Co-production for adaptive management: Where we’ve been and where to go from here

At the 2024 AFS Annual Meeting in Honolulu, Hawai‘i, we convened the session “Co-production of integrated ecosystem-based science for management decisions, “which was organized into three blocks that focused on a central theme of the conference—co-production, and its role in integrated ecosystem assessments (IEAs; a process to provide scientific information, considering all components including humans, to support ecosystem-based management [EBM]); IEAs with a focus on socioeconomic/sociocultural sciences (hereafter referred to as social sciences); and management strategy evaluations (MSEs; a key step in the IEA process). Presenters are credited throughout this essay, but we acknowledge that most of the work was collaborative and coauthors can be found online in the Annual Meeting Full Program (https://bit.ly/4gUgjdE). Our session concluded with a Mentimeter questionnaire for attendees and an open discussion (Figure 1). The goal of this essay is to highlight the progress that has been made through co-production to achieve EBM (which includes ecosystem-based fisheries management) across the United States and internationally, in an effort to identify the barriers and difficulties that may slow our progress, and to propose solutions to these challenges that can be implemented by the American Fisheries Society. Attendees were asked to share what the phrase “co-production” meant to them. Top answers included the following: collaboration, partnership, inclusive, collaborative, respect, reciprocity, and together. Co-production of knowledge is the contribution of knowledge from different interested groups spanning the ­science–policy–­society interface with the goal of co-creating information or products for environmental decision making (Lemos & Morehouse, 2005). By empowering co-ownership of the direction, methods, and final products of EBM, knowledge can be better integrated throughout, resulting in more robust and successful deliverables and actions (Djenontin & Meadow, 2018; Howarth & Monasterolo, 2017; Kirchhoff et al., 2013). This approach blends well with the adaptive nature of IEAs and MSEs, allowing for ample opportunity for increased participation, input, and ownership by interested groups and knowledge-holders. Effective co-production incorporates scale and intended application, as utility varies based on spatial and temporal scales of data and relevant management levers. Additionally, the most effective products are flexible, readily measurable, constructed with consistent, public-facing data, and must be directly relevant to management questions in the domain of interest (Montenero et al., 2021). The need for and benefits of EBM are well documented (e.g., Fogarty, 2014; Larkin, 1996; Link & Marshak, 2021; Pikitch et al., 2004). Ecosystem-based management takes an inclusive approach to management by considering the ecosystem as a whole rather than single-species or a collection of fisheries stocks. It includes all species, habitats, environmental factors, and human dimensions, not just individual fish stock population parameters, thereby enabling consideration of changing environmental conditions and human impacts for more sustainable and resilient fisheries management. In short, it aims to maintain healthy ecosystems that can provide long-term benefits for the environment and fishing communities. Adaptive management is a “means of linking learning with policy and implementation … learning from experience and modifying subsequent behavior in light of that experience” (Stankey et al., 2005) and a key process in support of EBM. It is a process in which co-production of knowledge creates an understanding of socioecological systems, including uncertainties, to necessitate a change in management. The IEA framework of defining goals, developing indicators, assessing ecosystems, analyzing risk, and evaluating management strategies invites co-production at each step leading to adaptive management and interaction of the process. Specifically, MSE, a “learning by modeling” process, relies on knowledge co-production to establish management objectives, model structure, and performance criteria. Most fisheries applications of MSE have been applied for single-species management, but ecosystem-level MSEs are becoming more common. Both IEAs and ecosystem-level MSEs have many common elements and are both necessary tools for EBM. Presenters from academia, various programs within the National Oceanic and Atmospheric Administration (NOAA), and regional fishery management councils shared examples of successful co-produced science that have been used for management or policy decisions. Examples included Mark Monaco’s (NOAA) tradeoff analysis of offshore infrastructure siting to minimize user conflicts of ocean space and Brittany Troast’s (NOAA) data visualization and trend analysis to capture changes and impacts of a sediment diversion project in Louisiana. Dan Dorfman (NOAA) showcased how NOAA’s Office of National Marine Sanctuaries relies on the co-production through community engagement with interested citizens, academics, government entities, and private sector partners to provide decision makers with tailored science information for sanctuary condition reports, which provide critical information to support development of sanctuary management plans and enable place-based ecosystem management. Steven Scyphers (University of South Alabama) discussed targeted management strategies by leveraging a diversity of knowledge to better understand the function of both key species and biodiversity in ecosystems as well as economic and social benefits. Presenters highlighted the strengths of utilizing a co-production process as part of MSE and clearly highlighted the pitfalls when such a process is absent. Ed Camp (University of Florida) presented the 2012 collapse of oyster populations in Apalachicola Bay, which highlighted an opportunity to explore viable management with interested parties and resulted in co-development of a socioecological model to predict the outcomes of various management actions. This participatory process proved successful in reaching agreement on the more suitable options, such as limited entry. However, support for such restrictive options was limited to participating individuals and not accepted by the broader community, highlighting the need for co-production processes to be broadly inclusive from the start. Desiree Tommasi (NOAA) discussed the process of integrating stakeholder input into the MSE for North Pacific Albacore Thunnus alalunga, which demonstrated that human communication and trust-building were critical for successful adoption of harvest strategies. This experience highlighted that overcoming challenges in MSE often relied more on stakeholder relationships than on the technical outputs of computer models. Jaclyn Cleary (Fisheries and Oceans Canada) presented lessons from a process launched in 2015 to update the management system for Pacific Herring Clupea pallasii in British Columbia. The