ICES Journal of
Marine Science
ICES Journal of Marine Science (2016), 73(5), 1306– 1318. doi:10.1093/icesjms/fsv192
Contribution to the Symposium: ‘Effects of Climate Change on the World’s Oceans’
Editor ’s Choice
Empirical evidence for different cognitive effects in explaining
the attribution of marine range shifts to climate change
Ingrid E. van Putten 1,2,3 *, Stewart Frusher 2,3, Elizabeth A. Fulton 1,3, Alistair J. Hobday1,3,
Sarah M. Jennings 3,4, Sarah Metcalf 5, and Gretta T. Pecl2,3
1
CSIRO Oceans and Atmosphere, GPO Box 1538, Hobart, TAS 7001, Australia
Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS 7000, Australia
3
Centre for Marine Socioecology, University of Tasmania, Hobart, TAS 7000, Australia
4
Tasmanian School of Business and Economics, University of Tasmania, Hobart, TAS 7000, Australia
5
Murdoch University, School of Management and Governance, South Street, Murdoch, WA 6150, Australia
2
*Corresponding author: e-mail: [email protected]
van Putten, I. E., Frusher, S., Fulton, E. A., Hobday, A. J., Jennings, Sarah M., Metcalf, S., and Pecl, G. T. Empirical evidence for different
cognitive effects in explaining the attribution of marine range shifts to climate change. – ICES Journal of Marine Science, 73: 1306– 1318.
Received 2 June 2015; revised 27 September 2015; accepted 2 October 2015; advance access publication 23 November 2015.
The changing geographical distribution of species, or range shift, is one of the better documented fingerprints of climate change in the marine
environment. Range shifts may also lead to dramatic changes in the distribution of economic, social, and cultural opportunities. These challenge
marine resource users’ capacity to adapt to a changing climate and managers’ ability to implement adaptation plans. In particular, a reluctance to
attribute marine range shift to climate change can undermine the effectiveness of climate change communications and pose a potential barrier to
successful adaptation. Attribution is a known powerful predictor of behavioural intention. Understanding the cognitive processes that underpin
the formation of marine resource users’ beliefs about the cause of observed marine range shift phenomena is therefore an important topic for
research. An examination of the attribution by marine resource users of three types of range shifts experienced in a marine climate change
hotspot in southeast Australia to various climate and non-climate drivers indicates the existence of at least three contributing cognitions.
These are: (i) engrained mental representations of environmental phenomena, (ii) scientific complexity in the attribution pathway, and (iii) dissonance from the positive or negative nature of the impact. All three play a part in explaining the complex pattern of attribution of marine
climate change range shifts, and should be considered when planning for engagement with stakeholders and managers around adaptation to
climate change.
Keywords: climate change, fisheries, perceptions, range shift.
Introduction
Climate change, clearly documented in many regions (Burrows
et al., 2011; IPCC, 2013; Mora et al., 2013; Poloczanska et al.,
2013), is one of many pressures that affect the marine environment,
in addition to fishing, pollution, coastal development, and introduced species (Thomas et al., 2004; Halpern et al., 2008). Much
science is aimed at ascertaining the mechanisms responsible for
ocean changes and to untangling impact pathways to attribute causality between the different pressures, although there have been calls
for caution in attributing individual impacts directly to rising
# International
greenhouse gas emissions (Brander et al., 2011). Parmesan et al.
(2011) argue that it is rarely possible to attribute specific responses
of individual wild species to human-induced climate change, partly
as a result of the difference in scale of broad climate forcing processes
and the more “local” climate experience of animals. Nevertheless, a
range of studies have been able to directly link observed marine
species shifts with the rate and direction of climate shifts across the seascape (Pinsky et al., 2013; Poloczanska et al., 2013; Sunday et al., 2015).
There is a high level of scientific consensus on the contribution of
humans to climate change (IPCC, 2013); however, the level of public
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Empirical evidence for different cognitive effects
consensus on the issue is much lower (Charles, 2012; Leviston
et al., 2012; Cook et al., 2013). Differences in public consensus
on human contribution are linked to factors that determine individual attitudes to climate change which can be driven by
personal values, political ideology, the media environment, and
personal experience (Boykoff and Boykoff, 2007; McCright,
2011; McCright and Dunlap, 2011; Whitmarsh, 2011). Aside
from beliefs and attitudes, which are precursors of behaviour
(Ajzen, 1991), many different cognitive biases, such as confirmation
and normalcy bias, also contribute to behavioural differences and
decision-making within human populations (Kahneman, 2011).
In the context of the public’s acceptance of human-induced climate
change and climate-related behaviour and decision-making, a
number of psychological barriers have been identified, including
“limited cognition about the problem, ideological worldviews that
tend to preclude pro-environmental attitudes and behaviour, comparisons with key other people, sunk costs and behavioural momentum, discredence toward experts and authorities, perceived risks of
change, and positive but inadequate behaviour change” (Gifford,
2011, p. 290).
Insights into the differing levels of public acceptance of
climate-related issues come from attribution theory, and the concepts of cognitive dissonance, motivated reasoning, and other cognitive biases. Attribution theory (Heider, 1958) is concerned with
how cognitive perception influences the attribution of causes to
events or occurrences (Lewandowsky et al., 2012). Attribution is
the process of assigning meaning where attribution is an explanation, or an inference (Malle, 2011). Attribution theory allows us
to investigate the effects of cognitive dissonance and motivated reasoning on the attribution of a cause to an observed phenomenon. In
this paper, we focus on attribution which may provide insight into
perceptions of climate-driven changes in the marine environment
by marine resource users.
