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Understanding Factors That Influence Stakeholder Trustof Natural Resource Science and Institutions
Steven Gray • Rachael Shwom • Rebecca Jordan
Received: 12 August 2010 / Accepted: 7 December 2011 / Published online: 1 January 2012
� Springer Science+Business Media, LLC 2011
Abstract Building trust between resource users and natu-
ral resource institutions is essential when creating conser-
vation policies that rely on stakeholders to be effective. Trust
can enable the public and agencies to engage in cooperative
behaviors toward shared goals and address shared problems.
Despite the increasing attention that trust has received
recently in the environmental management literature, the
influence that individual cognitive and behavioral factors
may play in influencing levels of trust in resource manage-
ment institutions, and their associated scientific assessments,
remains unclear. This paper uses the case of fisheries man-
agement in the northeast to explore the relationships between
an individual’s knowledge of the resource, perceptions of
resource health, and participatory experience on levels of
trust. Using survey data collected from 244 avid recreational
anglers in the Northeast U.S., we test these relationships
using structural equation modeling. Results indicate that
participation in fisheries management is associated with
increased trust across all aspects of fisheries management. In
addition, higher ratings of resource health by anglers are
associated with higher levels of trust of state and regional
institutions, but not federal institutions or scientific methods.
Keywords Cooperation � Fisheries management �Recreational anglers � Scientific assessment � Structural
equation modeling � Trust
Introduction
The benefits of developing and maintaining trust between
natural resource management agencies and natural resource
users have been well documented (Earle and Cvetkovich
1995; Beierle and Cayford 2002; Davenport and others
2007). Fostering trust between managers and those man-
aged has been shown to decrease public perception of risk
(Eiser and others 2007; Needham and Vaske 2008),
increase the likelihood of compliance behaviors (Dickson
and others 2009) increase coordination across diverse
stakeholders (Owen and Virderas 2008) and increase the
overall resilience of coupled social-ecological systems
(Ostrom and others 2008). These positive outcomes are
attributable, in part, to the ability of trust to minimize
social disorder by facilitating cooperation among individ-
uals and groups (Barber 1983).
Past research has highlighted the importance of learning
which enables trust to be built as individuals gather
information about the motives, objectives and behaviors of
others over time (Beratan 2007). Ultimately, the collection
of this information results in the acceptance or rejection of
another’s goals which then determines whether cooperation
is an appropriate response. Trust has also been framed in
terms of mental assessment of costs and benefits of coop-
eration. According to Rousseau and others (1998) trust is
best defined as a willingness to accept vulnerability based
upon positive expectations of the intentions or behaviors of
others. In these terms, individuals are rational actors and
the trust outcomes are carefully considered to determine
S. Gray (&)
Department of Natural Resources and Environmental
Management, University of Hawaii, Manoa, Honolulu,
HI 96822, USA
e-mail: [email protected]
R. Shwom
Department of Human Ecology, Rutgers University, Cook Office
Building, 55 Dudley Road, New Brunswick, NJ 08901, USA
R. Jordan
Department of Ecology, Evolution, and Natural Resources,
Rutgers University, 14 College Farm Road, New Brunswick,
NJ 08901, USA
123
Environmental Management (2012) 49:663–674
DOI 10.1007/s00267-011-9800-7
whether the benefits of cooperation outweigh the potential
costs to vulnerability. These definitions emphasize rational
responses and the role that knowledge, internalizing
information and learning play in influencing trust, which
may result in the decision to work together toward common
goals or to seek out an individually beneficial plan of
action.
However, studies have shown that not all trust judg-
ments are rational and learned appraisals. Rather, in the
absence of information about the motives and objectives of
others, emotions and heuristics seem to fill the knowledge
gap. In an experimental setting, Schwarz and Clore (1983)
found that people use their momentary affective states as
information. Building on this work Dunn and Schweitzer
(2005) determined that these ‘‘affect-as-information’’ heu-
ristics and familiarity with the trustee have a significant
influence on trust judgments. When the trustee is well
known, information is directly processed and evidence or
associations influence the trust decision. However, when
there is little information about the trustee, affect-as-
information and emotional associations may determine the
level of trust afforded to a trustee.
In this paper we investigated the factors that influence
trust in a natural resource management context using rec-
reational marine fisheries as a model. Specifically, we
designed and fielded a survey that sought to understand
how levels of anglers trust was related to familiarity with
management structures and science concepts, perceptions
of resource health, and whether or not anglers participated
in fisheries management. We hypothesized that these
variables would influence anglers’ level of reported trust in
fisheries management institutions and scientific assessment
methods because they are direct measures of self-reported
familiarity with processes and concepts which outline the
intentions of management- or are experiences (e.g., par-
ticipation) where the intentions of institutions are expected
to become better understood. To analyze the factors
influencing levels of trust quantitatively, we used structural
equation modeling (SEM), a type of multivariate analysis
used to determine strength of associations between pre-
dictor and response variables.