goal was to be as inclusive as possible, especially to First Nations, in the decision-making process. A MSE framework was developed, but full completion for all stocks has yet to be realized. Key lessons included the importance of co-developing objectives with participants, not just defining them through science. Furthermore, knowledge co-production worked best during the operating model phase and had relational benefits beyond MSE, supporting collaborative research and management efforts. One objective of our session was to identify frequent barriers that researchers face when trying to perform and deliver impactful products to decision makers, and brainstorm ways to overcome these obstacles. Session presenters and attendees were asked via Mentimeter to identify barriers to their research being used in management decisions, and ways to improve IEA efforts. One of the most mentioned barriers was the need for more and improved integration of social sciences. Over half (54%) of participants in our session questionnaire identified social sciences as being the least represented or most missing expertise in their IEA project team. Haley Oleynik (University of British Columbia) cited data availability as her biggest limitation in incorporating social sciences data into salmon fishery stock assessments in British Columbia. Lansing Perng (University of Hawai‘i) presented her work on identifying thresholds and regime shifts in fishing data by better understanding the socioeconomic system to make more informed management decisions. Therefore, data limitation may prevent scientists from capturing the actual variability in social science indicators used for these analyses. A large portion of our session’s open discussion focused on how to better implement the social sciences in IEAs for the future. At least one biologist admitted to trying to do social science in order to incorporate that field into their work, due to a lack of social scientist team members. This comment was followed by concern that, even if someone wanted to collaborate with a social scientist, there are capacity issues for social scientists due to staffing. Structural inertia in current management systems was identified as another barrier limiting the ability to include broader ecosystem information into assessments and decision making. Co-development among scientists, modelers, managers, and stakeholders is necessary to create and further incorporate socioecological models and indicators for EBM, but the ability to do so is limited because current fisheries management systems are caught up “in the rush of day-to-day business and annual management cycles … [and] putting out the latest fire” (Fulton, 2021). Participants also noted that funding for fisheries science and management is limited and, historically, has been spent on collecting biological data and creating single-species models. Some ecological information is beginning to be incorporated into fisheries management decisions through ecosystem modeling and analysis; however, funding availability limits data collection and modeling advancements that would better incorporate social sciences in fisheries stock assessments. We need to think of co-production not as one step to achieving a means, but an inclusive, iterative approach of co-design, co-development, and co-delivery; a beginning to end process. This is often conceptualized as a cyclical, step-wise loop, as depicted by NOAA’s IEA loop (Figure 2; Samhouri et al., 2014). Co-production of data collection, analysis, and construction of products ensures the utility of the data collected and products derived for applications outside of just a scientific journal. By identifying the aforementioned barriers to successful co-production for management decisions, this session was able to identify potential actions that can be taken to overcome them. We can begin by deepening relationships with resource managers to better understand how and when decisions are made; what science and products are considered heavily in these decisions and what are missing, but would be valuable in future decisions. These discussions (plural!) need to be thoughtful, intentional, multidisciplinary, and held at a minimum between managing groups, fisheries biologists/ecologists, ecosystem and stock assessment modelers, social scientists, and rights holders. Each of these groups provides their respective expertise in identifying importance, availability, and usability of data, and provide availability and usability of social and economic data/indicators along with the consequences of potential management decisions. The National Oceanic and Atmospheric Administration’s integrated ecosystem assessment loop, which encourages co-production at each step of the process (Samhouri et al., 2014). EBM = ecosystem-based management. An AFS-wide effort to improve soft “facilitation” skills, such as active listening, clear communication, and questioning, would be beneficial for extracting the correct information in these scenarios to provide a framework for specific, clear objectives to execute usable ecosystem science. Due to the nature of their data collection, social scientists are often well-equipped with these skills, further emphasizing their necessity from the beginning of the co-production process until the end. Additionally, aquatic resource management decisions are often made by considering only the potential ecological consequences of change, thus, limiting the impact of EBM strategies. The coupling of natural and social science information for use by decision makers can aid in optimizing both conservation and socioeconomic objectives of EBM actions. For example, as AFS members and participants, it is important for us to remember that “fisheries” encompasses so much more than solely “fish.” The word “fisheries” includes, foremost, a human component, with a rich history, that we, as fisheries biologists and ecologists, too frequently overlook in our work. Social scientists are able to provide data and perspective on the social and economic consequences of management decisions, better rounding out a true ecosystem-based approach to managing resources. Building an optimal framework for co-production and inclusion of the social sciences in management decisions will take time. Betterment of these methods will need to be iterative and flexible, much like the methodology of IEAs and MSEs, and will require future discussions about successes, failures, and new impediments. We invite you all to consider adopting our co-production suggestions and continue this conversation within your own research spaces and at future AFS Annual Meetings. None declared. The authors want to thank the presenters in this session for their time and effort spent to participate in the AFS Annual Meeting. The authors would also like to thank the session attendees for their participation in our Mentimeter questionnaire and contributing to a lively discussion. Lastly, the authors would like to thank the entirety of the session organizers.

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