Cognitive dissonance is a psychological theory which states that
contradicting cognitions serve as a driving force that compels the
mind to acquire or invent new thoughts or beliefs, or to modify
existing beliefs, so as to reduce the amount of cognitive dissonance (internal mental conflict) between cognitions (Festinger,
1957; Adams, 1973). Similarly, motivated reasoning (Kunda,
1990) provides insight into how motivation influences cognitive
representations that drive decision-making. Motivated reasoning
posits that people are motivated to selectively search their prior
knowledge to support a pre-desired conclusion. The concept of
motivated reasoning also provides insight into how people will
avoid negative emotion or cognitive dissonance (Lewandowsky
et al., 2012). People tend to seek out information that confirms
what they already believe and arrive at conclusions consistent
with those beliefs. For example, people might construct evidence
for their belief that there is no drought from the fact that it is currently raining. However, their ability to arrive at such conclusions
is constrained by their ability to construct seemingly reasonable
justifications for these conclusions (Kunda, 1990). Both motivated reasoning and cognitive dissonance theories assume reconstruction and justification is associated with behaviour (Bersoff,
1999).
Together cognitive dissonance and motivated reasoning theories
can account for many cognitive biases. For example, filtering and/or
ignoring information that conflicts with existing beliefs (confirmation bias, Nickerson, 1998) allows individuals to avoid the uncomfortable tension that results from having, or reconciling, two
conflicting thoughts at the same time, and reinforces current
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beliefs. The filtering or ignoring of information is reinforced when
attribution is complex (e.g. when the science is not straightforward
or is not effectively communicated; Lewandowsky et al., 2012)
which in turn influences the attribution of causes to events or occurrences. This same type of cognitive bias, ere information is ignored,
is also observed when the impact of accepting the information is
negative or comes at a cost (Broad and Wade, 1983). Other cognitive
biases that can constrain shifts in attitudes and beliefs about climate
change causation are, for instance, the false consensus effect (an overestimation of the extent to which someone’s belief or opinion is
typical of the opinion held by others) and pluralistic ignorance
(people privately reject a norm they publicly hold—under the
false assumption that most others accept the norm; Leviston et al.,
2012).
The way people give meaning to, explain, or change their belief
about events or occurrences is researched in many disciplines
(Haidt, 2001; Lewandowsky et al., 2013; Lodge and Taber, 2013),
but the science of certain ecological phenomena itself is sometimes
difficult for individuals to accept due to the influence of the beforementioned cognitive biases.
When evaluating questions of causation in science, the patternseeking function of the human brain may betray us because information may conflict with what our senses perceive. Illustrations of
how this manifests empirically are not commonly found in the literature, especially in the context of marine climate change.
However, understanding the empirical expression of cognitive dissonance is important, for instance, to effectively guide the design of
climate change adaptation strategies (defined here as actions to
reduce the impact of climate change) which may require behavioural change. Understanding resource user reasoning will allow tailored
adaptation strategies to be developed and, importantly, provides decision makers and scientists with insights from the public they might
not have previously considered.
Although barriers to adaptation may be reduced, basic scientific
process understanding does not automatically affect belief in
climate change (Weber and Stern, 2011; Kahan et al., 2012;
Tvinnereim and Fløttum, 2015). For example, although scientists
attribute certain changes in the marine environment to climate
change, similar changes observed by resource users such as fishers
(Nursey-Bray et al., 2012; Gledhill et al., 2014), and the general
public, do not necessarily receive the same attribution
(Lewandowsky et al., 2012). Here, we discuss the insights that attribution, cognitive dissonance, and motivated reasoning theory can
offer in explaining differences in ascribing change in the marine environment to climate change. In particular, we explore how cognitive dissonance can affect explanations of causation—specifically
with regard to climate-related shifts in the distribution of marine
species. We explore this by illustrating marine resource users’ cognitions of three categories of range shift that have been observed in
eastern Tasmania, which lies within an ocean warming hotspot
(Hobday and Pecl, 2014). Recognizing and being able to attribute
the causes of biological change may be a first step to helping
reduce barriers to adaptation to climate change (Nursey-Bray
et al., 2012).
Here, we hypothesize that three factors, either alone or in combination, create a level of cognitive dissonance and that they differentially affect the rejection or acceptance of the role of climate
change in observed marine range shifts. These factors are (i) existing
engrained mental representations, (ii) the complexity of cause and
effect linkages, and (iii) the directional nature of the impact (positive/beneficial or negative/costly).
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Marine resource users’ exposure and experience
Attribution of the causes of marine environment change is not
straightforward, and evidence for the dominant causes of change
can take some time to emerge, particularly given the complexity
of the climate system (Pauly, 1995; Hobday and Evans, 2013;
Parmesan et al., 2013; Chambers et al., 2014). This is particularly
evident when attributing changes to anthropogenic causes, with increasing levels of confidence attached to the anthropogenic contribution to warming in over a decade of successive IPCC reports (e.g.
IPCC, 2001 vs. 2013). There is some evidence that people struggle to
gather and process complex climate science information (Guy et al.,
2013). When information is complex, there is a cognitive tendency
to find alternative and simpler explanation pathways that more
readily fit into existing mental schemes (Sterman and Sweeney,
2007; Kahneman, 2011). Complex climate science information
can be made more accessible and cognitively simpler if the actual
biological and ecological changes can be observed by users
(Kuruppu and Liverman, 2011).
One way for the public to visually observe biological and ecological
change is through direct exposure and experiences (Keller and
McInerney, 2008). For instance, local level experience of the effects
of climate events, such as erosion damage and coral bleaching,
tends to shape current perception of climate change as a “real”
issue and facilitates an understanding of the link (or attribution)
between the event, the impact, and climate change (Huntington
and Fox, 2005). This is one of the central theories behind establishment of Internet sites where public reporting of range-shifting
species (e.g. Range Extension Database and Mapping or Redmap,
www.redmap.org.au), phenological events (e.g. ClimateWatch www
.climatewatch.org.au), and climate extremes (Witness King Tides
http://www.witnesskingtides.org/) can occur.