Trust in Natural Resource Management
Trust between individuals, groups, and an institution is
central to the effective management of shared natural
resources. In both experimental and field research, trust
appears to be a core variable to explain why participants
across settings tend to cooperate or not (Ostrom and
Walker 2003). This cooperation is especially important in
common-pool resource management because profit maxi-
mizing by harvesters has the capacity to threaten the sus-
tainability of a resource (Ostrom 2007). On short time
scales, harvesting restraint does not benefit the individual
and trust and cooperation are counter-intuitive responses
when the alternative response is to maximize returns
(McAllister and others 2005). Yet, considerable evidence
from past studies have indicated that trust and cooperation
are an appropriate response when the likelihood of
encountering the trustee again is high (Barclay 2004) and
the benefits of cooperation are clearly communicated
(Ostrom and Walker 2003). The mechanism for building
trust in a natural resource context is most often discussed
in terms of fostering shared values between manage-
ment agencies and stakeholder groups (Johnson 1999;
Cvetkovich and Winter 2003; Needham and Vaske 2008).
Aligning values increases cooperation by increasing the
perceived likelihood of accruing benefits. Shared values are
made explicit by reciprocity norms between individuals,
groups and institutions which are socially reinforced
(Ostrom and Walker 2003). These experiences and inter-
actions result in understanding the values of others which
then leads to trust judgments. As Johnson (1999) points
out, however, evidence of shared values is not necessarily
easily identified. Further, values are often complex and
multi-dimensional and are likely to vary across and within
stakeholder groups (Hoppner 2009).
Investigations of trust in a natural resource context have
overwhelmingly examined case studies between local
communities and government agencies. For example, in a
study investigating water-resource decision-making, Leahy
and Anderson (2008) qualitatively described the impor-
tance of trust between local community members and the
U.S. Army Corps of Engineers. In a review of three case
studies from river systems across the United States, Carroll
and Hendrix (1992) outlined trust’s contribution to col-
laborative management when local and affected citizens
were involved. Cvetkovich and Winter (2003) studied trust
between a range of local forest stakeholders and the U.S.
Forest Service management for the protection of endan-
gered species. All studies found that similar values between
local communities and agencies influenced level of trust in
management decisions and describe frameworks for agen-
cies to engage stakeholders through collaboration.
Research has also uncovered impediments to trust
building with local communities. In an investigation of
U.S. Forest Service and stakeholder groups, Davenport
(2007) found that low levels of community engagement,
unclear communication, and a history of adverse relation-
ships between communities and agencies can constrain
collaboration between communities and agencies. This
constraint can make it difficult, if not impossible, to
understand the values of stakeholders and communicate the
goals of the agency. A history of distrust in the federal
government, an agency, or in the management of a par-
ticular public resource can create a negative atmosphere
664 Environmental Management (2012) 49:663–674
123
that is difficult to dispel (Lawrence and others 1997).
Additionally, it has been found that it is much easier to
destroy trust than for trust to be built because negative
events have much greater impact on self-reported trust than
do positive events (Slovic 1993)
Public Participation as a Mechanism for Trust-Building
Although the benefits and outcomes attributed to trust are
somewhat clear, promoting and maintaining trust between
institutions and stakeholders is not an easily accomplished
goal (Johnson 1999). The most common tool available to
most natural resource policy-makers to promote trust is the
inclusion of stakeholders in the decision-making process.
However, this inclusion does not necessarily result in trust.
Measurements for success of these public engagements
vary and general typologies of participation are not easily
developed (Chess and Purcell 1999).
The term ‘‘public participation’’ refers to a diverse set of
activities which engage the public and vary greatly in terms
of who is involved, how early and often in the process, and
who has influence in the final outcome [National Research
Council (NRC) 2008]. Over the years, a set of general
guidelines for public participation have emerged (Rowe
and Frewer 2000). These guidelines emphasize the
importance of early contact and information exchange
between both parties in the management or planning pro-
cess. Researchers have also drawn attention to the impor-
tance of increasing the perception of procedural justice
(Webler and Tuler 2000). For example, public perceptions
regarding the ease of participation and that their input is
valued can be improved by offering multiple opportunities
to participate and engaging the public audiences through a
variety methods. In a natural resource context, Smith and
McDonough (2001) outline six themes which emerged
from focus group conversations regarding a participatory
ecosystem management project and call attention to the
importance of representation, voice, consideration, logic,
and desired outcomes when including the public in eco-
logical decision-making.
Understanding Angler Trust in Recreational Fisheries
Management
This paper uses the case of recreational anglers and fish-
eries management in the northeast to explore the factors
that predict their levels of trust. Using survey data collected
from 244 avid anglers in the Northeast U.S., we tested the
relationships using SEM. Recreational marine fisheries in
the U.S. offer a good opportunity to investigate individual
factors which may influence trust in natural resource
institutions beyond the local community case study
approach because recreational anglers are a loosely-
connected and diverse group of stakeholders. In addition,
marine fisheries management in the U.S. is designed
partially around public participation. Outlined by the
Magnuson Stevens Act (1976), resource managers consult
with stakeholder groups throughout all phases of manage-
ment, from the initial scoping process to selecting harvest
regulations, as a way to align goals and for management to
integrate stakeholder knowledge into the management
process. Stakeholders are even invited to participate in
some aspects of scientific assessment (Kaplan and McCay
2004) which has been shown to increase industry buy-in of
management procedures (Johnson and van Densen 2007).
