), and other species
of wildlife that humans value (Conover, 2002). Perceptions of these risks shape public
attitudes, beliefs, and support for wildlife management activities (Knuth, Stout, Siemer,
Decker, & Stedman, 1992), inﬂuence wildlife-stakeholder acceptance capacity (Riley &
Decker, 2000), affect trust in agencies and managers (Kasperson, Jhaveri, & Kasperson,
2001), and stimulate stakeholder action (Decker et al., 2002).

Many HWCs attract the attention of mass media (Corbett, 1995) because they
feature recognizable personalities, polarized perspectives, and have local signiﬁcance
(Price & Tewksbury, 1997). Media often highlight low-incidence, high-consequence
events such as wildlife-related human fatalities, and contentious issues like suburban deer
management and spotted owl conservation. Media coverage can inﬂuence and be
inﬂuenced by stakeholders’ risk perceptions (Gans, 2004); however, the relationship is
ill-deﬁned within a HWC context. Clarifying the association between risk perception and
media coverage of HWCs may aid wildlife managers in reﬁning outreach interventions,
reducing conﬂict among stakeholders, and more effectively engaging stakeholders in
discussions about management (Pelstring, Shanahan, & Perry, 1997). A longitudinal
examination of media coverage may provide insight into how and why management of a
wildlife species does or does not evolve into a contentious issue.

One species that has received considerable media attention in the Great Lakes
Basin is the double-crested cormorant (Phalacrocorax auritus). These piscivorous,
colonial-nesting waterbirds were virtually extirpated in the Basin by the 19703 due to

widespread use of dichloro-diphenyl-trichloroethane (DDT), polychlorinated biphenyls

66

(PCBs), and other contaminants (Weseloh & Collier, 1995; Weseloh, Pekarik, Havelka,
Barrett, & Reid, 2002). News coverage during the 1970s used cormorants as an example
of the many avian victims to commercial pesticides. Federal reductions in the use of DDT
(i.e., the US. Environmental Protection Agency banned commercial use in 1972), and
protection afforded by the Migratory Bird Treaty Act of 1918 helped cormorant numbers
rebound dramatically. Between 1970 and 1991, the population increased from 89 to
38,000 nesting pairs in the Basin (Weseloh et al., 2002). This exponential increase
continued throughout the 1990s and was accompanied by growing public concern about
the ecological and economic impacts perpetrated by the birds (Taylor & Dorr, 2003),
including the potential risks cormorants posed to recreational ﬁsheries, island vegetation,
and other colonial-nesting waterbirds. By 2002, approximately 115,000 breeding pairs of
cormorants visited the Basin during migration (Weseloh et al., 2002). Concerns about
cormorants and their associated risks in the Basin have inﬂuenced federal policies and
management decisions (USFWS, 2003).

Cormorants are perceived as overabundant by many stakeholders and appear to
have exceeded wildlife-stakeholder acceptance capacity of several stakeholder groups
(e.g., anglers, ﬁsh farmers) throughout their range (Taylor & Dorr, 2003). For other
groups (e.g., bird advocates, animal rights activists), however, the recent population
expansion signiﬁes a natural outcome of restoration of Basin ecosystems (Wires &
Cuthbert, 2006). Despite more than a decade of management actions to address human—
cormorant conﬂict in the Basin (e. g., hazing, egg-oiling, and lethal shooting activities),

debate persists about management, and stories on cormorants still frequent the media. To

67

this end, we examined 30 years of media coverage about cormorants in the Basin to better

understand the media’s role in changing risk perceptions.

CONCEPTUAL BACKGROUND & HYPOTHESES

Media, Framing, and Risk

Frames and framing are vague mass communication concepts and are often applied in
different situations to mean different things (Scheufele, 1999). Framing effects research
has generally focused on how information is presented, the medium employed (e.g., print
media), and how that information is interpreted by various publics. Frames highlight
certain pieces of information over others in an attempt to make those pieces more
conspicuous, memorable, or signiﬁcant (Entman, 1993). Individuals use frames to
organize, focus, and interpret their perceptions (Elliott, 2003). Frames may be inﬂuenced
not only by how information is communicated, but also by the personal traits of the
individual making a decision (Tversky & Kahneman, 1981). Frames help people deﬁne
problems, make moral judgments about those problems, and offer potential solutions
(Entman, 1993; Iyengar, 1991).

The way mass media portray the environment helps the audience interpret
environmental issues and shape opinions about those issues (Jensen, 2003). Media frames
also function at a sociocultural level and are capable of inﬂuencing the publics’
emotional responses toward the environment (Cottle, 1993). Journalists and editors use
photos, illustrations, attention—grabbing headlines, and text to communicate risks and help
frame their stories. Placement and repetition of keywords, phrases, and imagery can make

certain information salient (Entman, 1993). Frames of storylines in the mass media may

68

be inﬂuenced by the political orientation of the news medium, and by external politicians,
scientists, interest groups, or vocal stakeholders who are interviewed by journalists when
forming a news story (Gans, 2004). Media framing can inﬂuence readers or viewers by
telling them what to think about an issue, a process known as agenda setting, or how to
think about an issue (Wimmer & Dominick, 2003).

Framing inﬂuences beliefs about how wildlife-related issues should be addressed
and resolved (Siemer, Decker, & Shanahan, 2007) and can provide important historical
insight into management (Decker, Brown, & Siemer, 2001). Wolch, Gullo, and Lassiter
(1997), for example, investigated the Los Angeles Times’ portrayal of mountain lions
between 1985 and 1995 and found that coverage became increasingly negative in the
19905, which they attributed to escalating human—mountain lion conﬂicts throughout
California. Jensen (2003) acknowledged that everyday communications about social
issues (e.g., increasing frequency of HWCs) among publics are likely shaped by
storylines presented in the mass media, and those communications can reciprocally
inﬂuence the evolution of storylines in the media. Similar longitudinal studies on effects
of framing can be useful in identifying changing frames in news coverage over the
lifespan of an issue (Chyi & McCombs, 2004). Frame changes may be inﬂuenced by
available information on potential risks and negative events that increase risk (Marks,

Kalaitzandonakes, Wilkins, & Zakharova, 2007).

Risk Frames

Risk frames are powerful predictors of public risk perception (Elliott, 2003). Individuals

69

frame risks according to cognitive or affective characteristics of the risk, or some
combination of both (Marks et al., 2007). Unlike cognitive risk perception, which is an
individual’s assessment, or perceived probability, of a risk (Renn, 1998), affective risk
perception relies heavily on intuitive feelings or reactions to a risk (Sjoberg, 1998).
Affective risk perception is inﬂuenced by feelings of goodness or badness attached to a
particular stimulus (Slovic & Peters, 2006). Reporters use both cognitive and affective
elements when framing news stories. Media coverage also contributes to public
awareness of risks and victimization (Best, 1997). Because most news stories are episodic
(i.e., case-study oriented) in nature, coverage generally assigns responsibility to
individual victims or perpetrators, rather than to society (Iyengar, 1991). The media can
also identify which victims deserve sympathy and which do not (Best, 1997; Ryan,
2002).

The terms “victim” and “perpetrator” are applied to diverse disciplines and
offenses, from domestic abuse (e.g., Gortner, Gollan, & Jacobson, 1997) to wildlife
poaching (e.g., Lorenzini, 2005). A victim typically is deﬁned as an entity that receives
some sort of harm or negative effect, while a perpetrator is described as an entity that
inﬂicts harm or a negative effect (Young, 2007). Renn (1998) and Best (1997) similarly
noted that victims are usually typiﬁed as innocent and unsuspecting, and typically
exposed to risk involuntarily. Claims about victims often ﬁt a template for news coverage
of social issues because they (a) can be characterized in dramatic terms, (b) help to build
connections between the reader and the victim, and (c) offer hope that some management
intervention will occur (Best, 1997). Environmental criminology applies several

analytical frameworks based on whom or what plays the role of the victim— humans,

70

animals, or the environment (White, 2008). In this literature, however, the perpetrator of
interest is always human—individuals, corporations, or govemments—causing
environmental harm or risk (e. g., pollution, poaching).

The concepts of victims and perpetrators may be extended to HWCs, especially
when risk is involved. The role of perpetrator may be extended to wildlife when they are
perceived, or portrayed, as a source of risk. Wildlife may also be victims when they are
perceived, or portrayed, as the recipient of risk or harm. Understanding the risk frames
applied to cormorants and how those frames have evolved over the last three decades
may help wildlife professionals gain a better understanding of wildlife-related risk
perceptions and may have practical implications for how managers respond to media

coverage about cormorants (Gore, Siemer, Shanahan, Schuefele, & Decker, 2005).

Hypotheses

Our study sought to evaluate the risk-related content of news coverage about cormorants
and their management in the Basin over the last three decades (1978—2007). Our research
objectives were to (a) characterize the context of the coverage, (b) document how
coverage has evolved over the past 30 years, and (c) evaluate the risk frame (i.e., victim,
perpetrator, or neutral) applied to cormorants by the print media. Based on our literature

review, we developed the following hypotheses about cormorant-related news coverage:

H1. The predominant risk frame assigned to cormorants has evolved from victim to
perpetrator over our study period.

H2. Perpetrator coverage will be positively associated with the number of identiﬁed

71

stakeholder groups (per article).

H3. The total number of identiﬁed stakeholder groups (per article) will increase over our
study period.

H4. The total number of identiﬁed risks to cormorants (per article) will decrease over our
study period.

H5. The total number of identiﬁed risks from cormorants (per article) will increase over

our study period.

METHODS
Sampling Frame
In January 2008, we conducted a content analysis of US. and Canadian newspaper
coverage reporting on cormorants in the Basin. We searched Lexis-Nexis, an online
periodical database, for all articles printed between 1978 and 2007 using the key words:
“cormorant(s),” “double-crested cormorant(s),” and “Great Lake(s).” Articles did not
have to focus primarily on cormorants to be included in our population. We included
articles that discussed cormorants in a variety of contexts (e. g., angling, bird-watching,
avian diseases, pollution) to better understand risk frame evolution. Articles that did not
pertain to double-crested cormorants in the Basin were not included in the population.
We also excluded congressional testimonies and transcripts that appeared in federal news
services. We found 108 articles suitable for analysis.

We also sampled Newsbank with the key word “cormorant(s)” to search 20 (all
available) Michigan newspapers for articles printed between 2005 and 2007. This non-

traditional approach was used because our Lexis-Nexis search did not identify any

72

articles from Michigan newspapers. This was problematic as Michigan has more breeding
pairs of cormorants than any other state along the US. side of the Great Lakes (Wires,
Cuthbert, Trexel, & Joshi, 2001). Other geographic regions in the Basin experiencing
human—cormorant conﬂict (e. g., eastern New York) were represented by articles
generated with our Lexis-Nexis search. We used a random number generator to sample

articles (n = 32) from Newsbank.

Coding Protocol
Articles were coded based on our study objectives. Training seSsions were conducted
until percent agreement among coders was over 90% for most variables. Two individuals
coded all articles. Coders examined each article for identifying characteristics (e. g., date
of publication, origin of news source, section in which the article appeared) and identiﬁed
the predominant risk frame (i.e., victim, perpetrator, or neutral) applied to cormorants.
Coders also reported the presence/absence of 37 variables organized into four
content categories: (a) stakeholder groups (Table l), (b) risks to cormorants (Table 2), (c)
risks from cormorants (Table 3), and (d) attributions of responsibility (Table 4). The
phrase “attribution of responsibility” was used to mean that an article made one or more
statements indicating some individual or group (e.g., a wildlife management agency) was,

or should be, taking action to reduce risks associated with human—cormorant conﬂict.

Risk Frames
Cormorants were coded as victims when a news story presented them as receiving some

negative effect or risk, for example, from commercial contaminants (e. g., DDT), diseases

73

(e.g., avian botulism), poaching, or management actions (e.g., when cormorants were
presented as a scapegoat for other Great Lakes issues). Cormorants were coded as
perpetrators when a news story presented them as a source of some negative effect or
risk, for example, to the environment (e.g., destruction of vegetation), economy (e.g., loss
in tourism dollars in ﬁshing communities), or recreation (e.g., declines in angler success).
Some articles presented both victim and perpetrator-oriented risk frames. We adapted the
protocol from Siemer et al. (2007) to determine an overall risk frame for each article. We
labeled the predominant frame for each paragraph and summed paragraph assignments. If
one risk frame occurred in two or more paragraphs more than another risk frame, the
article was coded the predominant frame. If neither frame was used, or if there was an
equal number of perpetrator- and victim-oriented paragraphs (i.e., or within one

paragraph on either side), the story was coded as neutral.

Intercoder Reliabiiity

Cohen’s kappa (Cohen 1960; 1968) was used to assess intercoder reliability. Kappa is
commonly used to adjust for chance and is appropriate for two coders when categories
are exhaustive and mutually exclusive (Capozzoli, McSweeney, & Sinha, 1999). Kappa
values were computed for each variable across all 140 articles. A kappa of 0.7 or greater
is generally acceptable for exploratory research and represents a strong level of
agreement above chance (Lombard, Snyder-Dutch, & Bracken, 2002). We dropped all

variables with a kappa < 0.7 from our analysis.

74

Data Analysis

We used multinomial logistic regression analyses to predict risk frames (i.e., victim,
perpetrator, neutral) with two single-predictor models (i.e., article date to test HI, and
total number of stakeholders to test H2). The perpetrator frame served as our reference, or
baseline, category; neutral and victim frames were treated as comparison categories.
Wald Chi-Square tests were used to test our hypotheses that regression coefﬁcients for
the neutral and victim frames relative to the perpetrator frame would be less than zero.
Odds ratios for the coefﬁcients indicated the direction of association. We visually
represented the risk frame evolution using predicted probability over time (Figure 1).

We computed the total number of (a) stakeholder groups, (b) risks to cormorants,
and (c) risks from cormorants, for each article by summing the number of present
variables for each respective content category. These computed variables served as
dependent variables in linear regression analyses. (i.e., article date was the independent
variable) to test H3, H4, and H5. Logistic regression was used to describe associations of
dichotomous variables (i.e., presence/absence of individual risks and stakeholder groups)

with article date (i.e., through time).