Generally, the perception of risk associated with climate change
is that it is remote and removed from direct personal experience
(Bord et al., 1998; Stamm et al., 2000; Kirby, 2004; Lowe et al.,
2006). Therefore, direct experience of climate impacts can change
people’s perception of the risk, increase people’s concern, and ultimately their willingness to change their behaviours or choices
(Weber and Stern, 2011; Tam and McDaniels, 2013). On the other
hand, direct experience has also been shown to have the opposite
effect. Reduced support for any adaptation mounted in response
to, for instance, climate change, can occur if there is a belief that
the risk posed by the change is inevitable and cannot be prevented
(Wolf, 2011). In general, however, the cognitive presence of risk
associated with climate change increases through personal direct experience, especially experience associated with abrupt environmental change caused by extreme climatic events, such as floods (Höhle,
2002; Palutikof et al., 2013; Hodgkinson et al., 2014). If climate
change is only experienced as a slow and gradual modification of
average climate conditions coupled with considerable interannual
variation, as is often the case with annual rainfall levels, then
climate change is a difficult phenomenon to detect and track accurately based on personal experience (Weber and Stern, 2011). Direct
experience of abrupt or fast change is likely to bring the risk of
climate change to the fore, but the cognitive presence of climate
risk can also be affected by slower changes. Regardless of whether
the change is fast or slow, the observer has to have some mental baseline against which to compare the observed change. In other words,
an observer has to have both the ability to observe and to put the observation in context.
Although there is great diversity both between and within types
of marine resource users, fishers in particular are known to be keen
I. E. van Putten et al.
observers of their environment with many experiencing the marine
environment daily. The environment they typically experience is
dynamic, affected by seasonality and shifting patterns of ecology
and productivity (Hobday and Evans, 2013). Moreover, the
marine environment is susceptible to environmental shocks
caused by natural events (Coulthard, 2008; Garrabou et al., 2009;
Wernberg et al., 2012). Fishers (especially small-scale fishers) are
believed to develop intimate, detailed, and functionally oriented
knowledge of the marine ecosystems they exploit and the main
species they target (Silvano and Begossi, 2012). For the most part,
fisher marine-ecological knowledge has a utilitarian purpose
(related to catching), but often fishers are known to speculate more
broadly on the nature of the marine organisms that they target and
influences on the observed patterns of other marine species
(Goodwin, 2001; Nursey-Bray et al., 2012; Gledhill et al., 2014).
Studies have confirmed that as part of their personal and work
experiences, most fishers have observed changes in the marine environment and associated fish populations (Nursey-Bray et al., 2012;
Gledhill et al., 2014). Although these changes in the marine environment are often consistent with climate change (Zhang et al., 2011)
not all fishers who acknowledge observing climate-consistent
change also accept anthropogenic climate change as a driving
factor. This observation is not exclusive to the marine environment
as other studies have produced similar results related to perceptions
and attributions of climatic impacts (Hodgkinson et al., 2014). For
instance, in examining perceptions of drought and climate change
among Australian farmers, Milne et al. (2008) found that most
farmers attribute drought conditions to local stressors rather than
climate change alone. Here, we present a clear empirical case for cognitive dissonance in a group of marine resource users, largely composed of recreational and commercial fishers, in northeast
Tasmania, Australia. An understanding of dissonance can help to
explain why some climate-related changes are more easily accepted
than others, with implications for the development and implementation of adaptation options.
Methods
First, we describe a simple way of framing environmental change
and classifying the different types of marine range shift that occur
in the case study location. We then outline the data gathering
process and method of analysis to evaluate fisher perspectives on
these changes in the marine environment.
Case study location and local range shift phenomenon
The case study region lies within an ocean warming hotspot
(Hobday and Pecl, 2014), with observed warming faster than 90%
of the worlds’ oceans. Typically, range shifts have been fastest in
regions with a greater rate of warming (Burrows et al., 2011; Chen
et al., 2011; Neuheimer et al., 2011; Pinsky et al., 2013), and the
east coast of Tasmania is no exception with large shifts in many
species reported (Ling et al., 2009b; Pitt et al., 2010; Last et al.,
2011; Robinson et al., 2015).
To aid our analysis, we developed a relatively simple framing
characterizing environmental change, and range shifts in particular.
First, marine range shifts for any particular species in a region result
in an outcome that can be categorized by three factors: the relative
change in abundance (increase or decrease shown on the vertical
axis in Figure 1) and the ecological effect (neutral/positive or negative shown on the horizontal axis at the top of Figure 1) on the existing ecosystem. Negative ecological outcomes are the highest concern
to fishers and other users. The characterization of these two factors
Empirical evidence for different cognitive effects
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Figure 1. Marine range shift classification according to abundance change, ecological effect, and relative commercial value of the range shifting
species. Grey-highlighted cases (i), (ii), and (iii) are discussed in the text.
in Figure 1 is a simplification from what in practice is a continuum,
but it makes our subsequent analysis tractable. The third factor captures whether the species is commercially valuable; the potential
income effect (indicated in the text inside the eight boxes in
Figure 1). In this paper, we focus on commercial values, although
we recognize that both commercial and non-commercial species
can have recreational benefits, and that recreational and commercial
activity may not be independent when targeting the same resource.