Further, members of the management bodies (regional
fisheries management councils) are comprised of appoin-
tees who reflect the stakeholder make-up of the fisheries
under management (e.g., commercial fishermen, recrea-
tional anglers, environmental NGO representatives). Fish-
eries management has been designed deliberately this way
and is expected to increase legitimacy in decision-making
and produce more effective regulations by increasing
cooperation in common property management (Wilson and
others 2003).
Despite an extensive and ongoing participatory system
in place, levels of trust between fishery stakeholders and
management are not well understood. This is especially
true of geographically dispersed recreational anglers, for
which there is little data to support both their ecological
and political impact in modern fisheries management
(Arlinghaus 2005). However, because trust judgments are
theorized to be influenced by the varying types of infor-
mation resource users have collected (Beratan 2007) there
are a range of reasonable hypotheses that could be tested.
In our study we predicted that there are three types of
angler knowledge or information that will influence levels
of trust in management institutions and science: (1)
familiarity with fishery science and the management pro-
cesses (2) perceptions of resource health and (3) prior
participation in fisheries management.
To investigate the role of these factors empirically, we
tested the following hypotheses:
H1 High self-ratings of knowledge of fisheries science
influence higher level of trust in state, regional, federal
institutions and recreational and commercial science
If the level and type of knowledge held by anglers is not
consistent with the level and type of knowledge important
to fisheries management (which are scientific concepts)
then a potential disconnect between these two ‘‘knowledge
systems’’ may increase resource conflict (Skogen and
Thrane 2008) and decrease trust. This potential disconnect
between the often quantitative scientific assessment of
resource health and users’ qualitative assessment of
resource health may account for different preferences for
Environmental Management (2012) 49:663–674 665
123
management. Schisms originating from the tension
between scientific knowledge and lay knowledge in pre-
vious studies have been shown to increase resource con-
flicts (Dobbs 2000; Skogen 2001).
H2 High self-ratings of knowledge of fisheries manage-
ment influence higher level of trust in state, regional, fed-
eral institutions and recreational and commercial science
Low levels of knowledge or familiarity with concepts
key to fisheries management may reflect an uncertainty in
the values and goals of management, increasing the diffi-
culty anglers have in making direct and adequate assess-
ments about whether environmental management policies
are designed with angler goals in mind. Thus, the amount
of familiarity and knowledge stakeholders may have about
an institution and its practices are likely to influence the
amount of trust in a decision-making institution (Dietz and
others 2007).
H3 High ratings of fishery resource health influence
higher levels of trust in state, regional, federal institutions
and recreational and commercial science
Evidence of institutional success or failures, whether
accurate or not, is expected to influence trust of natural
resource management institutions. Recreational anglers
spend a great deal of time interacting with nature and their
evaluation of the current resource conditions, or produc-
tivity of these areas, may influence whether they trust the
performance of management bodies. Evidence of ecologi-
cal health may also influence risk perception. In other
wildlife contexts, hunter stakeholder groups who perceived
less ecological degradation reported higher ratings of trust
of management institutions (Needham and Vaske 2008).
H4 Participation in fisheries management will influence
higher level trust in state, regional, federal institutions and
recreational and commercial science
Trust has been repeatedly highlighted as an indicator of
success criteria in participatory decision-making and
planning (Beierle and Konisky 2000; Chess 2000; National
Research Council (NRC) 2008). Participation in manage-
ment processes is thought to increase trust of management
institutions because it allows for a space where shared
values can become better understood and conflicting values
can be addressed as groups work to co-construct a mutually
beneficial plan of action (National Research Council
(NRC) 2008). Further, past research has pointed to the
various types of participation adopted by management
agencies (Arnstein 1969; National Research Council
(NRC) 2008) which range from a top-down hierarchy or
placating system to a fully democratic system. If carried
out correctly, participation is expected to have a strong
positive effect on trust.
Method
In this section we will first describe how we measured the
variables hypothesized to be significant predictors of trust
in our model. We then describe how the survey was
administered and the survey sample. Finally, we discuss
the methods used for analyzing our survey data.
Survey Instrument Development and Administration
A survey instrument was developed to test the relationships
hypothesized above regarding what factors were significant
predictors of levels of trust in fisheries management and
science. Prior to surveying at the saltwater expos, local
interviews were conducted and a pilot questionnaire was
developed and administered to a subsample of 34 recrea-
tional anglers at a recreational fishing club in New Jersey.