RESULTS

We analyzed 140 articles. More than half (n = 79, 56%) were from six Canadian
newspapers: Toronto Star (n = 28, 20%), Globe and Mail (n = 25, 18%), Gazette (n = 9,
6%), Toronto Sun (n = 7, 5%), National Post (n = 5, 4%), and the Ottawa Citizen (n = 5,
4%). The most prevalent of the 20 US. newspapers (11 of which were Michigan

publications) included New York Times (n = 15, 11%), Bay City Times (n = 8, 6%),

75

Grand Rapids Press (n = 6, 4%), and the Flint Journal (n = 5, 4%). F ifty-one percent (n
= 71) of the articles discussed cormorants in < one paragraph, 9% (n = 13) in two to four

paragraphs, and 40% (n = 56) in > ﬁve paragraphs.

Risk Frames

We have evidence in support of H1 (i.e., that the predominant frame changed from
victim to perpetrator over our study period). Wald Chi-Square tests of the coefﬁcients for
the neutral (x2 (2, n = 140) = 8.76,p < .010) and victim frames (x2 (2, n = 140) = l6.66,p
< .001) relative to the perpetrator frame were both signiﬁcantly less than zero. Odds
ratios for the coefﬁcients (OR = 0.90, p < .010, for the neutral frame and OR = 0.86, p <
.001, for the victim frame) demonstrate that the neutral and victim frames became less
likely over our study period, while the perpetrator frame became more likely over time
(Figure 1).

The data supported H2 (i.e., that perpetrator coverage was positively associated
with the total number of identiﬁed stakeholder groups). Wald Chi-Square tests of the
coefﬁcients for the neutral (x2 (2, n = 140) = 21.25, p < .001) and victim frames (x2 =
15.16, p < .001) relative to the perpetrator frame were signiﬁcantly less than zero. Odds
ratios for the coefﬁcients (OR = 0.55, p < .001, for the neutral frame and OR = 0.64, p <
.001, for the victim frame) show that the neutral and victim frames became less likely as
the total number of identiﬁed stakeholder groups increased, while the perpetrator frame

became more likely with an increasing number of stakeholder groups.

76

Stakeholder Groups

The total number of stakeholder groups identiﬁed (per article) increased over our study
period (r = .30, p < .001) providing support for H3. Articles reported up to 9 (of 15
possible) stakeholder groups (M = 3.4). State and provincial government agencies,
recreational anglers, and federal government agencies were each mentioned in >50% of
the articles (Table 1). Odds ratios indicated positive associations between article date and
an article’s inclusion of anglers (OR = 1.11, p < .001), nongovernmental organizations in
support of cormorant management (OR = 1.09, p = .030), state or provincial government
agencies (OR = 1.09, p = .002), and legislators (OR = 1.12, p = .003) (Table 1). In other
words, the more recent an article was published, the more likely it was for these
stakeholder groups to be identiﬁed. Only nongovernmental organizations speaking out

against cormorant management (OR = 0.17, p < .001) declined signiﬁcantly over time.

Cormorant-Related Risks

The total number of risks to cormorants identiﬁed (per article) did not change
signiﬁcantly over our study period (r = .14, p > .05); indicating that H4 was not
supported. The majority of articles (n = 71, 51%) identiﬁed one or more (of eight
possible) risks to cormorants; 31% identiﬁed one risk, 16% identiﬁed two risks, and 4%
identiﬁed three risks (M = 0.75). DDT (n = 34, 24%) and management action, when
cormorants were portrayed as being wrongfully managed (n = 22, 16%), were the most
commonly cited risks to cormorants (Table 2). We found a negative association between
article date and an article’s noting of cormorant deformities (OR = 0.85, p < .001) (Table

2).

77

The total number of risks from cormorants identiﬁed (per article) increased over
time (r = .27, p < .001), providing evidence for H5. Approximately half of the articles (n
= 72, 51%) identiﬁed one or more (of nine possible) risks from cormorants; 7% identiﬁed
one risk, 15% identiﬁed two risks, 8% identiﬁed three risks, and 21% identiﬁed between
four and eight risks (M = 1.7). The most commonly identiﬁed risks from cormorants were
risks to ﬁsh populations (n = 61, 44%) and recreational ﬁshing (n = 59, 42%) (Table 3).
The more recent an article was published, the more likely it was to have mentioned the
risks cormorants pose to ﬁsh populations (OR = 1.09, p = .003), recreational ﬁshing (OR
= 1.10, p < .001), and tourism (OR = 1.18, p = .028) (Table 3). Over time, articles were
also more likely to note negative psychological effects (OR = 1.08, p = .021) associated

with human—cormorant conﬂict (e. g., worry, fear).

Attributions of Responsibility

The majority of articles (n = 88, 63%) attributed responsibility to one or more stakeholder
groups; 34% (n = 48) attributed responsibility to one group; 26% (n = 36) attributed
responsibility to two groups; 2% (n = 3) attributed responsibility to three groups; and
<1% (n = 1) attributed responsibility to four groups (M = 0.95). Only 4% (n = 6) of the
articles analyzed suggested that citizens were responsible for resolving negative
interactions with cormorants in the Basin. Thirty-six percent (n = 51) of articles attributed
responsibility to a state or provincial agency for managing human—cormorant conﬂict,
30% (n = 42) to a federal agency, and 16% (n = 22) to legislators (Table 4). Article date
and attribution of responsibility to state or provincial government agencies (OR = 1.08, p

= .012) and legislators (OR = 1.15, p = .003) were positively associated. Article date and

78

attribution of responsibility to a federal government agency was negatively associated

(OR = 0.94, p = .031).

DISCUSSION

Media coverage about human-cormorant conﬂict in the Great Lakes Basin has been
dynamic over the last three decades. Articles have evolved from depicting cormorants
primarily as recipients of risk (e.g., from pesticides, diseases, and lethal management
actions) to principally sources of risk (e.g., to ﬁsh populations, vegetation, and tourism),
shifting the predominant risk frame applied to cormorants by the print media from victim
to perpetrator. This evolution of risk frame is reﬂected in several trends in coverage over
our 30-year study period. First, there was an increase in articles identifying the potential
risks perpetrated by cormorants to ﬁsh populations, recreational ﬁshing, and tourism.
There was also an increase in articles noting stakeholders’ worry or fear (e.g., negative
psychological effects) associated with human—cormorant conﬂict. Second, the number
and diversity of risks perpetrated by cormorants and covered by the media increased.
Coverage identiﬁed more risks from cormorants (per article) over time. Finally, the
number of stakeholder groups identiﬁed by cormorant coverage increased throughout our
study period. The presence of anglers, nongovernmental organizations, state and
provincial government agencies, and legislators—all stakeholder groups who have either
advocated for cormorant management or been engaged in implementation of cormorant
management activities—increased over time. The dynamic nature of this coverage,

coupled with the increasing diversity of stakeholders and cormorant-related risks present

79

in the articles, suggests that human— cormorant conﬂict in the Basin remains contentious
(Rittel & Webber, 1973).

Examination of media coverage about cormorants and their management over an
extended period of time provides a retrospective look at an issue as it progressed through
different stages of the issue evolution model, and provides vital entry points for learning
about the emergence of management contentiousness (Hahn, 1990). Decker et al. (2002)
noted different stakeholders can be at different stages of issue evolution at the same time;
therefore it is important for managers to be able to identify where each stakeholder group
is along the process. Management environments may change based on the predominant
risk frame of the species in question. Assessing risk frames applied by the media may
help managers identify where some stakeholders are, and predict where others may be in
the future, in issue evolution.

Longitudinal, retrospective inquiry of HWCs may identify trends and changes in
risk frames that may not be identiﬁed with short-term, cross-sectional approaches. This is
important because retrospective studies may identify patterns of change in media
coverage, and help managers predict future changes in risk frames. For example,
extensive media coverage of emerging diseases, such as type B botulism, which pose
serious risks to Basin cormorant populations (e. g., Shutt, Weseloh, Pekarik, & Robinson,
2005) may shift the predominant risk frame of cormorants back to victim in the future.

Our results indicate that the media has assigned wildlife management agencies
(i.e., state, provincial, or federal) and legislators with responsibility for addressing
human— cormorant conﬂict in the Basin. This ﬁnding differs from Siemer et al. (2007),

who found newspapers generally attributed responsibility to individual citizens for

80

negative interactions with black bears in New York. The difference in these results may
be explained by contextual factors, as well as by the nature of risks perpetrated by
cormorants vis-a-vis those risks perpetrated by black bears. New York media has
generally portrayed human—bear conﬂicts as personal problems, rather than public issues
(Siemer et al., 2007). Coverage on risks associated with black bears hasfocused primarily
on concerns for personal safety and economic losses associated with property damage
(e.g., bears getting into garbage). Coverage on risks from cormorants, however, has
emphasized potential risks to recreational opportunities in the Basin (e. g., ﬁshing) and the
local environment (e.g., denuding islands of vegetation), indicating that human-
cormorant conﬂicts are portrayed as public issues, not personal problems. Extending this
ﬁnding outside of the Basin, however, may not be appropriate. Media coverage in the
southern United States—where cormorant predation costs the aquaculture industry
millions in losses each year (Glahn, Tobin, & Blackwell, 2000)——may suggest human—
corrnorant conﬂicts are personal problems (e.g., for individual ﬁsh producers), not social
issues. The external validity of our ﬁndings could be assessed through replication of this
study in other geographic regions.

Another possible explanation for the difference between ﬁndings is that media
coverage and risk communication campaigns of wildlife agencies and other organizations
can readily offer information about how to avoid or minimize exposure to risks
associated with black bears, such as better waste disposal practices (Gore & Knuth, in
press). Outreach interventions and risk communication efforts offering information about
how to prevent or minimize exposure to risks perpetrated by cormorants—with the

exception of information targeted for preventing depredation at aquaculture facilities—is

81

sparse. This, coupled with the federal protection afforded to cormorants in the United
States by the Migratory Bird Treaty Act of 1918 (and provincial legislation in Canada),
may leave stakeholders feeling they have little or no control over their exposure to risks
from cormorants, which may contribute to ampliﬁed public perceptions of risk (Slovic,
1987) and escalate human—cormorant conﬂict. In these situations, agencies might
consider a participatory approach that engages different stakeholder groups affected by
cormorants in management activities (Schusler, Chase, & Decker, 2000). By actively
engaging stakeholders in management planning and implementation, wildlife
professionals may increase public trust in management agencies, as well as provide
affected stakeholders with a sense of control (i.e., ability to reduce their exposure to
cormorant-related risks), reducing human—cormorant conﬂict in the Basin.

Our study supports the utility of using risk as a framework for understanding
HWCs related to birds. Risk frames applied to cormorants by the print media could be
one factor that has inﬂuenced individual risk perceptions about human—cormorant
conﬂict; however, caution is necessary when making generalizations about the context of
news coverage to actual public perceptions. Content analysis alone cannot identify media
effects (Wimmer & Dominick, 2003). Risk information can be manipulated by an
individual’s interpretation of the risk presented in the media (Slovic, 1987). Although
newspaper coverage of wildlife is said to be fairly representative of actual perceptions
and attitudes held toward wildlife (Kellert, 1985), stakeholder-informed research is
needed to assess Basin stakeholders’ perceptions of risks related to cormorants to see if

they align with current media portrayal.

82

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86

Figure 3.1. Predicted probability of each risk frame through time (i.e., article date). The
predicted probability of both neutral and victim frames declined over time, while the
predicted probability of the perpetrator increased over time.

 

    

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87

Table 3.1. Logistic regression analyses describing the effect of article date on an

article’s inclusion of stakeholder groups involved in human-cormorant conﬂict in the
Great Lakes Basin from 1978—2007.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Logistic Regression Modell
Dependent Variable K f [3 SE Wald p-value OR 12 p-value
anglers .82 74 .1 1 .03 13.45 <.001 1.1 1 15.39 <.001
commercial ﬁshermen .83 25 .05 .04 1.66 .197 1.05 1.77 .184
ﬁsh farmers 1.0 12 .02 .04 0.11 .739 0.99 0.11 .741
hunters .71 28 .06 .04 2.61 .106 1.06 2.82 .093
ngo (anti-management) .71 19 —. 1 7 .24 55.04 <.001 1.79 14.38 <.001
ngo (pro-management) .70 26 .08 .04 4.71 .030 1.09 5.37 .021
local government .74 6 .05 .07 0.44 .508 1.05 0.47 .493
state/provincial agency .78 78 .09 .03 9.58 .002 1.09 10.46 <.001
federal agency .79 72 -.03 .03 1.20 .274 0.97 1.21 .271
tribes .70 18 .01 .04 0.01 .928 1.00 0.01 .928
business owners .72 23 .04 .04 0.98 .323 1.04 1.02 .312
birders .82 28 -.06 .03 3.18 .074 0.95 3.18 .075
animal-rights activists .78 16 .07 .05 2.51 .1 13 1.08 2.83 .093
colleges/universities .84 17 .02 .04 0.16 . .690 1.02 0.16 .687
legislators/politicians .73 34 .l l .04 9.02 .003 1.12 10.92 <.001

 

 

 

 

 

 

 

 

 

 

' n = 140, df= 1 for all models.

88

 

Table 3.2. Logistic regression analyses describing the effect of article date on an
article’s inclusion of individual risks from cormorants in the Great Lakes Basin from

 

 

 

 

 

 

 

 

 

 

 

1978—2007.
Logistic Regression Modell

Dependent Variable K f 8 SE Wald p-value OR XI p-value
DDT .76 34 .01 .03 0.01 .91 1 1.00 0.01 .911
PCBs .79 9 -.08 .05 2.50 .114 0.93 2.44 .118
chlorine .85 -. 12 .08 2.26 .133 0.89 2.22 .136
poaching .85 10 -.01 .05 0.02 .885 0.99 0.02 .886
deformities .88 18 -.16 .04 14.27 < .001 0.85 17.44 <.001
new castle disease .89 4 -.12 .07 2.80 .094 0.89 2.77 .096
scapegoat .83 22 .06 .04 2.08 .150 1.06 2.25 .134
botulism .72 5 .23 .13 3.03 .082 1.26 5.17 .023

 

 

 

 

 

 

 

 

 

 

ln = 140, df= 1 for all models.