To illustrate marine resource users’ cognitions of change in the
marine environment and corresponding attribution (or lack of attribution) to climate change-related marine range shifts, we focus
on three types of range shifts in eastern Tasmania where climate
has been implicated by scientific studies as a causal factor in each
case. The types of range shifts observed in Tasmania (Figure 2 and
discussed in detail below) are also observed in other regions of the
world. These range shifts are (i) decreasing abundance of existing
commercial species with a neutral ecosystem effect (e.g. Sissener
and Bjørndal, 2005; Hannesson, 2006, 2007; Stenevik and Sundby,
2007), (ii) increasing abundance of non-commercial species with
negative ecosystem impacts, e.g. pests (e.g. Zeidberg and Robison,
2007), and (iii) increasing abundance of new commercial species
with a neutral ecosystem effect (e.g. Engelhard et al., 2008; Figure 2).
A reduction in abundance of commercial species (case i)—
particularly southern rock lobster (Jasus edwardsii)—has been
observed on the northeast Tasmanian coast (Last et al., 2011;
Green et al., 2012; Robinson et al., 2015). This regional decrease
in abundance and commercial catches of southern rock lobster
have been attributed by scientists to the impact of climate changedriven sea surface temperature (SST) increases and ocean current
changes on larval dispersal and settlement (Pecl et al., 2009, 2014;
Johnson et al., 2011; Frusher et al., 2014). Most commercial species
in this region generally also have a smaller recreational component.
In the same region, a range shifting habitat-modifying species,
the sea urchin (Centrostephanus rodgersii) has become more abundant, but with negative ecosystem consequences (case ii, Figure 2).
High densities of this urchin lead to over-grazing and loss of kelp
forest habitat (Ling et al., 2009b), resulting in urchin barrens (an
area where no—or very little—marine vegetation remains) which
in turn reduces abundance of commercial species such as rock
lobster and abalone (Johnson et al., 2011) thereby reducing biodiversity (Ling, 2008). This native Australian species was first
recorded in Tasmania in the late 1970s and has moved steadily
southward since (Johnson et al., 2005; Ling et al., 2009b).
However, consistent with other research on invasive species in this
region (e.g. Valentine and Johnson, 2003; Thresher et al., 2003),
the urchin was initially considered an invasive pest species, rather
than the first of many range-expanding species. A range of scientific
studies now show that the range extension has been facilitated by
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I. E. van Putten et al.
Figure 2. Three different range shift phenomena along the northeast coast of Tasmania, Australia. CC stands for climate change. Cases (i), (ii), and
(iii) are discussed in the text.
two factors—larval movements facilitated by the strengthening
East Australian Current (EAC) that also penetrates further south
(Cai et al., 2005; Ridgway, 2007) and larval survival which is increased
by warmer winter temperatures (Ling et al., 2009b). A second example
of range-extending species with negative consequences for the environment in this region is an increased frequency of harmful algal
blooms usually associated with more northern plankton species
(Hallegraeff, 2010) which has led to fishery closures (http://www.
dpiw.tas.gov.au/inter.nsf/WebPages/SWIS-92A3LJ?open).
The third type of range shift involves arrival of new (and potential future) commercial species not previously abundant in the
region (case iii; Figure 2) and now appearing further south due to
the extending EAC and increasing water temperature. An octopus
species (Octopus tetricus) has been increasingly reported in commercial fisher logbooks on the north Tasmanian coast (Ramos et al.,
2014, 2015; Robinson et al., 2015). This species was first reported in
2005 and over the last 7 years has increased to 13% of the commercial
catch of octopus in this region (unpublished data, Department of
Primary Industries and Water, Wild Fisheries Management Branch
Tasmania). A second example involves the eastern rock lobster (Jasus
verreauxi) which is common further north off mainland Australia
and is now found frequently in Tasmania (Robinson et al., 2015).
Many of these future commercial species are initially many recreational
until abundance is sufficient to make commercial effort an economic
proposition. In addition, recreational fishers are reporting increasingly
frequent catches of key recreational game fish, such as snapper and
yellowtail kingfish (Last et al., 2011; Robinson et al., 2015), which are
popular targets in mainland Australian waters but previously rarely
caught in Tasmania, and may become targeted in commercial fisheries
in the future.
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Empirical evidence for different cognitive effects
Data collection
From past research, there was some evidence that fishers in this
region had been reluctant to acknowledge the impacts of a changing
climate on their target species and fishing activities (Nursey-Bray
et al., 2012; but see Frusher et al., 2014). Although some scientific
uncertainties remain, largely related to the speed and magnitude
of change, all examples of the three range shift cases in Tasmania
(Figure 2) have been attributed to climate change by scientists
(Engelhard et al., 2008; Ling et al., 2009a; Last et al., 2011; Frusher
et al., 2014; Pecl et al., 2014; Robinson et al., 2015).
An understanding of fisher perceptions with regard to each of
these range shifts was gained via semi-structured interviews conducted in northeast Tasmania in February 2013, as part of a large
project (Frusher et al., 2013). Interview respondents were contacted
primarily by a local member of an independent organization,
OceanWatch (http://www.oceanwatch.org.au/), who had been
working in the region for a number of years and, as an ex-fisher,
had good rapport with local fishers. Some additional respondents
were recruited through snowball sampling (Goodman, 1961) and
responses to public media. The primary purpose of these interviews
was to understand the relationship between adaptive capacity and
vulnerability (Metcalf et al., 2013, in press; van Putten et al., 2014).
Over a period of 1 month, a total of 35 respondents were interviewed. Interviews were recorded with the respondent’s permission,
and took place in the interviewees preferred location and lasted
60 min. New respondents were sought until preliminary analysis
showed that no new data and insights were being reported (e.g.
Hagerman et al., 2010). At this point, the number of interview
respondents was deemed sufficiently robust to draw inferences
about the relationship between adaptive capacity and vulnerability.