Questionnaire items were validated for face validity
through one-on-one informal interviews which took, on
average, about 20 min per interview. The final survey
instrument measured the following exogenous and endog-
enous variables used in the model (see Fig. 1):
Exogenous Variables: Trust in Fisheries Management
and Science
We divide the exogenous variables into five separated
components: three levels of fishery management institu-
tions (state, regional, and federal) and two components of
fisheries science (methods used for assessment of
FisheriesManagementKnowledge
ResourceRating
Participation
FisheryScience
Knowledge
NMFS
RecreationalScience
CommercialScience
State
Regional
Age Class
Sex
Habitat
Size
Catch
Inolved
FMPs
MSA
OverallResources
ParticipateFishery
Bluefish
Participate
Fig. 1 Hypothesized structural model. Rectangles indicate measured
variables and ellipses indicate latent variables
666 Environmental Management (2012) 49:663–674
123
recreational stocks and pressure, and those used for com-
mercial stocks and pressure). Although these institutions
and scientific methods are related and rely on one another
to make decisions, they can be considered discrete entities
because management jurisdictions and decisions do vary
by state, region and federal levels. These levels of man-
agement include State Fisheries and Wildlife Departments,
the Regional Fisheries Management Councils, and
NOAA’s National marine fisheries service (NMFS).
Anglers were ask to rate their level of trust in each of these
five management components on a 5 point scale from fully
trust to fully distrust.
Endogenous Variables: Familiarity of Fisheries
Management and Science, Perceptions of Resource Health,
and Participation
To investigate subjective knowledge, anglers were asked to
rate their knowledge on key concepts important to fisheries
management and science on a scale from 1 (very knowl-
edgeable) to 5 (very un-knowledgeable). A subjective scale
was selected instead of an objective measure of knowledge
because past studies have indicated that personal beliefs,
which include self-rated confidence, are central to personal
trust judgments (Castelfranchi and Falcone 2000). To
assess knowledge about fishery science, anglers were asked
‘‘How would you rate your knowledge in the following
areas about the fish species you fish for:’’ in subject areas
fundamental to fisheries science including habitat needs,
determining age class, and determining sex of fish species.
To assess knowledge about civic literacy, anglers were
asked ‘‘How would you rate your knowledge about the
following areas of fisheries management and their pro-
cesses:’’ which included questions about how size and
catch limitations are determined, how to be involved in the
management process, the development of fisheries man-
agement plans, and about the federal mandate which guides
fishery decision-making, the Magnuson Stevens Act.
Anglers were also asked to rate the current state of
marine fishery resources. To assess angler perceptions of
resource health, anglers were asked, using a scale from 1
(excellent) to 5 (very poor), ‘‘How would you rate the
current state of the following resources’’. The resources
rated included several popular recreational fisheries from
the Northeast US, the overall fishery resources in the
region, and the fishery in which they participate most often.
Finally, anglers were asked whether they participated in
fisheries decision-making. In a marine fisheries context,
there are several opportunities in which stakeholders can
participate in fisheries decision-making. These range from
appointment to regional councils and fishery advisory
panels to attendance at fishery management meetings to
membership in organized groups who comment on
proposed fishery actions. Given the wide range of oppor-
tunities and the varied ways in which the idea of partici-
pation can be interpreted by individuals as a meaningful
endeavor, anglers were asked on a dichotomous scale to
indicate whether or not they participated in fisheries man-
agement decision-making. This question was designed to
characterize the number of anglers who believed that they
were involved in the fishery decision-making process in
some manner and not to determine the efficacy or the
extent of different levels of participation.
The final survey instrument was administered in person
(either computer-based or pen and paper) at two north-
eastern fishing expo events. Researchers manned a booth
and anglers were solicited to take part in the study.
Study Sample
Participants in this study were attendees at two northeast-
ern US saltwater fishing expositions in the late winter and
early spring of 2008. These are large trade shows typically
held in convention centers or similar venues with atten-
dance averaging between 5,000 and 10,000. Exhibitor
booths at these events range from recreational fishing ser-
vices and equipment to non-governmental and govern-
mental organizations. They are usually held in late winter
in the northeast US when conditions for fishing are poor.
Study participants were a convenience sample of general
audience attendees over a period of three days. The number
of surveys administered were similar at both 3 day events
in New Jersey (n = 118) and in Rhode Island (n = 122).
Given the nature of the events as a primarily commercial
endeavor and the restrictions placed on survey adminis-
tration by sponsors of these events, a random sample of
attendees was not possible. Although the data collected are
not representative of the population of saltwater expo
attendees, sampling techniques did attempt to solicit par-
ticipation from all general audience members which came
in close proximity of the survey booth. We estimate that
approximately 25 to 30% of individuals who were verbally
or visually invited to participate (e.g., through the banner
which advertised the survey above the booth) filled out the
survey to completion.
Although recreational anglers can be typified by a
variety of characteristics including consumptive behavior
(Fedler and Ditton 1994) and fisheries policy support
(Arlinghaus 2005), recreational anglers on the whole
remain a relatively diverse group. Our sample represents
coastal anglers who were predominantly male (*95%).
Most reported to fish from personal boats in coastal waters
at least 6–12 times per year (*79%) and most (64%)
fished on average more than once a week. According to
recent assessments, the average recreational angler effort is
13 days per year in New Jersey and 11 days per year in
Environmental Management (2012) 49:663–674 667
123
Rhode Island (US Fish & Wildlife Service (USFW) 2006).
Thus, the majority of our study participants reported well
above average fishing effort compared to the general
population of recreational anglers in both states and can be
thought of as frequent marine anglers.