89

 

Table 3.3. Logistic regression analyses describing the effect of article date on an
article’s inclusion of individual risks from cormorants in the Great Lakes Basin from

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1978—2007.
Logistic Regression Modell

Dependent Variable K f 0 SE Wald p-value OR 12 p-value
ﬁsh populations .84 61 .09 .03 8.95 .003 1.09 9.92 .002
vegetation .93 26 .07 .04 3.71 .054 1.08 4.14 .042
other birds .78 14 .09 .05 2.83 .093 1.09 3.28 .070
islands .84 19 .08 .04 3.24 .072 1.08 3.68 .055
tourism .85 10 .17 .08 4.83 .028 1.18 6.90 .009
ﬁshing .76 59 .09 .03 10.17 <.001 1.10 11.48 <.001
aquaculture .95 1 1 -.01 .05 0.03 .862 0.99 0.03 .863
psychological effects .72 34 .08 .03 5.30 .021 1.08 5.94 .015
private property .85 3 .12 .12 1.01 .315 1.13 1.29 .257

 

 

 

 

 

 

ln = 140, df= l for all models.

90

 

Table 3.4. Logistic regression analyses describing the effect of article date on an
article’s inclusion of the stakeholder groups assigned with responsibility for addressing

human-cormorant conﬂicts in the Great Lakes Basin from 1978—2007.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Logistic Regression ModelI
Dependent Variable K f [1 SE Wald p-value OR 12 p-value
citizens .71 6 -.01 .06 0.05 .824 0.99 0.05 .825
state/provincial agency .70 51 .07 .03 6.25 .012 1.08 6.83 .009
federal agency .72 42 -.06 .03 4.67 .031 0.94 4.82 .028
legislators/politicians .71 22 .14 .05 8.62 .003 1.15 1 1.27 .001

 

‘n = 140, df= 1 for all models.

91

 

CHAPTER 4

SUMMARY OF RESEARCH FINDINGS: IMPLICATIONS FOR
THEORY, METHODS, & PRACTICE

Research results presented in this thesis make a number of theoretical,
methodological, and empirical contributions to the existing literature on risk perception,
social networks, and media frames related to wildlife management. Public perceptions of
wildlife-related risks are helping inform management decisions about numerous species
(e.g., Riley & Decker, 2000a; 2000b; Stout et al., 1993; Wieczorek-Hudenko, Siemer, &
Decker, 2008); however, none of these studies have focused on cormorants or on the
inﬂuence of social networks on wildlife-related risk perceptions. The research reported in
Chapters 1 and 2 is novel in the risk perception and human dimensions literature. Roger’s
(2003) and Burt’s (1987) inﬂuential work on diffusion of innovations and social
contagion has served as a conceptual framework for many theoretical and empirically-
based studies on social networks (e.g., Scherer & Cho, 2003). My research, which is
contextually different from these studies, offers an opportunity to consider the extent to
which previous ﬁndings are applicable to wildlife management.

Research herein adapts previous theories and methods applied to wildlife-related
risk perception by Gore et al. (2006; 2007a; 2007b), Riley & Decker (2000a; 2000b), and
Siemer et al. (2007). Much of the existing literature on wildlife-related risk has focused
on wildlife species that pose potential threats to human safety (e. g., black bears, mountain
lions). Concerns about cormorants, however, are centered around their potential effects
on resources such as recreational ﬁsheries, other colonial-nesting waterbirds, and the

aesthetic appeal of Great Lakes islands (Muter et al., 2009). This work provides a unique

92

opportunity to evaluate which factors inﬂuencing risk perception are most applicable to
cormorants. These ﬁndings should have relevance for other human-wildlife interactions
that involve similar perceptions of risk (e. g., conﬂicts in Alaska over wolf depredation on
moose).

Literature on mass media frames and their effects on public perceptions of
environmental risks is abundant (e.g., Arvai & Mascarenhas, 2001; Gore etal., 2005).
Studies on wildlife-related media have primarily characterized the frequency and types of
content (e.g., Corbett, 1995); however, Chapter 3 demonstrates the ﬁrst time principles
from criminology (i.e., victim and perpetrator) have been adapted and applied to wildlife-
related risks. This research was also ﬁrst to study the content of media coverage about
cormorants, and is one of few studies that have explored dynamics of wildlife-related
media coverage through time (e.g., Wolch et al., 1997).

Although there is an increasing body of literature on cormorants and their
management in the Great Lakes, only one peer-reviewed publication exists (Schusler et
al., 2000) that has systematically considered the human dimensions of cormorant
management in the Great Lakes. Findings herein help to ﬁll a substantial gap in
knowledge and offer a baseline upon which future empirical human dimensions inquiry
may occur. Below I will summarize key ﬁndings, discuss implications for theory,

methods, and practice and make recommendations for future research.

93

THEORETICAL IMPLICATIONS

Factors of Wildlife-Related Risk Perception

Research presented in Chapter 1 illustrates ﬁve factors (i.e., certainty, dread, ﬁequency,
responsiveness, and seriousness) inﬂuencing cormorant-related risk perception that can
be signiﬁcantly predicted by dyadic tie strength Most of these factors (all except
responsiveness) have been previously categorized as factors of individual capacity (i.e.,
variables that are internal to an individual’s exposure to wildlife-related risks) rather than
agency capacity (i.e., variables that are peripheral to an individual’s exposure to wildlife-
related risks) (Gore et al., 2006). Thus, social networks may be best suited to predict risk
perception of factors related to individual capacity.

Dyadic tie strength was not a signiﬁcant predictor of the control, naturalness, and
trust factors associated with cormorant-related risk perceptions. Control has been cited as
conceptually problematic in the human dimensions literature. Gore et al. (2007a), for
example, noted that control was not sufﬁciently discussed by campground managers and
users in regards to negative human-black bear interactions in New York. In the context of
cormorant management, control may be related to agency capacity as cormorants are
federally protected migratory birds and management actions have overwhelmingly been
conducted by agency professionals. Thus, control could be related to feelings of
helplessness among non-governmental stakeholders who are unaware of what actions
they can legally take to reduce their exposure to cormorant-related risks.

Naturalness (i.e., natural vs. man-made risks) has received considerable attention
in the environmental and technological hazard literature (e. g., Brun, 1992; Kasperson &

Pijawka, 1985), but has also been conceptually problematic for human dimensions

94

research (Gore eta1., 2007b). In its current form, the construct may simply be too abstract
as there is an implicit philosophical challenge of trying to separate natural from
unnatural; attempting to measure this construct may be even more difﬁcult. If
naturalness is to be meaningful for understanding wildlife-related risk perception, future
research is needed to revise the current operational deﬁnition so that it can be more easily
communicated and measured on survey instruments.

If communication is a requisite for social contagion of cormorant-related risk
perceptions, this may indicate that control, trust, and naturalness related to HCCs are not
being substantively discussed within communities of network actors. It is also possible
that some (or even all) of these factors would be signiﬁcant predictors of cormorant-
related risk perception if the network were restricted to (a) only agency professionals, or
(b) only non-governmental stakeholders. Future research could investigate relationships
between dyadic tie strength and these eight risk perception factors in expert networks
(i.e., agency professionals) and non-expert networks (i.e., non-governmental
stakeholders). Comparisons of these smaller, more homogenous networks with the larger
network ﬂaresented herein) may lend additional theoretical insight into contagion of

wildlife-related risk perceptions.

Social Network Contagion Theory of Risk Perception

Social networks — via dyadic tie strength — are an important, and potentially often
overlooked, mechanism capable of inﬂuencing stakeholder risk perceptions about
wildlife, such as cormorants. Chapter 1 included a discussion about the presence of

contagion effects in a mixed network of expert (e.g., agency professionals) and non-

95

expert stakeholder groups (e.g., anglers, bird enthusiasts). Prior research on contagion
(Burt, 1987) has speculated that structural equivalence, rather than cohesion, creates more
social pressure among experts to adopt an innovation and is therefore not as effective at
predicting expert perceptions. This study, however, suggests the cohesion model is
relevant for both expert and non-expert stakeholders involved in wildlife management.
Future research could investigate the role of structural equivalence (particularly in the

network of agency professionals) in inﬂuencing risk perceptions about wildlife.

Networks & Risk Behaviors
One inference from my results was that dyadic tie strength was a‘signiﬁcant predictor of _
risk perceptions related to HCCs in northern Lake Huron; however, it did not address
whether dyadic tie strength was a signiﬁcant predictor of risk-behaviors associated with
HCCs. Additional research is needed to evaluate how networks inﬂuence risk-related
behaviors of non-governmental stakeholders engaged human-wildlife interactions. For
example with DCCOS, non-governmental stakeholders may use the MDNR’s online
cormorant complaint form’, volunteer for cormorant harassment programs, or partake in

illegal activities such as poaching.

Issue Contentiousness

Findings presented in Chapter 1 demonstrate utility for Scherer & Cho’s (2003) social
network contagion theory of risk perception by successfully applying it to wildlife-related
risks. Further, this research provides additional support for applying the theory to

contentious environmental issues, including HCCs. Contagion of risk perceptions seems

96

dependent on communication among actors about a particular hazard; however, it is still
unclear as to what point an issue becomes contentious enough to mobilize contagion
effects. This empirical question may be answered with future inquiry designed to
investigate diverse human—wildlife interactions at varying stages of issue evolution and

contention (i.e., from emerging to chronic issues).

METHODOLOGICAL IMPLICATIONS

Boundary Specification of Network Sampling

One meaningful implication from my ﬁndings is that social networks can extend beyond
traditional community or political boundaries (e. g., those that exist on paper). There are
many agency professionals (e.g., state, provincial, tribal, and federal) and non-
governmental actors (e.g., universities, bird interests, business interests, and anglers)
involved in cormorant management, many of whom neither live nor work in the regions
currently experiencing conﬂicts. In Chapter 2, for example, some of the most central, or
inﬂuential, network actors were considered non-local. This has important methodological
implications for boundary speciﬁcation of network sampling. Although network sampling
protocols that are too inclusive can be problematic in terms of data collection (i.e., an
overwhelming number of potential network actors), procedures that are too exclusive
may fail to identify inﬂuential network actors. Future research applying social networks
to similar contexts should consider the costs and beneﬁts of more inclusive sampling
approaches across wider geographic boundaries, especially when agency professionals
(who are often not physically located in the communities experiencing HWCs) are to be

included in the sampling frame.

97

Methods of Data Collection

Most data herein was collected through face—to-face interviews with network actors;
however, telephone interviews were also used if necessary. Although there are beneﬁts of
conducting interviews in person (e. g., building trust with participants), researchers should
not shy away from using multiple methods (i.e., both face-to-face and telephone
interviews) to collect network data (especially if the alternative is that an actor is
excluded from a sample). For studies with an extensive geographic sampling boundary,

telephone interviews may serve as a cost-effective alternative to data collection.

Institutional Review Board (IRB) Issues

One noteworthy challenge of using SNA to investigate applied wildlife management
issues is that some of the most meaningful practical ﬁndings gleaned from SNA cannot
be reported without violating university policies designed to protect research participant
privacy. In Chapter 2, for example, I reported centrality measures for agency
professionals and non-governmental stakeholders involved in HCC around northern Lake
Huron. Actors with high centrality scores represent individuals in the network who are
ideally positioned to either (a) connect disconnected groups within the network, or (b)
disseminate risk information quickly and efﬁciently. It would be valuable to all network
individuals if the identiﬁes of central (and non-central) actors could be revealed.
Identifying individuals as well as their placement within the network could enable
wildlife professions to better exploit results from analysis to the beneﬁt of management.
When third parties, such as universities, employ SNA methodologies, they should be

aware that some meaningful results from analysis (e.g., who actor 0003 is) will not be

98

able to be shared. If possible, researchers could work with institutional research boards
(IRBs) to ensure that collected data can be utilized to the fullest extent without violating
participant rights. IRBs may consider modifying existing privacy rules to better
accommodate social network methodologies. Management agencies are not bound by
institutional review boards; wildlife professional may be able to employ social network
methodologies without being subjected to the privacy constraints that are put on
university researchers. However, agencies may not be able to collect the same quality of
data (i.e., obtain unbiased information) if participants are being surveyed by agency
professionals, especially if the public (i.e., potential study participants) has little trust in
the management agency. Care would be needed to avoid any threats to validity and

reliability.

Coding Scheme

In Chapter 3, a coding protocol was adapted from Siemer et al. (2007) to assign the
overall risk frame applied to cormorants (i.e., victim, perpetrator, or neutral) in each
newspaper article. This procedure (see Appendix F, Section H) involved assessing each
paragraph in the article, assigning a predominant risk frame for each paragraph, and
summing paragraph assignments. If a risk frame occurred in two or more paragraphs
more than another frame, I coded the article the predominant frame; otherwise it was
coded as neutral. This coding scheme was effective; adoption of these methods to assess
risk frames in diverse media sources (e.g., intemet, television, print media) may be

helpful in studying other HWCs. Replication of this work will provide greater insight into

99

historical trends of wildlife-related media coverage and issue evolution of HWCs (Hahn,

1990)

PRACTICAL IMPLICATIONS
Managing Cormorant-Related Risk Perceptions

Cormorant-related risk perceptions were moderate to high for most network
actors. The factors of highest concern were related to individual capacity (e. g., dread,
certainty) rather than agency capacity (e.g., trust in management, responsiveness of
management). Managers may be able to best address factors of highest concern by
providing information about what stakeholders can do if they are concerned about
cormorant-related risks. For example, the MDNR currently hosts an online nuisance
complaint form that stakeholders can complete and submit to report cormorant activity in
their area]. Agencies could also provide additional information on their websites about
what people can legally do to minimize cormorant-related impacts on their property, or
elsewhere, as well as provide information about existing community-based cormorant
harassment programs (i.e., groups of citizens trained and overseen by USDA-Wildlife
Services who volunteer to harass cormorants through the use of pyrotechnics, lethal
shooting, and other means to prevent birds from foraging in locales where ﬁsh stocks are
vulnerable to predation), or how to explore opportunities to start a new harassment

program.

 

lhttp://www.dnr.state.mi.us/corrnorantobs/

100

Wildlife-Related Risk Communication
There is opportunity to improve the communication capacity and practices of wildlife
management agencies (e.g., Madden, 2008; Shanahan, Decker, & Pelstring, 2001).
Wildlife professionals should be aware that mass media and social networks are two
important channels in which information about cormorant-related risks are
communicated, and as a result inﬂuence stakeholders’ risk perceptions about wildlife and
wildlife management. These channels can be employed proactively by agency
professionals for risk communication efforts that aim to reduce HWCs to a level deemed
acceptable for both humans and wildlife (Decker etal., 2002; Gore & Knuth, 2009).
Agency professionals could beneﬁt by considering more than just individuals
when designing and implementing risk communication related to HWCs (Lundgren &
McMakin, 2009). Although individual attributes (e.g., age, county of residence,
education) are meaningful, inquiry into how social interactions among and between
agency professionals and non-governmental stakeholder groups can either impede or
enhance management objectives may improve effectiveness of communication programs.
Risk communication efforts are usually most successful when risk messages are tailored
to speciﬁc stakeholder groups and disseminated through the primary communication
channels these stakeholders use (Decker et al., 2002). Wildlife-related risk
communication designed with consideration of social networks may improve
effectiveness because networks cross geographic and political boundaries, as well as host
interactions among and between diverse stakeholder groups. Evaluation of the

effectiveness (i.e., speed of message diffusion, accurateness of information over time) of

101

using social networks for disseminating risk information about HWCs may help

managers develop better communication programs.