Interview participants were from a variety of industries and
backgrounds including commercial fishing, aquaculture, marine
tourism, accommodation, retail, restaurants, education, local councils, boat maintenance, and marine safety. All interview participants
had strong associations with the local marine environment and were
current or retired recreational or commercial fishers, and we collectively refer to them as either fishers or resource users. It is estimated
that 60% of local commercial fishers (who operate out of the local
port) were interviewed including rock lobster, pippies, abalone,
urchin, and finfish fishers. The majority (85%) of respondents
were male.
The interviews were semi-structured and organized around four
topics. First, details of the respondents’ employment and/or business interests were recorded. This included social and economic
detail such as how many years they had lived in the local area and
their social connections to the community. In the second part of
the survey, respondents were asked about their perception of the potential impact of socio-economic changes and changes in the marine
environment on their business and their community. In the third
section, the focus was narrowed to a description of the impact of
(biological) change on marine sectors including the potential
flow-on effects. In the final part of the survey, respondents were
asked to identify any future opportunities to deal with change and
potential adaptations to improve community outcomes. The interviews were free-flowing and the respondents were not specifically
asked to comment on the three types of range shift but rather respondent comments about the range shifts were volunteered unprompted. Information provided in interview sections 2 and 3
provided the data used in the analysis.
After the interview, the participants were also asked to take home
and fill out a survey containing a set of demographic questions (such
as age, time resident in the locality, education, community memberships, and income) and to indicate their level of involvement in different community organizations and activities. Fifty per cent of
interviewees mailed this survey to the researchers in the weeks following the interviews. The vulnerability and adaptive capacity analyses are reported in Metcalf et al. (2013, in press) and van Putten
et al. (2014).
Recorded interviews were available for 24 respondents which
were subsequently re-analysed for this study and a new database
constructed to determine contributing cognitions of the three
types of range shift. Although a total of 35 people were interviewed,
participants who indicated they did not want the interview
recorded, or in cases where the recording was of unusable quality
due to back ground noise, these were excluded from the analysis.
The information contained within the interviews (further referred
to as the data) was entered in the database according to the
number of mentions of topics, organized in four themes (Table 1)
with each theme comprising between three and six subgroups.
Each subgroup further consisted of several items. For example,
data were recorded at the individual species level in each of the subgroups of the species change theme (using the range shift classification shown in Figures 1 and 2). The subgroup “inadequate
management controls” contained items such as lack of regulation,
wrong size limits, lack of bag limits, or high total allowable catch
(TAC) limits. Each of the non-climate and indirect climate explanations were coded according to whether it applied to range shift case
(i), (ii), or (iii) or any combination of these three types of range shift.
Our results are based on an analysis of the content of the new
database by counting each respondent’s number of mentions for
each of the themes as they relate to the attribution of climate
change to each of the three range shift types. The identified cognitions were later ascribed based on the relative count of climate
Table 1. Coded interview data themes and subgroups.
Theme
Environmental change
Species change
Non-climate explanations
Indirect climate
explanations
a
Subgroup
Barrens
Turbidity
Nutrients
Silting/sedimentation
Habitat decline
Commercial (case i)
Pests (case ii)
Recreational (case iii)a
Unusual sightings
Education and science
Inadequate management controls
Overharvesting
Species-specific issuesb (including
bycatch)
Disease
Pollution
Change in ocean (temp. and current)
Change in drought/rain/floods
Other (e.g. change in sea-level, ozone, etc.)
The term recreational is used here because initially new species come into
the region not in adequate numbers to “support” a commercial fishery. A
commercial fishery would/could develop at a later stage if abundances grow
thus increasing the commercial viability of catching the species.
b
This category includes issues that affect abundance, but these effects are
indirect, through another species, such as due to an increase in prey species
abundance. Another example is where the abundance of a particular species
is affected because it is the bycatch species in a fishery for another species.
1312
I. E. van Putten et al.
and non-climate mentions for the three range shifts, a broader interpretation of the interview statements, and extant background
knowledge (available in the literature and residing with the
authors) for each of the range shift phenomena.
Results
Interviewees who provided the information that we used to characterize the attributions of the three different cases of locally observed
range shift were between 39 and 67 years of age (the average age was
52) and had lived in the case study area between 6 and 47 years (an
average of 24 years). Despite the relatively long residency of respondents in the local area, most (81%) were not born there, but all indicated they had no intention to move elsewhere in the future.
Nineteen respondents (79% of all respondents) had observed
general environmental change, such as degradation of habitat and
barrens formation, increased turbidity and nutrients, and siltation
(38 mentions). Fifteen of these respondents observed general environmental change as well as at least one of the three cases of range
shift. Four respondents observed general environmental changes
without specifically raising examples in any of the three cases of
range shifts.
Interview respondents offered a total of 23 non-climate-related
explanations for the three types of range shifts observed in the
marine environment and included examples from each of the six
subgroups (Table 1). As any one non-climate explanation could
be mentioned more than once by any interviewee, there were a
total of 86 mentions of non-climate explanations. The inadequacy
of management controls was the most frequently mentioned explanation (32 times).
Respondents mentioned eight different indirect climate-related
explanations for range shift 53 times in the interviews, again providing examples of all three subgroups (Table 1).
Interviewees were not explicitly asked if they believed in climate
change; however, some volunteered an opinion. Only three respondents explicitly indicated that they believed climate change was happening and linked this to warming ocean waters and changing ocean
currents. Four respondents expressed uncertainty about whether
climate change was occurring but acknowledged there may be a
link between changing ocean temperatures and ocean currents
and climate change. Two respondents explicitly denied the existence
of climate change, although they indicated changing ocean temperatures and changes in the currents were responsible for the increasing
abundance of some recreational species.