Survey Analysis
After survey responses were collected, confirmatory factor
analysis (CFA) was conducted to ensure construct valid-
ity. To validate the variables and questions, we carried
out a reliability analysis using Cronbach’s alpha. Under
the analysis, items which had low factor loadings (\0.6)
or low Cronbach alphas (\0.6) were omitted as suggested
by Kim (2004) and Salisbury and others (2001). Using
this reliability analysis, the final latent variables and
questions which comprise these constructs used in the
final model are shown in Table 1. Ultimately, fisheries
science knowledge included three variables, fisheries
management knowledge included five variables, rating of
the resources included four variables, and participation
included one variable. To test the hypothesized model,
maximum likelihood estimates were obtained using
AMOS 17 software. The covariance matrix used to fit the
proposed model was calculated using survey data col-
lected in both New Jersey and Rhode Island and param-
eter estimates were obtained.
Results
CFA validated question categories and Cronbach’s alpha
for all latent variables indicated reliability between 0.84
and 0.91 (Table 1). Several model fit measures are usually
used to determine goodness of fit. Our model surpassed
the recommended values for all model fit indices, indi-
cating a higher likelihood that our model was valid
(Table 2). The most common goodness of fit test is the
chi square index which should reflect no significant dif-
ference and the model would ideally yield a value of
between 2.0 and 5.0. Our obtained value 2.7 indicated
good fit. The root mean square error of approximation
(RMSEA) provides an indication of the discrepancy
between the observed and model generated covariance.
A RMSEA value [0.05 indicates a good fitting model
where a value between 0.05 and 0.08 indicates a rea-
sonable model fit and [0.08 indicates an ill fitting model.
Our obtained value 0.078 indicated reasonable model fit.
Goodness of fit index (GFI) and Adjusted Goodness of Fit
Index (AGFI) measures fit compared to no model at all
(Joreskog and Sorbom 2001) and both values should be
[0.9 (GFI) and [0.8 (AGFI). Our obtained values 0.9
and 0.83 indicated reasonable fit.
Knowledge of Fisheries Management and Science
Survey responses indicate similarities between New Jersey
and Rhode Island recreational anglers in rating their
familiarity with fishery science and fishery management on
a scale from (1) very knowledgeable to (5) very
unknowledgeable. Here, we report the overall mean value
of responses. Overall, recreational anglers hovered around
the slightly knowledgeable side of the middle designation
(M = 3.0) with determining age class based on size
(M = 2.45), healthy habitat designation for larval and
juveniles fish (M = 2.63) and determining sex of a fish
when caught (M = 2.98). Similarly, recreational anglers
had higher, but similar mid-range ratings of familiarity
with civic aspects of fisheries management such as how
size (M = 2.13) and catch (M = 2.12) limits were deter-
mined with less reported familiarly with how to be
involved in the fisheries management process (M = 2.66)
familiarity in the development of fisheries management
(M = 2.66) plans and fishery legislation (M = 2.60).
Ratings of the Resource
Overall, recreational anglers rate the current state of fish-
eries resources as fair to good in all categories on a scale
from (1) Excellent to (5) Very Poor. The bluefish fishery
was most highly rated (M = 2.05), followed by the fishery
the individual participates in most (M = 2.30), followed by
overall regional (either Aid-Atlantic or New England)
resources (M = 2.67) with similar ratings for the summer
flounder fishery (M = 2.66).
Trust by Management Construct
Survey results indicate that trust in fisheries science and
management varies by scale. Survey responses for amount
of trust for state, regional, federal, recreational science and
commercial science were averaged. Only state (M = 2.82)
and regional (M = 2.90) institutions were more trusted
than not trusted while recreational (M = 3.01) science,
federal level management (M = 3.08) and commercial
science (M = 3.38) all fell on the distrust side of the
spectrum.
Structural Equation Modeling (SEM)
The structural equation model standardized multiple
regression indicated that participation had the most influ-
ence in determining level of trust (Table 3). In fact, par-
ticipation predicted strong positive correlations with state
(r = 0.72), regional, (r = 0.77), federal (r = 0.79), recre-
ational science (r = 0.79) and commercial science
(r = 0.82). These were all found to be statistically
668 Environmental Management (2012) 49:663–674
123
significant at 0.05. Ratings of the resources were also found
to have positive correlations and strongly influence trust,
but were only significantly for state (r = 0.26) and regional
(r = 0.26) levels of management and not for the other
constructs.
