Norway is a global leader in salmon farming , with the aquaculture sector expecting to grow in the future to reach consumer demand. A dvocates argue farm raised salmon have a low carbon footprint, and aquaculture can therefore play a pivotal role in reducing the carbon footprint of food production. The detractors, on the other hand, argue aquaculture poses an environmental threat as escaped salmon may hybridize with natural populations, and high population densities in pens lead to an increase in local pollution and sea lice occurrence . Furthermore, d elousing of the fish is a challenge for fish welfare, the opponents argue. New production systems for salmon fish farming (i.e., land-based, floating closed, semi-closed, and open ocean aquaculture systems ) aim to counter these challenges, as well as utilise new areas for production . More knowledge is needed regarding how these new production systems should be regulated, and how they will influence the public perception of the salmon farming industry.
In this study , variables relevant for exploring key future scenarios are co-developed during participatory stakeholder workshops using Fuzzy Cognitive Mapping (FCM) , a soft computing framework. Industry stakeholders decide on relevant variables to include in models , how they influence each other, and discuss feedback mechanisms in participatory workshops . Data collected during workshops are then used as the basis for the creation of FCM models (Kosko 1986) , which combine fuzzy logic and recurrent neural networks, to produce predictions of changes to the perception of salmon farming in response to potential future scenarios. The results from models (i.e., values that represent the strength and direction of change to the perception of salmon farming in response to different scenarios) were then made interactable and accessible through their integration into a lightweight web application as a first-generation policy action tool .
The application is developed to make the results from th is study accessible to diverse stakeholder groups . Th us,
a concise description of how the model functions and how to interpret results from the scenarios is included in the app. In addition, information on the relevant variables defined by stakeholders and the fuzzy cognitive map describing the relationship between variables stakeholders defined in workshops is provided to users for easier interpretation of results.
Stakeholders included in the participatory workshops included industry representatives working with new aquaculture systems in Norway, researchers, and representatives from trade organisations. The variables that stakeholders identified as relevant to Norwegian salmon farming and their interactions were visualized in the freeware Mental Modeler throughout workshops to facilitate the co-production of a map of the system. Connections between variables were quantified on a continuous scale between -1 and +1, where a negative value indicated that if one variable increased, the variable on the receiving end of the “negative” connection would decrease . -1 indicated a strong decrease in the connected variable ( and it follows +1 indicated an increase in one variable would also result in the direct, strong increase in the connected variable and values near zero describe weak relationships between variables). These values served as the basis of a semi-quantitative model we used to describe our system and the basis of the creation of the projected future outcomes that were possible to interact with in the web application. Variables and their relationships were calibrated and validated in subsequent workshops.
Models were developed using the FCM package (Dikopoulou and Papageorgiou 2017 ) in R. Models were fit with the rescale inference rule which is preferred where there is not previous information about a concept-state, and we did not have information on the initial state of the system (Papageorgiou 2011) . A sigmoidal transformation function was applied as sigmoidal (continuous) FCMs are recommended for quantitative and qualitative scenarios with complex feedback structures as we found in our system (Tsadiras 2008) . The weight matrix consisted of the values obtained from the participatory workshops. The application was built using Shiny (Chang et al. 2023), a n open-source framework for building interactive web applications. One interactive element of the application is in the form of a drop-down menu where users c an select what variables to have a positive value in the activation vector. Visualizations and the table of values predicted for each variable in the application show values reached once the model has reached convergence and the system has reached an equilibrium point . The model outputs shown in visualisations from the user’s chosen scenario are based on the stakeholders’ perception of the system if there is a change to the current system. Feedback from stakeholders have been and will be implemented to make the app more user friendly. Specifically, s imilar variables were grouped together to simplify the interpretation of the results and the app is being developed in both Norwegian and English to match the language needs of different users (from local industry actors to academics) . Stakeholders will be invited to give feedback on the application to ensure a user-friendly interface is created as development of the app continues.
Results & Discussion
Following the axiom “all models are wrong, but some are useful,” the outputs of the workshops and FCM models in the web application will not be used as predictions of how perceptions will change as Norwegian salmon farming changes. Indeed, t he data collected from stakeholders is limited due to the small number of actors it is possible to include in workshops . Outputs from the models may be useful 1) in the context of engaging non-experts in research and 2) for serving as conversational focal points for ideating scenarios and informing decision making. The FCM developed in workshops also serves an important purpose as a simplification of the challenges faced by the Norwegian salmon farming industry, which allows for the visualisation of important and sometimes surprising relationships between identified variables. The app’s value comes from its ability to bridge gaps between researchers and stakeholders and between stakeholders themselves who may have differing opinions on how different variables will affect other variable under future scenarios. Indeed, the app may be used as a policy action tool, and to improve the communication between resource managers, regulators, policy makers, and actors from industry who make critical choices and researchers beyond a traditional scientific article or report. The conversations that result from interaction with the digital tool can thus be used to inform decision makers on how to develop Norwegian salmon farming in coming decades under different scenarios.
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Dikopoulou , Zoumpoulia , and Elpiniki Papageorgiou. "Inference of fuzzy cognitive maps (FCMs)." The Comprehensive R Archive Network (CRAN) (2017).
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