Of specific interest in this research were respondent observations
of the three types of range shift. We used the interviews as a basis for
understanding marine resource user’s acceptance or rejection of the
role of climate change in attributing causal linkages to marine
climate change. We illustrate support for our interpretation of the
interviewee statements for range shift cases (i), (ii), and (iii) with
representative quotes.
Reduced abundance of seven commercial species (case i) was
mentioned by 38% of respondents for a total of 13 times (Table 2).
Non-climate-related explanations were given ten times more frequently for these abundance changes than were climate change
explanations (63 vs. 6). Some interviewee statements around nonclimate attributions illustrate the perceived relationship between
commercial species and inadequate management controls and overharvesting. For instance, one retired fisher compares the change in
biomass levels of what was a virgin fishery (i.e. a fishery that has
not yet been significantly affected by harvesting) then to lower
biomass levels now due to commercial harvesting.
It was rampant with virgin fisheries. We’ve had a reduction of
virgin stocks—but that’s everywhere. You fish down virtually
every commercial fishery (retired fisher 750010).
I know we’ve had an impact with fishing—we’re catching less
fish. More to do with habitat not being there—don’t know
about the climate (fisher 750004).
Crays can go to Flinders Island [a location further north] or
somewhere else. . . . Not necessarily something to do with
the climate (fisher 750006).
Seventy-one per cent of respondents mentioned the increased abundance of eight different pest species in the local area (just over threequarter of these respondents mentioned the urchins). Changing
abundance of pest species was mentioned a total of 34 times. A
total of 28 non-climate vs. 29 climate explanations were given to
explain increasing abundance of non-commercial species with
negative ecological impacts (range shift case ii). This was evidenced
by a wide range of statements consistent with climate change such as:
Why have we got a bay full of jelly fish? . . . .Because of the
[extended] currents [bringing them down] (fisher 750003).
Changes in the environment are massive. We first noticed the
first urchin barrens 15 –20 years ago. The temperatures here
are insane it’s so much warmer some of the [commercial
fishing] industries are really going to struggle (recreational
diver 570027).
Table 2. Relative number of climate and non-climate explanations and the number of mentions for three different types of range shift.
Range shift type
Case i—decreasing
abundance of existing
commercial species
Case ii—increasing
abundance of pest
species
Case iii—increasing
abundance of new
commercial species
a
Interviewees
mentioning range shift
type (proportion)
38%
Total number of
Total number of non-climate
times mentioneda explanations
13
63
Proportion interviewees
who mention non-climate
explanations only
78%
Total number of
climate
explanations
6
71%
34
29
18%
28
58%
41
30
14%
37
More than one mention possible for each respondent.
Empirical evidence for different cognitive effects
In other interviews, attributions of environmental change were less
obviously related to climate change:
1313
affect the level of rejection or acceptance of the role of climate
change in observed marine range shifts.
That long string kelp was ripped out and created space for the
urchin [that’s why they are here] (retired fisher 850001).
The role of existing engrained mental representations
as blocks to attribution
If the water is warmer there it makes no difference on the
barrens—they are here too [where it’s colder] (fisher 750006).
It may be that in the absence of accurate or understandable schematic representations (or symbolized and simple representations) that
link the elements of climate science to local effects, fishers are
inclined to assimilate and associate their observations with existing
local pressures for which schemas have been developed (Kuruppu
and Liverman, 2011). In this way, individuals can reassert a sense
of “control” over uncertainty by cognitively restructuring a situation where one is aware of the likely course of actions and outcomes
(Mandler, 1990). Cognitive dissonance could thus be avoided by
rejecting or avoiding the information that challenges the belief
systems or by interpreting dissonant information in a biased way
(Festinger, 1957; Adams, 1973; Bradshaw and Borchers, 2000).
The effect of mental models on the differential acceptance of
climate change as an explanation for abundance change was
evident for all three range shift phenomena (cases i, ii, and iii).
More than half of respondents already seem to have a clear mental
model for the cause of any abundance change, particularly in relation to the decrease in abundance of existing commercial species
(with 78% attribution to exclusively non-climate explanations).
In the past, the main explanation (attribution) given by scientists
for declines in the abundance of commercial fish species has been
overfishing (e.g. Musick et al., 2000; Jackson et al., 2001). In the
Tasmanian region, for example, declines in southern rock lobster
(SRL) abundance led to implementation of fishery management
changes in 1998, including a limit on TAC and the abundance of
SRL subsequently increased (Hamon et al., 2009). Due to the apparent effectiveness of this management approach in increasing abundance, there was a deepening of understanding and acceptance that
there is a link between overfishing and reduced abundance
(Bradshaw, 2004) for most fishers. It is largely the same generation
of fishers who are again observing changes in abundance. This
overlap of experience and the existence of fishers’ previously
hard-won mental model (i.e. it took time to convince fishers that
overfishing was occurring and changes in behaviour were needed)
may explain the fisher’s tendency to attribute this current abundance change also to overfishing. In other words, based on past experience, fishers associate reductions in the TAC as an appropriate
response to overfishing (Costello et al., 2008) and use this to justify
their belief that current observed reductions in abundance must therefore be due to overfishing. Recent reductions in TACs in the fishery in
response to recruitment declines (which may be related to lesser abundance of females) may further mask the linkages between climate
change and fisheries by way of enhancing fishers existing mental
models of exploitation driving responses in fishery resources.
The concomitant rejection of climate change as an explanation
for current reductions in rock lobster abundance may be to avoid
cognitive dissonance to the fact that fishers have an existing
mental model that attributes reducing abundance to overfishing,
which was the main reason respondents gave in the interviews.