Discussion
Our results begin to shed light on the complex issue of trust
in natural resource management. First, our findings from
those surveyed indicate that trust in fisheries management
varies across dimensions (in scientific assessments versus
government agencies) and scale (local versus state versus
federal agencies). This has important implications for
efforts to increase trust in fisheries management and
potentially across natural resource management institu-
tions. These findings should also inform future studies on
the role of trust in fisheries management, in particular, its
measurement. Second, we find that trust in fisheries
Table 1 Summary of latent variables, measurement instrument, question loadings, validation and averages to questions responses for NJ and RI
Latent variable NJ mean (SD) RI mean (SD) T mean (SD) Alpha (a)
loadings
Survey questions
Knowledge of fisheries sciencea 0.89
Habitat conditions needed for larval or juvenile fish 2.60(1.3) 2.65(1.3) 2.63(1.3) 0.75
Determine age class based on size 2.37(1.1) 2.54(1.0) 2.45(1.0) 0.71
Determine sex of a fish caught 2.8(1.2) 2.9(1.2) 2.98(1.3) 0.7
Knowledge of fisheries managementa 0.91
How size limitations are determined 2.07(1.1) 2.20(1.1) 2.13(1.1) 0.78
How catch limitations are determined 2.11(1.1) 2.15(1.1) 2.12(1.1) 0.77
How to be involved in the management process 2.66(1.4) 2.66(1.4) 2.66(1.4) 0.74
The development of fishery management plans 2.72(1.4) 2.62(1.4) 2.66(1.4) 0.72
The Magnuson Stevens Act 2.65(1.5) 2.5(1.6) 2.60(1.6) 0.69
Rating of the resourcesb 0.84
Overall fishery resources 2.61(1.1) 2.71(1.1) 2.67(1.1) 0.72
Fisheries in which you participate most 2.25(1.1) 2.35(1.1) 2.30(1.1) 0.67
Summer flounder fishery 2.42(1.3) 2.9(1.2) 2.68(1.3) 0.73
Bluefish fishery 2.04(1.0) 2.07(1.0) 2.05(1.0) 0.66
Institutional trustc 0.9
State fisheries institutions 2.84(1.4) 2.78(1.2) 2.82(1.2) 0.73
Regional fisheries management councils 3.08(1.4) 2.84(1.1) 2.9(1.3) 0.79
Federal fisheries management (NMFS) 3.27(1.5) 2.7(1.4) 3.01(1.5) 0.81
Scientific trustc 0.9
Assessment science used to set seasonal limits for commercial fishermen 3.66(1.4) 3.13(1.3) 3.38(1.4) 0.81
Assessment science used to set seasonal limits recreational fishermen 3.33(1.5) 2.87(1.2) 3.09(1.4) 0.8
Participation
Do you participate in fisheries management in some way? Yes: 48% Yes: 38% Yes: 43% n/a
No: 52% No: 61% No: 57%
a Derived Cronbach’s alpha reliability test and factor loadings derived from principle components analysis (PCA)a Scale of (1) very knowledgeable to (5) very unknowledgeableb Scale (1) excellent to (5) very poorc Scale (1) fully trust to (5) fully distrust (3 is neutral)
Table 2 Summary of model fit indices, recommended, and obtained
values for hypothesized model
Statistic Recommended
value (P)
Obtained
value
X2 – 286.95
df – 116
X2/df [0.05** 2.47
Goodness of fit (GFI) [0.9** 0.9
AGFI [0.8** 0.829
CFI [0.9** 0.932
NFI [0.9** 0.9
RMSEA 0.05–0.08** 0.078
** Surpasses recommended value
Environmental Management (2012) 49:663–674 669
123
management is influenced by two factors. Although par-
ticipation in fisheries management was the only variable
that predicted trust across all constructs measured, an
individual’s perception of the health of a fishery was also
correlated with levels of trust. These survey results provide
us preliminary insights into the type of environments in
which trust in natural resource management institutions
might be formed.
Partitioning our survey results to just examine the
reported levels of trust in the concepts measured indicated
lower levels of trust in scientific assessments than gov-
ernmental agencies (with only the federal management
agency reporting as low levels of trust as the scientific
assessments). This lack of trust in scientific assessments is
problematic because fisheries management relies heavily
on the scientific assessment of the resource (population
estimates) and its social pressures (amount and frequency
of fishing activity) to set regulations. These estimates are
often made under conditions of high uncertainty yet have
direct implications for anglers because they are used as a
reference point for setting harvest limits. This uncertainty
is a result of the current limitations of stock assessment
methods to account for the multitude of non-linear rela-
tionships beyond fishing pressure that influence population
abundance. Retrospective analyses have highlighted that
over-estimates of population have led to stock collapses
(Myers and others 1997), while underestimates of popula-
tions have limited fisheries ability to produce social and
economic benefits to society (Hilborn 2002). In a stochastic
environmental system like the ones that characterize fish-
eries, the same assessment methodology may be applied
over a relatively short period of time to the same stock yet
yield oscillating estimates which may be interpreted by
stakeholders as erratic, imprecise, and uncertain. Manage-
ment decisions based on seemingly non-stable behavior
may result in lower levels of trust and compromise the
willingness of an angler to accept vulnerability (e.g.,
limiting harvests) based on these seemingly unstable
estimates.