Identifying Intentional & Unintentional Risk Messengers in Wildlife-Related Networks
An important consideration in developing any risk communication initiative is who is
delivering the message (e. g., Lasswell, 1948). There is extensive literature to describe
characteristics of risk messengers (e.g., Lundgren & McMakin, 2009; Slovic, 1986); this
research reiterates the need to challenge the assumption that risk messengers are only
experts. Research herein illustrates both agency professionals and non-governmental
stakeholders may serve as risk messengers and that these individuals may or may not be
aware of their power and inﬂuence in their networks. In Chapter 2, I described
characteristics of central network actors who are best positioned to disseminate risk
information. Local agency professionals (i.e., those agency professionals who live and
work in the communities in which they deal with wildlife management) were among the
most central actors in the network, and as a result may be better positioned for delivering
risk messages. Although these professionals may be subordinates to non-local agency
professionals, they tended to communicate more frequently with non-governmental
stakeholders, and likely have greater inﬂuence on stakeholder perceptions. This
observation reveals a need for agency professionals at all levels to have some formal

training in risk communication about wildlife.

102

REFERENCES

Arvai, J ., & Mascarenhas, M. (2001). Print media framing of the Paciﬁc Northwest
forestry debate: Public opinion and environmentalists, Environmental
Management, 27, 705—714.

Brun, W. (1992). Cognitive components of risk perception: Natural versus manmade
risks. Journal of Behavioral Decision Making, 5(2), 117—132.

Burt, R. S. (1987). Social contagion and innovation: Cohesion versus structural
equivalence. American Journal of Sociology, 92, 1287—1335.

Corbett, J. B. (1995). When wildlife makes the news: An analysis of rural and urban
north-central U.S. newspapers. Public Understanding of Science 4, 397—410.

Decker, D. J ., Lauber, T. B., & Siemer, W. F. (2002). Human-wildlife conﬂict
management: A practitioner’s guide. Ithaca, NY: Northeast Wildlife Damage
Management Research and Outreach Cooperative.

Gore, M. L., & Knuth, B. A. (2009). Mass media effect on the operating environment
of a wildlife-related risk communication campaign. Journal of Wildlife
Management, 73, 1407—1413.

Gore, M. L., Knuth, B. A., Curtis, P. D., & Shanahan, J. E. (2006). Stakeholder
perceptions of risk associated with human-black bear conﬂicts in New York’s

Adirondack Park campgrounds: implications for theory and practice. Wildlife
Society Bulletin, 34, 36—42.

Gore, M. L., Knuth, B. A., Curtis, P. D., & Shanahan, J. E. (2007a). Campground
manager and user perceptions of risk associated with human-black bear conﬂict:
Implications for communication. Human Dimensions of Wildlife, 12, 31—43.

Gore, M. L., Knuth, B. A., Curtis, P. D., & Shanahan, J. E. (2007b). Factors inﬂuencing
risk perception associated with human-black bear conﬂict. Human Dimensions of
Wildlife 12, 133—136.

Gore, M. L., Siemer, W. F., Shanahan, J. E., Schuefele, D., & Decker, D. J. (2005).
Effects on risk perception of media coverage of a black bear-related human

fatality. Wildlife Society Bulletin, 33, 507—516.

Hahn, A. J. (1990). Issue-oriented public policy education: A framework for integrating
the process. Journal of Extension, 28, 15—19.

103

Kasperson, R. E., & Pijawka, K. D. (1985). Societal response to hazards and major
hazard events: Comparing natural and technological hazards. Public
Administration Review, 45, 7—18.

Lasswell, H. (1948). The structure and function of communication in society. In L.
Bryson (Ed), The communication of ideas: a series of addresses (pp. 37—5 1).
New York: Harper.

Lundgren, R. E. & McMakin, A. (2009). Risk communication: A handbook for
communicating environmental, safety, and health risks. (4th ed). Hoboken, NJ:
John Wiley & Sons.

Madden, F. (2008). Creating coexistence between humans and wildlife: Global

perspectives on local efforts to address human-wildlife conﬂict. Human
Dimensions of Wildlife, 9, 247—257.

Muter, B. A., Gore, M. L., & Riley, S. J. (2009). From victim to perpetrator: Evolution of
risk frames related to htunan-cormorant conﬂict in the Great Lakes. Human
Dimensions of Wildlife, 14, 366—379.

Riley, S. J ., & Decker, D. J. (2000a). Risk perception as a factor in wildlife stakeholder
acceptance capacity for cougars in Montana, Human Dimensions of Wildlife, 5,
50-62.

Riley, S. J ., & Decker, D. J. (2000b). Wildlife stakeholder acceptance capacity for
cougars in Montana. Wildlife Society Bulletin, 28, 931-939.

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.

Scherer, C. W., & Cho, H. C. (2003). A social network contagion theory of risk
perception. Risk Analysis, 23, 261—267.

Schusler, T. M., Chase, L. C., & Decker, D. J. (2000). Community-based comanagement:
Sharing responsibility when tolerance for wildlife is exceeded. Human
Dimensions of Wildlife, 5, 34—49.

Shanahan, J. E., Decker, D. J ., & Pelstring, L. M. (2001). Communication for effective
wildlife management. In D. J. Decker, T. L. Brown, & W. F. Siemer (Eds.),

Human dimensions of wildlife management in North America (pp. 171—190).
Bethesda, MD: The Wildlife Society.

Siemer, W. F ., Decker, D. J ., & Shanahan, J. (2007). Media frames for black bear

management stories during issue emergence in New York. Human Dimensions of
Wildlife, 12, 89—100.

104

Slovic, P. (1986).Informing and educating the public about risk. Risk Analysis, 6,
403—415.

Stout, R. J ., Stedman, R. C., Decker, D. J ., & Knuth, B. A. (1993). Perceptions of risk
from deer-related vehicle accidents: Implications for public preferences for deer
herd size. Wildlife Society Bulletin, 21 , 237—249.

Wieczorek-Hudenko, H. A., Decker, D. J ., & Siemer, W. F. (2008). Stakeholder insights
into the human-coyote interface in Westchester County, New York. Department
of Natural Resources, New York State College of Agriculture and Life Sciences.

HDRU Series Report 08-1. Ithaca, NY.

Wolch, J. R., Gullo, A., & Lassiter, U. (1997). Changing attitudes toward Califomia’s
cougars. Society and Animals, 5, 95—116.

105

APPENDIX A

Interview Guide

106

Cormorant-Related Social Networks
INTERVIEW GUIDE

Thank you for taking the time to sit down with me to participate in this study. As I
mentioned when we talked on the phone, I am a graduate student in the Department of
Fisheries and Wildlife at Michigan State University where I am researching attitudes
toward double-crested cormorants in northern Lake Huron. This research, which is
funded by the Great Lakes Fishery Commission and is the subject of my master’s thesis,
will also look at communication networks of resource managers and citizens who are
actively engaged in cormorant management.

I am very interested in hearing your opinions on this topic. Your participation will not
only help me fulﬁll the requirements of my graduate degree, but will also help us better
understand how to more effectively involve the public in resource management decisions,
such as those concerning cormorant management.

Throughout the interview, you will be asked for your opinions about cormorant
management, as well as to name individuals with whom you have spoken to about
cormorants in the last year. Your responses are completely conﬁdential. Your name will
not be linked to your responses in any way that a third party could reveal or connect your
responses to your name. The entire process will last no longer than one hour.

I would like to use a digital voice recorder during the interview. My research aide and I
will be the only people to hear the recording (and the aide will not be given your name,
only a unique ID number); however, I am happy to take hand-written notes if you prefer.
This interview is 100% voluntary. You may choose not to answer any question or to stop
the interview at any time.

Before we begin, I have a brief consent form that I need your signature on. This form
indicates your willingness to participate in this study [explain consent form].

Introduction & Ice-Breakers

These questions focus on your experiences with cormorants around northern Lake Huron.
By northern Lake Huron, this is the areal am referring to [show map]. This region
includes locations in both Michigan and Ontario, like Thunder Bay near Alpena, the Les
Cheneaux Islands, and the North Channel.

1. What types of activities bring you to northern Lake Huron?
a. Which of these activities is most important to you?
b. About how much time have you spent around northern Lake Huron this year?

2. While visiting northern Lake Huron, have you ever seen double-crested
cormorants? (IF NO), have you seen cormorants elsewhere?

107

a. (lF YES to either) Tell me about the experience. Where did you see them?
b. How many did you see?

c. How often did/do you see them?

(1. What were they doing?

3. How do/did you feel when you see them?

Section 1: Knowledge & Information Sources
1. Have you ever heard about cormorants from the news?

a. (IF YES) Can you tell me about it? What was/were the source(s)?
b. (IF KNOWN) Can you recall the name(s)? What are they?
0. (If more than one is mentioned) Which one do/did you refer to most?

d. What can you tell me about the coverage? Did it show cormorants in a positive,
neutral, or negative light?

2. What do you know about the history of cormorants in the Great Lakes?
a. Where do you think that knowledge comes from?

3. If you had a question about cormorants in northern Lake Huron, what would
you do to find an answer?

4. Are you currently employed in a profession related to cormorant management?
a. (IF YES) How many years have you been involved in cormorant management?

b. (IF NO) Have you ever been employed in a profession related to cormorant
management?

i. (IF YES to b) How many years were you involved in cormorant
management?

5. Aside from your employer, are you involved in any groups in which cormorant
management in northern Lake Huron is of interest?

a. (IF YES) What are your involvements? What are your roles in these groups?

b. Which one are you most involved with?

108

Section 2: Name Generators

People belong to social networks - groups of individuals who are connected in some way.
Group members may be friends, family members, neighbors, co-workers and others. I am
interested in knowing about who is in your cormorant social network — the individuals
with whom you talk to about cormorants or their management.

The next several questions will ask you to name these individuals. These people will be
contacted for an interview (if they have not been previously); however, I will not tell
them you mentioned their name. I will tell them that their name was generated during an
interview.

1. Have you talked to any natural resource agency employees about cormorants
specific to northern Lake Huron in the last calendar year?

a. (If yes) Please write down the names (ﬁrst and last) of all of those individuals.

b. (If they name more than ﬁve) Out of these, which ﬁve do you communicate
with most frequently?

2. Have you talked to anyone who is NOT currently a natural resource agency
employee about cormorants speciﬁc to northern Lake Huron in the last calendar
year?

a. (If yes) Please write down the names (ﬁrst and last) of all of those individuals.

b. (If they name more than ﬁve) Out of these, which ﬁve do you communicate
with most frequently?

Now I would like to revisit the names of those individuals you have mentioned. I am
interested in your connection with each person. (The following questions will be asked
for each set of 5 individuals named by the informant.)

l. About how many years have you known X?

2. How would you best describe your connection with X?

D Stranger D Co-worker El Stakeholder
[j Acquaintance , El Friend

[:1 Neighbor 1:] Close Friend

I] Colleague [:| Family Member

3. About how often do you communicate with X?

[:1 Daily El 5 or 6 times a year El Once a month
[:1 Several times a week D 2 or 3 times a year

[:1 Once a week [:1 Once a year

El Twice a month [:1 Less than once a year

109

4. Would you say that X contacts you more frequently than you contact X, you
contact X more frequently than X contacts you, or that you contact each other
equally?

[:I X contacts me more frequently than I contact X.
[:l I contact X more frequently than X contacts me.
[:1 We contact each other equally.

5. How does most of your communication with X take place?
[I Electronically
[3 Telephone
D In-Person
Section 3: Open-Ended Questions
1. In your opinion, are there risks northern Lake Huron from cormorants?
a. (IF YES) What are those risks? Please explain.
2. Of the risks you have mentioned, which of these is most important to you? Why?
3. While some people believe cormorants are the source of risks, others believe
cormorants are at risk. In your opinion, are cormorants in northern Lake Huron
at risk from people?

a. (IF YES) Please explain.

b. Of the risks to cormorants you have mentioned, which is most important to
you?

4. Are you satisﬁed with current cormorant management in northern Lake Huron?
a. (IF NO) What are your frustrations?

b. In your opinion, what is the biggest challenge to cormorant management in
northern Lake Huron?

5. Is there anything else related to cormorants that you would like to share with me
that you think I missed?

Before we close, I have a brief but very important questionnaire for you to complete that
will address some personal attributes, as well as, questions asking about the risks
associated with double-crested cormorants and their management. I '11 give you some
privacy while you complete the questionnaire. Should you have any questions, please
don ’t hesitate to ask.

110

Thank you again for your time. Here is my contact information should you have any
further questions or concerns. After this research is completed, I will post a summary of
research ﬁndings online www.fw.msu.edu. If you would like to give me your e-mail or
mailing address I would also be happy to send you the summary of these results when
they are available.

111

APPENDIX B

Questionnaire

112

 

 

A Survey of Your Views About
DOUBLE-CRESTED CORMORANTS

IN NORTHERN LAKE HURON

 

 

MICHIGAN STATE UNIVERSITY
- c; DEPARTMENT OF FISHERIES & WILDLIFE
‘5. 13 Natural Resources Building

,§. East Lansing, MI 48824

   

‘gK—T‘w‘ www.fw.msu.edu
1) state ‘3

 

113

 

 

 

DOUBLE-CRESTED CORMORANTS

IN NORTHERN LAKE HURON
A Survey of Your Views

The purpose of his questionnaire is to learn more about your attitudes
toward double-crested cormorants and their management in northern Lake
Huron. Your views on this topic are extremely important and will be used to
help us understand how to more effectively involve the public in resource
management decisions, such as those concerning cormorant management.

The interviewer will give you privacy while you complete this questionnaire. It
consists of 13 questions and should take approximately 5 to 10 minutes to
complete. If you are unable to complete the questionnaire while the
interviewer is present, please complete it at your earliest convenience, seal
it, and drop it in any mailbox (no envelope is needed). You will be provided
with return postage.