Moreover, during the earlier period when overfishing was the
main reason for reduced fish abundance, fishers found overfishing
difficult to accept. It required a significant amount of effort for
fishers to accept overfishing as the reason evidenced for instance,
by the number of public and private meetings between managers,
fishers, and scientists that took place at the time. Furthermore, a
long time elapsed between scientific evidence of overfishing, fisher
The [urchin] Centro is definitely the biggest [environmental]
change—but I don’t know why they are here (professional
diver 750013).
Everyone complains about the weed in the bay—we’ve
watched it become more prolific—but maybe it’s coming
back now as it was 80 years ago (recreational fisher and
shop owner 750026).
The increased abundance of 22 different fish species that had not
previously been observed in large numbers in the local area was
mentioned by 58% of respondents, a total of 41 times (we refer to
these as recreational species as initially abundances are too low to
support a commercial fishery). A greater number of climate explanations (37) vs. non-climate explanations (30) were given for the
changing abundance range shift type iii. Although there remained
a large number of mentions of non-climate explanations, the
increased abundance of new commercial species (case iii) most
often invoked climate change (or the symptom of the change
expressed in terms of warming ocean waters).
Snapper and whiting they are all seen here now and seem to be
increasing in numbers (especially in the last 20 years or so).
Most of these are from the warmer waters. You’d nearly
have to think that way—that it [the current] is bringing
them further down (fisher 750002).
Now we were catching eels as far down as St Helens in our
pots—this year we had flying fish—warm current is closer
into shore [and further down] and that’s brought them in
(fisher 750019).
See more whales now—pretty much consistently—don’t
know why. We see some flying fish in summer and they
seem to come down in the warmer water (fisher 750028).
Without any proof I would say I believe in climate change. For
instance, all of a sudden we’re starting to get new species (e.g.
tailor that are New South Wales or Queensland fish) not just
in ones or twos (recreational fisher and diver 750030).
Overall, these results show that climate change was invoked to different degrees when explaining how the three types of range shift may
have occurred.
Discussion
As set out in the introduction to this paper, we hypothesize that attribution theory, cognitive dissonance, and motivated reasoning
may help explain fishers’ ascription of climate change as a cause of
the observed marine range shifts phenomena described in the
Results section. We contend that cognitive dissonance is central to
the ascription of climate change as a cause of the three range shift
phenomena. In particular, the internal mental conflict created by
(i) existing engrained mental representations, (ii) the complexity
of the science between cause and effect, and (iii) the directional
nature of the impact (positive/beneficial or negative/costly) may
1314
support, and management change. This may partly explain why it is
more difficult to now shift this mental model. People have invested
in the mental model and may subconsciously hold strongly to it. We
acknowledge that, as in any survey involving people, some “strategic” answers (Dunning, 1999) might have been given by fishers
whose aim was to make a point. For instance, fishers may have
answered that there was no reduced abundance even if they might
have observed it, due to their wariness of governments reducing
TACs as a consequence. Similarly, fishers may have wanted to
appear consistent with what they thought their peers might be
saying in response to the same question. This phenomenon was previously referred to as pluralistic ignorance (Leviston et al., 2012). We
do not think this has affected our conclusions here, because of the
open discussions that were part of the interview process with a
trusted interviewee.
Mental schemes may already exist for the arrival of new noncommercial “negative” species. Attribution of the establishment
of marine pests to discharge of wastewater from sea freight
(Carlton and Geller, 1993) and run-off from some land-based activities (i.e. aquaculture) were mentioned in about one-third of the
interviews. However, due to the long period of scientific research, effective science extension, and regional fisheries management meetings, the attribution of the range shifting urchin pest seemed to be
increasingly recognized by fishers as climate driven, and mental
schemes may thus be in the process of changing. In other words,
the successful communication of the extensively studied urchins
where the attribution to climate change was established (although
somewhat complicated because there is also a potential feedback
between urchin success and the lack of large predatory lobsters,
Marzloff et al., 2011) seems to be creating a new mental schema
for fishers.
In contrast, our results indicate a weaker reliance on non-climate
explanations and pre-existing mental schema around the arrival of
new commercial species. This appears to have left the way open for a
more ready attribution of this phenomena to climate change and
willingness of fishers to entertain new possibilities as facilitated by
the exchange of information of reported new sightings (e.g. www.
redmap.org.au, Range Extension Database and Mapping project),
or because the arrival can be simply (and intuitively) explained by
ocean currents.
The role of complexity
The complexity of the underlying science linking changes in abundance of marine species and climate change also seems to affect the
relative acceptance of climate change as an explanation of the different types of marine range shift. In fact, the complexity of the science,
the relative number of existing studies, and the “indirectness” of the
impact pathway from climate change to the biological response
seemed to compound the adherence to existing schematic representation. The way the southern rock lobster is impacted by climatedriven change (i.e. larval dispersal and settlement) is complex and
not well understood by scientists. Interview respondents did not
seem to have absorbed the limited science that was available and
were uncertain of the link between the complex ecological information and climate change. In contrast, there is a high level of scientific
understanding of the way in which new pest species became resident
in the region. For instance, the relationship between increasing temperature and the successful survival of organisms under warmer
ocean temperatures in winter (Ling et al., 2009b) is relatively
straightforward. The science underpinning the arrival of new commercial species is mainly around two interlinked biophysical
I. E. van Putten et al.
changes: ocean temperature increases, and the strengthening of
the EAC (Ridgway, 2007; Frusher et al., 2014). These two concepts
were well understood and the idea of fish following their most preferred habitat characteristics, and thus moving south (in the southern hemisphere case) is a relatively tangible concept for fishers.