Another reasonable explanation for low levels of trust in
science maybe reflected in stakeholder conflation between
understanding scientific methodology and the resulting
policy that emerges from these assessments. Low levels of
trust may reflect an issue of management credibility, where
respondents assign low truth value to the claims made by
the assessments (Barber 1983). Interestingly, participants
in our study rated commercial scientific assessments as less
trusted than recreational scientific assessments. This raises
an interesting question for future research on if this dis-
tinction is consistent and why it would be that frequent
recreational anglers perceive a difference in the processes
or outcomes in the two. Do they really think the assess-
ments are not valid? Or are they more concerned with the
policy-making process where outcomes of these assess-
ments are used to justify various policy decisions? In a
fisheries context, scientific assessments where a fish stock
has fallen will be used to justify a decision to limit recre-
ational and commercial harvests. If trust is low in scientific
assessments because the public confuses them with
unpopular policy outcomes (such as limiting harvests) this
may not be addressed by changing the assessment process
or increasing public participation in commercial and rec-
reational scientific assessments. The exact reasons for low
ratings of trust in science are unclear and are an area that
would benefit from further research.
In addition to respondents differentiating between sci-
entific and governmental institutions, trust also appears to
differ with scale of governance. The highest levels of trust
are reported for state fisheries institutions whereas the
federal government has the lowest level of trust. Past
research has indicated that familiarity is thought to affect
trust (Dunn and Schweitzer 2005) and local level gover-
nance is often more trusted than higher levels of organi-
zation (La Porta and others 1997). Although not large
Table 3 Structure equation model coefficients, and standardized multiple regression coefficients
Trust of fishery management institutions Trust of fishery science
State Regional Federal Recreational Commercial
coefficient
(standardized b)
coefficient
(standardized b)
coefficient
(standardized b)
coefficient
(standardized b)
coefficient
(standardized b)
Fishery science
knowledge
0.06(0.04) -0.05(-0.04) -0.03(-0.02) -0.04(-0.03) 0.19(0.12)
Fishery management
knowledge
0.01(0.01) 0.12(0.09) 0.08(0.06) -0.05(-0.03) -0.08(-0.05)
Resource ratings 0.36(0.26)*** 0.37(0.26)*** 0.18(0.11) 0.10(0.07) 0.10(0.06)
Participation 6.99(0.72)*** 7.53(0.77)*** 9.19(0.79)*** 8.56(0.79)*** 9.02(0.82)***
R2 0.58 0.68 0.69 0.64 0.68
*** Indicates statistical significance at the 0.05 level
670 Environmental Management (2012) 49:663–674
123
differences in the level of trust, these differences indicate
that our survey participants may discern between levels of
government and have higher levels of trust for local gov-
ernment. Anglers may feel more familiar with their state
agency and may perceive a clearer understanding of their
goals and intentions. Conversely, the goals of management
institutions which are more removed from the local context
may be unknown or difficult to assess. Smaller-scale gov-
ernance which is more familiar to the user may be seen as
more credible which has been shown to improve resource
health. In a comparison of top-down management decisions
based on scientific models which were not credible among
users to management decisions that were user-generated,
Dietz and others (2003) found increases in resource health
as a function of community lead assessments and the
generation of acceptable rules which increased compliance
behaviors.
Along with seeking to understand the varying degrees of
institutional trust, this study also attempted to identify
factors which influence trust. Of the variables investigated,
participation in fisheries management was the only variable
that accounted for higher levels of trust across all con-
structs. This finding may confirm previous studies that have
long supported that trust between parties increases as the
level of participation in decision-making increases (Beierle
and Konisky 2000; Chess 2000; National Research Council
(NRC) 2008). These findings add to this literature by
providing preliminary data that indicate that trust in sci-
entific methods of environmental assessment may also
increase with participation. Science plays a unique role in
environmental decision-making and ideally assessments
are guided by the knowledge, values and preferences of the
affected parties (National Research Council (NRC) 2008).
However our results indicate that stakeholders may also
learn to trust scientific assessments as they become more
familiar with the assessment techniques, questions, and the
institutions charged with conducting them through partic-
ipation. As Beratan (2007) points out, shared understanding
and trust are built through many personal interactions over
time which facilitates learning and participating in deci-
sion-making may allow for opportunities for this type of
learning. As stakeholders gain a better understanding of
institutional values and practices, the goals and intent
of scientific assessments may become more familiar,
therefore increasing trust.
Anglers’ perceptions that a fishery was in good health
was also found to positively influence trust, but only for the
state and regional levels of management. Higher ratings of
fishery resources were found to indicate higher levels of
trust in state and regional management. These ratings
indicate that respondents may attribute resource health to
the decisions and actions of smaller scale management
institutions. However, the inverse may also be true: if
respondents rate resource health as being in poor condition,
they may report lower levels of trust in the managing
institutions. This supports the idea that trust may be a
reflection of a respondent’s confidence in the institution’s
technical competence to carry out their mission (Barber
1983).
There are limitations to our study. First, our sample is
limited in its representativeness of the range of recreational
anglers that exist. It was a convenience sample ascertained
through a limited selection of those attending fisheries
expos in Rhode Island and New Jersey. Surveying a ran-
dom sample of anglers is difficult as there was no publicly
available listing of those who participated in recreational
marine fisheries at the time the survey was undertaken.
This method of recruitment was preferable to random
sampling of the public. As mentioned, the anglers surveyed
reported fishing more frequently than the average angler.
