Fisheries knowledge exchange and mobilization through a network of policy and practice actors
Introduction
Conservation science, as an applied discipline, is oriented towards active protection and restoration of biodiversity and ecosystems (Kareiva and Marvier, 2012). Research has shown that conservation scientists are motivated by seeing their research used in practical ways (Singh et al., 2014). However, direct impacts of university-based research on policy and practice are rare, and indirect impacts are not always evident, occur circuitously, and/or are significantly time-delayed (Adams and Sandbrook, 2013, Rose, 2015). In conceptualizing the challenge of encouraging (and observing) impact, we begin with Phipps et al.’s (2016) conceptualization of research impact as any instance in which an organization or community takes up new information to use it as a basis for a decision to maintain, adjust, or substantially change a given policy or practice. Conceptualizing impact in this way puts the emphasis on real-world decisions by end users, rather than by tracking readership or citation of articles as is often done (Phipps et al., 2016). Several recent papers have similarly argued that while traditional metrics of research impact that focus on dissemination are important, higher level impacts come from social, environmental, and economic outcomes that are not well captured using those measures (Singh et al., 2019, Cooke et al., 2020, Louder et al., 2021).
Our approach to knowledge generation and exchange is rooted in the sociology of science, similar to that of Fazey et al. (2014). In that seminal article, Fazey and colleagues argued that knowledge is constructed and that its interpretation is influenced by an individual’s prior knowledge, personal and professional experience, and group and organizational culture. This means that factors such as social norms, values, and power influence how knowledge is received and applied, often in the form of narratives distilled from data or findings (Buschke et al., 2019, Stern et al., 2021). Narratives that are favoured by influential and trusted actors ultimately shape policy and practice directions (Nursey-Bray et al., 2014, Armitage et al., 2015, Berdej et al., 2015, Rose, 2015, Rose and Parsons, 2015, Clark et al., 2016).
Studies of knowledge exchange and knowledge mobilization have shown that social and professional relationships are critical for facilitating the movement of knowledge within and across organizations (e.g., Crona and Parker, 2011; Kulig and Westlund, 2015; Nguyen et al., 2020). Interpersonal relationships move knowledge via advice-seeking, and add important dimensions of personalization and trust (Young et al., 2016a). Relationships help decision-makers access the information and knowledge that they need (Gale and Cadman, 2014, Kulig and Westlund, 2015), where knowledge is pulled and pushed between the domain of science and the domain of action (e.g. conservation and management) in an iterative process (Roux et al., 2006). When making decisions or plans, conservation actors have been shown to draw on personal experience, discussion with colleagues and experts, guidelines from governments and NGOs, and other informal sources (Pullin et al., 2004, Cook et al., 2012, Gale and Cadman, 2014, Rose, 2015, Rose and Parsons, 2015, Fabian et al., 2019, Kadykalo et al., 2021a).
There is also an extensive literature on barriers to the use of scientific evidence for conservation in practice and policy. Barriers include actors not having access to peer reviewed literature, limited organizational capacity for accessing and interpreting the science, institutional inertia, mismatches in priorities or decision-making processes, lack of trust in the research or researchers, and the influence of advocacy groups with an interest in maintaining the status quo (see Rose et al., 2018; Nguyen et al., 2019; Walsh et al., 2019). Underlying these barriers, adoption of scientific knowledge can often be hindered by a reluctance to take the political risk to change policy or management approaches, rather than a lack of knowledge among conservation staff (Shafer et al., 2015; Artelle et al., 2018; Nguyen et al., 2018).
We investigate scientific knowledge mobilization and exchange in relation to rainbow trout (Oncorhynchus mykiss) management in British Columbia (BC), Canada (Kadykalo et al., 2020, Kadykalo et al., 2021b). We use qualitative data from interviews to analyse how actors involved in the management of rainbow trout, as potential knowledge users, come into contact and become familiar with scientific research. Rainbow trout are important for recreational and subsistence fisheries, but impacts from climate change are putting greater pressure on wild populations. As cold-water salmonids, rainbow trout are impacted by hydrological changes such as increased water temperatures in summer, decreased water oxygen content, and increasing frequency of drought (Wenger et al., 2011, Jones et al., 2012, Whitney et al., 2016). These changes in habitat quality and quantity arising from climate change will have direct and indirect effects on fish health, condition, and survival (Whitney et al., 2016) with associated knock-on effects on fish populations and communities (Lynch et al., 2016).