Consequently, the way that the arrival of new species was explained
by fishers was not scientifically complex, with one fisher explaining
that the fish simply “floated down” on the extending EAC.
Negative or positive impact: influence on attribution
The degree of acceptance of climate change as an explanation of the
different types of marine range shift was not only affected by the existence of fixed mental schemes and scientific complexity, but we
contend that it is also affected by whether the effect was positive
(beneficial) or negative (costly; Figure 1). There are many cost (or
loss) components associated with changing abundance, with some
more obvious (direct) than others. For instance, the losses in
revenue from reduced catches might be an obvious cost, but the
need to learn new catching methods for new species is an indirect
outcome and may not be as obvious.
An obvious cost (loss) to resource users is associated with decreasing abundance of existing commercial species and results in a
negative change in the form of extra financial costs or reduced
profit margins. Such negative change can be very difficult to cope
with especially for fishers who are already facing tight financial circumstances (more than 90% of fishers indicated that they were
“struggling” financially). A small number of interviewed fishers
indicated that climate-driven pressure on abundance was seen as a
further impost and because they have already suffered financially
they were unsure how to cope with further change. For (i) range
shift (Figure 2), there is a personal cost in terms of behavioural
change (e.g. changing fishing gear, travelling further, generating
new expertise, or changing target species) for accepting climate
change as a cause of changing abundance or the target species. In
contrast, believing that fisheries management actions will contain
the problem means there is no perceived pressure for costly
large-scale change in practices.
Significant costs can be associated with regional establishment of
new pest species (i.e. the ecological impact on commercially fished
species and/or cost of control and monitoring). The cost impact
of pests can change over time, for instance, with development of a
commercial harvest of the pest urchin. The shift from being a pest
species and a cost, to providing commercial opportunities (and
thus beneficial) may be associated with an increasing acceptance
of attributing climate change driving this pest species range shift.
Fishers may have embraced or may desire the climate-driven
change under the assumption that benefits will be substantial
(maybe greater than can actually be realized; Kahneman, 2011).
New species (case iii) generate a potential (additional or alternative) profit for commercial fishers and recreational opportunities
with new recreational game fish species. While range shifts of this
type may also involve costs, for instance, acquiring new knowledge
and expertise to efficiently catch these new species and establish a
commercial enterprise, on first assessment, benefits may outweigh
costs.
Implications for climate change communication
and adaptation
The theories mentioned in the introduction may help explain an individual fishers’ rejection or acceptance of attributing marine range
shift phenomena to climate change. Interview responses in a case
1315
Empirical evidence for different cognitive effects
study area in a marine climate change hotspot in southeastern
Australia indicate that existing mental models, scientific complexity,
and the relative cost or benefit of the change may all contribute to
explaining the different attribution of different types of range
shifts (but essentially the same marine climate change phenomena)
to climate and non-climate drivers.
The increase in SST and the strengthening of the EAC are the
main mechanisms through which climate change impacts range
shifting species in the focal region. The arrival of new commercial
species was the case for which resource users seem to most readily
acknowledge an attribution to climate change. We suggest this is
because the science was not complex, they had no pre-existing
mental model, and impacts were at first glance beneficial. In contrast, reduced abundance (by the poleward movement) of a commercial species was not commonly attributed to climate change.
This could be explained by a number of factors including the
strong pre-existing mental model that overfishing negatively
affects abundance and the difficulty in separating these effects
from climate and other drivers. This rejection of the climate
change explanation is compounded by the complexity of the
science and the clear cost associated with reduced fish abundance.
The study shows that the acceptance of one causal link for a
change in a particular aspect of an ecosystem (i.e. climate change
as an explanation for range shifting species) does not mean that
the same causal links for other elements in the same system are
also accepted. This information is useful not only when trying to
understand human responses to climate-related information, but
for managers and policy-makers seeking to advance climate
change responses. Understanding on one aspect (e.g. one species)
does not necessarily mean further acceptance will be easy or straightforward, and stakeholder engagement processes may need to repeat
previous steps on each new issue.
It must be emphasized to further unpack the process of attribution
of a broad range of climate change-driven effects in the marine environment through targeted surveys. A dedicated understanding is
needed to ensure that no time and opportunity is lost and more is
learned of the way people experience and attribute change. This is particularly important where it concerns the individuals who directly and
frequently interact with changing ecosystems who may have nonscientific insights that add to the pool of scientific understanding.
The psychology that explains how climate change phenomena
are observed and interpreted by key stakeholders and also the
ways by which these same stakeholders attribute meaning to them
has to be understood to adequately prepare people for potential
climate-driven changes. This empirical study suggests that not
only the biophysical outcome, but also the economic situation,
the relative direction of change, the historical context of change,
and the specific situation of individuals involved has to be fully
understood to understand the likely attribution responses. This
awareness can enhance approaches that seek efficient and effective
adaptation to climate-driven change in the marine environment.
With increased recognition of the need for planned adaptation by
Governments to the increasing impacts of climate change, it is essential that individuals and industry perceive that there is a common
cause that needs to be addressed. Our results demonstrate that
there remains considerable work that still needs to be done to
ensure that users recognize the cause of their observations, as attribution can vary across different outcomes from the same cause—in
our case range shifting species.
To provide additional insights into our thesis, future studies are
deemed necessary. Further investigation is needed of the cognitions
we have outlined and confirmation of the issue of cognitive effect in
attribution has to be robustly investigated using methods and
approaches common to empirical and experimental psychology.
Acknowledgements
We would like to thank the anonymous reviewers and the editor
for their help and suggestions. This research was funded by the
Fisheries Research and Development Corporation and the former
Department of Climate Change. This research would not have
been possible without the local participants.
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Handling editor: Sarah Kraak