This clearly makes them an important stakeholder group
for the management of the recreational fisheries because
arguably they have more interaction with the managed
resources and therefore their beliefs and behaviors are
important components which need to be considered when
decisions are being made. But it also means that the gen-
eralizability of our results is limited and may vary from
those that spend less time fishing. For example, if the lack
of trust of scientific assessments stems from confusion of
its use in the political process to limit fishing then this
group might be more affected and thus less trusting. In
addition, the sample is limited geographically in the
Northeast. Different states and regions may reflect different
levels of trust with the state and regional fisheries relevant
to them because of historical experiences and a different
knowledge-based by which trust judgments are formed. In
addition, the sample size, although adequate, is relatively
small for the type of analysis performed. Despite these
shortcomings, this sample is useful for exploring relation-
ships between variables using SEM and does provide
empirical evidence to support potential relationships
between cognitive and behavioral factors and trust in nat-
ural resource management constructs.
Second, our survey measurement items are limited. We
define trust as a willingness to accept vulnerability based
upon positive expectations of the intentions or behaviors of
others (Rousseau and others 1998). However, those
answering our survey may have different understandings of
trust such as those based more upon assessments of an
institution’s technical competence and ability to fulfill
responsibilities. In addition, the data we have on past
participation is simply a binary yes or no. This measure
should certainly be refined in future studies to more thor-
oughly investigate the relationship between trust and par-
ticipation. Though the length of a survey is always an
important consideration, given the emergent importance of
Environmental Management (2012) 49:663–674 671
123
participation on trust in fisheries management institutions,
it would be helpful to know more about the form, content
and extent of the participation to help disentangle the
relationship. A more detailed analysis of objectively
defined knowledge and fine-scale analysis of type of par-
ticipation and their influence on trust is expected to be the
next step in parsing these variables beyond looking for
general correlations. However, given the dearth of infor-
mation in the literature about predictors of trust, we con-
sider this paper to be an initial inspection by which more
detailed hypotheses can be developed.
In addition, this study measured a respondent’s assess-
ment of trust at a specific point in time. It is important to
note that building trust is a dynamic and evolving process
and these levels are not likely to remain constant. The
causality between trust and participation is not unidirec-
tional. Rather, initial levels of trust may predict participa-
tion and participation may lead to more or less trust. Trust
is fragile, slow to grow and easy to break and as stake-
holders learn about potential changes in management
action, stakeholder trust may change (McKnight and
Chervany 1996; Beratan 2007). However, the process of
building trust is also seen as self-reinforcing where existing
trust may maintain trust in the absence of new events or
information (Blomqvist 1997). Therefore, although we
report the levels of trust at a certain point in time, we can
only expect these levels to remain as constant as new
significant developments in the fishery. Future studies
could be developed to survey individuals over time and
monitor changing trust and participatory experiences.
There are still many questions regarding other reliable
predictors of trust in natural resource management. In our
study, familiarity with scientific concepts used to make
regulations was not a significant predictor in trust judg-
ments in fisheries science. Likewise, familiarity with fish-
ery management processes did not yield significant positive
associations with trust judgments of institutions. These
results indicate that trust is not affected by how knowl-
edgeable individuals rate themselves in areas of abstract
components and processes of environmental management.
Rather, it is much more important that stakeholders have an
opportunity to interact with these components. As Rowe
and Frewer (2000) point out, there is not only a need for
institutions to learn how to effectively communicate
complex ideas to stakeholder groups, but also to create
opportunities where these complex ideas can be discussed
and debated (Hunt and others 1999).
Conclusions
The results of our investigation on trust can be interpreted
as both a learned and affective responses. As many have
pointed out, participation in decision-making by those
affected by the decision is thought to increase trust
(Beierle1998; Beierle and Cayford 2002; Dietz and others
2003; National Research Council (NRC) 2008). This is the
result of institutions and users forming relationships where
the goals of both groups are clearly articulated (Rousseau
and others 1998; Beratan 2007). In these cases, trust is the
result of active information processing and relies less on
emotions and more on a learned experience. However, in
large-scale environments where there few interactions
between institutions and stakeholders, stakeholders will rely
more on evidence generated from their own experiences and
associations to determine the intentions of institutions. Dunn
and Schweitzer (2005) found that when there is little history
or experience between individuals and a trustee, emotions
supplant information to form trust judgments. Thus, higher
ratings of trust can be expected with smaller scale institutions
and when experience indicates to stakeholders that the
resources and the environment are healthy.
It may be more difficult, however, to build trust in the
scientific methods used to make resource management
decisions. Although our study indicates that participation in
environmental decision-making is positively associated
with trust in science, low ratings of trust in science were
reported overall. Previous studies have linked distrust to
science to stakeholder conflation of scientific assessment,
the resulting policy, and the outcome of policy (Haerlin
and Parr 1999). Therefore, natural resource managers
should clearly outline the scientific questions being asked,
the methods and knowledge produced, how this knowledge
informs natural resource management policy and most
importantly how the knowledge created can be integrated
with the goals of stakeholders.
Acknowledgment This research was conducted under NOAA
Award NA07NOS4200129. The authors would like to thank the
Jacques Cousteau National Estuary Research Reserve (JCNERR), the
Rhode Island Saltwater Anglers Association, Brandon Johnson, Caron
Chess, and Josh Kohut.
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