Your responses are completely conﬁdential. Your name will not be
linked to your responses in any way that a third party could reveal or
connect your responses to your name.

If you have any questions or concerns regarding this survey, please write

Bret Muter, Project Coordinator, at the address on the back cover of this

survey, or at muterbre@'nsu.edu. You can also reach him by telephone at
(989) 284—0976.

THANK YOU FOR YOUR PARTICIPATION I

Page 1

 

ll4

 

 

 

A. RECREATIONAL EXPERIENCE

1. About how often do you participate in

 

the following recreational activities around % 5‘
northern Lake Huron? (Please check one 2 -§ 5
response for each item). 3 g g g-

z a: o l:
Backpacking D E] [:j E]
Biking III III III III
Bird/Wildlife Watching [I [I I] E]
Boating E] E] [:I D
Camping El Cl E] El
Canoeing/Kayaking I] [:I D [:j
Fishing [3 [:I [:1 [3
Hiking III El III III
Hunting [:j I] E] El
Nature Photography E] [I [:j D
Other (Write-in): [:I [:I D D

 

B. YOUR ATTITUDES ABOUT CORMORANTS

2. People have different feelings about cormorants. Which one of the
following statements best reflects how you feel about cormorants
occurring in northern Lake Huron.

[:I I enjoy the presence of cormorants AND I do not worry about problems
they may cause.

 

E] I enjoy the presence of cormorants AND I Q worry about problems they
may cause.

D I do not enjoy the presence of cormorants AND I Q worry about
problems they may cause.

I] I do not enjoy the presence of cormorants AND I do not worry about
problems they may cause.

[3 I have no particular feelings about cormorants.

 

115

 

 

 

3. How likely do you think it is that recreational Opportunities in northern
Lake Huron will be negatively affected by cormorants in the next year?

Not At All Somewhat Extremely
Likely LIE Likely

 

DDEIDEIDEI

4. How likely do you think it is that the environment of northern Lake
Huron will be negatively affected by cormorants in the next year’?

Not At All Somewhat Extremely
Likely Llﬂy Likely

 

DDDDDDD

5. How likely do you think it is that the economy of northern Lake Huron
will be negatively affected by cormorants in the next year?

Not At All Somewhat Extremely
Likely um Likely

 

UCIDEIEIDEI

6. To what extent do you agree or disagree with the following statements
about cormorants? (Please check orly one response for each statement).

 

t6 ‘6
age as?
9 °‘ 9 E
6?. ago a E a 6‘3 5
AGREE g DISAGREE
Ifthe cormorant population El El El El El El El
increases, human-cormorant
interactions will Increase.
Iworry about the risks from El El El El El El El
cormorants.
Problems involving cormorants El El El El El E] El

are increased by man-made
factors.

Page 3

 

116

 

 

 

Managing the risks from
cormorants in northern Lake Huron
will continue to be important in the
future.

I believe that l havethe
opportunity to voice my opinions
about cormorant management in
northern Lake Huron.

Cormorants have the right to exist
wherever they may occur.

I feel that l have control over the
risks from cormorants.

If there is a problem with
cormorants, the resource agencies
responsible for management will
respond accordingly.

Science is the most rational way
to approach cormorant
management.

I trust the resource agencies
involved in cormorant
management to manage
cormorants appropriately.

Cormorant management should
be atop priority for ﬁsheries and
wildlife managers in northern
Lake Huron.

The presence of cormorants In
northern Lake Huron is the sign of
a healthy environment.

 

ﬁg; rag->9
mmmémmm
AGREE L2” DISAGREE
DDDUEJDEI
EIEIEIElL—JEIEI
DDDEIDEICI

DUE]
DUE]
DBL—l

[IUD

DEIEI

[:1

El
[:1

Ell]
DE]
CID

[I

Page 4

 

117

 

 

 

 

>. ‘9‘ . if g.
E E 543-“ 5‘9 Ere
g -‘ E .15» E ‘5 E e.
o _ :I: = 5»
U) U) U) C 1")
AGREE E DISAGREE
The risks posed by cormorants to
recreation in northern Lake Huron D E] D E] D D D
are acceptably low.
The risks posed by cormorants to E] E] E] E] El El [I
the environment in northern Lake
Huron are acceptably low.
The risks posed by cormorants to E) E] [:l E] D E) D

the economy In northern Lake
Huron are amptably low.

Cormorant population reduction is E] E] E) E] E] [:j C)
an acceptable method of reducing
risks from cormorants.

7. How do you believe cormorant populations in northern Lake Huron
have changed (if at all) in the past 5 years?

Increased Stayed Decreased Not
Greatly the Same Greatly Sure
III El I] [:1 El III E] El

8. How would you like cormorant populations in northern Lake Huron to
change in the next 5 years?

Increase Stay Decrease Not
Greatly the Same Greatly Sure
III III [:1 El El E1 El [:1

9. How important to you is it that the change you indicated in Question 8
occur in northern Lake Huron over the next 5 years?

Not Moderately Extremely Not
Important Important Important Sure

[I El E1 El El El El [I
Page 5

 

118

 

 

 

C. BACKGROUND INFORMATION
Please answer the following questions on your background to help us better
understand your responses. Your answers will remain conﬁdential.

10. Where do you currently live?

 

County (write-in):
Country (check one): D Canada El United States

11. What is your highest completed level of education?

[:I Less than a high school diploma E] Associate’s Degree (2 years)
I] High school diploma or GED E] Bachelor's Degree (4 years)
[:1 Vocational or trade school I] Graduate/Professional Degree

[I Some college

12. In what year were you born? 19

13. Please use this remaining space for any additional comments or
questions that you would like to share.

 

 

El Please check this box if you would like to receive a
summary of the survey results.

THANK YOU AGAIN FOR YOUR
PARTICIPATION!

 

Page 6

 

119

 

APPENDIX C

Research Participant Information & Consent Form

120

Research Participant Information and Consent Form

You are being asked to participate in a research project. Researchers are required to provide a
consent form to inform you about the study, to convey that participation is voluntary, to
explain the risks and beneﬁts of participation, and to empower you to make an informed
decision. You should feel free to ask the researchers any questions you may have.

Study Title: Role Of Communication Networks in Inﬂuencing Stakeholder Attitudes about
Double-Crested Cormorants and their Management in Northern Lake Huron.

Researcher and Title: Dr. Shawn J. Riley, Associate Professor; Dr. Meredith L. Gore,
Assistant Professor; and Bret A. Muter, Project Coordinator, MS Student

Department and Institution: Department of Fisheries and Wildlife, Michigan State
University

Address and Contact Information: 13 Natural Resources Building; East Lansing, MI
48824, 517-432-4943

PURPOSE OF RESEARCH:

You are being asked to participate in a research study of stakeholder attitudes toward double-
crested cormorants (Phalacrocorax auritus) and their management in northern Lake Huron.
This research will also look at communication networks of resource managers and citizens
who are actively engaged in cormorant management. You have been selected as a possible
participant in this study because your name was generated as someone who is potentially
interested, and engaged, in cormorant management in northern Lake Huron.

From this study, the researchers hope to learn about the role of communication networks in
inﬂuencing an individual’s attitudes towards cormorant management. Your participation in
this study will take no longer than one hour. If you are under 18, you cannot participate in
this study.

WHAT YOU WILL DO:

This study has two components. The ﬁrst part will be a face-to-face interview, in which you
will be asked for your opinions about cormorant management, as well as to name individuals
with whom you have spoken to about cormorants in the last year. After completing the
interview, you will be asked to complete a short questionnaire that will address some
personal attributes, as well as questions asking about the risks associated with cormorants and
their management.

If you wish, you will be provided with an executive summary of the research ﬁndings upon
completion of the study.

POTENTIAL BENEFITS:

You will not directly beneﬁt from your participation in this study. However, your
participation may contribute to a better understanding of how natural resource professionals
can more effectively involve the public in resource management decisions, such as those
concerning cormorant management.

121

POTENTIAL RISKS:
There are no foreseeable risks associated with this study.

PRIVACY AND CONFIDENTIALITY:

Information about you will be kept conﬁdential to the maximum extent allowable by law.
Your name will not be linked to your responses in any way that a third party could reveal or
connect your responses to your name.

Participants will be assigned a unique, conﬁdential identiﬁcation number for the purpose Of
data analysis. The data for this project will be kept conﬁdential. All data will be stored on a
single, password-protected computer in a locked ofﬁce in 33 Natural Resources Building at
Michigan State University. Hard copies of data and a list of codes and participants will be
stored in a locked ﬁle cabinet in 33 Natural Resources Building at MSU. The results from
this study may be published or presented at professional meetings, but the identities of all
research participants will remain anonymous. Interviews will be recorded using a digital
voice recorder with your consent; however, if you prefer, the researcher will take hand-
written notes.

I agree to allow audio-taping of the interview.

[:1 Yes [:1 No Initials

YOUR RIGHTS TO PARTICIPATE, SAY NO, OR WITHDRAW

Participation in this research project is completely voluntary. You have the right to say no or
to change your mind at any time and withdraw. You may chose not answer speciﬁc questions
or to stOp participating at any time.

COSTS AND COMPENSATION FOR BEING IN THIS STUDY:
You will not receive money or any form of compensation for participating in this study.

CONTACT IN FORMATION FOR QUESTIONS OR CONCERNS

If you have concerns or questions about this study, please contact one of the primary
investigators Dr. Shawn J. Riley or Dr. Meredith Gore, or co-investigator, Bret Muter at
Department of Fisheries and Wildlife, 13 Natural Resources Building, MSU, East Lansing,
MI 48824; phone 517-432-4943 or email rileysh2@msu.edu, gorem@msu.edu or
muterbre@msu.edu.

If you have any questions or concerns about your role and rights as a research participant, or
would like to register a complaint about this study, you may contact, anonymously if you
wish, the Michigan State University’s Human Research Protection Program at 517-355-2180,
Fax 517-432-4503, e-mail irb@msu.edu, or regular mail at 202 Olds Hall, MSU, East
Lansing, MI 48824.

DOCUMENTATION OF INFORMED CONSENT
Your signature below means that you voluntarily agree to participate in this research study.

 

 

Signature Date

122

APPENDIX D
Additional Risk Perception Tables

123

Table A.1. Cormorant-related risk perceptions of agency professionals and non-governmental actors
engaged in human-cormorant conﬂict around northern Lake Huron, August 2008—August 2009.

 

Questionnaire Item

Professionals

Stakeholders

 

Mean

SD

It

Mean

SD

p-value*

 

[Certainty] If the cormorant population
increases, human-cormorant interactions
will increase.

5.48

0.97

65

5.25

l .46

.667

 

[Dread] I worry about the risks from
cormorants.

48

4.15

1.60

65

4.45

2.11

.044

 

[Natural vs. Man-Made] Problems
involving cormorants are increased by man-
made factors.

48

4.31

1.81

65

3.03

2.44

.009

 

[Frequency] Managing the risks from
cormorants in northern Lake Huron will
continue to be important in the future.

47

5.11

1.13

65

5.23

1.60

.063

 

[Control] I feel that I have control over the
risks from cormorants.

48

3.25

1.78

64

4.34

1.76

.001

 

[Responsiveness] If there is a problem with
cormorants, the resource agencies
responsible for management will respond
accordingly.

48

2.46

1.81

65

3.82

2.02

.000

 

[Trust] I trust the resource agencies
involved in cormorant management to
manage cormorants appropriately.

47

1.98

1.65

65

3.66

2.16

.000

 

[Seriousness] Cormorant management
should be a top priority for ﬁsheries and
wildlife managers in northern Lake Huron.

48

3.71

1.96

65

4.48

2.19

.009

 

Belief in Science

48

.65

.863

64

1.78

2.11

.011

 

Science is the most rational way to
approach cormorant management.

48

.65

.863

64

1.78

2.11

.011

 

Risk Likelihood Scale

48

3.12

1.65

64

4.09

2.00

.003

 

How likely dO you think it is that
recreational Opportunities in northern Lake
Huron will be negatively affected by
cormorants in the next year?

48

3.35

1.66

65

3.98

2.16

.055

 

How likely do you think it is that the
environment of northern Lake Huron will
be negatively affected by cormorants in the
next year?

48

2.81

1.92

64

4.03

2.02

.002

 

How likely do you think it is that the
economy Of northern Lake Huron will be
negatively affected by cormorants in the
next year?

48

3.19

1.72

64

4.23

2.11

.002

 

Risk Acceptability Scale

48

3.45

1.74

64

4.58

1.87

.000

 

The risks posed by cormorants to recreation
in northern Lake Huron are acceptably low.

48

3.60

1.94

64

4.66

2.05

.001

 

The risks posed by cormorants to the
environment in northern Lake Huron are
acceptablylow.

48

3.19

1.89

64

4.45

2.02

.000

 

 

The risks posed by cormorants to the
economy in northern Lake Huron are
acceptablLlow.

 

48

3.56

 

 

1.84

 

64

4.64

 

 

1.83

 

.001

 

*p-values of Mann-Whitney tests to compare group means

124

 

Table A.2. Cormorant-related risk perceptions of Canadian and U.S. actors engaged in human-

connorant conﬂict around northern Lake Huron, August 2008—August 2009.

 

Questionnaire Item

Canadian

U.S.

 

Mean

SD

Mean

SD

p-value*

 

[Certainty] If the cormorant population
increases, human-cormorant interactions
will increase.

5.04

1.43

5.43

1 .22

.038

 

[Dread] I worry about the risks from
cormorants.

25

4.08

1.66

88

4.39

1.97

.179

 

[Natural vs. Man-Made] Problems
involving cormorants are increased by man-
made factors.

25

3.60

2.27

88

3.57

2.29

.783

 

[Frequency] Managing the risks from
cormorants in northern Lake Huron will
continue to be important in the future.

24

4.92

1.41

88

5.25

1.42

.087

 

[Control] I feel that 1 have control over the
risks from cormorants.

24

4.38

1.77

88

3.74

1-85

.123

 

[Responsiveness] If there is a problem with
cormorants, the resource agencies
responsible for management will respond
accordingly.

25

4.60

1.92

88

2.85

1.91

.000

 

[Trust] I trust the resource agencies
involved in cormorant management to
manage cormorants appropriately.

25

4.56

1.83

87

2.49

1.98

.000

 

[Seriousness] Cormorant management
should be a top priority for ﬁsheries and
wildlife managers in northern Lake Huron.

