A Best Practices Case Study for Scientific Collaboration between Researchers and Managers

Abstract

Effective engagement among scientists, government agency staff, and policymakers is necessary for solving fisheries challenges, but remains challenging for a variety of reasons. We present seven practices learned from a collaborative project focused on invasive species in the Great Lakes region (USA-CAN). These practices were based on a researcher-manager model composed of a research team, a management advisory board, and a bridging organization. We suggest this type of system functions well when (1) the management advisory board is provided compelling rationale for engagement; (2) the process uses key individuals as communicators; (3) the research team thoughtfully selects organizations and individuals involved; (4) the funding entity provides logistical support and allows for (5) a flexible structure that prioritizes management needs; (6) a bridging organization sustains communication between in-person meetings; and (7) the project team determines and enacts a project endpoint. We predict these approaches apply equally effectively to other challenges at the research-management-policy interface, including reductions of water pollution, transitions to renewable energy, increasing food security, and addressing climate change.

Insights from a novel, user-driven science transfer program for resource management

“…Thoughtful self-reflection five years into implementation of a new Science Transfer Program designed to close the knowledge-action gap allowed us to identify six key success factors for effective knowledge transfer at the program and project levels. While none of the success factors we identified explicitly overlapped with those recently presented by Newcomb et al (2021), several commonalities occur and their model of research-management collaboration (their Fig. 1) is remarkably similar to the relationships supporting the GLFC Science Transfer Program (shown herein as Fig.…”

“…Ideally, modern natural resource management is "science-based," insofar as scientific data, evidence, and knowledge are important inputs to these decisions (Ehrlich and Daily 1993) alongside other factors such as stakeholder and rightsholder interests, cultural priorities, economic considerations, and political priorities (Garcia and Cochrane 2005;Ludwig et al 1993;Young 2015). However, it is increasingly clear that significant gaps exist between the data, evidence, and knowledge that are generated by researchers and those that are actually used by natural resource managers to make decisions (Arlettaz et al 2010;Cvitanovic et al 2015;Fabian et al 2019;Newcomb et al 2021). This so-called knowledge-action gap is due in part to the time lag between the generation of new knowledge (heretofore a shorthand term for data, evidence, and knowledge) and its communication and transfer, lack of formal management structures (i.e., statute, administrative code, or policy), as well as institutional inertia to its uptake (reviewed in Cook et al 2013; see Table 1 for glossary of terms used herein).…”

Evaluating stakeholder engagement in collaborative research: co-producing knowledge for climate resilience

“…Finally, engagement outcomes are highly scalar-dependent in terms of time and space. Institutional expectations, combined with time constraints imposed upon grant-funded initiatives (Newcomb et al 2021), may limit the development and/or sustainability of long-term relationships between researchers and stakeholders (Church et al 2022), further confounding collaborative research processes and outcomes (Worosz et al 2022). Therefore, collaborative research designs should strive to match engagement modality and intensity to the goals of the research, recognizing that while stakeholders' deeply held values change slowly, their preferences for policy solutions may be influenced over shorter timescales through social learning (Vincent et al 2021(Vincent et al , 2018Slater and Robinson 2020;Gerlak et al 2019;Djenontin and Meadow 2018) and deliberative knowledge exchange (Koebele 2020;Meadow et al 2015).…”

“…While scientists often perceive that they generate information intended to improve resource management decisions, resource managers often wonder why science does not provide the information they need to make decisions (Cooke 2019 ). Past reliance on top down, unidirectional science research that segregates academic disciplines and the research process from public involvement (Steelman et al 2021 ) has inadvertently led to what has been called the science–policy divide (Steelman et al 2019 ; Newcomb et al 2021 ), knowledge–action gap (Knutti 2019 ), or theory–practice gap (Cooke et al 2021 ). To help remedy this problem, transdisciplinary collaborative science research approaches have emerged to intentionally engage decision-makers and other stakeholders in the research process (Dekker et al 2021 ; Steelman et al 2021 ) with the goal of co-producing new knowledge that can inform and support actionable change on the ground (Caniglia et al 2021 ).…”

Research disciplinary interactions on scientific collaboration network in photocatalytic hydrogen evolution: Characteristics and dynamics

“…Subsequently, various informal academic information interaction and cooperation are formed in academic social networks [ 11 ]. Scientific collaboration can appear in different scholars, disciplines, institutions, regions or countries [ 12 , 13 ].…”