Section snippets
Knowledge-action framework
This research makes use of the knowledge-action framework developed by Nguyen et al. (2017). The framework is intended to assist description and analysis of the movement of knowledge from generation to application. Fig. 1 offers an updated framework that places additional emphasis on (1) the influence of social norms, values, and political-economy (i.e., the political and economic interests of key groups), (2) knowledge exchange and mobilization as non-linear processes, and (3) social
Methods
The research presented in this article is part of a larger project entitled “Sustaining Freshwater Recreational Fisheries in a Changing Environment” that uses genomics tools to support the rainbow trout recreational fishery in British Columbia (BC). The project has both natural science and social science research goals. Its overall aim is to identify governance recommendations for sustainable rainbow trout populations and its recreational fishery (see also Grummer et al., 2019; Taylor et al.,
Results and analysis
Interview coding revealed four knowledge mediation spaces in which we were able to analyse processes of knowledge mobilization and exchange (Table 2). The inductive coding process initially yielded seven categories. Some of these categories were removed due to insufficient data and others were combined due to internal similarities, thus refining the categories into the four knowledge mediation spaces. As this was an inductive, case-specific process we do not suggest that they will be
Discussion
We examined the ways that government agents, stakeholders, and rights holders interact within four knowledge mediation spaces. These types of interactions are important to analyse because we know that scientific knowledge – in this case about rainbow trout – is not taken at face value, but is interpreted based on the immediate needs of actors (Fazey et al., 2014, Reed et al., 2014). Analysis of interviews revealed that there is frequent intra- and inter- organization interaction as actors seek
Conclusion
This article has used the case study of rainbow trout in British Columbia to explore knowledge mobilization and exchange from scientific research to policy and programs. Research has shown the importance of political, economic, and social influence on the ways that scientific research is adopted and used. Analysis of in-depth interviews with government staff and other stakeholders and rights holders illustrates this to be true in this case study, especially when it comes to policy and practice
CRediT authorship contribution statement
M. Andrachuk: Methodology, Analysis, Writing – original draft, Writing – review & editing. A.N. Kadykalo: Conceptualization, Methodology, Data collection, Writing – review & editing. S.J. Cooke: Conceptualization, Funding acquisition, Methodology, Writing – review & editing. N. Young: Conceptualization, Funding acquisition, Methodology, Writing – review & editing. V.M. Nguyen: Conceptualization, Writing – review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This project was funded through Genome British Columbia/Genome Canada [242RTE]. Andrew Kadykalo also received funding through Natural Sciences and Engineering Research Council of Canada (NSERC) [PGSD2-534299-2019].
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2023, Environmental Science and PolicyCitation Excerpt :This similarity has stimulated the development of specialized areas and highly trained personnel to mediate KEPs among a wide network of research institutions (KEP 1) in conjunction with other non-scientific actors (KEP 2) related to the conservation and sustainable use of Mexican biodiversity. Compared to the KEPs stages identified in the scientific literature to design research projects, websites, workshops or systematized reviews of the scientific literature (Pullin and Knight, 2003; Sutherland et al., 2004; Hart et al., 2015; López-Rodríguez et al., 2015; Löschner et al., 2016; Andrachuk et al., 2021), we offer a general model (Fig. 1) to design other types of tools for decision-making. In addition, our findings on the KEPs’ four phases, are a contribution to the discussion related to the complexity of the generation, mediation, and use of knowledge for decision-making (Reed et al., 2014; Nguyen et al., 2016; Andrachuk et al., 2021).
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2022, Journal of Environmental ManagementCitation Excerpt :Many environmental professionals seek to help research and management work together more effectively to achieve better environmental management outcomes. Select examples of existing approaches to research-management collaborations include research-within-management (vs trickle-down, transfer-and-translate, user-push; Gosselin et al., 2018), use of knowledge mediation spaces (Andrachuk et al., 2021), translational ecology (e.g., Enquist, 2017), a social-ecological watershed system framework (Nguyen et al., 2016), and adaptive management (e.g., Williams et al., 2009). We do not seek to modify, critique, replace, or comprehensively review these existing approaches.
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