25

4.12

2.21

88

4.16

2.11

.879

 

Belief in Science

25

1.04

1.70

87

1.37

1.81

.388

 

Science is the most rational way to
a proach cormorant management.

25

1.04

1.70

87

1.37

1.81

.388

 

Risk Likelihood Scale

25

3.64

1.95

3.67

1.90

.939

 

How likely do you think it is that
recreational opportunities in northern Lake
Huron will be negatively affected by
cormorants in the next year?

25

3.88

1.92

88

3.67

2.02

.676

 

How likely do you think it is that the
environment of northern Lake Huron will
be negatively affected by cormorants in the
next year?

25

3.32

2.19

87

3.56

2.03

.636

 

How likely do you think it is that the
economy of northern Lake Huron will be
negatively affected by cormorants in the
next year?

25

3.72

2.09

87

3.80

2.0

.867

 

Risk Acceptabiligi Scale

24

3.89

2.01

88

4.16

1.86

.654

 

The risks posed by cormorants to recreation
in northern Lake Huron are acceptably low.

24

4.00

2.17

88

4.26

2.04

.626

 

The risks posed by cormorants to the
environment in northern Lake Huron are
acceLtably low.

24

3.67

2.35

88

3.98

1.98

.825

 

 

The risks posed by cormorants to the
economy in northern Lake Huron are
acceptably low.

 

24

4.00

 

 

2.02

 

88

 

4.23

 

1.88

 

.634

 

*p-values of Mann-Whitney tests to compare group means

125

 

Table A.3. Cormorant-related risk perceptions of local and non-local actors engaged in human-

corrnorant conﬂict around northern Lake Huron, August 2008-August 2009.

 

Questionnaire Item

Local Actors

Non-Local Actors

 

n

Mean

SD

It

Mean

SD

p-value*

 

[Certainty] If the cormorant population
increases, human-cormorant interactions
will increase.

61

5.41

1.31

52

5.27

l .24

.172

 

[Dread] I worry about the risks from
cormorants.

61

4.98

1.48

52

3.54

2.06

.000

 

[Natural vs. Man-Made] Problems
involving cormorants are increased by man-
made factors.

61

2.85

2.42

52

4.42

1.76

.001

 

[Frequency] Managing the risks from
cormorants in northern Lake Huron will
continue to be important in the future.

61

5.66

0.93

51

4.61

1.67

.000

 

[Control] I feel that l have control over the
risks from cormorants.

61

4.23

1.85

51

3.45

1.76

.013

 

[Responsiveness] If there is a problem with
cormorants, the resource agencies
responsible for management will respond
accordingly.

61

3.46

2.17

52

2.98

1.86

.180

 

[Trust] I trust the resource agencies
involved in cormorant management to
manage cormorants appropriately.

61

3.36

2.20

51

2.47

1.94

.038

 

[Seriousness] Cormorant management
should be a top priority for ﬁsheries and
wildlife managers in northern Lake Huron.

61

5.23

1.48

52

2.88

2.06

.000

 

Belief in Science

60

1.67

2.05

52

0.87

1.30

.063

 

Science is the most rational way to
apgoach cormorant management.

60

1.67

2.05

52

0.87

1.30

.063

 

Risk Likelihood Scale

61

4.72

2.43

52

2.43

1.78

.000

 

How likely do you think it is that
recreational opportunities in northern Lake
Huron will be negatively affected by
cormorants in the next year?

61

4.69

1.51

52

2.58

1.89

.000

 

How likely do you think it is that the
environment of northern Lake Huron will
be negatively affected by cormorants in the
next Lear?

60

4.63

1.38

52

2.21

1.95

.000

 

How likely do you think it is that the
economy Of northern Lake Huron will be
negatively affected by cormorants in the
next year? i

60

4.90

1.46

52

2.50

1.79

.000

 

Risk Acceptability Scale

61

5.08

1.35

51

2.92

1.77

.000

 

The risks posed by cormorants to recreation
in northern Lake Huron are acceptably low.

61

5.25

1.47

51

2.96

1.99

.000

 

The risks posed by cormorants to the
environment in northern Lake Huron are
acceptably low.

61

4.85

1.59

51

2.78

1.99

.000

 

 

The risks posed by cormorants to the
economy in northern Lake Huron are
accgltablylow.

 

61

5.15

 

 

1.36

 

51

 

3.02

 

1.82

 

.000

 

*p-values of Mann-Whitney tests to compare group means

126

 

Table A.4. Cormorant-related risk perceptions Of clique actors (i.e., belong to one or more cliques) and
non-clique actors (i.e., do not belong to any cliques) engaged in human-cormorant conﬂict around
northern Lake Huron, August 2008-August 2009.

 

Questionnaire Item

Clique Actors

Non-Clique Actors

 

It

Mean

SD

N

Mean

SD

p-value*

 

[Certainty] If the cormorant population
increases, human-cormorant interactions
will increase.

89

5.38

1.32

24

5.21

1.10

.156

 

[Dread] I worry about the risks from
cormorants.

89

4.30

1.92

24

4.38

1.91

.867

 

[Natural vs. Man-Made] Problems
involving cormorants are increased by man-
made factors.

89

3.79

2.25

24

2.79

2.23

.055

 

[Frequency] Managing the risks from
cormorants in northern Lake Huron will
continue to be important in the future.

88

5.18

l .43

24

5.17

1.40

.850

 

[Control] I feel that 1 have control over the
risks from cormorants.

88

3.74

1.78

24

4.38

2.02

.067

 

[Responsiveness] If there is a problem with
cormorants, the resource agencies
responsible for management will respond

accordingly.

89

2.94

1.96

24

4.33

1.99

.003

 

[Trust] I trust the resource agencies
involved in cormorant management to
manage cormorants appropriately.

88

2.51

1.98

24

4.58

1.86

.000

 

[Seriousness] Cormorant management
should be a top priority for ﬁsheries and
wildlife managers in northern Lake Huron.

89

3.94

2.22

24

4.92

1.50

.051

 

BeligLin Science

88

1.23

1.67

24

1.54

2.15

.868

 

Science is the most rational way to
approach cormorant management.

88

1.23

1.67

24

1.54

2.15

.868

 

Risk Likelihood Scale

89

3.50

1.89

24

4.29

1.87

.056

 

How likely do you think it is that
recreational Opportunities in northern Lake
Huron will be negatively affected by
cormorants in the next year?

89

3.55

1.99

24

4.33

1.90

.076

 

How likely do you think it is that the
environment of northern Lake Huron will
be negatively affected by cormorants in the
next year?

88

3.32

2.05

24

4.21

1.98

.055

 

How likely do you think it is that the
economy of northern Lake Huron will be
negatively affected by cormorants in the
next year?

88

3.64

1.99

24

4.33

2.04

.088

 

Risk Acceptability Scale

88

4.02

1.88

24

4.38

1.94

.273

 

The risks posed by cormorants to recreation
in northern Lake Huron are acceptably low.

88

4.18

2.04

24

4.29

2.18

.560

 

The risks posed by cormorants to the
environment in northern Lake Huron are
acceptably low.

88

3.76

2.05

24

4.46

2.04

.066

 

 

The risks posed by cormorants to the
economy in northern Lake Huron are
accpptably low.

 

88

4.13

 

 

1.93

 

24

 

4.38

 

1.84

 

.629

 

*p-values of Mann-Whitney tests to compare group means

127

 

APPENDIX E

Additional Sociograms

128

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III \x.‘
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129

= 25, represented by gray nodes) and U.S. network actors (n
88, represented by white nodes) engaged in human-cormorant conﬂict around northern Lake Huron, August 2008 —August 2009.

Figure A.1. Sociogram showing directional ties of Canadian actors (n

130

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\tl'5\: '5

91¢
/’

l :1”)
5‘30"“? I

51,- 3‘
‘° I 3‘94/

f/

 

61, represented by gray nodes) and non—local network actors (n

52, represented by white nodes) engaged in human-cormorant conﬂict in nonhem Lake Huron, August 2008—August 2009.

Figure A.2: Sociogram showing directional ties of local actors (n

APPENDIX F

Content Analysis Protocol

131

Cormorants in the Media
Media Content Analysis Protocol
“Revised December 12, 2007'”

Contact Information
Project Coordinator: Bret Muter

Email: muterbre@msu.edu
Phone: 989.284.0976

Introduction

Content analysis is an objective and systematic procedure (Wimmer and Dominick, 2003)
for examining the content of documented information (i.e., newspapers, magazines,
radio/television transcripts). Social scientists have used content analyses for decades
(Wimmer and Dominick, 2003); however, the method is becoming increasingly utilized
in the ﬁsheries and wildlife arena because it is able to provide historical insight on issues
in management (Decker et al., 2006). A few recent studies have looked at how media
coverage of a black bear-related human fatality in New York affected public risk
perceptions (Gore et al., 2005) and the role of media frames of black bear management in
New York (Siemer et al., 2007).

This content analysis will explore how double-crested cormorants (Phalacrocorax
aruitus) are portrayed in popular media. It will address a variety of questions related to
the frequency and type of coverage, as well as media framing. Data from this analysis
will be used in at least one peer-reviewed paper, a chapter of the project coordinator’s
thesis and will be used to inform further human-dimensions exploration of how wildlife
and wildlife-related issues are addressed in the media.

Before you begin coding, you’ll participate in a coder training session. Coder training is
an opportunity for you to work closely with the project coordinator to: (1) learn more
about the method of content analysis and its applicability to this research; (2) receive a
set of instructions and guidelines for coding; (3) become familiar with the coding
instrument; and (4) assist in the reﬁnement of the coding instrument and process.

This protocol will serve as your instruction manual for the coding process. It will
compliment the coding sheet that you’ll ﬁll out as you code each article. Please feel free
to make any notes in the document to keep as a reference.

Study Objectives

The purpose of this study is to examine how double-crested cormorants are framed in the
media. Framing refers to the way a piece of information is presented. It is a technique
used to make certain information about an issue “more noticeable, meaningful, or
memorable to audiences” (Entman, 1993, p. 53).

This project has three objectives: (1) to characterize media coverage of double-crested
cormorants in the Great Lakes from 1985 to 2007; (2) to evaluate risk frame of media
coverage of double-crested cormorants in the Great Lakes from 1985 to 2007; and (3) to
apply Siemer et al’s (2007) hypotheses of bear-related media frames to double-crested

132

cormorants. Several hypotheses under each objective will be tested with the results
provided from this analysis.

Your Role: Keys to Conducting a Successful Content Analysis

Conducting a content analysis is not an easy feat, and is very time intensive. Your role as
a coder plays a vital role in the success of this study. By following the rules and
instructions for coding, you can help ensure accuracy and consistency of results. Here are
some important things to keep in mind:

' Objectivity is the ﬁrst key to conducting a successful content analysis.
It is extremely important that you code only for what is written, not for what is
implied. We’re not evaluating articles for the accuracy of their information, but
for the presence or absence of topics and other variables. You may want to take
notes on the article as it will help you as you code and can be referred to later if
there are any questions or discrepancies.

° Reproducibility is the second key to conducting a successful content analysis.
Keep in mind there will be multiple coders on this project. The reason for using
multiple coders is to identify if two coders classify or identify the same
information in the same manner (which is the ultimate goal). A statistical test,
known as Cohen’s Kappa, will be used to determine this inter-coder reliability
(consistency between two coders). Reﬁnements can be made to the instrument if
needed to increase inter-coder reliability.

0 Please contact the project coordinator immediately if you come across any issues.
If improvements are made, the project coordinator will prepare an updated version
of the coding sheet (the instrument) and will redistribute to the coders (the
revision date will be prominently displayed at the top of the revised coding sheet).

Instructions

Each coder will be given an identical set of 121 articles. Each article will be identiﬁed by
a unique number (located in the upper right-hand corner). Articles were selected because
they contain some discussion related to double-crested cormorants within the Great
Lakes; however, cormorants are not the primary topic in all articles (though they will be
in many). If you come across an article that you do not think is relevant to the objectives
of the analysis, please bring it to the project coordinator’s attention before taking the time
to code it.

1. Read each article in its entirety before you begin coding.
2. If you disagree with a particular coding scheme or ﬁnd a poorly deﬁned category
please bring it to the attention of the project coordinator. If possible, address these

concerns during the coder training session.

3. Always start at the top of the coding sheet and work your way down. You may
ﬁnd that a question, section or sections of the instrument are not addressed or are

133

not particularly relevant to your article. (In fact, it will probably be very rare that
every section on the coding sheet will be relevant to a single article). You should
indicate those question(s)/section(s) is/are not applicable.

4. Instead of printing a hundred copies of the coding sheet for each coder, you will
be given an Excel spreadsheet ﬁle to insert your coded data. Please take your time
to ensure that you have not made any errors in data entry.

5. Finally, if at any time you ﬁnd yourself in doubt, contact the project coordinator.
Thank you for participating in the study! I look forward to working with you!

Further Instructions & Definitions

The remainder of this protocol will provide you with additional instructions and
information to assist you as you begin the coding process. Here, each section of the
codebook is expanded upon. This is where you’ll ﬁnd deﬁnitions of variables, as well as
examples of things you will be “looking for” as you code. Please be sure to read this
document several times before you begin to code and be sure to have it next to you at all
times. If any of the items below are still unclear, please contact the project coordinator.

SECTION A: GENERAL ARTICLE INFORMATION

This ﬁrst section gathers general information about the article (title, source, origin, etc.)
The ﬁrst eleven variables will already be coded by the project coordinator (since there
should be no discrepancies with these items).

Al: Article Number
Article numbers are already coded A001 through A121.

A2: Name of Publication/Transcript
Already Coded.

A3: Article Date - Month
Article months are already coded 01 (January) through 12 (December).

A4: Article Date — Day
Article days are already coded 01 through 31.

A5: Article Day — Year
Article years are already coded 1985 through 2007.

A6: Newspaper/Program Origin — Country
Country of newspaper origins are already coded I for United States and 2 for
Canada.

134

A7:

A8:

A9:

A10:

A11:

A12:

Newspaper/Program Origin - State/Province
Identify the state or province in which the article/program was published/aired.
Add codes as needed.

Section/Desk/Type
LexisNexis provides this information at the t0p of the article below the story title,
typically following “SECTION.”

Photos, Tables & Figures

LexisNexis does not actually provide photos, ﬁgures or tables (on rare occasion a
table or ﬁgure will appear in the printout); however, you can determine if a
graphic was included if the word “GRAPHIC” appears after the end of the story.
Photo/ﬁgure captions are also typically included. Only code 1 (yes) for this
variable if the caption tells you the photo is of a cormorant(s), or if a ﬁgure/graph
contains information related to cormorants.

How many words are there in the story?
LexisNexis provides this information at the top of the article below the story title.

How paragraphs in the story discuss or are directly related to double-crested
cormorants?

What is the primary article topic?

To determine the primary topic (Variable 11) ﬁrst use the title. If you are unable
to make a distinction from the title, the ﬁrst couple paragraphs of the story should
tell you. Several of topics below may occur in each article; therefore, you should
code the topic that is discussed most as the primary topic. Use the table below for
descriptions and examples of article topics.

' Negative Impacts from Cormorants: article discusses one or more
negative effects or impacts from cormorants on humans (i.e., health/safety,
economic, psychological, etc.) or the environment. Some examples
include: impacts of cormorants on Great Lakes ﬁsheries, aquaculture,
vegetation, other birds, tourism, local communities, etc.

° Agency Response to Cormorants: article discusses a management action
or response to the “cormorant issue.” Some examples include instances of
culling, egg-oiling, hazing, embarking on new agency/government-funded
research on cormorants and their impacts, etc.

° Diseases, Conditions & Negative Impacts (to Cormorants): article
discusses some kind of disease or condition that is affecting cormorants
(and potentially other species of wildlife). In many cases, cormorants will
only be brieﬂy mentioned as one of the victims of such conditions.
Examples include: DDT, bill and feet deformities, PCB’s, Newcastle
Disease, etc. Do not code yes for instances of cormorant poaching (as this
would be coded as poaching) or for instances of cormorants being killed as

135

the result of a management action (as this would be coded as an agency
response to cormorants).

' Aesthetic Values Placed on Cormorants: article discusses pleasure with
cormorants and their viewing. Will typically be associated with non-
consumptive outdoor recreation (i.e., travel, bird-watching, kayaking,
camping, boating) in which cormorants are aesthetically viewed.
Additional examples include: viewing cormorants as a sign of healthier
Great Lakes, sighting(s) of a cormorant(s) in an unusual place, etc.

' Consumptive Outdoor Recreation: article discusses some form of
consumptive outdoor recreation (i.e., hunting and ﬁshing) and mentions
cormorants in some context to those activities.

° Poaching: article discusses an instance of poaching where cormorants
(and possibly other birds, like pelicans) are illegally killed. Examples
include: Little Galloo incident, etc.

0 Research/Education: article discusses a current academic research project
on cormorants or an education program designed to teach people about
cormorants.

° Legislation/Politics: article discusses legislation related to cormorants and
their management. Also code yes for legislation dealing with controlling
or regulating contaminants (which affect cormorants). Examples include: a
state or province’s new legislation to manage cormorants, etc.

° Other: articles that don’t seem to ﬁt with any of the above coding
schemes. Very few articles should fall into this category. If this list gets
too large, we will have to revisit these articles to discuss the creation of
additional content categories.

A13 - Other Topics Discussed

A20: Variables A13 through A20 list the individual codes from A12 and asks if these
topics are also discussed. Code yes or no for each of the variables that are
mentioned in the article (Note: you should also code yes for the topic you
indicated as the primary article topic in A12). Use the list above if you need to
refer to descriptions and examples of each of the listed topics.

SECTION B: STAKEHOLDER GROUPS

This section is designed to identify the stakeholders involved/discussed in each
cormorant-related article. Stakeholder groups are groups of individuals that hold some
stake in an issue. Examples of cormorant-related stakeholder groups include (a)

ﬁshermen; (b) local, state and federal governments; (c) tribes; (d) business owners; and
(e) NGO’s, etc.

B1 — Stakeholder Groups:

BIS: Variables B2 through B14 list a variety of different stakeholder groups that have
been linked to cormorant-related issues. Code yes for those stakeholder groups
mentioned in the article. Please let the project coordinator know if any other
categories of stakeholder groups are encountered. Some tips are included below:

136

° If you see the word “anglers” or “sports-ﬁshermen” code yes for the
recreational ﬁshermen stakeholder group (B1).

' If you only see the word “ﬁshermen” (and there is no context to make you
believe they are discussing commercial ﬁshing) code yes for the
recreational ﬁshermen stakeholder group (Bl).

° Only code yes for commercial ﬁshermen (B2) if they are referring to
catching ﬁsh for commercial distribution. Do not include charter ﬁshing
captains as commercial ﬁshermen (we will classify them as business
owners — Bl 1).

° Examples of business owners (B11) include motels, hotels, bait-shops,
charter-ﬁshing companies, etc. Do not code yes here for aquaculture (since
you will have already coding yes for B3).

0 Examples of non-proﬁt organizations that want to protect cormorants (B6)
might include Cormorant Defenders International, PETA, Audubon
Society, etc.

° Only code yes for animals rights activists (B13) if it said animal rights,
animal rights advocates, etc. Do not code yes for PETA, Humane Society,
etc. (as you will have already coded these as NGOs wanting to protect
cormorants — B6).

0 Similarly, only code yes for birders or omithologists (B12) if those or
similar terms appear (i.e., “bird watchers,” “bird-enthusiasts,” “wildlife-
watchers,” etc.). Do not code yes for organizations like the Audubon
Society or Canadian Society for Endangered and Threatened Birds (as you
will have likely already coded these as NGOs wanting to protect
cormorants).

0 Examples of non-proﬁt organizations that are upset with cormorants (B5)
might include local ﬁshing and sporting clubs, etc.

SECTION C: NATURAL HISTORY INFORMATION

This section is designed to see what natural history/biological information the author
includes about cormorants, like (a) diet, (b) behavior and (c) history within Great Lakes,
etc. Be sure to keep your eye peeled for strategically placed and subtle pieces of
information.

Cl: Cormorant Diet?
Code yes if the article mentions aspects of the bird’s diet (i.e. eating ﬁsh)

° Look for phrases like, “these ﬁsh-eating birds...” etc.
C2: Cormorant Behavior?
Code yes if the article mentions non-diet behaviors. Examples of non-diet

behaviors include migration, nesting, breeding, diving, defecating, vomiting,
perched with wings out to dry, etc.

137

C3:

C4:

C5:

C6:

Cormorant is Federally Protected?
Code yes if the article mentions that the cormorant is a federally protected bird or
is protected by the Federal Migratory Bird Treaty Act.

Cormorant History with DDT or PCBs?

Code yes if the article mentions that cormorants are falling (or fell) victim to
DDT, PCBs and other pesticides. The article may simply say contaminants.
Examples might include: mention of cormorant populations following those of
bald eagles and osprey in the 1960’s and 1970’s as a result of commercial use of
DDT, discusses how cormorants often suffered with deformities from PCB
exposure, etc.

Qualitative information about population?

Code yes if the author or someone in the article makes a statement about the
population of cormorants without giving a numerical statistic. Some examples
might include:

' “The cormorant population explosion...”

° “Cormorant populations skyrocketed.”

° “The populations increased greatly since the 1970’s.”

° “The cormorant population is much larger than it was 20 years ago.”

Quantitative information about population

Code yes if the author or someone in the article uses numbers or statistics to
indicate the current cormorant population or trends in the cormorant population.
Some examples might include:

° “In 1970’s there were only 12 pairs of cormorants on the island; today
there are 1,500.”

° “Populations have increased 300-fold.”

' “There are over 500,000 cormorants in North America today.”

SECTION D: IMPACTS FROM CORMORANTS (Perpetrator Frame)

Variables have been created to record presence/absence of negative impacts (actual or
perceived) from cormorants. Impacts may be ecological or economic. Some examples
include: (a) destroying vegetation; (b) negative impacts on ﬁsheries; and (c) economic
effects associated with cormorants. Please let the project coordinator know if any other
categories of impacts from cormorants are encountered.

D1 -
D10:

Impacts from Cormorants:

Variables D2 through D11 list a variety of different perceived and assessed
economic and ecological impacts from cormorants. Code yes for those impacts
mentioned in the article. Please let the project coordinator know if any other
categories of impacts from cormorants are encountered. Some tips are included
below:

138

 

' Cost does not need to be mentioned to indicate an economic effect. Words
like damaged or ruined are a good indicator.

° Code yes for negative ecological effects to Great Lakes ﬁsheries (D1) if
statements are made indicating that cormorants are (or are perceived to be)
changing the food web in the Great Lakes (or another body of water),
depleting stocks of game ﬁsh, stocks of baitﬁsh that game ﬁsh depend on,
etc.

° Only code yes for negative economic effects to tourism (D6) if statements
are made indicating that tourism in an area is suffering because of
cormorants or because of declining ﬁsh populations. Must use the word
tourism.

° Code yes for negative impacts to commercial or recreational ﬁshing (D8),
if statements are made indicating like: “We don’t catch as many ﬁsh as we
used to,” “We have to ﬁsh harder to catch the same number of ﬁsh that we
used to,” “Cormorants are eating all of the perch and bass,” “Cormorants
are eating the baitﬁsh that salmon and walleye depend on,” etc.

SECTION E: IMPACTS ON CORMORANTS (Victim Frame)

Variables have been created to record presence/absence of several impacts on or to
cormorants. These are impacts that cause physical harm to cormorants either directly or
indirectly through effects on the ecosystem. Some examples include: (a) DDT and other
pesticides, (b) bill deformities caused by PCBs, (c) diseases, etc. Please let the project
coordinator know if other categories of impacts on cormorants are encountered.

E1 - Impacts on Cormorants

E7: Variables El through E7 list a variety of different impacts to/on cormorants. Code
yes for those impacts mentioned in the article. Please let the project coordinator
know if any other categories of impacts to cormorants are encountered. Some tips
include:

' Only code yes for E7 if the author or someone in the article makes a clear
statement that cormorants are being wrongfully accused for depleting ﬁsh
stocks or are a scapegoat for some other issue that is causing negative
impacts. Must use words or phrases like, “scapegoat,” “wrongfully
accused,” “incorrectly blamed,” etc.

SECTION F: RISK PERCEPTIONS

Variables have been created to record presence/absence of psychological effects of
cormorants (i.e., dislike, worry, etc.) Variables Fl through F4 list a variety of different
risk perceptions related to cormorants. Code yes for those perceptions mentioned in the
article. Please let the project coordinator know if other categories of psychological effects
are encountered.

F1: Satisfaction with Agency Response

Code yes if the author or someone within the article makes a statement that they
are happy or satisﬁed with an agency’s response or decision to cormorants (i.e.,

139

F2:

F3:

F4:

management activities). Also code yes for statements indicating that someone
would like to see the agency carry out more of these types of activities.

Dissatisfaction with Agency Response

Code yes if the author or someone within the article makes a statement that they
are not happy with an agency’s response or decision to/regarding cormorants (i.e.,
management activities). Code yes for statements like: “they shouldn’t be killing
the cormorants,” “this isn’t the right way to address the issue,” or “they’re not
doing enough.”

Worry or concern about future negative impacts to cormorants?

Code yes if the author or someone within the article makes a statement clearly
indicating that they are worried or concerned about negative impacts cormorants
might face in the future (i.e., from contaminants, disease, persecution, wrongfully
being culled, etc.)

Worry or concern about future negative impacts from cormorants?

Code yes if the author or someone within the article makes a statement clearly
indicating that they are worried or concerned about negative impacts cormorants
might cause or continue to cause (i.e., economically, environmentally, or socially)
in the future.

SECTION G: PROBLEM, SOLUTION & RESPONSIBILITY ATTRIBUTIONS

G1 —
G5:

Problem Causes

Variables G1 through G5 list a variety of perceived causes of the “cormorant
issue.” Code yes for those perceived causes if the author suggests or a statement
made within the article suggests that problems from cormorants are being causes
by the corresponding variable. Some tips include:

° Only code yes for G3 if the author or someone within the article makes a
statement clearly indicating an agency is not taking action when they
should be. Examples: “The government really needs to step in and help,”
“The government should really do something about the cormorant
problem,” etc.

' Only code yes for G4 if the author or someone within the article makes a
statement clearly indicating that an agency is not doing enough to manage
cormorants. Examples: “They should be culling more birds,” “The
government needs to kill them all,” etc.

' Only code yes for G5 if the author or someone within the articles make a
statement clearly indicating that an agency is taking in appropriate action
(i.e., in other words they are killing cormorants when they shouldn’t be).
Examples: “The cormorant problem is all imagined, the government
shouldn’t be killing them,” “Cormorants aren’t the problem; the real
problem is invasive species. Instead of killing cormorants, the government

140

 

G6 -
G12:

G13 -
G17:

should be focusing their efforts elsewhere,” or “It’s absurd to think that
the government would kill cormorants because they are eating ﬁsh.”

Problem Solutions

Variables G6 through G12 list a variety of suggestions the author or someone
within the article may makes to address the cormorant issue and ﬁnd a solution.
Example solutions include: taking no action, taking lethal action, taking non-
lethal action, establishing a hunting season or legislation to manage cormorants,
etc. Code yes for those suggested solutions mentioned.

Attributions of Responsibility

Variables G13 through G17 list a variety of suggestions the author or someone
within the article may make regarding who should is responsible in addressing the
cormorant issue (i.e. citizens, local, state or federal agencies, etc.). Code yes for
those suggested individuals/organizations responsibility has been attributed to.
Please note that action that has already taken place or is taking place is a form of
accepting responsibility.

SECTION H: NEWS FRAMES

As mentioned earlier, framing refers to the way a piece of information is presented. In
this section we want to ﬁnd out how the media frames cormorants, and if this framing has
changed over time. We also want to know how the articles have been framed to tell their
“cormorant story.”

H1:

Does this article frame cormorants as a victim or as a perpetrator?

We deﬁne a victim as someone or something that suffers, loses, is targeted, or
serves as a scapegoat. Speciﬁcally, we want to deﬁne cormorants as a victim if
“harm” is being inﬂicted upon them (i.e., deformities due to PCBs, deaths due to
DDT, poaching, etc).

On the other hand, we deﬁne a perpetrator as someone or something that inﬂicts
or is accused of causing “harm” (i.e. cormorants depleting ﬁsh stocks, causing
economic hardships, destroying vegetation, etc). We would also like for you to
identify cormorants as a perpetrator when they are targeted by a management
action (i.e. culling, egg-oiling, etc.). Although it seems like we could place this
instance in the victim category, we are assuming these actions are being carried
out, because cormorants were acting as a “perpetrator.” The only exception to this
rule would be is if the article is about one’s displeasure with the management
action (in this case, they would in fact be portrayed as a victim).

More than likely both risk-frames will be presented in the same article, therefore
you will need to code for the risk frame that is most predominant. To do this, read
each paragraph and label each (on the article) that uses a victim frame as a 1 and
each paragraph that uses a perpetrator frame as a 2. If the paragraph is neutral, or
doesn’t discuss cormorants, label it as a 0. Once you’ve ﬁnished labeling each
paragraph, count up the number of 1’s and 2’3.

141

H2:

Disregard the zeros. If your total number of 1’s exceeds your number of 2’s by
more than one, code I for predominantly victim-frame for variable H1. If your
number of 2’s exceeds your number of 1’s by more than one, code 2 for
predominantly perpetrator frame for variable H1. If your number of 1’s and 2’s
are equal or within +/- one, than code 0 for mixed (or equal) frame for variable
H1.

Does this article demonstrate thematic or episodic coverage?

Finally! The last variable asks you to make a determination on whether an article
demonstrates predominantly episodic or thematic coverage. In his book Is anyone
responsible?, Iyengar (1991) details the concepts of both of these frames.

Episodic coverage typically focuses on a single event and serves as a summary of
what happened. Episodic stories are typically approached as case studies. Other
characteristics of episodic coverage include:

' Describes concrete events that illustrate an issue or issues.
' Reports a speciﬁc event or case, but doesn’t detail the social or political
background or history of that event.

Thematic coverage, on the other hand, looks at the “big picture.” An event may be
discussed, but that event is placed in general context as it discusses policies or
history. Thematic stories examine connections between similar events and look
for trends, often asking questions like “how” and “why.” Other characteristics of
thematic overage include:

° Mentions trends in cormorant populations and negative impacts.

' Serves as a background report to illustrate general outcomes or conditions.

0 Presents evidence (i.e., gives information about typical cormorant
behavior, etc.)

Identifying an article as either episodic or thematic can be an extremely difﬁcult
task, as most thematic articles will have an episodic element. On a similar note,
episodic coverage often contains thematic elements. Instead of making a single
subjective decision based on each article as a whole, we’ll indentify each
paragraph within the story as either episodic or thematic.

Starting with paragraph 2, go through the article and identify each paragraph as
either predominantly episodic or predominantly thematic. Label each paragraph
with an “E” or “T” accordingly.

Once you’ve labeled each paragraph count up the total number of E’s and the total

number of T’s. Code as thematic if the number of “T”s exceeds the number of
“E”s by more than one and vice versa. Code a 1 for predominantly episodic and 2

142

for predominantly thematic. In the case that both frames are used equally, or
within +/- one, than code 3 for use of mixed frames.

Here are some tips on what to look for when decided on how to label each
paragraph.

Example Thematic Elements to Look For:

° Discuss cormorant trends in the area over time -— increased populations,
etc.
Give biological (natural history) background information on cormorants.
Suggestions are made to solve/remediate cormorant problems.
Attributions of responsibility are made.
Potential causes of the cormorant problems are addressed.

Example Episodic Elements to Look For:
0 Talks about a particular management action in a speciﬁc place at a speciﬁc
time.
° Talks about a speciﬁc instance of poaching.

SECTION J: ADDITIONAL INFORMATION

Due to the diversity of articles and topics re: corms in this sample, it’s possible we’ve
overlooked something extremely interesting or important. Please use this section to make
any additional notes on the article that were not addressed in the previous sections, and
let the project coordinator know if you see a recurring theme in articles that is not being
addressed in the codebook.

References & Relevant Readings

Decker, D. J., Brown, T. L., & Siemer, W. F. (Eds) (2001). Human Dimensions of
Wildlife Management in North America. Bethesda, MD: The Wildlife Society.

Entman, R. M. (1993). Framing: Toward clariﬁcation of a fractured paradigm. Journal of
Communication, 43, 51—58.

Gore, M.L., W.F. Siemer, J.E. Shanahan, D. Schuefele and DJ. Decker. (2005). Effects
on risk perception of media coverage of a black bear-related hmnan fatality.
Wildlife Society Bulletin, 33(2), 507—516.

Iyengar, S. (1991). Is Anyone Responsible? Chicago: University of Chicago Press.
Siemer, W. F ., Decker, D. J ., & Shanahan, J. (2007). Media frames for black bear
management stories during issue emergence in New York. Human Dimensions of

Wildlife, 12, 89—100.

Wimmer, R. D., & Dominick, J. R. (2003). Mass media research: An introduction.
Belmont, CA: Wadsworth.

143

APPENDIX G
Content Analysis Codebook

144

Cormorants in the Media
Codebook
”Revised December 7, 2007”

ARTICLES COLLECTED BY LEXISNEXIS SEARCH
(November 2007 SPSS Code Sheet)

 

 

 

 

 

 

 

 

 

 

 

Coder Initial: _
Section A: Article Description
# Variable Description Code

A1 Article Number Already Coded

A2 Name of Publication/Transcript Already Coded

A3 Publication/Air Date -— Month Already Coded

A4 Publication/Air Date — Day Already Coded

A5 Publication/Air Date — Year Already Coded

A6 Newspaper/Program Origin — Country 0 = Missing (N/A)
1 = United States
2 = Canada

A7 Newspaper/Program Origin - State/Province O = Missing (N/A)
1 = New York
2 = Ontario
3 = Quebec
4 = Pennsylvania
[add more codes as
needed]

A8 Section/Desk/Type 0 = Missing (N/A)
1 = News ~
2 = Sports
3 = Opinions
4 = People
5 = MetrOpolitan
6 = Letter
7 = Radio Transcript
8 = Television Transcript
[add more codes as
needed]

A9 Are any photos or graphs/tables related to double- 0 = None (N/A)

crested cormorants used in the article? 1 = Photo Only

2 = Graph/Table Only
3 = Both Photo and
Graph/Table

A10 How many words are there in the story? 0 = Missing (N/A)
1 = < 300 words

 

 

 

 

145

 

2 = 300 to 600 words

3 = 601 to 900 words

4 = 901 to 1,200 words

5 = 1,201 to 1,500 words
6 = 1,501 + words

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

All How paragraphs in the story discuss or are directly 1 = 1 paragraph
related to double-crested cormorants? 2 = 2 paragraphs
3 = 3 paragraphs, etc.
A12 What is the main topic of this article? 1 = Negative Impacts ﬁom
See protocol for topic descriptions and examples. Cormorants
2 = Agency Response to
Cormorants
3 = Negative Impacts to
Cormorants
4 = Aesthetic Values
Placed on Corrns
5 = Consumptive Outdoor
Recreation
6 = Poaching
7 = Research/Education
8 = Legislation/Politics
9 = Other
[add more codes as
needed]
# Does the article also discuss: Code
A13 Negative impacts from cormorants? 1 = Yes 0 = No
A14 Agency response to cormorants? 1 = Yes 0 = No
A15 Negative impacts to cormorants? 1 = Yes 0 = No
A16 Aesthetic values placed on cormorants? 1 = Yes 0 = No
A17 Consumptive outdoor recreation? 1 = Yes 0 = No
A18 Poaching (or illegal killing) of cormorants? l = Yes 0 = No
A19 Research or education programs on cormorants? l = Yes 0 = No
A20 Politics or legislation dealing with cormorants? l = Yes 0 = No
SECTION B: STAKEHOLDER GROUPS
Please add additional stakeholder groups as necessary.
# Does the article mention the following Code
stakeholder groups...
Bl Recreational ﬁshermen, anglers, sports ﬁshermen, l = Yes 0 = No
etc.
B2 Commercial ﬁshermen? 1 = Yes 0 = No
B3 Fish farmers, Fish producers (i.e., aquaculture)? l = Yes 0 = No
B4 Hunters? 1 = Yes 0 = No
BS Non-govemmental organization (upset with l = Yes 0 = No
cormorants)?

 

 

 

 

146

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

B6 Non-govemmental organizations (wanting to 1 = Yes 0 = No
protect cormorants)?

B7 Local (city or county) government? 1 = Yes 0 = No

B8 State/provincial government agncies? l = Yes 0 = No

B9 Federal government agencies? 1 = Yes 0 = No

B10 Tribes? 1 = Yes 0 = No

B11 Business owners (i.e., motel/hotel, bait-shOps, l = Yes 0 = No
charter-caLtains, etc.)

B12 Birders, omithologists? l = Yes 0 = No

B13 Animal-rights activists? l = Yes 0 = No

B14 Colleges/Universities? 1 = Yes 0 = No

B15 Legislators/Politicians? 1 = Yes 0 = No

SECTION C: NATURAL HISTORY INFORMATION
# Does the article mention... Code

C1 Cormorant diet? 1 = Yes 0 = No

C2 Cormorant behavior (non-diet, i.e. migration, 1 = Yes 0 = No
nesting, etc.)?

C3 The cormorant is federally protected or is listed 1 = Yes 0 = No
under the Federal Mijratory Bird Act?

C4 Cormorant history with DDT or PCBs? l = Yes 0 = No

C5 Qualitative information/data about population? 1 = Yes 0 = No

C6 Quantitative information/data about population? 1 = Yes 0 = No

 

 

 

 

 

SECTION D: IMPACTS FROM CORMORANTS (PERPETRATOR-FRAME]

Please add additional negative impacts from cormorants as necessary.

 

 

 

 

 

 

 

 

 

 

 

 

 

# Does the article mention actual or perceived... Code

D1 Negative ecological impacts of cormorants to l = Yes 0 = No
Great Lakes ﬁsheries (i.e. food webs, etc)?

D2 Negative ecological impacts of cormorant 1 = Yes 0 = No
droppings?

D3 Negative ecological impacts of cormorants to 1 = Yes 0 = No
vggetation?

D4 Negative ecological impacts of cormorants to 1 = Yes 0 = No
other species of birds?

D5 Negative ecological impacts of cormorants to 1 = Yes 0 = No
Great Lakes islands?

D6 Negative economic impacts of cormorants on 1 = Yes 0 = No
tourism (must say tourism)?

D7 Negative economic impacts of cormorants on 1 = Yes 0 = No
small businesses (i.e. bait shops, motels, charter-
ﬁshing companies, etc.)?

D8 Negative impacts of cormorants on recreational or 1 = Yes 0 = No

 

147

 

 

 

commercial ﬁshing?

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

D9 Negative economic impacts of cormorants on 1 = Yes 0 = No
aquaculture?
D10 Cormorant-related damage to residential/personal 1 = Yes 0 = No
property?
SECTION E: IMPACTS ON CORMORANTS (VICTIM-FRAME]
Please add additional impacts on cormorants as necessary.
# Does the article mention... Code
El Deaths of cormorants due to DDT? l = Yes 0 = No
E2 Deaths of cormorants due to PCBs? l = Yes 0 = No
E3 Deaths of cormorants due to chlorine? l = Yes 0 = No
E4 Deaths of cormorants due to poaching? 1 = Yes 0 = No
E5 Deformities (twisted beaks, clubbed feet, etc.) of 1 = Yes 0 = No
cormorants?
E6 Deaths of cormorants due to New Castle Disease? 1 = Yes 0 = No
E7 Someone (or group) is making cormorants a 1 = Yes 0 = No
scapegoat?
E8 Deaths of cormorants due to botulism? 1 = Yes 0 = No
SECTION F: RISK PERCEPTIONS
# Does the author or statements made within the Code
article mention...
F l Satisfaction with an agency’s response to 1 = Yes 0 = No
cormorants (i.e., management activities)?
F2 Dissatisfaction with an agency’s respdnse to l = Yes 0 = No
cormorantsLie, management activities)?
F3 Worry or concern about future negative impacts to 1 = Yes 0 = No
cormorants?
F4 Worry or concern about future negative impacts 1 = Yes 0 = No
from cormorants?
SECTION G: PROBLEM ATTRIBUTION
Problem Causes
# Does the author or statements made within the Code
article suggest that problems from cormorants
are beingcaused by...
G1 The increasing number of cormorants? 1 = Yes 0 = No
G2 Cormorants expanding their range? 1 = Yes 0 = No
G3 Agencies/managers failing to take action? 1 = Yes 0 = No
G4 Agencies/managers taking insufﬁcient action? 1 = Yes 0 = No
G5 Agencies/managers taking inappropriate action? 1 = Yes 0 = No

 

 

 

 

 

148

 

 

 

 

Problem Solutions

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

# Does the author or statements made within the Code
article suggest that problems with cormorants be
addressed by...
G6 Taking no action? 1 = Yes 0 = No
G7 Non-lethal control methods? 1 = Yes 0 = No
G8 Lethal control methods? 1 = Yes 0 = No
G9 Establishing a cormorant hunting season? 1 = Yes 0 = No
G10 Establishing legislation to deal with cormorants? 1 = Yes 0 = No
G11 Academic research? 1 = Yes 0 = No
G12 Education/outreach efforts? 1 = Yes 0 = No
Attributions of Responsibility
# Does the author or statements made within the Code
article gggest that:
G13 A citizen is taking action/responsibility or someone I = Yes 0 = No
in the article is suggesting that citizens should take
action/responsibility?
G14 A local (i.e. town, village, city, county, etc.) agency 1 = Yes 0 = No
is taking action/responsibility or someone in the
article is suggesting they should take
action/responsibility?
G15 A state or provincial agency is taking 1 = Yes 0 = No
action/responsibility or someone in the article is
suggesting they should take action/responsibility?
G16 A federal agency is taking action/responsibility or 1 = Yes 0 = No
someone in the article is suggesting they should
take action/responsibility.
G17 Legislators are taking action/responsibility or 1 = Yes 0 = No
someone in the article is suggesting they should
take action/responsibility.
SECTION H: NEWS FRAMES
Victim vs. Perpetrator* Do for all articles.
H1 Does this article frame cormorants as a victim or as 0 = Neither
a perpetrator? 1 = Victim

 

 

See protocol for deﬁnitions and examples.

 

2 = Perpetrator

 

Episodic vs. Thematic" Do for all articles.

 

H2

 

 

Does this article demonstrate thematic or episodic
coverage?
See protocol for further instructions.

 

l = Episodic
2 = Thematic
3 = Mixed

 

149

 

 

 

 

SECTION I: ADDITIONAL INFORMATION

 

Il

 

 

Is there anything else about this article you think is noteworthy? Please use this
space to make any additional notes.

 

150